Deformation and failure of welded steels used in offshore constructions

Hydrocarbons are the most common form of energy used to date. The activities involving exploration and exploitation of large oil and gas fields are constantly in operation and have extended to such hostile environments as the North Sea. This enforces much greater demands on the materials which are used, and the need for enhancing the endurance of the existing ones which must continue parallel to the explorations. Due to their ease in fabrication, relatively high mechanical properties and low costs, steels are the most widely favoured material for the construction of offshore platforms. The most critical part of an offshore structure prone to failure are the welded nodal joints, particulary those which are used within the vicinity of the splash zones. This is an area of high complex stress concentrations, varying mechanical and metallurgical properties in addition to severe North Sea environmental conditions. The main are of this work has been concerned with the durability studies of this type of steel, based on the concept of the worst case analysis, consisting of combinations of welds of varying qualities, various degrees of stress concentrations and the environmental conditions of stress corrosion and hydrogen embrittlement. The experiments have been designed to reveal significance of defects as sites of crack initiation in the welded steels and the extent to which stress corrosion and hydrogen embrittlement will limit their durability. This has been done for various heat treatments and in some experiments deformation has been forced through the welded zone of the specimens to reveal the mechanical properties of the welds themselves to provide data for finite element simulations. A comparison of the results of these simulations with the actual deformation and fracture behaviour has been done to reveal the extent to which both mechanical and metallurgical factors control behaviour of the steels in the hostile environments of high stress, corrosion, and hydrogen embrittlement at their surface.

Understanding data collection behaviour of mental health practitioners

Failure to detect patients at risk of attempting suicide can result in tragic consequences. Identifying risks earlier and more accurately helps prevent serious incidents occurring and is the objective of the GRiST clinical decision support system (CDSS). One of the problems it faces is high variability in the type and quantity of data submitted for patients, who are assessed in multiple contexts along the care pathway. Although GRiST identifies up to 138 patient cues to collect, only about half of them are relevant for any one patient and their roles may not be for risk evaluation but more for risk management. This paper explores the data collection behaviour of clinicians using GRiST to see whether it can elucidate which variables are important for risk evaluations and when. The GRiST CDSS is based on a cognitive model of human expertise manifested by a sophisticated hierarchical knowledge structure or tree. This structure is used by the GRiST interface to provide top-down controlled access to the patient data. Our research explores relationships between the answers given to these higher-level 'branch' questions to see whether they can help direct assessors to the most important data, depending on the patient profile and assessment context. The outcome is a model for dynamic data collection driven by the knowledge hierarchy. It has potential for improving other clinical decision support systems operating in domains with high dimensional data that are only partially collected and in a variety of combinations.