A probabilistic-based method to evaluate hygrothermal performance of an internally insulated brick wall
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A probabilistic-based method to evaluate hygrothermal performance of an internally insulated brick wall Research Article
Jianhua Zhao1 (), Jianshun “Jensen” Zhang2, John Grunewald3, Shuo Feng4 1. Institute of Architectural Technology & Science, School of Architecture, Tianjin University, China 2. College of Mechanical & Aerospace Engineering, Syracuse University, USA 3. Institute of Building Climatology, School of Architecture, Technische Universität Dresden, Germany 4. Qinhuangdao Municipal Bureau of Foreign Affairs and Commerce, China
Abstract
Keywords
Uncertainty exists in many aspects of building simulation. A deterministic hygrothermal analysis may not sufficiently give a reliable guidance if a number of input variables are subject to uncertainty. In this paper, a probabilistic-based method was developed to evaluate the hygrothermal performance of building components. The approach accounts for the uncertainties from model inputs and propagates them to the outputs through the simulation model, thus it provides a likelihood of performance risk. Latin hypercube sampling technique, incorporated with correlation structure among the inputs, was applied to generate the random samples that follows the intrinsic relations. The performance of an internally insulated masonry wall was evaluated by applying the proposed approach against different criteria. Thermal performance, condensation and mould growth potential of the renovated wall can overall satisfy the requirements stipulated in multifold standards. The most influential inputs were identified by the standardized regression sensitivity analysis and partial correlation technique. Both methods deliver the same key parameters for the single and time-dependent output variables in the case study. The probabilistic method can provide a comprehensive risk analysis and support the decision-maker and engineer in the design and optimization of building components.
probabilistic approach,
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Introduction
E-mail: [email protected]
building component, uncertainty analysis, sensitivity analysis
Article History Received: 16 March 2020 Revised: 21 July 2020 Accepted: 24 July 2020 © Tsinghua University Press and Springer-Verlag GmbH Germany, part of Springer Nature 2020
parameters may be not exactly defined in the early design stage. With the continuous enrichment of information, these parameters are progressively determined. This type of uncertainty is classified as subjective uncertainty, which is attributed to the shortage of knowledge to precisely describe a quantity and is deductible by obtaining additional data or improving the model. However, there is still so called stochastic uncertainty that is irreducible (Helton 1997; Macdonald 2002). For example, different laboratories may deliver the inconsistent material property data even following the same instruction due to the operation skill of manipulators and material’s intrinsic inhomogeneity (Roels et al. 2004). In the operational stage, the heat and moisture loads of the building are subject to the uncertai
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