Control of interior surface materials for speech privacy in high-speed train cabins
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Jang, Hyung-Suk | - |
dc.contributor.author | Lim, Hansol | - |
dc.contributor.author | Jeon, Jin Yong | - |
dc.date.accessioned | 2022-07-14T04:08:17Z | - |
dc.date.available | 2022-07-14T04:08:17Z | - |
dc.date.created | 2021-05-12 | - |
dc.date.issued | 2017-05 | - |
dc.identifier.issn | 0905-6947 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/152432 | - |
dc.description.abstract | The effect of interior materials with various absorption coefficients on speech privacy was investigated in a 1:10 scale model of one high-speed train cabin geometry. The speech transmission index (STI) and privacy distance (r(P)) were measured in the train cabin to quantify speech privacy. Measurement cases were selected for the ceiling, sidewall, and front and back walls and were classified as high-, medium- and low-absorption coefficient cases. Interior materials with high absorption coefficients yielded a low r(P), and the ceiling had the largest impact on both the STI and r(P) among the interior elements. Combinations of the three cases were measured, and the maximum reduction in r(P) by the absorptive surfaces was 2.4m, which exceeds the space between two rows of chairs in the high-speed train. Additionally, the contribution of the interior elements to speech privacy was analyzed using recorded impulse responses and a multiple regression model for r(P) using the equivalent absorption area. The analysis confirmed that the ceiling was the most important interior element for improving speech privacy. These results can be used to find the relative decrease in r(P) in the acoustic design of interior materials to improve speech privacy in train cabins. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | WILEY | - |
dc.title | Control of interior surface materials for speech privacy in high-speed train cabins | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Jeon, Jin Yong | - |
dc.identifier.doi | 10.1111/ina.12339 | - |
dc.identifier.scopusid | 2-s2.0-84991833035 | - |
dc.identifier.wosid | 000399681800017 | - |
dc.identifier.bibliographicCitation | Indoor Air, v.27, no.3, pp.670 - 679 | - |
dc.relation.isPartOf | Indoor Air | - |
dc.citation.title | Indoor Air | - |
dc.citation.volume | 27 | - |
dc.citation.number | 3 | - |
dc.citation.startPage | 670 | - |
dc.citation.endPage | 679 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Construction & Building Technology | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalResearchArea | Public, Environmental & Occupational Health | - |
dc.relation.journalWebOfScienceCategory | Construction & Building Technology | - |
dc.relation.journalWebOfScienceCategory | Engineering, Environmental | - |
dc.relation.journalWebOfScienceCategory | Public, Environmental & Occupational Health | - |
dc.subject.keywordPlus | SOUND-PROPAGATION | - |
dc.subject.keywordPlus | SCALE-MODEL | - |
dc.subject.keywordPlus | INTELLIGIBILITY | - |
dc.subject.keywordPlus | COMFORT | - |
dc.subject.keywordPlus | NOISE | - |
dc.subject.keywordPlus | IMPACT | - |
dc.subject.keywordAuthor | absorption coefficient | - |
dc.subject.keywordAuthor | high-speed train cabin | - |
dc.subject.keywordAuthor | interior surfaces | - |
dc.subject.keywordAuthor | scale model | - |
dc.subject.keywordAuthor | speech privacy | - |
dc.subject.keywordAuthor | surface materials | - |
dc.identifier.url | https://onlinelibrary.wiley.com/doi/10.1111/ina.12339 | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
222, Wangsimni-ro, Seongdong-gu, Seoul, 04763, Korea+82-2-2220-1365
COPYRIGHT © 2021 HANYANG UNIVERSITY.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.