Author/Authors
KÖKSAL, Erdal Şehit Sertaç Uzun ATL ve METEM, Turkey , ÖZKAN, Murat Tolga Gazi Üniversitesi - Teknik Eğitim Fakültesi - Makina Eğitimi Bölümü, Turkey , ELDEM, Cengiz Gazi Üniversitesi - Teknik Eğitim Fakültesi - Makina Eğitimi Bölümü, Turkey
Title Of Article
Notch Sensitivity Factor Determination With Artificial Neural Network For Shafts Under The Tension Stress
شماره ركورد
28192
Abstract
Notch, hole, tap and a variety of geometric shapes such as curves or discontinuities can be found with various reasons in the design of Machine Element. Especially in the field of stress concentration is caused by sudden change in cross section and various discontinuities in the force flow. Stress concentration can occur with the reason of material features of size or direction of forces application. This type of Stress concentration in the material brings out the effect of notch. Notch impact can lead to distortions and breakage of materials. In this study, A software that is determined the Notch Sensitivity Factor has been developed with Artificial Neural Network System (ANN) for under the effect of tension stresses on shafts. The software has developed using Pythia. With this software, the user can be obtained the accurate value by entering shaft dimension and the applied force without the need for notch sensitivity factor tables and any calculations.
From Page
81
NaturalLanguageKeyword
Notch Sensitivity Factor , Machine Design , Artificial Neural Network
JournalTitle
Erciyes University Journal Of The Institute Of Science and Technology
To Page
89
JournalTitle
Erciyes University Journal Of The Institute Of Science and Technology
Link To Document