Study of the approximate approaches to the POD based spectral representation method

Abstract The spectral representation method (SRM) is most widely used in simulating the stochastic field. The proper orthogonal decomposition (POD) based SRM is an important form. This paper investigates the approximate approaches to the POD-based SRM in simulating two typical problems, i.e., the se...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Wu, YongXin [verfasserIn] Gao, YuFeng [verfasserIn] Li, DaYong [verfasserIn] Xu, ChangJie [verfasserIn] Mahfouz, Ali Hasson [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2013

Schlagwörter:	stochastic field simulation coherency matrix based spectral representation method proper orthogonal decomposition approximation

Übergeordnetes Werk:	Enthalten in: Science in China - Heidelberg : Springer, 1997, 56(2013), 4 vom: 05. März, Seite 970-979
Übergeordnetes Werk:	volume:56 ; year:2013 ; number:4 ; day:05 ; month:03 ; pages:970-979

Links:	Volltext

DOI / URN:	10.1007/s11431-013-5180-y

Katalog-ID:	SPR019279817

Internformat


LEADER	01000caa a22002652 4500
001	SPR019279817
003	DE-627
005	20220111065423.0
007	cr uuu---uuuuu
008	201006s2013 xx \|\|\|\|\|o 00\| \|\|eng c
024	7		\|a 10.1007/s11431-013-5180-y \|2 doi
035			\|a (DE-627)SPR019279817
035			\|a (SPR)s11431-013-5180-y-e
040			\|a DE-627 \|b ger \|c DE-627 \|e rakwb
041			\|a eng
082	0	4	\|a 600 \|q ASE
082	0	4	\|a 600 \|q ASE
084			\|a 50.00 \|2 bkl
100	1		\|a Wu, YongXin \|e verfasserin \|4 aut
245	1	0	\|a Study of the approximate approaches to the POD based spectral representation method
264		1	\|c 2013
336			\|a Text \|b txt \|2 rdacontent
337			\|a Computermedien \|b c \|2 rdamedia
338			\|a Online-Ressource \|b cr \|2 rdacarrier
520			\|a Abstract The spectral representation method (SRM) is most widely used in simulating the stochastic field. The proper orthogonal decomposition (POD) based SRM is an important form. This paper investigates the approximate approaches to the POD-based SRM in simulating two typical problems, i.e., the seismic ground motion and wind velocity fields simulations. Then, the accuracy resulting from the power spectral density matrix-based POD method (PSRM) is compared to that of the coherency matrix-based POD method (CPSRM). It is concluded that the CPSRM maintains a much higher accuracy than the PSRM. In the CPSRM, the linear interpolation of eigenvectors and third-order polynomial interpolation of eigenvalues can be accepted to attain high accuracy; the linearly distributed interpolation nodes are effective in the ground motions simulation; however, the exponentially distributed interpolation nodes are effective in the wind velocity simulation.
650		4	\|a stochastic field simulation \|7 (dpeaa)DE-He213
650		4	\|a coherency matrix based \|7 (dpeaa)DE-He213
650		4	\|a spectral representation method \|7 (dpeaa)DE-He213
650		4	\|a proper orthogonal decomposition \|7 (dpeaa)DE-He213
650		4	\|a approximation \|7 (dpeaa)DE-He213
700	1		\|a Gao, YuFeng \|e verfasserin \|4 aut
700	1		\|a Li, DaYong \|e verfasserin \|4 aut
700	1		\|a Xu, ChangJie \|e verfasserin \|4 aut
700	1		\|a Mahfouz, Ali Hasson \|e verfasserin \|4 aut
773	0	8	\|i Enthalten in \|t Science in China \|d Heidelberg : Springer, 1997 \|g 56(2013), 4 vom: 05. März, Seite 970-979 \|w (DE-627)385614756 \|w (DE-600)2142897-9 \|x 1862-281X \|7 nnns
773	1	8	\|g volume:56 \|g year:2013 \|g number:4 \|g day:05 \|g month:03 \|g pages:970-979
856	4	0	\|u https://dx.doi.org/10.1007/s11431-013-5180-y \|z lizenzpflichtig \|3 Volltext
912			\|a GBV_USEFLAG_A
912			\|a SYSFLAG_A
912			\|a GBV_SPRINGER
912			\|a GBV_ILN_20
912			\|a GBV_ILN_22
912			\|a GBV_ILN_23
912			\|a GBV_ILN_24
912			\|a GBV_ILN_31
912			\|a GBV_ILN_32
912			\|a GBV_ILN_39
912			\|a GBV_ILN_40
912			\|a GBV_ILN_60
912			\|a GBV_ILN_62
912			\|a GBV_ILN_65
912			\|a GBV_ILN_69
912			\|a GBV_ILN_70
912			\|a GBV_ILN_73
912			\|a GBV_ILN_74
912			\|a GBV_ILN_90
912			\|a GBV_ILN_95
912			\|a GBV_ILN_100
912			\|a GBV_ILN_105
912			\|a GBV_ILN_110
912			\|a GBV_ILN_120
912			\|a GBV_ILN_138
912			\|a GBV_ILN_152
912			\|a GBV_ILN_161
912			\|a GBV_ILN_171
912			\|a GBV_ILN_187
912			\|a GBV_ILN_224
912			\|a GBV_ILN_250
912			\|a GBV_ILN_281
912			\|a GBV_ILN_285
912			\|a GBV_ILN_293
912			\|a GBV_ILN_370
912			\|a GBV_ILN_602
912			\|a GBV_ILN_702
936	b	k	\|a 50.00 \|q ASE
951			\|a AR
952			\|d 56 \|j 2013 \|e 4 \|b 05 \|c 03 \|h 970-979

Indexfelder

author_variant	y w yw y g yg d l dl c x cx a h m ah ahm
matchkey_str	article:1862281X:2013----::tdoteprxmtapocetteobsdpcrle
hierarchy_sort_str	2013
bklnumber	50.00
publishDate	2013
allfields	10.1007/s11431-013-5180-y doi (DE-627)SPR019279817 (SPR)s11431-013-5180-y-e DE-627 ger DE-627 rakwb eng 600 ASE 600 ASE 50.00 bkl Wu, YongXin verfasserin aut Study of the approximate approaches to the POD based spectral representation method 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The spectral representation method (SRM) is most widely used in simulating the stochastic field. The proper orthogonal decomposition (POD) based SRM is an important form. This paper investigates the approximate approaches to the POD-based SRM in simulating two typical problems, i.e., the seismic ground motion and wind velocity fields simulations. Then, the accuracy resulting from the power spectral density matrix-based POD method (PSRM) is compared to that of the coherency matrix-based POD method (CPSRM). It is concluded that the CPSRM maintains a much higher accuracy than the PSRM. In the CPSRM, the linear interpolation of eigenvectors and third-order polynomial interpolation of eigenvalues can be accepted to attain high accuracy; the linearly distributed interpolation nodes are effective in the ground motions simulation; however, the exponentially distributed interpolation nodes are effective in the wind velocity simulation. stochastic field simulation (dpeaa)DE-He213 coherency matrix based (dpeaa)DE-He213 spectral representation method (dpeaa)DE-He213 proper orthogonal decomposition (dpeaa)DE-He213 approximation (dpeaa)DE-He213 Gao, YuFeng verfasserin aut Li, DaYong verfasserin aut Xu, ChangJie verfasserin aut Mahfouz, Ali Hasson verfasserin aut Enthalten in Science in China Heidelberg : Springer, 1997 56(2013), 4 vom: 05. März, Seite 970-979 (DE-627)385614756 (DE-600)2142897-9 1862-281X nnns volume:56 year:2013 number:4 day:05 month:03 pages:970-979 https://dx.doi.org/10.1007/s11431-013-5180-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 50.00 ASE AR 56 2013 4 05 03 970-979
spelling	10.1007/s11431-013-5180-y doi (DE-627)SPR019279817 (SPR)s11431-013-5180-y-e DE-627 ger DE-627 rakwb eng 600 ASE 600 ASE 50.00 bkl Wu, YongXin verfasserin aut Study of the approximate approaches to the POD based spectral representation method 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The spectral representation method (SRM) is most widely used in simulating the stochastic field. The proper orthogonal decomposition (POD) based SRM is an important form. This paper investigates the approximate approaches to the POD-based SRM in simulating two typical problems, i.e., the seismic ground motion and wind velocity fields simulations. Then, the accuracy resulting from the power spectral density matrix-based POD method (PSRM) is compared to that of the coherency matrix-based POD method (CPSRM). It is concluded that the CPSRM maintains a much higher accuracy than the PSRM. In the CPSRM, the linear interpolation of eigenvectors and third-order polynomial interpolation of eigenvalues can be accepted to attain high accuracy; the linearly distributed interpolation nodes are effective in the ground motions simulation; however, the exponentially distributed interpolation nodes are effective in the wind velocity simulation. stochastic field simulation (dpeaa)DE-He213 coherency matrix based (dpeaa)DE-He213 spectral representation method (dpeaa)DE-He213 proper orthogonal decomposition (dpeaa)DE-He213 approximation (dpeaa)DE-He213 Gao, YuFeng verfasserin aut Li, DaYong verfasserin aut Xu, ChangJie verfasserin aut Mahfouz, Ali Hasson verfasserin aut Enthalten in Science in China Heidelberg : Springer, 1997 56(2013), 4 vom: 05. März, Seite 970-979 (DE-627)385614756 (DE-600)2142897-9 1862-281X nnns volume:56 year:2013 number:4 day:05 month:03 pages:970-979 https://dx.doi.org/10.1007/s11431-013-5180-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 50.00 ASE AR 56 2013 4 05 03 970-979
allfields_unstemmed	10.1007/s11431-013-5180-y doi (DE-627)SPR019279817 (SPR)s11431-013-5180-y-e DE-627 ger DE-627 rakwb eng 600 ASE 600 ASE 50.00 bkl Wu, YongXin verfasserin aut Study of the approximate approaches to the POD based spectral representation method 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The spectral representation method (SRM) is most widely used in simulating the stochastic field. The proper orthogonal decomposition (POD) based SRM is an important form. This paper investigates the approximate approaches to the POD-based SRM in simulating two typical problems, i.e., the seismic ground motion and wind velocity fields simulations. Then, the accuracy resulting from the power spectral density matrix-based POD method (PSRM) is compared to that of the coherency matrix-based POD method (CPSRM). It is concluded that the CPSRM maintains a much higher accuracy than the PSRM. In the CPSRM, the linear interpolation of eigenvectors and third-order polynomial interpolation of eigenvalues can be accepted to attain high accuracy; the linearly distributed interpolation nodes are effective in the ground motions simulation; however, the exponentially distributed interpolation nodes are effective in the wind velocity simulation. stochastic field simulation (dpeaa)DE-He213 coherency matrix based (dpeaa)DE-He213 spectral representation method (dpeaa)DE-He213 proper orthogonal decomposition (dpeaa)DE-He213 approximation (dpeaa)DE-He213 Gao, YuFeng verfasserin aut Li, DaYong verfasserin aut Xu, ChangJie verfasserin aut Mahfouz, Ali Hasson verfasserin aut Enthalten in Science in China Heidelberg : Springer, 1997 56(2013), 4 vom: 05. März, Seite 970-979 (DE-627)385614756 (DE-600)2142897-9 1862-281X nnns volume:56 year:2013 number:4 day:05 month:03 pages:970-979 https://dx.doi.org/10.1007/s11431-013-5180-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 50.00 ASE AR 56 2013 4 05 03 970-979
allfieldsGer	10.1007/s11431-013-5180-y doi (DE-627)SPR019279817 (SPR)s11431-013-5180-y-e DE-627 ger DE-627 rakwb eng 600 ASE 600 ASE 50.00 bkl Wu, YongXin verfasserin aut Study of the approximate approaches to the POD based spectral representation method 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The spectral representation method (SRM) is most widely used in simulating the stochastic field. The proper orthogonal decomposition (POD) based SRM is an important form. This paper investigates the approximate approaches to the POD-based SRM in simulating two typical problems, i.e., the seismic ground motion and wind velocity fields simulations. Then, the accuracy resulting from the power spectral density matrix-based POD method (PSRM) is compared to that of the coherency matrix-based POD method (CPSRM). It is concluded that the CPSRM maintains a much higher accuracy than the PSRM. In the CPSRM, the linear interpolation of eigenvectors and third-order polynomial interpolation of eigenvalues can be accepted to attain high accuracy; the linearly distributed interpolation nodes are effective in the ground motions simulation; however, the exponentially distributed interpolation nodes are effective in the wind velocity simulation. stochastic field simulation (dpeaa)DE-He213 coherency matrix based (dpeaa)DE-He213 spectral representation method (dpeaa)DE-He213 proper orthogonal decomposition (dpeaa)DE-He213 approximation (dpeaa)DE-He213 Gao, YuFeng verfasserin aut Li, DaYong verfasserin aut Xu, ChangJie verfasserin aut Mahfouz, Ali Hasson verfasserin aut Enthalten in Science in China Heidelberg : Springer, 1997 56(2013), 4 vom: 05. März, Seite 970-979 (DE-627)385614756 (DE-600)2142897-9 1862-281X nnns volume:56 year:2013 number:4 day:05 month:03 pages:970-979 https://dx.doi.org/10.1007/s11431-013-5180-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 50.00 ASE AR 56 2013 4 05 03 970-979
allfieldsSound	10.1007/s11431-013-5180-y doi (DE-627)SPR019279817 (SPR)s11431-013-5180-y-e DE-627 ger DE-627 rakwb eng 600 ASE 600 ASE 50.00 bkl Wu, YongXin verfasserin aut Study of the approximate approaches to the POD based spectral representation method 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The spectral representation method (SRM) is most widely used in simulating the stochastic field. The proper orthogonal decomposition (POD) based SRM is an important form. This paper investigates the approximate approaches to the POD-based SRM in simulating two typical problems, i.e., the seismic ground motion and wind velocity fields simulations. Then, the accuracy resulting from the power spectral density matrix-based POD method (PSRM) is compared to that of the coherency matrix-based POD method (CPSRM). It is concluded that the CPSRM maintains a much higher accuracy than the PSRM. In the CPSRM, the linear interpolation of eigenvectors and third-order polynomial interpolation of eigenvalues can be accepted to attain high accuracy; the linearly distributed interpolation nodes are effective in the ground motions simulation; however, the exponentially distributed interpolation nodes are effective in the wind velocity simulation. stochastic field simulation (dpeaa)DE-He213 coherency matrix based (dpeaa)DE-He213 spectral representation method (dpeaa)DE-He213 proper orthogonal decomposition (dpeaa)DE-He213 approximation (dpeaa)DE-He213 Gao, YuFeng verfasserin aut Li, DaYong verfasserin aut Xu, ChangJie verfasserin aut Mahfouz, Ali Hasson verfasserin aut Enthalten in Science in China Heidelberg : Springer, 1997 56(2013), 4 vom: 05. März, Seite 970-979 (DE-627)385614756 (DE-600)2142897-9 1862-281X nnns volume:56 year:2013 number:4 day:05 month:03 pages:970-979 https://dx.doi.org/10.1007/s11431-013-5180-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 50.00 ASE AR 56 2013 4 05 03 970-979
language	English
source	Enthalten in Science in China 56(2013), 4 vom: 05. März, Seite 970-979 volume:56 year:2013 number:4 day:05 month:03 pages:970-979
sourceStr	Enthalten in Science in China 56(2013), 4 vom: 05. März, Seite 970-979 volume:56 year:2013 number:4 day:05 month:03 pages:970-979
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	stochastic field simulation coherency matrix based spectral representation method proper orthogonal decomposition approximation
dewey-raw	600
isfreeaccess_bool	false
container_title	Science in China
authorswithroles_txt_mv	Wu, YongXin @@aut@@ Gao, YuFeng @@aut@@ Li, DaYong @@aut@@ Xu, ChangJie @@aut@@ Mahfouz, Ali Hasson @@aut@@
publishDateDaySort_date	2013-03-05T00:00:00Z
hierarchy_top_id	385614756
dewey-sort	3600
id	SPR019279817
language_de	englisch
fullrecord	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">SPR019279817</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20220111065423.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">201006s2013 xx \|\|\|\|\|o 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s11431-013-5180-y</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR019279817</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s11431-013-5180-y-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">600</subfield><subfield code="q">ASE</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">600</subfield><subfield code="q">ASE</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">50.00</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Wu, YongXin</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Study of the approximate approaches to the POD based spectral representation method</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2013</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract The spectral representation method (SRM) is most widely used in simulating the stochastic field. The proper orthogonal decomposition (POD) based SRM is an important form. This paper investigates the approximate approaches to the POD-based SRM in simulating two typical problems, i.e., the seismic ground motion and wind velocity fields simulations. Then, the accuracy resulting from the power spectral density matrix-based POD method (PSRM) is compared to that of the coherency matrix-based POD method (CPSRM). It is concluded that the CPSRM maintains a much higher accuracy than the PSRM. In the CPSRM, the linear interpolation of eigenvectors and third-order polynomial interpolation of eigenvalues can be accepted to attain high accuracy; the linearly distributed interpolation nodes are effective in the ground motions simulation; however, the exponentially distributed interpolation nodes are effective in the wind velocity simulation.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">stochastic field simulation</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">coherency matrix based</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">spectral representation method</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">proper orthogonal decomposition</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">approximation</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Gao, YuFeng</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Li, DaYong</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Xu, ChangJie</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Mahfouz, Ali Hasson</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Science in China</subfield><subfield code="d">Heidelberg : Springer, 1997</subfield><subfield code="g">56(2013), 4 vom: 05. März, Seite 970-979</subfield><subfield code="w">(DE-627)385614756</subfield><subfield code="w">(DE-600)2142897-9</subfield><subfield code="x">1862-281X</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:56</subfield><subfield code="g">year:2013</subfield><subfield code="g">number:4</subfield><subfield code="g">day:05</subfield><subfield code="g">month:03</subfield><subfield code="g">pages:970-979</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://dx.doi.org/10.1007/s11431-013-5180-y</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_SPRINGER</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_23</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_31</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_32</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_39</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_60</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_62</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_74</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_90</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_100</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_105</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_120</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_138</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_152</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_161</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_171</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_187</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_224</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_250</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_281</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_285</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_293</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_370</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_602</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_702</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">50.00</subfield><subfield code="q">ASE</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">56</subfield><subfield code="j">2013</subfield><subfield code="e">4</subfield><subfield code="b">05</subfield><subfield code="c">03</subfield><subfield code="h">970-979</subfield></datafield></record></collection>
author	Wu, YongXin
spellingShingle	Wu, YongXin ddc 600 bkl 50.00 misc stochastic field simulation misc coherency matrix based misc spectral representation method misc proper orthogonal decomposition misc approximation Study of the approximate approaches to the POD based spectral representation method
authorStr	Wu, YongXin
ppnlink_with_tag_str_mv	@@773@@(DE-627)385614756
format	electronic Article
dewey-ones	600 - Technology
delete_txt_mv	keep
author_role	aut aut aut aut aut
collection	springer
remote_str	true
illustrated	Not Illustrated
issn	1862-281X
topic_title	600 ASE 50.00 bkl Study of the approximate approaches to the POD based spectral representation method stochastic field simulation (dpeaa)DE-He213 coherency matrix based (dpeaa)DE-He213 spectral representation method (dpeaa)DE-He213 proper orthogonal decomposition (dpeaa)DE-He213 approximation (dpeaa)DE-He213
topic	ddc 600 bkl 50.00 misc stochastic field simulation misc coherency matrix based misc spectral representation method misc proper orthogonal decomposition misc approximation
topic_unstemmed	ddc 600 bkl 50.00 misc stochastic field simulation misc coherency matrix based misc spectral representation method misc proper orthogonal decomposition misc approximation
topic_browse	ddc 600 bkl 50.00 misc stochastic field simulation misc coherency matrix based misc spectral representation method misc proper orthogonal decomposition misc approximation
format_facet	Elektronische Aufsätze Aufsätze Elektronische Ressource
format_main_str_mv	Text Zeitschrift/Artikel
carriertype_str_mv	cr
hierarchy_parent_title	Science in China
hierarchy_parent_id	385614756
dewey-tens	600 - Technology
hierarchy_top_title	Science in China
isfreeaccess_txt	false
familylinks_str_mv	(DE-627)385614756 (DE-600)2142897-9
title	Study of the approximate approaches to the POD based spectral representation method
ctrlnum	(DE-627)SPR019279817 (SPR)s11431-013-5180-y-e
title_full	Study of the approximate approaches to the POD based spectral representation method
author_sort	Wu, YongXin
journal	Science in China
journalStr	Science in China
lang_code	eng
isOA_bool	false
dewey-hundreds	600 - Technology
recordtype	marc
publishDateSort	2013
contenttype_str_mv	txt
container_start_page	970
author_browse	Wu, YongXin Gao, YuFeng Li, DaYong Xu, ChangJie Mahfouz, Ali Hasson
container_volume	56
class	600 ASE 50.00 bkl
format_se	Elektronische Aufsätze
author-letter	Wu, YongXin
doi_str_mv	10.1007/s11431-013-5180-y
dewey-full	600
author2-role	verfasserin
title_sort	study of the approximate approaches to the pod based spectral representation method
title_auth	Study of the approximate approaches to the POD based spectral representation method
abstract	Abstract The spectral representation method (SRM) is most widely used in simulating the stochastic field. The proper orthogonal decomposition (POD) based SRM is an important form. This paper investigates the approximate approaches to the POD-based SRM in simulating two typical problems, i.e., the seismic ground motion and wind velocity fields simulations. Then, the accuracy resulting from the power spectral density matrix-based POD method (PSRM) is compared to that of the coherency matrix-based POD method (CPSRM). It is concluded that the CPSRM maintains a much higher accuracy than the PSRM. In the CPSRM, the linear interpolation of eigenvectors and third-order polynomial interpolation of eigenvalues can be accepted to attain high accuracy; the linearly distributed interpolation nodes are effective in the ground motions simulation; however, the exponentially distributed interpolation nodes are effective in the wind velocity simulation.
abstractGer	Abstract The spectral representation method (SRM) is most widely used in simulating the stochastic field. The proper orthogonal decomposition (POD) based SRM is an important form. This paper investigates the approximate approaches to the POD-based SRM in simulating two typical problems, i.e., the seismic ground motion and wind velocity fields simulations. Then, the accuracy resulting from the power spectral density matrix-based POD method (PSRM) is compared to that of the coherency matrix-based POD method (CPSRM). It is concluded that the CPSRM maintains a much higher accuracy than the PSRM. In the CPSRM, the linear interpolation of eigenvectors and third-order polynomial interpolation of eigenvalues can be accepted to attain high accuracy; the linearly distributed interpolation nodes are effective in the ground motions simulation; however, the exponentially distributed interpolation nodes are effective in the wind velocity simulation.
abstract_unstemmed	Abstract The spectral representation method (SRM) is most widely used in simulating the stochastic field. The proper orthogonal decomposition (POD) based SRM is an important form. This paper investigates the approximate approaches to the POD-based SRM in simulating two typical problems, i.e., the seismic ground motion and wind velocity fields simulations. Then, the accuracy resulting from the power spectral density matrix-based POD method (PSRM) is compared to that of the coherency matrix-based POD method (CPSRM). It is concluded that the CPSRM maintains a much higher accuracy than the PSRM. In the CPSRM, the linear interpolation of eigenvectors and third-order polynomial interpolation of eigenvalues can be accepted to attain high accuracy; the linearly distributed interpolation nodes are effective in the ground motions simulation; however, the exponentially distributed interpolation nodes are effective in the wind velocity simulation.
collection_details	GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702
container_issue	4
title_short	Study of the approximate approaches to the POD based spectral representation method
url	https://dx.doi.org/10.1007/s11431-013-5180-y
remote_bool	true
author2	Gao, YuFeng Li, DaYong Xu, ChangJie Mahfouz, Ali Hasson
author2Str	Gao, YuFeng Li, DaYong Xu, ChangJie Mahfouz, Ali Hasson
ppnlink	385614756
mediatype_str_mv	c
isOA_txt	false
hochschulschrift_bool	false
doi_str	10.1007/s11431-013-5180-y
up_date	2024-07-04T00:56:29.343Z
_version_	1803607961077022720
fullrecord_marcxml	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">SPR019279817</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20220111065423.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">201006s2013 xx \|\|\|\|\|o 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s11431-013-5180-y</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR019279817</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s11431-013-5180-y-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">600</subfield><subfield code="q">ASE</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">600</subfield><subfield code="q">ASE</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">50.00</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Wu, YongXin</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Study of the approximate approaches to the POD based spectral representation method</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2013</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract The spectral representation method (SRM) is most widely used in simulating the stochastic field. The proper orthogonal decomposition (POD) based SRM is an important form. This paper investigates the approximate approaches to the POD-based SRM in simulating two typical problems, i.e., the seismic ground motion and wind velocity fields simulations. Then, the accuracy resulting from the power spectral density matrix-based POD method (PSRM) is compared to that of the coherency matrix-based POD method (CPSRM). It is concluded that the CPSRM maintains a much higher accuracy than the PSRM. In the CPSRM, the linear interpolation of eigenvectors and third-order polynomial interpolation of eigenvalues can be accepted to attain high accuracy; the linearly distributed interpolation nodes are effective in the ground motions simulation; however, the exponentially distributed interpolation nodes are effective in the wind velocity simulation.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">stochastic field simulation</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">coherency matrix based</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">spectral representation method</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">proper orthogonal decomposition</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">approximation</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Gao, YuFeng</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Li, DaYong</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Xu, ChangJie</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Mahfouz, Ali Hasson</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Science in China</subfield><subfield code="d">Heidelberg : Springer, 1997</subfield><subfield code="g">56(2013), 4 vom: 05. März, Seite 970-979</subfield><subfield code="w">(DE-627)385614756</subfield><subfield code="w">(DE-600)2142897-9</subfield><subfield code="x">1862-281X</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:56</subfield><subfield code="g">year:2013</subfield><subfield code="g">number:4</subfield><subfield code="g">day:05</subfield><subfield code="g">month:03</subfield><subfield code="g">pages:970-979</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://dx.doi.org/10.1007/s11431-013-5180-y</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_SPRINGER</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_23</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_31</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_32</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_39</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_60</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_62</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_74</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_90</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_100</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_105</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_120</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_138</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_152</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_161</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_171</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_187</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_224</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_250</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_281</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_285</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_293</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_370</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_602</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_702</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">50.00</subfield><subfield code="q">ASE</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">56</subfield><subfield code="j">2013</subfield><subfield code="e">4</subfield><subfield code="b">05</subfield><subfield code="c">03</subfield><subfield code="h">970-979</subfield></datafield></record></collection>
score	7.402466

Nicht das Richtige dabei?

Schreiben Sie uns!

Study of the approximate approaches to the POD based spectral representation method

Nicht das Richtige dabei?

Zugang & Verfügbarkeit

Vorhandene Bände

Nicht das Richtige dabei?