Metaheuristics-Based Materials Optimization: Enhancing Materials Applications - Brossura

 
9780443291623: Metaheuristics-Based Materials Optimization: Enhancing Materials Applications
Brossura
ISBN 10: 0443291624 ISBN 13: 9780443291623
Casa editrice: Woodhead Publishing, 2025

Sinossi

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.

Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.

Informazioni sugli autori

Harbinder Singh received the B.Tech. (Hons.) degree in Electronics and Communication Engineering from Kurukshetra University, Kurukshetra, India, in 2011, the M.Tech. degree with specialization in antennas from Punjab Technical University, Jalandhar, India, in 2014, and the Ph.D. degree in Electronics and Communication Engineering from Chandigarh University, India, in 2019. He is currently working as an Associate Professor at Chandigarh University, Punjab, India. He has substantial teaching and research experience and has published research articles in SCI‑ and Scopus‑indexed journals. He is the author of the book Electromagnetics and Antennas. His primary research interests include metamaterials, smart antennas, antenna arrays, radio absorbers, sensors, frequency‑reconfigurable antennas, MIMO antennas, wearable antennas, SAR, and UWB antennas.

Dr. Shailendra Rajput is an Associate Professor at Department of Physics, University Centre for Research & Development, Chandigarh University, Mohali, India. He was a postdoctoral fellow at Ariel University, Israel (September 2017-April 2021) and Xi'an Jiaotong University, China (May 2015-July 2017). His main research work is associated with Energy harvesting, Solar energy, Energy storage, Ferroelectricity, Piezoelectricity, and biomedical application of electromagnetic waves.

Dr. Abhishek Sharma received his master’s degree in robotics engineering from the University of Petroleum and Energy Studies (UPES), Dehradun, India, in 2014. He was a Senior Research Fellow in a DST funded project under the Technology Systems Development Scheme and worked as an Assistant Professor with the Department of Electronics and Instrumentation, UPES. He also worked as a research fellow in Ariel university (Israel) and received Emerging Scientist award in 2021. Currently he is working as a research assistant professor at Graphic Era University (India). His research interests include machine learning, optimization theory, swarm intelligence, embedded system, control and robotics.

Dalla quarta di copertina

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.

Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.

Editore
Woodhead Publishing
Data di pubblicazione
2025
Lingua
Inglese
ISBN 10 
0443291624
ISBN 13 
9780443291623
Rilegatura
Copertina flessibile
Numero edizione
1
Numero di pagine
552
Redattore
Singh
Contatto del produttore
non disponibile
Persona responsabile
gpsr@libri.de
gpsr@libri.de

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