Minding the geotechnical data gap:appraisal of the variability of key soil parameters for slope stability modelling in Saint Lucia

Identification of failure thresholds and critical uncertainties associated with slope stability often requires the specification of geotechnical parameter values for input into a physically-based model. The variation of these parameters (including mechanical soil properties such as effective friction angle and cohesion) can have a significant impact on the computed factor of safety. These uncertainties arise from natural variations in soils, measurement techniques, and lack of reliable information. Researchers may use statistical analysis coupled with numerical simulation to determine possible ranges of slope factors of safety and the relative influence of geotechnical and other parameters, such as topsoil depth and rainfall. This study investigates the variation of geotechnical parameters observed on the island of Saint Lucia in the Eastern Caribbean. A database of particle size distributions, in-situ moisture contents, Atterberg and direct shear box test results is compiled from 91 samples of tropical soils in Saint Lucia. A study of various probability distributions shows that the Weibull distribution may be favoured for the effective friction angle of the Saint Lucian soils considered based on the Akaike information criterion, employed as an estimator of the relative quality of statistical models dealing with the trade-off between goodness-of-fit and simplicity of the model

Digital methods for ethnography: analytical concepts for ethnographers exploring social media environments

The aim of this article is to introduce some analytical concepts suitable for ethnographers dealing with social media environments. As a result of the growth of social media, the Internet structure has become a very complex, fluid, and fragmented space. Within this space, it is not always possible to consider the 'classical' online community as the privileged field site for the ethnographer, in which s/he immerses him/herself. Differently, taking inspiration from some methodological principles of the Digital Methods paradigm, I suggest that the main task for the ethnographer moving across social media environments should not be exclusively that of identifying an online community to delve into but of mapping the practices through which Internet users and digital devices structure social formations around a focal object (e.g., a brand). In order to support the ethnographer in the mapping of social formations within social media environments, I propose five analytical concepts: community, public, crowd, self-presentation as a tool, and user as a device

Railway bridge structural health monitoring and fault detection: state-of-the-art methods and future challenges

Railway importance in the transportation industry is increasing continuously, due to the growing demand of both passenger travel and transportation of goods. However, more than 35% of the 300,000 railway bridges across Europe are over 100-years old, and their reliability directly impacts the reliability of the railway network. This increased demand may lead to higher risk associated with their unexpected failures, resulting safety hazards to passengers and increased whole life cycle cost of the asset. Consequently, one of the most important aspects of evaluation of the reliability of the overall railway transport system is bridge structural health monitoring, which can monitor the health state of the bridge by allowing an early detection of failures. Therefore, a fast, safe and cost-effective recovery of the optimal health state of the bridge, where the levels of element degradation or failure are maintained efficiently, can be achieved. In this article, after an introduction to the desired features of structural health monitoring, a review of the most commonly adopted bridge fault detection methods is presented. Mainly, the analysis focuses on model-based finite element updating strategies, non-model-based (data-driven) fault detection methods, such as artificial neural network, and Bayesian belief network–based structural health monitoring methods. A comparative study, which aims to discuss and compare the performance of the reviewed types of structural health monitoring methods, is then presented by analysing a short-span steel structure of a railway bridge. Opportunities and future challenges of the fault detection methods of railway bridges are highlighted