Determination of stress concentration factors for shafts under tension

Author:

Ozkan Murat Tolga1,Erdemir Fulya1

Affiliation:

1. Industrial Design Engineering Department, Faculty of Technology, Gazi University, 06500 Besevler Ankara , Turkey

Abstract

Abstract Computer-based design and optimization have become increasingly important in recent years. This paper has investigated the stress concentration factors (SCF) Kt for shoulder filleted shafts with a hole and without a hole. This study contains two types of shoulder filleted shafts, i. e., a stepped bar of circular cross section with shoulder filleted and a tube with filleted shafts under tension stresses. Investigations on SCF that have been carried out in experimental and theoretical studies, were updated and validated for 2 types of shafts. The charts have been converted into numerical value using high precision computer techniques. Dimensional ratios and SCF were determined using previous work charts. This study determines maximum stresses for shoulder filleted shafts by three dimensional finite element analysis (FEA) and artificial intelligence techniques. A set of SCF charts was converted into numerical values and this data was organized and stored in an Excel file. ANSYS models were created and applied the boundary conditions on the models. And also mesh optimizations were performed. Artificial neural networks (ANN) models were designed using previously collected and verified data. Previous works, ANSYS and ANN results were compared to each other. As a result, ANN model and chart results show a good agreement. The usage of ANN model does not require any mathematical formulae or converting the numerical data action for determining the Kt result for shafts. ANN model usage was identified as a very useful and practical method.

Publisher

Walter de Gruyter GmbH

Subject

Mechanical Engineering,Mechanics of Materials,General Materials Science

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3