journal article·2014-03

Development of the positive mean stress diagrams using genetic algorithm approach

T. Sekercioglu, O. E. Canyurt

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Abstract

ABSTRACT In this numerical study, a new optimum positive mean stress fatigue failure equation is developed using previous experimental data and genetic algorithm. Two independent curve fitting coefficients are implemented in the equation to supply better correlations with experimental data of the failure strength envelope. In the literature, Gerber, Goodman, Soderberg, Morrow, Bagci, ASME (elliptic line), Clemson, Sekercioglu and so on suggested different equations for estimating fatigue strength envelope under mean stress condition. In these models, the effect of the materials was not considered in details. Some of these mean stress linear expressions are very conservative or have stress area bigger than the yield limit. The yield strength and the effect of materials are considered in the proposed model. The values of the positive mean stress, which correspond to fatigue failure, are obtained, and a minimum average absolute error among the models presented in the literature is remarked. The proposed model, which has less conservative structure, can be effectively used in the mechanical design process.
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Research context

OpenAlex topics: Fatigue and fracture mechanics · Topology Optimization in Engineering · Structural Load-Bearing Analysis

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Mechanical Engineering Department, Engineering Faculty Pamukkale University Denizli Turkey

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