Simulating the thermal behavior of buildings using artificial neural networks-based coarse-grain modeling

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dc.contributor.author Abi-Shdid, C.
dc.contributor.author Flood, I.
dc.contributor.author Issa, R.
dc.date.accessioned 2016-10-14T09:32:07Z
dc.date.available 2016-10-14T09:32:07Z
dc.date.copyright 2004 en_US
dc.date.issued 2016-10-14
dc.identifier.issn 0887-3801 en_US
dc.identifier.uri http://hdl.handle.net/10725/4600
dc.description.abstract This paper reports on the development of a new approach for simulating the thermal behavior of buildings that overcome the limitations of conventional heat-transfer simulation methods such as the finite difference method and the finite element method. The proposed technique uses a coarse-grain approach to model development whereby each element represents a complete building component such as a wall, internal space, or floor. The thermal behavior of each coarse-grain element is captured using empirical modeling techniques such as artificial neural networks (ANNs). The main advantages of the approach compared to conventional simulation methods are (1) simplified model construction for the end-user; (2) simplified model reconfiguration; (3) significantly faster simulation runs (orders of magnitude faster for two- and three-dimensional models); and (4) potentially more accurate results. The paper demonstrates the viability of the approach through a number of experiments with a model of a composite wall. The approach is shown to be able to sustain highly accurate long-term simulation runs, if the coarse-grain modeling elements are implemented as ANNs. In contrast, an implementation of the coarse-grain elements using a linear model is shown to function inaccurately and erratically. The paper concludes with an identification of on-going work and future areas for development of the technique. en_US
dc.language.iso en en_US
dc.title Simulating the thermal behavior of buildings using artificial neural networks-based coarse-grain modeling en_US
dc.type Article en_US
dc.description.version Published en_US
dc.author.school SOE en_US
dc.author.idnumber 199431340 en_US
dc.author.department Civil Engineering en_US
dc.description.embargo N/A en_US
dc.relation.journal Journal of Computing in Civil Engineering en_US
dc.journal.volume 18 en_US
dc.journal.issue 3 en_US
dc.article.pages 207-214 en_US
dc.keywords Building en_US
dc.keywords Energy conservation en_US
dc.keywords Finite difference methods en_US
dc.keywords Thermal engineering en_US
dc.keywords Finite element analysis en_US
dc.keywords Civil engineering computing en_US
dc.identifier.doi http://dx.doi.org/10.1061/(ASCE)0887-3801(2004)18:3(207) en_US
dc.identifier.ctation Flood, I., Issa, R. R., & Abi-Shdid, C. (2004). Simulating the thermal behavior of buildings using artificial neural networks-based coarse-grain modeling. Journal of computing in civil engineering, 18(3), 207-214. en_US
dc.author.email caesar.abishdid@lau.edu.lb en_US
dc.identifier.tou http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php en_US
dc.identifier.url http://ascelibrary.org/doi/abs/10.1061/(ASCE)0887-3801(2004)18:3(207) en_US
dc.orcid.id https://orcid.org/0000-0002-7114-4795

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