A method for determining the adaptation time length of subjective thermal environment assessment
Through a dynamic human biothermal model and thermal comfort database, combining stable limitations and confidence, the adaptation time length is determined, and the problem of inaccurate or excessive cost of determining the adaptation time length in the prior art is solved, and the accuracy and cost-effectiveness of subjective thermal comfort assessment is achieved.
Patent Information
- Application Number
- CN202411575878.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-06
- Publication Date
- 2025-07-01
- Estimated Expiration
- 2044-11-06
AI Technical Summary
The prior art lacks reliable methods to determine the length of adaptation time for subjective thermal environment assessments, resulting in inaccurate assessment results or excessive cost.
By obtaining physiological parameters of the initial and stable states based on the dynamic human biothermal model and thermal comfort database, the adaptation time length is determined.
Ensure the accuracy of the subjective thermal comfort assessment results, while shortening the adaptation phase time and reducing cost investments such as time and money.
Smart Images
Figure CN119416530B_ABST
Abstract
Description
Technical Field
[0001] The present invention belongs to the technical field of thermal comfort, and particularly relates to a method for determining the adaptation time length of subjective thermal environment assessment. Background Art
[0002] The adaptation stage is an important stage in subjective thermal comfort assessment, and its purpose is to eliminate the influence of the previous exposure environment (thermal history) of personnel on the results of subjective thermal comfort assessment. At present, there is a lack of a method for determining the adaptation time length of subjective thermal environment assessment in practice. Currently, in practice, the adaptation time length of thermal environment assessment is determined based on experience. Different practitioners determine the adaptation time length of thermal environment assessment based on experience, resulting in a relatively scattered adaptation time length of thermal environment assessment. For example, the adaptation stage duration 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." by Luo et al. is only 10 minutes, while the adaptation stage duration 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." by Li et al. is extended to 40 minutes. There are two major risks in determining the adaptation time length of subjective thermal environment assessment based on experience: when the adaptation stage time is too short, the results of subjective thermal environment assessment are inaccurate; when the adaptation stage time is too long, the costs such as time and money for subjective thermal comfort assessment are too high. Therefore, how to determine the adaptation time length required for reliable thermal comfort assessment at reasonable costs such as time and money is a technical problem that urgently needs to be solved. Summary of the Invention
[0003] In order to overcome the above-mentioned problems in the prior art, the purpose of the present invention is to provide a method for determining the adaptation time length of subjective thermal environment assessment, which aims to shorten the adaptation stage time and reduce the input of costs such as time and money for subjective thermal comfort assessment on the basis of ensuring the accuracy of the results of subjective thermal comfort assessment.
[0004] To achieve the above purpose, the technical solution of the present invention is as follows:
[0005] A method for determining the adaptation time length of subjective thermal environment assessment, comprising the following steps:
[0006] Step 1: Obtain the statistical distribution of physiological parameters based on prior knowledge or a thermal comfort database.
[0007] Step 2: Based on the statistical distribution of physiological parameters, determine the initial skin temperature, the initial core temperature, and the thermal environment of the environmental chamber during the adaptation phase.
[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, use a dynamic human bioheat model to determine the dynamic change curve of the skin temperature.
[0009] Step 4: According to the stability limit, based on the dynamic change curve of the skin temperature, determine the stable time length.
[0010] Step 5: According to the confidence level, based on the stable time length, obtain the adaptation time length.
[0011] The specific content of Step 1 includes:
[0012] (1.1) Use numerical simulation software to build a steady-state human bioheat model.
[0013] (1.2) Based on prior knowledge or a thermal comfort database and the built steady-state human bioheat model, obtain the changes in skin temperature and core temperature, establish the correlation formula T c between the core temperature T sk and the skin temperature T c = f(T sk ), and obtain the statistical distribution of the skin temperature.
[0014] The specific content of Step 2 includes:
[0015] (2.1) Sample the skin temperature from the statistical distribution of the skin temperature as the initial skin temperature; use the correlation formula T c between the core temperature T sk and the skin temperature T c = f(T sk ) to calculate the initial core temperature based on the initial skin temperature.
[0016] (2.2) The thermal environment of the environmental chamber during the adaptation phase is a thermoneutral environment, characterized by a Predicted Mean Vote equal to 0; or a slightly warm environment, characterized by a Predicted Mean Vote equal to 0.5; or a slightly cool environment, characterized by a Predicted Mean Vote equal to -0.5.
[0017] The specific content of Step 3 includes:
[0018] (3.1) Build a dynamic human bioheat model using numerical simulation software;
[0019] (3.2) Based on the initial skin temperature, initial core temperature, and the thermal environment of the environmental chamber during the adaptation phase, use the dynamic human bioheat model to calculate the dynamic changes of human physiological parameters and determine the dynamic change curve of skin temperature.
[0020] The specific steps of step four are as follows:
[0021] (4.1) Set a stability limit ε, where ε is a non - negative number; the stability limit is determined by the person in charge of thermal environment assessment and is selected within the range of 0.1°C - 0.5°C. The smaller the value of the stability limit ε, the closer the equivalent stable state is to the stable state, and the longer the stability time length. One sampled skin temperature corresponds to one stability time length, and all stability time lengths form a stability time length distribution;
[0022] (4.2) Based on the stability limit and the dynamic change curve of skin temperature, determine the time t corresponding to the equivalent stable state e : The stable skin temperature of the dynamic change curve of skin temperature is T s , when the skin temperature in the initial state is higher than the stable skin temperature T s , the skin temperature of the equivalent stable state is T s + ε; when the skin temperature in the initial state is lower than the stable skin temperature T s , the skin temperature of the equivalent stable state is T s - ε; the time corresponding to the equivalent stable state obtained from the dynamic change curve of skin temperature is t e ; the expression of the stability time length is as shown in formula (1):
[0023] Δt s = t e - t i (1)
[0024] Where, Δt s is the stability time length; t e is the time corresponding to the equivalent stable state; t i is the starting time.
[0025] The specific steps of step five are as follows:
[0026] (5.1) Set a confidence level σ; the confidence level is determined by the person in charge of thermal environment assessment. The larger the value of the confidence level σ, the stronger the reliability of the determined adaptation time length, and the larger the TLAP;
[0027] (5.2) According to the determined confidence level σ, from the stability time length Δt sThe stable time length that satisfies the cumulative probability of the following region being σ is selected, and this stable time length is the adaptation time length TLAP (Time Length of Adaptation Phase).
[0028] Compared with the prior art, the beneficial effects of the present invention are as follows:
[0029] (1) Based on the dynamic human body bioheat model and the physiological parameters obtained in the initial state and stable state phases, the present invention determines the dynamic change curve of human physiological parameters, and determines the adaptation time based on the stability limit, ensuring the accuracy of the subjective thermal comfort evaluation result.
[0030] (2) According to the analysis of the human physiological heat stability theory, and using the confidence guarantee, the determined adaptation time length is large enough to meet the requirements of the accuracy of the subjective thermal comfort evaluation result, and it is ensured that the determined adaptation time length is not too large, avoiding waste of inputs such as time and money.
[0031] In summary, the present invention first proposes a method for determining the adaptation time length, which solves the problems that currently only the adaptation time length is determined according to experience, there is a risk of inaccurate subjective thermal environment evaluation caused by too short adaptation time, and a risk of excessive inputs such as time and money caused by too long adaptation time. Based on the dynamic human body bioheat model and the physiological parameters obtained in the initial state and stable state phases, the present invention determines the dynamic change curve of human physiological parameters, and determines the adaptation time. On the premise of ensuring the accuracy of the subjective thermal comfort evaluation result, the adaptation phase time length is significantly shortened. The determined appropriate adaptation time length not only meets the requirements of the accuracy of the subjective thermal comfort evaluation result, but also ensures that the determined adaptation time length is not too large, avoiding waste of inputs such as time and money. BRIEF DESCRIPTION OF THE DRAWINGS
[0032] Figure 1 It is a schematic diagram for inferring the initial state provided in the first step of the present invention.
[0033] Figure 2 It is a schematic diagram for determining the adaptation time length of the subjective thermal environment evaluation of the present invention.
[0034] Figure 3 It is the skin temperature and core temperature distribution calculated based on the prior knowledge ASHRAE Thermal Comfort Database II; among them, Figure 3 (a) in it is the summer skin temperature; (b) is the summer core temperature; (c) is the winter skin temperature; (d) is the winter core temperature.
[0035] Figure 4 It is a graph of the change result of the stable time length under different working conditions; among them, Figure 4 (a) in it is summer; (b) is winter.
[0036] Figure 5 It is a graph of the adaptation time distribution under different steady-state limits in the summer condition.
[0037] Figure 6 It is a graph of the adaptation time distribution under different steady-state limits in the winter condition.
[0038] Figure 7 It is a graph of the adaptation time distribution under different confidence levels and different steady-state limits; among them, Figure 7 (a) in it is summer; (b) is winter. Specific implementation manner
[0039] The present invention will be described in detail below with reference to the accompanying drawings.
[0040] A method for determining the adaptation time length of subjective thermal environment assessment includes the following steps:
[0041] Step 1: Based on prior knowledge or a thermal comfort database, obtain the change range and statistical distribution of physiological parameters;
[0042] When the initial state is unknown, the initial state can be sampled according to prior knowledge or a thermal comfort database to confirm the adaptation time. Refer to Figure 1 , the present invention first uses numerical simulation software to build a steady-state human bioheat 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, etc., based on the built steady-state human bioheat model, obtain the changes in skin temperature and core temperature, and establish a correlation formula T c of the core temperature T sk and the skin temperature T c = f(T sk ), and summarize the statistical distribution of skin temperature.
[0043] Step 2: Based on the statistical distribution of physiological parameters, determine the initial skin temperature, the initial core temperature, and the thermal environment of the environmental chamber during the adaptation stage, specifically:
[0044] (2.1) Sample the skin temperature from the statistical distribution of skin temperature as the initial skin temperature; use the correlation formula T c of the core temperature T sk and the skin temperature T c = f(T sk ), and calculate the initial core temperature based on the initial skin temperature;
[0045] (2.2) The thermal environment of the environmental chamber in the adaptation stage is a thermoneutral environment, characterized by a Predicted Mean Vote equal to 0; or a slightly warm environment, characterized by a Predicted Mean Vote equal to 0.5; or a slightly cool environment, characterized by a 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 in the adaptation stage, use the dynamic human bioheat model to determine the dynamic change curve of the skin temperature. Specifically:
[0047] (3.1) Use numerical simulation software to build a dynamic human bioheat model;
[0048] (3.2) Based on the initial skin temperature, initial core temperature, and the thermal environment of the environmental chamber in the adaptation stage, use the dynamic human bioheat model to calculate the dynamic changes of human physiological parameters and determine the dynamic change curve of the skin temperature.
[0049] Refer to Figure 2 , the adaptation stage occurs when the person enters the environmental chamber in the adaptation stage from the original environment (i.e., the thermal history). Random sampling is performed based on the statistical distribution of the skin temperature obtained in Step 1 as the initial skin temperature, and the initial core temperature is calculated based on the correlation between the core temperature and the skin temperature. Use numerical simulation software to build a dynamic human bioheat model, and calculate the dynamic changes of human physiological parameters and obtain the corresponding change curves based on the initial state, the thermal environment of the environmental chamber in the adaptation stage, and the built dynamic human bioheat model.
[0050] Step 4: Based on the dynamic change curve of the skin temperature, determine the stable time length according to the stability limit;
[0051] (4.1) Set the stability limit ε, where ε is a non - negative number; the stability limit is determined by the thermal environment assessor and is selected within the range of 0.1°C - 0.5°C. The smaller the value of the stability limit ε, the closer the equivalent stable state is to the stable state, and the larger the stable time length; one sampled skin temperature corresponds to one stable time length, and all stable time lengths form a stable time length distribution.
[0052] (4.2) Based on the stability limit and the dynamic change curve of the skin temperature, determine the time t corresponding to the equivalent stable state e : The stable skin temperature of the dynamic change curve of the skin temperature is T s , when the skin temperature in the initial state is higher than the stable skin temperature T s , the skin temperature of the equivalent stable state is T s + ε; when the skin temperature in the initial state is lower than the stable skin temperature T s , the skin temperature of the equivalent stable state is Ts -ε; The time corresponding to the equivalent steady state obtained from the dynamic change curve of skin temperature is t e ; The expression of the steady time length is as shown in formula (1):
[0053] Δt s =t e -t i (1)
[0054] Where, Δt s is the steady time length; t e is the time corresponding to the equivalent steady state; t i is the starting time.
[0055] The time required for stabilization is the time required for a person to change from the initial state to the equivalent steady state, where the time t e corresponding to the equivalent steady state will be determined by the stability limit ε and the dynamic change curve of skin temperature, and the corresponding skin temperature T e will be jointly determined by the steady skin temperature T s of the dynamic change curve and the stability limit ε. When the skin temperature in the initial state is higher than the steady skin temperature T s , the skin temperature in the equivalent steady state is T s +ε; when the skin temperature in the initial state is lower than the steady skin temperature T s , the skin temperature in the equivalent steady state is T s -ε; thus, the steady time length Δt s =t e -t i , which is the difference between the time corresponding to the equivalent steady state and the starting time.
[0056] Step Five: Obtain the adaptation time length based on the confidence level and the steady time length.
[0057] One initial state (i.e., the initial skin temperature sampled and the corresponding calculated initial core temperature) corresponds to one steady time length. Based on Steps One to Five, a steady time length distribution can be aggregated. Set the confidence level σ; the confidence level is determined by the hot environment assessment leader. The larger the value of the confidence level σ, the stronger the reliability of the determined adaptation time length, and the larger the TLAP. According to the determined confidence level σ, select the steady time length that satisfies the cumulative probability of the lower region being σ from the steady time length Δt s distribution. This steady time length is the adaptation time length TLAP (Time Length of Adaptation Phase, TLAP).
[0058] Example One
[0059] First, based on Figure 1According to the prior knowledge or the thermal comfort database, the present invention selects the ASHRAE Thermal Comfort Database II covering a variety of thermal conditions for the inference of the initial state, and the results are plotted as Figure 3 (a)- Figure 3 (d). Based on the ASHRAE Thermal Comfort Database II and the steady-state human bio-thermal model, the overall distribution of skin temperature is in the range of 30°C - 36°C; the skin temperature generally follows a normal distribution. The mean and standard deviation of skin temperature in the summer scenario are 33.78°C and 0.79°C respectively, and the mean and standard deviation of skin temperature in the winter scenario are 33.89°C and 0.98°C respectively. The overall distribution of core temperature is in the range of 36.7°C - 37.3°C. The mean and standard deviation of core temperature in the summer scenario are 36.88°C and 0.06°C respectively, and the mean and standard deviation of core temperature in the winter scenario are 36.89°C and 0.09°C respectively. Based on the above data, the correlation formula between the core temperature and the skin temperature is summarized, and the specific expression is shown in the following formula (2). This correlation formula effectively establishes the connection between the core temperature and the skin temperature, and the mean absolute deviation is only 0.03°C.
[0060]
[0061] In the formula, T c is the core temperature, °C; T sk is the skin temperature, °C.
[0062] The relative humidity, wind speed and metabolic rate are set to 50%, 0.10 m / s and 1.1 m / s in summer and winter. The mean radiant temperature is the same as the air temperature. The clothing thermal resistance in summer is 0.5 clo, and the clothing thermal resistance in winter is 1.0 clo. When the environment in the adaptation stage is a thermoneutral environment, the air temperature in summer is 25.7°C, and the air temperature in winter is 22.6°C. The present invention determines the stable time length of the subjective thermal environment assessment under five stable limits of 0.1°C, 0.2°C, 0.3°C, 0.4°C and 0.5°C, and the results are plotted in Figure 4Taking the summer working condition as an example, when the stability limit is 0.5°C, when the initial state increases from 30°C to 34°C, the stable time length decreases from the original 63.4 min to 0 min, shortening by 63.4 min; when the initial state increases from 34°C to 36°C, the stable time length increases from the original 0 min to 18.2 min, increasing by 18.2 min. At a given initial state, when the stability limit decreases, the stable time length increases accordingly. When the initial skin temperature is 30°C, when the stability limit decreases from 0.5°C to 0.1°C, the stable time length increases from 63.4 min to 76.8 min. And the influence of the stability limit on the stable time length is non-linear. For example, when the stability limit decreases from 0.5°C to 0.2°C, the stable time length increases by 7.4 min, and when the stability limit further decreases from 0.2°C to 0.1°C, the stable time length increases by 6.0 min. Compared with the summer working condition, the stable time length in the winter working condition is longer, mainly because the clothing in winter causes the skin temperature to change more slowly.
[0063] Since the initial state randomly changes in practical life and is generally considered to follow a normal distribution, in order to reliably determine the adaptation time length for subjective thermal environment assessment, the present invention assumes that the mean value and standard deviation of the skin temperature follow a normal distribution, and the initial skin temperature is randomly sampled from the normal distribution. As an important physiological parameter that can characterize the state of a person, the core temperature can be determined by the correlation formula between the core temperature and the skin temperature (formula (2)). 10,000 different initial states are randomly sampled for reliable statistical analysis. The stable time length distributions of the randomly sampled initial states under different stability limits are as Figure 5 and Figure 6 shown. It can be found that most of the sample points are concentrated in the interval of 0 min for the stable time length. This is mainly because the randomly sampled thermal states are distributed near thermal neutrality, and the initial state is similar to the environment during the adaptation stage, so the required stable time length is 0 min. As the stability limit increases, the stable time length distribution tends to 0 min. And the stable time length distribution in the summer working condition is closer to 0 min than that in the winter working condition. However, overall, the stable time length distributions in the summer and winter working conditions are in the range of 0 min - 80 min. Therefore, for different adaptation processes, the adaptation time should be carefully determined to avoid large differences in the results of subjective thermal comfort assessment due to the adaptation time.
[0064] The present invention determines the adaptation time length for 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. And 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. When the stability limit further increases, the adaptation time length decreases slowly. Taking the summer working condition 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 38.9 min to 32.8 min, shortening by 6.1 min; when the stability limit further increases from 0.2°C to 0.5°C, the adaptation time decreases from the original 32.8 min to 25.2 min, shortening by 7.6 min. At a given stability limit, the adaptation time length decreases with the decrease of the confidence level. And when the confidence level decreases from 97.5% to 95.0%, the adaptation time length required for subjective thermal environment assessment decreases rapidly. When the confidence level further decreases, the adaptation time decreases slowly. When the stability limit is 0.1°C, when the confidence level decreases from 97.5% to 95.0%, the adaptation time decreases from the original 38.9 min to 35.4 min, shortening by 3.5 min; when the confidence level further decreases from 95.0% to 90.0%, the adaptation time decreases from the original 35.4 min to 31.2 min, shortening by 4.2 min.
[0065] The thermal environment of the environmental chamber during the adaptation stage in the present invention includes the thermoneutral state. Merely changing the thermal environment (such as changing the thermoneutral environment to a warmer or cooler environment) still falls within the protection scope of the present invention.
[0066] The physiological parameters in the present invention include skin temperature. Merely changing the physiological parameters (such as changing the skin temperature to heart rate) still falls within the protection scope of the present invention.
[0067] The initial state statistical distribution in the present invention includes normal distribution. Merely changing the form of the statistical distribution (such as changing the normal distribution to a statistical distribution inferred from 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; 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 follows: 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 starting time; 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.
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 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.
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.