摘要
在岩土工程设计中,准确地衡量土层参数的空间变异性决定了设计结构的可靠性和经济性,土参数的自相关距离是反映其空间变异性的一个重要指标。目前对于自相关距离与结构可靠性之间的关系的研究还很不完善。本文以单桩可靠性设计为例,选取工程场地的静力触探试验数据,引入随机场理论描述侧摩阻力和锥尖阻力的分布特征,利用递推平均法计算各地基土层侧摩阻力和锥尖阻力的自相关距离,在描述土层侧摩阻力和锥尖阻力的分布特征时考虑了自相关距离的影响,进一步结合蒙特卡洛法计算单桩的可靠指标。结果表明土参数取值考虑自相关距离的影响后,降低了土参数分布的离散程度,计算的单桩可靠指标更高。在保证桩基安全度的前提下,设计结果能够降低工程成本。
In geotechnical engineering design,accurately measuring the spatial variability of soil parameters determines the reliability and economy of the design structure,and the distance of auto-correlation of soil parameters is an important index to reflect its spatial variability.At present,the relationship between auto-correlation distance and structural reliability is not perfect.In this paper,the reliability design of pile foundation is taken as an example.The static cone penetration test(CPT)data of engineering site are chosen,and the random field theory is introduced to describe the distribution characteristics of side friction and tip resistances in the soil layers.The auto-correlation distance of side friction and tip resistances is respectively calculated by the spatial average method.The auto-correlation distance is considered to reflect the distribution of side friction and tip resistances,and the reliability index of pile foundation is calculated by the Monte Carlo method.The results show that the value of soil parameters,taking into account the influence of the auto-correlation distance,the dispersion degree of soil parameter distribution can be reduced,and then the pile foundation reliability index is higher.
作者
刘超
袁颖
左朝晖
宁志杰
周爱红
LIU Chao;YUAN Ying;ZUO Zhaohui;NING Zhijie;ZHOU Aihong(School of Exploration Technology and Engineering, Hebei GEO University, Shijiazhuang, Hebei 050031, China;Hebei Center for Ecological and Environmental Geology Research, Hebei GEO University, Shijiazhuang, Hebei 050031, China)
出处
《水文地质工程地质》
CAS
CSCD
北大核心
2020年第3期122-127,共6页
Hydrogeology & Engineering Geology
基金
国家自然科学基金项目资助(41807231)
河北省自然科学基金项目资助(D2019403182)
河北省高等学校科学技术研究项目资助(QN2019196)。
关键词
自相关距离
递推平均法
蒙特卡洛法
可靠指标
auto-correlation distance
spatial average method
Monte Carlo method
reliability index