Introduction

The aim of this paper is to demonstrate that non-parameteric spectral analysis is a powerful tool for improving simulation models. In the first part of this paper, main theoretical bases are summarized and dedicated tools are defined. The proposed tools are based on the use of ordinary and partial coherence functions and on the identification of frequency responses. A smoothing procedure is used for spectral estimation. In the second part of the paper, the authors use actual data to emphasize the difficulties of spectral analysis, to illustrate the procedure recommended for smoothing spectral estimation and to quantify the variability of the proposed validation tools. The third part of this paper is dedicated to four validation exercises performed on a building thermal simulation program. It is shown how spectral analysis helped improving the performances of this model by comparing its prediction with actual data issued from three runs involving two buildings.