Abstract
In recent years, the technique of measuring velocity, temperature and pollutant concentration which constitutes indoor air condition has been simplified and quickened by the use of computer. Especially for velocity measurement, PIV technique has been proposed to improve the density of observed data. However the problems of errors included in data derived from measurement systems and artificial factors, and the problems of data omission especially in PIV technique still exit. Therefore it is hard to grasp whole room condition quantitatively with sufficient accuracy. On the other hand, various methods which attempt to reduce errors and supplement data to data omission points by applying governing equations have been proposed. In this paper, we classify and systematize these methods according to the types of observations and equations used. Subsequently, we propose GCFM (Generalized Cost Function Method) which reflects the observation data of velocity, temperature and mass concentration to the mutual estimation of each field by using the cost function defined by the summation of the residuals of governing equations and data corrections. Finally we execute a numerical experiment for 2-dimentional steady non-isothermal flow field which contains pollutant emission sources to verify the effectiveness of GCFM, and we can confirm that our method is effective in the grasping of the flow fields.
