无粘性土中横向荷载长桩的数值分析

IF 2 4区 计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS
Ayman Abd-Elhamed, M. Fathy, K. M. Abdelgaber
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引用次数: 1

摘要

桩承受水平荷载的能力是一个主要的设计问题。目前的研究工作旨在采用温克勒基础梁模型的概念,对横向荷载下桩的响应进行数值研究。推导了弹性地基上横向荷载桩的控制微分方程。基于legende - galerkin法和四阶和五阶龙格-库塔公式,求解了路基反力模量随深度线性变化的均质砂土中长桩的挠曲方程。作为世界领先的计算软件之一,Mathematica被用于解决方案的实施。所提出的数值方法提供了整个桩长在侧向荷载作用下的响应。所采用的数值方法与先前发表的实验和分析结果进行了验证,显示出对横向荷载桩响应的更准确估计。因此,所提出的方法既能保持数学上的简单性,又能保持与实验结果相当的精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Numerical Analysis of Laterally Loaded Long Piles in Cohesionless Soil
: The capability of piles to withstand horizontal loads is a major design issue. The current research work aims to investigate numerically the responses of laterally loaded piles at working load employing the concept of a beam-on-Winkler-foundation model. The governing differential equation for a laterally loaded pile on elastic subgrade is derived. Based on Legendre-Galerkin method and Runge-Kutta formulas of order four and five, the flexural equation of long piles embedded in homogeneous sandy soils with modulus of subgrade reaction linearly variable with depth is solved for both free- and fixed-headed piles. Mathematica, as one of the world’s leading computational software, was employed for the implementation of solutions. The proposed numerical techniques provide the responses for the entire pile length under the applied lateral load. The utilized numerical approaches are validated against experimental and analytical results of previously published works showing a more accurate estimation of the response of laterally loaded piles. Therefore, the proposed approaches can maintain both mathematical simplicity and comparable accuracy with the experimental results.
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来源期刊
Cmc-computers Materials & Continua
Cmc-computers Materials & Continua 工程技术-材料科学:综合
CiteScore
5.30
自引率
19.40%
发文量
345
审稿时长
1 months
期刊介绍: This journal publishes original research papers in the areas of computer networks, artificial intelligence, big data management, software engineering, multimedia, cyber security, internet of things, materials genome, integrated materials science, data analysis, modeling, and engineering of designing and manufacturing of modern functional and multifunctional materials. Novel high performance computing methods, big data analysis, and artificial intelligence that advance material technologies are especially welcome.
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