Department of Civil, Environmental and Geomatics Engineering

This thesis presents the development of an innovative Geographic Information System (GIS)-based Interactive Online Watershed Dashboard aimed at flood risk assessment and mitigation in Charlotte County, Florida. The research leverages advanced GIS techniques, including flood inundation simulations using CASCADE 2001, integrating LiDAR DEM data and GIS layers such as impervious surfaces, waterbodies, and soil characteristics to model flood behavior in 61 inundation probability scenarios. Key results include detailed flood inundation probability maps categorizing risk levels based on Z-scores, providing actionable insights for flood risk management and emergency planning. Spatial analysis reveals demographic vulnerabilities, with population density and ethnic compositions intersecting flood vulnerability. The study assesses flood impacts on transportation infrastructure and prioritizes critical facilities for resilience strategies. The dashboard's design integrates diverse datasets and analytical results, allowing users to interactively explore flood risk scenarios, critical infrastructure vulnerabilities, and demographic impacts. This research contributes essential tools for informed decision-making, enhancing flood resilience and disaster preparedness in Charlotte County, Florida.

Intermodal facilities, including port operations, play a significant role in the economic framework of the United States by making substantial contributions to the country's GDP, but face challenges managing increased freight volumes. However, increased transportation time within port facilities leads to higher costs, emissions, and impacts on efficiency and sustainability. This thesis aims to develop a concept of operations (ConOps) for improving the efficiency of heavy truck movement outside ports, with goals of reducing congestion, considering greenhouse gas (GHG) emissions, and addressing issues faced by the truck drivers. The study proposes integrating technological solutions to streamline heavy truck traffic at intermodal port facilities, including scheduled truck arrivals and departures, truck stop and rest areas near ports, real-time traffic information, implementation of dedicated truck lanes, and autonomous truck platooning. The focus is improving communication, efficiency, and safety for trucking companies, operations managers, and truck drivers. Using microsimulation modeling in PTV VISSIM (2023), a traffic impact study is also conducted, focusing on a case study near the Port of Miami. A base scenario is developed to represent current traffic conditions, and additional scenarios are implemented to evaluate different strategies, such as dedicated and exclusive truck lanes, freeway lane restrictions, and autonomous truck platooning. Simulation findings emphasize the positive impact of these strategies on travel times and delays, and forecast scenarios account for increased truck volumes. Dedicated truck lanes and truck platooning demonstrate promising results in reducing congestion and improving overall traffic flow. This research supports decision-making for government officials and logistics service providers in sustainable and efficient intermodal freight planning. The study also suggests opportunities for future extensions, including emerging technologies and tailored solutions for different port locations and contexts.

Today’s mainstream vehicles are partially automated via an advanced driver assistance feature (ADAS) known as Adaptive Cruise Control (ACC). ACC uses data from on-board sensors to automatically adjust speed to maintain a safe following distance with the preceding vehicle. Contrary to expectations, ICE vehicles equipped with ACC may reduce capacity at bottlenecks because its delayed response and limited initial acceleration during queue discharge could increase the average headway. On the other hand, ACC equipped EVs can potentially mitigate this effect for having ready torque and quicker acceleration. However, this has not been investigated for cases when lane changers enter from the adjacent lane. ACC could respond differently under these conditions, and this car following behavior is often referred as receiving lane change car following. Carefully planned field experiments on lane change car following demonstrate that lane changes and the subsequent receiving lane change car following from ICE vehicles equipped with ACC increases the gap unless the lane changer and the target lane traffic have identical or similar speeds for internal combustion engine (ICE) vehicles and ACC in the EVs doesn’t increase the gap after lane change increasing capacity for merging compared to ICE vehicles. For ICE, this trend also correlates with the selected ACC gap, with larger gap selection resulting in longer gap following the lane change maneuver and the receiving lane change car following in response. Larger gap setting shows better results after lane change for EVs.

Today’s mainstream vehicles are partially automated via an Advanced Driver Assistance Feature (ADAS) known as Adaptive Cruise Control (ACC). ACC relies on data from onboard sensors to automatically adjust speed to maintain a safe following distance with the preceding vehicle. Contrary to expectations for automated vehicles, ACC may reduce capacity at bottlenecks because its delayed response and limited initial acceleration during queue discharge could increase the average headway. Fortunately, when ACC is paired with fully electric vehicles (EVs), EV’s unique powertrain characteristics such as instantaneous torque and aggressive regenerative braking could allow ACC to adopt shorter headways and accelerate more swiftly to maintain shorter headways during queue discharge, therefore reverse the negative impact on capacity. This has been verified in a series of car following field experiments. Field experiments demonstrate that EVs with ACC can achieve a capacity as high as 3333 veh/hr/lane when cruising in steady state conditions at typical freeway speeds (60 mph and 55 mph) and arterial speeds (45 mph and 35 mph). Furthermore, speed fluctuations and disturbances that may come from queues forming at or near the bottleneck do not reduce the capacity, unlike ACC-equipped internal combustion engine (ICE) vehicles, making ACC-equipped EVs outperform ICE vehicles with ACC, as well as human drivers.

Artificial reefs are coastal structures built to improve marine life and prevent beach erosion. During earlier days artificial reefs were constructed for recreational fishing using discarded scraps and waste materials. Later on, ships were scuttled for constructing artificial reefs. Artificial reefs dissipate the energy of the wave by making the wave break over the reef. The artificial reefs used for coastal protection are usually in submerged condition as this condition does not affect the aesthetic beauty of the beach. Wave transmission decides the efficiency of submerged-detached artificial reef in protecting the beach from the incoming waves. The efficiency of submerged detached coastal protection structures in protecting the beach is usually measured in terms of wave transmission coefficient.
The experimental investigation in the present study is carried out for submerged two-dimensional impermeable and permeable reefs for three water depths. The crest width of the reefs considered for the experimental studies are 60 cm and 20 cm. The permeable artificial reefs are made up of oyster shells in Nylon bags and biodegradable bags. The water levels considered for the study are 35 cm, 34 cm, and 33 cm. The effect of pore space between the oyster shells, crest width, water depth and wave parameters on the wave transmission coefficient for submerged impermeable and permeable artificial reefs are studied experimentally. The wave transmission coefficient is calculated for submerged impermeable and permeable reefs for different water levels and crest widths. Based on the results of the present experimental studies, it is logical to conclude that both submerged impermeable and permeable artificial reefs contribute to a significant extent to the attenuation of the incident wave.

As the global population is increasing, the generation of various waste materials (fats, oils and grease, fruit waste etc.) is increasing, which when landfilled, takes up valuable landfill space. Anaerobic digestion techniques have been developed that potentially convert these waste materials into energy and fertilizer, thus reducing landfill demand. It has been hypothesized that addition of high strength organic waste to conventional wastewater sludge can enhance the generation of onsite biogas at wastewater treatment plants, to meet the energy requirements of the plant partially or fully.
To determine the anaerobic biodegradability of fats, oils and grease and fruit waste residuals, lab scale ultimate digestibility tests were conducted for a period of 63 days under mesophilic conditions. High strength organic wastes, thickened waste activated sludge and inoculum were mixed at 9 different ratios, and the mixtures were incubated in 500 mL serum bottles. After 63 days, the highest methane yield of 280 mL/gVS and 243 mL/gVS were obtained with mixtures containing 10% FOG with 10% red apples and 10% FOG only respectively whereas the methane yield of inoculum was only 8 mL/gVS. Preliminary cost analyses were conducted using the laboratory derived data

Pile foundations are subjected to vertical loads and significantly higher lateral loads due to wind, seismic effects, ocean waves and currents, and floating ice sheets. Applied vertical load on a pile is resisted by the skin friction and base resistance. The base resistance is provided by the soil layer and skin friction develops at the soil-pile interface. The lateral load on the pile is resisted by the soil-pile interaction effect, which is dependent on the pile and soil parameters. Published literature shows that a properly designed Pile-to-Pile Cap (PTPC) connection will offer significant lateral resistance to the applied loads. The soil-pile system behavior is highly non-linear which requires a detailed study on the soil-structure interaction considering multi-layered soil strata and their properties.
This Dissertation is divided into two parts: Evaluation of (A) the behavior and performance of PTPC connections, and (B) the load-displacement responses of a pile embedded in a multi-layered non-linear elastic soil strata subjected to static loads. A comprehensive literature review has been performed to study the factors affecting the PTPC connection performances and the load-displacement behavior of piles subjected to static lateral and axial loads considering soil-pile interactions. The objective of the study in Part A is to develop a PTPC connection design capable of producing adequate moment capacity of the pile by relying only on plain pile embedments without any special connection reinforcement details. The present study evaluates the local and global behavior of the PTPC connections with plain pile embedment through Finite Element Analyses (FEA).

Amine-grafted silica (i.e., aminosilicas) was investigated for single-stage landfill gas purification via simultaneous removal of CO2, H2S, and water vapor. Aminosilica materials were synthesized by covalent triamine grafting onto mesoporous silica with custom amounts of water and amine. Screening adsorption experiments were completed in dry 30 vol.% CO2 in N2 at 40 °C and assessed using thermogravimetric analysis. Materials with equilibrium CO2 uptakes greater than 1.5 mmol/g were chosen for CO2 adsorption kinetics assessments. The highest-performing aminosilica achieved fast CO2 adsorption by reaching 80% of its equilibrium uptake in one minute. This material also maintained 100% of its initial CO2 uptake when subjected to rigorous 100-cycle testing. It underwent column-breakthrough tests in the presence of different dry and humid gas streams containing CO2, H2S, and water vapor, and achieved concurrent and complete (100%) removal of all target impurities. The results suggest that aminosilicas can purify landfill gas in a single stage.

Mainstream vehicles sold today are equipped with the Advanced Driver Assistance System (ADAS) known as Adaptive Cruise Control (ACC). ACC automatically adjusts speeds and maintains a safe following distance with the preceding vehicle. This enables partial automation by automating longitudinal car-following. Despite the ever-increasing market penetration, ACC-equipped vehicles will likely operate in a mixed environment with other human-driven vehicles first. However, the traffic flow impact of human driver behavior when following ACC-equipped vehicles is largely unknown, and it is uncertain whether this deserves special consideration when modeling human driver behavior near ACC enabled vehicles. This study conducted a preliminary real-world experiment on a freeway (a portion of Interstate 95) and an urban arterial (a portion of state route A1A) to investigate the human driver behavior with and without the presence of vehicles in ACC mode as the leaders. This unbiased experiment was conducted in naturalistic traffic conditions. Results from the field experiments demonstrate that in a mixed environment with ACC-equipped vehicles as leaders, the human driven vehicles as the follower adopt similar headway, spacing, and acceleration on both freeway and arterial, with no statistically significant difference. The only exception is when traveling at speeds below 15 mph on urban arterials, where human drivers adopt significantly larger spacing while following ACC-enabled vehicles. We expect that findings from these field experiments will provide important initial insights to future research on human driver car following models in a mixed traffic environment and dedicated lanes for automated vehicles.

Adaptive cruise control (ACC) system is the first widely offered automated functionality that regulates the longitudinal movement of the vehicle using onboard radar sensors, and they can maintain a safe following distance with the preceding vehicle. In most of the field experiments with ACC-equipped vehicles conducted with internal combustion engine vehicles, there is still a gap in research on how the automation systems such as ACC combined with electric powertrains will influence the traffic flow be examined.
This study refined and recalibrated an ACC car-following model for EVs and integrated it into AIMSUN to realistically simulate ACC-equipped vehicles and their impact on the fundamental diagram of traffic flow. Simulations were conducted for various ACC market penetrations, and fundamental diagrams were constructed for those market penetrations using detector measurements at various locations along the simulated segment. Overall, the capacity and the jam density increase as the EV with ACC market penetration rises. EVs with ACC can achieve higher capacities compared to ICEs with ACC.