BAYESIAN METHOD FOR ESTIMATING AIRTIGHTNESS COEFFICIENTS FROM PRESSURIZATION MEASUREMENTS

A new method for processing pressurization data of a building is presented. The inverse problem theory is applied to the estimation of airtightness coefficients. The method, based on the conjunction of theoretical and experimental information, provides better confidence intervals than a classical least mean square fit method and allows one to take into account more sources of error. The airtightness coefficients are major parameters for predicting air renewal from weather data and they usually have very large confidence intervals whose reduction merits some numerical efforts.