Uncertain Optimization Design Based on Interval Structure Analysis

2020 ◽  
pp. 221-242
Author(s):  
Xu Han ◽  
Jie Liu
2011 ◽  
Vol 374-377 ◽  
pp. 1916-1919
Author(s):  
Jian Xiao Zheng ◽  
Bin Li ◽  
Si Cong Yuan

The overall three-dimensional parametric model of the crankshaft has been completed based on the ANSYS Parametric Design Language (APDL) from the software of ANSYS and by combing the structure analysis capability with the statistical analysis capability of its PDS module, the reliability analysis of Monte Carlo finite element method (FEM) will be achieved according to the finite element analysis technology and the reliability basic principles. The 4110 diesel engine crankshaft was taken as an example, the parametric design will be introduced into the finite element structure analysis to implement the rapid adjustment of the structure parameter, produce the anatomic model automatically and complete the process of the structural analysis and reliability analysis. The process that the reliability analysis of the crankshaft has been realized will be described in detail. According to the results of probability analysis, the sensitivity relation between the design variable and the object variable will be obtained and at the same time the maximum stress probability distribution function of these dangerous parts and the main affective factor for object variable will be given, which will offer the useful data for the structure reliability optimization design.


2021 ◽  
Vol 1802 (2) ◽  
pp. 022003
Author(s):  
Bin Li ◽  
Peng Zhang ◽  
Hai Gu ◽  
Jie Jiang ◽  
Jianhua Sun ◽  
...  

2014 ◽  
Vol 587-589 ◽  
pp. 1577-1580
Author(s):  
Chang Huan Kou ◽  
Tsung Ta Wu ◽  
Pei Yu Lin

In order to solve structural optimization problems in the past, it is necessary to integrate structure analysis software and optimization software. Since structural analysis has been the only function considered when developing most of structure analysis software, they suffer from closeness of system. Therefore, it is not easy to integrate them with optimization software. This study proposes an experimental design method to solve this problem including following steps: (1) generate experimental design, (2) implement experimental design, (3) construct a response variable model, (4) define optimization problem, (5) solve optimization problem. The purpose of step (1) through step (3) is to create a response variable model of alternative structure analysis software. This model is a set of regular and simple functions, it can easily define the optimization problem in step (4), in order to facilitate step (5) to solve the optimization problem. The reason to employ neural network instead of traditional regression analysis in step (3) is that the relationship between internal forces and displaced cross section dimension of the structure are often nonlinear. Neural network is a nonlinear system that gives itself the greatest advantage to accurately construct a nonlinear model. This case study is based on optimization design of cable force and tower height in an extradosed bridge, evaluating the feasibility of above method and comparing with published references to confirm the proposed method in this study is applicable to the optimization design of extradosed bridge.


2013 ◽  
Vol 405-408 ◽  
pp. 997-1001
Author(s):  
Guo Qiang Yu ◽  
Fei Wang ◽  
Guang Du

In order to provide evidence for optimization design of directly buried heating pipeline tees, finite element models of tees with different ratios of branch-main pipe diameters had been established and simulated by structure analysis soft ANSYS. The change law of maximum equivalent stress values in pipe-nozzle intersection area had been obtained at same temperature, pressure loads and displacement constraints. The results show that maximum equivalent stress values of stamped tees are less than welded tees with same specifications. And stamped tees with lager fillet radius and local wall thickness can effectively decrease maximum equivalent stress values of pipe-nozzle intersection area.


Author(s):  
Shengxi Jia ◽  
Longxi Zheng ◽  
Qing Mei

A flexible rotor optimization design considering the uncertainty of the unbalance is carried out in this paper. Assuming that the magnitude and phase of unbalance obey normal distribution and uniform distribution respectively, the uncertainty can be quantitatively described. The classical 6 Sigma method is used to perform uncertain optimization design of the rotor system considering this uncertainty. The theoretical results are verified by experiments in which 36 sets of unbalance are artificially distributed to the rotor to simulate the uncertainty. In experiment, the amplitude response of the two disks and the acceleration response of the two bearings are decreased by 14%, 21.5%, 37.2% and 46% respectively in terms of standard deviation. It can be concluded that the optimization design considering the uncertainty can reduce the fluctuation of the response and improving the robustness of the results.


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