Fig. 1. Probability of failure in reliability-based design
Fig. 2. Comparison of estimated and observed ultimate bearing capacity
Fig. 3. Relationship between the predicted ultimate bearing capacity and the resistance bias
Fig. 4. Cumulative distribution of sample resistance biases and fitted normal distribution
Fig. 5. P-P plot for diagnosing normal distribution of sample resistance biases
Fig. 6. Probability density function of total resistance according to COVsu of 10, 20, and 30%
Fig. 7. Relationships between parameters for probability distribution of ln(λR) and COVTotal
Table 1. Summary statistics for proposed MLR
Table 2. Performance of MLR model by Bong and Kim (2017)
Table 3. Summary of results of Chi-square test
Table 4. Statistic properties of total resistance bias
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