Method, system, device and medium for detecting thermophysical performance parameters of ice and snow materials

Abstract

The application provides a kind of ice and snow material thermophysical property parameter detection method, system, equipment and medium, it is related to material parameter detection technical field, method includes obtaining the hardware data of ice and snow material module to be measured, the ice and snow material module to be measured includes ice and snow material to be measured, isolation layer and heat insulation layer, the ice and snow material to be measured, the isolation layer and the heat insulation layer are sequentially connected;According to the steady heat transfer theory and the hardware data, the heat insulation layer thickness of the heat insulation layer is generated;According to the steady heat transfer theory and the heat insulation layer thickness, the heat insulation layer thermophysical property parameter is generated;According to the hardware data, the steady heat transfer theory, the heat insulation layer thickness and the heat insulation layer thermophysical property parameter, the ice and snow material thermophysical property parameter of the ice and snow material to be measured is generated.The detection method of the application can simply and efficiently complete ice and snow material thermophysical property parameter detection under the condition that the detection equipment and the detection equipment of the hot room room temperature meet the national standard.

Description

Technical Field

[0001] This invention relates to the field of material parameter testing technology, and more specifically, to a method, system, equipment, and medium for testing the thermophysical performance parameters of ice and snow materials. Background Technology

[0002] Ice shell architecture is a type of building constructed using ice and snow materials in cold regions. It serves as a venue for human activities in cold areas, such as exhibitions, performances, bars, and restaurants, and has great market value in the cultural heritage and tourism industries.

[0003] In existing technologies, the design and construction of ice shell buildings mainly focus on structural mechanics, with less research and testing on the thermophysical aspects of materials. Furthermore, existing testing equipment and methods require the material's cold-side environment temperature to be below 0°C and its hot-side environment temperature to be above 0°C in order to measure its thermophysical performance parameters. However, due to the unique characteristics of ice and snow materials used in ice shell buildings, they can only exist in low-temperature environments below 0°C. Above 0°C, the ice and snow materials will melt, thus affecting the accuracy of testing their thermophysical performance parameters. Therefore, existing testing equipment and methods cannot obtain accurate thermophysical performance parameters, resulting in a lack of basis and technical support for the internal thermal environment design of ice shell buildings, and significantly limiting the expansion of their internal functions. Summary of the Invention

[0004] The problem addressed by this invention is how to improve the detection accuracy of thermophysical performance parameters of ice and snow materials and obtain accurate thermophysical performance parameters.

[0005] To address the aforementioned problems, in a first aspect, the present invention provides a method for detecting the thermophysical performance parameters of ice and snow materials, comprising:

[0006] Acquire hardware data of the ice and snow material module to be tested, wherein the ice and snow material module to be tested includes the ice and snow material to be tested, an isolation layer and an insulation layer, and the ice and snow material to be tested, the isolation layer and the insulation layer are connected in sequence;

[0007] Based on the steady-state heat transfer theory and the hardware data, the insulation layer thickness of the insulation layer is generated.

[0008] Based on the steady-state heat transfer theory and the insulation layer thickness, the thermophysical performance parameters of the insulation layer are generated.

[0009] Based on the hardware data, the steady-state heat transfer theory, the insulation layer thickness, and the thermophysical performance parameters of the insulation layer, the thermophysical performance parameters of the ice and snow material to be tested are generated.

[0010] Optionally, generating the insulation layer thickness based on steady-state heat transfer theory and the hardware data includes:

[0011] Based on the steady-state heat transfer theory, a set of thickness formulas is constructed according to the hardware data, wherein the hardware data includes the insulation layer thickness of the insulation layer, the insulation layer thermal conductivity of the insulation layer, and the first insulation layer thermal conductivity of the insulation layer.

[0012] The thickness formula set includes:

[0013]

[0014] Where, d 隔离 λ is the thickness of the isolation layer. 隔离 Let d be the thermal conductivity of the isolation layer. 绝热 λ is the thickness of the insulation layer. 绝热.0 t0 is the thermal conductivity of the first insulation layer of the insulation layer, t1 is the hot side surface temperature of the ice and snow material to be tested, t2 is the cold side surface temperature of the ice and snow material to be tested, and q0 is the first heat flux density.

[0015] Based on the set of thickness formulas, the range of insulation layer thickness is generated;

[0016] The thickness of the insulation layer is determined according to the insulation layer thickness range and preset rules.

[0017] Optionally, the thermophysical performance parameters of the insulation layer include the thermal resistance of the insulation layer and the thermal conductivity of the second insulation layer. Generating the thermophysical performance parameters of the insulation layer based on the steady-state heat transfer theory and the thickness of the insulation layer includes:

[0018] A first testing environment is constructed using a wall heat transfer coefficient testing system and first preset environmental conditions. The first testing environment includes a second heat flux density, the hot side surface temperature of the insulation layer, and the cold side surface temperature of the insulation layer.

[0019] Based on the steady-state heat transfer theory, a thermal conductivity formula for the insulation layer is constructed according to the first detection environment and the insulation layer thickness. The thermal conductivity formula for the insulation layer includes:

[0020]

[0021] Among them, R 绝热 d is the thermal resistance of the insulation layer. 绝热 λ is the thickness of the insulation layer. 绝热.1 t1 is the thermal conductivity of the second insulation layer, t3 is the hot-side surface temperature of the insulation layer, q1 is the cold-side surface temperature of the insulation layer, and q1 is the second heat flux density.

[0022] The thermal physical performance parameters of the insulation layer are generated based on the thermal conductivity formula of the insulation layer.

[0023] Optionally, the thermophysical performance parameters of the ice and snow material include the thermal resistance, thermal conductivity, and heat transfer coefficient of the outer surface of the ice and snow material. The step of generating the thermophysical performance parameters of the ice and snow material to be tested based on the hardware data, the steady-state heat transfer theory, the insulation layer thickness, and the thermophysical performance parameters of the insulation layer includes:

[0024] A second testing environment was constructed using a wall heat transfer coefficient testing system and second preset environmental conditions;

[0025] Based on the second detection environment, the hardware data, the steady-state heat transfer theory, the insulation layer thickness, and the thermophysical performance parameters of the insulation layer, the thermal resistance and thermal conductivity of the ice and snow material are generated.

[0026] The heat transfer coefficient of the outer surface of the ice and snow material is generated based on the second detection environment.

[0027] Optionally, generating the thermal resistance and thermal conductivity of the ice and snow material based on the second detection environment, the hardware data, the steady-state heat transfer theory, the insulation layer thickness, and the thermophysical performance parameters of the insulation layer includes:

[0028] Based on the steady-state heat transfer theory, and according to the second detection environment, the hardware data, the insulation layer thickness, and the thermophysical performance parameters of the insulation layer, a thermal resistance formula for ice and snow materials is constructed. The second detection environment includes a third heat flux density, the hot-side surface temperature of the insulation layer, and the cold-side surface temperature of the ice and snow material under test. The hardware data includes the thermal resistance of the insulation layer, the material thickness of the ice and snow material under test, the insulation layer thickness, and the insulation layer thermal conductivity.

[0029] The thermal resistance formula for ice and snow materials includes:

[0030]

[0031] Among them, R 待测 R is the thermal resistance of the ice and snow material. 隔离 R is the thermal resistance of the isolation layer. 绝热 For the thermal resistance of the insulation layer, d 待测 λ is the material thickness of the ice and snow material to be tested. 待测 Let d be the thermal conductivity of the ice and snow material. 隔离 λ is the thickness of the isolation layer. 隔离 Let d be the thermal conductivity of the isolation layer. 绝热 λ is the thickness of the insulation layer. 绝热.1t1 is the thermal conductivity of the second insulation layer of the insulation layer, t2 is the hot side surface temperature of the insulation layer, t2 is the cold side surface temperature of the ice and snow material to be tested, and q2 is the third heat flux density.

[0032] Based on the thermal resistance formula of the ice and snow material, the thermal resistance and thermal conductivity of the ice and snow material are generated.

[0033] Optionally, generating the heat transfer coefficient of the outer surface of the ice and snow material based on the second detection environment includes:

[0034] Based on the second detection environment, a formula for the heat transfer coefficient of the outer surface of the ice and snow material is constructed, wherein the second detection environment includes the third heat flux density, the cold side surface temperature of the ice and snow material to be tested, and the cold side ambient temperature of the ice and snow material to be tested;

[0035] The formula for the heat transfer coefficient of the outer surface of the ice and snow material includes:

[0036]

[0037] Wherein, α is the heat transfer coefficient of the outer surface of the ice and snow material, t2 is the cold side surface temperature of the ice and snow material to be tested, t4 is the cold side ambient temperature of the ice and snow material to be tested, and q2 is the third heat flux density;

[0038] The heat transfer coefficient of the outer surface of the ice and snow material is generated according to the formula for the heat transfer coefficient of the outer surface of the ice and snow material.

[0039] Optionally, the insulation layer thickness, determined according to the insulation layer thickness range and a preset rule, includes:

[0040] The minimum value within the range of insulation layer thickness is selected as the insulation layer thickness.

[0041] Secondly, the present invention provides a system for detecting the thermophysical performance parameters of ice and snow materials, comprising:

[0042] The acquisition module is used to acquire hardware data of the ice and snow material module to be tested. The ice and snow material module to be tested includes the ice and snow material to be tested, the isolation layer and the insulation layer, which are connected in sequence.

[0043] The thickness module is used to generate the insulation layer thickness of the insulation layer based on the steady-state heat transfer theory and the hardware data.

[0044] The insulation layer parameter module is used to generate the thermophysical performance parameters of the insulation layer based on the steady-state heat transfer theory and the insulation layer thickness.

[0045] The material parameter module is used to generate the thermophysical performance parameters of the ice and snow material to be tested based on the hardware data, the steady-state heat transfer theory, the insulation layer thickness, and the thermophysical performance parameters of the insulation layer.

[0046] Thirdly, the present invention provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the method for detecting the thermophysical performance parameters of ice and snow materials as described above.

[0047] Fourthly, the present invention provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the method for detecting the thermophysical performance parameters of ice and snow materials as described above.

[0048] The beneficial effects of the method, system, equipment, and medium for detecting the thermophysical performance parameters of ice and snow materials of the present invention are as follows:

[0049] The insulation layer of the ice and snow material module prevents melting of the material during testing due to temperatures exceeding 0°C on one side. This allows for simple and efficient testing of the thermophysical properties of the ice and snow material using standard testing equipment, such as wall heat transfer coefficient testing systems, and within the ambient temperature of the testing chamber. This approach offers high applicability and yields highly accurate results. Furthermore, the isolation layer separates the ice and snow material from the insulation layer, preventing moisture absorption by the insulation layer due to the characteristics of the ice and snow material, which could affect the insulation board's insulation performance. The thermal effect improves the accuracy of thermophysical performance parameter testing for ice and snow materials. Since a large insulation layer thickness can lead to excessively low surface temperatures on the hot side of the tested ice and snow material, which is detrimental to the detection of its thermophysical performance parameters, the optimal insulation layer thickness is obtained through steady-state heat transfer theory and the hardware data of the ice and snow material module. This allows the insulation layer to better reduce and control the surface temperature on the hot side of the tested ice and snow material. Furthermore, the thermophysical performance parameters of the insulation layer are generated using steady-state heat transfer theory and the insulation layer thickness. Finally, by combining the hardware data, steady-state heat transfer theory, insulation layer thickness, and insulation layer thermophysical performance parameters, accurate thermophysical performance parameters of the tested ice and snow material can be obtained. Attached Figure Description

[0050] Figure 1 A schematic flowchart of the method for detecting the thermophysical performance parameters of ice and snow materials provided in an embodiment of the present invention;

[0051] Figure 2 This is a schematic diagram of the structure of the ice and snow material module to be tested provided in an embodiment of the present invention;

[0052] Figure 3 This is a schematic diagram of the structure of the thermophysical performance parameter detection system for ice and snow materials provided in an embodiment of the present invention.

[0053] Explanation of reference numerals in the attached figures:

[0054] 1-The ice and snow material to be tested, 2-Insulation layer, 3-Insulation layer. Detailed Implementation

[0055] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Although some embodiments of the present invention are shown in the drawings, it should be understood that the present invention can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of the present invention. It should be understood that the accompanying drawings and embodiments of the present invention are for illustrative purposes only and are not intended to limit the scope of protection of the present invention.

[0056] It should be understood that the various steps described in the method embodiments of the present invention may be performed in different orders and / or in parallel. Furthermore, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present invention is not limited in this respect.

[0057] The term "comprising" and its variations as used herein are open-ended, meaning "including but not limited to". The term "based on" means "at least partially based on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments"; the term "optionally" means "optional embodiments". Definitions of other terms will be given in the following description. It should be noted that the concepts of "first", "second", etc., mentioned in this invention are used only to distinguish different devices, modules, or units, and are not intended to limit the order of functions performed by these devices, modules, or units or their interdependencies.

[0058] It should be noted that the terms "a" and "a plurality of" used in this invention are illustrative rather than restrictive. Those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0059] In existing technologies, the methods for detecting the thermophysical properties of materials mainly include four types: large-scale equipment testing, on-site testing, instrument testing, and inference estimation.

[0060] Large-scale equipment testing refers to the use of wall heat transfer coefficient testing systems that conform to national standards, such as "Determination, Calibration and Protective Hot Box Method for Steady-State Heat Transfer Properties of Insulation Materials" (GBT 13475) or "Determination of Steady-State Thermal Resistance and Related Properties of Insulation Materials by Heat Flow Meter Method" (GBT 10295), to test the heat transfer coefficient and surface heat transfer coefficient of materials. After testing, the thermal conductivity of the tested material can be derived based on steady-state heat transfer theory for use in building thermal and thermal environment design. However, since national standards are aimed at conventional building materials and do not consider the special case of ice and snow materials, the temperature of the hot chamber or hot box side of such equipment is above 0°C, making it unsuitable for testing ice and snow materials. Furthermore, the cost of developing equipment for testing ice and snow materials is high, resulting in a low return on investment, and modifying or developing new testing equipment specifically for testing the thermophysical performance parameters of ice and snow materials is not feasible.

[0061] On-site testing refers to measuring the thermophysical properties of ice and snow materials in ice-shell structures. However, on-site testing is inevitably affected by numerous uncontrollable factors, leading to low accuracy. More importantly, on-site testing is conducted amidst diurnal temperature fluctuations, which are unstable and constitute unsteady-state heat transfer in heat transfer theory. Such on-site testing involves selecting a relatively long time period (generally over 96 hours) and averaging the data, approximating a non-steady-state heat transfer problem as a steady-state one. This approximation itself introduces significant bias. Furthermore, since ice and snow materials only exist in winter for a short period, it is difficult to find periods with minimal fluctuations in external temperature, further exacerbating these fluctuations. Under these circumstances, the bias from approximating unsteady conditions as steady-state conditions becomes even more pronounced. Therefore, the accuracy of thermophysical properties such as thermal conductivity obtained through on-site testing is generally low.

[0062] Instrumental testing refers to measuring thermal conductivity using instruments such as the Hot Disk thermal conductivity meter, based on the principle of dynamic heat transfer, and offers high accuracy. However, ice and snow materials are mixtures, such as composite ice materials made by mixing, stirring, and pouring paper fibers and water in a certain proportion, making it difficult to process them into a "homogeneous" material on a small scale. Theoretically, thermal conductivity meters are not suitable for testing the thermal conductivity of building materials with multiple components, i.e., they are not applicable to non-homogeneous materials like ice and snow. Furthermore, when using various thermal conductivity meters to test the thermal conductivity of ice and snow materials, the ambient temperature must be ensured to be below 0°C, which is more costly than ensuring the ambient temperature is above 0°C. In conclusion, instrumental testing is unsuitable for measuring the thermophysical properties of ice and snow materials.

[0063] Estimation by inference refers to making estimates based on existing data about the material. For example, the thermal conductivity and heat capacity of pure ice can be obtained by consulting relevant data. Similarly, the thermal conductivity of composite ice formed by adding materials such as paper fibers and wood chips to water can be estimated based on existing data. However, due to the complex structure of the mixture, the accuracy of the estimation is not high. The thermophysical properties of ice and snow materials are related not only to the snow formation process but also primarily to the density of the compressed material. Therefore, parameters such as the thermal conductivity of ice and snow materials are often estimated based on density, and the resulting deviations are still difficult to eliminate.

[0064] like Figure 1 As shown, this embodiment of the invention provides a method for detecting the thermophysical performance parameters of ice and snow materials, including:

[0065] S1, acquire the hardware data of the ice and snow material module to be tested. The ice and snow material module to be tested includes ice and snow material 1 to be tested, isolation layer 2 and heat insulation layer 3, which are connected in sequence.

[0066] Specifically, ice and snow materials refer to materials used to construct ice shell buildings, such as composite ice materials. The method for detecting the thermophysical performance parameters of ice and snow materials in this invention constructs a testing environment using existing testing equipment, such as a wall heat transfer coefficient testing system, to complete the detection of these parameters. Figure 2 The ice and snow material module shown includes ice and snow material 1, isolation layer 2, and insulation layer 3. The cross-sectional shapes of ice and snow material 1, isolation layer 2, and insulation layer 3 are compatible. Isolation layer 2 is used to isolate ice and snow material 1 and insulation layer 3 to prevent insulation layer 3 from getting damp due to ice and snow material 1. Insulation layer 3 is used to reduce and control the hot side surface temperature of ice and snow material to ensure that the temperature is below 0°C, thereby completing the test.

[0067] For example, the testing environment includes a cold chamber temperature simulating outdoor temperature conditions, which can be set to approximately -15°C, and a hot chamber temperature simulating indoor temperature conditions, which can be set to approximately 20°C. The isolation layer 2 can be made of a material with sufficient strength and high thermal conductivity, such as steel plate, so that the isolation layer 2 can bear the load of the ice and snow material 1 to be tested. This facilitates casting and processing into the ice and snow material module to be tested. Simultaneously, a high thermal conductivity means strong heat conduction capacity, minimal impact on parameter detection, and improved testing accuracy. The insulation layer 3 can also serve as a thermal insulation layer. The insulation layer 3 can be made of materials with low compression ratio, low water absorption rate, and a smooth appearance, such as extruded polystyrene board, polystyrene board, polyurethane board, rock wool board, ceramic insulation materials, and silicate insulation materials.

[0068] In one embodiment, prior to acquiring the hardware data of the ice and snow material module to be tested, the method further includes:

[0069] Obtain the ice and snow material 1 to be tested, the isolation layer 2, and the heat insulation layer 3;

[0070] The ice and snow material 1 to be tested is poured or pressed onto one side of the isolation layer 2, and the heat insulation layer 3 is placed on the other side of the isolation layer 2 to construct the ice and snow material module to be tested.

[0071] Specifically, when outdoor temperature conditions permit in winter, the ice and snow material 1 to be tested can be poured or pressed onto one side of the insulation layer 2 outdoors. The dimensions of the ice and snow material 1, the insulation layer 2, and the insulation layer 3 can be set according to actual conditions, and the length and width of the ice and snow material 1 to be tested should not be less than 10 times its thickness, so that steady-state heat transfer can be simplified into a one-dimensional heat transfer problem, which is convenient for subsequent calculations. For example, the thickness of the insulation layer 2 can be set to 5 mm, and the thickness of the ice and snow material 1 to be tested can be set to 100 mm.

[0072] It should be noted that the wall heat transfer coefficient testing system refers to testing equipment that conforms to national standards. Any testing equipment similar to the wall heat transfer coefficient testing system can be used for the testing method of thermophysical performance parameters of ice and snow materials in this invention, and is not limited here. National standards include GB / T 13475 Determination, Calibration and Protective Heat Chamber Method for Steady-State Heat Transfer Properties of Insulation Materials and GB / T 10295 Determination of Steady-State Thermal Resistance and Related Properties of Insulation Materials by Heat Flow Meter Method, etc.

[0073] S2, Based on the steady-state heat transfer theory and the hardware data, the insulation layer thickness of the insulation layer 3 is generated.

[0074] For example, the hardware data includes the insulation layer thickness of the insulation layer 2, the insulation layer thermal conductivity of the insulation layer 2, and the first insulation layer thermal conductivity of the insulation layer 3.

[0075] In one embodiment, generating the insulation layer thickness of the insulation layer 3 based on steady-state heat transfer theory and the hardware data includes:

[0076] Based on the steady-state heat transfer theory, a set of thickness formulas is constructed according to the hardware data, wherein the hardware data includes the insulation layer thickness of the insulation layer 2, the insulation layer thermal conductivity of the insulation layer 2, and the first thermal conductivity of the insulation layer 3.

[0077] The thickness formula set includes:

[0078]

[0079] Where, d 隔离 λ is the thickness of the isolation layer 2. 隔离 Let d be the thermal conductivity of the isolation layer 2. 绝热 λ is the thickness of the insulation layer.绝热.0 t0 is the thermal conductivity of the first insulation layer of the insulation layer 3, t1 is the hot side surface temperature of the ice and snow material 1 to be tested, t2 is the cold side surface temperature of the ice and snow material 1 to be tested, and q0 is the first heat flux density.

[0080] Based on the set of thickness formulas, the range of insulation layer thickness is generated;

[0081] The thickness of the insulation layer is determined according to the insulation layer thickness range and preset rules.

[0082] Specifically, the hardware data refers to the dimensions and correlation coefficients of the ice and snow material 1, the isolation layer 2, and the insulation layer 3 under test. The steady-state heat transfer theory states that "the total thermal resistance of a multi-layer material is equal to the sum of the thermal resistances of each layer." Based on the steady-state heat transfer theory, a set of thermal conductivity formulas for the ice and snow material module under test can be generated. The set of thermal conductivity formulas includes:

[0083]

[0084] By combining the three formulas in the thermal conductivity formula set, the thickness formula set can be obtained.

[0085] Among them, R 待测 R is the thermal resistance of the ice and snow material 1 to be tested. 隔离 R is the thermal resistance of the isolation layer. 绝热 d is the thermal resistance of the insulation layer 3. 待测 λ is the material thickness of the ice and snow material 1 to be tested. 预估 Let d be the estimated thermal conductivity of the ice and snow material 1 to be tested. 隔离 λ is the thickness of the isolation layer. 隔离 d is the thermal conductivity of the insulation layer. 绝热 λ is the thickness of the insulation layer. 绝热.0 λ is the thermal conductivity of the first insulation layer, t0 is the hot-side surface temperature of the ice and snow material 1 under test, t1 is the hot-side surface temperature of the insulation layer 3, t2 is the cold-side surface temperature of the ice and snow material 1 under test, and q0 is the first heat flux density; where λ 预估 The actual data should be unknown, but it is an estimated value, R, used to calculate the optimal insulation layer thickness. 隔离 R 绝热 d 待测 d 隔离 , λ 隔离 , λ 绝热.0 t1, t2, and q0 can all be obtained by searching existing data or through observation. t0 is the hot-side surface temperature of the ice and snow material 1 to be tested, and is unknown, such as... Figure 2As shown, t0 is also the temperature between the ice and snow material 1 to be tested and the isolation layer 2. In order to avoid the ice and snow material 1 to be tested from melting, t0 has a range of values, that is, t0 is less than or equal to 0℃. At the same time, considering other uncertain factors, this invention sets t0≤-5.

[0086] In one embodiment, the insulation layer thickness, determined according to the insulation layer thickness range and a preset rule, includes:

[0087] The minimum value within the range of insulation layer thickness is selected as the insulation layer thickness.

[0088] Specifically, based on the thickness formula set, the range of insulation layer thickness can be obtained as follows:

[0089]

[0090] According to the thickness formula set, when the insulation layer thickness d 绝热 The larger the thickness d, the smaller the surface temperature t0 of the hot side of the tested ice and snow material 1; conversely, the larger the thickness d, the smaller the surface temperature t0 of the hot side of the tested ice and snow material 1. 绝热 The smaller the temperature, the greater the surface temperature t0 of the hot side of the ice and snow material 1 under test. Since the present invention first sets the range of t0, that is, limits the maximum value of t0, the insulation layer thickness is taken as the minimum value of the insulation layer thickness range.

[0091] S3. Based on the steady-state heat transfer theory and the insulation layer thickness, generate the thermophysical performance parameters of the insulation layer.

[0092] Specifically, the steady-state heat transfer theory states that "the total thermal resistance of a multilayer material is equal to the sum of the thermal resistances of each layer." By using the steady-state heat transfer theory and the insulation layer thickness in the wall heat transfer coefficient detection system, the thermophysical performance parameters of the insulation layer can be obtained.

[0093] In one embodiment, the thermophysical performance parameters of the insulation layer include the thermal resistance of the insulation layer and the thermal conductivity of the second insulation layer. Generating the thermophysical performance parameters of the insulation layer based on the steady-state heat transfer theory and the thickness of the insulation layer includes:

[0094] A first testing environment is constructed using a wall heat transfer coefficient testing system and a first preset environmental condition. The first testing environment includes a second heat flux density, the hot side surface temperature of the insulation layer (3), and the cold side surface temperature of the insulation layer (3).

[0095] Based on the steady-state heat transfer theory, a thermal conductivity formula for the insulation layer is constructed according to the first detection environment and the insulation layer thickness. The thermal conductivity formula for the insulation layer includes:

[0096]

[0097] Among them, R 绝热d is the thermal resistance of the insulation layer. 绝热 λ is the thickness of the insulation layer. 绝热.1 t1 is the thermal conductivity of the second insulation layer, t3 is the hot side surface temperature of the insulation layer 3, q1 is the cold side surface temperature of the insulation layer 3, and q1 is the second heat flux density.

[0098] The thermal physical performance parameters of the insulation layer are generated based on the thermal conductivity formula of the insulation layer.

[0099] Specifically, before testing the thermophysical performance parameters of the ice and snow material 1 under test, the thermophysical performance parameters of the insulation layer 3 in the ice and snow material module under test are retested, namely the thermal resistance of the insulation layer and the thermal conductivity of the second insulation layer, and these are used as inputs for the testing of the thermophysical performance parameters of the ice and snow material to improve the testing accuracy. The first preset environmental conditions include a cold chamber temperature simulating outdoor temperature conditions and a hot chamber temperature simulating indoor temperature conditions; the constructed first testing environment includes a cold chamber temperature set to -15℃ and a hot chamber temperature set to 20℃. Data of t1, t3, and q1 can be obtained through the first testing environment.

[0100] S4. Based on the hardware data, the steady-state heat transfer theory, the insulation layer thickness, and the insulation layer thermophysical performance parameters, generate the thermophysical performance parameters of the ice and snow material 1 to be tested.

[0101] Specifically, in the wall heat transfer coefficient detection system, based on the steady-state heat transfer theory and by using hardware data on the insulation layer thickness and the insulation layer's thermophysical performance parameters, the thermophysical performance parameters of the ice and snow materials can be obtained.

[0102] This invention utilizes an insulation layer on the ice and snow material module to prevent melting of the ice and snow material during testing, which can occur when one side of the material is above 0°C. This allows for simple and efficient testing of the thermophysical properties of ice and snow materials under standard testing equipment and ambient temperature conditions within the equipment's heated chamber. It offers high applicability and yields highly accurate results. Furthermore, an isolation layer within the ice and snow material module separates the material from the insulation layer, preventing moisture absorption that could affect the insulation's performance and thus improving the accuracy of thermophysical property parameter testing. This invention solves the problems of existing methods—large-scale equipment testing, on-site testing, instrument testing, and inference estimation—which suffer from limitations in detecting ice and snow materials, high costs, and low accuracy.

[0103] In one embodiment, the thermophysical performance parameters of the ice and snow material include the thermal resistance, thermal conductivity, and heat transfer coefficient of the outer surface of the ice and snow material. The step of generating the thermophysical performance parameters of the ice and snow material 1 to be tested based on the hardware data, the steady-state heat transfer theory, the insulation layer thickness, and the thermophysical performance parameters of the insulation layer includes:

[0104] A second testing environment was constructed using a wall heat transfer coefficient testing system and second preset environmental conditions;

[0105] Based on the second detection environment, the hardware data, the steady-state heat transfer theory, the insulation layer thickness, and the thermophysical performance parameters of the insulation layer, the thermal resistance and thermal conductivity of the ice and snow material are generated.

[0106] The heat transfer coefficient of the outer surface of the ice and snow material is generated based on the second detection environment.

[0107] Specifically, a second testing environment is constructed using a wall heat transfer coefficient testing system. The second preset environmental conditions include a cold room temperature simulating outdoor temperature conditions and a hot room temperature simulating indoor temperature conditions; the constructed second testing environment includes a cold room temperature set to -15℃ and a hot room temperature set to 20℃. Based on the obtained data and steady-state heat transfer theory, the thermophysical performance parameters of the ice and snow materials can be obtained.

[0108] Optionally, generating the thermal resistance and thermal conductivity of the ice and snow material based on the second detection environment, the hardware data, the steady-state heat transfer theory, the insulation layer thickness, and the thermophysical performance parameters of the insulation layer includes:

[0109] Based on the steady-state heat transfer theory, and according to the second detection environment, the hardware data, the insulation layer thickness, and the thermophysical performance parameters of the insulation layer, a thermal resistance formula for ice and snow materials is constructed. The second detection environment includes the third heat flux density, the hot-side surface temperature of the insulation layer 3, and the cold-side surface temperature of the ice and snow material 1 to be tested. The hardware data includes the thermal resistance of the insulation layer, the material thickness of the ice and snow material 1 to be tested, the insulation layer thickness of the insulation layer 2, and the thermal conductivity of the insulation layer 2.

[0110] The thermal resistance formula for ice and snow materials includes:

[0111]

[0112] Among them, R 待测 R is the thermal resistance of the ice and snow material. 隔离 R is the thermal resistance of the isolation layer. 绝热 For the thermal resistance of the insulation layer, d 待测 λ is the material thickness of the ice and snow material 1 to be tested. 待测Let d be the thermal conductivity of the ice and snow material. 隔离 λ is the thickness of the isolation layer 2. 隔离 Let d be the thermal conductivity of the isolation layer 2. 绝热 λ is the thickness of the insulation layer. 绝热.1 t1 is the thermal conductivity of the second insulation layer of the insulation layer 3, t2 is the hot side surface temperature of the insulation layer 3, t2 is the cold side surface temperature of the ice and snow material 1 to be tested, and q2 is the third heat flux density.

[0113] Based on the thermal resistance formula of the ice and snow material, the thermal resistance and thermal conductivity of the ice and snow material are generated.

[0114] Specifically, based on the steady-state heat transfer theory that "the total thermal resistance of a multilayer material is equal to the sum of the thermal resistances of each layer" and various data, a thermal resistance formula for ice and snow materials can be constructed. By substituting the known and detected data into the thermal resistance formula for ice and snow materials, the thermal resistance and thermal conductivity of ice and snow materials can be obtained.

[0115] Optionally, generating the heat transfer coefficient of the outer surface of the ice and snow material based on the second detection environment includes:

[0116] Based on the second detection environment, a formula for the heat transfer coefficient of the outer surface of the ice and snow material is constructed, wherein the second detection environment includes the third heat flux density, the cold side surface temperature of the ice and snow material 1 to be tested, and the cold side ambient temperature of the ice and snow material 1 to be tested.

[0117] The formula for the heat transfer coefficient of the outer surface of the ice and snow material includes:

[0118]

[0119] Wherein, α is the heat transfer coefficient of the outer surface of the ice and snow material, t2 is the cold side surface temperature of the ice and snow material 1 to be tested, t4 is the cold side ambient temperature of the ice and snow material 1 to be tested, and q2 is the third heat flux density.

[0120] The heat transfer coefficient of the outer surface of the ice and snow material is generated according to the formula for the heat transfer coefficient of the outer surface of the ice and snow material.

[0121] Specifically, based on steady-state heat transfer theory and the second detection environment, a formula for the heat transfer coefficient of the outer surface of ice and snow materials is constructed. By substituting the known and detected data into the formula for the heat transfer coefficient of the outer surface of ice and snow materials, the heat transfer coefficient of the outer surface of ice and snow materials can be obtained.

[0122] like Figure 3 As shown, another embodiment of the present invention provides a system for detecting the thermophysical performance parameters of ice and snow materials, comprising:

[0123] The acquisition module is used to acquire hardware data of the ice and snow material module to be tested. The ice and snow material module to be tested includes ice and snow material 1, isolation layer 2 and heat insulation layer 3, which are connected in sequence.

[0124] The thickness module is used to generate the insulation layer thickness of the insulation layer 3 based on the steady-state heat transfer theory and the hardware data.

[0125] The insulation layer parameter module is used to generate the thermophysical performance parameters of the insulation layer based on the steady-state heat transfer theory and the insulation layer thickness.

[0126] The material parameter module is used to generate the thermophysical performance parameters of the ice and snow material 1 to be tested based on the hardware data, the steady-state heat transfer theory, the insulation layer thickness, and the thermophysical performance parameters of the insulation layer.

[0127] Another embodiment of the present invention provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the method for detecting the thermophysical performance parameters of ice and snow materials as described above.

[0128] Another embodiment of the present invention provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the method for detecting the thermophysical performance parameters of ice and snow materials as described above.

[0129] While the present invention has been disclosed above, its scope of protection is not limited thereto. Those skilled in the art can make various changes and modifications without departing from the spirit and scope of the invention, and all such changes and modifications will fall within the scope of protection of the present invention.

Claims

1. A method for testing the thermophysical performance parameters of ice and snow materials, characterized in that, include: Obtain hardware data of the ice and snow material module to be tested. The ice and snow material module to be tested includes the ice and snow material to be tested (1), the isolation layer (2) and the insulation layer (3), which are connected in sequence. Based on the steady-state heat transfer theory and the hardware data, the insulation layer thickness of the insulation layer (3) is generated; Based on the steady-state heat transfer theory and the insulation layer thickness, the thermophysical performance parameters of the insulation layer are generated. Based on the hardware data, the steady-state heat transfer theory, the insulation layer thickness, and the insulation layer thermophysical performance parameters, the thermophysical performance parameters of the ice and snow material (1) to be tested are generated. The thermophysical performance parameters of the ice and snow material include the thermal resistance, thermal conductivity, and heat transfer coefficient of the outer surface of the ice and snow material. The generation of the thermophysical performance parameters of the ice and snow material (1) to be tested, based on the hardware data, the steady-state heat transfer theory, the insulation layer thickness, and the thermophysical performance parameters of the insulation layer, includes: A second testing environment was constructed using a wall heat transfer coefficient testing system and second preset environmental conditions; Based on the second detection environment, the hardware data, the steady-state heat transfer theory, the insulation layer thickness, and the thermophysical performance parameters of the insulation layer, the thermal resistance and thermal conductivity of the ice and snow material are generated; based on the second detection environment, the heat transfer coefficient of the outer surface of the ice and snow material is generated.

2. The method for detecting the thermophysical performance parameters of ice and snow materials according to claim 1, characterized in that, The step of generating the insulation layer thickness of the insulation layer (3) based on the steady-state heat transfer theory and the hardware data includes: Based on the steady-state heat transfer theory, a set of thickness formulas is constructed according to the hardware data, wherein the hardware data includes the insulation layer thickness of the insulation layer (2), the insulation layer thermal conductivity of the insulation layer (2), and the first insulation layer thermal conductivity of the insulation layer (3). The thickness formula set includes: ； in, The thickness of the isolation layer (2) is given by the following formula: The thermal conductivity of the isolation layer (2) is given by [reference needed]. The thickness of the insulation layer is [missing information]. The thermal conductivity of the first insulation layer of the insulation layer (3) is given by [reference to thermal conductivity]. The surface temperature of the hot side of the ice and snow material (1) to be tested. The thermal side surface temperature of the insulation layer (3) is... The cold-side surface temperature of the ice and snow material (1) to be tested. The first heat flux density; Based on the set of thickness formulas, the range of insulation layer thickness is generated; The thickness of the insulation layer is determined according to the insulation layer thickness range and preset rules.

3. The method for detecting the thermophysical performance parameters of ice and snow materials according to claim 1, characterized in that, The thermophysical performance parameters of the insulation layer include the thermal resistance of the insulation layer and the thermal conductivity of the second insulation layer. The generation of these thermophysical performance parameters based on the steady-state heat transfer theory and the insulation layer thickness includes: A first testing environment is constructed using a wall heat transfer coefficient testing system and a first preset environmental condition. The first testing environment includes a second heat flux density, the hot side surface temperature of the insulation layer (3), and the cold side surface temperature of the insulation layer (3). Based on the steady-state heat transfer theory, a thermal conductivity formula for the insulation layer is constructed according to the first detection environment and the insulation layer thickness. The thermal conductivity formula for the insulation layer includes: ； in, The thermal resistance of the insulation layer, The thickness of the insulation layer is [missing information]. The thermal conductivity of the second insulation layer is... The thermal side surface temperature of the insulation layer (3) is... The temperature of the cold side surface of the insulation layer (3) is the temperature of the cold side surface. This is the second heat flux density; The thermal physical performance parameters of the insulation layer are generated based on the thermal conductivity formula of the insulation layer.

4. The method for detecting the thermophysical performance parameters of ice and snow materials according to claim 1, characterized in that, The thermophysical performance parameters of the ice and snow material include the thermal resistance, thermal conductivity, and heat transfer coefficient of the outer surface of the ice and snow material. The generation of the thermophysical performance parameters of the ice and snow material (1) to be tested, based on the hardware data, the steady-state heat transfer theory, the insulation layer thickness, and the thermophysical performance parameters of the insulation layer, includes: A second testing environment was constructed using a wall heat transfer coefficient testing system and second preset environmental conditions; Based on the second detection environment, the hardware data, the steady-state heat transfer theory, the insulation layer thickness, and the thermophysical performance parameters of the insulation layer, the thermal resistance and thermal conductivity of the ice and snow material are generated. The heat transfer coefficient of the outer surface of the ice and snow material is generated based on the second detection environment.

5. The method for detecting the thermophysical performance parameters of ice and snow materials according to claim 4, characterized in that, The step of generating the thermal resistance and thermal conductivity of the ice and snow material based on the second detection environment, the hardware data, the steady-state heat transfer theory, the insulation layer thickness, and the thermophysical performance parameters of the insulation layer includes: Based on the steady-state heat transfer theory, a thermal resistance formula for ice and snow materials is constructed according to the second detection environment, the hardware data, the thickness of the insulation layer, and the thermophysical performance parameters of the insulation layer. The second detection environment includes the third heat flux density, the hot side surface temperature of the insulation layer (3), and the cold side surface temperature of the ice and snow material (1) to be tested. The hardware data includes the thermal resistance of the insulation layer, the material thickness of the ice and snow material (1) to be tested, the insulation layer thickness of the insulation layer (2), and the insulation layer thermal conductivity of the insulation layer (2). The thermal resistance formula for ice and snow materials includes: ； in, The thermal resistance of the ice and snow material is... The thermal resistance of the isolation layer, For the thermal resistance of the insulation layer, The thickness of the ice and snow material (1) to be tested. The thermal conductivity of the ice and snow material is given. The thickness of the isolation layer (2) is given by the following formula: The thermal conductivity of the isolation layer (2) is given by [reference needed]. The thickness of the insulation layer is [missing information]. The thermal conductivity of the second insulation layer of the insulation layer (3) is given. The thermal side surface temperature of the insulation layer (3) is... The cold-side surface temperature of the ice and snow material (1) to be tested. The third heat flux density; Based on the thermal resistance formula of the ice and snow material, the thermal resistance and thermal conductivity of the ice and snow material are generated.

6. The method for detecting the thermophysical performance parameters of ice and snow materials according to claim 4, characterized in that, The step of generating the heat transfer coefficient of the outer surface of the ice and snow material according to the second detection environment includes: Based on the second detection environment, a formula for the heat transfer coefficient of the outer surface of the ice and snow material is constructed, wherein the second detection environment includes the third heat flux density, the cold side surface temperature of the ice and snow material (1) to be tested, and the cold side ambient temperature of the ice and snow material (1) to be tested; The formula for the heat transfer coefficient of the outer surface of the ice and snow material includes: ； in, The heat transfer coefficient of the outer surface of the ice and snow material is given. The cold-side surface temperature of the ice and snow material (1) to be tested. The cold-side ambient temperature of the ice and snow material (1) to be tested. The third heat flux density; The heat transfer coefficient of the outer surface of the ice and snow material is generated according to the formula for the heat transfer coefficient of the outer surface of the ice and snow material.

7. The method for detecting the thermophysical performance parameters of ice and snow materials according to claim 1, characterized in that, The insulation layer thickness, according to the insulation layer thickness range and preset rules, includes: The minimum value within the range of insulation layer thickness is selected as the insulation layer thickness.

8. A system for testing the thermophysical performance parameters of ice and snow materials, characterized in that, include: The acquisition module is used to acquire the hardware data of the ice and snow material module to be tested. The ice and snow material module to be tested includes the ice and snow material to be tested (1), the isolation layer (2) and the insulation layer (3), which are connected in sequence. The thickness module is used to generate the insulation layer thickness of the insulation layer (3) based on the steady-state heat transfer theory and the hardware data. The insulation layer parameter module is used to generate the thermophysical performance parameters of the insulation layer based on the steady-state heat transfer theory and the insulation layer thickness. The material parameter module is used to generate the ice and snow material thermophysical performance parameters of the ice and snow material (1) to be tested based on the hardware data, the steady-state heat transfer theory, the insulation layer thickness and the insulation layer thermophysical performance parameters. The thermophysical performance parameters of the ice and snow material include the thermal resistance, thermal conductivity, and heat transfer coefficient of the outer surface of the ice and snow material. The generation of the thermophysical performance parameters of the ice and snow material (1) to be tested, based on the hardware data, the steady-state heat transfer theory, the insulation layer thickness, and the thermophysical performance parameters of the insulation layer, includes: A second testing environment was constructed using a wall heat transfer coefficient testing system and second preset environmental conditions; Based on the second detection environment, the hardware data, the steady-state heat transfer theory, the insulation layer thickness, and the thermophysical performance parameters of the insulation layer, the thermal resistance and thermal conductivity of the ice and snow material are generated; based on the second detection environment, the heat transfer coefficient of the outer surface of the ice and snow material is generated.

9. A computer device, characterized in that, The method includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the method for detecting the thermophysical performance parameters of ice and snow materials as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, which, when executed by a processor, implements the method for detecting the thermophysical performance parameters of ice and snow materials as described in any one of claims 1 to 7.

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