We were approached by a client to undertake a thermal comfort study of a car workshop where the occupants had expressed thermal discomfort. The client wished for the car workshop to have optimal thermal comfort conditions. In their view, this would mean a temperature target of 23°C +/- 1°C within the workshop. They were seeking our help to measure the current conditions and model, analyse and evaluate different active and passive strategies, which could enhance the thermal comfort and meet the temperature target within the workshop.
For this study, we adopted an iterative approach. Measurements of the current conditions would inform a baseline, which would be modelled in 3D and used to study various enhancement strategies:
1. The first step was to review the targeted comfort criteria set by the client. The building is located in Kuala Lumpur. The targeted temperature of 23°C +/- 1°C could therefore only be achieved by air conditioning the workshop. Since the car workshop was not intended to be fully air-conditioned the optimal perceived temperature target was increased to 25°C - 26°C +/-1°C, which can be achieved by implementing adaptive comfort ventilation (elevated airspeed, in the form of ceiling or wall fans).
Fig. Design Strategies for Kuala Lumpur weather data
2. The current conditions in the workshop would be analysed. Measurement loggings of temperature and relative humidity were conducted. The loggers were placed in 4 different locations within the workshop (within the working zone and above the working zone). The loggers were left for 3 weeks to collect measurements. Surface temperatures of the ceiling, floor and walls were measured during site visits.
Fig. Section of the workshop with measured surface temperatures.
3. As-built drawings and specifications for the building were obtained and reviewed.
4. An energy model was created in IES Virtual Environment (VE) and the baseline model was calibrated to replicate the measured conditions.
Fig. IES VE model used for simulation of cases.
5. Various active and passive strategies were simulated in IES VE. Each case would be analysed and evaluated against the comfort criteria.
The temperature measurements from the workshop showed that the air temperature within the workshop was on average between 31°C to 32°C in the working zone, with maximum and minimum air temperatures between 29°C to 33.6°C.
Fig. Measured temperatures from the workshop using HOBO U12-012 loggers.
The internal surface temperatures for the floor, ceiling and walls were measured to an average temperature of 32°C, 37.5°C and 37°C respectively. ASHRAE 55 were used to estimate the Predicted Percentage Dissatisfied (PPD) due to radiant temperature asymmetry from the warm ceiling and warm floor. The estimated percentage dissatisfied were 6% and 20% respectively for warm ceiling and warm floor. The average operative temperature (the perceived temperature, an average of the mean radiant temperature from surrounding surfaces and the air temperature) was found to be 32.8°C due to the surrounding surface temperatures.
Fig. Measured surface temperatures in the workshop, using Fluke Camera.
With the initial temperature measurements in place, an energy model was modelled in IES VE and the baseline was calibrated to match the measured temperatures.
Fig. IES VE calibrated baseline vs measured temperatures in the workshop.
A total of 9 cases were initially modelled to test how various passive and active strategies could reduce the temperature and enhance the thermal comfort.
Fig. Simulated cases, 1 - 9 single strategies, 10, 12 and 12b combined strategies.
The results showed that increasing the natural ventilation and adding additional louvres would lower the temperature the most. Dumping air-conditioned exhaust air from the showroom inside the workshop would have the highest temperature reduction. However, the strategy could create concerns regarding the air quality within the workshop. Further, adding a shading canvas around the workshop facade would help to reduce the temperatures, mainly as a small alley behind the workshop was paved with asphalt and the building facade was black. A shading canvas would help to lower the surface temperatures and keep the adjacent air cooler in these areas. In general, the best performing strategies was found to lower the temperature by 1°C to 1.35°C. An adaptive approach with ceiling fans would help to increase the thermal comfort and lower the Predicted Percentage Dissatisfied (PPD) even further for each of the cases.
Table. Single strategy cases results.
The best performing cases were combined and it was found that cases 10, 12 and 12b would help to lower the temperature the most with 2°C - 3.3°C.
Table. Combined strategy cases results.
In addition, the study found that having a high reflective roof painting would have a limited effect on the internal temperatures unless all the exterior walls surrounding the workshop was properly insulated or using the same high reflective paint.
Based on our simulations we could conclude that the temperature target wished by the client of 23°C +/-1°C could not be met without air conditioning the workshop. However, the studies found that a combination of the best performing strategies, such as covering the adjacent alley, allowing for 24-hours natural ventilation of the workshop, adding new higher placed louvres for increased natural ventilation and dumping of exhaust air from the showroom inside the workshop could reduce the temperature and the estimated predicted percentage dissatisfied. The best results for all the cases would be achieved with an adaptive approach where the cases would be combined with elevated airspeed in the form of High Volume Low Speed (HVLS) ceiling fans.
Fig. Thermal comfort evaluation of cases, evaluated with clothing insulation of 0.7clo and a metabolic rate of 1.7met for the occupants.
Additionally, it was found that the thermal comfort could be enhanced by lowering the clothing insulation (clo) value for the occupants, for example by selecting more breathable trousers. Lowering the clo in case 12 from 0.7 to 0.5 would lower the Predicted Percentage Dissatisfied (PPD) from 18% to 9%.