Method for evaluating human thermal comfort of a radiation-cooled fabric

Abstract

This invention discloses a method for evaluating the thermal comfort of radiative cooling fabrics, comprising: acquiring optical performance parameters of the radiative cooling fabric to be tested; collecting temperature data at multiple measurement locations when a person wears the fabric under set environmental conditions to construct human temperature change parameters; and simultaneously acquiring human thermal sensation evaluation values ​​under reference and wearing conditions to determine human thermal sensation change parameters. The optical performance parameters, human temperature change parameters, and human thermal sensation change parameters are standardized to obtain dimensionless evaluation parameters, which are then weighted and fused based on weighting coefficients to construct a human thermal comfort evaluation index. This index can be used for performance comparison and structural optimization analysis of different radiative cooling fabrics. This invention integrates material optical properties, human physiological response, and subjective thermal sensation to achieve multi-dimensional unified quantitative evaluation, improving the accuracy and comparability of the thermal comfort performance evaluation of radiative cooling fabrics.

Description

Technical Field

[0001] This invention belongs to the technical field of performance evaluation of functional textiles, and specifically relates to a method for evaluating human thermal comfort of radiation-cooled fabrics. Background Technology

[0002] With the increasing frequency of extreme high-temperature environments, radiation-cooling fabrics, which can achieve passive cooling without external energy input, have significant application prospects in the field of personal thermal management. In existing technologies, the performance evaluation of radiation-cooling fabrics mainly relies on optical parameters such as solar reflectivity and mid-infrared emissivity, or on surface temperature test results under experimental conditions.

[0003] However, the aforementioned evaluation methods have significant limitations. On the one hand, a single optical parameter is insufficient to reflect the overall cooling effect of fabrics in actual wearing environments; on the other hand, evaluation methods based on surface temperature fail to fully consider the body's own thermoregulation process and the differences in temperature response between different body parts, resulting in discrepancies between the evaluation results and actual human thermal comfort perception. Furthermore, subjective thermal sensation, as an important indicator for measuring human thermal comfort, has not been effectively integrated into the existing evaluation system.

[0004] In the prior art, CN120708909A discloses a method for evaluating thermal comfort based on individual thermal regulation. This method calculates and evaluates human thermal comfort through the human body thermal balance equation, a segmental heat transfer model of the human body, and the mapping relationship between heat load and average skin temperature. This type of method mainly relies on the theoretical calculation of human body thermal regulation models and thermal environment parameters, and its evaluation process focuses on being driven by thermophysiological models.

[0005] However, this type of method still has the following technical problems: First, the evaluation process is mainly based on the derivation of human body thermal regulation models and thermal environment parameters, and fails to be directly combined with the optical thermal management performance of specific materials, making it difficult to use for performance comparison analysis between different radiation-cooling fabric materials; Second, the evaluation results mainly rely on physiological calculation indicators such as heat load and skin temperature, which do not adequately characterize the radiation-cooling performance of the fabric materials themselves, making it difficult to fully reflect the differences at the material level in the evaluation results; Third, the evaluation system does not effectively integrate the unified correlation between fabric optical performance, human body temperature response, and subjective thermal sensation, and lacks a multi-dimensional parameter collaborative evaluation mechanism.

[0006] Therefore, existing technologies for evaluating the thermal comfort of radiative cooling fabrics still suffer from problems such as a single evaluation dimension, insufficient correlation between material properties and human sensation, and a lack of unified quantitative evaluation indicators, making it difficult to achieve accurate, unified, and comparable evaluations among different radiative cooling fabrics. Summary of the Invention

[0007] The purpose of this invention is to overcome the shortcomings of the prior art and provide a method for evaluating human thermal comfort using radiation-cooled fabrics.

[0008] The objective of this invention can be achieved through the following technical solutions: This invention provides a method for evaluating human thermal comfort using radiation-cooled fabrics, comprising the following steps: Obtain the optical performance parameters of the radiation-cooled fabric to be tested; Under set environmental conditions, temperature data from multiple measurement locations are collected when a human body is wearing the radiation-cooling fabric to be tested, and human body temperature change parameters are determined based on the temperature data. The thermal sensation evaluation values ​​of the human body are obtained in a reference state and when wearing the radiation-cooling fabric to be tested, and the thermal sensation change parameters of the human body are determined based on the thermal sensation evaluation values ​​in the two states. The optical performance parameters, human body temperature change parameters, and human body thermal sensation change parameters are standardized to obtain the corresponding dimensionless evaluation parameters. Based on the pre-set weighting coefficients, the dimensionless evaluation parameters are weighted and fused to obtain the human thermal comfort evaluation index. Based on the human thermal comfort evaluation index, the thermal comfort performance of the radiation cooling fabric is quantitatively evaluated or compared.

[0009] Furthermore, the optical performance parameters include the reflectivity parameter of the radiation-cooling fabric under test in the solar radiation band and the emissivity parameter in the mid-infrared band; the reflectivity parameter is a characterizing parameter of the reflectivity of the radiation-cooling fabric under test to incident radiation energy in the solar radiation band, used to characterize the reflectivity level of the radiation-cooling fabric under test to solar radiation; the emissivity parameter is a characterizing parameter of the ability of the radiation-cooling fabric under test to radiate heat energy outward in the mid-infrared band, used to characterize the ability of the radiation-cooling fabric under test to radiate heat to the external environment; the reflectivity parameter and the emissivity parameter are measured by a spectral testing device.

[0010] Furthermore, the step of collecting temperature data at multiple measurement locations when a human body is wearing the radiation-cooling fabric under the specified environmental conditions specifically includes: Temperature sensors are deployed at multiple preset measurement locations on the human body to obtain surface temperature data at the corresponding measurement locations; Under the set environmental conditions, temperature data at each measurement location are recorded when the human body is in a reference state and when it is wearing the radiation-cooling fabric to be tested.

[0011] Furthermore, determining the human body temperature change parameters based on the temperature data specifically includes: Based on temperature data from the same measurement location under both a reference state and while wearing the radiation-cooling fabric to be tested, the temperature difference at each measurement location is determined as the temperature change at that measurement location. The reference state is the state after the human body reaches thermal steady state under the same set environmental conditions when it is not wearing the radiation-cooling fabric to be tested or wearing the control fabric. Temperature change at all measurement locations Statistical processing was performed to obtain parameters of overall human body temperature change. ; Among them, the human body temperature change parameter Temperature change at each measurement location The average value is calculated using the following formula: in, Indicates the number of measurement locations.

[0012] Furthermore, the acquisition of thermal sensation evaluation values ​​of the human body in a reference state and while wearing the radiation-cooling fabric to be tested specifically includes: Under the set environmental conditions, subjective thermal sensation evaluations were collected from the subjects when the human body was in a reference state and when the subjects were wearing the radiation-cooling fabric to be tested. A pre-set thermal sensation evaluation scale was used to quantify the thermal sensation of the subjects and obtain the corresponding thermal sensation evaluation value. The thermal sensation evaluation value obtained under the reference state is denoted as . The thermal sensation evaluation value obtained while wearing the radiation-cooling fabric under test is denoted as . .

[0013] Furthermore, the determination of human thermal sensation change parameters based on thermal sensation evaluation values ​​under two states specifically includes: Thermal sensation evaluation value based on reference state Thermal sensation evaluation value when wearing the tested radiation-cooled fabric The difference between the two states is calculated to obtain the parameters of human thermal sensation change. The formula is: in, These are parameters related to changes in human thermal sensation.

[0014] Furthermore, the standardization process is described by the following formula: in, It represents any one of the optical performance parameters, human body temperature change parameters, or human body thermal sensation change parameters; These represent the minimum and maximum values ​​of the corresponding parameters within a preset sample range, respectively. This represents the dimensionless evaluation parameter after the corresponding parameter has been standardized.

[0015] Furthermore, the step of weighting and fusing the dimensionless evaluation parameters based on pre-set weighting coefficients to obtain the human thermal comfort evaluation index specifically includes: Based on pre-set weighting coefficients, the dimensionless evaluation parameters are weighted and summed to obtain the human thermal comfort evaluation index. The formula is: in, , , , These are the weighting coefficients. ; These are the standardized reflectivity parameters; These are the standardized radiation capability parameters; These are standardized parameters representing changes in human body temperature. These are the parameters representing changes in human thermal sensation after standardization.

[0016] Furthermore, the weighting coefficients are set according to the degree of influence of each dimensionless evaluation parameter on human thermal comfort, or adjusted through data analysis methods. The data analysis methods include statistical analysis methods or data-driven analysis methods, which are used to evaluate the contribution of each dimensionless evaluation parameter to changes in human thermal comfort.

[0017] Furthermore, the human thermal comfort evaluation index is constructed using a nonlinear combination form, specifically including an exponential function form or a product form. The nonlinear combination form is a form in which the dimensionless evaluation parameters are nonlinearly transformed and then combined for calculation.

[0018] Compared with the prior art, the present invention has the following advantages: (1) In the prior art, the evaluation of radiation-cooling fabrics mainly relies on single optical parameters such as solar reflectivity and mid-infrared emissivity or test results based on surface temperature. Such methods fail to quantitatively characterize the comprehensive thermal comfort performance of different fabrics within a unified framework, making it difficult to conduct direct and objective horizontal comparisons between different materials. This invention constructs a unified thermal comfort evaluation index based on optical performance parameters, human body temperature change parameters, and human body thermal sensation change parameters, and standardizes and weights the multi-source parameters to achieve a unified quantitative expression of multi-dimensional information. This enables direct comparison and quantitative ranking of different radiation-cooling fabrics, effectively solving the problem of scattered evaluation indicators and the inability to make unified comparisons in the prior art, and improving the comparability and engineering application value of the evaluation results.

[0019] (2) Existing technologies rely solely on a single dimension such as material optical parameters or surface temperature for evaluation, which fails to reflect the true impact of fabrics on the human body's thermal state under actual wearing conditions, resulting in discrepancies between the evaluation results and the actual human body's thermal response. This invention introduces human body temperature change parameters and combines them with fabric optical performance parameters to construct an evaluation system, establishing a direct correlation between material thermal management performance and human physiological response. This allows for a more realistic reflection of the cooling effect of fabrics in actual use environments, improving the adaptability and accuracy of the evaluation results to real thermal environments.

[0020] (3) In existing technologies, when evaluating the thermal comfort of radiant cooling fabrics, the analysis is often based solely on a single overall index such as the overall human body heat load or average skin temperature. This fails to fully consider the dynamic changes in the human body's own thermoregulation process and the differences in temperature response between different body parts, leading to evaluation results that deviate to some extent from the actual thermal comfort experience, thus affecting the authenticity and reliability of the evaluation. This invention collects temperature data from multiple measurement locations on the human body under set environmental conditions and constructs human body temperature change parameters based on temperature differences between different body parts. Simultaneously, it integrates thermal sensation change parameters reflecting subjective human sensation and fabric optical performance parameters for unified evaluation, thereby establishing a comprehensive evaluation system that simultaneously considers local temperature response differences and overall thermal state changes. This effectively characterizes the temperature response differences of different parts of the human body during the wearing of radiant cooling fabrics and incorporates them into a unified evaluation model. This ensures that the evaluation results not only reflect overall thermal state changes but also local thermoregulation characteristics, significantly reducing the deviation between the evaluation results and the actual thermal comfort experience, and improving the accuracy and authenticity of the thermal comfort evaluation.

[0021] (4) Existing technologies are mainly designed for specific thermal environments or specific human body thermal regulation models, making it difficult to apply to the unified evaluation and extended application of different types of radiation-cooling fabrics or other thermal management materials. This invention constructs a general evaluation index framework based on multi-source parameter fusion and uses adjustable weight coefficients to flexibly configure different influencing factors, making the evaluation method not only applicable to the performance comparison between radiation-cooling fabrics, but also extendable to the performance evaluation of other thermal management material systems, with good versatility and scalability. Attached Figure Description

[0022] Figure 1 This is a flowchart of the human thermal comfort evaluation method for radiation-cooled fabrics according to an embodiment of the present invention. Figure 2 This is a schematic diagram illustrating the principle of constructing the evaluation index in an embodiment of the present invention; Figure 3 This is a schematic diagram illustrating the influence of different evaluation parameters on human thermal comfort in an embodiment of the present invention. Figure 4 This is a schematic diagram comparing the predicted results of human thermal comfort evaluation with the actual results in an embodiment of the present invention. Figure 5 This is a schematic diagram illustrating the predictive performance evaluation of the human thermal comfort evaluation model according to an embodiment of the present invention. Detailed Implementation

[0023] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0024] Example 1: This embodiment provides a method for evaluating human thermal comfort using radiant cooling fabrics, such as... Figure 1 , Figure 2 As shown, it includes the following steps: Step S1: Obtain the optical performance parameters of the radiation-cooled fabric to be tested; The reflectivity parameter characterizes the degree to which a fabric reflects incident radiation energy within the solar spectrum, reflecting the fabric's ability to suppress external heat input. Increasing this parameter reduces the absorption of solar radiation energy by the fabric, thereby reducing heat accumulation in the fabric and on the human body, providing a basis for passive cooling. The emissivity parameter characterizes the fabric's ability to radiate heat energy into the environment in the mid-infrared band. This ability directly corresponds to the efficiency of heat dissipation from the human body and the fabric system. Enhancing this parameter increases the rate of heat release to the environment, thereby improving the thermal balance.

[0025] Both reflectance and emissivity parameters were obtained through spectral testing equipment. Specifically, the spectral response characteristics of the fabric in the solar radiation band and mid-infrared band were collected, and the corresponding reflectance and emissivity characterization results were calculated based on spectral integration. The reason for using spectral testing is that it can accurately reflect the fabric's response characteristics to radiation energy of different wavelengths within a continuous wavelength range. Compared with single-point measurement methods, it has higher representativeness and stability, thereby improving the objectivity and comparability of optical performance parameters.

[0026] Step S2: Under set environmental conditions, collect temperature data at multiple measurement locations when the human body is wearing the radiation-cooling fabric to be tested, and determine the human body temperature change parameters based on the temperature data; In one specific implementation process, the temperature response of a human body wearing the radiation-cooling fabric under test is collected under set environmental conditions. The set environmental conditions are used to simulate actual heat exposure scenarios, placing the human body in a stable and repeatable thermal environment to ensure the comparability of temperature data under different conditions.

[0027] First, temperature sensors are deployed at multiple pre-defined measurement locations on the human body to achieve distributed monitoring of temperature changes in different body parts. The measurement locations can cover typical heat exchange areas of the human body, such as the torso and limbs, thereby obtaining more comprehensive information on the body surface temperature response. By collecting surface temperature data from each measurement location using sensors, the temperature information is expanded from single-point measurement to multi-regional distributed data, which is beneficial for reflecting differences in local thermal response within the human body.

[0028] Under the established environmental conditions, temperature data at various measurement locations were recorded both when the human body was in a reference state and when it was wearing the radiation-cooling fabric to be tested. The reference state served as a benchmark, representing the state of the human body under the same environmental conditions after sufficient time to reach thermal steady state, either without wearing the radiation-cooling fabric to be tested or wearing a control fabric. The purpose of introducing the thermal steady-state condition was to eliminate the influence of transient thermal fluctuations on the measurement results, ensuring that the temperature data stably reflected the thermal equilibrium state of the human body under the influence of the fabric.

[0029] Based on temperature data from the same measurement location under reference and wearing conditions, the temperature difference at that location is calculated to characterize local temperature response changes. This difference is defined as the amount of temperature change at that measurement location. By introducing a difference calculation method, the differences in initial body temperature among individuals and the influence of environmental background can be eliminated, making temperature changes between different states comparable.

[0030] After obtaining the temperature changes at each measurement location, the data from all measurement locations are statistically processed to obtain the overall human body temperature change parameters. The reason for using the averaging method is that different regions of the human body have different thermal responses. Averaging can reduce the impact of local abnormal fluctuations while preserving the overall trend, thereby improving parameter stability.

[0031] Human body temperature change parameters The calculation is expressed as: in, This parameter represents the overall temperature change of the human body and is used to characterize the degree of change in the overall thermal state of the human body under the influence of fabric. Indicates the first The temperature change at each measurement location is used to characterize the temperature response differences of local body parts. Indicates the number of measurement locations.

[0032] By using the above processing method, it is possible to achieve a step-by-step summary from local temperature changes to the overall thermal state, so that the human body temperature change parameters can reflect both the differences in local thermal response and the overall thermal regulation trend, thereby improving the ability and stability of subsequent thermal comfort evaluation results to represent the true thermal state of the human body.

[0033] Step S3: Obtain the thermal sensation evaluation values ​​of the human body in the reference state and when wearing the radiation-cooled fabric to be tested, and determine the thermal sensation change parameters of the human body based on the thermal sensation evaluation values ​​in the two states. In a specific implementation process, subjective thermal sensations of the human body are collected under set environmental conditions to reflect the human body's perceptual response to changes in the thermal environment. These set environmental conditions ensure a consistent thermal exposure background across different test states, thereby improving the comparability and stability of subjective evaluation results.

[0034] Subjective thermal sensation assessments were collected from subjects in both a reference state and while wearing the radiation-cooling fabric to be tested. The reference state served as a baseline perception level. Subjects rated their current thermal sensation based on their own thermal comfort in each state, thus quantifying subjective thermal sensation.

[0035] A pre-designed thermal sensation assessment scale was used to quantify the subjects' thermal sensation. The scale employs the ASHRAE seven-point thermal sensation scale system to transform subjective thermal sensation into discrete or semi-continuous numerical indicators. The numerical values ​​represent the trend of thermal sensation change from very cold to very hot, thus making subjective sensation calculable and comparable. This scale was chosen because of its international applicability and consistency in evaluation results, effectively reducing evaluation bias caused by individual subjective differences and improving the statistical reliability of subjective data.

[0036] The thermal sensation evaluation value obtained under the reference state is denoted as . The thermal sensation evaluation value obtained while wearing the radiation-cooled fabric under test is denoted as . .

[0037] Thermal sensation evaluation value based on reference state Thermal sensation evaluation value when wearing the radiation-cooled fabric to be tested The difference between the two states is calculated to characterize the degree of change in the human body's subjective thermal sensation before and after the fabric application, thus obtaining parameters for changes in human thermal sensation. The calculation formula is as follows: in, These parameters represent changes in human thermal sensation and are used to reflect the degree of improvement or deterioration in the human body's subjective thermal comfort. This represents the thermal sensation evaluation value under reference conditions, used to characterize the baseline thermal sensation level; This represents the thermal sensation evaluation value when wearing the radiation-cooled fabric under test, used to characterize the thermal sensation level after the fabric has been applied.

[0038] By using the above method, the subjective thermal sensation of the human body is transformed from a qualitative description into a calculable parameter, which, together with the parameters of human body temperature change and optical performance parameters, constitutes the input basis for subsequent thermal comfort evaluation, thereby improving the consistency of the evaluation results in representing the actual human comfort experience.

[0039] Step S4: Standardize the optical performance parameters, human body temperature change parameters, and human body thermal sensation change parameters to obtain the corresponding dimensionless evaluation parameters; The standardization process is defined by the following formula: in, It represents any one of the following parameters: optical performance parameters, human body temperature change parameters, or human body thermal sensation change parameters; These represent the minimum and maximum values ​​of the corresponding parameters within a preset sample range, respectively. This represents the dimensionless evaluation parameter after the corresponding parameter has been standardized.

[0040] Step S5: Based on the pre-set weighting coefficients, the dimensionless evaluation parameters are weighted and fused to obtain the human thermal comfort evaluation index; In a specific implementation process, after standardizing the optical performance parameters, human body temperature change parameters, and human body thermal sensation change parameters, the corresponding dimensionless evaluation parameters are obtained. These dimensionless evaluation parameters include those corresponding to the reflectivity parameters. Radiation capability parameters corresponding to Human body temperature change parameters corresponding to and the parameters corresponding to changes in human thermal sensation .

[0041] Based on this, pre-defined weighting coefficients are introduced to perform weighted fusion processing on the dimensionless evaluation parameters, so as to achieve a comprehensive expression of different types of parameters under a unified scale. The weighting coefficients a, b, c, and d correspond to the reflectivity parameter, radiativity parameter, human body temperature change parameter, and human thermal sensation change parameter, respectively, and are used to characterize the importance of each parameter's impact on human thermal comfort. The sum of the weighting coefficients is limited to 1, which is set to ensure the consistency of the relative contribution relationship of each evaluation dimension in the overall evaluation system, thereby avoiding the excessive influence of any single factor on the evaluation results.

[0042] Furthermore, by performing a weighted summation of the dimensionless evaluation parameters, the Human Thermal Comfort Index (HTCI) is obtained, and its calculation expression is as follows: in, , , , These are the weighting coefficients. ; These are the standardized reflectivity parameters; These are the standardized radiation capability parameters; These are standardized parameters representing changes in human body temperature. These are the parameters representing changes in human thermal sensation after standardization.

[0043] The weighting coefficients can be set manually based on the degree of influence of each dimensionless evaluation parameter on human thermal comfort, or they can be dynamically adjusted through data analysis methods. These data analysis methods include statistical analysis or data-driven analysis, used to analyze historical experimental or sample data to assess the contribution of each evaluation parameter to changes in human thermal comfort, thereby optimizing the configuration of the weighting coefficients and making the evaluation results more closely reflect actual human thermal comfort experiences.

[0044] In another implementation, the human thermal comfort evaluation index can also be constructed using a nonlinear combination method. This involves performing nonlinear transformations on the dimensionless evaluation parameters before combining them for calculation, such as in exponential or product form. The reason for using nonlinear combination is that human thermal comfort perception exhibits nonlinear response characteristics, and different thermal environment parameters exhibit coupling enhancement or inhibition effects. Nonlinear mapping can more realistically characterize the interaction relationships between parameters, thereby improving the evaluation model's ability to fit and express changes in human thermal comfort under complex thermal environments, and further enhancing the accuracy and applicability of the evaluation results.

[0045] Step S6: Based on the human thermal comfort evaluation index, quantitatively evaluate or comparatively analyze the thermal comfort performance of radiant cooling fabrics. In a specific implementation process, after obtaining the human thermal comfort evaluation index, the thermal comfort performance of different radiative cooling fabrics is quantitatively evaluated or compared based on the evaluation index, so as to achieve an objective assessment of the fabric's thermal regulation capability.

[0046] This evaluation index, as a unified quantitative indicator, can be used to compare the performance of different radiative cooling fabrics. By comparing the numerical values ​​of the evaluation index for different fabrics, the superiority or inferiority of each fabric in terms of overall thermal comfort performance can be determined. The better the evaluation index value, the more significant the comprehensive effect of the fabric in terms of solar radiation suppression, mid-infrared heat dissipation, and improvement of human body temperature and subjective thermal sensation, thus exhibiting a better overall thermal comfort performance.

[0047] Furthermore, this evaluation index can also be used for material structure optimization analysis. By comparing and analyzing the fabric evaluation indices corresponding to different structural parameters or different design schemes, key structural factors affecting thermal comfort performance can be identified, thus providing a quantitative basis for the structural design of radiant cooling fabrics. In this way, the material optimization process, which originally relied on experience-based judgment, can be transformed into a quantitative analysis process based on evaluation indices, improving the scientific rigor and relevance of material design.

[0048] Example 2: To verify the effectiveness and accuracy of the human thermal comfort evaluation method for radiant cooling fabrics proposed in this invention, a series of experiments were conducted in this embodiment, and the predictive performance of the model was systematically evaluated using the obtained data. The specific implementation process and results are described below.

[0049] 1. Multi-parameter influence analysis and weight determination: To determine the relative importance of optical performance parameters, human body temperature change parameters, and human thermal sensation change parameters in the final evaluation index, this embodiment conducted an influence analysis. Through statistical analysis methods and data-driven algorithms, this embodiment quantified the contribution of each dimensionless evaluation parameter to changes in human thermal comfort.

[0050] Analysis results as follows Figure 3 As shown in the figure, the differences in the impact of different evaluation parameters on human thermal comfort are clearly illustrated. It can be observed that parameters related to changes in human body temperature and changes in human thermal sensation contribute most significantly to the final thermal comfort index, confirming the correctness of this invention in using human physiological and psychological responses as the core evaluation dimensions. Simultaneously, the optical properties of the fabric, as the physical basis for achieving cooling, also demonstrate a stable influence.

[0051] 2. Comparison between model predictions and actual results: After determining the weights, this embodiment selected multiple groups of different radiation-cooling fabric samples and applied the evaluation method of this invention to calculate their predicted Human Thermal Comfort Index (HTCI) values. Simultaneously, this embodiment recorded the actual overall thermal comfort feedback from the subjects through a controlled environment human wearing experiment, which served as the actual result (or true value).

[0052] Figure 4 The graph shows a comparison between the model's predicted results and the actual results. The scatter points are densely distributed near the diagonal, indicating that the Thermal Comfort Index (HTCI) calculated using the method of this invention is highly consistent with actual human thermal sensation. The predicted values ​​accurately reflect the relative superiority and inferiority and changing trends of actual thermal comfort, fully demonstrating that the evaluation model constructed in this invention has good accuracy and reliability, and can effectively replace complex and time-consuming human experiments to quickly and accurately predict and rank the thermal comfort performance of fabrics.

[0053] 3. Quantitative evaluation of model predictive performance: To further quantify the predictive performance of the model, this embodiment uses widely used statistical metrics for evaluation, and the results are as follows: Figure 5 As shown in the figure. This graph typically includes parameters such as the coefficient of determination (R²). 2 Indicators such as root mean square error (RMSE).

[0054] from Figure 5 It can be intuitively seen that the coefficient of determination (R²) between the model's predicted values ​​and the actual values... 2 ) reached a very high level (e.g., R) 2 > 0.9), while the root mean square error (RMSE) remains in an extremely low range. High R... 2 The values ​​indicate that the model can explain most of the data variation, and a low RMSE value indicates that the model's prediction error is very small. This strongly confirms from a statistical perspective that the human thermal comfort evaluation model proposed in this invention has excellent prediction accuracy and robustness, and can serve as an effective tool for the research and development, performance comparison, and quality evaluation of radiant cooling fabrics.

[0055] The verification through this embodiment clearly concludes that the method for evaluating human thermal comfort using radiant cooling fabrics provided by this invention not only has a scientific theoretical framework but also strong practicality and high predictive accuracy. This method successfully integrates fabric physical properties, human physiological responses, and subjective feelings, and can accurately predict actual thermal comfort effects in a quantified index form, providing a reliable solution to the evaluation challenges in existing technologies.

[0056] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0057] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and these modifications or substitutions should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for evaluating human thermal comfort using radiant cooling fabrics, characterized in that, Includes the following steps: Obtain the optical performance parameters of the radiation-cooled fabric to be tested; Under set environmental conditions, temperature data from multiple measurement locations are collected when a human body is wearing the radiation-cooling fabric to be tested, and human body temperature change parameters are determined based on the temperature data. The thermal sensation evaluation values ​​of the human body are obtained in a reference state and when wearing the radiation-cooling fabric to be tested, and the thermal sensation change parameters of the human body are determined based on the thermal sensation evaluation values ​​in the two states. The optical performance parameters, human body temperature change parameters, and human body thermal sensation change parameters are standardized to obtain the corresponding dimensionless evaluation parameters. Based on the pre-set weighting coefficients, the dimensionless evaluation parameters are weighted and fused to obtain the human thermal comfort evaluation index. Based on the human thermal comfort evaluation index, the thermal comfort performance of the radiation cooling fabric is quantitatively evaluated or compared.

2. The method for evaluating human thermal comfort using radiant cooling fabrics according to claim 1, characterized in that, The optical performance parameters include the reflectivity parameters of the radiation-cooled fabric under test in the solar radiation band and the emissivity parameters in the mid-infrared band; the reflectivity parameters are characterizing parameters of the reflectivity of the radiation-cooled fabric under test to incident radiation energy in the solar radiation band, and are used to characterize the reflectivity level of the radiation-cooled fabric under test to solar radiation. The radiation capability parameter is a characterization parameter of the ability of the radiation-cooling fabric under test to radiate heat energy outward in the mid-infrared band, and is used to characterize the ability of the radiation-cooling fabric under test to radiate heat to the external environment. The reflectivity parameter and the emissivity parameter are obtained by measuring with a spectral testing device.

3. The method for evaluating human thermal comfort using radiant cooling fabrics according to claim 1, characterized in that, The process of collecting temperature data at multiple measurement locations under set environmental conditions when a human body is wearing the radiation-cooling fabric to be tested specifically includes: Temperature sensors are deployed at multiple preset measurement locations on the human body to obtain surface temperature data at the corresponding measurement locations; Under the set environmental conditions, temperature data at each measurement location are recorded when the human body is in a reference state and when it is wearing the radiation-cooling fabric to be tested.

4. The method for evaluating human thermal comfort using radiant cooling fabrics according to claim 1, characterized in that, The step of determining the human body temperature change parameters based on the temperature data specifically includes: Based on temperature data from the same measurement location under both a reference state and while wearing the radiation-cooling fabric to be tested, the temperature difference at each measurement location is determined as the temperature change at that measurement location. The reference state is the state after the human body reaches thermal steady state under the same set environmental conditions when it is not wearing the radiation-cooling fabric to be tested or wearing the control fabric. Temperature change at all measurement locations Statistical processing was performed to obtain parameters of overall human body temperature change. ; Among them, the human body temperature change parameter Temperature change at each measurement location The average value is calculated using the following formula: in, Indicates the number of measurement locations.

5. The method for evaluating human thermal comfort using radiant cooling fabrics according to claim 1, characterized in that, The acquisition of thermal sensation evaluation values ​​of the human body in a reference state and while wearing the radiation-cooling fabric to be tested specifically includes: Under the set environmental conditions, subjective thermal sensation evaluations were collected from the subjects when the human body was in a reference state and when the subjects were wearing the radiation-cooling fabric to be tested. A pre-set thermal sensation evaluation scale was used to quantify the thermal sensation of the subjects and obtain the corresponding thermal sensation evaluation value. The thermal sensation evaluation value obtained under the reference state is denoted as . The thermal sensation evaluation value obtained while wearing the radiation-cooling fabric under test is denoted as . .

6. The method for evaluating human thermal comfort using radiant cooling fabrics according to claim 1, characterized in that, The determination of human thermal sensation change parameters based on thermal sensation evaluation values ​​under two states specifically includes: Thermal sensation evaluation value based on reference state Thermal sensation evaluation value when wearing the tested radiation-cooled fabric The difference between the two states is calculated to obtain the parameters of human thermal sensation change. The formula is: in, These are parameters related to changes in human thermal sensation.

7. The method for evaluating human thermal comfort using radiant cooling fabrics according to claim 1, characterized in that, The standardization process is defined by the following formula: in, It represents any one of the optical performance parameters, human body temperature change parameters, or human body thermal sensation change parameters; These represent the minimum and maximum values ​​of the corresponding parameters within a preset sample range, respectively. This represents the dimensionless evaluation parameter after the corresponding parameter has been standardized.

8. The method for evaluating human thermal comfort using radiant cooling fabrics according to claim 1, characterized in that, The step of weighting and fusing the dimensionless evaluation parameters based on pre-set weighting coefficients to obtain the human thermal comfort evaluation index specifically includes: Based on pre-set weighting coefficients, the dimensionless evaluation parameters are weighted and summed to obtain the human thermal comfort evaluation index. The formula is: in, , , , These are the weighting coefficients. ; These are the standardized reflectivity parameters; These are the standardized radiation capability parameters; These are standardized parameters representing changes in human body temperature. These are the parameters representing changes in human thermal sensation after standardization.

9. The method for evaluating human thermal comfort using a radiant cooling fabric according to claim 8, characterized in that, The weighting coefficients are set according to the degree of influence of each dimensionless evaluation parameter on human thermal comfort, or adjusted through data analysis methods. The data analysis methods include statistical analysis methods or data-driven analysis methods, which are used to evaluate the contribution of each dimensionless evaluation parameter to changes in human thermal comfort.

10. The method for evaluating human thermal comfort using radiant cooling fabrics according to claim 1, characterized in that, The human thermal comfort evaluation index is constructed using a nonlinear combination form, specifically including an exponential function form or a product form. The nonlinear combination form is a form in which the dimensionless evaluation parameters are nonlinearly transformed and then combined for calculation.

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