Comparison of different calculation methods for estimating scale of fluctuation of design soil properties based on indirect measurement data

• Published in: IOP conference series. Earth and environmental science 2019-09, Vol.304 (5), p.52102
• Main Authors: Tian, Mi, Sheng, Xiaotao, Li, Lihua, Zhang, Fan, Xiao, Henglin
• Format: Article
• Language: English
• Subjects: Autocorrelation functions; Bayesian analysis; Cone penetration tests; Design; Empirical analysis; Estimation; Fields (mathematics); Mathematical models; Mean; Penetration tests; Regression analysis; Regression models; Reliability analysis; Soil properties; Soil testing; Soils; Statistical analysis; Transformations; Uncertainty
• ISSN: 1755-1307; 1755-1315
• DOI: 10.1088/1755-1315/304/5/052102

Determination of scale of fluctuation (SOF) is a necessary prerequisite for describing the inherent spatial variability (ISV) of design soil properties (i.e., effective friction angle φ') using a stationary random field in geotechnical reliability analysis. It is very important to select an appropriate method to enable an accurate estimate of SOF. However, it has been a challenging task due to the fact that the true SOF is actually unknown. In addition, when the number of direct test data of design soil properties are too limited to generate meaningful statistics, the design soil properties are indirectly estimated through transformation models which involve transformation uncertainty. This paper investigates the validity and accuracy of three commonly-used calculation methods (e.g., Bayesian approaches, mean average method, and fitting sample autocorrelation function (ACF) method) for estimating SOF of φ' using indirect cone penetration test (CPT) data. It is found that Bayesian approaches provide more accurate estimates of λ of φ' because it takes the transformation uncertainty from empirical regression models into reasonable consideration. The mean average method and fitting sample ACF method underestimate λ of φ'.