2018
DOI: 10.1016/j.enbuild.2018.03.075
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Effects of different CFD modeling approaches and simplification of shape on prediction of flow field around manikin

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Cited by 22 publications
(15 citation statements)
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“…Furthermore, the limitations of the Reynolds Averaged Navier-Strokes (RANS) turbulence models (e.g. the standard k-ε model used in this study) in predicting complex flows involving swirls, vortices, locally transitional flows, etc.occurring in room ventilation can also cause some discrepancies[37,51]. On the other hand, the omnidirectional thermal anemometers used in this study are difficult to accurately measure low air velocities[52].…”
mentioning
confidence: 93%
“…Furthermore, the limitations of the Reynolds Averaged Navier-Strokes (RANS) turbulence models (e.g. the standard k-ε model used in this study) in predicting complex flows involving swirls, vortices, locally transitional flows, etc.occurring in room ventilation can also cause some discrepancies[37,51]. On the other hand, the omnidirectional thermal anemometers used in this study are difficult to accurately measure low air velocities[52].…”
mentioning
confidence: 93%
“…Although no single turbulence model can optimally and economically handle all flow elements-e.g., jet flow, momentum-driven flow, stratified flow, and buoyancy-driven flow [30]-there is still a great necessity to utilize more accurate turbulence models or predict the human body microenvironment characterized by a complex flow characteristic. In fact, LES has been applied to predict the microenvironment around a manikin, mostly using simplified geometry [140][141][142]. With increasing computer power, LES may gain popularity for PV studies.…”
Section: Turbulence Modelsmentioning
confidence: 99%
“…Although existing literature has not examined the effect of CTM geometry simplification on PV performance, a few studies have qualified the influence of geometric complexity on an indoor environment, e.g., the shape and size of CTM [144]. One study pointed out that a detailed manikin shape can provide more accurate predictions (4-10%) at some locations, especially those close to the body [141]. Another study revealed that although human body simplification only affected airflow field prediction of the thermal plume regions, it could increase the predictive error of contaminant transport in the whole computational domain [145].…”
Section: Geometry Of Ctmsmentioning
confidence: 99%
“…Compared with the standard k-ε turbulent model and the Realizable k-ε turbulent model, the RNG k-ε turbulent model can better be able to deal with the multiple complicated flow problems like swirling flow, high strain rate flow, and sharply curved streamline flow. The governing equations of the RNG k-ε turbulent model [47] in the form of a tensor index can be expressed as…”
Section: Governing Equations Of Fluid Domainmentioning
confidence: 99%