An improved aerodynamic performance optimization method of 3-D low Reynolds number rotor blade

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Shuyi Zhang ◽  
Bo Yang
Keyword(s):  
Neural Network ◽  
Reynolds Number ◽  
Performance Optimization ◽  
Rotor Blade ◽  
Optimization Method ◽  
Aerodynamic Performance ◽  
Aerodynamic Optimization ◽  
Parametrization Method ◽  
Value Evaluation ◽  
Fitness Value

Abstract In this paper, an improved aerodynamic performance optimization method for 3-D low Reynolds number (Re) rotor blade is proposed. A conventional optimization procedure of blade is usually divided into three parts, such as the parameterization method, the fitness value evaluation and the optimization algorithm. This work is mainly focused on the first two parts. The parametrization method, Camber-FFD, is presented based on the camber parametrization method and the free-form deformation algorithm (FFD). The shape of 3-D blade is parameterized by the incidence angles and the coordinates of the maximum camber points. The fitness value evaluation has been realized with the help of an adaptive topological back propagation multi-layer forward artificial neural network (BP-MLFANN). During the training of BP-MLFANN, the hybrid particle swarm optimization method combined with the modified very fast simulate annealing algorithm (HPSO-MVFSA) is adopted to determine the neural network topology adaptively. To verify the effectiveness of this aerodynamic optimization method, the aerodynamic performance of a 3-D low-Re blade, such as Blade D900, is optimized, and the results are compared and analyzed based on the experiments and simulations. It is proved that this aerodynamic optimization method is feasible.

scholarly journals Research on Fan Operation Evaluation and Error State Judgment Relying on Improved Neural Network and Intelligent Computing

2021 ◽  
Vol 2083 (4) ◽  
pp. 042005
Author(s):  
Xueyi Liu ◽  
Junhao Dong ◽  
Guangyu Tu
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Fault Diagnosis ◽  
Wind Turbine ◽  
Performance Prediction ◽  
Optimization Method ◽  
Aerodynamic Performance ◽  
Evaluation Index ◽  
Genetic Optimization ◽  
Quantum Genetic Algorithm

Abstract Fan, as the most commonly used mechanical equipment, is widely used. In order to solve the problem of fan bearing fault diagnosis, this paper analyzes the main factors affecting fan spindle speed and power generation in operation. The input and output parameters of the performance prediction model are determined. The performance prediction model of wind turbine is established by using generalized regression neural network, and the smoothing factor of GRNN is optimized by comparing the prediction accuracy of the model. Based on this model, the sliding data window method is used to calculate the residual evaluation index of wind turbine speed and power in real time. When the evaluation index continuously exceeds the pre-set threshold, the abnormal state of wind turbine can be judged. In order to obtain wind turbine blades with better aerodynamic performance, a blade aerodynamic performance optimization method based on quantum heredity is proposed. The B é zier curve control point is used as the design variable to represent the continuous chord length and torsion angle distribution of the blade, the blade shape optimization model aiming at the maximum power is established, and the quantum genetic algorithm is used to optimize the chord length and torsion angle of the blade under different constraints. The optimization results of quantum genetic algorithm and classical genetic algorithm are compared and analyzed. Under the same parameters and boundary conditions, the proposed blade aerodynamic optimization method based on quantum genetic optimization is better than the classical genetic optimization method, and can obtain better blade aerodynamic shape and higher wind energy capture efficiency. This method makes up for the shortcomings of traditional fault diagnosis methods, improves the recognition rate of fault types and the accuracy of fault diagnosis, and the diagnosis effect is good.

scholarly journals Applications of an Improved Aerodynamic Optimization Method on a Low Reynolds Number Cascade

Processes ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1150 ◽  
Author(s):  
Shuyi Zhang ◽  
Bo Yang ◽  
Hong Xie ◽  
Moru Song
Keyword(s):  
Reynolds Number ◽  
Simulated Annealing Algorithm ◽  
Design Method ◽  
Incidence Angle ◽  
Thickness Distribution ◽  
Low Reynolds Number ◽  
Pressure Coefficient ◽  
Optimization Method ◽  
Aerodynamic Optimization ◽  
Low Reynolds

The effect of cascade aerodynamic optimization on turbomachinery design is very significant. However, for most traditional cascade optimization methods, aerodynamic parameters are considered as boundary conditions and rarely directly used as the optimization variables to realize optimization. Given this problem, this paper proposes an improved cascade aerodynamic optimization method in which an incidence angle and nine geometric parameters are used to parameterize the cascade and one modified optimization algorithm is adopted to find the cascade with the optimal aerodynamic performance. The improved parameterization approach is based on the Non-Uniform Rational B-Splines (NURBS) method, the camber line superposing thickness distribution molding (CLSTDM) method, and the plane cascade design method. To rapidly and effectively find the cascade with the largest average lift-drag ratio within a certain range of incidence angles, modified particle swarm optimization combined with the modified very fast simulated annealing algorithm (PSO-MVFSA) is adopted. To verify the feasibility of the method, a cascade with NACA4412 and a practical cascade are optimized. It is found that the average lift-drag ratios of two optimal performance cascades are respectively increased by 13.38% and 15.21% in comparison to those of two original cascades. Meanwhile, through optimizing the practical cascade of the Blade D500, under different volume flow rates, the pressure coefficient of the optimized cascade is increased by an average of more than 6.12% compared to that of the prototype, and the average efficiency is increased by 11.15%. Therefore, this improved aerodynamic optimization method is reliable and feasible for the performance improvement of cascades with a low Reynolds number.

scholarly journals Two-stage aerodynamic optimization method based on early termination of CFD convergence and variable-fidelity model

2021 ◽  
Vol 39 (1) ◽  
pp. 148-158
Author(s):  
Ji Miao ◽  
Chunlin Gong ◽  
Chunna Li
Keyword(s):  
Optimization Method ◽  
Aerodynamic Performance ◽  
Early Termination ◽  
Computational Time ◽  
High Fidelity ◽  
Aerodynamic Optimization ◽  
Two Stage ◽  
Optimization Stage ◽  
Variable Fidelity ◽  
Fidelity Model

Efficient aerodynamic design optimization method is of great value for improving the aerodynamic performance of little UAV's airfoil. Using engineering or semi-engineering estimation method to analyze aerodynamic forces in solving aerodynamic optimization problems costs little computational time, but the accuracy cannot be guaranteed. However, CFD method ensuring high accuracy needs much more computational cost, which is unfordable for optimization. Surrogate-based optimization can reduce the number of high-fidelity analyses to increase the optimization efficiency. However, the cost of CFD analyses is still huge for aerodynamic optimization due to multiple design variables, multi-optimal and strong nonlinearities. To solve this problem, a two-stage aerodynamic optimization method based on early termination of CFD convergence and variable-fidelity model is proposed. In the first optimization stage, the solutions by early termination CFD convergence and the convergenced CFD solutions are regarded as low-and high-fidelity data respectively for building variable-fidelity model. Then, the multi-island genetic algorithm is used in the global optimization based on the built variable-fidelity model. The modeling efficiency can be greatly improved due to many cheap low-fidelity data. In the second stage optimization, the global optimum from the first optimization stage is treated as the start of the Hooke-Jeeves algorithm to search locally based on convergenced CFD computations in order to acquire better-optimum. The proposed method is utilized in optimizing the aerodynamic performance of the airfoil of little UAV, and is compared with the EGO method based on single-fidelity Kriging surrogate model. The results show that the present two-level aerodynamic optimization method consumes less time.

scholarly journals In-Orbit Operational Parameter Calculation and Performance Optimization in KOMPSAT-6 Synthetic Aperture Radar

2021 ◽  
Vol 13 (12) ◽  
pp. 2342
Author(s):  
Jin-Bong Sung ◽  
Sung-Yong Hong
Keyword(s):  
Synthetic Aperture Radar ◽  
Performance Optimization ◽  
Pulse Repetition Frequency ◽  
Optimization Method ◽  
Synthetic Aperture ◽  
Operational Parameters ◽  
Operational Parameter ◽  
Design Methodologies ◽  
And Performance ◽  
Aperture Radar

A new method to design in-orbit synthetic aperture radar operational parameters has been implemented for the Korean Multi-purpose Satellite 6 mission. The implemented method optimizes the pulse repetition frequency when a satellite altitude changes from its nominal one, so it has the advantage that the synthetic aperture radar performances can satisfy the requirements for the in-orbit operation. Other commanding parameters have been designed to conduct trade-off between those parameters. This paper presents the new optimization method to maintain the synthetic aperture radar performances even in the case of an altitude variation. Design methodologies to determine operational parameters, respectively, at nominal altitude and in orbit are presented. In addition, numerical simulation is presented to validate the proposed optimization and the design methodologies.

scholarly journals A Fast Optimization Method for Reliability and Performance of Cloud Services Composition Application

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Zhao Wu ◽  
Naixue Xiong ◽  
Yannong Huang ◽  
Qiong Gu ◽  
Chunyang Hu ◽  
...  
Keyword(s):  
Cloud Computing ◽  
State Space ◽  
Generating Function ◽  
Performance Optimization ◽  
Optimization Method ◽  
Cloud Services ◽  
Services Composition ◽  
Fast Optimization ◽  
And Performance ◽  
Universal Generating Function

At present the cloud computing is one of the newest trends of distributed computation, which is propelling another important revolution of software industry. The cloud services composition is one of the key techniques in software development. The optimization for reliability and performance of cloud services composition application, which is a typical stochastic optimization problem, is confronted with severe challenges due to its randomness and long transaction, as well as the characteristics of the cloud computing resources such as openness and dynamic. The traditional reliability and performance optimization techniques, for example, Markov model and state space analysis and so forth, have some defects such as being too time consuming and easy to cause state space explosion and unsatisfied the assumptions of component execution independence. To overcome these defects, we propose a fast optimization method for reliability and performance of cloud services composition application based on universal generating function and genetic algorithm in this paper. At first, a reliability and performance model for cloud service composition application based on the multiple state system theory is presented. Then the reliability and performance definition based on universal generating function is proposed. Based on this, a fast reliability and performance optimization algorithm is presented. In the end, the illustrative examples are given.

Measurements of the Tip Clearance Flow for a High-Reynolds-Number Axial-Flow Rotor

1995 ◽  
Vol 117 (4) ◽  
pp. 522-532 ◽  
Author(s):  
W. C. Zierke ◽  
K. J. Farrell ◽  
W. A. Straka
Keyword(s):  
Reynolds Number ◽  
Flow Visualization ◽  
Vortex Core ◽  
Rotor Blade ◽  
High Reynolds Number ◽  
Tip Clearance ◽  
Tip Leakage Vortex ◽  
Tip Leakage ◽  
Blade Tip ◽  
High Reynolds

A high-Reynolds-number pump (HIREP) facility has been used to acquire flow measurements in the rotor blade tip clearance region, with blade chord Reynolds numbers of 3,900,000 and 5,500,000. The initial experiment involved rotor blades with varying tip clearances, while a second experiment involved a more detailed investigation of a rotor blade row with a single tip clearance. The flow visualization on the blade surface and within the flow field indicate the existence of a trailing-edge separation vortex, a vortex that migrates radially upward along the trailing edge and then turns in the circumferential direction near the casing, moving in the opposite direction of blade rotation. Flow visualization also helps in establishing the trajectory of the tip leakage vortex core and shows the unsteadiness of the vortex. Detailed measurements show the effects of tip clearance size and downstream distance on the structure of the rotor tip leakage vortex. The character of the velocity profile along the vortex core changes from a jetlike profile to a wakelike profile as the tip clearance becomes smaller. Also, for small clearances, the presence and proximity of the casing endwall affects the roll-up, shape, dissipation, and unsteadiness of the tip leakage vortex. Measurements also show how much circulation is retained by the blade tip and how much is shed into the vortex, a vortex associated with high losses.

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