On the Nonlinear Growth of Multiphase Richtmyer-Meshkov Instability in Dilute Gas-Particles Flow

We discuss evolutions of nonlinear features in Richtmyer-Meshkov instability(RMI)f which are known as spikes and bubbles.In single-phase RMI,the nonlinear growth has been extensively studied but the relevant investigation in multiphase RMI is insufficient.Therefore,we illustrate the dynamic coupling behaviors between gas phase and particle phase and then analyze the growth of the nonlinear features theoretically.A universal model is proposed to describe the nonlinear finger(spike and bubble)growth velocity qualitatively in multiphase RMI.Both the effects of gas and particles have been taken into consideration in this model.Further,we derive the analytical expressions of the nonlinear growth model in limit cases(equilibrium How and frozen How).A novel compressible multiphase particle-in-cell(CMP-PIC)method is used to validate the applicability of this model.Numerical finger growth velocity matches well with our model.The present study reveals that particle volume fraction,particle density and Stokes number are the three key factors,which dominate the interphase momentum exchange and further induce the unique property of multiphase RMI.

Discovery of Partial Differential Equations from Highly Noisy and Sparse Data with Physics-Informed Information Criterion

Data-driven discovery of partial differential equations(PDEs)has recently made tremendous progress,and many canonical PDEs have been discovered successfully for proof of concept.However,determining the most proper PDE without prior references remains challenging in terms of practical applications.In this work,a physics-informed information criterion(PIC)is proposed to measure the parsimony and precision of the discovered PDE synthetically.The proposed PIC achieves satisfactory robustness to highly noisy and sparse data on 7 canonical PDEs from different physical scenes,which confirms its ability to handle difficult situations.The PIC is also employed to discover unrevealed macroscale governing equations from microscopic simulation data in an actual physical scene.The results show that the discovered macroscale PDE is precise and parsimonious and satisfies underlying symmetries,which facilitates understanding and simulation of the physical process.The proposition of the PIC enables practical applications of PDE discovery in discovering unrevealed governing equations in broader physical scenes.