Aerogel aging simulation prediction system and method based on multi-field coupling conditions

Abstract

The application discloses an aerogel aging simulation prediction system and method based on multi-field coupling conditions, and relates to the aging test technology of aerogel materials; the system is composed of a hardware device module and a software algorithm module. The hardware device module is integrated with a heating component, a stress loading component and an atmosphere composition loading component through a sealed simulation cavity, and can build a service environment of thermal, force and atmosphere multi-field coupling. The software algorithm module collects temperature, heat flow, stress and atmosphere data in real time, calculates a thermal resistance degradation curve, calibrates multi-field acceleration coefficients based on accelerated aging test data under different coupling conditions, and establishes a life prediction model. The method realizes accelerated aging test under conditions close to real conditions, online monitoring of performance degradation and quantitative prediction of service life, and solves the problems that the existing technology has single test conditions and cannot effectively associate accelerated test with real life.

Description

Technical Field

[0001] This invention relates to aerogel material aging testing technology, specifically to an aerogel aging simulation and prediction system and method based on multi-field coupling conditions. Background Technology

[0002] Aerogel materials are widely used in high-temperature insulation applications such as industrial kilns, metallurgical heating furnaces, petrochemical cracking furnaces, and cement rotary kilns due to their ultra-low thermal conductivity, high porosity, and lightweight properties. However, in actual service, aerogels are not subjected to a single transient thermal shock environment, but are exposed to complex conditions of thermo-mechanical-atmosphere coupling for a long time, such as high temperature gradients, continuous mechanical compression / creep, cyclic loads, and mixed atmospheres containing oxygen, water vapor, carbon dioxide, or other reactive components.

[0003] In existing technologies, the evaluation of the high-temperature resistance of aerogels often employs methods such as single high-temperature calcination, transient thermal shock, isothermal compression creep, or single-atmosphere corrosion. These methods typically have the following shortcomings: Considering only a single physical field is insufficient to reflect the structure-performance evolution path caused by the synergy of multiple fields; Most of these are short-term or transient tests, which cannot characterize the cumulative effects and threshold behavior during long-term service. The lack of an equivalent model for accelerated aging makes it difficult to establish a traceable correspondence between test time and actual service time; The lack of online monitoring and data closed-loop for thermal resistance degradation means that life assessments rely heavily on empirical extrapolation, resulting in insufficient reliability and portability.

[0004] To this end, we propose an aerogel aging simulation and prediction system and method based on multi-field coupling conditions. Summary of the Invention

[0005] The purpose of this invention is to provide a system and method for simulating and predicting aerogel aging under multi-field coupling conditions.

[0006] The technical problem solved by this invention is: how to provide a real service environment for aerogels under multiple coupled thermal, mechanical, and atmospheric conditions and to perform real-time online monitoring, so as to accurately predict the remaining life of aerogel materials under target operating conditions.

[0007] This invention can be achieved through the following technical solution: an aerogel aging simulation and prediction system based on multi-field coupling conditions, including a hardware device module and a software algorithm module; the hardware device module includes a base and a top lifting seat, and the base and the lifting seat form a sealed simulation cavity after contact, closure and fixation. A positioning plate is fixed to the bottom of the base inside the sealed simulation chamber. A sample fixing block for supporting the sample body is installed on the top of the positioning plate. A heating component is provided on the circumferential side wall of the base at the corresponding position as the hot end. A cold source pipe connected to the positioning plate is buried at the bottom of the base as the cold end. A sliding sealing piston is slidably installed inside the lifting seat. A pressing block for squeezing the sample body is fixed at its bottom. The sliding sealing piston is moved by injecting hydraulic oil into the upper part of the sealed simulation chamber. An air distribution ring groove is provided in the side wall of the lifting seat to introduce external multi-source air and connect to the sealed simulation chamber through an air outlet. The software algorithm module includes a data acquisition unit, a simulation control unit, and a life prediction unit. The data acquisition unit collects the temperature field distribution, compressive stress, displacement change, and atmosphere parameters in the sealed simulation cavity in real time. The simulation control unit is used to control the loading mode of the temperature field, load stress, and atmosphere. The life prediction unit plots the thermal resistance degradation curve based on the real-time acquired data and constructs a life prediction model to predict the remaining life under the target service boundary.

[0008] A further technical improvement of the present invention is that a fixing frame is coaxially fixed at the top opening of the base, and multiple loading cavities are evenly arranged on the fixing frame, each loading cavity being loaded with ceramic particles.

[0009] A further technical improvement of the present invention is that: the upper and lower sides of the sliding sealing piston are symmetrically provided with sealing lips, the sealing lips abut against the inner wall of the lifting seat, the sealing lips expand outward from the middle to the upper and lower ends, and there is a sealing cavity between the two sealing lips and the lifting seat.

[0010] A further technical improvement of the present invention is that: a force sensor is installed at the bottom of the pressing block, a displacement sensor is installed on the sliding sealing piston, an atmosphere sensor is connected to the side wall of the base, a thermocouple array is installed on the inner side wall of the base for real-time monitoring of stress, displacement, atmosphere and temperature field distribution, and a heat flow meter is installed on the heat flow path.

[0011] A method for simulating and predicting aerogel aging using the above system, the method comprising the following steps: S1: After clamping and fixing the sample body, set the boundary parameters of multi-field coupling loading. The boundary parameters include hot / cold end temperature, temperature gradient, load compressive stress, atmosphere composition and aging time. S2: A controlled temperature field and atmosphere field are established in the sealed simulation cavity, and a controllable load compressive stress is applied to simulate the aging of the sample body under the multi-field coupling conditions of temperature-atmosphere-stress. S3: During the aging simulation, heat flux density, temperature difference between hot and cold ends, compressive stress, sample thickness change and atmospheric composition parameters are collected simultaneously. After data preprocessing, a time series dataset D(t) is formed. S4: Calculate the degradation curve of thermal resistance coefficient R(t) over time based on the time series dataset D(t), and determine the failure state of the sample based on the preset failure threshold; thermal resistance R(t) is calculated by the following formula: R(t) = ΔT(t) / q(t), where ΔT(t) is the temperature difference between the hot end and the cold end, and q(t) is the heat flux density through the sample; S5: Based on the thermal resistance degradation curves under different temperature, load stress and atmospheric composition combinations, obtain the failure time corresponding to each condition, calibrate the multi-field coupling acceleration coefficient K, complete the accelerated aging equivalent conversion, and obtain the service life equivalent time, i.e. tservice=K·ttest, where ttest is the simulation time and tservice is the service life equivalent time.

[0012] A further technical improvement of the present invention is that: in step S2, multi-source gas is introduced into the gas distribution ring groove through the gas source connector installed on the side wall of the lifting seat. After the gas is preheated and homogenized through the gaps of the ceramic particles, it enters the sealed simulation cavity to form a uniform atmosphere field.

[0013] A further technical improvement of the present invention is that the simulation mode in step S2 includes at least one of the following: isothermal-constant load-humidified oxidizing atmosphere synchronous coupling mode; stepped heating and cooling-stepped load-CO2 / humidified atmosphere progressively enhanced coupling mode; temperature gradient-cyclic load-low oxygen / inert atmosphere periodically alternating coupling mode.

[0014] A further technical improvement of the present invention is that: in the synchronous coupling mode of isothermal-constant load-humidified oxidizing atmosphere, the atmosphere is a N2 / O2 / H2O mixture, the O2 volume fraction is 10%, and the dew point is 40°C; A further technical improvement of the present invention is that in the stepped heating and cooling-stepped load-CO2 / humid atmosphere progressive enhancement coupling mode, the CO2 volume fraction is 5-20% and the dew point temperature is 20-60℃.

[0015] A further technical improvement of the present invention is that in the temperature gradient-cyclic load-low oxygen / inert atmosphere periodically alternating coupling mode, the O2 volume fraction is 1-5%, and the gas dew point or ratio is switched periodically.

[0016] Compared with the prior art, the present invention has the following beneficial effects: 1. This invention integrates a sealed simulation chamber, a heating component, a hydraulically driven pressure loading mechanism, and a multi-channel controllable atmosphere input system. It can accurately reproduce the real service conditions of high temperature, stress load, and complex corrosive atmosphere in a laboratory environment, providing a reliable experimental platform for studying the aging mechanism of aerogels under multi-field coupling.

[0017] 2. This invention utilizes a gas distribution ring groove and a structure filled with ceramic particles. This allows the injected atmosphere to pass through the gaps in the heated ceramic particles before entering the main simulation chamber, achieving preheating and homogenization of the atmosphere. This effectively avoids the severe interference caused by direct introduction of low-temperature atmosphere to the stable thermal field within the chamber, ensuring the stability and controllability of the heat-atmosphere coupling conditions. Simultaneously, pressure is applied to the sample by injecting hydraulic oil into the upper part of the sealed simulation chamber to push the sliding sealing piston, replacing the traditional mechanical direct drive. This hydraulic drive method avoids the dynamic seal leakage problem caused by the transmission rod passing through the cavity, ensuring the long-term sealing performance of the simulation chamber under high-stress loading conditions.

[0018] 3. This invention, based on online monitoring data, calculates the degradation curves of key thermal insulation performance indicators such as thermal resistance over time in real time and sets failure thresholds. By conducting accelerated aging tests under different multi-field coupling conditions, the corresponding failure times are obtained, thereby calibrating the multi-field coupling acceleration coefficient. This coefficient can be used to convert the laboratory accelerated test time into an equivalent actual service time, achieving reliable prediction from accelerated testing to long-term lifespan, significantly improving the accuracy and efficiency of lifespan assessment. Attached Figure Description

[0019] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings.

[0020] Figure 1 This is a system configuration block diagram of the present invention; Figure 2 This is a three-dimensional structural diagram of the hardware device module of the present invention; Figure 3 This is a cross-sectional schematic diagram of the hardware device module of the present invention; Figure 4 This is a schematic diagram of the fixing frame structure of the present invention; Figure 5 for Figure 3 An enlarged schematic diagram of part A of the structure.

[0021] In the diagram: 1. Base; 2. Lifting seat; 3. Cover plate; 4. Fixing plate; 5. Connector; 6. Column; 7. Top plate; 8. Slide seat; 9. Hydraulic cylinder; 10. Adjustable connector; 11. Air source connector; 12. Positioning plate; 13. Sample fixing block; 14. Sample body; 15. Heating component; 16. Fixing frame; 17. Ceramic particles; 18. Connecting column; 19. Pressing block; 20. Sliding sealing piston; 201. Gas distribution ring groove; 202. Air outlet; 1601. Loading cavity; 2001. Sealing lip; 2002. Sealing cavity gap. Detailed Implementation

[0022] To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the following detailed description of the specific implementation methods, structures, features, and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided.

[0023] Please see Figure 1-5 As shown, the aerogel aging simulation and prediction system based on multi-field coupling conditions includes a hardware device module and a software algorithm module. The hardware device module is used to provide the physical environment for aging simulation, including the multi-field coupling environment states such as sealed simulation chamber, thermal field construction, load loading, and atmosphere mixing. The software algorithm module is used to collect simulation data collected by the hardware device module during the simulation process, and then control the boundary conditions and perform aging state analysis and prediction. Specifically, the hardware module, namely the aging simulation device, includes a base 1, a top plate 7 horizontally arranged directly above the base 1, four columns 6 arranged parallel between the top plate 7 and the base 1, the two ends of the four columns 6 being fixedly connected to the top plate 7 and the base 1 respectively, and a lifting seat 2 being vertically adjustable between the base 1 and the top plate 7; a sliding seat 8 is fixed to the outer periphery of the lifting seat 2, and the sliding seat 8 slides one-to-one with the columns 6 on the outer periphery; a cover plate 3 is coaxially fixed to the top of the lifting seat 2 to close the top of the lifting seat 2. A hydraulic cylinder 9 is fixedly installed on the top of the top plate 7. The hydraulic rod of the hydraulic cylinder 9 passes through the top plate 7 and a connector 5 is fixedly fixed at the end. The connector 5 is a circular plate. A fixing plate 4 is coaxially arranged directly below the connector 5. The connector 5 and the fixing plate 4 are connected and fixed by evenly arranged connecting rods. The fixing plate 4 is coaxially fixedly installed on the top of the cover plate 3. The fixing plate 4 is annular and has a clearance hole in its middle to make way for the adjustable connector 10 installed on the top of the cover plate 3.

[0024] After the base 1 and the lifting seat 2 are connected and fixed, a sealed simulation cavity is formed. A positioning plate 12 is fixed at the bottom of the base 1 in the lower part of the sealed simulation cavity. The top of the positioning plate 12 is provided with a positioning groove for fixing the sample fixing block 13. The top of the sample fixing block 13 supports and fixes the sample body 14. Specifically, the top wall of the sample fixing block 13 is provided with a recess for placing the sample body 14. The upper part of the sample body 14 is higher than the top of the sample fixing block 13. The side of the sample body 14 and the recess on the top of the sample fixing block 13 are closely fitted to ensure good thermal contact. Combined with the hot field above and the cold source below, it is easy to establish and maintain a one-dimensional longitudinal temperature gradient inside the sample body 14. Heating components 15 are circumferentially distributed and installed on the inner side wall of the base 1 at the corresponding height of the sample body 14. The heating components 15 are specifically multiple sets of electric heating wires. A sliding sealing piston 20 is slidably installed inside the lifting seat 2. A connecting column 18 is vertically fixed at the bottom of the sliding sealing piston 20. A pressing block 19 is coaxially fixed at the bottom of the connecting column 18. A fixing frame 16 is coaxially fixed at the opening of the base 1. The connecting column 18 passes through the fixing frame 16 and slides relative to it. Multiple loading chambers 1601 are provided on the fixing frame 16. Each loading chamber 1601 is loaded with a large number of ceramic particles 17. An air distribution ring groove 201 is provided in the bottom side wall of the lifting seat 2. Several air outlets 202 are provided at corresponding positions on the inner side wall of the lifting seat 2. The air outlets 202 are connected to the air distribution ring groove 201. Multiple air source connectors 11 are installed at corresponding positions on the outer side wall of the lifting seat. The air source connectors 11 adopt a one-way valve structure that only allows air in and does not allow air out, and are connected to the air distribution ring groove 201.

[0025] It should be noted that the sliding sealing piston 20 is provided with sealing lips 2001 on both the upper and lower sides. The sealing lips 2001 abut against the inner wall of the lifting seat 2. The sealing lips 2001 expand outward from the middle to the upper and lower ends, so that there is a sealing cavity 2002 between the two sealing lips 2001 and the lifting seat 2. The gas remaining in the sealing cavity 2002 will provide reverse pressure when the sealing lips 2001 are deformed by pressure, thereby providing reverse support protection for the sealing lips 2001 and preventing them from being over-deformed and crushed.

[0026] When using this device, the sample body 14 is fixed on the sample fixing block 13 and then placed on the positioning plate 12. The lifting seat 2 is driven down by the hydraulic cylinder 9 until it contacts the base 1 and is pressed and fixed. It can also be further locked with bolts to increase safety. The heating component 15 controls the thermal field, and multiple gas sources are injected into the sealed simulation cavity through multiple gas source connectors 11 to form an atmosphere field. After entering through the gas distribution ring groove 201, the gas flows downward through the gaps of the heated ceramic particles, increasing the temperature and achieving a uniform atmosphere field. This avoids the introduction of the atmosphere field causing severe interference fluctuations to the thermal field in the simulation cavity. Pressure is applied to the sample body 14, and hydraulic oil is released to the upper part of the sealed simulation cavity through the adjustable connector 10, pushing the sliding sealing piston 20 downward and causing the pressing block 19 to press the sample body 14 downward. The up and down movement of the pressing block 19 can be controlled by controlling the amount of hydraulic oil entering. This driving method perfectly solves the problem of poor sealing performance caused by mechanical structure drive.

[0027] It should be noted that, in order to obtain the state parameters inside the sealed simulation cavity and control the internal field loading, a force sensor is installed at the bottom of the pressing block 19 and a displacement sensor is installed on the sliding sealing piston 20. At the same time, an atmosphere sensor is connected from the side wall of the base 1 to obtain the atmosphere parameters inside the sealed simulation cavity. In addition, a thermocouple array is installed on the inner side wall of the base 1 inside the sealed simulation cavity to obtain the temperature field distribution inside the cavity, and a thermocouple is embedded in the inner wall of the recessed part of the sample fixing block 13 to record the temperature of the bottom of the sample body 14. The heating component 15 is used to stably provide the heat source, and a cold source pipe connected to the positioning plate 12 is buried at the bottom of the base 1. The cold source is at least one of water cooling, air cooling, or thermoelectric cooling. In addition, a heat flow meter is set on the heat flow path to collect the heat flow density passing through the sample body 14. To ensure the accuracy of heat flow measurement, the heat flow meter adopts a differential heat flow sensor, which is symmetrically arranged on the hot end surface and cold end surface of the sample body 14.

[0028] The software algorithm module includes a data acquisition unit, a simulation control unit, and a life prediction unit. Specifically, the data acquisition unit collects real-time data on temperature field distribution, compressive stress magnitude, displacement changes, and atmospheric parameter distribution. The simulation control unit controls the simulation mode. Subsequently, under different simulation modes, thermal resistance degradation curves are plotted based on the real-time acquired data, and a life prediction model is constructed to predict the remaining life under the target service boundary. The entire aging simulation and life prediction method includes the following steps: Step S1: After the sample body 14 is assembled and clamped, set the multi-field coupling loading boundary parameters. The boundary parameters include at least the hot / cold junction temperature T or the temperature gradient. T, load compressive stress σ, atmosphere composition C, and aging time t; Step S2: Establish a controlled temperature field and atmosphere field in the sealed simulation cavity and apply a controlled compressive stress load to simulate the aging of the sample body 14 under the multi-field coupling conditions of temperature-atmosphere-stress. Step S3: During the aging simulation, heat flow q and hot / cold end temperature are collected simultaneously to obtain temperature difference ΔT, compressive stress, sample thickness change calculated based on displacement, and atmospheric composition parameters. After data preprocessing, a time series dataset D(t) is formed. The atmospheric composition includes one or more of oxygen O2, water vapor H2O, carbon dioxide CO2, nitrogen N2, and inert gases. Data preprocessing includes operations such as data missing value completion, duplicate value removal, and time alignment. Step S4: Calculate the degradation curve of thermal insulation performance index over time based on the time series dataset D(t). The thermal insulation performance index includes at least the thermal resistance coefficient R(t), and determine the failure state based on a preset threshold. The thermal resistance R(t) is calculated as follows: R(t) = ΔT(t) / q(t), where ΔT(t) is the temperature difference between the hot end and the cold end, and q(t) is the heat flux density through the sample. Step S5: Acceleration factor and life model calibration. Based on the thermal resistance degradation curves under different temperature distribution fields, load stress and atmosphere composition combinations, obtain the failure time under the corresponding conditions. Then, calibrate the multi-field coupling acceleration coefficient K through simulation data, complete the accelerated aging equivalent conversion, and obtain the service life equivalent time, i.e. tservice=K·ttest, where ttest is the simulation time and tservice is the service life equivalent time. The above simulation modes include (1) synchronous coupling mode of isothermal-constant load-humid oxidizing atmosphere; (2) incremental coupling mode of stepped temperature rise and fall-step load-CO2 / humid atmosphere; and (3) periodic coupling mode of temperature gradient-cyclic load-low oxygen / inert atmosphere. Each of the three simulation modes will be illustrated using an example: Example 1: Simultaneous Coupling Mode of Isothermal-Constant Load-Humid Oxidizing Atmosphere The sample was processed into a 50mm×50mm×10mm specimen and then clamped and fixed. The hot end temperature and cold end temperature are set to 1000℃ and 200℃ respectively to form a stable temperature difference. The constant load compressive stress σ=1MPa, the atmosphere is a N2 / O2 / H2O mixture, the O2 volume fraction is 10%, and the dew point is 40℃. Real-time parameters are collected through online monitoring to form a time series dataset and calculate the thermal resistance coefficient, and plot the thermal resistance degradation curve. The failure criterion is that R(t) / R0 drops to 0.8, and R0 is the initial thermal resistance. The acceleration coefficient K is obtained by combining at least two sets of different O2 volume fraction operating conditions for joint calibration, thereby predicting the equivalent service life time of the target service boundary.

[0029] Example 2: Stepped temperature rise / fall - stepped load - CO2 / humid atmosphere progressive enhancement coupling mode The temperature range was set as a stepped heating and cooling process of 800→1000→1200→1000→800℃, with dwell times of 10s, 60s, 10min, 1h, and 4h set in each temperature range; the load stress was increased from 0.5MPa to 2MPa, and the load was applied in the heating and holding stages. The atmosphere was a mixture of N2, CO2, and H2O, with a CO2 volume fraction of 5–20% and a dew point temperature of 20–60℃. The rest of the steps were exactly the same as those in Example 1.

[0030] Example 3: Temperature gradient-cyclic load-low oxygen / inert atmosphere alternating coupling mode Set temperature gradient T is 20–60℃ / mm. The gradient is stabilized by heating at the hot end and dissipating heat at the cold end. The load is cyclically applied at a rate of 0.2–1 MPa and a frequency of 0.1–2 Hz. The atmosphere is a low-oxygen or inert atmosphere with an O2 volume fraction of 1–5%. The dew point or gas ratio is switched periodically. The rest of the steps are exactly the same as those in Example 1.

[0031] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. An aerogel aging simulation and prediction system based on multi-field coupling conditions, characterized in that, It includes a hardware device module and a software algorithm module; the hardware device module includes a base (1) and a lifting seat (2) that is vertically mounted above the base (1), and the base (1) and the lifting seat (2) form a sealed simulation cavity after they are in contact, closed and fixed. A positioning plate (12) fixed to the bottom of the base (1) is provided in the sealed simulation cavity. A sample fixing block (13) that carries the sample body (14) is installed on the top of the positioning plate (12). A heating component (15) is provided on the circumferential side wall of the base (1) at the corresponding position as the hot end. A cold source pipe connected to the positioning plate (12) is buried at the bottom of the base (1) as the cold end. A sliding sealing piston (20) is slidably provided in the lifting seat (2). A pressing block (19) for squeezing the sample body (14) is fixed at its bottom. The sliding sealing piston (20) is moved by injecting hydraulic oil into the upper part of the sealed simulation cavity. An air distribution ring groove (201) is provided in the side wall of the lifting seat (2) to introduce external multi-source air and connect to the sealed simulation cavity through the air outlet. The software algorithm module includes a data acquisition unit, a simulation control unit, and a life prediction unit. The data acquisition unit collects the temperature field distribution, compressive stress, displacement change, and atmosphere parameters in the sealed simulation cavity in real time. The simulation control unit is used to control the loading mode of the temperature field, load stress, and atmosphere. The life prediction unit fits the thermal resistance degradation curve based on the real-time acquired data and constructs a life prediction model to predict the remaining life under the target service boundary.

2. The aerogel aging simulation and prediction system based on multi-field coupling conditions according to claim 1, characterized in that, The top wall of the sample fixing block (13) is provided with a recessed part, and a fixing frame (16) is coaxially fixed at the top opening of the base (1). Multiple loading cavities (1601) are evenly arranged on the fixing frame (16), and each loading cavity (1601) is filled with ceramic particles (17).

3. The aerogel aging simulation and prediction system based on multi-field coupling conditions according to claim 1, characterized in that, The sliding sealing piston (20) is symmetrically provided with sealing lips (2001) on the upper and lower sides. The sealing lips (2001) abut against the inner wall of the lifting seat (2). The sealing lips (2001) expand outward from the middle to the upper and lower ends, and there is a sealing cavity (2002) between the two sealing lips (2001) and the lifting seat (2).

4. The aerogel aging simulation and prediction system based on multi-field coupling conditions according to claim 1, characterized in that, A force sensor is installed at the bottom of the pressing block (19), a displacement sensor is installed on the sliding sealing piston (20), an atmosphere sensor is connected to the side wall of the base (1), and a thermocouple array is installed on the inner side wall of the base (1) for real-time monitoring of stress, displacement, atmosphere and temperature field distribution. A heat flow meter is installed on the heat flow path and is installed on the hot end and cold end surfaces of the sample body (14).

5. A method for simulating and predicting aerogel aging using the system described in any one of claims 1-4, characterized in that, The method includes the following steps: S1: After clamping and fixing the sample body (14), set the boundary parameters of the multi-field coupling loading. The boundary parameters include hot / cold end temperature, temperature gradient, load compressive stress, atmosphere composition and aging time. S2: Establish a controlled temperature field and atmosphere field in the sealed simulation cavity, and apply a controllable load compressive stress to simulate the aging of the sample body (14) under the multi-field coupling conditions of temperature-atmosphere-stress. S3: During the aging simulation, heat flux density, temperature difference between hot and cold ends, compressive stress, sample thickness change and atmospheric composition parameters are collected simultaneously. After data preprocessing, a time series dataset D(t) is formed. S4: Calculate the degradation curve of thermal resistance coefficient R(t) over time based on the time series dataset D(t), and determine the failure state of the sample based on the preset failure threshold; thermal resistance R(t) is calculated by the following formula: R(t) = ΔT(t) / q(t), where ΔT(t) is the temperature difference between the hot end and the cold end, and q(t) is the heat flux density through the sample; S5: Based on the thermal resistance degradation curves under different temperature, load stress and atmospheric composition combinations, obtain the failure time corresponding to each condition, calibrate the multi-field coupling acceleration coefficient K, complete the accelerated aging equivalent conversion, and obtain the service life equivalent time, i.e. tservice=K·ttest, where ttest is the simulation time and tservice is the service life equivalent time.

6. The aerogel aging simulation and prediction method according to claim 5, characterized in that, In step S2, multi-source gas is introduced into the gas distribution ring groove (201) through the gas source connector (11) installed on the side wall of the lifting seat (2). After the gas is preheated and homogenized through the gaps of the ceramic particles (17), it enters the sealed simulation cavity to form a uniform atmosphere field.

7. The aerogel aging simulation and prediction method according to claim 5, characterized in that, The simulation modes in step S2 include at least one of the following: isothermal-constant load-humid oxidizing atmosphere synchronous coupling mode; stepped temperature rise and fall-step load-CO2 / humid atmosphere progressively enhanced coupling mode; temperature gradient-cyclic load-low oxygen / inert atmosphere periodically alternating coupling mode.

8. The aerogel aging simulation and prediction method according to claim 7, characterized in that, In the isothermal-constant-humidified oxidizing atmosphere synchronous coupling mode, the atmosphere is a N2 / O2 / H2O mixture, with an O2 volume fraction of 10% and a dew point of 40℃.

9. The aerogel aging simulation and prediction method according to claim 7, characterized in that, In the stepped temperature rise / fall - stepped load - CO2 / humid atmosphere progressive enhancement coupling mode, the CO2 volume fraction is 5-20% and the dew point temperature is 20-60℃.

10. The aerogel aging simulation and prediction method according to claim 7, characterized in that, In the temperature gradient-cyclic load-low oxygen / inert atmosphere periodically alternating coupling mode, the O2 volume fraction is 1-5%, and the gas dew point or ratio is switched periodically.

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