Nd To End Learning News Today : Breaking News, Live Updates & Top Stories | Vimarsana

Cross-drainage hydraulic structures such as culverts and bridges in urban landscapes are prone to get blocked by the transported debris (e.g., urban, vegetated), which often reduces their hydraulic capacity and triggers flash floods. Unavailability of relevant data from blockage-originated flooding events and complex nature of debris accumulation are highlighted factors hindering the research within the blockage management domain. Wollongong City Council (WCC) blockage conduit policy is the leading formal guidelines to incorporate blockage into design guidelines; however, are criticized by the hydraulic engineers for its dependence on the post-flood visual inspections (i.e., visual blockage) instead of peak floods hydraulic investigations (i.e., hydraulic blockage). Apparently, no quantifiable relationship is reported between the visual blockage and hydraulic blockage; therefore, many consider WCC blockage guidelines invalid. This paper exploits the power of Artificial Intelligence (AI ....

Lab Dataset , Wollongong City Council , Lab Blockage Dataset , City Council , Artificial Intelligence , Hydraulics Lab Blockage Dataset , Visual Hydraulics Lab Dataset , Ross Drainage Hydraulic Structures , Deep Learning , Nd To End Learning , Ydraulic Blockage , Caled Physical Models , Isual Blockage ,