000890024 001__ 890024
000890024 005__ 20210127115426.0
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000890024 037__ $$aFZJ-2021-00618
000890024 041__ $$aEnglish
000890024 1001_ $$0P:(DE-HGF)0$$aLauer, Patrick$$b0
000890024 1112_ $$aFire and Evacuation Modelling Technical Conference 2020$$cvirtual$$d2020-09-09 - 2020-09-11$$gFEMTC 2020$$wvirtual
000890024 245__ $$aRole Of The Cost Function For Material Parameter Determination
000890024 260__ $$c2020
000890024 300__ $$a12
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000890024 520__ $$aCost functions in optimisation processes are used as a measure to compute the distance between two data sets. Commonly, the root mean square error is used as a cost function for the estimation of material parameters based on bench-scale experiments. Due to the noise and variance in the target experimental data, this may not be the best choice. This contribution presents three other approaches, which are implemented into the PROPTI framework. Their application is demonstrated on experiments with a PMMA sample in a controlled atmosphere pyrolysis apparatus (CAPA II). Although, in the specific case investigated here, the impact of the various cost function classes is small, a benefit is expected for other samples with varying complexity.
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000890024 536__ $$0G:(DE-Juel1)PHD-NO-GRANT-20170405$$aPhD no Grant - Doktorand ohne besondere Förderung (PHD-NO-GRANT-20170405)$$cPHD-NO-GRANT-20170405$$x1
000890024 7001_ $$0P:(DE-Juel1)174283$$aHehnen, Tristan$$b1
000890024 7001_ $$0P:(DE-HGF)0$$aTrettin, Corinna$$b2
000890024 7001_ $$0P:(DE-HGF)0$$aBrännström, Fabian$$b3
000890024 7001_ $$0P:(DE-Juel1)132044$$aArnold, Lukas$$b4$$eCorresponding author
000890024 8564_ $$uhttps://juser.fz-juelich.de/record/890024/files/2020_d3-13-lauer-paper.pdf$$yOpenAccess
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000890024 9141_ $$y2020
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