Method for determining adaptive time duration of subjective thermal environment assessment

Abstract

The invention discloses a method for determining adaptive time duration of subjective thermal environment assessment, and the method comprises the steps: obtaining physiological parameter statistical distribution based on priori knowledge or a thermal comfort database; determining an initial skin temperature, an initial core temperature and a thermal environment of an environment chamber in an adaptive stage; based on the initial skin temperature, the initial core temperature and the thermal environment of the adaptive stage environment chamber, determining a skin temperature dynamic change curve by using a dynamic human body biological thermal model; according to the stability limit, based on the skin temperature dynamic change curve, determining the stability time length; obtaining an adaptive time length based on the stable time length according to the confidence coefficient; the method solves the problems that the adaptive time length is determined only according to experience at present, the risk that subjective thermal environment assessment is inaccurate due to too short adaptive time exists, and the risk that time, money and other investments are too large due to too long adaptive time exists, and is helpful for guiding how to evaluate the thermal environment under reasonable time, money and other costs. And determining a reliable thermal environment evaluation adaptation time length.

Description

Technical Field

[0001] The invention belongs to the technical field of thermal comfort, and in particular relates to a method for determining the length of adaptation time for subjective thermal environment assessment. Background Art

[0002] The adaptation phase is an important stage in subjective thermal comfort assessment, and its purpose is to eliminate the influence of personnel's previous exposure environment (thermal history) on the subjective thermal comfort assessment results. At present, there is a lack of methods to determine the length of adaptation time for subjective thermal environment assessment. At present, the length of adaptation time for thermal environment assessment is determined based on experience. Different practitioners determine the length of adaptation time for thermal environment assessment based on experience, which makes the length of adaptation time for thermal environment assessment more dispersed. For example, the adaptation phase duration of Luo et al. in the article "Luo M, Xu S, Tang Y, et al. Dynamic thermal responses and showering thermal comfort under different conditions [J]. Building and Environment, 2023, 237: 110322." was only 10 minutes, and the adaptation phase duration of Li et al. in the article "Li Z, Zhou B, Yang B, et al. Occupant thermal and draft perceptions under various intermittent regimes of an intermittent airjet strategy [J]. Building and Environment, 2024, 262: 111839." was extended to 40 minutes. There are two major risks in determining the length of adaptation time for subjective thermal environment assessment based on experience: when the adaptation period is too short, the subjective thermal environment assessment results are inaccurate; when the adaptation period is too long, the time and money costs of subjective thermal comfort assessment are too high. Therefore, how to determine the length of adaptation time required for reliable thermal comfort assessment at a reasonable time and money cost is a technical problem that needs to be solved urgently. Summary of the invention

[0003] In order to overcome the above-mentioned problems of the prior art, the purpose of the present invention is to provide a method for determining the length of adaptation time for subjective thermal environment assessment. This method aims to shorten the adaptation phase time and reduce the cost investment in time and money for subjective thermal comfort assessment on the basis of ensuring the accuracy of the subjective thermal comfort assessment results.

[0004] To achieve the above object, the technical solution of the present invention is:

[0005] A method for determining the length of time for subjective thermal environment assessment adaptation comprises the following steps:

[0006] Step 1: Obtain the statistical distribution of physiological parameters based on prior knowledge or thermal comfort database;

[0007] Step 2: Determine the initial skin temperature, initial core temperature and thermal environment of the environmental chamber during the adaptation phase based on the statistical distribution of physiological parameters;

[0008] Step 3: Based on the initial skin temperature, the initial core temperature, and the thermal environment of the environmental chamber during the adaptation phase, a dynamic human bioheat model is used to determine the dynamic change curve of the skin temperature;

[0009] Step 4: According to the stability limit and the skin temperature dynamic change curve, determine the stability time length;

[0010] Step 5: According to the confidence level and the stable time length, the adaptation time length is obtained.

[0011] The step 1 specifically includes:

[0012] (1.1) Use numerical simulation software to build a steady-state human biothermal model;

[0013] (1.2) Based on prior knowledge or thermal comfort database and the steady-state human biothermal model, obtain the changes in skin temperature and core temperature and establish the core temperature T c With skin temperature T sk The correlation formula T c =f(T sk ) and obtain the statistical distribution of skin temperature.

[0014] The step 2 specifically includes:

[0015] (2.1) Sample the skin temperature from the statistical distribution of skin temperature as the initial skin temperature; use the core temperature T c and skin temperature T sk The correlation formula T c =f(T sk ), the initial core temperature is calculated based on the initial skin temperature;

[0016] (2.2) During the acclimatization phase, the thermal environment of the environmental chamber is a thermoneutral environment, represented by Predicted Mean Vote equal to 0; or a hot environment, represented by Predicted Mean Vote equal to 0.5; or a cool environment, represented by Predicted Mean Vote equal to -0.5.

[0017] The step three specifically includes:

[0018] (3.1) Use numerical simulation software to build a dynamic human biothermal model;

[0019] (3.2) Based on the initial skin temperature, initial core temperature, and thermal environment of the environmental chamber during the adaptation phase, the dynamic human biothermal model is used to calculate the dynamic changes of human physiological parameters and determine the dynamic change curve of skin temperature.

[0020] The step 4 specifically includes:

[0021] (4.1) Set the stability limit ε, which is a non-negative number. The stability limit is determined by the thermal environment assessment leader and is selected within 0.1℃–0.5℃. The smaller the stability limit ε is, the closer the equivalent stable state is to the stable state, and the longer the stable time length is. One sampled skin temperature corresponds to one stable time length, and all stable time lengths are aggregated into a stable time length distribution.

[0022] (4.2) Determine the time t corresponding to the equivalent stable state based on the stability limit and the skin temperature dynamic change curve e :The stable skin temperature of the skin temperature dynamic change curve is T s , the initial skin temperature is higher than the stable skin temperature T s When the equivalent steady-state skin temperature is T s +ε; the initial skin temperature is lower than the stable skin temperature T s When the equivalent steady-state skin temperature is T s -ε; the time corresponding to the equivalent stable state obtained from the skin temperature dynamic change curve is t e ; The expression of stable time length is as follows:

[0023] Δt s =t e -t i (1)

[0024] Among them, Δt s is the stable time length; t e is the time corresponding to the equivalent stable state; t i is the start time.

[0025] The step five specifically includes:

[0026] (5.1) Set the confidence level σ; the confidence level is determined by the thermal environment assessment leader. The larger the confidence level σ, the more reliable the determination of the adaptation time length, and the larger the TLAP;

[0027] (5.2) According to the determined confidence level σ, from the stable time length Δt sThe distribution selects the stable time length that satisfies the cumulative probability of the lower area being σ, and the stable time length is the adaptation time length TLAP (Time Length of Adaptation Phase, TLAP).

[0028] Compared with the prior art, the present invention has the following beneficial effects:

[0029] (1) The present invention determines the dynamic change curve of human physiological parameters based on the dynamic human biothermal model and the physiological parameters obtained in the initial state and stable state stages, and determines the adaptation time based on the stability limit, thereby ensuring the accuracy of the subjective thermal comfort evaluation results.

[0030] (2) The present invention is based on the theoretical analysis of human physiological thermal stability and uses confidence to ensure that the determined adaptation time is long enough to meet the accuracy requirements of the subjective thermal comfort assessment results, and to ensure that the determined adaptation time is not too long to avoid waste of time and money.

[0031] In summary, the present invention proposes for the first time a method for determining the length of adaptation time, which solves the problem that the length of adaptation time is currently determined only based on experience, and there is a risk of inaccurate subjective thermal environment assessment due to too short an adaptation time, and a risk of excessive investment in time and money due to too long an adaptation time. The dynamic change curve of human physiological parameters is determined based on a dynamic human biothermal model and the acquired physiological parameters in the initial and stable states, and the adaptation time is determined based on stability limits. Under the premise of ensuring the accuracy of the subjective thermal comfort assessment results, the length of the adaptation stage is greatly shortened. The determined appropriate length of adaptation time not only meets the requirements of the accuracy of the subjective thermal comfort assessment results, but also ensures that the determined length of adaptation time is not too long, thereby avoiding waste of time and money. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 A schematic diagram for inferring the initial state provided for step 1 of the present invention.

[0033] Figure 2 It is a schematic diagram of the present invention for determining the adaptation time length of subjective thermal environment assessment.

[0034] Figure 3 is the skin temperature and core temperature distribution calculated based on the prior knowledge ASHRAE Thermal Comfort Database II; where, Figure 3 (a) is summer skin temperature; (b) is summer core temperature; (c) is winter skin temperature; (d) is winter core temperature.

[0035] Figure 4 This is the result diagram of the change of stable time length under different working conditions; among them, Figure 4 (a) is summer; (b) is winter.

[0036] Figure 5 This is the adaptation time distribution result diagram under different stability limits in summer conditions.

[0037] Figure 6 This is the adaptation time distribution result diagram under different stability limits in winter conditions.

[0038] Figure 7 This is the adaptation time distribution result diagram under different confidence levels and different stability limits; among them, Figure 7 (a) is summer; (b) is winter. DETAILED DESCRIPTION

[0039] The present invention will be described in detail below in conjunction with the accompanying drawings.

[0040] A method for determining the length of time for subjective thermal environment assessment adaptation comprises the following steps:

[0041] Step 1: Based on prior knowledge or thermal comfort database, obtain the variation range and statistical distribution of physiological parameters;

[0042] When the initial state is unknown, the initial state sampling can be performed based on prior knowledge or the thermal comfort database to confirm the adaptation time. Figure 1 The present invention first uses numerical simulation software to build a steady-state human bio-thermal model, and based on prior knowledge or a thermal comfort database, such as the ASHRAE Thermal Comfort Database II covering a variety of thermal conditions, obtains skin temperature and core temperature changes based on the built steady-state human bio-thermal model, and establishes the core temperature T c and skin temperature T sk Correlation T c =f(T sk ), summarizing the statistical distribution of skin temperature.

[0043] Step 2: Based on the statistical distribution of physiological parameters, determine the initial skin temperature and initial core temperature, as well as the thermal environment of the environmental chamber during the adaptation phase, specifically:

[0044] (2.1) Sample the skin temperature from the statistical distribution of skin temperature as the initial skin temperature; use the core temperature T c and skin temperature T sk The correlation formula T c =f(T sk ), the initial core temperature is calculated based on the initial skin temperature;

[0045] (2.2) During the acclimatization phase, the thermal environment of the environmental chamber is a thermoneutral environment, represented by Predicted Mean Vote equal to 0; or a hot environment, represented by Predicted Mean Vote equal to 0.5; or a cool environment, represented by Predicted Mean Vote equal to -0.5.

[0046] Step 3: Based on the initial skin temperature, initial core temperature, and the thermal environment of the environmental chamber during the adaptation phase, the dynamic human biothermal model is used to determine the dynamic change curve of skin temperature, specifically:

[0047] (3.1) Use numerical simulation software to build a dynamic human biothermal model;

[0048] (3.2) Based on the initial skin temperature, initial core temperature, and thermal environment of the environmental chamber during the adaptation phase, the dynamic human biothermal model is used to calculate the dynamic changes of human physiological parameters and determine the dynamic change curve of skin temperature.

[0049] Reference Figure 2 The adaptation phase occurs when the personnel enter the environmental chamber of the adaptation phase from the original environment (i.e., thermal history). Based on the statistical distribution of skin temperature obtained in step 1, random sampling is performed as the initial skin temperature, and the initial core temperature is calculated based on the correlation between core temperature and skin temperature. A dynamic human bio-thermal model is constructed using numerical simulation software, and the dynamic changes of human physiological parameters are calculated based on the initial state, the thermal environment of the environmental chamber in the adaptation phase, and the constructed dynamic human bio-thermal model, and the corresponding change curves are obtained.

[0050] Step 4: According to the stability limit and the skin temperature dynamic change curve, determine the stability time length;

[0051] (4.1) Set the stability limit ε, which is a non-negative number. The stability limit is determined by the thermal environment assessment leader and is selected within 0.1℃–0.5℃. The smaller the stability limit ε is, the closer the equivalent stable state is to the stable state, and the longer the stable time length is. One sampled skin temperature corresponds to one stable time length, and all stable time lengths are aggregated into a stable time length distribution.

[0052] (4.2) Determine the time t corresponding to the equivalent stable state based on the stability limit and the skin temperature dynamic change curve e :The stable skin temperature of the skin temperature dynamic change curve is T s , the initial skin temperature is higher than the stable skin temperature T s When the equivalent steady-state skin temperature is T s +ε; the initial skin temperature is lower than the stable skin temperature T s When the equivalent steady-state skin temperature is Ts -ε; the time corresponding to the equivalent stable state obtained from the skin temperature dynamic change curve is t e ; The expression of stable time length is as follows:

[0053] Δt s =t e -t i (1)

[0054] Among them, Δt s is the stable time length; t e is the time corresponding to the equivalent stable state; t i is the start time.

[0055] The time required for stabilization is the time required for the personnel to change from the initial state to the equivalent stable state, where the time corresponding to the equivalent stable state is t e The corresponding skin temperature T is determined by the stability limit ε and the skin temperature dynamic change curve. e The stable skin temperature T of the dynamic change curve s The initial skin temperature is higher than the stable skin temperature T s When the equivalent steady-state skin temperature is T s +ε; the initial skin temperature is lower than the stable skin temperature T s When the equivalent steady-state skin temperature is T s -ε; thus the stable time length Δt is obtained s =t e -t i , which is the difference between the time corresponding to the equivalent stable state and the start time.

[0056] Step 5: According to the confidence level and the stable time length, the adaptation time length is obtained.

[0057] An initial state (i.e., the sampled initial skin temperature and the corresponding calculated initial core temperature) corresponds to a stable time length, which can be aggregated into a stable time length distribution based on steps 1 to 5. Set the confidence level σ; the confidence level is determined by the thermal environment assessment leader. The larger the confidence level σ, the stronger the reliability of the adaptation time length determination and the larger the TLAP. According to the determined confidence level σ, from the stable time length Δt s The distribution selects the stable time length that satisfies the cumulative probability of the lower area being σ, and the stable time length is the adaptation time length TLAP (Time Length of Adaptation Phase, TLAP).

[0058] Embodiment 1

[0059] Firstly based on Figure 1The process shown is based on prior knowledge or thermal comfort database. The present invention selects ASHRAE thermal comfort database II covering various thermal conditions to infer the initial state and plots the result as Figure 3 (a)- Figure 3 (d). Based on the ASHRAE Thermal Comfort Database II and the steady-state human biothermal model, the skin temperature is generally distributed in the range of 30℃-36℃; the skin temperature generally obeys a normal distribution, with the mean and standard deviation of the skin temperature in the summer scene being 33.78℃ and 0.79℃, respectively, and the mean and standard deviation of the skin temperature in the winter scene being 33.89℃ and 0.98℃, respectively. The core temperature is generally distributed in the range of 36.7℃-37.3℃, with the mean and standard deviation of the core temperature in the summer scene being 36.88℃ and 0.06℃, respectively, and the mean and standard deviation of the core temperature in the winter scene being 36.89℃ and 0.09℃, respectively. Based on the above data, the correlation between the core temperature and the skin temperature is summarized, and the specific expression is shown in the following equation (2). This correlation effectively establishes the connection between the core temperature and the skin temperature, with an average absolute deviation of only 0.03℃.

[0060]

[0061] Where, T c is the core temperature, °C; T sk is the skin temperature, ℃.

[0062] Relative humidity, wind speed and metabolic rate are set to 50% in summer, 0.10m / s and 1.1m / s in winter. The average radiation temperature is the same as the air temperature. The thermal resistance of summer clothing is 0.5clo and that of winter clothing is 1.0clo. When the environment in the adaptation stage is a thermoneutral environment, the temperature in summer is 25.7℃ and the temperature in winter is 22.6℃. The present invention determines the stable time length of subjective thermal environment assessment based on five stable limits of 0.1℃, 0.2℃, 0.3℃, 0.4℃ and 0.5℃, and plots the results on Figure 4. Taking the summer working condition as an example, when the stability limit is 0.5℃, when the initial state increases from 30℃ to 34℃, the stability time length decreases from the original 63.4min to 0min, shortening by 63.4min; when the initial state increases from 34℃ to 36℃, the stability time length increases from the original 0min to 18.2min, increasing by 18.2min. Under a given initial state, when the stability limit decreases, the stability time length increases accordingly. When the initial skin temperature is 30℃, when the stability limit decreases from 0.5℃ to 0.1℃, the stability time length increases from 63.4min to 76.8min. And the effect of the stability limit on the stability time length is nonlinear. For example, when the stability limit decreases from 0.5℃ to 0.2℃, the stability time length increases by 7.4min, and when the stability limit further decreases from 0.2℃ to 0.1℃, the stability time length increases by 6.0min. The stabilization time is longer in winter conditions compared to summer conditions, mainly because skin temperature changes more slowly in winter clothing.

[0063] Since the initial state varies randomly in practical life, it is generally believed that it follows a normal distribution. Therefore, in order to reliably determine the adaptation time length of the subjective thermal environment assessment, the present invention assumes that the mean and standard deviation of the skin temperature follow a normal distribution, and the initial skin temperature is randomly sampled from the normal distribution. The core temperature is an important physiological parameter that can characterize the state of a person. The core temperature can be determined by the core temperature and skin temperature correlation formula (Formula (2)). 10,000 different initial states are randomly sampled for reliable statistical analysis. The distribution of the stable time length of the randomly sampled initial states under different stability constraints is shown in the following figure. Figure 5 and Figure 6 As shown. It can be found that most of the sample points are concentrated in the interval of 0min stable time length. This is mainly because the randomly sampled thermal state distribution is near thermal neutrality, and the initial state is similar to the adaptation stage environment, so the required stable time length is 0min. As the stability limit increases, the stable time length distribution tends to 0min. And the stable time length distribution of summer working conditions is closer to 0min than that of winter working conditions. But overall, the stable time length distribution of summer working conditions and winter working conditions is in the range of 0min-80min. Therefore, for different adaptation processes, the adaptation time should be carefully determined to avoid large differences in the results of subjective thermal comfort evaluation caused by the adaptation time.

[0064] The present invention determines the adaptation time length of subjective thermal environment assessment based on four confidence levels of 90.0%, 92.5%, 95.0% and 97.5%. At a given confidence level, the adaptation time length decreases with the increase of the stability limit. When the stability limit increases from 0.1°C to 0.2°C, the adaptation time length required for subjective thermal environment assessment decreases rapidly, and when the stability limit increases further, the adaptation time length decreases slowly. Taking summer working conditions as an example, when the confidence level is 97.5%, when the stability limit increases from 0.1°C to 0.2°C, the adaptation time decreases from the original 38.9min to 32.8min, shortened by 6.1min; when the stability limit further increases from 0.2°C to 0.5°C, the adaptation time decreases from the original 32.8min to 25.2min, shortened by 7.6min. Under a given stability limit, the adaptation time length decreases with the decrease of the confidence level. When the confidence level decreased from 97.5% to 95.0%, the adaptation time required for subjective thermal environment assessment decreased rapidly. When the confidence level was further reduced, the adaptation time decreased slowly. When the stability limit was 0.1℃, when the confidence level decreased from 97.5% to 95.0%, the adaptation time decreased from 38.9min to 35.4min, a decrease of 3.5min; when the confidence level was further reduced from 95.0% to 90.0%, the adaptation time decreased from 35.4min to 31.2min, a decrease of 4.2min.

[0065] The thermal environment of the environmental chamber in the adaptation stage of the present invention includes a thermally neutral state, and only changing the thermal environment (such as changing the thermally neutral environment to a slightly hotter or cooler environment) still falls within the protection scope of the present invention.

[0066] The physiological parameters in the present invention include skin temperature, and only changing the physiological parameters (such as changing the skin temperature to the heart rate) still falls within the protection scope of the present invention.

[0067] The initial state statistical distribution in the present invention includes a normal distribution, and only changing the statistical distribution form (such as changing the normal distribution to a statistical distribution inferred based on measured data) still falls within the protection scope of the present invention.

Claims

1. A method for determining the length of time for subjective thermal environment assessment adaptation, characterized in that: The following steps are involved: Step 1: Obtain the statistical distribution of physiological parameters based on prior knowledge or thermal comfort database; Step 2: Determine the initial skin temperature, initial core temperature and thermal environment of the environmental chamber during the adaptation phase based on the statistical distribution of physiological parameters; Step 3: Based on the initial skin temperature, the initial core temperature, and the thermal environment of the environmental chamber during the adaptation phase, a dynamic human bioheat model is used to determine the dynamic change curve of the skin temperature; Step 4: According to the stability limit and the skin temperature dynamic change curve, determine the stability time length; Step 5: According to the confidence level and the stable time length, the adaptation time length is obtained.

2. A method for determining the length of time for subjective thermal environment assessment adaptation according to claim 1, characterized in that: The step 1 specifically includes: (1.1) Use numerical simulation software to build a steady-state human biothermal model; (1.2) Based on prior knowledge or thermal comfort database and the steady-state human biothermal model, obtain the changes in skin temperature and core temperature and establish the core temperature T c With skin temperature T sk The correlation formula T c =f(T sk ) and obtain the statistical distribution of skin temperature.

3. The method for determining the length of time for subjective thermal environment assessment adaptation according to claim 1, characterized in that: The step 2 specifically includes: (2.1) Sample the skin temperature from the statistical distribution of skin temperature as the initial skin temperature; use the core temperature T c and skin temperature T sk The correlation formula T c =f(T sk ), the initial core temperature is calculated based on the initial skin temperature; (2.2) During the acclimatization phase, the thermal environment of the environmental chamber is a thermally neutral environment, represented by Predicted Mean Vote equal to 0; or a relatively hot environment, represented by Predicted Mean Vote equal to 0.5; or a relatively cool environment, represented by Predicted Mean Vote equal to -0.

5.

4. The method for determining the length of time for subjective thermal environment assessment adaptation according to claim 1, characterized in that: The step three specifically includes: (3.1) Use numerical simulation software to build a dynamic human biothermal model; (3.2) Based on the initial skin temperature, initial core temperature, and thermal environment of the environmental chamber during the adaptation phase, the dynamic human biothermal model is used to calculate the dynamic changes of human physiological parameters and determine the dynamic change curve of skin temperature.

5. The method for determining the length of time for subjective thermal environment assessment adaptation according to claim 1, characterized in that: The step 4 specifically includes: (4.1) Set the stability limit ε, which is a non-negative number. The stability limit is determined by the thermal environment assessment leader and is selected within 0.1℃–0.5℃. The smaller the stability limit ε is, the closer the equivalent stable state is to the stable state, and the longer the stable time length is. One sampled skin temperature corresponds to one stable time length, and all stable time lengths are aggregated into a stable time length distribution. (4.2) Determine the time t corresponding to the equivalent stable state based on the stability limit and the skin temperature dynamic change curve e :The stable skin temperature of the skin temperature dynamic change curve is T s , the initial skin temperature is higher than the stable skin temperature T s When the equivalent steady-state skin temperature is T s +ε; the initial skin temperature is lower than the stable skin temperature T s When the equivalent steady-state skin temperature is T s -ε; the time corresponding to the equivalent stable state obtained from the skin temperature dynamic change curve is t e ; The expression of stable time length is as shown in formula (1): Δt s =t e -t i (1) Among them, Δt s is the stable time length; t e is the time corresponding to the equivalent stable state; t i is the start time.

6. A method for determining the length of time for subjective thermal environment assessment adaptation according to claim 1, characterized in that: The step five specifically includes: (5.1) Set the confidence level σ; the confidence level is determined by the thermal environment assessment leader. The larger the confidence level σ, the more reliable the determination of the adaptation time length, and the larger the TLAP; (5.2) According to the determined confidence level σ, from the stable time length Δt s The distribution selects a stable time length that satisfies the cumulative probability of the lower area being σ, and this stable time length is the adaptation time length TLAP.

Images