4 citations · 4 across the 4 of their papers we have counts for
5 papers
Diff-NekRS: A Scalable Differentiable Framework for Multi-Timestep Solver-in-the-Loop Training
Junoh Jung, Riccardo Balin, Bethany Lusch +1
Hybrid physics-machine-learning solvers improve under-resolved simulations by embedding trainable corrections into the time integration. During autoregressive inference, repeated s…
A Physics-Informed B-Spline Framework for Continuous Approximation of Flow Data
Junoh Jung, David Lenz, Emil Constantinescu +1
Continuous approximations of flow data are useful for downstream analysis, differentiation, and visualization, but purely data-driven reconstructions do not, in general, preserve t…
Resolvent-based estimation of a turbulent wake
Junoh Jung, Aaron Towne
We present a resolvent-based framework for estimating turbulent velocity fluctuations in the wake of a spanwise-periodic NACA0012 airfoil at Mach 0.3, Reynolds number 23,000, and a…
Resolvent-based estimation and control of a laminar airfoil wake
Junoh Jung, Rutvij Bhagwat, Aaron Towne
We develop an optimal resolvent-based estimator and controller to predict and attenuate unsteady vortex shedding fluctuations in the laminar wake of a NACA 0012 airfoil at an angle…
Efficient harmonic resolvent analysis via time-stepping
Ali Farghadan, Junoh Jung, Rutvij Bhagwat +1
We present an extension of the RSVD- algorithm initially developed for resolvent analysis of statistically stationary flows to handle harmonic resolvent analysis of time-period…