6,008 research outputs found

    Thermal comfort guidelines for production spaces within multi-storey garment factories located in Bangladesh

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    This research presents extensive field data on indoor thermal conditions along with workers' comfort votes taken at their workstations within three existing multi-storied garment factories during the three seasons (cool-dry, hot-dry and warm-humid) of Bangladesh. The main objective of the study was to observe the impact of thermal conditions on workers’ indoor thermal perception during each season of a year and from this identify thermal comfort guidelines (e.g. neutral temperatures, comfort ranges, preferred airspeeds and directions) to execute their production work comfortably. Subjective votes were collected from a total of 908 workers with the thermal data, physiological data and adaptive measures recorded simultaneously. Statistical analyses revealed that workers can accept a wider and relatively higher comfort range than the predicted band during cool-dry and hot-dry seasons, for instance, 22.7–29.1 °C and 22.3–30.4 °C respectively. A narrower comfort band (e.g. 28.7–30.9 °C), close to the predicted range, was found during the warm-humid season, which can be maintained by reducing radiant temperature and elevating airspeed. Further analyses indicated that workers prefer a mean airspeed of 0.3  m/s and comfort range of 0–3.0  m/s specific to their activities preferably from inlets located on south, north and east facades while upward and downward air movement, from for example ceiling fans, causes a rise of air temperature in the occupational zone and thermal discomfort. This research also suggested that the maximum distances of workstations from the ventilation inlets (windows) should be maintained at 12–18 m for sufficient cross ventilation, personal controls and adaptive opportunities to help maintain preferred thermal condition

    Robust e-Voting Composition

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    Comfort driven adaptive window opening behaviour and the influence of building design

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    It is important to understand and model the behaviour of occupants in buildings and how this behaviour impacts energy use and comfort. It is similarly important to understand how a buildings design affects occupant comfort, occupant behaviour and ultimately the energy used in the operation of the building. In this work a behavioural algorithm for window opening developed from field survey data has been implemented in a dynamic simulation tool. The algorithm is in alignment with the proposed CEN standard for adaptive thermal comfort. The algorithm is first compared to the field study data then used to illustrate the impact of adaptive behaviour on summer indoor temperatures and heating energy. The simulation model is also used to illustrate the sensitivity of the occupant adaptive behaviour to building design parameters such as solar shading and thermal mass and the resulting impact on energy use and comfort. The results are compared to those from other approaches to model window opening behaviour. The adaptive algorithm is shown to provide insights not available using non adaptive simulation methods and can assist in achieving more comfortable and lower energy buildings
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