Advances in Multidisciplinary Analysis and Optimization (eBook)

Proceedings of the 2nd National Conference on Multidisciplinary Analysis and Optimization

Raviprakash R. Salagame, Palaniappan Ramu, Indira Narayanaswamy, Dhish Kumar Saxena (Herausgeber)

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2020 | 1st ed. 2020
XXII, 316 Seiten
Springer Singapore (Verlag)
978-981-15-5432-2 (ISBN)

This volume contains select papers presented during the 2nd National Conference on Multidisciplinary Analysis and Optimization. It discusses new developments at the core of optimization methods and its application in multiple applications. The papers showcase fundamental problems and applications which include domains such as aerospace, automotive and industrial sectors. The variety of topics and diversity of insights presented in the general field of optimization and its use in design for different applications will be of interest to researchers in academia or industry.

Dr. Raviprakash Salagame brings over 25 years of industry experience. He is currently a senior global leader at APTIV Technical Center India. Previously, Ravi held leadership and engineering positions at GE Corporate Research Center (at JFWTC) and IBM Almaden Research Center at San Jose, California. He completed his Ph.D. in Mechanical Engineering from Pennsylvania State University in 1995, Master's degree from Indian Institute of Science in 1988 and Bachelor's degree from BMS College of Engineering in 1986. He is a certified Six Sigma black belt and a technical expert in Design Optimization, CAE, data science and statistical methods. He has published over 15 international journal and conference papers and delivered several industry keynotes in India. He also serves on the board of IUCEE (Indo-Universal Collaboration for Excellence in Engineering Education) and a few of the leading universities in India.

Dr. Palaniappan Ramu is an Associate Professor in the Department of Engineering Design, IIT Madras. He heads the Advanced Design Optimization and Probabilistic Techniques (ADOPT) Laboratory where work revolves around using probability, statistics and optimization for design decisions. He investigates problems of varied interests in different areas. It includes optimal designs of computer models built in FEM/CFD towards light weighting, understanding performance of machine learning algorithms as surrogates, digital twins and visual exploration of design spaces. He holds a B.Eng. in Mechanical from Madurai Kamaraj University, India and a Ph.D. in Aerospace Engineering from University of Florida, USA. He has 10+ years' experience working on optimization for engineering applications. He teaches courses on optimization, reliability, surrogates and DfMA.

Dr. Indira Narayanaswamy is a research Professor in Ramaiah University of Applied Sciences, Bangalore, India. She has previously served as a scientist and technology Director in the Aeronautical Development Agency, Bangalore. Dr. Narayanaswamy's areas of specialization are CFD applications for Aerodynamics Shape Optimization and Multidisciplinary Design Optimization (MDO), MDO for MAV design, Numerical Investigations on Supersonic Retro Propulsion (SRP). She has authored more than 150 research papers and technical reports.

Dr. Dhish Kumar Saxena is an Associate Professor in the Department of Mechanical & Industrial Engineering, IIT Roorkee. His main research interests lie in multi-objective, multi-disciplinary optimization, and multi-criterion decision making. He is currently the principal investigator/co-investigator of different international projects in these domains, focusing on large scale industrial problems. He is also on the Reviewer Board and Project Monitoring Committee member for different national/international projects launched by the Ministry of Electronics & Information Technology, and Department of Science & Technology. Dr. Saxena brings on board his work experience in the United Kingdom where he worked with universities like Cranfield and Bath, in collaboration with companies like British Aerospace Systems, Hewlett Packard, and Airbus.

Erscheint lt. Verlag	10.8.2020
Reihe/Serie	Lecture Notes in Mechanical Engineering
Reihe/Serie	Lecture Notes in Mechanical Engineering
Zusatzinfo	XXII, 316 p. 216 illus., 175 illus. in color.
Sprache	englisch
Themenwelt	Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
	Mathematik / Informatik ► Mathematik ► Angewandte Mathematik
	Mathematik / Informatik ► Mathematik ► Finanz- / Wirtschaftsmathematik
	Technik
Schlagworte	approximation methods • approximations • machine learning • multidisciplinary optimization • Neural networks • optimization algorithms • Surrogate Models • Topology
ISBN-10	981-15-5432-3 / 9811554323
ISBN-13	978-981-15-5432-2 / 9789811554322

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