Aeronautics

Scale Resolving Jet Noise Simulations to Reduce Airport Noise

Overview

NASA’s Commercial Supersonic Technology (CST) project has formulated a technical challenge to design a quiet, low boom supersonic aircraft that meets Federal Aviation Administration noise regulations. Landing and takeoff noise (LTO) poses a high risk to the commercial supersonic market. However, there is currently no certification noise rule for commercial supersonic aircraft. For this reason, technical committees need reliable noise predictions to assess environmental impacts against the economic benefits of supersonic travel, and it is important that the community agrees on the quality of the underlying data before approving a future regulation.

Snapshot of a low-boom supersonic aircraft simulation

To address this problem, our team of research scientists at the NASA Advanced Supercomputing (NAS) facility at NASA’s Ames Research Center performed wall-modeled large-eddy simulations (WMLES) with the Launch, Ascent, and Vehicle Aerodynamics (LAVA) computational fluid dynamics (CFD) software to predict jet noise for single-stream asymmetric round jets at several flow conditions. The simulations address the new Prediction Uncertainty Reduction technical challenge within the context of the CST project, with the goal to quantify and reduce uncertainties from scale-resolving simulations to assess noise characteristics of next-generation quiet supersonic commercial jets during LTO conditions where the noise from the exhaust jet dominates. Our simulation results show an order of magnitude cost reduction—attributed to algorithm and software improvements— compared to an earlier study of this configuration, and demonstrates that WMLES can be used as a cost-competitive approach for jet noise predictions.

Project Details

Frames from wall-modeled larged eddy simulation with two-stream internally mixed nozzle

Under the Transformational Tools and Technologies project, we performed scale-resolving simulations with the LAVA solver to predict jet acoustics for NASA’s Low Boom Flight Demonstrator (LBFD). This included using both hybrid Reynolds-Averaged Navier-Stokes/Large-Eddy Simulation and WMLES methods on validation cases with increasing complexity, such as jet-surface interaction noise, multi-stream, and chevron nozzle designs. First, we developed best practices and assessed the uncertainties, strengths, and drawbacks of each simulation method. To better quantify uncertainties, we generated an extensive database comprising several simulations in static and in-flight conditions, and carefully compared them with experimental data. We then applied our lessons learned to a complex configuration, including several jet noise reduction technologies like internally lobed mixers, plugs, and multi-streams.

Results and Impact

Snapshot of wall-modeled large eddy simulation of a complex multi-stream nozzle for a low-boom supersonic aircraft configuration

By improving WMLES capabilities within the LAVA solver, we successfully predicted jet noise and jet-surface interaction noise. Great performance improvements reduced the overall simulation time by about 65x (since 2019) and the runtime from weeks to hours. The findings from these simulations have resulted in new insights and additional experimental investigations of certain flow phenomena, performed in collaboration with researchers at NASA’s Glenn Research Center. The code improvements also enabled generation of a database with several static and in-flight flow configurations. By increasing the output of scale-resolving simulations from a few per year to several per month, we have a better understanding of the uncertainties and strengths of WMLES for jet noise predictions. Gaining confidence in the predictive capabilities of LES for jet noise is another step toward vehicle certification by analysis.

Why HPC Matters

Supercomputers at the NAS facility are instrumental in enabling next-level, large-scale computational aeroacoustics. Due to the nature of the broadband noise generated by jets, it is necessary to run our simulations with a very small timestep over long periods, requiring computational tools that can use current computer hardware very efficiently. Additionally, new load balancing features developed at NAS enabled strong scaling, and we used 128 AMD Rome nodes on the Aitken supercomputer for 250-million-grid-point grid systems—resulting in simulation wall-times of less than two hours to predict broadband noise. Each simulation generates hundreds of terabytes of data that is then analyzed in the frequency domain. For this, special post-processing tools were developed that reduce the cost of accessing data on disk and help go beyond what traditional data analysis tools offer.

What's Next

Simulation of noise generated by a jet

While great emphasis has been placed on making the numerical tools as efficient as possible, gaining speedups of more than 6500%, the manual mesh generation effort is still the biggest bottleneck to increase turnaround times for generating larger databases. The mesh generation for complex configurations utilizing curvilinear meshes is labor intensive and can take an experienced engineer days or weeks of meshing. Ongoing work within the LAVA solver framework is focused on applying WMLES to a mesh paradigm that enables automated meshing, reducing the mesh generation time from weeks
to minutes on a modern workstation.

Presentation

More Information

Researchers

  • Gerrit-Daniel Stich, NASA Ames Research Center
    Gerrit-Daniel, Stich
  • Aditya Ghate, NASA Ames Research Center
  • Jeffrey Housman, NASA Ames Research Center
  • Cetin Kiris, NASA Ames Research Center
    Cetin Kiris