scholarly journals Development of CAE Analysis in Three-Roll-Type Ring Rolling

2009 ◽  
Vol 50 (584) ◽  
pp. 873-877 ◽  
Author(s):  
Morihiko NAKASAKI ◽  
Toshifusa NAKAMIZO ◽  
Ichiro TAKASU ◽  
Hiroshi UTSUNOMIYA
Keyword(s):  
Ring Rolling ◽  
Roll Type ◽  
Cae Analysis

Clarification of Rolling Characteristics in Three-roll-type Ring Rolling Process and Application to Profiled Ring Products

2015 ◽  
Vol 56 (659) ◽  
pp. 1039-1043
Author(s):  
Toshifusa NAKAMIZO ◽  
Morihiko NAKASAKI ◽  
Masaya NAGAI ◽  
Hiroyuki MYOCHIN ◽  
Ichiro TAKASU ◽  
...  
Keyword(s):  
Rolling Process ◽  
Ring Rolling ◽  
Roll Type ◽  
Ring Rolling Process

scholarly journals Experimental Study of Deformation Characteristicsin Three-roll-type and Two-roll-type Ring Rolling Process

2012 ◽  
Vol 53 (613) ◽  
pp. 130-134 ◽  
Author(s):  
Toshifusa NAKAMIZO ◽  
Morihiko NAKASAKI ◽  
Ichiro TAKASU ◽  
Hiroshi UTSUNOMIYA
Keyword(s):  
Experimental Study ◽  
Rolling Process ◽  
Ring Rolling ◽  
Roll Type ◽  
Ring Rolling Process

MPS-CAE ANALYSIS OF DEVELOPED SPIRAL AGITATION METHOD FOR BACKFILLING OF PULLOUT HOLES OF EXISTING PILES

2020 ◽  
Vol 76 (4) ◽  
pp. 441-452
Author(s):  
Shinya INAZUMI ◽  
Shuichi KUWAHARA ◽  
Ken-ichi SHISHIDO
Keyword(s):  
Cae Analysis

3D coupled thermo‐mechanical FE modelling and simulation of radial‐axial ring rolling

2011 ◽  
Vol 15 (sup1) ◽  
pp. s221-s224 ◽  
Author(s):  
G Zhou ◽  
L Hua ◽  
J Lan ◽  
D S Qian
Keyword(s):  
Modelling And Simulation ◽  
Ring Rolling ◽  
Fe Modelling ◽  
Axial Ring

scholarly journals Machine Learning-Based Models for the Estimation of the Energy Consumption in Metal Forming Processes

Metals ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 833
Author(s):  
Irene Mirandola ◽  
Guido A. Berti ◽  
Roberto Caracciolo ◽  
Seungro Lee ◽  
Naksoo Kim ◽  
...  
Keyword(s):  
Machine Learning ◽  
Finite Element ◽  
Energy Consumption ◽  
Metal Forming ◽  
Mutual Influence ◽  
Rolling Process ◽  
Ring Rolling ◽  
Gradient Boosting ◽  
Average Error ◽  
Ring Rolling Mill

This research provides an insight on the performances of machine learning (ML)-based algorithms for the estimation of the energy consumption in metal forming processes and is applied to the radial-axial ring rolling process. To define the mutual influence between ring geometry, process settings, and ring rolling mill geometries with the resulting energy consumption, measured in terms of the force integral over the processing time (FIOT), FEM simulations have been implemented in the commercial SW Simufact Forming 15. A total of 380 finite element simulations with rings ranging from 650 mm < DF < 2000 mm have been implemented and constitute the bulk of the training and validation datasets. Both finite element simulation settings (input), as well as the FI (output), have been utilized for the training of eight machine learning models, implemented with Python scripts. The results allow defining that the Gradient Boosting (GB) method is the most reliable for the FIOT prediction in forming processes, being its maximum and average errors equal to 9.03% and 3.18%, respectively. The trained ML models have been also applied to own and literature experimental cases, showing a maximum and average error equal to 8.00% and 5.70%, respectively, thus proving once again its reliability.

Structure Improvement on Dual Variable Gear Shaft of the Transmission for ZL50 Wheel Loader

2012 ◽  
Vol 496 ◽  
pp. 50-53
Author(s):  
Zhan Shun Yin ◽  
Yong Wei Han ◽  
Xi Chun Cai
Keyword(s):  
Heat Treatment ◽  
Service Life ◽  
Dual Variable ◽  
Practical Application ◽  
Hydraulic Pump ◽  
Wheel Loader ◽  
Geometric Tolerance ◽  
Structure Improvement ◽  
Cae Analysis ◽  
Market Feedback

Based on the CAE analysis. The dual variable gear shaft of the transmission for domestic ZL50 wheel loader was redesigned and the processing technology was optimized. The problem of the hardness of the spline which connects the dual variable gear shaft and the working hydraulic pump can not meet the requirements after heat treatment caused by unreasonable design was solved. The problem of the low geometric tolerance and early wear of the spline were solved. After practical application, the market feedback shows that the failure rate, service life and reliability greatly of new designed shaft were enhanced

Sign in / Sign up

Export Citation Format

Share Document