Integrated HPC OGV and Pre-Diffuser Design Optimization Using Kriging Surrogate Model

2013 ◽  
Author(s):  
Hongtao Wang ◽  
Weiliang Xie ◽  
Meining Chen
Keyword(s):  
Design Optimization ◽  
Boundary Layers ◽  
Surrogate Model ◽  
High Performance ◽  
Guide Vane ◽  
Thickness Distribution ◽  
Adverse Pressure Gradient ◽  
Optimization Process ◽  
Expected Improvement ◽  
Kriging Surrogate Model

The integration of high compressor outlet guide vane (OGV) and combustor pre-diffuser requires some radial turning to be performed within the OGV passage. However, the enhanced loading of OGV leads to the increase in adverse pressure gradient within the OGV passage. Consequently, both the end-wall and blade boundary layers are thickened which could lead to boundary layers separation. In this work, an adaptive global optimization process is applied for the OGV/pre-diffuser system, which combines design of experiment (DOE), Kriging surrogate model and micro genetic algorithm. The meridional flow passage of OGV/pre-diffuser system is parameterized using Bezier curves with the combination of mean line and thickness distribution. In order to prevent the OGV corner separation, the bowed design is applied to the OGV to help delay flow separation. A composite curve combined with two straight lines and a conic Bezier curve is used to represent the OGV stacking line along circumference so that the bowed blades could be parameterized. Aerodynamic performance evaluations of the compressor are performed using a three dimensional Reynolds-averaged Navier-stokes computational fluid dynamics solver — NUMECA. In the optimization process, expected improvement sample criteria is adopted for balancing the exploration and exploitation with Kriging surrogate model. Reasonably high performance is confirmed by comparing the baseline and optimal designs. This study gives some insights into design optimization of an integrated OGV/Pre-diffuser for axial compressor.

scholarly journals Drug Release Analysis and Optimization for Drug-Eluting Stents

2013 ◽  
Vol 2013 ◽  
pp. 1-5 ◽  
Author(s):  
Hongxia Li ◽  
Yihao Zhang ◽  
Bao Zhu ◽  
Jinying Wu ◽  
Xicheng Wang
Keyword(s):  
Drug Release ◽  
Surrogate Model ◽  
Expected Improvement ◽  
Drug Eluting Stents ◽  
Optimization Approach ◽  
Optimized Design ◽  
Kriging Surrogate Model ◽  
Adaptive Optimization ◽  
Release Analysis ◽  
Drug Eluting

The drug release analysis and optimization for drug-eluting stents in the arterial wall are studied, which involves mechanics, fluid dynamics, and mass transfer processes and design optimization. The Finite Element Method (FEM) is used to analyze the process of drug release in the vessels for drug-eluting stents (DES). Kriging surrogate model is used to build an approximate function relationship between the drug distribution and the coating parameters, replacing the expensive FEM reanalysis of drug release for DES in the optimization process. The diffusion coefficients and the coating thickness are selected as design variables. An adaptive optimization approach based on kriging surrogate model is proposed to optimize the lifetime of the drug in artery wall. The adaptive process is implemented by an infilling sampling criterion named Expected Improvement (EI), which is used to balance local and global search and tends to find the global optimal design. The effect of coating diffusivity and thickness on the drug release process for a typical DES is analyzed by means of FEM. An implementation of the optimization method for the drug release is then discussed. The results demonstrate that the optimized design can efficiently improve the efficacy of drug deposition and penetration into the arterial walls.

Using Kriging Surrogate Models to Predict the Vibration Responses of a Submerged Riser

2020 ◽  
Author(s):  
Marcelo Damasceno ◽  
Hélio Ribeiro Neto ◽  
Tatiane Costa ◽  
Aldemir Cavalini Júnior ◽  
Ludimar Aguiar ◽  
...  
Keyword(s):  
Surrogate Model ◽  
High Performance ◽  
Computational Cost ◽  
Offshore Structures ◽  
Surrogate Models ◽  
Computational Time ◽  
Kriging Surrogate Model ◽  
Efficient Manner ◽  
Modeling Tools ◽  
Fluid Structure

Abstract Fluid-structure interaction modeling tools based on computational fluid dynamics (CFD) produce interesting results that can be used in the design of submerged structures. However, the computational cost of simulations associated with the design of submerged offshore structures is high. There are no high-performance platforms devoted to the analysis and optimization of these structures using CFD techniques. In this context, this work aims to present a computational tool dedicated to the construction of Kriging surrogate models in order to represent the time domain force responses of submerged risers. The force responses obtained from high-cost computational simulations are used as outputs for training and validated the surrogate models. In this case, different excitations are applied in the riser aiming at evaluating the representativeness of the obtained Kriging surrogate model. A similar investigation is performed by changing the number of samples and the total time used for training purposes. The present methodology can be used to perform the dynamic analysis in different submerged structures with a low computational cost. Instead of solving the motion equation associated with the fluid-structure system, a Kriging surrogate model is used. A significant reduction in computational time is expected, which allows the realization of different analyses and optimization procedures in a fast and efficient manner for the design of this type of structure.

scholarly journals Design Optimization of Coronary Stent Based on Finite Element Models

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Hongxia Li ◽  
Tianshuang Qiu ◽  
Bao Zhu ◽  
Jinying Wu ◽  
Xicheng Wang
Keyword(s):  
Finite Element ◽  
Surrogate Model ◽  
Optimization Method ◽  
Expected Improvement ◽  
Finite Element Models ◽  
Rectangular Grid ◽  
Kriging Surrogate Model ◽  
Expansion Process ◽  
Grid Sampling ◽  
Expansion Behavior

This paper presents an effective optimization method using the Kriging surrogate model combing with modified rectangular grid sampling to reduce the stent dogboning effect in the expansion process. An infilling sampling criterion named expected improvement (EI) is used to balance local and global searches in the optimization iteration. Four commonly used finite element models of stent dilation were used to investigate stent dogboning rate. Thrombosis models of three typical shapes are built to test the effectiveness of optimization results. Numerical results show that two finite element models dilated by pressure applied inside the balloon are available, one of which with the artery and plaque can give an optimal stent with better expansion behavior, while the artery and plaque unincluded model is more efficient and takes a smaller amount of computation.

scholarly journals A CFD-Based Shape Design Optimization Process of Fixed Flow Passages in a Francis Hydro Turbine

Processes ◽  
2020 ◽  
Vol 8 (11) ◽  
pp. 1392
Author(s):  
Ujjwal Shrestha ◽  
Young-Do Choi
Keyword(s):  
Design Optimization ◽  
Draft Tube ◽  
Guide Vane ◽  
Optimization Techniques ◽  
Optimization Process ◽  
Shape Design ◽  
Flow Uniformity ◽  
Hydro Turbine ◽  
Shape Design Optimization ◽  
Hydro Turbines

In recent times, optimization began to be popular in the turbomachinery field. The development of computational fluid dynamics (CFD) analysis and optimization technology provides the opportunity to maximize the performance of hydro turbines. The optimization techniques are focused mainly on the rotating components (runner and guide vane) of the hydro turbines. Meanwhile, fixed flow passages (stay vane, casing, and draft tube) are essential parts for the proper flow uniformity in the hydro turbines. The suppression of flow instabilities in the fixed flow passages is an inevitable process to ensure the power plant safety by the reduction of vortex-induced vibration and pressure pulsation in the hydro turbines. In this study, a CFD-based shape design optimization process is proposed with response surface methodology (RSM) to improve the flow uniformity in the fixed flow passages of a Francis hydro turbine model. The internal flow behaviors were compared between the initial and optimal shapes of the stay vane, casing, and the draft tube with J-Groove. The optimal shape design process for the fixed flow passages proved its remarkable effects on the improvement of flow uniformity in the Francis hydro turbine.

scholarly journals Design optimization of stent and its dilatation balloon using kriging surrogate model

2017 ◽  
Vol 16 (1) ◽  
Author(s):  
Hongxia Li ◽  
Tao Liu ◽  
Minjie Wang ◽  
Danyang Zhao ◽  
Aike Qiao ◽  
...  
Keyword(s):  
Design Optimization ◽  
Surrogate Model ◽  
Kriging Surrogate Model

Multi-levels Kriging surrogate model-based robust aerodynamics optimization design method

2020 ◽  
Vol 34 (14n16) ◽  
pp. 2040115
Author(s):  
Neng Xiong ◽  
Yang Tao ◽  
Jun Lin ◽  
Xue-Qiang Liu
Keyword(s):  
Design Optimization ◽  
Surrogate Model ◽  
Optimization Design ◽  
Design Method ◽  
Computational Cost ◽  
Optimization Method ◽  
Mean Value ◽  
Robust Design Optimization ◽  
Efficient Global Optimization ◽  
Kriging Surrogate Model

Robust design optimization has a great potential application in many engineering fields. In the conventional robust aerodynamics design optimization method, the main difficulty is expensive computational cost related to a large number of function evaluations for uncertainty quantification (UQ). To alleviate the expensive burden for UQ, two levels Kriging surrogate model was introduced. The first level is for the mean value and the second level is for the variances. Through the second level Kriging surrogate models, the method of Monte Carlo Simulation (MCS), which requires a huge number of function evaluations, can be effectively applied to the analysis of variance. Efficient Global Optimization algorithm (EGO) was employed to achieve the global optimized results. To validate the performance of the design method, both one-dimensional function and two-dimensional function were applied. Finally, robust aerodynamics design optimization was applied for a low-drag airfoil. The results show that the optimal solutions obtained from the uncertainty-based optimization formulation are less sensitive to uncertainties to small manufacturing errors.

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