Advances in Multidisciplinary Design, Analysis and Optimization

Beschreibung

This book presents the proceedings of the 8th National Conference on Multidisciplinary Design, Analysis and Optimization (NCMDAO 2025), providing a collection of contemporary research advancing the field of multidisciplinary design optimization (MDO). The book showcases innovative methodologies and practical applications that bridge classical optimization techniques with emerging technologies such as artificial intelligence, quantum computing, digital twins, and data-driven optimization.
The volume covers a diverse range of topics, including structural optimization, metamaterials, multi-scale and multi-physics modeling, additive manufacturing, surrogate modeling, Bayesian and evolutionary optimization, uncertainty quantification, reliability-based design, and machine learning for optimization. It further highlights real-world applications in aerospace, manufacturing, biomedical engineering, and other engineering domains, featuring studies on aircraft structures, lattice and origami-inspired metamaterials, compliant mechanisms, and advanced computational design frameworks.
Organized into thematic sections, the book provides readers with both theoretical developments and application-oriented case studies, offering a balanced perspective on current trends and future directions in MDO.
This volume serves as a valuable resource for researchers, graduate students, practicing engineers, and professionals from academia, government research laboratories, and industry who are interested in design optimization, computational engineering, advanced manufacturing, and the development of next-generation engineering systems.

This book presents the proceedings of the 8th National Conference on Multidisciplinary Design, Analysis and Optimization (NCMDAO 2025), providing a collection of contemporary research advancing the field of multidisciplinary design optimization (MDO). The book showcases innovative methodologies and practical applications that bridge classical optimization techniques with emerging technologies such as artificial intelligence, quantum computing, digital twins, and data-driven optimization.
The volume covers a diverse range of topics, including structural optimization, metamaterials, multi-scale and multi-physics modeling, additive manufacturing, surrogate modeling, Bayesian and evolutionary optimization, uncertainty quantification, reliability-based design, and machine learning for optimization. It further highlights real-world applications in aerospace, manufacturing, biomedical engineering, and other engineering domains, featuring studies on aircraft structures, lattice and origami-inspired metamaterials, compliant mechanisms, and advanced computational design frameworks.
Organized into thematic sections, the book provides readers with both theoretical developments and application-oriented case studies, offering a balanced perspective on current trends and future directions in MDO.
This volume serves as a valuable resource for researchers, graduate students, practicing engineers, and professionals from academia, government research laboratories, and industry who are interested in design optimization, computational engineering, advanced manufacturing, and the development of next-generation engineering systems.

Autor*in

Sourav Rakshit

Themen in »Advances in Multidisciplinary Design, Analysis and Optimization«

Structural optimization Design and optimization of materials, and metamaterials Systems design and optimization Evolutionary and Bayesian optimization Uncertainty modeling Reliability and robustness in design Industry applications and case studies in optimal design MDAO in aerospace, automotive, biomedical, and other domains

Stimmen zu »Advances in Multidisciplinary Design, Analysis and Optimization«

Details

Link teilen