Adaptive processes explain variations in human thermal sensation

M. Schweiker
{"title":"Adaptive processes explain variations in human thermal sensation","authors":"M. Schweiker","doi":"10.1080/23328940.2016.1200204","DOIUrl":null,"url":null,"abstract":"Models for human perception of thermal environments included in so-called thermal comfort standards are either based on principles of thermal heat balance, or on large empirical datasets that include human adaptations to different thermal environments (i.e. so-called adaptive approach). The framework for an adaptive thermal heat balance model (ATHB) combines these 2 approaches, improves the predictive performance and offers further potentials to explain variations in human thermal sensation as discussed below. At first, due to different foundations of both models it may seem illogical to combine the heat balance approach with the adaptive approach. One is based on a steady-state heat balance of the human body taking into account the indoor environmental parameters air temperature, mean radiant temperature, air velocity, and air humidity as well as the clothing level and metabolic rate of a person. The other established a theoretical framework including behavioral, physiological, and psychological adaptive processes and considers averaged floating outdoor conditions. The combination of the 2 approaches as described by the ATHB is realized by setting up simple exemplary equations for each of the 3 adaptive processes individually. These equations adapt the values for the clothing level and the metabolic rate used as input for the heat balance model equations. The equation related to behavioral adaptation is a linear function with the running mean outdoor temperature as independent and the clothing level as dependent variable. With increasing outdoor temperatures, people are wearing lighter clothing ensembles. Maximum and minimum clothing insulation values are specified. Related to physiological adaptation, a linear equation modifies the metabolic rate based on the running mean outdoor temperature. With increasing outdoor temperatures, metabolic rate decreases as we assumed that people’s thermo-regulative system adapts to warm conditions and gets more efficient. Psychological adaptive processes were assumed to alter metabolic rate, too. This can happen on the one hand in a variable form depending on an environmental stimulus, e.g. with higher indoor temperatures, perceived control was found to decrease, which let the metabolic rate increase. On the other hand, this can be a fixed offset in metabolic rate depending on the type of environment, e.g., a higher number of people in the same room increased metabolic rate due to psychological stress while a higher number of control opportunities decreased metabolic rate. Using data from experimental studies in our LOBSTER facility, a realistic office environment with a controllable thermal indoor environment and possibilities for subjects to interact with the outdoor environment through operable windows (Fig. 1A), we derived the corresponding coefficients for these equations through mixed effect regression analyses. Thereby, the magnitude of increase and decrease of the metabolic rate was inferred from measurements of the heart rate and corresponding regression analyses. Differences in the metabolic rate or the degree of its adaptation between individuals or groups of individuals were neglected so far. However, the results of such analysis could be incorporated in future advancements of the approach as discussed below. Through the application of the framework to Fanger’s PMVmodel, it was possible to draw the relationship between operative temperatures perceived as neutral and the running mean outdoor temperature. Including all 3 adaptive","PeriodicalId":22565,"journal":{"name":"Temperature: Multidisciplinary Biomedical Journal","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2016-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Temperature: Multidisciplinary Biomedical Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/23328940.2016.1200204","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

Models for human perception of thermal environments included in so-called thermal comfort standards are either based on principles of thermal heat balance, or on large empirical datasets that include human adaptations to different thermal environments (i.e. so-called adaptive approach). The framework for an adaptive thermal heat balance model (ATHB) combines these 2 approaches, improves the predictive performance and offers further potentials to explain variations in human thermal sensation as discussed below. At first, due to different foundations of both models it may seem illogical to combine the heat balance approach with the adaptive approach. One is based on a steady-state heat balance of the human body taking into account the indoor environmental parameters air temperature, mean radiant temperature, air velocity, and air humidity as well as the clothing level and metabolic rate of a person. The other established a theoretical framework including behavioral, physiological, and psychological adaptive processes and considers averaged floating outdoor conditions. The combination of the 2 approaches as described by the ATHB is realized by setting up simple exemplary equations for each of the 3 adaptive processes individually. These equations adapt the values for the clothing level and the metabolic rate used as input for the heat balance model equations. The equation related to behavioral adaptation is a linear function with the running mean outdoor temperature as independent and the clothing level as dependent variable. With increasing outdoor temperatures, people are wearing lighter clothing ensembles. Maximum and minimum clothing insulation values are specified. Related to physiological adaptation, a linear equation modifies the metabolic rate based on the running mean outdoor temperature. With increasing outdoor temperatures, metabolic rate decreases as we assumed that people’s thermo-regulative system adapts to warm conditions and gets more efficient. Psychological adaptive processes were assumed to alter metabolic rate, too. This can happen on the one hand in a variable form depending on an environmental stimulus, e.g. with higher indoor temperatures, perceived control was found to decrease, which let the metabolic rate increase. On the other hand, this can be a fixed offset in metabolic rate depending on the type of environment, e.g., a higher number of people in the same room increased metabolic rate due to psychological stress while a higher number of control opportunities decreased metabolic rate. Using data from experimental studies in our LOBSTER facility, a realistic office environment with a controllable thermal indoor environment and possibilities for subjects to interact with the outdoor environment through operable windows (Fig. 1A), we derived the corresponding coefficients for these equations through mixed effect regression analyses. Thereby, the magnitude of increase and decrease of the metabolic rate was inferred from measurements of the heart rate and corresponding regression analyses. Differences in the metabolic rate or the degree of its adaptation between individuals or groups of individuals were neglected so far. However, the results of such analysis could be incorporated in future advancements of the approach as discussed below. Through the application of the framework to Fanger’s PMVmodel, it was possible to draw the relationship between operative temperatures perceived as neutral and the running mean outdoor temperature. Including all 3 adaptive
适应性过程解释了人类热感觉的变化
所谓的热舒适标准中包含的人类对热环境感知的模型要么基于热平衡原理,要么基于包括人类对不同热环境适应的大型经验数据集(即所谓的适应性方法)。自适应热平衡模型(ATHB)的框架结合了这两种方法,提高了预测性能,并提供了进一步解释人体热感觉变化的潜力,如下所述。首先,由于两种模型的基础不同,将热平衡方法与自适应方法结合起来似乎是不合逻辑的。一种是基于人体的稳态热平衡,考虑到室内环境参数——空气温度、平均辐射温度、空气速度和空气湿度,以及人的衣服水平和代谢率。另一个建立了一个理论框架,包括行为、生理和心理适应过程,并考虑了平均漂浮的室外条件。ATHB所描述的两种方法的结合是通过分别为3种自适应过程中的每一种建立简单的示例方程来实现的。这些方程适应了作为热平衡模型方程输入的服装水平和代谢率的值。行为适应方程是一个以室外平均温度为自变量,服装水平为因变量的线性函数。随着室外温度的升高,人们开始穿轻便的服装。规定了最大和最小服装绝缘值。与生理适应相关,一个基于室外平均温度的线性方程修正了代谢率。随着室外温度的升高,代谢率降低,因为我们假设人体的热调节系统适应了温暖的环境并变得更有效率。心理适应过程也被认为会改变代谢率。一方面,这可能以一种取决于环境刺激的可变形式发生,例如,在较高的室内温度下,感知控制被发现减少,这使得代谢率增加。另一方面,根据环境类型,这可能是代谢率的固定偏移,例如,由于心理压力,同一房间中人数较多会增加代谢率,而控制机会较多则会降低代谢率。利用我们在LOBSTER设施中进行的实验研究数据,我们通过混合效应回归分析得出了这些方程的相应系数,该设施是一个真实的办公环境,具有可控的室内热环境,并且受试者可以通过可操作的窗户与室外环境进行互动(图1A)。因此,代谢率的增加和减少的幅度是从心率的测量和相应的回归分析中推断出来的。迄今为止,个体或群体之间代谢率或适应程度的差异一直被忽视。但是,这种分析的结果可以纳入下文讨论的方法的未来进展。通过将该框架应用于Fanger的pmv模型,可以绘制出被视为中性的操作温度与运行平均室外温度之间的关系。包括所有三个自适应
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信