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Reliable prediction of rocket injector flows introduces significant challenges associated with the complex physics involving recirculation, turbulence, scalar mixing, chemical reactions and wall heat transfer. This work is aimed at assessing the importance of turbulence-chemistry interaction and non-equilibrium effects in experimentally characterized single and multi-element injector flows. By examining the different chemistry models (laminar finite rate, assumed PDF with either flamelet or equilibrium assumption), it was found that for both cases investigated, chemical nonequilibrium is insignificant while substantial turbulence-chemistry interaction is observed. A zonal wall treatment was developed based on a blend of SST low-Re turbulence wall treatment and lawof-the-wall, showing improved predictive capability. A heat flux extraction method was also proposed to estimate heat flux results from adiabatic flamelet model under the consideration that wall heat loss is small compared to the overall energy generated by chemical reactions. Nomenclature

In this study, we present a parallelized adaptive moving boundary computation technique on distributed memory multi-processor systems for multi-scale multiphase flow simulations. The solver utilizes the Eulerian-Lagrangian method to track moving (Lagrangian) interfaces explicitly on the stationary (Eulerian) Cartesian grid where the flow fields are computed. Since there exists strong data and task dependency between two distinct Eulerian and Lagrangian domain, we address the decomposition strategies for each domain separately. We then propose a trade-off approach aiming for parallel scalability. Spatial domain decomposition is adopted for both Eulerian and Lagrangian domains for load balancing and data locality to minimize inter-processor communication. In addition, a cellbased unstructured parallel adaptive mesh refinement (AMR) technique is implemented for the flexible local refinement with efficient grid usage and even-distributed computational workload among processors. The parallel performance is evaluated independently for the Cartesian grid solver and sub-procedures in cell-based unstructured AMR. The capability and the overall performance of the parallel adaptive Eulerian-Lagrangian method including moving boundary and topological change is demonstrated by modeling binary droplet collisions. With the aid of the present techniques, large scale moving boundary problems can be effectively computed.

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