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Message from 2014 Best Paper Award Winners

Lloret-Cabot, M., G.A. Fenton, and M.A. Hicks. 2014. “On the Estimation of Scale of Fluctuation in Geostatistics.” Georisk Vol. 8, No. 2, pp. 129–140. Major current and future challenges in geotechnical engineering are increasingly associated with the need to identify, understand and assess uncertainties in geomaterials (rocks and soils). The quantification of these uncertainties is crucial to properly modelling the geotechnical risk of engineering infrastructures during their construction and lifetime. Examples of such engineered geotechnical systems are often strategic and frequently linked to socio-economic development and, as a consequence, are progressively more global, not only onshore but also offshore. An essential component of the acceptable performance of such infrastructures is the performance of the ground/rock supporting (or surrounding, in the case of underground structures) them – in other words, the ground is the foundation of all civil engineering structures. Uncertainty in the ground can (and should) be reduced, not only by making more efficient use of all accessible on-site information but also by employing the powerful computational techniques/resources currently available. This paper provides a framework to complement existing resources and improve their ability to rigorously assess the reliability of geotechnical structures. It is well known that soil properties vary spatially as a result of natural weathering, geological processes, or engineering construction and, hence, consistent incorporation of such inherent variability in soil deposits becomes a powerful tool to better assess the reliability of geotechnical solutions. More specifically, the correlation length θ (or scale of fluctuation) is a key parameter in the correlation model used to represent the spatial variability of a site through a random field. It is therefore of fundamental importance to accurately estimate θ in order to best model the actual soil heterogeneity. In the light of this, two methodologies are investigated in this paper to assess their abilities to estimate the vertical and horizontal correlation lengths of a particular site using in situ Cone Penetration Test (CPT) data. The first method belongs to the family of more traditional approaches, which are based on best fitting a theoretical correlation model to available CPT data. The second method involves a new strategy which combines information from conditional random fields with the traditional approach. Both methods are applied to a case study involving the estimation of θ at three two-dimensional sections across a site and the results obtained show general agreement between the two methods, suggesting a similar level of accuracy between the new and traditional approaches. However, in order to further assess the relative accuracy of estimates provided by each method, a second numerical analysis is proposed. The results of this second analysis confirm the general consistency observed in the case study calculations, particularly in the vertical direction where a large amount of data are available. Interestingly, for the horizontal direction, where data are typically scarce, some additional improvement in terms of relative error is obtained with the new approach. Finally, we are delighted to have the opportunity to thank the editorial team of the journal Georisk for selecting our article for the Best Paper Award for 2014. This recognition gives us confidence that our work is of practical value and provides us with incentive to continue extending the areas of investigation described in the paper. Congratulations to the editorial team and Taylor & Francis for making Georisk the peer‐reviewed journal of choice for quality papers that aim at more realistic modelling and improved understanding of risk in geomaterials.