ASHRAE Adaptive Thermal Comfort Standard

重庆地区通风舒适区及通风季节划分的探讨重庆大学李永兵张华玲张慧玲符佩佩摘要：本文以适应性模型为基础，根据人体热舒适及人体卫生学的要求，探讨了重庆地区通风环境下室内舒适温度、舒适风速、相对湿度，结合有效温度，综合考虑了它们之间的相互影响，绘制了重庆地区的通风舒适区。

同时与ASHRAE舒适区相比较，划分了重庆地区的通风季节。

关键词：通风；舒适；温度；季节1 前言近年来，随着环境问题的日益突出和能源的日益紧张，人们开始研究建筑如何适应当地的气候特点，在满足室内居住条件和舒适条件的前提下，有效的减少建筑能源消耗的比例，缓解能源供应的压力。

国家“十一”五课题提出研究长江流域居住建筑通风季节与时段的划分，就是研究的新的技术和方法，充分利用当地的气候资源，减少能源的消耗和利用，走可持续发展的能源道路。

2 室内热环境的影响因素及评价指标2.1 室内热环境舒适性的影响因素由于人体与环境之间不停地进行能量交换, 所以影响热舒适的因素包括环境气象条件、人的生理调节、心理影响、卫生等都会影响人体的热感觉，因而,热舒适是一个综合作用的结果。

大体上归结为空气温度、相对湿度、空气流速、平均辐射温度四个物理因素和衣服热阻、人体新陈代谢率两个人为因素。

为了便于对问题的研究，同时考虑到人体随着气候的变化会不断调整自己的着装，即人体的自我适应能力。

在对重庆地区通风舒适区的划分不考虑衣着、新陈代谢率等个体的差异以及平均辐射温度对其他各个因素的影响。

2.2 室内热环境的评价指标对热环境的评价可根据三类不同的标准[1]即1)生存标准；2)舒适性标准；3)工作效率标准。

目前用于室内热环境评价的主要指标见表1。

表1 热环境评价指标3 通风舒适区的确定3.1适应性模型的提出ASHRAE Standard 55[2]和ISO7730[3]对室内热环境的评价指标都是基于稳态的热环境条件下，对非空调建筑下的热环境研究存在明显的不足。

大量的研究与实测表明，在空调稳态热环境下的PMV与实际的热感觉投票TSV吻合较好，而在自然通风环境下，两者存在明显的区别。

air conditioning 空调air-air heat pump 气-气热泵air-blower 鼓风机air-cooling coil空气冷却盘管air-flow 空气流量airflow meter 空气流量表air-free 真空的air-meter 风速计air-vent 排气口、通风口airborne pollution大气污染airness 通风airway 风道专业名词缩写Air condition空调Air compressor空气压缩机Air condenser空气冷凝器Air cooler 空气冷却器EER （energy efficiency ratio）能效比COP （coefficient of performance）性能系数IAQ （Indoor Air Quality）室内空气品质IEQ (Indoor Environmental Quality)GSHP（Ground source heat pump）地源热泵PCM（Phase change material）相变材料Theory(Fundamentals of HVAC)Thermodynamics and Refrigeration Cycles （热力学和制冷循环）Fluid mechanics (流体力学)Heat Transfer (传热）Mass Transfer（传质学）Psychrometrics （焓湿学）Emphasis: English to ChineseTheory(Fundamentals of HVAC)Thermodynamics and Refrigeration Cycles （热力学和制冷循环）Fluid mechanics (流体力学)Heat Transfer (传热）Mass Transfer（传质学）Psychrometrics （焓湿学）Emphasis: English to ChineseTheory(Fundamentals of HVAC)Thermodynamics and Refrigeration Cycles （热力学和制冷循环）Fluid mechanics (流体力学)Heat Transfer (传热）Mass Transfer（传质学）Psychrometrics （焓湿学）Emphasis: English to ChineseTheory(Fundamentals of HVAC)Thermodynamics and Refrigeration Cycles （热力学和制冷循环）Fluid mechanics (流体力学)Heat Transfer (传热）Mass Transfer（传质学）Psychrometrics （焓湿学）Emphasis: English to ChineseTheory(Fundamentals of HVAC)Thermodynamics and Refrigeration Cycles （热力学和制冷循环）Fluid mechanics (流体力学)Heat Transfer (传热）Mass Transfer（传质学）Psychrometrics （焓湿学）Emphasis: English to ChineseTheory(Fundamentals of HVAC)Thermodynamics and Refrigeration Cycles （热力学和制冷循环）Fluid mechanics (流体力学)Heat Transfer (传热）Mass Transfer（传质学）Psychrometrics （焓湿学）Emphasis: English to ChineseTheory(Fundamentals of HVAC)Thermodynamics and Refrigeration Cycles （热力学和制冷循环）Fluid mechanics (流体力学)Heat Transfer (传热）Mass Transfer（传质学）Psychrometrics （焓湿学）Emphasis: English to ChineseTheory(Fundamentals of HVAC)Thermodynamics and Refrigeration Cycles （热力学和制冷循环）Fluid mechanics (流体力学)Heat Transfer (传热）Mass Transfer（传质学）Psychrometrics （焓湿学）Emphasis: English to ChineseEngineering InformationThermal Comfort （热舒适）Air Contaminant （空气污染物）Emphasis: Chinese to English; AbstractHVAC systems and EquipmentCentral cooling and Heating (集中供冷、供热）Decentralized Cooling and Heating(非集中式供冷、供热）Air-cooling and Dehumidifying coils （冷却去湿盘管）Air cleaners for particulate contaminants (可吸入颗粒污染物空气净化器)Unitary Air Conditioners and Unitary Heat Pumps (单元式空调机组和热泵）Emphasis: Reading Comprehension;Potential energy (势能)Thermal energy (内能)Kinetic energy (动能)Chemical energy (化学能)Nuclear (atomic) energy (原子能)Mechanical or shaft work (W)（机械功或轴功）Flow work（流动功）Saturated liquid (饱和液体)If a substance exists as liquid at the saturation temperature and pressure, it is called saturated liquid. Subcooled liquid (过冷液体)Compressed liquid (压缩液体)Saturated vapor (饱和蒸汽)Dry saturated vapor (干饱和蒸汽)Superheated vapor (过热蒸汽)Quality 干度Thermodynamics (热力学）Entropy (熵）；enthalpy (焓）Internal energy （内能）Potential energy （势能）Kinetic energy (动能）Saturated liquid （饱和液体）Subcooled liquid （过冷液体）Saturated vapor (饱和蒸汽）Super-heated vapor (过热蒸汽）Law of the conservation of energy (能量守恒定律）First law of thermodynamics (热力学第一定律）Second law of thermodynamics (热力学第二定律）Calculating Thermodynamic PropertiesBubble point 气泡点，始沸点Bubble point curve 气泡曲线Dew point 露点Zeotrope 非共沸点Azeotropic 共沸点Refrigeration cycle （制冷循环）Coefficient of Performance (性能系数）Refrigerating efficiency（制冷效率）Isentropic expansion （等熵膨胀）Isentropic compression（等熵压缩）Isothermal compression（等温压缩）Isobaric (等压）Equation of state (状态方程）Expansion valve (膨胀阀Fluid mechanics (流体力学)Shearing stress （切应力）Laminar flow （层流）Turbulence (紊流)Density(密度)Viscosity (粘度)absolute viscosity or dynamic viscosity(动力粘度); kinematic viscosity（运动粘度）Generalized Bernoulli equation （广义伯努利方程）Reynolds number （雷诺数）Boundary layer （边界层）Drag coefficient （阻力系数）Shearing stress (切应力）, NKinematic viscosity (运动粘度），m2/sThe ratio of absolute viscosity to density.Velocity gradient (速度梯度）Wall friction (壁面摩擦力）Heat transfer process（传热过程）Steady-State Conduction（稳态导热）Fourier lawOverall heat transfer process（总的传热）Transient heat flow （非稳态传热）Thermal Radiation (热辐射)Heat transfer (传热)Thermal conduction (热传导)Thermal convection (热对流)Thermal radiation (辐射)Natural (free) convection (自然对流)Forced convection (强迫对流)Boundary layer (边界层)Fully developed laminar flow （充分发展的层流流动）Fully developed turbulent flow （充分发展的紊流流动）Laminar sublayer (层流底层)Buffer layer (过渡层, 缓冲层)Turbulent region (紊流区)Thermal resistance in series(串联热阻)Thermal resistance in parallel(并联热阻)In the direction of (沿…方向)Be termed (被称为)Be designated as (被定义为)Thermal circuit (热力循环）Overall heat transfer coefficient (总传热系数) Logarithmic mean temperature difference(对数平均温差法)效率，效能) NTU (Number of heat exchanger heat Transfer Unit, 传热单元)Capacity Rate Ratio z (热容比)Parallel flow exchangers (顺流换热器)Counterflow exchangers (逆流换热器)Total rate of energy emission per unit area (单位面积总辐射力）Monochromatic emissive power （单色辐射力）Wien’s displacement law (维恩位移定律）Nonbalck (非黑体）Hemispherical emittance (半球辐射率）Gray（灰体）Absorptance (吸收率）Transmittance （透射率）Reflectance （反射率）Kirchhoff’s law（基尔霍夫定律）Lambert’s law（兰贝特定律）Diffuse radiation （漫辐射）Angle factor (角系数）Nonabsorbing media （非吸收性介质）Thermal circuit (热力循环）Overall heat transfer coefficient (总传热系数) Logarithmic mean temperature difference(对数平均温差法)效率，效能) NTU (Number of heat exchanger heat Transfer Unit, 传热单元)Capacity Rate Ratio z (热容比)Parallel flow exchangers (顺流换热器)Counterflow exchangers (逆流换热器) concentration gradient （浓度梯度）Molecular diffusion (分子扩散)Fick’s law （菲克定律）Mass diffusivity (扩散系数)Mass transfer coefficient (传质系数)Mass/Molar flux （质量/物质的量通量）Significant error (显著误差)Moist air （湿空气）Partial pressure gradient （分压力梯度）Convection of mass （对流传质）Lewis Relation （刘易斯关系）air washer（空气洗涤器）cooling tower (冷却塔)dehumidifying coil（除湿盘管）liquid absorbent(液体吸收剂)evaporative condenser(蒸发式冷凝器)dilute component（稀释成分）a binary gas mixture(二元气体混合物)random molecular motion（分子无规则运动）Stagnant fluids（停滞流体）nonpolar gas（非极性气体）mass transfer:Molecular diffusion（分子扩散）Convective mass transfer（对流传质）Atmospheric air (大气)Moist air (湿空气）Dry air （干空气）Thermodynamic temperature scale （热力学温标）Water at saturation （饱和水）Liquid water（液态水）barometric pressure （大气压力）troposphere（对流层）stratosphere（同温层、平流层）thermodynamic temperature scale（热力学温标）Humidity ratio （含湿量）Saturation humidity ratio (饱和含湿量）Specific humidity (比湿度）Degree of saturation (饱和度）Relative humidity (相对湿度）absolute humidity (绝对湿度）Dew-point temperature (露点温度）Thermodynamic wet-bulb temperature (热力学湿球温度）psychrometer 温度计Composition of Dry and Moist Air (干空气和湿空气组成成分)United States Standard Atmosphere （美国大气标准）Thermodynamic Properties of Moist Air （湿空气热力学性质）Thermodynamic Properties of Water at Saturation（饱和水的热力学性质）Humidity Parameters （湿度参数）Thermodynamic wet-bulb Temperature and Dew-point temperature（热力学湿球温度和露点温度）Psychrometric charts（焓湿图）troposphere(对流层）stratosphere(同温层）Absolute humidity (绝对湿度）Saturation humidity ratio (饱和含湿量）Degree of saturation (饱和度）Dew-point temperature (露点温度）Relative humidity (相对湿度）Thermodynamic wet-bulb temperature (热力学湿球温度）Psychrometric charts（焓湿图）energy expenditure（能量消耗）Human Thermoregulation(人体热调节)Energy Balance （能量平衡）Conditions for Thermal Comfort （热舒适状况）Prediction of Thermal Comfort （热舒适的预测）Thermostat setting(温度调节装置）thermoregulation（体温调节）hyperthermia（体温过高）hypothermia（体温过低）hypothalamus （下丘脑）vasodilation （血管舒张）Skin wettedness（皮肤潮湿率）Integral control（积分控制）Sensible heat（显热）Latent heat （潜热）ASHRAE thermal sensation scale(ASHRAE 热感觉指标）Clothing insulation levels(衣服热阻）Predicted mean vote （PMV）index(预期平均评价表）Thermal load(热负荷）Predicted percent dissatisfied (PPD）(预期不满意百分数）Two-Node Model (两节点模型）Skin compartment (皮肤间隔）Adaptive models (自适应模型）Hypothalamus(下丘脑)The metabolic activities（新陈代谢）dissipated（消耗）hyperthermia（体温过高）hypothermia（体温过低Sensible and latent heat losses(显热和潜热损失)heat storage（蓄热）Energy Balance （能量平衡）Conditions for Thermal Comfort （热舒适状况）Prediction of Thermal Comfort （热舒适的预测）Steady-State Energy Balance（稳态能量平衡）Prediction of Thermal Comfort （热舒适的预测）Essential values（基准值）Classification of Air Contaminants(空气污染物分类) Particulate Contaminants（颗粒污染物）Arise from:Wind erosion (风的侵蚀)Sea spray evaporation(海水蒸发)Volcanic eruption(火山喷发)Metabolism or decay of organic matter(有机物质的新陈代谢或腐烂)Human activityElectric power-generating plants(发电厂)Various modes of transportation(各种运输方式) Industrial processesMining（采矿）, smelting（冶炼）, construction（建筑）Agriculture generateAir Contaminants（空气污染物）helium （氦）particulate（颗粒，微粒）dusts(粉尘）fumes(烟雾、烟尘）mist(轻雾）fogs（雾）smog（烟雾）bioaerosols(生物气溶胶）inhalable(可吸入的)respirable（呼吸性的）anthropogenic (人为的)bacteria（菌）viruses（病毒）fungus（菌类）pollen（花粉）environmental tobacco smoke （环境香烟烟雾，二手烟）inhalable mass（可吸入物）thoracic particle mass（胸部颗粒物）respirable particulate mass (可吸入颗粒物) aerodynamic （equivalent）diameter （空气动力学（当量）直径）Optical particle counters(光学粒子计数器)Minimum efficiency reporting value (最低效率报告值) Condensation nucleus counter (凝结核计数器)Optical density (光密度)Microscope(显微镜)Cascade impactor (分级采样仪)inhalable mass（可吸入物）thoracic particle mass（胸部颗粒物）respirable particulate mass(可吸入颗粒物)An efficiency by mass(质量效率)Suspended particles （悬浮颗粒）Preassessment (预评估)Air sampling(空气取样)Dry filter paper(干滤纸)Glass impingers (玻璃吸收瓶)Slit samples (膜取样)Culture plate impactors (培养皿采样仪)Slit-to-agar samplers(膜-琼脂采样)Filter cassette samplers (过滤盒采样)Data interpretation(数据说明)Redundancy （富裕量）Reliability （可靠性）Flexibility （灵活性）Life cycle analysis （生命周期分析）Construction budget（施工预算）CENTRAL COOLING AND HEATING（集中制冷与供热）DECENTRALIZED COOLING AND HEATING（分散式制冷与供热）AIR-COOLING AND DEHUMIDFYING COILS（空气冷却与除湿盘管）AIR CLEANERS FOR PARTICULATE CONTAMINANTS（颗粒污染物的空气净化器）UNITARY AIR CONDITIONERS AND UNITARY HEAT PUMPS （单元式空调器与热泵）Refrigeration Equipment（制冷设备）Heating Equipment（供热设备）Distribution(输配)Instrumentation （仪表）Space Requirements（空间需求）Central Plant Loads（集中设备负荷）Geothermal (地热)Maintenance and labor costs（维护和劳动成本）Decentralized plant（分散式设备）Boiler（锅炉）Centrifugal refrigeration units（离心式制冷机组）Absorption chillers（吸收式冷水机组）Heat reclaim（热回收）Exhaust gases（废气）Air distribution（气流组织）Ice thermal storage（冰蓄冷）Conventional system（常规系统）Energy penalty=energy loss（能量损失）chilled water （冷冻水）decentralized plant（分散式设备）Boilers（锅炉）absorption chillers （吸收式冷水机组）heat reclaim （热回收）any exhaust gases（废气）ir distribution（气流组织）water and ice thermal storage（冰蓄冷）conventional system（常规系统）he energy penalty（能量损失）reciprocating compressors(活塞式压缩helical rotary compressors（螺杆式压缩机）centrifugal compressors（离心式压缩机）absorption chillers（吸收式制冷机）frequently field assembled（现场组装）air-cooled or evaporative condensers （空气冷却或蒸发式冷凝器）remote installation（远程安装）Air cooled condensers（风冷冷凝器）Evaporative condensers（(蒸发式冷凝器）8.2HEATING EQUIPMENTWorking medium(工质)Circulation rate（循环流量）Fire tube boilers（火管锅炉）Water tube boilers（水管锅炉）Cast iron sectional boilers（铸铁组合锅炉）Negative pressure （负压）Positive pressure（正压）Natural draft boiler（自然通风锅炉）Stack（烟道）Chimney（烟囱）Condenser water(冷凝水)Condensate(凝结水)Boiler feed（锅炉供水）Fuel oil(燃料油)Load calculation (负荷计算）Solar radiation (太阳辐射）Thermal equilibrium (热平衡）Conduct heat gain (导热得热）External wall (外墙）Sensible heat (显热）Heat transfer coefficient (传热系数）Shading coefficient (遮阳系数）Latent heat (潜热）Exterior window (外窗）Wind velocity (风速）Wind pressure (风压）Stack effect (烟囱效应）Cooling load （冷负荷）Commercial building (商业建筑）Residential building (居住建筑）System characteristics(系统特征)Economizers（节能装置）Through-the-wall and Window-mounted Air Conditions and Heat Pumps（穿墙式和窗式空调及热泵）Interconnected Room-by-room System（互联的室室系统）heating coil （加热盘管）Cooling coil （冷却盘管）Window air conditioners（窗式空调器）through-the-wall room air conditioners（穿墙式房间空调器）unitary air conditioners （单元式空调器）air-source heat pumps （空气源热泵）water-source heat pumps （水源热泵）Self-contained units（独立式机组）discharge air temperature（排风温度）Air-handling systems（空气处理系统）Self-contained units（独立式机组）outdoor air damper, relief damper, return air damper(室外空气阀、排风阀、回风阀)variable-volume relief fan（变量排风风机）static pressure （静压）dynamic pressure （动压）direct-expansion cooling coil（直接蒸发式表冷器）variable-air-volume （VAV变风量）Packaged terminal air conditioners(组合式末端空调器) ductwork(管道系统)cabinet enclosure(箱体外壳)stack effect(烟囱效应)Hermetic reciprocating compressors(全封闭活塞式压缩机)scroll compressors(涡旋式压缩机)expansion valves(膨胀阀)energy efficiency ratio (coefficient of performance) defrost(除霜)Warm air furnaces (暖风机）Hot water boilers (热水锅炉fire tube boilers（烟管锅炉）water tube boilers（水管锅炉）cast-iron sectional boilers（铸铁模块锅炉）electric boilers（电锅炉）Air handlers (空气处理装置)Field built-up system（现场组合系统）Economic analysis （经济性分析）Air handler(空气处理装置、空调箱)Aqueous glycol(乙二醇水溶液)Barometric pressure(大气压力)Bypass damper(旁通风管)cleanliness(洁净度)Constant pressure expansion valve(恒压膨胀阀)Cross-counterflow(交叉逆流)dehumidify（除湿、减湿）Drain plug（泄水阀）Eliminator plate（挡水板）Throttling vavle（节流阀）Water and Aqueous Glycol Coils (水和乙二醇盘管) Direct-Expansion Coils(直接蒸发盘管)outside diameter(外径)tube spacing ranges（管间距）Water and Aqueous Glycol(乙二醇溶液)CoilsThe capillary tube （毛细管）thermostatic expansion valve(TXV)（热力膨胀阀）General Exhaust (Dilution) Ventilation Systems(全面通风) Local Exhaust Ventilation Systems（局部通风）Fan SelectionHoods （排风罩）Ducts（管道）Air CleanersStacks （烟囱）Make-up Air Systems （补风）Make-up air systems补风系统ventilation system 通风系统emission sources 排放源污染源general exhaust ventilation全面通风dilution ventilation 稀释通风local exhaust ventilation 局部通风number of air changes 换气次数mixing efficiency 混合效率hood排风罩contaminant 污染物make-up air 补充空气air cleaner 空气处理器stacks烟囱static pressure 静压velocity pressure动压axial flow fan 轴流风机centrifugal fan离心风机entry losses 入口损失friction losses摩擦损失precipitator除尘器cyclone 旋风除尘器negative pressure负压positive pressure正压air-handling system 空气处理系统recirculated air（循环风）airborne particles（尘埃粒子）microorganisms（微生物）Air Cleaning Applications （空气净化应用）Mechanisms of Particle collection （除尘机理）Evaluating Air Cleaners （评价空气净化器）Types of Air Cleaners （空气净化器的类型）Filter Types and Their Performance （过滤器的类型及性质）smaller particles, the respirable（可吸入）fraction Electronic air cleaners （静电空气净化器）medium-to high-efficiency filters （中高效过滤器）high-or ultrahigh-efficiency filters（高效或超高效过滤器）Efficiency(效率)Resistance to airflow（气流阻力）Dust-holding capacity（容尘量）Efficiency(效率)Resistance to airflow（气流阻力）Dust-holding capacity（容尘量）Arrestance（捕集率）ASHRAE Atmospheric Dust-Spot Efficiency（ASHRAE大气比色效率）Fractional Efficiency or Penetration （分级效率或穿透率）Efficiency by Particle Size（粒径效率）Dust Holding Capacity（容尘量）Types of Air Cleaners （空气净化器的类型）Fibrous media unit filter 纤维过滤器Renewable media unit filter 可再生介质过滤器Electronic air cleaners 静电空气净化器Combination air cleaners 组合式空气净化器Filter Types and Their Performance （过滤器的类型及性质）Viscous impingement panel filter 粘性撞击板式过滤器Dry-type extended-surface filter 干式折叠式过滤器Electret filter 静电过滤器Very high-efficiency dry filter 高效干式过滤器Membrane filter 膜过滤器Negative ionizer 阴离子发生器Space charge 空间电荷Ozone臭氧Types of unitary Equipment（单元式设备的类型）Equipment and System Standards（设备和系统标准）12.1Types of unitary Equipment（单元式设备的类型）Arrangement 布置Heat Rejection 排热量Heat Source/Sink 热源/汇Unit Exterior室外机Placement 安装位置Ventilation Air新风Desuperheaters过热器12.2Equipment and System Standards（设备和系统标准）Energy Conservation and Efficiency 节能和效率the Energy Policy and Conservation Act能源政策和能源保护法the Federal Trade Commission (FTC)联邦商务委员会The U.S. Department of Energy (DOE)美国能源部The seasonal energy efficiency ratio (SEER)季节能效比a heating seasonal performance factor (HSPF)供热季节性能系数ARI Certification Programs ARI认证程序Safety Standards and Installation Codes安全标准和安装法规heat pump 热泵reversing valve 四通换向阀heating cycle 制热循环cooling cycle制冷循环indoor coil室内盘管outdoor coil 室外盘管frost 霜结霜defrost 除霜energy efficiency ratio (EER) 能效比coefficient of performance (COP) 性能系数heating seasonal performance factor (HSPF) 制热季节性能系数seasonal energy efficiency ratio (SEER) (制冷)季节能效比ambient temperatures室外气温air-source heat pump 空气源热泵water-source heat pump 水源热泵ground-water heat pump 地下水源热泵geothermal closed-loop heat pump 闭环地源(或土壤源)热泵Frost formation(结霜).。

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科学技术创新2021.12模型预测结果。

参考文献[1]Fanger P.O.Thermal comfort,Analysis and application in environmental engineering,McGraw Hill.1970.[2]De Dear RJ.The adaptive model of thermal comfort and energy conversation in the built Environment Intl J Biomaterial,45,2001;p.100-108.[3]王海英,胡松涛.对PMV 热舒适模型适用性的分析[J].建筑科学,2009,25(006):108-114.[4]黑赏罡,姜曙光,杨骏,等.Fanger PMV 热舒适模型发展过程及适用性分析[J].低温建筑技术,2017(10).[5]丁勇花,狄育慧,王智鹏.热舒适模型与热适应模型的对比分析[J].低温建筑技术,2015,37(4):149-152.[6]ASHRAE.Standard 55.Thermal Environmental Conditions for Human Occupancy.Atlanta:ASHRAE;2004.[7]ISO 7730,Thermal comfort using calculation of the PMV and PPD indices and local thermal consideration,International Organization Standardization (2005).[8].au/rp -884/ashrae_rp884.html [Accessed on dated 21-04-2014].[9]de Dear R,Brager G,Cooper D.Developing an adaptive model of thermal comfort and preference:Final Report ASHRAE RP -884.Sydney,Australia:Macquarie University;1997.基金项目:2019年国家级大学生创新创业训练计划项目,课题编号201910205005。

eScholarship provides open access, scholarly publishing services to the University of California and delivers a dynamicresearch platform to scholars worldwide.Center for the Built EnvironmentUC BerkeleyPeer ReviewedTitle:Developing an Adaptive Model of Thermal Comfort and Preference Author:de Dear, Richard , Macquarie UniversityBrager, G. S., University of California, Berkeley Publication Date:01-01-1998Series:Indoor Environmental Quality (IEQ)Publication Info:Indoor Environmental Quality (IEQ), Center for the Built Environment, Center for Environmental Design Research, UC BerkeleyPermalink:/uc/item/4qq2p9c6Additional Info:ORIGINAL CITATION: de Dear, R.J., and G.S. Brager. 1998. “Towards an Adaptive Model of Thermal Comfort and Preference.” ASHRAE Transactions, Vol 104 (1), pp. 145-167.Abstract:The adaptive hypothesis predicts that contextual factors and past thermal history modify building occupants' thermal expectations and preferences. One of the predictions of the adaptive hypothesis is that people in warm climate zones prefer warmer indoor temperatures than people living in cold climate zones. This is contrary to the static assumptions underlying the current ASHRAE comfort standard 55-92. To examine the adaptive hypothesis and its implications for Standard 55-92, the ASHRAE RP-884 project assembled a quality-controlled database from thermal comfort field experiments worldwide (circa 21,000 observations from 160 buildings). Our statistical analysis examined the semantics of thermal comfort in terms of thermal sensation,acceptability, and preference, as a function of both indoor and outdoor temperature. Optimum indoor temperatures tracked both prevailing indoor and outdoor temperatures, as predicted by the adaptive hypothesis. The static predicted means vote (PMV) model was shown to be partially adaptive by accounting for behavioral adjustments, and fully explained adaptation occurring in HVAC buildings. Occupants in naturally ventilated buildings were tolerant of a significantly wider range of temperatures, explained by a combination of both behavioral adjustment and psychological adaptation. These results formed the basis of a proposal for a variable indoor temperature standard.THIS PREPRINT IS FOR DISCUSSION PURPOSES ONLY , FOR INCLUSION IN ASHRAE TRANSACTIONS 1998, V. 104, Pt. 1. Not to be reprinted in whole or in part without written permission of the American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc., 1791 Tullie Circle, NE, Atlanta, GA 30329.Opinions, findings, conclusions, or recommendations expressed in this paper are those of the author(s) and do not necessarily reflect the views of ASHRAE. Written ABSTRACTThe adaptive hypothesis predicts that contextual factors and past thermal history modify building occupants' thermal expectations and preferences. One of the predictions of the adaptive hypothesis is that people in warm climate zones prefer warmer indoor temperatures than people living in cold climate zones. This is contrary to the static assumptions underlying the current ASHRAE comfort standard 55-92. To examine the adaptive hypothesis and its implications for Standard 55-92,the ASHRAE RP-884 project assembled a quality-controlled database from thermal comfort field experiments worldwide (circa 21,000 observations from 160 buildings). Our statistical analysis examined the semantics of thermal comfort in terms of thermal sensation, acceptability, and preference, as a func-tion of both indoor and outdoor temperature. Optimum indoor temperatures tracked both prevailing indoor and outdoor temperatures, as predicted by the adaptive hypothesis. The static predicted means vote (PMV) model was shown to be partially adaptive by accounting for behavioral adjustments,and fully explained adaptation occurring in HVAC buildings.Occupants in naturally ventilated buildings were tolerant of a significantly wider range of temperatures, explained by a combination of both behavioral adjustment and psychological adaptation. These results formed the basis of a proposal for a variable indoor temperature standard.INTRODUCTIONCurrent comfort standards are intended to optimize the thermal acceptability of indoor environments. Unfortunately,they have tended to require energy-intensive environmental control strategies and often preclude thermally variable solu-tions, such as many climate-responsive and energy-conserv-ing designs, or innovative mechanical strategies that allow for personal control. These standards (ASHRAE 1992, ISO 1994)prescribe a narrow band of temperature to be applieduniformly through space and time. They are based on a static model of thermal comfort that views occupants as passive recipients of thermal stimuli driven by the physics of the body’s thermal balance with its immediate environment, and mediated by autonomic physiological responses. The static model of thermal comfort is represented in contemporary ther-mal comfort standards such as the current ANSI/ASHRAE Standard 55-1992 (1992) that prescribe relatively constant indoor design temperatures with, at most, a slight seasonal difference to accommodate differences in summer and winter clothing patterns. These standards have come to be regarded as universally applicable across all building types, climate zones, and populations (e.g., Parsons 1994). But many researchers are beginning to challenge the assumption of universality, arguing that it ignores important cultural,climatic, social, and contextual dimensions of comfort, lead-ing to an exaggeration of the need for air conditioning (Kemp-ton and Lutzenhiser 1992).Growing dissatisfaction with static comfort temperatures and the ensuing environmental impact caused by mismanage-ment of energy resources, has prompted interest in a variable indoor temperature standard to supplement the current Stan-dard 55. A variable indoor temperature standard, based on the adaptive model of thermal comfort, would have particular relevance to naturally ventilated buildings and other situations in which building occupants have some degree of indoor climatic control. A variable temperature standard links indoor temperatures to the climatic context of the building and accounts for past thermal experiences and current thermal expectations of their occupants.Ideally, a variable temperature standard would be based on an alternative to traditional comfort theory, termed the adaptive model of comfort, in which factors beyond funda-mental physics and physiology interact with thermal percep-tion. An important premise of the adaptive model is that building occupants are no longer regarded as passive recipi-Developing an Adaptive Modelof Thermal Comfort and PreferenceRichard J. de Dear, Ph.D.Gail Schiller Brager, Ph.D.Member ASHRAERichard de Dear is a the Deputy Director of the Climatic Impacts Centre for the School of Earth Sciences, Macquarie University, Sydney,Australia. Gail Schiller Brager is an Associate Professor of Architecture at the Center for Environmental Design Research, University of Cali-fornia, Berkeley.SF-98-7-3 (4106) (RP-884)© 1998, American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc.(). Published in ASHRAE Transactions 1998, Vol 104, Part 1. For personal use only.Additional distribution in either paper or digital form is not permitted without ASHRAE’s permission.ents of the thermal environment, as in the case of climate chamber experimental subjects, but rather, play an active role in creating their own thermal preferences. Contextual factors and past thermal history are believed to modify expectations and thermal preferences. Satisfaction with an indoor climate results from matching actual thermal conditions in a given context and one’s thermal expectations of what the indoor climate should be like in that same context (Auliciems 1981, 1989, de Dear 1994a, Nicol 1993). In short, satisfaction occurs through appropriate adaptation to the indoor climatic environ-ment.The generic term adaptation might be interpreted broadly as the gradual diminution of the organism’s response to repeated environmental stimulation. Within this broad defini-tion it is possible to clearly distinguish three categories of ther-mal adaptation (Folk 1974, 1981, Goldsmith 1974, Prosser 1958, Clark and Edholm 1985):Behavioral Adjustment. This includes all modifications a person might consciously or unconsciously make that in turn modify heat and mass fluxes governing the body’s thermal balance. Adjustment can be further sub-classified into personal (e.g., removing an item of clothing), technological (e.g., turning on an air conditioner), and cultural responses (e.g., having a siesta in the heat of the day).Physiological. The most comprehensive definition of physiological adaptation would include changes in the phys-iological responses that result from exposure to thermal envi-ronmental factors, and which lead to a gradual diminution in the strain induced by such exposure. Physiological adaptation can be broken down into genetic adaptation (intergenera-tional) and acclimatization (within the individual’s lifetime).Psychological. The psychological dimension of thermal adaptation refers to an altered perception of, and reaction to, sensory information due to past experience and expectations. Personal comfort setpoints are far from thermostatic. Relax-ation of expectations can be likened to the notion of habitua-tion in psychophysics (Glaser 1966, Frisancho 1981) where repeated exposure to a stimulus diminishes the magnitude of the evoked response.In many commentators’ minds there is a belief that the static and “adaptive” schools of thought are irreconcilable (e.g., Auliciems 1989, Nicol 1993). The static heat balance models are grounded in a fairly linear, deterministic logic, and are tested with extensive and rigorous laboratory experiments yielding fairly consistent, reproducible results. But the simplistic cause-and-effect approach embodied in the static approach is not so easily applied to the more complex envi-ronments within real buildings populated by real occupants as opposed to subjects. Our opinion is that the adaptive perspec-tive complements rather than contradicts the static heat-balance view. The heat-balance model is more correctly regarded as a partially adaptive model, since it acknowledges the effects of behavioral adjustments made by occupants to thermal environmental parameters, clothing, and metabolic rate. We believe that a variable indoor temperature standard can successfully combine features of both the static and adap-tive models by incorporating behavioral, physiological, and psychological modes of thermal adaptation.This paper reports results from the ASHRAE RP-884 project—Developing an Adaptive Model of Thermal Comfort and Preference. The research is premised on the development and analysis of a quality-controlled, cumulative database of thermal comfort field experiments worldwide (see de Dear 1998 for more details on the RP-884 database). The specific objectives of RP-884 were to use this global database to: 1.Elaborate and define adaptive processes in the context ofindoor climatic perception.2.Examine the semantics of thermal sensation, acceptability,and preference scales within the context of an adaptive model of thermal comfort.3.Develop statistical models of thermal comfort based on thevarious processes of adaptation, including adjustment, acclimatization, and habituation.pare these adaptive models with predictions of the so-called static models across the database.5.Propose a variable temperature standard that, in time, mighteventually supplement and/or modify Standard 55.This paper highlights the most significant findings of RP-884, while a more detailed treatment can be found in the project’s final report (de Dear et al., 1997). BACKGROUNDBrager and de Dear (1998) present an extensive literature review on thermal adaptation in the built environment, elab-orating the different mechanisms of adaptation, linking the static vs. adaptive comfort theories through a conceptual model with interactive feedback loops, and presenting a wide range of both climate chamber and field evidence for the different modes of adaptation. Many of the highlights of that previous work helped to clarify the conceptual approach and analysis of RP-884, and are presented here for background.Of the three types of adaptation, behavioral adjustment of the body’s heat-balance probably offers the greatest opportu-nity for people to play an active role in maintaining their own comfort (Nicol and Humphreys 1972, Humphreys 1994a). The extent to which contextual factors offer building occu-pants scope to behaviorally interact with their indoor climate can be described in terms of adaptive opportunity (Baker and Standeven 1994). This concept helps to differentiate those buildings in which a deterministic relationship between the thermal environment and human response is applicable, and those in which an adaptive feedback loop is fully operational. Adaptive opportunity can be thought of as a continuum—at one extreme is the climate chamber, and at the other extreme we find the single-occupant room with full adaptive possibil-ities from operable windows through to task-ambient air conditioning.The evidence for physiological acclimatization is more thoroughly documented for heat exposure than for cold, andfor prolonged heat stress induced by a regimen of work in heat (Folk 1974, 1981, Fox 1974, Bruce 1960, Berglund and McNall 1973, Givoni and Goldman 1973). Unlike most behavioral adaptation, where a person consciously takes corrective action when uncomfortable, acclimatization is an unconscious feedback loop mediated by the autonomic nervous system. As shown later in this section, a review of the literature (Brager and de Dear 1998) demonstrated that accli-matization is not likely to be a factor for the moderate range of conditions found in most buildings.Psychological adaptation encompasses the effects of cognitive and cultural variables, and describes the extent to which habituation and expectation alter thermal perceptions. The role of expectation in thermal comfort research was acknowledged in the earlier work of McIntyre (1980), who stated that “a person’s reaction to a temperature, which is less than perfect will depend very much on his expectations, personality, and what else he is doing at the time.” Although the least studied of the three adaptive mechanisms, psycho-logical adaptation might actually play the most significant role in explaining the differences between observed and predicted thermal responses. This can be seen particularly in light of different environmental contexts, such as the laboratory vs. home vs. office, or when comparing responses in air-condi-tioned vs. naturally-ventilated buildings (Fishman and Pimbert 1982, Heijs and Stringer 1988, Busch 1990, de Dear et al. 1991c, Rowe 1995, Oseland 1995).Climate chamber evidence against the effects of acclima-tization on thermal comfort in moderate thermal environments comes from an experimental research design known as the preferred temperature method, in which the temperature within the chamber is directly controlled by its single subject. Using this technique, Fanger (1972 et al., 1977) tested subjects with differing climatic experiences (winter swimmers, work-ers from a refrigerated storeroom, long-term inhabitants of the tropics, and control groups), and found that their temperature preferences were all approximately the same. de Dear et al. (1991a) replicated Fanger’s tropical experiment with heat acclimated students on location in Singapore, and produced similar results. Gonzalez (1979) also studied the role of natu-ral heat acclimatization during a five day humid heat wave in New Haven, Connecticut. He found that for exercising subjects there was a discernible increase in preferred temper-ature after the heat wave (Gonzalez 1979), but there were no statistically significant differences in resting subjects. In conclusion, on the basis of the majority of experimental evidence published to date, subjective discomfort and thermal acceptability under conditions most typically encountered in residences and office buildings, by resting or lightly active building occupants, appear to be unaffected by the physiolog-ical processes of acclimatization.Although chamber studies have the advantage of careful control, field research is best for assessing the potential impacts of behavioral or psychological adaptations as they occur in realistic settings. Humphreys’ (1975) early review of 36 thermal comfort field studies worldwide produced one of the first, and most widely referenced, statistical relationships between indoor thermal neutralities and prevailing indoor temperatures. He found that building occupants were able to find comfort in indoor temperatures covering a broad band of more than 13 K, and attributed this to the adaptive processes, concluding that “. . . the range of recent experience is better regarded as one of the factors that will contribute to the accept-ability of the environment to which the respondent is exposed.” Subsequent work by both Humphreys (1978) and Auliciems (1981) found convincing evidence for a relation-ship between indoor thermal neutralities and outdoor climate, particularly in so-called free running buildings that had no centralized heating or cooling plant (i.e., naturally ventilated).While this work has been widely cited as the first to reveal a strong statistical association between neutralities and outdoor climate, the actual causal mechanisms were left unclear. To more rigorously test the relative influences of behavioral, physiological, and psychological adaptive influ-ences, field researchers have to collect simultaneous measure-ments of all of the input variables to Fanger’s predicted mean vote (PMV) model (ISO 1994). de Dear (1994a) and Brager and de Dear (1998) present a meta-analysis of results from such field experiments conducted in both climate-controlled (air-conditioned) and free-running (naturally ventilated) buildings located in a broad spectrum of climates and seasons (Busch 1990, de Dear and Auliciems 1985, de Dear and Foun-tain 1994b, de Dear et al. 1991c, Donnini et al. 1996, Schiller et al. 1988). The purpose of the meta-analysis was to compare observed comfort temperatures (based on sensation votes) with those predicted by the static heat balance model (Fanger’s PMV index). The PMV model predicted comfort temperatures with reasonable accuracy in most air-condi-tioned buildings, but failed significantly in the naturally venti-lated buildings, with the magnitude of the discrepancy increasing in the more extreme climate zones of the meta-anal-ysis. Since all basic physical parameters governing the body’s heat balance were included in PMV’s calculations, including the previously ignored contribution of the insulating value of the chair, the mismatch between observation and prediction in naturally ventilated buildings implicate adaptive factors beyond the body’s heat-balance.While we have known for a long time that clothing was a key input to the comfort problem (e.g., the clo inputs to Fanger’s 1970 PMV model), only a few studies have exam-ined field evidence of behavioral adjustment in the form of clothing changes. Fishman and Pimbert (1982) found that clo values had a strong linear dependence on outdoor weather and season, especially for women. Humphreys (1994b) and Nicol et al. (1994) concluded that as much as one-half the seasonal changes in comfort temperature could be attributed to clothing flexibility. In a longitudinal study, Nicol and Raja (1996) found that clothing changes were more strongly dependent on the succession of outdoor temperatures that occurred prior to the measurement, compared to the instantaneous or dailymean outdoor temperature, or for that matter, the instanta-neous indoor temperature, implying that we dress more for outdoor climate than indoor climate. By asking separate ques-tions about availability, use, and effectiveness of a variety of behavioral adaptive mechanisms, Benton and Brager (1994) found that clothing adjustments were given one of the highest effectiveness ratings. These findings all support the hypothe-sis that the statistical dependence of indoor neutrality on outdoor climate may, in part, be due to behavioral adjustments that directly affect the heat balance, rather than acclimatiza-tion or habituation.Evidence for psychological adaptation examines how contextual factors influence one’s perception of control and expectation, which in turn affect thermal response. Paciuk’s (1990) analysis of available control (adaptive opportunity), exercised control (behavioral adjustment), and perceived control (expectation) revealed that perceived degree of control was one of the strongest predictors of thermal comfort in office buildings, and had a significant impact in shaping both ther-mal comfort and satisfaction. This finding was also supported by the work of Williams (1995), in which office workers expressed higher levels of satisfaction when they perceived themselves to have more control over their environment. The effect of air conditioning on perceived control, expectation, and resulting thermal response has been investigated by several other researchers as well (Rowe et al. 1995, Fishman and Pimbert 1982, Black and Milroy 1966, Rohles et al. 1977). Their findings consistently indicate that people have a wider tolerance of variations in indoor thermal conditions if they can exert some control over them, such as in naturally ventilated buildings. In contrast, people in large open-plan air-condi-tioned buildings, typically devoid of any individualized control, had higher expectations for homogeneity and cool temperatures, and soon became critical if thermal conditions did not match these expectations.MethodsOur literature review (Brager and de Dear 1998) indicated that the overwhelming weight of evidence supporting human thermal adaptation came from field research, rather than climate chamber laboratory experiments. Therefore, the RP-884 approach focused exclusively on field data, and began the process of assembling a database by sending a three-page questionnaire on field research methods to most of the thermal comfort research community currently or recently active in field research. On the basis of the questionnaire returns, we requested data from researchers whose:1.methods of measurement, both physical and subjective,came as close as possible to laboratory-grade,2.data were structured to allow each set of questionnaireresponses to be linked to a concurrent set of indoor and outdoor climate observations, and 3.indoor climatic observations were comprehensive enoughto enable heat-balance indices (the static model) to be calculated for each questionnaire respondent.A primary goal was to keep the internal consistency of the database as high as possible. To this end, the RP-884 database was assembled from raw field data files instead of processed or published findings, enabling us to apply a variety of quality controls and standardized data processing techniques. Since the database is described in detail in de Dear 1998, the purpose of the next section is to briefly outline its contents and the basic steps taken to ensure its integrity.Assembling the World Comfort DatabaseThe raw data comprising the RP-884 database came from four continents and a broad spectrum of climatic zones. Nearly 21,000 sets of raw data were compiled from several locations in England and Wales, Bangkok, Thailand, several Califor-nian locations, Montreal and Ottawa in Canada, six cities across Australia, five cities in Pakistan, Athens in Greece, Singapore, and Grand Rapids in Michigan.Each complete set of raw data was structured within the database using the template developed in previous ASHRAE-funded research projects, particularly RP-462 in a Mediterra-nean climate (Schiller et al. 1988), RP-702 in a hot-humid climate (de Dear and Fountain 1994c), and RP-821 in a cold climate (Donnini et al. 1996). The data fields included:•thermal questionnaire responses (sensation, acceptabil-ity, and preference),•clothing and metabolic estimates,•concurrent indoor climate observations (air and globe temperatures, air velocity, dew point, and plane radiant asymmetry temperature),•thermal indices (mean radiant temperature, operative temperature, turbulence intensity, ET*, SET*, TSENS, DISC, PMV/PPD, and PD draft risk) were recalculated for each set of observations using the ASHRAE RP-781 software package known as the ASHRAE Thermal Comfort Tool (Fountain and Huizenga 1996),•outdoor meteorological observations including daily temperatures and relative humidities at 600 hours and 1500 hours, and daily effective temperatures (ET*) also calculated with the software package(excluding the effects of solar radiation).Of all these variables, it was the clothing insulation esti-mate that provided the RP-884 team with the most difficulties, since a variety of estimation methods were used in the various database contributions. To standardize the database, clo unit estimates based on either the Sprague and Munson (1974) method (also described in McIntyre 1980), the ISO Standard 7730 (1984) method, or the ISO Standard 7730 (1994) method were converted into their equivalents under the Standard 55 technique by using a set of conversion coefficients described in de Dear (1998). Accompanying each clothing insulationestimate in the database was an indication of whether or not the subject was seated at the time of their questionnaire response, since McCullough and Olesen (1994) have indicated that this has a significant effect on thermal insulation. An increment of 0.15 clo was added to the overall thermal insulation estimate for all seated subjects to account for the insulating value of a typical office chair.Once the field experiments supplied by original research-ers had been quality controlled and standardized into the RP-884 database template, they were broken down according to season (summer/winter) and building type (centrally-controlled buildings—HV AC), naturally ventilated buildings (NV), and mixed-mode buildings. The classification of build-ings largely depended on the judgment of the original researchers supplying raw data, but the main distinction between centrally-controlled HV AC and naturally ventilated buildings was that individual occupants in the former had little or no control over their immediate thermal environment, while occupants in naturally ventilated buildings at least had access to operable windows. It should be pointed out that most of the naturally ventilated buildings were only studied in the summer, and so the type of heating system was irrelevant. The few that were studied in winter may still have had a heating system in operation, but it was of the type that permitted occu-pant control. The sample included too few mixed-mode build-ings to permit meaningful analysis, so the remainder of this paper refers exclusively to NV and HV AC buildings.Meta-Analysis MethodsThe statistical analysis underlying the RP-884 adaptive models was conducted at the scale of individual buildings, of which there were 160 in the database. The main reason for this aggregation was that several parameters critical to the objec-tives of the project, such as thermal neutrality and preferred temperature, can only sensibly be derived from grouped comfort responses. Therefore, the RP-884 adaptive modeling exercise can be thought of as a meta-analysis of the separate statistical analyses conducted on each of the 160 buildings within the database.Several basic assumptions were made at the outset of the RP-884 meta-analysis. Field experiments with longitudinal research designs (repeated sampling of a few subjects) were assumed to have independence between observations and were statistically analyzed in the same way as cross-sectional research designs (once-off sampling of many subjects). For all statistical modeling conducted on the meta-file, each building data point was weighted according to the number of question-naire respondents it represented (i.e., sample size within the building). Derived statistical products such as a building’s thermal neutrality and preferred temperature were appended as new variables in the meta-file, but if the model or test in question failed to reach statistical significance at p < 0.05, the building registered a missing value code for that particular variable in the meta-file. The effect of this significance crite-rion was to eliminate from further analysis those buildings that had small sample sizes or that had uniformly hot or cold indoor temperature.Statistical analysis of subjective thermal sensation votes within each building were used to define thermal neutrality—the operative temperature found to correspond most closely with the scale’s central vote of neutral. Neutrality was calcu-lated for each building in the meta-analysis by the following steps:1.We binned the building’s indoor operative temperatureobservations into half-degree (K) increments, and analysed the bins’ mean thermal sensation responses.2.We fitted a weighted linear regression model betweensensations and operative temperature (t o):mean thermal sensation = a + b* (t o)3.Neutrality was derived by solving each building’s regres-sion model for a mean sensation of zero.Apart from neutrality, other information also was extracted from these regression models. Accepting the statis-tical assumptions underlying Fanger’s PMV/PPD model (1970), our range of t o corresponding with 80% acceptable thermal sensations was determined by solving each building’s regression model for mean thermal sensations of +0.85 (close to slightly cool or warm). The range of t o corresponding with 90% acceptable thermal sensations was determined in a simi-lar fashion, by solving for mean thermal sensations of +0.5.In addition to observed neutralities for each building, the meta-file also contained neutralities predicted by Fanger’s (1970) PMV heat-balance index. Our method consisted of inputting each building’s mean values for each of the five PMV variables (t o, rh, v, I cl + chair insulation,met) to the ASHRAE Thermal Comfort Tool software (Fountain and Huizenga 1996). The PMV model was then solved iteratively by adjusting t o (t a with t r linked) until the PMV output field equaled zero.Preferred temperature was assessed directly in a subset of 55 buildings in the RP-884 database with questionnaire items resembling this:“At this point in time, would you prefer to feel warmer,cooler, or no change?”The categorical responses to this question led us to probit analysis (Finney 1971, Ballantyne et al. 1977) rather than linear regression. Separate probit models were then fitted to the want warmer and want cooler percentages within each half-degree (K) operative temperature bin. Our operational definition of the preferred temperature within a particular building is the operative temperature corresponding to the intersection of the two fitted probit curves.The RP-884 work statement specified separate analyses of thermal comfort (assumed to be associated with specified thermal sensations) and preference. The rationale behind this distinction is known as the “semantic artefact hypothesis,”which suggests the preferred temperature in cold climates may, in fact, be described as slightly warm, whereas residents。

Journal of Thermal Biology 26(2001)415–418Activity rates andthermal comfort ofoffice occupants in SydneyDavidMalcolm Rowe*Department of Architectural and Desi g n Science,Wilkinson Buildin g (G04),The Uni v ersity of Sydney,NSW 2006,AustraliaAbstractDesigns for air conditioning systems are based on steady-state equilibrium theories of heat exchange and rely on the estimation of an average activity rate for building occupants.This is,however,an uncertain procedure.In a longitudinal field study of thermal comfort in an office building in Sydney,weightings were applied to self-reported activity rates to account for decay over the hour preceding the report.The average rate was nearly constant at 1.2met,in good agreement with other recent studies.However random individual variability may be a cause of some of the frequent complaints about thermal comfort in offices.r 2001Elsevier Science Ltd.All rights reserved.Keywords:Thermal comfort;Metabolic rate;Air conditioning;Field studies;Dissipation of metabolic heat1.IntroductionHuman thermal comfort depends on a balance between the rate of production of metabolic heat and losses due to exchange with the surrounding environ-ment.It is well established that the balance depends on four physical variables (air temperature,mean radiant temperature,air velocity andhumid ity)andthree personal variables (insulation provided by clothing,rate of production of metabolic heat and mechanical work performedby the subject).Mechanical work performed by sedentary office workers is negligible and is ignored.Modern office interiors are usually characterised by large open plannedareas.Design of air cond itioning systems for them is basedon the assumption of stead y state equilibrium conditions including clothing insula-tion andmetabolic rate as recommend edby the recognised standards ISO Document 7730ISO (1994)andASHRAE Stand ard55ASHRAE (1992).Designers aim to provide comfort for the largest possible propor-tion of occupants by maintenance of uniform steady state conditions as nearly as possible throughout theoccupiedspace.The physical variables can be controlled by design procedures but the designers have no such control over the personal variables.For the activity rate they rely on steady state averages for various types of activity that have been identified by strictly controlled laboratory experiments.The ISO andASHRAE stan-dards both suggest an average steady state value of 1.2met for the metabolic rate for typical office workers.Despite the best efforts of system designers,thermal comfort still remains problematic.From his analysis of unsolicitedcomplaints from 23,500occupants in 690buildings,Federspiel (1998)found that ‘‘thermal sensa-tion complaints (hot and cold)are the sin g le most common kind of unsolicited complaint in buildin g s and the o v erwhelmin g majority of unsolicited en v ironmental complaints (77%)’’Over the last decade or so a number of high quality field experiments have been conducted to study thermal comfort in office environments.Examples include investigations reportedby Schiller et al.(1988)and de Dear et al.(1993).Laboratory grade instruments have been usedto take accurate measurements of the physical variables while participants preparedreports of their current thermal sensations,together with details of current items of clothing andactivities in several time intervals over the preceding hour.Values for insulation*Corresponding author.Tel.:+61-2-9351-2490;fax:+61-2-9351-3031.E-mail address:***************.edu.au (D.M.Rowe).0306-4565/01/$-see front matter r 2001Elsevier Science Ltd.All rights reserved.PII:S 0306-4565(01)00053-5provided by clothing and activity rates have been estimatedfrom the information provid edin the sensa-tion reports with reference to tables of rates for individual garments and particular activities as tabu-lated in the ISO and ASHRAE standards.The aim of these studies was to determine optimal thermal conditions in a variety of climates.Activity rate is typically reportedas an average value for the whole group of subjects.Brager et al.(1994)have analyseda number of these studies and have concluded that a good average value for the metabolic rate of typical office workers is1.2met as stated in the standards.This paper reports some results from a longitudinal field study conducted over a period of two years in a typical office building in an inner suburb of Sydney, Australia.During the study1627thermal sensation reports with concurrent physical measurements were collected.Activity rates were estimated by a similar methodto those usedin thefieldstud ies referredto above with adhoc weighting factors d evisedby the author to account for the passage of time andintake of foodandbeverages.It was foundthat while the average for the whole study period was in good agreement with the standards,there was a discrepancy between the actual mean comfort vote andthe pred ictedmean vote (PMV)as calculatedfrom the averages of the variables. This discrepancy suggests that the estimated activity rate could be about10%low.Considerable diurnal and between-subject variation was observedwhich could account for some reports of occasional unacceptability of thermal conditions.2.Materials and methodsParticipants in the study were selected by invitation from occupants of two typicalfloors of the building with approximately equal numbers from each.The study extended from July1996to June1998with visits for measurement at approximately monthly intervals.Visits were suspended forfive months between February and August1997.Subject to availability,each participant was visitedtwice on each visit d ay(morning and afternoon)in an attempt to capture transient effects experienced during the day.Reports of their current activities were collectedfrom participants on separate visits to each of the selected levels at approximately monthly intervals.The report protocol was approvedby the human ethics committee of the university of Sydney.Activities were reported by checking boxes under the headings‘‘sitting quietly’’(55WmÀ2);‘‘sitting typing’’(65WmÀ2);‘‘standing still’’(70WmÀ2);‘‘on your feet working’’(80WmÀ2);‘‘driving a car’’(90WmÀ2)and‘‘walking around’’(100WmÀ2). Ratings were convertedto met values at the rate of 58WmÀ2=1.0met.The boxes were labelled‘‘last ten minutes’’,‘‘10minutes preceding’’,‘‘ten before that’’and ‘‘the half an hour before that’’.This methodof estimating activity rates was ad opted so that results couldbe comparedwith those of others working in thefield.It seems reasonable to expect that more recent activities wouldbe more influential than earlier ones on the current rate but,as far as it is known, no indication of appropriate weightings is given by other investigators.In the absence of such information adhoc factors were appliedas50%of the rating for activity during the last ten minutes,25%for the next,15%for the last ten minutes and10%for the half an hour before that.The resulting ratings for each periodwere totalled to produce an estimate of the rate for a whole hour. Boxes were also checked to indicate intake of food,hot or coldbeverages andsmoking cigarettes andfurther weighting was appliedas plus10%for a snack or meal andplus5%for a beverage or cigarette.Other information collectedon each visit includ ed current thermal sensation on the ASHRAE seven point scale fromÀ3(cold)to+3(hot);thermal preference (want warmer,want no change,want cooler)anda binary indication of acceptability.Respondents also tickedboxes to ind icate garments worn at the time and the data were used to estimate insulative values of clothing.Whilst the sensation report was being completedat each workstation,concurrent measurements of thermal conditions within one metre were made.Instruments were mountedon a trolley at1100mm above thefloor with a secondair temperature point at100mm above the floor.They included a shielded platinum resistance element for air temperature;an omnidirectional tem-perature compensatedconstant temperature anem-ometer for air velocity;a chilledmirror d ew-point sensor for relative humidity;and1801opposedsmall black andgoldplatedplane elements for plane rad iant temperature.Mean radiant temperature was calculated from the six orthogonal readings of radiant temperature andoperative temperature was calculatedas the arithmetic mean of air andmean rad iant temperatures. The instruments met ASHRAE andISO specifications. Values for PMV for the whole group andsubgroups were calculatedfrom averages of temperature,mean radiant temperature,air velocity,relative humidity,clo andmet.3.ResultsA total of1627activity reports with concurrent reports of clothing worn andmeasurements of physical variables were collectedfrom144persons who took part in the study.Approximately two-thirds of the partici-pants were males.Ages rangedfrom20to more than60 with50%in the bandfrom40to49years.About halfD.M.Rowe/Journal of Thermal Biology26(2001)415–418 416were professional or sub-professional scientists engaged in typical office work such as reading,writing,data entry or administrative tasks when sampled.The remainder were occupiedin management or ad ministrative assis-tance.Due to work commitments not all participants were present during all visits.During the study operative temperatures were observedin the occupiedspace ranging from201C to271C depending on season and time of day.The activity rate for each participant was calculated by the methodoutlinedabove andround edto thefirst decimal place.The whole sample mean was1.21met with standard deviation of0.22.Rates ranged from1.0 met to1.9met with distribution as shown in Table1 below.532morning/afternoon pairs of reports were collected and78%of respondents reported a different activity or activities resulting in rate estimates being different for the afternoon than that from the morning.For13 percent the difference was0.4met or more.A diurnal change in clothing insulation value was notedfor38% of respondents.Logarithmic regression was appliedto test for relationship between activity rate andoutd oor and indoor thermal conditions and a weak relationship was foundwith ind oor operative temperature(R2¼0:3).No relationship was found with outdoor conditions.During the course of the study71subjects submitted ten or more andup to34sensation reports.Analysis reveals that most of them couldreport thermal acceptability within a personal range of4–61C.On some occasions,however,they reportedcond itions as unac-ceptable within as well as outside the personal range. Space limitations preclude a full presentation of the results but some otherfindings of interest are shown in Table2below.4.DiscussionThe methodof estimating activity rates by analysing the range of activities performedby each subject andhis/ her intake of foodor beverages over the past hour was adopted to correspond with the method used by otherTable1Distribution of estimatedactivity rate observations in an office build ing,1met=58WmÀ2Activity rate(met) 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 Number of subjects36345230022216510146481810 %of the sample212617131063310.5Table2Summary of main results.Standard deviations are shown in brackets.S indicates the difference is significant at the95%confidence levelWhole sample Female Male Morning Afternoon Operative temperature(1C)23.623.423.623.823.4(1.3)(1.3)(1.3)(1.4)S(1.2)SAir velocity(m/s)0.140.130.140.140.14(0.07)(0.08)S(0.08)S(0.08)(0.07) Relative humidity(%)4242434242(10)(10)(10)(10)(10) Estimatedactivity rate(met) 1.25 1.20 1.21 1.21(0.22)S(0.21)S(0.21)(0.22) Clothing insulation(clo)0.690.720.680.690.69(0.17)(0.21)S(0.14)S(0.17)(0.16) Actual thermal sensation vote0.170.0960.1990.270.09(1.06)(1.045)(1.05)(1.06)S(1.06)S PMVÀ0.13+0.08À0.14À0.07À0.18 Standard effective temperature SET*(1C)24.224.424.124.424.1(1.6)(1.7)S(1.5)S(1.5)S(1.5)SD.M.Rowe/Journal of Thermal Biology26(2001)415–418417recent thermal comfort researchers so that results could be comparedd irectly with theirs.Measurement of heart rate might have provided a useful check on the method but was considered too intrusive for application in a long term study involving a large number of subjects. The estimatedaverage activity rate of1.2met is in goodagreement with the results of a number of stud ies reviewedby Brager et al.(1994)andwith levels suggested in the ISO and ASHRAE standards.How-ever,when usedwith average values of other variables to calculate PMV a discrepancy was found between the actual mean comfort vote of+0.17andthe PMV of À0.13.This suggests an error in the estimation of the activity rate,the insulative value of clothing or both as the most likely cause.If the cause of the error was limitedto the activity rate estimate it wouldamount to an underestimation of about10%and an underestima-tion of the neutral temperature of about0.51C.This order of error is considered acceptable having in mind the intrusive nature of alternative methods of measure-ment.Of possibly greater significance is the considerable between-subject andd iurnal variance of activity rates.A negative relationship between indoor temperature and activity rate suggests that some of the subjects may be deliberately reducing activity levels as conditions be-come warmer.Humphreys andNicol(1998)have proposedthat alteration of activity rate is one among a number of behavioural adaptive actions that people may take to accommodate less than optimal conditions. The weakness of the relationship suggests,however,that many of the observedvariations are the result of task or recreational activities.Between-subject andd iurnal variations in the insulative value of clothing were also observedandsome of them may compensate ad apta-tions.Application of the PMV relationship as set out in ISO Document7730shows that a difference of0.1met can be expected to produce a thermal sensation difference equivalent to that brought about by a difference in temperature of11C,sufficient to be noticedby a thermally sensitive person.A difference of0.4met will produce a sensation difference equivalent to a2.5–31C temperature difference,sufficient to induce some subjects to complain.As an example in a fairly typical situation where air andmean rad iant temperatures are equal at241C,air velocity is0.14m/s,relative humidity is43%and clothing insulation is0.7clo a person with an activity rate of1.2met wouldbe pred ictedby the PMV analysis to feel a neutral thermal sensation i.e.neither cool nor warm andwell within ISO comfort limits.With an activity rate of1.6,the PMV wouldbe0.58andoutsid e the comfort limit recommended in ISO Document7730. The scale of variation notedis such that thermally sensitive persons may be ledto complain.Diagnosis of the cause of such complaint wouldbe d ifficult if not impossible by the normal diagnostic techniques avail-able to service technicians.This suggests that when physical measurements fail to identify the cause of complaint,inquiry about recent activity levels may provide an explanation.Corrective action in a typical open plannedoffice environment may be d ifficult but at least a rational explanation,with assurance that the comfort sensation will improve with a return to more usual patterns of activity,may serve to relieve the anxiety of the complainant.AcknowledgementsThis work was supportedby fund s from the Aus-tralian Department of Education,Employment,Train-ing andYouth Affairs grantedthrough the Australian Research Council.The author is grateful to participants who provided sensation reports over a long time with patience andgoodhumour.ReferencesAmerican Society of Heating Refrigeration andAircond ition-ing Engineers,1992.Standard55F Thermal Environmental Conditions for Human Occupancy.ASHRAE,Atlanta. Brager,G.S.,Fountain,M.,Benton, C.C.,Arens, E.A., Bauman,F.S.,1994.A comparison of methods for assessing thermal sensation and acceptability in thefield.In:Oseland, N.A.,Humphreys M.A.(Eds.),Thermal Comfort:Past Present andFuture.BRE,Lond on,pp.17–38.de Dear,R.J.,Fountain,M.E.,Popovic,S.,Watkins,S., Brager,G.S.,Arens,E.A.,Benton,C.C.,1993.Afieldstud y of occupant comfort andoffice thermal environments in a hot humid climate.Macquarie Park Research Ltd.,Sydney. Federspiel, C.C.,1998.Statistical analysis of unsolicited thermal sensation complaints in commercial buildings.ASHRAE Tech.Data Bull.14(1),143–154. Humphreys,M.A.,Nicol,F.,1998.Understanding the adaptive approach to thermal comfort.ASHRAE Tech.Data Bull.14(1),1–14.ISO,1994.International Standard7730:moderate thermal environments F determination of the PMV and PPD Indices andspecification of the cond itions for thermal comfort.International Standards Organisation,Geneva.Schiller,G.E.,Arens, E.A.,Benton, C.C.,Bauman, F.S., Fountain,M.E.,Doherty,T.J.A.,1988.Afieldstud y of thermal environments andcomfort in office build ings.ASHRAE Trans.94(2).D.M.Rowe/Journal of Thermal Biology26(2001)415–418 418。

ASHRAE TC 9.9美国采暖制冷空调工程师技术委员会9.9 2011数据处理环境热指标——扩展数据中心和使用指导此白皮书由美国采暖制冷空调学会9.9技术委员会编写关键任务设施，技术领域，电子设备这篇有关于数据中心环境指引的白皮书是由9.9技术委员会的成员编写的（IT设备制造商和提交的TC9.9的审查和批准投票权的成员。

）在这份文件中，术语“服务器”一般是用来描述IT设备（ITE）的，比如服务器、存储器、网络产品、数据中心等应用。

执行摘要ASHREA 9.9委员会在2004年创造了《数据处理热指引》第一版。

在这之前必要的环境参数，都是经验理论值给每一个IT厂商。

在2008年ASHRAE 9.9委员会进行了第二次编辑，并扩充了热环境数据中心的范围，一边更多的人可以方便的查询到数据，以节约时间。

在第一次编写‘热指标’时候最重要的目标是建立一个一套公用环境指标，以符合环保准则。

尽管计算效率是重要的，但是性能和可用性依然是创建规范和设定温湿度额度所考虑的优先级，随着21世纪第一个十年的到来，计算效率已经被更加重视，创造一个可衡量的方式来了解数据中心设计和数据中心效率的运行效果电力使用效率（PUE），这成为衡量数据中心的新指标。

从第二版（2008年）的‘热指标’我们的建议信封就是以给予数据中心操作员指导为目的，让他们的工作维持高可靠度，并且提供最有效的营运能源效率方案。

这个信封是为了大部分的跨专业和跨越很多条件而创造。

无论如何，不同的环境信封可能会适合更多的商业价值和气候条件，因此允许经营不同的信封可能提供更大的节能效果，此白皮书提供服务器规范，这将有助于数据中心运营商创建一个符合他们商业价值的操作系统信封。

其中的每个指标描述，更多的细节将在书“数据处理环境热准则“第三版提供。

任何在建议之外的选择将会破坏冷却系统平衡并且影响节约能源，这一过程以简单的图片形式显示在图1，以下这些是决定创建自己的信封，不用建议信封去经营他们的数据中心的方案。