Adjoint-based Particle Forcing Reconstruction and Uncertainty Quantification

The forcing of particles in turbulent environments influences dynamical properties pertinent to many fundamental applications involving particle-flow interactions. Current study explores the determination of forcing for one-way coupled passive particles, under the assumption that the ambient velocity fields are known. When measurements regarding particle locations are available but sparse, direct evaluation of the forcing is intractable. Nevertheless, the forcing for finite-size particles can be determined using adjoint-based data assimilation. This inverse problem is formulated with the framework of optimization, where the cost function is defined as the difference between the measured and predicted particle locations. The gradient of the cost function, with respect to the forcing can be calculated from the adjoint dynamics. When measurements are subject to Gaussian noise, samples within the probability distribution of the forcing can be drawn using Hamiltonian Monte Carlo. The algorithm is tested in the Arnold-Beltrami-Childress flow as well as the homogeneous isotropic turbulence. Results demonstrate that the forcing can only be determined accurately for particle Reynolds number between 1 and 5, where the majority of Reynolds number history along the particle trajectory falls in

Numerical Analysis of Shock Wave Diffraction

This work reports analysis of complex shock wave diffraction and longtime behavior of shock-vortex dynamics over splitter geometry encountered in both external and internal compressible flows. The simulation resolved the experimental findings of literature, and the insight of the flow topology is being presented with the probability density functions (PDFs) of various contributing terms of enstrophy transport equation and the invariants of the velocity gradient tensor. We use an artificial viscosity (AV)-based explicit discontinuous spectral element method (DSEM)-based compressible flow solver for this purpose. The numerical scheme utilizes entropy generation-based artificial viscosity and thermal conductivity to simulate the conservative form of the governing compressible flow equations. A shock sensor-based switch is used to reduce the addition of AV coefficients in rotation-dominated regions