Evaluation of structural integrity of steel components by non-destructive magnetic methods

Magnetic non-destructive methods utilising the Magnetic Flux Leakage (MFL) and Magnetic Barkhausen Noise (MBN) phenomena are widely used in the evaluation of the structural integrity of steel components. The MFL method is effectively applied for in-service flaw monitoring of oil and gas pipelines, fuel storage tank floors and rails; whereas the MBN method, due to high sensitivity of Barkhausen emission to residual and applied stress, has become one of the most popular NDE tools for investigating this condition of steels. Despite the affirming research and successful applications, which helped these methods to gain acceptance as a viable non-destructive tools, there is still a requirement for establishing a quantitative links between magnetic and mechanical properties of steel which would enable their further understanding and optimisation. In this thesis the applications of MFL and MBN methods for flaw and stress detection are analysed via analytical and numerical modelling. A new model relating the MBN amplitude and stress for materials having different magnetostrictive behaviour under load is proposed and validated in the quantitative stress evaluation of different grades of steel. Moreover, a new method for determining depth dependence of stress from measured magnetic Barkhausen signals is presented. A complete set of newly derived equations describing the detected Barkhausen signals in terms of the actual emissions that are generated inside the material and how these appear when they propagate to the surface is given. The results from finite element modelling of magnetic flux leakage signals above unflawed and flawed rails energised in various directions are presented. These results enabled to identify the most effective current injection procedure and optimise the probability of transverse flaw detection in the rail inspection. The agreement between modelled and measured electromagnetic signals indicating presence of transverse rail defects has been justified

Impact of clinical phenotypes on management and outcomes in European atrial fibrillation patients: a report from the ESC-EHRA EURObservational Research Programme in AF (EORP-AF) General Long-Term Registry

Background: Epidemiological studies in atrial fibrillation (AF) illustrate that clinical complexity increase the risk of major adverse outcomes. We aimed to describe European AF patients\u2019 clinical phenotypes and analyse the differential clinical course. Methods: We performed a hierarchical cluster analysis based on Ward\u2019s Method and Squared Euclidean Distance using 22 clinical binary variables, identifying the optimal number of clusters. We investigated differences in clinical management, use of healthcare resources and outcomes in a cohort of European AF patients from a Europe-wide observational registry. Results: A total of 9363 were available for this analysis. We identified three clusters: Cluster 1 (n = 3634; 38.8%) characterized by older patients and prevalent non-cardiac comorbidities; Cluster 2 (n = 2774; 29.6%) characterized by younger patients with low prevalence of comorbidities; Cluster 3 (n = 2955;31.6%) characterized by patients\u2019 prevalent cardiovascular risk factors/comorbidities. Over a mean follow-up of 22.5 months, Cluster 3 had the highest rate of cardiovascular events, all-cause death, and the composite outcome (combining the previous two) compared to Cluster 1 and Cluster 2 (all P <.001). An adjusted Cox regression showed that compared to Cluster 2, Cluster 3 (hazard ratio (HR) 2.87, 95% confidence interval (CI) 2.27\u20133.62; HR 3.42, 95%CI 2.72\u20134.31; HR 2.79, 95%CI 2.32\u20133.35), and Cluster 1 (HR 1.88, 95%CI 1.48\u20132.38; HR 2.50, 95%CI 1.98\u20133.15; HR 2.09, 95%CI 1.74\u20132.51) reported a higher risk for the three outcomes respectively. Conclusions: In European AF patients, three main clusters were identified, differentiated by differential presence of comorbidities. Both non-cardiac and cardiac comorbidities clusters were found to be associated with an increased risk of major adverse outcomes