The quality of in situ data is key to calculating resistance factor of bored piles. However, it is difficult to summarize accuracy data due to various uncertainties in engineering. This paper employs the Bayesian method and mathematical statistics theory to put forward an estimation method for updating in situ data. A testing database (33 tests in noncohesive soils and 53 tests in cohesive soils) of bored piles is summarized. The model factor of bored piles is quantified as the ratio of the measured capacity to the calculated capacity. The proposed method is used to classify summarized data into three categories, which are “good data,” “general data,” and “bad data.” The “bad data” are discarded because of bad contribution to calculation, and Bayesian theory is incorporated into updating the model factor statistics. Three methods are used to calculate the reliability index and resistance factor of bored piles, and the results show that the reliability index and resistance factor are sensitive to the quality of data. Finally, the available values of resistance factors are proposed based on resistance factor design for bridge design specification, which can offer references to revision relevant specifications. The proposed method can be used to update other geotechnical data.

中文翻译：

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基于载荷试验数据库的钻孔桩阻力系数贝叶斯估计

现场数据的质量是计算钻孔桩阻力系数的关键。然而，由于工程中的各种不确定性，很难总结精度数据。本文运用贝叶斯方法和数理统计理论，提出了一种现场数据更新的估计方法。总结了钻孔桩的测试数据库（非粘性土壤中的33个测试和粘性土壤中的53个测试）。钻孔桩的模型因子量化为测得的承载力与计算的承载力之比。所提出的方法用于将汇总数据分为三类，即“好数据”，“一般数据”和“不良数据”。由于对计算的不良贡献而将“不良数据”丢弃，并且将贝叶斯理论纳入了更新模型因子统计的过程。通过三种方法计算了钻孔桩的可靠性指标和抗力系数，结果表明，可靠性指标和抗力系数对数据质量敏感。最后，基于桥梁设计规范中的电阻系数设计提出了电阻系数的可用值，可以为修订相关规范提供参考。所提出的方法可用于更新其他岩土数据。