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Information Journal Paper

Title

Investigation of the effect of defects under the influence of composite loads in metallic silos using radial stem nerve networks

Pages

  10-18

Abstract

 Failure and buckling in shell structures, including silos, can be created for various reasons such as distortion, defects created during construction, defects created during operation, or environmental factors, etc. Silos can be subjected to a variety of lateral and axial loads, but since they are in fact affected by the combination of these loads, silos behave under the influence of composite loads. The silos in this research are hot-rolled and located on the ground. The variables of this research are type and scope of defect. Silos are also evaluated in semi-filled and semi-solid state. The model silos were analyzed in ANSYS software. The radial radial neural network RBF was used to predict the buckling capacity of the cylindrical shells. The results of this study indicate that artificial neural networks are a good tool for predicting buckling capacity of silos with defects.

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  • Cite

    APA: Copy

    abootaleb, nasser, Ghorbani, amin, & Alizadeh Giashi, Mona. (2019). Investigation of the effect of defects under the influence of composite loads in metallic silos using radial stem nerve networks. CIVIL AND PROJECT JOURNAL, 1(1 ), 10-18. SID. https://sid.ir/paper/268502/en

    Vancouver: Copy

    abootaleb nasser, Ghorbani amin, Alizadeh Giashi Mona. Investigation of the effect of defects under the influence of composite loads in metallic silos using radial stem nerve networks. CIVIL AND PROJECT JOURNAL[Internet]. 2019;1(1 ):10-18. Available from: https://sid.ir/paper/268502/en

    IEEE: Copy

    nasser abootaleb, amin Ghorbani, and Mona Alizadeh Giashi, “Investigation of the effect of defects under the influence of composite loads in metallic silos using radial stem nerve networks,” CIVIL AND PROJECT JOURNAL, vol. 1, no. 1 , pp. 10–18, 2019, [Online]. Available: https://sid.ir/paper/268502/en

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