A method, system, equipment and medium for testing the performance of fireproof boards.

Abstract

This application discloses a method, system, equipment, and medium for testing the performance of fireproof boards, relating to the field of fireproof board performance testing technology. The method includes the following steps: constructing a multi-dimensional coupling testing scenario for the target fireproof board based on a simulation model; obtaining the thermal insulation performance index, fire resistance performance index, mechanical performance index, and corrosion resistance performance index of the target fireproof board under different multi-dimensional coupling testing scenarios; inputting the thermal insulation performance index, fire resistance performance index, mechanical performance index, and corrosion resistance index under the same multi-dimensional coupling testing scenario into a preset coupling performance testing model to obtain the coupling performance index of the target fireproof board under the corresponding multi-dimensional coupling testing scenario; and inputting each coupling performance index into a preset comprehensive performance evaluation model to obtain the comprehensive performance index of the target fireproof board. This application has the advantages of effectively characterizing the multi-dimensional coupling effect under real fire scenarios and improving the testing results.

Description

Technical Field

[0001] This application relates to the field of fireproof board performance testing technology, and in particular to a method, system, equipment and medium for testing fireproof board performance. Background Technology

[0002] As a core material for building fire safety, fire-resistant boards directly determine the safety and durability of buildings in fire scenarios through their thermal insulation, fire resistance, mechanical properties, and corrosion resistance. Currently, existing technologies for testing the performance of fire-resistant boards employ a "single performance independent testing + direct superposition of test results" model. This involves individually testing the thermal insulation performance, fire resistance limit, mechanical strength, and corrosion resistance of the fire-resistant board under a standard laboratory environment (constant temperature and humidity, no coupling interference), and then simply adding or weighting the results of each individual performance test to characterize the overall performance of the fire-resistant board.

[0003] The aforementioned testing methods have the following core defects: they lack consideration of the coupling effect of various performance indicators and cannot characterize the multi-dimensional coupling performance in real fires. In real fire scenarios, fireproof boards will simultaneously face the synergistic effects of multiple factors such as high temperature, corrosion, and mechanical loads. There are significant mutual influences between various performance characteristics (for example, high temperature environments will accelerate the corrosion rate of fireproof boards and cause a significant decrease in their mechanical strength; corrosion will damage the internal structure of fireproof boards, thereby reducing their heat insulation and fire resistance performance). The independent testing modes of existing technologies cannot capture this multi-dimensional coupling effect, resulting in a large deviation between the test results and the performance under real fire scenarios, and the test results are not very reliable. Summary of the Invention

[0004] The main purpose of this application is to provide a method, system, equipment and medium for testing the performance of fireproof boards, which aims to solve the technical problem that the fireproof board performance testing method adopts an independent testing mode for each test index, making it difficult to accurately characterize the multi-dimensional coupling effect under real fire scenarios, resulting in inaccurate test results.

[0005] To achieve the above objectives, this application provides a method for testing the performance of fire-resistant boards, comprising the following steps: A multi-dimensional coupled detection scenario for the target fireproof board is constructed based on a simulation model. The multi-dimensional coupled detection scenario includes a variable temperature fire-mechanical-corrosion coupled scenario, a variable humidity-corrosion-insulation coupled scenario, an airflow interference-variable temperature-insulation coupled scenario, and an aging-corrosion-fire resistance coupled scenario. The thermal insulation performance index, fire resistance performance index, mechanical performance index, and corrosion resistance performance index of the target fireproof board were obtained under different multi-dimensional coupled testing scenarios. The thermal insulation performance index, fire resistance performance index, mechanical performance index and corrosion resistance performance index under the same multidimensional coupling test scenario are respectively input into the preset coupling performance test model to obtain the coupling performance index of the target fireproof board under the corresponding multidimensional coupling test scenario. The coupling performance indices are input into a preset comprehensive performance evaluation model to obtain the comprehensive performance index of the target fireproof board.

[0006] Optionally, the expression for the coupling performance testing model is: ; In the formula, I represents the coupling performance index of the target fireproof board in the corresponding multidimensional coupling detection scenario. T I represents the thermal insulation performance index corresponding to a certain multidimensional coupled testing scenario. t I represents the fire resistance performance index corresponding to a certain multidimensional coupled detection scenario. M I represents the mechanical performance index corresponding to a certain multidimensional coupled detection scenario. ω Let w1 be the corrosion resistance index corresponding to a certain multidimensional coupled detection scenario, w2 be the first weighting coefficient, w3 be the second weighting coefficient, and w4 be the fourth weighting coefficient.

[0007] Optionally, the expression for the comprehensive performance evaluation model is: ; In the formula, I total Let n be the comprehensive performance index of the target fireproof board, n be the number of multi-dimensional coupled detection scenarios, and k be the comprehensive performance index of the target fireproof board. i Let I be the weight coefficient corresponding to the i-th multidimensional coupled detection scenario. i Let ε be the coupling performance index corresponding to the i-th multidimensional coupling detection scenario, and ε be the correction coefficient.

[0008] Optionally, the correction coefficient ε is obtained as follows: Obtain the actual density ρ and actual thickness h of the target fireproof board to obtain the material deviation factor Δη of the target fireproof board. m ; Obtain the actual installation angle θ of the target fireproof board to obtain the installation angle deviation factor Δη. θ ; According to the material deviation factor Δη m and installation angle deviation factor Δη θ To obtain the correction coefficient ε, the expression for ε is: ε=w5·Δη m +w6·Δη θ ; In the formula, w5 is the fifth weighting coefficient and w6 is the sixth weighting coefficient.

[0009] Optionally, the material deviation factor Δη m The expression is: ; In the formula, ρ0 is the reference density of the industry standard fireproof board, and h0 is the sample thickness of the standard fireproof board.

[0010] Optionally, the installation angle deviation factor Δη θ The expression is: Δη θ =sinθ-sinθ0; In the formula, θ0 is the vertical installation reference angle of the fireproof board, i.e., θ0 = 90°.

[0011] Optionally, the thermal insulation performance index, fire resistance performance index, mechanical performance index, and corrosion resistance performance index of the target fireproof board under different multi-dimensional coupled testing scenarios are obtained, including: Obtain the average temperature difference ΔT between the two sides of the target fireproof board under the corresponding multidimensional coupled detection scenario to obtain the thermal insulation performance index I. T Among them, I T =ΔT / ΔT0×100, where ΔT0 is the baseline value of the temperature difference between the two sides of the target fireproof board under standard conditions; Obtain the fire resistance limit time t of the target fireproof board under the corresponding multidimensional coupled detection scenario to obtain the fire resistance performance index I. t Among them, I t =t / t0×100, where t0 is the reference value of the fire resistance limit time of the target fireproof board under standard environment; Obtain the compressive strength σ and flexural strength τ of the target fireproof board under the corresponding multidimensional coupled detection scenario to obtain the mechanical performance index I. M Among them, I M =(σ+τ) / (σ0+τ0)×100, where σ0 is the benchmark value of the compressive strength of the target fireproof board under standard conditions, and τ0 is the benchmark value of the flexural strength of the target fireproof board under standard conditions. Obtain the mass loss rate ω of the target fireproof board under the corresponding multidimensional coupled detection scenario to obtain the corrosion resistance index I. ω Among them, I ω =[1-(ω-ω0) / (1-ω0)]×100, where ω0 is the benchmark value of the mass loss rate of the target fireproof board under standard conditions.

[0012] To achieve the above objectives, this application also provides a fireproof board performance testing system, comprising: The coupling scenario construction module is used to construct multi-dimensional coupling detection scenarios for the target fireproof board based on the simulation model. Among them, the multi-dimensional coupling detection scenarios include temperature change fire-mechanics-corrosion coupling scenario, humidity change-corrosion-insulation coupling scenario, airflow interference-temperature change-insulation coupling scenario, and aging-corrosion-fire resistance coupling scenario. The performance index acquisition module is used to acquire the thermal insulation performance index, fire resistance performance index, mechanical performance index and corrosion resistance performance index of the target fireproof board under different multi-dimensional coupled testing scenarios. The coupling detection module is used to input the thermal insulation performance index, fire resistance performance index, mechanical performance index and corrosion resistance performance index under the same multidimensional coupling detection scenario into the preset coupling performance detection model to obtain the coupling performance index of the target fireproof board under the corresponding multidimensional coupling detection scenario. The comprehensive performance evaluation module is used to input the various coupled performance indices into a preset comprehensive performance evaluation model to obtain the comprehensive performance index of the target fireproof board.

[0013] To achieve the above objectives, this application also provides a computer device, which includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the above-described method.

[0014] To achieve the above objectives, this application also provides a computer-readable storage medium storing a computer program, on which a processor executes the computer program to implement the above-described method.

[0015] The beneficial effects that this application can achieve are as follows: This application constructs a multi-dimensional coupled detection scenario for the target fireproof board based on a simulation model. This scenario effectively simulates multi-dimensional coupled scenarios in real fires and actual building environments to match the complex conditions of real building environments. Then, it simultaneously detects the thermal insulation performance index, fire resistance performance index, mechanical performance index, and corrosion resistance performance index of the target fireproof board under different multi-dimensional coupled detection scenarios. This captures the coupling influence between various performance indicators, characterizing the synergistic effect of each performance indicator in complex environments. The thermal insulation performance index, fire resistance performance index, mechanical performance index, and corrosion resistance performance index under the same multi-dimensional coupled detection scenario are then input into a preset coupled performance detection model to obtain the coupled performance index of the target fireproof board under the corresponding multi-dimensional coupled detection scenario. Finally, each coupled performance index is input into a preset comprehensive performance evaluation model to calculate the comprehensive performance index of the target fireproof board. This achieves accurate characterization of the true performance of the target fireproof board, effectively solving the problem of existing technologies' detection results being disconnected from real scenarios and unable to characterize coupled performance. The final detection results have strong reference and guidance value. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the specific embodiments of this application or the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn to scale.

[0017] Figure 1 This is a flowchart illustrating a method for testing the performance of a fireproof board according to an embodiment of this application; Figure 2 This is a schematic diagram of the framework of a fireproof board performance testing system according to an embodiment of this application; Figure 3 This is a schematic diagram of the computer device structure of the hardware operating environment involved in the embodiments of this application.

[0018] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0019] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0020] It should be noted that if the embodiments of this application involve descriptions such as "first" or "second," these descriptions are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, features defined with "first" or "second" may explicitly or implicitly include at least one of those features. Furthermore, the technical solutions of the various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. When the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed in this application.

[0021] Example 1 Reference Figure 1 This embodiment provides a method for testing the performance of fireproof boards, including the following steps: Step S10: Construct a multi-dimensional coupled detection scenario for the target fireproof board based on the simulation model; wherein, the multi-dimensional coupled detection scenario includes the temperature change fire-mechanics-corrosion coupled scenario, the humidity change-corrosion-insulation coupled scenario, the airflow interference-temperature change-insulation coupled scenario, and the aging-corrosion-fire resistance coupled scenario. In this step, multiphysics coupling simulation software (such as ANSYS, COMSOL Multiphysics, etc.) can be used to construct a three-dimensional simulation model by combining the material parameters (density, thickness, composition, thermal conductivity, mechanical parameters, etc.) and installation parameters (installation angle, fixing method) of the target fireproof board. This model accurately replicates the actual structure and installation state of the target fireproof board. The simulation model can significantly reduce the equipment investment, sample loss, and testing cycle of physical scene simulation, and is especially suitable for batch sample testing, performance prediction of new fireproof boards, and simulation of extreme environment scenarios. At the same time, the simulation model can flexibly adjust scene parameters to quickly adapt to the testing needs of different building application scenarios. It can also embed core physical models such as fire dynamics, heat conduction, mechanical load, and corrosion dynamics to achieve accurate simulation of multidimensional coupled testing scenarios. Four representative core coupled scenarios were constructed here. Among them, the variable-temperature fire-mechanics-corrosion coupled scenario is used to simulate the variable-temperature process of a real fire (e.g., from room temperature to the peak fire temperature of 800-1200℃, with a heating rate of 5-15℃ / min, maintaining the peak temperature for 1-3 hours and then naturally cooling down). At the same time, mechanical pressure simulating the building structure load (0.1-10MPa, which can be adjusted according to the actual application scenario of the fireproof board) is applied, and corrosive media (such as acidic gases SO2 and NO in fire smoke) are introduced. X The concentration is 50-500ppm, which focuses on simulating the synergistic effect of high temperature, mechanical load, and corrosion in a fire; the humidification-corrosion-insulation coupling scenario is used to simulate the humidification process of the actual building environment (e.g., relative humidity 30%-95%, periodic alternation, period 12-24h), introducing a corrosive medium (as above), and applying a gradient temperature (25-600℃) to simulate the coupled effect of humid environment and corrosion on the heat insulation performance of fireproof boards; the airflow interference-temperature change-insulation coupling scenario is suitable for high-rise buildings, tunnels, and other scenarios with airflow interference, and is used to simulate the coupled effect of airflow and temperature changes on the heat insulation performance of fireproof boards during a fire. For example, specific parameters can be set as follows: simulating the temperature change process of a fire (room temperature rises to 700-1... The system operates at 000℃ with a heating rate of 8-12℃ / min, while simultaneously applying an airflow velocity of 0.5-3m / s (simulating wind loads in high-rise buildings and airflow in tunnels). It monitors the temperature difference and heat transfer rate on both sides of the fireproof board in real time to analyze the attenuation of insulation performance under airflow interference, ensuring that the insulation performance testing of fireproof boards in high-rise buildings, tunnels, and other scenarios is realistic. The aging-corrosion-fire resistance coupling scenario is suitable for long-term used buildings (such as old factories and existing building renovations) to simulate the synergistic effects of long-term aging of fireproof boards, environmental corrosion, and high temperatures during fire. For example, specific parameters can be set as follows: first, the fireproof board is placed in an aging environment (temperature 40℃, relative humidity 85%) for 30-90 days, then corrosive media (SO2, NO) are introduced. XThe fireproof board was corroded for 24-72 hours with a mixed gas (concentration 100-300ppm). Finally, the fire resistance limit and heat release rate of the fireproof board were tested by simulating the fire temperature change process (room temperature rises to 800-1100℃) to evaluate the performance stability of the fireproof board in a fire after long-term use, and to provide a test basis for the replacement and maintenance of fireproof boards in existing buildings.

[0022] It should be noted that, in addition to the four core multidimensional coupling detection scenarios mentioned above, corresponding multidimensional coupling detection scenarios can also be constructed based on the environmental characteristics of the region where the fireproof board is used. For example, the salt spray-high temperature-mechanical coupling scenario and the low temperature-freeze-thaw-mechanical coupling scenario. The salt spray-high temperature-mechanical coupling scenario is suitable for buildings in coastal and high salt spray areas (such as coastal office buildings and port warehouses), and can simulate the synergistic effect of salt spray corrosion, summer high temperature and building structural load in this area. The low temperature-freeze-thaw-mechanical coupling scenario is suitable for buildings in cold and frigid areas (such as northern residences and plateau buildings), and can simulate the coupling effect of winter low temperature freeze-thaw cycle and building structural load.

[0023] The above-mentioned multi-dimensional coupled detection scenarios require defining the coupling relationships between various physical fields (such as the attenuation correlation of high temperature on material mechanical parameters, and the influence coefficient of corrosion on thermal insulation performance) to ensure the consistency between the simulation scenario and the real scenario and the physical detection scenario, thereby fitting the fireproof board detection scenario and accurately quantifying the interaction law of field quantities. The specific coupling relationships between various physical fields are defined as follows: (1) The coupling relationship between the temperature field and the mechanical field (core coupling) Definition logic: Temperature changes cause the mechanical parameters (compressive / flexural strength) of fireproof board materials to decrease, and mechanical deformation, in turn, affects the temperature conduction efficiency, forming a two-way coupling.

[0024] The definition of quantification is as follows: ① Formula for the decay of mechanical parameters with temperature (related to temperature field → mechanical field):

[0025] ; In the formula: , These are the compressive strength and flexural strength at a certain temperature T, respectively. , These are the benchmark values ​​for compressive strength and flexural strength at standard temperature (25℃), respectively. The temperature decay coefficient (determined based on the properties of the fireproof board material, such as basalt fiber). T represents the real-time temperature of the temperature field. .

[0026] ② The effect of mechanical deformation on temperature conduction (related mechanical field → temperature field): Set mechanical deformation amount With thermal conductivity Relationships: In the formula, For the fireproof board, the mechanical deformation is Real-time thermal conductivity coefficient at that time To ensure that the fireproof board does not deform mechanically ( The reference thermal conductivity coefficient when =0); based on this formula, it can be characterized that the greater the deformation, the greater the thermal conductivity coefficient and the worse the thermal insulation performance, thus indicating that the internal structure of the fireproof board becomes loose and the heat conduction is accelerated after deformation.

[0027] (2) Coupling relationship between temperature field and corrosion field Definition logic: High temperature accelerates the reaction rate of corrosive media, corrodes and damages the surface and internal structure of fireproof board, thereby affecting temperature conduction (thermal insulation performance), forming a coupling of unidirectional dominance and bidirectional influence.

[0028] The definition of quantification is as follows: ① Formula for corrosion rate as a function of temperature (temperature field → corrosion field): ; In the formula, The corrosion rate at temperature T (mass loss rate / hour); The baseline corrosion rate is set at 25°C. Corrosion temperature coefficient (e.g., for SO2 media) ).

[0029] ② The effect of corrosion on temperature conduction (corrosion field → temperature field): Corrosion quality loss rate Related thermal conductivity coefficient: , To ensure the fireproof board has a corrosion-induced quality loss rate The real-time thermal conductivity coefficient at that time is used to characterize the severity of corrosion. The larger the internal structure, the more pores it has, the faster it conducts heat, and the more significant the decrease in its heat insulation performance.

[0030] (3) Coupling relationship between mechanical field and corrosion field Definition logic: Mechanical loads cause microcracks on the surface of the fireproof board, which increases the penetration area of ​​the corrosive medium and accelerates corrosion; the defects caused by corrosion (such as surface pitting and internal pores) reduce the mechanical strength of the material, forming a two-way coupling.

[0031] The definition of quantification is as follows: ① The effect of mechanical load on corrosion rate (mechanical field → corrosion field): ; In the formula, The corrosion rate at temperature T. For real-time mechanical loads (including compressive strength and flexural strength); As the reference mechanical load, The load influence coefficient is typically taken as 0.2 to 0.5. The greater the load, the more microcracks appear, and the faster the corrosion occurs.

[0032] ② The effect of corrosion on mechanical properties (corrosion field → mechanical field): Combined with corrosion quality loss rate Corrected mechanical strength: , To reduce corrosion quality loss rate Under real-time mechanical loads, corrosion-induced mass loss directly reduces material density, and mechanical strength decreases synchronously.

[0033] (4) Coupling relationship between humidity field and other fields (adapting to scenarios of humidity change, corrosion and heat insulation) Definition logic: Increased humidity accelerates the corrosion reaction and affects the heat conduction efficiency of the fireproof board (humid materials conduct heat faster), which in turn affects the mechanical properties (humid environments cause the material to soften).

[0034] The definition of quantification is as follows: ① The effect of humidity on corrosion rate: RH stands for relative humidity (30%~95%). The value represents the corrosion rate at relative humidity. The higher the humidity, the easier it is for corrosive media (such as SO2) to dissolve and form an acidic solution, resulting in faster corrosion.

[0035] ② The effect of humidity on temperature conduction: , The real-time thermal conductivity coefficient of the fireproof board under relative humidity is shown. The thermal conductivity of the damp fireproof board is significantly higher than that in the dry state, resulting in a decrease in its thermal insulation performance.

[0036] Simulation implementation instructions for coupling relationships: By inputting the above quantitative definition formulas and correlation logic into simulation software such as ANSYS / COMSOL, the construction of various multidimensional coupled detection scenarios can be realized. The specific definition is completed through the following steps: 1. Establish the basic models for each physical field (using the heat conduction equation for the temperature field, the elasticity equation for the mechanical field, and the reaction kinetics equation for the corrosion field); 2. In the software's "Multi-Field Coupling Settings", import the above correlation formulas and set the coupling boundary conditions (such as the correlation between the surface temperature of the fireproof board and the corrosion rate, and the correlation between mechanical load and microcrack propagation). 3. Set the coupling solution order (according to the real physical process: temperature / humidity → corrosion → mechanics, or temperature → mechanics → corrosion) to ensure that the simulation results are close to reality.

[0037] Step S20: Obtain the thermal insulation performance index, fire resistance performance index, mechanical performance index, and corrosion resistance performance index of the target fireproof board under different multi-dimensional coupling test scenarios; In this step, dynamic monitoring data of parameters (temperature, humidity, mechanical load, and concentration of corrosive medium) of each scenario are collected in real time based on the constructed multidimensional coupled detection scenarios. For each coupled scenario, the index of each performance is calculated to reflect the degree of performance degradation under the coupled environment.

[0038] As an optional implementation, step S20 specifically includes the following steps: Step S21: Obtain the average temperature difference ΔT between the two sides of the target fireproof board in the corresponding multidimensional coupling detection scenario to obtain the thermal insulation performance index I. T Among them, I T =ΔT / ΔT0×100, where ΔT0 is the baseline value of the temperature difference between the two sides of the target fireproof board under standard conditions; Step S22: Obtain the fire resistance limit time t of the target fireproof board under the corresponding multidimensional coupled detection scenario, so as to obtain the fire resistance performance index I. t Among them, I t =t / t0×100, where t0 is the reference value of the fire resistance limit time of the target fireproof board under standard environment; Step S23: Obtain the compressive strength σ and flexural strength τ of the target fireproof board under the corresponding multidimensional coupled detection scenario to obtain the mechanical performance index I. M Among them, I M =(σ+τ) / (σ0+τ0)×100, where σ0 is the benchmark value of the compressive strength of the target fireproof board under standard conditions, and τ0 is the benchmark value of the flexural strength of the target fireproof board under standard conditions. Step S24: Obtain the mass loss rate ω of the target fireproof board under the corresponding multidimensional coupled detection scenario, so as to obtain the corrosion resistance index I. ω Among them, I ω =[1-(ω-ω0) / (1-ω0)]×100, where ω0 is the benchmark value of the mass loss rate of the target fireproof board under standard conditions.

[0039] In this embodiment, temperature difference data of both sides (i.e., both planes) of the target fireproof board are collected at different time periods, and the average temperature difference value ΔT is calculated. The ratio of ΔT to the baseline temperature difference value ΔT0 under standard conditions reflects the heat conduction capacity, thereby indirectly reflecting the heat insulation performance. Multiplying the ratio by 100 results in the final calculated fire resistance performance index I. tBetween 0 and 100, a higher value indicates better thermal insulation performance and less attenuation under coupled conditions. Similarly, the fire resistance performance can be reflected by the ratio of the measured fire resistance limit time t of the target fireproof board to the baseline fire resistance limit time t0 under the corresponding multidimensional coupled testing scenario. The final calculated fire resistance performance index I... t The value is between 0 and 100; the higher the value, the better the fire resistance under coupled conditions. Mechanical performance can be reflected by the ratio of the measured mechanical load (including compressive strength σ and flexural strength τ) to the corresponding benchmark value. The calculated mechanical performance index I... M Between 0 and 100, a larger value indicates less mechanical performance degradation and better structural stability under coupled conditions. The corrosion resistance performance can be reflected by the ratio of the measured mass loss rate ω to the corresponding baseline value ω0, and the final calculated corrosion resistance index I... ω Between 0 and 100, the larger the value, the better the corrosion resistance and the smaller the mass loss in the coupled environment.

[0040] Step S30: Input the thermal insulation performance index, fire resistance performance index, mechanical performance index and corrosion resistance performance index under the same multidimensional coupling test scenario into the preset coupling performance test model to obtain the coupling performance index of the target fireproof board under the corresponding multidimensional coupling test scenario. In this step, the thermal insulation performance index, fire resistance performance index, mechanical performance index, and corrosion resistance performance index calculated under each multidimensional coupling test scenario are input into the coupling performance test model, and the coupling performance index under different multidimensional coupling test scenarios can be calculated respectively.

[0041] As an optional implementation, the expression for the coupling performance detection model is: ; In the formula, I represents the coupling performance index of the target fireproof board in the corresponding multidimensional coupling detection scenario. T I represents the thermal insulation performance index corresponding to a certain multidimensional coupled testing scenario. t I represents the fire resistance performance index corresponding to a certain multidimensional coupled detection scenario. M I represents the mechanical performance index corresponding to a certain multidimensional coupled detection scenario. ω Let w1 be the corrosion resistance index corresponding to a certain multidimensional coupled detection scenario, w2 be the first weighting coefficient, w3 be the second weighting coefficient, and w4 be the fourth weighting coefficient.

[0042] In this embodiment, since the calculated values ​​of each performance index are between 1 and 100, the influence of dimensions is eliminated. Therefore, a weighted summation method can be used to calculate the coupling performance index I. The final value of the coupling performance index I is also between 0 and 100. w1-w4 are the weight coefficients of each individual performance, which can be adjusted according to the application scenario of the fireproof board (e.g., for building firewalls, which focus on fire resistance and heat insulation performance, w1=0.3, w2=0.4, w3=0.15, w4=0.15; for building ceilings, which focus on mechanical and heat insulation performance, w1=0.35, w2=0.2, w3=0.35, w4=0.1), and w1+w2+w3+w4=1. The weight coefficients can be optimized and determined by the analytic hierarchy process or machine learning algorithm to improve the scientific nature of the index calculation.

[0043] Step S40: Input each coupling performance index into the preset comprehensive performance evaluation model to obtain the comprehensive performance index of the target fireproof board. The expression of the comprehensive performance evaluation model is: ; In the formula, I total Let n be the comprehensive performance index of the target fireproof board, n be the number of multi-dimensional coupled detection scenarios, and k be the comprehensive performance index of the target fireproof board. i Let I be the weight coefficient corresponding to the i-th multidimensional coupled detection scenario. i Let ε be the coupling performance index corresponding to the i-th multidimensional coupling detection scenario, and ε be the correction coefficient.

[0044] In this step, the number n of multidimensional coupling detection scenarios is set according to the probability of occurrence of each coupling scenario, and there should be at least one (i.e., n≥1). For example, coupling scenarios with a probability greater than 30% should be considered. Then, the coupling performance indices calculated for different multidimensional coupling detection scenarios are input into the above formula. Based on the usage conditions such as the region and building structure where the target fireproof board will be used, the possible coupling scenarios are evaluated, and the corresponding weight coefficient k for each multidimensional coupling detection scenario is set accordingly. i That is, adjusting the weighting coefficient k according to the probability of the scenario occurring in actual fire and building environments. i If the assessment includes scenarios such as temperature-dependent fire-mechanical-corrosion and humidity-dependent corrosion-insulation, and the temperature-dependent fire-mechanical-corrosion scenario is assessed as having a higher probability of occurrence, then the corresponding weighting coefficient is set to k1=0.6, while the weighting coefficient for the humidity-dependent corrosion-insulation scenario is set to k2=0.4. Furthermore, a correction coefficient ε is used to correct for model prediction errors, improving calculation accuracy. Finally, the comprehensive performance index I is calculated. total It can accurately quantify the overall performance in complex scenarios, and has strong reference and guidance value.

[0045] It should be noted that the comprehensive performance index I obtained from the calculation... totalIt allows setting grading standards to determine the overall performance level of the target fireproof board, and simultaneously outputs individual performance indices, coupled performance indices, and overall performance indices for each coupled scenario, generating a complete test report. For example, the specific grading standards are as follows: Excellent: I total ≥90; Good: 80≤I total <90; qualified: 70≤I total <80; Unacceptable: I total <70.

[0046] In the above formula, the correction coefficient ε is obtained as follows: Obtain the actual density ρ and actual thickness h of the target fireproof board to obtain the material deviation factor Δη of the target fireproof board. m Material deviation factor Δη m The expression is: ; In the formula, ρ0 is the reference density of the industry standard fireproof board, and h0 is the sample thickness of the standard fireproof board. Obtain the actual installation angle θ of the target fireproof board to obtain the installation angle deviation factor Δη. θ Installation angle deviation factor Δη θ The expression is: Δη θ =sinθ-sinθ0; In the formula, θ0 is the vertical installation reference angle of the fireproof board, i.e., θ0 = 90°; According to the material deviation factor Δη m and installation angle deviation factor Δη θ To obtain the correction coefficient ε, the expression for ε is: ε=w5·Δη m +w6·Δη θ ; In the formula, w5 is the fifth weighting coefficient and w6 is the sixth weighting coefficient.

[0047] In this embodiment, the correction coefficient ε comprehensively considers the error effects caused by the material deviation of the target fireproof board and the installation angle, wherein the material deviation factor Δη m By comprehensively calculating the relative deviations in density and thickness, the deviations between the inherent parameters of the fireproof board material and the standard sample can be characterized; the installation angle deviation factor Δη θThe performance deviation between the actual installation angle and the standard testing angle is characterized by the difference in the sine value between the actual installation angle and the vertical installation reference angle. This factor can accurately quantify the impact of tilted and horizontal installation on the stress, heat transfer, and fire resistance performance of the fireproof board. Since θ takes values ​​of 0°-90°, sinθ takes values ​​of 0-1, and sinθ0=1, the range of Δηθ is [-1, 0]. The calculated material deviation factor Δη... m and installation angle deviation factor Δη θ Since it has no dimensionless units, the correction coefficient ε can be calculated by weighted summation, abandoning the traditional fixed numerical correction method. Based on the material parameters and installation angle parameters of the fireproof board itself, the accuracy of the model output is effectively improved.

[0048] In summary, the solution of this embodiment has the following significant advantages compared with the prior art: (1) It solves the problem that existing technologies cannot characterize multidimensional coupling performance: By constructing multidimensional coupling scenarios in real fire and actual building environments, multiple properties of fireproof boards are tested simultaneously, and the coupling effects between various performance indicators are captured (such as the attenuation effect of high temperature on mechanical and corrosion resistance, and the destructive effect of corrosion on heat insulation and fire resistance). It can accurately answer practical questions such as "how mechanical strength is attenuated at high temperature" and "how much heat insulation performance is reduced after corrosion". The test results are more in line with real application scenarios.

[0049] (2) It achieves the matching of the testing environment with the actual building environment: simulates actual building environment factors such as temperature change, humidity change, different installation methods, and corrosion, breaks the limitations of the ideal environment of the standard laboratory, and enables the test results to be directly mapped to the actual application, providing accurate technical support for building fire protection design and material selection. Referring to the application effect of the flexible fireproof board multi-physics field coupling test platform, it can significantly improve the reliability of fireproof board in actual application.

[0050] (3) A scientific comprehensive performance evaluation model was constructed to improve the accuracy and practicality of the test results: The decay law of each performance index was quantified by the algorithm formula, and a comprehensive performance evaluation model was constructed by combining machine learning algorithm. This avoids the drawback of the existing technology of "simple superposition". It can accurately output the comprehensive performance index. At the same time, the weight coefficient can be adjusted according to different application scenarios to adapt to the test requirements of different types of fireproof boards. The model prediction accuracy is high and the test accuracy meets the standard requirements of multi-field coupling performance test.

[0051] Example 2 Reference Figure 2 Based on the same inventive concept as the foregoing embodiments, this embodiment also provides a fireproof board performance testing system, including: The coupling scenario construction module is used to construct multi-dimensional coupling detection scenarios for the target fireproof board based on the simulation model. Among them, the multi-dimensional coupling detection scenarios include temperature change fire-mechanics-corrosion coupling scenario, humidity change-corrosion-insulation coupling scenario, airflow interference-temperature change-insulation coupling scenario, and aging-corrosion-fire resistance coupling scenario. The performance index acquisition module is used to acquire the thermal insulation performance index, fire resistance performance index, mechanical performance index and corrosion resistance performance index of the target fireproof board under different multi-dimensional coupled testing scenarios. The coupling detection module is used to input the thermal insulation performance index, fire resistance performance index, mechanical performance index and corrosion resistance performance index under the same multidimensional coupling detection scenario into the preset coupling performance detection model to obtain the coupling performance index of the target fireproof board under the corresponding multidimensional coupling detection scenario. The comprehensive performance evaluation module is used to input the various coupled performance indices into a preset comprehensive performance evaluation model to obtain the comprehensive performance index of the target fireproof board.

[0052] The explanations and examples of the modules in this embodiment can be found in the methods of the foregoing embodiments, and will not be repeated here.

[0053] Example 3 Based on the same inventive concept as the foregoing embodiments, this embodiment provides a computer device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-described method.

[0054] As an optional implementation method, refer to Figure 3 , Figure 3This is a schematic diagram of the computer device structure of the hardware operating environment involved in this embodiment. The computer device may include: a processor 1001, such as a central processing unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. The communication bus 1002 is used to realize communication between these components. The user interface 1003 may include a display screen and an input unit such as a keyboard. The user interface 1003 may also include standard wired interfaces and wireless interfaces. The network interface 1004 may optionally include standard wired interfaces and wireless interfaces (such as a Wi-Fi interface). The memory 1005 may be a high-speed random access memory (RAM) or a stable non-volatile memory (NVM), such as a disk storage device. The memory 1005 may also optionally be a storage device independent of the aforementioned processor 1001.

[0055] Those skilled in the art will understand that Figure 3 The structure shown does not constitute a limitation on the computer device and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0056] like Figure 3 As shown, the memory 1005, which serves as a storage medium, may include an operating system, a data storage module, a network communication module, a user interface module, and electronic programs.

[0057] exist Figure 3 In the computer device shown, the network interface 1004 is mainly used for data communication with the network server; the user interface 1003 is mainly used for data interaction with the user; the processor 1001 and the memory 1005 in the computer device of this embodiment can be set in the computer device. The computer device calls the fireproof board performance testing system stored in the memory 1005 through the processor 1001 and executes the fireproof board performance testing method provided in the above embodiment.

[0058] Example 4 Based on the same inventive concept as the foregoing embodiments, this embodiment provides a computer-readable storage medium storing a computer program, and a processor executes the computer program to implement the above-described method.

[0059] In some embodiments, the computer-readable storage medium may be a memory such as FRAM, ROM, PROM, EPROM, EEPROM, flash memory, magnetic surface memory, optical disk, or CD-ROM; or it may be a variety of devices including one or any combination of the above-mentioned memories.

[0060] The above are merely preferred embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.

Claims

1. A method for testing the performance of fireproof boards, characterized in that, Includes the following steps: A multi-dimensional coupled detection scenario for the target fireproof board is constructed based on a simulation model. The multi-dimensional coupled detection scenario includes a variable temperature fire-mechanical-corrosion coupled scenario, a variable humidity-corrosion-insulation coupled scenario, an airflow interference-variable temperature-insulation coupled scenario, and an aging-corrosion-fire resistance coupled scenario. The thermal insulation performance index, fire resistance performance index, mechanical performance index, and corrosion resistance performance index of the target fireproof board were obtained under different multi-dimensional coupled testing scenarios. The thermal insulation performance index, fire resistance performance index, mechanical performance index and corrosion resistance performance index under the same multidimensional coupling test scenario are respectively input into the preset coupling performance test model to obtain the coupling performance index of the target fireproof board under the corresponding multidimensional coupling test scenario. The coupling performance indices are input into a preset comprehensive performance evaluation model to obtain the comprehensive performance index of the target fireproof board.

2. The method for testing the performance of fireproof boards as described in claim 1, characterized in that, The expression for the coupling performance testing model is: ； In the formula, I represents the coupling performance index of the target fireproof board in the corresponding multidimensional coupling detection scenario. T I represents the thermal insulation performance index corresponding to a certain multidimensional coupled testing scenario. t I represents the fire resistance performance index corresponding to a certain multidimensional coupled detection scenario. M I represents the mechanical performance index corresponding to a certain multidimensional coupled detection scenario. ω Let w1 be the corrosion resistance index corresponding to a certain multidimensional coupled detection scenario, w2 be the first weighting coefficient, w3 be the second weighting coefficient, and w4 be the fourth weighting coefficient.

3. A method for testing the performance of fireproof boards as described in claim 1 or 2, characterized in that, The expression for the comprehensive performance evaluation model is: ； In the formula, I total Let n be the comprehensive performance index of the target fireproof board, n be the number of multi-dimensional coupled detection scenarios, and k be the comprehensive performance index of the target fireproof board. i Let I be the weight coefficient corresponding to the i-th multidimensional coupled detection scenario. i Let ε be the coupling performance index corresponding to the i-th multidimensional coupling detection scenario, and ε be the correction coefficient.

4. The method for testing the performance of fireproof boards as described in claim 3, characterized in that, The correction coefficient ε is obtained as follows: Obtain the actual density ρ and actual thickness h of the target fireproof board to obtain the material deviation factor Δη of the target fireproof board. m ; Obtain the actual installation angle θ of the target fireproof board to obtain the installation angle deviation factor Δη. θ ; According to the material deviation factor Δη m and installation angle deviation factor Δη θ To obtain the correction coefficient ε, the expression for ε is: ε=w5·δ m +w6·D θ ; In the formula, w5 is the fifth weighting coefficient and w6 is the sixth weighting coefficient.

5. The method for testing the performance of fireproof boards as described in claim 4, characterized in that, Material deviation factor Δη m The expression is: ； In the formula, ρ0 is the reference density of the industry standard fireproof board, and h0 is the sample thickness of the standard fireproof board.

6. The method for testing the performance of fireproof boards as described in claim 4, characterized in that, Installation angle deviation factor Δη θ The expression is: See you later. θ =sinθ-sinθ0; In the formula, θ0 is the vertical installation reference angle of the fireproof board, i.e., θ0 = 90°.

7. A method for testing the performance of fireproof boards as described in claim 1 or 2, characterized in that, The thermal insulation performance index, fire resistance performance index, mechanical performance index, and corrosion resistance performance index of the target fireproof board were obtained under different multi-dimensional coupled testing scenarios, including: Obtain the average temperature difference ΔT between the two sides of the target fireproof board under the corresponding multidimensional coupled detection scenario to obtain the thermal insulation performance index I. T Among them, I T =ΔT / ΔT0×100, where ΔT0 is the baseline value of the temperature difference between the two sides of the target fireproof board under standard conditions; Obtain the fire resistance limit time t of the target fireproof board under the corresponding multidimensional coupled detection scenario to obtain the fire resistance performance index I. t Among them, I t =t / t0×100, where t0 is the reference value of the fire resistance limit time of the target fireproof board under standard environment; Obtain the compressive strength σ and flexural strength τ of the target fireproof board under the corresponding multidimensional coupled detection scenario to obtain the mechanical performance index I. M Among them, I M =(σ+τ) / (σ0+τ0)×100, where σ0 is the benchmark value of the compressive strength of the target fireproof board under standard conditions, and τ0 is the benchmark value of the flexural strength of the target fireproof board under standard conditions. Obtain the mass loss rate ω of the target fireproof board under the corresponding multidimensional coupled detection scenario to obtain the corrosion resistance index I. ω Among them, I ω =[1-(ω-ω0) / (1-ω0)]×100, where ω0 is the benchmark value of the mass loss rate of the target fireproof board under standard conditions.

8. A fireproof board performance testing system, characterized in that, include: The coupling scenario construction module is used to construct multi-dimensional coupling detection scenarios for the target fireproof board based on the simulation model. Among them, the multi-dimensional coupling detection scenarios include temperature change fire-mechanics-corrosion coupling scenario, humidity change-corrosion-insulation coupling scenario, airflow interference-temperature change-insulation coupling scenario, and aging-corrosion-fire resistance coupling scenario. The performance index acquisition module is used to acquire the thermal insulation performance index, fire resistance performance index, mechanical performance index and corrosion resistance performance index of the target fireproof board under different multi-dimensional coupled testing scenarios. The coupling detection module is used to input the thermal insulation performance index, fire resistance performance index, mechanical performance index and corrosion resistance performance index under the same multidimensional coupling detection scenario into the preset coupling performance detection model to obtain the coupling performance index of the target fireproof board under the corresponding multidimensional coupling detection scenario. The comprehensive performance evaluation module is used to input the various coupled performance indices into a preset comprehensive performance evaluation model to obtain the comprehensive performance index of the target fireproof board.

9. A computer device, characterized in that, The computer device includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement a method for testing the performance of a fireproof board as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, and the processor executes the computer program to implement a method for testing the performance of a fireproof board as described in any one of claims 1-7.

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