Geophysical surveys integrated with rainfall data analysis for the study of soil piping phenomena occurred in a densely urbanized area in eastern Sicily

The occurrence of strong and abrupt rainfall, together with a wrong land use planning and an uncontrolled urban development, can constitute a risk for infrastructure and population. The water flow in the subsoil, under certain conditions, may cause underground cavities formation. This phenomena known as soil piping can evolve and generate the surface collapse. It is clear that such phenomena in densely urbanized areas represent an unpredictable and consistent risk factor, which can interfere with social activities. In this study a multidisciplinary approach aimed to obtain useful information for the mitigation of the risks associated with the occurrence of soil piping phenomena in urban areas has been developed. This approach is aimed at defining the causes of sudden soil subsidence events, as well as the definition of the extension and possible evolution of these instability areas. The information obtained from rainfall data analysis, together with a study of the morphological, geological and hydrogeological characteristics, have allowed us to evaluate the causes that have led to the formation of soil pipes. Furthermore, performance of 3D electrical resistivity surveys in the area affected by the instability have allowed us to estimate their extension in the subsoil and identifying the presence of further areas susceptible to instability.

Developing Machine Learning-Based Models for Railway Inspection

Smart railway maintenance is crucial to the safety and efficiency of railway operations. Successful deployment of technologies such as condition-based monitoring and predictive maintenance will enable railway companies to conduct proactive maintenance before defects and failures take place to improve operation safety and efficiency. In this paper, we first propose to develop a classification-based method to detect rail defects such as localized surface collapse, rail end batter, or rail components—such as joints, turning points, crossings, etc.—by using acceleration data. In order to improve the performance of the classification-based models and enhance their applicability in practice, we further propose a deep learning-based approach for the detection of rail joints or defects by deploying convolutional neural networks (CNN). CNN-based models can work directly with raw data to reduce the heavy preprocessing of feature engineering and directly detect joints located on either the left or the right rail. Two convolutional networks, ResNet and fully convolutional networks (FCN), are investigated and evaluated with the collected acceleration data. The experimental results show both deep neural networks obtain good performance, which demonstrate that the deep learning-based methods are effective for detecting rail joints or defects with the expected performance.

Geological and Geophysical Study in Udheri Khola Area, Nalgad Hydroelectric Project, Jajarkot District, Lesser Himalaya, Western Nepal

Subsidence in carbonate rock is one of common and challenging action in terms of engineering construction. Geological study and geophysical investigation carried out in the intake area of Nalgad Hydroelectric Project Jajarkot, western Nepal Lesser Himalaya. The main objective was to identify the cause of subsidence in the intake area of Nalgad Hydroelectric Project, Jajarkot. Geological study of the area was carried to understand the lithology, thickness and structure of the area. The study area comprises two distinct rock units, namely, Dolomite Unit followed up by the Slate Unit. The Dolomite Unit is composed of light grey to grayish white stromatolitic dolomite which is thrusted over the Slate Unit near to Laikham village and Sepu Khola area. The Slate Unit is made up of grayish black to graphitic slate. A thin prominent calcareous horizon wasconfined between Slate Unit. 2D-Electric Resistivity Tomography (ERT) measurements were deployed in four different lines to investigate the cause of the subsidence in the carbonate terrain. A concentric very high resistivity patch shown by Tomogram ER-D-01 survey line was identified and interpreted as dry cavity. The result of the 2D- ERT survey was correlated with core log data of geotechnical exploration in the suspicious point to ensure the presence of karst in the Dolomite Unit at right bank of Nalsyagu Khola near dam axis of Nalgad Hydroelectric Project. The 2D – ERT survey together with geotechnical investigation is capable of identifying subsurface karst feature as the cause of surface collapse in the area.

Prediction of ground surface collapse by instrumental observation data on rock mass movements during underground mining

Using the data of long-term surveying at the Saranovsky chrome iron ore deposit, movements of rock mass were analyzed with a view to identifying potential early signs of ground surface collapse. The research findings are unique as one of the instrumental observation series was accomplished on the eve of the ground surface sinking above non-backfilled voids of earlier stoping. It was found that the test area experienced vertical alternating movements, and sinking was preceded by upheaval of ground surface. However, the further analysis revealed no clear cause-and-effect between the event and insufficiency of its study. The subsequent research identified a local cluster of rock mass subsidences at gradually increasing velocities, which showed up a few years before the sink appeared on ground surface above its initiation source. The absence of this cluster zone in the period before the collapse is explained by the damage of check points in this site. Finally, the conclusion is drawn that in certain geological conditions, deformation processes are localized and manifest no visible signs of impact on the enclosing rock mass and ground surface. Manifestations of these processes from the instrumental observations concentrate directly in the local area of their development, which should be taken into account in the analysis and prediction of movements. It is emphasized that the existing and new criteria of hazardous deformation processes should be corrected and updated for geomechanical monitoring of mineral mining objects.

Hip arthrodiastasis combined with core decompression and diamond concept for postcollapse femoral head avascular necrosis

In postcollapse hip avascular necrosis (AVN), the femoral head cannot be salvaged, necessitating total hip replacement. We report a case of a 39-year-old woman who developed idiopathic femoral head AVN with marked symptoms and radiological evidence of articular surface collapse. We treated her with core decompression combined with the ‘diamond concept’ (implantation of bone marrow concentrate, a growth factor and bone graft substitute) and distracted the hip joint with external fixator. Four years postoperatively the articular surface has been restored and the patient reports excellent quality of life. Hip arthrodiastasis with core decompression and ‘diamond concept’ regeneration could be considered a treatment option in advanced AVN of the femoral head.