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Barad, Michael

Publications and source records attributed to Barad, Michael.

17 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Predicting Quadcopter Drone Noise Using the Lattice Boltzmann Method

The market for new vertical takeoff and landing vehicles, including autonomous urban air taxis and drones for applications such as package delivery, imaging, and surveillance, is growing rapidly. However, aerodynamic noise continues to be the biggest roadblock to community acceptance and adoption. To predict the aerodynamic noise generated by an isolated quadcopter drone, derived from from first principles, we used the Lattice Boltzmann flow solver within NASA’s Launch Ascent and Vehicle Aerodynamics (LAVA) solver framework. The solver’s computational efficiency, and the complete absence of labor-intensive manual volume mesh generation in the workflow, are key to making routine aeroacoustic analysis of urban air taxis and drones from first principles possible.

Cadieux, Francois↗
NASA NTRS2018

High-Resolution Launch Environment Simulations

After many years of harsh rocket launches, the Main Flame Deflector (MFD) at Kennedy Space Center has been upgraded in anticipation of flights of NASA’s next generation Space Launch System. The new MFD has a much easier to maintain shingled steel surface.

Launch↗
NASA NTRS2018

Performance Enhancements for the Lattice-Boltzmann Solver in the LAVA Framework

Performance enhancements in NASA's recently developed Lattice Boltzmann solver within the Launch Ascent and Vehicle Aerodynamics (LAVA) framework are presented. Two key algorithmic developments are highlighted. A coarse-fine interface treatment that discretely conserves mass and momentum has been implemented and successfully verified and validated. Code optimizations targeting improved serial and parallel performance were presented. For a simple turbulent Taylor-Green Vortex problem, we were able to demonstrate a 2.3 times speedup over the baseline code for a single Skylake-SP node containing 40 physical cores, and a 2.14 times speedup for 64 nodes containing 2560 physical cores. In addition, we were able to show that the optimizations enabled us to scale the code almost perfectly to 20480 physical cores where, including ghost cells, the problem size was 10 billion cells.

Barad, Michael↗
NASA NTRS2018

Performance Enhancements for the Lattice-Boltzmann Solver in the LAVA Framework

Performance enhancements in NASA's recently developed Lattice Boltzmann solver within the Launch Ascent and Vehicle Aerodynamics (LAVA) framework are presented. Two key algorithmic developments are highlighted. A coarse-fine interface treatment that discretely conserves mass and momentum has been implemented and successfully verified and validated. Code optimizations targeting improved serial and parallel performance were presented. For a simple turbulent Taylor-Green Vortex problem, we were able to demonstrate a 2.3 times speedup over the baseline code for a single Skylake-SP node containing 40 physical cores, and a 2.14 times speedup for 64 nodes containing 2560 physical cores. In addition, we were able to show that the optimizations enabled us to scale the code almost perfectly to 20480 physical cores where, including ghost cells, the problem size was 10 billion cells.

LAVA↗
NASA NTRS2018

Wall-Modeled Lattice Boltzmann and Navier-Stokes Approaches for Separated Flows

Lattice Boltzmann (LB) and hybrid Reynolds-averaged Navier-Stokes/large eddy simulation (RANS/LES) methods within the Launch Ascent and Vehicle Aerodynamics (LAVA) solver framework are applied to NASA's Revolutionary Computational Aerosciences (RCA) standard test cases for separated flows. A detailed comparison between the performance and accuracy of the two emerging numerical methodologies for turbulence resolving simulations, i.e. the LB and hybrid RANS/LES methods will be presented. This contribution addresses the RCA technical challenge to identify and down-select critical turbulence, transition, and numerical method technologies for 40% reduction in predictive error for standard turbulence separated flow test cases. Results for the 2D NASA wall-mounted hump and the axisymmetric transonic bump including time-averaged pressure coefficient, skin friction, and velocity pro les, as well as resolved and modeled Reynolds stresses for both numerical approaches will be presented and differences between LB and hybrid RANS/LES will be discussed.

Lattice Boltzmann↗
NASA NTRS2017

Lattice Boltzmann for Airframe Noise Predictions

Increase predictive use of High-Fidelity Computational Aero- Acoustics (CAA) capabilities for NASA's next generation aviation concepts. CFD has been utilized substantially in analysis and design for steady-state problems (RANS). Computational resources are extremely challenged for high-fidelity unsteady problems (e.g. unsteady loads, buffet boundary, jet and installation noise, fan noise, active flow control, airframe noise, etc) ü Need novel techniques for reducing the computational resources consumed by current high-fidelity CAA Need routine acoustic analysis of aircraft components at full-scale Reynolds number from first principles Need an order of magnitude reduction in wall time to solution!

Barad, Michael↗