Prediction of Fatigue Life for Spot Welds Using Back-Propagation Neural Networks

Jungme Park; Hongtae Kang

doi:10.1016/j.matdes.2006.10.014

Prediction of Fatigue Life for Spot Welds Using Back-Propagation Neural Networks

Jungme Park, Hongtae Kang

Kettering University

University of Michigan - Dearborn

Research output: Contribution to journal › Article › peer-review

Abstract

In this research, the authors developed back-propagation neural networks (BNNs) to predict the fatigue life of spot welds subjected to various geometric factors and loading conditions. This paper described the developing procedures of the BNNs in detail for the spot weld fatigue. Then, the BNNs developed in this study were employed to predict the fatigue life of the spot welds subjected to combined tension and shear loading and tensile-shear loading. The BNNs showed reasonable accuracy for the cases tested in this study. The BNNs can be employed as a practical method for calculating fatigue life of spot welds under various geometric dimensions and loading conditions.

Original language	American English
Journal	Materials Design
Volume	28
DOIs	https://doi.org/10.1016/j.matdes.2006.10.014
State	Published - 2007

Keywords

Backpropagation Neural Network
Combined tension and shear loading

Disciplines

Engineering

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Cite this

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title = "Prediction of Fatigue Life for Spot Welds Using Back-Propagation Neural Networks",

abstract = " In this research, the authors developed back-propagation neural networks (BNNs) to predict the fatigue life of spot welds subjected to various geometric factors and loading conditions. This paper described the developing procedures of the BNNs in detail for the spot weld fatigue. Then, the BNNs developed in this study were employed to predict the fatigue life of the spot welds subjected to combined tension and shear loading and tensile-shear loading. The BNNs showed reasonable accuracy for the cases tested in this study. The BNNs can be employed as a practical method for calculating fatigue life of spot welds under various geometric dimensions and loading conditions.",

keywords = "Backpropagation Neural Network, Combined tension and shear loading",

author = "Jungme Park and Hongtae Kang",

note = "In this research, the authors developed back-propagation neural networks (BNNs) to predict the fatigue life of spot welds subjected to various geometric factors and loading conditions. This paper described the developing procedures of the BNNs in detail for the spot weld fatigue.",

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T1 - Prediction of Fatigue Life for Spot Welds Using Back-Propagation Neural Networks

AU - Park, Jungme

AU - Kang, Hongtae

N1 - In this research, the authors developed back-propagation neural networks (BNNs) to predict the fatigue life of spot welds subjected to various geometric factors and loading conditions. This paper described the developing procedures of the BNNs in detail for the spot weld fatigue.

PY - 2007

Y1 - 2007

N2 - In this research, the authors developed back-propagation neural networks (BNNs) to predict the fatigue life of spot welds subjected to various geometric factors and loading conditions. This paper described the developing procedures of the BNNs in detail for the spot weld fatigue. Then, the BNNs developed in this study were employed to predict the fatigue life of the spot welds subjected to combined tension and shear loading and tensile-shear loading. The BNNs showed reasonable accuracy for the cases tested in this study. The BNNs can be employed as a practical method for calculating fatigue life of spot welds under various geometric dimensions and loading conditions.

AB - In this research, the authors developed back-propagation neural networks (BNNs) to predict the fatigue life of spot welds subjected to various geometric factors and loading conditions. This paper described the developing procedures of the BNNs in detail for the spot weld fatigue. Then, the BNNs developed in this study were employed to predict the fatigue life of the spot welds subjected to combined tension and shear loading and tensile-shear loading. The BNNs showed reasonable accuracy for the cases tested in this study. The BNNs can be employed as a practical method for calculating fatigue life of spot welds under various geometric dimensions and loading conditions.

KW - Backpropagation Neural Network

KW - Combined tension and shear loading

UR - https://www.sciencedirect.com/science/article/pii/S0261306906003189

U2 - 10.1016/j.matdes.2006.10.014

DO - 10.1016/j.matdes.2006.10.014

M3 - Article

VL - 28

JO - Materials Design

JF - Materials Design

ER -

Prediction of Fatigue Life for Spot Welds Using Back-Propagation Neural Networks

Abstract

Keywords

Disciplines

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