Kriging Surrogate Model Enhanced by Coordinate Transformation of Design Space Based on Eigenvalue Decomposition

2015 ◽  
pp. 321-335 ◽  
Author(s):  
Nobuo Namura ◽  
Koji Shimoyama ◽  
Shigeru Obayashi
Keyword(s):  
Coordinate Transformation ◽  
Surrogate Model ◽  
Design Space ◽  
Eigenvalue Decomposition ◽  
Kriging Surrogate Model

Optimization of Balloon-Stent System Based on Nonlinear Material Using Kriging Surrogate Model

2012 ◽  
Vol 502 ◽  
pp. 463-468
Author(s):  
Hong Xia Li ◽  
Xi Cheng Wang
Keyword(s):  
Surrogate Model ◽  
Design Space ◽  
Optimization Method ◽  
Nonlinear Material ◽  
Kriging Surrogate Model ◽  
Adaptive Optimization ◽  
Model Combining ◽  
Stent System ◽  
Global Optimal ◽  
The Relationship

Computer-aided technology was used for balloon-stent system design. Nonlinear material was used to simulate the dilation of balloon-stent system. Based on finite element results, an adaptive optimization method based on the kriging surrogate model combining with LHS approach and EI function was employed for the optimization of balloon length to reduce stent dogboning effect during its dilation. The kriging surrogate model can approximate the relationship between dogboning rate and balloon length, replacing the expensive reanalysis of the stent dilation. Sample points from LHS can represent the information of all parts on the design space. EI function is used to balance local and global search, and tends to find the global optimal design. Numerical results demonstrate that this adaptive optimization methed based on kriging surrogate model can be used for the optimization of balloon length of balloon-stent system.

Kriging surrogate model with coordinate transformation based on likelihood and gradient

2017 ◽  
Vol 68 (4) ◽  
pp. 827-849 ◽  
Author(s):  
Nobuo Namura ◽  
Koji Shimoyama ◽  
Shigeru Obayashi
Keyword(s):  
Coordinate Transformation ◽  
Surrogate Model ◽  
Kriging Surrogate Model

scholarly journals Updated Kriging-Assisted Shape Optimization of a Gravity Dam

Water ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 87
Author(s):  
Yongqiang Wang ◽  
Ye Liu ◽  
Xiaoyi Ma
Keyword(s):  
Surrogate Model ◽  
Computational Cost ◽  
Region Of Interest ◽  
Optimization Procedure ◽  
Optimal Shape ◽  
Small Sample ◽  
Gravity Dam ◽  
Kriging Surrogate Model ◽  
Gravity Dams ◽  
Sample Set

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.

Aerodynamic Efficiency Optimization of the 1st Stage of Transonic High Pressure Turbine through Lean and Sweep Angles

2019 ◽  
Vol 36 (3) ◽  
pp. 245-256
Author(s):  
Yoonki Kim ◽  
Sanga Lee ◽  
Kwanjung Yee ◽  
Young-Seok Kang
Keyword(s):  
High Pressure ◽  
Surrogate Model ◽  
Design Space ◽  
Latin Hypercube Sampling ◽  
Expected Improvement ◽  
Total Efficiency ◽  
High Pressure Turbine ◽  
Sweep Angle ◽  
Design Variables ◽  
Optimal Latin Hypercube Sampling

Abstract The purpose of this study is to optimize the 1st stage of the transonic high pressure turbine (HPT) for enhancement of aerodynamic performance. Isentropic total-to-total efficiency is designated as the objective function. Since the isentropic efficiency can be improved through modifying the geometry of vane and rotor blade, lean angle and sweep angle are chosen as design variables, which can effectively alter the blade geometry. The sensitivities of each design variable are investigated by applying lean and sweep angles to the base nozzle and rotor, respectively. The design space is also determined based on the results of the parametric study. For the design of experiment (DoE), Optimal Latin Hypercube sampling is adopted, so that 25 evenly distributed samples are selected on the design space. Sequentially, based on the values from the CFD calculation, Kriging surrogate model is constructed and refined using Expected Improvement (EI). With the converged surrogate model, optimum solution is sought by using the Genetic Algorithm. As a result, the efficiency of optimum turbine 1st stage is increased by 1.07 % point compared to that of the base turbine 1st stage. Also, the blade loading, pressure distribution, static entropy, shock structure, and secondary flow are thoroughly discussed.

scholarly journals Crack Parameters Identification Based on a Kriging Surrogate Model for Operating Rotors

2018 ◽  
Vol 2018 ◽  
pp. 1-12
Author(s):  
Danyang Wang ◽  
Chunrong Hua ◽  
Dawei Dong ◽  
Biao He ◽  
Zhiwen Lu
Keyword(s):  
Surrogate Model ◽  
Parameters Identification ◽  
The Finite Element Method ◽  
Breathing Crack ◽  
Kriging Surrogate Model ◽  
Crack Location ◽  
Rotor Bearing ◽  
Location Depth ◽  
Nondominated Sorting ◽  
Bearing System

Parameters identification of cracked rotors has been gaining importance in recent years, but it is still a great challenge to determine the crack parameters including crack location, depth, and angle for operating rotors. This work proposes a new method to identify crack parameters in a rotor-bearing system based on a Kriging surrogate model and an improved nondominated sorting genetic algorithm-III (NSGA-III). A rotor-bearing system with a breathing crack is established by the finite element method and the superharmonic components are used as index to detect the cracks, the Kriging surrogate model between crack parameters and the superharmonic component amplitudes of the vibration response for rotors are constructed, and an improved NSGA-III is proposed to obtain the optimal crack parameters. Numerical experiments show that the proposed method can identify the crack location, depth, and angle accurately and efficiently for operating rotors.

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