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Fatigue Behavior Of Microalloy Steel

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2001 Annual Conference


Albuquerque, New Mexico

Publication Date

June 24, 2001

Start Date

June 24, 2001

End Date

June 27, 2001



Page Count


Page Numbers

6.497.1 - 6.497.9



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K Sudhakar

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Mohammed Haque

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NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract

Session 1464

Fatigue Behavior of Microalloy Steel

K. V. Sudhakar, Ph.D., Mohammed E. Haque, Ph.D., P.E.

Central Michigan University, MI/Texas A&M University, TX


Microalloy steels are potentially used for applications in earthmoving equipments and automobile components. Their excellent combination of strength and ductility/formability at lower costs are the distinct advantages over similar high strength low alloy steels. In the present investigation, fatigue behavior/fracture toughness of microalloy steel was studied to evaluate their influence on microstructure. It was found that the fatigue properties (in terms of fracture toughness) as well as the tensile properties (in terms of 0.2% proof stress) of microalloy steels increased with increase in martensite content. Artificial neural network (ANN) based theoretical prediction model was developed and was found to exhibit excellent matching with the experimental results. This simultaneous increase in fatigue and strength properties of microalloy steels makes them potential materials for various engineering applications.

1. Introduction

The normal approach for avoiding premature material failure is by designing stresses well below the yield strength of the material. However, many of the new high strength and/or high elastic materials under extreme conditions, when the same approach was used leading to catastrophic failures. The fractures occurred in a brittle manner and the materials did not exhibit their typical ductility even at lower stress levels. Design criteria have been subsequently developed for the safe use of materials on the basis of fracture toughness. Fracture toughness is a fundamental material property that depends on many factors, the most influential of which is microstructure of the material. The influence of microstructure on fatigue crack growth behavior in steels has been a subject of considerable research interest for many years. Some of the recent research finding of the current authors in this direction have been highly encouraging 1-5. Evaluation of newer materials with improved combinations of strength, ductility and toughness has led to the emergence of microalloy steels in recent years. Microalloy steels were developed to satisfy an increasing need, primarily in the automobile industry, for new high strength steels that permit weight reduction with neither sacrificing formability nor dramatically increasing costs.

Artificial Neural Network (ANN) can be effectively used to develop models to analyze and predict mechanical properties of materials. Neural computing is a relatively new field of artificial intelligence (AI), which tries to mimic the structure and operation of biological neural systems, such as the human brain, by creating an Artificial Neural Network (ANN) on a computer. These ANNs are modeling techniques that are especially useful to address problems where solutions

Proceedings of the 2001 American Society for Engineering Education Annual Conference & Exposition Copyright © 2001, American Society for Engineering Education

Sudhakar, K., & Haque, M. (2001, June), Fatigue Behavior Of Microalloy Steel Paper presented at 2001 Annual Conference, Albuquerque, New Mexico. 10.18260/1-2--9269

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