A new three-phase algorithm for computation of reliability index and its application in structural mechanics

Computation of reliability index or probability of failure in practical problems is still a challenge. In this paper, an efficient three-phase non-gradient-based algorithm is proposed to be used in structural reliability analysis. Like approximation methods, the purpose in the proposed algorithm is...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Roudak, Mohammad Amin [verfasserIn] Shayanfar, Mohsen Ali [verfasserIn] Barkhordari, Mohammad Ali [verfasserIn] Karamloo, Mohammad [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2017

Schlagwörter:	Reliability index Probability of failure Design point Fitness function Adjusting constant

Übergeordnetes Werk:	Enthalten in: Mechanics research communications - Amsterdam [u.a.] : Elsevier, 1974, 85, Seite 53-60
Übergeordnetes Werk:	volume:85 ; pages:53-60

DOI / URN:	10.1016/j.mechrescom.2017.08.008

Katalog-ID:	ELV000708178

Internformat


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100	1		\|a Roudak, Mohammad Amin \|e verfasserin \|4 aut
245	1	0	\|a A new three-phase algorithm for computation of reliability index and its application in structural mechanics
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520			\|a Computation of reliability index or probability of failure in practical problems is still a challenge. In this paper, an efficient three-phase non-gradient-based algorithm is proposed to be used in structural reliability analysis. Like approximation methods, the purpose in the proposed algorithm is to locate the position of design point. However, for this purpose, at the iterations of the phases random samples are generated based on a moving sampling density function, like what is done in adaptive importance sampling. At each phase, by representing an updating criterion, the position of the candidate of design point is updated to approach the real design point. Two criteria of the first and second phase are to reduce the initial relatively large distance between the candidate of design point and the real one. In the third phase, after introducing a new effective fitness function, the third updating criterion is represented to take the final smaller steps of approaching design point. Through various numerical examples, the accuracy and efficiency of three aforementioned phases have been shown.
650		4	\|a Reliability index
650		4	\|a Probability of failure
650		4	\|a Design point
650		4	\|a Fitness function
650		4	\|a Adjusting constant
700	1		\|a Shayanfar, Mohsen Ali \|e verfasserin \|4 aut
700	1		\|a Barkhordari, Mohammad Ali \|e verfasserin \|4 aut
700	1		\|a Karamloo, Mohammad \|e verfasserin \|4 aut
773	0	8	\|i Enthalten in \|t Mechanics research communications \|d Amsterdam [u.a.] : Elsevier, 1974 \|g 85, Seite 53-60 \|h Online-Ressource \|w (DE-627)319950131 \|w (DE-600)2013977-9 \|w (DE-576)259484822 \|x 1873-3972 \|7 nnns
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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_150
912			\|a GBV_ILN_151
912			\|a GBV_ILN_187
912			\|a GBV_ILN_224
912			\|a GBV_ILN_370
912			\|a GBV_ILN_602
912			\|a GBV_ILN_702
912			\|a GBV_ILN_2001
912			\|a GBV_ILN_2003
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912			\|a GBV_ILN_2048
912			\|a GBV_ILN_2049
912			\|a GBV_ILN_2050
912			\|a GBV_ILN_2055
912			\|a GBV_ILN_2056
912			\|a GBV_ILN_2059
912			\|a GBV_ILN_2061
912			\|a GBV_ILN_2064
912			\|a GBV_ILN_2065
912			\|a GBV_ILN_2068
912			\|a GBV_ILN_2088
912			\|a GBV_ILN_2111
912			\|a GBV_ILN_2112
912			\|a GBV_ILN_2113
912			\|a GBV_ILN_2118
912			\|a GBV_ILN_2122
912			\|a GBV_ILN_2129
912			\|a GBV_ILN_2143
912			\|a GBV_ILN_2147
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912			\|a GBV_ILN_2152
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912			\|a GBV_ILN_4323
912			\|a GBV_ILN_4324
912			\|a GBV_ILN_4325
912			\|a GBV_ILN_4326
912			\|a GBV_ILN_4333
912			\|a GBV_ILN_4334
912			\|a GBV_ILN_4335
912			\|a GBV_ILN_4338
912			\|a GBV_ILN_4393
936	b	k	\|a 50.31 \|j Technische Mechanik
936	b	k	\|a 50.33 \|j Technische Strömungsmechanik
936	b	k	\|a 51.32 \|j Werkstoffmechanik
951			\|a AR
952			\|d 85 \|h 53-60

Indexfelder

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publishDate	2017
allfields	10.1016/j.mechrescom.2017.08.008 doi (DE-627)ELV000708178 (ELSEVIER)S0093-6413(17)30250-1 DE-627 ger DE-627 rda eng 670 DE-600 50.31 bkl 50.33 bkl 51.32 bkl Roudak, Mohammad Amin verfasserin aut A new three-phase algorithm for computation of reliability index and its application in structural mechanics 2017 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Computation of reliability index or probability of failure in practical problems is still a challenge. In this paper, an efficient three-phase non-gradient-based algorithm is proposed to be used in structural reliability analysis. Like approximation methods, the purpose in the proposed algorithm is to locate the position of design point. However, for this purpose, at the iterations of the phases random samples are generated based on a moving sampling density function, like what is done in adaptive importance sampling. At each phase, by representing an updating criterion, the position of the candidate of design point is updated to approach the real design point. Two criteria of the first and second phase are to reduce the initial relatively large distance between the candidate of design point and the real one. In the third phase, after introducing a new effective fitness function, the third updating criterion is represented to take the final smaller steps of approaching design point. Through various numerical examples, the accuracy and efficiency of three aforementioned phases have been shown. Reliability index Probability of failure Design point Fitness function Adjusting constant Shayanfar, Mohsen Ali verfasserin aut Barkhordari, Mohammad Ali verfasserin aut Karamloo, Mohammad verfasserin aut Enthalten in Mechanics research communications Amsterdam [u.a.] : Elsevier, 1974 85, Seite 53-60 Online-Ressource (DE-627)319950131 (DE-600)2013977-9 (DE-576)259484822 1873-3972 nnns volume:85 pages:53-60 GBV_USEFLAG_U SYSFLAG_U GBV_ELV GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 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_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 50.31 Technische Mechanik 50.33 Technische Strömungsmechanik 51.32 Werkstoffmechanik AR 85 53-60
spelling	10.1016/j.mechrescom.2017.08.008 doi (DE-627)ELV000708178 (ELSEVIER)S0093-6413(17)30250-1 DE-627 ger DE-627 rda eng 670 DE-600 50.31 bkl 50.33 bkl 51.32 bkl Roudak, Mohammad Amin verfasserin aut A new three-phase algorithm for computation of reliability index and its application in structural mechanics 2017 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Computation of reliability index or probability of failure in practical problems is still a challenge. In this paper, an efficient three-phase non-gradient-based algorithm is proposed to be used in structural reliability analysis. Like approximation methods, the purpose in the proposed algorithm is to locate the position of design point. However, for this purpose, at the iterations of the phases random samples are generated based on a moving sampling density function, like what is done in adaptive importance sampling. At each phase, by representing an updating criterion, the position of the candidate of design point is updated to approach the real design point. Two criteria of the first and second phase are to reduce the initial relatively large distance between the candidate of design point and the real one. In the third phase, after introducing a new effective fitness function, the third updating criterion is represented to take the final smaller steps of approaching design point. Through various numerical examples, the accuracy and efficiency of three aforementioned phases have been shown. Reliability index Probability of failure Design point Fitness function Adjusting constant Shayanfar, Mohsen Ali verfasserin aut Barkhordari, Mohammad Ali verfasserin aut Karamloo, Mohammad verfasserin aut Enthalten in Mechanics research communications Amsterdam [u.a.] : Elsevier, 1974 85, Seite 53-60 Online-Ressource (DE-627)319950131 (DE-600)2013977-9 (DE-576)259484822 1873-3972 nnns volume:85 pages:53-60 GBV_USEFLAG_U SYSFLAG_U GBV_ELV GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 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_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 50.31 Technische Mechanik 50.33 Technische Strömungsmechanik 51.32 Werkstoffmechanik AR 85 53-60
allfields_unstemmed	10.1016/j.mechrescom.2017.08.008 doi (DE-627)ELV000708178 (ELSEVIER)S0093-6413(17)30250-1 DE-627 ger DE-627 rda eng 670 DE-600 50.31 bkl 50.33 bkl 51.32 bkl Roudak, Mohammad Amin verfasserin aut A new three-phase algorithm for computation of reliability index and its application in structural mechanics 2017 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Computation of reliability index or probability of failure in practical problems is still a challenge. In this paper, an efficient three-phase non-gradient-based algorithm is proposed to be used in structural reliability analysis. Like approximation methods, the purpose in the proposed algorithm is to locate the position of design point. However, for this purpose, at the iterations of the phases random samples are generated based on a moving sampling density function, like what is done in adaptive importance sampling. At each phase, by representing an updating criterion, the position of the candidate of design point is updated to approach the real design point. Two criteria of the first and second phase are to reduce the initial relatively large distance between the candidate of design point and the real one. In the third phase, after introducing a new effective fitness function, the third updating criterion is represented to take the final smaller steps of approaching design point. Through various numerical examples, the accuracy and efficiency of three aforementioned phases have been shown. Reliability index Probability of failure Design point Fitness function Adjusting constant Shayanfar, Mohsen Ali verfasserin aut Barkhordari, Mohammad Ali verfasserin aut Karamloo, Mohammad verfasserin aut Enthalten in Mechanics research communications Amsterdam [u.a.] : Elsevier, 1974 85, Seite 53-60 Online-Ressource (DE-627)319950131 (DE-600)2013977-9 (DE-576)259484822 1873-3972 nnns volume:85 pages:53-60 GBV_USEFLAG_U SYSFLAG_U GBV_ELV GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 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_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 50.31 Technische Mechanik 50.33 Technische Strömungsmechanik 51.32 Werkstoffmechanik AR 85 53-60
allfieldsGer	10.1016/j.mechrescom.2017.08.008 doi (DE-627)ELV000708178 (ELSEVIER)S0093-6413(17)30250-1 DE-627 ger DE-627 rda eng 670 DE-600 50.31 bkl 50.33 bkl 51.32 bkl Roudak, Mohammad Amin verfasserin aut A new three-phase algorithm for computation of reliability index and its application in structural mechanics 2017 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Computation of reliability index or probability of failure in practical problems is still a challenge. In this paper, an efficient three-phase non-gradient-based algorithm is proposed to be used in structural reliability analysis. Like approximation methods, the purpose in the proposed algorithm is to locate the position of design point. However, for this purpose, at the iterations of the phases random samples are generated based on a moving sampling density function, like what is done in adaptive importance sampling. At each phase, by representing an updating criterion, the position of the candidate of design point is updated to approach the real design point. Two criteria of the first and second phase are to reduce the initial relatively large distance between the candidate of design point and the real one. In the third phase, after introducing a new effective fitness function, the third updating criterion is represented to take the final smaller steps of approaching design point. Through various numerical examples, the accuracy and efficiency of three aforementioned phases have been shown. Reliability index Probability of failure Design point Fitness function Adjusting constant Shayanfar, Mohsen Ali verfasserin aut Barkhordari, Mohammad Ali verfasserin aut Karamloo, Mohammad verfasserin aut Enthalten in Mechanics research communications Amsterdam [u.a.] : Elsevier, 1974 85, Seite 53-60 Online-Ressource (DE-627)319950131 (DE-600)2013977-9 (DE-576)259484822 1873-3972 nnns volume:85 pages:53-60 GBV_USEFLAG_U SYSFLAG_U GBV_ELV GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 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_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 50.31 Technische Mechanik 50.33 Technische Strömungsmechanik 51.32 Werkstoffmechanik AR 85 53-60
allfieldsSound	10.1016/j.mechrescom.2017.08.008 doi (DE-627)ELV000708178 (ELSEVIER)S0093-6413(17)30250-1 DE-627 ger DE-627 rda eng 670 DE-600 50.31 bkl 50.33 bkl 51.32 bkl Roudak, Mohammad Amin verfasserin aut A new three-phase algorithm for computation of reliability index and its application in structural mechanics 2017 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Computation of reliability index or probability of failure in practical problems is still a challenge. In this paper, an efficient three-phase non-gradient-based algorithm is proposed to be used in structural reliability analysis. Like approximation methods, the purpose in the proposed algorithm is to locate the position of design point. However, for this purpose, at the iterations of the phases random samples are generated based on a moving sampling density function, like what is done in adaptive importance sampling. At each phase, by representing an updating criterion, the position of the candidate of design point is updated to approach the real design point. Two criteria of the first and second phase are to reduce the initial relatively large distance between the candidate of design point and the real one. In the third phase, after introducing a new effective fitness function, the third updating criterion is represented to take the final smaller steps of approaching design point. Through various numerical examples, the accuracy and efficiency of three aforementioned phases have been shown. Reliability index Probability of failure Design point Fitness function Adjusting constant Shayanfar, Mohsen Ali verfasserin aut Barkhordari, Mohammad Ali verfasserin aut Karamloo, Mohammad verfasserin aut Enthalten in Mechanics research communications Amsterdam [u.a.] : Elsevier, 1974 85, Seite 53-60 Online-Ressource (DE-627)319950131 (DE-600)2013977-9 (DE-576)259484822 1873-3972 nnns volume:85 pages:53-60 GBV_USEFLAG_U SYSFLAG_U GBV_ELV GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 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_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 50.31 Technische Mechanik 50.33 Technische Strömungsmechanik 51.32 Werkstoffmechanik AR 85 53-60
language	English
source	Enthalten in Mechanics research communications 85, Seite 53-60 volume:85 pages:53-60
sourceStr	Enthalten in Mechanics research communications 85, Seite 53-60 volume:85 pages:53-60
format_phy_str_mv	Article
bklname	Technische Mechanik Technische Strömungsmechanik Werkstoffmechanik
institution	findex.gbv.de
topic_facet	Reliability index Probability of failure Design point Fitness function Adjusting constant
dewey-raw	670
isfreeaccess_bool	false
container_title	Mechanics research communications
authorswithroles_txt_mv	Roudak, Mohammad Amin @@aut@@ Shayanfar, Mohsen Ali @@aut@@ Barkhordari, Mohammad Ali @@aut@@ Karamloo, Mohammad @@aut@@
publishDateDaySort_date	2017-01-01T00:00:00Z
hierarchy_top_id	319950131
dewey-sort	3670
id	ELV000708178
language_de	englisch
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author	Roudak, Mohammad Amin
spellingShingle	Roudak, Mohammad Amin ddc 670 bkl 50.31 bkl 50.33 bkl 51.32 misc Reliability index misc Probability of failure misc Design point misc Fitness function misc Adjusting constant A new three-phase algorithm for computation of reliability index and its application in structural mechanics
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topic_title	670 DE-600 50.31 bkl 50.33 bkl 51.32 bkl A new three-phase algorithm for computation of reliability index and its application in structural mechanics Reliability index Probability of failure Design point Fitness function Adjusting constant
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title	A new three-phase algorithm for computation of reliability index and its application in structural mechanics
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title_full	A new three-phase algorithm for computation of reliability index and its application in structural mechanics
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title_sort	a new three-phase algorithm for computation of reliability index and its application in structural mechanics
title_auth	A new three-phase algorithm for computation of reliability index and its application in structural mechanics
abstract	Computation of reliability index or probability of failure in practical problems is still a challenge. In this paper, an efficient three-phase non-gradient-based algorithm is proposed to be used in structural reliability analysis. Like approximation methods, the purpose in the proposed algorithm is to locate the position of design point. However, for this purpose, at the iterations of the phases random samples are generated based on a moving sampling density function, like what is done in adaptive importance sampling. At each phase, by representing an updating criterion, the position of the candidate of design point is updated to approach the real design point. Two criteria of the first and second phase are to reduce the initial relatively large distance between the candidate of design point and the real one. In the third phase, after introducing a new effective fitness function, the third updating criterion is represented to take the final smaller steps of approaching design point. Through various numerical examples, the accuracy and efficiency of three aforementioned phases have been shown.
abstractGer	Computation of reliability index or probability of failure in practical problems is still a challenge. In this paper, an efficient three-phase non-gradient-based algorithm is proposed to be used in structural reliability analysis. Like approximation methods, the purpose in the proposed algorithm is to locate the position of design point. However, for this purpose, at the iterations of the phases random samples are generated based on a moving sampling density function, like what is done in adaptive importance sampling. At each phase, by representing an updating criterion, the position of the candidate of design point is updated to approach the real design point. Two criteria of the first and second phase are to reduce the initial relatively large distance between the candidate of design point and the real one. In the third phase, after introducing a new effective fitness function, the third updating criterion is represented to take the final smaller steps of approaching design point. Through various numerical examples, the accuracy and efficiency of three aforementioned phases have been shown.
abstract_unstemmed	Computation of reliability index or probability of failure in practical problems is still a challenge. In this paper, an efficient three-phase non-gradient-based algorithm is proposed to be used in structural reliability analysis. Like approximation methods, the purpose in the proposed algorithm is to locate the position of design point. However, for this purpose, at the iterations of the phases random samples are generated based on a moving sampling density function, like what is done in adaptive importance sampling. At each phase, by representing an updating criterion, the position of the candidate of design point is updated to approach the real design point. Two criteria of the first and second phase are to reduce the initial relatively large distance between the candidate of design point and the real one. In the third phase, after introducing a new effective fitness function, the third updating criterion is represented to take the final smaller steps of approaching design point. Through various numerical examples, the accuracy and efficiency of three aforementioned phases have been shown.
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title_short	A new three-phase algorithm for computation of reliability index and its application in structural mechanics
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A new three-phase algorithm for computation of reliability index and its application in structural mechanics

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