Modeling and Convexity

Modeling and Convexity

By: Rubens Sampaio (author), Eduardo Souza de Cursi (author)Hardback

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Description

This reference book gives the reader a complete but comprehensive presentation of the foundations of convex analysis and presents applications to significant situations in engineering. The presentation of the theory is self-contained and the proof of all the essential results is given. The examples consider meaningful situations such as the modeling of curvilinear structures, the motion of a mass of people or the solidification of a material. Non convex situations are considered by means of relaxation methods and the connections between probability and convexity are explored and exploited in order to generate numerical algorithms.

About Author

Eduardo Souza De Cursi is Professor at the National Institute for Applied Sciences in Rouen, France, where he is also Dean of International Affairs and Director of the Laboratory for the Optimization and Reliability in Structural Mechanics. Rubens Sampaio is the author of Modeling and Convexity, published by Wiley.

Contents

Introduction ix PART 1 MOTIVATION: EXAMPLES AND APPLICATIONS 1 Chapter 1 Curvilinear Continuous Media 3 1.1 One-dimensional curvilinear media 4 1.2 Supple membranes 22 Chapter 2 Unilateral System Dynamics 33 2.1 Dynamics of ideally flexible strings 34 2.2 Contact dynamics 40 Chapter 3 A Simplified Model of Fusion/Solidification 53 3.1 A simplified model of phase transition 53 Chapter 4 Minimization of a Non-Convex Function 61 4.1 Probabilities, convexity and global optimization 61 Chapter 5 Simple Models of Plasticity 69 5.1 Ideal elastoplasticity 72 PART 2 THEORETICAL ELEMENTS 77 Chapter 6 Elements of Set Theory 79 6.1 Elementary notions and operations on sets 80 6.2 The axiomof choice 83 6.3 Zorn's lemma 89 Chapter 7 Real Hilbert Spaces 97 7.1 Scalar product and norm 99 7.2 Bases anddimensions 107 7.3 Open sets and closed sets 114 7.4 Sequences 123 7.5 Linear functionals 137 7.6 Complete space 146 7.7 Orthogonal projection onto a vector subspace 160 7.8 Riesz's representationtheory 167 7.9 Weak topology 173 7.10 Separable spaces: Hilbert bases and series 184 Chapter 8 Convex Sets 201 8.1 Hyperplanes 201 8.2 Convexsets 208 8.3 Convexhulls 212 8.4 Orthogonal projection on a convex set 217 8.5 Separationtheorems 228 8.6 Convexcone 241 Chapter 9 Functionals on a Hilbert Space 253 9.1 Basic notions 254 9.2 Convexfunctionals 261 9.3 Semi-continuous functionals 271 9.4 Affine functionals 298 9.5 Convexification and LSC regularization 303 9.6 Conjugate functionals 320 9.7 Subdifferentiability 331 Chapter 10 Optimization 361 10.1 The optimization problem 361 10.2 Basic notions 362 10.3 Fundamental results 374 Chapter 11 Variational Problems 421 11.1 Fundamental notions 421 11.2 Zeros of operators 455 11.3 Variational inequations 463 11.4 Evolutionequations 469 Bibliography 487 Index 495

Product Details

  • ISBN13: 9781848211773
  • Format: Hardback
  • Number Of Pages: 504
  • ID: 9781848211773
  • weight: 912
  • ISBN10: 1848211775

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