This seminar presents high-fidelity simulations of single-phase compressible flows and multiphase flows with a liquid-gas interface. Active control of turbulent jet noise, moving embedded boundary method for compressible flows with adaptive mesh refinement (AMR), and an all-Mach multiphase flow solver with AMR are presented.

Compressible flows: 

1.      A novel, active flow control strategy using linear feedback with co-located actuator(s)/sensor(s) suitable for affecting the dynamics of compressible flows is developed. The methodology uses the flow’s receptivity information from the forward and adjoint global modes of the baseflow obtained from direct/large-eddy simulations. Noise reduction from an axisymmetric Mach 1.5 jet and a turbulent Mach 0.9 jet is demonstrated.

2.      A computational technique is developed for compressible flows with moving boundaries within the compressible Navier-Stokes (CNS) framework of AMReX. A ghost-cell approach is developed to compute the fluxes on the moving embedded boundary (EB) faces. A third-order least-squares formulation is developed to compute the wall velocity gradients, and was found to significantly improve the estimation of the skin friction coefficient. Inviscid and viscous test cases are performed to validate the method.

Multiphase flows : An all-Mach multiphase flow algorithm that was developed in [1] is integrated into AMReX[2]. The compressible flow equations are solved, and the multiphase treatment uses an unsplit, geometric volume-of-fluid (VOF) approach with a piecewise linear interface calculation (PLIC) for the liquid-gas interface reconstruction. Simulations of a liquid jet in supersonic crossflow and spray atomization with acoustic excitation are performed. Weak and strong scaling results are presented. Adaptive mesh refinement is shown to reduce the resource usage by 50%.

[1] O. Desjardins, M. Natarajan, M. Kuhn, “Numerical Study of Liquid Jet Atomization in Supersonic Crossflows”, ILASS-Americas 29th Annual Conference on Liquid Atomization and Spray Systems, Atlanta, GA, May 2017.

[2] Zhang, Weiqun, Ann Almgren, Vince Beckner, John Bell, Johannes Blaschke, Cy Chan, Marcus Day et al. “AMReX: a framework for block-structured adaptive mesh refinement.” Journal of Open Source Software 4, no. 37 (2019): 1370-1370.

Biographical sketch

Mahesh Natarajan received his Bachelor’s degree in Mechanical Engineering from the University of Calicut in 2007, and Master’s in Aerospace Engineering from the Indian Institute of Science in 2009. He completed his Ph.D. from the Department of Aerospace Engineering at the University of Illinois at Urbana-Champaign in 2017, and was a postdoctoral researcher in the Department of Mechanical and Aerospace Engineering at Cornell University until 2019. He worked as Researcher II at the Computational Science Center of National Renewable Energy Laboratory (NREL) until 2021, and then joined the Computational Aerosciences branch of NASA Ames Research Center as an Aerospace Engineer.