A simplified numerical study on the energy performance and thermal environment of a bedroom TAC system

Abstract In subtropics, the higher energy consumption of air conditioning system in summer period brought about the application of task/ambient air conditioning (TAC) systems, not only in commercial buildings, but also in residential buildings. To better assess the performance of the TAC system, a numerical study was carried out to predict the energy and thermal performance of a bedroom TAC system in a bedroom in subtropical area. To conveniently predict the indoor thermal environment, response surface methodology (RSM) was applied to simplify the procedure of numerical simulation. Firstly, CFD study was carried out to evaluate the thermal and energy performance of the TAC system. Secondly, RSM method was used to establish the predictive models of important index of indoor thermal environment to form the simplified numerical method. Thirdly, these two methods were used and the predicted values were compared. It was found that the energy consumption was reduced from 260 to 160 W when the ts was increased from 19 to 23 °C, and the averaged draft risk (DRoz) reached at 20% when the Qs was set at 110 l/s. The significant vertical non-uniformity of air temperature, air velocity and relative humidity were also reported. Besides, the CFD method was compared with the simplified numerical method (RSM method). It was found that the maximum deviation between using the RSM and CFD methods was less than 5% in predicting energy consumption, draft risk, thermal parameters in the occupied zone, stratified air temperature and stratified air relative humidity. Overall, the simplified numerical method (CFD based RSM method) can predict the indoor thermal environment accurately.

[1]  Shiming Deng,et al.  Application of TOPSIS method in evaluating the effects of supply vane angle of a task/ambient air conditioning system on energy utilization and thermal comfort , 2016 .

[2]  Dongmei Pan,et al.  Thermal, ventilation and energy saving performance evaluations of a ductless bed-based task/ambient air conditioning (TAC) system , 2013 .

[3]  Shiming Deng,et al.  Review on building energy performance improvement using phase change materials , 2018 .

[4]  Muhsin Kilic,et al.  Numerical analysis of air flow, heat transfer, moisture transport and thermal comfort in a room heat , 2011 .

[5]  Shiming Deng,et al.  A questionnaire survey on sleeping thermal environment and bedroom air conditioning in high-rise residences in Hong Kong , 2006 .

[6]  Hua Chen,et al.  Locating room air-conditioners at floor level for energy saving in residential buildings , 2009 .

[7]  Dongmei Pan,et al.  Performance evaluation of an air conditioning system with different heights of supply outlet applied to a sleeping environment , 2014 .

[8]  Giovanni Vincenzo Fracastoro,et al.  Experimental and numerical analysis of air and radiant cooling systems in offices , 2009 .

[9]  Dongmei Pan,et al.  Comparative studies on using RSM and TOPSIS methods to optimize residential air conditioning systems , 2018 .

[10]  Qingyan Chen,et al.  A Procedure for Verification, Validation, and Reporting of Indoor Environment CFD Analyses , 2002 .

[11]  Noël Djongyang,et al.  An investigation into thermal comfort and residential thermal environment in an intertropical sub-Saharan Africa region: Field study report during the Harmattan season in Cameroon , 2010 .

[12]  A. Melikov,et al.  Performance of “ductless” personalized ventilation in conjunction with displacement ventilation: Impact of disturbances due to walking person(s) , 2010 .

[13]  Wan Ki Chow Numerical studies of airflows induced by mechanical ventilation and air-conditioning (MVAC) systems , 2001 .

[14]  Standard Ashrae Thermal Environmental Conditions for Human Occupancy , 1992 .

[15]  Dongmei Pan,et al.  A numerical study on influences of building envelope heat gain on operating performances of a bed-based task/ambient air conditioning (TAC) system in energy saving and thermal comfort , 2017 .

[16]  F. Menter Two-equation eddy-viscosity turbulence models for engineering applications , 1994 .

[17]  Facundo Bre,et al.  A computational multi-objective optimization method to improve energy efficiency and thermal comfort in dwellings , 2017 .

[18]  Jianlei Niu,et al.  Thermal comfort models: A review and numerical investigation , 2012 .

[19]  Yanming Kang,et al.  Heating energy consumption of impinging jet ventilation and mixing ventilation in large-height spaces: A comparison study , 2016 .

[20]  Saman Rashidi,et al.  Heat transfer enhancement and pressure drop penalty in porous solar heat exchangers: A sensitivity analysis , 2015 .

[21]  Dongmei Pan,et al.  Experimental and numerical study on air flow and moisture transport in sleeping environments with a task/ambient air conditioning (TAC) system , 2016 .

[22]  Jianlei Niu,et al.  Experimental and numerical investigations on stratified air distribution systems with special configuration: Thermal comfort and energy saving , 2013 .

[23]  Anastasios I. Stamou,et al.  Verification of a CFD model for indoor airflow and heat transfer , 2006 .

[24]  Dongmei Pan,et al.  Computational fluid dynamics analysis of convective heat transfer coefficients for a sleeping human body , 2017 .

[25]  D. Shiming,et al.  Computational fluid dynamics (CFD) modelling of air flow field, mean age of air and CO2 distributions inside a bedroom with different heights of conditioned air supply outlet , 2016 .

[26]  Jianlei Niu,et al.  CFD study on micro-environment around human body and personalized ventilation , 2004 .

[27]  Shinichi Tanabe,et al.  Thermal sensation and comfort with different task conditioning systems , 2007 .

[28]  Edward Ng,et al.  Response surface models for CFD predictions of air diffusion performance index in a displacement ventilated office , 2008 .

[29]  Zhao Zhang,et al.  Evaluation of Various Turbulence Models in Predicting Airflow and 1 Turbulence in Enclosed Environments by CFD : Part-1 : 2 Summary of Prevalent Turbulence Models 3 4 , 2007 .

[30]  M. Bezerra,et al.  Response surface methodology (RSM) as a tool for optimization in analytical chemistry. , 2008, Talanta.

[31]  Wontae Kim,et al.  Thermal characteristics of a personal environment module task air conditioning system: an experimental study , 2001 .

[32]  Zhao Li,et al.  Numerical investigations on the effects of envelope thermal loads on energy utilization potential and thermal non-uniformity in sleeping environments , 2017 .

[33]  P. J. Jones,et al.  Computational fluid dynamics for building air flow prediction—current status and capabilities , 1992 .

[34]  Mao Ning,et al.  Experimental and numerical studies on the performance evaluation of a bed-based task/ambient air conditioning (TAC) system , 2014 .

[35]  Shiming Deng,et al.  A study on the characteristics of nighttime bedroom cooling load in tropics and subtropics , 2004 .

[36]  Dongmei Pan,et al.  Performance evaluation of a novel bed-based task/ambient conditioning (TAC) system , 2012 .

[37]  G. D. Raithby,et al.  A Finite-Volume Method for Predicting a Radiant Heat Transfer in Enclosures With Participating Media , 1990 .

[38]  Dongmei Pan,et al.  A numerical study on the effects of design/operating parameters of the radiant panel in a radiation-based task air conditioning system on indoor thermal comfort and energy saving for a sleeping environment , 2017 .

[39]  Hua Zhang,et al.  Comparison of indoor air temperatures of different under-floor heating pipe layouts , 2011 .

[40]  Ali Malkawi,et al.  Defining the Influence Region in neighborhood-scale CFD simulations for natural ventilation design , 2016 .

[41]  Jean-Louis Scartezzini,et al.  Passive design optimization of newly-built residential buildings in Shanghai for improving indoor thermal comfort while reducing building energy demand , 2017, Energy and Buildings.

[42]  Zhiqiang Zhai,et al.  Application of Computational Fluid Dynamics in Building Design: Aspects and Trends , 2006 .