001     824688
005     20240711092256.0
024 7 _ |a 10.1016/j.calphad.2016.03.004
|2 doi
024 7 _ |a WOS:000377315100008
|2 WOS
037 _ _ |a FZJ-2016-07246
082 _ _ |a 540
100 1 _ |a Pillai, Rishi
|0 P:(DE-Juel1)156565
|b 0
|e Corresponding author
245 _ _ |a Methods to Increase Computtional Efficiency of CALPHAD-Based Thermodynamic and Kinetic Models Employed in Describing High Temperature Material Degradation
260 _ _ |a Amsterdam [u.a.]
|c 2016
|b Elsevier Science
336 7 _ |a article
|2 DRIVER
336 7 _ |a Output Types/Journal article
|2 DataCite
336 7 _ |a Journal Article
|b journal
|m journal
|0 PUB:(DE-HGF)16
|s 1481207879_21512
|2 PUB:(DE-HGF)
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a JOURNAL_ARTICLE
|2 ORCID
336 7 _ |a Journal Article
|0 0
|2 EndNote
520 _ _ |a Coupled thermodynamic and kinetic models rely on the thermodynamic and mobility databases which are compiled using critically assessed thermodynamic and diffusivity data acquired from various sources of experimental data. A continuous influx of experimental thermodynamic and kinetic data means that the respective databases have not only increased in complexity but also in size. The time and computational effort for the equilibrium calculations increases with increasing number of components and phases to be considered.In the present work, the applicability of a few methods was investigated to increase the computational efficiency of coupled thermodynamic and kinetic models. Three cases of varying complexities in terms of the number of phases, alloying elements and phenomena to be modelled were considered for demonstration. The distribution of the intensive thermodynamic calculations on multiple computing cores using MPI (Message Passing Interface) was undertaken. The interpolation scheme for dynamic storage of thermodynamic data available in the commercial software DICTRA was employed on a single computing core and the resulting performance was compared with the MPI computations. Additionally, the interpolation scheme was also parallelised to test its scaling capability in comparison to the computations performed solely with MPI.A linear scaling of computation speeds was observed with parallelisation of the thermodynamic calculations with MPI. However, the degree of scaling was dependent on the complexity of the calculation. The interpolation scheme on a single core in comparison with MPI on 48 cores was 20 times faster in one case but about 20–50 times slower in the other two cases. A parallelisation of the interpolation scheme improved its performance in the other two cases. However, the computational scaling was still poor compared to the MPI computations
536 _ _ |a 111 - Efficient and Flexible Power Plants (POF3-111)
|0 G:(DE-HGF)POF3-111
|c POF3-111
|f POF III
|x 0
536 _ _ |0 G:(DE-Juel1)HITEC-20170406
|x 1
|c HITEC-20170406
|a HITEC - Helmholtz Interdisciplinary Doctoral Training in Energy and Climate Research (HITEC) (HITEC-20170406)
700 1 _ |a Galiullin, Timur
|0 P:(DE-Juel1)162507
|b 1
700 1 _ |a Chyrkin, Anton
|0 P:(DE-Juel1)129701
|b 2
700 1 _ |a Quadakkers, Willem J.
|0 P:(DE-Juel1)129782
|b 3
773 _ _ |a 10.1016/j.calphad.2016.03.004
|0 PERI:(DE-600)1501512-9
|p 62-71
|t Calphad
|v 53
|y 2016
|x 0364-5916
856 4 _ |u https://juser.fz-juelich.de/record/824688/files/1-s2.0-S0364591616300244-main.pdf
|y Restricted
856 4 _ |x icon
|u https://juser.fz-juelich.de/record/824688/files/1-s2.0-S0364591616300244-main.gif?subformat=icon
|y Restricted
856 4 _ |x icon-1440
|u https://juser.fz-juelich.de/record/824688/files/1-s2.0-S0364591616300244-main.jpg?subformat=icon-1440
|y Restricted
856 4 _ |x icon-180
|u https://juser.fz-juelich.de/record/824688/files/1-s2.0-S0364591616300244-main.jpg?subformat=icon-180
|y Restricted
856 4 _ |x icon-640
|u https://juser.fz-juelich.de/record/824688/files/1-s2.0-S0364591616300244-main.jpg?subformat=icon-640
|y Restricted
856 4 _ |x pdfa
|u https://juser.fz-juelich.de/record/824688/files/1-s2.0-S0364591616300244-main.pdf?subformat=pdfa
|y Restricted
909 C O |o oai:juser.fz-juelich.de:824688
|p VDB
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 0
|6 P:(DE-Juel1)156565
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 1
|6 P:(DE-Juel1)162507
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 2
|6 P:(DE-Juel1)129701
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 3
|6 P:(DE-Juel1)129782
913 1 _ |a DE-HGF
|l Energieeffizienz, Materialien und Ressourcen
|1 G:(DE-HGF)POF3-110
|0 G:(DE-HGF)POF3-111
|2 G:(DE-HGF)POF3-100
|v Efficient and Flexible Power Plants
|x 0
|4 G:(DE-HGF)POF
|3 G:(DE-HGF)POF3
|b Energie
914 1 _ |y 2016
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1160
|2 StatID
|b Current Contents - Engineering, Computing and Technology
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0600
|2 StatID
|b Ebsco Academic Search
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b CALPHAD : 2015
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
915 _ _ |a WoS
|0 StatID:(DE-HGF)0110
|2 StatID
|b Science Citation Index
915 _ _ |a WoS
|0 StatID:(DE-HGF)0111
|2 StatID
|b Science Citation Index Expanded
915 _ _ |a IF < 5
|0 StatID:(DE-HGF)9900
|2 StatID
915 _ _ |a Peer Review
|0 StatID:(DE-HGF)0030
|2 StatID
|b ASC
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1150
|2 StatID
|b Current Contents - Physical, Chemical and Earth Sciences
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
915 _ _ |a No Authors Fulltext
|0 StatID:(DE-HGF)0550
|2 StatID
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Thomson Reuters Master Journal List
920 1 _ |0 I:(DE-Juel1)IEK-2-20101013
|k IEK-2
|l Werkstoffstruktur und -eigenschaften
|x 0
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a UNRESTRICTED
980 _ _ |a I:(DE-Juel1)IEK-2-20101013
981 _ _ |a I:(DE-Juel1)IMD-1-20101013


LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21