A method, apparatus, and medium for three-dimensional heat transfer simulation of a clothing system

Abstract

The present application relates to a kind of clothing system three-dimensional heat transfer simulation method, equipment and medium, wherein the method comprises: obtaining the point cloud data of lying human body in naked, wearing pajamas and covering clothing three kinds of states by three-dimensional scanning technology respectively, and post-processing;Based on the body pressure distribution data, establish the geometric model of bed pillow and determine its contact area with human-clothing system, after adjusting the spatial position of both sides to match the contact area, execute the intersection Boolean operation of model contact site;After processing, the human body, clothing and bed pillow geometric model are assembled as a whole, and the human body model is divided into trunk section;Establish "human-clothing-environment" three-dimensional heat transfer model;Based on the segmented warm body dummy experimental data, the model is verified and optimized to ensure its prediction accuracy. Using the established model can systematically analyze the influence of clothing material parameters on skin temperature distribution and prediction equation, and provide theoretical basis and technical support for precise design and optimization of high-performance sleep clothing.

Description

TECHNICAL FIELD

[0001] The present application relates to the thermal performance design and evaluation of a sleep bedding system, in particular to a three-dimensional heat transfer simulation method, device and medium for a bedding system based on three-dimensional scanning and multi-physics simulation and verified by experiments. BACKGROUND

[0002] Sleep is a core physiological activity for maintaining the homeostasis of human body, and is essential for fatigue recovery and health protection. However, internal factors such as individual health and mental stress, and environmental factors such as noise, light, air temperature and humidity often lead to a decrease in sleep quality. Among the many environmental factors that affect sleep, poor thermal comfort is a key inducement. According to the ISO 7730 standard, thermal comfort refers to the subjective psychological state of satisfaction of the human body in the thermal environment. During sleep, the metabolic rate of the human body decreases significantly, and the body temperature regulation system is more sensitive. When the environmental temperature deviates from the thermal neutral zone of the human body, thermal discomfort is easily induced, which can cause multiple awakenings and interrupt the sleep structure. In this process, the microenvironment formed by the "bedding system" composed of the human body, bedding and bedding is more direct and significant in influencing the thermal comfort of the human body during sleep than the macro environment of the bedroom.

[0003] From the perspective of thermodynamic system, "human body-bedding-environment" is a complex and dynamically coupled system, and its thermal equilibrium state is determined by the body temperature regulation mechanism of the human body, the thermal physical properties of the bedding system, and the thermodynamic characteristics of the environment. The heat and moisture transfer process in this system involves multiple disciplines such as thermal physiology, heat transfer, fluid mechanics and textile material science. The research methods mainly include physical experiments and numerical simulations. Traditional physical experiment methods, such as thermal manikin test and real person experiment, have inherent limitations such as high cost, poor repeatability, and large influence of individual differences. At the same time, physical experiments rely on limited spatial point arrangement of sensors to obtain data, and it is difficult to fully and non-interferingly reveal the three-dimensional dynamic transfer mechanism inside the system.

[0004] With the development of computer technology, numerical simulation methods such as computational fluid dynamics provide a powerful tool for studying the heat exchange of the "human-environment" system. However, most existing simulation studies have significant shortcomings when simulating sleep scenarios: first, the model is often oversimplified and does not fully consider the overall clothing system consisting of a quilt, a mattress, a pillow and a garment worn during sleep, especially the key role of the thermal resistance distribution of the garment and the quilt in sleep heat transfer, resulting in a serious discrepancy between the model and the actual situation; second, the interface relationship and three-dimensional spatial form of the human body and the quilt, mattress and pillow have not been fully considered in the heat transfer of the entire system, and many models assume that the quilt and the garment have uniform thermal resistance, without considering the three-dimensional form between the human body and the clothing, resulting in poor simulation accuracy; third, there is a lack of systematic research and clear explanation of the internal mechanism of how the key parameters of the clothing system (such as quilt thickness and thermal conductivity) and environmental parameters (such as environmental temperature and air flow rate) work together to affect the three-dimensional thermal field distribution and dynamic changes of the sleep microclimate.

[0005] Therefore, there is an urgent need in the art for a research method that can accurately construct a numerical model containing the complete three-dimensional form of the "human-clothing-environment" system and systematically reveal the heat and moisture transfer rules of the clothing system under the synergistic action of multiple parameters, in order to provide reliable theoretical basis and technical support for the optimization design of high-performance and high-comfort clothing products. SUMMARY

[0006] The technical problem to be solved by the present application is to overcome the inability of existing clothing heat transfer simulation simulation technology in the prior art to truly reflect the overall clothing system consisting of a quilt, a mattress, a pillow and a garment worn during sleep, thereby accurately simulating the heat transfer between the clothing and the human body and the environment.

[0007] To solve the above technical problems, the technical solution adopted by the present application is:

[0008] A three-dimensional heat transfer simulation method for a clothing system, comprising the following steps:

[0009] S1: Obtain point cloud data of a lying human body in three states of nakedness, wearing a nightgown and covering a quilt through three-dimensional scanning technology, and perform reverse engineering post-processing on the point cloud data to construct a human body model and a clothing model;

[0010] S2: Establish a pillow geometry model and determine its contact area with the human-clothing system, and adjust the spatial positions of both parties to match the contact area, then perform intersection Boolean operation to complete the geometric assembly of the contact part;

[0011] S3: Assemble the processed human body model, clothing model, pillow and mattress model as a whole, and divide the human body model into multiple body segments according to the physiological structure;

[0012] S4: In a multi-physical field simulation environment, set the bedroom environment parameters, the clothing physical property parameters, and the human body sleep local heat flux parameters based on the body segment division, couple the heat transfer and fluid flow physical fields, the heat transfer and radiation physical fields, and establish a "human body-clothing-environment" three-dimensional heat transfer model;

[0013] S5: Based on the measured data obtained from the segmented warm body mannequin experiment, optimize and verify the three-dimensional heat transfer model until the simulation accuracy reaches a preset threshold;

[0014] S6: Use the verified three-dimensional heat transfer model to simulate and calculate the effect of clothing physical property parameters on skin temperature, and output a skin temperature prediction equation or analysis results for guiding clothing design.

[0015] The foregoing three-dimensional heat transfer simulation method of a clothing system, characterized in that the post-processing of the reverse engineering in step S1 includes the following steps performed in sequence:

[0016] Point cloud data processing stage, mainly for filtering and optimizing the point cloud data, deleting unnecessary data, noise data, overlapping data, and retaining necessary human body and clothing feature points;

[0017] Polygon data processing stage, converting the processed point cloud data into polygon data, and converting the human body and clothing into a geometric model composed of triangular faces;

[0018] Surface processing stage, used for converting the grid model into a smooth surface model.

[0019] The foregoing three-dimensional heat transfer simulation method of a clothing system, characterized in that the intersection Boolean operation between the contact part of the pillow geometric model and the human-clothing system in step S2 includes:

[0020] Adjust the spatial position of the human-clothing model and the pillow geometric model so that the cut human body model surface area is similar to the contact area determined in the body pressure distribution experiment;

[0021] Perform intersection Boolean operation on the human-clothing combination and the mattress-pillow combination in contact, and delete the overlapping volume inside the model after operation.

[0022] The foregoing three-dimensional heat transfer simulation method of a clothing system, characterized in that in step S3, the processed human body model, clothing model, pillow and mattress model are assembled and spatially aligned according to the actual sleep position in three-dimensional space to accurately reproduce the complete sleep system composed of "human body-clothing-pillow".

[0023] The three-dimensional heat transfer simulation method of a clothing system, characterized in that: in step S3, the human body model is divided into multiple body segments, including but not limited to: head, face, neck, shoulder, chest, abdomen, hips, upper arm, forearm, hand, thigh, lower leg, and foot, which can be combined as needed.

[0024] The three-dimensional heat transfer simulation method of a clothing system, characterized in that: in step S4, the local heat flux parameter of the human body during sleep is the dry heat flux density of the body surface when the human body is in a thermal neutral state, which is set based on the differences in metabolic rate and blood flow distribution of each body segment.

[0025] The determination of the dry heat flux density includes:

[0026] Based on a known human physiological heat regulation model, the total heat flux density and the evaporative heat flux density of each local area of the human body in a thermal neutral state during sleep are calculated.

[0027] The dry heat flux density is the difference between the total heat flux density and the evaporative heat flux density.

[0028] When the human body partition of the known human physiological heat regulation model is inconsistent with the human body partition of the target thermal manikin, the calculated heat flux density data is converted to local heat flux density matching the partition of the target thermal manikin based on the proportional relationship of heat conservation and the area of each local body surface.

[0029] The three-dimensional heat transfer simulation method of a clothing system, characterized in that: in step S5, the measured data includes at least the local skin temperature of the human body, the temperature of the space under the quilt, and the temperature of the outer surface of the quilt.

[0030] The optimization specifically adjusts the key physical parameters or boundary conditions in the three-dimensional heat transfer model based on the measured data to control the relative error between the local part simulation data and the measured data within 3%.

[0031] The three-dimensional heat transfer simulation method of a clothing system, characterized in that: in step S6, the skin temperature prediction equation is:

[0032] ;

[0033] Where T sk,i is the skin temperature, T a is the ambient temperature, v a is the air flow rate, D is the thickness of the quilt, k is the thermal conductivity of the quilt, and the intercept h and the regression coefficients a, b, c, d are determined by taking the skin temperature as the dependent variable, the ambient temperature T a , the air flow rate v a, quilt thickness D, quilt thermal conductivity k as independent variables, through multivariate linear fitting.

[0034] An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the three-dimensional heat transfer simulation method of the clothing system when executing the computer program.

[0035] A computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the three-dimensional heat transfer simulation method of the clothing system.

[0036] The beneficial effects of the present application are:

[0037] 1. The present application constructs a complete sleep system geometric model including "human body-clothing (including clothes and quilt)-bed pillow" through three-dimensional scanning and reverse engineering, and performs accurate spatial Boolean operation on the contact part. This technical solution completely overcomes the simulation distortion problem caused by ignoring the clothes worn during sleep and simplifying the contact interface of the mattress in the existing model, especially making it possible to simulate the complex scene of multi-layer dressing in winter sleep, and providing an unprecedented high-fidelity model basis for revealing the three-dimensional heat transfer mechanism in the real sleep environment.

[0038] 2. The present application sets non-uniform body surface dry heat flux in the thermal neutral state for the divided multiple physiological segments (such as head, trunk, limbs, etc.) based on the differences in metabolic rate and blood flow distribution of each body segment. This parameter setting method driven by heat physiology makes the model more realistically simulate the thermal regulation response of the human body in the sleep state, and improves the physiological significance and accuracy of the simulation results from the source.

[0039] 3. The present application constructs a reliable simulation prediction tool that can be used for quantitative analysis and is strictly verified by experimental data (error controlled within 3%). Through the model, the internal action mechanism between key physical property parameters such as quilt thickness and thermal conductivity and sleep microenvironment heat transfer can be systematically revealed, thereby providing accurate quantitative basis for performance prediction, material selection and structure optimization of the clothing system. This effectively overcomes the traditional trial-and-error physical experiment development mode, and significantly improves the development efficiency and design success rate of high-performance clothing products. BRIEF DESCRIPTION OF DRAWINGS

[0040] Figure 1 The flowchart of the establishment and application method of the three-dimensional heat transfer simulation method of the clothing system in the embodiments of the present application;

[0041] Figure 2The body in a natural lying posture, the body in a lying posture wearing a nightgown and the whole set of bedding covering the body surface in the three-dimensional heat transfer simulation method of the bedding system in an embodiment of the present application;

[0042] Figure 3 The three-dimensional point cloud data graph of the body in a natural lying posture, the body wearing a nightgown and the outer surface of the covered bedding system in the three-dimensional heat transfer simulation method of the bedding system in an embodiment of the present application;

[0043] Figure 4 The model graph after point cloud data processing in the three-dimensional heat transfer simulation method of the bedding system in an embodiment of the present application;

[0044] Figure 5 The model graph after polygon data processing in the three-dimensional heat transfer simulation method of the bedding system in an embodiment of the present application;

[0045] Fig. 6(a) is a process graph of precise surface formation of the body in the three-dimensional heat transfer simulation method of the bedding system in an embodiment of the present application;

[0046] Fig. 6(b) is a process graph of precise surface formation of the clothing in the three-dimensional heat transfer simulation method of the bedding system in an embodiment of the present application;

[0047] Fig. 6(c) is a process graph of precise surface formation of the quilt in the three-dimensional heat transfer simulation method of the bedding system in an embodiment of the present application;

[0048] Fig. 7(a) is a body pressure distribution measurement site and a measured body pressure distribution graph in the three-dimensional heat transfer simulation method of the bedding system in an embodiment of the present application;

[0049] Fig. 7(b) is a relative position determination between the body and the mattress model and a contact area graph in the three-dimensional heat transfer simulation method of the bedding system in an embodiment of the present application;

[0050] Figure 8 The combined model trunk division and local area division graph of the body and the clothing in the three-dimensional heat transfer simulation method of the bedding system in an embodiment of the present application;

[0051] Figure 9 The "body-bedding-environment" geometric model graph in the three-dimensional heat transfer simulation method of the bedding system in an embodiment of the present application;

[0052] Figure 10 The bedding internal temperature sensor placement point in the three-dimensional heat transfer simulation method of the bedding system in an embodiment of the present application;

[0053] Figure 11The three-dimensional heat transfer simulation method of the bedding system in the embodiment of the present application is placed at a point under the outer temperature sensor in an embodiment;

[0054] Figure 12 The physical experimental measurement value and the simulation value of the temperature of the lower micro-space in the three-dimensional heat transfer simulation method of the bedding system in the embodiment of the present application in an embodiment;

[0055] Figure 13 The temperature value of the outer surface of the quilt in the physical experiment and the numerical simulation in the three-dimensional heat transfer simulation method of the bedding system in the embodiment of the present application in an embodiment;

[0056] Fig. 14(a) is a trend graph of the local skin temperature of the human arm, chest, abdomen, waist, hip, thigh and calf changing with the thickness of the quilt in the three-dimensional heat transfer simulation method of the bedding system in the embodiment of the present application in an embodiment;

[0057] Fig. 14(b) is a trend graph of the average skin temperature of the human torso changing with the thickness of the quilt in the three-dimensional heat transfer simulation method of the bedding system in the embodiment of the present application in an embodiment. DETAILED DESCRIPTION

[0058] In order to make the content of the present application more easily understood, the present application will be further described in detail below according to the specific embodiments of the present application and in conjunction with the accompanying drawings. Embodiment 1

[0059] The present application provides a heat transfer simulation method of a bedding system, comprising:

[0060] S1: obtaining point cloud data of a lying human body in three states of nakedness, wearing pajamas and covering quilted clothing by three-dimensional scanning technology, and performing reverse engineering post-processing on the point cloud data to construct a human body model and a bedding model;

[0061] S2: establishing a pillow geometric model based on physical experimental data such as body pressure distribution and determining the contact area thereof with the human-body-bedding system, then adjusting the spatial positions of both parties to match the contact area, and performing intersection Boolean operation to complete the geometric assembly of the contact part;

[0062] S3: assembling the processed human body model, bedding model, pillow and mattress model as a whole, and dividing the human body model into multiple trunk segments according to physiological structure;

[0063] S4: in a multi-physical field simulation environment, setting parameters including bedroom environment parameters, bedding physical property parameters, and human body sleep local heat flux parameters based on the trunk segment division, coupling heat transfer and fluid flow physical fields, and establishing a three-dimensional heat transfer model of “human body-bedding-environment”;

[0064] S5: Based on the measured data obtained by the segmented thermal manikin experiment, the three-dimensional heat transfer model is optimized and verified until the simulation accuracy reaches the preset threshold;

[0065] S6: Using the verified three-dimensional heat transfer model, the effect of clothing physical parameters on skin temperature is simulated and calculated, and a skin temperature prediction equation or analysis result is output to guide the design of clothing.

[0066] The following will introduce the embodiment in detail:

[0067] As shown in Figure 1 , Figure 1 The flow chart of the establishment of the clothing system heat transfer simulation method provided by the present application, the steps include:

[0068] S1: Obtain the three-dimensional point cloud data of the human body model in a natural lying posture, the lying posture human body model wearing pajamas and the outer surface of the whole set of clothing covering on the body surface by non-contact three-dimensional scanning technology. Then, the point cloud data is processed by reverse engineering, and the human body model and the clothing model are constructed.

[0069] In one embodiment, the specific process of obtaining the geometric model by non-contact three-dimensional scanning technology includes: first, paste scanning positioning point stickers on the surface of the lying posture thermal manikin to assist the scanner to quickly position and data splicing; then, use a high-precision HandySCAN handheld three-dimensional laser scanner (resolution: 0.050 mm, accuracy: 0.030 mm) to perform whole body scanning in the order of from head to foot and from back to front, and obtain a high-fidelity initial human body geometric model. Let the manikin repeat the above positioning point pasting and system scanning process in the conditions of wearing pajamas and wearing pajamas and covering quilt, and finally obtain the three-dimensional point cloud data of the naked human body in a natural lying posture, the human body wearing pajamas and the outer surface of the whole set of clothing covering on the body surface. Figure 2 The natural lying posture human body, the lying posture human body wearing pajamas and the whole set of clothing covering on the body surface, Figure 3 The three-dimensional point cloud data of the naked human body in a natural lying posture, the human body wearing pajamas and the outer surface of the whole set of clothing covering on the body surface obtained by scanning.

[0070] Then, the scanned.obj point cloud data model is imported into Geomagic Wrap 2021 reverse engineering software for post-processing to convert the original rough scanning data into accurate, complete and usable three-dimensional models, so that they finally meet the calculation requirements of finite element analysis. The post-processing includes three stages of point cloud data processing, polygon data processing and surface processing.

[0071] Point cloud data processing stage:

[0072] ① Delete "non-connecting items" and "in vitro isolated points", delete point cloud data of non-target objects;

[0073] ② Reduce scanning noise points formed by slight shaking of the hand or shaking of the dummy during scanning;

[0074] ③ Keep necessary human and clothing feature points, delete overlapping point clouds, reduce point cloud quantity, and improve calculation efficiency. Default interval setting and curvature priority, maintain boundaries;

[0075] ④ Keep the original data, delete the smallest component, and the default maximum number of triangles is 3,200,000, and the highest quality is executed.

[0076] Polygon data processing stage:

[0077] ① Convert point cloud data to polygon data, and convert the human body and clothing into a geometric model composed of triangular surfaces;

[0078] ② Adjust the coordinate system of the system where the human body and clothing are located, with the center of the human hip as the coordinate origin, the height direction of the human body and clothing as the z-axis, and the cross-sectional direction as the x-axis;

[0079] ③ Use the plane clipping tool to divide the human body and clothing into two symmetrical parts along the dummy centerline, and delete the right part and keep the left part;

[0080] ④ Select the appropriate curvature to fill the missing holes in the scanning process to form a complete closed human body contour;

[0081] ⑤ Remove the concave and convex parts of the dummy surface abdomen, arms, legs, and joint connections, and use the polygon repair tool to repair the secondary holes on the surface of the dummy and the rough surface of the clothing to form smooth human body and clothing curves;

[0082] ⑥ Symmetrically process the divided left half dummy model to generate a complete human body and clothing model;

[0083] ⑦ Check for non-manifold edges, high refraction edges, spikes, small holes, etc. in each model and automatically repair them;

[0084] ⑧ Reduce the number of triangular surfaces, reduce the model size while ensuring model accuracy, and improve the efficiency of subsequent numerical simulation operations; Relax the grid to make the grid smoother.

[0085] Surface processing stage:

[0086] ① Detect and edit contour lines: define curvature sensitivity, delimiter sensitivity, and minimum area to automatically detect contour lines. Adjust the contour lines through the contour line editing tool;

[0087] ② Surface Patch and Grating Processing: Surface patches are constructed using automatic estimation, and surface patch repair tools are used to correct surfaces with intersecting paths or excessively large angles. Grating tools are used to divide the human body and clothing surfaces into grids.

[0088] ③ Generate accurate NURBS surfaces;

[0089] Export the processed human body and clothing surface model as a model file. Figure 4 This is a model diagram after processing point cloud data; Figure 5 Figure 6(a), Figure 6(b), and Figure 6(c) are diagrams of the process of accurate surface rendering.

[0090] S2: Based on physical experimental data, a simplified geometric model of the pillow and mattress is established, and the contact area between the pillow and the human bedding system is calculated. Then, spatial Boolean operations are used to complete the geometric assembly of the contact points, ultimately simulating the sleep contact interface. The solution for the contact area between the pillow / bedroom geometric model and the human bedding system is based on body pressure distribution measurements. The spatial Boolean operations between the mattress and the human model include: adjusting the spatial positions of the human model, bedding model, mattress model, and pillow model so that the surface area of ​​the cut human model is close to the contact area determined in the body pressure distribution experiment; performing an intersection Boolean operation on the human-bedding assembly and the mattress-pillow assembly in contact, and deleting the overlapping volumes within the models after the operation.

[0091] In one embodiment, a corresponding cuboid geometry is created in numerical simulation software based on the actual dimensions (mattress: 160 cm × 220 cm × 20 cm; pillow: 80 cm × 45 cm × 10 cm) as a preliminary model of the mattress and pillow.

[0092] Subsequently, the spatial relative positions of the human-clothing assembly with the mattress and pillow are determined. The process for determining the relative positions of the human model and mattress model and assembling the models is as follows: The contact area between the human body and the mattress is indirectly determined using the body pressure distribution measurement method, and the relative positions of the two are deduced from this.

[0093] Firstly, the body pressure sensor BPMS (body pressure measure system, Tekscan, USA) was laid on the surface of the mattress, and the human body was laid on the body pressure sensor. The measurement and recording time was 3 min, the sampling rate was 8 f / s, and the test pressure was recorded in units of KPa. The spacing of the sensor matrix on the pressure pad was 1.061 cm. After the body pressure data was collected, a pressure matrix was formed and saved as a.csv file. The number of matrixes with pressure display parts was calculated using Excel software, and the contact area between the human body model and the mattress was obtained by multiplying the area of a single sensor matrix. This operation was repeated three times to finally determine the contact area.

[0094] Then, the spatial position of the human body model was adjusted in the Geomagic Wrap software using the moving function to make the lower surface of the human body model tangent to the xy plane. By adjusting the position of the plane along the positive direction of the z axis, the area of the cut human body model surface was similar to the contact area determined in the body pressure distribution experiment, thereby determining the relative position of the human body model and the mattress model. The human body-clothing combination with the determined spatial position and the mattress-pillow combination were imported into the COMSOL numerical simulation software. To simulate the contact state during sleep, a Boolean difference operation was performed: along the surface of the dummy back, the volume coinciding with the human body was subtracted from the mattress and pillow geometry, thereby accurately generating the contact interface after being pressed, and automatically removing all overlapping parts of the geometry to avoid conflicts during meshing.

[0095] To simplify the calculation and focus on the heat transfer research of the clothing system, the model sets the mattress and pillow as thermal insulators, ignoring their own heat transfer effects. FIG. 7(a) is the body pressure distribution measurement site and the measured body pressure distribution diagram, and FIG. 7(b) is the determination of the relative position between the human body and the mattress model and the contact area diagram.

[0096] S3: The high-quality human body model, clothing model, pillow model, and mattress model obtained by the foregoing steps are assembled and spatially aligned according to the actual sleeping position in the three-dimensional space to accurately reproduce the complete sleep system composed of “human body-clothing-mattress and pillow”. The human body model is divided into multiple body segments. The multiple body segments include: head, face, neck, shoulder, chest, abdomen, hips, upper arm, lower arm, hand, thigh, lower leg, and foot.

[0097] In one embodiment, to facilitate the definition of heat transfer parameters of different sections of the human body in the simulation and the collection and analysis of data of the local human body and the quilt microenvironment, the study divides the human body-clothing combination model into body segments according to the Newton human body surface partitioning method using the segmentation tool in COMSOL, and also divides the quilt into local regions. The divided model is as shown in Figure 8 ​

[0098] S4: In the multi-physical field simulation environment, the parameters of the bedroom environment, the parameters of the clothing and bedding, and the parameters of the local heat flux of the human body in sleep based on the division of the body segments are set. The parameters of the local heat flux of the human body in sleep are the dry heat flux density of the body surface in the heat neutral state of the human body based on the differences in the metabolic rate and blood flow distribution of each body segment.

[0099] To accurately simulate the heat transfer process between the human body in sleep and the clothing and bedding system in the bedroom, the heat transfer mechanism of the body surface of the human body in sleep is analyzed. The body surface area exposed to the air exchanges heat with the surrounding air by convection, and the heat exchange efficiency depends on the flow pattern of the air. The body surface area in contact with the mattress exchanges heat with the mattress by conduction. It is assumed that the thermal resistance of the mattress is extremely large, and the effect of conduction heat dissipation will be very limited. In addition, there is also heat energy transmission in the form of electromagnetic wave radiation between the body surface temperature and the wall surface of the climate chamber. When the wall surface temperature is lower than the body surface temperature, the heat transfer direction is from the body surface to the wall surface. When calculating the local heat flux density of the body surface, it is considered that the evaporation heat dissipation generated by the sweat secretion of the human body in sleep has a limited effect on maintaining the heat balance in the state of maintaining thermal comfort. The heat exchange between the environment and the body surface is mainly in the form of dry heat (such as convection and radiation heat transfer), so the simulation only considers the dry heat transfer of the body surface, and does not discuss the heat transfer process generated by the evaporation latent heat and sweat heat dissipation. Therefore, the clothing and bedding system model is coupled with the physical fields of heat transfer and fluid flow, heat transfer and radiation, and a three-dimensional heat transfer model of “human body-clothing and bedding-environment” is established. Among them, the physical fields include solid heat transfer field, fluid heat transfer field, turbulent flow field, radiation heat transfer physical field, and non-isothermal flow physical field.

[0100] In one embodiment, for the radiation heat transfer between the human body surface and the clothing surface, the mattress surface, and the wall surface of the climate chamber, a surface-to-surface (S2S) radiation model is used to calculate the heat transfer model coupled with the surface-to-surface radiation heat transfer model. The radiation model is suitable for describing the radiation heat transfer between the inner surfaces of an enclosed body, and does not involve the internal medium, which meets the heat transfer simulation conditions.

[0101] The standard k -ε model and heat transfer model were coupled to calculate the non-isothermal flow and heat transfer model for convective heat transfer. The standard k -ε model can well simulate the fluid flow in the fully developed turbulent flow region, and the approximate estimate is given by the empirical function for the transition region with low Reynolds number and near the wall. The thickness of the quilt and clothing was measured by a digital fabric thickness tester (according to GB / T3820 standard), the mass of the fabric sample was measured by an electronic balance (referring to GB / T 4669-2008 standard) and the density was converted, the thermal conductivity was measured by a REFOND cold feeling and thermal conductivity tester (according to GB / T 11048-2018 standard), and the specific heat capacity was measured by a DSC differential calorimeter (referring to GB / T 19466-2004 standard). The whole sample was placed in the crucible of the equipment for measurement. The measured values of the related material properties of the quilt and clothing system used in the simulation are shown in Table 1, and the material properties used in the simulation are set as follows.

[0102] Table 1

[0103]

[0104] The boundary condition setting includes fluid flow variables and boundary heat variables. The calculation domain of the quilt and clothing system model is the human body, quilt and clothing, mattress and bedroom environment. The related values of the human body, quilt and clothing system, mattress surface, bedroom wall and air outlet are defined.

[0105] (1) Human body

[0106] According to the surface characteristics of the human body, the surface emissivity of the human body is set to 0.95. The local heat flux parameter of the human body during sleep is the body surface dry heat flux density of the human body in the heat neutral state, which is set based on the metabolic rate and blood flow distribution of each body segment. The determination of the body surface dry heat flux density is based on the Fiala human body thermal regulation model, which calculates the total heat flux density and evaporation heat flux density of each local area of the human body in the heat neutral state of sleep. The dry heat flux density qdryis the difference between the total heat flux density qtotand the evaporation heat flux density qevap. q dry q sk q esk Since the human body partition of the Fiala thermal regulation model is not consistent with the human body partition in the quilt and clothing heat transfer model, the local heat flux density suitable for the human body in the heat transfer model is calculated based on the proportion of the heat conservation and the local body surface area. Table 2 gives the local body surface area S i in the Fiala model, and Table 3 gives the local total heat flux density q sk,i , evaporation heat flux density q esk,i and dry heat flux density q dry,i ​​The local heat Q is calculated from equation 1 i The local heat flux q is calculated from equation 2, combined with the distribution of the body surface area A of each part of the body in the heat transfer model i (see Table 4) and equation 2. i。

[0107] (1)

[0108] (2).

[0109] Table 2

[0110]

[0111] Table 3

[0112]

[0113] Table 4

[0114]

[0115] (2) Clothing system

[0116] The quilt and the clothing are set as thin layer structures, and the properties of the thin layer materials of the quilt and the clothing are defined according to the test results of the fabric properties. The quilt surface layer and the clothing are both cotton fabrics, and the radiation emissivity is set to 0.8.

[0117] (3) Mattress surface

[0118] It is pointed out by research that the thermal resistance of the mattress is extremely high, and the heat dissipation through the mattress is only about 3% of the total heat dissipation. In order to reduce the calculation cost, the mattress is often regarded as adiabatic in the numerical simulation of the heat transfer of the body surface of the sleeping human body, and the conduction heat dissipated from the body surface through the mattress is ignored. The mattress surface is wrapped with cotton fabric, and the emissivity is set to 0.8.

[0119] (4) Wall surface of the bedroom

[0120] The temperature of the wall surface in the bedroom depends on the temperature of the surrounding air, and the ambient temperature is 12 ℃. It is assumed that there is no heat exchange between the indoor and outdoor, and therefore the wall surface is set as adiabatic. The wall surface material is set in reference to the material properties of the wall surface of the artificial climate chamber, and the emissivity of the wall is defined as 0.05.

[0121] (5) Air outlet and inlet

[0122] The air outlet and inlet are set as shown in Figure 9 , and the indoor wind speed is set to 0.2 m / s. In addition, all the geometric space domains are divided by the symmetrical surface, so that the calculation amount is reduced by half, and the simulation calculation efficiency is improved.

[0123] S5: Based on the measured data obtained by the segmented warm body dummy experiment, the three-dimensional heat transfer model is optimized and verified until its simulation accuracy reaches the preset threshold. Among them, the measured data at least includes human local skin temperature, bedding microspace temperature and quilt outer surface temperature. Human body surface skin temperature is the primary verification index, which can provide key data support for human sleep thermal comfort research. Secondly, the temperature of the bedding microenvironment during human sleep also has an important influence on the heat transfer between the human body and the microenvironment, and is therefore an essential verification index.

[0124] In one embodiment, the segmented warm body dummy experiment process is as follows:

[0125] ① Turn on the total switch of the climate chamber, close the climate cabin door and the indoor light, and adjust the temperature of the climate cabin to 12 ± 0.5 ℃ and the relative humidity to 60 ± 5% according to the daily indoor environment in winter;

[0126] ② Observe the temperature change of the climate cabin and wait for the temperature of the climate cabin to stabilize at 12 ± 0.5 ℃ and the relative humidity to stabilize at 60 ± 5%;

[0127] ③ Enter the climate cabin to put on pure cotton pajamas on the warm body dummy, and place the dummy on the mattress in a supine position with hands on both sides of the body. Use medical tape to fix the temperature probe heads of the temperature sensors in the air respectively between the arms and the torso, on the outside of the arms, between the legs, on the outside of the legs, and on the feet, as shown in Figure 10 , and measure and record the specific coordinates of the temperature measurement points at the same time. Finally, cover the dummy limbs and body torso with a down quilt. Use a yellow three-dimensional cutting marker to mark six temperature measurement points, 1, 2, 3, 4, 5, and 6, on the outer surface of the quilt, and use medical tape to fix the temperature probe heads of the temperature sensors at the six points to measure the temperature distribution on the outer surface of the quilt, as shown in Figure 11 ;

[0128] ④ Close the climate cabin and prohibit personnel from entering. Observe the temperature change of the climate cabin and wait for the temperature of the climate chamber to stabilize again at 12 ± 0.5 ℃ and the relative humidity to stabilize at 60 ± 5%;

[0129] ⑤ Open the ThermDAC software of the computer, set the local heating power of the warm body dummy, and allow a variation rate of ± 5%;

[0130] ⑥ Start the experiment and observe the surface skin temperature changes of each region of the warm body dummy in the software at all times. End the experiment when the surface temperature of each region of the warm body dummy gradually stabilizes, i.e., the variation rate is ≤5%;

[0131] ⑦ Open the climate chamber door, enter the climate chamber, use the infrared camera to shoot the overall temperature distribution of the quilt outer surface at this time, then uncover the down quilt and cover it again, close the climate chamber door and the chamber light;

[0132] ⑧ Wait until the surface skin temperature of the thermal manikin decreases to room temperature, repeat the above steps, a total of 3 repeated experiments, and take the average of 3 measurements as the final experimental result.

[0133] To further compare and verify the experimental data and the simulated temperature, the relative error between the simulation value at the end of the calculation experiment and the average value of the physical experiment. The comparison of experimental data and simulation data is shown in Table 5. It can be seen that the relative error of the skin temperature of each local part of the manikin trunk is less than 3%, among which the relative error of the arm, chest, abdomen, waist and hip is less than 1.5%, which can prove that the simulation value and the experimental value have good consistency.

[0134] Table 5

[0135]

[0136] Figure 12 The temperature of the physical experiment and the simulation value of the microspace under the quilt. As can be seen from the figure, except that the temperature of the microspace under the quilt between the two feet is about 2 ℃ lower than the experimental value due to the low simulation temperature of the feet, the simulation temperature of each trunk part of the manikin is basically consistent with the experimental data, and the relative error is less than 1.5%, indicating that the simulation result and the experimental measurement have good consistency. Figure 13 The temperature of the physical experiment and the simulation value of the microspace under the quilt. As can be seen from the figure, except that the temperature of the microspace under the quilt between the two feet is about 2 ℃ lower than the experimental value due to the low simulation temperature of the feet, the simulation temperature of each trunk part of the manikin is basically consistent with the experimental data, and the relative error is less than 1.5%, indicating that the simulation result and the experimental measurement have good consistency.

[0137] The comparison and analysis of the experimental value and the simulation value of the human body skin temperature, the temperature of the microspace under the quilt and the temperature of the outer surface of the quilt can prove that the model and the experiment have good consistency, and it is believed that the established heat transfer model including the quilted clothing can better simulate the heat transfer process between the sleeping human body, the quilted clothing and the environment.

[0138] S6: Using the three-dimensional heat transfer model verified to pass, simulating the effect of quilted clothing physical property parameters on skin temperature, and outputting a skin temperature prediction equation or analysis result for guiding quilted clothing design.

[0139] The heat transfer simulation method of the quilted clothing system provided in the present application is used for heat transfer analysis between the quilted clothing and the human body, for example as follows:

[0140] Example 1: Based on the verified "human-clothing-environment" three-dimensional heat transfer model, the effect of clothing physical property parameters on skin temperature is simulated and calculated, and the analysis results are output to guide the design of clothing. By controlling other variables, a single-factor experiment of quilt thickness is carried out to analyze the influence of single parameter change on human thermal comfort, and the effect of quilt thermal property parameters on skin temperature is discussed, and then the mechanism of key parameters (such as quilt thickness) of quilt system on three-dimensional heat transfer of sleep system is revealed. According to the detailed analysis of the heat transfer mechanism, the quilt design scheme is further optimized. The specific implementation method is as follows:

[0141] Four levels of quilt thickness, 1 cm, 3 cm, 5 cm, and 7 cm, are set, covering different quilt thicknesses from light to heavy (this thickness is the quilt thickness d measured directly under no pressure), which can reflect the sleep needs of different seasons and regions (such as the difference between north and south). The environmental temperature, wind speed, and quilt thermal conductivity are set to 12.4 ℃, 0.20 m / s, and 0.03 W / (m·K), respectively. The parameter values are changed for simulation calculation, and the simulation results are analyzed, including data analysis and visual image analysis. The following is the analysis of the effect of quilt thickness and quilt thermal conductivity on sleep human heat transfer:

[0142] Figures 14(a) and 14(b) are trend charts of local skin temperature of arm, chest, abdomen, waist, hip, thigh, and calf, and average skin temperature of trunk with changes in quilt thickness. Only the body area covered by the quilt is considered in this part, and the average skin temperature of the trunk is set as the area-weighted average of the skin temperatures of the seven selected parts in this study. With the increase of quilt thickness, the local skin temperature of human body gradually increases and the increasing speed gradually slows down. This shows that the increase of quilt thickness can improve its thermal resistance, thereby reducing the heat loss from the human body to the environment, significantly improving the thermal insulation performance, and thus improving the human thermal comfort; but this performance improvement is limited, when the quilt thickness reaches a certain threshold, the convective and radiative heat loss becomes the main heat transfer mode, and further increasing the thickness has limited effect on suppressing convective and radiative heat loss, thus leading to a slowdown in the increase of skin temperature. In addition, the figure shows that the skin temperature of different body parts responds differently to the change in quilt thickness. For example, the skin temperature of the chest and abdomen is higher, while the skin temperature of the arm and calf is lower. This may be because the chest and abdomen are close to the core area and produce more metabolic heat, while the extremities (such as arms and calves) are far from the core area and have a larger exposed area, so the heat is lost faster. This difference shows that it is valuable to optimize the zoned design for different body parts in the design of clothing system, such as adding thermal insulation materials in the extremities to improve overall thermal comfort.

[0143] Fig. 14(b) shows the variation trend of the average skin temperature of the torso with the increase of the thickness of the quilt, which is basically consistent with Fig. 14(a). As the thickness of the quilt increases from 1 cm to 7 cm, the average skin temperature gradually rises from 28.5 °C to 31.5 °C, further verifying the positive correlation between the thickness of the quilt and the skin temperature.

[0144] Therefore, through the analysis of the simulation results of different quilt thicknesses, the following conclusions can be drawn: when designing the quilt system, the difference in local heat demand should be considered for zoning design to balance the overall thermal comfort. It is valuable to optimize the zoning design according to the heat demand of different body parts, such as increasing the thermal insulation material in the limbs to improve the overall thermal comfort.

[0145] Example 2: Based on the verified "human-quilt-environment" three-dimensional heat transfer model, the effect of quilt physical property parameters on skin temperature is simulated and calculated, and a skin temperature prediction equation is output to guide quilt design. The prediction equation considers the influence of environmental temperature T a , air flow rate v a , quilt thickness D and quilt thermal conductivity k on local heat transfer of human sleep, and orthogonal design is used for 4-factor 4-level parameterization simulation. Through multivariate regression fitting analysis of the simulated skin temperature values and parameter values, a skin temperature prediction model is established. The factor level table is shown in Table 6.

[0146] Table 6

[0147]

[0148] The "human-quilt-environment" sleep heat transfer model simulates the average skin temperature T sk,0 of the torso and the local skin temperature of the arm T sk,1 , chest T sk,2 , abdomen T sk,3 , waist T sk,4 , hip T sk,5 , thigh T sk,6 and calf T sk,7 under 16 sets of corresponding parameter test conditions. The parameterization simulation results of the model are shown in Table 7.

[0149] Table 7

[0150]

[0151] Taking the skin temperature as the dependent variable, the environmental temperature T a , air flow rate v a, quilt thickness D, quilt thermal conductivity k as independent variables, through multiple linear fitting (using the fitting method of the prior art to achieve), the fitting equation parameters of the average trunk skin temperature and each local skin temperature (symbol h, a, b, c, d) are shown in Table 8 below, and the skin temperature prediction model is shown in formula 3. The goodness of fit R 2 of each fitting equation is greater than 0.99, indicating that the model equation is meaningful and the fitting degree is good.

[0152] Table 8

[0153]

[0154] (3)

[0155] Wherein, T sk,i is the skin temperature, T a is the ambient temperature, v a is the airflow velocity, D is the quilt thickness, k is the quilt thermal conductivity, h is the intercept, and a, b, c, d are all regression coefficients. Specifically, by taking the skin temperature as the dependent variable, the ambient temperature T a , the airflow velocity v a , the quilt thickness D, and the quilt thermal conductivity k as the independent variables, through multiple linear fitting, the fitting equation parameters of the average trunk skin temperature and each local skin temperature (including the intercept h and the regression coefficients a, b, c, d) are obtained.

[0156] The above skin temperature prediction model can be used to evaluate the thermal comfort of the human body during sleep and provide a scientific basis for selecting appropriate bedding systems. The following is a specific application method of the skin prediction model:

[0157] (1) By solving the skin temperature prediction model, the thermal comfort of the human body under different combinations of environmental conditions and bedding parameters can be quantitatively evaluated. The parameters of the ambient temperature T a , the airflow velocity v a , the quilt thickness D, and the quilt thermal conductivity k are input into the prediction model; the average trunk skin temperature and the local skin temperature are calculated using the regression equation; according to the calculation results of the skin temperature, combined with the thermal comfort standard (such as ISO 7730 or ASHRAE 55), the thermal comfort state of the human body under specific conditions is evaluated.

[0158] (2) By solving the skin temperature prediction model, theoretical support can be provided for the optimization design of the bedding system. First, the ambient temperature, the airflow velocity, and the target skin temperature are determined, and then the bedding thickness and the thermal conductivity combination that meet the target skin temperature can be deduced by solving the prediction model; or the bedding material can be specified, and based on the prediction model, the development and design of zoned bedding can be scientifically guided to improve the thermal comfort performance of the product.

[0159] (3) The skin temperature prediction model can provide a scientific basis for the design of indoor environment control systems. According to the prediction model, the settings of indoor environment temperature and air speed are optimized to ensure the thermal comfort of the human body during sleep; through the prediction model, the combination of environmental parameters under the lowest energy consumption is determined to achieve the balance between energy saving and thermal comfort.

[0160] (4) The skin temperature prediction model can also be used for the development of intelligent health monitoring and early warning systems. Combined with sensor data, the environmental parameters and clothing state are monitored in real time, and the skin temperature is calculated using the prediction model; when the predicted skin temperature exceeds the comfort range, the system can issue a warning to prompt the user to adjust the environment or clothing parameters. Embodiment 2

[0161] The embodiment provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the steps of the three-dimensional heat transfer simulation method of the clothing system in the embodiment when executing the computer program. Embodiment 3

[0162] The embodiment provides a computer-readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the steps of the three-dimensional heat transfer simulation method of the clothing system in Embodiment 1.

[0163] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can adopt a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can adopt 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 codes. The solutions in the embodiments of the present application can be implemented in various computer languages, such as object-oriented programming languages Java and interpreted scripting language JavaScript.

[0164] The present application is described with reference to flowcharts and / or block diagrams according to the methods, devices (systems), and computer program products of the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of the flows and / or blocks in the flowcharts and / or block diagrams can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices produce a device that implements the functions described in the flowcharts and / or block diagrams. Figure 1 one flow or multiple flows and / or blocks Figure 1apparatuses that carry out the specified functions in one or more of the flowcharts or other flowcharts and / or blocks in the flowcharts.

[0165] These computer program instructions can also be stored in a computer- readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instructions which implement the flowcharts Figure 1 one or more flowcharts and / or blocks in the flowcharts. Figure 1 one or more flowcharts and / or blocks in the flowcharts.

[0166] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the flowcharts Figure 1 one or more flowcharts and / or blocks in the flowcharts. Figure 1 one or more flowcharts and / or blocks in the flowcharts.

[0167] While the preferred embodiments of the application have been described, additional variations and modifications can be made to the embodiments by those of skill in the art once they have the benefit of the present disclosure. Therefore, it is to be understood that the appended claims are intended to cover all such modifications and changes as fall within the scope of the application. In compliance with the statute, the application has been described in language more or less specific to structural

[0168] Obviously, numerous modifications and variations of the present application are possible in light of the above teachings. It is therefore to be understood that within the scope of the appended claims, the application can be practiced otherwise than as specifically described herein.

Claims

1. A method for simulating three-dimensional heat transfer in a clothing system, characterized in that: Includes the following steps: S1: Using 3D scanning technology, point cloud data of a lying human body in three states—naked, wearing pajamas, and covered with bedding—are obtained respectively. The point cloud data is then reverse engineered and post-processed to construct a human body model and a clothing model. S2: Establish the geometric model of the bed pillow and determine its contact area with the human-clothing system. After adjusting the spatial positions of both parties to match the contact area, perform the intersection Boolean operation to complete the geometric assembly of the contact parts. S3: Assemble the processed human body model, clothing model, pillow and mattress model as a whole, and divide the human body model into multiple body segments according to physiological structure; S4: In a multiphysics simulation environment, set parameters including bedroom environment parameters, clothing properties parameters, and local heat flux parameters of human body during sleep based on the body segment division, couple the heat transfer and fluid flow physical fields, and the heat transfer and radiation physical fields to establish a three-dimensional heat transfer model of "human body-clothing-environment". S5: Based on the measured data obtained from the segmented warm body dummy experiment, the three-dimensional heat transfer model is optimized and verified until its simulation accuracy reaches a preset threshold. S6: Using the verified three-dimensional heat transfer model, simulate and calculate the effect of clothing material properties on skin temperature, and output skin temperature prediction equations or analysis results to guide clothing design. The Boolean operation for the intersection of the bed pillow geometric model and the contact area between the human-clothing system in step S2 includes: Adjust the spatial position of the human body model and the clothing model relative to the bed pillow geometric model so that the surface area of ​​the cut human body model is close to the contact area determined in the body pressure distribution experiment; Perform an intersection Boolean operation on the human-clothing assembly and the mattress-pillow assembly that are in contact, and delete the overlapping volumes inside the model after the operation; In step S3, the processed human body model, bedding model, pillow and mattress model are assembled and aligned in three-dimensional space according to the actual sleeping position to accurately reproduce the complete sleep system composed of "human body-bedding-bed pillow". The local heat flux parameter of human body during sleep in step S4 is the dry heat flux density of the human body surface in a thermoneutral state, which is set based on the differences in metabolic rate and blood flow distribution in different body segments. The determination of the dry heat flux density at the body surface includes: Based on the known human physiological thermoregulation model, the total heat flux density and evaporative heat flux density of each local area of ​​the human body under the thermoneutral state of sleep were calculated. The dry heat flux density at the body surface is the difference between the total heat flux density and the evaporation heat flux density; When the human body partition of the known human physiological thermoregulation model is inconsistent with the human body partition of the target warm-body dummy, the calculated heat flux density data is converted to a local heat flux density that matches the partition of the target warm-body dummy based on the heat conservation and the proportional relationship between the surface area of ​​each local body. In step S5: the measured data includes at least the local skin temperature of the human body, the temperature of the microspace under the quilt, and the temperature of the outer surface of the quilt; The optimization specifically involves using the measured data as a benchmark and iteratively adjusting the key physical property parameters or boundary conditions in the three-dimensional heat transfer model to control the relative error between the simulated data and the measured data in local areas to within 3%.

2. The method for three-dimensional heat transfer simulation of a clothing system according to claim 1, characterized in that: The reverse engineering post-processing in step S1 includes the following steps performed sequentially: During the point cloud data processing stage, point cloud data is filtered and optimized to remove unnecessary data, including noise data and overlapping data, while retaining necessary human and clothing feature points. In the polygon data processing stage, the processed point cloud data is converted into polygon data, so that the human body and clothing are transformed into a geometric model composed of triangular faces. The surface processing stage is used to transform the mesh model into a smooth surface model.

3. The method for three-dimensional heat transfer simulation of a clothing system according to claim 2, characterized in that: In step S3, the human body model is divided into multiple body segments, specifically including: head, face, neck, shoulders, chest, abdomen, buttocks, upper arm, forearm, hand, thigh, calf, and foot. These parts are combined as needed.

4. The method for three-dimensional heat transfer simulation of a clothing system according to claim 1, characterized in that: The skin temperature prediction equation in step S6 is: ； Among them, T sk,i For skin temperature, T a For ambient temperature, v a Let H be the airflow velocity, D be the quilt thickness, k be the quilt thermal conductivity, and the intercept h and regression coefficients a, b, c, d be obtained by using skin temperature as the dependent variable and ambient temperature T. a airflow velocity v a The quilt thickness D and the quilt thermal conductivity k are the independent variables, and the results are obtained through multiple linear fitting.

5. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, it implements the steps of the three-dimensional heat transfer simulation method for the clothing system as described in any one of claims 1 to 4.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, it implements the steps of the three-dimensional heat transfer simulation method for the clothing system as described in any one of claims 1 to 4.

Images