A Coupled Thermomechanical Modeling Method for Predicting Grinding Residual Stress Based on Randomly Distributed Abrasive GrainsSource: Journal of Manufacturing Science and Engineering:;2019:;volume( 141 ):;issue: 008::page 81005DOI: 10.1115/1.4043799Publisher: American Society of Mechanical Engineers (ASME)
Abstract: In this research, we propose a coupled thermomechanical modeling method for predicting grinding residual stress based on randomly distributed grains. In order to deal with the problem that the nominal grinding force is too small to generate the plastic deformation, we hold the opinion that grinding residual stress is totally derived from three factors: thermal stress, the nominal grinding force (pressure) over the entire grinding zone, and the equivalent plowing force just under the bottom of the abrasive wheel. Finite element model (FEM) simulation of the single-grain grinding (SGG) is conducted to obtain the critical plowing depth and the SGG force at an arbitrary cutting depth. Based on the randomly distributed abrasive grains, the equivalent grinding heat source model, the equivalent SGG plowing force model, and the equivalent nominal pressure model are all established. A 2D coupled thermomechanical model is established to simulate the grinding process for temperature fields and grinding residual stress fields. In addition, verification tests are conducted to validate the model. It turns out that the coupled model can accurately predict the multiphysical fields on both temperature and residual stress. Based on the simulation results of the model, the generation mechanism of grinding residual stress is quantitatively studied. This research provides a promising pathway to residual stress control of grinding.
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contributor author | Nie, Zhenguo | |
contributor author | Wang, Gang | |
contributor author | Wang, Liping | |
contributor author | Rong, Yiming (Kevin) | |
date accessioned | 2019-09-18T09:02:11Z | |
date available | 2019-09-18T09:02:11Z | |
date copyright | 6/10/2019 12:00:00 AM | |
date issued | 2019 | |
identifier issn | 1087-1357 | |
identifier other | manu_141_8_081005 | |
identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4258106 | |
description abstract | In this research, we propose a coupled thermomechanical modeling method for predicting grinding residual stress based on randomly distributed grains. In order to deal with the problem that the nominal grinding force is too small to generate the plastic deformation, we hold the opinion that grinding residual stress is totally derived from three factors: thermal stress, the nominal grinding force (pressure) over the entire grinding zone, and the equivalent plowing force just under the bottom of the abrasive wheel. Finite element model (FEM) simulation of the single-grain grinding (SGG) is conducted to obtain the critical plowing depth and the SGG force at an arbitrary cutting depth. Based on the randomly distributed abrasive grains, the equivalent grinding heat source model, the equivalent SGG plowing force model, and the equivalent nominal pressure model are all established. A 2D coupled thermomechanical model is established to simulate the grinding process for temperature fields and grinding residual stress fields. In addition, verification tests are conducted to validate the model. It turns out that the coupled model can accurately predict the multiphysical fields on both temperature and residual stress. Based on the simulation results of the model, the generation mechanism of grinding residual stress is quantitatively studied. This research provides a promising pathway to residual stress control of grinding. | |
publisher | American Society of Mechanical Engineers (ASME) | |
title | A Coupled Thermomechanical Modeling Method for Predicting Grinding Residual Stress Based on Randomly Distributed Abrasive Grains | |
type | Journal Paper | |
journal volume | 141 | |
journal issue | 8 | |
journal title | Journal of Manufacturing Science and Engineering | |
identifier doi | 10.1115/1.4043799 | |
journal fristpage | 81005 | |
journal lastpage | 081005-12 | |
tree | Journal of Manufacturing Science and Engineering:;2019:;volume( 141 ):;issue: 008 | |
contenttype | Fulltext |