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  • Open Access

    PROCEEDINGS

    Thermal-Mechanical Buckling and Postbuckling Analysis of Thin-Walled Structures Using a Reduced Order Method

    Ke Liang1,*, Zhen Yin1, Zheng Li1, Jiaqi Mu1

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.26, No.2, pp. 1-2, 2023, DOI:10.32604/icces.2023.09020

    Abstract Thermal-mechanical buckling has become one of the major failure modes of thin-walled structures which suffer from the high temperature service environment. These structures, such as plates and shells, are commonly involved in many branches of engineering, especially for the aerospace structures. Thermalmechanical buckling analysis plays an important role for lightweight design of aircrafts and launch vehicles, which significantly influences the load-carrying capability of the structure. Geometrical nonlinearities should be well considered to determine an accurate value of the critical buckling temperature/load as well as the postbuckling response.
    In this work, a reduced-order method is proposed for geometrically nonlinear thermal-mechanical analysis… More >

  • Open Access

    PROCEEDINGS

    Efficient and Robust Temperature Field Simulation of Long-Distance Crude Oil Pipeline Based on Bayesian Neural Network and PDE

    Weixin Jiang1,*, Qing Yuan2, Zongze Li3, Junhua Gong3, Bo Yu4

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.25, No.4, pp. 1-2, 2023, DOI:10.32604/icces.2023.08861

    Abstract The hydraulic and thermal simulation of crude oil pipeline transportation is greatly significant for the safe transportation and accurate regulation of pipelines. With reasonable basic parameters, the solution of the traditional partial differential equation (PDE) for the axial soil temperature field on the pipeline can obtain accurate simulation results, yet it brings about a low calculation efficiency problem. In order to overcome the low-efficiency problem, an efficient and robust hybrid solution model for soil temperature field coupling with Bayesian neural network and PDE is proposed, which considers the dynamic changes of boundary conditions. Four models, including the proposed hybrid model,… More >

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