Titlebook: Reduced-Order Modeling (ROM) for Simulation and Optimization; Powerful Algorithms Winfried Keiper,Anja Milde,Stefan Volkwein Book 2018 Spr

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长矛

Model Order Reduction for Rotating Electrical Machines,e strategy based on proper orthogonal decomposition is developed to overcome these difficulties. Equipped with an a posteriori error estimator, the obtained solution is certified. Numerical examples are presented to demonstrate the effectiveness of the proposed method.

勉励

Book 2018cientific computing, e.g. reduced basis methods for industrial problems and MOR approaches for electrochemical processes. The target audience comprises research experts and practitioners in the field of simulation, optimization and control, but the book may also be beneficial for graduate students alike. .

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Set-Oriented Multiobjective Optimal Control of PDEs Using Proper Orthogonal Decomposition, for reduced-order models based on Proper Orthogonal Decomposition in order to efficiently solve multiobjective optimization problems governed by partial differential equations. An error bound for a semilinear heat equation is developed in such a way that the errors in the conflicting objectives can

Intuitive

Sequential Reduced-Order Modeling for Time-Dependent Optimization Problems with Initial Value Contral value controls. The numerical solution of such a problem requires Hessian-times-vector multiplications, each of which requires solving a linearized state equation with initial value given by the vector and solving a second-order adjoint equation. Projection-based ROMs are applied to these differe

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A Direct Index 1 DAE Model of Gas Networks,space discretization results in a system of index 2 nonlinear differential algebraic equations (DAE). Those are hard to simulate, and model order reduction techniques are not very developed for this system class. However, we can show that a simple approximation results in an index 1 system of nonlin

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