This book discusses various passive and active techniques for controlling unsteady flow dynamics and associated coupled mechanics of fluid-structure interaction. Coupled multiphysics and multidomain simulations are emerging and challenging research areas, which have received significant attention during the past decade. One of the most common multiphysics and multidomain problems is fluid-structure interaction (FSI), i.e., the study of coupled physical systems involving fluid and a structure that have a mechanical influence on each other. Regardless of the application area, the investigation toward modeling of fluid-structure interaction and the underlying mechanisms in dealing with coupled fluid-structure instability with real-world applications remains a challenge to scientists and engineers. This book is designed for students and researchers who seek knowledge of computational modeling and control strategies for fluid-structure interaction. Specifically, this book provides acomprehensive review of the underlying unsteady physics and coupled mechanical aspects of the fluid-structure interaction of freely vibrating bluff bodies, the self-induced flapping of thin flexible structures, and aeroelasticity of shell structures. Understanding flow-induced loads and vibrations can lead to safer and cost-effective structures, especially for light and high-aspect ratio structures with increased flexibility and harsh environmental conditions. Using the body-fitted and moving mesh formulations, the physical insights associated with structure-to-fluid mass ratios, Reynolds number, nonlinear structural deformation, proximity interference, near-wall contacts, free-surface, and other interacting physical fields are covered in this book. In conjunction with the control techniques, data-driven model reduction approaches based on subspace projection and deep neural calculus are covered for low-dimensional modeling of unsteady fluid-structure interaction.
Dr. Rajeev K. Jaiman is currently an associate professor and NSERC/Seaspan industrial chair in the Department of Mechanical Engineering at the University of British Columbia (UBC), Vancouver, Canada. An aeronautical engineer by training, his research concentrates on high-fidelity multiphysics modeling and data-driven computing, with emphasis on large-scale computations of fluid–solid and fluid–fluid interface problems. Prior to his current appointment at UBC, he was an assistant professor in the Department of Mechanical Engineering at the National University of Singapore (NUS). Before joining NUS, he was the director of Computational Fluid Dynamics (CFD) Development at Altair Engineering, Inc., Mountain View, California. The CFD technologies that Dr. Jaiman has developed are routinely used in marine/offshore, wind turbine, nuclear reactors, automotive and aerospace industries. Dr. Jaiman earned his first degree in Aerospace Engineering from the Indian Institute of Technology,Mumbai. He received his master's and doctorate degrees from the University of Illinois at Urbana-Champaign (UIUC). He has authored/co-authored more than 150 journals papers and conference proceedings and serves as an expert reviewer for numerous journals and books. He is currently an associate editor of ASME-OMAE Journal, a senior member of AIAA and member of ASME, SNAME, USACM, APS, AAM, and SIAM.
Dr. Li Guojun is currently a research assistant in the Unmanned System Research Institute at the Northwestern Polytechnic University (NPU), Xi’an China. Dr. Li received his doctorate degree from the National University of Singapore (NUS). His research concentrates on high-fidelity multibody aeroelastic modeling and physical analysis of bio-inspired flexible wings. He earned his master’s and bachelor's degrees in Aerospace Engineering from the Northwestern Polytechnic University (NPU), China, focusing on mathematical modeling and physics of flutter from subsonic to supersonic conditions. He is also interested in fluid–structure–acoustic interaction problems, passive/active control strategies and optimization design based on deep learning for biological flight and civil aircraft.
Amir Chizfahm is a graduate research assistant in the mechanical engineering department at the University of British Columbia (UBC). He is a UBC alumni and holds a MASc in mechanical engineering. His research concentrates on data-driven computing of fluid–structure interaction problems using physics-based high-fidelity simulations, stability analysis and active feedback control of wake flow and vortex-induced vibrations under supervision of Dr. Rajeev Jaiman. He also holds another master's degree and a bachelor's degree in mechanical engineering from Shiraz University, Iran, focusing on dynamic modeling and optimal control of wind powered bladeless turbines and energy harvesters. His areas of interest include fluid–structure interaction of marine and offshore applications, vortex-induced vibration energy harvesters, active feedback control strategies and deep learning.
