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Multimodal Imaging Of Structural Concrete Using Image Fusion And Deep Learning, Sina Mehdinia
Multimodal Imaging Of Structural Concrete Using Image Fusion And Deep Learning, Sina Mehdinia
Dissertations and Theses
Concrete structures may be exposed to a variety of loads and environments during their service life. Non-destructive testing (NDT) techniques can be helpful in evaluating the condition of a structure. Imaging provides a visual representation of the interior of concrete and its condition non-destructively. Ground penetrating radar (GPR) and ultrasonic echo array (UEA) using electromagnetic and stress waves, respectively, provide the data that can be used to reconstruct an image. In this PhD dissertation, image reconstruction and fusion algorithms, simulation, and a deep learning model were investigated with the goal to lay the foundation for enhanced imaging applications for concrete. …
Seismic Performance Design Criteria Of Existing Bridge Bent Plastic Hinge Region And Rapid Repair Measures Of Earthquake Damaged Bridges Considering Future Resilience, A K M Golam Murtuz
Seismic Performance Design Criteria Of Existing Bridge Bent Plastic Hinge Region And Rapid Repair Measures Of Earthquake Damaged Bridges Considering Future Resilience, A K M Golam Murtuz
Dissertations and Theses
The main objective of this research was to evaluate the seismic performance of existing sub-standard reinforced concrete (RC) bridge column-spread footing subassemblies and to quantify the material strain limits through a full-scale experimental program. A total of six column-footing test specimens with pre-1990 construction details were subjected to reverse cyclic lateral loading, utilizing a conventional three-cycle symmetric loading protocol and a protocol representing the demands expected from a CSZ earthquake. Additionally, the tests were designed so that variable axial loading could be applied to simulate the secondary load effects experienced during an earthquake in a column that is part of …
Towards Simulation Of Complex Ocean Flows: Analysis And Algorithm For Computation Of Coupled Partial Differential Equations, Wenbin Dong
Dissertations and Theses
The hybrid CFD models which usually consist of 2 sub-models, develop our capability to simulate many emerging problems with multiphysics and multiscale flows, especially for the coastal ocean flows interacted with local phenomena of interest. For most cases, the sub-models are connected with direct interpolation which is easy and workable. It becomes urgently needed to investigate the inner mechanism of such model integration as this simple method does not work well if the two sub-models are different in governing equations, numerical methods, and computational grids. Also, it can not treat complex flow structures as well as the balance in mass …
On A New Framework For Detecting, Classifying, And Forecasting Floods For Large-Scale Flood Risk Analysis, Equisha Glenn
On A New Framework For Detecting, Classifying, And Forecasting Floods For Large-Scale Flood Risk Analysis, Equisha Glenn
Dissertations and Theses
Increasing trends in flooding events are projected to continue as climate changes have increased the chance of extreme weather events. Given the significant, damaging impacts of extreme floods, the ability to effectively model floods is crucial for risk management and mitigation of the impacts of these extreme flooding events. This dissertation presents a new framework for detecting and predicting large-scale flood risk in the United States using climate information. This methodology categorizes regional, simultaneous floods into an index that is used to forecast the risk of extreme flooding a season ahead. The index proposed herein, named the Spatial Flood Index …
A Citizen-Science Approach For Urban Flood Risk Analysis Using Data Science And Machine Learning, Candace Agonafir
A Citizen-Science Approach For Urban Flood Risk Analysis Using Data Science And Machine Learning, Candace Agonafir
Dissertations and Theses
Street flooding is problematic in urban areas, where impervious surfaces, such as concrete, brick, and asphalt prevail, impeding the infiltration of water into the ground. During rain events, water ponds and rise to levels that cause considerable economic damage and physical harm. The main goal of this dissertation is to develop novel approaches toward the comprehension of urban flood risk using data science techniques on crowd-sourced data. This is accomplished by developing a series of data-driven models to identify flood factors of significance and localized areas of flood vulnerability in New York City (NYC). First, the infrastructural (catch basin clogs, …