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邓肯-张E-B模型参数对软土路堤沉降计算结果的影响 总被引:11,自引:2,他引:9
有限单元法是计算路堤沉降常见的数值计算方法,其土体模型参数的准确性是计算结果可靠性高的保证。邓肯-张E-B模型是岩土工程分析计算中常用的一种非线性弹性模型。本文针对模型参数敏感性进行大量非线性有限元计算,得到了各参数与路堤沉降和侧向位移之间的关系,确定了该模型中影响软基路堤沉降和侧向变形的主要参数。 相似文献
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高填石路堤蠕变本构模型及其参数反演分析与应用 总被引:1,自引:0,他引:1
结合高填石路堤工后沉降变形机理与工程特点,基于工程实测数据,提出了高填石路堤工后沉降蠕变变形的双曲线型三参数本构模型,并引进遗传算法与有限元分析理论,建立了该模型参数的反演分析方法。在此基础上,利用蠕变有限元分析手段,深入探讨了高填石路堤工后沉降的分析计算方法,并开发了相应的分析计算软件。结合某高填石路堤工程实践,探讨了高填石路堤双曲线三参数蠕变本构模型和高填石路堤工后沉降计算的应用方法。工程实例分析表明,提出的本构模型及其工后沉降计算方法简单,可以满足工程要求,初步建立了一种新的高填石路堤工后沉降计算方法。 相似文献
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路堤下软土地基侧向位移与沉降关系分析研究 总被引:1,自引:0,他引:1
总结了软土地基下侧向位移的研究现状,从路堤中最大侧向位移和路中沉降之间的比例关系出发进行了分析研究。利用有限单元法,建立了路堤下软土地基的计算模型。计算结果表明,在路堤填筑期间最大侧向位移和路中沉降的增量大致相等,而在固结期两者的比例关系在0.14左右。不同的加载方式在数值上也有所不同。计算结果对路堤下地基侧向变形的计算分析具有一定的指导作用。 相似文献
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路堤下复合地基“三等沉区模型” 总被引:1,自引:0,他引:1
路堤下复合地基桩顶沉降小于桩间土沉降,桩体上部为负摩擦力,因此不能采用常规复合地基理论分析受力和变形。试验和数值分析表明,路堤下复合地基的路堤、桩身、下卧层范围内均存在一个等沉区,等沉区内同一水平面上不同点的沉降相同的区域。据此提出了“三等沉区模型”,该模型不但地基与桩体参数对复合地基的影响,而且可以考虑路堤高度、下卧层厚度、强度等参数对复合地基的影响。实测和数值模拟表明该模型是合理可行的。 相似文献
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试论连云港海相软土路堤沉降规律 总被引:5,自引:0,他引:5
根据连云港至徐州高速公路连云港段60多个断面的现场实测沉降资料,分析了在路堤荷载作用下连云港海相软土的沉降和固结规律。实测数据表明,在路堤荷载作用下连云港海相软土地基的沉降曲线符合双曲线形式,故可采用双曲线法预测最终沉降。由此可以分析在不同施工期的地基沉降和固结特性,得到不同地基处理条件下路堤填筑期和预压期地基平均固结度与施工时间的关系。分析亦表明,粉喷桩加固能加速地基的固结速率。最后,针对沉降和固结理论计算中计算参数的难以合理确定的局限性,对现场实测沉降数据采用数理统计方法,提出了适用于连云港地区海相软土路堤沉降和固结估算经验公式。 相似文献
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高填方地基的填方体量大、填方高度高的特征决定了高填方地基具有较大的工后沉降,可能会影响工程的实际应用,研究高填方地基工后沉降的计算方法对于控制工后沉降具有重要意义。蠕变沉降是高填方地基工后沉降的重要组成部分,试验表明,土的蠕变变形主要受时间和应力历史等因素影响。基于考虑时间效应的统一硬化模型,以瞬时正常压缩线为参考线,引入弹性瞬时压缩线,建立了可以同时考虑时间和应力历史影响的高填方地基一维蠕变沉降计算方法,并对室内试验进行了计算,计算结果与试验结果基本一致。所建计算方法所用参数除一个参数外其余都为常见参数,而新参数可以通过常规试验确定,该计算方法便于工程应用。 相似文献
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Correction of soil parameters in calculation of embankment settlement using a BP network back-analysis model 总被引:3,自引:0,他引:3
Finite element method (FEM) have been widely used for the calculation of settlement of embankment on soft soils in the last decade. However, due to the complexity of construction, spatial inhomogeneity of soils, as well as sensitivity of numerical results to the variation of soil parameters, large discrepancy typically exists between numerical outputs and field observations. This paper presents a novel method, combining FEM and an improved back-propagation (BP) neural network, for correction of soil parameters in numerical prediction of embankment settlement. Duncan–Chang hyperbolic soil model is adopted with the sensitivity of eight constitutive parameters numerically investigated. The soil parameters with large sensitivity are identified, and together with the representative settlements, are used for the training of the improved BP neural network which, once established, generates correction factors of soil parameters for subsequent more accurate FEM forward predictions. It is demonstrated that the proposed numerical back-analysis framework is very efficient in practical engineering applications to calculate highway settlement. 相似文献
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Tenfold cross validation artificial neural network modeling of the settlement behavior of a stone column under a highway embankment 总被引:1,自引:1,他引:0
Zamri Chik Qasim A. Aljanabi Anuar Kasa Mohd Raihan Taha 《Arabian Journal of Geosciences》2014,7(11):4877-4887
Construction of embankments in engineering structures on soft clay soils normally encounters problems related to excessive settlement issues. The conventional methods are inadequate to analyze and predict the surface settlement when the necessary parameters are difficult to determine in the field and in the laboratory. In this study, artificial neural network systems (ANNs) were used to predict settlement under embankment load using soft soil properties together with various geometric parameters as input for each stone column (SC) arrangement and embankment condition. Data from a highway project called Lebuhraya Pantai Timur2 in Terengganu, Malaysia, were investigated. The FEM package of Plaxis v8 program analysis was utilized. The actual angle of internal friction, spacing between SC, diameter of SC, length of SC, and height of embankment were used as the input parameters, and the settlement was used as the main output. Non cross validation (NCV) and tenfold cross validation (TFCV) were used to build the ANN model. The results of the TFCV model were more accurate than those of the NCV model. Comparisons made with the predictions of the Priebe model showed that the proposed TFCV model could provide better predictions than conventional methods. 相似文献
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软土路基沉降变权重组合S型曲线预测方法研究 总被引:11,自引:0,他引:11
通过对软土路基沉降发展规律及其沉降曲线特点进行深入研究,在S型单项预测模型基础上,基于5种S型增长曲线模型,引进组合预测的思想,重点探讨了软土路基沉降发展的预测方法与理论,并建立了软土路基沉降预测的变权重组合S型增长模型,通过数学规划方法求解,从而可根据有限的实测沉降观测数据预测软土路基沉降发展过程。工程实例分析表明,利用该模型与方法得到的预测曲线与实测曲线吻合良好,能够满足工程要求,此外,变权重组合预测模型比其它单项模型具有明显的优越性,为软土路基沉降发展预测提供了一种有效而实用的方法。 相似文献