國立虎尾科技大學 |

Advances in Evolutionary and Deterministic Methods for Design, Optimization and Control in Engineering and Sciences

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Advances in Evolutionary and Deterministic Methods for Design, Optimization and Control in Engineering and Sciences/ edited by David Greiner, Blas Galván, Jacques Périaux, Nicolas Gauger, Kyriakos Giannakoglou, Gabriel Winter.
其他作者:	Greiner, David.
面頁冊數:	XI, 522 p. 240 illus.online resource. :
Contained By:	Springer Nature eBook
標題:	Engineering design. -
電子資源:	https://doi.org/10.1007/978-3-319-11541-2
ISBN:	9783319115412

Advances in Evolutionary and Deterministic Methods for Design, Optimization and Control in Engineering and Sciences
Advances in Evolutionary and Deterministic Methods for Design, Optimization and Control in Engineering and Sciences[electronic resource] /edited by David Greiner, Blas Galván, Jacques Périaux, Nicolas Gauger, Kyriakos Giannakoglou, Gabriel Winter. - 1st ed. 2015. - XI, 522 p. 240 illus.online resource. - Computational Methods in Applied Sciences,361871-3033 ;. - Computational Methods in Applied Sciences,36.

Preface -- Part 1: Theoretical and Numerical Methods and Tools for Optimization -- 1.1 Theoretical Methods and Tools -- 1.1.1 Multi-Objective Evolutionary Algorithms in Real-World Applications: Some Recent Results and Current Challenges, by Carlos A. Coello Coello -- 1.1.2 Hybrid Optimization Algorithms and Hybrid Response Surfaces, by George S. Dulikravich and Marcelo J. Colaco -- 1.1.3 A genetic algorithm for a sensor device location problem, by Egidio D'Amato, Elia Daniele and Lina Mallozzi -- 1.1.4 The Role of Artificial Neural Networks in Evolutionary Optimization: A Review, by Mustapha Maarouf, Adriel Sosa, Blas Galván, David Greiner, Gabriel Winter, Máximo Mendez and Ricardo Aguasca -- 1.1.5 Reliability-based Design Optimization with the Generalized Inverse Distribution Function, by Domenico Quagliarella, Giovanni Petrone and Gianluca Iaccarino -- 1.2 Numerical Methods and Tools -- 1.2.1 On the choice of surrogates for multilevel aircraft performance models, by Manon Bondouy, Sophie Jan, Serge Laporte and Christian Bes -- 1.2.2 Multi-objective design optimization using high-order statistics for CFD applications, by Pietro M. Congedo, Gianluca Geraci, Remi Abgrall and Gianluca Iaccarino -- 1.2.3 Extension of the One-Shot Method for Optimal Control with Unsteady PDEs, by Stefanie Gunther, Nicolas R. Gauger and Qiqi Wang -- 1.2.4 Adaptive Aerodynamic Design Optimization for Navier-Stokes using Shape Derivatives with Discontinuous Galerkin Methods, by Lena Kaland, Matthias Sonntag and Nicolas R. Gauger -- 1.2.5 Optimal Flow Control and Topology Optimization Using the Continuous Adjoint Method in Unsteady Flows, by Ioannis S. Kavvadias, George K. Karpouzas, Evangelos M. Paoutsis-Kiachagias, Dimitris I. Papadimitrou and Kyriakos C. Giannakoglou -- Part 2: Engineering Design and Societal Applications -- 2.1 Turbomachinery -- 2.1.1 Design optimization of the Primary Pump of a Nuclear Reactor, by Tom Verstraete and Lasse Mueller -- 2.1.2 Direct 3D Aerodynamic Optimization of Turbine Blades with GPU-accelerated CFD, by Philipp Amtsfeld, Dieter Bestle and Marcus Meyer -- 2.1.3 Evaluation of Surrogate Modelling Methods for Turbo-Machinery Component Design Optimization, by Gianluca Badjan, Carlo Poloni, Andrew Pike and Nadir Ince -- 2.1.4 Robust Aerodynamic Design Optimization of Horizontal Axis Wind Turbine Rotors, by Marco Caboni, Edmondo Minisci and Michele Sergio Campobaso -- 2.1.5 Horizontal axis hydroturbine shroud airfoil optimization, by Elia Daniele, Elios Ferrauto and Domenico P. Coiro -- 2.1.6 Parametric Blending and FE-Optimization of a Compressor Blisk Test Case, by Kai Karger and Dieter Bestle -- 2.1.7 Modular Automated Aerodynamic Compressor Design Process, by Fiete Poehlmann, Dieter Bestle, Peter Flassig and Michèl Hinz -- 2.1.8 Design-Optimization of a Compressor Blading on a GPU Cluster, by Konstantinos T. Tsiakas, Xenofon S. Trompoukis, Varvara G. Asouti and Kyriakos C. Giannakoglou -- 2.2 Structures, Materials and Civil Engineering -- 2.2.1 Immune and Swarm Optimization of Structures, by Tadeusz Burczyński, Arkadiusz Poteralski and Miroslaw Szczepanik -- 2.2.2 Investigation of three genotypes for mixed variable evolutionary optimization, by Rajan Filomeno Coelho, Manyu Xiao, Aurore Guglielmetti, Manuel Herrera and Weihong Zhang -- 2.2.3 A Study of Nash-Evolutionary Algorithms for Reconstruction Inverse Problems in Structural Engineering, by David Greiner, Jacques Périaux, José María Emperador, Blas Galván and Gabriel Winter -- 2.2.4 A comparative study on design optimization of polygonal and Bézier curve-shaped thin noise barriers using dual BEMformulation, by Rayco Toledo, Juan J. Aznárez, Orlando Maeso and David Greiner -- 2.2.5 A Discrete Adjoint Approach For Trailing-Edge Noise Minimization using Porous Material, by Beckett Y. Zhou, Nicolas R. Gauger, Seong R. Koh and Wolfgang Schröder -- 2.3 Aeronautics and Astronautics -- 2.3.1 Conceptual Design of Single-Stage Launch Vehicle with Hybrid Rocket Engine Using Design Informatics, by Kazuhisa Chiba, Masahiro Kanazaki, Koki Kitagawa and Toru Shimada -- 2.3.2 Robust optimization of a helicopter rotor airfoil using multifidelity approach, by Francesca Fusi, Pietro Marco Congedo, Alberto Guardone and Giuseppe Quaranta -- 2.3.3 Computational results for flight test points distribution in the flight envelope, by Lina Mallozzi, Pierluigi De Paolis, Gabriele Di Francesco and Alessandro D'Argenio -- 2.3.4 Optimal Separation Control on the Flap of a 2D High-Lift Configuration, by Anil Nemili, Emre Ozkaya, Nicolas Gauger, Felix Kramer and Frank Thiele -- 2.4 Societal Applications -- 2.4.1 New Challenges and opportunities in reliability and risk based optimization, by Sebastián Martorell, Maryory Villamizar, Isabel Martón, Ana Sánchez and Sofía Carlos -- 2.4.2 Bi-objective Discrete PSO for Service-oriented VRPTW, by Julio Brito, Airam Expósito and José A. Moreno-Pérez -- 2.4.3 An approach for the evaluation of risk impact of changes addressing uncertainties in a Surveillance Requirement optimization context, by Sebastián Martorell, Maryory Villamizar, Isabel Martón, Carmen Armero and Ana Sánchez -- 2.4.4 Scalable Deployment of Efficient Transportation Optimization for SMEs and Public Sector, by Pekka Neittanmäki and Tuukka Puranen -- 2.5 Electrical and Electronical Applications -- 2.5.1 Estimation of the Electricity Demand of La Palma Island (Spain), by Begoña González, Antonio Pulido, Miguel Martínez and Gabriel Winter -- 2.5.2 Optimization of the Dimensionless Model of an Electrostatic Microswitch Based on AMGA Algorithm, by Jorge Santana-Cabrera, José Miguel Monzón-Verona, Francisco Jorge Santana-Martín, Santiago García-Alonso and Juan Antonio Montiel-Nelson -- 2.5.3 Generation of New Detection Codes for GPS Satellites Using NSGA-II, by Javier Sosa, Tomás Bautista, Daniel Alcaraz, Santiago García-Alonso and Juan A. Montiel-Nelson -- Author Index .

This book contains state-of-the-art contributions in the field of evolutionary and deterministic methods for design, optimization and control in engineering and sciences. Specialists have written each of the 34 chapters as extended versions of 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 2013). The conference was one of the Thematic Conferences of the European Community on Computational Methods in Applied Sciences (ECCOMAS). Topics treated in the various chapters are classified in the following sections: theoretical and numerical methods and tools for optimization (theoretical methods and tools; numerical methods and tools) and engineering design and societal applications (turbo machinery; structures, materials and civil engineering; aeronautics and astronautics; societal applications; electrical and electronics applications), focused 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.

ISBN: 9783319115412

Standard No.: 10.1007/978-3-319-11541-2doiSubjects--Topical Terms:

560518
Engineering design.

LC Class. No.: TA174

Dewey Class. No.: 620.0042

Advances in Evolutionary and Deterministic Methods for Design, Optimization and Control in Engineering and Sciences
LDR:08959nam a22004215i 4500 001 960769
003 DE-He213
005 20200630113611.0
007 cr nn 008mamaa
008 201211s2015 gw | s |||| 0|eng d
020 $a 9783319115412 $9 978-3-319-11541-2
024 7 $a 10.1007/978-3-319-11541-2 $2 doi
035 $a 978-3-319-11541-2
050 4 $a TA174
050 4 $a TA403.6
072 7 $a TBD $2 bicssc
072 7 $a TEC016020 $2 bisacsh
072 7 $a TBD $2 thema
082 0 4 $a 620.0042 $2 23
245 1 0 $a Advances in Evolutionary and Deterministic Methods for Design, Optimization and Control in Engineering and Sciences $h [electronic resource] / $c edited by David Greiner, Blas Galván, Jacques Périaux, Nicolas Gauger, Kyriakos Giannakoglou, Gabriel Winter.
250 $a 1st ed. 2015.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2015.
300 $a XI, 522 p. 240 illus. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a Computational Methods in Applied Sciences, $x 1871-3033 ; $v 36
505 0 $a Preface -- Part 1: Theoretical and Numerical Methods and Tools for Optimization -- 1.1 Theoretical Methods and Tools -- 1.1.1 Multi-Objective Evolutionary Algorithms in Real-World Applications: Some Recent Results and Current Challenges, by Carlos A. Coello Coello -- 1.1.2 Hybrid Optimization Algorithms and Hybrid Response Surfaces, by George S. Dulikravich and Marcelo J. Colaco -- 1.1.3 A genetic algorithm for a sensor device location problem, by Egidio D'Amato, Elia Daniele and Lina Mallozzi -- 1.1.4 The Role of Artificial Neural Networks in Evolutionary Optimization: A Review, by Mustapha Maarouf, Adriel Sosa, Blas Galván, David Greiner, Gabriel Winter, Máximo Mendez and Ricardo Aguasca -- 1.1.5 Reliability-based Design Optimization with the Generalized Inverse Distribution Function, by Domenico Quagliarella, Giovanni Petrone and Gianluca Iaccarino -- 1.2 Numerical Methods and Tools -- 1.2.1 On the choice of surrogates for multilevel aircraft performance models, by Manon Bondouy, Sophie Jan, Serge Laporte and Christian Bes -- 1.2.2 Multi-objective design optimization using high-order statistics for CFD applications, by Pietro M. Congedo, Gianluca Geraci, Remi Abgrall and Gianluca Iaccarino -- 1.2.3 Extension of the One-Shot Method for Optimal Control with Unsteady PDEs, by Stefanie Gunther, Nicolas R. Gauger and Qiqi Wang -- 1.2.4 Adaptive Aerodynamic Design Optimization for Navier-Stokes using Shape Derivatives with Discontinuous Galerkin Methods, by Lena Kaland, Matthias Sonntag and Nicolas R. Gauger -- 1.2.5 Optimal Flow Control and Topology Optimization Using the Continuous Adjoint Method in Unsteady Flows, by Ioannis S. Kavvadias, George K. Karpouzas, Evangelos M. Paoutsis-Kiachagias, Dimitris I. Papadimitrou and Kyriakos C. Giannakoglou -- Part 2: Engineering Design and Societal Applications -- 2.1 Turbomachinery -- 2.1.1 Design optimization of the Primary Pump of a Nuclear Reactor, by Tom Verstraete and Lasse Mueller -- 2.1.2 Direct 3D Aerodynamic Optimization of Turbine Blades with GPU-accelerated CFD, by Philipp Amtsfeld, Dieter Bestle and Marcus Meyer -- 2.1.3 Evaluation of Surrogate Modelling Methods for Turbo-Machinery Component Design Optimization, by Gianluca Badjan, Carlo Poloni, Andrew Pike and Nadir Ince -- 2.1.4 Robust Aerodynamic Design Optimization of Horizontal Axis Wind Turbine Rotors, by Marco Caboni, Edmondo Minisci and Michele Sergio Campobaso -- 2.1.5 Horizontal axis hydroturbine shroud airfoil optimization, by Elia Daniele, Elios Ferrauto and Domenico P. Coiro -- 2.1.6 Parametric Blending and FE-Optimization of a Compressor Blisk Test Case, by Kai Karger and Dieter Bestle -- 2.1.7 Modular Automated Aerodynamic Compressor Design Process, by Fiete Poehlmann, Dieter Bestle, Peter Flassig and Michèl Hinz -- 2.1.8 Design-Optimization of a Compressor Blading on a GPU Cluster, by Konstantinos T. Tsiakas, Xenofon S. Trompoukis, Varvara G. Asouti and Kyriakos C. Giannakoglou -- 2.2 Structures, Materials and Civil Engineering -- 2.2.1 Immune and Swarm Optimization of Structures, by Tadeusz Burczyński, Arkadiusz Poteralski and Miroslaw Szczepanik -- 2.2.2 Investigation of three genotypes for mixed variable evolutionary optimization, by Rajan Filomeno Coelho, Manyu Xiao, Aurore Guglielmetti, Manuel Herrera and Weihong Zhang -- 2.2.3 A Study of Nash-Evolutionary Algorithms for Reconstruction Inverse Problems in Structural Engineering, by David Greiner, Jacques Périaux, José María Emperador, Blas Galván and Gabriel Winter -- 2.2.4 A comparative study on design optimization of polygonal and Bézier curve-shaped thin noise barriers using dual BEMformulation, by Rayco Toledo, Juan J. Aznárez, Orlando Maeso and David Greiner -- 2.2.5 A Discrete Adjoint Approach For Trailing-Edge Noise Minimization using Porous Material, by Beckett Y. Zhou, Nicolas R. Gauger, Seong R. Koh and Wolfgang Schröder -- 2.3 Aeronautics and Astronautics -- 2.3.1 Conceptual Design of Single-Stage Launch Vehicle with Hybrid Rocket Engine Using Design Informatics, by Kazuhisa Chiba, Masahiro Kanazaki, Koki Kitagawa and Toru Shimada -- 2.3.2 Robust optimization of a helicopter rotor airfoil using multifidelity approach, by Francesca Fusi, Pietro Marco Congedo, Alberto Guardone and Giuseppe Quaranta -- 2.3.3 Computational results for flight test points distribution in the flight envelope, by Lina Mallozzi, Pierluigi De Paolis, Gabriele Di Francesco and Alessandro D'Argenio -- 2.3.4 Optimal Separation Control on the Flap of a 2D High-Lift Configuration, by Anil Nemili, Emre Ozkaya, Nicolas Gauger, Felix Kramer and Frank Thiele -- 2.4 Societal Applications -- 2.4.1 New Challenges and opportunities in reliability and risk based optimization, by Sebastián Martorell, Maryory Villamizar, Isabel Martón, Ana Sánchez and Sofía Carlos -- 2.4.2 Bi-objective Discrete PSO for Service-oriented VRPTW, by Julio Brito, Airam Expósito and José A. Moreno-Pérez -- 2.4.3 An approach for the evaluation of risk impact of changes addressing uncertainties in a Surveillance Requirement optimization context, by Sebastián Martorell, Maryory Villamizar, Isabel Martón, Carmen Armero and Ana Sánchez -- 2.4.4 Scalable Deployment of Efficient Transportation Optimization for SMEs and Public Sector, by Pekka Neittanmäki and Tuukka Puranen -- 2.5 Electrical and Electronical Applications -- 2.5.1 Estimation of the Electricity Demand of La Palma Island (Spain), by Begoña González, Antonio Pulido, Miguel Martínez and Gabriel Winter -- 2.5.2 Optimization of the Dimensionless Model of an Electrostatic Microswitch Based on AMGA Algorithm, by Jorge Santana-Cabrera, José Miguel Monzón-Verona, Francisco Jorge Santana-Martín, Santiago García-Alonso and Juan Antonio Montiel-Nelson -- 2.5.3 Generation of New Detection Codes for GPS Satellites Using NSGA-II, by Javier Sosa, Tomás Bautista, Daniel Alcaraz, Santiago García-Alonso and Juan A. Montiel-Nelson -- Author Index .
520 $a This book contains state-of-the-art contributions in the field of evolutionary and deterministic methods for design, optimization and control in engineering and sciences. Specialists have written each of the 34 chapters as extended versions of 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 2013). The conference was one of the Thematic Conferences of the European Community on Computational Methods in Applied Sciences (ECCOMAS). Topics treated in the various chapters are classified in the following sections: theoretical and numerical methods and tools for optimization (theoretical methods and tools; numerical methods and tools) and engineering design and societal applications (turbo machinery; structures, materials and civil engineering; aeronautics and astronautics; societal applications; electrical and electronics applications), focused 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.
650 0 $a Engineering design. $3 560518
650 0 $a Mechanics. $3 527684
650 0 $a Mechanics, Applied. $3 596630
650 0 $a Computer mathematics. $3 1199796
650 0 $a Mathematical optimization. $3 527675
650 1 4 $a Engineering Design. $3 670857
650 2 4 $a Theoretical and Applied Mechanics. $3 670861
650 2 4 $a Computational Science and Engineering. $3 670319
650 2 4 $a Optimization. $3 669174
700 1 $a Greiner, David. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1064161
700 1 $a Galván, Blas. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1254845
700 1 $a Périaux, Jacques. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1254846
700 1 $a Gauger, Nicolas. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1254847
700 1 $a Giannakoglou, Kyriakos. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1254848
700 1 $a Winter, Gabriel. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1254849
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783319115429
776 0 8 $i Printed edition: $z 9783319115405
776 0 8 $i Printed edition: $z 9783319364247
830 0 $a Computational Methods in Applied Sciences, $x 1871-3033 ; $v 36 $3 1254850
856 4 0 $u https://doi.org/10.1007/978-3-319-11541-2
912 $a ZDB-2-ENG
912 $a ZDB-2-SXE
950 $a Engineering (SpringerNature-11647)
950 $a Engineering (R0) (SpringerNature-43712)