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2018
DOI: 10.2478/ama-2018-0006
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Numerical Analysis of Stress Intensity Factor in Specimens with Different Fillet Geometry Subjected to Bending

Abstract: The article presents the maps of xx stress component and compares values of analytical and numerical calculations for the stress intensity factor range of welded specimens with fillet welds which subjected to cyclic bending. The tests were performed under constant value of moment amplitude Ma= 9.20 N·m and stress ratio R = σmin/ σmax= −1. The specimens were made of drag steel rod S355. The specimens were solid and welded. The numerical models were simulated with ABAQUS suite and numerical calculations performe… Show more

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Cited by 2 publications
(2 citation statements)
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“…A fatigue fracture is defined as a "partial or complete fracture due to its inability to withstand non-visible stresses applied rhythmically, repeatedly, and below the threshold" [1] Fatigue fractures occur due to the accumulation of stress-induced microfractures. One should investigate the stress intensity factor and the outcomes of both experimental (analytical) and numerical calculations for the range of stress intensities in order to evaluate the effects of cyclic fatigue on metallic specimens with diverse physical features [2]. Using heterogeneous image fusion to reduce picture-related disturbances in intensity or range image data and to reduce uncertainties through cross-domain feature correlation, a deep convolutional neural network-based crack segmentation methodology was provided [3].…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…A fatigue fracture is defined as a "partial or complete fracture due to its inability to withstand non-visible stresses applied rhythmically, repeatedly, and below the threshold" [1] Fatigue fractures occur due to the accumulation of stress-induced microfractures. One should investigate the stress intensity factor and the outcomes of both experimental (analytical) and numerical calculations for the range of stress intensities in order to evaluate the effects of cyclic fatigue on metallic specimens with diverse physical features [2]. Using heterogeneous image fusion to reduce picture-related disturbances in intensity or range image data and to reduce uncertainties through cross-domain feature correlation, a deep convolutional neural network-based crack segmentation methodology was provided [3].…”
Section: Introductionmentioning
confidence: 99%
“…To describe and present the data in a more understandable way, Equation (1) undergoes linearization, which is presented in Equation (2). In this way, the data obtained can be graphed and interpreted.…”
Section: Introductionmentioning
confidence: 99%