A system and method for analyzing the compression deformation and resilience performance of a thermally conductive gasket

Abstract

The present invention relates to the technical field of thermal performance analysis, and in particular to a compression deformation rebound performance analysis system and method for a thermally conductive gasket. The method comprises the following steps: obtaining the thermally conductive gasket structure data and constructing a constitutive model; obtaining the thermally conductive gasket working condition data and integrating them to obtain a gasket temperature-pressure time series distribution diagram; integrating according to the gasket temperature-pressure time series distribution diagram to obtain a gasket dynamic compression stress distribution diagram; evaluating the gasket dynamic compression stress distribution diagram to obtain the thermally conductive gasket rebound performance data; analyzing based on the gasket dynamic compression stress distribution diagram and the thermally conductive gasket rebound performance data to obtain the gasket fatigue damage accumulation data, and extrapolating to obtain the thermally conductive gasket service life data; optimizing according to the thermally conductive gasket service life data, the thermally conductive gasket rebound performance data and the gasket fatigue damage accumulation data to obtain the optimized thermally conductive gasket structure data. The present invention can improve the performance of thermally conductive gaskets under complex working conditions.

Description

Technical Field

[0001] The present invention relates to the technical field of thermal performance analysis, and in particular to a compression deformation rebound performance analysis system and method for a thermally conductive gasket. Background Art

[0002] With the continuous miniaturization and high performance of modern electronic devices, especially in electric vehicles, computer hardware, smart phones and other consumer electronic products, thermal management technology has become increasingly important. As a common thermal management material, thermal pads are mainly used for heat conduction between electronic components and heat sinks. Its function is to improve the thermal conductivity of the contact interface and reduce thermal resistance by filling tiny gaps, thereby effectively improving the heat dissipation efficiency. However, in actual use, the performance of thermal pads does not only depend on the thermal conductivity of the material, but is also significantly affected by compression deformation and resilience. Compression deformation usually refers to the thickness change of the thermal pad under working pressure, while resilience refers to its ability to restore its original thickness after the external force is removed. Excessive compression deformation or insufficient resilience will affect the long-term sealing and thermal conduction efficiency of the gasket, and may even cause poor thermal contact, thereby affecting the thermal management effect and reliability of electronic components. Traditional static analysis methods only focus on the compression state of the thermal pad at a certain moment, but fail to consider the dynamic behavior of the material in actual use. In real working environments, thermal pads are often affected by factors such as temperature fluctuations, frequent thermal cycles and vibrations, which can significantly change the compression set and rebound characteristics. Static methods cannot fully reflect this complex time-varying process. Summary of the invention

[0003] Based on this, it is necessary for the present invention to provide a system and method for analyzing the compression deformation and resilience performance of a thermally conductive gasket to solve at least one of the above technical problems.

[0004] To achieve the above object, a method for analyzing the compression deformation resilience performance of a thermally conductive gasket comprises the following steps:

[0005] Step S1: Acquire the thermal pad structure data, and perform gasket material property modeling based on the thermal pad structure data, thereby obtaining the thermal pad material property model; perform gasket material constitutive description on the thermal pad material property model, thereby obtaining the thermal pad constitutive model;

[0006] Step S2: Acquire the working condition data of the thermal conductive gasket, and perform multi-physics field working condition simulation on the constitutive model of the thermal conductive gasket according to the working condition data of the thermal conductive gasket, so as to obtain the working condition simulation data of the thermal conductive gasket; integrate the temperature-pressure distribution based on the working condition simulation data of the thermal conductive gasket, so as to obtain the gasket temperature-pressure time series distribution diagram;

[0007] Step S3: performing a gasket dynamic response simulation according to the gasket temperature-pressure time series distribution diagram to obtain gasket dynamic response data, and integrating the gasket dynamic compressive stress distribution based on the gasket dynamic response data to obtain a gasket dynamic compressive stress distribution diagram;

[0008] Step S4: extracting the gasket unloading working condition simulation data from the thermal conductive gasket working condition simulation data, thereby obtaining the gasket unloading working condition simulation data; evaluating the thermal conductive gasket working condition rebound performance based on the gasket unloading working condition simulation data and the gasket dynamic compression stress distribution diagram, thereby obtaining the thermal conductive gasket rebound performance data;

[0009] Step S5: performing a gasket thermal-mechanical fatigue analysis based on the gasket dynamic compression stress distribution diagram and the thermal conductive gasket rebound performance data, thereby obtaining gasket fatigue damage accumulation data, and performing a thermal conductive gasket service life estimation based on the gasket fatigue damage accumulation data, thereby obtaining thermal conductive gasket service life data;

[0010] Step S6: Analyze the fluctuation range of the thermal gasket's operating performance based on the thermal gasket's service life data, the thermal gasket's rebound performance data, and the gasket's fatigue damage accumulation data, so as to obtain the thermal gasket's operating performance fluctuation range data; optimize the thermal gasket's structure data based on the thermal gasket's operating performance fluctuation range data, so as to obtain the optimized thermal gasket structure data.

[0011] The present invention can deeply analyze the behavior and performance of thermally conductive gaskets under complex working conditions by comprehensively considering the multi-physics field characteristics, dynamic response, rebound performance and fatigue damage of thermally conductive gaskets, and provide more accurate thermal management solutions. By obtaining the structural data of the thermally conductive gasket and constructing a material property model, its thermal conductivity, compressibility and deformation characteristics can be accurately described, thereby providing an accurate basis for subsequent performance analysis. Based on these characteristic models, the thermal-mechanical response of the thermally conductive gasket can be simulated under different working conditions, especially the distribution time series of temperature and pressure, to help analyze the changes in its thermal conduction efficiency and the changes in thermal resistance of the contact interface in actual working conditions. Further dynamic response simulation can capture the behavior of the thermally conductive gasket under temperature fluctuations, vibrations and other dynamic loads, and accurately evaluate its stress distribution and thermal conductivity under different compression states. This dynamic compression stress analysis based on the time series distribution diagram not only provides a more detailed working state prediction, but also reveals the compression deformation and insufficient rebound problems that may occur in the thermally conductive gasket during long-term use, which is crucial to ensure the long-term reliability of components. Unloading condition simulation and rebound performance evaluation further help detect the recovery ability of the thermal gasket after the load is released, avoiding poor contact or reduced sealing due to insufficient rebound. In addition, fatigue damage analysis provides a quantitative evaluation of the service life of the thermal gasket, ensuring that the design can meet the long-term stability under high load and high temperature environments. Through in-depth analysis of the fluctuation range of operating conditions, the extreme conditions that the thermal gasket may encounter in actual work can be identified, thereby providing a scientific basis for its structural optimization and improving the overall performance and durability of the thermal gasket. In summary, through the integrated optimization of this series of steps, the thermal conduction efficiency, sealing, rebound ability and fatigue life of the thermal gasket under complex conditions can be significantly improved, providing reliable support for the thermal management of electronic components and other related fields. This comprehensive analysis and optimization method not only improves the application performance of the thermal gasket, but also lays the foundation for the future development of thermal management technology.

[0012] Optionally, step S1 specifically includes:

[0013] Step S11: Acquire thermal pad structure data, and extract thermal pad material features from the thermal pad structure data, thereby obtaining thermal pad material data;

[0014] Step S12: acquiring a gasket material experimental database, and extracting thermally conductive gasket material characteristic data from the gasket material experimental database according to the thermally conductive gasket material data, thereby obtaining the thermally conductive gasket material characteristic data;

[0015] Step S13: constructing a thermally conductive gasket material characteristic model according to the thermally conductive gasket material characteristic model and the thermally conductive gasket structure data, and performing multi-physics field simulation on the thermally conductive gasket material characteristic model, thereby obtaining gasket compression simulation data;

[0016] Step S14: integrating the microstructure features of the compressed gasket based on the gasket compression simulation data, thereby obtaining the gasket compression microstructure data;

[0017] Step S15: Perform constitutive description of the gasket material according to the gasket compression microstructure data, so as to obtain a constitutive model of the thermal conductive gasket.

[0018] The present invention can effectively improve the design and optimization accuracy of thermally conductive gaskets by systematically acquiring and processing the structure, characteristics and microstructure data of thermally conductive gasket materials. The acquisition of thermally conductive gasket structure data and the extraction of material characteristics are helpful to provide more accurate basic data for subsequent analysis and modeling, so that the expression of material characteristics is more scientific and reasonable, and avoids relying on overly simple assumptions or empirical formulas. By acquiring the gasket material experimental database and extracting the thermally conductive gasket material characteristic data, more comprehensive and reliable data support can be provided for the evaluation of material performance, thereby ensuring the accuracy and extensiveness of material characteristic data, and further improving the data support capability in the design process. By constructing a thermally conductive gasket material characteristic model and performing multi-physical field simulation, it is possible to truly simulate various physical effects such as heat conduction and pressure distribution of the gasket during actual use, thereby providing accurate performance prediction and optimization basis for the design, especially performance prediction under complex working conditions, so that the design can be more forward-looking. By integrating microstructure characteristics based on gasket compression simulation data, it can help designers to have a deep understanding of the microscopic deformation characteristics of the gasket under compression, thereby revealing the true behavior of the gasket material under extreme working conditions, and providing a more detailed description of material behavior. The description of the material constitutive model based on the compressed microstructure data of the gasket provides a key theoretical basis for the accurate modeling and further optimization of the entire system. This series of steps not only improves the performance prediction accuracy of the thermal conductive gasket, but also enhances the adaptability of the material under complex working conditions, providing more scientific and precise guidance for the design and application of thermal conductive gaskets.

[0019] Optionally, step S2 specifically includes:

[0020] Step S21: obtaining the working condition data of the thermal conductive gasket, and dividing the working condition data of the thermal conductive gasket into working condition data, so as to obtain the working condition data of the thermal conductive gasket compression and the working condition data of the thermal conductive gasket unloading;

[0021] Step S22: performing a multi-physics field compression working condition simulation on the constitutive model of the thermal conductive gasket according to the compression working condition data of the thermal conductive gasket, so as to obtain the gasket compression working condition simulation data;

[0022] Step S23: performing a multi-physics field unloading condition simulation on the thermal conductive gasket constitutive model according to the thermal conductive gasket unloading condition data, thereby obtaining the gasket unloading condition simulation data;

[0023] Step S24: performing working condition simulation coupling on the gasket compression working condition simulation data and the gasket unloading working condition simulation data, so as to obtain the thermal conductive gasket working condition simulation data;

[0024] Step S25: integrating the temperature-pressure distribution based on the thermal gasket working condition simulation data, thereby obtaining a gasket temperature-pressure time series distribution diagram.

[0025] The present invention can accurately extract the behavior characteristics of the gasket under different load and stress states by obtaining the working condition data of the thermal gasket and dividing the working conditions, which provides real basic data for subsequent multi-physics field simulation. By simulating the compression condition and unloading condition data separately, it can ensure that the physical response of the gasket under two extreme conditions is fully considered, so as to obtain more accurate simulation results. By coupling the compression and unloading condition simulation data, the comprehensive performance of the thermal gasket in the entire working cycle can be fully presented, especially the temperature and pressure changes during dynamic loading and unloading. This coupling analysis can reveal the comprehensive thermodynamic behavior of the thermal gasket under actual working conditions, better reflect its working state, and provide an important basis for engineering design and optimization. Based on the integration of the temperature-pressure time series distribution diagram, the heat-force distribution of the gasket at different positions and different time points during the working process can be intuitively presented, helping designers to evaluate the thermal stability, pressure resistance and service life of the gasket, thereby achieving more efficient design and more reliable product performance prediction.

[0026] Optionally, step S24 is specifically:

[0027] Step S241: extracting simulated pressure features from the gasket compression working condition simulation data and the gasket unloading working condition simulation data respectively, thereby obtaining compression pressure distribution data and unloading pressure regression data;

[0028] Step S242: performing physical pressure smoothing processing according to the compression pressure distribution data and the unloading pressure regression data, thereby obtaining pressure smoothing data;

[0029] Step S243: performing data docking on the gasket compression working condition simulation data and the gasket unloading working condition simulation data, so as to obtain physical superposition simulation data;

[0030] Step S244: performing physical field coupling on the physical superposition simulation data according to the pressure smoothing data, so as to obtain thermal pad working condition simulation data.

[0031] The present invention can effectively extract the pressure characteristics of the gasket under different working conditions by processing the simulation data of the gasket compression working condition and the unloading working condition, and then obtain the compression pressure distribution data and the unloading pressure regression data. This process makes the simulation results more accurate, can truly reflect the stress conditions of the gasket in actual use, and provide a reliable data basis for subsequent physical pressure smoothing and data docking. By performing physical pressure smoothing on the compression pressure distribution data and the unloading pressure regression data, it is possible to eliminate the calculation error or discontinuity, so that the pressure data is more stable and uniform, in line with the needs of the actual working conditions, and further improve the accuracy of the simulation. The step of data docking combines the data of the compression and unloading working conditions, integrates the physical properties under different working conditions, and thus generates physical superposition simulation data. This data has stronger comprehensiveness and representativeness, and can more comprehensively describe the performance changes of the gasket under various working conditions. By coupling the physical field of the physical superposition simulation data, the authenticity and applicability of the simulation results are further enhanced, and the obtained thermal conductive gasket working condition simulation data can better reflect the thermal conductivity characteristics and performance of the thermal conductive gasket in the actual working environment, thereby providing strong support for subsequent product design, optimization and testing. The combination of this series of steps can minimize errors during the simulation analysis process, improve the accuracy and reliability of the model, and provide more valuable technical data and theoretical basis for practical engineering applications.

[0032] Optionally, step S3 specifically includes:

[0033] Step S31: selecting a time step according to the gasket temperature-pressure time series distribution diagram, thereby obtaining time-pressure data and time-temperature data;

[0034] Step S32: setting dynamic loading conditions based on the time-pressure data and the time-temperature data, thereby obtaining dynamic loading conditions;

[0035] Step S33: performing a gasket dynamic response simulation according to the dynamic loading conditions and the constitutive model of the thermal conductive gasket, thereby obtaining gasket dynamic response data;

[0036] Step S34: extracting the gasket dynamic deformation characteristics and the gasket dynamic stress distribution characteristics from the gasket dynamic response data, thereby obtaining the gasket dynamic deformation data and the gasket dynamic stress distribution data;

[0037] Step S35: integrating the dynamic compressive stress distribution according to the gasket dynamic deformation data and the gasket dynamic stress distribution data, so as to obtain a gasket dynamic compressive stress distribution diagram.

[0038] The present invention can ensure that a sufficiently fine time resolution is captured in the simulation and accurate time-pressure data and time-temperature data are obtained by selecting a suitable time step according to the gasket temperature-pressure time series distribution diagram. This provides an accurate basis for the subsequent setting of dynamic loading conditions, ensuring that the loading process conforms to the changing characteristics of the actual working conditions. Using these data to set the dynamic loading conditions helps to more accurately simulate the behavior of the gasket under different loads, thereby obtaining more realistic dynamic response data. Through the analysis of the gasket dynamic response data, the deformation characteristics and stress distribution characteristics of the gasket under dynamic conditions can be extracted, and the physical reaction of the gasket in actual work can be deeply understood, which is crucial for optimizing the design. Further, the integration of dynamic deformation data and dynamic stress distribution data can form a complete dynamic compression stress distribution diagram, which provides a clear mechanical performance for engineering design, helping to better evaluate the stress bearing capacity of the gasket and its reliability and stability under complex working conditions. Each step of this process enhances the understanding of gasket performance, ensuring that the design and optimization are more in line with actual application requirements.

[0039] Optionally, step S35 is specifically:

[0040] Step S351: dividing the gasket dynamic deformation data into gasket deformation regions, thereby obtaining high-frequency deformation region data and low-frequency deformation region data;

[0041] Step S352: performing time series analysis on the dynamic stress distribution data of the gasket to obtain the time series maximum compressive stress area data;

[0042] Step S353: performing a regional intersection operation based on the time series maximum compression stress region data and the high-frequency deformation region data, thereby obtaining stress concentration region data; performing a regional intersection operation based on the time series maximum compression stress region data and the low-frequency deformation region data, thereby obtaining stress buffer region data;

[0043] Step S354: integrating the dynamic compressive stress distribution of the gasket dynamic stress distribution data according to the stress buffer area data and the stress concentration area data, thereby obtaining a dynamic compressive stress distribution diagram of the gasket.

[0044] The present invention can effectively identify the deformation characteristics of different frequencies by dividing the dynamic deformation data of the gasket into regions, and then divide the gasket into a high-frequency deformation region and a low-frequency deformation region. This division helps to deeply analyze the dynamic behavior of the gasket under different working conditions, especially to clearly distinguish the region that has a greater impact on stress and the region with a relatively gentle deformation, providing important basic data for subsequent analysis. By performing time series analysis on the dynamic stress distribution data of the gasket, the stress change law of the gasket in the entire cycle can be captured, thereby identifying the time series maximum compressive stress region. This information plays an important role in determining the high stress concentration area that may exist in the gasket under dynamic load, and can help designers predict potential material fatigue and damage risks. Then, using the time series maximum compressive stress area data and the high-frequency deformation area data to perform regional intersection operations, the stress concentration area data can be obtained. This area usually bears a large stress concentration, so it needs special attention during design to avoid premature failure. And by obtaining the stress buffer area data through the intersection operation with the low-frequency deformation area data, it can provide attention to the low stress area for the design, which helps to reduce unnecessary design burdens, and also ensure the balance and safety of the structure. Finally, by combining the stress buffer area data and the stress concentration area data, the dynamic stress distribution data of the gasket is integrated, and finally the dynamic compression stress distribution diagram of the gasket is obtained. This diagram provides a complete and accurate stress distribution for engineering design and optimization, and can effectively guide the performance evaluation, life prediction and risk control of the gasket under different working conditions.

[0045] Optionally, step S4 is specifically:

[0046] Step S41: extracting the gasket unloading working condition simulation data from the thermal conductive gasket working condition simulation data, thereby obtaining the gasket unloading working condition simulation data;

[0047] Step S42: calculating the gasket deformation stress influence factor according to the gasket dynamic compression stress distribution diagram, thereby obtaining the gasket deformation stress influence factor;

[0048] Step S43: extracting unloading heat energy characteristics and unloading stress characteristics based on the gasket unloading condition simulation data, thereby obtaining unloading heat energy data and unloading stress data;

[0049] Step S44: performing a gasket springback simulation according to the gasket deformation stress influencing factor, the unloading heat energy data, and the unloading stress data, thereby obtaining gasket springback simulation data;

[0050] Step S45: integrating the gasket rebound characteristics based on the gasket rebound simulation data, thereby obtaining the gasket rebound characteristic data;

[0051] Step S46: Evaluate the gasket rebound performance of the gasket rebound characteristic data to obtain the thermal conductive gasket rebound performance data.

[0052] The present invention can effectively evaluate the stress, thermal energy change and rebound characteristics of the thermal gasket during operation by simulating and extracting data on the unloading working conditions and rebound characteristics of the thermal gasket. By extracting the simulated data of the working conditions of the thermal gasket, the stress change of the gasket during the unloading process can be obtained, providing basic data for the subsequent deformation stress analysis. By using the dynamic compression stress distribution diagram of the gasket to calculate the deformation stress influencing factor, the key factors of the gasket deformation under various working conditions can be clarified, which helps to optimize the gasket design and enhance its pressure resistance and stability. On this basis, by extracting the unloading thermal energy characteristics and unloading stress characteristics, the thermal conductivity characteristics of the gasket in actual use and its response behavior under stress can be accurately captured, providing a scientific basis for the thermal performance evaluation of the gasket. The gasket rebound simulation can not only simulate the rebound process of the gasket under actual working conditions, but also extract the key parameters affecting the rebound performance through the integration of the rebound characteristics, and further evaluate the stability and reliability of the gasket under long-term working conditions. Through the rebound performance evaluation, the comprehensive rebound performance data of the thermal pad can be comprehensively obtained to accurately understand its recovery ability and durability in the working environment. This series of steps, through data simulation and feature extraction, can not only provide a theoretical basis for gasket design optimization, but also greatly improve the performance evaluation accuracy and reliability of the thermal pad, thereby improving its work efficiency and service life in practical applications.

[0053] Optionally, step S5 specifically includes:

[0054] Step S51: integrating the gasket working condition heat energy distribution based on the thermal conductive gasket working condition simulation data to obtain the gasket working condition heat energy distribution diagram, and performing gasket temperature field change analysis on the gasket working condition heat energy distribution diagram to obtain gasket temperature field change data;

[0055] Step S52: Identifying the mechanical stress behavior of the gasket according to the resilience performance data of the thermal conductive gasket, thereby obtaining the mechanical stress behavior data of the gasket;

[0056] Step S53: performing stress-strain cycle analysis according to the gasket temperature field change data and the gasket mechanical stress behavior data, thereby obtaining gasket loading cycle data;

[0057] Step S54: performing fatigue damage accumulation calculation on the gasket loading cycle data, thereby obtaining gasket fatigue damage accumulation data;

[0058] Step S55: Calculate the service life of the thermally conductive gasket according to the accumulated data of gasket fatigue damage, so as to obtain service life data of the thermally conductive gasket.

[0059] The present invention integrates and analyzes the heat energy distribution based on the working condition simulation data of the thermally conductive gasket, and can accurately obtain the temperature field changes of the gasket under the actual working state. This process can provide engineers with the thermal behavior characteristics of the gasket under different working conditions, help optimize the gasket design, and reduce the thermal stress and deformation problems caused by uneven temperature. By conducting an in-depth analysis of the changes in the gasket temperature field, it is also possible to predict the thermal stability and high temperature resistance of the gasket under different working environments, thereby improving the reliability of the product. The mechanical stress behavior is identified through the gasket rebound performance data, which can reveal the mechanical load conditions that the gasket may encounter during actual use. Obtaining the mechanical stress behavior data of the gasket can provide theoretical support for subsequent structural optimization, help designers identify potential stress concentration areas in advance, optimize the thickness, material and shape of the gasket, and then extend its service life and avoid failure caused by local overload. Based on the combined analysis of the gasket temperature field changes and mechanical stress behavior data, a stress-strain cycle analysis is performed, which helps to more accurately simulate the load fluctuations and deformations experienced by the gasket during actual work. This analysis can not only provide the load history that the gasket may experience in long-term work, but also effectively predict its fatigue characteristics and help evaluate the fatigue resistance of the gasket. This process is a key step to improve the safety and durability of gasket design, avoid premature failure and improve the overall performance of the gasket. The fatigue damage accumulation calculation using the gasket loading cycle data can simulate the degree of damage accumulated by the thermal conductive gasket in actual use. Through this calculation, the microcracks and deformation that may occur in the gasket during multiple loading and unloading processes can be quantified, the possible fatigue damage risks can be discovered in time, and the arrangement and preventive measures of the maintenance cycle can be guided. The service life of the gasket can be calculated based on the fatigue damage accumulation data of the gasket, which can provide accurate life prediction for actual engineering applications. This can not only help users scientifically evaluate the replacement cycle of the gasket and avoid equipment failures caused by excessive use, but also reduce unnecessary maintenance and cost investment to a certain extent. The whole process provides detailed data support and theoretical basis for the research and development, optimization and use of thermal conductive gaskets through comprehensive thermodynamics, mechanics, fatigue and life analysis, which greatly improves the reliability, durability and economy of thermal conductive gaskets.

[0060] Optionally, step S6 specifically includes:

[0061] Step S61: performing Monte Carlo simulation on the thermal pad working condition data to obtain random pad working condition data;

[0062] Step S62: constructing a mathematical model of resilience performance according to the resilience performance data of the thermally conductive gasket; constructing a damage accumulation model according to the service life data of the thermally conductive gasket, the constitutive model of the thermally conductive gasket and the fatigue damage accumulation data of the gasket;

[0063] Step S63: performing model structure coupling on the rebound performance mathematical model and the damage accumulation model, thereby obtaining a thermal conductive gasket performance evaluation model;

[0064] Step S64: performing a gasket operating performance evaluation on the random gasket operating condition data using a thermal conductive gasket performance evaluation model, thereby obtaining random gasket operating condition performance evaluation data;

[0065] Step S65: performing a performance fluctuation range analysis based on the random gasket operating condition performance evaluation data, thereby obtaining thermal conductive gasket operating condition performance fluctuation range data;

[0066] Step S66: Optimizing the thermally conductive gasket structure data based on the thermally conductive gasket operating performance fluctuation range data, thereby obtaining optimized thermally conductive gasket structure data.

[0067] The present invention can comprehensively evaluate the performance fluctuations of the gasket under different working conditions under random conditions by performing Monte Carlo simulation on the working condition data of the thermal gasket. This simulation method can effectively reflect the various working condition differences that may occur in the actual application of the thermal gasket, thereby providing a reliable random data basis for subsequent performance evaluation. By constructing a mathematical model of rebound performance and a gasket fatigue damage accumulation model, it is possible to scientifically describe the various physical changes and damages that the thermal gasket may experience during operation, and further reveal the recovery of the gasket under different working environments and the fatigue durability of the material. The establishment of the damage accumulation model, combined with the rebound performance model, can achieve an accurate evaluation of the comprehensive performance of the thermal gasket, thereby providing a key basis for design and optimization. The thermal gasket performance evaluation model obtained by coupling the rebound performance mathematical model and the damage accumulation model can comprehensively analyze the performance of the gasket from multiple dimensions. This performance evaluation model not only improves the prediction accuracy of the long-term operating stability of the thermal gasket, but also helps engineers understand the damage trend that may occur in the gasket under different workloads and working conditions. Based on this evaluation model, the gasket performance evaluation data under random working conditions can further reveal the actual working state of the gasket and provide a scientific basis for the extreme working conditions that may be encountered in actual applications. By analyzing the performance fluctuation range of these evaluation data, the fluctuation range of the gasket performance under various random working conditions can be obtained. This analysis not only helps to evaluate the reliability of the gasket, but also provides clear performance fluctuation parameters for subsequent optimization design, helps predict the worst case scenario that the gasket may face during actual use, and then provides guidance for preventive design adjustments. Finally, based on the performance fluctuation range data of the thermal gasket, the optimization of the thermal gasket structure can not only ensure the reliability and durability of the thermal gasket under various working conditions, but also improve its heat conduction efficiency and service life, making the design of the thermal gasket more adaptable to complex engineering needs. Overall, this process, from simulation to optimization, forms a comprehensive and systematic closed loop of thermal gasket performance analysis and optimization, which effectively improves the engineering application performance and economic benefits of the thermal gasket.

[0068] Optionally, the present specification also provides a compression deformation and resilience performance analysis system of a thermally conductive gasket, which is used to perform the compression deformation and resilience performance analysis method of the thermally conductive gasket as described above, and the compression deformation and resilience performance analysis system of the thermally conductive gasket includes:

[0069] The gasket material constitutive description module is used to obtain the thermal conductive gasket structure data, and to perform gasket material property modeling based on the thermal conductive gasket structure data, thereby obtaining the thermal conductive gasket material property model; perform gasket material constitutive description on the thermal conductive gasket material property model, thereby obtaining the thermal conductive gasket constitutive model;

[0070] The multi-physics field working condition simulation module is used to obtain the working condition data of the thermal conductive gasket, and perform multi-physics field working condition simulation on the constitutive model of the thermal conductive gasket according to the working condition data of the thermal conductive gasket, so as to obtain the working condition simulation data of the thermal conductive gasket; based on the working condition simulation data of the thermal conductive gasket, the temperature-pressure distribution is integrated to obtain the gasket temperature-pressure time series distribution diagram;

[0071] A stress distribution integration module is used to simulate the dynamic response of the gasket according to the gasket temperature-pressure time series distribution diagram, so as to obtain the dynamic response data of the gasket, and integrate the dynamic compression stress distribution of the gasket based on the gasket dynamic response data, so as to obtain the dynamic compression stress distribution diagram of the gasket;

[0072] The resilience performance evaluation module is used to extract the gasket unloading working condition simulation data from the thermal conductive gasket working condition simulation data, so as to obtain the gasket unloading working condition simulation data; based on the gasket unloading working condition simulation data and the gasket dynamic compression stress distribution diagram, the thermal conductive gasket working condition resilience performance evaluation is performed, so as to obtain the thermal conductive gasket resilience performance data;

[0073] A damage accumulation calculation module is used to perform a gasket thermal-mechanical fatigue analysis based on the gasket dynamic compression stress distribution diagram and the thermal conductive gasket rebound performance data, thereby obtaining the gasket fatigue damage accumulation data, and to perform a thermal conductive gasket service life estimation based on the gasket fatigue damage accumulation data, thereby obtaining the thermal conductive gasket service life data;

[0074] The performance fluctuation range analysis module is used to analyze the performance fluctuation range of the thermal gasket according to the service life data of the thermal gasket, the rebound performance data of the thermal gasket and the cumulative fatigue damage data of the gasket, so as to obtain the performance fluctuation range data of the thermal gasket; based on the performance fluctuation range data of the thermal gasket, the thermal gasket structure data is optimized to obtain the optimized thermal gasket structure data.

[0075] The compression deformation and rebound performance analysis system of the thermally conductive gasket of the present invention can implement the compression deformation and rebound performance analysis method of any thermally conductive gasket of the present invention, and is used to combine the operation and signal transmission medium between various modules to complete the compression deformation and rebound performance analysis method of the thermally conductive gasket. The internal modules of the system cooperate with each other, thereby significantly improving the performance of the thermally conductive gasket under complex working conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0076] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments thereof made with reference to the following drawings:

[0077] Figure 1 It is a schematic diagram of the steps of the method for analyzing the compression deformation resilience performance of the thermal conductive gasket of the present invention;

[0078] Figure 2 Detailed step flow diagram of step S1 in the present invention;

[0079] Figure 3 Detailed step flow diagram of step S2 in the present invention;

[0080] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0081] The technical method of the present invention is described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by technicians in this field without creative work are within the scope of protection of the present invention.

[0082] In addition, the accompanying drawings are only schematic illustrations of the present invention and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities. The functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor methods and / or microcontroller methods.

[0083] It should be understood that, although the terms "first", "second", etc. may be used herein to describe various units, these units should not be limited by these terms. These terms are used only to distinguish one unit from another unit. For example, without departing from the scope of the exemplary embodiments, the first unit may be referred to as the second unit, and similarly the second unit may be referred to as the first unit. The term "and / or" used herein includes any and all combinations of one or more of the listed associated items.

[0084] To achieve this, please refer to Figures 1 to 3 The present invention provides a method for analyzing the compression deformation resilience performance of a thermally conductive gasket, the method comprising the following steps:

[0085] Step S1: Acquire the thermal pad structure data, and perform gasket material property modeling based on the thermal pad structure data, thereby obtaining the thermal pad material property model; perform gasket material constitutive description on the thermal pad material property model, thereby obtaining the thermal pad constitutive model;

[0086] In this embodiment, the structural data of the thermally conductive gasket, including thickness, porosity, surface roughness, material type (such as metal, rubber, ceramic, etc.), etc., are obtained by three-dimensional scanning or computer-aided design (CAD) tools. These data will serve as the basis for modeling material properties. Using the finite element analysis (FEA) method, the thermal conductivity characteristics are modeled according to different materials (such as aluminum alloys and rubbers), and the thermal conductivity, specific heat capacity, density and other parameters of the material are obtained. Based on these material data, a constitutive model (such as a thermoelastic constitutive model) is constructed to describe the behavior of the material under thermal and mechanical loads. For example, in the temperature range of 20°C to 150°C, the thermal conductivity of aluminum alloys can vary between 150 W / m·K and 250 W / m·K, while rubber materials exhibit a nonlinear response. Finally, the accuracy of the material model is verified by experiments and the model parameters are adjusted.

[0087] Step S2: Acquire the working condition data of the thermal conductive gasket, and perform multi-physics field working condition simulation on the constitutive model of the thermal conductive gasket according to the working condition data of the thermal conductive gasket, so as to obtain the working condition simulation data of the thermal conductive gasket; integrate the temperature-pressure distribution based on the working condition simulation data of the thermal conductive gasket, so as to obtain the gasket temperature-pressure time series distribution diagram;

[0088] In this embodiment, the working condition data of the gasket, including the working environment temperature, contact pressure, loading rate, etc., are obtained through the thermally conductive gasket manufacturing workshop. It is assumed that the working environment of the thermally conductive gasket in the application of electronic equipment is 50°C to 120°C and the contact pressure is 1-10 MPa. Multi-physics field simulation is performed using thermal-mechanical coupling simulation software (such as COMSOL or ANSYS) to simulate the thermal conduction, mechanical behavior and coupled response of the gasket under different working conditions. Through the precise input of the material model, the distribution of temperature and pressure is obtained by simulation. Based on the working condition simulation data, a temperature-pressure distribution diagram is generated, which shows the changing trend of temperature and pressure at different time nodes. For example, the thermally conductive gasket may show a thermal stress concentration phenomenon at 120°C and 10 MPa pressure, resulting in a significant increase in the compressive stress in the local area. The temperature-pressure time series distribution diagram can intuitively display the thermal-mechanical response of the gasket under different working conditions.

[0089] Step S3: performing a gasket dynamic response simulation according to the gasket temperature-pressure time series distribution diagram to obtain gasket dynamic response data, and integrating the gasket dynamic compressive stress distribution based on the gasket dynamic response data to obtain a gasket dynamic compressive stress distribution diagram;

[0090] In this embodiment, a dynamic response simulation is performed according to the temperature-pressure time series distribution diagram of the gasket under different working conditions. This can be done by performing finite element dynamic analysis using the time stepping method to simulate the effects of temperature and pressure on the thermally conductive gasket at different times, and obtain its dynamic behavior under changing working conditions. For example, during the change of the operating temperature, the deformation of the gasket will trigger a dynamic stress wave, and as the pressure increases, the compressive stress gradually concentrates on the edge area of ​​the gasket. During the dynamic simulation, the compressive stress at each moment is recorded, and a dynamic compressive stress distribution diagram of the gasket is generated. The diagram can show the effects of temperature and pressure changes on the stress distribution of various parts of the gasket. For example, at 100 ° C, the compressive stress of the gasket may reach 4 MPa, while at 200 ° C, the compressive stress in some areas may exceed 7 MPa, indicating a potential risk of failure.

[0091] Step S4: extracting the gasket unloading working condition simulation data from the thermal conductive gasket working condition simulation data, thereby obtaining the gasket unloading working condition simulation data; evaluating the thermal conductive gasket working condition rebound performance based on the gasket unloading working condition simulation data and the gasket dynamic compression stress distribution diagram, thereby obtaining the thermal conductive gasket rebound performance data;

[0092] In this embodiment, the unloading condition data of the thermal gasket is extracted, such as the pressure release rate, the temperature change rate, etc. It is analyzed whether the gasket can return to its initial state when the pressure or temperature of the gasket is gradually reduced. A thermo-mechanical coupling simulation model is used to simulate the effects of temperature and pressure changes on the gasket during the unloading process. For example, when simulating the unloading of the gasket, the temperature of the thermal gasket is reduced to 50°C, and the pressure is reduced to 2 MPa. The material rebound during the stress release process is recorded to evaluate the rebound performance. The rebound rate can be calculated based on the stress recovery during the rebound process (such as a stress recovery rate of more than 90% indicates good rebound performance). The rebound performance data will provide information about the recovery ability of the thermal gasket under cyclic load and its performance during long-term work.

[0093] Step S5: performing a gasket thermal-mechanical fatigue analysis based on the gasket dynamic compression stress distribution diagram and the thermal conductive gasket rebound performance data, thereby obtaining gasket fatigue damage accumulation data, and performing a thermal conductive gasket service life estimation based on the gasket fatigue damage accumulation data, thereby obtaining thermal conductive gasket service life data;

[0094] In this embodiment, when performing thermal-mechanical fatigue analysis, a thermal-mechanical coupling fatigue model (such as the Morrow or Basquin model) is used to calculate the accumulation of fatigue damage in combination with the dynamic compressive stress distribution diagram and the rebound performance data of the gasket. Through multiple temperature and pressure cyclic loading simulations, the fatigue life of the gasket under different working conditions is estimated. For example, when the temperature and pressure reach certain limit values, the gasket may undergo permanent deformation. Based on the known fatigue damage accumulation law, the expected service life of the thermal conductive gasket can be calculated. For example, under the conditions of 200°C and 8 MPa pressure, the fatigue life of the gasket may be 5000 cycles. Through the fatigue damage accumulation data, the service life data can be obtained, and it can be judged whether the gasket can work stably within the expected working cycle.

[0095] Step S6: Analyze the fluctuation range of the thermal gasket's operating performance based on the thermal gasket's service life data, the thermal gasket's rebound performance data, and the gasket's fatigue damage accumulation data, so as to obtain the thermal gasket's operating performance fluctuation range data; optimize the thermal gasket's structure data based on the thermal gasket's operating performance fluctuation range data, so as to obtain the optimized thermal gasket structure data.

[0096] In this embodiment, the performance fluctuation range of the gasket under different working conditions is analyzed by combining the rebound performance data of the thermal gasket with the cumulative fatigue damage data. For example, when the temperature range is 20°C to 120°C and the pressure fluctuation range is 1 MPa to 10 MPa, the performance of the thermal gasket may fluctuate greatly, affecting its long-term use effect. Based on these fluctuation range data, an optimization algorithm (such as genetic algorithm or particle swarm optimization) is used to optimize the structure of the thermal gasket, aiming to reduce fatigue damage and improve the rebound performance. The optimization focuses on material selection, thickness distribution, surface treatment process, etc. For example, by adjusting the thickness and density of the gasket structure and reducing the stress concentration generated during operation, the optimized structure can improve its heat resistance and pressure resistance, thereby extending the service life and reducing performance fluctuations.

[0097] Optionally, step S1 specifically includes:

[0098] Step S11: Acquire thermal pad structure data, and extract thermal pad material features from the thermal pad structure data, thereby obtaining thermal pad material data;

[0099] In this embodiment, the microstructure of the thermally conductive gasket is photographed using a scanning electron microscope (SEM), and the three-dimensional structural data of the thermally conductive gasket is obtained using computer tomography (CT) technology. These data can provide key parameters such as gasket thickness, porosity, fiber arrangement, and material distribution. Based on the structural data, finite element analysis (FEA) or computational fluid dynamics (CFD) software is used to simulate the thermal performance of the material. By simulating material properties such as thermal conductivity, thermal diffusion coefficient, and specific heat capacity at different temperatures and pressures, the thermal conductivity of the thermally conductive gasket is extracted. The thermal conductivity of the material can be obtained by numerical simulation or experimental testing (such as heat flow meter testing).

[0100] Step S12: acquiring a gasket material experimental database, and extracting thermally conductive gasket material characteristic data from the gasket material experimental database according to the thermally conductive gasket material data, thereby obtaining the thermally conductive gasket material characteristic data;

[0101] In this embodiment, existing material databases, such as MatWeb, Granta MI, etc., are used to obtain experimental data of common thermal gasket materials, including thermal conductivity, compressive strength, thermal expansion coefficient, etc. These databases usually contain experimental data of various materials at different temperatures and pressures. Based on the obtained thermal gasket material data, the corresponding material property data in the experimental database is extracted. For example, if the material of the thermal gasket is a certain specific composite material, the corresponding thermal conductivity, heat resistance temperature and other properties are extracted according to the data in the database, and compared and corrected with the simulation results.

[0102] Step S13: constructing a thermally conductive gasket material characteristic model according to the thermally conductive gasket material characteristic model and the thermally conductive gasket structure data, and performing multi-physics field simulation on the thermally conductive gasket material characteristic model, thereby obtaining gasket compression simulation data;

[0103] In this embodiment, finite element analysis (FEA) software (such as ANSYS, COMSOL Multiphysics, etc.) is used, and a material property model of the thermally conductive gasket is established based on the extracted material property data and structural data. The model needs to integrate the microstructure (such as porosity, fiber arrangement, etc.) and material properties (such as thermal conductivity, specific heat capacity, etc.) of the thermally conductive gasket. Then, a multi-physics simulation tool (such as ANSYS or COMSOL Multiphysics) is used to simulate the thermal conduction behavior of the thermally conductive gasket under different compression states, especially the thermal conductivity of the gasket under high temperature and high pressure. The coupling of thermodynamics, mechanics and heat conduction should be considered during the simulation process to obtain the thermal conductivity change data of the gasket under compression.

[0104] Step S14: integrating the microstructure features of the compressed gasket based on the gasket compression simulation data, thereby obtaining the gasket compression microstructure data;

[0105] In this embodiment, based on the obtained simulation data, the microstructural changes during the compression process are analyzed, such as the fiber spacing, pore deformation, pressure distribution, etc. of the material. The stress and deformation state inside the gasket during the compression process can be analyzed by post-processing tools, and the microstructural characteristics after compression can be extracted. Through multi-scale modeling technology, combined with data from microscale to macroscale, the microstructural changes of the gasket under compression are integrated. In particular, factors such as porosity and fiber rearrangement are described in detail to further analyze the thermodynamic behavior of the gasket.

[0106] Step S15: Perform constitutive description of the gasket material according to the gasket compression microstructure data, so as to obtain a constitutive model of the thermal conductive gasket.

[0107] In this embodiment, based on the obtained compression microstructure data, a constitutive model (such as an elastic-plastic model, a thermoelastic model, etc.) is used to describe the deformation and heat conduction behavior of the thermally conductive gasket material. According to the experimental data and simulation data, a material model (such as a linear elastic model, a nonlinear constitutive model, etc.) is used to define the stress-strain relationship of the material. The constitutive model is compared and verified with the experimental data of the actual material to ensure that the model can accurately describe the mechanical and thermal properties of the material. The accuracy of the model can be verified by physical experiments, such as high-temperature compression experiments and heat conduction experiments. For example, by analyzing the microscopic pore structure, stress distribution and heat conduction path of the material, the constitutive equation is used to describe the stress-strain relationship of the material under compression, as well as the relationship between its thermal conductivity and temperature and pressure. The constitutive model is verified by the finite element analysis method (FEM) to ensure its accuracy and reliability under actual working conditions.

[0108] Optionally, step S2 specifically includes:

[0109] Step S21: obtaining the working condition data of the thermal conductive gasket, and dividing the working condition data of the thermal conductive gasket into working condition data, so as to obtain the working condition data of the thermal conductive gasket compression and the working condition data of the thermal conductive gasket unloading;

[0110] In this embodiment, the working condition data of the thermally conductive gasket is obtained through field testing, simulation or historical data of the thermally conductive gasket manufacturing workshop. The working condition data includes physical quantities such as temperature, pressure, load, and strain. These data can be monitored in real time by sensors installed near the thermally conductive gasket, such as temperature sensors, pressure sensors, strain gauges and other equipment. According to these real-time data, the working state of the thermally conductive gasket can be divided into two main working conditions: compression condition and unloading condition. Specifically, the compression condition refers to the deformation process of the gasket under pressure, while the unloading condition refers to the process in which the gasket returns to its original state after the load is removed. The two working condition data will be stored separately for subsequent constitutive model simulation and analysis. Assume that in a thermal management system of an electric vehicle battery pack, the thermally conductive gasket is used to maintain the thermal conductivity between the battery and the shell. The temperature and pressure changes during the battery charging and discharging process are monitored in real time by thermocouple sensors and pressure sensors. According to the sensor data, it can be identified that when the battery is in a charging state, the pressure on the gasket increases, which is a compression condition; and when the battery is discharged or shut down, the pressure decreases, which is an unloading condition.

[0111] Step S22: performing a multi-physics field compression working condition simulation on the constitutive model of the thermal conductive gasket according to the compression working condition data of the thermal conductive gasket, so as to obtain the gasket compression working condition simulation data;

[0112] In this embodiment, the compression working condition data of the thermally conductive gasket is used as input, and the constitutive model of the thermally conductive gasket verified by the physical field simulation software (such as COMSOL, ANSYS, etc.) is combined to perform multi-physical field simulation. During the simulation process, it is necessary to consider the material properties of the gasket (such as thermal conductivity, elastic modulus, thermal expansion coefficient, etc.), and simulate under different temperature and pressure conditions. The simulation of the compression working condition mainly focuses on the distribution and evolution of physical fields such as stress, strain, and temperature field of the gasket under pressure. In a high temperature and high pressure environment, such as a heat exchange device, the thermally conductive gasket needs to withstand pressure from the outside under compression conditions. By establishing a constitutive model based on the finite element method (FEM), the compression working condition data (such as maximum pressure value, temperature range) collected by the sensor is input into the preset constitutive model of the thermally conductive gasket in the simulation software, and a thermal-mechanical coupling analysis is performed to obtain the simulation data such as the stress distribution, heat flux density, and temperature gradient of the gasket under compression.

[0113] Step S23: performing a multi-physics field unloading condition simulation on the thermal conductive gasket constitutive model according to the thermal conductive gasket unloading condition data, thereby obtaining the gasket unloading condition simulation data;

[0114] In this embodiment, the unloading process of the thermal gasket is simulated according to the unloading condition data obtained. The unloading condition usually refers to the process in which the gasket gradually returns to its original shape during the unloading process. During this process, physical parameters such as temperature and pressure will change, resulting in the reverse change of stress and strain. The unloading condition data of the thermal gasket is used as input, and the constitutive model of the thermal gasket is used for multi-physics field simulation, which can predict the thermal response, mechanical response and other performances of the gasket during the unloading process, thereby obtaining detailed unloading condition simulation data. Assume that the thermal gasket needs to be restored to its original state after the battery is shut down. At this time, the temperature may be high and the pressure has disappeared. This process is simulated by the constitutive model of the thermal gasket preset in the simulation software. Under different unloading speeds and environmental conditions, the thermal expansion behavior of the gasket material during the unloading process, the change in thermal conductivity, etc. are simulated to evaluate whether the gasket can effectively restore its initial performance and ensure stability in long-term use.

[0115] Step S24: performing working condition simulation coupling on the gasket compression working condition simulation data and the gasket unloading working condition simulation data, so as to obtain the thermal conductive gasket working condition simulation data;

[0116] In this embodiment, coupling analysis is performed on the basis of the simulation data of the gasket compression condition and the simulation data of the gasket unloading condition. Specifically, the simulation results of the two conditions are first matched in time and space to form a comprehensive condition data set. Through multi-physics field coupling analysis, the mutual influence of physical quantities such as temperature, pressure, and stress during the loading and unloading process of the gasket in actual work is simulated. For example, the stress generated under the compression condition may affect the thermal conductivity of the gasket, while under the unloading condition, the temperature change during the recovery process may affect the release of stress. For example, when simulating the thermal management system of an electric vehicle, the gasket experiences different pressure and temperature fluctuations during charging and discharging. The system couples the simulation data of the compression and unloading conditions to evaluate the long-term thermo-mechanical behavior of the gasket under different conditions. This process can be completed by integrating heat conduction, thermal expansion, and elastic mechanics models to obtain the working condition simulation data of the thermally conductive gasket throughout its life cycle.

[0117] Step S25: integrating the temperature-pressure distribution based on the thermal gasket working condition simulation data, thereby obtaining a gasket temperature-pressure time series distribution diagram.

[0118] In this embodiment, the obtained working condition simulation data is used to integrate the time series distribution of temperature and pressure. First, the temperature and pressure data at different time points are extracted according to the simulation results. Then, these data are plotted into a temperature-pressure distribution diagram to show the change pattern of temperature and pressure of the gasket during the entire working cycle. This chart helps to analyze the thermal management performance of the thermally conductive gasket under different working conditions and provide a basis for optimizing the design. Assume that the thermally conductive gasket is used in a heat exchange device under a high temperature environment. During the working cycle of the entire equipment, the temperature and pressure will fluctuate with the change of load. Through the temperature-pressure time series distribution diagram drawn based on the simulation data, it can be intuitively seen that during the startup, operation and shutdown of the equipment, the temperature and pressure changes that the gasket is subjected to. Based on these charts, designers can evaluate the thermal stability and pressure resistance of the gasket, and make improvements in material selection, structural optimization and other aspects.

[0119] Optionally, step S24 is specifically:

[0120] Step S241: extracting simulated pressure features from the gasket compression working condition simulation data and the gasket unloading working condition simulation data respectively, thereby obtaining compression pressure distribution data and unloading pressure regression data;

[0121] In this embodiment, the compression and unloading conditions of the gasket are set in the finite element analysis software (such as ANSYS, ABAQUS). In the compression condition, the force direction of the gasket is compression, simulating its stress and strain at different time points or loading conditions; the unloading condition simulates the mechanical response of the gasket after the external load is gradually removed. After the simulation is completed, the pressure data at each moment or each pressure interval is extracted from the simulation results. For the compression condition, when extracting data points, it can be set to the distribution of pressure during different loading processes or at different time points to obtain "compression pressure distribution data"; for the unloading condition, the extracted data is the data of the regression change of pressure over time during the unloading process, and the "unloading pressure regression data" is obtained.

[0122] Step S242: performing physical pressure smoothing processing according to the compression pressure distribution data and the unloading pressure regression data, thereby obtaining pressure smoothing data;

[0123] In this embodiment, a smoothing algorithm is selected to smooth the compression pressure distribution data and the unloading pressure regression data. For example, methods such as Gaussian filtering, Savitzky–Golay filtering or wavelet transform can be used. For the compression pressure distribution data, the data can be smoothed by Gaussian filtering to reduce the impact of simulation errors or noise; and the unloading pressure regression data can be smoothed by Savitzky-Golay filtering by fitting polynomials. The smoothed data output is continuous pressure data without significant noise, which can better represent the actual pressure changes under physical conditions.

[0124] Step S243: performing data docking on the gasket compression working condition simulation data and the gasket unloading working condition simulation data, so as to obtain physical superposition simulation data;

[0125] In this embodiment, a data interpolation method is used to connect the simulation data of the compression condition and the unloading condition. For example, the data of the compression stage and the unloading stage are connected by bilinear interpolation to ensure the continuity of pressure at the connection point and the consistency of physical meaning. During the docking process, the data of the compression and unloading stages are guaranteed to be physically continuous. For example, the pressure value at the end of compression matches the pressure value at the beginning of unloading to avoid physically unreasonable mutations. After completing the data docking, the compression pressure distribution data and the unloading pressure regression data are superimposed to generate a new pressure data set, which represents the physical pressure evolution during the entire compression and unloading process.

[0126] Step S244: performing physical field coupling on the physical superposition simulation data according to the pressure smoothing data, so as to obtain thermal pad working condition simulation data.

[0127] In this embodiment, a thermal-mechanical coupling model is established in a simulation platform (such as ANSYS, COMSOL, etc.), and the obtained pressure smoothing data is used as input, considering the thermal conductivity characteristics, thermal expansion coefficient and the relationship between the gasket material and the external load. The coupling model should not only simulate the change of pressure, but also consider the influence of temperature on the thermal conductivity of the material. In the coupling model, the relationship between pressure and temperature field is solved by numerical methods to obtain the simulation results of the thermally conductive gasket under actual working conditions. This includes temperature distribution, heat flux density and thermal conductivity coefficient of the material. The specific operation includes first defining the thermal conduction model of the gasket, which is usually based on physical parameters such as thermal conductivity, thickness, and temperature distribution of the material. Then, the pressure data in the physical superposition simulation data is used as the boundary condition or load condition of heat conduction for coupling solution. For example, assuming that under compression conditions, the external pressure on the gasket affects the heat flux distribution, and the high pressure in the compression zone may cause the local temperature to rise. Therefore, the temperature change in the area is calculated according to the pressure smoothing data to obtain the thermal response of the entire gasket during operation. During the unloading process, the pressure gradually decreases and the distribution of heat flow will also change. The simulation data of the thermal conductive gasket working condition obtained through coupling can reflect the interaction between the thermal properties and mechanical response of the gasket during compression and unloading.

[0128] Optionally, step S3 specifically includes:

[0129] Step S31: selecting a time step according to the gasket temperature-pressure time series distribution diagram, thereby obtaining time-pressure data and time-temperature data;

[0130] In this embodiment, according to the gasket temperature-pressure time series distribution diagram, a suitable time step is selected to ensure that the data sampling rate is high enough to accurately capture the small fluctuations of temperature and pressure over time. For example, if the temperature and pressure change cycle is short, a shorter time step should be selected (such as sampling data once per second); if the change cycle is long, a longer time step can be selected (such as sampling data once per minute). The time-pressure data and time-temperature data obtained through this step can provide a basis for the subsequent dynamic loading condition setting.

[0131] Step S32: setting dynamic loading conditions based on the time-pressure data and the time-temperature data, thereby obtaining dynamic loading conditions;

[0132] In this embodiment, the dynamic loading conditions of the gasket can be set according to the obtained time-pressure and time-temperature data. Assuming that the gasket will experience the alternating effects of temperature and pressure during a certain working process, a multivariate loading condition model can be established, such as using a polynomial or exponential function to fit the relationship between time-temperature and time-pressure. Through numerical analysis methods (such as finite element analysis), the response of the gasket under different temperature and pressure conditions is simulated. Through the calculated temperature and pressure time series, the amplitude and direction of action of a dynamic loading can be determined for each moment. For example, if the gasket is subjected to a pressure of 5MPa at a certain point in time and the temperature is 300°C, the dynamic loading condition may be set to apply a load of 300°C and a pressure of 5MPa. The dynamic loading condition provides input for subsequent response simulations.

[0133] Step S33: performing a gasket dynamic response simulation according to the dynamic loading conditions and the constitutive model of the thermal conductive gasket, thereby obtaining gasket dynamic response data;

[0134] In this embodiment, the constitutive model of the thermally conductive gasket is used to perform dynamic response simulation. The constitutive model of the thermally conductive gasket includes parameters such as the elastic modulus, plastic behavior, thermal expansion coefficient, and thermal conductivity of the material. By selecting an appropriate numerical simulation method (such as the finite element method), the obtained dynamic loading conditions (loading curves of temperature and pressure changing with time) are used as input conditions to perform dynamic calculations of the time step. Specifically, within each time step, the model will calculate the response results such as deformation, stress distribution, and temperature change of the gasket under different temperature and pressure conditions. For example, if the pressure applied at a certain moment is 10MPa and the temperature is 500°C, the constitutive model can be used to simulate the effect of the temperature increase of the gasket on its stiffness and stress state, and further analyze the dynamic response of the gasket. Finally, the dynamic response data of the gasket can be obtained through simulation, including deformation data, stress data, heat conduction data, etc.

[0135] Step S34: extracting the gasket dynamic deformation characteristics and the gasket dynamic stress distribution characteristics from the gasket dynamic response data, thereby obtaining the gasket dynamic deformation data and the gasket dynamic stress distribution data;

[0136] In this embodiment, after obtaining the dynamic response data of the gasket, the dynamic deformation characteristics and dynamic stress distribution characteristics of the gasket are extracted therefrom by a feature extraction method. Specifically, the dynamic response data is first subjected to a time series analysis to extract the deformation mode of the gasket, for example, by changing the displacement field or strain field, the local deformation area of ​​the gasket is identified. Using the deformation data, the maximum deformation amount of the gasket at different time points, the local deformation situation, etc. can be calculated. For example, a strain gauge or an image processing method is used to extract the strain value of the local deformation area, thereby obtaining dynamic deformation data. At the same time, the dynamic stress distribution of the gasket in each time step is extracted by stress field analysis. By performing a thermodynamic analysis on the stress field data, the distribution characteristics of the gasket stress are identified. For example, the maximum value, minimum value and stress concentration area of ​​the gasket stress under different temperature and pressure conditions are determined by the stress field output by finite element analysis. Finally, the dynamic stress distribution data of the gasket is obtained, including the stress distribution diagram and its changing trend under each time step.

[0137] Step S35: integrating the dynamic compressive stress distribution according to the gasket dynamic deformation data and the gasket dynamic stress distribution data, so as to obtain a gasket dynamic compressive stress distribution diagram.

[0138] In this embodiment, the compressive stress distribution is integrated according to the extracted dynamic deformation data and dynamic stress distribution data. Compressive stress is the main mechanism for the gasket to deform under external loads, and is usually closely related to factors such as temperature and pressure. The stress concentration area on the gasket surface or contact area is analyzed through the dynamic stress distribution diagram, and then the deformation data is combined with the stress data, and the compressive stress distribution of the gasket is obtained by calculating the stress state in different areas of the gasket. Using the stress-strain relationship, the deformation data and stress data are matched and integrated, and finally a dynamic compressive stress distribution diagram showing the gasket under dynamic loading conditions is obtained. This figure can show the distribution of the compressive stress of the gasket in space and time at different time nodes and loading conditions. For complex geometric shapes or loading conditions, it may be necessary to further refine the grid or use more sophisticated calculation methods (such as high-order finite element analysis) to improve the accuracy of the results.

[0139] Optionally, step S35 is specifically:

[0140] Step S351: dividing the gasket dynamic deformation data into gasket deformation regions, thereby obtaining high-frequency deformation region data and low-frequency deformation region data;

[0141] In this embodiment, a strain gauge or a displacement sensor is used to measure the dynamic deformation data of the gasket to obtain the deformation conditions at different time points. Then, the data is Fourier transformed based on the frequency response function (FRF) to decompose it into high-frequency components and low-frequency components. The high-frequency deformation area is usually related to local vibration or local instability, while the low-frequency deformation area is related to the overall compression or tension behavior. By setting a deformation threshold (for example, a deformation exceeding a certain amplitude is considered to be a high-frequency deformation), the dynamic deformation area of ​​the gasket can be divided. The high-frequency area is usually defined as an area where the dynamic deformation amplitude exceeds a set value, while the low-frequency area is defined as an area where the vibration frequency is lower than a threshold. Finally, through the analysis of spatial distribution, the deformation area is divided into multiple areas according to time periods for subsequent analysis.

[0142] Step S352: performing time series analysis on the dynamic stress distribution data of the gasket to obtain the time series maximum compressive stress area data;

[0143] In this embodiment, the dynamic stress distribution data of the gasket is analyzed by time series analysis technology (such as autocorrelation analysis or sliding average method) to find the maximum compression value of stress in each time period. In particular, the sliding window method is used to analyze the change trend of stress, select the moment of maximum compression stress as the key time point, and extract the area where the maximum compression stress is located based on the data at these moments. Finally, based on the time distribution of the maximum compression stress area, the time series maximum compression stress area data is generated to facilitate the subsequent analysis of stress concentration and buffer area.

[0144] Step S353: performing a regional intersection operation based on the time series maximum compression stress region data and the high-frequency deformation region data, thereby obtaining stress concentration region data; performing a regional intersection operation based on the time series maximum compression stress region data and the low-frequency deformation region data, thereby obtaining stress buffer region data;

[0145] In this embodiment, the intersection operation is performed using the data of the time-series maximum compressive stress area and the data of the high-frequency deformation area. The purpose of the intersection operation is to find stress concentration areas, that is, those areas where there are both large dynamic stresses (maximum compressive stress areas) and large dynamic deformations (high-frequency deformation areas). These areas are usually potential locations for gasket failure or damage. For example, in the dynamic stress distribution diagram of the gasket, the intersection of the time-series maximum compressive stress area and the high-frequency deformation area is marked, and these intersection areas usually have more serious stress concentration phenomena. Similarly, the intersection operation of the time-series maximum compressive stress area and the low-frequency deformation area data is performed to obtain stress buffer area data. These buffer areas usually mean areas with relatively low stress, which help to mitigate the concentration effect of stress.

[0146] Step S354: integrating the dynamic compressive stress distribution of the gasket dynamic stress distribution data according to the stress buffer area data and the stress concentration area data, thereby obtaining a dynamic compressive stress distribution diagram of the gasket.

[0147] In this embodiment, the obtained stress buffer area data and stress concentration area data are integrated. First, the dynamic stress data of the gasket is mapped to a two-dimensional or three-dimensional coordinate system to form a complete stress distribution map. Then, according to the data of the stress concentration area and the buffer area obtained by the intersection operation, the dynamic compressive stress of the gasket is enhanced or weakened respectively. For the stress concentration area, the stress value of the area is enhanced; and for the stress buffer area, the stress value of the area is appropriately reduced. Finally, the integrated stress distribution map can be verified by numerical simulation (such as finite element analysis), and the display of the stress map can be adjusted according to the actual situation, so as to obtain a dynamic and accurate dynamic compressive stress distribution map of the gasket. This map will help engineers locate potential high stress areas or low stress areas during the design or maintenance process, so as to make corresponding optimizations.

[0148] Optionally, step S4 is specifically:

[0149] Step S41: extracting the gasket unloading working condition simulation data from the thermal conductive gasket working condition simulation data, thereby obtaining the gasket unloading working condition simulation data;

[0150] In this embodiment, finite element analysis (FEA) or other numerical simulation software (such as ANSYS, COMSOL, etc.) can be used to simulate the stress conditions of the thermally conductive gasket under different working conditions. It is assumed that the working conditions of the gasket during use include changes in temperature, pressure and stress. During the simulation process, various physical quantities (such as temperature, pressure and deformation) during the unloading process of the gasket are recorded, especially the stress distribution and temperature field after unloading. These data include the stress release process of the gasket, the temperature change trend, etc., to form the unloading condition simulation data. During implementation, the accuracy and stability of the simulation results are ensured through multiple iterations of numerical simulation. Assume that in an actual application scenario, the thermally conductive gasket is used for electronic equipment in a high temperature environment. Through numerical simulation, the stress and temperature distribution of the gasket in the process of gradually decreasing temperature and gradually releasing pressure are obtained, and the simulation data under the unloading condition is generated for use in subsequent steps.

[0151] Step S42: calculating the gasket deformation stress influence factor according to the gasket dynamic compression stress distribution diagram, thereby obtaining the gasket deformation stress influence factor;

[0152] In this embodiment, a stress distribution diagram of the gasket during the compression process is obtained through dynamic compression experiments or numerical simulations. The figure shows the stress magnitude and distribution in different regions. On this basis, the deformation stress influencing factor is calculated using the following formula or method: I_{f}=\frac{\sum(\sigma\cdot\Delta x)}{\text{total stress}}; where \sigma is the stress value, \Delta x is the deformation amount, and I_f is the deformation stress influencing factor. The calculation of the deformation stress influencing factor can quantify the influence of stress on the deformation of the gasket, and then evaluate how the gasket recovers to its original state during the unloading process. For example, in the simulation model, after the gasket is subjected to the initial compressive stress, the stress values ​​in certain areas are significantly reduced as the unloading process proceeds. By calculating the stress change, the deformation stress influencing factors of different regions are obtained, providing key data for the subsequent rebound simulation.

[0153] Step S43: extracting unloading heat energy characteristics and unloading stress characteristics based on the gasket unloading condition simulation data, thereby obtaining unloading heat energy data and unloading stress data;

[0154] In this embodiment, based on the extracted unloading condition simulation data, the characteristics related to thermal energy during the unloading process are first extracted, such as the temperature change rate, thermal conductivity, thermal expansion coefficient, etc. Then, the characteristics of stress changes during the unloading process are extracted through stress analysis, including the maximum stress value, stress release rate, etc. These thermal energy and stress characteristics are accurately calculated using numerical analysis tools and converted into usable numerical data for subsequent analysis. Assuming that in a thermal management system of an engine, the temperature change of the gasket has significant fluctuations during the unloading process, numerical simulation can be used to extract the temperature change rate and stress change curve, so as to obtain thermal energy characteristics and stress characteristic data. These data help to further understand the performance of the gasket during the unloading process.

[0155] Step S44: performing a gasket springback simulation according to the gasket deformation stress influencing factor, the unloading heat energy data, and the unloading stress data, thereby obtaining gasket springback simulation data;

[0156] In this embodiment, finite element analysis software is used to take the deformation stress influencing factor, unloading heat energy data and unloading stress data as input to perform numerical simulation of the gasket rebound process. Select a suitable material model (such as an elastic-plastic model, a thermal expansion model, etc.), and consider the thermal-mechanical coupling effect in the simulation. Through simulation, the rebound of the gasket after unloading is obtained, including data such as rebound stress, rebound speed and rebound amount. In electronic equipment, after the temperature of the thermal conductive gasket is reduced, the rebound performance of the material is crucial to the heat dissipation effect of the equipment. By inputting heat energy and stress data into the simulation model, the rebound process of the gasket from a high-pressure state to a low-pressure state can be simulated, and the geometric shape changes and stress recovery after rebound can be predicted.

[0157] Step S45: integrating the gasket rebound characteristics based on the gasket rebound simulation data, thereby obtaining the gasket rebound characteristic data;

[0158] In this embodiment, during the rebound simulation process, a number of key features in the rebound process are obtained, such as rebound displacement, rebound stress distribution, rebound time, etc. These data can be integrated through data fusion methods (such as weighted average, principal component analysis, etc.) to obtain comprehensive rebound characteristic data. The integrated data can fully reflect the rebound performance of the gasket, including its recovery ability and adaptability to temperature and pressure changes. For example, based on the rebound simulation data, the rebound displacement, rebound velocity and rebound stress data are integrated to obtain a rebound characteristic curve. This curve can help designers evaluate the adaptability of the gasket in different working environments, such as the rebound performance in a high temperature environment.

[0159] Step S46: Evaluate the gasket rebound performance of the gasket rebound characteristic data to obtain the thermal conductive gasket rebound performance data.

[0160] In this embodiment, based on the obtained rebound characteristic data, the gasket rebound performance is evaluated using performance evaluation indicators (such as rebound accuracy, rebound time, rebound stability, etc.). The specific method may include comparing experimental data and simulation data to evaluate whether the rebound performance meets the design requirements. Standardized test methods (such as ASTM, ISO, etc.) can also be used to verify performance to ensure its reliability and stability in practical applications. Assuming that a gasket is designed for a high-pressure environment, the rebound accuracy is crucial to maintaining sealing. Through the rebound characteristic evaluation, the rebound performance of the gasket under high temperature and heavy load conditions can be obtained. If the rebound accuracy reaches ±0.1mm, which meets the design requirements, the gasket has a high reliability in actual use.

[0161] Optionally, step S5 specifically includes:

[0162] Step S51: integrating the gasket working condition heat energy distribution based on the thermal conductive gasket working condition simulation data to obtain the gasket working condition heat energy distribution diagram, and performing gasket temperature field change analysis on the gasket working condition heat energy distribution diagram to obtain gasket temperature field change data;

[0163] In this embodiment, the heat conduction of the thermally conductive gasket under working conditions is simulated by numerical simulation software (such as ANSYS, COMSOL Multiphysics, etc.). Assuming that the gasket material is a graphite-based composite material, the thermal condition simulation is performed within the operating temperature range (such as 300°C to 800°C). By setting different heat load conditions (such as the heat generated by the engine or electronic components), and simulating the temperature field of the gasket, the temperature distribution of each position is obtained. According to the simulation data, the heat energy distribution of each point of the gasket is integrated, and a heat energy distribution diagram is drawn. The temperature field change analysis depends on the changes in time, load and temperature. The thermo-mechanical coupling model is used to perform multiple simulation calculations to obtain the temperature changes of the gasket during operation (such as temperature peak, temperature gradient, etc.). Through these data, the influence of temperature fluctuations on the performance of the gasket material is further analyzed, and finally the gasket temperature field change data is obtained.

[0164] Step S52: Identifying the mechanical stress behavior of the gasket according to the resilience performance data of the thermal conductive gasket, thereby obtaining the mechanical stress behavior data of the gasket;

[0165] In this embodiment, the rebound performance of the thermally conductive gasket is obtained according to the rate and degree of rebound recovery of the rebound performance data. These data can be used for mechanical property testing by a universal testing machine, including drawing stress-strain curves, measuring the rebound modulus, etc. Assuming that the rebound performance of the thermally conductive gasket is strong, its rebound modulus can be defined as a specific value, such as 5 GPa. Through the collection of rebound performance data, combined with the geometric shape of the gasket (such as thickness, diameter, etc.) and the stress distribution in the working environment, the mechanical stress behavior of the gasket under different working conditions is analyzed and identified. For example, if the gasket is in a high temperature and high pressure environment, it will experience large compressive stress and tensile stress, identify the size and action area of ​​these stresses, and finally obtain the gasket mechanical stress behavior data.

[0166] Step S53: performing stress-strain cycle analysis according to the gasket temperature field change data and the gasket mechanical stress behavior data, thereby obtaining gasket loading cycle data;

[0167] In this embodiment, based on the data obtained, a finite element analysis (FEA) method is used to perform stress-strain cycle analysis. Taking into account the temperature field changes and mechanical stress behavior of the gasket under working conditions, combined with actual loading cycle conditions (such as temperature and pressure changes during engine operation), dynamic loading simulation is performed. For example, in the work of an engine sealing gasket, it is assumed that under one working condition, the gasket undergoes multiple loading cycles, including stress fields alternating between high temperature (500°C) and low temperature (100°C). By using a stress-strain relationship model (such as a Masing model or a Bauschinger effect model), the effects of alternating temperature and stress changes on the gasket material can be simulated, and then a stress-strain cycle diagram can be calculated. This process helps identify each round of stress-strain cycle data experienced by the gasket in the actual working environment, thereby obtaining the loading cycle data of the gasket. These data are used to predict the fatigue performance and life of the gasket.

[0168] Step S54: performing fatigue damage accumulation calculation on the gasket loading cycle data, thereby obtaining gasket fatigue damage accumulation data;

[0169] In this embodiment, the fatigue damage accumulation model based on the Miner's Rule or the rain flow counting method is used to process the gasket loading cycle data. The Miner's Rule assumes that the fatigue damage of each loading cycle is independent, and estimates the overall fatigue damage by accumulating the damage values ​​of different cycles. Assume that in a test, the gasket is subjected to a stress-strain cycle caused by pressure changes at a high temperature of 500°C, and the stress amplitude of each cycle is 50 MPa. Under the action of temperature changes, the fatigue damage of the gasket gradually increases in each cycle. By accumulating the degree of damage of each cycle, the fatigue damage accumulation data of the gasket under each working condition can be obtained. If the fatigue life of the gasket is based on the SN curve (stress-life curve), the fatigue damage accumulation rate under specific working conditions (such as temperature, pressure and cycle frequency) can be calculated, and the final failure time of the gasket can be predicted.

[0170] Step S55: Calculate the service life of the thermally conductive gasket according to the accumulated data of gasket fatigue damage, so as to obtain service life data of the thermally conductive gasket.

[0171] In this embodiment, based on the fatigue damage accumulation data obtained, combined with the fatigue limit of the material and the operating conditions, the service life prediction model (such as based on Miners' law or Coffin-Manson equation) is used to estimate the service life of the gasket. Specifically, based on the damage accumulation, operating temperature, load and stress state of each cycle, combined with the fatigue properties of the gasket material, the life of the gasket in a specific use environment can be obtained. For example, for a gasket operating at 500°C and 100 MPa compression load, the fatigue damage data shows that after 10,000 loading cycles, the damage level of the gasket has reached 0.8 (i.e. 80% damage). According to the fatigue life model, it is further estimated that the service life of the gasket is 1,200 hours.

[0172] Optionally, step S6 specifically includes:

[0173] Step S61: performing Monte Carlo simulation on the thermal pad working condition data to obtain random pad working condition data;

[0174] In this embodiment, the working condition data of the thermal pad is generated by Monte Carlo simulation. First, the main working condition parameters of the thermal pad are determined, such as working temperature, pressure, contact surface roughness, contact time, etc. The distribution type and value range of these parameters are obtained through experiments or theoretical analysis. For example, the working temperature fluctuates between 50°C and 200°C, the contact pressure fluctuates between 5MPa and 50MPa, and the contact surface roughness is between Ra 0.2μm and Ra 1.0μm. In the Monte Carlo simulation, these parameters are simulated by random sampling to generate a large amount of working condition data. Through statistical analysis of these data, the performance distribution of the thermal pad under different working conditions can be obtained. The simulation calculation formula can be: Xi = f (P1, P2, ..., Pn); wherein Xi represents the working condition data generated by the i-th simulation, and P1, P2, \dots, Pn are the parameters of each working condition. After multiple simulations, a set of random gasket working condition data sets are finally obtained.

[0175] Step S62: constructing a mathematical model of resilience performance according to the resilience performance data of the thermally conductive gasket; constructing a damage accumulation model according to the service life data of the thermally conductive gasket, the constitutive model of the thermally conductive gasket and the fatigue damage accumulation data of the gasket;

[0176] In this embodiment, according to the relevant experimental data and the rebound performance data of the thermal pad, it can be obtained that the rebound performance is usually related to the elastic modulus, rebound rate and compression stress of the gasket material. Assuming that the material of the gasket is silicone rubber, it has a certain elastic modulus EE and rebound rate RR, and its rebound performance mathematical model can be expressed as: \delta=\frac{P_{\text{max}}}{E}\cdot\left(1-R\right); where \delta is the rebound amount after compression deformation, P_{\text{max}} is the maximum compression pressure, E is the elastic modulus of the material, and R is the rebound rate. This model can quantify the rebound performance of the thermal pad. According to the fatigue test data of the thermal pad, the service life data of the thermal pad, the constitutive model of the thermal pad and the fatigue damage accumulation data of the gasket, the Paris' law or the linear damage accumulation theory (Miner's rule) is used to construct a damage accumulation model. Assume that each loading action causes a certain degree of damage, and its damage accumulation gradually increases with the increase of the number of loading times. The specific damage accumulation equation can be: D=\sum_{i=1}^{N}\left(\frac{n_i}{N_i}\right); where D is the total damage, n_i is the number of i-th loading, and N_i is the number of lifespans under the corresponding load. In this way, the damage of thermal pads in long-term use can be simulated and predicted.

[0177] Step S63: performing model structure coupling on the rebound performance mathematical model and the damage accumulation model, thereby obtaining a thermal conductive gasket performance evaluation model;

[0178] In this embodiment, the rebound performance mathematical model and the damage accumulation model are structurally coupled, taking into account the mutual influence of rebound performance and damage. Assuming that the rebound performance will decrease with the increase of the degree of damage, it can be described by a coupling function. The specific coupling model is as follows: P_{\text{cff}}=P_{\text{base}}\cdot(1-D) \cdot(1-f(R)); wherein P_{\text{eff}} is the effective performance after the influence of rebound and damage, P_{\text{base}} is the baseline performance when undamaged, D is the degree of damage, and f(R) is the influence function of the rebound rate. Through the coupling model, the comprehensive performance evaluation of the thermal conductive gasket under actual working conditions can be obtained.

[0179] Step S64: performing a gasket operating performance evaluation on the random gasket operating condition data using a thermal conductive gasket performance evaluation model, thereby obtaining random gasket operating condition performance evaluation data;

[0180] In this embodiment, the performance evaluation model constructed is used to perform performance evaluation on the generated random gasket working condition data. For example, assuming that the random working condition data includes different contact pressures and temperature ranges, by substituting these data into the performance evaluation model, the gasket performance indicators (such as thermal conductivity, resilience, fatigue life, etc.) under each working condition are calculated. The evaluation can be performed in the following manner: P_{\text{evaluated}}=P_{\text{model}}(P1,P2,…,Pn); wherein P_{\text{evaluated}} is the performance evaluation result under each random working condition, and P_1,P_2,\dots,P_n are different working condition parameters. In this way, a set of performance evaluation data can be obtained.

[0181] Step S65: performing a performance fluctuation range analysis based on the random gasket operating condition performance evaluation data, thereby obtaining thermal conductive gasket operating condition performance fluctuation range data;

[0182] In this embodiment, based on the obtained random gasket working condition performance evaluation data, performance fluctuation range analysis is performed by statistical analysis methods (such as variance analysis, standard deviation calculation, extreme value method, etc.). For example, a statistical method is used to calculate the performance fluctuation range of the thermal conductive gasket under different working conditions, such as the maximum value, minimum value and standard deviation of the thermal conductivity efficiency. Assuming that the performance evaluation data is a set of data points P_{\text{evaluated}}=\{P_1,P_2,\dots,P_k\}, its fluctuation range can be calculated in the following way: \Delta P=P_{\text{max}}−P_{\text{min}}; wherein P_{\text{max}} and P_{\text{min}} are the maximum and minimum values ​​in the performance evaluation data, respectively, and \Delta P is the performance fluctuation range. In this way, the performance fluctuation range data of the thermal conductive gasket under different working conditions can be obtained.

[0183] Step S66: Optimizing the thermally conductive gasket structure data based on the thermally conductive gasket operating performance fluctuation range data, thereby obtaining optimized thermally conductive gasket structure data.

[0184] In this embodiment, based on the obtained performance fluctuation range data of the thermal gasket working condition, a structural optimization algorithm (such as a genetic algorithm, simulated annealing method, etc.) is used to optimize the structural parameters of the thermal gasket. For example, assuming that the structural parameters of the thermal gasket include thickness, density, surface roughness, etc., the gasket performance fluctuation is minimized by the optimization algorithm, thereby improving its stability and performance. The specific optimization goal can be to reduce the performance fluctuation range \Delta P, so that the performance of the thermal gasket is more stable under various working conditions. The optimization process can be described by the following formula: \min\Delta P=\min\left(P_{\max}-P_{\min}\right); the optimized structural data includes the optimal thickness, surface treatment method or material selection, so as to obtain the best thermal gasket structure.

[0185] Optionally, the present specification also provides a compression deformation and resilience performance analysis system of a thermally conductive gasket, which is used to perform the compression deformation and resilience performance analysis method of the thermally conductive gasket as described above, and the compression deformation and resilience performance analysis system of the thermally conductive gasket includes:

[0186] The gasket material constitutive description module is used to obtain the thermal conductive gasket structure data, and to perform gasket material property modeling based on the thermal conductive gasket structure data, thereby obtaining the thermal conductive gasket material property model; perform gasket material constitutive description on the thermal conductive gasket material property model, thereby obtaining the thermal conductive gasket constitutive model;

[0187] The multi-physics field working condition simulation module is used to obtain the working condition data of the thermal conductive gasket, and perform multi-physics field working condition simulation on the constitutive model of the thermal conductive gasket according to the working condition data of the thermal conductive gasket, so as to obtain the working condition simulation data of the thermal conductive gasket; based on the working condition simulation data of the thermal conductive gasket, the temperature-pressure distribution is integrated to obtain the gasket temperature-pressure time series distribution diagram;

[0188] A stress distribution integration module is used to simulate the dynamic response of the gasket according to the gasket temperature-pressure time series distribution diagram, so as to obtain the dynamic response data of the gasket, and integrate the dynamic compression stress distribution of the gasket based on the gasket dynamic response data, so as to obtain the dynamic compression stress distribution diagram of the gasket;

[0189] The resilience performance evaluation module is used to extract the gasket unloading working condition simulation data from the thermal conductive gasket working condition simulation data, so as to obtain the gasket unloading working condition simulation data; based on the gasket unloading working condition simulation data and the gasket dynamic compression stress distribution diagram, the thermal conductive gasket working condition resilience performance evaluation is performed, so as to obtain the thermal conductive gasket resilience performance data;

[0190] A damage accumulation calculation module is used to perform a gasket thermal-mechanical fatigue analysis based on the gasket dynamic compression stress distribution diagram and the thermal conductive gasket rebound performance data, thereby obtaining the gasket fatigue damage accumulation data, and to perform a thermal conductive gasket service life estimation based on the gasket fatigue damage accumulation data, thereby obtaining the thermal conductive gasket service life data;

[0191] The performance fluctuation range analysis module is used to analyze the performance fluctuation range of the thermal gasket according to the service life data of the thermal gasket, the rebound performance data of the thermal gasket and the cumulative fatigue damage data of the gasket, so as to obtain the performance fluctuation range data of the thermal gasket; based on the performance fluctuation range data of the thermal gasket, the thermal gasket structure data is optimized to obtain the optimized thermal gasket structure data.

[0192] Therefore, the embodiments should be regarded as illustrative and non-restrictive from all points, and the scope of the present invention is limited by the appended claims rather than the above description, and it is therefore intended that all changes falling within the meaning and range of equivalent elements of the application documents are included in the present invention.

[0193] The above description is only a specific embodiment of the present invention, so that those skilled in the art can understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but should conform to the widest scope consistent with the principles and novel features invented herein.

Claims

1. A method for analyzing the compression deformation and resilience performance of a thermally conductive gasket, characterized in that: The following steps are involved: Step S1: Acquire the thermal pad structure data, and perform pad material property modeling based on the thermal pad structure data, thereby obtaining a thermal pad material property model; Perform constitutive description of the thermal conductive gasket material characteristic model to obtain a constitutive model of the thermal conductive gasket; Step S2: Acquire the working condition data of the thermal conductive gasket, and perform multi-physics field working condition simulation on the constitutive model of the thermal conductive gasket according to the working condition data of the thermal conductive gasket, so as to obtain the working condition simulation data of the thermal conductive gasket; integrate the temperature-pressure distribution based on the working condition simulation data of the thermal conductive gasket, so as to obtain the gasket temperature-pressure time series distribution diagram; Step S3: performing a gasket dynamic response simulation according to the gasket temperature-pressure time series distribution diagram to obtain gasket dynamic response data, and integrating the gasket dynamic compressive stress distribution based on the gasket dynamic response data to obtain a gasket dynamic compressive stress distribution diagram; Step S4: extracting the gasket unloading working condition simulation data from the thermal conductive gasket working condition simulation data, thereby obtaining the gasket unloading working condition simulation data; Based on the gasket unloading condition simulation data and the gasket dynamic compression stress distribution diagram, the thermal conductive gasket working condition rebound performance evaluation is performed to obtain the thermal conductive gasket rebound performance data; Step S5: Performing a gasket thermal-mechanical fatigue analysis based on the gasket dynamic compression stress distribution diagram and the thermal gasket rebound performance data to obtain the gasket fatigue damage accumulation data, and performing a thermal gasket service life estimation based on the gasket fatigue damage accumulation data to obtain the thermal gasket service life data; Step S5 is specifically as follows: Step S51: integrating the gasket working condition heat energy distribution based on the thermal conductive gasket working condition simulation data to obtain the gasket working condition heat energy distribution diagram, and performing gasket temperature field change analysis on the gasket working condition heat energy distribution diagram to obtain gasket temperature field change data; Step S52: Identifying the mechanical stress behavior of the gasket according to the resilience performance data of the thermal conductive gasket, thereby obtaining the mechanical stress behavior data of the gasket; Step S53: performing stress-strain cycle analysis according to the gasket temperature field change data and the gasket mechanical stress behavior data, thereby obtaining gasket loading cycle data; Step S54: performing fatigue damage accumulation calculation on the gasket loading cycle data, thereby obtaining gasket fatigue damage accumulation data; Step S55: Calculating the service life of the thermal conductive gasket according to the accumulated data of gasket fatigue damage, thereby obtaining service life data of the thermal conductive gasket; Step S6: analyzing the fluctuation range of the thermal gasket working condition performance according to the thermal gasket service life data, the thermal gasket rebound performance data, and the gasket fatigue damage accumulation data, thereby obtaining the thermal gasket working condition performance fluctuation range data; Based on the performance fluctuation range data of the thermal conductive gasket working condition, the thermal conductive gasket structure data is optimized to obtain the optimized thermal conductive gasket structure data. Step S6 is specifically as follows: Step S61: performing Monte Carlo simulation on the thermal pad working condition data to obtain random pad working condition data; Step S62: constructing a mathematical model of resilience performance according to the resilience performance data of the thermally conductive gasket; constructing a damage accumulation model according to the service life data of the thermally conductive gasket, the constitutive model of the thermally conductive gasket and the fatigue damage accumulation data of the gasket; Step S63: performing model structure coupling on the rebound performance mathematical model and the damage accumulation model, thereby obtaining a thermal conductive gasket performance evaluation model; Step S64: performing a gasket operating performance evaluation on the random gasket operating condition data using a thermal conductive gasket performance evaluation model, thereby obtaining random gasket operating condition performance evaluation data; Step S65: performing a performance fluctuation range analysis based on the random gasket operating condition performance evaluation data, thereby obtaining thermal conductive gasket operating condition performance fluctuation range data; Step S66: Optimizing the thermally conductive gasket structure data based on the thermally conductive gasket operating performance fluctuation range data, thereby obtaining optimized thermally conductive gasket structure data.

2. The compression deformation resilience performance analysis method of the thermal conductive gasket according to claim 1, characterized in that: Step S1 is specifically as follows: Step S11: Acquire thermal pad structure data, and extract thermal pad material features from the thermal pad structure data, thereby obtaining thermal pad material data; Step S12: acquiring a gasket material experimental database, and extracting thermally conductive gasket material characteristic data from the gasket material experimental database according to the thermally conductive gasket material data, thereby obtaining the thermally conductive gasket material characteristic data; Step S13: constructing a thermally conductive gasket material characteristic model according to the thermally conductive gasket material characteristic model and the thermally conductive gasket structure data, and performing multi-physics field simulation on the thermally conductive gasket material characteristic model, thereby obtaining gasket compression simulation data; Step S14: integrating the microstructure features of the compressed gasket based on the gasket compression simulation data, thereby obtaining the gasket compression microstructure data; Step S15: Perform constitutive description of the gasket material according to the gasket compression microstructure data, so as to obtain a constitutive model of the thermal conductive gasket.

3. The compression deformation resilience performance analysis method of the thermal conductive gasket according to claim 1, characterized in that: Step S2 is specifically as follows: Step S21: obtaining the working condition data of the thermal conductive gasket, and dividing the working condition data of the thermal conductive gasket into working condition data, so as to obtain the working condition data of the thermal conductive gasket compression and the working condition data of the thermal conductive gasket unloading; Step S22: performing a multi-physics field compression working condition simulation on the constitutive model of the thermal conductive gasket according to the compression working condition data of the thermal conductive gasket, so as to obtain the gasket compression working condition simulation data; Step S23: performing a multi-physics field unloading condition simulation on the thermal conductive gasket constitutive model according to the thermal conductive gasket unloading condition data, thereby obtaining the gasket unloading condition simulation data; Step S24: performing working condition simulation coupling on the gasket compression working condition simulation data and the gasket unloading working condition simulation data, so as to obtain the thermal conductive gasket working condition simulation data; Step S25: integrating the temperature-pressure distribution based on the thermal gasket working condition simulation data, thereby obtaining a gasket temperature-pressure time series distribution diagram.

4. The compression deformation resilience performance analysis method of the thermal conductive gasket according to claim 3, characterized in that: Step S24 is specifically as follows: Step S241: extracting simulated pressure features from the gasket compression working condition simulation data and the gasket unloading working condition simulation data respectively, thereby obtaining compression pressure distribution data and unloading pressure regression data; Step S242: performing physical pressure smoothing processing according to the compression pressure distribution data and the unloading pressure regression data, thereby obtaining pressure smoothing data; Step S243: performing data docking on the gasket compression working condition simulation data and the gasket unloading working condition simulation data, so as to obtain physical superposition simulation data; Step S244: performing physical field coupling on the physical superposition simulation data according to the pressure smoothing data, so as to obtain thermal pad working condition simulation data.

5. The compression deformation resilience performance analysis method of the thermal conductive gasket according to claim 1, characterized in that: Step S3 is specifically as follows: Step S31: selecting a time step according to the gasket temperature-pressure time series distribution diagram, thereby obtaining time-pressure data and time-temperature data; Step S32: setting dynamic loading conditions based on the time-pressure data and the time-temperature data, thereby obtaining dynamic loading conditions; Step S33: performing a gasket dynamic response simulation according to the dynamic loading conditions and the constitutive model of the thermal conductive gasket, thereby obtaining gasket dynamic response data; Step S34: extracting the gasket dynamic deformation characteristics and the gasket dynamic stress distribution characteristics from the gasket dynamic response data, thereby obtaining the gasket dynamic deformation data and the gasket dynamic stress distribution data; Step S35: integrating the dynamic compressive stress distribution according to the gasket dynamic deformation data and the gasket dynamic stress distribution data, so as to obtain a gasket dynamic compressive stress distribution diagram.

6. The compression deformation resilience performance analysis method of the thermal conductive gasket according to claim 5, characterized in that: Step S35 is specifically as follows: Step S351: dividing the gasket dynamic deformation data into gasket deformation regions, thereby obtaining high-frequency deformation region data and low-frequency deformation region data; Step S352: performing time series analysis on the dynamic stress distribution data of the gasket to obtain the time series maximum compressive stress area data; Step S353: performing a region intersection operation according to the time series maximum compression stress region data and the high-frequency deformation region data, thereby obtaining stress concentration region data; Performing a regional intersection operation based on the time series maximum compression stress area data and the low-frequency deformation area data to obtain stress buffer area data; Step S354: integrating the dynamic compressive stress distribution of the gasket dynamic stress distribution data according to the stress buffer area data and the stress concentration area data, thereby obtaining a dynamic compressive stress distribution diagram of the gasket.

7. The compression deformation resilience performance analysis method of a thermally conductive gasket according to claim 1, characterized in that: Step S4 is specifically as follows: Step S41: extracting the gasket unloading working condition simulation data from the thermal conductive gasket working condition simulation data, thereby obtaining the gasket unloading working condition simulation data; Step S42: calculating the gasket deformation stress influence factor according to the gasket dynamic compression stress distribution diagram, thereby obtaining the gasket deformation stress influence factor; Step S43: extracting unloading heat energy characteristics and unloading stress characteristics based on the gasket unloading condition simulation data, thereby obtaining unloading heat energy data and unloading stress data; Step S44: performing a gasket springback simulation according to the gasket deformation stress influencing factor, the unloading heat energy data, and the unloading stress data, thereby obtaining gasket springback simulation data; Step S45: integrating the gasket rebound characteristics based on the gasket rebound simulation data, thereby obtaining the gasket rebound characteristic data; Step S46: Evaluate the gasket rebound performance of the gasket rebound characteristic data to obtain the thermal conductive gasket rebound performance data.

8. A compression deformation and resilience performance analysis system for a thermally conductive gasket, characterized in that: Used to perform the compression deformation and resilience performance analysis method of the thermal conductive gasket as claimed in claim 1, the compression deformation and resilience performance analysis system of the thermal conductive gasket comprises: The gasket material constitutive description module is used to obtain the thermal conductive gasket structure data, and to perform gasket material property modeling based on the thermal conductive gasket structure data, thereby obtaining the thermal conductive gasket material property model; perform gasket material constitutive description on the thermal conductive gasket material property model, thereby obtaining the thermal conductive gasket constitutive model; The multi-physics field working condition simulation module is used to obtain the working condition data of the thermal conductive gasket, and perform multi-physics field working condition simulation on the constitutive model of the thermal conductive gasket according to the working condition data of the thermal conductive gasket, so as to obtain the working condition simulation data of the thermal conductive gasket; based on the working condition simulation data of the thermal conductive gasket, the temperature-pressure distribution is integrated to obtain the gasket temperature-pressure time series distribution diagram; A stress distribution integration module is used to simulate the dynamic response of the gasket according to the gasket temperature-pressure time series distribution diagram, so as to obtain the dynamic response data of the gasket, and integrate the dynamic compression stress distribution of the gasket based on the gasket dynamic response data, so as to obtain the dynamic compression stress distribution diagram of the gasket; The resilience performance evaluation module is used to extract the gasket unloading working condition simulation data from the thermal conductive gasket working condition simulation data, so as to obtain the gasket unloading working condition simulation data; based on the gasket unloading working condition simulation data and the gasket dynamic compression stress distribution diagram, the thermal conductive gasket working condition resilience performance evaluation is performed, so as to obtain the thermal conductive gasket resilience performance data; A damage accumulation calculation module is used to perform a gasket thermal-mechanical fatigue analysis based on the gasket dynamic compression stress distribution diagram and the thermal conductive gasket rebound performance data, thereby obtaining the gasket fatigue damage accumulation data, and to perform a thermal conductive gasket service life estimation based on the gasket fatigue damage accumulation data, thereby obtaining the thermal conductive gasket service life data; The performance fluctuation range analysis module is used to analyze the performance fluctuation range of the thermal gasket according to the service life data of the thermal gasket, the rebound performance data of the thermal gasket and the cumulative fatigue damage data of the gasket, so as to obtain the performance fluctuation range data of the thermal gasket; based on the performance fluctuation range data of the thermal gasket, the thermal gasket structure data is optimized to obtain the optimized thermal gasket structure data.

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