Thermal Comfort of Wood-wall House in Coastal and Mountainous Region in Tropical Area

Abstract Thermal comfort theory of Predicted Mean Vote (PMV) is proven incompatible for tropical area. Actual Mean Vote (AMV) is a way to recognize the thermal comfort based on inhabitant's behaviour and psychology (adaptive thermal comfort). The purpose of this research is to analyse the difference between AMV and PMV in wooden walls traditional houses in coastal and mountainous region which will be used to establish the theory of adaptive thermal comfort. Method of this research is quantitative by measurement thermal variable (temperature, globe temperature, velocity, relative humidity) use thermal measurement tools. This measurement carried out in conjunction with filling out the thermal comfort questionnaire from ASHRAE (American Society of Heating, Refigeration, Air conditioning Engineering) standard. The number of sample taken is 25 houses in coastal region and 25 houses in mountainous region with criteria of more than one inhabitant in each house. Mountainous region chosen is Wonosobo Regency whereas coastal region selected is Demak Regency. The analysis is conducted by using PMV program from ASHRAE and statistic test undergone is to obtain the difference of PMV and AMV. The result obtained is the average difference between AMV and PMV in coastal region in the amount of +0.73, while the houses in mountainous region have the average difference of -0.81. It is concluded that bias in the wood-frame houses in mountainous region are bigger than those in coastal region. AMV Value for the houses in coastal is -0.28 and AMV value for the houses in mountainous is -1.12, it mean that occupants in the coastal houses are more comfortable than occupants in the mountainous houses.

[1]  Paola Ricciardi,et al.  A field study on thermal comfort in naturally-ventilated buildings located in the equatorial climatic region of Cameroon , 2014 .

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

[3]  H. Rijal,et al.  Seasonal and regional differences in neutral temperatures in Nepalese traditional vernacular houses , 2010 .

[4]  Sigrid Reiter,et al.  AN ADAPTIVE THERMAL COMFORT MODEL FOR HOT HUMID SOUTH- EAST ASIA , 2012 .

[5]  Manoj Kumar Singh,et al.  Adaptive thermal comfort model for different climatic zones of North-East India , 2011 .

[6]  Francesco Martellotta,et al.  The influence of clothing distribution and local discomfort on the assessment of global thermal comfort , 2013 .

[7]  Cinzia Buratti,et al.  Thermal comfort in open plan offices in northern Italy: An adaptive approach , 2012 .

[8]  J. F. Nicol,et al.  Understanding the adaptive approach to thermal comfort , 1998 .

[9]  Eusébio Z. E. Conceição,et al.  Application of a developed adaptive model in the evaluation of thermal comfort in ventilated kindergarten occupied spaces , 2012 .

[10]  R. Yao,et al.  A theoretical adaptive model of thermal comfort – Adaptive Predicted Mean Vote (aPMV) , 2009 .

[11]  Lieve Helsen,et al.  Evaluation of adaptive thermal comfort models in moderate climates and their impact on energy use in , 2011 .

[12]  Luis de la Ossa,et al.  Design and simulation of a thermal comfort adaptive system based on fuzzy logic and on-line learning , 2012 .

[13]  Madhavi Indraganti,et al.  Adaptive use of natural ventilation for thermal comfort in Indian apartments , 2010 .

[14]  Jing Liu,et al.  A method to weight three categories of adaptive thermal comfort , 2012 .

[15]  Madhavi Indraganti,et al.  Effect of age, gender, economic group and tenure on thermal comfort: A field study in residential buildings in hot and dry climate with seasonal variations , 2010 .

[16]  Hermawan,et al.  The Difference of Thermal Performance between Houses with Wooden Walls and Exposed Brick Walls in Tropical Coasts , 2015 .

[17]  Michael A. Humphreys,et al.  ADAPTIVE THERMAL COMFORT AND SUSTAINABLE THERMAL STANDARDS FOR BUILDINGS , 2002 .