Optimization Method and System for Thermal Protection Scheme of Thermal Insulation and Heat Protection Integrated Structure

Abstract

The present invention provides an optimization method and system for a thermal protection scheme of an integrated heat insulation and heat protection structure, including: setting optimization input parameters according to the use environment, characteristics of alternative materials, and structural space structure, and randomly generating an initial population containing a certain number of individuals; establishing a calculation model based on the finite volume method according to the characteristics of the individuals; for each individual in the population, carrying out strength calculation and heat conduction calculation; for each individual in the population, calculating the objective function and penalty function according to the strength calculation result, temperature calculation result, and characteristics of the previous generation population to obtain the fitness of each individual; evaluating the fitness of all individuals in the current generation population, if the exit requirement is met, the optimization is completed, otherwise, a new generation population is generated according to the adaptive parameters, and then the optimization is carried out again. The present invention can carry out optimal design of the thermal protection scheme for an integrated heat insulation and heat protection material composed of a functionally graded material with continuously varying material properties in space.

Description

Technical Field

[0001] The present invention relates to the fields of thermal protection scheme design and structural weight reduction optimization. Specifically, it relates to an optimization method and system for the thermal protection scheme of an integrated thermal insulation and heat protection structure, and particularly to a multi-constraint adaptive optimization method for the thermal protection scheme of an integrated thermal insulation and heat protection structure. Background Art

[0002] With the increasing flight speed and distance of aircraft, the aerodynamic heating environment they face is becoming increasingly severe. In order to ensure that the temperature of the cabin structure and in-cabin equipment is within the range that meets the usage requirements during flight, it is necessary to design a thermal protection scheme for the aircraft. Considering that lightweight design has a significant effect on improving the performance of the aircraft, how to reasonably select the thickness of the thermal protection material and the load-bearing metal material to minimize the structural weight of the thermal protection scheme while meeting multiple constraints such as structural temperature, strength, and space has become one of the important issues in the development of hypersonic aircraft.

[0003] Research shows that the strength limit of most metal materials decreases with the increase in temperature. Increasing the thickness of the thermal protection material will increase the load-bearing capacity by reducing the temperature of the metal material. Metal materials have a large heat sink. Increasing the thickness of the metal material can reduce the cross-sectional stress and temperature simultaneously. The additional weight introduced by increasing the thickness of the thermal protection material is relatively small, while the additional weight introduced by increasing the thickness of the metal material is relatively large. On the other hand, reducing the temperature by increasing the thickness of the thermal protection material will occupy more space. It can be seen that this optimization problem is affected by multiple factors and it is difficult to find the optimal solution through simple analysis and calculation.

[0004] In engineering practice, forward design based on engineering experience is still relatively common. That is, engineers directly determine the thickness of the structural metal and the thickness of the heat protection material according to past design experience, and then carry out stress calculation and heat conduction calculation respectively, and judge and optimize whether they meet the load-bearing requirements according to the calculation results. The above method has certain limitations. On the one hand, the design process depends on the design experience of engineers, and it is difficult to quantify and standardize the structural load-bearing margin. On the other hand, due to the many influencing factors, it is difficult to directly judge which layer of material has a better weight reduction effect, and it can only be achieved through a large number of trials and errors, which limits the efficiency and effect of structural weight reduction optimization. Therefore, in order to facilitate engineers to carry out the design and optimization of the structural thermal protection scheme of hypersonic aircraft, it is necessary to provide a new rapid optimization method for the thermal protection scheme of an axisymmetric integrated thermal insulation and heat protection structure. Summary of the Invention

[0005] Aiming at the defects in the prior art, the purpose of the present invention is to provide an optimization method and system for the thermal protection scheme of an integrated thermal insulation and heat protection structure.

[0006] An optimization method for a thermal protection solution for an integrated heat insulation and heat protection structure provided by the present invention includes:

[0007] Step S1: Set optimization input parameters according to the use environment, characteristics of alternative materials, and structural space structure, and randomly generate an initial population containing a certain number of individuals;

[0008] Step S2: Establish a calculation model based on the finite volume method according to the characteristics of the individuals;

[0009] Step S3: For each individual in the population, carry out strength calculation and heat conduction calculation;

[0010] Step S4: For each individual in the population, calculate the objective function and penalty function according to the strength calculation result, temperature calculation result, and characteristics of the previous generation population, and obtain the fitness of each individual;

[0011] Step S5: Evaluate the fitness of all individuals in the current generation population. If the exit requirement is met, the optimization is completed, and the heat protection solution given by the individual with the minimum fitness in the currently evolved population is used as the optimization result. Otherwise, enter Step S6;

[0012] Step S6: Retain, cross, and mutate the individuals according to the adaptive parameters to generate a new generation population, and then repeat Steps S2 - S5.

[0013] Preferably, Step S1 includes:

[0014] For an integrated heat insulation and heat protection structure composed of n layers of materials, given the core parameters of the genetic algorithm, the maximum number of evolutions gen max , the population size pop, the maximum allowable temperature T limit of the characteristics of the alternative materials, and the maximum structural thickness H limit allowed for optimization;

[0015] Randomly generate an initial population containing pop individuals. Each individual g includes a set of material thicknesses, that is:

[0016] g = [h 1 , h 2 ,..., h n .

[0017] Preferably, Step S2 includes:

[0018] For each individual g, based on its thickness h i (i = 1, 2,..., n) of each layer, discretize it into a series of units based on the finite volume method, and assign material parameters to each unit. The material parameters include the thermal conductivity k, specific heat capacity c, and density ρ;

[0019] For metallic materials, heat protection materials, and heat insulation materials, since their material parameters do not vary with space, the same material parameter values are assigned to all elements of the material;

[0020] For a two-phase functionally graded material composed of heat protection materials and heat insulation materials, considering the case where its composition varies linearly with space, the material parameters of each element are assigned according to the following method:

[0021]

[0022] C grad = (1 - V β )C α + V β C β

[0023] ρ grad = (1 - V β )ρ α + V β ρ β

[0024] where the subscript grad represents the functionally graded material, and the subscripts α and β represent the two phases that make up the functionally graded material. For this method, α represents the heat protection material and β represents the heat insulation material, and V β is the volume fraction of the heat insulation material;

[0025] The initial conditions set for the calculation model are the global initial temperature. The boundary conditions of the calculation model include thermal loads and force loads. The thermal loads are input in the form of the second kind of boundary condition or the third kind of boundary condition, and the force loads include the maximum bending moment M borne by the structure and the outer diameter D of the structure.

[0026] Preferably, the step S3 includes:

[0027] For each individual evolving currently, calculate the maximum stress of the cross-section:

[0028]

[0029] where I is the moment of inertia, which is calculated by the following formula:

[0030]

[0031] where d is the inner diameter of the structure;

[0032] Judge whether it meets the strength requirement at normal temperature; judge according to the yield strength S N of the metal at normal temperature:

[0033] σ max ≤ S N

[0034] If the above equation does not hold, the individual does not meet the strength constraint condition, assign a large value to the fitness fit and jump to step S4;

[0035] If the above equation holds, the structure of the individual meets the requirements at room temperature, and continue to carry out the temperature response calculation; use the finite volume method calculation model established in step S2 to perform one-dimensional transient heat conduction calculation to obtain the temperature T of each unit at each calculation time; screen within the spatial region of the temperature constraint, and take out the maximum temperature T within the full time range max ;

[0036] Use T max Perform linear interpolation in the metal strength limit curve to obtain the high-temperature strength limit S under the highest temperature condition H , if the maximum temperature exceeds the temperature range of the strength limit, make the high-temperature strength limit S H = 1, so that it can continue to calculate and be quickly eliminated during evolution.

[0037] Preferably, the step S4 includes:

[0038] Calculate the objective function for each individual in the current evolution, and take the linear density ρ l as the objective function, and its expression is:

[0039] ρ l = ρ α A α +∫ρ grad (R)c grad (R)dR+ρ β A β +ρ m A m

[0040] where A is the cross-sectional area, and the subscripts α, grad, β, and m represent the heat protection material, two-phase gradient material, heat insulation material, and metal material respectively; R is the structural radius, and the above equation is further arranged as:

[0041]

[0042] where R 0 , R 1 , R 2 , R 3 , R 4 are the outer radius of the heat protection layer, the inner radius of the heat protection layer, the inner radius of the gradient layer, the inner radius of the heat insulation layer, and the inner radius of the metal layer respectively;

[0043] For all individuals in the current evolution, calculate the adaptive penalty factor δ according to the current evolution generation and the maximum evolution generation:

[0044] δ(gen)=10 λy(gen)

[0045] where λ is the introduced constant parameter, and the expression of y(gen) is as follows:

[0046]

[0047] For each individual in the current evolution, according to the calculation results in step S3 and the thicknesses of each layer of materials included in the individual, calculate the satisfaction of strength constraints, temperature constraints, and space constraints, and obtain its penalty function P, whose expression is:

[0048]

[0049] where p i (g) is the constraint function, and b is the total number of constraint conditions;

[0050] The strength constraint is expressed by the remaining strength coefficient, and the expression of its constraint function is:

[0051]

[0052] The temperature constraint is in a dimensionless expression, and the expression of its constraint function is:

[0053]

[0054] The space constraint is in a dimensionless expression, and the expression of its constraint function is:

[0055]

[0056] For each individual in the current evolution, calculate the fitness value through the following formula:

[0057] fit(gen,g) = ρ l (g) + δ(gen)P(g).

[0058] Preferably, the step S5 includes:

[0059] For the entire population in the current evolution, calculate the average fitness according to the following formula

[0060]

[0061] For the entire population in the current evolution, compare the minimum fitness and the average fitness, and the current evolution generation and the maximum evolution generation:

[0062]

[0063] gen ≥ gen max

[0064] where Δαthres The threshold for ending the optimization.

[0065] If one of the above two equations holds, the optimization is completed, and a set of material thicknesses [h 1 , h 2 , K, h n included in the individual with the minimum fitness is the minimum-weight thermal protection solution obtained by this optimization method, and the optimization is terminated.

[0066] If neither of the above two equations holds, the optimization is not completed, and jump to step S6.

[0067] Preferably, the step S6 includes:

[0068] For the entire population evolving currently, calculate the crossover probability and mutation probability of the adaptive genetic algorithm;

[0069] The crossover probability p c is calculated by the following formula:

[0070]

[0071] where p max , p min are the upper and lower limits of the crossover probability respectively, r max , r min are the maximum limiting probability and minimum limiting probability of the adaptive crossover probability respectively, Δα is the difference between the minimum fitness and the average fitness at the current generation of evolution, and it is calculated by the following formula:

[0072]

[0073] Δα 0 is the difference between the minimum fitness value and the average fitness value of the initial population.

[0074] The mutation probability p m is calculated by the following formula:

[0075] p m = 1 - p e - p c

[0076] where p e is the retention ratio; for the entire population evolving currently, multiply the above probabilities by the population size to obtain the number of individuals for retention, crossover, and mutation;

[0077] The crossover individuals are determined as follows: Each time, randomly select two individuals from the population for crossover to obtain a new individual until the number of crossover individuals is reached;

[0078] The mutant individuals are determined as follows: Each time, a single individual is randomly selected from the population and randomly mutated until the number of mutant individuals is reached;

[0079] The retained individuals, newly generated crossover individuals, and mutant individuals form a new generation of population, and steps S2 - S5 are repeated.

[0080] An optimization system for the thermal protection scheme of an integrated heat insulation and heat protection structure according to the present invention includes:

[0081] Module M1: Set the optimization input parameters according to the use environment, characteristics of alternative materials, and structural space structure, and randomly generate an initial population containing a certain number of individuals;

[0082] Module M2: Establish a computational model based on the finite volume method according to the characteristics of the individuals;

[0083] Module M3: For each individual in the population, carry out strength calculation and heat conduction calculation;

[0084] Module M4: For each individual in the population, calculate the objective function and penalty function based on the strength calculation result, temperature calculation result, and characteristics of the previous generation of population, and obtain the fitness of each individual;

[0085] Module M5: Evaluate the fitness of all individuals in the current generation of population. If the exit requirement is met, the optimization is completed, and the heat protection scheme given by the individual with the minimum fitness in the currently evolved population is used as the optimization result; otherwise, enter Module M6;

[0086] Module M6: Retain, crossover, and mutate the individuals according to the adaptive parameters to generate a new generation of population, and then repeat Modules M2 - S5.

[0087] Preferably, the Module M1 includes:

[0088] For an integrated heat insulation and heat protection structure composed of n layers of materials, the core parameters of the genetic algorithm, the maximum number of evolutions gen max , the population size pop, the maximum allowable temperature T limit of the characteristics of alternative materials, and the maximum structural thickness H limit allowed for optimization are given;

[0089] Randomly generate an initial population containing pop individuals. Each individual g includes a set of material thicknesses, that is:

[0090] g = [h 1 , h 2 ,..., h n .

[0091] Preferably, the Module M2 includes:

[0092] For each individual g, according to its thickness h of each layer i (i = 1, 2, ..., n), it is discretized into a series of cells based on the finite volume method, and material parameters are assigned to each cell. The material parameters include thermal conductivity k, specific heat capacity c, and density ρ;

[0093] For metallic materials, thermal protection materials, and thermal insulation materials, their material parameters do not vary with space, and the same material parameter values are assigned to all cells of this material;

[0094] For a two-phase functionally graded material composed of thermal protection materials and thermal insulation materials, considering the case where its composition varies linearly with space, the material parameters of each cell are assigned according to the following method:

[0095]

[0096] C grad =(1 - V β )C α +V β C β

[0097] ρ grad =(1 - V β )ρ α +V β ρ β

[0098] where the subscript grad represents the functionally graded material, and the subscripts α and β represent the two phases that make up the functionally graded material. For this method, α represents the thermal protection material, and β represents the thermal insulation material. V β is the volume fraction of the thermal insulation material;

[0099] The set initial conditions of the calculation model are the global initial temperature. The boundary conditions of the calculation model include thermal loads and force loads. The thermal loads are input in the form of the second kind of boundary condition or the third kind of boundary condition. The force loads include the maximum bending moment M borne by the structure and the outer diameter D of the structure.

[0100] Preferably, the module M3 includes:

[0101] For each individual in the current evolution, calculate the maximum stress of the cross-section:

[0102]

[0103] where I is the moment of inertia, which is calculated by the following formula:

[0104]

[0105] where d is the inner diameter of the structure;

[0106] Judge whether it meets the normal temperature strength requirement; according to the strength limit S of the metal at normal temperature N Make a judgment as follows:

[0107] σ max ≤S N

[0108] If the above formula does not hold, the individual does not meet the strength constraint condition, assign a large value to the fitness fit and jump to module M4;

[0109] If the above formula holds, the structure of the individual meets the requirements at normal temperature, and continue to carry out the temperature response calculation; use the finite volume method calculation model established in step S2 to perform one-dimensional transient heat conduction calculation to obtain the temperature T of each unit at each calculation time; screen within the spatial region of the temperature constraint and take out the maximum temperature T during the whole time within the range max ;

[0110] Use T max Perform linear interpolation in the metal strength limit curve to obtain the high-temperature strength limit S under the highest temperature condition H , if the maximum temperature exceeds the temperature range of the strength limit, set the high-temperature strength limit S H = 1, so that it can continue to calculate and be quickly eliminated during evolution.

[0111] Preferably, the module M4 includes:

[0112] Calculate the objective function for each individual in the current evolution, take the linear density ρ l as the objective function, and its expression is:

[0113] ρ l = ρ α A α +∫ρ grad (R)c grad (R)dR+ρ β A β +ρ m A m

[0114] where A is the cross-sectional area, and the subscripts α, grad, β, and m respectively represent the thermal protection material, the two-phase gradient material, the heat insulation material, and the metal material; R is the structure radius, and the above formula is further sorted out as:

[0115]

[0116] where R 0 、R 1 、R 2 、R 3 、R 4They are the outer radius of the heat insulation layer, the inner radius of the heat insulation layer, the inner radius of the gradient layer, the inner radius of the heat insulation layer, and the inner radius of the metal layer respectively;

[0117] For all individuals evolving currently, according to the current generation number of evolution and the maximum generation number of evolution, calculate the adaptive penalty factor δ:

[0118] δ(gen) = 10 λy(gen)

[0119] Where λ is the introduced constant parameter, and the expression of y(gen) is as follows:

[0120]

[0121] For each individual evolving currently, according to the calculation result of module M3 and the thicknesses of each layer of materials included in the individual, calculate the satisfaction of strength constraint, temperature constraint, and space constraint, and obtain its penalty function P, and its expression is:

[0122]

[0123] Where p i (g) is the constraint function, and b is the total number of constraint conditions;

[0124] The strength constraint is expressed by the remaining strength coefficient, and its constraint function expression is:

[0125]

[0126] The temperature constraint is in a dimensionless expression, and its constraint function expression is:

[0127]

[0128] The space constraint is in a dimensionless expression, and its constraint function expression is:

[0129]

[0130] For each individual evolving currently, calculate the fitness value through the following formula:

[0131] fit(gen,g) = ρ l (g) + δ(gen)P(g).

[0132] Preferably, the module M5 includes:

[0133] For the entire population evolving currently, calculate the average fitness according to the following formula

[0134]

[0135] For the entire population in the current evolution, compare the minimum fitness and the average fitness, as well as the current generation number of evolution and the maximum generation number of evolution:

[0136]

[0137] gen≥gen max

[0138] where Δα thres is the threshold for ending the optimization.

[0139] If one of the above two equations holds, the optimization has been completed, and a set of material thicknesses [h 1 ,h 2 ,K,h n included in the individual corresponding to the minimum fitness is the minimum-weight thermal protection scheme obtained by this optimization method, and the optimization is terminated.

[0140] If neither of the above two equations holds, the optimization has not been completed, and jump to step S6.

[0141] Preferably, the module M6 includes:

[0142] For the entire population in the current evolution, calculate the crossover probability and mutation probability of the adaptive genetic algorithm;

[0143] The crossover probability p c is calculated by the following formula:

[0144]

[0145] where p max , p min are the upper and lower limits of the crossover probability respectively, r max , r min are the maximum limiting probability and minimum limiting probability of the adaptive crossover probability respectively, and Δα is the difference between the minimum fitness and the average fitness at the current generation of evolution, which is calculated by the following formula:

[0146]

[0147] Δα 0 is the difference between the minimum fitness value and the average fitness value of the initial population.

[0148] The mutation probability p m is calculated by the following formula:

[0149] p m =1 - p e - p c

[0150] where p eis the retention ratio; for the entire population evolving currently, multiply the above probabilities by the population size to obtain the number of individuals for retention, crossover, and mutation;

[0151] The crossover individuals are determined as follows: Each time, randomly select two individuals from the population for crossover to obtain a new individual until the number of crossover individuals is reached;

[0152] The mutation individuals are determined as follows: Each time, randomly select an individual from the population and randomly mutate it until the number of mutation individuals is reached;

[0153] The retained individuals, newly generated crossover individuals, and mutation individuals form a new generation of population, and repeat modules M2 - M5.

[0154] Compared with the prior art, the present invention has the following beneficial effects:

[0155] 1. The present invention expands the range of materials that can be optimized compared with the prior art, and can carry out the optimization design of the thermal protection scheme for the thermal insulation integrated material composed of the functionally graded material with continuously varying material properties in space.

[0156] 2. The present invention expands the scenarios that can be optimized compared with the prior art, and can carry out the optimization design of the thermal protection scheme under the usage conditions with constraints on strength, temperature, and space simultaneously.

[0157] 3. The present invention improves the optimization algorithm specifically by introducing new constraint transformation methods and adaptive methods compared with the prior art, and improves the optimization efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0158] By reading the detailed description of the non - restrictive embodiments with reference to the following drawings, other features, purposes, and advantages of the present invention will become more obvious:

[0159] Figure 1 is a flowchart of an adaptive optimization method for the thermal protection scheme of the thermal insulation integrated structure;

[0160] Figure 2 is a schematic diagram of the calculation model in the embodiment of the present invention;

[0161] Figure 3 is the input heat flux curve diagram in the embodiment of the present invention;

[0162] Figure 4 is a schematic diagram of the change of the minimum fitness of the population with the increase of the number of evolution generations in the embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0163] The present invention will be described in detail below in conjunction with specific embodiments. The following embodiments will help those skilled in the art to further understand the present invention, but do not limit the present invention in any form. It should be noted that those of ordinary skill in the art can make several changes and improvements without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0164] Example 1

[0165] A multi-constraint adaptive optimization method for a thermal protection scheme of an integrated heat insulation and heat protection structure according to the present invention includes: as Figure 1 shown,

[0166] Step S1: According to the use environment, characteristics of alternative materials, and structural space structure, given the maximum number of evolutions gen max , population size pop, maximum allowable temperature T limit , maximum structural thickness H limit and other optimization input parameters, and randomly generate a population containing pop individuals, each individual being a structural form composed of n layers of different materials, which is determined by a set of material thickness parameters [h 1 , h 2 ,..., h n , where h i (i = 1, 2,..., n) is the thickness value of each layer of material from the outer surface to the inner surface.

[0167] Step S2: According to the thickness of each layer of material [h 1 , h 2 ,..., h n of the individual, divide the integrated heat insulation and heat protection structure into calculation units, assign material parameters to each unit according to the unit division, set the initial conditions and boundary conditions of the calculation model, and establish a calculation model based on the finite volume method.

[0168] Step S3: For each individual in the current evolution, perform the maximum stress calculation σ max , and judge whether it meets the normal temperature strength requirement. If it does not meet, assign the fitness fit to a maximum value and jump to Step S4. If it meets, according to the calculation model established in S2, perform the temperature response calculation and obtain the highest temperature T max , and calculate the high temperature strength S H .

[0169] Step S4: For each individual in the current evolution, calculate its objective function linear density ρ l according to the thickness of each layer of material, calculate the adaptive penalty function factor δ according to the current evolution generation gen and the maximum evolution generation gen max , and according to the maximum structural thickness Hlimit Constraint, maximum allowable temperature T limit and high-temperature strength constraint S H Satisfaction, calculate its penalty function P, according to ρ l , δ, P to calculate the fitness value fit of this individual.

[0170] Step S5: Evaluate the fitness value characteristics of the current evolutionary population. If the difference between the average fitness and the minimum fitness of the population is less than the threshold, or the current generation gen reaches the maximum number of evolutions gen max , it is considered that the optimization has been completed, and a set of thicknesses [h 1 , h 2 , K, h n included in the individual with the minimum fitness in the population is used as the optimization result, otherwise continue.

[0171] Step S6: Calculate the crossover probability p c and the mutation probability p m values, select individuals from the current population for retention, crossover and mutation, generate a new generation of population, and repeat Step S2 - Step S5.

[0172] Specifically, the said Step S1 includes:

[0173] For the thermal insulation and heat protection integrated structure composed of n layers of materials, given the core parameters of the genetic algorithm, the maximum number of evolutions gen max , population size pop, maximum allowable temperature T limit of the alternative material properties, the maximum structural thickness H limit allowed for optimization.

[0174] Randomly generate an initial population containing pop individuals, and each individual g contains a set of material thicknesses, that is:

[0175] g = [h 1 , h 2 ,..., h n

[0176] Specifically, the said Step S2 includes:

[0177] For each individual g, according to the thickness h of each layer i ​(i = 1, 2, ..., n), it is discretized into a series of cells based on the finite volume method, and material parameters are assigned to each cell. The material parameters include the thermal conductivity k, specific heat capacity c, and density ρ. For metallic materials, thermal protection materials, and thermal insulation materials, their material parameters do not vary with space, and the same material parameter values are assigned to all cells of this material. For the two-phase functionally graded material composed of thermal protection materials and thermal insulation materials, considering the case where its composition varies linearly with space, the material parameters of each cell are assigned according to the following method:

[0178]

[0179] C grad = (1 - V β )C α + V β C β

[0180] ρ grad = (1 - V β )ρ α + V β ρ β

[0181] where the subscript grad represents the functionally graded material, and the subscripts α and β represent the two phases that make up the functionally graded material. For this method, α represents the thermal protection material, and β represents the thermal insulation material. V β is the volume fraction of the thermal insulation material. Under the condition of linear variation, it can be expressed as the ratio of the position of the current cell to the total thickness of the gradient layer.

[0182] The initial condition of the set calculation model is the global initial temperature. The boundary conditions of the calculation model include thermal loads and force loads. The thermal loads can be divided into the second kind of boundary condition and the third kind of boundary condition. The force loads include the maximum bending moment M borne by the structure and the outer diameter D of the structure.

[0183] Specifically, the step S3 includes:

[0184] For each individual in the current evolution, calculate the maximum stress of the cross-section according to the following formula of material mechanics:

[0185]

[0186] where I is the moment of inertia. For the circular ring cross-section involved in this method, it can be calculated by the following formula:

[0187]

[0188] where d is the inner diameter of the structure.

[0189] Judge whether it meets the normal temperature strength requirement. This method assumes that the thermal protection material, thermal insulation material, and functionally gradient material do not have load-bearing capacity, and all stresses are borne by the metal material. Therefore, according to the strength limit S of the metal at normal temperature N Make a judgment:

[0190] σ max ≤S N

[0191] If the above formula does not hold, that is, for this individual, the structure cannot meet the load-bearing requirement at normal temperature. Since the strength limit of most metal materials decreases with the increase of temperature, it is obvious that it cannot meet the load-bearing requirement at high temperature, that is, the individual does not meet the strength constraint condition. Therefore, assign the fitness fit to a maximum value and jump to step S4.

[0192] If the above formula holds, that is, for this individual, the structure can meet the requirement at normal temperature. Continue to carry out the temperature response calculation. Use the finite volume method calculation model established in step S2 to perform one-dimensional transient heat conduction calculation to obtain the temperature T of each unit at each calculation time. Screen within the spatial region of the temperature constraint and take out the maximum temperature T during the whole time within the range max .

[0193] Calculate and strictly examine the structure, assuming that the moment when the structure bears the maximum load is the same as the moment when the structure appears the maximum temperature. The strength limit of the metal is a function of temperature. Therefore, use T max Perform linear interpolation in the metal strength limit curve to obtain the high-temperature strength limit S under the condition of the highest temperature H . If the maximum temperature exceeds the temperature range of the strength limit, the metal material can no longer bear the load in essence. For the convenience of calculation, let the high-temperature strength limit S H = 1 so that the calculation can continue and it will be quickly eliminated during evolution.

[0194] Specifically, step S4 includes:

[0195] For each individual in the current evolution, calculate the objective function. The optimization objective of the thermal protection scheme is to minimize the weight as much as possible while meeting the constraint conditions. Therefore, take the linear density ρ l as the objective function. The linear density in this method refers to the mass per unit length along the axis direction. Its expression is:

[0196] ρ l = ρ α A α +∫ρ grad (R)c grad (R)dR+ρ β A β +ρ m A m

[0197] Where A is the cross-sectional area, and the subscripts α, grad, β, and m represent the thermal protection material, two-phase gradient material, thermal insulation material, and metal material respectively. R is the structural radius. In particular, for the circular cross-sectional structure mainly targeted by the method, and assuming there are no significant gaps between the layers of materials, the above formula can be further arranged as:

[0198]

[0199] Where R 0 、R 1 、R 2 、R 3 、R 4 are the outer radius of the thermal protection layer, the inner radius of the thermal protection layer, the inner radius of the gradient layer, the inner radius of the thermal insulation layer, and the inner radius of the metal layer respectively. Using the above formula to replace the ordinary average density as the objective function, considering the influence of the structural diameter on the actual material volume, the optimization accuracy is improved, especially for the optimization effect of small-diameter structures.

[0200] For all individuals in the current evolution, according to the current generation number of evolution and the maximum generation number of evolution, calculate the adaptive penalty factor δ:

[0201] δ(gen) = 10 λy(gen)

[0202] Where λ is the introduced constant parameter, and the expression of y(gen) is as follows:

[0203]

[0204] This adaptive penalty factor makes the weight of the penalty function show a process of changing from high to low and then high during the evolution process, enabling the optimization method to quickly exclude infeasible solutions at the initial stage of evolution, avoiding the elimination of individuals near the infeasible region of the optimal solution generated by crossover or mutation during the middle stage of evolution, and reducing the probability of the optimal solution falling into the infeasible side at the later stage of evolution, which helps to improve the efficiency of the optimization method.

[0205] For each individual in the current evolution, according to the calculation result of step S3 and the thickness of each layer of material included in the individual, calculate the satisfaction of strength constraint, temperature constraint, and space constraint, and obtain its penalty function P. This optimization method uses the exterior point penalty function method, and its expression is:

[0206]

[0207] Where p i (g) is the constraint function, and b is the total number of constraint conditions. The constraint functions of strength constraint, temperature constraint, and space constraint are given below respectively.

[0208] The strength constraint is expressed by the remaining strength coefficient, and its constraint function expression is:

[0209]

[0210] The temperature constraint is expressed by a dimensionless expression, and its constraint function expression is:

[0211]

[0212] The space constraint is expressed by a dimensionless expression, and its constraint function expression is:

[0213]

[0214] The constraint functions all use dimensionless expressions, so that the magnitudes of the strength, temperature, and space constraints are kept consistent, avoiding the situation where one of the constraints is too large and causes the other constraints to be ignored, or one of the constraints is too small and causes itself to be masked by other constraints and unable to be correctly constrained.

[0215] For each individual in the current evolution, the fitness value is obtained through the following formula:

[0216] fit(gen,g) = ρ l (g) + δ(gen)P(g)

[0217] Specifically, the step S5 includes:

[0218] For the entire population in the current evolution, the average fitness is calculated according to the following formula

[0219]

[0220] For the entire population in the current evolution, compare the minimum fitness and the average fitness, and the current evolution generation and the maximum evolution generation:

[0221]

[0222] gen ≥ gen max

[0223] where Δα thres is the threshold for ending the optimization.

[0224] If one of the above two formulas holds, the optimization has been completed, and a set of material thicknesses [h 1 ,h 2 ,K,h n included in the individual corresponding to the minimum fitness is the minimum-weight thermal protection solution obtained by this optimization method, and the optimization is terminated.

[0225] If neither of the above two equations holds, the optimization is not yet complete, and jump to step S6.

[0226] Specifically, step S6 includes:

[0227] For the entire population evolving currently, calculate the crossover probability and mutation probability of the adaptive genetic algorithm.

[0228] Crossover probability p c Calculate using the following formula:

[0229]

[0230] Where p max , p min are the upper and lower limits of the crossover probability respectively, r max , r min are the maximum defined probability and minimum defined probability of the adaptive crossover probability respectively, Δα is the difference between the minimum fitness and the average fitness at the current generation of evolution, and it is calculated using the following formula:

[0231]

[0232] Δα 0 is the difference between the minimum fitness value and the average fitness value of the initial population.

[0233] Mutation probability p m Calculate using the following formula:

[0234] p m = 1 - p e - p c

[0235] Where p e is the retention ratio, which means that the individuals in the current population are sorted in ascending order of fitness, and the individuals within this ratio range do not participate in crossover and mutation during evolution.

[0236] For the entire population evolving currently, multiply the above probabilities by the population size to obtain the number of individuals for retention, crossover, and mutation. Determine the crossover individuals in the following way: Randomly select two individuals from the population for crossover each time to obtain a new individual until the number of crossover individuals is reached. Determine the mutation individuals in the following way: Randomly select an individual from the population and randomly mutate it until the number of mutation individuals is reached.

[0237] The retained individuals, newly generated crossover individuals, and mutation individuals form a new generation of population, and repeat steps S2 - S5.

[0238] Example 2

[0239] Embodiment 2 is a variant of Embodiment 1.

[0240] Taking the design optimization problem of a thermal protection solution for an axisymmetric thermal insulation integrated structure composed of heat-resistant materials, gradient materials, thermal insulation materials, and metal materials as an example. The thermal physical properties of the materials involved in the example are shown in Table 1:

[0241] Table 1

[0242]

[0243] The designed material strength properties are shown in Table 2:

[0244] Table 2

[0245]

[0246] Step 1: Given the core parameters of the genetic algorithm, the maximum number of evolutions gen max = 140, the population size pop = 120, the maximum allowable temperature T of the thermal insulation material limit = 900K, the maximum allowable thickness H for optimization limit = 5mm. Randomly generate an initial population containing 120 individuals, and each individual in the population contains a set of material thicknesses:

[0247] g = [h 1 , h 2 , h 3 , h 4

[0248] Step 2: For each individual g in the current population, divide the heat-resistant and thermal insulation materials into units every 0.05mm, divide the metal materials into 10 units in total, and assign thermal physical properties to each unit. Divide the gradient material into units every 0.05mm, and assign values to each unit according to the given formula. For a material divided into 20 units, the thermal physical properties of each unit are shown in Table 3:

[0249] Table 3

[0250]

[0251]

[0252] The geometric schematic diagram of the finite volume method calculation model is as Figure 2 shown.

[0253] Set the boundary conditions of the calculation model. The thermal load is given as a time-varying heat flux (the second type of boundary condition), and its heat flux curve varying with time is as Figure 3 shown. The force load is a bending moment M = 4600 N·m, and the outer diameter D of the aircraft is 100mm.

[0254] ​Set the initial conditions of the calculation model, with the initial global temperature being 298K.

[0255] Step 3: For each individual in the current evolution, calculate the maximum stress of the cross-section according to the formula:

[0256]

[0257] where the moment of inertia I is calculated according to the formula for the cross-section of a circular ring:

[0258]

[0259] where d is the inner diameter of the structure. For each individual, it can be calculated from a set of thicknesses g = [h 1 , h 2 , h 3 , h 4 included in the individual:

[0260] d = D - 2×(h 1 + h 2 + h 3 + h 4 ) = 0.1 - 2×(h 1 + h 2 + h 3 + h 4 )

[0261] For each individual, judge whether it meets the strength requirement at normal temperature. According to the temperature-strength limit relationship given in Table 2, the normal temperature strength S of this metal material can be obtained N = 1400MPa. For each individual in the population, make a judgment:

[0262] σ max ≤ 1400

[0263] For individuals for which this formula does not hold, that is, the structure cannot meet the load-bearing requirement at normal temperature, assign a large value of fitness fit = 10 6 to this individual and jump to step S5.

[0264] For individuals for which this formula holds, continue to carry out the temperature response calculation. Perform one-dimensional transient heat conduction calculation according to the finite volume method calculation model established in step S2 to obtain the temperature T of each unit of the thermal insulation layer at each moment, and screen out the maximum value T max .

[0265] According to the temperature-strength limit relationship given in Table 2, use T max for interpolation to obtain the corresponding high-temperature strength limit S H (T max ). If T max > 1673K, the material has failed. Let SH = 1 MPa.

[0266] Step 4: For each individual in the current evolution, calculate the objective function, penalty factor, and penalty function in sequence to obtain the fitness. The objective function is the linear density, which can be calculated according to the formula:

[0267]

[0268] where R 1 , R 2 , R 3 , R 4 varies from individual to individual and is calculated from the thickness g = [h 1 , h 2 , h 3 , h 4 contained in each individual according to the following formula:

[0269] R 1 = 0.05 - h 1

[0270] R 2 = R 1 - h 2

[0271] R 3 = R 2 - h 3

[0272] R 4 = R 3 - h 4

[0273] For all individuals in the current evolution, take the constant parameter λ = 4 and obtain the adaptive penalty factor δ(gen) according to the current generation number gen and the maximum generation number gen max through the formula.

[0274] For each individual in the current evolution, calculate the strength constraint, temperature constraint, and space constraint in sequence and obtain the penalty function P(g):

[0275]

[0276]

[0277]

[0278] P(g) = min(0, p 1 (g)) 2 + min(0, p 2 (g)) 2 + min(0, p 3(g)) 2

[0279] According to the line density, penalty factor, and penalty function, the fitness value can be obtained as follows:

[0280] fit(gen,g) = ρ l (g) + δ(gen)P(g)

[0281] Step 5: Calculate the average fitness for the entire population evolving currently

[0282]

[0283] Take the ending optimization threshold Δα thres = 10 -4 , compare the minimum fitness of the currently evolving population with the average fitness, and compare the current generation number with the maximum generation number. If one of the following formulas is satisfied, it is considered that the optimization has been completed; otherwise, continue with Step 6:

[0284]

[0285] gen ≥ 140

[0286] For this example, the process of the minimum fitness decreasing with evolution is as Figure 4 shown. After optimization, the thicknesses of the heat-insulating material, gradient material, heat-resistant material, and metal material in the heat protection solution are 0 mm, 3.44 mm, 0 mm, and 1.51 mm respectively. Its remaining strength coefficient is 1.0036, and the total thickness is 4.95 mm, both of which meet the constraint conditions. Since there is no heat-insulating layer, the temperature constraint condition is automatically satisfied.

[0287] Step 6: For this example, set the upper and lower limits of the crossover probability p max , p min to 80% and 20% respectively, and set the corresponding percentages r max , r min of the upper and lower limits of the crossover probability to 100% and 30% respectively. For the first-generation population, calculate Δα 0 :

[0288]

[0289] For the first-generation population, the crossover probability is the upper limit of the crossover probability p max = 80%. For the remaining generations of the population, the crossover function p c is as follows:

[0290]

[0291] For this example, take the elite individual ratio pe = 5%, to obtain the mutation probability p m :

[0292] p m = 0.95 - p c

[0293] For the first-generation population, based on the total number of population individuals 120, the elite individual ratio, the crossover probability, and the mutation probability, the numbers of reserved, crossed, and mutated individuals are obtained as 6, 96, and 18 respectively. For the remaining generations of the population, the numbers are determined according to the above formula. After determination, new-generation individuals are generated in sequence to form the next-generation population.

[0294] A matrix is formed by the contact heat transfer coefficients corresponding to the newly generated reserved individuals, crossed individuals, and mutated individuals, that is, a new-generation population is formed, and steps S2 - S5 are repeated.

[0295] The present invention also discloses an optimization system for the thermal protection scheme of the heat insulation and heat protection integrated structure, including:

[0296] Module M1: Set the optimization input parameters according to the use environment, alternative material characteristics, and structural spatial structure, and randomly generate an initial population containing a certain number of individuals;

[0297] Module M2: Establish a calculation model based on the finite volume method according to the characteristics of the individuals;

[0298] Module M3: For each individual in the population, carry out strength calculation and heat conduction calculation;

[0299] Module M4: For each individual in the population, calculate the objective function and the penalty function according to the strength calculation result, the temperature calculation result, and the characteristics of the previous-generation population, and obtain the fitness of each individual;

[0300] Module M5: Evaluate the fitness of all individuals in the current generation of the population. If the exit requirement is met, the optimization is completed, and the heat protection scheme given by the individual with the minimum fitness in the currently evolved population is used as the optimization result. Otherwise, enter Module M6;

[0301] Module M6: Retain, cross, and mutate the individuals according to the adaptive parameters to generate a new-generation population, and then repeat Modules M2 - S5.

[0302] The said Module M1 includes:

[0303] For the heat insulation and heat protection integrated structure composed of n layers of materials, the core parameters of the genetic algorithm, the maximum number of evolutions gen max , the population size pop, the maximum allowable temperature T of the alternative material characteristics limit , the maximum structural thickness H allowed for optimization limit ;

[0304] Randomly generate an initial population containing pop individuals, and each individual g contains a set of material thicknesses, namely:

[0305] g = [h 1 , h 2 ,..., h n .

[0306] The module M2 includes:

[0307] For each individual g, according to the thickness h of each layer i (i = 1, 2,..., n), discretize it into a series of cells based on the finite volume method, and assign material parameters to each cell. The material parameters include thermal conductivity k, specific heat capacity c, and density ρ;

[0308] For metallic materials, heat protection materials, and thermal insulation materials, their material parameters do not vary with space, and the same material parameter values are assigned to all cells of this material;

[0309] For the two-phase functionally graded material composed of heat protection materials and thermal insulation materials, considering the case where its composition varies linearly with space, assign material parameters to each cell according to the following method:

[0310]

[0311] C grad = (1 - V β )C α + V β C β

[0312] ρ grad = (1 - V β )ρ α + V β ρ β

[0313] where the subscript grad represents the functionally graded material, and the subscripts α and β represent the two phases that make up the functionally graded material. For this method, α represents the heat protection material, β represents the thermal insulation material, and V β is the volume fraction of the thermal insulation material;

[0314] The initial conditions of the set calculation model are the global initial temperature. The boundary conditions of the calculation model include thermal loads and force loads. The thermal loads are input in the form of the second kind of boundary condition or the third kind of boundary condition. The force loads include the maximum bending moment M borne by the structure and the outer diameter D of the structure.

[0315] Those skilled in the art know that in addition to implementing the system and its various devices, modules, and units provided by the present invention in the form of pure computer-readable program code, the method steps can be logically programmed to enable the system and its various devices, modules, and units provided by the present invention to be implemented in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers, etc. to achieve the same functions. Therefore, the system and its various devices, modules, and units provided by the present invention can be considered as a kind of hardware component, and the devices, modules, and units included therein for implementing various functions can also be regarded as the structures within the hardware component; the devices, modules, and units for implementing various functions can also be regarded as either software modules for implementing the method or structures within the hardware component.

[0316] The specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the above specific embodiments, and those skilled in the art can make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. Without conflict, the embodiments of the present application and the features in the embodiments can be combined with each other arbitrarily.

Claims

1. An optimization method for the thermal protection scheme of the integrated heat insulation and heat protection structure, characterized in that, it includes: Step S1: Set the optimization input parameters according to the use environment, alternative material characteristics and structural space structure, and randomly generate an initial population containing a certain number of individuals; Step S2: Establish a calculation model based on the finite volume method according to the characteristics of the individuals; Step S3: For each individual in the population, carry out strength calculation and heat conduction calculation; Step S4: For each individual in the population, calculate the objective function and penalty function according to the strength calculation result, temperature calculation result, and characteristics of the previous generation population, and obtain the fitness of each individual; Step S5: Evaluate the fitness of all individuals in the current generation population. If the exit requirement is met, the optimization is completed, and the heat protection scheme given by the individual with the minimum fitness in the currently evolved population is used as the optimization result. Otherwise, enter Step S6; Step S6: Retain, cross, and mutate the individuals according to the adaptive parameters to generate a new generation population, and then repeat Steps S2 - S5; The said Step S1 includes: For the integrated heat insulation and heat protection structure composed of n layers of materials, given the core parameters of the genetic algorithm, the maximum number of evolutions gen max , the population size pop, and the maximum allowable temperature T limit of the alternative material properties, and the maximum allowable structure thickness H limit ; Randomly generate an initial population containing pop individuals, and each individual g contains a set of material thicknesses, that is: g = [h 1 , h 2 ,..., h n ; The said Step S4 includes: Calculate the objective function for each individual in the current evolution, and take the line density ρ l as the objective function, and its expression is: ρ l = ρ α A α + ∫ ρ grad (R)c grad (R) dR + ρ β A β + ρ m A m Where A is the cross-sectional area, and the subscripts α, grad, β, and m represent the heat protection material, two-phase gradient material, heat insulation material, and metal material respectively; R is the structural radius, and the above formula is further sorted out as: wherein R 0 , R 1 , R 2 , R 3 , R 4 are the outer radius of the heat insulation layer, the inner radius of the heat insulation layer, the inner radius of the gradient layer, the inner radius of the heat insulation layer, and the inner radius of the metal layer, respectively; For all individuals in the current evolution, calculate the adaptive penalty factor δ according to the current evolution generation and the maximum evolution generation: δ(gen)=10 λy(gen) Where λ is the introduced constant parameter, and the expression of y(gen) is as follows: For each individual in the current evolution, according to the calculation result of Step S3 and the thickness of each layer of material contained in the individual, calculate the satisfaction of the strength constraint, temperature constraint, and space constraint, and obtain its penalty function P, and its expression is: where p i (g) is a constraint function, and b is the total number of constraint conditions; The strength constraint is expressed by the remaining strength coefficient, and its constraint function expression is: The temperature constraint is expressed by a dimensionless expression, and its constraint function expression is: The space constraint is expressed by a dimensionless expression, and its constraint function expression is: For each individual in the current evolution, calculate the fitness value through the following formula: fit(gen,g) = ρ l (g) + δ(gen)P(g).

2. The optimization method for the thermal protection scheme of the integrated heat insulation and heat protection structure according to claim 1, characterized in that: The said Step S2 includes: For each individual g, according to its thickness h of each layer i (i = 1, 2,..., n), it is discretized into a series of cells based on the finite volume method, and material parameters are assigned to each cell. The material parameters include thermal conductivity k, specific heat capacity c, and density ρ; For the metal material, heat protection material, and heat insulation material, their material parameters do not change with space, and the same material parameter value is assigned to all units of this material; For the two-phase functional gradient material composed of the heat protection material and the heat insulation material, considering the case where its composition changes linearly with space, the material parameters of each unit are assigned according to the following method: C grad = (1 - V β ) C α + V β C β ρ grad =(1 - V β )ρ α + V β ρ β where the subscript grad represents the functionally graded material, and the subscripts α and β represent the two phases that make up the functionally graded material. For this method, α represents the heat protection material and β represents the thermal insulation material. V β is the volume fraction of the thermal insulation material; The initial condition set for the calculation model is the global initial temperature. The boundary conditions of the calculation model include thermal load and force load. The thermal load is input in the form of the second kind of boundary condition or the third kind of boundary condition, and the force load includes the maximum bending moment M borne by the structure and the outer diameter D of the structure.

3. The optimization method for the thermal protection scheme of the integrated heat insulation and heat protection structure according to claim 1, characterized in that: The said Step S3 includes: For each individual in the current evolution, calculate the maximum stress of the cross-section: Where I is the moment of inertia, which is calculated by the following formula: Where d is the inner diameter of the structure; Judge whether it meets the requirements of normal temperature strength; according to the ultimate strength S of the metal at normal temperature N Make a judgment: σ max ≤ S N If the above formula does not hold, the individual does not meet the strength constraint condition, assign a large value to the fitness fit and jump to step S4; If the above equation holds, the structure of the individual meets the requirements at normal temperature, and the temperature response calculation continues; using the finite volume method calculation model established in step S2, one-dimensional transient heat conduction calculation is performed to obtain the temperature T of each unit at each calculation moment; screening is carried out within the spatial region of the temperature constraint, and the maximum temperature T during the entire time within the range is taken out max ; Adopt T max Perform linear interpolation in the metal strength limit curve to obtain the high-temperature strength limit S under the highest temperature condition H , if the maximum temperature exceeds the temperature range of the strength limit, set the high-temperature strength limit S H = 1 to enable continuous calculation and be quickly eliminated during evolution 4. The optimization method for the thermal protection scheme of the integrated thermal insulation and heat protection structure according to claim 1, Characterized in that: The step S5 includes: For the entire population of the current evolution, calculate the average fitness according to the following formula For the entire population evolving currently, compare the minimum fitness and the average fitness, and the current generation number of evolutions and the maximum generation number of evolutions: gen≥gen max where Δα thres is the threshold for ending the optimization; If one of the above two equations holds, the optimization is completed, and the set of material thicknesses [h 1 , h 2 ,..., h n included in the individual with the minimum fitness is the minimum-weight thermal protection solution obtained by this optimization method, and the optimization is terminated; If neither of the above two formulas holds, the optimization is not completed yet, jump to step S6.

5. The optimization method for the thermal protection scheme of the integrated thermal insulation and heat protection structure according to claim 1, Characterized in that: The step S6 includes: For the entire population evolving currently, calculate the crossover probability and mutation probability of the adaptive genetic algorithm; Crossing probability p c It is calculated by the following formula: Among them, p max and p min are the upper and lower limits of the crossover probability respectively, r max and r min are the maximum and minimum limiting probabilities of the adaptive crossover probability respectively. Δα is the difference between the minimum fitness and the average fitness at the current evolutionary generation, which is calculated by the following formula: Δα 0 is the difference between the minimum fitness value and the average fitness value of the initial population; Mutation probability p m It is calculated by the following formula: p m = 1 - p e -p c where p e is the retention ratio; for the entire population evolving currently, multiply the above probabilities by the population size to obtain the number of individuals for retention, crossover, and mutation; The crossover individuals are determined as follows: Randomly select two individuals from the population for crossover each time to obtain a new individual until the number of crossover individuals is reached; The mutated individuals are determined as follows: Randomly select one individual from the population and randomly mutate it until the number of mutated individuals is reached; Retain the individuals, the newly generated crossover individuals and the mutated individuals to form a new generation of population, and repeat steps S2 - S5.

6. An optimization system for the thermal protection scheme of the integrated thermal insulation and heat protection structure, Characterized in that, Including: Module M1: Set the optimization input parameters according to the use environment, characteristics of alternative materials and the spatial structure of the structure, and randomly generate an initial population containing a certain number of individuals; Module M2: Establish a calculation model based on the finite volume method according to the characteristics of the individuals; Module M3: For each individual in the population, carry out strength calculation and heat conduction calculation; Module M4: For each individual in the population, calculate the objective function and the penalty function according to the strength calculation result, temperature calculation result and characteristics of the previous generation population to obtain the fitness of each individual; Module M5: Evaluate the fitness of all individuals in the current generation population. If the exit requirement is met, the optimization is completed, and the thermal protection scheme given by the individual with the minimum fitness in the currently evolving population is used as the optimization result. Otherwise, enter module M6; Module M6: Retain, crossover and mutate the individuals according to the adaptive parameters to generate a new generation of population, and then repeat modules M2 - S5; The module M1 includes: For the integrated heat insulation and heat protection structure composed of n layers of materials, the maximum number of evolutions gen, which is the core parameter of the genetic algorithm max 、the population size pop, and the maximum allowable temperature T limit of the alternative material properties; the maximum allowable structural thickness H limit allowed for optimization; Randomly generate an initial population containing pop individuals, and each individual g contains a set of material thicknesses, that is: g = [h 1 , h 2 ,..., h n ; The module M4 includes: Calculate the objective function for each individual in the current evolution, and take the line density ρ l as the objective function, and its expression is: ρ l = ρ α A α + ∫ ρ grad (R)c grad (R) dR + ρ β A β + ρ m A m Where A is the cross-sectional area, and the subscripts α, grad, β, and m respectively represent the thermal protection material, two-phase gradient material, thermal insulation material and metal material; R is the radius of the structure, and the above formula is further arranged as: wherein R 0 , R 1 , R 2 , R 3 , R 4 are respectively the outer radius of the heat insulation layer, the inner radius of the heat insulation layer, the inner radius of the gradient layer, the inner radius of the heat insulation layer and the inner radius of the metal layer; For all individuals evolving currently, calculate the adaptive penalty factor δ according to the current generation number of evolutions and the maximum generation number of evolutions: δ(gen) = 10 λy(gen) Where λ is the introduced constant parameter, and the expression of y(gen) is as follows: For each individual evolving currently, calculate the satisfaction of the strength constraint, temperature constraint and space constraint according to the calculation result of step S3 and the thicknesses of each layer of materials included in the individual to obtain its penalty function P, and its expression is: where p i (g) is a constraint function, and b is the total number of constraint conditions; The strength constraint is expressed by the remaining strength coefficient, and its constraint function expression is: The temperature constraint is expressed by a dimensionless expression, and its constraint function expression is: The space constraint is expressed by a dimensionless expression, and its constraint function expression is: For each individual in the current evolution, the fitness value is obtained by calculating according to the following formula: fit(gen,g) = ρ l (g) + δ(gen)P(g).

7. The optimization method for the thermal protection scheme of the heat insulation and heat protection integrated structure according to claim 6, characterized in that: The module M2 includes: For each individual g, according to its thickness h at each layer i (i = 1, 2,..., n), it is discretized into a series of cells based on the finite volume method, and material parameters are assigned to each cell. The material parameters include thermal conductivity k, specific heat capacity c, and density ρ; For metal materials, heat protection materials and heat insulation materials, their material parameters do not change with space, and the same material parameter values are assigned to all units of this material; For the two-phase functionally gradient material composed of heat protection materials and heat insulation materials, considering the case where its composition changes linearly with space, the material parameters of each unit are assigned according to the following method: C grad = (1 - V β ) C α + V β C β ρ grad = (1 - V β ) ρ α + V β ρ β where the subscript grad represents the functionally graded material, and the subscripts α and β represent the two phases that make up the functionally graded material. For this method, α represents the heat protection material and β represents the heat insulation material. V β is the volume fraction of the heat insulation material; The initial condition of the set calculation model is the global initial temperature. The boundary conditions of the calculation model include thermal load and force load. The thermal load is input in the form of the second kind of boundary condition or the third kind of boundary condition. The force load includes the maximum bending moment M borne by the structure and the outer diameter D of the structure.

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