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首页> 外文期刊>Canadian Journal of Civil Engineering >Full-scale pile tests in sand and development of a computer program for predicting load capacity
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Full-scale pile tests in sand and development of a computer program for predicting load capacity

机译:在沙土中进行全面桩桩测试并开发计算机程序以预测负载能力

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摘要

An interactive computer program GLAMPILE has been developed for predicting the static load capacity of single piles formed in any soil profile. A variety of well-known prediction methods have been incorporated into the program, including (i) soil mechanics based formulae; (ii) direct and indirect cone penetration test (CPT) based methods with and without accounting for scale effects of the cone on pile base capacity; and (iii) a new CPT-based method that considers the effects of "critical depth" and shaft resistance distribution, although the method has only been calibrated for relatively short piles. GLAMPILE can cope with different pile types installed with or without a permanent casing. The program has been applied to predict the axial capacities of 11 piles that were recently installed in sand and statically loaded to failure. Results from the soil mechanics procedures indicate increases, on the in situ value, of the earth pressure coefficient by up to 37 percent, which lies within the range 0 percent-100 percent recommended in the literature. The best CPT-based prediction method applied yields a mean (mu) and coefficient of variation (COV) of predicted to measured pile head capacity [P_(uh(p))/P_(uh(m))] of 0.83 and 0.12, respectively. Scale effects are shown to be nominal for the cases analysed. An improved method is recommended, which yields mu = 1.00 and COV = 0.10, implying higher accuracy and reliability compared with the other methods.
机译:已经开发了交互式计算机程序GLAMPILE,用于预测在任何土壤剖面中形成的单桩的静态承载能力。程序中包含了许多众所周知的预测方法,包括:(i)基于土壤力学的公式; (ii)基于直接和间接圆锥渗透试验(CPT)的方法,有无考虑了圆锥对桩基承载力的比例效应; (iii)一种基于CPT的新方法,该方法考虑了“临界深度”和竖井阻力分布的影响,尽管该方法仅针对相对较短的桩进行了校准。 GLAMPILE可以应对安装有或没有永久性套管的不同桩类型。该程序已应用于预测最近安装在沙子中并静态加载至破坏的11个桩的轴向承载力。土壤力学程序的结果表明,就地值而言,土压力系数增加了多达37%,这在文献中建议的范围是0%-100%。应用的最佳基于CPT的预测方法得出的预测桩头容量[P_(uh(p))/ P_(uh(m))]的平均值(mu)和变异系数(COV)为0.83和0.12,分别。对于所分析的案例,规模效应显示为名义上的。建议使用一种改进的方法,该方法产生的mu = 1.00,COV = 0.10,这意味着与其他方法相比,其准确性和可靠性更高。

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