scholarly journals Inverse Design of Transonic Airfoils Using Variable-Resolution Modeling and Pressure Distribution Alignment

2011 ◽  
Vol 4 ◽  
pp. 1234-1243 ◽  
Author(s):  
Leifur Leifsson ◽  
Slawomir Koziel ◽  
Stanislav Ogurtsov
Keyword(s):  
Pressure Distribution ◽  
Inverse Design ◽  
Variable Resolution

Inverse Design of Axial-Flow Compressor Blades Using Elastic Surface Algorithm in Subsonic and Transonic Flow Regimes With Separation

2016 ◽  
Author(s):  
M. H. Noorsalehi ◽  
M. Nili-Ahamadabadi ◽  
E. Shirani ◽  
M. Safari
Keyword(s):  
Pressure Distribution ◽  
Transonic Flow ◽  
Design Method ◽  
Axial Flow ◽  
Flow Regimes ◽  
Inverse Design ◽  
Elastic Surface ◽  
Axial Flow Compressor ◽  
Inverse Design Method ◽  
Flow Compressor

In this study, a new inverse design method called Elastic Surface Algorithm (ESA) is developed and enhanced for axial-flow compressor blade design in subsonic and transonic flow regimes with separation. ESA is a physically based iterative inverse design method that uses a 2D flow analysis code to estimate the pressure distribution on the solid structure, i.e. airfoil, and a 2D solid beam finite element code to calculate the deflections due to the difference between the calculated and target pressure distributions. In order to enhance the ESA, the wall shear stress distribution, besides pressure distribution, is applied to deflect the shape of the airfoil. The enhanced method is validated through the inverse design of the rotor blade of the first stage of an axial-flow compressor in transonic viscous flow regime. In addition, some design examples are presented to prove the effectiveness and robustness of the method. The results of this study show that the enhanced Elastic Surface Algorithm is an effective inverse design method in flow regimes with separation and normal shock.

Design Optimization of Cryogenic Pump Inducer Considering Suction Performance and Cavitation Instability

2011 ◽  
Author(s):  
Hiroyoshi Watanabe ◽  
Hiroshi Tsukamoto
Keyword(s):  
Pressure Distribution ◽  
Design Optimization ◽  
Surface Pressure ◽  
Design Approach ◽  
Inverse Design ◽  
Blade Surface ◽  
Free Vortex ◽  
Surface Pressure Distribution ◽  
Cavitation Instability ◽  
Suction Performance

This paper presents the result of design optimization for three-bladed pump inducer using a three-dimensional (3-D) inverse design approach, Computational Fluid Dynamics (CFD) and DoE (Design of Experiments) taking suction performance and cavitation instability into consideration. The parameters to control streamwise blade loading distribution and spanwise work (free vortex or non-free vortex) for inducer were chosen as design optimization variables for the inverse design approach. Cavitating and non-cavitating performances for inducers designed using the design variables arranged in the DoE table were analyzed by steady CFD. Objective functions for non-cavitating operating conditions were the head and efficiency of inducers at a design flow (Qd), 80% Qd and 120% Qd. The volume of the inducer cavity region with a void ratio above 50% was selected as the objective function for inducer suction performance. In order to evaluate cavitation instability by steady CFD, the dispersion of the blade surface pressure distribution on each blade was selected as the evaluation parameter. This dispersion of the blade surface pressure distribution was caused by non-uniformity in the cavitation length that was developed on each inducer blade and increased when the cavitation number was reduced. The effective design parameters on suction performance and cavitation instability were confirmed by sensitivity analysis during the design optimization process. Inducers with specific characteristics (stable, unstable) designed using the effective parameters were evaluated through experiments.

A Novel Two Dimensional Viscous Inverse Design Method for Turbomachinery Blading

2002 ◽  
Author(s):  
L. de Vito ◽  
R. A. Van den Braembussche ◽  
H. Deconinck
Keyword(s):  
Pressure Distribution ◽  
Design Method ◽  
Turbine Blades ◽  
Inverse Design ◽  
Navier Stokes ◽  
Particular Solution ◽  
Target Pressure ◽  
Inverse Design Method ◽  
Euler Solver ◽  
Stagger Angle

This paper presents a novel iterative viscous inverse method for turbomachinery blading design. It is made up of two steps: The first one consists of an analysis by means of a Navier-Stokes solver, the second one is an inverse design by means of an Euler solver. The inverse design resorts to the concept of permeable wall, and recycles the ingredients of Demeulenaere’s inviscid inverse design method that was proven fast and robust. The re-design of the LS89 turbine nozzle blade, starting from different arbitrary profiles at subsonic and transonic flow regimes, demonstrates the merits of this approach. The method may result in more than one blade profile that meets the objective, i.e. that produces the viscous target pressure distribution. To select one particular solution among all candidates, a target mass flow is enforced by adjusting the outlet static pressure. The resulting profiles are smooth (oscillation-free). The design of turbine blades with arbitrary pressure distribution at transonic and supersonic outflow illustrates the correct behavior of the method for a large range of applications. The approach is flexible because only the pitch chord ratio is fixed and no limitations are imposed on the stagger angle.

Development of Turbine Blade Profiles Using Iterative Inverse Design Methodology

2017 ◽  
Author(s):  
Nanthini Rajendran ◽  
Bhamidi Prasad ◽  
Y. V. S. S. Sanyasiraju
Keyword(s):  
Pressure Distribution ◽  
Design Methodology ◽  
Turbine Blades ◽  
Three Dimensional ◽  
Geometric Constraints ◽  
Inverse Design ◽  
Normal Velocity ◽  
Permeable Membrane ◽  
Flow Parameters ◽  
Blade Geometry

An iterative inverse design methodology is used to design gas turbine blades for the prescribed flow conditions. The input flow parameter considered here is the pressure distribution along the suction and pressure surfaces of the blade. The flow is regarded as inviscid. A guess blade is presumed and the flow analysis over the blade is determined using the existing commercial software. In case of mismatch of the flow parameters, the guessed profile surface is considered as a permeable membrane and the normal velocity on the blade surface is computed by conservation of momentum flux approach. The computed normal velocity is used to revise the blade geometry by mass conservation principle till the flow parameters converge. A few geometric constraints are enforced on the model to avoid quixotic blade model. The validation of the above method is being done using NACA profiles. The robustness of the method is verified by using various combinations of NACA blade profiles, where different initial guessed profiles are taken for the same prescribed pressure distribution. This approach can be extended to three dimensional cases. To incorporate the complications attached with the three dimensional flows, three two dimensional sections can be considered on the blade geometry namely at hub, mid span and tip.

Optimal Design of Axe-Symmetric Diffuser via Genetic Algorithm and Ball-Spine Inverse Design Method

2012 ◽  
Author(s):  
Navid S. Vaghefi ◽  
Mahdi Nili Ahmadabadi ◽  
Mohammad R. Roshani
Keyword(s):  
Genetic Algorithm ◽  
Boundary Layer ◽  
Pressure Distribution ◽  
Pressure Coefficient ◽  
Initial Guess ◽  
Inverse Design ◽  
Numerical Code ◽  
Maximum Pressure ◽  
Optimum Pressure ◽  
Design Algorithm

In this research, an optimal aerodynamic design of an axe-symmetric diffuser is performed via combination of a developed boundary layer numerical code, BSA inverse design Algorithm and genetic optimization algorithm. To do this, developed numerical boundary layer code is incorporated into the genetic algorithm to reach to an optimum pressure distribution on the wall in such a way that the maximum pressure recovery is obtained without separation. To validate the developed boundary layer code, the calculated quantities are compared with Blasius and Howart’s analytical results. Then, the optimized pressure distribution will be the candidate “target pressure distribution” for the inverse design algorithm to find out the relevant optimum geometry. Geometry modification takes place based on the combination of Ball-Spine algorithm and fluent software as the flow field solver. Implementation of this combination is completed through User Defined Function (UDF) feature of Fluent. Fluent advantageous provides the capabilities for extension of the proposed method to turbulent flows, complicated geometries and employment of both structured and unstructured grids. To show the true performance of the proposed method of inverse design, several issues have been investigated for different initial guess. To validate the effect of the presented method, increased pressure coefficient for an optimized diffuser is illustrated.

Inverse Design of Airfoils Using Convolutional Neural Network and Deep Neural Network

2021 ◽  
Author(s):  
Amit Kumar ◽  
Nagabhushana Rao Vadlamani
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Convolutional Neural Network ◽  
Pressure Distribution ◽  
Mean Squared Error ◽  
Inverse Design ◽  
Batch Size ◽  
Squared Error ◽  
Order Of Magnitude ◽  
Target Pressure

Abstract In this paper, we compare the efficacy of two neural network based models: Convolutional Neural Network (CNN) and Deep Neural Networks (DNN) to inverse design the airfoil shapes. Given the pressure distribution over the airfoil in pictorial (for CNN) or numerical form (for DNN), the trained neural networks predict the airfoil shapes. During the training phase, the critical hyper-parameters of both the models, namely — learning rate, number of epochs and batch size, are tuned to reduce the mean squared error (MSE) and increase the prediction accuracy. The training parameters in DNN are an order of magnitude lower than that of CNN and hence the DNN model is found to be ≈ 7× faster than the CNN. In addition, the accuracy of DNN is also observed to be superior to that of CNN. After processing the raw airfoil shapes, the smoothed airfoils are shown to yield the target pressure distribution thereby validating the framework.

An Inverse Geometry Design Problem in Optimizing Hull Surfaces

1998 ◽  
Vol 42 (02) ◽  
pp. 79-85
Author(s):  
Cheng-Hung Huang ◽  
Cheng-Chia Chiang ◽  
Shean-Kwang Chou
Keyword(s):  
Inverse Problem ◽  
Pressure Distribution ◽  
Design Problem ◽  
Inverse Design ◽  
Control Points ◽  
Surface Geometry ◽  
Geometry Design ◽  
Spline Surface ◽  
Surface Method ◽  
Inverse Design Problem

The technique of the inverse design problem for optimizing the shape of a bow from a specified pressure distribution is presented. This desired pressure distribution can be obtained by modifying the existing pressure distribution of the parent ship. The surface geometry of the ship is generated using the B-spine surface method which enables the shape of the hull to be completely specified using only a small number of parameters (i.e. control points). The technique of parameter estimation for the inverse problem is thus chosen. Results show that the accuracy of the final desired ship form depends on the number of polygons used in 6-spline surface fitting; only when enough polygons are used can the good final geometry that was calculated based on a given pressure distribution be obtained.

scholarly journals Full Three-Dimensional Inverse Design Method for S-Ducts Using a New Dimensionless Flow Parameter

2021 ◽  
Vol 11 (3) ◽  
pp. 1119
Author(s):  
Atefeh Kariminia ◽  
Mahdi Nili-Ahmadabadi ◽  
Kyung Chun Kim
Keyword(s):  
Pressure Distribution ◽  
Design Method ◽  
Target Function ◽  
Wall Pressure ◽  
Inverse Design ◽  
Cross Sectional ◽  
Dimensionless Pressure ◽  
Pressure Parameter ◽  
The Cross ◽  
Inverse Design Method

In this study, a new inverse design method is proposed for the full 3-D inverse design of S-ducts using curvature-based dimensionless pressure distribution as a target function. The wall pressure distribution in a 3-D curved duct is a function of the centerline curvature and the cross-sectional profile and area. A dimensionless pressure parameter was obtained as a function of the duct curvature and height of the cross-sections based on the normal pressure gradient equation. The dimensionless pressure parameter was used to eliminate the effect of the cross-sectional area on the wall pressure distribution. Full 3-D inverse design of an S-shaped duct was carried out by substituting the 3-D duct with a large number of 2-D planar ducts. The ball-spine inverse design method with vertical spins was coupled with the dimensionless pressure parameter as a target function for the design of the planar ducts. The inverse design process was performed in two steps. First, the height of each cross-section was considered constant, and only the duct centerline was allowed to be deformed by applying the difference between the dimensionless pressure on the upper and lower lines of symmetry plane. Then, a constant curvature was considered for each centerline in the equation, and the difference between the current and the target dimensionless pressure was applied to each upper and lower line of the planar sections to correct the heights of the 2-D planar sections, separately. The method was validated by choosing a straight duct as an initial guess, which converges to the target S-shaped duct. The results showed that the method is an efficient physical-based residual-correction method with low computational cost and good convergence rate. The 3-D wall pressure distribution of a high-deflected 3-D S-shaped diffuser was modified to eliminate the separation, secondary flow, and outlet distortion. Finally, the geometry corresponding to the modified pressure was obtained by the proposed 3-D inverse design method, which revealed higher pressure recovery, lower total pressure loss, and lower outlet flow distortion and swirl angle.

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