Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Tunnel QRA: Present and Future Perspectives
Luleå University of Technology. Cyient Limited, Hyderabad, India.
Western Norway University of Applied Sciences, Haugesund, Norway.
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.ORCID iD: 0000-0001-8111-6918
Luleå University of Technology.
2019 (English)In: System Performance and Management Analytics / [ed] P. K. Kapur, Yury Klochkov, Ajit Kumar Verma, Gurinder Singh, Springer, 2019, p. 387-403Chapter in book (Refereed)
Abstract [en]

With the vision of faster in-land transportation of humans and goods, long tunnels with increasing engineering complexities are being designed, constructed and operated. Such complexities arise due to terrain (network of small tunnels) and requirement of multiple entries and exits (network of traffics leading to non-homogenous behaviour). Increased complexities of such tunnels throw unique challenges for performing QRA for such tunnels, which gets compounded due to handful number of experiments performed in real tunnels, as they are costly and dangerous. A combined approach of CFD modelling of scaled down tunnels could be a relatively less resource intensive solution, nevertheless, associated with its increased uncertainties due to introduction of scaling multiplication factors. Further, with the advent of smart system designs and cheap computational cost, a smart tunnel which manages its own traffic of both dangerous goods carriers and other passenger vehicles based on continuously updated dynamic risk estimate, is not far from reality.

Place, publisher, year, edition, pages
Springer, 2019. p. 387-403
Series
Asset Analytics, ISSN 2522-5162
Keywords [en]
Quantitative risk assessment (QRA), Tunnels, Fire dynamics, Risk analysis, F-N, EV, QRAM, Froude scaling, Smart tunnel, Dynamic risk of tunnel
National Category
Other Civil Engineering
Research subject
Operation and Maintenance Engineering
Identifiers
URN: urn:nbn:se:ltu:diva-70277DOI: 10.1007/978-981-10-7323-6_31ISBN: 978-981-10-7322-9 (print)ISBN: 978-981-10-7323-6 (electronic)OAI: oai:DiVA.org:ltu-70277DiVA, id: diva2:1237413
Available from: 2018-08-08 Created: 2018-08-08 Last updated: 2024-04-11Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full text

Authority records

Kumar, Uday

Search in DiVA

By author/editor
Kumar, Uday
By organisation
Luleå University of TechnologyOperation, Maintenance and Acoustics
Other Civil Engineering

Search outside of DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 3752 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf