On the optimal experimental design for heat and moisture parameter estimation

TL;DR

This paper develops a methodology for optimal experimental design to accurately estimate heat and moisture parameters in porous materials, enhancing the efficiency of in-situ measurements and identification methods.

Contribution

It introduces a formal approach using Fisher information for optimal sensor placement and boundary conditions in heat and moisture experiments.

Findings

Optimal experiment design improves parameter estimation accuracy.

Method validated through two case studies with different heat transfer scenarios.

Framework applicable to other thermal and fluid science problems.

Abstract

In the context of estimating material properties of porous walls based on in-site measurements and identification method, this paper presents the concept of Optimal Experiment Design (OED). It aims at searching the best experimental conditions in terms of quantity and position of sensors and boundary conditions imposed to the material. These optimal conditions ensure to provide the maximum accuracy of the identification method and thus the estimated parameters. The search of the OED is done by using the Fisher information matrix and a priori knowledge of the parameters. The methodology is applied for two case studies. The first one deals with purely conductive heat transfer. The concept of optimal experiment design is detailed and verified with 100 inverse problems for different experiment designs. The second case study combines a strong coupling between heat and moisture transfer through a porous building material. The methodology presented is based on a scientific formalism for efficient planning of experimental work that can be extended to the optimal design of experiments related to other problems in thermal and fluid sciences.