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<p>Empty steel-tanks are very much susceptible against buckling induced by wind loading. Ring and vertical stiffeners are commonly used to provide necessary strength to thin-walled steel tanks to resist wind-induced buckling. The authors have studied the performance of a unique, ribonucleic acid structure-inspired, stiffening-helix mechanism against the wind-induced buckling of open-top, cylindrical, empty, steel-tank. The most important output parameter of this study is the load multiplier (<i>λ</i>) of buckling, as it defines the stability of tank-shell against wind-induced buckling. The study variables are tank-height to tank-diameter (<i>H</i>/<i>D</i>) ratio, tank-radius to wall-thickness (<i>r</i>/<i>t</i>) ratio, basic wind speed (<i>V</i><sub>b</sub>) and helix pitch length to tank-height (<i>L</i><sub>P</sub>/<i>H</i>) ratio. This study has been performed through multiphysics system-coupling of computational fluid dynamics and structural mechanics (eigenvalue buckling). The stiffening-helix can provide necessary strength to open-top, cylindrical, steel-tank economically against wind-induced buckling. An artificial neural network (ANN) has been trained with the analytical data to develop a predictive model. The proposed predictive ANN model produces 99.11% average accuracy.</p>

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Wind-structure interaction data-driven neural-network model proposition for assessing performance of unique stiffening-helix against wind-induced open-top tank-buckling

  • 期刊论文

  • 发表日期：

    2025年8月8日

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  • Soumya Mukherjee,
  • Dilip Kumar Singha Roy

摘要

Empty steel-tanks are very much susceptible against buckling induced by wind loading. Ring and vertical stiffeners are commonly used to provide necessary strength to thin-walled steel tanks to resist wind-induced buckling. The authors have studied the performance of a unique, ribonucleic acid structure-inspired, stiffening-helix mechanism against the wind-induced buckling of open-top, cylindrical, empty, steel-tank. The most important output parameter of this study is the load multiplier (λ) of buckling, as it defines the stability of tank-shell against wind-induced buckling. The study variables are tank-height to tank-diameter (H/D) ratio, tank-radius to wall-thickness (r/t) ratio, basic wind speed (Vb) and helix pitch length to tank-height (LP/H) ratio. This study has been performed through multiphysics system-coupling of computational fluid dynamics and structural mechanics (eigenvalue buckling). The stiffening-helix can provide necessary strength to open-top, cylindrical, steel-tank economically against wind-induced buckling. An artificial neural network (ANN) has been trained with the analytical data to develop a predictive model. The proposed predictive ANN model produces 99.11% average accuracy.