scholarly journals Multidisciplinary constraints within a two-dimensional aerodynamic optimization method

2021 ◽  
Author(s):  
Maureen Kolla
Keyword(s):  
Global Minimum ◽  
Optimization Method ◽  
Curvature Function ◽  
Maximum Point ◽  
Two Dimensional ◽  
Aerodynamic Optimization ◽  
Minimum Thickness ◽  
Airfoil Surface ◽  
High Lift ◽  
Additional Constraints

This research demonstrates the importance of including multi-disciplinary constraints within a two-dimensional aerodynamic optimization method. These constraints increase the methods flexibility and versatility by providing the aerodynamic designer with the latitude to expand the design envelope. The additional constraints include a global minimum thickness, a maximum point thickness, an area, two curvature functions and a stowability constraint. The global minimum thickness constraint is used to prevent airfoil surface crossovers. The maximum point thickness and area constraint address airfoil structural requirements. The curvature function constraints deal with the airfoils manufacturability. Finally, the stowability constraints combines flap trajectory, including the flap mechanics, together with the final airfoil shape, to ensure high-lift stowability

scholarly journals Multidisciplinary constraints within a two-dimensional aerodynamic optimization method

2021 ◽  
Author(s):  
Maureen Kolla
Keyword(s):  
Global Minimum ◽  
Optimization Method ◽  
Curvature Function ◽  
Maximum Point ◽  
Two Dimensional ◽  
Aerodynamic Optimization ◽  
Minimum Thickness ◽  
Airfoil Surface ◽  
High Lift ◽  
Additional Constraints

This research demonstrates the importance of including multi-disciplinary constraints within a two-dimensional aerodynamic optimization method. These constraints increase the methods flexibility and versatility by providing the aerodynamic designer with the latitude to expand the design envelope. The additional constraints include a global minimum thickness, a maximum point thickness, an area, two curvature functions and a stowability constraint. The global minimum thickness constraint is used to prevent airfoil surface crossovers. The maximum point thickness and area constraint address airfoil structural requirements. The curvature function constraints deal with the airfoils manufacturability. Finally, the stowability constraints combines flap trajectory, including the flap mechanics, together with the final airfoil shape, to ensure high-lift stowability

Stowability Constraint Within a Two-Dimensional Aerodynamic Optimization Method

2009 ◽  
Vol 46 (2) ◽  
pp. 696-699 ◽  
Author(s):  
M. L. Kolla ◽  
J. W. Yokota ◽  
J. V. Lassaline ◽  
I. Fejtek
Keyword(s):  
Optimization Method ◽  
Two Dimensional ◽  
Aerodynamic Optimization

The Improvement of Newton Method and the Validation of Optimization Idea of Blind Walking Repeatedly

2011 ◽  
Vol 250-253 ◽  
pp. 4061-4064
Author(s):  
Chun Ling Zhang
Keyword(s):  
Saddle Point ◽  
Newton Method ◽  
Optimization Problem ◽  
Initial Point ◽  
Optimization Method ◽  
Maximum Point ◽  
Optimal Result ◽  
Feasible Domain ◽  
Parallel Arithmetic ◽  
Newton Direction

The existence of maximum point, oddity point and saddle point often leads to computation failure. The optimization idea is based on the reality that the optimum towards the local minimum related the initial point. After getting several optimal results with different initial point, the best result is taken as the final optimal result. The arithmetic improvement of multi-dimension Newton method is improved. The improvement is important for the optimization method with grads convergence rule or searching direction constructed by grads. A computational example with a saddle point, maximum point and oddity point is studied by multi-dimension Newton method, damped Newton method and Newton direction method. The importance of the idea of blind walking repeatedly is testified. Owing to the parallel arithmetic of modernistic optimization method, it does not need to study optimization problem with seriate feasible domain by modernistic optimization method.

scholarly journals An Adaptive Optimization Method Based on Learning Rate Schedule for Neural Networks

2021 ◽  
Vol 11 (2) ◽  
pp. 850
Author(s):  
Dokkyun Yi ◽  
Sangmin Ji ◽  
Jieun Park
Keyword(s):  
Artificial Intelligence ◽  
Cost Function ◽  
Numerical Experiments ◽  
Global Minimum ◽  
Optimization Method ◽  
Learning Method ◽  
Adaptive Optimization ◽  
The Cost ◽  
Proof Of Convergence ◽  
Learning Data

Artificial intelligence (AI) is achieved by optimizing the cost function constructed from learning data. Changing the parameters in the cost function is an AI learning process (or AI learning for convenience). If AI learning is well performed, then the value of the cost function is the global minimum. In order to obtain the well-learned AI learning, the parameter should be no change in the value of the cost function at the global minimum. One useful optimization method is the momentum method; however, the momentum method has difficulty stopping the parameter when the value of the cost function satisfies the global minimum (non-stop problem). The proposed method is based on the momentum method. In order to solve the non-stop problem of the momentum method, we use the value of the cost function to our method. Therefore, as the learning method processes, the mechanism in our method reduces the amount of change in the parameter by the effect of the value of the cost function. We verified the method through proof of convergence and numerical experiments with existing methods to ensure that the learning works well.

Non-Axisymmetric Turbine Endwall Aerodynamic Optimization Design: Part I — Turbine Cascade Design and Experimental Validations

2014 ◽  
Author(s):  
Hao Sun ◽  
Jun Li ◽  
Liming Song ◽  
Zhenping Feng
Keyword(s):  
Secondary Flow ◽  
Evaluation Method ◽  
Pressure Coefficient ◽  
Optimization Method ◽  
Experimental Measurements ◽  
Turbine Cascade ◽  
Aerodynamic Optimization ◽  
Flow Losses ◽  
Flow Intensity ◽  
Performance Evaluation Method

The non-axisymmetric endwall profiling has been proven to be an effective tool to reduce the secondary flow loss in turbomachinery. In this work, the aerodynamic optimization for the non-axisymmetric endwall profile of the turbine cascade and stage was presented and the design results were validated by annular cascade experimental measurements and numerical simulations. The parametric method of the non-axisymmetric endwall profile was proposed based on the relation between the pressure field variation and the secondary flow intensity. The optimization system combines with the non-axisymmetric endwall parameterization method, global optimization method of the adaptive range differential evolution algorithm and the aerodynamic performance evaluation method using three-dimensional Reynolds-Averaged Navier-Stokes (RANS) and k–ω SST turbulent with transition model solutions. In the part I, the optimization method is used to design the optimum non-axisymmetric endwall profile of the typical high loaded turbine stator. The design objective was selected for the maximum total pressure coefficient with constrains on the mass flow rate and outlet flow angle. Only five design variables are needed for one endwall to search the optimum non-axisymmetric endwall profile. The optimized non-axisymmetric endwall profile of turbine cascade demonstrated an improvement of total pressure coefficient of 0.21% absolutely, comparing with the referenced axisymmetric endwall design case. The reliability of the numerical calculation used in the aerodynamic performance evaluation method and the optimization result were validated by the annular vane experimental measurements. The static pressure distribution at midspan was measured while the cascade flow field was measured with the five-hole probe for both the referenced axisymmetric and optimized non-axisymmetric endwall profile cascades. Both the experimental measurements and numerical simulations demonstrated that both the secondary flow losses and the profile loss of the optimized non-axisymmetric endwall profile cascade were significantly reduced by comparison of the referenced axisymmetric case. The weakening of the secondary flow of the optimized non-axisymmetric endwall profile design was also proven by the secondary flow vector results in the experiment. The detailed flow mechanism of the secondary flow losses reduction in the non-axisymmetric endwall profile cascade was analyzed by investigating the relation between the change of the pressure gradient and the variation of the secondary flow intensity.

The Effect of Turning Angle on the Loss Generation of LP Turbines

2017 ◽  
Author(s):  
Diego Torre ◽  
Guillermo Garcia-Valdecasas ◽  
David Cadrecha
Keyword(s):  
High Speed ◽  
Pressure Coefficient ◽  
Experimental Results ◽  
Cfd Simulations ◽  
Airfoil Surface ◽  
High Lift ◽  
Turning Angle ◽  
Pressure Losses ◽  
Coefficient Distribution ◽  
Inlet Angle

The effect of turning angle on the loss generation of Low Pressure (LP) Turbines has been investigated experimentally in a couple of turbine high-speed rigs. Both rigs consisted of a rotor-stator configuration. All the airfoils are high lift and high aspect ratio blades that are characteristic of state of the art LP Turbines. Both rigs are identical with exception of the stator. Therefore, two sets of stators have been manufactured and tested. The aerodynamic shape of both stators has been designed in order to achieve the same spanwise distribution of Cp (Pressure coefficient) over the airfoil surface, each one to its corresponding turning angles. Exit angle in both stators is the same. Therefore the change in turning is obtained by a different inlet angle. The aim of this experiment is to obtain the sensitivity of profile and endwall losses to turning angle by means of a back-to-back comparison between both sets of airfoils. Because the two sets of stators maintain the same pressure coefficient distribution, Reynolds number and Mach number, each one to its corresponding velocity triangles, one can state that the results are only affected by the turning angle. Experimental results are presented and compared in terms of area average, radial pitchwise average distributions and exit plane contours of total pressure losses. CFD simulations for the two sets of stators are also presented and compared with the experimental results.

Design and optimization method for a two-dimensional hydrofoil

2006 ◽  
Vol 18 (S1) ◽  
pp. 316-322
Author(s):  
Ching-Yeh Hsin ◽  
Jia-Lin Wu ◽  
Sheng-Fong Chang
Keyword(s):  
Optimization Method ◽  
Two Dimensional ◽  
Design And Optimization

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.

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