ACAT1 Benchmark of RANS-Informed Analytical Methods for Fan Broadband Noise Prediction—Part I—Influence of the RANS Simulation

Abstract

A benchmark of Reynolds-Averaged Navier-Stokes (RANS)-informed analytical methods, which are attractive for predicting fan broadband noise, was conducted within the framework of the European project TurboNoiseBB. This paper discusses the first part of the benchmark, which investigates the influence of the RANS inputs. Its companion paper focuses on the influence of the applied acoustic models on predicted fan broadband noise levels. While similar benchmarking activities were conducted in the past, this benchmark is unique due to its large and diverse data set involving members from more than ten institutions. In this work, the authors analyze RANS solutions performed at approach conditions for the ACAT1 fan. The RANS solutions were obtained using different CFD codes, mesh resolutions, and computational settings. The flow, turbulence, and resulting fan broadband noise predictions are analyzed to pinpoint critical influencing parameters related to the RANS inputs. Experimental data are used for comparison. It is shown that when turbomachinery experts perform RANS simulations using the same geometry and the same operating conditions, the most crucial choices in terms of predicted fan broadband noise are the type of turbulence model and applied turbulence model extensions. Chosen mesh resolutions, CFD solvers, and other computational settings are less critical.

ACAT1 Benchmark of RANS-Informed Analytical Methods for Fan Broadband Noise Prediction: Part II—Influence of the Acoustic Models

“…The peak frequency of RSI noise is approximately 3 times the blade passing frequency (BPF), which is close to the empirical factor of 2.5 proposed by Heidmann [37]. The Strouhal number St given in x-axis of the graphs in Figure 3 is defined in accordance with Kissner et al [1]: St = f R/W 0 , with f the frequency, R ≈ 4.23 m the radius at the duct casing upstream of the stator leading edge, and W 0 (≈240 m/s at Sideline) the averaged flow velocity upstream of the stator. The second non-dimensional number kR shown on the top x-axis of the graphs corresponds to the Helmholtz number.…”

“…The benchmark organised as part of the European project TurboNoiseBB is a contribution to the assessment of RANS-informed analytical methods applied to rotor-stator interaction (RSI) broadband noise. While a first part reported in the companion paper by Kissner et al [1] focuses on the effect of the RANS model, the present work focuses on the impact of the acoustic model.…”

“…With the two questions raised at the beginning of the introduction in mind, a benchmark was organised reconsidering the impact of the two main ingredients of the method-(1) the RANS calculation (in particular the choice of the turbulence model) and (2) the aeroacoustic models. While the first part of the study is addressed in a companion paper by Kissner et al [1], this second part deals with the impact of the acoustic models. The benchmark character is unique as more than ten independent European institutions using different CFD and acoustic solvers were involved.…”

Aeroacoustic design and broadband noise predictions of a fan stage with serrated outlet guide vanes

“…In this study, RANS simulations are based on k −  Smith and k − ω Menter SST turbulence models from ONERA and DLR using elsA 21 and TRACE codes, respectively. 22 For fast assessment of major aerodynamic features of a turbofan stage, a mixing plane approach is currently adopted in fan-OGV calculations instead of expensive unsteady RANS simulations.…”

“…As discussed in Ref. 22 , the choice of the RANS turbulence model as well as the way adopted to assess the TLS can have a significant impact on the noise results. This is the reason why two major models ( Smith and Menter SST) that are often used for turbomachinery applications have been selected.…”