2008
DOI: 10.1016/j.autcon.2007.06.004
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Coupled simulations for naturally ventilated residential buildings

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Cited by 45 publications
(25 citation statements)
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“…In internal coupling, the CFD module is built into the BS program and matrix formation in each module (thermal analysis, airflow network or CFD) is affected due to data exchange in each time step. This makes it difficult to employ parallel computing techniques (Wang and Wong 2008). The application of CFD-BS integration could increase the accuracy of energy saving prediction due to the inclusion of natural ventilation in sustainable design and the confidence in considering natural ventilation for sustainable design.…”
Section: Discussionmentioning
confidence: 99%
“…In internal coupling, the CFD module is built into the BS program and matrix formation in each module (thermal analysis, airflow network or CFD) is affected due to data exchange in each time step. This makes it difficult to employ parallel computing techniques (Wang and Wong 2008). The application of CFD-BS integration could increase the accuracy of energy saving prediction due to the inclusion of natural ventilation in sustainable design and the confidence in considering natural ventilation for sustainable design.…”
Section: Discussionmentioning
confidence: 99%
“…Assuming that BPS developers do not want or do not have enough expertise to fully implement those visual comfort and blind control models, co-simulation becomes a feasible option to integrate those models with the BPS program for a fully consistent analysis. Similar examples can be described for computational fluid dynamics (CFD) based natural ventilation studies predicting the performance of natural ventilation in large-scale naturally ventilated buildings (Wang and Wong, 2008;Wang and Wong, 2009;Tan and Glicksman, 2005).…”
Section: Co-simulationmentioning
confidence: 96%
“…The distribution pattern is different from that of cross-ventilation mode. Rooms located in two sides of the building (rooms [14][15][16][17][18][24][25][26] tend to obtain better ventilation performance than rooms in the middle (rooms 19-23).…”
Section: As Indicated Inmentioning
confidence: 99%
“…To better explain the phenomenon, Figure 15 illustrates the age of air and velocity vector in a plane of the 7th floor under S wind direction. In each floor (Figure 15), the leeward-side rooms are defined as C type (room number of 14,16,18,20,22,24,26) and D type (room number of 15, 17 19, 21, 23, 25). Figure 14, the spatial mean age of air in leeward-side rooms alternates periodically with older air in rooms C than rooms D. That could be due to the strong circulation region in rooms A (Figure 15), causing the wind to flow out of rooms A to blow into rooms D, making rooms D to draw younger air than rooms C. Figure 14(b) shows the distribution of ACH of leeward-side rooms under S wind.…”
Section: Introduction Of Local Mean Age Of Air and Achmentioning
confidence: 99%