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.

Autorentext

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 conference proceedings. He led several collaborative research and industrial sponsored projects including supervising M.S., Ph.D. and Postdoctoral Fellows.His research interests include the development of experimentally validated macro/micro/nano-mechanics-based constitutive theories for small and large deformation multi-scale and multi-physics behavior of polymers, metals, metamaterials, smart materials, architected materials, multifunctional composites and advanced manufacturing processes simulation, modeling of textile composites materials and lightweight sandwich structures containing 2D and 3D textile reinforcements, generation of micro-CT based geometrical models and computational analysis of material twins for composite manufacturing.

Inhalt
1. Introduction.- 2. Generation of Material Twin using Micro CT Scanning.- 3. Experimental Techniques for Reinforcement Characterization.- 4. Experimental-Numerical Hybrid Reinforcement Characterization Framework.- 5. Reinforcement Compaction Response.- 6. Flow Fields and Reinforcement Permeability.- 7. Experimental-Empirical Hybrid Approach.