A system and method for analyzing the thermal performance of a multi-layer material
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- BOSIDENG DOWN WEAR LTD
- Filing Date
- 2026-03-27
- Publication Date
- 2026-07-03
Smart Images
Figure CN121917599B_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of materials technology, and in particular to a system and method for analyzing the thermal insulation performance of multilayer materials. Background Technology
[0002] In the textile industry, the thermal insulation performance of materials is an important indicator that directly affects the user experience of end products such as clothing and home textiles.
[0003] The thermal insulation performance of a material depends on its ability to prevent heat loss and its capacity to absorb and store heat. However, traditional testing methods often rely on single static parameters. For example, the steady-state thermal resistance method only reflects insulation performance under steady-state conditions and cannot simulate the dynamic heat transfer of multi-layered materials under temperature changes in real-world environments (such as human movement or exercise indoors and outdoors). Therefore, existing testing methods cannot accurately characterize the heat storage capacity of multi-layered materials under dynamic thermal interaction environments, and thus cannot effectively assess their thermal insulation performance. Summary of the Invention
[0004] In view of this, this application provides a system and method for analyzing the thermal insulation performance of multilayer materials, which aims to reliably evaluate the thermal insulation performance of multilayer materials.
[0005] In a first aspect, this application provides a system for analyzing the thermal insulation performance of multilayer materials, including:
[0006] A temperature control device is disposed on the outer surface of a test sample, the test sample comprising multiple layers of material;
[0007] A temperature sensor is provided corresponding to the test layer material in the test sample;
[0008] A heat flow sensor is disposed on the hot surface and the cold surface of the test layer material, wherein the hot surface is the surface of the test layer material closer to the heat source, and the cold surface is the surface opposite the hot surface;
[0009] The processor, connected to the temperature control device, the temperature sensor, and the heat flux sensor, is used to switch the temperature control device to maintain the temperature of the test sample in a steady state or in a preset fluctuating state; in the steady state, based on the temperature fed back by the temperature sensor and the steady-state heat flux density fed back by the heat flux sensor, the thermal conductivity of the test layer material is determined; in the fluctuating state, based on the transient heat flux density of the hot and cold surfaces of the test layer material fed back by the heat flux sensor, the heat storage of the test layer material within a preset time period is determined.
[0010] Optionally, there are two temperature control devices;
[0011] One temperature control device serves as a hot plate, located on the first surface of the sample to be tested; another temperature control device serves as a cold plate, located on the second surface of the sample to be tested, with the first surface and the second surface being two opposite outer surfaces of the sample to be tested.
[0012] The processor is further configured to control both the hot plate and the cold plate to maintain a constant temperature, with the hot plate temperature being greater than the cold plate temperature, until the heat flux density in the test sample is constant and the temperature in the test sample is constant, thus establishing a steady state in the temperature of the test sample; based on the steady state, the processor switches to control the hot plate temperature to change over time according to a preset program, and controls the cold plate temperature to remain constant or change in tandem with the hot plate temperature, so that the temperature in the test sample fluctuates.
[0013] Optionally, if there is a material layer attached to the cold surface side of the material to be tested, temperature sensors are respectively configured in the test area of the material to be tested and the test area of the material layer attached to the cold surface side.
[0014] When there is no adhering material layer on the cold surface side of the material to be tested, a temperature sensor is configured in the test area of the material to be tested.
[0015] The test area is either the material interface or the interior of the material.
[0016] Optionally, the temperature sensors are arranged in an array along the stacking direction of the multiple layers of materials in the test sample, and multiple temperature sensors are sequentially set to correspond to one layer of material in the test sample.
[0017] The heat flow sensors are arranged in an array along the stacking direction of the multiple layers of materials in the test sample. Multiple heat flow sensors are sequentially set for a layer surface. The layer surface includes the contact surface between two adjacent layers of materials, the surface between the test sample and the hot plate, and the surface between the test sample and the cold plate.
[0018] Optionally, it also includes a sealed temperature and humidity control chamber; the two temperature control devices are respectively disposed on the opposite chamber walls of the sealed temperature and humidity control chamber, the temperature sensor is disposed on the first side wall perpendicular to the chamber wall, and the heat flow sensor is disposed on the second side wall perpendicular to the chamber wall.
[0019] Optionally, both the temperature sensor and the heat flow sensor can be installed in a direction perpendicular to the bulkhead.
[0020] Secondly, this application provides a method for analyzing the thermal insulation performance of multilayer materials, applied to a processor in any of the above-mentioned systems, the method comprising:
[0021] Establish a steady-state temperature in the sample to be tested, and determine the thermal conductivity of the test layer material based on the temperature fed back by the temperature sensor and the steady-state heat flux density fed back by the heat flux sensor.
[0022] Based on the steady state, the system switches to a fluctuating state, and based on the transient heat flux density of the hot and cold surfaces of the test layer material fed back by the heat flux sensor, the heat storage status of the test layer material within a preset time period is determined.
[0023] Optionally, determining the thermal conductivity of the test layer material based on the temperature fed back by the temperature sensor and the steady-state heat flux density fed back by the heat flux sensor includes:
[0024] Based on the temperature feedback from the temperature sensor, the thermal conductivity temperature difference generated by the thermal conductivity of the material layer under test, and the steady-state heat flux density feedback from the heat flux sensor, one or more of the thermal conductivity, thermal resistance, and thermal resistance contribution rate of the material layer under test are determined.
[0025] The determination of the heat storage status of the test layer material within a preset time period based on the transient heat flux density of the hot and cold surfaces of the test layer material fed back by the heat flux sensor includes:
[0026] The dynamic heat storage capacity of the test layer material is determined by integrating the difference between the transient heat flux density of the hot and cold surfaces of the test layer material fed back by the heat flux sensor over time within the preset time period.
[0027] Optionally, the method further includes:
[0028] The Dynamic Heat Storage Index (DSI) is determined based on the ratio of the first value to the second value. The first value is the difference between the heat flux integral corresponding to the temperature rise period under the fluctuating state and the system heat storage correction value. The heat flux integral is the integral of the product of the transient heat flux density fed back by the heat flux sensor on the surface between the test sample and the hot plate and the effective test area of the test sample under the temperature rise period. The second value is the product of the effective test area of the test sample and the temperature rise amplitude under the fluctuating state.
[0029] Optionally, the method further includes:
[0030] Generate one or more of the following: a layered thermal conductivity table, a layered dynamic heat storage curve, an overall dynamic heat storage report, and a thermal performance graph; the layered thermal conductivity table includes the thermal conductivity, thermal resistance, and thermal resistance contribution rate of each layer of the test sample; the layered dynamic heat storage curve is the curve showing the change of dynamic heat storage of each layer over time; the overall dynamic heat storage report is the curve showing the change of the DSI value, TSC value, and the difference between the heat flux integral under fluctuating conditions and the ratio of the system heat storage correction value to the effective test area over time; the thermal performance graph is a two-dimensional distribution map of the thermal conductivity and dynamic heat storage per unit thickness of each layer.
[0031] Thirdly, this application provides an apparatus comprising a memory and a processor, the memory for storing instructions or code, and the processor for executing the instructions or code to cause the apparatus to perform a method for analyzing the thermal insulation performance of a multilayer material as described in any of the first aspects above.
[0032] Fourthly, this application provides a computer storage medium storing code, wherein when the code is executed, a device running the code implements the method for analyzing the thermal insulation performance of a multilayer material as described in any of the first aspects above.
[0033] This application provides a system and method for analyzing the thermal insulation performance of multilayer materials. It includes a temperature control device disposed on the outer surface of a test sample, the test sample comprising multilayer materials; a temperature sensor disposed corresponding to the test layer material in the test sample; a heat flux sensor disposed on the hot and cold surfaces of the test layer material, the hot surface being the surface of the test layer material closest to the heat source, and the cold surface being the opposite surface of the hot surface; and a processor connected to the temperature control device, the temperature sensor, and the heat flux sensor, used to switch the temperature control device to maintain the temperature of the test sample in a steady state or in a preset fluctuating state; in the steady state, determining the thermal conductivity of the test layer material based on the temperature feedback from the temperature sensor and the steady-state heat flux density feedback from the heat flux sensor; and in the fluctuating state, determining the heat storage capacity of the test layer material within a preset time period based on the transient heat flux density of the upper and lower surfaces of the test layer material feedback from the heat flux sensor. Based on this, the processor communicates with various devices, enabling automatic switching between steady-state and fluctuating temperature modes. This better aligns with the actual usage scenarios of the test samples (such as stable human body temperature / heat generation during exercise, sudden changes in ambient temperature, etc.), providing a more practical basis for materials research and development. Simultaneously, in steady-state conditions, the thermal conductivity of the test layer material can be calculated based on the temperature data from the temperature sensor and the steady-state heat flux density from the heat flux sensor. In fluctuating conditions, the heat storage capacity of the test layer material within a preset time period can be calculated based on the transient heat flux density changes on the upper and lower surfaces of the heat flux sensor. Integrating steady-state thermal conductivity testing and dynamic heat storage testing into the same system, and achieving independent detection and analysis down to the single-layer material level, breaks through the limitations of traditional overall testing, ensuring the reliability of the thermal insulation analysis of different layers in the test sample. Attached Figure Description
[0034] To more clearly illustrate the technical solutions in this embodiment or the prior art, the drawings used in the description of the embodiment or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0035] Figure 1 This is a schematic diagram of the structure of a multilayer material thermal insulation performance analysis system provided in an embodiment of this application;
[0036] Figure 2 A schematic diagram of a multilayer material structure of a test sample provided in an embodiment of this application;
[0037] Figure 3 A schematic diagram of another multilayer material thermal insulation performance analysis system provided in this application embodiment;
[0038] Figure 4 This is a flowchart illustrating a method for analyzing the thermal insulation performance of multilayer materials, as provided in an embodiment of this application.
[0039] Explanation of the attached drawing numbers:
[0040] 1-Hot plate; 2-Cold plate; 3-Temperature sensor; 4-Heat flow sensor; 5-Sealed temperature and humidity control chamber; 51-First side wall; 52-Second side wall. Detailed Implementation
[0041] To provide a more detailed understanding of the features and technical content of the embodiments of this disclosure, the implementation of the embodiments of this disclosure will be described in detail below with reference to the accompanying drawings. The accompanying drawings are for illustrative purposes only and are not intended to limit the embodiments of this disclosure. In the following technical description, for ease of explanation, several details are used to provide a full understanding of the disclosed embodiments. However, one or more embodiments may still be implemented without these details. In other cases, well-known structures and devices may be simplified in their depiction to simplify the drawings.
[0042] The terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this disclosure are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate for the embodiments of this disclosure described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion.
[0043] Unless otherwise stated, the term "multiple" means two or more. In embodiments of this disclosure, the character " / " indicates that the preceding and following objects are in an "or" relationship. For example, A / B means: A or B. The term "and / or" describes an association between objects, indicating that three relationships can exist. For example, A and / or B means: A or B, or, A and B.
[0044] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.
[0045] See Figure 1 , Figure 1 This application provides a schematic diagram of the structure of a multilayer material thermal insulation performance analysis system, which includes:
[0046] A temperature control device is disposed on the outer surface of the test sample, which comprises multiple layers of material.
[0047] Optionally, the test sample can be a multi-layered textile material sample obtained from actual textile products such as down jackets, windbreakers, or aerospace thermal clothing, or a multi-layered textile material sample to be processed into an actual textile product. Of course, it can also be a multi-layered textile material sample from other scenarios (such as laboratory research). A temperature sensor array is embedded at the interfaces of each material layer.
[0048] It should be noted that the surfaces mentioned in this application (such as the aforementioned outer surfaces and the hot and cold surfaces mentioned later) refer to those in the direction of the superposition of multiple layers of materials in the test sample (e.g., Figure 2 The diagram shows a multilayer material structure of a test sample, including a first layer of material, a second layer of material, ..., an nth layer of material stacked in the direction indicated by the arrows, and the thickness of each layer of material has been predetermined. Figure 2 The middle arrow indicates the surface where the superposition direction intersects. Furthermore, the end face of the test sample that intersects with the surface of the test sample can be called the material interface.
[0049] Optionally, at least one outer surface of the test sample is equipped with a temperature controller.
[0050] In one example, the system includes a temperature controller that simulates the human body as a heat source, providing heat to a surface of the test sample. The heat from this heat source is transferred sequentially through multiple layers of material in the test sample. This facilitates subsequent acquisition of temperature and heat flux density data within the multiple layers of material using temperature and heat flux sensors, allowing analysis of the thermal conductivity and heat storage properties of each layer. For example, in simulating a human-test-environment scenario, the temperature controller simulates the body surface temperature on the human side, while the environment can be simulated using a temperature and humidity controlled chamber or a real outdoor environment.
[0051] In another example, the system may include two temperature control devices. One temperature control device acts as a hot plate, located on a first surface of the sample to be tested; the other temperature control device acts as a cold plate, located on a second surface of the sample to be tested, the first and second surfaces being two opposite outer surfaces of the sample. Exemplarily, the hot and cold plates are independently temperature-controlled to establish a stable temperature difference driving heat flow sequentially through the multilayer material of the sample to be tested. Exemplarily, the hot plate acts as a heat source, its temperature simulating the surface of a human body; the cold plate temperature simulating ambient temperature. The hot plate temperature is higher than the cold plate temperature.
[0052] Optionally, the aforementioned temperature control device (simulating human skin heat source) serving as a heat source can have a built-in precision heater, capable of stable operation at a specified temperature of 25~38℃ with an accuracy of ±0.2℃. It is used to provide controllable heat flux and measure the temperature of each layer of material in the sample under test, as well as the heat flux density on the surface of each layer. The aforementioned temperature control device (simulating ambient cold source) serving as a cold plate has a built-in temperature control module (<10℃) used to set and maintain a temperature lower than the lower hot plate, thereby establishing a constant or dynamic temperature difference between the multiple layers of material stacked in the sample under test.
[0053] A temperature sensor is provided corresponding to the test layer material in the test sample. A heat flow sensor is disposed on the hot surface and cold surface of the test layer material, wherein the hot surface is the surface of the test layer material closer to the heat source, and the cold surface is the surface opposite the hot surface.
[0054] It is understood that the aforementioned test layer material is any one of the multilayer materials included in the test sample. Of course, this application can simultaneously configure corresponding temperature sensors and heat flux sensors for one or more test layer materials in the test sample to achieve synchronous acquisition of temperature and heat flux density of one or more test layer materials, thereby enabling analysis of a single test layer material or comparative analysis of multiple test layer materials.
[0055] Understandably, heat flows from the hot surface of each test layer material to the cold surface.
[0056] The processor, connected to the temperature control device, the temperature sensor, and the heat flux sensor, is used to switch the temperature control device to maintain the temperature of the test sample in a steady state or in a preset fluctuating state; in the steady state, based on the temperature fed back by the temperature sensor and the steady-state heat flux density fed back by the heat flux sensor, the thermal conductivity of the test layer material is determined; in the fluctuating state, based on the transient heat flux density of the upper and lower surfaces of the test layer material fed back by the heat flux sensor, the heat storage of the test layer material within a preset time period is determined.
[0057] The aforementioned steady state is achieved by using a temperature control device to maintain a constant temperature difference between the two outer surfaces of the test sample that are perpendicular to the direction of the multilayer material stacking.
[0058] For example, the processor can control both the hot plate and the cold plate to maintain a constant temperature, with the hot plate temperature being greater than the cold plate temperature, until the heat flux density in the test sample is constant and the temperature in the test sample is constant, thus determining that the temperature in the test sample has reached a steady state.
[0059] In this context, a constant heat flux density and constant temperature in the test sample can be defined as follows: the heat flux density received by the processor from multiple heat flux density sensors in the test sample reaches a constant value (the coefficient of variation of the heat flux data recorded by the multiple heat flux sensors is <3%), and simultaneously, the temperature received by the processor from multiple temperature sensors in the test sample remains constant. If these conditions are met, then steady-state establishment is considered complete. Subsequently, the processor can continue to collect the steady-state heat flux density q. s Temperature. The temperature corresponding to different material layers is different. The temperature of each material layer collected from the hot plate side to the cold plate side of the test sample can be represented as T1, T2, ...
[0060] The aforementioned preset fluctuation state dynamically adjusts the temperature of the temperature control device, which serves as the heat source, according to preset laws such as sine, step, or a certain slope. For example, based on the established steady state, the hot plate is switched to control its temperature change over time according to a preset program, while the cold plate temperature is kept constant or changes in tandem with the hot plate temperature, causing the temperature in the test sample to fluctuate, thereby stimulating the dynamic thermal response of the sample. Furthermore, after establishing the fluctuation state, the processor can collect the transient heat flux density q(t) of the hot and cold surfaces of the test layer in real time through a heat flux sensor. The processor can also synchronously acquire the transient temperature T(t) at the location of the temperature sensor through a temperature sensor. The transient temperatures corresponding to different layers of material are different, and the transient temperatures collected from each layer of material from the hot plate side to the cold plate side of the test sample can be represented as T1(t), T2(t), ...
[0061] Optionally, when the fluctuation state changes sinusoidally, the coordinated change can refer to the cold plate temperature being dynamically adjusted according to the same sinusoidal amplitude and phase difference as the hot plate; when the fluctuation state is a step heating, the coordinated change can refer to the cold plate temperature being dynamically adjusted according to the same step amplitude and interval as the hot plate; when the fluctuation state is a heating at a certain slope, the coordinated change can refer to the cold plate temperature being dynamically adjusted according to the same slope as the hot plate.
[0062] The aforementioned preset time period can be any time period under fluctuating conditions, or it can be the time period corresponding to a preset temperature rise range under fluctuating conditions, such as the time period corresponding to the entire process from the initial temperature to the target temperature.
[0063] Based on the aforementioned system, the processor of this application communicates with each device, enabling switching between steady-state and fluctuating temperature modes. This better aligns with the actual usage scenarios of the test samples (such as stable human body temperature / heat generation during exercise, sudden changes in ambient temperature, etc.), providing a more practical basis for material development. Simultaneously, in steady-state conditions, the thermal conductivity of the test layer material can be calculated based on the temperature data from the temperature sensor and the steady-state heat flux density from the heat flux sensor. In fluctuating conditions, the heat storage capacity of the test layer material within a preset time period can be calculated based on the transient heat flux density changes on the upper and lower surfaces of the heat flux sensor. Integrating steady-state thermal conductivity testing and dynamic heat storage testing into the same system, and achieving independent detection and analysis down to the single-layer material level, breaks through the limitations of traditional overall testing, ensuring the reliability of the thermal insulation analysis of different layers in the test sample.
[0064] In one possible implementation, the aforementioned thermal conductivity can include determining one or more of the thermal conductivity, thermal resistance, and thermal resistance contribution rate of the material under test based on the thermal conductivity temperature difference generated by the thermal conductivity of the material under test layer determined by the temperature feedback from the temperature sensor under steady state and the steady-state heat flux density fed back by the heat flux sensor.
[0065] To determine this thermal conductivity temperature difference, this application employs the following two configuration scenarios when configuring temperature sensors for each test layer material in the test sample:
[0066] In scenario one, if there is a material layer attached to the cold surface of the material to be tested, temperature sensors are respectively configured in the test area of the material to be tested and the test area of the material layer attached to the cold surface.
[0067] In this case, the thermal conductivity temperature difference is the difference between the temperature reported by the temperature sensor in the test area of the test layer material and the temperature reported by the temperature sensor in the test area of the material layer that is in contact with the cold surface of the test layer material.
[0068] In scenario two, if there is no adhering material layer on the cold surface side of the material to be tested, a temperature sensor is configured in the test area of the material to be tested.
[0069] In this case, the thermal conductivity temperature difference is the difference between the temperature fed back by the temperature sensor in the test area of the material to be tested and the temperature of the cold plate.
[0070] Based on the determined thermal conductivity temperature difference, further, taking the i-th layer material in the test sample as an example, the formula for calculating the thermal conductivity of the test layer material can be:
[0071] (1)
[0072] In equation (1) above, λ iλ is the thermal conductivity of the i-th layer material, in W / (m·℃). i The smaller the value, the better the insulation performance of the layer. s The steady-state heat flux density (the coefficient of variation of the heat flux density recorded by the heat flux sensor under steady-state conditions is less than 3%), unit: W / m². δ i T represents the thickness of the i-th layer of material, in meters (m). i,s The temperature is the temperature returned by the temperature sensor in the test area of the material under test. (T) i+1,s The temperature referred to is the temperature of the test area of the material layer in contact with the cold surface of the test layer material in Case 1 above, or the temperature of the cold plate mentioned in Case 2 above, in degrees Celsius (°C). The above T... i,s -T i+1,s =ΔT i This refers to the thermal conductivity temperature difference.
[0073] Optionally, the test area can be either a material interface or the interior of the material. The material interface of the test area can be the end face connecting the hot and cold surfaces of the material under test. In this case, a micro-invasive temperature sensor can be used. The probe of the micro-invasive temperature sensor can be precisely aligned with and lightly touch the material interface of the material under test to measure the temperature of the material interface during steady-state and dynamic processes. Of course, if the material is a flocculent type, the temperature sensor can be placed inside the material.
[0074] Furthermore, when all layers in the sample to be tested are test layers, each multilayer material needs to be equipped with a temperature sensor and a heat flow sensor. The specific arrangement can be as follows:
[0075] The temperature sensors are arranged in an array along the stacking direction of the multiple layers of materials in the test sample, with multiple temperature sensors sequentially corresponding to one layer of material in the test sample.
[0076] The heat flow sensors are arranged in an array along the stacking direction of the multiple layers of materials in the test sample. Multiple heat flow sensors are sequentially set for a layer surface. The layer surface includes the contact surface between two adjacent layers of materials, the surface between the test sample and the hot plate, and the surface between the test sample and the cold plate.
[0077] Optionally, the aforementioned heat flux sensor can be an extremely thin, flexible film heat flux sensor, enabling direct measurement of the heat flux density on the cold and hot surfaces of each material layer.
[0078] In one possible implementation, the processor calculates the heat storage status of the test layer material within a preset time period by: determining the dynamic heat storage capacity of the test layer material by integrating the difference between the transient heat flux densities of the upper and lower surfaces of the test layer material fed back by the heat flux sensor over time within the preset time period.
[0079] For both the hot and cold surfaces of the material under test, heat flux sensors are configured. Under fluctuating conditions, the transient heat flux density q fed back from the heat flux sensor on the hot surface is acquired at high frequency and synchronously. i-1 (t) and the transient heat flux density q fed back by the heat flux sensor on the cold surface. i (t).
[0080] Under fluctuating conditions, for the i-th layer of material, its net heat absorption rate is equal to the difference between the heat flux density flowing into and out of the layer. This difference leads to a change in the internal energy of the layer (manifested as a temperature increase and possible phase transition). Therefore, the net heat absorbed (i.e., heat storage) per unit area by the i-th layer of material from the initial time t0 to time t can be:
[0081] d (2)
[0082] (2) In the formula, ΔH i (t): The net heat absorbed per unit area by the i-th layer of material (the layer under test) from time t0 to time t (preset time period), in J / m². Characterizes the dynamic heat storage capacity of the layer under test. i-1 (t) represents the heat flux density flowing into the i-th layer of material (which can be obtained from the heat flux sensor HFS on the hot surface of the layer to be measured). i-1 (Measured), unit: W / m². q i (t) represents the heat flux density flowing out of the i-th layer of material (which can be obtained from the heat flux sensor HFS on the cold surface of the layer of material to be tested). i (Measured), unit: W / m². Integral term [q] i-1 (τ)-q i [(τ)] represents the net heat absorption rate of the i-th layer material at time τ, in W / m².
[0083] Therefore, ΔHi(t) essentially reflects the heat storage situation of the material layer during dynamic heat conduction.
[0084] The above calculation formula directly calculates the dynamic heat storage capacity of each layer of material by integrating the difference in heat flow sensor readings between the cold and hot surfaces of the tested material over time. This greatly simplifies the calculation, avoids the introduction of complex parameters, and significantly improves the accuracy and efficiency of characterizing the dynamic thermal performance of multilayer insulation materials. Especially under transient conditions, this method can accurately reflect the differences in heat storage response among the layers in real time.
[0085] Based on the above embodiments, see Figure 3The diagram shows another structural schematic of a multi-layer material thermal insulation performance analysis system. The system can be a sealed temperature and humidity control chamber 5, equipped with two temperature control devices (such as…). Figure 3 The hot plate 1 and cold plate 2 are respectively disposed on the opposite walls of the sealed temperature and humidity control chamber 5. The temperature sensor is disposed on the first side wall 51 perpendicular to the chamber wall, and the heat flow sensor 4 is disposed on the second side wall 52 perpendicular to the chamber wall.
[0086] Optionally, both the temperature sensor 3 and the heat flow sensor 4 can be moved perpendicular to the bulkhead and fixed in place after reaching a suitable position. Figure 3 As shown, multiple vertically movable temperature sensors are installed on the first sidewall 51 to accommodate different layer thicknesses and facilitate the measurement of temperature gradients between layers. Multiple vertically movable heat flow sensors 4 are installed on the second sidewall 52 to accommodate different layer thicknesses, monitor the entire system's heat transfer until it reaches a stable state, and record the heat flow. Furthermore, Figure 3 The number of temperature sensors 3 and heat flow sensors 4 configured in the sample is not limited, and the configuration is based on the actual number of layers of the sample to be tested.
[0087] Based on the above embodiments, in addition to calculating the heat conduction under steady-state conditions and the dynamic heat storage under fluctuating conditions, the processor can also calculate the overall dynamic heat storage index (DSI) of the test sample under fluctuating conditions. The specific implementation process can be as follows:
[0088] Optionally, during the dynamic temperature change under fluctuating conditions, the transient heat flux density fed back by the first heat flux sensor (HFS0, located on the surface between the test sample and the hot plate) is integrated based on the total heat absorbed from the hot plate.
[0089] In one example, the Dynamic Heat Storage Index (DSI) is determined based on the ratio of a first value to a second value; the first value is the difference between the heat flux integral corresponding to the temperature rise period under the fluctuating state and the system heat storage correction value, wherein the heat flux integral is the integral of the product of the transient heat flux density fed back by the heat flux sensor disposed on the surface between the test sample and the hot plate and the effective test area of the test sample under the temperature rise period; the second value is the product of the effective test area of the test sample and the temperature rise amplitude under the fluctuating state.
[0090] Defined at hot plate temperature from T start Change to T end Preset time period (T) start The corresponding time t start To T end The corresponding time t end Within this range, the dynamic heat storage index of the sample to be tested is:
[0091] = (3)
[0092] (3) In the formula, DSI is the overall dynamic heat storage index, with units of J / (m²·K), representing the total net heat absorbed per unit area and per unit temperature rise of the overall sample. q0(t) is the transient heat flux density flowing from the hot plate into the test sample, measured by HFS0, with units of W / m². A is the effective test area of the test sample, with units of m². C is the system heat storage correction value, with units of J, determined through calibration experiments without a sample (or a standard sample with known heat capacity), used to deduct the heat storage effect of the equipment itself (such as the hot plate). ΔH total This represents the net heat absorption per unit area of the test sample within a specified temperature rise range, expressed in J / m². Further, the total area of the test sample and ΔH can be calculated. total The product of these factors determines the TSC value (Total Thermal Storage Capacity).
[0093] Based on the above embodiments, this application determines the thermal conductivity under steady-state conditions, the dynamic heat storage under fluctuating conditions, and the overall dynamic heat storage index of the entire test sample. Based on this, the processor of this application also generates multi-dimensional reports based on the data calculated by the processor, which can be connected to a display for easy user analysis.
[0094] In one example, the multi-dimensional report may include:
[0095] Layered thermal conductivity performance report: one or more of the following: thermal conductivity λi, thermal resistance Ri (=δi / λi), and thermal resistance contribution rate (the proportion of the thermal resistance of the test layer material in the sum of the thermal resistances of all layers in the test sample).
[0096] Layered dynamic heat storage curves: Curves showing the change of ΔHi(t) of each test layer material with time or overall average temperature, which can be used to intuitively compare and analyze the heat storage contribution of each test layer in the dynamic process.
[0097] Overall dynamic heat storage report: Overall ΔH total -T curve, DSI value, TSC (total heat storage capacity).
[0098] Comprehensive thermal performance spectrum: Presented in a two-dimensional chart format, the thermal conductivity λ of each test layer material is analyzed. -1 The data is visualized on two dimensions: “the thermal insulation capacity” and “the dynamic heat storage capacity per unit thickness within a preset time period (ΔHi / δi, representing the volumetric heat storage capacity)”.
[0099] The above describes some specific implementations of a system for analyzing the thermal insulation performance of multilayer materials provided in this application. Based on this, this application also provides a corresponding method. The apparatus provided in this application will be described below from the perspective of the method.
[0100] See Figure 4 The flowchart shown illustrates a method for analyzing the thermal insulation performance of multilayer materials. This method, applicable to the processor in any of the above embodiments, includes:
[0101] S401. Establish a steady state of temperature in the sample to be tested, and determine the thermal conductivity of the material to be tested based on the temperature fed back by the temperature sensor and the steady state heat flux density fed back by the heat flux sensor.
[0102] S402. Based on the steady state, switch to the fluctuating state, and determine the heat storage status of the test layer material within a preset time period based on the transient heat flux density of the hot and cold surfaces of the test layer material fed back by the heat flux sensor.
[0103] Based on the steps S101-S102 above, applied to the aforementioned system, automatic switching between steady-state and fluctuating states is achieved. Simultaneous acquisition of data from multiple sensor signals allows for the calculation of the thermal conductivity of the test layer material under steady-state conditions, and the calculation of the heat storage capacity of the test layer material within a preset time period based on the changes in transient heat flux density on the upper and lower surfaces of the heat flux sensor under fluctuating conditions. This integrates steady-state thermal conductivity testing and dynamic heat storage testing into a single system, enabling independent detection and analysis down to the individual layer material level. This overcomes the limitations of traditional overall testing and ensures the reliability of the thermal insulation analysis of different layers in the test sample.
[0104] In step S401 above, determining the thermal conductivity of the test layer material based on the temperature fed back by the temperature sensor and the steady-state heat flux density fed back by the heat flux sensor may include:
[0105] Based on the temperature difference generated by the thermal conductivity of the material layer under test, determined by the temperature feedback from the temperature sensor, and the steady-state heat flux density fed back by the heat flux sensor, one or more of the following parameters of the material layer under test are determined: thermal conductivity, thermal resistance, and thermal resistance contribution rate.
[0106] Optionally, the thermal conductivity λ of the test layer material. i The specific calculation method is as shown in equation (1) above.
[0107] Optional, thermal resistance is R i (=δ i / λ i ), where δ i The thickness of the material to be tested is given.
[0108] Optionally, the thermal resistance contribution rate is R i In total thermal resistance R total The percentage of the total thermal resistance of all layers in the test sample is used to quantify the impact of each layer on the overall thermal conductivity.
[0109] Optionally, a layered thermal conductivity table is generated, which includes the thermal conductivity, thermal resistance, and thermal resistance contribution rate of each layer of the sample to be tested.
[0110] In step S402 above, determining the heat storage status of the test layer material within a preset time period based on the transient heat flux density of the hot and cold surfaces of the test layer material fed back by the heat flux sensor may include:
[0111] The dynamic heat storage capacity of the test layer material is determined by integrating the difference between the transient heat flux density of the hot and cold surfaces of the test layer material fed back by the heat flux sensor over time within the preset time period.
[0112] Optionally, the dynamic heat storage ΔH in the test layer material can be... i (t) can be calculated and determined according to the above formula (2).
[0113] Optionally, it is also possible to generate layered dynamic heat storage curves and establish curves of ΔHi(t) of each layer changing with time or overall average temperature, so that the heat storage contribution of each layer in the dynamic process can be directly compared.
[0114] Furthermore, the above method may also include:
[0115] The Dynamic Heat Storage Index (DSI) is determined based on the ratio of the first value to the second value. The first value is the difference between the heat flux integral corresponding to the temperature rise period under the fluctuating state and the system heat storage correction value. The heat flux integral is the integral of the product of the transient heat flux density fed back by the heat flux sensor on the surface between the test sample and the hot plate and the effective test area of the test sample under the temperature rise period. The second value is the product of the effective test area of the test sample and the temperature rise amplitude under the fluctuating state.
[0116] Optionally, the above DSI value can be determined according to equation (3) above, and ΔH can be determined based on equation (3). total (The difference between the integral of heat flux under fluctuating conditions and the ratio of the system heat storage correction value to the effective test area) is used to establish ΔH. total A curve showing the change over time or temperature.
[0117] Optionally, the thermal conductivity (λ) of each material layer can also be displayed in a two-dimensional chart. -1 "(representing thermal insulation capacity)" and "dynamic heat storage per unit thickness (ΔH)" i / δi The thermal performance is visualized on two dimensions: "volume heat storage capacity" and "thermal performance graph".
[0118] Based on the above embodiments, the beneficial effects of the above system and method are as follows:
[0119] 1. By directly measuring the heat flux density on both surfaces of each material layer and integrating the difference, the heat storage capacity can be obtained. The principle is clear and direct, simplifying the calculation and eliminating the need for prior parameters such as material heat capacity, which are difficult to obtain accurately.
[0120] 2. Steady-state and fluctuating state, overall and layered measurements are completed synchronously under the same system, the same experiment, and the same time reference. All data are highly correlated, which facilitates accurate and in-depth analysis of each layer and the overall material.
[0121] 3. A correlation graph was established to obtain the thermal conductivity (characterizing its ability to impede heat flow) and dynamic heat storage (characterizing its ability to store heat) of each material layer, visually depicting the dual role of each material layer in heat transfer process as both conduction and heat storage.
[0122] 4. Traditional testing methods, based on small temperature differences, lack sufficient accuracy for measuring thin and light materials. This application improves test sensitivity by increasing the temperature difference through a cold plate and hot plate structure. It clearly quantifies the specific contributions of each layer in terms of insulation and heat storage. This provides a precise basis for selecting materials or improving specific functional layers in scenarios such as clothing design.
[0123] Based on the above embodiments, this application also provides specific application examples, as follows:
[0124] Example 1: Testing a three-layer composite insulation material.
[0125] 1. Test Objective
[0126] The thermal conductivity (λ), thermal resistance contribution ratio, and heat storage capacity of each layer in a three-layer composite thermal insulation material are quantified to evaluate the thermal insulation effect of the static air layer.
[0127] 2. Test Sample Structure and Test Conditions
[0128] The structure of the test sample is as follows: Layer 1 (outer layer) is nylon windproof fabric with a thickness of δ1=0.3 mm; Layer 2 (middle layer) is a closed still air layer with a thickness of δ2=5 mm; Layer 3 (inner layer) is polyester fleece with a thickness of δ3=4 mm.
[0129] Test conditions: Steady-state temperature T of the hot plate (simulating skin) h = 33.0°C; Steady-state temperature T of the upper cooling plate (simulated environment) c= 8.0°C. The test procedure under fluctuating conditions involves linearly heating the hot plate from 15.0°C to 35.0°C at a rate of 0.5°C / min to accurately capture the dynamic process.
[0130] 3. Testing Process and Data
[0131] The test sample was placed in the sealed temperature and humidity control chamber mentioned above in this application, and three movable sensor probes were accurately positioned at the material interface of the three-layer material.
[0132] After reaching steady state, record the steady-state heat flux density: q s = 9.8 W / m² (due to the large temperature difference, the heat flux signal is enhanced). Steady-state temperature of the interface between each material layer: T 1,s = 31.5°C, T 2,s = 30.1°C, T 3,s = 9.5°C.
[0133] Then, a heating program is executed, and transient temperature and transient heat flux density data are collected simultaneously.
[0134] 4. Result Calculation and Analysis
[0135] (1) Calculation of layered thermal conductivity and thermal resistance
[0136] Layer 1 (Nylon fabric):
[0137] λ1=(9.8×0.0003) / (31.5-30.1)≈0.021W / (m °C).
[0138] R1=δ1 / λ1≈0.0143(m 2 °C) / W.
[0139] Layer 2 (Still air layer):
[0140] λ2=(9.8×0.0050) / (30.1-9.5)≈0.024W / (m °C).
[0141] R² = δ² / λ² ≈ 0.2083 (m²) °C) / W.
[0142] Layer 3 (Fleece):
[0143] λ3=(9.8×0.0040) / (9.5-8.0)≈0.026W / (m °C).
[0144] R3 = δ3 / λ3 ≈ 0.1538 (m2) °C) / W.
[0145] Total thermal resistance R total =R1+R2+R3≈0.3764(m2 °C) / W.
[0146] The thermal resistance contribution ratio of each layer was calculated: the still air layer contributed approximately 55.4%, making it the most important insulation layer; the fleece layer contributed approximately 40.9%.
[0147] (2) Calculation of stratified dynamic heat storage capacity
[0148] Integrating the heat flux difference during the fluctuating heating process (15°C→35°C):
[0149] ΔH1 (fabric layer) ≈ 1,850 J / m²
[0150] ΔH2 (air layer) ≈ 3,200 J / m² (Although the heat capacity is small, the temperature difference is large)
[0151] ΔH3 (fleece layer) ≈ 28,500 J / m²
[0152] (3) The overall dynamic heat storage index DSI is calculated to be 12.1 kJ / (m²·°C).
[0153] 5. Example 1 Conclusion: In this three-layer composite insulation structure, the static air layer contributes over 55% of the insulation, making it crucial for "blocking heat flow"; while the fleece inner layer, due to its larger mass and heat capacity, stores over 80% of the dynamic heat, serving as the main "thermal buffer." Based on this, it can be understood that by increasing the test temperature difference (setting the cold plate <10°C), the system can more sensitively distinguish the different dominant roles of each layer in insulation and heat storage.
[0154] Example 2: Testing a mountaineering apparel fabric system containing phase change materials (PCM).
[0155] 1. Test Objective
[0156] The thermal performance of a multi-layer system (including a PCM temperature-regulating layer) for mountaineering apparel under severe temperature difference conditions was evaluated, with a focus on quantifying the peak-shaving and valley-filling effect of the PCM layer on dynamic heat flux within the phase transition range.
[0157] 2. Test Sample Structure and Test Conditions
[0158] The test sample consists of four layers of material, simulating the structure of mountaineering clothing. Specifically, layer 1 is a waterproof and breathable membrane with a thickness δ1=0.1mm. Layer 2 is a polyester wadding (containing PCM microcapsules, with a phase transition point of approximately 23°C) with a thickness δ2=6.0mm. Layer 3 is a mesh breathable insulating layer with a thickness δ3=2.0mm. Layer 4 is a skin-friendly and quick-drying lining with a thickness δ4=0.4mm.
[0159] Steady-state condition: Steady-state temperature difference is T h = 35.0°C, T c = 5.0°C (simulating a frigid environment).
[0160] Dynamic testing procedure: The hot plate temperature is stepped in multiple steps (0.5°C) between 18°C and 28°C to precisely capture the PCM phase transition behavior.
[0161] 3. Test Results and Feature Analysis
[0162] (1) Steady-state thermal conductivity
[0163] The steady-state heat flux density q was measured. s = 15.2 W / m².
[0164] The calculated λ values for each layer are: λ1≈0.045, λ2≈0.038, λ3≈0.120 (the mesh layer has higher thermal conductivity), and λ4≈0.055.
[0165] Total thermal resistance R total ≈ 0.394 (m²·°C) / W, of which the PCM flocculent layer (layer 2) contributes the most thermal resistance (approximately 65%).
[0166] (2) Dynamic heat storage characteristics
[0167] In dynamic testing, when the temperature passed the 23°C phase transition point: the ΔH(t) curves of other layers changed gradually. The ΔH2(t) curve of the PCM layer (layer 2) showed a steep upward plateau, indicating that a large amount of heat flow was used for the latent heat of phase transition. Calculations showed that the cumulative heat storage ΔH2 of the PCM layer reached as high as 68,000 J / m² in the 18-28°C range, accounting for 72% of the total heat storage of the four layers.
[0168] (3) Overall dynamic performance
[0169] The overall DSI value is 8.5 kJ / (m²·°C) in the 18-23°C range, and jumps to 22.0 kJ / (m²·°C) in the 23-28°C range, which significantly demonstrates the temperature regulation capability of PCM.
[0170] 4. Example 2 Conclusion: Under simulated extreme cold (5°C cold plate) and drastic temperature difference with human body heat, this system not only verified that layer 2 is the main steady-state insulation material, but more importantly, it quantified for the first time, through direct differential heat flow measurement, its exceptionally strong dynamic heat absorption capacity (DSI jump) near the phase transition point. This provides direct experimental evidence for the thermal comfort advantages of smart temperature-regulating clothing using this test sample under sudden environmental changes.
[0171] Comparative Example 3: Sample of Example 1 was tested using the conventional steady-state hot plate method (ISO 11092).
[0172] 1. Testing Methods
[0173] A three-layer sample identical to the one described above was tested using a sweat protection hot plate apparatus conforming to ISO 11092. This standard method typically uses a cold plate temperature of 20°C to simulate a "warm" environment.
[0174] 2. Test Results
[0175] The overall thermal resistance of the sample was measured to be Rct = 0.38 (m). 2 °C) / W. And this is the only parameter available.
[0176] 3. Limitations Analysis and Comparison
[0177] The steady-state hot plate method suffers from insufficient temperature difference, resulting in low sensitivity. Traditional methods use a 20°C cold plate to create a 13°C temperature difference with a 33°C hot plate, while this application uses an 8°C cold plate to create a 25°C temperature difference. This larger temperature difference results in a stronger heat flow signal through lightweight textiles, significantly improving the signal-to-noise ratio and measurement accuracy. Traditional methods exhibit significant uncertainty in measuring lightweight fabrics with low thermal resistance. Furthermore, the steady-state thermal resistance method cannot perform layer-by-layer analysis, only obtaining the total thermal resistance value, failing to determine whether the air layer contributes more than half of the insulation effect, and also failing to determine the specific thermal conductivity of each layer.
[0178] Therefore, researchers might mistakenly believe that the insulation performance of all materials needs to be uniformly improved based solely on an overall thermal resistance value measured under "warm and hot conditions". However, the division of labor mechanism of "air layer for main insulation and fleece layer for main heat storage" disclosed in this application guides targeted optimization (such as maintaining the thickness of the air layer and selecting fleece with higher heat capacity).
[0179] Furthermore, the steady-state thermal resistance method operates at a constant temperature and therefore cannot obtain any dynamic heat storage data (ΔH). i Therefore, it is impossible to evaluate the thermal buffering performance of the material when the temperature changes (such as the start / stop of motion), and it is even more impossible to capture the dynamic response characteristics of the PCM layer in Example 2 when transient heat absorption and release near the phase transition point.
[0180] In summary, compared with traditional steady-state methods, this invention, through a superior test configuration (cold plate <10°C to increase temperature difference and improve sensitivity) and innovative layered sensing technology, not only solves the problem of traditional methods being unable to analyze multi-layered structures, but also overcomes their inherent limitation of being unable to evaluate dynamic performance. The data dimensions provided in this application (layered λ, layered ΔH, overall DSI) expand and deepen the information compared to the traditional single thermal resistance value, representing a significant improvement in evaluating the comprehensive thermal comfort of modern high-performance textile materials.
[0181] This application also provides corresponding devices and computer storage media for implementing the solutions provided in this application.
[0182] The device includes a memory and a processor. The memory stores instructions or code, and the processor executes the instructions or code to enable the device to perform a method for analyzing the thermal insulation performance of multilayer materials as described in any embodiment of this application.
[0183] The computer storage medium stores code, and when the code is run, the device running the code implements a method for analyzing the thermal insulation performance of multilayer materials as described in any embodiment of this application.
[0184] As can be seen from the above description of the embodiments, those skilled in the art can clearly understand that all or part of the steps in the methods of the above embodiments can be implemented by means of software plus a general-purpose hardware platform. Based on this understanding, the technical solution of this application can be embodied in the form of a software product. This computer software product can be stored in a storage medium, such as a read-only memory (ROM) / RAM, magnetic disk, optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, a server, or a network communication device such as a router) to execute the methods described in various embodiments or some parts of the embodiments of this application.
[0185] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on describing the differences from other embodiments. The above descriptions are merely exemplary implementations of this application and are not intended to limit the scope of protection of this application.
Claims
1. A system for analyzing the thermal insulation performance of multilayer materials, characterized in that, include: A temperature control device is disposed on the outer surface of a test sample, the test sample comprising multiple layers of material; A temperature sensor is provided corresponding to the test layer material in the test sample; A heat flow sensor is disposed on the hot surface and the cold surface of the test layer material, wherein the hot surface is the surface of the test layer material closer to the heat source, and the cold surface is the surface opposite the hot surface; The processor, connected to the temperature control device, the temperature sensor, and the heat flux sensor, is used to switch the temperature control device to maintain the temperature of the test sample in a steady state or in a preset fluctuating state; in the steady state, based on the temperature fed back by the temperature sensor and the steady-state heat flux density fed back by the heat flux sensor, the thermal conductivity of the test layer material is determined; in the fluctuating state, based on the transient heat flux density of the hot and cold surfaces of the test layer material fed back by the heat flux sensor, the heat storage of the test layer material within a preset time period is determined. There are two temperature control devices; One temperature control device serves as a hot plate, located on the first surface of the sample to be tested; another temperature control device serves as a cold plate, located on the second surface of the sample to be tested, with the first surface and the second surface being two opposite outer surfaces of the sample to be tested. The processor is further configured to control both the hot plate and the cold plate to maintain a constant temperature, with the hot plate temperature being greater than the cold plate temperature, until the heat flux density in the test sample is constant and the temperature in the test sample is constant, thus establishing a steady state in the temperature of the test sample; based on the steady state, the processor switches to control the hot plate temperature to change over time according to a preset program, and controls the cold plate temperature to remain constant or change in tandem with the hot plate temperature, so that the temperature in the test sample fluctuates.
2. The system according to claim 1, characterized in that, When there is a material layer attached to the cold surface side of the material to be tested, temperature sensors are respectively configured in the test area of the material to be tested and the test area of the material layer attached to the cold surface side of the material to be tested. When there is no adhering material layer on the cold surface side of the material to be tested, a temperature sensor is configured in the test area of the material to be tested. The test area is either the material interface or the interior of the material.
3. The system according to claim 2, characterized in that, The temperature sensors are arranged in an array along the stacking direction of the multiple layers of materials in the test sample, and the multiple temperature sensors are sequentially set to correspond to one layer of material in the test sample. The heat flow sensors are arranged in an array along the stacking direction of the multiple layers of materials in the test sample. Multiple heat flow sensors are sequentially set for a layer surface. The layer surface includes the contact surface between two adjacent layers of materials, the surface between the test sample and the hot plate, and the surface between the test sample and the cold plate.
4. The system according to any one of claims 2-3, characterized in that, It also includes a sealed temperature and humidity control chamber; two temperature control devices are respectively disposed on opposite chamber walls of the sealed temperature and humidity control chamber, the temperature sensor is disposed on a first side wall perpendicular to the chamber wall, and the heat flow sensor is disposed on a second side wall perpendicular to the chamber wall.
5. The system according to claim 4, characterized in that, Both the temperature sensor and the heat flow sensor can be moved in a direction perpendicular to the bulkhead.
6. A method for analyzing the thermal insulation performance of multilayer materials, characterized in that, The method, applied to a processor in any one of claims 1-5, comprises: Establish a steady-state temperature in the sample to be tested, and determine the thermal conductivity of the test layer material based on the temperature fed back by the temperature sensor and the steady-state heat flux density fed back by the heat flux sensor. Based on the steady state, the system switches to a fluctuating state, and based on the transient heat flux density of the hot and cold surfaces of the test layer material fed back by the heat flux sensor, the heat storage status of the test layer material within a preset time period is determined.
7. The method according to claim 6, characterized in that, The determination of the thermal conductivity of the test layer material based on the temperature feedback from the temperature sensor and the steady-state heat flux density feedback from the heat flux sensor includes: Based on the temperature feedback from the temperature sensor, the thermal conductivity temperature difference generated by the thermal conductivity of the material layer under test, and the steady-state heat flux density feedback from the heat flux sensor, one or more of the thermal conductivity, thermal resistance, and thermal resistance contribution rate of the material layer under test are determined. The determination of the heat storage status of the test layer material within a preset time period based on the transient heat flux density of the hot and cold surfaces of the test layer material fed back by the heat flux sensor includes: The dynamic heat storage capacity of the test layer material is determined by integrating the difference between the transient heat flux density of the hot and cold surfaces of the test layer material fed back by the heat flux sensor over time within the preset time period.
8. The method according to claim 7, characterized in that, The method further includes: The Dynamic Heat Storage Index (DSI) is determined based on the ratio of the first value to the second value. The first value is the difference between the heat flux integral corresponding to the temperature rise period under the fluctuating state and the system heat storage correction value. The heat flux integral is the integral of the product of the transient heat flux density fed back by the heat flux sensor on the surface between the test sample and the hot plate and the effective test area of the test sample under the temperature rise period. The second value is the product of the effective test area of the test sample and the temperature rise amplitude under the fluctuating state.
9. The method according to claim 8, characterized in that, The method further includes: Generate one or more of the following: a layered thermal conductivity table, a layered dynamic heat storage curve, an overall dynamic heat storage report, and a thermal performance graph; the layered thermal conductivity table includes the thermal conductivity, thermal resistance, and thermal resistance contribution rate of each layer of the test sample; the layered dynamic heat storage curve is the curve showing the change of dynamic heat storage of each layer over time; the overall dynamic heat storage report is the curve showing the change of the DSI value, TSC value, and the difference between the heat flux integral under fluctuating conditions and the ratio of the system heat storage correction value to the effective test area over time; the thermal performance graph is a two-dimensional distribution map of the thermal conductivity and dynamic heat storage per unit thickness of each layer.