Method and system for evaluating heat resistance and shock resistance of refractory material

Abstract

The method comprises the following steps: constructing a thermal shock test environment, carrying out a thermal shock cycle test on the refractory material, and collecting thermal shock cycle data; monitoring and recording the performance change of the material in the thermal shock cycle process; based on the thermal shock cycle data, a thermal shock historical memory model of the refractory material is established, and the change rule of the performance of the refractory material along with thermal shock cycle is analyzed; constructing a life prediction model, and predicting the service life of the material under a specific working condition; comprehensively evaluating the heat resistance and earthquake resistance of the material according to a model analysis result, and outputting an evaluation result. By monitoring the temperature gradient, the residual stress and the crack propagation in the thermal shock cycle in real time, the cumulative damage model and the service life prediction model are established, and accurate quantitative evaluation of the heat resistance and shock resistance of the refractory material is realized. The scientificity and dynamic adaptability of material performance evaluation are remarkably improved, and technical support is provided for material optimization design and high-temperature environment application.

Description

Technical Field

[0001] The present invention relates to the field of material science and technology, and in particular to a method and system for evaluating the heat and shock resistance of refractory materials. Background Art

[0002] As a key material in high temperature industry, refractory materials are widely used in metallurgy, building materials, energy, chemical industry and other fields. Their performance is directly related to the safety, durability and economy of industrial equipment. In recent years, with the development of high temperature industry, the requirements for the performance of refractory materials have gradually increased, especially the heat and shock resistance of materials under high temperature impact and rapid cooling and heating conditions have become the focus of research and application.

[0003] Traditional refractory material evaluation methods usually focus on the high-temperature strength, thermal conductivity or thermal expansion of materials under a single working condition, and lack a systematic evaluation of the changes in material performance under the interaction of multiple factors in actual complex working conditions. For example, existing technologies mostly use static experimental methods to subject materials to a limited number of thermal shock cycles, which makes it difficult to fully capture the dynamic performance evolution of materials during actual industrial use. In addition, existing technologies' research on material failure mechanisms mostly stays at the analysis of surface phenomena, lacking a quantitative description and prediction of damage accumulation and performance degradation processes.

[0004] The existing technologies have the following major deficiencies in the evaluation of the thermal and shock resistance of refractory materials: First, most evaluation methods focus on the single thermal shock performance test of the material, lack the consideration of the long-term stability and durability of the material performance under multiple cycles of thermal shock conditions, and it is difficult to accurately reflect the actual service life of the material; second, the existing testing equipment and methods mostly focus on the measurement of macroscopic performance parameters, such as strength and crack extension, and fail to fully combine the microstructural change data for in-depth analysis, resulting in the accuracy and scientificity of the evaluation results being limited; third, there is a lack of effective modeling tools to link experimental data with the performance degradation process under actual working conditions. The existing life prediction models are mostly based on simple empirical formulas, which are difficult to adapt to the changing needs of complex working conditions. These technical limitations significantly reduce the efficiency of reliability evaluation of refractory materials in high temperature environments, and cannot provide sufficient theoretical support for material improvement and working condition optimization. Summary of the invention

[0005] In view of the above-mentioned problems, the present invention is proposed.

[0006] Therefore, the technical problem solved by the present invention is that the existing refractory material heat and shock resistance assessment technology mainly has the problems of insufficient assessment depth, inaccurate life prediction and limited scope of application.

[0007] In order to solve the above technical problems, the present invention provides the following technical solutions: A method for evaluating the thermal shock resistance of refractory materials, comprising: constructing a thermal shock test environment, performing a thermal shock cycle test on the refractory materials, and collecting thermal shock cycle data; Monitor and record the performance changes of materials during thermal shock cycles; Based on the thermal shock cycle data, a thermal shock history memory model of refractory materials is established to analyze the change of its performance with thermal shock cycles; Construct a life prediction model to predict the service life of materials under specific working conditions; Based on the model analysis results, a comprehensive evaluation of the thermal and seismic resistance of the material is conducted and the evaluation results are output.

[0008] As a preferred embodiment of the method for evaluating the thermal shock resistance of refractory materials described in the present invention, the thermal shock cycle test includes rapidly heating and cooling the refractory materials within a set temperature range, and controlling the heating rate and the cooling rate to simulate the thermal shock conditions in actual use.

[0009] As a preferred embodiment of the method for evaluating the thermal shock resistance of refractory materials of the present invention, the collecting of thermal shock cycle data includes collecting temperature distribution, thermal expansion coefficient, thermal stress and surface crack growth data generated in real time during the thermal shock cycle of the material; The collected data are stored and preliminarily processed in real time to generate a time series data set containing material performance parameters during multiple thermal shock cycles.

[0010] As a preferred embodiment of the method for evaluating the thermal shock resistance of refractory materials of the present invention, the monitoring and recording of the performance changes of the material during the thermal shock cycle includes using an ultrasonic emission sensor to monitor the formation and expansion of cracks inside the material in real time; The dynamic changes of the temperature field on the material surface are recorded by thermal imager; Use strain sensors to measure the stress-strain distribution of materials under thermal shock; Perform comprehensive analysis to generate a property change profile that includes crack behavior, temperature response, and stress changes.

[0011] As a preferred embodiment of the method for evaluating the thermal shock resistance of refractory materials of the present invention, the establishment of a thermal shock history memory model of refractory materials includes extracting key parameters related to material damage and performance changes based on the collected thermal shock cycle data, including temperature gradient , residual stress , crack length and thermal shock cycles ; Construct the cumulative damage function and establish the cumulative damage model of the material , which is of the form: , in, and It is a material property index, reflecting the influence of temperature gradient and residual stress on damage; Establish performance degradation model based on cumulative damage function , establish material properties The relationship model with the degree of damage is in the form of: , in, is the initial performance index of the material, is the performance attenuation coefficient; Use the least squares method or machine learning algorithm to adjust the parameters in the model. , , Perform fitting and optimization; Applying optimized thermal shock history memory model to predict material properties Over time or thermal shock cycles of the changing trend.

[0012] As a preferred embodiment of the method for evaluating the thermal shock resistance of refractory materials according to the present invention, the life prediction model is constructed by establishing a relationship model between thermal shock damage and the number of cycles, based on the cumulative damage function. and thermal shock cycles , construct the functional relationship between thermal shock damage and cycle number: , in, For the The temperature gradient of the thermal shock, For the The residual stress of thermal shock, For the Secondary thermal shock crack length, and is the material characteristic parameter; Construct critical damage criteria for life prediction and set critical damage values ​​for materials , that is, the cumulative damage degree when the material performance decays to the critical point of failure, meets the following conditions: , in, The minimum acceptable performance index of the material. is the initial performance of the material; Calculate the thermal shock cycle life according to the damage criterion , combined with the thermal shock damage model , solve the equation , and the corresponding number of thermal shock cycles is obtained , which is the predicted service life of the material under specific thermal shock conditions; Adjust the damage model parameters according to the actual working conditions , , and critical damage value , recalculate the material life , to predict its service life under different working conditions; The results of the life prediction model calculation are output as a report, including the thermal shock life, failure trend and key influencing factors of the material under specific working conditions.

[0013] As a preferred embodiment of the method for evaluating the thermal shock resistance of refractory materials of the present invention, the comprehensive evaluation of the thermal shock resistance of the material includes extracting key performance indicators of the material, including cumulative damage value, performance retention rate and predicted life, based on the analysis results of the thermal shock history memory model and the life prediction model; Classify materials according to the degree of damage and performance attenuation rate into high performance, medium performance, low performance and failure categories; Evaluate the crack growth rate, performance change trend and failure risk of materials; Output evaluation report, including material performance level, predicted life, failure cause and optimization suggestions.

[0014] A refractory material heat and shock resistance evaluation system, characterized in that it includes: Thermal shock test module: build a thermal shock test environment, conduct thermal shock cycle tests on refractory materials, and collect thermal shock cycle data; Performance change monitoring module: monitors and records the performance changes of materials during thermal shock cycles; Thermal shock history memory model building module: based on the thermal shock cycle data, a thermal shock history memory model of refractory materials is established to analyze the change of its performance with thermal shock cycles; Life prediction module: build a life prediction model to predict the service life of materials under specific working conditions; Comprehensive evaluation module: Based on the model analysis results, the thermal and seismic resistance of the material is comprehensively evaluated and the evaluation results are output.

[0015] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above method when executing the computer program.

[0016] A computer-readable storage medium stores a computer program, which implements the steps of the method described above when executed by a processor.

[0017] The beneficial effects of the present invention are as follows: by constructing a thermal shock test environment and collecting multiple cycles of thermal shock data, the present invention can fully reflect the dynamic performance changes of refractory materials under complex thermal shock conditions, thereby overcoming the limitations of the prior art that only focuses on a single condition or short-term performance; By establishing a thermal shock history memory model, the damage accumulation process of the material in the thermal shock cycle is quantified, and the relationship between damage and performance degradation is deeply revealed, providing a scientific basis for accurately analyzing the performance degradation law of the material; Combining the thermal shock history memory model and the life prediction model, it is possible to calculate the remaining life of the material according to the specific working conditions, predict the maximum number of thermal shock cycles of the material, and provide guidance for the safety of use and replacement cycle of refractory materials; Through comprehensive evaluation of the heat and shock resistance of materials, it provides performance grade classification, life prediction results and optimization suggestions to help users select suitable materials or adjust working parameters to improve the reliability and economy of material use; The present invention is applicable to various types of refractory materials, and can flexibly adjust test parameters and model settings to meet different working conditions, and has strong versatility and applicability; Through scientific evaluation methods, the present invention reduces the trial and error costs in the use of refractory materials, reduces equipment operation risks, and improves the operating efficiency and safety of high-temperature industries. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work, among which: Figure 1 An overall flow chart of a method for evaluating the thermal and shock resistance of refractory materials provided in the first embodiment of the present invention. DETAILED DESCRIPTION

[0019] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0020] Example 1, reference Figure 1 , as one embodiment of the present invention, provides a method for evaluating the heat and shock resistance of refractory materials, comprising: S1: Construct a thermal shock test environment, conduct thermal shock cycle tests on refractory materials, and collect thermal shock cycle data.

[0021] The refractory material is rapidly heated and cooled within a set temperature range, and the heating rate and cooling rate are controlled to simulate the thermal shock conditions in actual use.

[0022] Collect the temperature distribution, thermal expansion coefficient, thermal stress and surface crack extension data generated in real time during the thermal shock cycle of the material; store and preliminarily process the collected data in real time to generate a time series data set containing material performance parameters during multiple thermal shock cycles.

[0023] Furthermore, temperature distribution refers to the temperature values ​​of a material at different locations at a certain moment, usually expressed in the form of spatial distribution (e.g. ). Temperature gradient is a physical quantity derived from temperature distribution. When a material experiences rapid heating or cooling in a thermal shock cycle, a significant temperature gradient will form between the surface and the interior. The larger the temperature gradient, the more significant the thermal stress. Therefore, temperature distribution is the basis of temperature gradient, and temperature gradient directly affects the magnitude of thermal stress.

[0024] Coefficient of thermal expansion Describes the expansion or contraction behavior of a material when subjected to temperature changes and is defined as: , in, is the change in material length, is the initial length, For temperature changes.

[0025] Heat stress It arises from the restricted expansion or contraction of a material when it is subject to a temperature gradient and is expressed as: , in, is the elastic modulus of the material, is the coefficient of thermal expansion, is the temperature gradient.

[0026] Residual stress After thermal shock cycles, there may be thermal stresses in the material that cannot be completely released. These stresses are called residual stresses. The magnitude and distribution of residual stresses depend on the thermal expansion coefficient, temperature gradient, and plastic deformation capacity of the material.

[0027] The thermal expansion coefficient is a key factor affecting residual stress and thermal stress. The temperature gradient in the thermal shock cycle causes the strain change of the material through the thermal expansion coefficient, which in turn generates thermal stress. When the thermal shock stops, part of the thermal stress cannot restore equilibrium, forming residual stress.

[0028] Surface crack growth is a dynamic behavior that describes the crack growth during thermal shock cycles and is usually expressed in terms of crack length. and crack growth rate Indicates that crack growth is affected by the combined effects of thermal stress and temperature gradient.

[0029] The driving force for crack growth mainly comes from thermal stress. When the thermal stress exceeds the fracture toughness of the material When , the crack will expand rapidly. The expression of crack expansion is: , in, is heat stress, is the elastic modulus; Indicates a proportional relationship, where it represents the crack growth rate and the square of stress ( ) and is proportional to the elastic modulus This means that at the same elastic modulus, the greater the thermal stress, the faster the crack propagation rate.

[0030] Crack length The expansion rate increases with the number of thermal shock cycles, and is controlled by the temperature distribution, thermal expansion coefficient, and fracture toughness of the material.

[0031] Crack extension is a dynamic manifestation of crack length. Monitoring of surface crack extension reflects the change of crack length over time, and crack length can be used to quantify the degree of damage accumulation of materials during thermal shock cycles.

[0032] Furthermore, the temperature gradient is the direct cause of thermal stress, and the temperature distribution determines the size and direction of the gradient. The thermal expansion coefficient connects the thermal and mechanical responses of the material and is an important parameter of thermal stress and residual stress. Thermal stress provides the driving force for crack propagation, and residual stress affects the direction and rate of crack propagation. Crack propagation behavior directly determines the growth of crack length, and crack length is an important representation of the degree of material damage.

[0033] This close physical relationship makes temperature gradient, thermal expansion coefficient, thermal stress, residual stress and crack extension data the core parameters for evaluating the thermal and shock resistance of materials. By collecting these data and analyzing their relationship, the performance change mechanism and failure law of materials under thermal shock environment can be fully revealed, providing a scientific basis for the optimized design and application of materials.

[0034] It should be noted that controlling the heating and cooling rates and setting a specific temperature range can comprehensively examine the thermal stress response and crack propagation behavior of refractory materials in a rapid temperature change environment, providing more accurate data support for the reliability analysis of the material. By accurately controlling the heating and cooling rates and collecting real-time performance data, the present invention can be widely used in the design optimization and failure analysis of refractory materials, especially in high-temperature equipment in the fields of metallurgy, chemical industry and energy. The collected time series data set can provide scientific input for subsequent thermal shock history memory models and life prediction models, support dynamic evaluation of the long-term performance of materials, and provide theoretical guidance for the safe operation of high-temperature equipment.

[0035] S2: Monitor and record the performance changes of materials during thermal shock cycles.

[0036] Ultrasonic emission sensors are used to monitor the formation and expansion of cracks inside the material in real time.

[0037] The dynamic changes of the material surface temperature field are recorded by a thermal imager.

[0038] The strain sensor is used to measure the stress and strain distribution of the material under thermal shock.

[0039] Perform comprehensive analysis to generate a property change profile that includes crack behavior, temperature response, and stress changes.

[0040] Furthermore, the ultrasonic emission sensor is a highly sensitive device for monitoring the dynamic behavior of cracks inside materials, and can capture high-frequency sound wave signals released by cracks during their expansion. In the present invention, the ultrasonic emission sensor monitors the formation and expansion process of cracks in real time, and converts the signals into crack expansion rate and energy parameters. The acoustic wave characteristics of crack expansion can directly reflect the cumulative state of damage inside the material, and are the core tools of non-destructive testing (NDT). Acoustic emission monitoring technology can capture the transient behavior of crack initiation and expansion, and has significant advantages in the detection of hidden damage inside materials. By recording the frequency and intensity of the ultrasonic emission signal in real time, the crack expansion rate and energy release can be quantified, thereby revealing the dynamic mechanism of crack behavior. This dynamic monitoring capability enables the present invention to accurately determine the critical point of crack expansion, laying the foundation for material performance evaluation and life prediction.

[0041] The thermal imager captures infrared radiation on the surface of the material to generate a real-time distribution map of the temperature field. In the present invention, the thermal imager is used to record the changes in the temperature field on the surface of the material during the thermal shock cycle, and infer the thermal stress distribution of the material by analyzing the temperature gradient. The surface temperature field directly determines the thermal expansion behavior and the area of ​​thermal stress concentration, and is an important influencing factor for crack initiation and propagation. The thermal imager captures the changes in the temperature field on the surface of the material, which can not only locate the area of ​​thermal stress concentration, but also infer the direction and potential path of crack propagation through temperature gradient analysis. Compared with traditional methods, the non-contact measurement of the thermal imager ensures the continuity and high resolution of the data, providing important support for the real-time evaluation of the thermal shock performance of materials.

[0042] Strain sensors are used to measure the stress-strain response of materials under thermal shock and generate strain time series data. In the present invention, the strain sensor can capture the distribution and dynamic changes of tiny strains caused by uneven temperature fields. The distribution characteristics of stress and strain are important indicators for evaluating the degradation of mechanical properties and crack behavior of materials. The strain sensor records the strain distribution of materials in thermal shock cycles in real time, and can accurately reflect the mechanical response caused by thermal expansion and thermal stress. By analyzing the strain data, the elastic limit and plastic behavior of the material can be determined, further revealing the mechanical cause of the damage. This mechanical property monitoring capability provides a theoretical basis for material design and optimization.

[0043] Performance change records refer to dynamic data sets generated by comprehensive analysis of crack behavior, temperature response, and stress changes during thermal shock cycles. Through multi-parameter linkage analysis, the performance evolution of materials under thermal shock conditions can be fully revealed, providing high-quality input data for subsequent model construction.

[0044] Furthermore, the present invention realizes the synchronous collection and analysis of multiple physical quantities by integrating the real-time monitoring functions of ultrasonic emission sensors, thermal imagers and strain sensors. This cross-domain data fusion technology breaks through the limitations of traditional single parameter monitoring, allowing the internal cracks, surface temperature fields and stress-strain responses of materials to be fully captured during thermal shock cycles, improving the refinement and timeliness of data.

[0045] Comprehensive analysis of crack behavior, temperature response and stress changes to generate performance change records can not only fully reveal the dynamic damage law of the material, but also provide high-quality multi-dimensional data input for subsequent modeling. Compared with single parameter analysis, comprehensive analysis can more accurately describe the dynamic change process of material performance and provide scientific support for life prediction and optimized design.

[0046] S3: Based on the thermal shock cycle data, a thermal shock history memory model of refractory materials is established to analyze how its performance changes with thermal shock cycles.

[0047] Extract key parameters related to material damage and performance changes, including temperature gradients, from acquired thermal shock cycle data , residual stress , crack length and thermal shock cycles .

[0048] Construct the cumulative damage function and establish the cumulative damage model of the material , which is of the form: , in, and It is a material property index, reflecting the influence of temperature gradient and residual stress on damage; The effect of temperature gradient on damage is expressed by the exponential It indicates the nonlinear effect of temperature gradient. The residual stress is expressed as an exponential Affects damage, reflecting the correlation between stress concentration and damage rate; In order to use a logarithmic function to describe the effect of crack extension on damage and prevent the crack parameters from introducing a non-physical infinite increase trend.

[0049] Establish performance degradation model based on cumulative damage function , establish material properties The relationship model with the degree of damage is in the form of: , in, is the initial performance index of the material, is the performance attenuation coefficient.

[0050] Use the least squares method or machine learning algorithm to adjust the parameters in the model. , , Perform fitting and optimization.

[0051] Applying optimized thermal shock history memory model to predict material properties Over time or thermal shock cycles of the changing trend.

[0052] Assume that the experiment collects discrete time points Data, damage function It can be expressed as a discrete integral form: , This expression captures the damage increment of the material at each moment by summing up the discrete data.

[0053] Damage Function After the calculation is completed, the performance degradation model can be substituted: , By calculation The values ​​at different time points can be used to plot the performance change over time and further deduce the service life of the material.

[0054] It should be noted that the thermal shock history memory model aims to quantify the law of damage accumulation of materials in thermal shock cycles and provide basic data for subsequent performance degradation models. , residual stress , crack length and thermal shock cycles The model can capture the dynamic behavior of material performance degradation by taking into account key parameters such as .

[0055] Damage Accumulation Function The design is based on the fact that material damage in actual working conditions is caused by multiple factors. These factors include: temperature gradient The inhomogeneity of the temperature field leads to thermal stress concentration, which plays a major role in crack initiation and expansion; residual stress The magnitude and distribution of residual stress directly affect the crack growth rate and is an important driving factor for material damage; the crack length , crack extension is the external manifestation of damage accumulation, and its growth is closely related to the internal stress field and the fracture toughness of the material.

[0056] The model models the nonlinear relationship between these parameters in fractional form, reflecting the mutual coupling between temperature gradient, stress distribution and crack behavior. Used to smooth out the extreme effects of crack growth on damage and prevent the model from losing stability.

[0057] Integration range of cumulative damage Make sure the model captures the cumulative effect of damage over time, rather than just focusing on one moment in time.

[0058] S4: Construct a life prediction model to predict the service life of materials under specific working conditions.

[0059] Establish the relationship model between thermal shock damage and cycle number, based on the cumulative damage function and thermal shock cycles , construct the functional relationship between thermal shock damage and cycle number: , in, For the The temperature gradient of the thermal shock, For the The residual stress of thermal shock, For the Secondary thermal shock crack length, and is the material characteristic parameter.

[0060] Construct critical damage criteria for life prediction and set critical damage values ​​for materials , that is, the cumulative damage degree when the material performance decays to the critical point of failure, meets the following conditions: , in, The minimum acceptable performance index of the material. is the initial performance of the material.

[0061] Calculate the thermal shock cycle life according to the damage criterion , combined with the thermal shock damage model , solve the equation , and the corresponding number of thermal shock cycles is obtained , which is the predicted service life of the material under specific thermal shock conditions. "Specific conditions" refer to the specific temperature gradient range, stress distribution and crack length that the refractory material may be subjected to in actual use.

[0062] Adjust the damage model parameters according to the actual working conditions , , and critical damage value , recalculate the material life , in order to predict its service life under different working conditions.

[0063] The results of the life prediction model calculation are output as a report, including the thermal shock life, failure trend and key influencing factors of the material under specific working conditions.

[0064] It should be noted that by introducing the integral form, accumulating the contribution of each thermal shock cycle to material damage, and comprehensively considering the three core factors of temperature gradient, residual stress and crack extension, the multi-physical field coupling mechanism of the damage process is reflected. The fractional structure and logarithmic function smooth the influence of extreme values, ensuring the stability and physical rationality of the model. Existing life assessment methods are usually based on empirical formulas, lacking a quantitative description of the cumulative effects of multiple thermal shocks, and are difficult to reflect the dynamic damage evolution under complex working conditions. The present invention constructs a cumulative damage model by coupling multiple factors, which can accurately describe the damage accumulation process of the material and significantly improve the scientificity and accuracy of the prediction.

[0065] by Expressing the critical state of material performance, the failure condition of the material is related to the cumulative damage function. By setting the critical performance value , which can uniformly measure the failure point of materials under different working conditions. Traditional methods are difficult to quantify the relationship between material performance degradation and damage accumulation. This invention uses a performance degradation model to convert the cumulative damage value It is converted into the physical quantity of performance degradation and clarifies the judgment criteria for performance failure.

[0066] Model parameters can be dynamically adjusted according to different working conditions , , , recalculate material life , providing flexible prediction capabilities for material applications in complex environments.

[0067] S5: Based on the model analysis results, conduct a comprehensive evaluation of the thermal and seismic resistance of the material and output the evaluation results.

[0068] Based on the analysis results of the thermal shock history memory model and the life prediction model, the key performance indicators of the material are extracted, including the cumulative damage value, performance retention rate and predicted life.

[0069] Materials are graded according to the degree of damage and performance attenuation rate and divided into high performance, medium performance, low performance and failure categories.

[0070] The crack growth rate, performance change trend and failure risk of the material are evaluated.

[0071] Output evaluation report, including material performance level, predicted life, failure cause and optimization suggestions.

[0072] Specifically, when the performance indicators of the material are shown according to the model analysis results In the test temperature gradient range The initial performance curve is met and the damage accumulation degree Less than critical value 20% (i.e. ), the evaluation model classifies the material according to the high performance category; further analysis of the damage growth rate , if its maximum value satisfies (in, is the maximum number of cycles tested), it is classified as a “high performance material”.

[0073] Output evaluation report including material performance retention rate , damage accumulation value, thermal and shock resistance level, and the performance stability conclusion of the material under the existing working conditions, and predict the applicable fields and service life recommendations.

[0074] When the model analysis results show the performance indicators of the material In the test temperature gradient range The internal amplitude does not exceed the initial performance index ±10% fluctuation (i.e. ), and the degree of damage accumulation When the evaluation model is used, the material is classified according to the medium performance category; the crack length Growth rate If the maximum value satisfies (in is the maximum permissible crack length), it is classified as a “medium performance material”.

[0075] Output evaluation report, including the material performance variation range, the impact of crack propagation behavior on material stability, and optimization and improvement measures for the material under this condition. Deviation from initial performance indicators More than ±10% and less than ±30% (i.e. ), and the degree of damage accumulation When the material is classified into low performance categories, the evaluation model further analyzes the performance decay rate. , if its maximum value satisfies , it is classified as "low performance material".

[0076] Output evaluation report, including material life prediction value ( ), the contribution of crack propagation behavior, as well as failure risk warning and alternative solution recommendations of the material under this working condition.

[0077] When the model analysis results show the performance indicators of the material Below minimum performance index , and the degree of damage accumulation When evaluating the model, the failure category of the material is classified; the superposition effect of thermal shock cycles on damage is further analyzed, and the crack growth acceleration is calculated. , if its maximum value satisfies , it is attributed to the failure dominated by crack behavior. Output evaluation report, including failure cause analysis, risk assessment for specific working conditions, and emergency adjustment strategy and optimization plan.

[0078] When the model analysis results show the performance indicators of the material under various thermal shock cycle conditions Thermal Shock History Memory Model The fitting error More than 5% (i.e. ), and the damage accumulation curve shows nonlinear mutation (such as ), trigger the abnormal condition identification process; extract the key environmental parameters that cause performance mutations (such as temperature change rate Output evaluation report, including material sensitivity analysis to special working conditions, performance impact range under abnormal environment, and selection suggestions for optimized materials.

[0079] It should be noted that in performance failure analysis, the crack growth acceleration is introduced and damage deviation error , which can accurately identify the nonlinear damage growth behavior and abnormal working conditions of materials, especially the assessment of failure risks in extreme environments. The existing technology is difficult to accurately predict the nonlinear trend of crack growth and the risk of sudden failure. The present invention can identify the failure risk at an early stage by analyzing the crack growth acceleration and model error, and propose an optimization plan by adjusting the parameters.

[0080] According to the performance classification results, it can help engineering and technical personnel quickly select materials suitable for high-temperature environments, especially for application scenarios with high life requirements, such as metallurgical furnace linings, chemical equipment, etc. Risk assessment based on crack growth acceleration and model error provides a scientific basis for failure warning of high-temperature industrial equipment, reduces the possibility of accidents, and improves the safety of equipment operation. For different working conditions, the optimization scheme proposed in the report can guide the use of materials and the adjustment of equipment operating parameters, extend the service life of materials and improve the economy of equipment. This model and analysis method can also be used for material performance evaluation in other dynamic environments, such as spacecraft protective materials, nuclear energy equipment, etc., and has broad application prospects.

[0081] Embodiment 2 is the second embodiment of the present invention, which is different from the previous embodiment in that: If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention can be essentially or partly embodied in the form of a software product that contributes to the prior art or partly in the current technical solution. The current computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., which can store program codes.

[0082] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0083] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0084] Example 3 is an embodiment of the present invention, which provides a refractory material thermal shock resistance assessment system, characterized in that it includes a thermal shock test module, a performance change monitoring module, a thermal shock history memory model construction module, a life prediction module and a comprehensive assessment module.

[0085] Thermal shock test module: construct a thermal shock test environment, conduct thermal shock cycle tests on refractory materials, and collect thermal shock cycle data.

[0086] Performance change monitoring module: monitors and records the performance changes of materials during thermal shock cycles.

[0087] Thermal shock history memory model building module: Based on the thermal shock cycle data, a thermal shock history memory model of refractory materials is established to analyze the change pattern of its performance with thermal shock cycles.

[0088] Life prediction module: Build a life prediction model to predict the service life of materials under specific working conditions.

[0089] Comprehensive evaluation module: Based on the model analysis results, the thermal and seismic resistance of the material is comprehensively evaluated and the evaluation results are output.

[0090] Example 4 is an embodiment of the present invention, which provides a method for evaluating the thermal and shock resistance of refractory materials. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation / comparative experiments.

[0091] In order to verify the thermal and shock resistance of different refractory materials, a thermal shock test environment was constructed and six materials (marked as material A to material F) were tested. The specific steps of the experiment are as follows: High-precision thermal shock test equipment was used, and the test temperature range was set from 310K to 520K, the heating rate was 50K / s, the cooling rate was 40K / s, and a single cycle lasted for 2 minutes to simulate high-frequency thermal shock conditions.

[0092] Six samples were selected from commonly used industrial refractory materials and processed into standard cubes with a size of 10mm×10mm×10mm to ensure the consistency of the test samples and the reliability of the data.

[0093] Place the specimen in the test equipment for continuous thermal shock cycles. Gradually increase the number of thermal shock cycles and record key data every 10 times until the material properties approach the critical value or obvious signs of failure appear.

[0094] Use an infrared thermal imager to measure the temperature difference on the sample surface and record the temperature gradient ; Monitoring residual stress after thermal shock by strain gauges ;Use ultrasonic emission sensors to capture crack formation and expansion signals and measure crack length .

[0095] The temperature gradient, residual stress, and crack length of each material under different numbers of thermal shock cycles are collected, and the damage accumulation and performance retention rate are recorded to provide basic data for subsequent analysis.

[0096] Based on the experimental data, the performance retention rate and predicted life of each material are calculated, and the material performance is graded through the model analysis results.

[0097] The output includes a comprehensive evaluation report of material performance level, damage accumulation trend and life prediction value, and provides optimization suggestions to guide material application and working condition adjustment.

[0098] The final experimental data is shown in Table 1.

[0099] Table 1 Experimental data table Material Type Temperature gradient (K) Residual stress(Pa) Crack length(mm) Damage accumulation (D) Predicted life (number of cycles) Performance retention rate (%) Material A 310 2150000 0.08 0.12 1300 96 Material B 340 2400000 0.13 0.22 1050 90 Material C 390 2600000 0.17 0.35 900 83 Material D 420 2850000 0.22 0.42 750 78 Material E 470 3050000 0.29 0.55 550 70 Material F 520 3300000 0.35 0.65 400 60 From the table data, we can clearly see the performance differences of different materials in thermal shock cycles.

[0100] High-performance materials (materials A and B): performance retention rates are 96% and 90% respectively, crack length is short (0.08mm and 0.13mm), damage accumulation value is low (0.12 and 0.22), and predicted life is long (1300 times and 1050 times). These materials show good thermal shock resistance and are suitable for high-frequency thermal shock conditions.

[0101] Medium performance materials (materials C and D): performance retention rates are 83% and 78%, crack length and residual stress have increased, damage accumulation values ​​are 0.35 and 0.42 respectively, and the predicted life is shortened to 900 and 750 times. This type of material is suitable for moderate thermal shock conditions, but crack extension control needs to be optimized.

[0102] Low performance materials (materials E and F): performance retention rates are 70% and 60%, crack length increases significantly (0.29 mm and 0.35 mm), damage accumulation values ​​are high (0.55 and 0.65), and predicted life is short (550 times and 400 times). These materials are difficult to meet application requirements under high-intensity thermal shock conditions.

[0103] The present invention can accurately quantify the impact of thermal shock cycles on material properties by real-time collection of temperature gradient, residual stress and crack extension data and combining cumulative damage model and performance attenuation model.

[0104] The results of performance retention rate and predicted life in the table intuitively show the attenuation trend of the material under different working conditions. The present invention provides a scientific basis for material optimization design by establishing a performance classification standard.

[0105] High-performance materials (such as materials A and B) can be used in high-frequency thermal shock environments, such as metallurgical furnace linings and high-temperature chemical equipment.

[0106] For medium and low performance materials, their service life can be extended by adjusting the operating conditions (such as reducing temperature gradients or stress levels).

[0107] The data results provide clear directions for optimizing material selection and design for different operating conditions.

[0108] In terms of damage accumulation and life prediction, the model method of the present invention solves the problem that the prior art is difficult to quantify the coupling effect of multiple physical fields.

[0109] In summary, this embodiment verifies the scientificity and innovation of the present invention in the evaluation of thermal shock resistance of refractory materials through dynamic testing and multi-parameter modeling, and provides comprehensive technical support for the optimal design of materials in high-temperature environments.

[0110] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for evaluating the heat and shock resistance of refractory materials, characterized in that: include: Construct a thermal shock test environment, conduct thermal shock cycle tests on refractory materials, and collect thermal shock cycle data; Monitor and record the performance changes of materials during thermal shock cycles; Based on the thermal shock cycle data, a thermal shock history memory model of refractory materials is established to analyze the change of its performance with thermal shock cycles; Construct a life prediction model to predict the service life of materials under specific working conditions; Based on the model analysis results, a comprehensive evaluation of the thermal and seismic resistance of the material is conducted and the evaluation results are output.

2. The method for evaluating the heat and shock resistance of refractory materials according to claim 1, characterized in that: The thermal shock cycle test includes rapidly heating up and cooling down the refractory material within a set temperature range, and controlling the heating rate and the cooling rate to simulate the thermal shock condition in actual use.

3. The method for evaluating the heat and shock resistance of refractory materials according to claim 2, characterized in that: The collecting of thermal shock cycle data includes collecting temperature distribution, thermal expansion coefficient, thermal stress and surface crack extension data generated in real time during the thermal shock cycle of the material; The collected data are stored and preliminarily processed in real time to generate a time series data set containing material performance parameters during multiple thermal shock cycles.

4. The method for evaluating the heat and shock resistance of refractory materials according to claim 3, characterized in that: The monitoring and recording of the performance changes of the material during the thermal shock cycle includes using an ultrasonic emission sensor to monitor the formation and expansion of cracks inside the material in real time; The dynamic changes of the temperature field on the material surface are recorded by thermal imager; Use strain sensors to measure the stress-strain distribution of materials under thermal shock; Perform comprehensive analysis to generate a property change profile that includes crack behavior, temperature response, and stress changes.

5. The method for evaluating the heat and shock resistance of refractory materials according to claim 4, characterized in that: The establishment of the thermal shock history memory model of refractory materials includes extracting key parameters related to material damage and performance changes based on the collected thermal shock cycle data, including temperature gradient , residual stress , crack length and thermal shock cycles ; Construct the cumulative damage function and establish the cumulative damage model of the material , which is of the form: ， in, and It is a material property index, reflecting the influence of temperature gradient and residual stress on damage; Establish performance degradation model based on cumulative damage function , establish material properties The relationship model with the degree of damage is in the form of: ， in, is the initial performance index of the material, is the performance attenuation coefficient; Use the least squares method or machine learning algorithm to adjust the parameters in the model. , , Perform fitting and optimization; Applying optimized thermal shock history memory model to predict material properties Over time or thermal shock cycles 's changing trend.

6. The method for evaluating the heat and shock resistance of refractory materials according to claim 5, characterized in that: The life prediction model is constructed by establishing a relationship model between thermal shock damage and cycle number, based on the cumulative damage function. and thermal shock cycles , construct the functional relationship between thermal shock damage and cycle number: ， in, For the The temperature gradient of the thermal shock, For the The residual stress of thermal shock, For the Secondary thermal shock crack length, and is the material characteristic parameter; Construct critical damage criteria for life prediction and set critical damage values ​​for materials , that is, the cumulative damage degree when the material performance decays to the critical point of failure, meets the following conditions: ， in, The minimum acceptable performance index of the material. is the initial performance of the material; Calculate the thermal shock cycle life according to the damage criterion , combined with the thermal shock damage model , solve the equation , and the corresponding number of thermal shock cycles is obtained , which is the predicted service life of the material under specific thermal shock conditions; Adjust the damage model parameters according to the actual working conditions , , and critical damage value , recalculate the material life , to predict its service life under different working conditions; The results of the life prediction model calculation are output as a report, including the thermal shock life, failure trend and key influencing factors of the material under specific working conditions.

7. The method for evaluating the heat and shock resistance of refractory materials according to claim 6, characterized in that: The comprehensive evaluation of the thermal and shock resistance of the material includes extracting key performance indicators of the material, including cumulative damage value, performance retention rate and predicted life, based on the analysis results of the thermal shock history memory model and the life prediction model; Classify materials according to the degree of damage and performance attenuation rate into high performance, medium performance, low performance and failure categories; Evaluate the crack growth rate, performance change trend and failure risk of materials; Output evaluation report, including material performance level, predicted life, failure cause and optimization suggestions.

8. A system for evaluating the thermal and shock resistance of refractory materials, used for implementing the method for evaluating the thermal and shock resistance of refractory materials as claimed in any one of claims 1 to 7, characterized in that: Thermal shock test module: build a thermal shock test environment, conduct thermal shock cycle tests on refractory materials, and collect thermal shock cycle data; Performance change monitoring module: monitors and records the performance changes of materials during thermal shock cycles; Thermal shock history memory model building module: based on the thermal shock cycle data, a thermal shock history memory model of refractory materials is established to analyze the change of its performance with thermal shock cycles; Life prediction module: build a life prediction model to predict the service life of materials under specific working conditions; Comprehensive evaluation module: Based on the model analysis results, the thermal and seismic resistance of the material is comprehensively evaluated and the evaluation results are output.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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