A5102824125- Flood Risk Assessment and Management
- Tropical and Extratropical Cyclones Research
- Hydrology and Watershed Management Studies
- Coastal and Marine Dynamics
- Meteorological Phenomena and Simulations
- Hydrological Forecasting Using AI
- Hydrology and Drought Analysis
- Soil erosion and sediment transport
- Environmental Changes in China
- Advanced Combustion Engine Technologies
- Infrastructure Maintenance and Monitoring
- Hydrology and Sediment Transport Processes
- Advanced Aircraft Design and Technologies
- Facilities and Workplace Management
- Rocket and propulsion systems research
- Geographic Information Systems Studies
- Structural Health Monitoring Techniques
- Traffic Prediction and Management Techniques
- Life Cycle Costing Analysis
- Geotechnical Engineering and Underground Structures
- Concrete Corrosion and Durability
- BIM and Construction Integration
University of Virginia
2017-2024
Corteva (United States)
2023
Engineering Systems (United States)
2019-2022
Northwestern Polytechnical University
2020
McCormick (United States)
2017
Abstract Mitigating the adverse impacts caused by increasing flood risks in urban coastal communities requires effective prediction for prompt action. Typically, physics‐based 1‐D pipe/2‐D overland flow models are used to simulate pluvial flooding. Because these require significant computational resources and have long run times, they often unsuitable real‐time at a street scale. This study explores potential of machine learning method, Random Forest (RF), serve as surrogate model...
This study explores the use of Deep Convolutional Neural Network (DCNN) for semantic segmentation flood images. Imagery datasets urban flooding were used to train two DCNN-based models, and camera images test application models with real-world data. Validation results show that both extracted extent a mean F1-score over 0.9. The factors affected performance included still water surface specular reflection, wet road surface, low illumination. In testing, reduced visibility during storm...
Low-lying coastal cities across the world are vulnerable to combined impact of rainfall and storm tide. However, existing approaches lack ability model effect these flood mechanisms, especially under climate change sea level rise (SLR). Thus, increase resilience cities, modeling techniques improve understanding prediction hazards critical. To address this need, study presents a system for assessing on selected future scenarios that leverages ocean with land surface capable resolving urban...
Climate change and sea-level rise are increasingly leading to higher prolonged high tides, which, in combination with the growing intensity of rainfall storm surges, insufficient drainage infrastructure, result frequent recurrent flooding coastal cities. There is a pressing need understand occurrence roadway incidents order enact appropriate mitigation measures. Agency data for events scarce resource-intensive collect. Crowdsourced can provide low-cost alternative mapping flood real time;...
Civil infrastructure systems have traditionally been designed assuming stationarity in precipitation. However, climate change is making this assumption invalid, affecting both existing and the design of new infrastructure. Although many studies analyzed potential increases precipitation due to change, fewer attempted translate these changes into impact stream discharge a way that could be incorporated design. Therefore, study aimed assess on rainfall peak aid bridge road Results showed...
Hurricanes cause substantial inundation of transportation networks, rendering them inaccessible to emergency response vehicles. Because storm tides and heavy rainfall often co-occur during hurricanes, a reliable assessment roadway in coastal areas requires adequate representation both flood sources. This study serially coupled hydrodynamic surge model with two-dimensional for rainfall-driven flow quantify compound flooding region. The output this modeling approach is used as an input...
Hydrology in low-relief coastal plains is especially challenging to simulate flood modeling applications. Two-dimensional (2D) hydrodynamic models are often necessary, but creating such for regional-scale systems at a high spatial resolution presents significant data challenges. The objective of this research explore these challenges using 2D model built 5,800-km2 region the plain Virginia as case study. Systematic enhancements model's topographic, bathymetric, streamline, surface roughness,...
The successful prediction of civil infrastructure's deterioration process is crucial for making optimal maintenance, rehabilitation, and replacement (MR&R) decisions under financial constraints. majority current models simulate the a single structure element infrastructure; such thus ignore interaction between dependent elements. However, elements often plays an important role in overall structure. Therefore, primary objective this paper to address these by developing method infrastructure...
This study explores the use of Deep Convolutional Neural Network (DCNN) for semantic segmentation flood images. Imagery datasets urban flooding were used to train two DCNN-based models, and camera images test application models with real-world data. Validation results show that both extracted extent a mean F1-score over 0.9. The factors affected performance included still water surface specular reflection, wet road surface, low illumination. In testing, reduced visibility during storm...
Abstract Hydraulic events are a leading cause of bridge failures. While these hydraulic accounted for in design, changing environmental and land use conditions require continual updating this risk. For example, after has been constructed, streamflow can change unanticipated ways as result changes, geomorphic climate change. The objective research was to create screening method able quickly inexpensively estimate overtopping risk across collection bridges based on the current conditions. uses...
The coastal regions in the U.S. East Coast and Gulf of Mexico are under risk storm surge precipitation-driven flooding. adverse impacts climate change including sea level rise (SLR), potential increase intensity frequency extreme storms, precipitation increases vulnerability communities to common practice for flood hazard assessment urban areas can result some errors as effect overland flow not considered simultaneously. In this study, we combine results two hydrodynamic models, one other...
Based on the analysis of overall structure variable cycle engine, A fan component model and a core-driven stage for distinguishing blade root characteristics from tip are established. According to steady-state dynamic working equations reflecting variation geometry components Referring establishment method dual-shaft turbofan engine is established based MATLAB/Simulink platform. The can be used design point calculation, simulation transition state in single/double culvert mode. results show...
<p>Nuisance flooding, which is repetitive flooding caused by both tidal and rainfall-driven events, increasing in frequency severity for many coastal communities. As climate change causes sea level rise more frequent intense storm these nuisance events are producing significant disruptions impacts to The objective of this study improve modeling decision support activities around and, particular, its impact on transportation infrastructure. Our region partner the research City...
Low-lying coastal cities across the world are vulnerable to combined impact of rainfall and storm tide. However, existing approaches lack ability model effect these flood mechanisms. Thus, increase resilience, modeling techniques improve understanding prediction hazards critical. To address this need, study presents a system for assessing risk under changing climate conditions that leverages ocean with land surface capable resolving urban drainage infrastructure within city. The approach is...