001     156271
005     20210129214231.0
024 7 _ |a 10.1016/j.trpro.2014.09.081
|2 doi
024 7 _ |a WOS:000366304000096
|2 WOS
037 _ _ |a FZJ-2014-05062
041 _ _ |a English
100 1 _ |a Zhang, J.
|0 P:(DE-Juel1)156196
|b 0
|e Corresponding Author
|u fzj
111 2 _ |a The Conference on Pedestrian and Evacuation Dynamics 2014
|g PED 2014
|c Delft
|d 2014-10-22 - 2014-10-25
|w The Netherlands
245 _ _ |a Quantitative Validation of PEDFLOW for Description of Unidirectional Pedestrian Dynamics
260 _ _ |c 2014
295 1 0 |a Transportation Research Procedia
300 _ _ |a 733–738
336 7 _ |a Contribution to a conference proceedings
|b contrib
|m contrib
|0 PUB:(DE-HGF)8
|s 1412863308_26707
|2 PUB:(DE-HGF)
336 7 _ |a Contribution to a book
|0 PUB:(DE-HGF)7
|2 PUB:(DE-HGF)
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336 7 _ |a Conference Paper
|0 33
|2 EndNote
336 7 _ |a CONFERENCE_PAPER
|2 ORCID
336 7 _ |a Output Types/Conference Paper
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336 7 _ |a conferenceObject
|2 DRIVER
336 7 _ |a INPROCEEDINGS
|2 BibTeX
520 _ _ |a The results of a systematic quantitative validation of PEDFLOW based on the experimental data from FZJ are presented. Uni- directional flow experiments, totaling 28 different combinations with varying entry, corridor and exit widths, were considered. The condition imposed on PEDFLOW was that all the cases should be run with the same input parameters. The exit times and fundamental diagrams for the measuring region were evaluated and compared. This validation process led to modifications and enhancements of the model underlying PEDFLOW. The preliminary conclusions indicate that the results agree well for densities smaller than 3 m-2 and a good agreement is observed even at high densities for the corridors with bcor = 2.4 m, and bcor = 3.0 m. For densities between 1 and 2 m-2 the specific flow and velocities are underpredicted by PEDFLOW.
536 _ _ |a 411 - Computational Science and Mathematical Methods (POF2-411)
|0 G:(DE-HGF)POF2-411
|c POF2-411
|f POF II
|x 0
588 _ _ |a Dataset connected to CrossRef, juser.fz-juelich.de
700 1 _ |a Britto, D.
|0 P:(DE-HGF)0
|b 1
700 1 _ |a Chraibi, M.
|0 P:(DE-Juel1)132077
|b 2
|u fzj
700 1 _ |a Löhner, R.
|0 P:(DE-HGF)0
|b 3
700 1 _ |a Haug, E.
|0 P:(DE-HGF)0
|b 4
700 1 _ |a Gawenat, B.
|0 P:(DE-HGF)0
|b 5
773 _ _ |a 10.1016/j.trpro.2014.09.081
|p 733–738
|v 2
909 C O |o oai:juser.fz-juelich.de:156271
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910 1 _ |a Forschungszentrum Jülich GmbH
|0 I:(DE-588b)5008462-8
|k FZJ
|b 0
|6 P:(DE-Juel1)156196
910 1 _ |a Forschungszentrum Jülich GmbH
|0 I:(DE-588b)5008462-8
|k FZJ
|b 2
|6 P:(DE-Juel1)132077
913 2 _ |a DE-HGF
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|l Key Technologies
|1 G:(DE-HGF)POF3-510
|0 G:(DE-HGF)POF3-511
|2 G:(DE-HGF)POF3-500
|v Supercomputing & Big Data
|x 0
913 1 _ |a DE-HGF
|b Schlüsseltechnologien
|l Supercomputing
|1 G:(DE-HGF)POF2-410
|0 G:(DE-HGF)POF2-411
|2 G:(DE-HGF)POF2-400
|v Computational Science and Mathematical Methods
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|4 G:(DE-HGF)POF
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914 1 _ |y 2014
920 1 _ |0 I:(DE-Juel1)JSC-20090406
|k JSC
|l Jülich Supercomputing Center
|x 0
980 _ _ |a contrib
980 _ _ |a VDB
980 _ _ |a contb
980 _ _ |a I:(DE-Juel1)JSC-20090406
980 _ _ |a UNRESTRICTED


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