Multi-objective Optimization of a Flexible Rotor in Magnetic Bearings With Critical Speeds and Control Current Constraints

1997 ◽  
Vol 119 (1) ◽  
pp. 186-195 ◽  
Author(s):  
Ting Nung Shiau ◽  
Chun Pao Kuo ◽  
Jiunn Rong Hwang

This paper presents the single objective optimization and the multi-objective optimization for a flexible rotor system with magnetic bearings. The weight of rotor shaft and the transmitted forces at the magnetic bearings are minimized either individually or simultaneously under the constraints on the critical speeds and the control currents of magnetic bearings. The design variables are the cross-sectional area of the shaft, the bias currents of magnetic bearings, and the positions of the disk and the magnetic bearings. The dynamic characteristics are analyzed using the generalized polynomial expansion method and the sensitivity analysis is also studied. For single objective optimization, the method of feasible directions (MFD) is applied. For multi-objective optimization, the weighting method (WM), the goal programming method (GPM), and the fuzzy method (FM) are employed. It is found that the system design can be significantly affected by the choices of the bias currents of magnetic bearings, the position of the disk with unbalance, and the magnetic bearings. The results also show that a better compromised design can always be obtained for multi-objective optimization.

Author(s):  
Ting Nung Shiau ◽  
Chun Pao Kuo ◽  
Jiunn Rong Hwang

This paper presents the single objective optimization and the multi-objective optimization for a flexible rotor system with magnetic bearings. The weight of rotor shaft and the transmitted forces at the magnetic bearings are minimized either individually or simultaneously under the constraints on the critical speeds and the control currents of magnetic bearings. The design variables are the cross-sectional area of the shaft, the bias currents of magnetic bearings, and the positions of the disk and the magnetic bearings. The dynamic characteristics are analyzed using the generalized polynomial expansion method and the sensitivity analysis is also studied. For single objective optimization, the method of feasible directions (MFD) is applied. For multi-objective optimization, the methods including the weighting method (WM), goal programming method (GPM), and the fuzzy method (FM) are employed. It is found that the system design can be significantly affected by the choices of the bias currents of magnetic bearings, the position of the disk with unbalance and the magnetic bearings. The results also show that a better compromized design can always be obtained for multi-objective optimization.


1993 ◽  
Vol 115 (2) ◽  
pp. 246-255 ◽  
Author(s):  
T. N. Shiau ◽  
J. R. Chang

An efficient optimal design algorithm is developed to minimize, individually or simultaneously, the total weight of the shaft and the transmitted forces at the bearings. These factors play very important roles in designing a rotor-bearing system under the constraints of critical speeds. The cross-sectional area of the shaft, the bearing stiffness, and the positions of bearings and disks are chosen as the design variables. The dynamic characteristics are determined by applying the generalized polynomial expansion method and the sensitivity analysis is also investigated. For multi-objective optimization, the weighting method (WM), the goal programming method (GPM), and the fuzzy method (FM) are applied. The results show that the present multi-objective optimization algorithm can greatly reduce both the weight of the shaft and the forces at the bearings with critical speed constraints.


Author(s):  
Ting Nung Shiau ◽  
Jer Rong Chang

An efficient optimal design algorithm is developed to individually or simultaneously minimize the total weight of shaft and the transsmitted forces at the bearings which play very important roles in designing a rotor-bearing system under the constraints of critical speeds. The cross sectional area of shaft, the bearing stiffness, and the positions of bearings and disks are chosen as the design variables. The dynamic characteristics are determined by applying the generalized polynomial expansion method and the sensitivity analysis is also investigated. For multiobjective optimization, the weighting method (WM), the goal programming method (GPM), and the fuzzy method (FM) are applied. The results show that the present multiobjective optimization algorithm can greatly reduce both the weight of shaft and the forces at the bearings with critical speeds constraints.


Energies ◽  
2020 ◽  
Vol 13 (5) ◽  
pp. 1155
Author(s):  
Lifang Zeng ◽  
Jianxin Hu ◽  
Dingyi Pan ◽  
Xueming Shao

A mono tiltrotor (MTR) design which combines concepts of a tiltrotor and coaxial rotor is presented. The aerodynamic modeling of the MTR based on blade element momentum theory (BEMT) is conducted, and the method is fully validated with previous experimental data. An automated optimization approach integrating BEMT modeling and optimization algorithms is developed. Parameters such as inter-rotor spacing, blade twist, taper ratio and aspect ratio are chosen as design variables. Single-objective (in hovering or in cruising state) optimizations and multi-objective (both in hovering and cruising states) optimizations are studied at preset design points; i.e., hovering trim and cruising trim. Two single-objective optimizations result in different sets of parameter selections according to the different design objectives. The multi-objective optimization is applied to obtain an identical and compromised selection of design parameters. An optimal point is chosen from the Pareto front of the multi-objective optimization. The optimized design has a better performance in terms of the figure of merit (FM) and propulsive efficiency, which are improved by 7.3% for FM and 13.4% for propulsive efficiency from the prototype, respectively. Further aerodynamic analysis confirmed that the optimized rotor has a much more uniform load distribution along the blade span, and therefore a better aerodynamic performance in both hovering and cruising states is achieved.


2016 ◽  
Vol 693 ◽  
pp. 243-250
Author(s):  
Zhi Zhong Guo ◽  
Yun Shun Zhang ◽  
Shi Hao Liu

It is discovered that the vibration resistance of spindle systems needs to be improved based on the statics analysis, modal analysis and heating-force coupling analysis of spindle systems of CNC gantry machine tools. The design variables of optimization are set according to sensitivity analysis, multi-objective and dynamic optimization design is realized and its designing scheme is gained for spindle structure. The research results show that vibration resistance can be improved without change of the quality and static property of spindle systems of CNC gantry machine tools.


Author(s):  
Mikhail Gritckevich ◽  
Kunyuan Zhou ◽  
Vincent Peltier ◽  
Markus Raben ◽  
Olga Galchenko

A comprehensive study of several labyrinth seals has been performed in the framework of both single-objective and multi-objective optimizations with the main focus on the effect of stator grooves formed due to the rubbing during gas turbine engine operation. For that purpose, the developed optimization workflow based on the DLR-AutoOpti optimizer and ANSYS-Workbench CAE environment has been employed to reduce the leakage flow and windage heating for several seals. The obtained results indicate that the seal designs obtained from optimizations without stator grooves have worse performance during the lifecycle than those with the stator grooves, justifying the importance of considering this effect for real engineering applications.


2018 ◽  
Vol 23 (13) ◽  
pp. 4911-4925 ◽  
Author(s):  
F. Passos ◽  
R. González-Echevarría ◽  
E. Roca ◽  
R. Castro-López ◽  
F. V. Fernández

Author(s):  
Huizhuo Cao ◽  
Xuemei Li ◽  
Vikrant Vaze ◽  
Xueyan Li

Multi-objective pricing of high-speed rail (HSR) passenger fares becomes a challenge when the HSR operator needs to deal with multiple conflicting objectives. Although many studies have tackled the challenge of calculating the optimal fares over railway networks, none of them focused on characterizing the trade-offs between multiple objectives under multi-modal competition. We formulate the multi-objective HSR fare optimization problem over a linear network by introducing the epsilon-constraint method within a bi-level programming model and develop an iterative algorithm to solve this model. This is the first HSR pricing study to use an epsilon-constraint methodology. We obtain two single-objective solutions and four multi-objective solutions and compare them on a variety of metrics. We also derive the Pareto frontier between the objectives of profit and passenger welfare to enable the operator to choose the best trade-off. Our results based on computational experiments with Beijing–Shanghai regional network provide several new insights. First, we find that small changes in fares can lead to a significant improvement in passenger welfare with no reduction in profitability under multi-objective optimization. Second, multi-objective optimization solutions show considerable improvements over the single-objective optimization solutions. Third, Pareto frontier enables decision-makers to make more informed decisions about choosing the best trade-offs. Overall, the explicit modeling of multiple objectives leads to better pricing solutions, which have the potential to guide pricing decisions for the HSR operators.


2012 ◽  
Vol 433-440 ◽  
pp. 2808-2816
Author(s):  
Jian Jin Zheng ◽  
You Shen Xia

This paper presents a new interactive neural network for solving constrained multi-objective optimization problems. The constrained multi-objective optimization problem is reformulated into two constrained single objective optimization problems and two neural networks are designed to obtain the optimal weight and the optimal solution of the two optimization problems respectively. The proposed algorithm has a low computational complexity and is easy to be implemented. Moreover, the proposed algorithm is well applied to the design of digital filters. Computed results illustrate the good performance of the proposed algorithm.


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