Rajeev Jaiman

Rajeev Jaiman

Rajeev Jaiman

Associate Professor

B. Tech. (IIT Bombay), M.S., Ph.D. (U of Illinois, Urbana-Champaign, Aerospace Engineering), Senior Member AIAA, Member APS, ASME, SIAM, USACM

phone: (604) 827 0609
fax: (604) 822 2403
email: rjaiman@mech.ubc.ca
website: Computational Multiphysics Laboratory
office: CEME 2208F

Research Interests

  • Fluid-structure interaction
  • Computational methods and numerical analysis
  • Data-driven computing
  • Model order reduction
  • Bluff-body flows and flow-induced vibration
  • Flow control and drag reduction
  • Multiphase flows

Current Research Work

My current research projects are concentrated on a diverse set of topics related to coupled multiphysics and multiphase simulations, fluid-structure interaction (FSI), flow control techniques, model order reduction and data-driven computing. A major thrust of my current research is the development of advanced numerical algorithms on high-performance computing systems for simulating turbulent flow interacting with elastic structures. For instance, I have worked on various multifield/FSI aspects of offshore risers and platforms in ocean environment, subsea pipelines, wind-turbine blades, aircraft wing oscillations and flutter, solid rocket motor with interaction of hot gases and propellant, unsteady flow control and turbulent drag reduction devices, droplet-wall interaction in microfluidics, and various other coupled dynamical systems. The understanding and prediction of such coupled interactions are essential for a safer and more effective design of these engineering systems.

While the traditional high-fidelity full-order simulations provide a valuable physical insight for coupled problems, these full-order models (FOM) are strongly mechanistic, computationally expensive, memory demanding and time-consuming for design space exploration, even on supercomputing facilities. Another dimension of our research involves the development of efficient data-driven model order reduction (MOR) or dimensionality reduction techniques, which are of practical importance in a broad range of problems in aerospace and marine/offshore engineering. The idea is to capture the essential dynamics for multidisciplinary design optimization, parametric analysis, and feedback control. In my current research program, we focus on unifying the full-order high fidelity and the low-order data-driven models for large-scale modeling of nonlinear dynamical systems for parametric design optimization and control. Some highlights of ongoing projects in our research group are as follows:

  • Computational Methods and Numerical Analysis: Over the past years, we have developed a broad range of methods and algorithms to address challenges in simulating large-scale multifield, multiphase and multidomain problems. The main difficulty arises in the treatment of interface for wide ranging and differing physical scales and underlying discretizations. Traditional predictive approaches to nonlinear problems pursued by the computational mechanics community have provided many achievements, but have fallen short of the reliability, robustness, and accuracy, in particular for strong inertial coupling of thin-structures with an incompressible flow. In our group, we have solved several numerical issues about fluid-structure interaction, e.g. the strong inertial coupling associated with added-mass effects, non-matching spatial and temporal discretizations and asynchronous time integrations. Based on novel techniques, the developed in-house multiphysics solver provides a fully coupled analysis tool for marine/offshore, wind-turbine, aerospace and bio-mechanics applications.
  • Software Development and Practical Applications: The parallel 3D Multiphysics computational framework is novel in a number of ways and is general-purpose to simulate large-scale engineering applications, owing to the underlying principle of partitioned iterative scheme for coupled partial differential equations. Our in-house variational 3D parallel solver can handle a wide range of boundary conditions and can simulate arbitrary CAD geometries using unstructured meshes. Recently, the coupled solver has been extended to include the Allen-Cahn phase-field model based on our proposed variational technique, which enables computation of combined fluid-structure interaction with multiphase flow in a single analysis.
  • Physics of Fluid-Structure Interaction and Aeroelasticity: Besides the development and the applications of discretization techniques to real-world problems, the developed methods are explored to answer a range of fundamental questions arising from both canonical and practical problems. Owing to the high accuracy and robustness, new methods and numerical solvers enable to simulate a wide range of physical scales and complexity associated with structure-to-fluid mass ratios, Reynolds number, large structural deformation, and proximity interference with the flexibility to use non-matching spatial and temporal discretizations. The physical understanding of fluid-structure interaction poses much more challenges when there are multiple bodies are involved in the coupled system and the complex phenomena such as wake-induced vibration (WIV), wall- and proximity-induced oscillations can become dominating effects. Some other examples and applications of such fluid-body interactions include fish swimming, bird and insect flight, fluttering of flags and leaves due to a wind flow. Such passive flapping dynamical effects are important and have applications in the field of micro-energy harvesting devices to generate the electric current from the fluid flow, efficient propulsive devices, flow separation control, drag reduction and bio-prosthetic devices such as heart valves.
  • Data-Driven Computing and Machine Learning: Advances in high-performance computing (HPC) have empowered us to perform large-scale simulations for billions of variables in complex coupled multifield, multibody and multiphase systems. These high-fidelity simulations have been providing invaluable physical insight for the development of new design and devices in offshore engineering. Despite efficient algorithms and powerful supercomputers, the state-of-art CFD and coupled fluid-structure simulations are somewhat inefficient hence less attractive with regard to design optimization, parameter space exploration and the development of control and monitoring strategies for engineering structures. Our recent developments focus on integrating the HPC-based high-fidelity CFD with the emerging field of data science and machine learning.
  • New Flow Control Techniques and Devices: The development of high-fidelity tools and the discovery of new physical mechanisms can naturally lead to a host of new designs and control strategies for practical use. As a part of my research focus since my graduate study, a variety of active and passive flow control techniques have been developed for the complex phenomena of vortex-induced vibration, wall turbulence, droplet-wall interaction and shock-boundary layer interaction. Various forms of grooves, auxiliary surfaces and patterns, and external excitations are being studied for controlling these phenomena.
  • Efficient Bio-inspired Structures and Feedback Flow Control: It is fair to assume that Nature provides somewhat optimized and well-evolved solutions to many engineering problems. The current challenge is the application of computer simulations to model bio-inspired systems for understanding the Nature’s best ideas and then tailor and train (via machine learning algorithms) these designs and processes to solve engineering problems. The primary source of complexity comes from interdisciplinary and coupled dynamics character of bio-inspired systems. A variety of concepts, ranging from morphing flexible structures, efficient locomotive systems to drag reduction techniques, have the potentials for improving the efficiency and advancement of the existing engineering systems and processes. Currently, we are extending our flexible multibody FSI framework to model bio-inspired flapping motion (e.g., fish or bat-like motion) to maximize aero-/hydrodynamic performance and/or to minimize acoustics and vibrational problems.

Selected Publications

  • Gurugubelli, P.S. and Jaiman, R.K. “Interaction of gap flow with flapping dynamics of two side-by-side elastic foils,” International Journal of Heat and Fluid Flow, 75, pp.239-255, 2019.
  • Joshi, V. and Jaiman, R.K., “A hybrid variational Allen‐Cahn/ALE scheme for the coupled analysis of two‐phase fluid‐structure interaction,” International Journal for Numerical Methods in Engineering, 117(4), pp.405-429, 2019.
  • Zhang, Q. and Jaiman, R.K., “Numerical analysis on the wake dynamics of a ducted propeller,” Ocean Engineering, 171, pp.202-224, 2019.
  • Li, G., Law, Y.Z. and Jaiman, R.K., “A 3D variational multibody aeroelastic formulation for bio-inspired flight dynamics in turbulent flow,” In AIAA Scitech 2019 Forum (p. 1894), 2019.
  • Joshi, V. and Jaiman, R.K., “A positivity preserving and conservative variational scheme for phase-field modeling of two-phase flows,” Journal of Computational Physics360, pp.137-166, 2018.
  • Wu, C.H., Ma, S., Kang, C.W., Lim, T.B.A., Jaiman, R.K., Weymouth, G. and Tutty, O., “Suppression of vortex-induced vibration of a square cylinder via continuous twisting at moderate Reynolds numbers,” Journal of Wind Engineering and Industrial Aerodynamics177, pp.136-154, 2018.
  • Toh, W., Tan, L.B., Jaiman, R.K., Tay, T.E. and Tan, V.B.C., “A comprehensive study on composite risers: Material solution, local end fitting design and global response,” Marine Structures61, pp.155-169, 2018.
  • Miyanawala, T.P. and Jaiman, R.K., “A Novel Deep Learning Method for the Predictions of Current Forces on Bluff Bodies,” In ASME 2018 37th International Conference on Ocean, Offshore and Arctic Engineering (pp. V002T08A003-V002T08A003). American Society of Mechanical Engineers, 2018.
  • Li, G., Law, Y.Z. and Jaiman, R.K., “A novel 3D variational aeroelastic framework for flexible multibody dynamics: Application to bat-like flapping dynamics,” Computers & Fluids, 2018.
  • Joshi, V. and Jaiman, R.K., “An adaptive variational procedure for the conservative and positivity preserving Allen-Cahn phase-field model”, J. of Computational Physics, 366, 478-504, 2018.
  • Li, Y., Law, YZ, V. Joshi, and Jaiman, R.K., “A 3D common-refinement method for non-matching meshes in partitioned variational fluid-structure analysis”, J. of Computational Physics, 374, 163-187, 2018.
  • Joshi, V. and Jaiman, R.K., “A positivity preserving and conservative variational scheme for phase-field modeling of two-phase flows”, J. of Computational Physics, 360, 137-166, 2018.
  • Miyanawala, T.P. and Jaiman, R.K., “Self-sustaining turbulent wake characteristics in fluid-structure interaction of a square cylinder”, J. of Fluids and Structures, 77, 80-101, 2018.
  • Yenduri, A., Ghoshal, R. and Jaiman, R. K., “A new partitioned staggered scheme for flexible multibody interactions with strong inertial effects”, Computer Methods in Applied Mechanics and Engineering, Vol. 315, pp. 316-347, 2017.
  • Joshi, V. and Jaiman, R.K., “A positivity preserving variational method for multi-dimensional convection-diffusion-reaction equation’’, J. of Computational Physics, 339, 247-284, 2017.
  • Yao, W. and Jaiman, R.K., “Feedback control of vortex-induced vibrations using eigensystem realization algorithm”, J. of Fluid Mechanics, 827, 357-393, 2017.
  • Yao, W. and Jaiman, R.K., “Model reduction and mechanism for the vortex-induced vibrations of bluff bodies”, J. of Fluid Mechanics, 827, 394-414, 2017.
  • Raman, K.A., Jaiman, R.K., Lee, T.S., and Low, H.T., “Rebound suppression of a droplet impacting on an oscillating horizontal surface”, Physical Review E, 94 (2), 023108, 2016.
  • Jaiman, R.K., Pillalamarri, N.R. and Guan, M.Z, “A stable second-order partitioned iterative scheme for freely vibrating low-mass bluff bodies in a uniform flow,” Computer Methods in Applied Mechanics and Engineering, 301:187–215, 2016.
  • Liu, B. and Jaiman, R.K., “Interaction dynamics of gap flow with vortex-induced vibration in side-by-side cylinder arrangement”, Physics of Fluids 28 (12), 127103, 2016.
  • Mysa, R.C., Kaboudian, A. and Jaiman, R.K., “On the origin of wake-induced vibration in two tandem circular cylinders at low Reynolds number”, J. of Fluids and Structures, 61, 76-98, 2016.
  • Law, Y.Z. and Jaiman, R.K., “Wake stabilization mechanism of low-drag suppression devices for vortex-induced vibration”, J. of Fluids and Structures, 70, 428-449, 2017.
  • Jaiman, R.K., Guan, M.Z., and Miyanawala, T.P., “Partitioned iterative and dynamic subgrid-scale methods for freely vibrating square-section structures at subcritical Reynolds number”, Computers and Fluids, 133:68–89, 2016.
  • Gurugubelli, P.S. and Jaiman R.K. “Self-induced flapping dynamics of inverted flexible foil”, J. of Fluid Mechanics, 781, 657-694, 2015.
  • Jaiman, R. K., Parmar, M. and Gurugubelli, “Added mass and aeroelastic stability of a flexible plate interacting with mean flow in a confined channel”, J. of Applied Mechanics, 81, 2014.

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