Prediction model of residual stress duringprecision glass molding of optical lenses

2022 ◽  
Author(s):  
Hang Fu ◽  
Changxi Xue ◽  
Yue Liu ◽  
Cao Bo ◽  
Changfu Lang ◽  
...  
Keyword(s):  
Residual Stress ◽  
Prediction Model ◽  
Glass Molding

scholarly journals Prediction Model of Surface Residual Stress for Multi-Pass Drawn High Carbon Steel Wire

2010 ◽  
Vol 19 (4) ◽  
pp. 224-229 ◽  
Author(s):  
D.W. Kim ◽  
S.K. Lee ◽  
B.M. Kim ◽  
J.Y. Jung ◽  
D.Y. Ban ◽  
...  
Keyword(s):  
Residual Stress ◽  
Carbon Steel ◽  
Prediction Model ◽  
Steel Wire ◽  
High Carbon Steel ◽  
High Carbon ◽  
Surface Residual Stress

scholarly journals Experimental Analysis and Prediction Model of Milling-Induced Residual Stress of Aeronautical Aluminum Alloys

2021 ◽  
Vol 11 (13) ◽  
pp. 5881
Author(s):  
Shouhua Yi ◽  
Yunxin Wu ◽  
Hai Gong ◽  
Chenxi Peng ◽  
Yongbiao He
Keyword(s):  
Residual Stress ◽  
Aluminum Alloy ◽  
Prediction Model ◽  
End Milling ◽  
Orthogonal Experiment ◽  
7075 Aluminum Alloy ◽  
Side Milling ◽  
Milling Parameters ◽  
Thin Walled ◽  
Machining Deformation Prediction

Aeronautical thin-walled frame workpieces are usually obtained by milling aluminum alloy plates. The residual stress within the workpiece has a significant influence on the deformation due to the relatively low rigidity of the workpiece. To accurately predict the milling-induced residual stress, this paper describes an orthogonal experiment for milling 7075 aluminum alloy plates. The milling-induced residual stress at different surface depths of the workpiece, without initial stress, is obtained. The influence of the milling parameters on the residual stress is revealed. The parameters include milling speed, feed per tooth, milling width, and cutting depth. The experimental results show that the residual stress depth in the workpiece surface is within 0.12 mm, and the residual stress depth of the end milling is slightly greater than that of the side milling. The calculation models of residual stress and milling parameters for two milling methods are formulated based on regression analysis, and the sensitivity coefficients of parameters to residual stress are calculated. The residual stress prediction model for milling 7075 aluminum alloy plates is proposed based on a back-propagation neural network and genetic algorithm. The findings suggest that the proposed model has a high accuracy, and the prediction error is between 0–14 MPa. It provides basic data for machining deformation prediction of aluminum alloy thin-walled workpieces, which has significant application potential.

scholarly journals Optimization of Forging Process Parameters and Prediction Model of Residual Stress of Ti-6Al-4V Alloy

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Xiurong Fang ◽  
Liu Liu ◽  
Jia Lu ◽  
Yang Gao
Keyword(s):  
Residual Stress ◽  
Prediction Model ◽  
Process Parameters ◽  
Multivariate Regression ◽  
Regression Models ◽  
Temperature Deformation ◽  
Deformation Degree ◽  
Forging Process ◽  
Plastic Forming ◽  
Deformation Speed

Nonisothermal forging is an efficient plastic forming method for titanium alloys, but at the same time, it can produce large and uneven residual stress, which seriously affects the service life of components. In order to quantitatively analyze the influence of forging process parameters on the residual stress of Ti-6Al-4V alloy forgings, a numerical model was first established and optimized in combination with experiments. Then, the effects of deformation temperature, deformation degree, and deformation speed on the residual stress of forgings were analyzed by orthogonal test, and the optimal combination of forging process parameters was obtained. Finally, the multiple regression analysis was employed to propose multivariate regression models for the prediction of the average equivalent residual stress. Results show that the prediction model can be used for predicting the residual stress of Ti-6Al-4V alloy forgings with a higher reliability.

scholarly journals ANALYSIS OF THE PROCESSING SEQUENCE ON AIRFRAME STRUCTURES MACHING DEFORMATION

2020 ◽  
Vol 7 (6) ◽  
pp. 1-10
Author(s):  
Guichu Ding ◽  
Tao Zhang ◽  
Hongwei Li ◽  
Xiaoming Huang
Keyword(s):  
Residual Stress ◽  
Finite Element ◽  
Prediction Model ◽  
Large Deformation ◽  
Initial Stress ◽  
Frame Structure ◽  
Initial Residual Stress ◽  
Deformation Law ◽  
Type Integral ◽  
Integral Structure

In order to reveal the influence of different processing procedures on the machining deformation of the whole structure of aviation frame type, a prediction model for the deformation of frame type integral structure caused by initial residual stress was established based on finite element. According to the deformation law of frame parts caused by initial stress of blank, the deformation of whole structure parts based on aviation frame is minimized. The influence of processing process on deformation of frame structure is studied. The results show that when removing the frame material, the deformation of the workpiece can be slowed down by first removing the area with large deformation and relatively concentrated material. And symmetrical removal of the frame material can also slow the deformation of the workpiece.

scholarly journals Surface Roughness and Residual Stresses of High Speed Turning 300 M Ultrahigh Strength Steel

2014 ◽  
Vol 6 ◽  
pp. 859207 ◽  
Author(s):  
Zhang Huiping ◽  
Zhang Hongxia ◽  
Lai Yinan
Keyword(s):  
Residual Stress ◽  
Surface Roughness ◽  
Prediction Model ◽  
Feed Rate ◽  
High Speed ◽  
Stress Test ◽  
Orthogonal Cutting ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Factors Affecting

Firstly, a single factor test of the surface roughness about tuning 300 M steel is done. According to the test results, it is direct to find the sequence of various factors affecting the surface roughness. Secondly, the orthogonal cutting experiment is carried out from which the primary and secondary influence factors affecting surface roughness are obtained: feed rate and corner radius are the main factors affecting surface roughness. The more the feed rate, the greater the surface roughness. In a certain cutting speed rang, the surface roughness is smaller. The influence of depth of cut to the surface roughness is small. Thirdly, according to the results of the orthogonal experiment, the prediction model of surface roughness is established by using regressing analysis method. Using MatLab software, the prediction mode is optimized and the significance test of the optimized model is done. It showed that the prediction model matched the experiment results. Finally, the surface residual stress test of turning 300 M steel is done and the residual stress of the surface and along the depth direction is measured.

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