An online composite thermal analysis method, system and storage medium

Abstract

The application relates to the technical field of composite material analysis, and discloses an online thermal analysis method and system for composite materials and a storage medium, which comprises multi-physical field coupling modeling, a thermal response coupling model containing solid-gas phase interaction is constructed, a correlation relationship between parameters and temperature and decomposition reaction progress is established, spatial discretization is carried out by using the Galerkin method, a thermal response differential equation set is solved by using an implicit or explicit time stepping algorithm, temperature field distribution, mass loss and carbon layer formation data are obtained, the carbon layer formation standard is that the mass fraction of a matrix is reduced by 20%, the carbon layer thickness is calculated by mass loss, a mechanical property parameter model is established, and the residual strength after a fire is calculated, and a temperature-time curve, residual strength distribution and parameter sensitivity analysis report can be visually displayed on an online platform. The application realizes full-process analysis from thermal response simulation to residual strength evaluation, improves prediction accuracy, and reduces the application threshold.

Description

Technical Field

[0001] This invention relates to the field of composite material analysis technology, specifically to an online composite material thermodynamic analysis method, system, and storage medium. Background Technology

[0002] The analysis of the thermal response and mechanical property evolution of composite materials under fire conditions is a crucial aspect of ensuring the safety of engineering structures. However, existing technologies face multiple challenges in practical applications. Composite materials under fire involve the coupled effects of multiple physical processes, including heat conduction, resin degradation, gas generation, and mechanical property deterioration. Traditional single-physics simulation tools struggle to achieve cross-scale, multi-mechanism collaborative analysis, resulting in insufficient accuracy in predicting material damage evolution paths. Furthermore, the dynamic changes in material thermophysical parameters (such as density and thermal conductivity) with temperature and degradation levels mean that traditional models based on constant parameter assumptions cannot accurately reflect material behavior in real fire scenarios, further exacerbating the discrepancy between theoretical predictions and experimental results.

[0003] Existing technologies face significant bottlenecks in engineering applications: general-purpose simulation software requires manual construction of multi-physics coupling logic and lacks dedicated constitutive models for the pyrolysis characteristics of composite materials, leading to complex analysis processes and susceptibility to modeling errors; while simplified empirical formulas can quickly estimate results, they cannot account for the spatial distribution differences in material degradation, making it difficult to accurately predict the thickness of the char layer and residual strength; academic research models mostly remain at the theoretical derivation level, lacking convenient parameter input interfaces and visualization functions, making them difficult for engineers to use directly. These technical contradictions are particularly prominent in fields with stringent fire safety requirements, such as aerospace and building structures, urgently requiring the development of integrated simulation tools to achieve end-to-end analysis from thermal response simulation to residual strength assessment. Summary of the Invention

[0004] The present invention aims to provide an online thermodynamic analysis method, system and storage medium for composite materials, which solves the problems of existing technologies in composite material fire response analysis, such as difficulty in achieving multi-physical process coupling modeling, accurate dynamic parameter processing and high threshold for engineering application.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: an online thermodynamic analysis method for composite materials, comprising the following steps, (1) Multiphysics coupling modeling: Simplify the simulation of the heating scenario of composite materials, select the physicochemical changes of materials under fire environment, and construct a thermal response coupling model including solid-gas phase interaction based on the heat conduction equation, resin degradation kinetic model and gas generation equation. (2) Dynamic parameter update: Adjust thermophysical parameters such as density, thermal conductivity, and specific heat capacity in real time according to the degree of material degradation, and establish the correlation between parameters and temperature and decomposition reaction progress; (3) Numerical solution: The Galerkin method is used for spatial discretization, and the thermal response differential equations are solved by implicit or explicit time stepping algorithms to obtain data on temperature field distribution, mass loss and carbon layer formation. (4) Residual strength assessment: Based on the two-layer theory, a 20% reduction in the matrix mass fraction is used as the standard for char layer formation. The char layer thickness is calculated through mass loss. A mechanical performance parameter model is established to calculate the residual strength after the fire. (5) Results output: The temperature-time curve, residual intensity distribution and parameter sensitivity analysis report are visualized through the online platform.

[0006] In addition, this solution also provides an online composite material thermodynamic analysis system, applied to the aforementioned online composite material thermodynamic analysis method, including: The parameter input module is used to receive basic property parameters, thermophysical parameters, boundary condition parameters, and finite element calculation parameters of composite materials through the online platform; The multiphysics coupling modeling module is used to construct a thermal response coupling model that includes solid-gas phase interaction based on the heat conduction equation, resin degradation kinetics model and gas generation equation. The dynamic parameter update module is used to adjust the thermophysical parameters in real time according to the degree of material degradation and to establish the correlation between the parameters and temperature and the progress of decomposition reaction. The numerical solution module is used to spatially discretize the data using the Galerkin method and solve the thermal response differential equations using a time-stepping algorithm to obtain data on temperature field distribution, mass loss, and carbon layer formation. The residual strength assessment module is used to calculate the tensile, compressive and flexural strength after a fire based on the two-layer theory and thermal analysis results. The results output module is used to visualize temperature-time curves, residual intensity distribution, and parameter sensitivity analysis reports through an online platform.

[0007] A computer-readable storage medium for storing computer instructions, which, when executed by a processor, perform the steps in the above method.

[0008] The principles and advantages of this scheme are: To address the complex physicochemical changes that occur in composite materials exposed to fire, this scheme establishes a computable thermal response model through simplified assumptions and theoretical analysis. Specifically, the multi-stage physicochemical processes during the fire are simplified, clarifying the temperature range and characteristic phenomena of each stage while neglecting complex processes. Based on the conservation of control volume energy, a set of thermal equilibrium differential equations incorporating solid-gas phase interactions is constructed, considering factors such as heat conduction, gas convection, and heat of reaction, providing a theoretical foundation for numerical solutions.

[0009] Secondly, to address the complexity of the thermal response model, this scheme employs the finite element method to solve the numerical solution problem. The one-dimensional laminate model is discretized into linear elements, and weakly formal equations are derived using the Galerkin method to handle different boundary conditions. Both implicit and explicit time-stepping algorithms are implemented to ensure the stability and efficiency of solving the nonlinear equations.

[0010] This solution addresses the strength calculation needs following material performance degradation caused by fire, and solves the quantitative assessment problem of residual strength based on the two-layer theory. Specifically, it uses a matrix mass fraction reduction of ~20% as the standard for char layer formation, calculates the char layer thickness through mass loss, and establishes calculation equations for tensile modulus, compressive modulus, flexural modulus, neutral axis position, and various strengths to achieve theoretical prediction of residual strength after a fire.

[0011] Furthermore, this scheme addresses the issue of changes in the thermophysical parameters of composite materials with temperature and degradation rate by proposing a practical method for parameter estimation and updating. Based on the decomposition reaction progress, the relationship between density, thermal conductivity, and specific heat capacity and degradation rate is established to achieve dynamic parameter updating.

[0012] This solution systematically addresses the core issues of fire thermal response simulation and residual strength assessment of composite materials through a complete design process encompassing theoretical modeling, parameter estimation, numerical solution, and program implementation. It provides a comprehensive solution for fire safety analysis of composite material structures, from mechanism to tools. Attached Figure Description

[0013] Figure 1 This is a schematic flowchart of an online thermodynamic analysis method for composite materials according to the present invention; Figure 2 This is a schematic diagram of the thermal model structure of the composite material laminate in this invention; Figure 3 This is a schematic diagram of the finite element discretization of the solution domain in this invention; Figure 4 This is a schematic diagram of the structure of an online composite material thermodynamic analysis system according to the present invention; Figure 5 This is a schematic diagram showing the output of the calculation results of temperature change over time along the thickness of a plate in an online composite material thermal analysis system of the present invention.

[0014] Figure 6 This is a schematic diagram showing the output of the calculation results of the law of temperature change of the unexposed surface over time in an online composite material thermal analysis system of the present invention. Detailed Implementation

[0015] The following detailed description illustrates the specific implementation method: This embodiment presents an online composite material thermodynamic analysis method, system, and storage medium. Utilizing multiphysics coupling and based on the conservation of volumetric energy, it derives a set of differential equations for thermal equilibrium involving solid-gas phase interactions. It also adjusts the correlation between thermophysical parameters and degradation levels in real time, solves the thermal response equation using the Galerkin method for spatial discretization and a time-stepping algorithm, calculates the post-fire intensity, and finally outputs the calculation results. This achieves a complete analysis process from thermal response simulation to residual strength assessment, improving prediction accuracy and lowering the application threshold.

[0016] Option 1 Provides an online thermodynamic analysis method for composite materials, as shown in the attached figure. Figure 1 As shown, it includes the following steps: (1) Multi-physics coupling modeling: Simplify the simulation of the heating scenario of composite materials, select the physical and chemical changes of materials under fire conditions, and construct a thermal response coupling model containing solid-gas phase interaction based on the heat conduction equation, resin degradation kinetic model and gas generation equation.

[0017] When composite materials are exposed to a fire environment, numerous complex physicochemical changes occur. As the temperature rises, the physicochemical processes within the composite laminate gradually change. Under fire conditions, composite materials involve multi-physics coupling effects such as heat conduction, resin degradation, and gas generation. Traditional single-physics simulation tools struggle to achieve cross-scale, multi-mechanism collaborative analysis. Furthermore, the thermophysical parameters of the material dynamically change with temperature and the degree of degradation. Fully considering the dynamic characteristics of all parameters would significantly increase model complexity and computational cost.

[0018] Therefore, in this embodiment, by ignoring complex processes such as matrix cracking, fiber-matrix interface degumming, and carbon layer oxidation, and focusing on core thermal response mechanisms such as heat conduction and resin pyrolysis, the model can be simplified while ensuring accuracy. By simplifying assumptions, the difficulty of numerical solutions can be reduced, making the model easier to implement in engineering applications using the finite element method.

[0019] In this embodiment, the following simplified assumptions are made: The decomposition gases do not accumulate in the solid phase, thermal expansion is not considered, thermal equilibrium is maintained between the decomposition gases and the solid phase, no intermediate compounds are produced when the resin material sublimates, the thermal and transport properties of the laminate are constant during the material decomposition process (temperature variation can be considered), there is no control volume for solid material entering the space, the solid material will be converted into the gas phase, resulting in mass loss, a first-order Arrhenius equation is used, and a zero value is applied to the final density of the resin material.

[0020] Based on the simplified physicochemical phenomena of composite combustion described above, a set of differential equations for the thermal response is established. (See attached) Figure 2As shown, in this embodiment, by assuming a uniform heat flow (or a specified temperature) applied to the plane of the composite laminate surface, the model is strictly one-dimensional, and heat is transferred only in the thickness direction of the laminate. An infinitely flat composite laminate with a finite thickness L is selected as the simulation object.

[0021] In this embodiment, the resin degradation kinetic model is described by the Arrhenius equation, and the gas generation equation takes into account the internal pressurization and convective heat transfer effects.

[0022] The composite material mainly consists of two phases during combustion: a solid phase, containing the matrix, reinforcing fibers, and residues from the decomposition reaction; and a gaseous phase, containing decomposition products, air, and water vapor. Consider a control volume, specifically the interval from x to x+Δx along the thickness direction of the composite panel. The energy balance within this volume can be expressed as: (1) In the formula, Internal energy density per unit volume (J / m³) -3 ); Heat flux (W / m³) -2 ); Gas mass flux (kg s) 1 m 2 ); Enthalpy of gas (J kg) -1 ); Heat generation rate per unit volume (W / m³) -3 ).

[0023] Since material structural deformation and ablation surface peeling are not considered, and Δx→0, it is assumed that the internal energy density and enthalpy of the mixture composed of fibers, matrix, and the decomposing matrix are related. Proportional, that is Furthermore, assuming no gas accumulation within the controlled volume, the gas generation rate can be expressed as the negative value of the rate of change of the material's solid phase density. Right now Meanwhile, assuming the gas enthalpy value... or Enthalpy of solids or .

[0024] After rearranging the equations, the coupled thermal response model can be expressed as follows: (2) (3) (4) In the formula, The absolute temperature is (K). Thermal conductivity (W / m) -1 K -1 ); The mass density of the solid phase (kg m³) -3 ); The specific heat of the original composite material (J kg) -1 K -1 ); The current mass density of the matrix (kg m³) -3 ); This is the enthalpy value of a solid. The ambient temperature (K) is the ambient temperature.

[0025] This embodiment also includes setting boundary conditions to define the heat exchange mode and physical constraints of the composite laminate under fire conditions, in order to achieve numerical simulation of thermal response. The boundary conditions include fire-exposed surface boundary conditions, unexposed surface boundary conditions, and gas mass flux boundary conditions.

[0026] Specifically, in this embodiment, initial conditions are first set based on the actual physical state. The initial conditions are as follows: ; ; In the formula, The initial temperature is (K).

[0027] The boundary conditions of the fire-exposed surface include the first type of temperature boundary, the second type of heat flow boundary, and the third type of convective heat transfer boundary.

[0028] The first type of temperature boundary is the thermal boundary condition for the fire-receiving surface, which can be expressed as: (5) In the formula, The surface heat transfer coefficient of the fire-receiving surface (W / m²) -2 K -1 ); Flame temperature (K); The surface temperature of the composite material exposed to fire is to be determined (in K).

[0029] The second type of heat flux boundary is based on the hydrocarbon flame temperature profile, where a time-dependent temperature is applied to the heat boundary. The standard curve has the following form: (6) In the formula, The ambient temperature (K) of the unexposed side; The rate of increase in furnace temperature can be expressed as: ;(7)

[0030] The third type of convective heat transfer boundary is a defined thermal boundary condition for the fire-receiving surface, which can be expressed as: (8) In the formula, For a specified heat flux (W / m³) -2 ).

[0031] By specifying surface temperature, heat flux density, or heat transfer coefficient using three types of boundary conditions, the heat input of a fire heat source to the material is simulated.

[0032] The back-fire boundary condition is defined by setting the ambient temperature and heat transfer coefficient to reflect the heat dissipation process of the material to the surrounding environment.

[0033] In this embodiment, the thermal boundary conditions of the unexposed surface are set, which can be expressed as follows: (9) In the formula, The surface heat transfer coefficient of the unexposed side (W / m²) -2 K -1 ); The surface temperature of the unexposed composite material is to be determined (in K).

[0034] Setting the thermal boundary conditions on the unexposed side can be expressed as follows: ;(10)

[0035] The gas mass flux boundary condition constrains the migration path of gaseous substances. That is, assuming that the decomposition gases do not escape through the backfire surface, the gas mass flux in the system can be eliminated, thus yielding the residual expression, expressed as: (11) In the formula, For variables The unknown function, mass density and related.

[0036] (2) Dynamic parameter update: Adjust thermophysical parameters such as density, thermal conductivity, and specific heat capacity in real time according to the degree of material degradation, and establish the correlation between parameters and temperature and decomposition reaction progress.

[0037] The dynamic parameter update uses a hybrid law to calculate the original material parameters. In this embodiment, if experimental data on the original composite material parameters is lacking, the material parameters of the original composite material can be estimated using the material parameters of the matrix and reinforcing fibers. The degradation degree is then correlated with the mass fraction F, where the thermal conductivity of the carbon layer considers the coupling effect of solid thermal conductivity and radiation.

[0038] In this embodiment, the composition of the matrix is ​​represented by the mixing equation for F, where F is the fraction of the matrix mass density in the solid phase, which can be written as: (12) In the formula, The mass density (kg m³) of the matrix after the decomposition reaction (carbon layer) is completed. -3 In this embodiment, assuming a density of 0, the mass density of the matrix can be expressed as: ;(13)

[0039] From this, the relationship between the parameter and each thermophysical parameter can be derived, which is expressed as: density (14) thermal conductivity (15) Specific heat capacity can be calculated in two ways. ;or (16) In the formula, Thermal conductivity of air (W / m) -1 K -1 ); Thermal conductivity (W / m) of the matrix after the decomposition reaction (carbon layer) -1 K -1 ); The Stefan-Boltzmann constant is 5.67e-8 (W m). -2 K -4 L is the thickness of the composite laminate (m); Specific heat capacity of air (J kg) -1 K -1 ).

[0040] This embodiment also includes an implicit update of the quality score F to avoid compromising the stability of the format. The update algorithm can then be expressed as follows: ;(17)

[0041] (3) Numerical solution: The Galerkin method is used for spatial discretization. The thermal response differential equations are solved by implicit or explicit time stepping algorithms to obtain data on temperature field distribution, mass loss and carbon layer formation.

[0042] In this embodiment, the numerical solution uses the Newton-Nicolson iteration method to handle the nonlinear equation system, and the time-stepping algorithm supports switching between the Crank-Nicolson implicit and explicit schemes.

[0043] As attached Figure 3As shown, assume the solution domain is of length. The one-dimensional model divides the length direction into uniform sections. There are one-dimensional linear units, each with a length of [missing information]. Each unit has 2 nodes, namely and Located on both sides of the element, the solution domain has a total of 1 node The number of grid nodes can be selected based on specific circumstances during actual calculations. Generally, when the number of grid nodes exceeds 10, the calculation results tend to be grid-independent.

[0044] In this embodiment, spatial discretization primarily calculates the various physical quantity data required for the current time step, including material density, thermal conductivity, specific heat capacity, current heat conduction, and gas decomposition data. Some physical quantities are represented by a one-dimensional or two-dimensional matrix, and some matrices require matrix inversion and multiplication. In this embodiment, the finite element method is used to numerically solve the equations to be solved. The spatial discretization equations vary slightly depending on the application of boundary conditions.

[0045] 1) When the fire-exposed surface adopts the first type of boundary, the unfired surface also adopts the first type of boundary.

[0046] The Galerkin method is used to discretize the space. The weighted residual method is then used to obtain the weak form of the governing equations. (18) In this embodiment, spatial discretization employs classic piecewise linear basis functions, set on the fire-receiving surface. There are nodes On the side away from the fire There are nodes By introducing both natural boundary conditions and initial conditions, we can obtain the degree trial function, expressed as follows: (19) The finite element equation can then be expressed as: (20) In the formula, It is a temperature vector; This is a compatibility matrix; This is the heat conduction matrix; The decomposition matrix; This is the gas convection matrix; For surface heat exchange matrix; Let be the thermal load vector. From this, we obtain the expressions for each component in equation (20), and solve them sequentially according to the current boundary solution method. , and In this embodiment, the boundary condition solution includes processing the boundary conditions using the surface temperature of the current time step and processing the boundary conditions using the surface temperature of the previous time step.

[0047] At the same time, solve according to equation (20) respectively , , , ,in, and These represent the node number and time step, respectively, to obtain data on temperature field distribution, mass loss, and carbon layer formation.

[0048] 2) When the fire-exposed side adopts the second type of boundary, the unexposed side adopts the first type of boundary.

[0049] The finite element method discretization method (weighted residual method, shape function, etc.) used is exactly the same as in case 1), but the boundary condition handling is different.

[0050] The exposed surface adopts a second type of boundary, setting the solid surface temperature of the composite material. That is, a solid surface temperature boundary value is introduced in each time step of the iterative calculation; the unexposed surface adopts a first type of boundary, setting the heat transfer coefficient. The first-order nonlinear differential equation system, i.e., the finite element equation, is shown in equation (20), which is solved sequentially according to the current boundary solution method. , , , , , and .

[0051] After obtaining all the data for the current step, these data are used as known quantities in the time discrete equation. The time discrete equation is then solved to obtain the temperature of the current step, thus completing the calculation of one time step.

[0052] In this embodiment, time discretization refers to the actual solution method for the time-discrete equation. Time discretization includes implicit and explicit algorithms, and the user can choose between either explicit or implicit computation based on their selection criteria.

[0053] In this embodiment, the implicit algorithm can use the weighted residual approximation method to solve the finite element equations, and the time discretization is performed by the following formula. ; ;(twenty one) Using time step parameters Using the Crank-Nicolson solution with a value of 0.5 to implicitly solve the matrix equations and calculate the nodal temperature after each iteration, it can be expressed as: ;(twenty two) Then, the Newton-Raphson iterative algorithm is used to solve the nonlinear algebraic equation system.

[0054] In the process of solving time steps, the explicit algorithm can use an explicit algorithm for iterative calculation, such as rewriting equation (22) in the implicit algorithm as an explicit expression of the node temperature to obtain data on temperature field distribution, mass loss and carbon layer formation.

[0055] (4) Residual strength assessment: Based on the two-layer theory, the carbon layer formation standard is a reduction of ~20% in the matrix mass fraction. The carbon layer thickness is calculated by mass loss. A mechanical performance parameter model is established to calculate the residual strength after the fire.

[0056] In this embodiment, the two-layer theory is used to calculate the residual strength of the composite material after a fire. When the mass fraction of the polymer matrix decreases by ~20% due to decomposition and evaporation, visible char begins to form in the thermosetting laminate. Using this as a standard for char formation, the degree of char growth in the laminate can be calculated based on the mass loss, the char layer thickness can be obtained, and then the residual strength can be calculated according to the two-layer theory.

[0057] The mechanical performance parameter model includes tensile modulus, compressive modulus, flexural modulus, neutral axis position, and various strengths. The tensile, compressive, and flexural strengths after a fire are calculated based on the thermal analysis results.

[0058] Specifically, the tensile modulus can be expressed as ;(twenty three) The compressive modulus can be expressed as ;(twenty four) Flexural modulus can be expressed as (25) The position of the neutral axis can be expressed as (26) Tensile strength can be expressed as (27) The tensile failure load can be expressed as (28) Compressive strength can be expressed as (29) Buckling load can be expressed as (30) The bending failure load can be expressed as ;(31)

[0059] (5) Results output: The temperature-time curve, residual intensity distribution and parameter sensitivity analysis report are visualized through the online platform.

[0060] The online platform supports parameter saving, loading, and result export. The visualization module includes temperature field cloud map, residual intensity curve, and comparison function with experimental data.

[0061] Compared with existing technologies, this solution first achieves a breakthrough in the multi-physics coupling mechanism. Existing technologies mostly rely on single-physics simulation tools, which make it difficult to coordinate the analysis of the coupling effects of multiple physical processes such as heat conduction, resin degradation, and gas generation in composite material fire environments. However, this solution constructs a multi-physics coupling model of "heat conduction-resin degradation-gas generation", clarifies the solid-gas phase interaction, and achieves cross-scale, multi-mechanism collaborative analysis.

[0062] Furthermore, in terms of dynamic parameter processing, traditional models, based on the assumption of constant parameters, cannot reflect the dynamic changes of thermophysical parameters such as density and thermal conductivity with temperature and degradation degree. This scheme, on the other hand, associates the material degradation degree with mass fraction F and updates material parameters in real time by combining the mixing law, establishing a dynamic correlation between parameters and temperature and reaction progress, which significantly improves the model's ability to depict real fire scenarios.

[0063] Furthermore, in terms of engineering applications, existing technologies often rely on professional simulation tools, which are complex to operate and have high application thresholds. This solution integrates the entire process of parameter input, modeling, solving, and evaluation through an online platform, supporting parameter saving / loading, result visualization, and experimental data comparison, effectively reducing the threshold for engineering applications.

[0064] In this embodiment, the Arrhenius kinetic equation is used to describe resin degradation, and a 20% reduction in matrix mass fraction is used as the criterion for char layer formation. Combined with the bilayer theory to calculate residual strength, the predicted thermal response and mechanical properties more closely resemble actual fire scenarios, thus improving prediction accuracy. The Galerkin method is used for spatial discretization, and the Crank-Nicolson implicit / explicit time-stepping algorithm and Newton iteration are used to handle the nonlinear equations, balancing computational stability and efficiency.

[0065] Option 2 In this embodiment, an online composite material thermodynamic analysis system is also provided, applied to the above-mentioned online composite material thermodynamic analysis method, as shown in the attached figure. Figure 4 As shown, it includes: The parameter input module is used to receive basic property parameters, thermophysical parameters, boundary condition parameters, and finite element calculation parameters of composite materials through the online platform.

[0066] In this embodiment, the material properties can be input as parameters as shown in Table 1 below.

[0067] Table 1

[0068] The finite element solution parameters are shown in Table 2 below. Table 2

[0069] The calculated boundary conditions and initial conditions are shown in Table 3 below. Table 3

[0070] The mechanical properties of the materials are shown in Table 4 below. Table 4

[0071] The multiphysics coupling modeling module is used to construct a thermal response coupling model that includes solid-gas phase interaction based on the heat conduction equation, resin degradation kinetics model and gas generation equation.

[0072] The dynamic parameter update module is used to adjust thermophysical parameters in real time according to the degree of material degradation and to establish the correlation between parameters and temperature and decomposition reaction progress.

[0073] The numerical solution module is used to spatially discretize the thermal response using the Galerkin method and solve the thermal response differential equations using a time-stepping algorithm to obtain data on temperature field distribution, mass loss, and carbon layer formation.

[0074] The residual strength assessment module is used to calculate the tensile, compressive, and flexural strength after a fire based on the two-layer theory combined with thermal analysis results.

[0075] The results output module is used to visualize temperature-time curves, residual intensity distribution, and parameter sensitivity analysis reports through an online platform.

[0076] In this embodiment, PyQt5 is used for interface construction and layout. QSS technology is used to decorate and beautify controls, and PyQt's event mechanism is used to trigger function execution logic. The interface includes three interfaces: thermal response parameter input, intensity calculation input parameter, and calculation result display, each corresponding to a separate tab. Each interface is encapsulated and coded in a separate class. Finally, the three pages are integrated into the Tab control of the MainWindow window to achieve interface switching.

[0077] As attached Figure 5 The image shows the temperature variation over time along the plate thickness, with the top surface being the exposed side and the bottom surface being the unexposed side. (See attached image.) Figure 6As shown, the temperature of the unexposed surface changes over time. In the figure, the thick dark blue line represents the calculated value, and the other nine thin lines represent the experimental value.

[0078] In this embodiment, the online platform can output multi-dimensional results such as temperature-time curves, mass fraction distribution, and residual strength values. It supports data export and experimental comparison, intuitively presents the fire response law of materials, and realizes full-process visual analysis. The modular architecture includes a parameter input module (receiving parameters such as material properties and boundary conditions), a multi-physics coupling modeling module (constructing a thermal response coupling model), a dynamic parameter update module (adjusting thermophysical parameters in real time), a numerical solution module (spatial / temporal discretization algorithm), a residual strength evaluation module (two-layer theoretical calculation), and a result output module (visual display).

[0079] The innovative approach employs the first-order Arrhenius equation to describe degradation kinetics, estimates the density and thermal properties of composite materials through the mixing law, and considers the coupling effect of solid thermal conductivity and radiation on the thermal conductivity of the carbon layer. It integrates support for parameter settings that vary with temperature, switching between four numerical solution methods, and multi-dimensional evaluation of residual strength, forming a complete and efficient thermodynamic analysis solution for composite materials.

[0080] In this embodiment, a computer-readable storage medium is also provided for storing computer instructions, which, when executed by a processor, complete the steps in the above method.

[0081] The above descriptions are merely embodiments of the present invention, and common knowledge such as specific technical solutions and / or characteristics are not described in detail here. It should be noted that those skilled in the art can make various modifications and improvements without departing from the technical solutions of the present invention, and these should also be considered within the scope of protection of the present invention. These modifications and improvements will not affect the effectiveness of the implementation of the present invention or the practicality of the patent. The scope of protection claimed in this application should be determined by the content of its claims, and the specific embodiments described in the specification can be used to interpret the content of the claims.

Claims

1. An online thermodynamic analysis method for composite materials, characterized in that, Includes the following steps, (1) Multiphysics coupling modeling: Simplify the simulation of the heating scenario of composite materials, select the physicochemical changes of materials under fire environment, and construct a thermal response coupling model including solid-gas phase interaction based on the heat conduction equation, resin degradation kinetic model and gas generation equation. (2) Dynamic parameter update: Adjust thermophysical parameters such as density, thermal conductivity, and specific heat capacity in real time according to the degree of material degradation, and establish the correlation between parameters and temperature and decomposition reaction progress; (3) Numerical solution: The Galerkin method is used for spatial discretization, and the thermal response differential equations are solved by implicit or explicit time stepping algorithms to obtain data on temperature field distribution, mass loss and carbon layer formation. (4) Residual strength assessment: Based on the two-layer theory, a reduction of ~20% in the matrix mass fraction is used as the standard for char layer formation. The char layer thickness is calculated through mass loss. A mechanical performance parameter model is established to calculate the residual strength after the fire. (5) Results output: The temperature-time curve, residual intensity distribution and parameter sensitivity analysis report are visualized through the online platform.

2. The online composite material thermodynamic analysis method according to claim 1, characterized in that: The resin degradation kinetic model in step (1) is described by the Arrhenius equation, and the gas generation equation considers internal pressurization and convective heat transfer effects; the thermal response coupling model is expressed as follows: ； ； ； In the formula, For gas mass flux; It is the enthalpy of a gas; Absolute temperature; Thermal conductivity; The mass density of the solid phase; The specific heat of the original composite material; The current mass density of the matrix; This is the enthalpy value for solids.

3. The online composite material thermodynamic analysis method according to claim 1, characterized in that: In step (1), the method of heat exchange and physical constraints of composite laminate under fire environment is defined by setting boundary conditions; the boundary conditions include fire-exposed surface boundary conditions, unexposed surface boundary conditions and gas mass flux boundary conditions.

4. The online composite material thermodynamic analysis method according to claim 3, characterized in that: The boundary conditions of the exposed surface include a first type of temperature boundary, a second type of heat flux boundary, and a third type of convective heat transfer boundary; the boundary conditions of the unexposed surface are determined by setting the ambient temperature and heat transfer coefficient to reflect the heat dissipation process of the material to the surrounding environment; the gas mass flux boundary conditions constrain the migration path of gaseous substances.

5. The online composite material thermodynamic analysis method according to claim 1, characterized in that: In step (2), the dynamic parameter update uses the mixing law to calculate the original material parameters and associates the degradation degree with the mass fraction F. The thermal conductivity of the carbon layer takes into account the coupling effect of solid thermal conductivity and radiation.

6. The online composite material thermodynamic analysis method according to claim 1, characterized in that: The numerical solution in step (3) uses the Newton-Nicolson iteration method to process the nonlinear equation system, and the time stepping algorithm supports switching between the Crank-Nicolson implicit format and the explicit format.

7. The online composite material thermodynamic analysis method according to claim 1, characterized in that: In step (4), the mechanical performance parameter model includes tensile modulus, compressive modulus, flexural modulus, neutral axis position and various strengths, and the tensile, compressive and flexural strengths after the fire are calculated in combination with the thermal analysis results.

8. The online composite material thermodynamic analysis method according to claim 1, characterized in that: The online platform in step (5) supports parameter saving, loading and result export. The visualization module includes temperature field cloud map, residual intensity curve and comparison with experimental data.

9. An online composite material thermodynamic analysis system, characterized in that, The online composite material thermodynamic analysis method applied to any one of claims 1-8 includes: The parameter input module is used to receive basic property parameters, thermophysical parameters, boundary condition parameters, and finite element calculation parameters of composite materials through the online platform; The multiphysics coupling modeling module is used to construct a thermal response coupling model that includes solid-gas phase interaction based on the heat conduction equation, resin degradation kinetics model and gas generation equation. The dynamic parameter update module is used to adjust the thermophysical parameters in real time according to the degree of material degradation and to establish the correlation between the parameters and temperature and the progress of decomposition reaction. The numerical solution module is used to spatially discretize the data using the Galerkin method and solve the thermal response differential equations using a time-stepping algorithm to obtain data on temperature field distribution, mass loss, and carbon layer formation. The residual strength assessment module is used to calculate the tensile, compressive and flexural strength after a fire based on the two-layer theory and thermal analysis results. The results output module is used to visualize temperature-time curves, residual intensity distribution, and parameter sensitivity analysis reports through an online platform.

10. A computer-readable storage medium, characterized in that: Used to store computer instructions, which, when executed by a processor, perform the steps of the method according to any one of claims 1-8.

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