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Reduced order methods for modeling and computational reduction [electronic resource]

Reduced order methods for modeling and computational reduction [electronic resource]

자료유형
E-Book(소장)
개인저자
Quarteroni, Alfio. Rozza, Gianluigi.
서명 / 저자사항
Reduced order methods for modeling and computational reduction [electronic resource] / Alfio Quarteroni, Gianluigi Rozza, editors.
발행사항
Cham :   Springer International Publishing :   Imprint: Springer,   2014.  
형태사항
1 online resource (x, 334 p.) : ill.
총서사항
MS&A,2037-5255 ; 9
ISBN
9783319020907
요약
This monograph addresses the state of the art of reduced order methods for modeling and computational reduction of complex parametrized systems, governed by ordinary and/or partial differential equations, with a special emphasis on real time computing techniques and applications in computational mechanics, bioengineering and computer graphics.  Several topics are covered, including: design, optimization, and control theory in real-time with applications in engineering; data assimilation, geometry registration, and parameter estimation with special attention to real-time computing in biomedical engineering and computational physics; real-time visualization of physics-based simulations in computer science; the treatment of high-dimensional problems in state space, physical space, or parameter space; the interactions between different model reduction and dimensionality reduction approaches; the development of general error estimation frameworks which take into account both model and discretization effects. This book is primarily addressed to computational scientists interested in computational reduction techniques for large scale differential problems.
일반주기
Title from e-Book title page.  
내용주기
1 W. H. A. Schilders, A. Lutowska: A novel approach to model order reduction for coupled multiphysics problems -- 2 A. C. Ionita, A. C. Antoulas: Case study. Parametrized Reduction using Reduced-Basis and the Loewner Framework -- 3 M. Bebendorf, Y. Maday, B. Stamm: Comparison of some reduced representation approximations -- 4 H. Antil, M. Heinkenschloss, D. C. Sorensen: Application of the Discrete Empirical Interpolation Method to Reduced Order Modeling of Nonlinear and Parametric System -- 5 K. Urban, S. Volkwein, O. Zeeb: Greedy Sampling using Nonlinear Optimization -- 6 P. Benner, L. Feng: A Robust Algorithm for Parametric Model Order Reduction based on Implicit Moment Matching -- 7 F. Chen, J. S. Hesthaven, X. Zhu: On the use of reduced basis methods to accelerate and stabilize the Parareal method -- 8 C. Farhat, D. Amsallem: On the stability of reduced-order linearized computational fluid dynamics models based on POD and Galerkin projection: descriptor vs non-descriptor forms -- 9 T. Lassila, A. Manzoni, A. Quarteroni, G. Rozza: Model Order Reduction in Fluid Dynamics: Challenges and Perspectives -- 10 L. Grinberg, M. Deng, A. Yakhot, G. Karniadakis: Window Proper Orthogonal Decomposition. Application to Continuum and Atomistic Data -- 11 M. Bergmann, T. Colin, A. Iollo, D. Lombardi, O. Saut, H. Telib: Reduced order models at work in Aeronautics and Medicine.
서지주기
Includes bibliographical references.
이용가능한 다른형태자료
Issued also as a book.  
일반주제명
Computer simulation.
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007 cr
008 200916s2014 sz a ob 000 0 eng d
020 ▼a 9783319020907
040 ▼a 211009 ▼c 211009 ▼d 211009
050 4 ▼a QA76.9.C65
082 0 4 ▼a 003.3 ▼2 23
084 ▼a 003.3 ▼2 DDCK
090 ▼a 003.3
245 0 0 ▼a Reduced order methods for modeling and computational reduction ▼h [electronic resource] / ▼c Alfio Quarteroni, Gianluigi Rozza, editors.
260 ▼a Cham : ▼b Springer International Publishing : ▼b Imprint: Springer, ▼c 2014.
300 ▼a 1 online resource (x, 334 p.) : ▼b ill.
490 1 ▼a MS&A, ▼x 2037-5255 ; ▼v 9
500 ▼a Title from e-Book title page.
504 ▼a Includes bibliographical references.
505 0 ▼a 1 W. H. A. Schilders, A. Lutowska: A novel approach to model order reduction for coupled multiphysics problems -- 2 A. C. Ionita, A. C. Antoulas: Case study. Parametrized Reduction using Reduced-Basis and the Loewner Framework -- 3 M. Bebendorf, Y. Maday, B. Stamm: Comparison of some reduced representation approximations -- 4 H. Antil, M. Heinkenschloss, D. C. Sorensen: Application of the Discrete Empirical Interpolation Method to Reduced Order Modeling of Nonlinear and Parametric System -- 5 K. Urban, S. Volkwein, O. Zeeb: Greedy Sampling using Nonlinear Optimization -- 6 P. Benner, L. Feng: A Robust Algorithm for Parametric Model Order Reduction based on Implicit Moment Matching -- 7 F. Chen, J. S. Hesthaven, X. Zhu: On the use of reduced basis methods to accelerate and stabilize the Parareal method -- 8 C. Farhat, D. Amsallem: On the stability of reduced-order linearized computational fluid dynamics models based on POD and Galerkin projection: descriptor vs non-descriptor forms -- 9 T. Lassila, A. Manzoni, A. Quarteroni, G. Rozza: Model Order Reduction in Fluid Dynamics: Challenges and Perspectives -- 10 L. Grinberg, M. Deng, A. Yakhot, G. Karniadakis: Window Proper Orthogonal Decomposition. Application to Continuum and Atomistic Data -- 11 M. Bergmann, T. Colin, A. Iollo, D. Lombardi, O. Saut, H. Telib: Reduced order models at work in Aeronautics and Medicine.
520 ▼a This monograph addresses the state of the art of reduced order methods for modeling and computational reduction of complex parametrized systems, governed by ordinary and/or partial differential equations, with a special emphasis on real time computing techniques and applications in computational mechanics, bioengineering and computer graphics.  Several topics are covered, including: design, optimization, and control theory in real-time with applications in engineering; data assimilation, geometry registration, and parameter estimation with special attention to real-time computing in biomedical engineering and computational physics; real-time visualization of physics-based simulations in computer science; the treatment of high-dimensional problems in state space, physical space, or parameter space; the interactions between different model reduction and dimensionality reduction approaches; the development of general error estimation frameworks which take into account both model and discretization effects. This book is primarily addressed to computational scientists interested in computational reduction techniques for large scale differential problems.
530 ▼a Issued also as a book.
538 ▼a Mode of access: World Wide Web.
650 0 ▼a Computer simulation.
700 1 ▼a Quarteroni, Alfio.
700 1 ▼a Rozza, Gianluigi.
830 0 ▼a MS&A ; ▼v 9.
856 4 0 ▼u https://oca.korea.ac.kr/link.n2s?url=http://dx.doi.org/10.1007/978-3-319-02090-7
945 ▼a KLPA
991 ▼a E-Book(소장)

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No. 1 소장처 중앙도서관/e-Book 컬렉션/ 청구기호 CR 003.3 등록번호 E14034221 도서상태 대출불가(열람가능) 반납예정일 예약 서비스 M

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