The Second-Order Adjoint Sensitivity Analysis Methodology
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| Title: | The Second-Order Adjoint Sensitivity Analysis Methodology |
|---|---|
| Description: | The Second-Order Adjoint Sensitivity Analysis Methodology generalizes the First-Order Theory presented in the author's previous books published by CRC Press. This breakthrough has many applications in sensitivity and uncertainty analysis, optimization, data assimilation, model calibration, and reducing uncertainties in model predictions. The book has many illustrative examples that will help readers understand the complexity of the subject and will enable them to apply this methodology to problems in their own fields. Highlights:• Covers a wide range of needs, from graduate students to advanced researchers• Provides a text positioned to be the primary reference for high-order sensitivity and uncertainty analysis• Applies to all fields involving numerical modeling, optimization, quantification of sensitivities in direct and inverse problems in the presence of uncertainties.About the Author: Dan Gabriel Cacuci is a South Carolina SmartState Endowed Chair Professor and the Director of the Center for Nuclear Science and Energy, Department of Mechanical Engineering at the University of South Carolina. He has a Ph.D. in Applied Physics, Mechanical and Nuclear Engineering from Columbia University. He is also the recipient of many awards including four honorary doctorates, the Ernest Orlando Lawrence Memorial award from the U.S. Dept. of Energy and the Arthur Holly Compton, Eugene P. Wigner and the Glenn Seaborg Awards from the American Nuclear Society. |
| Authors: | Dan Gabriel Cacuci |
| Resource Type: | eBook. |
| Subjects: | Large scale systems, Sensitivity theory (Mathematics), Nonlinear systems |
| Categories: | MATHEMATICS / Numerical Analysis, MATHEMATICS / Applied, MATHEMATICS / Optimization |
| Database: | eBook Collection (EBSCOhost) |
| FullText | Links: – Type: ebook-pdf Text: Availability: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: The Second-Order Adjoint Sensitivity Analysis Methodology – Name: Abstract Label: Description Group: Ab Data: The Second-Order Adjoint Sensitivity Analysis Methodology generalizes the First-Order Theory presented in the author's previous books published by CRC Press. This breakthrough has many applications in sensitivity and uncertainty analysis, optimization, data assimilation, model calibration, and reducing uncertainties in model predictions. The book has many illustrative examples that will help readers understand the complexity of the subject and will enable them to apply this methodology to problems in their own fields. Highlights:• Covers a wide range of needs, from graduate students to advanced researchers• Provides a text positioned to be the primary reference for high-order sensitivity and uncertainty analysis• Applies to all fields involving numerical modeling, optimization, quantification of sensitivities in direct and inverse problems in the presence of uncertainties.About the Author: Dan Gabriel Cacuci is a South Carolina SmartState Endowed Chair Professor and the Director of the Center for Nuclear Science and Energy, Department of Mechanical Engineering at the University of South Carolina. He has a Ph.D. in Applied Physics, Mechanical and Nuclear Engineering from Columbia University. He is also the recipient of many awards including four honorary doctorates, the Ernest Orlando Lawrence Memorial award from the U.S. Dept. of Energy and the Arthur Holly Compton, Eugene P. Wigner and the Glenn Seaborg Awards from the American Nuclear Society. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Dan+Gabriel+Cacuci%22">Dan Gabriel Cacuci</searchLink> – Name: TypePub Label: Resource Type Group: TypPub Data: eBook. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Large+scale+systems%22">Large scale systems</searchLink><br /><searchLink fieldCode="DE" term="%22Sensitivity+theory+%28Mathematics%29%22">Sensitivity theory (Mathematics)</searchLink><br /><searchLink fieldCode="DE" term="%22Nonlinear+systems%22">Nonlinear systems</searchLink> – Name: SubjectBISAC Label: Categories Group: Su Data: <searchLink fieldCode="ZK" term="%22MATHEMATICS+%2F+Numerical+Analysis%22">MATHEMATICS / Numerical Analysis</searchLink><br /><searchLink fieldCode="ZK" term="%22MATHEMATICS+%2F+Applied%22">MATHEMATICS / Applied</searchLink><br /><searchLink fieldCode="ZK" term="%22MATHEMATICS+%2F+Optimization%22">MATHEMATICS / Optimization</searchLink> |
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| RecordInfo | BibRecord: BibEntity: Classifications: – Code: 003.71 Scheme: ddc Type: prePub Languages: – Code: eng Text: English Subjects: – SubjectFull: Large scale systems Type: general – SubjectFull: Sensitivity theory (Mathematics) Type: general – SubjectFull: Nonlinear systems Type: general Titles: – TitleFull: The Second-Order Adjoint Sensitivity Analysis Methodology Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Dan Gabriel Cacuci – PersonEntity: Name: NameFull: Dan Gabriel Cacuci IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Type: published Y: 2018 – D: 23 M: 02 Type: profile Y: 2018 Identifiers: – Type: isbn-print Value: 9781138105294 – Type: isbn-print Value: 9781498726481 – Type: isbn-print Value: 9780367424923 – Type: isbn-electronic Value: 9781351646581 – Type: isbn-electronic Value: 9781498726498 – Type: isbn-electronic Value: 9781315120270 Titles: – TitleFull: The Second-Order Adjoint Sensitivity Analysis Methodology Type: main |
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