DOI: 10.1016/j.atmosenv.2017.08.003
Scopus记录号: 2-s2.0-85026858575
论文题名: Integrated analysis of numerical weather prediction and computational fluid dynamics for estimating cross-ventilation effects on inhaled air quality inside a factory
作者: Murga A ; , Sano Y ; , Kawamoto Y ; , Ito K
刊名: Atmospheric Environment
ISSN: 0168-2563
EISSN: 1573-515X
出版年: 2017
卷: 167 起始页码: 11
结束页码: 22
语种: 英语
英文关键词: Computational fluid dynamics
; Computer simulated person
; Cross-ventilation
; Dynamic downscaling
; Factory environment
; Numerical weather prediction
Scopus关键词: Air
; Air quality
; Atmospheric movements
; Computational fluid dynamics
; Contamination
; Dynamics
; Fluid dynamics
; Forecasting
; Indoor air pollution
; Numerical models
; Quality control
; Structural dynamics
; Ventilation
; Wind effects
; Atmospheric conditions
; Contaminant concentrations
; Cross ventilation
; Dynamic downscaling
; Indoor environmental quality
; Numerical weather prediction
; Numerical weather prediction models
; Wind pressure coefficient
; Weather forecasting
; air quality
; building
; climate prediction
; computational fluid dynamics
; computer simulation
; concentration (composition)
; downscaling
; estimation method
; indoor air
; integrated approach
; occupational exposure
; public health
; resident population
; urban atmosphere
; ventilation
; weather forecasting
; air conditioning
; air quality
; Article
; computational fluid dynamics
; controlled study
; forecasting
; hydrostatic pressure
; prediction
; priority journal
; sea surface temperature
; seashore
; shear stress
; surface property
; topography
; weather
; wind
; work environment
Scopus学科分类: Environmental Science: Water Science and Technology
; Earth and Planetary Sciences: Earth-Surface Processes
; Environmental Science: Environmental Chemistry
英文摘要: Mechanical and passive ventilation strategies directly impact indoor air quality. Passive ventilation has recently become widespread owing to its ability to reduce energy demand in buildings, such as the case of natural or cross ventilation. To understand the effect of natural ventilation on indoor environmental quality, outdoor–indoor flow paths need to be analyzed as functions of urban atmospheric conditions, topology of the built environment, and indoor conditions. Wind-driven natural ventilation (e.g., cross ventilation) can be calculated through the wind pressure coefficient distributions of outdoor wall surfaces and openings of a building, allowing the study of indoor air parameters and airborne contaminant concentrations. Variations in outside parameters will directly impact indoor air quality and residents’ health. Numerical modeling can contribute to comprehend these various parameters because it allows full control of boundary conditions and sampling points. In this study, numerical weather prediction modeling was used to calculate wind profiles/distributions at the atmospheric scale, and computational fluid dynamics was used to model detailed urban and indoor flows, which were then integrated into a dynamic downscaling analysis to predict specific urban wind parameters from the atmospheric to built-environment scale. Wind velocity and contaminant concentration distributions inside a factory building were analyzed to assess the quality of the human working environment by using a computer simulated person. The impact of cross ventilation flows and its variations on local average contaminant concentration around a factory worker, and inhaled contaminant dose, were then discussed. © 2017 Elsevier Ltd Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/82500
Appears in Collections: 气候变化事实与影响
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作者单位: Interdisciplinary Graduate School of Engineering Sciences, Kyushu University, Japan; Faculty of Design, Kyushu University, Japan; Faculty of Engineering Sciences, Kyushu University, Japan
Recommended Citation:
Murga A,, Sano Y,, Kawamoto Y,et al. Integrated analysis of numerical weather prediction and computational fluid dynamics for estimating cross-ventilation effects on inhaled air quality inside a factory[J]. Atmospheric Environment,2017-01-01,167