000878003 001__ 878003
000878003 005__ 20210130005322.0
000878003 0247_ $$2doi$$a10.1016/j.firesaf.2020.103154
000878003 0247_ $$2ISSN$$a0379-7112
000878003 0247_ $$2ISSN$$a1873-7226
000878003 0247_ $$2Handle$$a2128/25299
000878003 0247_ $$2altmetric$$aaltmetric:83749827
000878003 0247_ $$2WOS$$aWOS:000552648600011
000878003 037__ $$aFZJ-2020-02577
000878003 082__ $$a690
000878003 1001_ $$0P:(DE-HGF)0$$aSchröder, Benjamin$$b0$$eCorresponding author
000878003 245__ $$aA map representation of the ASET-RSET concept
000878003 260__ $$aNew York, NY [u.a.]$$bElsevier$$c2020
000878003 3367_ $$2DRIVER$$aarticle
000878003 3367_ $$2DataCite$$aOutput Types/Journal article
000878003 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1594989151_7849
000878003 3367_ $$2BibTeX$$aARTICLE
000878003 3367_ $$2ORCID$$aJOURNAL_ARTICLE
000878003 3367_ $$00$$2EndNote$$aJournal Article
000878003 520__ $$aAssessing life safety by comparing the available safe egress time (ASET) and the required safe egress time (RSET) is a prominent task in performance-based fire safety design. The calculation of a safety margin by subtracting RSET from ASET is a straightforward concept and is easy to understand. However, when the concept was developed, fire and evacuation models only provided punctual information derived from experimental correlations or hand calculations. Nowadays, complex computer models for fire and evacuation dynamics have become state of the art. However, the ASET-RSET concept has not adapted to these developments. While uncertainties related to the model input and the model application are widely recognised, uncertainties emerging from analysing the output only play a subordinate role.Therefore, we introduce a map representation of ASET and RSET. The maps are generated by a spatial evaluation of the quantities used to determine ASET and RSET. Based on that, a difference map is introduced to represent the safety margin throughout the entire domain. Finally, a method is proposed to reduce the high information content of the difference maps to one scalar measure of consequences. This facilitates multivariate or risk-based analysis approaches and thus is able to reduce the uncertainties in performance-based design.
000878003 536__ $$0G:(DE-HGF)POF3-511$$a511 - Computational Science and Mathematical Methods (POF3-511)$$cPOF3-511$$fPOF III$$x0
000878003 588__ $$aDataset connected to CrossRef
000878003 7001_ $$0P:(DE-Juel1)132044$$aArnold, Lukas$$b1
000878003 7001_ $$0P:(DE-Juel1)132266$$aSeyfried, Armin$$b2
000878003 773__ $$0PERI:(DE-600)1483569-1$$a10.1016/j.firesaf.2020.103154$$gVol. 115, p. 103154 -$$p103154 -$$tFire safety journal$$v115$$x0379-7112$$y2020
000878003 8564_ $$uhttps://juser.fz-juelich.de/record/878003/files/1-s2.0-S0379711219307209-main.pdf$$yRestricted
000878003 8564_ $$uhttps://juser.fz-juelich.de/record/878003/files/2020_ASET_RSET_Maps_PREPRINT.pdf$$yOpenAccess$$zStatID:(DE-HGF)0510
000878003 8564_ $$uhttps://juser.fz-juelich.de/record/878003/files/1-s2.0-S0379711219307209-main.pdf?subformat=pdfa$$xpdfa$$yRestricted
000878003 8564_ $$uhttps://juser.fz-juelich.de/record/878003/files/2020_ASET_RSET_Maps_PREPRINT.pdf?subformat=pdfa$$xpdfa$$yOpenAccess$$zStatID:(DE-HGF)0510
000878003 909CO $$ooai:juser.fz-juelich.de:878003$$pdnbdelivery$$pdriver$$pVDB$$popen_access$$popenaire
000878003 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)132044$$aForschungszentrum Jülich$$b1$$kFZJ
000878003 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)132266$$aForschungszentrum Jülich$$b2$$kFZJ
000878003 9131_ $$0G:(DE-HGF)POF3-511$$1G:(DE-HGF)POF3-510$$2G:(DE-HGF)POF3-500$$3G:(DE-HGF)POF3$$4G:(DE-HGF)POF$$aDE-HGF$$bKey Technologies$$lSupercomputing & Big Data$$vComputational Science and Mathematical Methods$$x0
000878003 9141_ $$y2020
000878003 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS$$d2019-12-20
000878003 915__ $$0StatID:(DE-HGF)0160$$2StatID$$aDBCoverage$$bEssential Science Indicators$$d2019-12-20
000878003 915__ $$0StatID:(DE-HGF)1160$$2StatID$$aDBCoverage$$bCurrent Contents - Engineering, Computing and Technology$$d2019-12-20
000878003 915__ $$0StatID:(DE-HGF)0600$$2StatID$$aDBCoverage$$bEbsco Academic Search$$d2019-12-20
000878003 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bFIRE SAFETY J : 2018$$d2019-12-20
000878003 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection$$d2019-12-20
000878003 915__ $$0StatID:(DE-HGF)0111$$2StatID$$aWoS$$bScience Citation Index Expanded$$d2019-12-20
000878003 915__ $$0StatID:(DE-HGF)9900$$2StatID$$aIF < 5$$d2019-12-20
000878003 915__ $$0StatID:(DE-HGF)0510$$2StatID$$aOpenAccess
000878003 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bASC$$d2019-12-20
000878003 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline$$d2019-12-20
000878003 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List$$d2019-12-20
000878003 920__ $$lyes
000878003 9201_ $$0I:(DE-Juel1)IAS-7-20180321$$kIAS-7$$lZivile Sicherheitsforschung$$x0
000878003 980__ $$ajournal
000878003 980__ $$aVDB
000878003 980__ $$aUNRESTRICTED
000878003 980__ $$aI:(DE-Juel1)IAS-7-20180321
000878003 9801_ $$aFullTexts