Finite Element Approximation for Optimal Shape Design: Theory and ApplicationsExplains how to speed the optimal shape design process using a computer. Outlines the problems inherent in optimal shape design and discusses methods of their solution. Concentrates on finite element approximation and describes numerical realization of optimization techniques. Treats optimal design problems via the optimal control theory when the state systems are governed by variational inequalities. Provides useful background information, followed by numerous approaches to optimal shape design, all supported by illustrative examples. Appendices provide algorithms and numerous examples and their calculations are included. |
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Page 94
... described in Figure 5.5 . OPTIMIZER is a general purpose nonlinear programming routine ( local optimizer ) which includes routines for handling linear and nonlinear con- straints . In practice the SQP - method ( Appendix IV ) or ...
... described in Figure 5.5 . OPTIMIZER is a general purpose nonlinear programming routine ( local optimizer ) which includes routines for handling linear and nonlinear con- straints . In practice the SQP - method ( Appendix IV ) or ...
Page 198
... described by unilateral boundary value problems , in which constraints are imposed on the boundary only . Now we shall present another kind of a state problem , namely the so - called free boundary value problem with constraints given ...
... described by unilateral boundary value problems , in which constraints are imposed on the boundary only . Now we shall present another kind of a state problem , namely the so - called free boundary value problem with constraints given ...
Page 199
Theory and Applications J. Haslinger, Pekka Neittaanmäki. is described by ( 9.1 ) - Au ( x ) f ( x ) , ΤΕΩ ( 9.2 ) u ( x ) ≥ 4 ( x ) , ΤΕΩ ( 9.3 ) - ( 9.4 ) ( − △ u ( x ) − f ( x ) ) ( u ( x ) − y ( x ) ) = 0 , u ( x ) = 0 , - ΤΕΩ x ...
Theory and Applications J. Haslinger, Pekka Neittaanmäki. is described by ( 9.1 ) - Au ( x ) f ( x ) , ΤΕΩ ( 9.2 ) u ( x ) ≥ 4 ( x ) , ΤΕΩ ( 9.3 ) - ( 9.4 ) ( − △ u ( x ) − f ( x ) ) ( u ( x ) − y ( x ) ) = 0 , u ( x ) = 0 , - ΤΕΩ x ...
Contents
Preliminaries | 1 |
Abstract setting of optimal shape design problem and | 28 |
Optimal shape design of systems governed by a unilateral | 53 |
Copyright | |
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adjoint algorithm Appendix applied approximation boundary value problem C₁ Céa compute constraints contact problems convex convex set cost functional defined denote design sensitivity analysis differentiable discrete domain elastic exist a subsequence Find finite element follows formula given Gm(a H¹(Î Haslinger Haug Hlaváček Ir(an jEJk Komkov Lagrange multipliers least one solution Lemma lim inf lim sup linear Lipschitz Lipschitz continuous lower semicontinuous mapping material derivative matrix minimization Nečas Neittaanmäki nodes nonlinear programming nonsmooth Numerical results obtain optimal control optimal design optimal pair optimal shape design parameter Pironneau Proof results for Example Section sensitivity analysis sequence shape design problems Shape optimization Sokolowski solves P(a subgradient subset T(Un T₁ Theorem triangulation triangulation T(h un(an unilateral boundary value variational inequality vector w₁ Zolesio г₁ дп