NASA@SC17

Aeronautics

Predicting Aircraft Noise and Spacecraft Acoustic Loads

Overview

For the last 20 years, the steady Reynolds-averaged Navier-Stokes (RANS) approach has been the workhorse for aerodynamic analysis of aerospace vehicles. However, RANS results are limited in the unsteady and acoustic information they can provide. This is where next-level computational aeroacoustics (CAA) methods like large-eddy simulation (LES) and hybrid RANS/LES can impact the design of NASA’s next-generation concept aircraft and space vehicles. Using the Launch Ascent and Vehicle Aerodynamics (LAVA) simulation suite, we are addressing the three main challenges in CAA: generating high-quality grids, physical modeling of turbulence, and reducing the otherwise large computational requirements.

Project Details

Using LAVA’s curvilinear overset grid paradigm coupled with innovations in zonal hybrid RANS/LES methods, a near-sonic jet plume was simulated to predict aircraft jet noise during approach. Agreement with experimental data was better than any that had been obtained previously. We used the Cartesian Navier-Stokes (CNS) paradigm to predict tonal noise generated by a new, fuel-efficient, open rotor aircraft engine. Predictions correlated closely with measurements in a wind tunnel test. LAVA’s CNS solver was also used to predict transient and acoustic loads ahead of the Orion spacecraft launch abort motor test, and for three launch abort scenarios. Blind comparisons showed good agreement with test measurements.

Using a revolutionary Lattice-Boltzmann approach, both far-field and near-field noise were predicted for a realistic aircraft nose landing gear and fuselage during landing. Results show great promise: they match the experimental data available at a greatly reduced computational cost—15 times lower than that of other methods.

Results and Impact

Recent success in predicting noise levels for aircraft and acoustic loads for spacecraft demonstrate the LAVA framework’s powerful capabilities. LAVA paves the way for the inclusion of more CAA analysis in the design of future aircraft and spacecraft. The jet noise prediction capability will impact the design and placement of the nozzle for the Low Boom Flight Demonstrator, a concept quiet supersonic aircraft. Tonal noise predictions will enable the design of quieter open rotor aircraft propulsion systems. The LAVA team’s work has already impacted the requirements for the final design of the launch abort vehicle. The computational efficiency of the Lattice-Boltzmann approach will also enable larger-scale, more accurate airframe and fan noise computations than were previously possible.

Why HPC Matters

NASA’s Pleaides supercomputer is instrumental in enabling these next-level, large-scale CAA simulations over hundreds of nodes and thousands of cores. Each simulation generates very large datasets (hundreds of terabytes). The data then needs to be analyzed in the frequency domain, requiring parallelized post-processing tools that hide the cost of accessing data on disk. Raw computational power is not enough—large and efficient distributed filesystems are also critical. NASA’s visualization services help us go beyond what traditional data analysis tools offer. The numerical Schlieren for the jet flow case helps to identify noise sources and provides a direct comparison to Schlieren high-speed photography in experiments.

More Information

Cetin Kiris, NASA Ames Research Center
cetin.c.kiris@nasa.gov
Francois Cadieux, NASA Ames Research Center
francois.cadieux@nasa.gov