Incorporating multi-source uncertainties in fast building wall thermal resistance estimation through physics-based and multi-fidelity statistical learning models

Authors

Guillaume Perrin (ORCID: https://orcid.org/0000-0002-0592-6094)
Séverine Demeyer (ORCID: https://orcid.org/0000-0001-7885-4143)
Rachida Chakir (ORCID: https://orcid.org/0000-0003-4844-3903)
Houssein Nasser
Julien Waeytens (ORCID: https://orcid.org/0000-0001-8858-7130)

Institutions

Laboratoire National de Métrologie et d'Essais (FR)
Laboratoire Modélisation et Simulation Multi-Echelle (FR)

Publication Details

Journal: Journal of Building Engineering
Published: 2024-10-22
DOI: https://doi.org/10.1016/j.jobe.2024.111027
Citations: 2
Primary Topic: Structural Health Monitoring Techniques
Type: article
Field-Weighted Citation Impact: 0.52

Funders

Agence Nationale de la Recherche

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article

Incorporating multi-source uncertainties in fast building wall thermal resistance estimation through physics-based and multi-fidelity statistical learning models

Guillaume Perrin, Séverine Demeyer, Rachida Chakir, Houssein Nasser et al.

Oct 22, 2024

2 citations

Journal of Building Engineering

Structural Health Monitoring Techniques

0.52

article

Incorporating multi-source uncertainties in fast building wall thermal resistance estimation through physics-based and multi-fidelity statistical learning models

Guillaume Perrin, Séverine Demeyer, Rachida Chakir, Houssein Nasser, Julien Waeytens

October 22, 2024article en

2 citations

Abstract

No abstract available for this paper.

Journal of Building EngineeringVol. 98

Laboratoire National de Métrologie et d'Essais (FR), Laboratoire Modélisation et Simulation Multi-Echelle (FR)

Agence Nationale de la Recherche

Affordable and clean energy

Openalex Percentile: Top 35%

Structural Health Monitoring Techniques

0.52

DOI Open Access PDF OpenAlex

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