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Computational Methods for Optimal Design and Control (Progress in Systems and Control Theory)
 
 
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Computational Methods for Optimal Design and Control (Progress in Systems and Control Theory) [Hardcover]

J. Borggaard (Author), John Burns (Author), Scott Schreck (Author)

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Book Description

0817640649 978-0817640644 October 23, 1998 1
This volume contains the proceedings of the Second International Workshop on Optimal Design and Control, held in Arlington, Virginia, USA, in October 1997. The workshop was a gathering of engineers and mathematicians involved in research in control and optimization, with the emphasis placed on optimal design problems governed by partial differential inequalities. The issues presented have applications to aerodynamic design, fluid flows, materials processing, inverse design and feedback control.

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Inside This Book (learn more)
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
shape differential equation, actuator placement, pressure distribution, multidisciplinary design optimization, sensitivity equation approach, reference design problem, continuous sensitivity equations, exact flow solution, pseudodifferential representation, discrete adjoint problem, maximum spatial transient growth, sensitivity calculation methods, computational facilitators, discrete flow equations, interface contraction, adjoint equation approach, sensitivity equation method, simplex gradient, noisy optimization problems, feedback kernel, boundary variation technique, actual convergence rate, finite difference sensitivity, hump modes, free convection problems
Key Phrases - Capitalized Phrases (CAPs): (learn more)
New York, Technical Report, Crystal Growth, Non Smooth Field, Fluid Mech, Nicholas Zabaras, Langley Research Center, Mathematical View Point, Aerodynamic Design-Optimization, Boundary Layers, Adjoint-Based Methods, Rice University, Journal of Computational Physics, Visual Tracking, Air Force Office of Scientific Research, Cambridge University Press, Virginia Tech, Academic Press, Modern Optimization Methods, Computer Methods, Springer Verlag, Scientific Computing, Optimization Using Surrogate Objectives, Semi-Automatic Differentiation, Partial Differential Equations
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