The risk of collapse in abandoned mine sites: the issue of data uncertainty

Ground collapses over abandoned underground mines constitute a new environmental risk in the world. The high risk associated with subsurface voids, together with lack of knowledge of the geometric and geomechanical features of mining areas, makes abandoned underground mines one of the current challenges for countries with a long mining history. In this study, a stability analysis of Montevecchia marl mine is performed in order to validate a general approach that takes into account the poor local information and the variability of the input data. The collapse risk was evaluated through a numerical approach that, starting with some simplifying assumptions, is able to provide an overview of the collapse probability. The nal results is an easy-accessible-transparent summary graph that shows the collapse probability. This approach may be useful for public administrators called upon to manage this environmental risk. The approach tries to simplify this complex problem in order to achieve a roughly risk assessment, but, since it relies on just a small amount of information, any nal user should be aware that a comprehensive and detailed risk scenario can be generated only through more exhaustive investigations

The risk of collapse in abandoned mine sites: the issue of data uncertainty

Ground collapses over abandoned underground mines constitute a new environmental risk in the world. The high risk associated with subsurface voids, together with lack of knowledge of the geometric and geomechanical features of mining areas, makes abandoned underground mines one of the current challenges for countries with a long mining history. In this study, a stability analysis of Montevecchia marl mine is performed in order to validate a general approach that takes into account the poor local information and the variability of the input data. The collapse risk was evaluated through a numerical approach that, starting with some simplifying assumptions, is able to provide an overview of the collapse probability. The nal results is an easy-accessible-transparent summary graph that shows the collapse probability. This approach may be useful for public administrators called upon to manage this environmental risk. The approach tries to simplify this complex problem in order to achieve a roughly risk assessment, but, since it relies on just a small amount of information, any nal user should be aware that a comprehensive and detailed risk scenario can be generated only through more exhaustive investigations

Algorithms for Vision-Based Quality Control of Circularly Symmetric Components

Quality inspection in the industrial production field is experiencing a strong technological development that benefits from the combination of vision-based techniques with artificial intelligence algorithms. This paper initially addresses the problem of defect identification for circularly symmetric mechanical components, characterized by the presence of periodic elements. In the specific case of knurled washers, we compare the performances of a standard algorithm for the analysis of grey-scale image with a Deep Learning (DL) approach. The standard algorithm is based on the extraction of pseudo-signals derived from the conversion of the grey scale image of concentric annuli. In the DL approach, the component inspection is shifted from the entire sample to specific areas repeated along the object profile where the defect may occur. The standard algorithm provides better results in terms of accuracy and computational time with respect to the DL approach. Nevertheless, DL reaches accuracy higher than 99% when performance is evaluated targeting the identification of damaged teeth. The possibility of extending the methods and the results to other circularly symmetrical components is analyzed and discussed

Generation of a Design Flood-Event Scenario for a Mountain River with Intense Sediment Transport

International directives encourage the incorporation of sediment transport analyses into flood risk assessment, in recognition of the significant role played by sediment in flood hazard. However, examples of risk analysis frameworks incorporating the effect of sediment transport are still not widespread in the literature, resulting in a lack of clear guidelines. This manuscript considers a study site in the Italian Alps and presents a hydro-morphologic model for generation of flood scenarios towards hazard assessment. The analysis is concentrated on a design flood event with 100-year return period, for which an outflowing discharge is computed as a result of the river modeling. However, it is also argued how suitable model input parameter values can be obtained from analyses of river flows in a yearly duration curve. Modeling tools are discussed with respect to their capabilities and limitations. The results of the analysis are site-specific, but the proposed methodology can be exported to other hydro-graphic basins

Monitoring riverbank erosion in mountain catchments using terrestrial laser scanning

Sediment yield is a key factor in river basins management due to the various and adverse consequences that erosion and sediment transport in rivers may have on the environment. Although various contributions can be found in the literature about sediment yield modeling and bank erosion monitoring, the link between weather conditions, river flow rate and bank erosion remains scarcely known. Thus, a basin scale assessment of sediment yield due to riverbank erosion is an objective hard to be reached. In order to enhance the current knowledge in this field, a monitoring method based on high resolution 3D model reconstruction of riverbanks, surveyed by multi-temporal terrestrial laser scanning, was applied to four banks in Val Tartano, Northern Italy. Six data acquisitions over one year were taken, with the aim to better understand the erosion processes and their triggering factors by means of more frequent observations compared to usual annual campaigns. The objective of the research is to address three key questions concerning bank erosion: "how" erosion happens, "when" during the year and "how much" sediment is eroded. The method proved to be effective and able to measure both eroded and deposited volume in the surveyed area. Finally an attempt to extrapolate basin scale volume for bank erosion is presented

Cardiovascular Post-Acute COVID-19 Syndrome: Definition, Clinical Scenarios, Diagnosis, and Management

Post-acute COVID-19 syndrome (PACS) describes the clinical condition of some SARS-CoV-2-infected patients in which a wide range of signs and symptoms that persist for several months after the acute phase of the disease. Cardiovascular symptoms including chest pain, dyspnea, elevated blood pressure, palpitations, inappropriate tachycardia, fatigue, and exercise intolerance are common in this condition. Some infected patients develop cardiovascular diseases such as myocarditis, pericarditis, new or worsening myocardial ischemia due to obstructive coronary artery disease, microvascular dysfunction, stress cardiomyopathy, thromboembolism, cardiovascular sequelae of pulmonary disease, arrhythmias, while others have cardiovascular symptoms without objective evidence of cardiovascular abnormalities. In the present chapter, definition, spectrum of manifestations, clinical scenarios, diagnosis, management, and therapy of cardiovascular PACS will be discussed