A Residential Case Study To Validate A New Default Detection Method Analyzing Discrepancies Between Simulated and Measured Data - Archive ouverte HAL
Conference Papers Year : 2017

A Residential Case Study To Validate A New Default Detection Method Analyzing Discrepancies Between Simulated and Measured Data

Abstract

Guarantee of performance (GP) is a big research challenge that we propose to address in this paper. Even if different guides have been developed, a need in automation of defaults detection in buildings is felt. In this paper, we propose a method helping the GP by detecting these defaults, using the method of Morris and the ABC-PMC bayesian algorithm. We apply it on an inhabited house, focusing the analysis on ab- sence periods. We test and compare 2 techniques for absence detection. Finally we study the impact of simulation on short periods on the Morris analysis.

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Dates and versions

hal-01584185 , version 1 (08-09-2017)

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  • HAL Id : hal-01584185 , version 1

Cite

Rozenn Josse-Buret, Frédéric Wurtz, Philippe Marchal, Etienne Wurtz. A Residential Case Study To Validate A New Default Detection Method Analyzing Discrepancies Between Simulated and Measured Data. IBPSA Building Simulation Conference 2017, Aug 2017, San Francisco, United States. ⟨hal-01584185⟩
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