Overview
- Discusses applications of multidisciplinary optimization in aerospace, manufacturing, and biomedical industries
- Focuses on design and analysis as applicable to optimization of systems
- Discusses both established techniques and emerging technologies
Part of the book series: Lecture Notes in Mechanical Engineering (LNME)
Included in the following conference series:
Conference proceedings info: NCMDAO 2021.
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Table of contents (48 papers)
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Front Matter
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Optimization Applications: Aerospace
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Front Matter
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Other volumes
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Advances in Multidisciplinary Analysis and Optimization
Editors and Affiliations
About the editors
Phanisri Pradeep Pratapa is an Assistant Professor in the Department of Civil Engineering at the Indian Institute of Technology (IIT) Madras. He obtained his Ph.D. from Georgia Tech, Atlanta, USA, and later worked with Prof. Glaucio H. Paulino as a postdoc where he was inspired by the ideas of origami engineering, metamaterials, and topology optimization. His current research focuses on exploring the use of optimization and origami principles in structural mechanics and engineering. His research interests also include the topics of lattice structures and 3D printing. His work has been published in highly reputed journals like Physical Review Letters and Journal of the Mechanics and Physics of Solids. Dr. Pratapa has a Bachelor's degree from IIT Madras and a Master's degree from The University of Texas at Austin, both in Civil Engineering.
Gurunathan Saravana Kumar is a Professor in the Department of Engineering Design at the Indian Institute of Technology (IIT) Madras. His research aims at development of representational and computational tools for virtual and physical prototyping applied to arrive at solutions to design problems. Some of the specific research areas include CAD, design optimization, and design for additive manufacturing. His current research focuses on exploring the capabilities of additive manufacturing to design novel structures for various applications including light weighting, compact heat exchangers, and orthopaedic implants. He has more than 100 publications in international journals and conferences. Dr. Saravana Kumar has a Bachelor's degree from the University of Madras and a Ph.D. from IIT Kanpur, both in Mechanical Engineering.
Palaniappan Ramu is an Associate Professor in the Department of Engineering Design at the Indian Institute of Technology (IIT) Madras. His research interests revolve around the treatment of uncertainties in design. His philosophy on the treatment of uncertainties is ‘More out of less’- to obtain more information with limited experiments or computer simulations and how not to be fooled by randomness. With this focus, he works on diverse problems which are predominantly data driven. Application areas include automotive/space structures, wind turbines, and internet marketing.
R K Amit is currently a Professor in the Department of Management Studies, Indian Institute of Technology (IIT) Madras, Chennai, India. He completed his undergraduate studies at IIT Kanpur, and his doctoral studies at the Indian Institute of Science (IISc), Bangalore. His research and teaching interests are game theory and decision theory, and their applications in operations management. His research has been published in journals of national and international repute. He is currently working on numerous industry-sponsored research projects in the areas of electric mobility, emergency medical services, and airlines revenue management.
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Bibliographic Information
Book Title: Advances in Multidisciplinary Analysis and Optimization
Book Subtitle: Proceedings of the 4th National Conference on Multidisciplinary Analysis and Optimization
Editors: P. Pradeep Pratapa, G. Saravana Kumar, Palaniappan Ramu, R. K. Amit
Series Title: Lecture Notes in Mechanical Engineering
DOI: https://doi.org/10.1007/978-981-19-3938-9
Publisher: Springer Singapore
eBook Packages: Engineering, Engineering (R0), Springer Nature Proceedings excluding Computer Science
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023
Hardcover ISBN: 978-981-19-3937-2Published: 25 September 2022
Softcover ISBN: 978-981-19-3940-2Published: 26 September 2023
eBook ISBN: 978-981-19-3938-9Published: 24 September 2022
Series ISSN: 2195-4356
Series E-ISSN: 2195-4364
Edition Number: 1
Number of Pages: XXVI, 467
Number of Illustrations: 48 b/w illustrations, 301 illustrations in colour
Topics: Mathematical and Computational Engineering, Optimization, Machine Learning