PurposeThe purpose of this paper is to analyse the thermal environment of two engineering testing centres cooled via different means using computational fluid dynamics (CFD), focussing on the indoor temperature and air movement. This computational technique has been used in the analysis of thermal environment in buildings where the profiles of thermal comfort parameters, such as air temperature and velocity, are studied.Design/methodology/approachA pilot survey was conducted at two engineering testing centres – a passively cooled workshop and an air-conditioned laboratory. Electronic sensors were used in addition to building design documentation to collect the required information for the CFD model–based prediction of air temperature and velocity distribution patterns for the laboratory and workshop. In the models, both laboratory and workshop were presumed to be fully occupied. The predictions were then compared to empirical data that were obtained from field measurements. Operative temperature and predicted mean vote (PMV)–predicted percentage dissatisfied (PPD) indices were calculated in each case in order to predict thermal comfort levels.FindingsThe simulated results indicated that the mean air temperatures of 21.5°C and 32.4°C in the laboratory and workshop, respectively, were in excess of the recommended thermal comfort ranges specified in MS1525, a local energy efficiency guideline for non-residential buildings. However, air velocities above 0.3 m/s were predicted in the two testing facilities, which would be acceptable to most occupants. Based on the calculated PMV derived from the CFD predictions, the thermal sensation of users of the air-conditioned laboratory was predicted as −1.7 where a “slightly cool” thermal experience would prevail, but machinery operators in the workshop would find their thermal environment too warm with an overall sensation score of 2.4. A comparison of the simulated and empirical results showed that the air temperatures were in good agreement with a percentage of difference below 2%. However, the level of correlation was not replicated for the air velocity results, owing to uncertainties in the selected boundary conditions, which was due to limitations in the measuring instrumentation used.Research limitations/implicationsDue to the varying designs, the simulated results of this study are only applicable to laboratory and workshop facilities located in the tropics.Practical implicationsThe results of this study will enable building services and air-conditioning engineers, especially those who are in charge of the air-conditioning and mechanical ventilation (ACMV) system design and maintenance to have a better understanding of the thermal environment and comfort conditions in the testing facilities, leading to a more effective technical and managerial planning for an optimised thermal comfort management. The method of this work can be extended to the development of CFD models for other testing facilities in educational institutions.Social implicationsThe findings of this work are particularly useful for both industry and academia as the indoor environment of real engineering testing facilities were simulated and analysed. Students and staff in the higher educational institutions would benefit from the improved thermal comfort conditions in these facilities.Originality/valueFor the time being, CFD studies have been carried out to evaluate thermal comfort conditions in various building spaces. However, the information of thermal comfort in the engineering testing centres, of particular those in the hot–humid region are scantily available. The outcomes of this simulation work showed the usefulness of CFD in assisting the management of such facilities not only in the design of efficient ACMV systems but also in enhancing indoor thermal comfort.
Diurnal and Seasonal Variations in the Effect of Urban Environmental Factors on Air Temperature: A Consecutive Regression Analysis Approach
