Springer CT Scan Generated Material Twins for Composites Manufacturing in Industry 4.0

This book highlights a novel and robust platform in the form of in-situ characterization setup for creating X-ray computed tomography (XCT)-based textile material twins. In this hybrid experimental–numerical platform, XCT images of different complex fibrous reinforcements at different levels of compaction are acquired. The images are converted into computational models for resin flow simulations. The capabilities of this hybrid framework are applied to a variety of reinforcements used in liquid composite molding processes such as 2D, 3D fabrics and dry tapes. This book is a milestone in the development of virtual manufacturing protocols using material twins of textiles, providing a step closer to the digitalization of advanced composites used in manufacturing processes for industry 4.0. From the Back Cover This book highlights a novel and robust platform in the form of in-situ characterization setup for creating X-ray computed tomography (XCT)-based textile material twins. In this hybrid experimental–numerical platform, XCT images of different complex fibrous reinforcements at different levels of compaction are acquired. The images are converted into computational models for resin flow simulations. The capabilities of this hybrid framework are applied to a variety of reinforcements used in liquid composite molding processes such as 2D, 3D fabrics and dry tapes. This book is a milestone in the development of virtual manufacturing protocols using material twins of textiles, providing a step closer to the digitalization of advanced composites used in manufacturing processes for industry 4.0. About the Author Muhammad Ali is a Post-Doctoral Researcher at the Aerospace Engineering Department, Khalifa University of Science and Technology, Abu Dhabi, UAE. He was previously at Georgia Tech USA where he completed his Masters in Aerospace Engineering. Dr Ali’s research interest is in computational analysis of CT based material twins, artificial intelligence and machine learning in composites manufacturing. Dr. Rehan Umer is an Associate Professor in the Aerospace Engineering Department, Khalifa University of Science and Technology, Abu Dhabi, UAE. He received his Ph.D. degree from The University of Auckland, New Zealand, in 2008. He then worked as a Research Engineer at CRC for Advanced Composites Structures and Airbus Helicopter, Brisbane, Australia. He completed his postdoctoral research career at the Composite Vehicle Research Center (CVRC), Michigan State University, USA, on polymer composites processing. He is the Co-Founder of the Aerospace Research and Innovation Center (ARIC), a multi-million-dollar joint venture between Khalifa University and Mubadala Aerospace. Dr. Umer is currently an Associate Editor of Frontiers in Materials (Polymeric and Composite Materials section). He edited two books, “Manufacturing, Characterization and Properties of Advanced Nanocomposites”, MDPI, ISBN: 978-3-03897-189-4, and “Fillers and Reinforcements for Advanced Nanocomposites”, Woodhead Publishers, ISBN: 9780081000793. Dr. Umer also authored and co-authored many papers in refereed journals, book chapters, and US patents and presented at number of international conferences. Dr. Umer’s research interest is in liquid composites molding (LCM), pultrusion, filament winding, multifunctional nano-composites, automated fiber placement (AFP), 3D reinforcements and prefroms, lightweight lattice sandwich structures and micro-CT-based digital twins for industry 4.0. Dr. Kamran A. Khan is an Assistant Professor in the Aerospace Engineering Department at Khalifa University of Science and Technology, UAE. He received both his M.S. and Ph.D. degrees in Mechanical Engineering from Texas A&M University, USA. Before joining Khalifa University, he worked as a Postdoctoral Fellow at King Abdullah University of Science and Technology, Saudi Arabia. Dr. Kamran has published many articles in archival journals and confer