Building Simulation

, Volume 11, Issue 3, pp 507–518 | Cite as

Predicting integrated thermal and acoustic performance in naturally ventilated high-rise buildings using CFD and FEM simulation

Research Article Building Thermal, Lighting, and Acoustics Modeling
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Abstract

The study of ventilation windows for both natural ventilation and noise mitigation has drawn significant attention recently. This paper presents the numerical approaches to analyse the integrated thermal and acoustical performance of ventilation windows, for a residential building in tropical climate which employs double-layer noise mitigation window for natural ventilation. Given a set of outdoor wind conditions, the distributions of indoor flow and temperature fields are simulated using Computational Fluid Dynamics (CFD) model. The thermal comfort is evaluated using statistical Predicted Mean Vote (PMV) method. For the acoustic performance, noise radiation from road traffic is assumed as the noise source, and the sound insulation of building façade is simulated using Finite Element Method (FEM). From the simulation results, it is found that the thermal satisfaction response is closely related to the inlet wind temperature and speed, and the window opening size greatly affects the ventilation performance. From the case study in Singapore, during certain season, day/night time and with sufficient wind flow, the ventilation window can provide enough fresh air, maintain adequate thermal comfort and quiet acoustic environment for the occupants. The numerical approaches presented in this paper are applicable to general window design studies, and the simulation findings can be incorporated into green building planning. The advantages of using simulation approaches are highlighted and their limitations are discussed.

Keywords

natural ventilation thermal comfort ventilation window sound insulation 

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Notes

Acknowledgements

This material is based on research/work supported by the Singapore Ministry of National Development and National Research Foundation under L2 NIC award No. L2NICCFP1- 2013-9.

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Copyright information

© Tsinghua University Press and Springer-Verlag GmbH Germany, part of Springer Nature 2017

Authors and Affiliations

  1. 1.Institute of High Performance ComputingAgency for Science, Technology and Research (A*STAR)SingaporeSingapore
  2. 2.School of ArchitectureUniversity of SheffieldSheffieldUK

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