A GPU-accelerated, hybrid FVM-RANS methodology for modeling rotorcraft brownout

Title of dissertation: A GPU-ACCELERATED, HYBRID FVM-RANS METHODOLOGY FOR MODELING ROTORCRAFT BROWNOUT Sebastian Thomas Doctor of Philosophy, 2013 Dissertation directed by: Professor James D. Baeder Department of Aerospace Engineering A numerically efficient, hybrid Eulerian-Lagrangian methodology has been developed to help better understand the complicated two-phase flowfield encountered in rotorcraft brownout environments. The problem of brownout occurs when rotorcraft operate close to surfaces covered with loose particles such as sand, dust or snow. These particles can get entrained, in large quantities, into the rotor wake leading to a potentially hazardous degradation of the pilots visibility. It is believed that a computationally efficient model of this phenomena, validated against available experimental measurements, can be a used as a valuable tool to reveal the underlying physics of rotorcraft brownout. The present work involved the design, development and validation of a hybrid solver that combines the numerical efficiency of a free-vortex method with the relatively high-fidelity of a 3D, time-accurate, Reynolds-averaged, Navier-Stokes (RANS) solver. For dual-phase simulations, this hybrid method can be unidirectionally coupled with a sediment tracking algorithm to study cloud development. To explore the use of GPUs for RANS simulations, a 3D, time-accurate, implicit, structured, compressible, viscous, turbulent, finite-volume RANS solver was designed and developed in CUDA-C. Validation and verification of the GPUbased solver was performed for both canonical and realistic bench-mark problems on a variety of GPU platforms. In these test-cases, a performance assessment of the GPU-RANS solver indicated that it was between one and two orders of magnitude faster than equivalent single CPU core computations ( as high as 50X for fine-grain computations on the latest platforms ). For simulations involving implicit methods, a multi-granular technique was used that sought to exploit the intermediate coarse-grain parallelism inherent in families of line-parallel methods like Alternating Direction Implicit (ADI) schemes coupled with conservative variable parallelism. The validated GPU-RANS solver was then coupled with GPU-based freevortex and sediment tracking methods to model single and dual-phase, modelscale brownout environments. A qualitative and quantitative validation of the methodology was performed by comparing predictions with available measurements, including flow field measurements and observations of particle transport mechanisms that have been made with laboratory-scale rotor/jet configurations in ground effect. In particular, dual-phase simulations were able to resolve key transport phenomena in the dispersed phase such as creep, vortex trapping and sediment wave formation. Furthermore, these simulations were demonstrated to be computationally more efficient than equivalent computations on a cluster of traditional CPUs a model-scale brownout simulation using the hybrid approach on a single GTX Titan now takes 1.25 hours per revolution compared to 6 hours per revolution on 32 Intel Xeon cores. A GPU-ACCELERATED, HYBRID FVM-RANS METHODOLOGY FOR MODELING ROTORCRAFT BROWNOUT