Assigning Robust Default Values in Building Performance Simulation Software for Improved Decision-Making in the Initial Stages of Building Design

Applying data mining techniques on a database of BIM models could provide valuable insights in key design patterns implicitly present in these BIM models. The architectural designer would then be able to use previous data from existing building projects as default values in building performance simu...

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Bibliographic Details
Main Author: Kyosuke Hiyama
Format: Article
Language:English
Published: Hindawi Limited 2015-01-01
Series:The Scientific World Journal
Online Access:http://dx.doi.org/10.1155/2015/246718
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spelling doaj-5e9fa397bdc64f08a3abe53f72176e0c2020-11-25T00:54:57ZengHindawi LimitedThe Scientific World Journal2356-61401537-744X2015-01-01201510.1155/2015/246718246718Assigning Robust Default Values in Building Performance Simulation Software for Improved Decision-Making in the Initial Stages of Building DesignKyosuke Hiyama0Faculty of Engineering, Yamaguchi University, 2-16-1 Tokiwadai, Ube-shi, Yamaguchi 755-8611, JapanApplying data mining techniques on a database of BIM models could provide valuable insights in key design patterns implicitly present in these BIM models. The architectural designer would then be able to use previous data from existing building projects as default values in building performance simulation software for the early phases of building design. The author has proposed the method to minimize the magnitude of the variation in these default values in subsequent design stages. This approach maintains the accuracy of the simulation results in the initial stages of building design. In this study, a more convincing argument is presented to demonstrate the significance of the new method. The variation in the ideal default values for different building design conditions is assessed first. Next, the influence of each condition on these variations is investigated. The space depth is found to have a large impact on the ideal default value of the window to wall ratio. In addition, the presence or absence of lighting control and natural ventilation has a significant influence on the ideal default value. These effects can be used to identify the types of building conditions that should be considered to determine the ideal default values.http://dx.doi.org/10.1155/2015/246718
collection DOAJ
language English
format Article
sources DOAJ
author Kyosuke Hiyama
spellingShingle Kyosuke Hiyama
Assigning Robust Default Values in Building Performance Simulation Software for Improved Decision-Making in the Initial Stages of Building Design
The Scientific World Journal
author_facet Kyosuke Hiyama
author_sort Kyosuke Hiyama
title Assigning Robust Default Values in Building Performance Simulation Software for Improved Decision-Making in the Initial Stages of Building Design
title_short Assigning Robust Default Values in Building Performance Simulation Software for Improved Decision-Making in the Initial Stages of Building Design
title_full Assigning Robust Default Values in Building Performance Simulation Software for Improved Decision-Making in the Initial Stages of Building Design
title_fullStr Assigning Robust Default Values in Building Performance Simulation Software for Improved Decision-Making in the Initial Stages of Building Design
title_full_unstemmed Assigning Robust Default Values in Building Performance Simulation Software for Improved Decision-Making in the Initial Stages of Building Design
title_sort assigning robust default values in building performance simulation software for improved decision-making in the initial stages of building design
publisher Hindawi Limited
series The Scientific World Journal
issn 2356-6140
1537-744X
publishDate 2015-01-01
description Applying data mining techniques on a database of BIM models could provide valuable insights in key design patterns implicitly present in these BIM models. The architectural designer would then be able to use previous data from existing building projects as default values in building performance simulation software for the early phases of building design. The author has proposed the method to minimize the magnitude of the variation in these default values in subsequent design stages. This approach maintains the accuracy of the simulation results in the initial stages of building design. In this study, a more convincing argument is presented to demonstrate the significance of the new method. The variation in the ideal default values for different building design conditions is assessed first. Next, the influence of each condition on these variations is investigated. The space depth is found to have a large impact on the ideal default value of the window to wall ratio. In addition, the presence or absence of lighting control and natural ventilation has a significant influence on the ideal default value. These effects can be used to identify the types of building conditions that should be considered to determine the ideal default values.
url http://dx.doi.org/10.1155/2015/246718
work_keys_str_mv AT kyosukehiyama assigningrobustdefaultvaluesinbuildingperformancesimulationsoftwareforimproveddecisionmakingintheinitialstagesofbuildingdesign
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