Large-Scale Pde-Constrained... | Buy

Optimal design, optimal control, and parameter estimation of systems governed by partial differential equations (PDEs) give rise to a class of problems known as PDE-constrained optimization. The size and complexity of the discretized PDEs often pose significant challenges for contemporary optimization methods. With the maturing of technology for PDE simulation, interest has now increased in PDE-based optimization. The chapters in this volume collectively assess the state of the art in PDE-constrained optimization, identify challenges to optimization presented by modern highly parallel PDE simulation codes, and discuss promising algorithmic and software approaches for addressing them. These contributions represent current research of two strong scientific computing communities, in optimization and PDE simulation. This volume merges perspectives in these two different areas and identifies interesting open questions for further research.

I Introduction

Large-Scale PDE-Constrained Optimization: An Introduction

(14)

Lorenz T. Biegler, Omar Ghattas, Matthias Heinkenschloss, Bart van Bloemen Waanders

II Large-Scale CFD Applications

Nonlinear Elimination in Aerodynamic Analysis and Design Optimization

(28)

D.P. Young, W.P. Huffman, R.G. Melvin, C.L. Hilmes, F.T. Johnson

Optimization of Large-Scale Reacting Flows using MPSalsa and Sequential Quadratic Programming

(18)

A.G. Salinger, R.P. Pawlowski, J.N. Shadid, B. van Bloemen Waanders, R. Bartlett, G.C. Itle, L. Biegler

III Multifidelity Models and Inexactness

First-Order Approximation and Model Management in Optimization

(17)

Natalia M. Alexandrov, Robert Michael Lewis

Multifidelity Global Optimization Using DIRECT

(13)

Steven E. Cox, Raphael T. Haftka

Inexactness Issues in the Lagrange-Newton-Krylov-Schur Method for PDE-constrained Optimization

(24)

George Biros, Omar Ghattas

IV Sensitivities for PDE-based Optimization

Solution Adapted Mesh Refinement and Sensitivity Analysis for Parabolic Partial Differential Equation Systems

117

(16)

Shengtai Li, Linda R. Petzold, James M. Hyman

Challenges and Opportunities in Using Automatic Differentiation with Object-Oriented Toolkits for Scientific Computing

133

(15)

Paul Hovland, Steven Lee, Lois Mclnnes, Boyang Norris, Barry Smith

Piggyback Differentiation and Optimization

148

(19)

Andreas Griewank, Christèle Faure

V NLP Algorithms and Inequality Constraints

Assessing the Potential of Interior Methods for Nonlinear Optimization

167

(17)

José Luis Morales, Jorge Nocedal, Richard A. Waltz, Guanghui Lin, Jean-Pierre Goux

An Interior-Point Algorithm for Large Scale Optimization

184

(15)

John T. Betts, Samuel K. Eldersveld, Paul D. Frank, John G. Lewis

SQP SAND Strategies that Link to Existing Modeling Systems

199

(19)

Lorenz T. Biegler and Andreas Wächter

Interior Methods For a Class of Elliptic Variational Inequalities

218

(18)

Randolph E. Bank, Philip E. Gill, Roummel F. Marcia

Hierarchical Control of a Linear Diffusion Equation

236

(17)

Anthony J. Kearsley, Jon W. Tolle, Paul T. Boggs

VI Time-Dependent Problems

A Sequential Quadratic Programming Method for Nonlinear Model Predictive Control

253

(15)

Kenneth R. Muske, James W. Howse

Reduced Order Modelling Approaches to PDE-Constrained Optimization Based on Proper Orthogonal Decomposition

268

(13)

Marco Fahl, Ekkehard W. Sachs

Adaptive Simulation, the Adjoint State Method, and Optimization

281

(20)

Mark S. Gockenbach, William W. Symes

VII Frameworks for PDE-Constrained Optimization

The SIERRA Framework for Developing Advanced Parallel Mechanics Applications

301

(15)

James R. Stewart, H. Carter Edwards

rSQP++ : An Object-Oriented Framework for Successive Quadratic Programming

316

(15)

Roscoe A. Bartlett, Lorenz T. Biegler

Sundance Rapid Prototyping Tool for Parallel PDE Optimization

331

(12)

Kevin R. Long

Color Plates

343

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