001     14723
005     20210129210614.0
024 7 _ |2 DOI
|a 10.1016/j.physleta.2011.01.015
024 7 _ |2 WOS
|a WOS:000287780300001
037 _ _ |a PreJuSER-14723
041 _ _ |a eng
082 _ _ |a 530
084 _ _ |2 WoS
|a Physics, Multidisciplinary
100 1 _ |a Lustfeld, H.
|b 0
|u FZJ
|0 P:(DE-Juel1)130810
245 _ _ |a Enhancement of precision and reduction of measuring points in tomographic reconstructions
260 _ _ |a Amsterdam
|b North-Holland Publ.
|c 2011
300 _ _ |a 1167 - 1171
336 7 _ |a Journal Article
|0 PUB:(DE-HGF)16
|2 PUB:(DE-HGF)
336 7 _ |a Output Types/Journal article
|2 DataCite
336 7 _ |a Journal Article
|0 0
|2 EndNote
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a JOURNAL_ARTICLE
|2 ORCID
336 7 _ |a article
|2 DRIVER
440 _ 0 |a Physics Letters A
|x 0375-9601
|0 4933
|y 8
|v 375
500 _ _ |a Record converted from VDB: 12.11.2012
520 _ _ |a Accurate external measurements are required in tomographic problems to obtain a reasonable knowledge of the internal structures. Crucial is the distribution of the external measuring points. We suggest a procedure how to systematically optimize this distribution viz, to increase the precision (i.e. to shrink error bars) of the reconstruction by detecting the important and by eliminating the irrelevant measuring points. In a realistic numerical example we apply our scheme to magnetotomography of fuel cells. The result is striking: Starting from a smooth distribution of measuring points on a surface of a cuboid around the fuel cell, the number of measuring points can systematically be reduced by more than 90%. At the same time the precision increases by a factor of nearly 3. (C) 2011 Elsevier B.V. All rights reserved.
536 _ _ |2 G:(DE-HGF)
|0 G:(DE-Juel1)FUEK412
|x 0
|c FUEK412
|a Grundlagen für zukünftige Informationstechnologien (FUEK412)
536 _ _ |0 G:(DE-Juel1)FUEK411
|x 1
|c FUEK411
|a Scientific Computing (FUEK411)
536 _ _ |a 411 - Computational Science and Mathematical Methods (POF2-411)
|0 G:(DE-HGF)POF2-411
|c POF2-411
|x 2
|f POF II
588 _ _ |a Dataset connected to Web of Science
650 _ 7 |a J
|2 WoSType
653 2 0 |2 Author
|a Inverse problems
653 2 0 |2 Author
|a Image reconstruction
653 2 0 |2 Author
|a Fuel cells
700 1 _ |a Hirschfeld, J. A.
|b 1
|u FZJ
|0 P:(DE-Juel1)130713
700 1 _ |a Reißel, M.
|b 2
|0 P:(DE-HGF)0
700 1 _ |a Steffen, B.
|b 3
|u FZJ
|0 P:(DE-Juel1)132269
773 _ _ |a 10.1016/j.physleta.2011.01.015
|g Vol. 375, p. 1167 - 1171
|p 1167 - 1171
|q 375<1167 - 1171
|0 PERI:(DE-600)1466603-0
|t Physics letters / A
|v 375
|y 2011
|x 0375-9601
856 7 _ |u http://dx.doi.org/10.1016/j.physleta.2011.01.015
909 C O |o oai:juser.fz-juelich.de:14723
|p VDB
913 2 _ |a DE-HGF
|b Key Technologies
|l Supercomputing & Big Data
|1 G:(DE-HGF)POF3-510
|0 G:(DE-HGF)POF3-511
|2 G:(DE-HGF)POF3-500
|v Computational Science and Mathematical Methods
|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
|x 2
|4 G:(DE-HGF)POF
|3 G:(DE-HGF)POF2
914 1 _ |a FE-Bereich
|y 2011
915 _ _ |0 StatID:(DE-HGF)0010
|a JCR/ISI refereed
920 1 _ |k PGI-1
|l Quanten-Theorie der Materialien
|g PGI
|0 I:(DE-Juel1)PGI-1-20110106
|x 0
920 1 _ |k IAS-1
|l Quanten-Theorie der Materialien
|g IAS
|z IFF-1
|0 I:(DE-Juel1)IAS-1-20090406
|x 1
920 1 _ |k JSC
|l Jülich Supercomputing Centre
|g JSC
|0 I:(DE-Juel1)JSC-20090406
|x 2
970 _ _ |a VDB:(DE-Juel1)127103
980 _ _ |a VDB
980 _ _ |a ConvertedRecord
980 _ _ |a journal
980 _ _ |a I:(DE-Juel1)PGI-1-20110106
980 _ _ |a I:(DE-Juel1)IAS-1-20090406
980 _ _ |a I:(DE-Juel1)JSC-20090406
980 _ _ |a UNRESTRICTED
981 _ _ |a I:(DE-Juel1)IAS-1-20090406
981 _ _ |a I:(DE-Juel1)JSC-20090406


LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21