HVAC visualization system - Pee, See Er (2014)
The issue of thermal comfort has been attracting increased attention around the world as people are more concerned with a comfortable indoor environment. In Singapore, occupants usually experience a cool exposure to the indoor environment after some time. As a result, the useful energy is wasted leading to high cost of energy. This report provides an informative visualisation system to show the variation condition of indoor environment. For example, data distribution such as air temperature and air velocity of a room can be monitored effectively. Also, the thermal comfort index of a room can be achieved easily by the users. The information of data distribution and thermal comfort index can be used as a feedback for the HVAC system. It is possible to design a controller of the HVAC system so as to obtain the desired output (e.g. the distribution of indoor temperature and air velocity); and to simultaneously save energy. This project focuses on developing a HVAC visualisation component toolkit to examine the conditions of indoor environment. This project aims to present the data visualisation in 1-D and 2-D plots based on real time analysis by using suitable data visualisation software. The data visualisation will be based on numerical simulations of a test room. The numerical simulations are completed by using CFD simulation results and estimations obtained from the assumed sensors placed in a test room; the compact air temperature and velocity data will be obtained from CFD simulation and compact humidity data will be taken from the estimation of assumed sensors placed in the test room by applying interpolation method. Moreover, the interactions between human and indoor environment will be focused on as well. This project will study the impact of primary factors for thermal comfort. The primary factors consist of air temperature, air velocity, humidity; mean radiant temperature, metabolic rate and clothing insulation on overall human satisfaction. Finally, this thermal comfort will be evaluated by predicted mean vote, PMV, and predicted percentage of dissatisfied, PPD, which is based on a 7 level of thermal sensational scale to reflect on thermal comfort.