Experimental and numerical study of airflow distribution in an aircraft cabin mock-up with a gasper on

You, Ruoyu; Chen, Jun; Shi, Zhu; Liu, Wei; Lin, Chao–Hsin; Wei, Daniel; Chen, Qingyan

doi:10.1080/19401493.2015.1126762

Cited by 51 publications

(50 citation statements)

References 29 publications

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“…The jet behaviour observed in previous studies You et al 2016) appears to be similar to that of a round jet. The present investigation explored the possibility of simplifying the gasper geometry as a round nozzle for CFD simulations.…”

Section: Methods For Simulating Air Distribution and Contaminant Transsupporting

confidence: 69%

“…Gaspers, the small, circular, and adjustable vents installed in aircraft cabins for each passenger above the seat, are used in commercial airplanes as a personalized ventilation system for regulating thermal comfort. Turing on gaspers may affect the air distribution in an aircraft cabin (You et al 2016) and further influence contaminant transport. It is crucial to investigate the air distribution and contaminant transport in cabins with gaspers turned on in order to evaluate the usefulness of gaspers in protecting passenger from exposure to contaminants.…”

Section: Introductionmentioning

confidence: 99%

“…Dai et al (2015) measured the flow field of a gasper-induced isothermal jet with a high-precision hotwire anemometer. You et al (2016) used a particle imaging velocimetry (PIV) technique to measure the interactions among the gasper-induced flow, the main flow in *Corresponding author. Email: yanchen@purdue.edu the cabin, and the thermal plume from a passenger in a cabin mockup.…”

Section: Introductionmentioning

confidence: 99%

“…Describing the geometry required millions of cells. You et al (2016) used the detailed geometry of the gasper in predicting the air distribution in half of a one-row, single-aisle cabin mockup with one gasper turned on. They found that the grid around the gasper accounted for 28% of the total grid, while the volume of this region was only 0.0006% of the total cabin mockup volume.…”

Section: Introductionmentioning

confidence: 99%

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Predicting airflow distribution and contaminant transport in aircraft cabins with a simplified gasper model

You

Liu

Chen

et al. 2016

Journal of Building Performance Simulation

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This study investigated the air distribution and contaminant transport in aircraft cabins with gaspers by using computational fluid dynamics (CFD). If the detailed gasper geometry were used in the CFD simulations, the grid number would be unacceptably high. To reduce the grid number, this investigation proposed a method for simplifying the gasper geometry. The method was then validated by two sets of experimental data obtained from a cabin mockup and a real aircraft cabin. It was found that for the cabin mockup, the CFD simulation with the simplified gasper model reduced the grid number from 1.58 to 0.3 million and the computing cost from 2 days to 1 hour without compromising the accuracy. In the five-row economyclass cabin of the MD-82 airplane, the CFD simulation with the simplified gasper model was acceptable in predicting the distribution of air velocity, air temperature, and contaminant concentration.

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Section: Methods For Simulating Air Distribution and Contaminant Transsupporting

confidence: 69%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Predicting airflow distribution and contaminant transport in aircraft cabins with a simplified gasper model

You

Liu

Chen

et al. 2016

Journal of Building Performance Simulation

Self Cite

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“…Kato et al 1992;Jiang and Chen 2002;Kurabuchi et al 2004;Hu et al 2005;van Hooff and Blocken 2010a,b;Novoselac 2011, 2013;Ramponi and Blocken 2012a,b;Ai and Mak 2014a,b;Perén et al 2015;Tong et al 2016a,b), for indoor airflow studies (e.g. Gan and Awbi 1994;Chen 1995;Nielsen 1998;Zhang et al 2007;Wang and Chen 2009;Cao and Meyers 2013;Liu et al 2013Liu et al , 2016aYou et al 2016) and for indoor pollutant concentration studies (e.g. Chung and Hsu 2001;Rouaud and Havet 2005;Chen et al 2014Chen et al , 2015.…”

Section: Introductionmentioning

confidence: 99%

Low-Reynolds number mixing ventilation flows: Impact of physical and numerical diffusion on flow and dispersion

Hooff

Blocken

2017

Build. Simul.

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Quality assurance in computational fluid dynamics (CFD) is essential for an accurate and reliable assessment of complex indoor airflow. Two important aspects are the limitation of numerical diffusion and the appropriate choice of inlet conditions to ensure the correct amount of physical diffusion. This paper presents an assessment of the impact of both numerical and physical diffusion on the predicted flow patterns and contaminant distribution in steady Reynolds-averaged NavierStokes (RANS) CFD simulations of mixing ventilation at a low slot Reynolds number (Re≈2,500). The simulations are performed on five different grids and with three different spatial discretization schemes; i.e. first-order upwind (FOU), second-order upwind (SOU) and QUICK. The impact of physical diffusion is assessed by varying the inlet turbulence intensity (TI) that is often less known in practice. The analysis shows that: (1) excessive numerical and physical diffusion leads to erroneous results in terms of delayed detachment of the wall jet and locally decreased velocity gradients; (2) excessive numerical diffusion by FOU schemes leads to deviations (up to 100%) in mean velocity and concentration, even on very high-resolution grids; (3) difference between SOU and FOU on the coarsest grid is larger than difference between SOU on coarsest grid and SOU on 22 times finer grid; (4) imposing TI values from 1% to 100% at the inlet results in very different flow patterns (enhanced or delayed detachment of wall jet) and different contaminant concentrations (deviations up to 40%); (5) impact of physical diffusion on contaminant transport can markedly differ from that of numerical diffusion.

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Numerical Study of the Airflow Distribution in a Passenger Car Cabin Validated with PIV

Ullrich

Buder

Boughanmi

et al. 2019

Notes on Numerical Fluid Mechanics and Multidisciplinary Design

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Experimental and numerical study of airflow distribution in an aircraft cabin mock-up with a gasper on

Cited by 51 publications

References 29 publications

Predicting airflow distribution and contaminant transport in aircraft cabins with a simplified gasper model

Predicting airflow distribution and contaminant transport in aircraft cabins with a simplified gasper model

Low-Reynolds number mixing ventilation flows: Impact of physical and numerical diffusion on flow and dispersion

Numerical Study of the Airflow Distribution in a Passenger Car Cabin Validated with PIV

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