Parallel Solution-adaptive Scheme for Multi-phase Core Flows in Rocket Motors

The development of a parallel adaptive mesh refinement (AMR) scheme is described for solving the governing equations for multi-phase (gas-particle) core flows in solid propellant rocket motors (SRM). An Eulerian formulation is used for both the gas and particle phases, which leads to a degenerate hyperbolic system of partial differential equations. The cause and effect of the degeneracy is examined. A cell-centered upwind finite-volume discretization and the use of limited solution reconstruction, Riemann solver based flux functions for the gas and particle phases, and explicit multi-stage timestepping allows for high solution accuracy and computational robustness. A Riemann problem is formulated for prescribing boundary data at the burning surface of the propellant grain and an iterative solver is proposed for its solution. Efficient and scalable parallel implementations are achieved with domain decomposition on distributed memory multi-processor architectures. High-scalability of the model has been achieved on a Beowulf-class cluster consisting of 104 processors. Numerical results are described to demonstrate the capabilities of the approach for predicting SRM core flows.