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Information modelling for urban building energy simulation—A taxonomic review

descriptionPublicationkeyboard_double_arrow_right Article , Journal 01 Jan 2022 Germany, Ireland Publisher:Elsevier BVJournal:Building and Environment, volume 208, page 108,552 (issn: 0360-1323,

Authors: Avichal Malhotra; Julian Bischof; Alexandru Nichersu; Karl-Heinz Häfele; Johannes Exenberger; Divyanshu Sood; James Allan; +4 Authors

doi: 10.1016/j.buildenv.2021.108552 , 10.18154/rwth-2021-10634 , 10.5445/ir/1000140791

Information modelling for urban building energy simulation—A taxonomic review

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Abstract

Building and environment 208, 108552 (2021). doi:10.1016/j.buildenv.2021.108552

Published by Elsevier, New York, NY [u.a.]

Countries

Germany, Ireland

Related Organizations

RWTH Aachen University
Germany
University College Dublin
Ireland
Swiss Federal Laboratories for Materials Science and Technology
Switzerland
Karlsruhe Institute of Technology
Germany
Karlsruhe Institute of Technology / KIT
Germany

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Keywords

ddc:004, Civil and Environmental Engineering, 690, Taxonomic review, Urban scale physics-based thermal simulation, DATA processing & computer science, info:eu-repo/classification/ddc/690, Interoperability, Reproducibility, 004, Urban building energy modelling, Energy simulation tools, info:eu-repo/classification/ddc/004

Impact byBIP!

	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	50
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Top 10%
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Top 10%
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Top 1%