黄土地区螺杆灌注桩复合地基承载特性与沉降分析  

Bearing Characteristics and Settlement Analysis of Screw Cast-in-place Pile Composite Foundation in Loess Region

作　　者：马志勇 MA Zhiyong(Guoneng Baorixile Energy Co.Ltd.,Hulunbuir Inner Mongolia 021000,China)

机构地区：[1]国能宝日希勒能源有限公司,内蒙古呼伦贝尔021000

出　　处：《铁道建筑》2022年第7期133-137,共5页Railway Engineering

摘　　要：结合实际工程及单桩承载力静荷载试验,基于桩身荷载传递规律,采用数值模拟分析不同荷载作用下螺杆灌注桩的承载特性及作用机理,采用不同沉降预测方法对不同工况沉降数据进行分析和预测,为螺杆灌注桩在西北黄土地区的应用提供技术支持。结果表明:随着荷载增加,螺纹段桩侧塑性区随桩身深度逐渐下移,直至桩端,在距离桩侧约3~4倍螺牙长度出现塑性贯通现象;对于静态预测方法,采用指数模型、双曲线模型、对数模型均具有较高的相关系数,而采用泊松模型时相关系数较低;对于动态预测方法,非等距灰色模型和BP神经网络模型均具有较高的相关系数。Combined with the actual project and the static load test of single pile bearing capacity,based on the load transfer regularities of pile body,the bearing characteristics and action mechanism of screw cast-in-place pile under different loads were analyzed by numerical simulation. Different settlement prediction methods were used to analyze and predict the settlement data under different working conditions,so as to provide technical support for the application of screw cast-in-place pile in northwest loess region. The results show that with the increase of load,the plastic zone on the side of the screw section of the pile gradually moves down with the depth of the pile body until the end of the pile,and plastic penetration occurs at about 3 ~ 4 times the length of the screw tooth from the side of the pile. For static prediction method,the exponential model,hyperbolic model and logarithmic model all have higher correlation coefficient,while the Poisson model has lower correlation coefficient. For dynamic prediction methods,non-equidistant grey model and BP neural network model all have higher correlation coefficients.

关 键 词：黄土地区 高速铁路路基 螺杆灌注桩 承载特性 沉降预测模型 

分 类 号：TU473.11[建筑科学—结构工程]