Advances in Evolutionary and Deterministic Methods for Design, Optimization and Control in Engineering and Sciences, Gaspar-Cunha Antуnio, Periaux Jacques, Giannakoglou Kyriakos C.
Описание: This book presents improved and extended versions of selected papers from EUROGEN 2019, a conference with interest on developing or applying evolutionary and deterministic methods in optimization of design and emphasizing on industrial and societal applications.
Описание: 1. Keynote: Risk, Optimization and Meanfield Type Control, by Olivier Pironneau and Mathieu Lauriиre.- 2. Surrogate-Based Optimization in Aerodynamic Design.- A Review of Surrogate Modeling Techniques for Aerodynamic Analysis and Optimization: Current Limitations and Future Challenges in Industry, by Raul Yondo, Kamil Bobrowski, Esther Andrйs and Eusebio Valero.- Constrained Single-Point Aerodynamic Shape Optimization of the DPW-W1 wing through Evolutionary Programming and Support Vector Machines, by E. Andrйs-Pйrez, D. Gonzбlez-Juбrez, M. J. Martin-Burgos, L. Carro-Calvo.- Enabling of Large Scale Aerodynamic Shape Optimization through POD-based Reduced-Order Modeling and Free Form Deformation, by A. Scardigli, R. Arpa, A. Chiarini and H. Telib.- Application of Surrogate-based Optimization Techniques to Aerodynamic Design Cases, by Emiliano Iuliano and Domenico Quagliarella.- Efficient Global Optimization method for multipoint airfoil design, by Davide Cinquegrana and Emiliano Iuliano.- 3. Adjoint Methods for Steady and Unsteady Optimization.- Checkpointing with time gaps for unsteady adjoint CFD, by Jan Christian Hueckelheim and Jens-Dominik Mueller.- Shape Optimization ofWind Turbine Blades using the Continuous Adjoint Method and Volumetric NURBS on a GPU Cluster, by Konstantinos T. Tsiakas, Xenofon S. Trompoukis, Varvara G. Asouti and Kyriakos C. Giannakoglou.- Aerodynamic Shape Optimization Using the Adjoint-based Truncated Newton Method, by Evangelos M. Papoutsis-Kiachagias, Mehdi Ghavami Nejad, and Kyriakos C. Giannakoglou.- Application of the adjoint method for the reconstruction of the boundary condition in unsteady shallow water flow simulation, by Asier Lacasta, Daniel Caviedes-Voulliиme and Pilar Garcнa-Navarro.- Aerodynamic Optimization of Car Shapes using the Continuous Adjoint Method and an RBF Morpher, by E.M. Papoutsis-Kiachagias, S. Porziani, C. Groth, M.E. Biancolini, E. Costa and K.C. Giannakoglou.- 4. Holistic Optimization in Marine Design.- Upfront CAD - Parametric modeling techniques for shape optimization, by S. Harries, C. Abt and M. Brenner.- Simulation-based Design Optimization by Sequential Multi-criterion Adaptive Sampling and Dynamic Radial Basis Functions, by Matteo Diez, Silvia Volpi, Andrea Serani, Frederick Stern and Emilio F. Campana.- Application of Holistic Ship Optimization in Bulkcarrier Design and Operation, by Lampros Nikolopoulos, Evangelos Boulougouris.- 5. Game Strategies Combined with Evolutionary Computation.- Designing Networks in Cooperation with ACO, by E. D'Amato, E. Daniele and L. Mallozzi.- Augmented Lagrangian approach for constrained potential Nash games, by Lina Mallozzi and Domenico Quagliarella.- A Diversity Dynamic Territory Nash Strategy in Evolutionary Algorithms: Enhancing Performances in Reconstruction Problems in Structural Engineering, by David Greiner, Jacques Pйriaux, J.M. Emperador, B. Galvбn, G. Winter.- Interactive Inverse Modeling Based Multiobjective Evolutionary Algorithm, by Karthik Sindhya and Jussi Hakanen.- Multi-Disciplinary Design Optimization of Air-breathing Hypersonic Vehicle Using Pareto Games and Evolutionary Algorithms, by Peng Wu, Zhili Tang, Jacques Periaux.- 6. Optimisation under Uncertainty.- Innovative methodologies for Robust Design Optimization with large number of uncertainties using modeFRONTIER, by Alberto Clarich, Rosario Russo.- A Novel Method for Inverse Uncertainty Propagation, by Xin Chen, ArturoMolina-Crist obal, Marin D. Guenov, Varun C. Datta, Atif Riaz.- Uncertainty Sources in the Baseline Configuration for Robust Design of a Supersonic Natural Laminar Flow Wing-Body, by Domenico Quagliarella and Emiliano Iuliano.- Robust Airfoil Design in the Context of Multi-Objective Optimization, by Lisa Kusch and Nicolas R. Gauger.- An alternative formulation for design under uncertainty, by F. Fusi and P. M. Congedo and G. Geraci and G. Iaccarino.- Polynomial Representation of Model Uncertainty in Dynamical
Описание: Preface.- PART I: Adjoint Methods for Optimisation, Mesh Adaptation and Uncertainty Quantification.- Gradient projection, constraints and surface regularization methods in adjoint shape optimization, by Pavlos P. Alexias and Eugene De Villiers.- Adjoint Shape Optimisation using model Boundary Representation, by E. Andres-Perez et al..- CAD and Adjoint based Multipoint Optimization of an Axial Turbine Profile, by Ismael Sanchez Torreguitart, Tom Verstraete, and Lasse Mueller.- A Comparative Study of Two Different CAD-Based Mesh Deformation Methods for Structural Shape Optimization, by Marc Schwalbach, Tom Verstraete, Jens-Dominik Miller, and Nicolas R. Gauger.- Node-based Adjoint Surface Optimization of U-bend duct for pressure loss reduction, by Giacomo Alessi, Lilla Koloszar, Tom Verstraete, and J. van Beeck.- On the Properties of Solutions of the 2D Adjoint Euler Equations, by Carlos Lozano.- Finite Transformation Rigid Motion Mesh Morpher, by Athanasios G. Liatsikouras, Guillaume Pierrot, Gabriel Fougeron, and George S. Eleftheriou.- The Unsteady Continuous Adjoint Method Assisted by the Proper Generalized Decomposition Method, by V. S. Papageorgiou, K. D. Samouchos and K. C. Giannakoglou.- A Two-Step Mesh Adaptation Tool Based on RBF with application to turbomachinery Optimization Loops, by Flavio Gagliardi, Konstantinos T. Tsiakas and Kyriakos C. Giannakoglou.- Adjoint-based Aerodynamic Optimisation of Wing Shape Using Non-Uniform Rational B-splines, by Xingchen Zhang, Rejish Jesudasan and Jens-Dominik Mьller.- PART II: Surrogate-assisted Optimization of Real World problems.- A comparative evaluation of surrogate models for transonic wing shape optimization, by Emiliano Iuliano.- Study of the influence of the initial a-priori training dataset size in the efficiency and convergence of surrogate-based evolutionary optimization, by Daniel Gonzalez Juarez and Esther Andres Perez.- Garteur AD/AG52: Surrogate-based global optimization methods in preliminary aerodynamic design, by E. Andres-Perez et al..- A Response Surface Based Strategy for Accelerated Compressor Map Computation, by Dmitrij Ivanov, Dieter Bestle, and Christian Janke.- Surrogate-Based Shape Optimization of the ERCOFTAC Centrifugal Pump Impeller, by Remo De Donno and Stefano Rebay and Antonio Ghidoni.- CFD based Design Optimization of a Cabinet Nitrogen Generator, by Bбrbara Arizmendi Gutiйrrez and Edmondo Minisci.- Delaunay-based global optimization in nonconvex domains defined by hidden constraints, by Shahrouz Ryan Alimo, Pooriya Beyhaghi, and Thomas R. Bewley.- PART III: Applications of optimization in engineering design automation.- Optimized Vehicle Dynamics Virtual Sensing using Metaheuristic Optimization and Unscented Kalman Filter, by Manuel Acosta and Stratis Kanarachos.- On Combinatorial Problem Representation based Ascent Assembly Design Optimization, by Michael Hellwig, Doris Entner, Thorsten Prante, Alexandru-Ciprian Zavoianu, Martin Schwarz, and Klara Fink.- On the Optimization of 2D Path Network Layouts in Engineering Designs via Evolutionary Computation Techniques, by Alexandru-Ciprian Ziivoianu, Susanne Saminger-Platz, Doris Entner, Thorsten Prante, Michael Hellwig, Martin Schwarz, and Klara Fink.- Taking Advantage of 3D Printing so as to Simultaneously Reduce Weight and Mechanical Bonding Stress, by Markus Schatz, Robert Schweikle, Christian Lausch, Michael Jentsch and Werner Konrad.- Interactive Optimization of Path Planning for a Robot Enabled by Virtual Commissioning, by Ruth Fleisch, Doris Entner, Thorsten Prante, Reinhard Pfefferkorn.- Box-Type Boom Design using Surrogate Modeling: Introducing an Industrial Optimization Benchmark, by Philipp Fleck, Doris Entner, Clemens Munzer, Michael Kommenda, Thorsten Prante, Martin Schwarz, Martin Hachl, and Michael Affenzeller.- Knowledge Objects Enable Mass-Individualization, by Joel Johansson and Fredrik Elgh.- Free-form Optimization of a Shell Structure with Curvature Constraint,
Описание: This book contains thirty-five selected papers presented at the International Conference on Evolutionary and Deterministic Methods for Design, Optimization and Control with Applications to Industrial and Societal Problems (EUROGEN 2017). This was one of the Thematic Conferences of the European Community on Computational Methods in Applied Sciences (ECCOMAS).Topics treated in the various chapters reflect the state of the art in theoretical and numerical methods and tools for optimization, and engineering design and societal applications. The volume focuses particularly on intelligent systems for multidisciplinary design optimization (mdo) problems based on multi-hybridized software, adjoint-based and one-shot methods, uncertainty quantification and optimization, multidisciplinary design optimization, applications of game theory to industrial optimization problems, applications in structural and civil engineering optimum design and surrogate models based optimization methods in aerodynamic design.
Автор: Kevin L. Moore Название: Iterative Learning Control for Deterministic Systems ISBN: 1447119142 ISBN-13(EAN): 9781447119142 Издательство: Springer Рейтинг: Цена: 11398.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The text follows with a complete and unifying analysis of the learning control problem for linear LTI systems using a system-theoretic approach which offers insight into the nature of the solution of the learning control problem.
Описание: This book compares four parameters of problems in arbitrary information systems: complexity of problem representation and complexity of deterministic, nondeterministic, and strongly nondeterministic decision trees for problem solving.
Описание: This brief examines a deterministic, ODE-based model for gene regulatory networks (GRN) that incorporates nonlinearities and time-delayed feedback. One chapter is devoted to the analysis of GRNs under negative feedback with time delays and a special case of a homogenous GRN is considered.
Автор: Mohamad S. Alwan; Xinzhi Liu Название: Theory of Hybrid Systems: Deterministic and Stochastic ISBN: 9811080453 ISBN-13(EAN): 9789811080456 Издательство: Springer Рейтинг: Цена: 18294.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book is the first to present the application of the hybrid system theory to systems with EPCA (equations with piecewise continuous arguments). The hybrid system paradigm is a valuable modeling tool for describing a wide range of real-world applications. Moreover, although new technology has produced, and continues to produce highly hierarchical sophisticated machinery that cannot be analyzed as a whole system, hybrid system representation can be used to reduce the structural complexity of these systems. That is to say, hybrid systems have become a modeling priority, which in turn has led to the creation of a promising research field with several application areas. As such, the book explores recent developments in the area of deterministic and stochastic hybrid systems using the Lyapunov and Razumikhin–Lyapunov methods to investigate the systems’ properties. It also describes properties such as stability, stabilization, reliable control, H-infinity optimal control, input-to-state stability (ISS)/stabilization, state estimation, and large-scale singularly perturbed systems.
Описание: This book is intended for researchers active in the field of (blind) system identification and aims to provide new identification ideas/insights for dealing with challenging system identification problems.
Автор: El-Kebir Boukas; Zi-Kuan Liu Название: Deterministic and Stochastic Time-Delay Systems ISBN: 1461266025 ISBN-13(EAN): 9781461266020 Издательство: Springer Рейтинг: Цена: 12196.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Most practical processes such as chemical reactor, industrial furnace, heat exchanger, etc., are nonlinear stochastic systems, which makes their con- trol in general a hard problem.
Автор: Mohamad S. Alwan; Xinzhi Liu Название: Theory of Hybrid Systems: Deterministic and Stochastic ISBN: 9811340471 ISBN-13(EAN): 9789811340475 Издательство: Springer Рейтинг: Цена: 18294.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book is the first to present the application of the hybrid system theory to systems with EPCA (equations with piecewise continuous arguments). The hybrid system paradigm is a valuable modeling tool for describing a wide range of real-world applications. Moreover, although new technology has produced, and continues to produce highly hierarchical sophisticated machinery that cannot be analyzed as a whole system, hybrid system representation can be used to reduce the structural complexity of these systems. That is to say, hybrid systems have become a modeling priority, which in turn has led to the creation of a promising research field with several application areas. As such, the book explores recent developments in the area of deterministic and stochastic hybrid systems using the Lyapunov and Razumikhin–Lyapunov methods to investigate the systems’ properties. It also describes properties such as stability, stabilization, reliable control, H-infinity optimal control, input-to-state stability (ISS)/stabilization, state estimation, and large-scale singularly perturbed systems.
Описание: This book covers the most recent advances in the field of evolutionary multiobjective optimization. With the aim of drawing the attention of up-and coming scientists towards exciting prospects at the forefront of computational intelligence, the authors have made an effort to ensure that the ideas conveyed herein are accessible to the widest audience. The book begins with a summary of the basic concepts in multi-objective optimization. This is followed by brief discussions on various algorithms that have been proposed over the years for solving such problems, ranging from classical (mathematical) approaches to sophisticated evolutionary ones that are capable of seamlessly tackling practical challenges such as non-convexity, multi-modality, the presence of multiple constraints, etc. Thereafter, some of the key emerging aspects that are likely to shape future research directions in the field are presented. These include: optimization in dynamic environments, multi-objective bilevel programming, handling high dimensionality under many objectives, and evolutionary multitasking. In addition to theory and methodology, this book describes several real-world applications from various domains, which will expose the readers to the versatility of evolutionary multi-objective optimization.
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