NASA Glenn Develops Advanced Jet-Noise Modeling Tools to Predict and Reduce Future Aircraft Engine Sound Levels

Research groups at NASA’s Glenn Research Center are building the theoretical foundations and software tools needed to forecast how loud aircraft engines will be—work that feeds directly into the design and assessment of next-generation propulsion systems. Many of these codes are available to engineers and researchers by request through NASA’s Software Catalog.

A major thrust of the effort focuses on predicting jet noise, a problem that links aerodynamics, turbulence, and acoustics. NASA Glenn’s JeNo code approaches the challenge using Lilley’s Acoustic Analogy together with mean-flow inputs generated by a Reynolds-Averaged Navier–Stokes (RANS) solver. That coupling is key: the accuracy of the sound prediction depends heavily on the accuracy of the underlying aerodynamic solution. For that reason, NASA’s jet-noise research does not stop at acoustics alone. Source modeling, turbulence modeling, and the development of advanced measurement systems are all central to improving overall predictive capability.

One advantage of RANS-based approaches such as JeNo is speed. They can deliver answers far more quickly than higher-fidelity alternatives like Large-Eddy Simulation (LES) or Direct Numerical Simulation (DNS), which are typically much more computationally expensive. JeNo is designed to compute far-field sound spectral density from axisymmetric jets, letting users specify an observer location and a frequency range of interest. NASA reports that JeNo has been validated for subsonic and low-supersonic axisymmetric jets that are unheated.

Before JeNo, NASA Glenn developed the MGBK jet-noise prediction code. Researchers have used MGBK to examine how jet-noise trends change for complex engine exhaust nozzle configurations. One notable application has been evaluating the noise-reduction impact of chevrons—serrated nozzle-edge features now commonly seen on commercial turbofan engines.

NASA Glenn’s portfolio also includes a suite of tools aimed at fan noise, particularly the tones and broadband components associated with rotor–stator interactions. The V072 code uses simplified representations of fan flow and geometry, yet has demonstrated value for studying rotor/stator interaction tone noise. It is intended for rapid assessments early in a design cycle, supporting decisions on variables such as blade and vane counts, the spacing between rotor and stator rows, and stator-vane sweep and lean—parameters that strongly influence tonal noise levels in a fan stage.

For a more advanced but still fast-running option, NASA offers TFaNS. Like V072, it predicts rotor–stator tone levels, but it also includes blade-row acoustic coupling—accounting for effects such as transmission and reflection—and can propagate tones out to the far field. This makes it useful for trend studies while keeping turnaround times compatible with early design work.

When simplified physics is no longer sufficient, Linflux provides a higher-fidelity pathway. It is built to handle realistic three-dimensional flows and blade geometries, requiring substantially more computing resources than V072 or TFaNS. Linflux predicts rotor/stator tone noise and has been carefully validated against experimental measurements, consistent with validation practices across NASA Glenn’s Acoustics Branch.

Broadband fan noise is addressed by BFANS, which estimates noise generated when turbulence impinges on the leading edges of rotor blades and stator vanes. The code relies on inputs such as turbulence intensity and characteristic length scale. NASA notes that pairing BFANS calculations with experimental results—including tests in facilities like Glenn’s 9-by-15-foot Low Speed Wind Tunnel—can help identify which fan-stage components contribute most to overall noise.

Another broadband-focused tool, RSI, targets the noise produced when turbulence in the fan rotor wake interacts with the exit guide vanes. The code calculates the resulting broadband noise spectrum and computes acoustic power spectra upstream and downstream of the stator.

Why it matters

Aircraft noise affects communities near airports, shapes regulatory compliance, and can constrain aircraft and engine design choices. NASA Glenn’s mix of fast-running design tools and more detailed physics-based models aims to help industry evaluate noise earlier and more reliably—before costly hardware is built. The next step to watch is continued validation and expansion of these models to more operating conditions and more realistic geometries as measurement capabilities improve.