A new design exploring framework based on sensitivity analysis and Gaussian process regression in the early design stage

With building energy codes getting strict, quantitative analysis is necessary in the early design stage of high-energy-performance buildings. To fully explore the design space, a highly efficient method is necessary. In the research, a new design exploring framework was proposed. Parameters are scre...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Journal of Asian architecture and building engineering 2021-05, Vol.20 (3), p.326-339
Hauptverfasser: Gao, Yun, Mae, Masayuki, Taniguchi, Keiichiro
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 339
container_issue 3
container_start_page 326
container_title Journal of Asian architecture and building engineering
container_volume 20
creator Gao, Yun
Mae, Masayuki
Taniguchi, Keiichiro
description With building energy codes getting strict, quantitative analysis is necessary in the early design stage of high-energy-performance buildings. To fully explore the design space, a highly efficient method is necessary. In the research, a new design exploring framework was proposed. Parameters are screened and separated into groups based on the sensitivity analysis, to reduce the dimension of inputs. Gaussian process regression, able to deal with the uncertainty in inputs, was used to make metamodels to reduce the calculation cost and fully explore the design space. Dashboards were made to visualize the data interactively, to help designers make decisions and make communications smooth. This framework was demonstrated with a case study and showed its efficiency.
doi_str_mv 10.1080/13467581.2020.1783271
format Article
fullrecord <record><control><sourceid>webofscience_doaj_</sourceid><recordid>TN_cdi_webofscience_primary_000553668100001</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><doaj_id>oai_doaj_org_article_a55890a551464eb68705537e78e74972</doaj_id><sourcerecordid>000553668100001</sourcerecordid><originalsourceid>FETCH-LOGICAL-c423t-944215300e0055f32cf324fb02deefcf4d69ebaa0da2cfe2643864899511dd133</originalsourceid><addsrcrecordid>eNqNkU1v1DAQhiMEEqXwE5B8Ryn-TJwb1QpKpUpc4GxN7Elwydor22Wbf1-n2_aIONgzGs_7ju2naT4yesGopp-ZkF2vNLvglNdSrwXv2avmrNb7lmvFXz_mXbs1vW3e5XxLqRBKsbPm_pIEPBKH2c-B4P1hicmHmUwJ9niM6Q8ZIaMjMZCMIfvi__qyEgiwrNnnmjhyBXc5ewjkkKLFnEnCOdXoq8gHUn4jQUjL-jwlF5jxffNmgiXjh6d43vz69vXn7nt78-Pqend501rJRWkHKTlTglKkVKlJcFuXnEbKHeJkJ-m6AUcA6qAeIe-k0J3Uw6AYc44Jcd5cn3xdhFtzSH4PaTURvHksxDQbSMXbBQ0opQdadyY7iWOn-zpS9Nhr7OXQ8-qlTl42xZwTTi9-jJoNhXlGYTYU5glF1X066Y44xilbj8Hii5ZuLxNdp1nN6Nat_7975wuU-tG7eBdKlX45SX2YYtpDBbg4U2CtVCvRYH024t93fQC1QrG_</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>A new design exploring framework based on sensitivity analysis and Gaussian process regression in the early design stage</title><source>DOAJ Directory of Open Access Journals</source><source>Web of Science - Science Citation Index Expanded - 2021&lt;img src="https://exlibris-pub.s3.amazonaws.com/fromwos-v2.jpg" /&gt;</source><source>Access via Taylor &amp; Francis (Open Access Collection)</source><source>EZB-FREE-00999 freely available EZB journals</source><creator>Gao, Yun ; Mae, Masayuki ; Taniguchi, Keiichiro</creator><creatorcontrib>Gao, Yun ; Mae, Masayuki ; Taniguchi, Keiichiro</creatorcontrib><description>With building energy codes getting strict, quantitative analysis is necessary in the early design stage of high-energy-performance buildings. To fully explore the design space, a highly efficient method is necessary. In the research, a new design exploring framework was proposed. Parameters are screened and separated into groups based on the sensitivity analysis, to reduce the dimension of inputs. Gaussian process regression, able to deal with the uncertainty in inputs, was used to make metamodels to reduce the calculation cost and fully explore the design space. Dashboards were made to visualize the data interactively, to help designers make decisions and make communications smooth. This framework was demonstrated with a case study and showed its efficiency.</description><identifier>ISSN: 1346-7581</identifier><identifier>EISSN: 1347-2852</identifier><identifier>DOI: 10.1080/13467581.2020.1783271</identifier><language>eng</language><publisher>ABINGDON: Taylor &amp; Francis</publisher><subject>Architecture ; Arts &amp; Humanities ; Construction &amp; Building Technology ; design dashboard ; Gaussian process ; interaction analysis ; Science &amp; Technology ; Sensitivity analysis ; Technology ; uncertainty</subject><ispartof>Journal of Asian architecture and building engineering, 2021-05, Vol.20 (3), p.326-339</ispartof><rights>2020 The Author(s). Published by Informa UK Limited, trading as Taylor &amp; Francis Group on behalf of the Architectural Institute of Japan, Architectural Institute of Korea and Architectural Society of China. 2020</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>true</woscitedreferencessubscribed><woscitedreferencescount>2</woscitedreferencescount><woscitedreferencesoriginalsourcerecordid>wos000553668100001</woscitedreferencesoriginalsourcerecordid><citedby>FETCH-LOGICAL-c423t-944215300e0055f32cf324fb02deefcf4d69ebaa0da2cfe2643864899511dd133</citedby><cites>FETCH-LOGICAL-c423t-944215300e0055f32cf324fb02deefcf4d69ebaa0da2cfe2643864899511dd133</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.tandfonline.com/doi/pdf/10.1080/13467581.2020.1783271$$EPDF$$P50$$Ginformaworld$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.tandfonline.com/doi/full/10.1080/13467581.2020.1783271$$EHTML$$P50$$Ginformaworld$$Hfree_for_read</linktohtml><link.rule.ids>315,781,785,865,2103,2115,27507,27929,27930,39263,59148,59149</link.rule.ids></links><search><creatorcontrib>Gao, Yun</creatorcontrib><creatorcontrib>Mae, Masayuki</creatorcontrib><creatorcontrib>Taniguchi, Keiichiro</creatorcontrib><title>A new design exploring framework based on sensitivity analysis and Gaussian process regression in the early design stage</title><title>Journal of Asian architecture and building engineering</title><addtitle>J ASIAN ARCHIT BUILD</addtitle><description>With building energy codes getting strict, quantitative analysis is necessary in the early design stage of high-energy-performance buildings. To fully explore the design space, a highly efficient method is necessary. In the research, a new design exploring framework was proposed. Parameters are screened and separated into groups based on the sensitivity analysis, to reduce the dimension of inputs. Gaussian process regression, able to deal with the uncertainty in inputs, was used to make metamodels to reduce the calculation cost and fully explore the design space. Dashboards were made to visualize the data interactively, to help designers make decisions and make communications smooth. This framework was demonstrated with a case study and showed its efficiency.</description><subject>Architecture</subject><subject>Arts &amp; Humanities</subject><subject>Construction &amp; Building Technology</subject><subject>design dashboard</subject><subject>Gaussian process</subject><subject>interaction analysis</subject><subject>Science &amp; Technology</subject><subject>Sensitivity analysis</subject><subject>Technology</subject><subject>uncertainty</subject><issn>1346-7581</issn><issn>1347-2852</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>0YH</sourceid><sourceid>HGBXW</sourceid><sourceid>DOA</sourceid><recordid>eNqNkU1v1DAQhiMEEqXwE5B8Ryn-TJwb1QpKpUpc4GxN7Elwydor22Wbf1-n2_aIONgzGs_7ju2naT4yesGopp-ZkF2vNLvglNdSrwXv2avmrNb7lmvFXz_mXbs1vW3e5XxLqRBKsbPm_pIEPBKH2c-B4P1hicmHmUwJ9niM6Q8ZIaMjMZCMIfvi__qyEgiwrNnnmjhyBXc5ewjkkKLFnEnCOdXoq8gHUn4jQUjL-jwlF5jxffNmgiXjh6d43vz69vXn7nt78-Pqend501rJRWkHKTlTglKkVKlJcFuXnEbKHeJkJ-m6AUcA6qAeIe-k0J3Uw6AYc44Jcd5cn3xdhFtzSH4PaTURvHksxDQbSMXbBQ0opQdadyY7iWOn-zpS9Nhr7OXQ8-qlTl42xZwTTi9-jJoNhXlGYTYU5glF1X066Y44xilbj8Hii5ZuLxNdp1nN6Nat_7975wuU-tG7eBdKlX45SX2YYtpDBbg4U2CtVCvRYH024t93fQC1QrG_</recordid><startdate>20210504</startdate><enddate>20210504</enddate><creator>Gao, Yun</creator><creator>Mae, Masayuki</creator><creator>Taniguchi, Keiichiro</creator><general>Taylor &amp; Francis</general><general>Taylor &amp; Francis Group</general><scope>0YH</scope><scope>17B</scope><scope>AKT</scope><scope>BLEPL</scope><scope>DTL</scope><scope>EGQ</scope><scope>HGBXW</scope><scope>IINQX</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>DOA</scope></search><sort><creationdate>20210504</creationdate><title>A new design exploring framework based on sensitivity analysis and Gaussian process regression in the early design stage</title><author>Gao, Yun ; Mae, Masayuki ; Taniguchi, Keiichiro</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c423t-944215300e0055f32cf324fb02deefcf4d69ebaa0da2cfe2643864899511dd133</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Architecture</topic><topic>Arts &amp; Humanities</topic><topic>Construction &amp; Building Technology</topic><topic>design dashboard</topic><topic>Gaussian process</topic><topic>interaction analysis</topic><topic>Science &amp; Technology</topic><topic>Sensitivity analysis</topic><topic>Technology</topic><topic>uncertainty</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Gao, Yun</creatorcontrib><creatorcontrib>Mae, Masayuki</creatorcontrib><creatorcontrib>Taniguchi, Keiichiro</creatorcontrib><collection>Access via Taylor &amp; Francis (Open Access Collection)</collection><collection>Web of Knowledge</collection><collection>Arts &amp; Humanities Citation Index</collection><collection>Web of Science Core Collection</collection><collection>Science Citation Index Expanded</collection><collection>Web of Science Primary (SCIE, SSCI &amp; AHCI)</collection><collection>Web of Science - Science Citation Index Expanded - 2021</collection><collection>Web of Science - Arts &amp; Humanities Citation Index - 2021</collection><collection>CrossRef</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Journal of Asian architecture and building engineering</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Gao, Yun</au><au>Mae, Masayuki</au><au>Taniguchi, Keiichiro</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A new design exploring framework based on sensitivity analysis and Gaussian process regression in the early design stage</atitle><jtitle>Journal of Asian architecture and building engineering</jtitle><stitle>J ASIAN ARCHIT BUILD</stitle><date>2021-05-04</date><risdate>2021</risdate><volume>20</volume><issue>3</issue><spage>326</spage><epage>339</epage><pages>326-339</pages><issn>1346-7581</issn><eissn>1347-2852</eissn><abstract>With building energy codes getting strict, quantitative analysis is necessary in the early design stage of high-energy-performance buildings. To fully explore the design space, a highly efficient method is necessary. In the research, a new design exploring framework was proposed. Parameters are screened and separated into groups based on the sensitivity analysis, to reduce the dimension of inputs. Gaussian process regression, able to deal with the uncertainty in inputs, was used to make metamodels to reduce the calculation cost and fully explore the design space. Dashboards were made to visualize the data interactively, to help designers make decisions and make communications smooth. This framework was demonstrated with a case study and showed its efficiency.</abstract><cop>ABINGDON</cop><pub>Taylor &amp; Francis</pub><doi>10.1080/13467581.2020.1783271</doi><tpages>14</tpages><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 1346-7581
ispartof Journal of Asian architecture and building engineering, 2021-05, Vol.20 (3), p.326-339
issn 1346-7581
1347-2852
language eng
recordid cdi_webofscience_primary_000553668100001
source DOAJ Directory of Open Access Journals; Web of Science - Science Citation Index Expanded - 2021<img src="https://exlibris-pub.s3.amazonaws.com/fromwos-v2.jpg" />; Access via Taylor & Francis (Open Access Collection); EZB-FREE-00999 freely available EZB journals
subjects Architecture
Arts & Humanities
Construction & Building Technology
design dashboard
Gaussian process
interaction analysis
Science & Technology
Sensitivity analysis
Technology
uncertainty
title A new design exploring framework based on sensitivity analysis and Gaussian process regression in the early design stage
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-12T15%3A13%3A06IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-webofscience_doaj_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=A%20new%20design%20exploring%20framework%20based%20on%20sensitivity%20analysis%20and%20Gaussian%20process%20regression%20in%20the%20early%20design%20stage&rft.jtitle=Journal%20of%20Asian%20architecture%20and%20building%20engineering&rft.au=Gao,%20Yun&rft.date=2021-05-04&rft.volume=20&rft.issue=3&rft.spage=326&rft.epage=339&rft.pages=326-339&rft.issn=1346-7581&rft.eissn=1347-2852&rft_id=info:doi/10.1080/13467581.2020.1783271&rft_dat=%3Cwebofscience_doaj_%3E000553668100001%3C/webofscience_doaj_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rft_doaj_id=oai_doaj_org_article_a55890a551464eb68705537e78e74972&rfr_iscdi=true