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Computational Fluid Dynamics for urban physics: Importance, scales, possibilities, limitations and ten tips and tricks towards accurate and reliable simulations
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Computational Fluid Dynamics for urban physics: Importance, scales, possibilities, limitations and ten tips and tricks towards accurate and reliable simulations

Blocken, Bert

Building and environment, 2015-09, Vol.91, p.219-245 [Periódico revisado por pares]

Elsevier Ltd

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Probable airborne transmission of SARS-CoV-2 in a poorly ventilated restaurant
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Probable airborne transmission of SARS-CoV-2 in a poorly ventilated restaurant

Li, Yuguo ; Qian, Hua ; Hang, Jian ; Chen, Xuguang ; Cheng, Pan ; Ling, Hong ; Wang, Shengqi ; Liang, Peng ; Li, Jiansen ; Xiao, Shenglan ; Wei, Jianjian ; Liu, Li ; Cowling, Benjamin J. ; Kang, Min

Building and environment, 2021-06, Vol.196, p.107788-107788, Article 107788 [Periódico revisado por pares]

England: Elsevier Ltd

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Validation of neural network model for predicting airtightness of residential and non-residential units in Poland
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Validation of neural network model for predicting airtightness of residential and non-residential units in Poland

Krstić, Hrvoje ; Otković, Irena Ištoka ; Kosiński, Piotr ; Wójcik, Robert

Energy and buildings, 2016-12, Vol.133, p.423-432 [Periódico revisado por pares]

Lausanne: Elsevier B.V

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Building Information Modeling (BIM) application framework: The process of expanding from 3D to computable nD
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Building Information Modeling (BIM) application framework: The process of expanding from 3D to computable nD

Ding, Lieyun ; Zhou, Ying ; Akinci, Burcu

Automation in construction, 2014-10, Vol.46, p.82-93 [Periódico revisado por pares]

Elsevier B.V

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5
Can the compressive strength of concrete be estimated from knowledge of the mixture proportions?: New insights from statistical analysis and machine learning methods
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Can the compressive strength of concrete be estimated from knowledge of the mixture proportions?: New insights from statistical analysis and machine learning methods

Young, Benjamin A. ; Hall, Alex ; Pilon, Laurent ; Gupta, Puneet ; Sant, Gaurav

Cement and concrete research, 2019-01, Vol.115, p.379-388 [Periódico revisado por pares]

Elmsford: Elsevier Ltd

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6
Surrogate modelling for sustainable building design – A review
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Surrogate modelling for sustainable building design – A review

Westermann, Paul ; Evins, Ralph

Energy and buildings, 2019-09, Vol.198, p.170-186 [Periódico revisado por pares]

Lausanne: Elsevier B.V

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Random Forest based hourly building energy prediction
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Random Forest based hourly building energy prediction

Wang, Zeyu ; Wang, Yueren ; Zeng, Ruochen ; Srinivasan, Ravi S. ; Ahrentzen, Sherry

Energy and buildings, 2018-07, Vol.171, p.11-25 [Periódico revisado por pares]

Lausanne: Elsevier B.V

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The gap between predicted and measured energy performance of buildings: A framework for investigation
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The gap between predicted and measured energy performance of buildings: A framework for investigation

de Wilde, Pieter

Automation in construction, 2014-05, Vol.41, p.40-49 [Periódico revisado por pares]

Kidlington: Elsevier B.V

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A performance comparison of multi-objective optimization algorithms for solving nearly-zero-energy-building design problems
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A performance comparison of multi-objective optimization algorithms for solving nearly-zero-energy-building design problems

Hamdy, Mohamed ; Nguyen, Anh-Tuan ; Hensen, Jan L.M.

Energy and buildings, 2016-06, Vol.121, p.57-71 [Periódico revisado por pares]

Elsevier B.V

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Modeling heating and cooling loads by artificial intelligence for energy-efficient building design
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Modeling heating and cooling loads by artificial intelligence for energy-efficient building design

Chou, Jui-Sheng ; Bui, Dac-Khuong

Energy and buildings, 2014-10, Vol.82, p.437-446 [Periódico revisado por pares]

Oxford: Elsevier B.V

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