An efficient sensitivity analysis for energy performance of building envelope: A continuous derivative based approach
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An efficient sensitivity analysis for energy performance of building envelope: A continuous derivative based approach
1. University of Grenoble Alpes, University of Savoie Mont Blanc, UMR 5271 CNRS, LOCIE, 73000 Chambéry, France 2. LaSIE, La Rochelle University, CNRS, UMR 7356, 17000 La Rochelle, France 3. University of Grenoble Alpes, CEA, LITEN, DTS, INES, F-38000, Grenoble, France
Abstract
Keywords
Within the framework of building energy assessment, this article proposes to use a derivative based sensitivity analysis of heat transfer models in a building envelope. Two, global and local, estimators are obtained at low computational cost, to evaluate the influence of the parameters on the model outputs. Ranking of these estimators values allows to reduce the number of model unknown parameters by excluding non-significant parameters. A comparison with variance and regression-based methods is carried out and the results highlight the satisfactory accuracy of the continuous-based approach. Moreover, for the carried investigations the approach is 100 times faster compared to the variance-based methods. A case study applies the method to a real-world building wall. The sensitivity of the thermal loads to local or global variations of the wall thermal properties is investigated. Additionally, a case study of wall with window is analyzed.
heat transfer,
Research Article
Ainagul Jumabekova1,3 (), Julien Berger2, Aurélie Foucquier3
sensitivity analysis, continuous derivative based approach, parameter estimation problem, DuFort–Frankel numerical scheme, sensitivity coefficients
Article History Received: 13 April 2020 Revised: 11 August 2020 Accepted: 17 August 2020 © Tsinghua University Press and Springer-Verlag GmbH Germany, part of Springer Nature 2020
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Introduction
E-mail: [email protected]
Building Thermal, Lighting, and Acoustics Modeling
Within the context of environmental sustainability, retrofit solutions help to decrease the heating and cooling demand of building stocks. In order to evaluate the efficiency of retrofit actions, engineers usually conduct energy audits of buildings. Numerical simulations are often used to analyze the energy performance of buildings according to the retrofit scenarios. However, despite the recent advances in building energy simulation programs, the gap between the actual and the predicted energy consumption still remains a challenging issue. In existing buildings, this discrepancy may arise from uncertainties in the thermophysical properties of building materials (Hughes et al. 2015). The properties change due to (i) time degradation, (ii) exposure to weather conditions, and (iii) traditional processes of construction. Therefore, the estimation of the actual material properties will improve the accuracy and reliability of building simulation software.
It is essential to have models that evaluate the impact of input parameters variability on the physical phenomena predictions. It enables to assess the sensitivity of the important fields such as the temperat
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