1 论文
Published Online: October 21, 2020
Improved method for settlement prediction of shallow foundations on sand 砂上浅层地基沉降预测方法的改进
Abstract: Shallow foundations on sands are typically designed with reference to settlements that are, in turn, difficult to predict with a high level of accuracy. The main uncertainties originate from soil non-linear behaviour and by the fact that methods currently adopted in practice rely on linear elastic approaches and empirical correlations between soil stiffness and in situ test results. To improve the prediction of foundation settlement it is necessary to account, even in relatively simple methods, for the dependence of stiffness on soil density, stress state, strain levels. The main objective of the paper is to provide a contribution in this field. An already formulated elastic approach is revised and modified in order to improve the assessment of soil stiffness, taking into account non linearity due to strain levels and to mechanical non-homogeneity as well, through a definition of the “active zone”, more consistent with the geometry and size of the foundation. The comparison among calculated and measured settlements highlights the feasability of the proposed non-linear method both for small and large deformation levels.
Keywords: Shallow foundations Design methods & aids Granular materials
摘要:砂地上的浅层地基通常是参照沉降量来设计的,而沉降量又很难准确预测。主要的不确定性来源于土壤的非线性行为,以及目前实践中采用的方法依赖于线性弹性方法和土壤刚度与现场试验结果之间的经验相关性。为了提高地基沉降的预测能力,即使在相对简单的方法中,也有必要考虑到刚度对土壤密度、应力状态、应变水平的依赖性。本文的主要目的是在这一领域做出贡献。为了改进对土壤刚度的评估,对已经制定的弹性方法进行了修订和修改,通过对 "活动区 "的定义,考虑到由于应变水平和机械非均匀性引起的非线性,使其更符合地基的几何形状和尺寸。计算沉降量与实测沉降量的比较,凸显了所提出的非线性方法对于小变形和大变形水平的可行性。
关键词:浅层地基 浅层地基 设计方法与辅助手段 颗粒材料
2 相关文献
[1] Settlement of foundations on sand and gravel
[2] A simplified method for prediction of embankment settlement in clays
[3] Settlement Prediction Method Using Observed Settlement Velocity
[4] Settlement Prediction of Stone Column Group
[5] Study on Methods for Predicting the Settlements of Soft Clay Roadbed
[6] Observational Methods for Predicting Embankment Settlement
[7] Shallow Foundation Settlement Quantification: Application of Hybridized Adaptive Neuro-Fuzzy Inference System Model
[8] Comparing Methods for Predicting Immediate Settlement of Shallow Foundations on Cohesive Soils Based on Hypothetical and Real Cases
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