DOI: 10.1016/j.atmosenv.2014.12.017
Scopus记录号: 2-s2.0-84916896933
论文题名: A method to optimize sampling locations for measuring indoor air distributions
作者: Huang Y ; , Shen X ; , Li J ; , Li B ; , Duan R ; , Lin C ; -H ; , Liu J ; , Chen Q
刊名: Atmospheric Environment
ISSN: 0168-2563
EISSN: 1573-515X
出版年: 2015
卷: 102 起始页码: 355
结束页码: 365
语种: 英语
英文关键词: CFD simulation
; Error analysis
; Gradient method
; Kriging interpolation
Scopus关键词: Cabins (aircraft)
; Computational fluid dynamics
; Error analysis
; Gradient methods
; Interpolation
; Wages
; CFD simulations
; Contaminant concentrations
; Field distribution
; Gradient-based method
; Interpolation error
; Kriging interpolation
; Measuring accuracy
; Ordinary kriging methods
; Air
; accuracy assessment
; air quality
; air temperature
; airflow
; error analysis
; indoor air
; interpolation
; kriging
; parameterization
; sampling
; sensor
; air pollutant
; air sampling
; air temperature
; ambient air
; analytical error
; Article
; kriging
; velocity
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: Indoor air distributions, such as the distributions of air temperature, air velocity, and contaminant concentrations, are very important to occupants' health and comfort in enclosed spaces. When point data is collected for interpolation to form field distributions, the sampling locations (the locations of the point sensors) have a significant effect on time invested, labor costs and measuring accuracy on field interpolation. This investigation compared two different sampling methods: the grid method and the gradient-based method, for determining sampling locations. The two methods were applied to obtain point air parameter data in an office room and in a section of an economy-class aircraft cabin. The point data obtained was then interpolated to form field distributions by the ordinary Kriging method. Our error analysis shows that the gradient-based sampling method has 32.6% smaller error of interpolation than the grid sampling method. We acquired the function between the interpolation errors and the sampling size (the number of sampling points). According to the function, the sampling size has an optimal value and the maximum sampling size can be determined by the sensor and system errors. This study recommends the gradient-based sampling method for measuring indoor air distributions. © 2014 Elsevier Ltd. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/82022
Appears in Collections: 气候变化事实与影响
There are no files associated with this item.
作者单位: School of Environmental Science and Engineering, Tianjin University, Tianjin, China; Environmental Control Systems, Boeing Commercial Airplanes, Everett, WA, United States; School of Mechanical Engineering, Purdue University, West Lafayette, IN, United States
Recommended Citation:
Huang Y,, Shen X,, Li J,et al. A method to optimize sampling locations for measuring indoor air distributions[J]. Atmospheric Environment,2015-01-01,102