Robust Optimization Design for Spring

2012 ◽  
Vol 190-191 ◽  
pp. 1376-1379
Author(s):  
Gang Chen ◽  
Yu Fei Ma
Keyword(s):  
Mathematical Model ◽  
Robust Optimization ◽  
Objective Function ◽  
Optimization Design ◽  
Structure Design ◽  
Structure Parameters ◽  
Stiffness Coefficient ◽  
Spring Stiffness ◽  
Optimum Structure ◽  
Robust Optimization Design

In here, a robust optimization mathematical model of the spring is presented. To minimize the error and maximal variations of spring stiffness coefficient related with structure parameters and its tolerances is chosen as its objective function, and the acceptable region is formed by some constraints. The theory is applied to the structure design of the closeing spring of spring actuator, the closeing characteristics are all satisfied at the optimum structure parameters, and the optimization results are discussed.

The Robust Optimization Design for Cylindrical Helical Compression Spring

2012 ◽  
Vol 433-440 ◽  
pp. 2201-2205 ◽  
Author(s):  
Hong Zhao ◽  
Gang Chen ◽  
Jun Zhe Zhou
Keyword(s):  
Mathematical Model ◽  
Robust Optimization ◽  
Optimization Design ◽  
Structure Design ◽  
Structure Parameters ◽  
Stiffness Coefficient ◽  
Spring Stiffness ◽  
Optimum Structure ◽  
Compression Spring ◽  
Robust Optimization Design

In here, a robust optimization mathematical model of the cylindrical helical compression spring is presented. To minimize the error and maximal variations of spring stiffness coefficient related with structure parameters and its tolerances is chosen as its objective function, and the acceptable region is formed by some constraints. The theory is applied to the structure design of the breaking spring of spring actuator, the breaking characteristics are all satisfied at the optimum structure parameters, and the optimization results are discussed.

The Robust Optimization Design for Breaking Spring of Spring Actuator of Vacuum Circuit Breaker

2011 ◽  
Vol 199-200 ◽  
pp. 1217-1222
Author(s):  
Bo Sun ◽  
Gang Chen ◽  
Xiao Ming Liu ◽  
Er Zhi Wang
Keyword(s):  
Robust Optimization ◽  
Optimization Design ◽  
Circuit Breaker ◽  
Structure Parameters ◽  
Stiffness Coefficient ◽  
Nonlinear Programming Problem ◽  
Spring Stiffness ◽  
Vacuum Circuit Breaker ◽  
Optimum Parameters ◽  
Robust Optimization Design

In this paper, the concept of robust optimization design for the breaking spring of spring actuator of vacuum circuit breaker is presented. The function, that is to minimize the error and maximal variations of spring stiffness coefficient related with structure parameters and its tolerances, is chosen as the objective function, and the acceptable region of the tolerances is formed by some constraints. The optimum parameters of the breaking spring are given by solving the nonlinear programming problem with multi-target and two-level optimization, and the optimization results are discussed.

The Effect of Different Optimization Methods on Robustness for Robust Optimization Design

2014 ◽  
Vol 721 ◽  
pp. 464-467
Author(s):  
Tao Fu ◽  
Qin Zhong Gong ◽  
Da Zhen Wang
Keyword(s):  
Robust Optimization ◽  
Objective Function ◽  
Robust Design ◽  
Optimization Design ◽  
Optimization Methods ◽  
Optimization Method ◽  
Design Parameters ◽  
Hybrid Particle Swarm Optimization ◽  
Design Variables ◽  
Robust Optimization Design

In view of robustness of objective function and constraints in robust design, the method of maximum variation analysis is adopted to improve the robust design. In this method, firstly, we analyses the effect of uncertain factors in design variables and design parameters on the objective function and constraints, then calculate maximum variations of objective function and constraints. A two-level optimum mathematical model is constructed by adding the maximum variations to the original constraints. Different solving methods are used to solve the model to study the influence to robustness. As a demonstration, we apply our robust optimization method to an engineering example, the design of a machine tool spindle. The results show that, compared with other methods, this method of HPSO(hybrid particle swarm optimization) algorithm is superior on solving efficiency and solving results, and the constraint robustness and the objective robustness completely satisfy the requirement, revealing that excellent solving method can improve robustness.

Robust optimization design for fatigue life

2011 ◽  
Vol 47 (10) ◽  
pp. 1186-1190 ◽  
Author(s):  
Feng Li ◽  
Guangwei Meng ◽  
Lirong Sha ◽  
Liming Zhou
Keyword(s):  
Fatigue Life ◽  
Robust Optimization ◽  
Optimization Design ◽  
Robust Optimization Design

Optimization Research on Dynamic Balance of Spatial Engine under Limiting Shaking Moment

2009 ◽  
Vol 626-627 ◽  
pp. 693-698
Author(s):  
Yong Yong Zhu ◽  
S.Y. Gao
Keyword(s):  
Mathematical Model ◽  
Objective Function ◽  
Kinetic Analysis ◽  
Optimization Design ◽  
Design Method ◽  
Dynamic Balance ◽  
Optimized Design ◽  
Design Variables ◽  
The Mathematical Model ◽  
Shaking Moment

Dynamic balance of the spatial engine is researched. By considering the special wobble-plate engine as the model of spatial RRSSC linkages, design variables on the engine structure are confirmed based on the configuration characters and kinetic analysis of wobble-plate engine. In order to control the vibration of the engine frame and to decrease noise caused by the spatial engine, objective function is choosed as the dimensionless combinations of the various shaking forces and moments, the restriction condition of which presents limiting the percent of shaking moment. Then the optimization design is investigated by the mathematical model for dynamic balance. By use of the optimization design method to a type of wobble-plate engine, the optimization process as an example is demonstrated, it shows that the optimized design method benefits to control vibration and noise on the engines and improve the performance practically and theoretically.

scholarly journals Multi-Objective Robust Optimization Using a Postoptimality Sensitivity Analysis Technique: Application to a Wind Turbine Design

2015 ◽  
Vol 137 (1) ◽  
Author(s):  
Weijun Wang ◽  
Stéphane Caro ◽  
Fouad Bennis ◽  
Ricardo Soto ◽  
Broderick Crawford
Keyword(s):  
Sensitivity Analysis ◽  
Robust Optimization ◽  
Wind Turbine ◽  
Optimization Design ◽  
Optimization Problems ◽  
Design Environment ◽  
Multi Objective ◽  
Pareto Ranking ◽  
Analysis Technique ◽  
Robust Optimization Design

Toward a multi-objective optimization robust problem, the variations in design variables (DVs) and design environment parameters (DEPs) include the small variations and the large variations. The former have small effect on the performance functions and/or the constraints, and the latter refer to the ones that have large effect on the performance functions and/or the constraints. The robustness of performance functions is discussed in this paper. A postoptimality sensitivity analysis technique for multi-objective robust optimization problems (MOROPs) is discussed, and two robustness indices (RIs) are introduced. The first one considers the robustness of the performance functions to small variations in the DVs and the DEPs. The second RI characterizes the robustness of the performance functions to large variations in the DEPs. It is based on the ability of a solution to maintain a good Pareto ranking for different DEPs due to large variations. The robustness of the solutions is treated as vectors in the robustness function space (RF-Space), which is defined by the two proposed RIs. As a result, the designer can compare the robustness of all Pareto optimal solutions and make a decision. Finally, two illustrative examples are given to highlight the contributions of this paper. The first example is about a numerical problem, whereas the second problem deals with the multi-objective robust optimization design of a floating wind turbine.

Simulation and Robust Optimization Design for Electromagnetic Railgun Performance

2019 ◽  
Vol 47 (6) ◽  
pp. 2964-2970
Author(s):  
Xiaobing Shang ◽  
Tao Chao ◽  
Ping Ma ◽  
Ming Yang
Keyword(s):  
Robust Optimization ◽  
Optimization Design ◽  
Robust Optimization Design
Sign in / Sign up

Export Citation Format

Share Document