壁挂式空调房间内流场温度场特性与人体热舒适的研究
|
摘要
随着我国经济的发展，家用空调器日益普及。由于空调器的使用而引发的“空调综合症”和能源危机问题越来越引起人们的广泛关注，直接影响着人们的身心健康和社会的发展。因此，研究不同送风参数下壁挂式空调房间内流场和温度场的分布特性，探讨室内气流形式与热舒适的关系，提出壁挂式空调器的合理使用方法，对改善人居环境、减少能源的消耗具有重要的意义；探索人体热舒适的实验方法，建立不同热环境下的人体热舒适评价模型，为进一步研究控制方法和控制策略提供理论基础，对房间空调器的发展具有重要的意义。
本文首先以装有壁挂式空调器的实际房间为对象，利用自制的热电偶和数采仪搭建的温度采集系统研究了不同送风参数下壁挂式空调器制冷运行时室内气流及温度场分布特性。研究发现，导风板的旋转角度和送风速度对于室内温度的降低速度有较大的影响；当导风板旋转角度为45°时，室内温度下降的较快，各高度层面间的温差较小，人体的热感觉较好，房间内的舒适程度较高；室内温度出现明显的下冷上热的分层现象；送风参数的变化对壁面温度的影响很小，可以忽略不计。
在实验研究的基础上，本文以实验房间为模型，应用FLUENT软件对壁挂式空调器制冷运行时室内不同送风参数下的流场和温度场分布特性进行了数值模拟，并将其计算结果与实验结果进行了对比。通过研究分析表明，数值模拟的结果能够正确地反映室内流场和温度场的分布特性，说明本文所采用的模型是合理可行的；利用修正的空气分布特性指标(ADPI)和能量利用系数(EUC)，能够对不同送风参数下壁挂式空调房间内流场和温度场的舒适性及房间能耗的经济性作出更加合理的评价；导风板旋转角度越小，ADPI值越大，房间内的舒适性越好；导风板旋转角度越大，EUC值越大，房间能耗就越小，经济性就越好。
本文还采用上述数值模拟的方法，对壁挂式空调器制热运行时室内不同送风参数下的流场和温度场分布特性进行了数值模拟。研究结果表明，导风板的旋转角度和送风速度对于室内温度的上升速度有较大的影响；当导风板旋转角度为105°时，室内温度上升的较快，各高度层面间的温差较小，人体的热感觉较好，房间内的舒适程度较高；送风角度越大，回风温度与室内平均温度的温差就越小；导风板旋转角度越大，ADPI值和EUC值越大，房间内的舒适性及房间能耗的经济性越好。
最后，根据热舒适理论，应用Matlab软件编写了PMV指标的计算程序，定量分析了热环境因素对PMV指标的影响，制定了人体热感觉的主客观调查表，建立了神经网络人体热舒适评判模型，并对其进行了实验验证。研究发现，随着室内空气温度、相对湿度和平均辐射温度的增大，PMV值增大，且近似成一次线性变化；随着室内空气流速的增大，PMV值急剧减小；神经网络人体热舒适评判模型的预测结果与目标值是比较吻合的，可以利用个体的学习样本来训练网络，能够解决不同的个体对相同环境的热感觉差异问题，对发展“个性化”空调具有非常重要的意义。
本文对壁挂式空调房间内流场温度场特性和人体热舒适性进行了比较系统的研究，以期为空调器的正确使用和空调器的功能优化等提供必要的理论依据。
Air-conditioners are becoming more and more popular with the development of economy, and the so-caused air-conditioner syndrome and energy problems caught more and more attention, which could affect people' health directly. Therefore, it is very important to study the distribution characteristics of airflow and temperature field under different air supplies condition in a room with wall air-conditioner and discuss the relationships between the indoor airflow and thermal comfort, thus bring forward the reasonable usage of wall air-conditioner to improve indoor air quality and reduce the energy consumption. To search for the experimental research method of human thermal comfort and establish the evaluation model of human thermal comfort in different thermal environments will also provide important theoretic instruction for the further practical control method and strategy of indoor thermal comfort, and that will facilitate the development of room air-conditioner.
In this paper, firstly the distribution characteristics of airflow and temperature field in an actual room with wall air-conditioner were studied under different air supply parameters, such as the airflow angle and speed when the air-conditioner was running for refrigeration. The distributions of temperature were detected by a self-made temperature acquisition system.The experiment results show that the temperature reducing rate is affected greatly by the angle of air deflector and air supply speed. When the angle was 45°, the room temperature reduced very fast, the temperature difference between contiguous layers was the least and human thermal feel was quite fine, and the degree of indoor thermal comfort was quite high. The upper part of the room is hot while the lower cool, which shows a stratification phenomenon. The effect of air supply parameters on the wall temperature is quite little, which could be ignored.
Base on the experiment situation, numerical simulation through FLUENT software was carried out to study the distribution characteristics of airflow and temperature field under different air supply conditions when the wall air-conditioner refrigeration. Compared with the foregoing experimental results under the similar conditions, the computational simulation results can reflect the distribution characteristics of airflow field and temperature field correctly, which shows that the model is rational and feasible. The thermal comfort degree and energy consumption under different air supplies of the room with wall air-conditioner could be evaluated more reasonably with the modified air diffusion performance index (ADPI) and energy utilization coefficient (EUC). The smaller the angle of the air reflector is, the larger is ADPI and the more comfortable is the room. The bigger the angle of the air reflector is, the larger is EUC and the higher is the economical efficiency.
The same numerical simulation method was also carried out to study the distribution characteristics of airflow and temperature field under different air supplies when the wall air-conditioner was running for heating. It was found that the temperature increasing rate is affected greatly by the angle and wind speed. When the air reflector angle is 105°, the temperature increases fastest and the temperature difference between layers is the least, meanwhile the human thermal feel is quite fine and the thermal comfort degree is high. Furthermore the larger the air refector angle is, the less is the temperature difference between the return air and the room average air temperature. The larger is the angle of air reflector, the larger ADPI and EUC are, the more comfort and the less energy consumption are.
According to thermal comfort theory, a computational program which could quantitatively analyse the effects of thermal environmental factors on predicted mean vote (PMV) index was compiled by using Matlab technique. Base on subjective and objective questionnaires about human thermal comfort, the neural network (NN) model of thermal comfort was established and validated by experimental results. It was found that the value of PMV increased with the room temperature, relative humidity and average radiation temperature, the relationship between them is almost of direct proportion. The value of PMV reduced sharply as air speed increased. The NN prediction results are agreed well with the target value. The NN could be trained by using individual study sample to solve the thermal comfort problem that different persons in the same thermal environment have different feeling, which will be more useful for the development of individual air-conditioner.
The airflow field and temperature field in the room with wall air-conditioner and the human thermal comfort degree were studied systematically, the research results will be very helpful for the correct use and improvement of air-conditioner.
本文首先以装有壁挂式空调器的实际房间为对象，利用自制的热电偶和数采仪搭建的温度采集系统研究了不同送风参数下壁挂式空调器制冷运行时室内气流及温度场分布特性。研究发现，导风板的旋转角度和送风速度对于室内温度的降低速度有较大的影响；当导风板旋转角度为45°时，室内温度下降的较快，各高度层面间的温差较小，人体的热感觉较好，房间内的舒适程度较高；室内温度出现明显的下冷上热的分层现象；送风参数的变化对壁面温度的影响很小，可以忽略不计。
在实验研究的基础上，本文以实验房间为模型，应用FLUENT软件对壁挂式空调器制冷运行时室内不同送风参数下的流场和温度场分布特性进行了数值模拟，并将其计算结果与实验结果进行了对比。通过研究分析表明，数值模拟的结果能够正确地反映室内流场和温度场的分布特性，说明本文所采用的模型是合理可行的；利用修正的空气分布特性指标(ADPI)和能量利用系数(EUC)，能够对不同送风参数下壁挂式空调房间内流场和温度场的舒适性及房间能耗的经济性作出更加合理的评价；导风板旋转角度越小，ADPI值越大，房间内的舒适性越好；导风板旋转角度越大，EUC值越大，房间能耗就越小，经济性就越好。
本文还采用上述数值模拟的方法，对壁挂式空调器制热运行时室内不同送风参数下的流场和温度场分布特性进行了数值模拟。研究结果表明，导风板的旋转角度和送风速度对于室内温度的上升速度有较大的影响；当导风板旋转角度为105°时，室内温度上升的较快，各高度层面间的温差较小，人体的热感觉较好，房间内的舒适程度较高；送风角度越大，回风温度与室内平均温度的温差就越小；导风板旋转角度越大，ADPI值和EUC值越大，房间内的舒适性及房间能耗的经济性越好。
最后，根据热舒适理论，应用Matlab软件编写了PMV指标的计算程序，定量分析了热环境因素对PMV指标的影响，制定了人体热感觉的主客观调查表，建立了神经网络人体热舒适评判模型，并对其进行了实验验证。研究发现，随着室内空气温度、相对湿度和平均辐射温度的增大，PMV值增大，且近似成一次线性变化；随着室内空气流速的增大，PMV值急剧减小；神经网络人体热舒适评判模型的预测结果与目标值是比较吻合的，可以利用个体的学习样本来训练网络，能够解决不同的个体对相同环境的热感觉差异问题，对发展“个性化”空调具有非常重要的意义。
本文对壁挂式空调房间内流场温度场特性和人体热舒适性进行了比较系统的研究，以期为空调器的正确使用和空调器的功能优化等提供必要的理论依据。
Air-conditioners are becoming more and more popular with the development of economy, and the so-caused air-conditioner syndrome and energy problems caught more and more attention, which could affect people' health directly. Therefore, it is very important to study the distribution characteristics of airflow and temperature field under different air supplies condition in a room with wall air-conditioner and discuss the relationships between the indoor airflow and thermal comfort, thus bring forward the reasonable usage of wall air-conditioner to improve indoor air quality and reduce the energy consumption. To search for the experimental research method of human thermal comfort and establish the evaluation model of human thermal comfort in different thermal environments will also provide important theoretic instruction for the further practical control method and strategy of indoor thermal comfort, and that will facilitate the development of room air-conditioner.
In this paper, firstly the distribution characteristics of airflow and temperature field in an actual room with wall air-conditioner were studied under different air supply parameters, such as the airflow angle and speed when the air-conditioner was running for refrigeration. The distributions of temperature were detected by a self-made temperature acquisition system.The experiment results show that the temperature reducing rate is affected greatly by the angle of air deflector and air supply speed. When the angle was 45°, the room temperature reduced very fast, the temperature difference between contiguous layers was the least and human thermal feel was quite fine, and the degree of indoor thermal comfort was quite high. The upper part of the room is hot while the lower cool, which shows a stratification phenomenon. The effect of air supply parameters on the wall temperature is quite little, which could be ignored.
Base on the experiment situation, numerical simulation through FLUENT software was carried out to study the distribution characteristics of airflow and temperature field under different air supply conditions when the wall air-conditioner refrigeration. Compared with the foregoing experimental results under the similar conditions, the computational simulation results can reflect the distribution characteristics of airflow field and temperature field correctly, which shows that the model is rational and feasible. The thermal comfort degree and energy consumption under different air supplies of the room with wall air-conditioner could be evaluated more reasonably with the modified air diffusion performance index (ADPI) and energy utilization coefficient (EUC). The smaller the angle of the air reflector is, the larger is ADPI and the more comfortable is the room. The bigger the angle of the air reflector is, the larger is EUC and the higher is the economical efficiency.
The same numerical simulation method was also carried out to study the distribution characteristics of airflow and temperature field under different air supplies when the wall air-conditioner was running for heating. It was found that the temperature increasing rate is affected greatly by the angle and wind speed. When the air reflector angle is 105°, the temperature increases fastest and the temperature difference between layers is the least, meanwhile the human thermal feel is quite fine and the thermal comfort degree is high. Furthermore the larger the air refector angle is, the less is the temperature difference between the return air and the room average air temperature. The larger is the angle of air reflector, the larger ADPI and EUC are, the more comfort and the less energy consumption are.
According to thermal comfort theory, a computational program which could quantitatively analyse the effects of thermal environmental factors on predicted mean vote (PMV) index was compiled by using Matlab technique. Base on subjective and objective questionnaires about human thermal comfort, the neural network (NN) model of thermal comfort was established and validated by experimental results. It was found that the value of PMV increased with the room temperature, relative humidity and average radiation temperature, the relationship between them is almost of direct proportion. The value of PMV reduced sharply as air speed increased. The NN prediction results are agreed well with the target value. The NN could be trained by using individual study sample to solve the thermal comfort problem that different persons in the same thermal environment have different feeling, which will be more useful for the development of individual air-conditioner.
The airflow field and temperature field in the room with wall air-conditioner and the human thermal comfort degree were studied systematically, the research results will be very helpful for the correct use and improvement of air-conditioner.
引文
[1] 2003 年中央空调市场研究报告[R]．
[2] 张智，涂旺荣等．空调制冷／制热时室内气流及温度分布数值研究[J]．工程热物理学报，2002，23(4)：457-460
[3] Nielsen P.V. Flow in Air Conditioned Rooms (English Translation)[D]. [ph.D, Thesis]. Copenhagen Technical University of Denmark, 1976
[4] R.J.Baker, P.T.Willianms, R.M.Kelso. Numerical Calculation of Room Air Motion-Part 1:Math, Physics and CFD Modeling[J]. ASHRAE, 1994, 100:514-530
[5] Guohui Gan. Evaluation of Room Air Distribution Systems Using Computational Fluid Dynamics[J].Energy and Buildings,1995,23:83-93
[6] Qingyan Chen, Weiran Xu. A Zero-equation Turbulence Model for Indoor Airflow Simulation[J].Energy and Buildings,1998,28:137-144
[7] Weiran Xu, Qingyan Chen. A Two-layer Turbulence Model for Simulating Indoor Airflow Part Ⅱ: Applications[J]. Energy and Buildings, 2001,33:627-639
[8] Weizhen Lu, Andrew T.Howarth, Alan P.Jeary. Prediction of Airflow and Temperature Field in a Room With Convective Heat Source[J].Building and Environment,1997,32(6):541-550
[9] S.L.Sinha, R.C.Arora, et al. Numerical Simulation of Two dimensional Room Airflow With and Without Buoyancy[J] .Energy and Buildings,2000, 32:121-129
[10] M.Bojic, F.Yik, T.Y.Lo. Locating Air-conditioners and Furniture inside Residential Flats to Obtain Good Thermal Comfort[J]. Energy and Buildings,2002,34:745-751
[11] Juan Ababto, Daniel Barrero, Marcelo Reggio, Benoit Ozell. Airflow Modeling in a Computer Room[J].Building and Environment,2004,39: 1393-1402
[12] 汤广发等．二维层流室内自然对流数值解[J]．空气动力学学报，1986，4(4)
[13] 汤广发等．用三维紊流数值方法优化水电站主厂房通风气流组织设计 [A]．第三届全国暖通专业计算机方法交流会[C]，1987
[14] 顾瑞英，武文斐．空调房间气流组织的数值模拟[A]．全国高等学校工程热物理研究会第四届学术会议论文集[C]，1992：157-160
[15] 王智伟，顾瑞英．具有内部障碍物及不规则形状边界问题的数值模拟 [J]．西安建筑科技大学学报，2000，32(1)：31-34
[16] 赵彬，李先庭，彦启森．用零方程湍流模型模拟通风空调室内的空气流动[J]．清华大学学报 (自然科学版)，2001，41(10)：109-113
[17] 赵彬，李冬宁，李先庭．室内空气流动数值模拟的误差预处理法[J]．清华大学学报 (自然科学版)，2001，41(10)：114-117
[18] 赵彬，李先庭，彦启森．室内空气流动数值模拟的 N 点风口动量模型 [J]．计算力学学报，2003，20(1)：64-69
[19] 赵彬，李先庭，彦启森．室内空气流动的简捷数值模拟方法[J]．暖通空调，2003，33(3)：102-104
[20] 徐丽，翁培奋，孙为民．三种通风方式下的室内气流组织和室内空气品质的数值分析[J]．空气动力学学报，2003，21(3)：311-319
[21] 荣庆兴，方怀红，苏鹰．带有地板辐射的地板送风空调系统的数值模拟 [J]．建筑热能通风空调，2004，23(6)：85-90
[22] 李晓冬，高军，高甫生．基于多区模型的大空间空调温度场数值模拟[J]．哈尔滨工业大学学报，2005，37(5)：683-686
[23] 那艳玲，涂光备，于松波．冷却顶板对置换通风系统的影响：CFD 研究 [J]．暖通空调，2005，35(1)：11-14，82
[24] 薛若军，王革，方磊．空调房间内热舒适度的数值模拟[J]．哈尔滨工业大学学报，2005，37(8)：1145-1147
[25] 陶建兴，杨亚东，孙庆宽．CFD仿真技术在空调房间温度场研究中的应用[J]．暖通空调，2002，32(2)：95-98
[26] P.O.Fanger. Calculation of Thermal Comfort[J].ASHRAE Trans,1967,73
[27] P.O.Fanger.Thermal Comfort-Analysis and Application in Environmental Engineering[M]. Copenhagen,Danish Technical Press, 1970
[28] 蒋薇．人体热舒适性的实验研究[D]．[学位论文]，天津大学，20010501
[29] Int-Hout D.Thermal Comfort Calculations: A Computer Model[J]. ASHRAE Trans, 1990,96(1):840-844
[30] Sherman M. A Simplified Model of Thermal Comfort[J].Energy and Buildings, 1985,8:37-50
[31] Federspiel CC, Asada H. User-adaptable Comfort Control for HVAC Systems[J]. Trans ASME 1994,116:474-486
[32] Shuzo Murakami, Shinsuke Kato, Jie Zeng. Combined Simulation of Airflow, Radiation and Moisture Transport for Heat Release from a Human Body[J].Building and Environment,2000,(35):489-500
[33] S.Atthajariyakul, T.Leephakpreeda. Neural Computing Thermal Comfort Index for HVAC Systems[J]. Energy Conversion and Management,2005 (46):2553-2565
[34] 夏一哉，赵荣义，江亿．北京市住宅环境热舒适研究 [J]．暖通空调，1999，29(2)：1-5
[35] 贾庆贤，赵荣义，许为全等．吹风对舒适性影响的主观调查和客观评价 [J]．暖通空调，2000，30(3)：15-17
[36] 吕芳．热舒适与建筑节能[D]．[硕士学位论文]，天津大学，20000101
[37] 王昭俊．严寒地区居室热环境与热舒适性研究[D]．[博士学位论文]，哈尔滨工业大学，20021101
[38] 王昭俊，廉乐明．严寒地区居室热环境模糊综合评判[J]．哈尔滨工业大学学报，2004，36(6)：752-755
[39] 王怡．寒冷地区居住建筑夏季室内热环境研究[D]．[博士学位论文]，西安建筑科技大学，20030601
[40] 连之伟，冯海燕．建筑室内热环境的模糊评判模型[J]．上海交通大学学报，2002，36(2)：169-172
[41] 赵博．基于人工神经网络的室内热舒适研究[D]．[硕士学位论文]，上海交通大学，20040101
[42] ISO7730-1984. Moderate Thermal Environments-Determination of the PMV and PPD Indices and Specification of the Conditions for Thermal Comfort[S].
[43] ASHRAE Standard 55-1992. American Society of Heating, Refrigerating and Air-conditioning Engineers[S]. Inc. Atlanta,CA30329
[44] 陶文铨．数值传热学 (第二版) [M]．西安交通大学出版社，2001：136-151，203-226，347-370
[45] 陆耀庆．实用供热空调设计手册[S]．北京：中国建筑工业出版 社，2002：15-76，707-737
[46] Weiwei Liu,Zhiwei Lian,Ye Yao.Optimization on Indoor Air Diffusion of Floor-standing Type Room Air-conditioners[J].Energy and Buildings, 2007,(1):1-12
[47] 沈晋明．西德人体热舒适性研究概况[J]．暖通空调，1984，(4)
[48] Dedear R J,Fountain M E. Field Experiments on Occurpant Comfort and Office Thermal Environments in a Hot-humid Climate[J]. ASHRAE Trans, 1994, 100(2):457-475
[49] Depaula Xavier A , Lamberts R. Indices of Thermal Comfort Developed from Field Survey in Brazil[J]. ASHRAE Trans,2000,106(part1):45-58
[50] D．A．McIntyre，龙惟定等译．室内气候[M]．上海：上海科学技术出版社，1988：92-93
[51] 钱以明．高层建筑空调与节能[M]．上海：同济大学出版社，1990：7-17
[52] 张锦松．PMV图算法探讨[J]．暖通空调，2002，(1)：37-39
[53] 薛定宇，陈阳泉．基于MATLAB／Simulink 的系统仿真技术与应用[M]．北京：清华大学出版社，2002：192-428
[54] P.O.Fanger. Calculation of Thermal Comfort[J]. ASHRAE Trans,1967,73
[55] 嵇赟喆，空气流速对人体热舒适影响的研究[D]．[硕士学位论文]，天津大学，20020201
[56] 巴赫基 L，Banhidi I，傅忠诚等译．房间的热微气候：按照人的热感觉计算舒适参数[M]．北京：中国建筑工业出版社，1987：12-16
[57] J J Hopfield．Neural Network Lecturing Course[M]，1990
[58] 丛爽．神经网络、模糊系统及其在运动控制中的应用[M]．合肥：中国科学技术大学，2001：13-20
[59] 韩滔．基于动态热舒适的空调控制方案研究 [D]．[硕士学位论文]，西南交通大学，20060501
[2] 张智，涂旺荣等．空调制冷／制热时室内气流及温度分布数值研究[J]．工程热物理学报，2002，23(4)：457-460
[3] Nielsen P.V. Flow in Air Conditioned Rooms (English Translation)[D]. [ph.D, Thesis]. Copenhagen Technical University of Denmark, 1976
[4] R.J.Baker, P.T.Willianms, R.M.Kelso. Numerical Calculation of Room Air Motion-Part 1:Math, Physics and CFD Modeling[J]. ASHRAE, 1994, 100:514-530
[5] Guohui Gan. Evaluation of Room Air Distribution Systems Using Computational Fluid Dynamics[J].Energy and Buildings,1995,23:83-93
[6] Qingyan Chen, Weiran Xu. A Zero-equation Turbulence Model for Indoor Airflow Simulation[J].Energy and Buildings,1998,28:137-144
[7] Weiran Xu, Qingyan Chen. A Two-layer Turbulence Model for Simulating Indoor Airflow Part Ⅱ: Applications[J]. Energy and Buildings, 2001,33:627-639
[8] Weizhen Lu, Andrew T.Howarth, Alan P.Jeary. Prediction of Airflow and Temperature Field in a Room With Convective Heat Source[J].Building and Environment,1997,32(6):541-550
[9] S.L.Sinha, R.C.Arora, et al. Numerical Simulation of Two dimensional Room Airflow With and Without Buoyancy[J] .Energy and Buildings,2000, 32:121-129
[10] M.Bojic, F.Yik, T.Y.Lo. Locating Air-conditioners and Furniture inside Residential Flats to Obtain Good Thermal Comfort[J]. Energy and Buildings,2002,34:745-751
[11] Juan Ababto, Daniel Barrero, Marcelo Reggio, Benoit Ozell. Airflow Modeling in a Computer Room[J].Building and Environment,2004,39: 1393-1402
[12] 汤广发等．二维层流室内自然对流数值解[J]．空气动力学学报，1986，4(4)
[13] 汤广发等．用三维紊流数值方法优化水电站主厂房通风气流组织设计 [A]．第三届全国暖通专业计算机方法交流会[C]，1987
[14] 顾瑞英，武文斐．空调房间气流组织的数值模拟[A]．全国高等学校工程热物理研究会第四届学术会议论文集[C]，1992：157-160
[15] 王智伟，顾瑞英．具有内部障碍物及不规则形状边界问题的数值模拟 [J]．西安建筑科技大学学报，2000，32(1)：31-34
[16] 赵彬，李先庭，彦启森．用零方程湍流模型模拟通风空调室内的空气流动[J]．清华大学学报 (自然科学版)，2001，41(10)：109-113
[17] 赵彬，李冬宁，李先庭．室内空气流动数值模拟的误差预处理法[J]．清华大学学报 (自然科学版)，2001，41(10)：114-117
[18] 赵彬，李先庭，彦启森．室内空气流动数值模拟的 N 点风口动量模型 [J]．计算力学学报，2003，20(1)：64-69
[19] 赵彬，李先庭，彦启森．室内空气流动的简捷数值模拟方法[J]．暖通空调，2003，33(3)：102-104
[20] 徐丽，翁培奋，孙为民．三种通风方式下的室内气流组织和室内空气品质的数值分析[J]．空气动力学学报，2003，21(3)：311-319
[21] 荣庆兴，方怀红，苏鹰．带有地板辐射的地板送风空调系统的数值模拟 [J]．建筑热能通风空调，2004，23(6)：85-90
[22] 李晓冬，高军，高甫生．基于多区模型的大空间空调温度场数值模拟[J]．哈尔滨工业大学学报，2005，37(5)：683-686
[23] 那艳玲，涂光备，于松波．冷却顶板对置换通风系统的影响：CFD 研究 [J]．暖通空调，2005，35(1)：11-14，82
[24] 薛若军，王革，方磊．空调房间内热舒适度的数值模拟[J]．哈尔滨工业大学学报，2005，37(8)：1145-1147
[25] 陶建兴，杨亚东，孙庆宽．CFD仿真技术在空调房间温度场研究中的应用[J]．暖通空调，2002，32(2)：95-98
[26] P.O.Fanger. Calculation of Thermal Comfort[J].ASHRAE Trans,1967,73
[27] P.O.Fanger.Thermal Comfort-Analysis and Application in Environmental Engineering[M]. Copenhagen,Danish Technical Press, 1970
[28] 蒋薇．人体热舒适性的实验研究[D]．[学位论文]，天津大学，20010501
[29] Int-Hout D.Thermal Comfort Calculations: A Computer Model[J]. ASHRAE Trans, 1990,96(1):840-844
[30] Sherman M. A Simplified Model of Thermal Comfort[J].Energy and Buildings, 1985,8:37-50
[31] Federspiel CC, Asada H. User-adaptable Comfort Control for HVAC Systems[J]. Trans ASME 1994,116:474-486
[32] Shuzo Murakami, Shinsuke Kato, Jie Zeng. Combined Simulation of Airflow, Radiation and Moisture Transport for Heat Release from a Human Body[J].Building and Environment,2000,(35):489-500
[33] S.Atthajariyakul, T.Leephakpreeda. Neural Computing Thermal Comfort Index for HVAC Systems[J]. Energy Conversion and Management,2005 (46):2553-2565
[34] 夏一哉，赵荣义，江亿．北京市住宅环境热舒适研究 [J]．暖通空调，1999，29(2)：1-5
[35] 贾庆贤，赵荣义，许为全等．吹风对舒适性影响的主观调查和客观评价 [J]．暖通空调，2000，30(3)：15-17
[36] 吕芳．热舒适与建筑节能[D]．[硕士学位论文]，天津大学，20000101
[37] 王昭俊．严寒地区居室热环境与热舒适性研究[D]．[博士学位论文]，哈尔滨工业大学，20021101
[38] 王昭俊，廉乐明．严寒地区居室热环境模糊综合评判[J]．哈尔滨工业大学学报，2004，36(6)：752-755
[39] 王怡．寒冷地区居住建筑夏季室内热环境研究[D]．[博士学位论文]，西安建筑科技大学，20030601
[40] 连之伟，冯海燕．建筑室内热环境的模糊评判模型[J]．上海交通大学学报，2002，36(2)：169-172
[41] 赵博．基于人工神经网络的室内热舒适研究[D]．[硕士学位论文]，上海交通大学，20040101
[42] ISO7730-1984. Moderate Thermal Environments-Determination of the PMV and PPD Indices and Specification of the Conditions for Thermal Comfort[S].
[43] ASHRAE Standard 55-1992. American Society of Heating, Refrigerating and Air-conditioning Engineers[S]. Inc. Atlanta,CA30329
[44] 陶文铨．数值传热学 (第二版) [M]．西安交通大学出版社，2001：136-151，203-226，347-370
[45] 陆耀庆．实用供热空调设计手册[S]．北京：中国建筑工业出版 社，2002：15-76，707-737
[46] Weiwei Liu,Zhiwei Lian,Ye Yao.Optimization on Indoor Air Diffusion of Floor-standing Type Room Air-conditioners[J].Energy and Buildings, 2007,(1):1-12
[47] 沈晋明．西德人体热舒适性研究概况[J]．暖通空调，1984，(4)
[48] Dedear R J,Fountain M E. Field Experiments on Occurpant Comfort and Office Thermal Environments in a Hot-humid Climate[J]. ASHRAE Trans, 1994, 100(2):457-475
[49] Depaula Xavier A , Lamberts R. Indices of Thermal Comfort Developed from Field Survey in Brazil[J]. ASHRAE Trans,2000,106(part1):45-58
[50] D．A．McIntyre，龙惟定等译．室内气候[M]．上海：上海科学技术出版社，1988：92-93
[51] 钱以明．高层建筑空调与节能[M]．上海：同济大学出版社，1990：7-17
[52] 张锦松．PMV图算法探讨[J]．暖通空调，2002，(1)：37-39
[53] 薛定宇，陈阳泉．基于MATLAB／Simulink 的系统仿真技术与应用[M]．北京：清华大学出版社，2002：192-428
[54] P.O.Fanger. Calculation of Thermal Comfort[J]. ASHRAE Trans,1967,73
[55] 嵇赟喆，空气流速对人体热舒适影响的研究[D]．[硕士学位论文]，天津大学，20020201
[56] 巴赫基 L，Banhidi I，傅忠诚等译．房间的热微气候：按照人的热感觉计算舒适参数[M]．北京：中国建筑工业出版社，1987：12-16
[57] J J Hopfield．Neural Network Lecturing Course[M]，1990
[58] 丛爽．神经网络、模糊系统及其在运动控制中的应用[M]．合肥：中国科学技术大学，2001：13-20
[59] 韩滔．基于动态热舒适的空调控制方案研究 [D]．[硕士学位论文]，西南交通大学，20060501