Multidisciplinary Design Optimization of a Low-Noise and Efficient Next-Generation Aero-Engine Fan

2020 ◽  
Author(s):  
Robert Jaron ◽  
Antoine Moreau ◽  
Sébastien Guérin ◽  
Lars Enghardt ◽  
Timea Lengyel-Kampmann ◽  
...  
Keyword(s):  
Design Optimization ◽  
Multidisciplinary Design Optimization ◽  
Hybrid Approach ◽  
Low Noise ◽  
Multidisciplinary Design ◽  
Noise Prediction ◽  
Noise Sources ◽  
Aerodynamic Efficiency ◽  
Aero Engine ◽  
Rans Simulations

Abstract Due to the increasing bypass ratios of modern engines, the fan stage is increasingly becoming the dominant source of engine noise. Accordingly, it is becoming more and more important to develop not only efficient but also quiet fan stages. In this paper the noise emission of a fan for an aero-engine with a bypass ratio of 19 is reduced within a multidisciplinary design optimization (MDO) by means of an hybrid noise prediction method while at the same time optimizing the aerodynamic efficiency. The aerodynamic performance of each configuration in the optimization is evaluated by stationary Reynolds-Averaged Navier-Stokes (RANS) simulations. These stationary flow simulations are also used to extract the aerodynamic excitation sources for the analytical fan noise prediction. The resulting large database of the optimization provides new insights into which extent an MDO can contribute to the design of both quiet and efficient fan stages. In addition to that the hybrid approach of numerical flow solutions and analytical description of the noise sources enables to understand the noise reduction mechanisms. In particular, the influence of rotor blade loading on the aerodynamic efficiency and the noise sources as well as the potential of configurations with a comparatively low number of outlet guide vanes (OGV) is explored. The acoustic results of selected configurations are confirmed by unsteady RANS simulations.

MULTIDISCIPLINARY DESIGN OPTIMIZATION OF A LOW-NOISE AND EFFICIENT NEXT-GENERATION AERO-ENGINE FAN

2021 ◽  
pp. 1-38
Author(s):  
Robert Jaron ◽  
Antoine Moreau ◽  
Sébastien Guérin ◽  
Lars Enghardt ◽  
Timea Lengyel ◽  
...  
Keyword(s):  
Design Optimization ◽  
Multidisciplinary Design Optimization ◽  
Hybrid Approach ◽  
Low Noise ◽  
Multidisciplinary Design ◽  
Noise Prediction ◽  
Noise Emission ◽  
Noise Sources ◽  
Aerodynamic Efficiency ◽  
Aero Engine

Abstract Due to the increasing bypass ratios of modern engines, the fan stage is increasingly becoming the dominant source of engine noise. Accordingly, it is becoming more and more important to develop not only efficient but also quiet fan stages. In this paper the noise emission of a fan for an aero-engine with bypass ratio of 19 is reduced within a multidisciplinary design optimization (MDO) by means of a hybrid noise prediction method while at the same time optimizing the aerodynamic efficiency. The aerodynamic performance of each configuration in the optimization is evaluated by stationary Reynolds-Averaged Navier- Stokes (RANS) simulations. These stationary flow simulations are also used to extract the aerodynamic excitation sources for the analytical fan noise prediction. The resulting large database of the optimization provides new insights into which extent an MDO can contribute to the design of both quiet and efficient fan stages. In addition to that the hybrid approach of numerical flow solutions and analytical description of the noise sources enables to understand the noise reduction mechanisms. In particular, the influence of rotor blade loading on the aerodynamic efficiency and the noise sources as well as the potential of configurations with a comparatively low number of outlet guide vanes (OGV) is explored.

Multidisciplinary Design Optimization on Conceptual Design of Aero-engine

2016 ◽  
Vol 33 (2) ◽  
Author(s):  
Xiao-bo Zhang ◽  
Zhan-xue Wang ◽  
Li Zhou ◽  
Zeng-wen Liu
Keyword(s):  
Design Optimization ◽  
Conceptual Design ◽  
Multidisciplinary Design Optimization ◽  
System Level ◽  
Multidisciplinary Design ◽  
Design Stage ◽  
Surface Model ◽  
Coupled Problem ◽  
Aero Engine ◽  
Integrated Performance

AbstractIn order to obtain better integrated performance of aero-engine during the conceptual design stage, multiple disciplines such as aerodynamics, structure, weight, and aircraft mission are required. Unfortunately, the couplings between these disciplines make it difficult to model or solve by conventional method. MDO (Multidisciplinary Design Optimization) methodology which can well deal with couplings of disciplines is considered to solve this coupled problem. Approximation method, optimization method, coordination method, and modeling method for MDO framework are deeply analyzed. For obtaining the more efficient MDO framework, an improved CSSO (Concurrent Subspace Optimization) strategy which is based on DOE (Design Of Experiment) and RSM (Response Surface Model) methods is proposed in this paper; and an improved DE (Differential Evolution) algorithm is recommended to solve the system-level and discipline-level optimization problems in MDO framework. The improved CSSO strategy and DE algorithm are evaluated by utilizing the numerical test problem. The result shows that the efficiency of improved methods proposed by this paper is significantly increased. The coupled problem of VCE (Variable Cycle Engine) conceptual design is solved by utilizing improved CSSO strategy, and the design parameter given by improved CSSO strategy is better than the original one. The integrated performance of VCE is significantly improved.

scholarly journals An Improved Collaborative Algorithm with Artificial Neural Network in Multidisciplinary Design Optimization of AUV

2017 ◽  
Author(s):  
Xiaodong Xu ◽  
Hongkai Li
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Design Optimization ◽  
Optimization Algorithm ◽  
Information Exchange ◽  
Multidisciplinary Design Optimization ◽  
Low Noise ◽  
Collaborative Optimization ◽  
Multidisciplinary Design ◽  
Artificial Neural

Multidisciplinary Design Optimization (MDO) is the most active field in the design of current complex system engineering, which is possessed with such two difficulties as subsystem information exchange and analytical and computational complexity of systems. Therefore, an improved collaborative optimization algorithm based on ANN (artificial neural network) response surface was proposed dependent on the consistency constraint algorithm and concurrent subspace algorithm. As an optimization method with secondary structure, it satisfied only local constraints in discipline layer, but provided a coordinated mechanism for interdisciplinary conflict in system layer. Finally, it was applied in the multidisciplinary design optimization of autonomous underwater vehicle (AUV). As shown from the result, the MDO convergence stability and reliability of low resistance, low noise and high maneuvering performance of the AUV shape can be ensured by the improved collaborative optimization algorithm, thus verifying the effectiveness of the algorithm.

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