Bored pile design in stiff clay II:Mechanisms and uncertainty

The soil mechanics related to pile design in clay has been the subject of substantial engineering research. In a companion paper, various codes of practice were reviewed showing the effect on pile capacity of the different global factors of safety that emerge from the various partial factor combinations for the ultimate limit state. Factors of safety are generally specified based on the opinions of experts. In this paper an assessment will be made of various objective procedures that can be used to reduce uncertainty in the design process, especially regarding the adoption of a pile resistance model and the selection of a soil strength profile as part of a ultimate limit state check, and the estimation of pile head settlement in the context of a serviceability limit state check. It is shown that both total stress and effective stress calculation methods are applicable in London Clay. Estimates of settlement using a non-linear soil stress–strain relationship are made and compared with published data. It is shown that the compression of the concrete dominates the settlement of long piles. Given the low settlements observed, recommendations are made for a reduction in standard factors of safety for bored pile design in stiff clays. </jats:p

The plastic limit of clays

The plastic limit of soils was first described by Atterberg in 1911. The thread-rolling test was standardised at the US Public Roads Bureau in the 1920s and 1930s, and has subsequently become one of the standard tests of soil mechanics. This paper reviews the original definitions of plastic limit as proposed by Atterberg, and proposes that the brittle failure observed in the plastic limit test is caused by either air entry or cavitation in the clay. Critical state soil mechanics is used to show that the observed range of undrained shear strengths of soils at plastic limit is consistent with this hypothesis. The fallacy that strength at plastic limit is a constant is highlighted, and the implications for geotechnical practice are discussed. </jats:p

Laboratory measurement of strength mobilisation in kaolin: link to stress history

This letter presents data from triaxial tests conducted as part of a research programme into the stress–strain behaviour of clays and silts at Cambridge University. To support findings from earlier research using databases of soil tests, eighteen CIU triaxial tests on speswhite kaolin were performed to confirm an assumed link between mobilisation strain (γM = 2) and overconsolidation ratio (OCR). In the moderate shear stress range (0·2cu to 0·8cu) the test data are essentially linear on log–log plots. Both the slopes and intercepts of these lines are simple functions of OCR. </jats:p

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