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Design engineer's reference guide : mathematics, mechanics, and thermodynamics / / Keith L. Richards
| Design engineer's reference guide : mathematics, mechanics, and thermodynamics / / Keith L. Richards |
| Autore | Richards Keith L. |
| Pubbl/distr/stampa | Boca Raton, FL : , : CRC Press, , [2014] |
| Descrizione fisica | 1 online resource (350 p.) |
| Disciplina | 620.0042015118 |
| Soggetto topico |
Engineering design - Mathematical models
Industrial design |
| ISBN |
0-429-16844-6
1-5231-0769-3 1-4665-9286-9 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Front Cover; Contents; Preface; Author; Acknowledgement; Chapter 1: Mathematics; Chapter 2: Introduction to Numerical Methods; Chapter 3: Properties of Sections and Figures; Chapter 4: Statics; Chapter 5: Dynamics; Chapter 6: Mechanical Vibrations; Chapter 7: Introduction to Control Systems Modelling; Chapter 8: Heat and Temperature; Chapter 9: Thermodynamic Basics; Chapter 10: Fluid Mechanics; Chapter 11: Introduction to Linkages; Back Cover |
| Record Nr. | UNINA-9910789401303321 |
Richards Keith L.
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| Boca Raton, FL : , : CRC Press, , [2014] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Design engineer's reference guide : mathematics, mechanics, and thermodynamics / / Keith L. Richards
| Design engineer's reference guide : mathematics, mechanics, and thermodynamics / / Keith L. Richards |
| Autore | Richards Keith L. |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Boca Raton, FL : , : CRC Press, , [2014] |
| Descrizione fisica | 1 online resource (350 p.) |
| Disciplina | 620.0042015118 |
| Soggetto topico |
Engineering design - Mathematical models
Industrial design |
| ISBN |
1-04-007363-8
0-429-16844-6 1-5231-0769-3 1-4665-9286-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Front Cover; Contents; Preface; Author; Acknowledgement; Chapter 1: Mathematics; Chapter 2: Introduction to Numerical Methods; Chapter 3: Properties of Sections and Figures; Chapter 4: Statics; Chapter 5: Dynamics; Chapter 6: Mechanical Vibrations; Chapter 7: Introduction to Control Systems Modelling; Chapter 8: Heat and Temperature; Chapter 9: Thermodynamic Basics; Chapter 10: Fluid Mechanics; Chapter 11: Introduction to Linkages; Back Cover |
| Record Nr. | UNINA-9910973837903321 |
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Richards Keith L.
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| Boca Raton, FL : , : CRC Press, , [2014] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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EngOpt 2018 Proceedings of the 6th International Conference on Engineering Optimization / / edited by H.C. Rodrigues, J. Herskovits, C.M. Mota Soares, A.L. Araújo, J.M. Guedes, J.O. Folgado, F. Moleiro, J. F. A. Madeira
| EngOpt 2018 Proceedings of the 6th International Conference on Engineering Optimization / / edited by H.C. Rodrigues, J. Herskovits, C.M. Mota Soares, A.L. Araújo, J.M. Guedes, J.O. Folgado, F. Moleiro, J. F. A. Madeira |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (1,486 pages) |
| Disciplina | 620.0042015118 |
| Soggetto topico |
Engineering design
Industrial management Engineering Design Industrial Management |
| ISBN | 3-319-97773-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910337647203321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Introduction to optimum design / / Jasbir Singh Arora
| Introduction to optimum design / / Jasbir Singh Arora |
| Autore | Arora Jasbir S. |
| Edizione | [Fourth edition.] |
| Pubbl/distr/stampa | London : , : Academic Press, , [2017] |
| Descrizione fisica | 1 online resource (xxi, 945 pages) : illustrations |
| Disciplina | 620.0042015118 |
| Collana | Gale eBooks |
| Soggetto topico | Engineering design - Mathematical models |
| ISBN |
0-12-800918-7
0-12-800806-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | I. The basic concepts -- Introduction to design optimization -- Optimum design problem formulation -- Graphical solution method and basic optimization concepts -- Optimum design concepts : optimality conditions -- More on optimum design concepts : optimaility conditions -- II. Numerical methods for continuous variable optimization -- 6. Optimum design : numerical solution process and Excel solver -- Optimum design with MATLAB -- Linear programming methods for optimum design -- More on linear programming methods and optimum design -- Numerical methods for unconstrained optimum design -- More on numerical methods for unconstrained optimum design -- Numerical methods for constrained optimum design -- More on numerical methods for constrained optimum design -- Practical applications of optimization -- III. Advanced and modern topics on optimum design --- Discrete variable optimum design concepts and methods -- Global optimization concepts and methods -- Nature-spired search methods -- Multi-objective optimum design concepts and methods -- 19. Additional topics on optimum design. |
| Record Nr. | UNINA-9910583337703321 |
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Arora Jasbir S.
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| London : , : Academic Press, , [2017] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Mathematical Modeling and Optimization of Complex Structures / / edited by Pekka Neittaanmäki, Sergey Repin, Tero Tuovinen
| Mathematical Modeling and Optimization of Complex Structures / / edited by Pekka Neittaanmäki, Sergey Repin, Tero Tuovinen |
| Edizione | [1st ed. 2016.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 |
| Descrizione fisica | 1 online resource (337 p.) |
| Disciplina | 620.0042015118 |
| Collana | Computational Methods in Applied Sciences |
| Soggetto topico |
Engineering design
Mathematics - Data processing Mechanics, Applied Engineering Design Computational Science and Engineering Engineering Mechanics |
| ISBN | 3-319-23564-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Foreword -- Preface -- Acknowledgements -- List of Contributors -- PART I Numerical Analysis -- Computational Issues for Optimal Shape Design in Hemodynamics, by Olivier Pironneau -- Functional A Posteriori Error Estimate for a Nonsymmetric Stationary Diffusion Problem, by Olli Mali -- Error Estimates of Uzawa Iteration Method for a Class of Bingham Fluids, by Marjaana Nokka and Sergey Repin -- An Automatic Differentiation Based Approach to the Level Set Method, by Jukka I. Toivanen -- PART II Mathematical Modeling in Mechanics -- Differential Fluid Mechanics Harmonization of Analytical, Numerical and Laboratory Models of Flows, by Yuli D. Chashechkin -- Effect of Friction in Sliding Contact of a Sphere over a Viscoelastic Halfspace, by Irina Goryacheva, Fedor Stepanov, and Elena Torskaya -- Stability of a Tensioned Axially Moving Plate Subjected to Cross-Direction Potential Flow, by Juha Jeronen, Tytti Saksa, and Tero Tuovinen -- Multiaxial fatigue criteria and durability of titanium compressordisks in low- and very-high-cycle fatigue modes, by Nikolay Burago and Ilia Nikitin -- Dynamic Analysis for Axially Moving Viscoelastic PoyntingThompson Beams, by Tytti Saksa and Juha Jeronen -- A projection approach to analysis of natural vibrations for beams with nonsymmetric cross sections, by Vasily Saurin and Georgy Kostin -- On bifurcation analysis of implicitly given functionals in the theory of elastic stability, by Nikolay Banichuk, Alexander Barsuk, Juha Jeronen, Pekka Neittaanmäki, and Tero Tuovinen -- PART III Optimization -- Proximal Bundle Method for Nonsmooth and Nonconvex Multiobjective Optimization, by Marko M. Mäkelä, Napsu Karmitsa and Outi Wilppu -- Efficient Parallel Nash Genetic Algorithm for solving Inverse Problems in Structural Engineering, by Jacques Périaux and David Greiner -- Efficient variational design sensitivity analysis, by Franz-Joseph Barthold, Nikolai Gerzen, Wojciech Kijanski, and Daniel Materna -- A Variational Approach to Modelling and Optimization in Elastic Structure Dynamics, by Georgy Kostin and Vasily Saurin -- Contact Optimization Problems for Stationary and Sliding Conditions, by István Páczelt, Attila Baksa, and Zenon Mroz -- Some Problems of Multipurpose Optimization for Deformed Bodies and Structures, by Alexander Sinitsin, Svetlana Ivanova, Evgeniy Makeev and Nikolay Banichuk. |
| Record Nr. | UNINA-9910254209003321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Metaheuristics for big data . volume 5 / / Clarisse Dhaenens, Laetitia Jourdan
| Metaheuristics for big data . volume 5 / / Clarisse Dhaenens, Laetitia Jourdan |
| Autore | Dhaenens Clarisse |
| Pubbl/distr/stampa | London, [England] ; ; Hoboken, New Jersey : , : ISTE : , : Wiley, , 2016 |
| Descrizione fisica | 1 online resource (216 p.) |
| Disciplina | 620.0042015118 |
| Collana | Computer Engineering Series : Metaheuristics Set |
| Soggetto topico |
Engineering design - Mathematical models
Cluster analysis Combinatorial optimization |
| ISBN |
1-119-34760-2
1-119-34756-4 1-119-34758-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover; Title Page ; Copyright ; Contents; Acknowledgments; Introduction; 1. Optimization and Big Data; 1.1. Context of Big Data; 1.1.1. Examples of situations; 1.1.2. Definitions; 1.1.3. Big Data challenges; 1.1.4. Metaheuristics and Big Data; 1.2. Knowledge discovery in Big Data; 1.2.1. Data mining versus knowledge discovery; 1.2.2. Main data mining tasks; 1.2.3. Data mining tasks as optimization problems; 1.3. Performance analysis of data mining algorithms ; 1.3.1. Context; 1.3.2. Evaluation among one or several dataset(s); 1.3.3. Repositories and datasets; 1.4. Conclusion
2. Metaheuristics - A Short Introduction2.1. Introduction; 2.1.1. Combinatorial optimization problems; 2.1.2. Solving a combinatorial optimization problem; 2.1.3. Main types of optimization methods; 2.2. Common concepts of metaheuristics; 2.2.1. Representation/encoding; 2.2.2. Constraint satisfaction; 2.2.3. Optimization criterion/objective function; 2.2.4. Performance analysis; 2.3. Single solution-based/local search methods; 2.3.1. Neighborhood of a solution; 2.3.2. Hill climbing algorithm; 2.3.3. Tabu Search; 2.3.4. Simulated annealing and threshold acceptance approach 2.3.5. Combining local search approaches2.4. Population-based metaheuristics; 2.4.1. Evolutionary computation; 2.4.2. Swarm intelligence; 2.5. Multi-objective metaheuristics; 2.5.1. Basic notions in multi-objective optimization; 2.5.2. Multi-objective optimization using metaheuristics; 2.5.3. Performance assessment in multi-objective optimization; 2.6. Conclusion; 3. Metaheuristics and Parallel Optimization; 3.1. Parallelism; 3.1.1. Bit-level; 3.1.2. Instruction-level parallelism; 3.1.3. Task and data parallelism; 3.2. Parallel metaheuristics ; 3.2.1. General concepts 3.2.2. Parallel single solution-based metaheuristics3.2.3. Parallel population-based metaheuristics; 3.3. Infrastructure and technologies for parallel metaheuristics ; 3.3.1. Distributed model; 3.3.2. Hardware model; 3.4. Quality measures ; 3.4.1. Speedup; 3.4.2. Efficiency; 3.4.3. Serial fraction; 3.5. Conclusion; 4. Metaheuristics and Clustering; 4.1. Task description; 4.1.1. Partitioning methods; 4.1.2. Hierarchical methods; 4.1.3. Grid-based methods; 4.1.4. Density-based methods; 4.2. Big Data and clustering; 4.3. Optimization model; 4.3.1. A combinatorial problem; 4.3.2. Quality measures 4.3.3. Representation4.4. Overview of methods; 4.5. Validation; 4.5.1. Internal validation; 4.5.2. External validation; 4.6. Conclusion; 5. Metaheuristics and Association Rules; 5.1. Task description and classical approaches ; 5.1.1. Initial problem; 5.1.2. A priori algorithm; 5.2. Optimization model; 5.2.1. A combinatorial problem; 5.2.2. Quality measures; 5.2.3. A monoor a multi-objective problem?; 5.3. Overview of metaheuristics for the association rules mining problem; 5.3.1. Generalities; 5.3.2. Metaheuristics for categorical association rules 5.3.3. Evolutionary algorithms for quantitative association rules |
| Record Nr. | UNINA-9910137073903321 |
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Dhaenens Clarisse
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||
| London, [England] ; ; Hoboken, New Jersey : , : ISTE : , : Wiley, , 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Metaheuristics for big data . volume 5 / / Clarisse Dhaenens, Laetitia Jourdan
| Metaheuristics for big data . volume 5 / / Clarisse Dhaenens, Laetitia Jourdan |
| Autore | Dhaenens Clarisse |
| Pubbl/distr/stampa | London, [England] ; ; Hoboken, New Jersey : , : ISTE : , : Wiley, , 2016 |
| Descrizione fisica | 1 online resource (216 p.) |
| Disciplina | 620.0042015118 |
| Collana | Computer Engineering Series : Metaheuristics Set |
| Soggetto topico |
Engineering design - Mathematical models
Cluster analysis Combinatorial optimization |
| ISBN |
1-119-34760-2
1-119-34756-4 1-119-34758-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover; Title Page ; Copyright ; Contents; Acknowledgments; Introduction; 1. Optimization and Big Data; 1.1. Context of Big Data; 1.1.1. Examples of situations; 1.1.2. Definitions; 1.1.3. Big Data challenges; 1.1.4. Metaheuristics and Big Data; 1.2. Knowledge discovery in Big Data; 1.2.1. Data mining versus knowledge discovery; 1.2.2. Main data mining tasks; 1.2.3. Data mining tasks as optimization problems; 1.3. Performance analysis of data mining algorithms ; 1.3.1. Context; 1.3.2. Evaluation among one or several dataset(s); 1.3.3. Repositories and datasets; 1.4. Conclusion
2. Metaheuristics - A Short Introduction2.1. Introduction; 2.1.1. Combinatorial optimization problems; 2.1.2. Solving a combinatorial optimization problem; 2.1.3. Main types of optimization methods; 2.2. Common concepts of metaheuristics; 2.2.1. Representation/encoding; 2.2.2. Constraint satisfaction; 2.2.3. Optimization criterion/objective function; 2.2.4. Performance analysis; 2.3. Single solution-based/local search methods; 2.3.1. Neighborhood of a solution; 2.3.2. Hill climbing algorithm; 2.3.3. Tabu Search; 2.3.4. Simulated annealing and threshold acceptance approach 2.3.5. Combining local search approaches2.4. Population-based metaheuristics; 2.4.1. Evolutionary computation; 2.4.2. Swarm intelligence; 2.5. Multi-objective metaheuristics; 2.5.1. Basic notions in multi-objective optimization; 2.5.2. Multi-objective optimization using metaheuristics; 2.5.3. Performance assessment in multi-objective optimization; 2.6. Conclusion; 3. Metaheuristics and Parallel Optimization; 3.1. Parallelism; 3.1.1. Bit-level; 3.1.2. Instruction-level parallelism; 3.1.3. Task and data parallelism; 3.2. Parallel metaheuristics ; 3.2.1. General concepts 3.2.2. Parallel single solution-based metaheuristics3.2.3. Parallel population-based metaheuristics; 3.3. Infrastructure and technologies for parallel metaheuristics ; 3.3.1. Distributed model; 3.3.2. Hardware model; 3.4. Quality measures ; 3.4.1. Speedup; 3.4.2. Efficiency; 3.4.3. Serial fraction; 3.5. Conclusion; 4. Metaheuristics and Clustering; 4.1. Task description; 4.1.1. Partitioning methods; 4.1.2. Hierarchical methods; 4.1.3. Grid-based methods; 4.1.4. Density-based methods; 4.2. Big Data and clustering; 4.3. Optimization model; 4.3.1. A combinatorial problem; 4.3.2. Quality measures 4.3.3. Representation4.4. Overview of methods; 4.5. Validation; 4.5.1. Internal validation; 4.5.2. External validation; 4.6. Conclusion; 5. Metaheuristics and Association Rules; 5.1. Task description and classical approaches ; 5.1.1. Initial problem; 5.1.2. A priori algorithm; 5.2. Optimization model; 5.2.1. A combinatorial problem; 5.2.2. Quality measures; 5.2.3. A monoor a multi-objective problem?; 5.3. Overview of metaheuristics for the association rules mining problem; 5.3.1. Generalities; 5.3.2. Metaheuristics for categorical association rules 5.3.3. Evolutionary algorithms for quantitative association rules |
| Record Nr. | UNINA-9910813734603321 |
|
Dhaenens Clarisse
|
||
| London, [England] ; ; Hoboken, New Jersey : , : ISTE : , : Wiley, , 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||