Lattice interlayer thermal protection structure of aircraft and design optimization method of lattice interlayer thermal protection structure

Abstract

The invention discloses a lattice sandwich thermal protection structure of an aircraft and a design optimization method thereof, and relates to the technical field of hypersonic aircrafts, the lattice sandwich thermal protection structure comprises a lattice sandwich structure, a thermal insulation functional layer and a phase change thermal storage layer; the dot matrix sandwich structure comprises an upper panel, a lower panel and a plurality of dot matrix cores; the upper panel is used for bearing a high-temperature heat source, and the lower panel faces the interior of the aircraft body; the dot matrix cores are used for connecting the upper panel and the lower panel to form a filling space; the heat insulation function layer and the phase change heat storage layer are arranged in the filling space, the heat insulation function layer is adjacent to the upper panel, the phase change heat storage layer is adjacent to the lower panel, the heat insulation function layer is filled with a heat insulation material, and the phase change heat storage layer is filled with a phase change material; and the filling thickness ratio of the thermal insulation material to the phase change material is 1: 1. The interior of the lattice sandwich structure is filled with the heat insulation material and the phase change material in a partitioned mode, a high-temperature heat source is directly prevented from being transmitted inwards, and the effective temperature control duration of the structure under high-temperature heat loads is prolonged.

Description

Technical Field

[0001] This invention relates to the field of hypersonic vehicle technology, and in particular to a lattice sandwich thermal protection structure for a vehicle and its design optimization method. Background Technology

[0002] Hypersonic technology, as a core driver of future warfare and space transportation transformation, has become a key area in the strategic layout of global military and space powers, attracting widespread attention and significant investment. Against this backdrop, hypersonic vehicles must operate in extreme flight environments involving transatlantic flight, high Mach numbers, and dramatic aerodynamic changes, facing severe aerodynamic heating challenges. This poses unprecedented technical challenges to their thermal protection systems (TPS). The TPS must not only ensure the vehicle's dimensional stability, structural integrity, and efficient thermal insulation performance under extreme thermal loads, but also achieve lightweight design to balance maneuverability, payload, and range. Therefore, technological breakthroughs in TPS have become a core bottleneck in the development of near-space hypersonic vehicles.

[0003] Lightweight sandwich structures, with their high specific strength, excellent structural stability, and flexible functional designability, have become an important research direction for thermal protection systems of hypersonic vehicles. These structures mainly include corrugated, lattice, foam, honeycomb, and multi-level sandwich structures. By integrating multifunctional materials or fluid channels into the core space, an integrated thermal protection structure combining lightweight, compactness, high-efficiency load-bearing capacity, and thermal insulation can be constructed. Currently, thermal protection structures are mainly divided into two categories: active and passive (including semi-passive). Active thermal protection removes structural heat through cooling fluids to achieve cooling, while passive thermal protection relies on radiation, insulation, or heat absorption mechanisms to block heat transfer. In the field of active thermal protection research, Waas et al. investigated the active cooling performance of coolant flow within a metal foam sandwich structure for the structural thermal protection system of hypersonic reentry vehicles, finding that cooling efficiency increases with increasing metal foam height, but with a significant limit. Feng et al. established a thermal conduction-convection coupling model for active cooling of lattice sandwich structures in high-temperature exhaust gas impact scenarios and verified the reliability of the model through experiments. Yan et al. fabricated a lightweight X-shaped lattice structure using a metal sheet stamping and folding process. Their convective heat transfer performance study showed that the overall heat dissipation capacity of this structure was significantly superior to other lattice structures with the same porosity. In passive insulation research, Xu et al. designed and fabricated a multi-level lattice thermal protection system. By adding a thermal insulation layer to the upper panel of a traditional lattice structure, they significantly improved thermal insulation performance and load-bearing capacity while reducing the overall structural density. Wei et al. conducted thermo-mechanical coupling response analysis under transient thermal loads on a C / SiC pyramid lattice thermal protection structure filled with thermal insulation material, focusing on revealing the evolution of peak thermal stress over time. In the field of semi-passive thermal protection, integrating heat pipes or phase change materials (PCMs) into sandwich structures can achieve temperature homogenization and latent heat storage functions. For example, Wadley et al. designed a multifunctional heat pipe sandwich structure and verified its thermal protection performance under the periodic impact of high-temperature gas; Wang Qiuwang et al. confirmed that the composite structure of porous metal and PCM can effectively enhance heat transfer in an acceleration field; Feng et al. compared two heat transfer models (pore-scale simulation and homogeneous porous medium model) of metal foam-filled PCM and found that the assumption of local thermal equilibrium between metal foam and paraffin does not affect the prediction accuracy of the homogeneous model; Li et al. developed a composite thermal protection component with both thermal insulation and phase change energy storage functions. High-temperature thermal shock experiments showed that the component can significantly reduce the back temperature and extend the effective temperature control time under the same heating conditions.

[0004] In the aerospace field, the heat transfer performance, lightweighting level, and mechanical properties of thermal protection structures are equally important. Therefore, multi-objective optimization research on lightweight sandwich structures has received considerable attention in recent years. Xu et al. used the geometric dimensions of X-shaped and pyramidal lattice structures as design variables and employed the NSGA-II genetic algorithm to solve a multi-objective optimization problem involving relative density, natural frequency, equivalent elastic modulus, and convective heat transfer performance. Gao et al., focusing on tetrahedral lattice structures under active cooling conditions, used core geometric parameters as design variables and employed the NSGA-II multi-objective genetic algorithm, taking specific modulus, specific strength, relative density, and maximum temperature as objective functions, ultimately determining the optimal comprehensive inclination angle of the sandwich rod to be 45°. Roper et al., using compressive strength, compressive modulus, density, and maximum heat flux as optimization objectives, constructed a multi-objective optimization model for microscale truss core and arterial core heat pipe sandwich plates, obtaining the Pareto optimal design surface for this problem. Feng et al. used response surface methodology and NSGA-II genetic algorithm to conduct multi-objective optimization of convective heat transfer, lightweight performance and load-bearing capacity of lattice sandwich structures. The optimization results were verified by forced convective heat transfer experiments and quasi-static out-of-plane compression mechanics experiments, which proved the effectiveness of NSGA-II genetic algorithm in multi-objective optimization.

[0005] Compared to active thermal protection structures, passive (including semi-passive) thermal protection structures do not require complex cooling fluid circulation systems, offering advantages such as simple structure and reliable operation, thus making them a preferred choice in engineering applications. However, existing research on integrated passive thermal protection structures largely focuses on single integrated insulation materials or phase change materials (PCMs). On the one hand, while relying solely on insulation materials can prevent heat transfer inwards, in scenarios where the height of the thermal protection structure is limited, it can still lead to excessively high back temperatures and cause the hot-face temperature to exceed the material's temperature resistance limit. On the other hand, while relying solely on phase change heat storage can absorb a large amount of heat flow, it cannot prevent external heat from rapidly spreading into the internal structure, resulting in a shortened temperature control time. Summary of the Invention

[0006] Based on the deficiencies of the existing technology, the present invention provides a lattice sandwich thermal protection structure for aircraft and its design optimization method, which solves the problems of excessively high back temperature caused by using only thermal insulation materials in the existing integrated passive thermal protection structure and shortened temperature control time caused by using phase change materials.

[0007] The present invention adopts the following technical solution: In a first aspect, the present invention provides a lattice sandwich thermal protection structure for an aircraft, comprising a lattice sandwich structure, a thermal insulation functional layer and a phase change thermal storage layer. The lattice sandwich structure includes an upper panel, a lower panel, and multiple lattice cores; the upper panel is used to withstand high-temperature heat sources, and the lower panel faces the interior of the aircraft body; multiple lattice cores are used to connect the upper panel and the lower panel to form a filling space; each lattice core includes multiple metal rods that are inclined and interconnected. The heat insulation functional layer and the phase change heat storage layer are disposed in the filling space. The heat insulation functional layer is adjacent to the upper panel, and the phase change heat storage layer is adjacent to the lower panel. The heat insulation functional layer is filled with heat insulation material, and the phase change heat storage layer is filled with phase change material. The filling thickness ratio of heat insulation material to phase change material is 1:1.

[0008] Preferably, the heat insulation layer is made of aerogel, and the phase change heat storage layer is made of paraffin.

[0009] Preferably, the lattice sandwich structure is made of TC4 titanium alloy.

[0010] Preferably, the dot matrix core has a tetrahedral structure, the metal rod has a diameter of 1mm to 3mm, and the angle between the metal rod and the panel is 30° to 60°.

[0011] In a first aspect, the present invention provides a method for designing and optimizing a lattice sandwich thermal protection structure for an aircraft, comprising the following steps: A unit cell heat transfer numerical model of the lattice sandwich thermal protection structure is established, wherein the unit cell heat transfer numerical model includes only one lattice core. Using the diameter of the metal rod, the tilt angle of the metal rod, and the thickness of the phase change material filling as design variables, and taking the improvement of temperature control time, lightweight performance, and mechanical properties as optimization objectives, a multi-objective optimization problem is constructed. The multi-objective optimization problem is solved using a multi-objective genetic algorithm to obtain the Pareto optimal solution set, and the optimal combination of design variables for the thermal protection structure is determined based on the Pareto optimal solution set.

[0012] Preferably, the multi-objective optimization problem is as follows: ; In the formula, f For a multi-objective optimization problem, f 1 represents the temperature control duration. f 2 is for lightweight performance, f 3 represents mechanical properties. x 1 represents the diameter of the metal rod. x 2 represents the inclination angle of the metal rod. x 3 represents the thickness of the phase change material filling.

[0013] Preferably, the objective function for the temperature control duration is as follows: ; The objective function for the lightweight performance is as follows: ; The objective function for the mechanical properties is as follows: ; In the formula, E 33 For the equivalent elastic modulus, E s For elastic modulus, G 13 For equivalent shear modulus, σ 33 For equivalent yield strength, σ Y For the material's yield strength, τ 13 Equivalent shear strength, w 1= w 2= w 3= w 4 = 0.25.

[0014] Compared with the prior art, the above-mentioned at least one technical solution adopted by the present invention can achieve the following beneficial effects: This invention provides a lattice-layered thermal protection structure for aircraft. The lattice-layered structure is filled with a thermal insulation layer and a phase change heat storage layer. The thermal insulation layer is filled with thermal insulation material, and the phase change heat storage layer is filled with phase change material. The thickness ratio of the thermal insulation material to the phase change material is 1:1. This invention achieves synergistic regulation of thermal insulation and phase change material by dividing the lattice-layered structure into zones. Specifically, the thermal insulation material with excellent temperature resistance is placed adjacent to the upper panel to directly block the transfer of high-temperature heat sources to the interior. By utilizing the complementary functions of the two materials, a synergistic regulation of "thermal insulation and heat storage" is achieved, ultimately extending the effective temperature control time of the structure under high-temperature thermal loads.

[0015] Meanwhile, considering multiple influencing factors such as the structural parameters of the lattice core and the filling thickness of the thermal insulation and phase change materials, a genetic algorithm was used to conduct a multi-objective optimization study on the lightweight characteristics, thermal insulation performance, and comprehensive mechanical properties of the lattice sandwich integrated thermal protection structure, obtaining the optimal design parameters for the lattice sandwich thermal protection structure. Through the synergistic design of material and structural parameters, a good balance can be achieved between structural weight, thermal insulation performance, and mechanical properties. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a schematic diagram of a lattice sandwich thermal protection structure for an aircraft according to the present invention; Figure 2 This is a schematic diagram of the lattice sandwich thermal protection structure of the filled thermal insulation material and PCM of the present invention. Figure 3 This is a schematic diagram of the unit cell heat transfer model and mesh division of the lattice sandwich thermal protection structure of the present invention; Figure 4 This is a schematic diagram of the filling process of the present invention; in, Figure 4 (a): Lattice sandwich test specimen, Figure 4 (b): Paraffin filler, Figure 4 (c): Aerogel filling; Figure 5 The DSC-TGA test curve of the paraffin of the present invention; in, Figure 5 (a): DSC curve, Figure 5 (b): TGA curve; Figure 6 This is a schematic diagram of the thermal insulation performance testing platform of the present invention; Figure 7 The temperature response curves at each monitoring point on the back panel of the test specimen of this invention are shown. Figure 8 The curves showing the temperature change at each monitoring point of the lattice sandwich structure of the present invention as a function of loading time after being heated are shown. Figure 9 This is a cloud map showing the internal temperature distribution of the lattice sandwich structure of the present invention during the heating process. in, Figure 9 (a): Internal temperature distribution contour map at 100s. Figure 9 (b): Internal temperature distribution contour map at 500s. Figure 9 (c): Internal temperature distribution contour map at 1000s. Figure 9 (d): Internal temperature distribution contour map at 1500s. Figure 9 (e): Internal temperature distribution contour map at 2000s. Figure 9 (f): Internal temperature distribution cloud map at 3000s; Figure 10Curves of the liquid fraction of PCM and the average temperature on the back panel surface varying with time during the melting process of the present invention; Figure 11 Relationship between the temperature control duration and the PCM filling thickness of the present invention; Figure 12 Unit cell model of the lattice sandwich thermal protection structure of the present invention; Figure 13 Objective function of the present invention f Response surface of 1; Among them, Figure 13 (a) of; x Response surface of the objective function 1 when 3 = 10 mm f of 1, Figure 13 (b) of; x Response surface of the objective function 1 when 1 = 2 mm f of 1, Figure 13 (c) of; x Response surface of the objective function 1 / f 2 (density ρ ) when 3 = 10 mm, Figure 13 of (d); x Response surface of the objective function 1 / f 2 (density ρ ) when 2 = 45°; Figure 14 Basic process of the NSGA-II genetic algorithm of the present invention; Figure 15 Pareto optimal boundary of the three-objective optimization problem of the present invention; Figure 16 Relationship between the rod diameter, the temperature control duration, and the comprehensive mechanical properties of the present invention; Figure 17 Relationship between the rod diameter, the temperature control duration, and the density of the present invention; Figure 18 Relationship between the inclination angle, the temperature control duration, and the comprehensive mechanical properties of the present invention; Figure 19 Relationship between the inclination angle, the temperature control duration, and the density of the present invention; Figure 20 Relationship between the PCM height, the temperature control duration, and the comprehensive mechanical properties of the present invention; Figure 21 Relationship between the PCM height, the temperature control duration, and the density of the present invention. Specific embodiments

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] Example 1 To address the technical requirements of integrated thermal protection structures for hypersonic vehicles, this invention proposes a composite temperature control strategy combining a lattice sandwich structure filled with thermal insulation material (aerogel) and PCM. Figure 1 By synergistically leveraging insulation and heat storage functions, the structural temperature control duration under non-sustained thermal loads is maximized. Simultaneously, considering multiple influencing factors such as lattice core structural parameters, insulation material, and PCM filling thickness, a multi-objective optimization study is conducted using response surface methodology and the NSGA-II genetic algorithm to evaluate the lightweight characteristics, insulation performance, and comprehensive mechanical properties of the integrated lattice sandwich thermal protection structure.

[0020] The integrated thermal protection structure proposed in this invention adopts a synergistic composite temperature control scheme of "insulation material-phase change material". By filling the interior of the lattice sandwich structure with insulation material and PCM in sections, the complementary functions of the two achieve synergistic regulation of "insulation-heat storage", ultimately extending the effective temperature control time of the structure under high temperature load. Among them, the insulation material, with its extremely low thermal conductivity, can significantly suppress the rate of heat transfer from the outside to the interior of the structure; the PCM, relying on its high latent heat of phase change, absorbs a large amount of heat during the melting process, ensuring that critical areas of the structure (such as the back panel) are maintained within the safe temperature threshold for a long time during heating.

[0021] Figure 2 This is a schematic diagram of a periodic unit of a lattice sandwich thermal protection structure, which mainly consists of three parts: a load-bearing frame (lattice sandwich structure), a thermal insulation layer, and a phase change thermal storage layer. The lattice sandwich structure includes an upper (thermal) panel, a lower (back) panel, and a lattice core. The lattice core is composed of interconnected metal rods. The lattice structure of this invention is a tetrahedral structure, but is not limited to a tetrahedral structure.

[0022] The top panel directly bears the external high-temperature heat source, while the back panel faces the interior of the aircraft fuselage. The lattice core serves as the core load-bearing component connecting the top and bottom panels, while also providing filling space for the thermal insulation material and PCM, achieving an integrated design of "structural load-bearing and functional accommodation". In addition, the thermal insulation material with excellent temperature resistance is adjacent to the top panel (hot side), directly blocking the transmission of high-temperature heat sources to the interior; the PCM with relatively weak temperature resistance is placed between the thermal insulation layer and the back panel, avoiding the PCM from direct contact with the high-temperature environment and premature failure, while maximizing its heat storage capacity to absorb heat penetrating the thermal insulation layer, forming a gradient protection system of "hot-side thermal insulation - intermediate heat storage - cold-side temperature control".

[0023] During service, the heat transfer process of the lattice sandwich thermal protection structure involves multiple components and various forms of coupling. For example... Figure 2 As shown, the upper panel of the structure absorbs heat ( Q in ) and transfer to the interior; the internal heat transfer methods of the structure include heat conduction between components ( Q cond ) and heat convection inside the phase change material ( Q conv ); the outer surface of the back panel is affected by heat radiation ( Q rad ) and natural convection ( Q conv It dissipates heat to the environment.

[0024] In the design of practical aircraft thermal protection systems, the structural volume is typically constrained by the aircraft's aerodynamic shape and internal space. Therefore, this invention sets the total height of the lattice sandwich thermal protection structure to a fixed value (including the height of the upper and lower panels and the lattice core). The design variables include: the geometric parameters of the lattice core (diameter of the metal rod, tilt angle) and the ratio of the thickness of the insulation layer to the PCM layer (the total thickness of both is fixed). By adjusting these parameters, an optimal balance between heat storage capacity and thermal insulation performance can be achieved while meeting structural volume constraints, while also considering structural lightweighting and load-bearing capacity.

[0025] Both the lattice sandwich structure (panel and lattice core) are made of TC4 titanium alloy. This material has excellent high specific strength, low density, and low thermal conductivity, and has been widely used in high-temperature structural applications. The thermal insulation material is ultralight nanoporous aerogel, which has extremely low thermal conductivity and good high-temperature resistance, making it a preferred high-efficiency thermal insulation material for high-temperature applications. Solid-liquid phase change paraffin (RT48) is selected as the phase change material, possessing advantages such as high latent heat of phase change, strong chemical inertness, small phase change volume change, low cost, and environmental friendliness. Tables 1 and 2 list the key thermophysical parameters of TC4 titanium alloy, aerogel, and RT48 paraffin, respectively. The latent heat of phase change and phase change temperature of RT48 paraffin were obtained using a differential scanning calorimeter (TAInstrumentsDSC250).

[0026] Table 1. Thermophysical properties of titanium and aerogel Table 2 Thermophysical properties of paraffin RT48 Example 2 Based on the same concept, this invention also provides a design optimization method for a lattice sandwich thermal protection structure. Specifically, it includes the following steps:

[0027] S1: Establish a unit cell heat transfer numerical model for the lattice sandwich thermal protection structure.

[0028] S11: Computational domain and boundary conditions.

[0029] Given the periodic repetitive characteristics of the lattice sandwich thermal protection structure, this invention selects a unit cell model as the computational domain for heat transfer simulation to accelerate computational efficiency, such as... Figure 3 As shown. The computational domain includes a lattice sandwich structure (upper and lower panels, lattice core), a thermal insulation layer, and a phase change thermal storage layer. The upper and lower panels have equal thickness ( t 1= t 2=1.5mm), sandwich layer height H=20mm, core rod (metal rod) diameter ( d The value range is 1mm~3mm (considering the balance between lightweight and load-bearing capacity), and the angle between the core rod and the panel is ( θ The value range is 30°~60° (to ensure excellent out-of-plane load-bearing capacity and functional layer filling rate), and the filling thickness of thermal insulation material and phase change material is a variable parameter.

[0030] The outer surface of the top panel of the lattice sandwich structure is subjected to isothermal boundary conditions, with a set temperature of 420℃ and a continuous thermal load duration of 3000s. The contact surfaces between the layers within the structure are set as coupled heat transfer boundaries. The outer surface of the back panel employs a combined boundary condition of natural convection and thermal radiation. The outer walls around each unit cell are set as adiabatic boundaries. Both the initial structural temperature and the ambient temperature are set to 20℃.

[0031] S12: Governing equation: To simplify the numerical model, the following reasonable assumptions are proposed: 1) neglect the thermal radiation inside the sandwich structure; 2) neglect the contact thermal resistance between the contact surfaces of different materials; 3) take the convective heat transfer coefficient of the back panel surface as a constant of 10W / (m2·℃) and the surface heating rate as 1.

[0032] Continuity equation: (1); Energy Equation: The enthalpy-based energy equation is employed. This method constructs a unified energy equation for the heat transfer process in the solid, liquid, and two-phase coexistence regions (pasty region) by treating enthalpy as a unified unknown function. Its core idea is to incorporate the latent heat of phase change into the definition of enthalpy, thereby avoiding explicit tracing of the phase interface and achieving a global solution across the entire region. The energy equation based on the enthalpy method is expressed as follows:

[0033] (2); (3); In the formula: H This is the total enthalpy value. H 0 (= c p T , c p Specific heat capacity is enthalpy. ∆H It is latent enthalpy. When PCM is a solid, ∆H The value is 0; when PCM is a liquid, ∆H for L (Latent heat value of PCM); when PCM is a paste-like substance between a solid and a liquid phase, ∆H Between 0 and L Between. This leads to the concept of liquid phase percentage. f l Concept:

[0034] (4); T m1 Indicates the lower limit of the phase transition temperature. T m2 This indicates the upper limit of the phase transition temperature.

[0035] Liquid phase fraction uniformity f l To express.

[0036] Momentum Equation: When PCM melts from a solid to a liquid state, the density difference caused by uneven temperature distribution generates buoyancy-driven natural convection under the influence of gravity, significantly affecting the heat transfer rate inside the PCM. To facilitate tracking phase interface movement and describing the natural convection process, the Navier-Stokes equation with an additional source term is used as the momentum equation:

[0037] (5); In the formula: μ It is dynamic viscosity. It is the buoyancy term. It is a power source item.

[0038] To simplify the buoyancy calculation, the Boussinesq assumption is adopted. This assumption assumes that the fluid density only varies with temperature in the buoyancy term, while the density is considered constant in the other terms. The magnitude of the buoyancy is proportional to the temperature difference between the fluid temperature and the reference temperature. (6); In the formula, β (=0.001K⁻¹) is the coefficient of thermal expansion of paraffin wax. T m1 This is a reference temperature.

[0039] By adding an additional source term to the momentum equation To address phase change interface issues: (7); In the formula, C It is an empirical constant, with a value range of 10. 5 ~10 7 , used to assign large values ​​to source terms in the solid region; η This is a local constant (0.001 in this invention) to prevent iterative divergence caused by a denominator of 0. In the fully liquid region, f l =1, at which point the momentum source term is 0, the momentum equation is not affected by additional drag, and the liquid phase PCM flow is free; in the completely solid region... f l =0, the source term value is extremely large, ensuring no flow in the solid phase region.

[0040] Meshing: FluentMeshing software was used for mesh generation. The mesh type is a polyhedral mesh, which can flexibly adapt to complex curved surfaces and 3D structures. Specific details of the mesh generation are as follows: Figure 3As shown in the figure, the minimum mesh size was set to 0.02 mm, the maximum size to 0.5 mm, and the total number of meshes was approximately 570,000. During mesh generation, the growth rate was set to 1.2, and the curvature normal angle was adjusted to 18 degrees. In the final generated mesh model, the minimum orthogonal quality was 0.21, and the average orthogonal quality reached 0.93. To ensure the reliability of the calculation results, the independence of mesh density and time step was calculated, showing that a mesh size of 570,000 and a time step of 1 second can meet the required accuracy without significantly increasing the computational burden.

[0041] In terms of numerical solutions, the SIMPLE algorithm is used to perform coupled calculations of pressure and velocity, and the convergence criterion for the iterative momentum equation is set to 10. -3 The convection term is discretized using a second-order upwind scheme, and the iterative convergence criterion for the energy equation is set to 10. -7 .

[0042] S2: Thermal insulation characteristics analysis.

[0043] First, we investigate the temperature response at different locations within the upper panel of the structure after heating. The results are as follows: Heating temperature 420℃, rod diameter 1.5mm, tilt angle 45°, and insulation material to phase change material thickness ratio 1:1. Figure 8 As shown in the figure. The results show that in the initial stage of heat loading, the temperature at monitoring point a at the center of the aerogel initially rises rapidly, but due to the low thermal conductivity of the aerogel, the heating rate at this point drops sharply after the initial rapid temperature rise. Monitoring point b, located at the interface between the aerogel and the phase change paraffin, does not experience the initial sharp temperature rise, and its temperature is about 150°C lower than that of monitoring point a. This is not only because heat needs to penetrate a thicker insulation layer, but also because the phase change process of the PCM significantly hinders heat flow transfer. The temperature at monitoring point c (located at the center of the phase change material) rises slowly in the initial stage. When it reaches the melting point of the phase change material, the phase change material begins to undergo phase change, absorbing a large amount of latent heat, which keeps the temperature at point c relatively stable for a period of time, entering the phase change plateau region. During the phase change stage, the temperature of the lower surface of the structure is close to the temperature of the phase change material at monitoring point c, but once the phase change is completed, the two temperatures deviate, with the temperature at monitoring point c being higher, reflecting the thermal resistance effect of the phase change material in the single-phase state.

[0044] To more intuitively demonstrate the temperature distribution pattern inside the lattice sandwich structure, Figure 9 Temperature distribution cloud maps of the structure at different times during the heating process are presented. After slicing, the temperature distribution of the lattice core rod, aerogel, and PCM within the structure can be clearly seen. In the initial stage of thermal loading (e.g., 100s), the heat has not yet fully penetrated the aerogel layer, resulting in dense temperature lines and a large temperature gradient within the aerogel layer, with the temperature of the entire aerogel layer exceeding 200℃.

[0045] As the heat loading time increases (500~1500s), the phase change material undergoes a phase change. Because the phase change material stores a large amount of heat, the heat flux transferred downwards is relatively small, resulting in sparse isotherms and a small temperature gradient within the phase change material layer. Simultaneously, the isotherms near the contact area between the core rod and the phase change material are flatter, indicating that the phase change material can improve the rapid conduction of absorbed heat on the core rod. Due to the latent heat absorption of the phase change material, the temperature of the lower panel of the structure remains near the phase change temperature during the phase change process, effectively achieving the temperature control effect of the thermal protection system. After 1500 seconds, the phase change material essentially melts, and the temperature distribution within the structure becomes more uniform, exhibiting a single-phase heat conduction law with a gradient decreasing in the thickness direction.

[0046] Figure 10 The PCM liquid phase fraction was shown. f l The curve showing the change in average temperature of the outer surface of the back panel over heating time is also provided, along with the inset. f l =0.1 / 0.5 / 1 corresponds to the solid-liquid distribution contour map of PCM at time points. The PCM phase transition process begins at approximately 250s and completes at 1500s. From f l The solid-liquid distribution cloud map of PCM at time 0.1 shows that in the initial stage, the melting of PCM extends outward and downward from the high thermal conductivity metal core rod, resulting in a concave curved surface morphology of the solid-liquid phase change interface near the core rod. After heating for 500 seconds, the liquid phase region expands away from the heat source; between 830 and 1120 seconds, the volume of the molten region increases significantly, and the phase interface advances from the four corners where the lower panel connects to the core rod towards the center of the panel. By 1525 seconds, the PCM has completely melted, and the latent heat of phase change has been absorbed. Throughout the phase change process, the average temperature of the lower panel increases with the increase of the PCM liquid phase fraction, but the heating rate is effectively controlled before the phase change is completed, and the panel temperature remains below the safe temperature. After the phase change is completed, the panel temperature rises rapidly, demonstrating the temperature control function of the phase change material.

[0047] In order to extend the time that the back panel is kept below the safe temperature (50°C) as much as possible (temperature control time), while keeping the total core height at 20mm, the filling thickness of the phase change material and the thermal insulation material was changed, and it was found that there is an optimal filling ratio that maximizes the temperature control time. Figure 11The relationship between the temperature control time and PCM filler thickness under three different core rod diameters is presented. As the PCM filler thickness increases, the temperature control time first increases and then decreases, indicating an optimal PCM filler thickness that maximizes the temperature control time. Under all three core rod diameters, the optimal filler height ratio of aerogel to PCM is approximately 1:1; and this optimal ratio is more significant when the core rod diameter is smaller (lower core porosity). When the PCM filler thickness is small, the insulation material is thicker, resulting in good insulation but limited heat storage capacity and a short temperature control time. Conversely, when the PCM filler thickness is too large, the insulation material thickness decreases, leading to rapid heat transfer into the structure. This causes the back panel temperature to exceed the temperature control requirements before the PCM completes its phase change, thus shortening the temperature control time.

[0048] S3: Using the core rod diameter, core rod inclination angle, and phase change material filling thickness as design variables, and temperature control time, lightweight performance, and comprehensive mechanical properties as optimization objectives, a multi-objective optimization problem is constructed.

[0049] The variables studied in this invention include lattice structure parameters (diameter of the core rod). d ,inclination θ The ratio of the phase change material to the insulation material's fill thickness is also considered. Here, the fill height of the phase change material is selected with the total core height fixed (H=20mm). h As research variables, it is foreseeable that when these variables change, the structure's weight, thermal insulation performance, and mechanical properties will all change. Therefore, the question is how to find the optimal combination of variable parameters to simultaneously achieve the best results in terms of lightweight performance, thermal insulation performance, and mechanical properties.

[0050] like Figure 12 As shown in the unit cell model, the research variables are x =[ x 1, x 2, x 3] T =[ d , θ , h ] T The goal of multi-objective optimization is to achieve the desired temperature control duration ( f 1) Lightweight performance ( f 2) Mechanical bearing capacity ( f 3) Synergistic improvement of indicators. In engineering design, it is necessary to constrain the range of variable variation based on actual conditions. In this invention, the diameter of the lattice core rod varies from 1mm to 3mm, the tilt angle varies from 30° to 60°, the phase change material filling thickness is 2 to 18mm, and the heating temperature is fixed at 420℃. Therefore, the mathematical description of the multi-objective optimization problem in this invention is as follows:

[0051] (8); Performance evaluation metrics include temperature control time ( f 1) Lightweight performance ( f 2) and mechanical bearing capacity ( f 3).

[0052] For aircraft subjected to non-sustained thermal loads, the temperature control duration of the thermal protection structure should be increased as much as possible under given constraints to ensure the aircraft's safe operation throughout its mission cycle. With a fixed heat source temperature of 420°C, this invention defines the temperature control duration as follows: the time during which the temperature of the back panel of the lattice sandwich structure remains below the safe temperature (50°C) after self-heating loading, using a function... f 1. As an evaluation indicator for temperature control duration:

[0053] (9); In the aerospace field, structural lightweighting is a perpetual goal. When designing thermal protection structures, the aircraft's shape and structural volume (or height) are typically predetermined; at this point, the structure's weight is directly related to its density. ρ Directly related:

[0054] (10); In the formula: ρ s , ρ p , ρ a The densities of the sandwich rod, paraffin wax, and aerogel materials are respectively. V s , V p , V a The volumes of the three are respectively; V t This represents the volume of the entire unit cell core, excluding the top and bottom panels.

[0055] Given that the optimization goals for temperature control time and mechanical performance indicators are both aimed at maximizing, while the optimization goal for density is minimization, a reciprocal method is introduced to transform the areal density index, which aims to minimize it, in order to maintain consistency among the optimization objectives. This results in a lightweight performance objective function. f 2 Defined as:

[0056] (11); To simplify the analysis, the influence of the infill material on the structural load-bearing capacity is ignored; only the influence of the core parameters (bar diameter, inclination angle, and height) of the pyramid lattice structure is considered here. The relative elastic modulus, relative shear modulus, relative yield strength, and relative shear strength of the pyramid lattice structure are all related to the structural geometric parameters and material properties.

[0057] (12); (13); (14); (15); In the formula: E 33 It is the equivalent elastic modulus. E s It is the elastic modulus of the material; G 13 It is the equivalent shear modulus; σ 33 It is the equivalent yield strength. σ Y It is the yield strength of the material; τ 13 It is the equivalent shear strength.

[0058] This invention employs a weighted aggregation method to integrate the above four indicators into a single function as the objective function for the comprehensive mechanical performance of the lattice sandwich structure. (16); In the formula: w 1, w 2, w 3, w 4 represents the weight of each indicator, which is taken in the optimization problem of this invention. w 1= w 2= w 3= w 4 = 0.25.

[0059] Temperature control duration ( f 1) and lightweight performance ( f 2) The objective function and design variables are implicitly related and cannot be directly used for multi-objective optimization. Therefore, this invention uses the Response Surface Methodology (RSM) method to construct an explicit expression for these two objective functions. This invention selects the Central Composite Design (CCD) as the sampling framework. In the three-factor CCD, when the center point experiment is repeated three times, its experimental layout will include 17 experimental points, specifically 8 corner points, 6 axis points, and 3 center points. Each variable in the CCD scheme adopts the three-level orthogonal design principle, as shown in Table 3.

[0060] Table 3. Three-factor CCD level table for variables. Table 4 lists the 17 experimental conditions and their corresponding objective function values ​​obtained based on the CCD framework. The objective function response value for each experimental point was obtained in the following way: temperature control time ( f 1) The response value is obtained based on numerical simulation of heat transfer in a single cell, while the areal density (1 / f 2) It can be directly calculated using the geometric modeling function of ANSYSDesignModeler.

[0061] Table 4. Experimental conditions based on three-factor CCD sampling and their corresponding objective function values. To maximize fitting accuracy, this invention selects a multinomial regression model that includes quadratic and cubic cross terms, the mathematical expression of which is: (17); In the formula: k The number of variables; β 0, β j , β jj , β jjj , β ij , β iij and β ijk All are undetermined coefficients; ε This is the error term.

[0062] This invention employs Design-Expert 13 software for response surface fitting, optimizes the parameters of the initial third-order polynomial model using a stepwise regression algorithm, and identifies and removes statistically insignificant higher-order interaction terms using analysis of variance. After model correction and residual analysis, the objective function is finally obtained. f 1 and 1 / f The optimized regression model for 2 is as follows:

[0063] (18); (19); The objective function was analyzed using variance analysis. f 1 and 1 / f The regression models of 2 were subjected to a statistical significance test, and the results showed that both regression models passed rigorous statistical validation. P <0.01). Objective function f 1. A linear term x 1, x 2 and quadratic terms x 1 2 ,x 3 2 All showed extremely high significance ( P <0.01), remaining linear term x 3 reached a significant level ( P <0.05); objective function 1 / f All regression coefficients in section 2 showed extremely high significance. P <0.01). Combining the ANOVA results in Tables 5 and 6, it can be seen that the constructed response surface model has high fitting accuracy and can accurately reflect the mathematical relationship between the design variables and the objective function. Sensitivity analysis of the regression model's parameters shows that the design variables have varying degrees of influence on the target response and on the objective function. f The degree of influence of 1 is ranked as follows: x 2> x 1> x 3. For the objective function 1 / f The sensitivity ranking of 2 is as follows: x 1> x 3> x 2.

[0064] To verify the significance of the regression equations, this invention conducted an analysis of variance on the regression equations and their terms for the two obtained optimization objectives. Simultaneously, the goodness of fit was determined using the coefficient of determination. R 2. An evaluation is performed, and its calculation expression is shown below:

[0065] (20); In the formula: m Indicates the number of experimental sites; It is a response surface prediction value; y i These are the numerical simulation results for each experimental point; This is the average value of the numerical simulation results at each experimental point. Simultaneously, the coefficients of determination for the two models... R 2 The values ​​are 0.9685 and 1 respectively, indicating that the constructed regression model has high prediction accuracy.

[0066] Table 5 Objective Function f Analysis of variance of the regression equation of 1 Table 6 Objective Function 1 / f Analysis of variance of the regression equation of 2 To illustrate the effect of the three design variables on the objective function f 1 (temperature control duration) and 1 / f 2 (density) ρ The influence pattern of ) Figure 13 Figures (a) and (b) plot the response surface of the objective function for temperature control duration, while... Figure 13 (c) and (d) present the response surface of the density objective function. From Figure 13 As can be seen in (a), under the condition that other variables are constant, with the diameter of the sandwich rod ( x 1) As the diameter of the core rod increases, the temperature control time decreases. This is because the heat conduction through the core rod into the structure increases; and as the diameter of the core rod increases, the density of the structure also increases. Figure 13 As shown in (c). From Figure 13 As can be seen in (b), under the condition that other variables are constant, with the increase of PCM filler thickness ( x 3) As the PCM filling thickness increases, the temperature control time first increases and then decreases, while the density monotonically increases with increasing PCM filling thickness. Figure 13 (d)

[0067] S4: A multi-objective optimization method based on the NSGA-II genetic algorithm.

[0068] Based on obtaining the explicit mathematical expression between the objective function and the design variables, this invention employs the Non-dominated sorting genetic algorithm-II (NSGA-II) to solve the current three-objective optimization problem. In solving the multi-objective optimization problem, the design variable space is first mapped to the solution space through the objective function. Then, the optimization algorithm transforms the solution space into a Pareto front in the objective space, achieving multi-objective trade-off analysis.

[0069] For a multi-objective optimization problem involving n decision variables and m objective variables, max F ( X If it exists X *belong Ω ( Ω (for the feasible set of solutions that satisfy the constraints), and for all j =1,2,...,m, and there is no other =m. belong Ω Make It holds true, and at least one inequality of the objective function is strictly true (i.e., If X* is the maximum value, then we call X* the maximum value. F ( X The Pareto optimal solution is obtained from the Pareto optimal solution. The set of objective space vectors corresponding to the optimal solutions constitutes the Pareto optimal front. PF * is defined as:

[0070] (twenty one); The basic process of the NSGA-II algorithm is as follows: Figure 14 As shown, its core steps consist of three operational mechanisms: first, establishing a hierarchical sorting system based on Pareto dominance; second, maintaining population diversity through the crowding distance operator; and finally, using genetic operators to achieve population evolution. During the iteration process, the algorithm iteratively executes selection, crossover, and mutation operations, causing the population individuals to gradually converge to the Pareto optimal front. According to the convergence criterion, when the number of iterations reaches a certain value, the population evolution will gradually stabilize, and the algorithm enters a stable convergence state.

[0071] The multi-objective optimization analysis of the NSGA-II genetic algorithm was implemented in Matlab software. During the parameter configuration phase of NSGA-II, the crossover probability was set to 1, forcing all parent individuals to undergo crossover; the polynomial mutation operator probability was set to 1 / 3 to control the probability of random perturbation of individual genes and avoid getting trapped in local optima; simultaneously, both the crossover exponent and the mutation exponent were adjusted to 20. During the computation, the population size was set to 150, as the number of individuals in each generation affects the convergence speed and solution set distribution; and the number of generations was set to 5000 to control the number of algorithm iterations and ensure sufficient convergence.

[0072] The Pareto front obtained by solving the three-objective optimization problem using the NSGA-II genetic algorithm is as follows: Figure 15 As shown. The Pareto front is formed by a curve in space, which allows the three objective functions ( f 1, f 2, f 3) Simultaneously achieving the maximum value while obtaining an outer contour line (optimized solution set) from the entire spatial design points. Therefore, Figure 15 Each red ball in the curve represents a design point. x 1, x 2, x 3) Under operating conditions, the structural temperature control time, lightweight performance, and overall mechanical properties simultaneously reach their optimal values. As can be seen from the projection distribution in the three directions of the figure, density and overall mechanical properties exhibit a consistent trend, both increasing or decreasing simultaneously. This aligns with physical realities, as both objective functions are closely related to the porosity of the lattice core. However, the optimization directions for density or overall mechanical properties are opposite to those for temperature control time; that is, increased density or overall mechanical properties lead to a shorter temperature control time. The Pareto front curves visually demonstrate the trade-offs among the three objective functions, providing designers with a basis for making reasonable choices among temperature control time, density, and overall mechanical properties based on actual application requirements.

[0073] To verify the reliability of the optimization results, three typical optimization solutions were selected from the optimization solution set for finite element numerical verification. The relative errors between the optimization prediction results and the numerical simulation results are shown in Table 7. Among these optimal design points, the maximum error between the predicted and simulated values ​​of temperature control time was 9.7%, while the maximum error between the predicted and simulated values ​​of density was controlled within 2.33%, indicating that the current optimization results have high credibility and accuracy.

[0074] Table 7 Comparison of Multi-Objective Optimization Prediction Results and Simulation Results Figure 16 and Figure 17 The distribution of rod diameters in the optimal solution set is shown. From Figure 16 It can be seen that the rod diameter and density (or comprehensive mechanical properties) both exhibit a monotonic linear relationship. The rod diameter is relatively uniformly distributed within the design range, without obvious aggregation or dispersion, indicating that the rod diameter is a key influencing factor on density (or comprehensive mechanical properties). Figure 17 It can be clearly seen that the rod diameter distribution exhibits a certain hierarchy based on the temperature control duration. When the temperature control duration is less than 1000 seconds, the rod diameter is distributed globally between 1-3 mm; while when the temperature control duration exceeds 1000 seconds, the rod diameter is concentrated at the lower limit of the design value, 1 mm. This result indicates that in order to obtain an ultra-long temperature control duration (>1000 s), the diameter of the core rod should be relatively small to avoid strong thermal conductivity. Furthermore, unlike the other two objectives, the temperature control duration is affected by factors other than the rod diameter.

[0075] Figure 18 and Figure 19 The distribution characteristics of the core rod inclination angle in the optimal solution set are shown. For example... Figure 18 As shown, in regions with low density and weak overall mechanical properties, the inclination angle is uniformly distributed between 35-60°; in regions with high density and strong overall mechanical properties, the inclination angle is mainly concentrated between 58-60°. This is because an increased inclination angle makes the structure more compact (reducing porosity), which improves density and overall mechanical properties. Regarding the temperature control time (see...), Figure 19 In areas where temperature control exceeds 1000 seconds, the tilt angle is distributed between 35-60°, indicating that the tilt angle is a significant influencing factor in long temperature control areas. When the temperature control time is shorter (<1000s), the tilt angle is mostly between 58-60°, with a small number distributed between 43-58°. This is because when the tilt angle is large, the structural porosity is low, the thermal conductivity of the core is enhanced, and therefore the temperature control time is shorter.

[0076] Figure 20 and Figure 21The distribution of phase change material (PCM) filling thickness in the optimal solution set is shown. The height of the PCM is almost entirely concentrated in the range of 10-10.4 mm, which is about half of the total core height. This means that the filling ratio of insulation material to PCM is approximately 1:1, which is consistent with the previous results of the parameter influence study, indicating that other factors have little impact on the optimal filling ratio.

[0077] Overall, the distribution range of the phase change material height is the smallest within the design range, followed by the core rod inclination angle, while the rod diameter has the widest distribution range. Therefore, the Pareto optimal solution for the three-objective optimization exhibits the lowest dependence on changes in the phase change material height and the highest dependence on changes in the rod diameter. This distribution pattern indicates that the rod diameter has greater adjustability during the optimization process to adapt to different optimization objectives, while the optimization results for the phase change material height are relatively concentrated. Analyzing the distribution patterns of different design variables in the Pareto optimal solution helps to understand the influence mechanism of each variable on the optimization objectives, providing a reference for subsequent structural design and optimization.

[0078] Example 3 To verify the above numerical model, thermal insulation performance tests of the lattice sandwich structure were conducted, including specimen preparation, thermocouple bonding, paraffin and aerogel filling, determination of paraffin thermophysical parameters, and thermal insulation performance testing.

[0079] Selective laser melting (SLM) 3D printing technology was used to fabricate TC4 titanium alloy load-bearing skeleton (upper and lower panels, lattice core) test pieces, such as... Figure 4 As shown in (a). The main dimensions of the test piece are set as follows: thickness of the upper and lower panels. t 1= t 2 = 1.5mm, total height of the sandwich layer H =20mm, core rod diameter d =1mm, Inclination angle θ =60. The overall length and width of the test specimen are 49.6 mm (including 3×3 unit cells). To prevent the PCM (paraffin wax) from melting and leaking during heating, a titanium alloy baffle with the same height (10 mm) and thickness (0.8 mm) as the PCM layer is integrally printed around the test specimen to form a closed filling space.

[0080] The functional material filling sequence is PCM first, followed by aerogel. For paraffin filling, both the paraffin and the test specimen are heated to 60°C until the paraffin is completely melted. Then, the liquid paraffin is slowly injected into the cavity formed by the surrounding baffles of the test specimen. During this process, the test specimen is gently shaken to remove air bubbles and ensure that the paraffin evenly covers the gaps between the lattice cores. The filling height is controlled at 10mm. After the paraffin cools and solidifies... Figure 4As shown in (b). The aerogel used for filling was an aqueous dispersion of SiO2 aerogel with a density of 400~600 kg / m³ and a thermal conductivity of 0.025~0.03 W / (m·K). This aerogel is in a putty-like state when wet, suitable for the complex gaps in the lattice core. It was filled layer by layer and compacted to ensure tight filling without damaging the lattice core. The final filling height was 10 mm (equal to the thickness of the paraffin layer). The test specimen after the aerogel dried and cured is shown in [image missing]. Figure 4 As shown in (c). Figure 4 (c) and Figure 4 Compared to (b), the orientation has been reversed, that is, the original bottom surface is on top and the original top surface is on the bottom.

[0081] Differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA) were used to measure the initial phase transition temperature, melting point, and latent heat of phase transition of paraffin (RT48). The heating rate during the test was 10℃ / min. The DSC test results are as follows: Figure 5 As shown in (a), the phase transition process of paraffin RT48 exhibits a double endothermic peak characteristic. The first endothermic peak has an initial temperature of 27.43℃, corresponding to a solid-solid phase transition, with a latent heat of phase transition of 31.76kJ / kg. The second endothermic peak corresponds to the solid-liquid phase transition of paraffin, with an initial temperature of 47.4℃, a peak temperature of 50.03℃, and a latent heat of phase transition of 147.52kJ / kg. Figure 5 (b) shows the mass loss curve of RT48 paraffin as a function of temperature obtained by TGA testing. When the temperature exceeds 118°C, the paraffin begins to thermally decompose significantly, and its mass decreases rapidly; when the temperature rises to 317°C, the mass loss reaches 94%. Therefore, 118°C can be considered the highest temperature at which paraffin can maintain its properties and be recycled.

[0082] The thermal insulation performance testing system includes a heating module, a temperature measuring module, and a thermal insulation module, such as... Figure 6 As shown. The heating module uses a 100mm×100mm×20mm cast copper heating plate with a heating power of 500W. It has good temperature uniformity and is equipped with a PID intelligent temperature controller with a temperature control accuracy of ±2℃, achieving constant temperature control within the range of 400~500℃. The temperature sensing module uses a K-type thermocouple with a total of 4 sensing points, one on the outer surface of the upper panel, as shown. Figure 4 (a) TC#4; 3 on the outer surface of the back panel, see Figure 4 TC#1, TC#2, and TC#3 of (c) are designated as monitoring points 1, 2, and 3, respectively. To ensure close contact between the heating plate and the specimen surface, a 0.5 mm deep groove is cut into the outer surface of the upper panel of the specimen to embed thermocouples. All thermocouples are connected to a temperature acquisition instrument (Agilent, 34970) to record temperature data. In the insulation module, the specimen is wrapped with high-temperature resistant aerogel with a thickness of 20 mm to reduce lateral heat exchange between the specimen and the environment.

[0083] Before the experiment, the filled test piece was placed in a room temperature environment to ensure that the initial temperature of the test piece was uniform and consistent with the ambient temperature. Then, the cast copper heating plate was turned on, and the target temperature was set to 440℃ using a PID temperature controller. The heating plate temperature was stabilized and maintained for 30 minutes. Subsequently, the preheated heating plate was quickly moved to the upper panel of the test piece, and the data acquisition system was started to record the temperature changes of each thermocouple. Finally, when the lowest temperature value among the three monitoring points on the back panel reached 118℃ (the maximum safe operating temperature of paraffin wax), the heating plate power was immediately turned off and removed, and data acquisition was stopped to avoid paraffin wax decomposition. To reduce contact thermal resistance, thermally conductive silicone grease was evenly applied to the contact surface between the heating plate and the test piece.

[0084] Under constant temperature heating at 440℃, the temperature response of the back panel of the test piece is as follows: Figure 7 As shown, the temperature curves at both monitoring points on the outer surface of the back panel exhibit a clear plateau, reflecting the latent heat absorption during the solid-liquid phase transition of the phase change material. Monitoring point 1 is located at the center of the panel, avoiding the core rod connection point, while monitoring point 2 is located at the connection between the core rod and the panel; therefore, monitoring point 2 heats up faster. Comparing the experimental and simulated temperatures at monitoring point 2 (the simulation model considers the surrounding baffles), the overall trends are consistent, both exhibiting a three-stage temperature change characteristic. Although factors such as heat loss and contact thermal resistance cause some deviation between the experimental and simulated results, the deviation is within an acceptable range, verifying the accuracy of the numerical model.

[0085] This invention investigated the thermal insulation properties of an integrated aerogel and phase change material (PCM) lattice sandwich structure, and the main conclusions are as follows: 1) By constructing a three-dimensional transient heat transfer model coupling thermal conduction and phase change heat transfer, the heat transfer law inside the integrated thermal protection structure was revealed. It was found that the phase change layer can significantly absorb the heat flux caused by the thermal short-circuit effect of the core rod. Parametric studies show that there is an optimal value for the ratio of phase change layer thickness to insulation layer thickness. The temperature control time shows a trend of first increasing and then decreasing with the increase of PCM thickness: when the PCM layer thickness is too large, a large amount of heat enters the structure due to the weakening of the insulation layer; when the PCM layer thickness is too small, the back panel temperature rises rapidly due to insufficient heat storage capacity.

[0086] 2) The thermal protection performance of the composite filled lattice sandwich structure was verified by 3D printing to prepare high-temperature resistant titanium alloy test pieces and carry out high-temperature loading thermal insulation test. The experimental results were in good agreement with the numerical simulation results, which proved the accuracy of the numerical model.

[0087] 3) Three-objective optimization studies were conducted on temperature control time, areal density, and comprehensive mechanical properties. It was found that the temperature control effect was best when the PCM filling height was concentrated at 10-10.4mm (i.e., filling ratio 1:1). The rod diameter had the greatest impact on comprehensive performance, followed by the tilt angle, and the PCM height had the lowest dependence. The Pareto front clearly showed the trade-off relationship between the three objectives, and the prediction error of the optimized solution set was controlled within 10%.

[0088] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0089] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A lattice sandwich thermal protection structure for an aircraft, characterized in that, It includes a lattice sandwich structure, a thermal insulation layer, and a phase change thermal storage layer; The lattice sandwich structure includes an upper panel, a lower panel, and multiple lattice cores; the upper panel is used to withstand high-temperature heat sources, and the lower panel faces the interior of the aircraft body; multiple lattice cores are used to connect the upper panel and the lower panel to form a filling space; each lattice core includes multiple metal rods that are inclined and interconnected. The heat insulation functional layer and the phase change heat storage layer are disposed in the filling space. The heat insulation functional layer is adjacent to the upper panel, and the phase change heat storage layer is adjacent to the lower panel. The heat insulation functional layer is filled with heat insulation material, and the phase change heat storage layer is filled with phase change material. The filling thickness ratio of heat insulation material to phase change material is 1:

1.

2. The lattice sandwich thermal protection structure for an aircraft as described in claim 1, characterized in that, The thermal insulation layer is made of aerogel, and the phase change thermal storage layer is made of paraffin.

3. The lattice sandwich thermal protection structure for an aircraft as described in claim 1, characterized in that, The lattice sandwich structure is made of TC4 titanium alloy.

4. The lattice sandwich thermal protection structure for an aircraft as described in claim 1, characterized in that, The dot matrix core has a tetrahedral structure, the metal rod has a diameter of 1mm to 3mm, and the angle between the metal rod and the panel is 30° to 60°.

5. A design optimization method for a lattice sandwich thermal protection structure for an aircraft as described in any one of claims 1-4, characterized in that, Includes the following steps: A unit cell heat transfer numerical model of the lattice sandwich thermal protection structure is established, wherein the unit cell heat transfer numerical model includes only one lattice core. Using the diameter of the metal rod, the tilt angle of the metal rod, and the thickness of the phase change material filling as design variables, and taking the improvement of temperature control time, lightweight performance, and mechanical properties as optimization objectives, a multi-objective optimization problem is constructed. The multi-objective optimization problem is solved using a multi-objective genetic algorithm to obtain the Pareto optimal solution set, and the optimal combination of design variables for the thermal protection structure is determined based on the Pareto optimal solution set.

6. The design optimization method for a lattice sandwich thermal protection structure for an aircraft as described in claim 5, characterized in that, The multi-objective optimization problem is as follows: ； In the formula, f For a multi-objective optimization problem, f 1 represents the temperature control duration. f 2 is for lightweight performance, f 3 represents mechanical properties. x 1 represents the diameter of the metal rod. x 2 represents the inclination angle of the metal rod. x 3 represents the thickness of the phase change material filling.

7. The design optimization method for a lattice sandwich thermal protection structure for an aircraft as described in claim 6, characterized in that, The objective function for the temperature control duration is as follows: ； The objective function for the lightweight performance is as follows: ； The objective function for the mechanical properties is as follows: ； In the formula, E 33 For the equivalent elastic modulus, E s For elastic modulus, G 13 For equivalent shear modulus, σ 33 For equivalent yield strength, σ Y For the material's yield strength, τ 13 Equivalent shear strength, w 1= w 2= w 3= w 4 = 0.25.

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