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The Optimal Design Of Grip Considering Uncertainties

Posted on:2022-08-17Degree:MasterType:Thesis
Country:ChinaCandidate:H XieFull Text:PDF
GTID:2492306509981039Subject:Mechanical design and theory
Abstract/Summary:PDF Full Text Request
As an efficient equipment of air transportation,aerial ropeways are widely used in our country.The grip is the equipment responsible for connecting the wire rope and the hanging box in the aerial ropeway.Therefore,its safety,stability and reliability must be ensured during the design process.However,due to the immature domestic design specifications for rope grippers,designers can only complete the design by referring to past experience.The method is relatively conservative,and it is easy to cause excessive weight and material waste in the process of pursuing structural safety.On the other hand,the fatigue analysis of the grip is limited to theoretical calculations.Considering that the load and working conditions of the grip are more complicated during the working process,the calculation results lack accuracy and reliability.In response to these problems,this article first conducts a finite element analysis on the grip,and optimizes the weight reduction of the grip on the basis of satisfying the structural strength and stability.The following problems and difficulties exist in the process of finite element analysis and optimization.First of all,when performing fatigue analysis on the grip,the stress spectrum and the S-N curve of the material cannot be directly obtained by measurement and experiment.Secondly,when optimizing the weight reduction of the grip,the analysis based on the finite element model usually takes a lot of time,and the optimization efficiency is greatly reduced.Finally,due to the influence of uncertain factors in actual engineering,the reliability of optimization cannot be guaranteed.In order to solve the above problems,this paper loads the load time file obtained from the dynamic simulation of the grip into the finite element model to obtain the stress spectrum,and uses the mathematical model to fit the material’s SN curve,and replaces it by constructing a Kriging surrogate model.The finite element model is optimized,and finally the distribution law of the uncertain factors in the project is analyzed,and the reliability analysis and optimization of the grip are carried out under the uncertainty.The main research contents of this paper are as follows:(1)Establish a parametric model of the grip for finite element analysis.According to the design drawings,Solid Works is used to establish the parametric model of the grip,the working condition and load analysis of the grip are carried out,and then the statics and modal analysis of the structure are carried out using ANSYS Workbench.Based on these results,combined with the material’s S-N curve and stress spectrum,use ANSYS n Code Design Life to perform fatigue analysis on the grip.(2)Sensitivity analysis and main factor selection of the grip.In order to reduce the dimensionality of the design variables,the Morris method is used to analyze the influence of the design variables on the quality,maximum stress,and the first and second order natural frequencies of the structure.According to the analysis results,the design variables that have a greater impact on the optimization problem are used as the main factors.(3)Construct a high-precision Kriging model.Establish Kriging models of inner grip mass,outer grip mass,inner grip stress,outer grip stress,first-order natural frequency and second-order natural frequency,then verify the accuracy of the model.(4)Deterministic optimization and reliability optimization.In order to improve the optimization efficiency of the grip,first perform deterministic optimization.On this basis,the reliability analysis of the deterministic optimization results is carried out,and the uncertainty optimization model is established by combining the probability distribution of the design variables,and obtain a light weight and high reliability new structure.
Keywords/Search Tags:Grip, Finite Element Analysis, Kriging Surrogate Model, Weight Reduction Optimization, Uncertainties
PDF Full Text Request
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