2019
DOI: 10.1016/j.engfailanal.2019.01.042
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Prediction of failure stages for double lap joints using finite element analysis and artificial neural networks

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Cited by 60 publications
(21 citation statements)
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“…The exception appears in the correlation between the normalized force values and the tightening torque values in all values of W / D and it is shown in Figure 5. The above results are completely consistent with that offered in Atta et al (2019).…”
Section: Resultssupporting
confidence: 92%
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“…The exception appears in the correlation between the normalized force values and the tightening torque values in all values of W / D and it is shown in Figure 5. The above results are completely consistent with that offered in Atta et al (2019).…”
Section: Resultssupporting
confidence: 92%
“…This part illustrates a comparison between the present experimental results and those predicted by the authors using artificial neural network (ANN) (Atta et al, 2019). Figure 8 illustrates the effect of torque on Stages 0 (the slipping load value) and 3 (the maximum load value) in both experimental and ANN results.…”
Section: Comparison Of the Resultssupporting
confidence: 56%
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“…With using this set of mesh properties, it was purposed to eliminate singularity zones. Mesh size was adopted as half of the adhesive thickness due to CZM and failure load is not strongly tied to mesh size [30,31]. The average element quality and aspect ratio were observed as 0.97 and 1.21 respectively.…”
Section: Preparing Finite Element Analysismentioning
confidence: 99%
“…In the FE models, the steel H-section and steel plate are simulated by eight-node uncoordinated three-dimensional solid element (C3D8I), while the core concrete is simulated by eight-node reduced integral three-dimensional solid element (C3D8R). The appropriate element sizes were selected in the FE models based on the sensitivity analysis and the balance between accuracy and time cost [20,21]. Therefore, mesh size sensitivity analysis has been carried out in this study.…”
Section: Development Of Modelsmentioning
confidence: 99%