A method and system for evaluating the thermal shock resistance of refractory materials

Abstract

The present invention discloses a method and system for evaluating the thermal shock resistance and seismic resistance of refractory materials, including: constructing a thermal shock test environment, conducting thermal shock cycle tests on refractory materials, and collecting thermal shock cycle data; monitoring and recording the performance changes of the materials during the thermal shock cycle; establishing a thermal shock historical memory model of the refractory materials based on the thermal shock cycle data, and analyzing the variation law of its performance with the thermal shock cycle; constructing a life prediction model to predict the service life of the materials under specific working conditions; comprehensively evaluating the thermal shock resistance and seismic resistance of the materials according to the model analysis results, and outputting the evaluation results. By real-time monitoring the temperature gradient, residual stress and crack propagation in the thermal shock cycle, and establishing a cumulative damage model and a life prediction model, the present invention realizes the accurate quantitative evaluation of the thermal shock resistance and seismic resistance of refractory materials. It significantly improves the scientificity and dynamic adaptability of material performance evaluation, and provides technical support for material optimization design and application in high-temperature environments.

Description

Technical Field

[0001] The present invention relates to the technical field of materials science, and particularly to a method and system for evaluating the thermal shock and thermal shock resistance of refractory materials. Background Art

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

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

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

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

[0006] Therefore, the technical problem solved by the present invention is that the existing evaluation technologies for the thermal shock and thermal shock resistance of refractory materials mainly have problems such as insufficient evaluation depth, inaccurate life prediction, and limited scope of application.

[0007] To solve the above technical problems, the present invention provides the following technical solutions: A method for evaluating the thermal shock and seismic resistance of refractory materials, comprising: constructing a thermal shock test environment, conducting a thermal shock cycle test on the refractory materials, and collecting thermal shock cycle data;

[0008] Monitoring and recording the performance changes of the material during the thermal shock cycle;

[0009] Based on the thermal shock cycle data, establishing a thermal shock historical memory model of the refractory material, and analyzing the variation law of its performance with the thermal shock cycle;

[0010] Constructing a life prediction model to predict the service life of the material under specific working conditions;

[0011] According to the model analysis results, comprehensively evaluating the thermal shock and seismic resistance performance of the material, and outputting the evaluation results.

[0012] As a preferred embodiment of the method for evaluating the thermal shock and seismic resistance of the refractory material according to the present invention, wherein: the thermal shock cycle test includes performing rapid heating and cooling operations on the refractory material within a set temperature range, and controlling the heating rate and the cooling rate to simulate the thermal shock working conditions in actual use.

[0013] As a preferred embodiment of the method for evaluating the thermal shock and seismic resistance of the refractory material according to the present invention, wherein: the collecting of the thermal shock cycle data includes collecting the temperature distribution, thermal expansion coefficient, thermal stress, and surface crack propagation data generated in real time by the material during the thermal shock cycle;

[0014] Storing and preliminarily processing the collected data in real time to generate a time series data set containing the material performance parameters during multiple thermal shock cycles.

[0015] As a preferred embodiment of the method for evaluating the thermal shock and seismic resistance of the refractory material according to the present invention, wherein: 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 propagation of internal cracks of the material in real time;

[0016] Recording the dynamic change of the surface temperature field of the material through an infrared thermal imager;

[0017] Using a strain sensor to measure the stress-strain distribution of the material under thermal shock;

[0018] Conducting comprehensive analysis to generate a performance change record including crack behavior, temperature response, and stress change.

[0019] As a preferred embodiment of the method for evaluating the thermal shock and seismic resistance of the refractory material according to the present invention, wherein: the establishing of the thermal shock historical memory model of the refractory material includes extracting key parameters related to material damage and performance changes according to the collected thermal shock cycle data, including temperature gradient , residual stress , crack length and number of thermal shock cycles ;

[0020] Construct a cumulative damage function and establish a cumulative damage model for the material , and its form is:

[0021] ,

[0022] wherein, and are material characteristic indices, reflecting the influence degrees of temperature gradient and residual stress on damage;

[0023] Establish a performance degradation model, and based on the cumulative damage function , establish a relationship model between the material performance and the degree of damage, and its form is:

[0024] ,

[0025] wherein, is the initial performance index of the material, is the performance degradation coefficient;

[0026] Adopt the least squares method or machine learning algorithm to fit and optimize the parameters , , in the model;

[0027] Apply the optimized thermal shock history memory model to predict the material performance over time or the change trend with the number of thermal shock cycles .

[0028] As a preferred scheme of the method for evaluating the thermal shock and thermal shock resistance of the refractory material described in the present invention, wherein: the construction of the life prediction model includes establishing a relationship model between thermal shock damage and the number of cycles, and based on the cumulative damage function and the number of thermal shock cycles , construct a functional relationship between thermal shock damage and the number of cycles:

[0029] ,

[0030] wherein, is the temperature gradient of the th thermal shock, is the residual stress of the th thermal shock, is the crack length of the th thermal shock, and are material characteristic parameters;

[0031] Construct a critical damage criterion for life prediction and set the critical damage value of the material , that is, the cumulative damage degree when the material performance decays to the failure critical point, and satisfies the following conditions:

[0032] ,

[0033] wherein, is the lowest acceptable performance index of the material, is the initial performance of the material;

[0034] Calculate the thermal shock cycle life. According to the damage criterion , combined with the thermal shock damage model , solve the equation to obtain the corresponding number of thermal shock cycles , that is, the predicted service life of the material under specific thermal shock conditions;

[0035] Adjust the damage model parameters , , and the critical damage value according to different actual working conditions, and recalculate the life of the material to predict its service life under different working conditions;

[0036] Output the results calculated by the life prediction model as a report, including the thermal shock life, failure trend and key influencing factors of the material under specific working conditions.

[0037] As a preferred solution of the method for evaluating the thermal shock and seismic resistance of refractory materials described in the present invention, wherein: the comprehensive evaluation of the thermal shock and seismic resistance of the material includes, based on the analysis results of the thermal shock historical memory model and the life prediction model, extracting the key performance indicators of the material, including the cumulative damage value, the performance retention rate and the predicted life;

[0038] Classify the material according to the damage degree and the performance attenuation rate, and divide it into high-performance, medium-performance, low-performance and failure categories;

[0039] Evaluate the crack propagation rate, performance change trend and failure risk of the material;

[0040] Output an evaluation report, which includes the material performance grade, predicted life, failure reason and optimization suggestions.

[0041] A system for evaluating the thermal shock and seismic resistance of refractory materials, characterized in that: it includes,

[0042] Thermal shock test module: build a thermal shock test environment, conduct thermal shock cycle tests on refractory materials, and collect thermal shock cycle data;

[0043] Performance change monitoring module: monitors and records the performance changes of materials during thermal shock cycles;

[0044] 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;

[0045] Life prediction module: build a life prediction model to predict the service life of materials under specific working conditions;

[0046] 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.

[0047] 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.

[0048] A computer-readable storage medium stores a computer program, which implements the steps of the method described above when executed by a processor.

[0049] 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;

[0050] 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;

[0051] 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;

[0052] 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;

[0053] 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;

[0054] Through scientific evaluation methods, the present invention reduces the trial-and-error costs in the use of refractory materials, lowers the operation risks of equipment, and improves the operation efficiency and safety of the high-temperature industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings, where:

[0056] Figure 1 FIG. is the overall flowchart of a method for evaluating the thermal and seismic resistance of refractory materials provided in the first embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0057] In order to make the above objects, features, and advantages of the present invention more obvious and understandable, the following detailed description of the specific embodiments of the present invention will be made in conjunction with the drawings of the specification. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the scope of protection of the present invention.

[0058] Example 1, referring to Figure 1 , which is an embodiment of the present invention, provides a method for evaluating the thermal and seismic resistance of refractory materials, including:

[0059] S1: Construct a thermal shock test environment, conduct a thermal shock cycle test on the refractory material, and collect thermal shock cycle data.

[0060] Perform rapid heating and cooling operations on the refractory material within a set temperature range, and control the heating rate and cooling rate to simulate the thermal shock conditions in actual use.

[0061] Collect the temperature distribution, thermal expansion coefficient, thermal stress, and surface crack propagation 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 the material performance parameters during multiple thermal shock cycles.

[0062] Furthermore, the temperature distribution refers to the temperature values of the material at different positions at a certain moment, usually represented in the form of a spatial distribution (such as ). The temperature gradient is a physical quantity derived from the temperature distribution. When the material undergoes rapid heating or cooling during the thermal shock cycle, a significant temperature gradient will be formed between the surface and the interior. The greater the temperature gradient, the more significant the thermal stress. Therefore, the temperature distribution is the basis of the temperature gradient, and the temperature gradient directly affects the magnitude of the thermal stress.

[0063] Coefficient of thermal expansion Describes the expansion or contraction behavior of a material when subjected to temperature changes, and is defined as:

[0064] ,

[0065] Wherein, is the change in the length of the material, is the initial length, is the temperature change.

[0066] Thermal stress Occurs when the expansion or contraction of a material is restricted by a temperature gradient, and its expression is:

[0067] ,

[0068] Wherein, is the elastic modulus of the material, is the coefficient of thermal expansion, is the temperature gradient.

[0069] Residual stress , After thermal shock cycling, there may be thermal stresses in the material that cannot be fully released, and these stresses are the residual stresses. The magnitude and distribution of the residual stresses depend on the coefficient of thermal expansion of the material, the temperature gradient, and the plastic deformation ability of the material.

[0070] The coefficient of thermal expansion is a key influencing factor for residual stress and thermal stress. The temperature gradient in thermal shock cycling causes strain changes in the material through the coefficient of thermal expansion, thereby generating thermal stress. When the thermal shock stops, part of the thermal stress cannot return to equilibrium and forms residual stress.

[0071] Surface crack propagation describes the dynamic behavior of crack propagation during thermal shock cycling, usually represented by the crack length and the crack propagation rate . Crack propagation is affected by the combined effects of thermal stress and temperature gradient.

[0072] The driving force for crack propagation mainly comes from thermal stress. When the thermal stress exceeds the fracture toughness of the material , the crack will propagate rapidly. The expression for crack propagation is:

[0073] ,

[0074] Wherein, is the thermal stress, is the elastic modulus; represents a proportional relationship to, here representing the crack propagation speed is proportional to the square of the stress ( )is proportional to and inversely proportional to the elastic modulus This means that at the same elastic modulus, the greater the thermal stress, the faster the crack propagation rate.

[0075] Crack length increases with the number of thermal shock cycles, and the propagation rate is jointly controlled by the temperature distribution, coefficient of thermal expansion, and fracture toughness of the material.

[0076] Crack propagation is the dynamic manifestation of crack length. Monitoring the surface crack propagation reflects the change of crack length over time, and the crack length can be used to quantify the degree of damage accumulation of the material during thermal shock cycles.

[0077] Furthermore, the temperature gradient is the direct cause of thermal stress, and the temperature distribution determines the magnitude and direction of the gradient. The coefficient of thermal expansion connects the thermal and mechanical responses of the material and is an important parameter for thermal stress and residual stress. Thermal stress provides the driving force for crack propagation, and residual stress affects the propagation direction and rate of cracks. The crack propagation behavior directly determines the growth of crack length, and the crack length is an important characterization of the degree of material damage.

[0078] This close physical relationship makes the temperature gradient, coefficient of thermal expansion, thermal stress, residual stress, and crack propagation data the core parameters for evaluating the thermal and seismic resistance of materials. By collecting these data and analyzing their relationships, the performance change mechanism and failure law of materials in the thermal shock environment can be comprehensively revealed, providing a scientific basis for the optimized design and application of materials.

[0079] It should be noted that controlling the heating and cooling rates and setting a specific temperature range can comprehensively investigate 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 materials. By precisely controlling the heating and cooling rates and collecting real-time performance data, the present invention can be widely applied to the design optimization and failure analysis of refractory materials, especially in high-temperature equipment in the metallurgical, chemical, and energy fields, with significant application value. The collected time series data set can provide scientific input for subsequent thermal shock history memory models and life prediction models, support the dynamic evaluation of the long-term performance of materials, and provide theoretical guidance for the safe operation of high-temperature equipment.

[0080] S2: Monitor and record the performance changes generated by the material during thermal shock cycles.

[0081] Use ultrasonic emission sensors to monitor the formation and propagation of internal cracks in the material in real time.

[0082] Record the dynamic changes of the surface temperature field of the material through an infrared thermal imager.

[0083] Use strain sensors to measure the stress-strain distribution of the material under thermal shock.

[0084] Conduct a comprehensive analysis to generate a record of performance changes including crack behavior, temperature response, and stress variation.

[0085] Furthermore, an ultrasonic emission sensor is a highly sensitive device for monitoring the dynamic behavior of internal cracks in materials, capable of capturing high-frequency acoustic wave signals released during crack propagation. In the present invention, the ultrasonic emission sensor monitors the formation and propagation process of cracks in real time and converts the signals into crack propagation rate and energy parameters. The acoustic wave characteristics of crack propagation can directly reflect the cumulative state of internal damage in materials and are the core tools for non-destructive testing (NDT). Acoustic emission monitoring technology can capture the transient behavior of crack initiation and propagation, especially having significant advantages in detecting hidden internal damage in materials. By recording the frequency and intensity of ultrasonic emission signals in real time, the crack propagation rate and energy release can be quantified, thereby revealing the dynamic mechanism of crack behavior. This dynamic monitoring ability enables the present invention to accurately judge the critical point of crack propagation, laying a foundation for material performance evaluation and life prediction.

[0086] The thermal imager generates a real-time distribution map of the temperature field by capturing the infrared radiation on the surface of the material. In the present invention, the thermal imager is used to record the temperature field changes 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, which are important influencing factors for crack initiation and propagation. The thermal imager captures the changes in the surface temperature field 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 data, providing important support for real-time evaluation of the thermal shock performance of materials.

[0087] The strain sensor is used to measure the stress-strain response of the material under thermal shock and generate strain time series data. In the present invention, the strain sensor can capture the minute strain distribution and dynamic changes caused by uneven temperature fields. The distribution characteristics of stress and strain are important indicators for evaluating the degradation of material mechanical properties and crack behavior. The strain sensor records the strain distribution of the material during the thermal shock cycle in real time, which 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 judged, further revealing the mechanical origin of damage. This mechanical property monitoring ability provides a theoretical basis for material design and optimization.

[0088] The record of performance changes refers to a dynamic data set generated by comprehensively analyzing crack behavior, temperature response, and stress changes during the thermal shock cycle. Through multi-parameter linkage analysis, the performance evolution law of the material under thermal shock conditions can be comprehensively revealed, providing high-quality input data for subsequent model construction.

[0089] Furthermore, by integrating the real-time monitoring functions of ultrasonic emission sensors, thermal imagers, and strain sensors, the present invention realizes the synchronous acquisition and analysis of multiple physical quantities. This cross-domain data fusion technology breaks through the limitations of traditional single-parameter monitoring, enabling the internal cracks, surface temperature field, and stress-strain response of materials to be comprehensively captured during thermal shock cycles, improving the refinement and timeliness of data.

[0090] By comprehensively analyzing crack behavior, temperature response, and stress changes to generate a record of performance changes, it can not only comprehensively reveal the dynamic damage law of materials 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 properties and provide scientific support for life prediction and optimization design.

[0091] S3: Based on the thermal shock cycle data, establish a thermal shock history memory model for refractory materials and analyze the change law of its performance with thermal shock cycles.

[0092] According to the collected thermal shock cycle data, extract key parameters related to material damage and performance changes, including temperature gradient , residual stress , crack length , and number of thermal shock cycles .

[0093] Construct a cumulative damage function and establish a cumulative damage model for the material , in the form of:

[0094] ,

[0095] where and are material characteristic indices, reflecting the influence degree of temperature gradient and residual stress on damage; The influence of temperature gradient on damage is represented by the exponent , reflecting the non-linear effect of temperature gradient; Residual stress affects damage with the exponent , reflecting the correlation between stress concentration and damage rate; The influence of crack propagation on damage is described by a logarithmic function to prevent the non-physical infinite increase trend introduced by crack parameters.

[0096] Establish a performance degradation model. Based on the cumulative damage function , establish a relationship model between material performance and damage degree, in the form of:

[0097] ,

[0098] where is the initial performance index of the material, is the performance attenuation coefficient.

[0099] Using the least squares method or machine learning algorithms, the parameters , , in the model are fitted and optimized.

[0100] Applying the optimized thermal shock history memory model to predict the material performance over time or the number of thermal shock cycles trend of change.

[0101] Assume that discrete time points data are collected in the experiment, and the damage function can be expressed in discrete integral form:

[0102] ,

[0103] This expression captures the damage increment of the material at each moment by summing the discrete data.

[0104] After the damage function is calculated, it can be substituted into the performance attenuation model:

[0105] ,

[0106] By calculating values at different time points, the change curve of performance over time can be plotted to further deduce the service life of the material.

[0107] It should be noted that the thermal shock history memory model aims to quantify the law of damage accumulation in the thermal shock cycle of the material and provide basic data for the subsequent performance attenuation model. By analyzing the temperature gradient , residual stress , crack length and the number of thermal shock cycles and other key parameters, the model can capture the dynamic behavior of material performance degradation.

[0108] The design of the damage accumulation function is based on the characteristics of material damage caused by the combined action of multiple factors in actual working conditions. These factors include: temperature gradient , the non-uniformity of the temperature field leads to thermal stress concentration, which plays a major role in crack initiation and propagation; residual stress , the magnitude and distribution of residual stress directly affect the crack propagation speed and are important driving factors for material damage; crack length , Crack propagation 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.

[0109] The model models the non-linear relationship of these parameters in a fractional form, reflecting the mutual coupling effect between the temperature gradient, stress distribution and crack behavior. In the denominator, is used to smooth the extreme influence of crack propagation on damage and prevent the model from losing stability.

[0110] The integral range of cumulative damage ensures that the model captures the cumulative effect of damage over the entire time period, rather than only focusing on a certain moment.

[0111] S4: Build a life prediction model to predict the service life of the material under specific working conditions.

[0112] Establish a relationship model between thermal shock damage and the number of cycles, based on the cumulative damage function and the number of thermal shock cycles , construct the functional relationship between thermal shock damage and the number of cycles:

[0113] ,

[0114] where, is the temperature gradient of the th thermal shock, is the residual stress of the th thermal shock, is the crack length of the th thermal shock, and are material characteristic parameters.

[0115] Construct the critical damage criterion for life prediction, and set the critical damage value of the material, that is, the degree of cumulative damage when the material performance decays to the failure critical point, satisfying the following conditions:

[0116] ,

[0117] where, is the lowest acceptable performance index of the material, is the initial performance of the material.

[0118] Calculate the thermal shock cycle life. According to the damage criterion , combined with the thermal shock damage model , solve the equation to obtain the corresponding number of thermal shock cycles , that is, the predicted service life of the material under specific thermal shock working conditions. "Specific working conditions" refers to the specific temperature gradient range, stress distribution and crack length that the refractory material may withstand in actual use.

[0119] Adjust the damage model parameters according to different actual working conditions 、 、 and the critical damage value ,recalculate the life of the material to predict its service life under different working conditions.

[0120] Output the results calculated by the life prediction model as a report, including the thermal shock life, failure trend and key influencing factors of the material under specific working conditions.

[0121] It should be noted that by introducing the integral form, the contribution of each thermal shock cycle to the material damage is accumulated, and the three core factors of temperature gradient, residual stress and crack propagation are comprehensively considered, which reflects the multi-physical field coupling mechanism of the damage process. The fractional structure and logarithmic function smooth the extreme value influence, ensuring the stability and physical rationality of the model. The existing life assessment methods usually mainly rely on empirical formulas, lacking a quantitative description of the cumulative effect of multiple thermal shocks and being 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.

[0122] Use to express the critical state of the material performance, and associate the failure condition of the material with the cumulative damage function. By setting the critical performance value , the failure points of the material under different working conditions can be uniformly measured. The traditional method is difficult to quantify the relationship between the material performance degradation and the damage accumulation. The present invention transforms the cumulative damage value into a physical quantity of performance degradation through the performance attenuation model, and clarifies the judgment criterion for performance failure.

[0123] The model parameters can be dynamically adjusted according to different working conditions 、 、 ,recalculate the material life to provide a flexible prediction ability for the application of materials in complex environments.

[0124] S5: According to the model analysis results, comprehensively evaluate the thermal shock and earthquake resistance performance of the material, and output the evaluation results.

[0125] Based on the analysis results of the thermal shock history memory model and the life prediction model, extract the key performance indicators of the material, including the cumulative damage value, performance retention rate and predicted life.

[0126] Classify the materials according to the damage degree and performance attenuation rate, and divide them into high-performance, medium-performance, low-performance and failure categories.

[0127] Evaluate the crack growth rate, performance change trend, and failure risk of the material.

[0128] Output an evaluation report, which includes the material performance grade, predicted life, failure cause, and optimization suggestions.

[0129] Specifically, when the performance indicators of the material are within the test temperature gradient range and conform to the initial performance curve, and the degree of damage accumulation is less than 20% of the critical value (i.e., ), the evaluation model classifies according to the high-performance category of the material; further analyze the damage growth rate , if its maximum value satisfies (where is the maximum number of cycles of the test), then it is classified as a "high-performance material".

[0130] Output an evaluation report, including the material performance retention rate , damage accumulation value, thermal and seismic resistance performance grade, and the conclusion of the material performance stability under the existing working conditions, and predict the applicable fields and service life suggestions.

[0131] When the model analysis results show that the performance indicators of the material are within the test temperature gradient range and there is a fluctuation within ±10% of the initial performance index (i.e., ), and the degree of damage accumulation is ), the evaluation model classifies according to the medium-performance category of the material; analyze the growth rate of the crack length , if its maximum value satisfies (where is the maximum allowable crack length), then it is classified as a "medium-performance material".

[0132] Output an evaluation report, including the material performance change range, the impact of crack growth behavior on material stability, and the optimization and improvement measures of the material under this working condition. When the model analysis results show that the performance indicators of the material deviate from the initial performance index by more than ±10% and less than ±30% (i.e., ), and the degree of damage accumulation is , the evaluation model classifies according to the low-performance category of the material; further analyze the performance decay rate , if its maximum value satisfies

[0133] Output an evaluation report, including the predicted life value of the material ( ), the contribution degree of crack propagation behavior, and the early warning of the failure risk of the material under this working condition and suggestions for alternative solutions.

[0134] When the model analysis results show that the performance indicators of the material are lower than the minimum performance indicators , and the degree of damage accumulation , the evaluation model is graded according to the failure category of the material; further analyze the superimposed effect of thermal shock cycles on damage, and calculate the crack propagation acceleration . If its maximum value satisfies , it is attributed to crack behavior-dominated failure. Output an evaluation report, including analysis of the cause of failure, risk assessment for specific working conditions, and propose emergency adjustment strategies and optimization plans.

[0135] When the model analysis results show that the performance indicators of the material under multiple thermal shock cycle working conditions and the fitting error of the thermal shock history memory model exceed 5% (i.e., ), and the damage accumulation curve shows a non-linear mutation (such as ), the abnormal working condition identification process is triggered; extract the key environmental parameters that cause the performance mutation (such as the temperature change rate exceeds 100 K / min). Output an evaluation report, including sensitivity analysis of the material to special working conditions, the influence range of performance under abnormal environments, and suggestions for optimizing the material selection.

[0136] It should be noted that in the performance failure analysis, the introduction of crack propagation acceleration and damage deviation error can accurately identify the non-linear damage growth behavior and abnormal working conditions of the material, especially the evaluation of the failure risk under extreme environments. It is difficult for the existing technology to accurately predict the non-linear trend of crack propagation and the sudden failure risk. The present invention can identify the failure risk at an early stage through the analysis of crack propagation acceleration and model error, and propose an optimization plan by adjusting parameters.

[0137] According to the performance grading results, it can help engineers quickly select materials suitable for high-temperature environments, especially for application scenarios with high lifespan requirements, such as metallurgical furnace linings, chemical equipment, etc. Based on the risk assessment of crack propagation acceleration and model error, it provides a scientific basis for the 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 solutions proposed in the report can guide the use of materials and the adjustment of equipment operation parameters, extend the service life of materials, and improve the economic efficiency of equipment. This model and analysis method can also be used for the performance evaluation of materials in other dynamic environments, such as spacecraft protection materials, nuclear energy equipment, etc., and has broad application prospects.

[0138] Embodiment 2 is the second embodiment of the present invention. What is different from the previous embodiment is:

[0139] If the said function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the current technical solution can be embodied in the form of a software product. The current computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. And the aforementioned storage medium includes: USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs, etc., which can store program codes.

[0140] The logic and / or steps represented in the flowchart or described in other ways herein, for example, can be considered as a definite sequence list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, apparatus, or device (such as a computer-based system, a system including a processor, or other systems that can fetch instructions from the instruction execution system, apparatus, or device and execute the instructions), or used in combination with these instruction execution systems, apparatus, or devices. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device.

[0141] More specific examples (non-exhaustive list) of computer-readable media include the following: electrical connections (electronic devices) with one or more wirings, portable computer disk cartridges (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber devices, and portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other media, followed by editing, interpretation, or other suitable processing as necessary, and then stored in a computer memory.

[0142] Example 3, an embodiment of the present invention, provides a system for evaluating the thermal shock and seismic resistance of refractory materials, 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 evaluation module.

[0143] Thermal shock test module: Construct a thermal shock test environment, conduct thermal shock cycle tests on refractory materials, and collect thermal shock cycle data.

[0144] Performance change monitoring module: Monitor and record the performance changes of the material during the thermal shock cycle.

[0145] Thermal shock history memory model construction module: Based on the thermal shock cycle data, establish a thermal shock history memory model of the refractory material and analyze the variation law of its performance with the thermal shock cycle.

[0146] Life prediction module: Construct a life prediction model to predict the service life of the material under specific working conditions.

[0147] Comprehensive evaluation module: According to the model analysis results, comprehensively evaluate the thermal shock and seismic resistance performance of the material and output the evaluation results.

[0148] Example 4, an embodiment of the present invention, provides a method for evaluating the thermal shock and seismic resistance of refractory materials. To verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation / contrast experiments.

[0149] To verify the thermal shock and seismic resistance performance of different refractory materials, a set of thermal shock test environments was constructed and six materials (labeled as Material A to Material F) were tested. The specific experimental steps are as follows:

[0150] Use high-precision thermal shock test equipment, set the test temperature range from 310K to 520K, the heating rate is 50K / s, the cooling rate is 40K / s, and the single cycle lasts for 2 minutes to simulate high-frequency thermal shock conditions.

[0151] Six samples were selected from commonly used industrial refractory materials and processed into standard cubes with dimensions of 10 mm × 10 mm × 10 mm to ensure the consistency of the test samples and the reliability of the data.

[0152] The specimens were placed in the test equipment for continuous thermal shock cycling. The number of thermal shock cycles was gradually increased, and key data were recorded every 10 cycles until the material properties approached the critical value or obvious signs of failure appeared.

[0153] An infrared thermal imager was used to measure the surface temperature difference of the specimens and record the temperature gradient ; the residual stress after thermal shock was monitored through strain gauges ; an ultrasonic emission sensor was used to capture the signals of crack formation and propagation and measure the crack length .

[0154] The temperature gradient, residual stress, and crack length of each material at different numbers of thermal shock cycles were collected, and the damage accumulation and performance retention rate were recorded to provide basic data for subsequent analysis.

[0155] Based on the experimental data, the performance retention rate and predicted life of each material were calculated, and the material properties were classified through model analysis results.

[0156] An integrated evaluation report containing the material performance grade, damage accumulation trend, and life prediction value was output, and optimization suggestions were provided to guide material application and working condition adjustment.

[0157] The final experimental data are shown in Table 1.

[0158] Table 1 Experimental data table

[0159] Material type Temperature gradient (K) Residual stress (Pa) Crack length (mm) Damage accumulation (D) Predicted life (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

[0160] It can be clearly seen from the table data that there are performance differences among different materials during thermal shock cycling.

[0161] High-performance materials (Materials A, B): The performance retention rates are 96% and 90% respectively, the crack lengths are short (0.08 mm and 0.13 mm), the damage accumulation values are low (0.12 and 0.22), and the predicted lives are long (1300 times and 1050 times). These materials show good thermal shock resistance and are suitable for high-frequency thermal shock working conditions.

[0162] Medium-performance materials (Materials C, D): The performance retention rates are 83% and 78%, the crack lengths and residual stresses both increase, the damage accumulation values are 0.35 and 0.42 respectively, and the predicted lives are shortened to 900 times and 750 times. Such materials are suitable for medium thermal shock working conditions, but crack propagation control needs to be optimized.

[0163] Low-performance materials (Materials E, F): The performance retention rates are 70% and 60%, the crack lengths increase significantly (0.29 mm and 0.35 mm), the damage accumulation values are relatively high (0.55 and 0.65), and the predicted lifetimes are short (550 times and 400 times). These materials are difficult to meet the application requirements under high-intensity thermal shock conditions.

[0164] By collecting temperature gradient, residual stress, and crack propagation data in real time and combining with the cumulative damage model and performance degradation model, the present invention can accurately quantify the impact of thermal shock cycles on material properties.

[0165] The results of the performance retention rate and predicted lifetime in the table intuitively show the attenuation trend of the material under different working conditions. By establishing a performance grading standard, the present invention provides a scientific basis for the optimized design of materials.

[0166] High-performance materials (such as Materials A, B) can be used in high-frequency thermal shock environments, such as metallurgical furnace linings and high-temperature chemical equipment.

[0167] For medium-performance and low-performance materials, their service life can be extended by adjusting the working conditions (such as reducing the temperature gradient or stress level).

[0168] The data results provide a clear direction for optimizing material selection and design for different working conditions.

[0169] In terms of damage accumulation and life prediction, the model method of the present invention solves the problem that it is difficult to quantify the coupling effect of multiple physical fields in the prior art.

[0170] In summary, through dynamic testing and multi-parameter modeling in this embodiment, the scientificity and innovation of the present invention in the evaluation of the thermal shock resistance of refractory materials are verified, providing comprehensive technical support for the optimized design of materials in high-temperature environments.

[0171] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not restrictive. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention, and they should all be covered within 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, conduct a comprehensive evaluation of the thermal and seismic resistance of the material and output the evaluation results; 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 characteristic parameter, 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 's changing trend.

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 construction of the life prediction model includes establishing a relationship model 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, is the performance attenuation coefficient; Calculate the thermal shock cycle life according to the critical damage value of the set material , 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.

6. The method for evaluating the heat and shock resistance of refractory materials according to claim 5, 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.

7. 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 6, 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.

8. 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 6 are implemented.

9. 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 6 are implemented.

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