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Metaheuristics-Based Materials Optimization: Enhancing Materials Applications: Elsevier Series in Mechanics of Advanced Materials

Editat de Harbinder Singh, Shailendra Rajput, Abhishek Sharma
en Limba Engleză Paperback – mar 2025
Metaheuristics-Based Materials Optimization: Enhancing Materials Applications provides a guide to using metaheuristics-based computational techniques to improve the design, performance, and broaden the applications of various materials. The book fuses optimization algorithms with materials engineering, enabling more accurate simulations and models for analyzing and predicting the behavior of materials under different conditions, allowing for design of materials with improved performance, durability, energy efficiency, cost-effectiveness, and other desired characteristics. Metaheuristic approaches for material synthesis and design, structural optimization, material characterization, property prediction, and process optimization are all covered, as are comparisons of different algorithms, step-by-step guidelines on how to implement them, and case studies of them being applied in real-world settings.

  • Provides a guide to using metaheuristics-based computational techniques to improve the design, performance, and broaden the applications of various materials
  • Presents real-world case studies as well as commonly encountered problems and their solutions
  • Allows for more accurate modeling, better material design, and development of materials tailored for specific applications
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Specificații

ISBN-13: 9780443291623
ISBN-10: 0443291624
Pagini: 330
Dimensiuni: 152 x 229 mm
Editura: ELSEVIER SCIENCE
Seria Elsevier Series in Mechanics of Advanced Materials


Cuprins

1. Introduction to Metaheuristic Algorithms
2. Overview of metaheuristic algorithms and their relevance to materials applications
3. Introduction to optimization techniques commonly used in materials science
4. Detailed exploration of metaheuristic algorithms applicable to materials-based optimization
5. Guidelines for selecting and customizing metaheuristic algorithms for specific materials applications
6. Real-world case studies demonstrating the successful application of metaheuristic algorithms in materials science and engineering
7. Step-by-step methodologies for integrating metaheuristic algorithms into materials-based processes and designs
8. Methods for evaluating and comparing the performance of metaheuristic algorithms in materials applications
9. Discussion of challenges and limitations encountered when applying metaheuristic algorithms to materials applications
10. Consideration of ethical, environmental, and societal implications associated with optimizing materials applications
11. Summary of key insights, methodologies, and best practices discussed throughout the book