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Today, fluid transportation via pipes can be found in many sectors. Therefore, safe fluid transportation possesses critical importance. While working, transportation pipes are exposed to unwanted loads that culminate in stresses which cause deformation on the part geometry especially in sharp corners, holes or sudden cross-section change areas considered as notched. The notch effect parameter is considered in the mechanical design formulas. This study is interested in the notch factor that is estimated for a cylinder which undergoes an inner pressure. Some users can use false numerical values due to misreading or lack of attention. Because of this reason, graphs were converted to the numerical value by using computer software. In this study, Peterson’s chart was accepted as scientifically valid. Stress concentration factors were obtained by using four other approaches. These are regression, analytical, artificial neural network and finite element analysis. Among these models, high accuracy values were given by the artificial neural network model.

Notch (stress concentration) factor estimation of a cylinder under internal pressure using different approaches