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    基于HHO-XFEM的地下结构裂缝智能反演识别研究

    Intelligent Inversion Identification of Underground Structural Cracks Based on HHO-XFEM

    • 摘要: 地下结构的裂损是影响其安全状态的一种重要因素,为了识别运营期交通地下结构的安全状态,基于无损检测信息,采用新型智能优化算法——哈里斯鹰优化(Harris Hawks Optimization,HHO)算法,并结合扩展有限元(Extended Finite Element Method,XFEM)技术,提出一种地下结构裂缝反演识别的HHO-XFEM新方法,并开展了静力与动力工况下的结构裂缝反演识别研究.研究结果表明:静力条件下反演裂缝的长度相对误差为2.5%,倾角相对误差为3.4%;而动力条件下反演裂缝的长度误差为6.9%,倾角误差为3.0%.总体反演识别效果良好.

       

      Abstract: The crack damage of underground structure is an important factor affecting its safety status.In order to identify the safety status of traffic underground structure,based on the nondestructive testing information,by using the new intelligent optimization algorithm,Harris Hawks optimization (HHO) algorithm,and combing with the extended finite element method (XFEM) technology,a new HHO-XFEM method for reverse identification of underground structural cracks is proposed.The identification of structural crack under static and dynamic conditions are all studied.The results show that for static condition,the relative errors of crack length and dip angle are 2.5% and 3.4% respectively,and for dynamic condition,those errors are 6.9% and 3.0% respectively.Therefore,the inversion identification effect of the new method is suitable.

       

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