This book contains select proceedings of the International Conference on Smart Technologies for Energy, Environment, and Sustainable Development (ICSTEESD 2020). The book is broadly divided into the themes of energy, environment, and sustainable development; and discusses the significance and solicitations of intelligent technologies in the domain of energy and environmental systems engineering. Topics covered in this book include sustainable energy systems including renewable technologies, energy efficiency, techno-economics of energy system and policies, integrated energy system planning, environmental management, energy efficient buildings and communities, sustainable transportation, smart manufacturing processes, etc. The book will be a valuable reference for young researchers, professionals, and policy makers working in the areas of energy, environment and sustainable development.

Autorentext

Prof. Dr. Mohan Lal Kolhe is a full professor in smart grid and renewable energy at the Faculty of Engineering and Science of the University of Agder (Norway). He is a leading renewable energy technologist with three decades of academic experience at the international level and previously held academic positions at the world's prestigious universities, e.g., University College London (UK / Australia), University of Dundee (UK); University of Jyvaskyla (Finland); Hydrogen Research Institute, QC (Canada); etc. In addition, he was a member of the Government of South Australia's first Renewable Energy Board (2009-2011) and worked on developing renewable energy policies. Due to his enormous academic contributions to sustainable energy systems, he has been offered the posts of Vice-Chancellor of Homi Bhabha State University Mumbai (Cluster University of Maharashtra Government, India), full professorship(s) / chair(s) in 'sustainable engineering technologies/systems' and 'smart grid' from the Teesside University (UK) and Norwegian University of Science and Technology (NTNU) respectively. He is Series Editor of Springer Proceedings in Energy. His research works in energy systems have been recognized within the top 2% of scientists globally by Stanford University's 2020, 2021 matrix. He is an internationally recognized pioneer in energy field, whose top 10 published works have an average of over 175 citations each.

Professor (Dr) Santosh Jaju obtained his master's degree in Industrial Engineering from VRCE (Now known to be VNIT), Nagpur, and received PhD from Rashtrasant Tukadoji Maharaj Nagpur University. He has completed Master of Business Administration from IGNOU, New Delhi. He is presently working as Dean (Research & Development) and Professor in the Department of Mechanical Engineering of G. H. Raisoni College of Engineering. He has more than 23 years of teaching experience. He has to his credit more than 100 research papers published in national and international journals and conferences, 01 book and 06 book chapters. He has attended more than 50 symposiums, short-term courses, training, and workshops. He has delivered more than 50 expert lectures in short-term training programmes and workshops. He served as convener of series of All India Seminar Quality Progress, general chair of International conference on advances in mechanical engineering, and program chair in IEEE International Conference on Emerging Trends in Engineering & Technology. He is serving as member on editorial board, reviewer of international journal, chaired number of technical sessions in conferences. He is associated with many prestigious professional societies like Institution of Engineers (India); ISTE New Delhi; Indian Institution of Industrial Engineering, Mumbai; Indian Society of Mechanical Engineers (ISME), New Delhi; IEEE-Robotics and Automation Society and ASME. He is a certified Lead Auditor of ISO 9001: 2008 QMS by IRCA UK. He has guided more than 20 PG dissertations, five PhDs awarded, 01 PhD student have submitted thesis. He has filed 6 patents, 1 copyright, completed research project of AICTE. He has visited National University of Singapore; Multimedia University, Malaysia; University of Technology, Mauritius; and various universities in Dubai. He received BEST TEACHER AWARD given by G. H.Raisoni College of Engineering for the year 2003-2004. He has also received BEST CASE STUDY AWARD (non-traditional area) in the form of Silver Medal by National Council of Indian Institution of Industrial Engineering, Navi Mumbai, for the year 2004-2005. He has received 07 Best Paper Awards. His research area includes quality cost, total quality management, supply chain management, service quality, lean manufacturing, productivity improvement techniques and industrial engineering areas. Professor (Dr) Prema Daigavane is currently professor at the Department of Electrical Engineering, G H Raisoni College of Engineering, Nagpur. She obtained her B.E. (Electrical) from Government college of Engineering Amravati and M.S. (Electronics & Control ) from BITS Pilani and PhD from Rashtrasant Tukadoji Maharaj Nagpur University, Nagpur. Her major areas of research interests include control engineering, soft computing tools, optimization techniques, renewable energy in electrical engineering. She has more than 30 years of teaching experience. He has to her credit more than 65 research papers published in national and international journals and conferences, 02 book chapters. She has attended more than 50 symposiums, short-term courses, training, and workshops. She received Best Teacher Award given by G. H.Raisoni College of Engineering for the year 2014-2015...

Inhalt

Seismic Analysis of 3D Printed Structures.- Efficiency of linear univariate programming method in estimating the parameters reflecting the behavior of R.C.C beam along the span.- Effect of Creep and Shrinkage on Construction Sequence Analysis of High Rise Building.- Experimental Investigation of Concrete used in Spent Fuel Pools of Nuclear Power Plants Subjected to Boiling Water Exposure.- Effect of Aspect Ratio on Fatigue Behaviour of Steel Shear Wall.- Extreme rainfall analysis using Extreme Value (EV-I) distribution based on L-Moment approach.- Application of Machine Learning for Accuracy Improvement of Projected Precipitation of Climate Change Data with Observed Data.