Predicting Jet Noise for Full-Scale Low-Boom Aircraft

Overview

NASA’s supersonic vehicle research addresses the development of tools, technologies, and knowledge to help eliminate the technical barriers to practical commercial supersonic flight. Although the major focus of this development work has been on reducing the ground signature at supersonic cruise, an airplane must also satisfy noise constraints during takeoff and landing when it is traveling at subsonic speeds in order to be certified. The dominant source of sound during this phase is jet noise. Computational aeroacoustic simulation tools can be used to assess new designs for NASA’s Low-Boom Flight Demonstrator (LBFD) aircraft at these lower speeds. The NASA Advanced Supercomputing (NAS) Division’s Launch Ascent and Vehicle Aerodynamics (LAVA) team is scrutinizing both modeling and simulation practices and the use of wall-modeled large eddy simulation (WMLES) methods, and are developing new methods to predict jet noise—including surface interaction noise—on a full flight configuration airplane.

"By improving WMLES capabilities within the LAVA solver framework, we achieved a successful prediction of jet noise as well as jet surface interaction noise. Findings from these simulations have already resulted in new insights and additional experimental investigations of certain flow phenomena."

Project Details

While great advancements have been made toward predicting jet noise with computational fluid dynamics (CFD) solvers—including high-fidelity simulations at flight Reynolds numbers and modeling of important geometric features, such as jet surface interaction noise—most simulations rely on Reynolds-Averaged Navier-Stokes (RANS) methods and are still limited to simple geometries due to the complexity of the problem. However, the scale-resolving simulations needed to predict accurate far-field noise are still too computationally demanding to investigate full airframe interaction noise.

A possible strategy to achieve full-scale airframe simulations that include jet-noise prediction with complex geometries like multi-stream chevron nozzles is to use WMLES. As a step toward predicting jet acoustics for the LBFD, we performed scale-resolving simulations with the NAS-developed LAVA solver scrutinizing hybrid RANS/LES methods on validation cases with increasing complexity, including jet surface interaction noise, multi-stream, and chevron nozzle designs. This work was funded by NASA's Commercial Supersonic Transport Project and NASA’s Transformational Tools and Technologies Project.

Results and Impact

By improving WMLES capabilities within the LAVA solver framework, we achieved a successful prediction of jet noise as well as jet surface interaction noise. Findings from these simulations have already resulted in new insights and additional experimental investigations of certain flow phenomena. Gaining confidence in the predictive capabilities of hybrid RANS/LES for jet noise is another step toward vehicle certification by analysis. This becomes more important when most non-mission-critical experiments have been canceled or paused due to the COVID-19 pandemic.

Why HPC Matters

The Pleiades and Electra supercomputers at the NAS facility are instrumental in enabling these next-level, large-scale computational aeroacoustics simulations over hundreds of nodes and thousands of cores. Each simulation generates hundreds of terabytes of data that is then analyzed in the frequency domain, which requires parallelized post-processing tools that reduce the cost of accessing data on disk. Raw computational power is not enough—large and efficient distributed filesystems are also critical. In addition, NAS’s visualization services help us go beyond what traditional data analysis tools offer.

Related Links

• Computational Framework for Launch, Ascent and Vehicle Aerodynamics (LAVA)
• Jet Noise Prediction using Hybrid RANS/LES with Structured Overset Grids
• Hybrid RANS/LES Simulation of Jet Surface Interaction Noise