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Estimating spatial correlation structures based on CPT data
Abstract:Spatial correlation structures are usually used while modelling inherent uncertainty associated with soil properties. To retrieve this information a sufficient number of measurements and equal intervals between measurements or samples are always required. However, in practice, it is not usual to conduct site investigation in that way subject to a limited budget. Therefore, it is of interest to understand the possible bias created by using samples with unequal intervals. This research focuses on estimating the vertical spatial correlation structures of cone penetration tests (CPT) data conducted at a liquefaction site in Taiwan. The appropriate fitting range used in calibrating the correlation model is also discussed. The results show that cone tip resistance has larger correlation distances than that of sleeve friction. The estimated correlation distances of the CPT profiles are similar while using an equal sampling interval within a certain fitting range (denoted as the critical interval of measurements in this research). The results indicate that the effect of using different curve-fitting ranges is relatively insignificant for correlation distances of sleeve friction, whereas the correlation distances of cone tip resistance are more sensitive to different curve-fitting ranges. Moreover, the mean values of correlation distances are more constant for the equal sampling interval cases than for the unequal interval cases.
Keywords:spatial correlation structure  random field  CPT  field test
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