A Method To Optimize Sampling Locations For Measuring Air Environment In Aircraft Cabin

People spend more than 80% time in the buildings and vehicles. 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. In order to make a healthy and comfortable indoor air environment, it is essential to investigate indoor air distribution and contaminant transportation. The point-measurement method is one of the most popular used methods to assess the detailed distributions of air parameters. 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 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 analysis indicates that the gradient-based sampling method obtained smaller interpolation error than the grid sampling method and it gave more detailed information in the large gradient region, such as near the air inlet, outlet and sources.This investigation also validated the gradient-based method in an office room. It also shows good performance in whole-field interpolation. Therefore, we recommend the gradient-based sampling method for measuring indoor air distributions.Furthermore, we analyzed the relationship between the sampling size and interpolation accuracy. The interpolation errors can be expressed as a function of sampling size(the number of sampling points) for measuring air distributions in an indoor space and the sampling size has an optimal value for an indoor space. When the sensor and system errors are assumed to be the same as the minimal interpolation errors, the maximal sampling size for the measurements can be determined.