Post optimization for accurate and efficient reliability‐based design optimization using second‐order reliability method based on importance sampling and its stochastic sensitivity analysis
In this study, a post optimization technique for a correction of inaccurate optimum obtained using first‐order reliability method (FORM) is proposed for accurate reliability‐based design optimization (RBDO). In the proposed method, RBDO using FORM is first performed, and then the proposed second‐ord...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Lim, Jongmin [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2016 |
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| Rechteinformationen: |
Nutzungsrecht: Copyright © 2015 John Wiley & Sons, Ltd. |
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| Schlagwörter: |
Second‐order reliability method Reliability‐based design optimization |
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| Übergeordnetes Werk: |
Enthalten in: International journal for numerical methods in engineering - Chichester [u.a.] : Wiley, 1969, 107(2016), 2, Seite 93-108 |
|---|---|
| Übergeordnetes Werk: |
volume:107 ; year:2016 ; number:2 ; pages:93-108 |
| Links: |
|---|
| DOI / URN: |
10.1002/nme.5150 |
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| Katalog-ID: |
OLC1979029326 |
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| 520 | |a In this study, a post optimization technique for a correction of inaccurate optimum obtained using first‐order reliability method (FORM) is proposed for accurate reliability‐based design optimization (RBDO). In the proposed method, RBDO using FORM is first performed, and then the proposed second‐order reliability method (SORM) is performed at the optimum obtained using FORM for more accurate reliability assessment and its sensitivity analysis. In the proposed SORM, the Hessian of a performance function is approximated by reusing derivatives information accumulated during previous RBDO iterations using FORM, indicating that additional functional evaluations are not required in the proposed SORM. The proposed SORM calculates a probability of failure and its first‐order and second‐order stochastic sensitivity by applying the importance sampling to a complete second‐order Taylor series of the performance function. The proposed post optimization constructs a second‐order Taylor expansion of the probability of failure using results of the proposed SORM. Because the constructed Taylor expansion is based on the reliability method more accurate than FORM, the corrected optimum using this Taylor expansion can satisfy the target reliability more accurately. In this way, the proposed method simultaneously achieves both efficiency of FORM and accuracy of SORM. Copyright © 2015 John Wiley & Sons, Ltd. | ||
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| 650 | 4 | |a Second‐order reliability method | |
| 650 | 4 | |a Reliability‐based design optimization | |
| 650 | 4 | |a Post optimization | |
| 650 | 4 | |a Stochastic sensitivity analysis | |
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10.1002/nme.5150 doi PQ20160720 (DE-627)OLC1979029326 (DE-599)GBVOLC1979029326 (PRQ)p1552-9ea3b7e92ec895e09816c9118b4ad626e5d2c357b41350cc109aba5e8b6510033 (KEY)0065660720160000107000200093postoptimizationforaccurateandefficientreliability DE-627 ger DE-627 rakwb eng 510 DNB 50.03 bkl Lim, Jongmin verfasserin aut Post optimization for accurate and efficient reliability‐based design optimization using second‐order reliability method based on importance sampling and its stochastic sensitivity analysis 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier In this study, a post optimization technique for a correction of inaccurate optimum obtained using first‐order reliability method (FORM) is proposed for accurate reliability‐based design optimization (RBDO). In the proposed method, RBDO using FORM is first performed, and then the proposed second‐order reliability method (SORM) is performed at the optimum obtained using FORM for more accurate reliability assessment and its sensitivity analysis. In the proposed SORM, the Hessian of a performance function is approximated by reusing derivatives information accumulated during previous RBDO iterations using FORM, indicating that additional functional evaluations are not required in the proposed SORM. The proposed SORM calculates a probability of failure and its first‐order and second‐order stochastic sensitivity by applying the importance sampling to a complete second‐order Taylor series of the performance function. The proposed post optimization constructs a second‐order Taylor expansion of the probability of failure using results of the proposed SORM. Because the constructed Taylor expansion is based on the reliability method more accurate than FORM, the corrected optimum using this Taylor expansion can satisfy the target reliability more accurately. In this way, the proposed method simultaneously achieves both efficiency of FORM and accuracy of SORM. Copyright © 2015 John Wiley & Sons, Ltd. Nutzungsrecht: Copyright © 2015 John Wiley & Sons, Ltd. Second‐order reliability method Reliability‐based design optimization Post optimization Stochastic sensitivity analysis Reliability analysis Lee, Byungchai oth Lee, Ikjin oth Enthalten in International journal for numerical methods in engineering Chichester [u.a.] : Wiley, 1969 107(2016), 2, Seite 93-108 (DE-627)129601217 (DE-600)241381-4 (DE-576)015094812 0029-5981 nnns volume:107 year:2016 number:2 pages:93-108 http://dx.doi.org/10.1002/nme.5150 Volltext http://onlinelibrary.wiley.com/doi/10.1002/nme.5150/abstract http://search.proquest.com/docview/1795564254 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_70 50.03 AVZ AR 107 2016 2 93-108 |
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10.1002/nme.5150 doi PQ20160720 (DE-627)OLC1979029326 (DE-599)GBVOLC1979029326 (PRQ)p1552-9ea3b7e92ec895e09816c9118b4ad626e5d2c357b41350cc109aba5e8b6510033 (KEY)0065660720160000107000200093postoptimizationforaccurateandefficientreliability DE-627 ger DE-627 rakwb eng 510 DNB 50.03 bkl Lim, Jongmin verfasserin aut Post optimization for accurate and efficient reliability‐based design optimization using second‐order reliability method based on importance sampling and its stochastic sensitivity analysis 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier In this study, a post optimization technique for a correction of inaccurate optimum obtained using first‐order reliability method (FORM) is proposed for accurate reliability‐based design optimization (RBDO). In the proposed method, RBDO using FORM is first performed, and then the proposed second‐order reliability method (SORM) is performed at the optimum obtained using FORM for more accurate reliability assessment and its sensitivity analysis. In the proposed SORM, the Hessian of a performance function is approximated by reusing derivatives information accumulated during previous RBDO iterations using FORM, indicating that additional functional evaluations are not required in the proposed SORM. The proposed SORM calculates a probability of failure and its first‐order and second‐order stochastic sensitivity by applying the importance sampling to a complete second‐order Taylor series of the performance function. The proposed post optimization constructs a second‐order Taylor expansion of the probability of failure using results of the proposed SORM. Because the constructed Taylor expansion is based on the reliability method more accurate than FORM, the corrected optimum using this Taylor expansion can satisfy the target reliability more accurately. In this way, the proposed method simultaneously achieves both efficiency of FORM and accuracy of SORM. Copyright © 2015 John Wiley & Sons, Ltd. Nutzungsrecht: Copyright © 2015 John Wiley & Sons, Ltd. Second‐order reliability method Reliability‐based design optimization Post optimization Stochastic sensitivity analysis Reliability analysis Lee, Byungchai oth Lee, Ikjin oth Enthalten in International journal for numerical methods in engineering Chichester [u.a.] : Wiley, 1969 107(2016), 2, Seite 93-108 (DE-627)129601217 (DE-600)241381-4 (DE-576)015094812 0029-5981 nnns volume:107 year:2016 number:2 pages:93-108 http://dx.doi.org/10.1002/nme.5150 Volltext http://onlinelibrary.wiley.com/doi/10.1002/nme.5150/abstract http://search.proquest.com/docview/1795564254 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_70 50.03 AVZ AR 107 2016 2 93-108 |
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10.1002/nme.5150 doi PQ20160720 (DE-627)OLC1979029326 (DE-599)GBVOLC1979029326 (PRQ)p1552-9ea3b7e92ec895e09816c9118b4ad626e5d2c357b41350cc109aba5e8b6510033 (KEY)0065660720160000107000200093postoptimizationforaccurateandefficientreliability DE-627 ger DE-627 rakwb eng 510 DNB 50.03 bkl Lim, Jongmin verfasserin aut Post optimization for accurate and efficient reliability‐based design optimization using second‐order reliability method based on importance sampling and its stochastic sensitivity analysis 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier In this study, a post optimization technique for a correction of inaccurate optimum obtained using first‐order reliability method (FORM) is proposed for accurate reliability‐based design optimization (RBDO). In the proposed method, RBDO using FORM is first performed, and then the proposed second‐order reliability method (SORM) is performed at the optimum obtained using FORM for more accurate reliability assessment and its sensitivity analysis. In the proposed SORM, the Hessian of a performance function is approximated by reusing derivatives information accumulated during previous RBDO iterations using FORM, indicating that additional functional evaluations are not required in the proposed SORM. The proposed SORM calculates a probability of failure and its first‐order and second‐order stochastic sensitivity by applying the importance sampling to a complete second‐order Taylor series of the performance function. The proposed post optimization constructs a second‐order Taylor expansion of the probability of failure using results of the proposed SORM. Because the constructed Taylor expansion is based on the reliability method more accurate than FORM, the corrected optimum using this Taylor expansion can satisfy the target reliability more accurately. In this way, the proposed method simultaneously achieves both efficiency of FORM and accuracy of SORM. Copyright © 2015 John Wiley & Sons, Ltd. Nutzungsrecht: Copyright © 2015 John Wiley & Sons, Ltd. Second‐order reliability method Reliability‐based design optimization Post optimization Stochastic sensitivity analysis Reliability analysis Lee, Byungchai oth Lee, Ikjin oth Enthalten in International journal for numerical methods in engineering Chichester [u.a.] : Wiley, 1969 107(2016), 2, Seite 93-108 (DE-627)129601217 (DE-600)241381-4 (DE-576)015094812 0029-5981 nnns volume:107 year:2016 number:2 pages:93-108 http://dx.doi.org/10.1002/nme.5150 Volltext http://onlinelibrary.wiley.com/doi/10.1002/nme.5150/abstract http://search.proquest.com/docview/1795564254 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_70 50.03 AVZ AR 107 2016 2 93-108 |
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10.1002/nme.5150 doi PQ20160720 (DE-627)OLC1979029326 (DE-599)GBVOLC1979029326 (PRQ)p1552-9ea3b7e92ec895e09816c9118b4ad626e5d2c357b41350cc109aba5e8b6510033 (KEY)0065660720160000107000200093postoptimizationforaccurateandefficientreliability DE-627 ger DE-627 rakwb eng 510 DNB 50.03 bkl Lim, Jongmin verfasserin aut Post optimization for accurate and efficient reliability‐based design optimization using second‐order reliability method based on importance sampling and its stochastic sensitivity analysis 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier In this study, a post optimization technique for a correction of inaccurate optimum obtained using first‐order reliability method (FORM) is proposed for accurate reliability‐based design optimization (RBDO). In the proposed method, RBDO using FORM is first performed, and then the proposed second‐order reliability method (SORM) is performed at the optimum obtained using FORM for more accurate reliability assessment and its sensitivity analysis. In the proposed SORM, the Hessian of a performance function is approximated by reusing derivatives information accumulated during previous RBDO iterations using FORM, indicating that additional functional evaluations are not required in the proposed SORM. The proposed SORM calculates a probability of failure and its first‐order and second‐order stochastic sensitivity by applying the importance sampling to a complete second‐order Taylor series of the performance function. The proposed post optimization constructs a second‐order Taylor expansion of the probability of failure using results of the proposed SORM. Because the constructed Taylor expansion is based on the reliability method more accurate than FORM, the corrected optimum using this Taylor expansion can satisfy the target reliability more accurately. In this way, the proposed method simultaneously achieves both efficiency of FORM and accuracy of SORM. Copyright © 2015 John Wiley & Sons, Ltd. Nutzungsrecht: Copyright © 2015 John Wiley & Sons, Ltd. Second‐order reliability method Reliability‐based design optimization Post optimization Stochastic sensitivity analysis Reliability analysis Lee, Byungchai oth Lee, Ikjin oth Enthalten in International journal for numerical methods in engineering Chichester [u.a.] : Wiley, 1969 107(2016), 2, Seite 93-108 (DE-627)129601217 (DE-600)241381-4 (DE-576)015094812 0029-5981 nnns volume:107 year:2016 number:2 pages:93-108 http://dx.doi.org/10.1002/nme.5150 Volltext http://onlinelibrary.wiley.com/doi/10.1002/nme.5150/abstract http://search.proquest.com/docview/1795564254 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_70 50.03 AVZ AR 107 2016 2 93-108 |
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10.1002/nme.5150 doi PQ20160720 (DE-627)OLC1979029326 (DE-599)GBVOLC1979029326 (PRQ)p1552-9ea3b7e92ec895e09816c9118b4ad626e5d2c357b41350cc109aba5e8b6510033 (KEY)0065660720160000107000200093postoptimizationforaccurateandefficientreliability DE-627 ger DE-627 rakwb eng 510 DNB 50.03 bkl Lim, Jongmin verfasserin aut Post optimization for accurate and efficient reliability‐based design optimization using second‐order reliability method based on importance sampling and its stochastic sensitivity analysis 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier In this study, a post optimization technique for a correction of inaccurate optimum obtained using first‐order reliability method (FORM) is proposed for accurate reliability‐based design optimization (RBDO). In the proposed method, RBDO using FORM is first performed, and then the proposed second‐order reliability method (SORM) is performed at the optimum obtained using FORM for more accurate reliability assessment and its sensitivity analysis. In the proposed SORM, the Hessian of a performance function is approximated by reusing derivatives information accumulated during previous RBDO iterations using FORM, indicating that additional functional evaluations are not required in the proposed SORM. The proposed SORM calculates a probability of failure and its first‐order and second‐order stochastic sensitivity by applying the importance sampling to a complete second‐order Taylor series of the performance function. The proposed post optimization constructs a second‐order Taylor expansion of the probability of failure using results of the proposed SORM. Because the constructed Taylor expansion is based on the reliability method more accurate than FORM, the corrected optimum using this Taylor expansion can satisfy the target reliability more accurately. In this way, the proposed method simultaneously achieves both efficiency of FORM and accuracy of SORM. Copyright © 2015 John Wiley & Sons, Ltd. Nutzungsrecht: Copyright © 2015 John Wiley & Sons, Ltd. Second‐order reliability method Reliability‐based design optimization Post optimization Stochastic sensitivity analysis Reliability analysis Lee, Byungchai oth Lee, Ikjin oth Enthalten in International journal for numerical methods in engineering Chichester [u.a.] : Wiley, 1969 107(2016), 2, Seite 93-108 (DE-627)129601217 (DE-600)241381-4 (DE-576)015094812 0029-5981 nnns volume:107 year:2016 number:2 pages:93-108 http://dx.doi.org/10.1002/nme.5150 Volltext http://onlinelibrary.wiley.com/doi/10.1002/nme.5150/abstract http://search.proquest.com/docview/1795564254 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_70 50.03 AVZ AR 107 2016 2 93-108 |
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510 DNB 50.03 bkl Post optimization for accurate and efficient reliability‐based design optimization using second‐order reliability method based on importance sampling and its stochastic sensitivity analysis Second‐order reliability method Reliability‐based design optimization Post optimization Stochastic sensitivity analysis Reliability analysis |
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ddc 510 bkl 50.03 misc Second‐order reliability method misc Reliability‐based design optimization misc Post optimization misc Stochastic sensitivity analysis misc Reliability analysis |
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ddc 510 bkl 50.03 misc Second‐order reliability method misc Reliability‐based design optimization misc Post optimization misc Stochastic sensitivity analysis misc Reliability analysis |
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ddc 510 bkl 50.03 misc Second‐order reliability method misc Reliability‐based design optimization misc Post optimization misc Stochastic sensitivity analysis misc Reliability analysis |
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International journal for numerical methods in engineering |
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International journal for numerical methods in engineering |
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Post optimization for accurate and efficient reliability‐based design optimization using second‐order reliability method based on importance sampling and its stochastic sensitivity analysis |
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Post optimization for accurate and efficient reliability‐based design optimization using second‐order reliability method based on importance sampling and its stochastic sensitivity analysis |
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Lim, Jongmin |
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International journal for numerical methods in engineering |
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Lim, Jongmin |
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10.1002/nme.5150 |
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510 |
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post optimization for accurate and efficient reliability‐based design optimization using second‐order reliability method based on importance sampling and its stochastic sensitivity analysis |
| title_auth |
Post optimization for accurate and efficient reliability‐based design optimization using second‐order reliability method based on importance sampling and its stochastic sensitivity analysis |
| abstract |
In this study, a post optimization technique for a correction of inaccurate optimum obtained using first‐order reliability method (FORM) is proposed for accurate reliability‐based design optimization (RBDO). In the proposed method, RBDO using FORM is first performed, and then the proposed second‐order reliability method (SORM) is performed at the optimum obtained using FORM for more accurate reliability assessment and its sensitivity analysis. In the proposed SORM, the Hessian of a performance function is approximated by reusing derivatives information accumulated during previous RBDO iterations using FORM, indicating that additional functional evaluations are not required in the proposed SORM. The proposed SORM calculates a probability of failure and its first‐order and second‐order stochastic sensitivity by applying the importance sampling to a complete second‐order Taylor series of the performance function. The proposed post optimization constructs a second‐order Taylor expansion of the probability of failure using results of the proposed SORM. Because the constructed Taylor expansion is based on the reliability method more accurate than FORM, the corrected optimum using this Taylor expansion can satisfy the target reliability more accurately. In this way, the proposed method simultaneously achieves both efficiency of FORM and accuracy of SORM. Copyright © 2015 John Wiley & Sons, Ltd. |
| abstractGer |
In this study, a post optimization technique for a correction of inaccurate optimum obtained using first‐order reliability method (FORM) is proposed for accurate reliability‐based design optimization (RBDO). In the proposed method, RBDO using FORM is first performed, and then the proposed second‐order reliability method (SORM) is performed at the optimum obtained using FORM for more accurate reliability assessment and its sensitivity analysis. In the proposed SORM, the Hessian of a performance function is approximated by reusing derivatives information accumulated during previous RBDO iterations using FORM, indicating that additional functional evaluations are not required in the proposed SORM. The proposed SORM calculates a probability of failure and its first‐order and second‐order stochastic sensitivity by applying the importance sampling to a complete second‐order Taylor series of the performance function. The proposed post optimization constructs a second‐order Taylor expansion of the probability of failure using results of the proposed SORM. Because the constructed Taylor expansion is based on the reliability method more accurate than FORM, the corrected optimum using this Taylor expansion can satisfy the target reliability more accurately. In this way, the proposed method simultaneously achieves both efficiency of FORM and accuracy of SORM. Copyright © 2015 John Wiley & Sons, Ltd. |
| abstract_unstemmed |
In this study, a post optimization technique for a correction of inaccurate optimum obtained using first‐order reliability method (FORM) is proposed for accurate reliability‐based design optimization (RBDO). In the proposed method, RBDO using FORM is first performed, and then the proposed second‐order reliability method (SORM) is performed at the optimum obtained using FORM for more accurate reliability assessment and its sensitivity analysis. In the proposed SORM, the Hessian of a performance function is approximated by reusing derivatives information accumulated during previous RBDO iterations using FORM, indicating that additional functional evaluations are not required in the proposed SORM. The proposed SORM calculates a probability of failure and its first‐order and second‐order stochastic sensitivity by applying the importance sampling to a complete second‐order Taylor series of the performance function. The proposed post optimization constructs a second‐order Taylor expansion of the probability of failure using results of the proposed SORM. Because the constructed Taylor expansion is based on the reliability method more accurate than FORM, the corrected optimum using this Taylor expansion can satisfy the target reliability more accurately. In this way, the proposed method simultaneously achieves both efficiency of FORM and accuracy of SORM. Copyright © 2015 John Wiley & Sons, Ltd. |
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| title_short |
Post optimization for accurate and efficient reliability‐based design optimization using second‐order reliability method based on importance sampling and its stochastic sensitivity analysis |
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http://dx.doi.org/10.1002/nme.5150 http://onlinelibrary.wiley.com/doi/10.1002/nme.5150/abstract http://search.proquest.com/docview/1795564254 |
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Lee, Byungchai Lee, Ikjin |
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