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Pile in the Unsaturated Cracked Substrate with Reliability Assessment based on Neural Networks

机译:基于神经网络的不饱和裂纹基体中桩的可靠性评估

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In this study, we present reliability assessments for a monopile socketed into a vertical fissured unsaturated substrate correlated with the degree of saturation. The pile was loaded by concentrated lateral force in a three-dimensional space. Procedures were prepared in the numerical analysis software FLAC 3D, fast lagrangian analysis of continua. FISH, a scripting language embedded within FLAC, was used to control the depth of cracks in unsaturated soil and manage a significant number of the calculations. The presented approach expands knowledge about piles loaded laterally and also the considerable influence of environmental changes. In the reliability part of the study, the excessive horizontal displacement of the pile head was examined as an implicit function. The analytical model of vertical water flux in the partially saturated soil was applied in connection with the iterative solution of the cracked depth of the substrate. The suction profile was estimated for a layer above the groundwater level. An important aspect of this paper is that the reliability analyses were prepared for this task in complex environmental conditions and with a horizontal load. All limit state functions were approximated following the response surface methodology, which was defined by neural networks based on modified perceptrons and was compared with well-known polynomials functions.
机译:在这项研究中,我们提出了插入垂直裂隙不饱和基底中的单桩与饱和度相关的可靠性评估。通过集中的横向力在三维空间中加载桩。程序在数值分析软件FLAC 3D中进行,连续性的快速拉格朗日分析。 FISH是FLAC中嵌入的一种脚本语言,用于控制非饱和土壤中裂缝的深度并管理大量计算。提出的方法扩展了有关横向加载的桩的知识,以及环境变化的巨大影响。在研究的可靠性部分中,桩头的水平位移过大被视为隐函数。结合部分裂缝深度的迭代解法,应用了部分饱和土壤中垂直水通量的解析模型。估算出地下水位以上一层的吸水曲线。本文的一个重要方面是,在复杂的环境条件下和水平载荷下,为此任务准备了可靠性分析。遵循响应面方法对所有极限状态函数进行近似,该方法由基于修改后的感知器的神经网络定义,并与众所周知的多项式函数进行比较。

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