ACAT1 Benchmark of RANS-Informed Analytical Methods for Fan Broadband Noise Prediction-Part I-Influence of the RANS Simulation
Artikel i vetenskaplig tidskrift, 2020

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.

fan broadband noise

turbulence models

ACAT1 fan

fan noise benchmark

RANS-informed noise prediction


Carolin Kissner

Deutsches Zentrums für Luft- und Raumfahrt (DLR)

Sebastien Guerin

Deutsches Zentrums für Luft- und Raumfahrt (DLR)

Pascal Seeler

Deutsches Zentrums für Luft- und Raumfahrt (DLR)

Mattias Billson

GKN Aerospace Sweden

Paruchuri Chaitanya

University of Southampton

Pedro Carrasco Larana

ITP Aero

Helene de Laborderie

SAFRAN Aircraft Engines

Benjamin Francois

ONERA - The French Aerospace Lab

Katharina Lefarth

MTU Aero Engines

Danny Lewis

Université de Lyon

Gonzalo Montero Villar

Chalmers, Mekanik och maritima vetenskaper, Strömningslära

Thomas Node-Langlois

Airbus Group


2624-599X (eISSN)

Vol. 2 3 539-578

Validation of improved turbomachinery noise prediction models and development of novel design methods for fan stages with reduced broadband noise (TurboNoiseBB)

Europeiska kommissionen (EU) (EC/H2020/690714), 2016-09-01 -- 2020-02-29.



Strömningsmekanik och akustik




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