A heat transfer simulation method and system based on shape memory fabric

Abstract

The present application relates to a kind of heat transfer simulation method and system based on shape memory fabric, it is related to shape memory fabric thermal simulation technical field, wherein, method includes: based on the point cloud data of SMF in heat source environment under the calculation of key feature parameters of SMF in complete deformation;Shape memory fabric system is constructed based on SMF, obtains the starting time, completion time of its deformation;Based on key feature parameters, the starting time, completion time of deformation, construct the SMF geometric model for reflecting the deformation process of SMF;Based on SMF geometric model and SMF geometric model related parameters, establish SMF transient heat transfer model;Based on SMF transient heat transfer model, the action law of the physical property parameter of shape memory fabric system to skin temperature and secondary burn time is calculated, to construct prediction equation.The present application prediction equation is used for the design of shape memory fabric SMF and the evaluation of heat transfer performance.

Description

Technical Field

[0001] This invention relates to the field of thermal simulation technology for shape memory fabrics, and in particular to a heat transfer simulation method and system based on shape memory fabrics. Background Technology

[0002] In fire rescue operations, the temperature at the fire scene can reach 400~2500℃. Although traditional protective clothing can provide basic protection, the heavy design not only increases the wearer's movement load and restricts their ability to move and work, but also easily causes heat accumulation, resulting in secondary skin damage.

[0003] Currently, the materials used in thermal protective clothing have a relatively mature manufacturing and application system in the industry. The material thickness and thermal insulation performance are designed according to existing protection standards. Traditional passive protective materials and clothing structures remain fixed after being shaped, making it difficult to adapt to changes in the external thermal environment. Moreover, they pay little attention to the generation of heat stress in the human body during wear, failing to achieve a dynamic balance between the external environment and the body's own heat dissipation needs. Shape memory materials (SMMs), on the other hand, have unique temperature response characteristics. After being shaped at high temperatures, they can freely change their shape after cooling, and completely return to their original shape after being reheated to their deformation temperature. When applied to thermal protective clothing, they mainly provide better thermal protection and comfort by expanding the air layer, offering a feasible solution to alleviate heat stress problems in fire rescue scenarios.

[0004] However, existing research only confirms that shape memory fabrics (SMFs) can form dynamic air layers between fabric layers through deformation under high-temperature environments, but the intrinsic relationship between their buckling wave structure characteristics and the deformed interlayer air layers remains unrevealed. Currently, there is a lack of quantitative understanding of the thickness, uniformity, and spatial distribution characteristics of the air layers under different buckling wave parameters, making it impossible to clarify the control mechanism of the fabric structure on the dynamic air layers and hindering the scientific optimization of thermal protection performance. On the other hand, under the influence of a heat source, the dynamic air layers of shape memory fabrics continuously change with time and temperature, resulting in a complex three-dimensional transient heat transfer process within the fabric. Current research has not yet clarified the physical mechanism of this dynamic heat transfer process, and the influence of key parameters such as heat source temperature, SMA diameter, spacing, SMF thermal conductivity, insulation layer thickness, and underlayer air layers on the heat transfer process and protective performance is also unclear, leading to a lack of in-depth theoretical explanation of the thermal protection mechanism of the entire dynamic thermal protection fabric system.

[0005] In summary, existing methods have failed to effectively reveal the heat transfer laws of shape memory fabric systems under the influence of multiple parameters, and it is difficult to design temperature-responsive dynamic thermal protection fabrics. Summary of the Invention

[0006] Therefore, the technical problem to be solved by the present invention is to overcome the problem that the existing technology cannot truly and effectively reveal the heat transfer law of shape memory fabrics, which makes it difficult to design temperature-responsive dynamic thermal protection fabrics.

[0007] To address the aforementioned technical problems, this invention provides a heat transfer simulation method based on shape memory fabric, comprising:

[0008] Step S1: Obtain point cloud data of different types of shape memory fabrics (SMFs) under full deformation in a heat source environment, and calculate key characteristic parameters of different types of shape memory fabrics (SMFs) under full deformation based on the point cloud data. The different types of shape memory fabrics (SMFs) are those with different diameters of shape memory alloy SMAs in the shape memory fabric (SMF), and / or different spacing between shape memory alloy SMAs, and / or different deformation directions of shape memory alloy SMAs.

[0009] Step S2: Construct a shape memory fabric system based on the shape memory fabric SMF, and obtain the start time and completion time of the deformation of the shape memory fabric system under heat exposure experiment;

[0010] Step S3: Based on the key feature parameters, the start time and completion time of deformation, construct an SMF geometric model to represent the deformation process of shape memory fabric (SMF);

[0011] Step S4: Import the SMF geometric model and related parameters into the simulation software, and establish the SMF transient heat transfer model through the simulation software;

[0012] Step S5: Based on the transient heat transfer model of the SMF, simulate and calculate the effect of the physical properties of the shape memory fabric system on skin temperature and the time of secondary burns. Construct a prediction equation based on the effect law. The prediction equation is used for the accurate design of shape memory fabric SMF and the evaluation of its heat transfer performance.

[0013] In one embodiment of the present invention, the method for calculating key characteristic parameters of different types of shape memory fabrics (SMFs) under full deformation based on the point cloud data in step S1 includes:

[0014] The point cloud data is denoised, and the denoised point cloud data is triangulated to construct a triangular mesh model of the shape memory fabric. The triangular mesh model is then converted into an XYZ three-dimensional coordinate system.

[0015] The triangular mesh model in the form of XYZ three-dimensional coordinate system is converted into discrete point cloud data, and several discrete points are obtained from the discrete point cloud data by curvature sampling, and the X, Y and Z spatial coordinates of the several discrete points are obtained.

[0016] Based on the buckling wave morphology of shape memory fabric (SMF) under full deformation, key characteristic parameters are calculated using the X, Y, and Z spatial coordinates of several discrete points. These key characteristic parameters include the vertical distance between the crest and adjacent trough of the buckling wave. Length of the half-cycle of the buckling wave .

[0017] In one embodiment of the invention, the vertical distance between the crest of the buckling wave and the adjacent trough is... Length of the half-cycle of the buckling wave They are represented as follows:

[0018] ;

[0019] in, Let Z be the arithmetic mean of the Z-axis coordinates of several discrete points near the wave crest region. It is the arithmetic mean of the Z-axis coordinates of several discrete points near the trough region;

[0020] ;

[0021] in, The arithmetic mean of the Y-axis coordinates of several discrete points near the wave crest region is given. It is the arithmetic mean of the Y-axis of several discrete points near the trough region.

[0022] In one embodiment of the present invention, step S2, which involves constructing a shape memory fabric system based on the shape memory fabric SMF and obtaining the start and end times of deformation of the shape memory fabric system under heat exposure experiments, includes the following method:

[0023] The heat insulation layer, shape memory fabric (SMF), waterproof and breathable layer, and protective outer layer are placed sequentially from top to bottom to form a shape memory fabric system, and the shape memory fabric system is fixed on the bracket;

[0024] Turn on the heat source and maintain its temperature above the deformation temperature of the shape memory alloy SMA. Then, instantly attach the support with the shape memory fabric system to the heat source.

[0025] Record a complete video of the entire process of the shape memory fabric SMF in the shape memory fabric system from heat exposure to deformation stabilization.

[0026] The moment when the first buckling fluctuation appears on the surface of the shape memory fabric (SMF) in the video is defined as the deformation initiation time. The moment when there is no visible deformation increment within a preset frame of continuous buckling fluctuation of the shape memory fabric (SMF) surface in the video is defined as the deformation completion time. .

[0027] In one embodiment of the present invention, step S3, which involves constructing an SMF geometric model to represent the deformation process of shape memory fabric (SMF) based on the key feature parameters, the start time and completion time of deformation, includes the following method:

[0028] During the dynamic deformation process of the shape memory fabric system, it is assumed that the deformation of the shape memory fabric SMF in the horizontal and vertical directions changes linearly with time, and the heat insulation layer on one side and the waterproof and breathable layer and protective outer layer on the other side of the shape memory fabric SMF are approximated as flat structures.

[0029] The deformation process of shape memory fabric (SMF) under heat exposure was simulated in multiple stages using software.

[0030] First, based on the key characteristic parameters of the shape memory fabric (SMF) under full deformation and the deformation completion time... After the thermal exposure ends, construct the fifth stage SMF geometric model under full deformation;

[0031] Secondly, the fifth-stage SMF geometric model is scaled proportionally along both the horizontal and vertical directions until it returns to a flat state. During the scaling process, four SMF geometric models with different deformation stages are constructed sequentially. Specifically, at the deformation initiation time... Time to completion of deformation Construct SMF geometric models for stages 4, 3, and 2, from time 0 to the deformation initiation time. The first stage SMF geometric model is constructed, and the deformation magnitude of the first to fifth stage SMF geometric models gradually changes from a flat state to complete deformation;

[0032] The SMF geometric models from stage 1 to stage 5 are arranged in reverse order of scaling, which corresponds to the complete process of shape memory fabric SMF gradually deforming from a flat state to full deformation.

[0033] In one embodiment of the present invention, the SMF geometric model in step S3 sequentially includes a heat source, a first air layer, a shape memory fabric system, a second air layer, and a skin layer. The shape memory fabric system includes, from bottom to top, a protective outer layer, a waterproof and breathable layer, a shape memory fabric SMF, and a heat insulation layer. The protective outer layer is close to the first air layer, and the heat insulation layer is close to the second air layer.

[0034] In one embodiment of the present invention, the SMF geometric model related parameters in step S4 include:

[0035] The heat source temperature, the physical properties of the shape memory fabric system, and the skin layer parameters are considered. Within the shape memory fabric system, two physical fields are coupled: solid heat transfer and surface-to-surface radiation. Within the corresponding air layers, fluid fields and heat transfer fields are considered. The fluid in the first air layer between the heat source and the outer protective layer adopts the physical fields of fluid heat transfer and turbulence-low Reynolds number k-ε. The fluid in the interlayer air layer within the shape memory fabric SMF and the second air layer between the insulation layer and the skin layer adopts the physical fields of fluid heat transfer and laminar flow. A biofield is applied within the skin layer.

[0036] In one embodiment of the present invention, step S4 further includes verifying the SMF transient heat transfer model, including:

[0037] The shape memory fabric system is simulated to be heated by a heat source in the software, and the temperature of the insulation layer of the SMF transient heat transfer model is statistically analyzed. At the same time, the shape memory fabric system is heated by a heat source in a real scenario, and the temperature of the actual insulation layer is measured.

[0038] When the temperature deviation between the insulation layer of the SMF transient heat transfer model and the actual insulation layer is less than the preset temperature range, it indicates that the SMF transient heat transfer model is consistent with the actual scenario. The SMF transient heat transfer model can simulate the heat transfer process of the actual shape memory fabric system, wherein the shape memory fabric system includes, from top to bottom, an insulation layer, shape memory fabric (SMF), a waterproof and breathable layer, and a protective outer layer.

[0039] In one embodiment of the present invention, the method for constructing the prediction equation in step S5 includes:

[0040] The transient heat transfer model of the SMF was simulated by heating with a first heat source and a second heat source respectively. The highest temperature at the skin interface and the start time of skin burn were taken as dependent variables, and the diameter of the shape memory alloy SMA in the shape memory fabric SMF, the spacing of the shape memory alloy SMA, the thermal conductivity of the shape memory fabric SMF, the thickness of the insulation layer, and the thickness of the second air layer were taken as independent variables to construct the prediction equation, which is expressed as follows:

[0041] ;

[0042] in, The temperature of the insulation layer under the first heat source is 1600 K. The skin interface temperature under the first heat source is 1600 K. The temperature of the insulation layer under the second heat source is 2600 K. The skin interface temperature under the second heat source is 2600 K. The time at which second-degree burns to the skin begin under a second heat source at 2600 K. The diameter of the shape memory alloy SMA The spacing of the shape memory alloy SMA arrangement. The thermal conductivity of shape memory fabric SMF is... For the thickness of the insulation layer, This represents the thickness of the second air layer.

[0043] To address the aforementioned technical problems, this invention provides a heat transfer simulation system based on shape memory fabric, comprising:

[0044] Calculation module: used to acquire point cloud data of different types of shape memory fabrics (SMFs) under full deformation in a heat source environment, and calculate key characteristic parameters of different types of shape memory fabrics (SMFs) under full deformation based on the point cloud data. The different types of shape memory fabrics (SMFs) are those with different diameters of shape memory alloy SMAs in the shape memory fabric (SMF), and / or different spacing between shape memory alloy SMAs, and / or different deformation directions of shape memory alloy SMAs.

[0045] Acquisition module: used to construct a shape memory fabric system based on the shape memory fabric SMF, and to acquire the start time and completion time of the deformation of the shape memory fabric system under heat exposure experiment;

[0046] First model construction module: used to construct an SMF geometric model that reflects the deformation process of shape memory fabric (SMF) based on the key feature parameters, the start time and completion time of deformation;

[0047] The second model construction module is used to import the SMF geometric model and related parameters into the simulation software, and to establish the SMF transient heat transfer model through the simulation software.

[0048] Prediction module: used to simulate and calculate the effect of the physical properties of the shape memory fabric system on skin temperature and time to secondary burns based on the transient heat transfer model of the SMF, and to construct prediction equations based on the effect. The prediction equations are used for the accurate design of shape memory fabric SMF and the evaluation of its heat transfer performance.

[0049] Compared with the prior art, the above-described technical solution of the present invention has the following advantages:

[0050] The heat transfer simulation method based on shape memory fabric described in this invention determines the distribution law of the dynamic air layer and calculates the core parameters of the buckling wave morphology of the shape memory fabric (SMF) under full deformation. (Vertical distance between the crest and the adjacent trough of the bend) and (The length of the half-cycle of the buckling wave), and a shape memory fabric system incorporating shape memory fabric SMF was constructed. The start time and completion time of the shape memory fabric SMF deformation were obtained through thermal exposure experiments, combined with parameters. and The SMF geometric model is constructed by taking the start and end times of the shape memory fabric SMF deformation, and a transient heat transfer model of SMF is constructed based on the SMF geometric model combined with various physical fields and physical property parameters.

[0051] This invention constructs a transient heat transfer model for SMF (Superficial Thermal Protective Fabric). By comparing the results of thermal protection performance tests with simulation results, the reliability of the model is verified, thus solving the problem of three-dimensional heat transfer simulation under dynamic air layer changes. This provides methodological support for in-depth research on the three-dimensional heat transfer mechanism of dynamic thermal protective fabrics, enriching and expanding the research content in this field.

[0052] This invention constructs a predictive equation that has been rigorously validated by experimental data and can be used for quantitative analysis. Through this predictive equation, the relationship between key physical properties of shape memory fabric systems, such as SMA diameter, arrangement spacing, and SMF thermal conductivity, and thermal protection performance can be systematically revealed, thereby effectively supporting the practical application of dynamic thermal protection fabrics. For heat source scenarios, the predictive equation can quickly screen the optimal combination of structural parameters that meets both thermal protection and comfort, significantly shortening the design cycle and reducing costs. At the same time, it can predict the performance compliance of fabrics with given parameters, clarify their application scenario boundaries, and effectively avoid the risks caused by using them beyond their permitted scope. Attached Figure Description

[0053] To make the content of this invention easier to understand, the invention will be further described in detail below with reference to specific embodiments and accompanying drawings.

[0054] Figure 1 This is a flowchart of the method in an embodiment of the present invention;

[0055] Figure 2 This is a point cloud data map of the shape memory fabric SMF in the fully deformed state exposed to a heat source in an embodiment of the present invention;

[0056] Figure 3 This is a model diagram after point cloud data processing in an embodiment of the present invention;

[0057] Figure 4 This is a discrete point cloud data map after establishing a coordinate system in an embodiment of the present invention;

[0058] Figure 5 This is a schematic diagram illustrating the measurement of key feature parameters of shape memory fabric in an embodiment of the present invention;

[0059] Figure 6 This is a schematic diagram of the shape memory fabric system structure in an embodiment of the present invention;

[0060] Figure 7 This is a phased diagram of the shape memory fabric in an embodiment of the present invention;

[0061] Figure 8 This is a phased SMF geometric model diagram of the shape memory fabric system in an embodiment of the present invention;

[0062] Figure 9 This is a verification curve of the simulated and actual values ​​of the shape memory alloy SMA fabric with a diameter of 0.3 mm and an arrangement spacing of 2 cm in the embodiment of the present invention.

[0063] Figure 10 This is a verification curve of the simulated and actual values ​​of the shape memory alloy SMA fabric with a diameter of 0.3 mm and an arrangement spacing of 2 cm in this embodiment of the invention.

[0064] Figure 11 This is a verification curve of the simulated and actual values ​​of the shape memory alloy SMA in fabric experiment 3 with a diameter of 0.3 mm and an arrangement spacing of 2 cm in this embodiment of the invention. Detailed Implementation

[0065] The present invention will be further described below with reference to the accompanying drawings and specific embodiments, so that those skilled in the art can better understand and implement the present invention. However, the embodiments described are not intended to limit the present invention.

[0066] Example 1

[0067] Reference Figure 1 As shown, this invention relates to a heat transfer simulation method based on shape memory fabric, comprising:

[0068] Step S1: Obtain point cloud data of different types of shape memory fabrics (SMFs) under full deformation in a heat source environment, and calculate key characteristic parameters of different types of shape memory fabrics (SMFs) under full deformation based on the point cloud data. The different types of shape memory fabrics (SMFs) are those with different diameters of shape memory alloy SMAs in the shape memory fabric (SMF), and / or different spacing between shape memory alloy SMAs, and / or different deformation directions of shape memory alloy SMAs.

[0069] Step S2: Construct a shape memory fabric system based on the shape memory fabric SMF, and obtain the start time and completion time of the deformation of the shape memory fabric system under heat exposure experiment;

[0070] Step S3: Based on the key feature parameters, the start time and completion time of deformation, construct an SMF geometric model to represent the deformation process of shape memory fabric (SMF);

[0071] Step S4: Import the SMF geometric model and related parameters into the simulation software, and establish the SMF transient heat transfer model through the simulation software;

[0072] Step S5: Based on the transient heat transfer model of the SMF, simulate and calculate the effect of the physical properties of the shape memory fabric system on skin temperature and the time of secondary burns. Construct a prediction equation based on the effect law. The prediction equation is used for the precise design of the shape memory fabric SMF and the preliminary evaluation of its heat transfer performance.

[0073] The following is a detailed description of this embodiment:

[0074] S1: Obtain point cloud data of shape memory fabric SMF composed of shape memory alloy SMA with different diameters and arrangement spacing under a fully deformed state exposed to a heat source environment by three-dimensional scanning technology, and obtain key characteristic parameters of shape memory fabric SMF under full deformation from the point cloud data.

[0075] It should be noted that the shape memory alloy SMA in this embodiment is filamentous, different diameters refer to the diameter of the filamentous SMA, and the arrangement spacing refers to the spacing between two adjacent filamentous SMA.

[0076] In one embodiment, the specific process of acquiring point cloud data using non-contact 3D scanning technology includes: First, placing the shape memory fabric (SMF) in a preset heat source environment. The heat source uses a black ceramic heating plate to simulate a low-radiation thermal environment, and the equipment strictly complies with the relevant environmental requirements for thermal protection performance testing in the ASTM F2731-18 testing standard. When the surface temperature of the shape memory fabric (SMF) reaches a critical threshold, it deforms and maintains a stable buckling wave shape.

[0077] The shape memory fabric (SMF) with a stable buckling wave morphology was instantly and smoothly fixed onto the testing platform to prevent deformation shifts caused by external forces. Subsequently, a handheld 3D scanner was used for non-contact scanning. Targeting the irregular curved surface characteristics of the fabric's buckling wave, multi-angle imaging and partitioned scanning modes were employed to acquire surface point cloud data, thereby obtaining... Figure 2 The preliminary geometric model of SMF is shown.

[0078] After scanning, the integrated raw point data (i.e., the preliminary SMF geometric model) is imported into Geomagic Wrap reverse engineering software for post-processing. First, data preprocessing is performed: environmental interference, redundant data points, and measurement error points are removed using the software's denoising function. Then, the denoised point cloud is simplified and optimized to improve subsequent data processing efficiency while ensuring the integrity of the fabric morphology. Next, to address typical defects such as holes and gaps that may exist in the preprocessed point cloud, a combination of automatic and manual repair methods is used to improve the model. After completion, a triangular mesh model of the fabric surface is generated through point cloud triangulation. Then, mesh smoothing and topology optimization are performed to improve the smoothness and structural integrity of the model. The preprocessed SMF preliminary geometric model is shown below. Figure 3 As shown.

[0079] In the data processing stage, the processed point cloud data (i.e., the pre-processed SMF preliminary geometric model) is converted into data in XYZ three-dimensional coordinate form. The specific operations are as follows:

[0080] (1) Identify and extract the reference plane of the initial geometric model of SMF through the "feature extraction" module of Geomagic Wrap software. Use the "align" function interface, select the "align to global" option, and in the pop-up parameter setting window, select the extracted reference plane as the reference plane of the coordinate system. At the same time, specify the warp direction as the X-axis, the weft direction of the fabric (the direction of alloy wire embedding) as the Y-axis, and the thickness direction as the Z-axis. After confirming that the parameter settings are correct, complete the calibration of the origin of the global space coordinates and the establishment of the XYZ three-dimensional coordinate system.

[0081] (2) Based on the established three-dimensional coordinate system, the optimized triangular mesh model is converted into discrete point cloud data using the "point cloud generation" module of Geomagic Wrap software. The discrete point cloud data after establishing the coordinate system is shown in the figure below. Figure 4 As shown in the figure. Several discrete points are obtained from the discrete point cloud data through curvature sampling. The sampling method is curvature sampling mode, and the sampling parameter is set to 100.

[0082] (3) Using the software's data export function, the generated point cloud data (i.e., the X, Y, and Z spatial coordinates of several discrete points) is exported as an .asc format file. During the export process, only the core data of the XYZ three-dimensional coordinates are retained, and non-coordinate-related redundant information such as color and normal vectors are removed. Finally, a CSV file is generated, with the three columns of data corresponding to the X, Y, and Z spatial coordinates of each sampling point on the fabric surface.

[0083] In the characteristic parameter measurement stage, key characteristic parameters are calculated based on the obtained X, Y, and Z spatial coordinates of several discrete points. Key characteristic parameters include the vertical distance between the buckling crests and adjacent troughs of the shape memory fabric. Length of the half-cycle of the buckling wave ,like Figure 5 As shown. The specific calculation is as follows:

[0084] (1) Measurement Distance: First, determine the measurement range. Within the region of the crest and trough, delineate a Y-axis coordinate interval that covers the complete meridional distribution of the crest and trough. The interval width is set to 5 mm (e.g., as follows). Several discrete points are selected, that is, a point is chosen every 5 mm in the peaks and troughs, in order to reduce To minimize computational errors, all data within the interval are used to ensure that all data cover the target feature area. Within the defined Y-axis coordinate interval, Z-axis coordinate data of the peak and adjacent trough regions are filtered and locked at 5 mm intervals to eliminate the influence of local point cloud fluctuations and random measurement errors on the parameters. The arithmetic mean of the Z-axis coordinates of the peak and trough regions is calculated and denoted as follows: and The final conclusion is:

[0085]

[0086] in, Let Z be the arithmetic mean of the Z-axis coordinates of several discrete points near the wave crest region. This is the arithmetic mean of the Z-axis coordinates of several discrete points near the trough region, all in mm, and the result is rounded to one decimal place.

[0087] (2) Measurement Distance: Based on the defined range above, calculate the arithmetic mean of the Y-axis of the peak and trough regions, denoted as . and The final conclusion is:

[0088]

[0089] in, The arithmetic mean of the Y-axis coordinates of several discrete points near the wave crest region is given. The result is the arithmetic mean of the Y-axis of several discrete points near the trough region, with the unit being mm, and the result is rounded to one decimal place.

[0090] For different types of shape memory fabrics, SMF was measured and calculated separately. and The value of .

[0091] S2: A heat exposure experiment was conducted, exposing the entire shape memory fabric system to a high-temperature environment and capturing images with a camera. Software was used to analyze frame-by-frame the start and completion times of deformation in different types of shape memory fabric systems. The specific operation procedure is as follows:

[0092] (1) First, place the heat insulation layer, shape memory fabric (SMF), waterproof and breathable layer and protective outer layer from top to bottom to establish the shape memory fabric system. Cut each layer of the shape memory fabric system to 200 mm × 200 mm and align and fix it. Fix the shape memory fabric system on the support so that the shape memory fabric system is in a vertical state.

[0093] (2) Subsequently, the heat source was turned on. After the heat source was preheated and stabilized, it was maintained at 150±5℃ (more than 30℃ above the deformation temperature of the shape memory alloy SMA). The support was then instantly pressed against the heat source. At the same time, a high-resolution camera (1920×1080 resolution, 30 fps frame rate) was used to record a 60-second video of the entire process of the shape memory fabric SMF in the shape memory fabric system from heat exposure to deformation stabilization. In order to reduce experimental error, the experiment was repeated 3 times under the same experimental conditions for shape memory fabric systems with different shape memory alloy SMA parameters (different diameters, different arrangement spacings).

[0094] (3) Import the above video into Premiere Pro software, split it frame by frame, and cut it. = 0 s until the deformation stabilizes. Define the deformation start time. The time at which the first identifiable buckling fluctuation appears on the surface of the shape memory fabric (SMF) is recorded; the time for deformation completion is specified. Based on the premise that there is no visible deformation increment on the surface buckling fluctuation of the shape memory fabric (SMF) within 10 consecutive frames, the corresponding time points are recorded. In addition, this embodiment can also calculate the deformation duration using the following formula:

[0095]

[0096] Take 3 experiments , , The average value is used as the final parameter.

[0097] S3: Key Feature Parameters of Shape Memory Fabric Systems and Deformation start time and completion time A five-stage SMF (Shape Memory Fabric) geometric model was constructed, representing the deformation process of the shape memory fabric (SMF). The model consists of a heat source, a first air layer, a shape memory fabric system, a second air layer, and a skin layer. The shape memory fabric system, from bottom to top, includes a protective outer layer, a waterproof and breathable layer, the SMF, and a heat insulation layer. The protective outer layer is located near the first air layer, and the heat insulation layer is located near the second air layer. The SMF geometric model is shown below. Figure 6 As shown. The specific operation process for constructing the SMF geometric model in 5 stages is as follows:

[0098] First, during the dynamic deformation process of the shape memory fabric system, it is assumed that the deformation of the shape memory fabric SMF in the horizontal and vertical directions changes linearly with time, and the heat insulation layer on one side (i.e., the upper layer) and the waterproof and breathable layer and protective outer layer on the other side (i.e., the lower layer) of the shape memory fabric SMF are approximated as flat structures.

[0099] The deformation process of shape memory fabric (SMF) under heat exposure was simulated in multiple stages using COMSOL software.

[0100] First, based on the key characteristic parameters of the shape memory fabric (SMF) under full deformation and the deformation completion time... After the thermal exposure ends, construct the fifth stage SMF geometric model under full deformation.

[0101] Secondly, in COMSOL software, the fifth-stage SMF geometric model is scaled proportionally along both the horizontal and vertical directions until it returns to a flat state. During the scaling process, four SMF geometric models with different deformation stages are constructed sequentially (e.g., Figure 7 As shown, Figure 7 (a) represents stage 5, (b) represents stage 4, (c) represents stage 3, and (d) represents stage 2. The deformation initiation time is... Time to completion of deformation Construct SMF geometric models for stages 4, 3, and 2, from time 0 to the deformation initiation time. The first stage SMF geometric model is constructed, and the deformation magnitude of the first to fifth stage SMF geometric models gradually changes from a flat state to complete deformation.

[0102] The SMF geometric models from stage 1 to stage 5 are arranged in reverse scaling order, corresponding to the complete process of shape memory fabric (SMF) gradually deforming from a flat state to full deformation, as detailed below. Figure 8 As shown, Figure 8 (a) represents stage 1, (b) represents stage 2, (c) represents stage 3, (d) represents stage 4, and (e) represents stage 5.

[0103] S4: The relevant parameters of the SMF geometric model are as follows:

[0104] In a multiphysics simulation environment, parameters including the heat source temperature (external heat source data is imported into COMSOL to make the simulated heat source close to the actual heat source), the physical properties of the shape memory fabric system, and the skin layer parameters are set. The physical fields of heat transfer and fluid flow, heat transfer and radiation are coupled to establish a transient heat transfer model for the SMF. This embodiment inputs various physical fields into COMSOL to make the simulation as close to reality as possible.

[0105] Regarding the material parameters, the density, thermal conductivity, emissivity, and constant-pressure heat capacity of the shape memory fabric system, the three air layers, and the skin layer were set. The thermal conductivity of the outer protective layer and the density and thermal conductivity of the air layers were both functions of temperature. Within the shape memory fabric system (equivalent to the fabric material), two physical fields—solid heat transfer and surface-to-surface radiation—were coupled. In the first air layer between the heat source and the outer protective layer, the fluid used a "fluid heat transfer" and "turbulent flow-low Reynolds number k-ε" physical field. In the interlayer air layers of the shape memory fabric system and the second air layer between the insulation layer and the skin layer, the fluid used a fluid heat transfer and laminar flow physical field. A biofield was applied within the skin layer. Simultaneously, "solid and fluid heat transfer" and "surface-to-surface radiation" were coupled into a "surface-to-surface radiation heat transfer" physical field. "Solid and fluid heat transfer," "turbulent flow-low Reynolds number k-ε," and "laminar flow" were each coupled into two independent non-isothermal flow physical fields.

[0106] S5: Protective performance test based on the SMF transient heat transfer model. In the software, the shape memory fabric system is simulated to heat using a heat source, and the insulation layer temperature of the SMF transient heat transfer model is recorded. Simultaneously, in a real-world scenario, the shape memory fabric system is heated using a heat source, and the actual insulation layer temperature is measured. When the temperature deviation between the insulation layer in the SMF transient heat transfer model and the actual insulation layer is less than a preset temperature range, it indicates that the SMF transient heat transfer model matches the actual scenario, and that the SMF transient heat transfer model can simulate the heat transfer process of the actual shape memory fabric system. During model verification, the skin layer is temporarily disregarded in the actual experimental scenario to ensure consistency between the boundary conditions of the experimental test and the simulation calculation.

[0107] In one embodiment, an accuracy verification experiment is conducted on the SMF transient heat transfer model. The specific steps of the verification experiment include:

[0108] A black ceramic heating plate was used as the heat source to simulate the low-radiative thermal environment of a forest fire scenario, and the experimental conditions conformed to ASTM F2731-18 standards. A 0.274 mm diameter T-type thermocouple (accuracy: 0.5 ℃) was used to detect temperature changes in the insulation layer. The data acquisition system used an NI-9213 data logger, coupled with a LabVIEW program, to record data at a sampling frequency of 10 Hz. The fabric system was fixed using a clamping device, and the T-type thermocouple was placed diagonally at the center of the insulation layer. During the experiment, the fabric system was first subjected to 150 s of continuous heat exposure, followed by a 150 s natural cooling phase with the support moved, and temperature changes were recorded synchronously throughout. To reduce experimental error, each experiment was repeated three times, and the average temperature of the three experiments was used as the measured data.

[0109] In the verification experiment, a shape memory fabric sample SMA with a diameter of 0.3 mm and an arrangement spacing of 2 cm was selected. A physical fabric system and a transient heat transfer model of SMF were constructed accordingly, and model verification tests were carried out.

[0110] from Figure 9 , Figure 10 , Figure 11 It can be seen that the actual insulation layer exhibits a temperature change trend that is basically consistent with that of experiments 1, 2, or 3. During the 0–150 s heat exposure phase, it shows a rapid temperature rise, approaching the peak temperature around 150 s. During the 150–300 s cooling phase, it simultaneously enters a slow cooling process. The temperature curves from the three repeated experiments are relatively concentrated, and the simulation curves closely match the experimental curves, further demonstrating that the SMF transient heat transfer model can simulate the heat transfer process of the shape memory fabric system. To quantitatively analyze the accuracy of the simulation and experimental results, three key time points were selected for analysis, and the relevant parameters are shown in Table 1. Table 1 shows that the standard deviation of the experimental data is less than 0.15 ℃, and the coefficient of variation is less than 0.3%. At the 150-second heat exposure endpoint, the simulated temperature was almost identical to the experimental average temperature, with a relative error of only 0.02%. The highest temperature in the simulation occurred at 160.8 seconds, with a value of 58.765 ℃, and the relative error between this and the experimental average highest temperature of 56.474 ℃ was 4.06%. This error was mainly due to the difference between the ideal time sequence of the shape memory alloy wire deformation in the model and the slight lag in the actual deformation time of the fabric in the experiment. At the 300-second cooling endpoint, the relative error was 1.69%, and the model could effectively reproduce the temperature decay process during the cooling stage.

[0111] Table 1 Comparison of key temperature parameters in the simulation and experiment of the insulation layer

[0112]

[0113] S6: Using the validated SMF transient heat transfer model, simulate and calculate the effect of the physical properties of the shape memory fabric system on skin temperature and secondary burn time, and output predictive equations for skin temperature and secondary burn time to guide the shape memory fabric system.

[0114] The prediction equation comprehensively considers the influence of SMA diameter, spacing, SMF thermal conductivity, insulation layer, second air layer thickness, and heat source temperature on thermal protection performance. An orthogonal design was used for a 5-factor, 4-level parametric simulation. A predictive model was established by performing multiple regression fitting analysis on the simulated skin temperature values ​​and secondary burn time with each parameter value. The factor levels are shown in Table 2.

[0115] Table 2 Factor Level Table

[0116]

[0117] Substituting the level values ​​of each factor into the transient heat transfer model of the temperature-responsive thermal protective fabric, and assigning temperatures of 1600 K and 2600 K to the heat source respectively, the insulation layer temperature and skin temperature under the corresponding test conditions were obtained through simulation calculations. The onset time of second-degree skin burns was then calculated using the Henriques skin burn prediction model. The final experimental results are shown in Tables 3 and 4. It should be noted that Table 3 did not reach the third-degree burn time, and some structural parameters in Table 4 did not reach the third-degree burn time; therefore, a prediction equation for the third-degree burn time was not constructed.

[0118] Table 3 Simulation results of SMF transient heat transfer model at a heat source temperature of 1600 K

[0119]

[0120] Table 4 Simulation results of SMF transient heat transfer model at a heat source temperature of 2600 K

[0121]

[0122] In the simulation results of the SMF transient heat transfer model, the highest temperature of the insulation layer, the highest temperature of the skin layer (epidermal-dermal layer) interface, and the onset time of skin burn were taken as dependent variables, respectively. The diameter of the shape memory alloy SMA in the shape memory fabric SMF was taken as the dependent variable. (mm), SMA (Stereostructured Memory Alloy) Alignment Spacing (cm), shape memory fabric SMF thermal conductivity kW / (m·K), insulation layer thickness (mm) and the thickness of the second air layer (mm) is the independent variable. After multiple linear fitting, the fitting analysis results are as follows:

[0123] in, The temperature of the insulation layer under a heat source of 1600 K. The skin interface temperature under a 1600 K heat source. The temperature of the insulation layer under a 2600 K heat source. The skin interface temperature under a 2600 K heat source. The time at which second-degree burns to the skin begin under a 2600 K heat source. The diameter of the shape memory alloy SMA The spacing of the shape memory alloy SMA arrangement. The thermal conductivity of shape memory fabric SMF is... For the thickness of the insulation layer, This represents the thickness of the second air layer.

[0124] The application method of shape memory fabrics based on the method provided in this embodiment is as follows:

[0125] (1) Rapid selection of structural parameters for dynamic thermal protection fabric systems. Based on the heat source temperature of the application scenario, a prediction model for the corresponding heat source is selected, and preset parameter ranges for SMA diameter, spacing, SMF thermal conductivity, insulation layer thickness, and second air layer thickness are input. The second air layer thickness is the core optimization focus; the insulation layer thickness is moderately optimized while reducing the optimization effort for the SMF thermal conductivity. Simultaneously, differentiated parameter design is implemented to match the heat source intensity: for medium-intensity heat sources, increasing the SMA diameter can indirectly increase the height of the interlayer air layer, enhancing the thermal insulation effect; for high-intensity heat sources, the SMA spacing is appropriately reduced to ensure the stability of the overall fabric structure. Based on this, the model is used to quickly calculate the core response index values ​​corresponding to various parameter combinations, thereby selecting the optimal parameter combination that simultaneously meets the multi-dimensional performance requirements of thermal protection and wearing comfort. This selection method can significantly reduce the R&D cycle of fabric structure design, effectively reduce the cost losses caused by repeated experiments, and improve design efficiency.

[0126] (2) Accurate prediction of thermal protection performance and assessment of scenario adaptability. For dynamic thermal protection fabrics with determined structural parameters, first verify whether the parameter values ​​are within the effective range of the model's independent variables. Substitute the parameters into the prediction model at the corresponding heat source temperature to calculate the predicted values ​​of the maximum temperature of the insulation layer, the maximum temperature of the skin layer interface, and the start time of second-degree skin burns. Compare the prediction results with the safety and comfort performance thresholds to determine whether the fabric meets the performance standards under the target heat source scenario, clarify its application scenario boundaries, and avoid the risk of thermal protection failure due to use beyond the scope.

[0127] Example 2

[0128] This embodiment provides a heat transfer simulation system based on shape memory fabric, including:

[0129] Calculation module: used to acquire point cloud data of different types of shape memory fabrics (SMFs) under full deformation in a heat source environment, and calculate key characteristic parameters of different types of shape memory fabrics (SMFs) under full deformation based on the point cloud data. The different types of shape memory fabrics (SMFs) are those with different diameters of shape memory alloy SMAs in the shape memory fabric (SMF), and / or different spacing between shape memory alloy SMAs, and / or different deformation directions of shape memory alloy SMAs.

[0130] Acquisition module: used to construct a shape memory fabric system based on the shape memory fabric SMF, and to acquire the start time and completion time of the deformation of the shape memory fabric system under heat exposure experiment;

[0131] First model construction module: used to construct an SMF geometric model that reflects the deformation process of shape memory fabric (SMF) based on the key feature parameters, the start time and completion time of deformation;

[0132] The second model construction module is used to import the SMF geometric model and related parameters into the simulation software, and to establish the SMF transient heat transfer model through the simulation software.

[0133] Prediction module: used to simulate and calculate the effect of the physical properties of the shape memory fabric system on skin temperature and time to secondary burns based on the transient heat transfer model of the SMF, and to construct prediction equations based on the effect. The prediction equations are used for the accurate design of shape memory fabric SMF and the evaluation of its heat transfer performance.

[0134] Example 3

[0135] This embodiment provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the heat transfer simulation method based on shape memory fabric described in Embodiment 1.

[0136] Example 4

[0137] This embodiment provides a computer-readable storage medium storing a computer program thereon. When the computer program is executed by a processor, it implements the steps of the heat transfer simulation method based on shape memory fabric described in Embodiment 1.

[0138] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. The solutions in the embodiments of this application can be implemented in various computer languages, such as the object-oriented programming language Java and the interpreted scripting language JavaScript.

[0139] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0140] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0141] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0142] Obviously, the above embodiments are merely illustrative examples for clear explanation and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations here. However, obvious variations or modifications derived therefrom are still within the scope of protection of this invention.

Claims

1. A heat transfer simulation method based on shape memory fabric, characterized in that, include: Step S1: Obtain point cloud data of different types of shape memory fabrics (SMFs) under full deformation in a heat source environment, and calculate key characteristic parameters of different types of shape memory fabrics (SMFs) under full deformation based on the point cloud data. The different types of shape memory fabrics (SMFs) are those with different diameters of shape memory alloy SMAs in the shape memory fabric (SMF), and / or different spacing between shape memory alloy SMAs, and / or different deformation directions of shape memory alloy SMAs. Step S2: Construct a shape memory fabric system based on the shape memory fabric SMF, and obtain the start time and completion time of the deformation of the shape memory fabric system under heat exposure experiment; Step S3: Based on the key feature parameters, the start time and completion time of deformation, construct an SMF geometric model to represent the deformation process of shape memory fabric (SMF); Step S4: Import the SMF geometric model and related parameters into the simulation software, and establish the SMF transient heat transfer model through the simulation software; Step S5: Based on the transient heat transfer model of the SMF, simulate and calculate the effect of the physical properties of the shape memory fabric system on skin temperature and the time of secondary burns. Construct a prediction equation based on the effect law. The prediction equation is used for the accurate design of shape memory fabric SMF and the evaluation of its heat transfer performance.

2. The heat transfer simulation method based on shape memory fabric according to claim 1, characterized in that: The method for calculating the key characteristic parameters of different types of shape memory fabrics (SMFs) under full deformation based on the point cloud data in step S1 includes: The point cloud data is denoised, and the denoised point cloud data is triangulated to construct a triangular mesh model of the shape memory fabric. The triangular mesh model is then converted into an XYZ three-dimensional coordinate system. The triangular mesh model in the form of XYZ three-dimensional coordinate system is converted into discrete point cloud data, and several discrete points are obtained from the discrete point cloud data by curvature sampling, and the X, Y and Z spatial coordinates of the several discrete points are obtained. Based on the buckling wave morphology of shape memory fabric (SMF) under full deformation, key characteristic parameters are calculated using the X, Y, and Z spatial coordinates of several discrete points. These key characteristic parameters include the vertical distance between the crest and adjacent trough of the buckling wave. Length of the half-cycle of the buckling wave .

3. The heat transfer simulation method based on shape memory fabric according to claim 2, characterized in that: The vertical distance between the crest and the adjacent trough of the buckling wave Length of the half-cycle of the buckling wave They are represented as follows: ； in, Let Z be the arithmetic mean of the Z-axis coordinates of several discrete points near the wave crest region. It is the arithmetic mean of the Z-axis coordinates of several discrete points near the trough region; ； in, The arithmetic mean of the Y-axis coordinates of several discrete points near the wave crest region is given. It is the arithmetic mean of the Y-axis of several discrete points near the trough region.

4. The heat transfer simulation method based on shape memory fabric according to claim 1, characterized in that: Step S2 involves constructing a shape memory fabric system based on the shape memory fabric SMF, and obtaining the start and end times of deformation of the shape memory fabric system under heat exposure experiments. The method includes: The heat insulation layer, shape memory fabric (SMF), waterproof and breathable layer, and protective outer layer are placed sequentially from top to bottom to form a shape memory fabric system, and the shape memory fabric system is fixed on the bracket; Turn on the heat source and maintain its temperature above the deformation temperature of the shape memory alloy SMA. Then, instantly attach the support with the shape memory fabric system to the heat source. Record a complete video of the entire process of the shape memory fabric SMF in the shape memory fabric system from heat exposure to deformation stabilization. The moment when the first buckling fluctuation appears on the surface of the shape memory fabric (SMF) in the video is defined as the deformation initiation time. The moment when there is no visible deformation increment within a preset frame of continuous buckling fluctuation of the shape memory fabric (SMF) surface in the video is defined as the deformation completion time. .

5. The heat transfer simulation method based on shape memory fabric according to claim 1, characterized in that: Step S3, which involves constructing an SMF geometric model to represent the deformation process of shape memory fabric (SMF) based on the key feature parameters, the start time of deformation, and the completion time of deformation, includes the following methods: During the dynamic deformation process of the shape memory fabric system, it is assumed that the deformation of the shape memory fabric SMF in the horizontal and vertical directions changes linearly with time, and the heat insulation layer on one side and the waterproof and breathable layer and protective outer layer on the other side of the shape memory fabric SMF are approximated as flat structures. The deformation process of shape memory fabric (SMF) under heat exposure was simulated in multiple stages using software. First, based on the key characteristic parameters of the shape memory fabric (SMF) under full deformation and the deformation completion time... After the thermal exposure ends, construct the fifth stage SMF geometric model under full deformation; Secondly, the fifth-stage SMF geometric model is scaled proportionally along both the horizontal and vertical directions until it returns to a flat state. During the scaling process, four SMF geometric models with different deformation stages are constructed sequentially. Specifically, at the deformation initiation time... Time to completion of deformation Construct SMF geometric models for stages 4, 3, and 2, from time 0 to the deformation initiation time. The first stage SMF geometric model is constructed, and the deformation magnitude of the first to fifth stage SMF geometric models gradually changes from a flat state to complete deformation; The SMF geometric models from stage 1 to stage 5 are arranged in reverse order of scaling, which corresponds to the complete process of shape memory fabric SMF gradually deforming from a flat state to full deformation.

6. The heat transfer simulation method based on shape memory fabric according to claim 1, characterized in that: The SMF geometric model in step S3 sequentially includes a heat source, a first air layer, a shape memory fabric system, a second air layer, and a skin layer. The shape memory fabric system includes, from bottom to top, a protective outer layer, a waterproof and breathable layer, a shape memory fabric (SMF), and a heat insulation layer. The protective outer layer is close to the first air layer, and the heat insulation layer is close to the second air layer.

7. The heat transfer simulation method based on shape memory fabric according to claim 6, characterized in that: The SMF geometric model parameters in step S4 include: The heat source temperature, the physical properties of the shape memory fabric system, and the skin layer parameters are considered. Within the shape memory fabric system, two physical fields are coupled: solid heat transfer and surface-to-surface radiation. Within the corresponding air layers, fluid fields and heat transfer fields are considered. The fluid in the first air layer between the heat source and the outer protective layer adopts the physical fields of fluid heat transfer and turbulence-low Reynolds number k-ε. The fluid in the interlayer air layer within the shape memory fabric SMF and the second air layer between the insulation layer and the skin layer adopts the physical fields of fluid heat transfer and laminar flow. A biofield is applied within the skin layer.

8. The heat transfer simulation method based on shape memory fabric according to claim 1, characterized in that: Step S4 further includes validating the SMF transient heat transfer model, including: The shape memory fabric system is simulated to be heated by a heat source in the software, and the temperature of the insulation layer of the SMF transient heat transfer model is statistically analyzed. At the same time, the shape memory fabric system is heated by a heat source in a real scenario, and the temperature of the actual insulation layer is measured. When the temperature deviation between the insulation layer of the SMF transient heat transfer model and the actual insulation layer is less than the preset temperature range, it indicates that the SMF transient heat transfer model is consistent with the actual scenario. The SMF transient heat transfer model can simulate the heat transfer process of the actual shape memory fabric system, wherein the shape memory fabric system includes, from top to bottom, an insulation layer, shape memory fabric (SMF), a waterproof and breathable layer, and a protective outer layer.

9. The heat transfer simulation method based on shape memory fabric according to claim 1, characterized in that: The method for constructing the prediction equation in step S5 includes: The transient heat transfer model of the SMF was simulated by heating with a first heat source and a second heat source respectively. The highest temperature at the skin interface and the start time of skin burn were taken as dependent variables, and the diameter of the shape memory alloy SMA in the shape memory fabric SMF, the spacing of the shape memory alloy SMA, the thermal conductivity of the shape memory fabric SMF, the thickness of the insulation layer, and the thickness of the second air layer were taken as independent variables to construct the prediction equation, which is expressed as follows: ； in, The temperature of the insulation layer under the first heat source is 1600 K. The skin interface temperature under the first heat source is 1600 K. The temperature of the insulation layer under the second heat source is 2600 K. The skin interface temperature under the second heat source is 2600 K. The time at which second-degree burns to the skin begin under a second heat source at 2600 K. The diameter of the shape memory alloy SMA The spacing of the shape memory alloy SMA arrangement. The thermal conductivity of shape memory fabric SMF is... For the thickness of the insulation layer, This represents the thickness of the second air layer.

10. A heat transfer simulation system based on shape memory fabric, characterized in that, include: Calculation module: used to acquire point cloud data of different types of shape memory fabrics (SMFs) under full deformation in a heat source environment, and calculate key characteristic parameters of different types of shape memory fabrics (SMFs) under full deformation based on the point cloud data. The different types of shape memory fabrics (SMFs) are those with different diameters of shape memory alloy SMAs in the shape memory fabric (SMF), and / or different spacing between shape memory alloy SMAs, and / or different deformation directions of shape memory alloy SMAs. Acquisition module: used to construct a shape memory fabric system based on the shape memory fabric SMF, and to acquire the start time and completion time of the deformation of the shape memory fabric system under heat exposure experiment; First model construction module: used to construct an SMF geometric model that reflects the deformation process of shape memory fabric (SMF) based on the key feature parameters, the start time and the completion time of deformation; The second model construction module is used to import the SMF geometric model and related parameters into the simulation software, and to establish the SMF transient heat transfer model through the simulation software. Prediction module: used to simulate and calculate the effect of the physical properties of the shape memory fabric system on skin temperature and secondary burn time based on the transient heat transfer model of the SMF, and to construct prediction equations based on the effect. The prediction equations are used for the accurate design of shape memory fabric SMF and the evaluation of its heat transfer performance.

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