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Full-Text Articles in Engineering
A Computer Vision-Based Method For Tack Coat Coverage Inspection Using Drone-Collected Images, Aida Da Silva
A Computer Vision-Based Method For Tack Coat Coverage Inspection Using Drone-Collected Images, Aida Da Silva
Graduate Theses, Dissertations, and Problem Reports
Tack coat is a thin asphalt applied between the existing surface and asphalt overlay during road rehabilitation. The uniformity of tack coat coverage plays a vital role in providing adhesive bonding between the two layers in the pavement structures. To ensure tack coat uniformity, the current practice primarily relies on manual inspection during construction by field experts. This process is time-consuming and tedious, and the results can be subjective and error-prone. Drones have emerged as a non-destructive sensing technology in the construction industry for many inspection practices. Unlike other non-destructive inspection technologies, drones offer benefits ranging from accelerating data collection …
Machine Learning Assisted Framework For Advanced Subsurface Fracture Mapping And Well Interference Quantification, Mohammad Faiq Adenan
Machine Learning Assisted Framework For Advanced Subsurface Fracture Mapping And Well Interference Quantification, Mohammad Faiq Adenan
Graduate Theses, Dissertations, and Problem Reports
The oil and gas industry has historically spent significant amount of capital to acquire large volumes of analog and digital data often left unused due to lack of digital awareness. It has instead relied on individual expertise and numerical modelling for reservoir development, characterization, and simulation, which is extremely time consuming and expensive and inevitably invites significant human bias and error into the equation. One of the major questions that has significant impact in unconventional reservoir development (e.g., completion design, production, and well spacing optimization), CO2 sequestration in geological formations (e.g., well and reservoir integrity), and engineered geothermal systems (e.g., …
Probabilistic Short Term Solar Driver Forecasting With Neural Network Ensembles, Joshua Daniell
Probabilistic Short Term Solar Driver Forecasting With Neural Network Ensembles, Joshua Daniell
Graduate Theses, Dissertations, and Problem Reports
Commonly utilized space weather indices and proxies drive predictive models for thermosphere density, directly impacting objects in low-Earth orbit (LEO) by influencing atmospheric drag forces. A set of solar proxies and indices (drivers), F10.7, S10.7, M10.7, and Y10.7, are created from a mixture of ground based radio observations and satellite instrument data. These solar drivers represent heating in various levels of the thermosphere and are used as inputs by the JB2008 empirical thermosphere density model. The United States Air Force (USAF) operational High Accuracy Satellite Drag Model (HASDM) relies on JB2008, and …