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 ◽  
...  
Author(s):  
Hongtao Wang ◽  
Weiliang Xie ◽  
Meining Chen

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.


2020 ◽  
Vol 34 (14n16) ◽  
pp. 2040115
Author(s):  
Neng Xiong ◽  
Yang Tao ◽  
Jun Lin ◽  
Xue-Qiang Liu

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.


Water ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 87
Author(s):  
Yongqiang Wang ◽  
Ye Liu ◽  
Xiaoyi Ma

The numerical simulation of the optimal design of gravity dams is computationally expensive. Therefore, a new optimization procedure is presented in this study to reduce the computational cost for determining the optimal shape of a gravity dam. Optimization was performed using a combination of the genetic algorithm (GA) and an updated Kriging surrogate model (UKSM). First, a Kriging surrogate model (KSM) was constructed with a small sample set. Second, the minimizing the predictor strategy was used to add samples in the region of interest to update the KSM in each updating cycle until the optimization process converged. Third, an existing gravity dam was used to demonstrate the effectiveness of the GA–UKSM. The solution obtained with the GA–UKSM was compared with that obtained using the GA–KSM. The results revealed that the GA–UKSM required only 7.53% of the total number of numerical simulations required by the GA–KSM to achieve similar optimization results. Thus, the GA–UKSM can significantly improve the computational efficiency. The method adopted in this study can be used as a reference for the optimization of the design of gravity dams.


Author(s):  
Mobayode O. Akinsolu ◽  
Bo Liu ◽  
Vic Grout ◽  
Pavlos I. Lazaridis ◽  
Maria Evelina Mognaschi ◽  
...  

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