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Full-Text Articles in Civil and Environmental Engineering

Nebraska Water Center Annual Report 2024 Jan 2024

Nebraska Water Center Annual Report 2024

Nebraska Water Center: Administrative Materials

The report's highlights updates including ongoing research, know your well, and the Nebraska master irrigator launch.


Geodatabase And Automation Code Used For Past And Real-Time Dynamic Landslide Hazard Maps In Eastern Kentucky, Nathaniel O'Leary, L. Sebastian Bryson, Jason M. Dortch Jan 2024

Geodatabase And Automation Code Used For Past And Real-Time Dynamic Landslide Hazard Maps In Eastern Kentucky, Nathaniel O'Leary, L. Sebastian Bryson, Jason M. Dortch

Earth and Environmental Sciences Research Data

We developed spatiotemporal landslide hazard maps (LHMs) using soil, hydrologic, and geomorphic parameters from the subaerial infinite slope factor of safety (FS) equation under unsaturated conditions. Soil properties were sourced from the NRCS WSS, while geomorphic variables were derived from a 1.5 m LiDAR-based DEM and ArcGIS Online. Soil moisture from Hydrus-1D, driven by precipitation and evapotranspiration (ET) data from Irrigation Manager, introduced temporal variability. Validation against known landslide sites demonstrated FS accuracy both spatially and temporally, despite some false positives. To reduce false positives and enhance slope stability representation, novel depth-to-bedrock (DTB) and soil root cohesion maps were incorporated …


Crowdsourced Geospatial Data Is Reshaping Urban Sciences, Xiao Huang, Siqin Wang, Tianjun Lu, Yisi Liu, Leticia Serrano-Estrada Jan 2024

Crowdsourced Geospatial Data Is Reshaping Urban Sciences, Xiao Huang, Siqin Wang, Tianjun Lu, Yisi Liu, Leticia Serrano-Estrada

Earth and Environmental Sciences Faculty Publications

For many years, urban sciences relied heavily on traditional, authoritative data sources. However, a paradigm shift has occurred recently with the advent of citizen-driven data contribution. This evolution in data acquisition for urban science is attributable to advancements in positioning and navigation technologies, widespread use of digital devices, the rise of Web 2.0, enhanced broadband communications, and refined data management techniques. The significance of crowdsourced geospatial data in the realm of urban sciences is now widely acknowledged. A diverse array of novel data sources has been increasingly gaining prominence. These include, but are not limited to, social media platforms, street …


A 3-Step, Open-Data, Ride-Hailing Ridership Model With Pricing Applications, Richard A. Mucci Jan 2024

A 3-Step, Open-Data, Ride-Hailing Ridership Model With Pricing Applications, Richard A. Mucci

Theses and Dissertations--Civil Engineering

Researchers and practitioners studied the effects ride-hailing had in cities before the covid-19 pandemic. Previous research found ride-hailing to produce negative externalities, such as reducing transit ridership and increasing congestion in various cities. Since the pandemic, ride-hailing ridership has nearly recovered to pre-pandemic levels in Chicago. Ride-hailing ridership has grown steadily since the pandemic while a rider’s willingness to share their trip stagnated. Ride-hailing ridership nearly recovering to pre-covid levels in Chicago suggests that transportation planners, and policy makers, will need to continue assessing the impacts ride-hailing trips have in their cities.

Pickup and drop off locations in the Chicago …


Lead Bioaccessibility And Commonly Measured Soil Characteristics (Detroit, Mi, Usa) – Phase 1, Sabrina R. Good, Allison R. Harris, Patrick Crouch, Conor T. Gowan, William D. Shuster, Shawn P. Mcelmurry Jan 2024

Lead Bioaccessibility And Commonly Measured Soil Characteristics (Detroit, Mi, Usa) – Phase 1, Sabrina R. Good, Allison R. Harris, Patrick Crouch, Conor T. Gowan, William D. Shuster, Shawn P. Mcelmurry

Open Data at Wayne State

Contaminated urban soil is one of the major contributors to child Pb exposure. To gain a better understanding of Pb risk in urban areas, composite samples were collected from 142 residential, privately owned, parcels in Detroit, Hamtramck, and Highland Park, Michigan, with approval from the property owners. The proximity of soil sampling and former smelter locations were also reported. Sample were collected from areas covered with turf grass. Four samples were collected, one from each cardinal direction (north, south, east, and west), 20 cm from an aluminum tent stake driven into the center of the sampling site. Soils were collected …


Ground Tire Rubber As A Sustainable Additive: Transforming Desert Sand Behavior, Nabil Ismael, Dalya Ismael, Asmaa Al-Ahmad Jan 2024

Ground Tire Rubber As A Sustainable Additive: Transforming Desert Sand Behavior, Nabil Ismael, Dalya Ismael, Asmaa Al-Ahmad

Engineering Technology Faculty Publications

Managing waste tires presents a significant challenge globally, particularly in regions experiencing high temperatures and shortage of landfill sites. This issue is affecting countries like Kuwait, where the abundance of waste tires is a major source of environmental and safety risks, particularly during the intensely hot summer months. This extreme heat has sparked numerous fires, leading to substantial air pollution due to thick black smoke. Given the limited disposal options, recycling waste tires and finding practical applications for ground tire rubber (GTR) is essential. To address the challenge, a comprehensive laboratory testing program was conducted, using locally produced rubber aggregates …


Digitalization Of Railway Transportation Through Ai-Powered Services: Digital Twin Trains, Salih Sarp, Murat Kuzlu, Vukica Jovanovic, Zekeriya Polat, Ozgur Guler Jan 2024

Digitalization Of Railway Transportation Through Ai-Powered Services: Digital Twin Trains, Salih Sarp, Murat Kuzlu, Vukica Jovanovic, Zekeriya Polat, Ozgur Guler

Engineering Technology Faculty Publications

Digitalization is a key concept that transformed the various industries through technologies like Internet of Things (IoT), Artificial Intelligence (AI), and Digital Twin (DT). Although innovations provided by the advancement of digitalization have paved the way for more efficient operations and products for transportation, the rail transportation sector struggles to keep up with the rest of the transportation industry, since trains are designed to last for decades, and the insufficient infrastructure investment leads to multiple railroad derailments across the globe. Therefore, the primary aim is to transform current railway systems into human-centric, adaptable, sustainable and future-proof networks, aligning with Industry …


Examining The Effectiveness Of Oiled Ballast Water Treatment Processes: Insights Into Hydrocarbon Oxidation Product Formation And Environmental Implications, Maxwell L. Harsha, Danielle E. Verna, Yanila Salas-Ortiz, Eduardo Osborn, Eduardo Turcios Valle, Aleksandar I. Goranov, Patrick G. Hatcher, Ana M. Aguilar-Islas, Patrick L. Tomco, David C. Podgorski Jan 2024

Examining The Effectiveness Of Oiled Ballast Water Treatment Processes: Insights Into Hydrocarbon Oxidation Product Formation And Environmental Implications, Maxwell L. Harsha, Danielle E. Verna, Yanila Salas-Ortiz, Eduardo Osborn, Eduardo Turcios Valle, Aleksandar I. Goranov, Patrick G. Hatcher, Ana M. Aguilar-Islas, Patrick L. Tomco, David C. Podgorski

Chemistry & Biochemistry Faculty Publications

Ballast water released from ships into coastal environments has been identified as a mechanism that introduces contaminants of concern into coastal ecosystems. This study investigates the treatment processes employed at a ballast water treatment facility in Valdez, Alaska, that remove hydrocarbons from unsegregated ballast water. Specifically, the aim is to quantify and characterize hydrocarbons of emerging concern, known as dissolved hydrocarbon oxidation products (HOPs) and heavy metals (HMs), throughout the treatment process. Specialized analytical techniques were employed, such as non-volatile dissolved organic carbon analysis, fluorescence spectroscopy, Fourier transform-ion cyclotron resonance-mass spectrometry, and inductively coupled plasma triple quadrupole mass spectrometry. Results …


Thermal Alteration Of The Mineralogy Of Calcium Sulfoaluminate Cements: Implications For The Performance Of Rapid Repair Materials, Jillian Cavellier Jan 2024

Thermal Alteration Of The Mineralogy Of Calcium Sulfoaluminate Cements: Implications For The Performance Of Rapid Repair Materials, Jillian Cavellier

Theses and Dissertations--Earth and Environmental Sciences

Calcium sulfoaluminate (CSA) was developed in part to lessen the environmental impact of cementitious materials compared to traditional Portland cements. CSA was first put into production in the 1970s and has been undergoing various performance testing to investigate its durability. Yet to be evaluated is CSA’s response to a rapid, high temperature event. In this study, X-ray diffraction, thermogravimetric analysis, Fourier transform infrared spectrometry and scanning electron microscope imaging were used to analyze alterations in the mineralogy due to such an event. As found in previous studies, after ~125°C, ettringite has been completely dehydrated. Ettringite decomposes into bassanite and calcium …


Visualizing And Automating Past, Real-Time, And Forecast Dynamic Hazard Maps For Shallow Colluvial Landslides In Eastern Kentucky, Nathaniel O'Leary Jan 2024

Visualizing And Automating Past, Real-Time, And Forecast Dynamic Hazard Maps For Shallow Colluvial Landslides In Eastern Kentucky, Nathaniel O'Leary

Theses and Dissertations--Earth and Environmental Sciences

Landslide hazards are a persistent threat to communities and infrastructure in Eastern Kentucky, where steep slopes, shallow colluvial soils, and variable hydrological conditions make slope failures frequent. This thesis presents an integrated approach to landslide hazard mapping (LHM) through the development of dynamic, spatiotemporal LHMs for shallow colluvial landslides. Two studies within this work investigate and refine the use of the Lu and Godt (2008) factor of safety (FS) equation to improve landslide predictions. The first study establishes a novel LHM workflow using Hydrus-1D to simulate soil moisture infiltration and fluctuations from precipitation and evapotranspiration (ET) data. This study also …


The Efficacy Of Wetland Treatment Systems Used To Treat Runoff Mixtures From Different Landscapes Across Kentucky, Emily Nottingham Jan 2024

The Efficacy Of Wetland Treatment Systems Used To Treat Runoff Mixtures From Different Landscapes Across Kentucky, Emily Nottingham

Theses and Dissertations--Biosystems and Agricultural Engineering

The overarching goal was to improve our understanding of the cumulative effect of increased use and occurrence of commonly detected contaminants of potential concern (CPCs) on nitrogen (N) transformation processes in wetlands. The central hypothesis was that those various mixtures of nutrients and CPCs entering treatment wetlands impact N removal pathways. The first study assessed the current state of the literature on the implications to N removal in wetlands in the presence of pesticides and antibiotics. 181 primary studies were identified. Removal efficiencies for nitrate varied widely across the studies, with CPCs impacting microbial communities. A knowledge gap remains in …


Predictive Modeling Of Healthcare Traffic Using Machine Learning: A Comparative Study, Shadman Mahmood Khan Pathan, Sakan Binte Imran, M. M. Shabab Iqbal, Muhammad Enayetur Rahman, Md Nurul Absar Siddiky, Muhammad Rezaur Rahman, Md. Rafid Hassan, Nondon Lal Dey, Md. Sobuj Hossain Jan 2024

Predictive Modeling Of Healthcare Traffic Using Machine Learning: A Comparative Study, Shadman Mahmood Khan Pathan, Sakan Binte Imran, M. M. Shabab Iqbal, Muhammad Enayetur Rahman, Md Nurul Absar Siddiky, Muhammad Rezaur Rahman, Md. Rafid Hassan, Nondon Lal Dey, Md. Sobuj Hossain

Electrical & Computer Engineering Faculty Publications

Effective healthcare traffic management is critical for ensuring prompt medical services, particularly in emergencies where delays can have life-threatening consequences. This study conducts a comparative analysis of three popular machine learning models—Linear Regression, Decision Trees, and Random Forests—for predicting healthcare-related traffic volumes. Utilizing a comprehensive dataset from a metropolitan interstate traffic system, the models were evaluated based on key performance metrics, including Mean Squared Error (MSE), R² Score, and execution time. The findings demonstrate that the Random Forest model outperforms the others, offering superior predictive accuracy and efficiency. These insights are valuable for optimizing traffic management in healthcare, ultimately contributing …


Assessing Stormwater Management Pond Water Quality, Function, And The Potential Biotic Effects To Receiving Waters, Mitchell Elstone Jan 2024

Assessing Stormwater Management Pond Water Quality, Function, And The Potential Biotic Effects To Receiving Waters, Mitchell Elstone

Theses and Dissertations (Comprehensive)

The use of stormwater management ponds (SWMPs) has been increasing over the past five decades. However, an in-depth understanding of the daily performance of SWMPs and functionality during cold periods is limited. This is in part because mandated monitoring is relatively infrequent, and the assumption that SWMPs are inactive between storm events and during the winter. The goals of this research were to better understand daily stormwater (SW) characteristics, the performance of SWMPs based on current forms of evaluation and assess the potential for SWMP effluent to impact downstream biota. Influent and effluent samples from two SWMPs were collected daily …


Advancing Environmental Engineering: The Role Of Artificial Intelligence In Sustainable Solutions - A Short Review, Amirreza Talaie, Hesam Kamyab, Ashkan Razmfarsa Jan 2024

Advancing Environmental Engineering: The Role Of Artificial Intelligence In Sustainable Solutions - A Short Review, Amirreza Talaie, Hesam Kamyab, Ashkan Razmfarsa

Management Faculty Publications

Artificial intelligence (AI) has emerged as a transformative force in environmental engineering, offering innovative solutions to complex environmental challenges. From air pollution monitoring and water resource management to waste management, climate change mitigation, and ecological preservation, AI is revolutionizing the way we address environmental issues. Machine learning, neural networks, and other AI technologies are enabling more accurate predictions, optimizing resource use, and improving conservation efforts. However, despite its many advantages, AI also faces challenges such as data availability, energy consumption, ethical concerns, and the need for transparency. This review explores the diverse applications of AI in environmental engineering, highlighting the …


Railroad Condition Monitoring Using Distributed Acoustic Sensing And Deep Learning Techniques, Md Arifur Rahman Jan 2024

Railroad Condition Monitoring Using Distributed Acoustic Sensing And Deep Learning Techniques, Md Arifur Rahman

College of Graduate Studies: Theses & Dissertations

Proper condition monitoring has been a major issue among railroad administrations since it might cause catastrophic dilemmas that lead to fatalities or damage to the infrastructure. Although various aspects of train safety have been conducted by scholars, in-motion monitoring detection of defect occurrence, cause, and severity is still a big concern. Hence extensive studies are still required to enhance the accuracy of inspection methods for railroad condition monitoring (CM). Distributed acoustic sensing (DAS) has been recognized as a promising method because of its sensing capabilities over long distances and for massive structures. As DAS produces large datasets, algorithms for precise …


Computationally Modeling The Human-Structure Interaction Response Of An Occupied Cantilevered Structure, Brennan Smith Jan 2024

Computationally Modeling The Human-Structure Interaction Response Of An Occupied Cantilevered Structure, Brennan Smith

Honors Theses

There is a limited understanding of the impact that passive human occupants have on a dynamic structural system, referred to as Human-Structure Interaction (HSI). Cantilevers are naturally prone to excessive vibrations due to their long unsupported spans, and cantilevered structures such as those commonly found in the seating area of a stadium facility or concert hall are designed to support a high density of occupancy.

This study determined that HSI in cantilevered structures can be modeled using a simple two-degree-of-freedom system. The results of the model were validated by data that was collected on a small-scale laboratory structure intentionally designed …


Determination Of Spore Viability In Concrete Across Several Factors Using Most Probable Number, Samuel Boyer Jan 2024

Determination Of Spore Viability In Concrete Across Several Factors Using Most Probable Number, Samuel Boyer

Williams Honors College, Honors Research Projects

To determine the lowest concentration of spore added to polyurethane-cement composite (PUCCO) particles that can still germinate after curing in concrete. This research project is a small addition to the larger research project being undertaken by Mirza Mohammed Rashiduzzaman for his Masters. The larger project involves the use of fungal spores added in concrete to act as a self-healing component when cracks form in the concrete structure over time. These spores are suspended in a protective oil and loaded into small, hardened sponge-like PUCCO cubes to act as growth points when water and air can reach the PUCCO in the …


Machine-Learning-Assisted Design Of Deep Eutectic Solvents Based On Uncovered Hydrogen Bond Patterns, Usman Lame Abbas, Yuxuan Zhang, Joseph Tapia, Md Selim, Jin Chen, Jian Shi, Qing Shao Jan 2024

Machine-Learning-Assisted Design Of Deep Eutectic Solvents Based On Uncovered Hydrogen Bond Patterns, Usman Lame Abbas, Yuxuan Zhang, Joseph Tapia, Md Selim, Jin Chen, Jian Shi, Qing Shao

Markey Cancer Center Faculty Publications

Non-ionic deep eutectic solvents (DESs) are non-ionic designer solvents with various applications in catalysis, extraction, carbon capture, and pharmaceuticals. However, discovering new DES candidates is challenging due to a lack of efficient tools that accurately predict DES formation. The search for DES relies heavily on intuition or trial-and-error processes, leading to low success rates or missed opportuni- ties. Recognizing that hydrogen bonds (HBs) play a central role in DES formation, we aim to identify HB features that distinguish DES from non-DES systems and use them to develop machine learning (ML) models to discover new DES systems. We first analyze the …


Perfluorooctanesulfonic Acid Exposure Leads To Downregulation Of 3-Hydroxy-3-Methylglutaryl-Coa Synthase 2 Expression And Upregulation Of Markers Associated With Intestinal Carcinogenesis In Mouse Intestinal Tissues, Josiane Weber Tessmann, Pan Deng, Jerika Durham, Chang Li, Moumita Banerjee, Qingding Wang, Ryan A. Goettl, Daheng He, Chi Wang, Eun Y. Lee, B. Mark Evers, Bernhard Hennig, Yekaterina Y. Zaytseva Jan 2024

Perfluorooctanesulfonic Acid Exposure Leads To Downregulation Of 3-Hydroxy-3-Methylglutaryl-Coa Synthase 2 Expression And Upregulation Of Markers Associated With Intestinal Carcinogenesis In Mouse Intestinal Tissues, Josiane Weber Tessmann, Pan Deng, Jerika Durham, Chang Li, Moumita Banerjee, Qingding Wang, Ryan A. Goettl, Daheng He, Chi Wang, Eun Y. Lee, B. Mark Evers, Bernhard Hennig, Yekaterina Y. Zaytseva

Markey Cancer Center Faculty Publications

Perfluorooctanesulfonic acid (PFOS) is a widely recognized environment pollutant known for its high bio- accumulation potential and a long elimination half-life. Several studies have shown that PFOS can alter multiple biological pathways and negatively affect human health. Considering the direct exposure to the gastrointestinal (GI) tract to environmental pollutants, PFOS can potentially disrupt intestinal homeostasis. However, there is limited knowledge about the effect of PFOS exposure on normal intestinal tissues, and its contribution to GI- associated diseases remains to be determined. In this study, we examined the effect of PFOS exposure on the gene expression profile of intestinal tissues of …


Stage And Discharge Prediction From Documentary Time-Lapse Imagery, Kenneth W. Chapman, Troy E. Gilmore, Mehrube Mehrubeoglu, Christian D. Chapman, Aaron R. Mittelstet, John E. Stranzl Jr. Jan 2024

Stage And Discharge Prediction From Documentary Time-Lapse Imagery, Kenneth W. Chapman, Troy E. Gilmore, Mehrube Mehrubeoglu, Christian D. Chapman, Aaron R. Mittelstet, John E. Stranzl Jr.

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Imagery from fixed, ground-based cameras is rich in qualitative and quantitative information that can improve stream discharge monitoring. For instance, time-lapse imagery may be valuable for filling data gaps when sensors fail and/or during lapses in funding for monitoring programs. In this study, we used a large image archive (> 40,000 images from 2012 to 2019) from a fixed, ground-based camera that is part of a documentary watershed imaging project (https://plattebasintimelapse.com/). Scalar image features were extracted from daylight images taken at one-hour intervals. The image features were fused with United States Geological Survey stage and discharge data as …


Life Cycle Greenhouse Gas Emissions In Maize No-Till Agroecosystems In Southern Brazil Based On A Long-Term Experiment, Guilherme Rosa Da Silva, Adam J. Liska, Cimelio Bayer Jan 2024

Life Cycle Greenhouse Gas Emissions In Maize No-Till Agroecosystems In Southern Brazil Based On A Long-Term Experiment, Guilherme Rosa Da Silva, Adam J. Liska, Cimelio Bayer

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Brazilian agriculture is constantly questioned concerning its environmental impacts, particularly greenhouse gas (GHG) emissions. This research study used data from a 34-year field experiment to estimate the life cycle GHG emissions intensity of maize production for grain in farming systems under no-tillage (NT) and conventional tillage (CT) combined with Gramineae (oat) and legume (vetch) cover crops in southern Brazil. We applied the Feedstock Carbon Intensity Calculator for modeling the “field-to-farm gate” emissions with measured annual soil N2O and CH4 emissions data. For net CO2 emissions, increases in soil organic C (SOC) were applied as a proxy, …


Closing Dichloramine Decomposition Nitrogen And Oxygen Mass Balances: Relative Importance Of End-Products From The Reactive Nitrogen Species Pathway, Huong T. Pham, David G. Wahman, Julian L. Fairey Jan 2024

Closing Dichloramine Decomposition Nitrogen And Oxygen Mass Balances: Relative Importance Of End-Products From The Reactive Nitrogen Species Pathway, Huong T. Pham, David G. Wahman, Julian L. Fairey

Civil Engineering Faculty Publications and Presentations

In drinking water chloramination, monochloramine autodecomposition occurs in the presence of excess free ammonia through dichloramine, the decay of which was implicated in N-nitrosodimethylamine (NDMA) formation by (i) dichloramine hydrolysis to nitroxyl which reacts with itself to nitrous oxide (N2O), (ii) nitroxyl reaction with dissolved oxygen (DO) to peroxynitrite or mono/dichloramine to nitrogen gas (N2), and (iii) peroxynitrite reaction with total dimethylamine (TOTDMA) to NDMA or decomposition to nitrite/nitrate. Here, the yields of nitrogen and oxygen-containing end-products were quantified at pH 9 from NHCl2 decomposition at 200, 400, or 800 μeq Cl2·L …


Urban Flood Extent Segmentation And Evaluation From Real-World Surveillance Camera Images Using Deep Convolutional Neural Network, Yidi Wang, Yawen Shen, Behrouz Salahshour, Mecit Cetin, Khan Iftekharuddin, Navid Tahvildari, Guoping Huang, Devin K. Harris, Kwame Ampofo, Jonathan L. Goodall Jan 2024

Urban Flood Extent Segmentation And Evaluation From Real-World Surveillance Camera Images Using Deep Convolutional Neural Network, Yidi Wang, Yawen Shen, Behrouz Salahshour, Mecit Cetin, Khan Iftekharuddin, Navid Tahvildari, Guoping Huang, Devin K. Harris, Kwame Ampofo, Jonathan L. Goodall

Civil & Environmental Engineering Faculty Publications

This study explores the use of Deep Convolutional Neural Network (DCNN) for semantic segmentation of flood images. Imagery datasets of urban flooding were used to train two DCNN-based models, and camera images were used to test the application of the models with real-world data. Validation results show that both models extracted flood extent with a mean F1-score over 0.9. The factors that affected the performance included still water surface with specular reflection, wet road surface, and low illumination. In testing, reduced visibility during a storm and raindrops on surveillance cameras were major problems that affected the segmentation of flood extent. …


Small-Strain Site Response Of Soft Soils In The Sacramento-San Joaquin Delta Region Of California Conditioned On Vₛ₃₀ And Mhvsr, Tristan E. Buckreis, Jonathan P. Stewart, Scott J. Brandenberg, Pengfei Wang Jan 2024

Small-Strain Site Response Of Soft Soils In The Sacramento-San Joaquin Delta Region Of California Conditioned On Vₛ₃₀ And Mhvsr, Tristan E. Buckreis, Jonathan P. Stewart, Scott J. Brandenberg, Pengfei Wang

Civil & Environmental Engineering Faculty Publications

Sites located in the Sacramento-San Joaquin Delta region of California typically have peaty-organic soils near the ground surface, which are characteristically soft, with shear wave velocities as low as 30 m/s. These unusually soft geotechnical conditions, which are outside the range of applicability of existing ergodic site amplification models, can be anticipated to produce significant site effects during earthquake shaking. We evaluate site response for 36 seismic stations in the Delta region using non-ergodic methods with low-amplitude ground motion data. We model first-order site effects using a period-dependent relation conditioned on the 30 m time-averaged shear wave velocity (V …


Contribution Of High Turbidity To Tidal Dynamics In A Curved Channel In Zhoushan Islands, China, Li Li, Fangzhou Shen, Zhiguo He, Gangfeng Ma, Jiachen Wang, Kailong Huangfu Jan 2024

Contribution Of High Turbidity To Tidal Dynamics In A Curved Channel In Zhoushan Islands, China, Li Li, Fangzhou Shen, Zhiguo He, Gangfeng Ma, Jiachen Wang, Kailong Huangfu

Civil & Environmental Engineering Faculty Publications

The curved tidal channel, Luotou Deep-water Navigational Channel, is the main channel of the Ningbo Zhoushan Port, which is ranked first in the world. Tidal dynamics in the channel are spatially and temporally asymmetric. In this study, the three-dimensional tidal dynamics in the channel were analyzed using field data and simulated using FVCOM. The results show that the tides in the channel flood/ebb along the northern/southern bank near the bottom/surface layer and these asymmetries are due to the imbalanced Coriolis force, centrifugal force, sea-level gradient, and density gradient. Residual current velocity peaks (0.7 m/s) in the middle of the channel …


Modeling Coupled Driving Behavior During Lane Change: A Multi-Agent Transformer Reinforcement Learning Approach, Hongyu Guo, Mehdi Keyvan-Ekbatani, Kun Xie Jan 2024

Modeling Coupled Driving Behavior During Lane Change: A Multi-Agent Transformer Reinforcement Learning Approach, Hongyu Guo, Mehdi Keyvan-Ekbatani, Kun Xie

Civil & Environmental Engineering Faculty Publications

In a lane change (LC) scenario, the lane change vehicle interacts with surrounding vehicles. The interactions not only affect their driving behaviors but also influence the traffic flow. This study aims to model the coupled behavior of the lane changer and the follower in the target lane during LC. Large-scale real-world connected vehicle (CV) data from the Safety Pilot Model Deployment (SPMD) program are used to extract LCs and study vehicle interactions. A multi-agent Transformer-based deep deterministic policy gradient (MA-TDDPG) method is proposed to model the coupled behaviors during LC. The multi-agent framework can handle the multiple agents’ behaviors with …


Implications Of Alternative Communications And Sensing Technologies For Implementing Variable Speed Limit Control Through Connected Vehicles: Sag Curve As A Case Study, Reza Vatani Nezafat, Mecit Cetin, Elizabeth Williams, George F. List Jan 2024

Implications Of Alternative Communications And Sensing Technologies For Implementing Variable Speed Limit Control Through Connected Vehicles: Sag Curve As A Case Study, Reza Vatani Nezafat, Mecit Cetin, Elizabeth Williams, George F. List

Civil & Environmental Engineering Faculty Publications

Connected vehicles (CVs) will enable various applications to improve traffic flow. This paper's focus is to investigate how the potential implementation of variable speed limit (VSL) through different types of communication and sensing technologies on CVs makes it possible to mitigate congestion at a sag curve bottleneck. A VSL algorithm is developed and implemented in a simulation environment for controlling the inflow of vehicles to a sag curve to minimize delays and increase throughput. Both vehicle-to-vehicle (V2V) and infrastructure-to-vehicle (I2V) options for CVs are investigated when implementing the VSL control strategy in a simulation environment. Also, for measuring traffic density …


Investigating The Viability Of Low Frequency Mhvsr Estimates Using Deep Shear Wave Velocity Profile, T. Mai, C. C. Nweke, P. Wang, F. J. Ornelas Jan 2024

Investigating The Viability Of Low Frequency Mhvsr Estimates Using Deep Shear Wave Velocity Profile, T. Mai, C. C. Nweke, P. Wang, F. J. Ornelas

Civil & Environmental Engineering Faculty Publications

Site response describes the alterations of seismic energy due to its interaction with subsurface geological interfaces and structures, which is usually estimated by one dimensional (1D) ground response analysis (GRA). However, 1D GRA requires subsurface information (e.g., shear wave velocity profile), which makes it not widely applicable, particularly for the sites where subsurface information is unavailable. Alternatively, the microtremor horizontal-to-vertical spectral ratio (mHVSR) from three-component recordings of ambient noise on the ground surface is easily measured and is believed to have the potential for site response prediction (the peaks in mHVSR are strongly associated with the site resonant frequencies). However,the …


A General Framework For Modeling Subregional Path Effects, T. E. Buckreis, P. Wang, S. J. Brandenberg, J. P. Stewart Jan 2024

A General Framework For Modeling Subregional Path Effects, T. E. Buckreis, P. Wang, S. J. Brandenberg, J. P. Stewart

Civil & Environmental Engineering Faculty Publications

Next Generation Attenuation (NGA) West2 ground motion models (GMMs) include regional path adjustments for broad jurisdictional regions, which necessarily averages spatially variable path effects within those regions. We extend that framework to account for systematic variations in attenuation within subregions defined in consideration of geologic differences. In recent years, cell-based methods which systematically account for spatial variations by summing the attenuation effects over a fine discretization of uniform-rectangular cells (e.g., Dawood and Rodriquez-Marek 2013; Kuehn et al. 2019) have been shown to be an effective alternative to regionalization and a step towards modelling non-ergodic path effects. The main drawbacks of …


Characterizing Climatic Socio-Environmental Tipping Points In Coastal Communities: A Conceptual Framework For Research And Practice, Julie Elizabeth Shortridge, Anamaria Bukvic, Molly Mitchell, Jesse Goldstein, Tom Allen Jan 2024

Characterizing Climatic Socio-Environmental Tipping Points In Coastal Communities: A Conceptual Framework For Research And Practice, Julie Elizabeth Shortridge, Anamaria Bukvic, Molly Mitchell, Jesse Goldstein, Tom Allen

Political Science & Geography Faculty Publications

The concept of climate tipping points in socio-environmental systems is increasingly being used to describe nonlinear climate change impacts and encourage social transformations in response to climate change. However, the processes that lead to these tipping points and their impacts are highly complex and deeply uncertain. This is due to numerous interacting environmental and societal system components, constant system evolution, and uncertainty in the relationships between events and their consequences. In the face of this complexity and uncertainty, this research presents a conceptual framework that describes systemic processes that could lead to tipping points socio-environmental systems, with a focus on …