Texas cone penetrometer foundation design method: Qualitative and quantitative assessment

R. Moghaddam, P. Jayawickrama, W. Lawson, J. Surles, Hoyoung Seo
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引用次数: 4

Abstract

This paper presents a qualitative and quantitative evaluation of the predictive validity of the Texas Cone Penetration (TCP) foundation design method. Allowable loads were determined using both strength-based and serviceability-based models and were further compared to predicted allowable loads using the TCP foundation design charts. The predictive validity of the TCP method was evaluated using a final dataset consisting of 60 full-scale load tests comprising 33 driven piles and 27 drilled shafts, all founded in soil materials. The qualitative evaluation consisted of a visual assessment of the scatterplot compared to the equal prediction line. In the case of the quantitative assessment, regression models were fitted to the dataset, and the accuracy and precision of the models were evaluated based on statistical analyses. Results show that the predictive validity of the TCP-based foundation design method is accurate with low precision. The qualitative evaluation of the strength-based data showed slight data scatter around the equal prediction line. In the case of the serviceability-based model, data points indicated the same slight scatter with major concentration above the equal prediction line in the conservative prediction region. With a p-value <.05, results from the quantitative analyses showed a statistically significant relationship between the proposed models and the allowable loads predicted using the TCP. The R-square value for the models was between 0.776 and 0.814.
德州锥贯仪基础设计方法:定性与定量评价
本文对得克萨斯锥贯贯(TCP)基础设计方法的预测有效性进行了定性和定量评价。使用基于强度和可使用性的模型确定许用载荷,并进一步与使用TCP基础设计图的预测许用载荷进行比较。TCP方法的预测有效性使用最终数据集进行评估,该数据集由60个全尺寸荷载测试组成,包括33个打入桩和27个钻孔井,全部建立在土壤材料中。定性评价包括对散点图与等值预测线的目视评价。在定量评价方面,对数据集进行回归模型拟合,并通过统计分析对模型的准确性和精密度进行评价。结果表明,基于tcp的基础设计方法预测精度较低,预测有效性较好。对基于强度的数据进行定性评价显示,在相等的预测线周围有轻微的数据分散。在基于可服务性的模型中,数据点在保守预测区域内表现出同样的轻微分散,但主要集中在等预测线上。p值<。2005年,定量分析的结果显示,所提出的模型与使用TCP预测的允许负荷之间存在统计学上显著的关系。模型的r平方值在0.776 ~ 0.814之间。
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