Comparison of DAC and MONACO DSMC Codes with Flat Plate Simulation

Various implementations of the direct simulation Monte Carlo (DSMC) method exist in academia, government and industry. By comparing implementations, deficiencies and merits of each can be discovered. This document reports comparisons between DSMC Analysis Code (DAC) and MONACO. DAC is NASA's standard DSMC production code and MONACO is a research DSMC code developed in academia. These codes have various differences; in particular, they employ distinct computational grid definitions. In this study, DAC and MONACO are compared by having each simulate a blunted flat plate wind tunnel test, using an identical volume mesh. Simulation expense and DSMC metrics are compared. In addition, flow results are compared with available laboratory data. Overall, this study revealed that both codes, excluding grid adaptation, performed similarly. For parallel processing, DAC was generally more efficient. As expected, code accuracy was mainly dependent on physical models employed

Particle kinetic simulation of high altitude hypervelocity flight

In this grant period, the focus has been on the effects of thermo-chemical nonequilibrium in low-density gases, and on interactions between such gases and solid surfaces. Such conditions apply to hypersonic flows of re-entry vehicles, and to the expansion plumes of small rockets. Due to the nonequilibrium nature of these flows, a particle approach has been adopted. The method continues to undergo refinement and application to typical flows of interest. A number of studies have been performed for flows in thermo-chemical nonequilibrium. The effects of vibrational nonequilibrium on the rate of dissociation were studied for diatomic nitrogen. It was found that a new model reproduced the nonequilibrium behavior observed experimentally

On the suitability of the connection machine for direct particle simulation

The algorithmic structure was examined of the vectorizable Stanford particle simulation (SPS) method and the structure is reformulated in data parallel form. Some of the SPS algorithms can be directly translated to data parallel, but several of the vectorizable algorithms have no direct data parallel equivalent. This requires the development of new, strictly data parallel algorithms. In particular, a new sorting algorithm is developed to identify collision candidates in the simulation and a master/slave algorithm is developed to minimize communication cost in large table look up. Validation of the method is undertaken through test calculations for thermal relaxation of a gas, shock wave profiles, and shock reflection from a stationary wall. A qualitative measure is provided of the performance of the Connection Machine for direct particle simulation. The massively parallel architecture of the Connection Machine is found quite suitable for this type of calculation. However, there are difficulties in taking full advantage of this architecture because of lack of a broad based tradition of data parallel programming. An important outcome of this work has been new data parallel algorithms specifically of use for direct particle simulation but which also expand the data parallel diction

Ab initio quantum-chemistry database for N2 (v, J) + N in a state-to-state implementation of the DSMC method

In this work, the implementation within DSMC of a coarse-grain model for nitrogen is presented. The main contribution of this thesis is the development of a methodology by which a detailed state-to-state reaction mechanism for internal energy exchange and molecular dissociation can be reduced to a manageable size and incorporated into a DSMC code. The feasibility of using this model to simulate problems with realistic 2D/3D geometries and conditions relevant for atmospheric entry applications is demonstrated

CHAOS: A multi-GPU PIC-DSMC solver for modeling gas and plasma flows

Numerical modeling of gas and plasma-surface interactions is critical to understanding the complex kinetic processes that dominate the extreme environments of planetary entry and in-space propulsion. However, simulations of these systems that evolve over multiple length- and time-scales is computationally expensive. Until recently, approximations were used to keep computational costs tenable, which in turn, increased the uncertainty in predictions and offered limited insights into the micro-scale flow properties and electron kinetics that dominate the macroscale processes. The need to perform high-fidelity physics-based gas and plasma simulations has led to the development of a three-dimensional, multi-GPU, Particle-in-cell (PIC)-direct simulation Monte Carlo (DSMC) solver called Cuda-based Hybrid Approach for Octree Simulations (CHAOS) that is presented in this work. This computational tool has been applied to candidate PICA-like TPS materials that consist of an irregular porous network of fibers to allow high-temperature boundary layer gases as well as pyrolysis by-products to penetrate in and flow out of the material. Quantifying bulk transport properties of these materials is essential for accurate prediction of the macroscopic ablation rate. The second application that CHAOS is being used with is the modeling of ion thruster plumes that consist of fast beam ions and slow neutrals that undergo charge-exchange (CEX) reactions to produce slow ions and fast neutrals. These slow CEX ions are strongly influenced by the electric field induced between the ion plume and the thruster surface, resulting in a backflow of ions towards the critical solar panel and thruster surfaces. Three backflow quantities, namely, ion flux, incidence angle, and incidence energy affect the macroscopic sputtering rate of the solar panel surfaces over extended operational times and are predicted from the PIC-DSMC simulations

NAS (Numerical Aerodynamic Simulation Program) technical summaries, March 1989 - February 1990

Given here are selected scientific results from the Numerical Aerodynamic Simulation (NAS) Program's third year of operation. During this year, the scientific community was given access to a Cray-2 and a Cray Y-MP supercomputer. Topics covered include flow field analysis of fighter wing configurations, large-scale ocean modeling, the Space Shuttle flow field, advanced computational fluid dynamics (CFD) codes for rotary-wing airloads and performance prediction, turbulence modeling of separated flows, airloads and acoustics of rotorcraft, vortex-induced nonlinearities on submarines, and standing oblique detonation waves

NAS technical summaries. Numerical aerodynamic simulation program, March 1992 - February 1993

NASA created the Numerical Aerodynamic Simulation (NAS) Program in 1987 to focus resources on solving critical problems in aeroscience and related disciplines by utilizing the power of the most advanced supercomputers available. The NAS Program provides scientists with the necessary computing power to solve today's most demanding computational fluid dynamics problems and serves as a pathfinder in integrating leading-edge supercomputing technologies, thus benefitting other supercomputer centers in government and industry. The 1992-93 operational year concluded with 399 high-speed processor projects and 91 parallel projects representing NASA, the Department of Defense, other government agencies, private industry, and universities. This document provides a glimpse at some of the significant scientific results for the year