Louisiana possesses over 350,000 acres of unique floating vegetated systems known as floating marshes or flotants. Due to their buoyant nature, floating marshes are susceptible to high energy changes in the hydrodynamic environment that may result from proposed river diversion projects which introduce flow to areas that are typically somewhat isolated. The overall goal of this research is to improve the understanding of how exposed flotants deteriorate under increased hydrodynamic stresses. More specifically, this thesis aims to answer how the material limits of floating marshes can be measured and how the mats interact with hydrodynamics. The two primary objectives are: 1) Develop a technique for accurate, in-situ measurement vegetative mat root-soil matrix material properties; and 2) Develop a means for predicting floating marsh washout (critical velocities) through numerically modeled derived empirical relationships.  The device constructed to capture the tensile properties of the vegetative mats, called the Marsh Mat Tensile Strength Tester (MMTST), successfully produced full stress-strain profiles including the Youngs modulus, yield stress, and ultimate strength of a root-soil matrix (sod). The estimated mean Youngs modulus, yield stress, and ultimate strength values (sod) were found to be 31.95 kPa, 9.58 kPa, and 9.91 kPa, respectively. Next, flows around 25 idealized mat geometries were simulated with 2-D & 3-D Fluent models. Mat-specific drag coefficients (Cd,m) were found ranging from 1.084-1.645 depending on mat aspect ratio. An equation developed for predicting Cd,m successfully estimated the modeled drag coefficients with a mean percentage error of 2.33%. A finite element analysis (FEA) was performed on the 25 mat shapes using the predicted drag forces and the material properties measured by the MMTST. By applying various failure criteria (Fc), a correlation was found between the modified mat width-to-length aspect ratio (𝛽) and critical velocity (Vc). The critical velocities ranged from 0.31-1.48 m/s depending on mat aspect ratio and material properties. The general equation developed for predicting floating marsh failure due to flow, in the form: Vc = f(𝛽,Fc), performed well with a mean percentage error of 3.33% relative to the unique values directly extracted from the FEA.

The studies conducted in this thesis evaluate the safety benefits of a blind spot warning (BSW) application and a do not pass warning (DNPW) application at low, medium, and high market penetrations (MP) of connected vehicles (CV) using a high-fidelity driving simulator. Using vehicle-to-vehicle (V2V) communication, CVs can exchange information to alert drivers of potential safety hazards and reduce potential crashes during lane change and overtaking maneuvers. A CV testbed was developed to relay visual and auditory warnings when dangerous thresholds were met for each application. For the BSW a proximity-based threshold was used to trigger a warning as a CV approached the simulator vehicles blind spot. To test the impact of MP on the effectiveness of the BSW Application, four simulation scenarios were developed with zero, 25%, 50%, and 75% MP rates. Drivers were instructed to perform lane change maneuvers whenever they felt comfortable. For each lane change, the simulator vehicle and blind spot vehicles speeds and gaps were collected. Two non-parametric tests, along with a post-hoc pairwise test, were used to compare the significance each MP had on the minimum time-to-collision (TTC) and the variance of the speed of the subject vehicle and blind spot vehicle. A similar study was performed to test the DNPW application. For this pilot study, a TTC threshold was designed to warn drivers of oncoming vehicles on a two-lane two-way rural roadway. Participants performed five overtaking maneuvers within each experiment, totaling to 30 maneuvers for each MP. The safety of each maneuver was evaluated by the TTC between the simulator and oncoming vehicle at the beginning and end of the maneuver, the time spent in the opposing lane, the headway between the simulator vehicle and the vehicle in the right lane before the maneuver, and the tailway between the two vehicles following the maneuver. The results of both studies indicated that a medium MP (50%) is required to achieve significant safety improvement from CV safety applications.

The Expanded Small-Scale Physical Model (ESSPM) is a distorted-scale, moveable bed model that will complement numerical and field studies studying management strategies in the lower ~140 miles of the Mississippi River and their effect on flooding, navigation and coastal restoration. It is recognized that relative sea level rise (RSLR), the combination of eustatic sea level rise (ESLR) and subsidence, will have an impact on the hydraulics and sediment transport in the lower River. However, it is physically impossible to replicate subsidence in the ESSPM; thus, future RSLR conditions will be experimentally simulated by raising Gulf of Mexico (GoM) levels commensurate to future RSLR. The purpose of this thesis is to develop 1- and 2-D numerical models to quantitatively compare the hydraulics and sediment transport characteristics at both the ESSPM and prototype scales under future RSLR conditions in two ways: (1) the natural conditions where river bathymetry is subsided and GoM levels are raised independently; and (2) ESSPM conditions where the combined effect is modeled as ESLR. HEC-RAS 5.0.3 was used to develop 1-D prototype and distorted models, as well as a 2-D prototype model. The 1-D prototype model was first calibrated and validated for 2009 and 2010 Mississippi River conditions. The prototype geometry was replicated at the ESSPM distortion (i.e. the vertical and horizontal axes were scaled 1:400 and 1:6000, respectively). A grid was created from the 1-D cross sections to create the 2-D prototype model. Five future subsidence and ESLR scenarios were simulated for each model under RSLR and model conditions (ESSPM SLR) to compare depth, bed shear stress, and velocity. Differences of depth between RSLR and ESSPM SLR decrease with each station approaching the downstream boundary condition of equal depths with maximum RMSE percentages still below 3%. Velocity and bed shear stress are roughly the same between RSLR and ESSPM SLR and start to deviate at Empire (RM 29.5) and Venice (RM 10.7) with significant differences. ESSPM SLR has a smaller impact on ESSPM model compared to prototype model, and differences in both models increase with each scenario. The 2-D prototype model estimates insignificant differences in all parameters compared to 1-D models.

Distracted driving has long been acknowledged as one of the leading causes of death or injury in roadway crashes. The focus of past research has been mainly on the change in driving performance due to distracted driving. However, only a few studies attempted to predict the type of distraction based on driving performance measures. In addition, past studies have proven that driving performance is influenced by the drivers socioeconomic characteristics, while not many studies have attempted to quantify that influence. In essence, this study utilizes the rich SHRP 2 Naturalistic Driving Study (NDS) database to (a) develop a model for detecting the likelihood of a drivers involvement in secondary tasks from distinctive attributes of driving performance, and (b) develop a grading system to quantify the crash risk associated with socioeconomic characteristics and distracted driving. The results show that the developed neural network models were able to detect the drivers involvement in calling, texting, and passenger interaction with an accuracy of 99.6%, 99.1%, and 100%, respectively. These results show that the selected driving performance attributes were effective in detecting the associated secondary tasks with driving performance. On the other hand, the grading system was developed by three main parameters: the crash risk coefficient, the significance level coefficient, and the category contribution coefficient. At the end, each drivers crash risk index could be calculated based on his or her socioeconomic characteristics. The developed detection models and the systematic grading process could assist the insurance company to identify a drivers probability of conducting distracted driving and assisting the development of cellphone banning regulation by states Departments of Transportation.

Following the Deepwater Horizon oil spill in April, 2010, hard structures were constructed to deter oil migration into sensitive marsh areas behind Fourchon Beach, LA These hard structures created conditions for accumulation and burial of oil across an 8 foot deep beach vertical profile. Buried oil persists in these areas due to anaerobic conditions of beach groundwater. The objectives of this thesis are to compare the rate and extent of biodegradation of 3-ring PAHs in crude oil deposits from the surface and subsurface, and to investigate effects on beach groundwater after introduction of O2. Field samples were removed from 2011-2016 from the area including oil samples from depth with a Geoprobe, oil-sand aggregates distributed over the surface of the beach, free oil floating on the groundwater surface and oil recovered during excavations used as part of response in 2013 and 2015. Weathering of PAHs was estimated based on ratios of alkylated phenanthrenes and dibenzothiophenes to poorly biodegradable chrysenes. The average weathering ratio was 0.731±0.22 for phenanthrenes and 0.48±0.22 for dibenzothiophenes. Results indicate that oil weathers significantly differently based on location in the beach vertical profile. Oil above the groundwater table was significantly more than buried oil below groundwater level. Oil above the groundwater table weathers up to 2 orders of magnitude faster than buried oil below groundwater level. A field trial of in situ biostimulation demonstrated the ability to amend groundwater with oxygen. Weathering of oil buried below the groundwater surface was seen. Terminal electron acceptors and nutrients were evaluated based on repetitive (pre and post oxygen introduction) groundwater analysis of O2, nitrate, nitrite, ferrous and ferric iron, sulfate, sulfide, ammonium, orthophosphate, pH and alkalinity. Results suggest that oxygenated groundwater is confined locally to emitter wells due to slow groundwater movement. Nutrient concentrations pH and temperature are sufficient for microbial function; however the hypersaline nature of the groundwater may limit microbe population.

Temperature differentials (TD) between the target laydown and actual laydown temperatures of asphalt paving mixtures have been noticed and measured since the late 1990s. Since then, numerous research studies conducted on the phenomena found inconclusive conclusions regarding the effects of TD on the initial pavement quality and the long-term performance. The objective of this study was to evaluate the effects of different levels of TD on the initial quality and the long-term performance of asphalt pavements by evaluating the core density and laboratory measured performance characteristics, respectively. Through the evaluation, it was also aimed to ascertain and establish allowable TD range, which would not adversely affect the quality and performance of the pavements. In addition, impacts of construction related factors such as using different types of material transfer vehicles (MTV), different contractors, ambient temperature, etc. on temperature and density differentials were also evaluated. Seven asphalt rehabilitation projects across Louisiana were selected for this study differing in use of mixture type, laydown temperature, mix layer, month of paving, etc. A multi-sensory infrared temperature scanning bar (IR-bar) system and a hand-held portable thermal camera were used to measure the temperature differentials. Field core samples were collected from thermally segregated areas, which were then evaluated in the laboratory using the Density test, Semi-Circular Bending (SCB) test, Loaded Wheel Tracking (LWT) test, and Indirect Tensile Dynamic Modulus (IDT|E*|) test. Two distinct temperature patterns were observed throughout all projects. Cyclic temperature patterns showing regular high-low temperature fluctuations while irregular patterns caused by work stoppages were present in all thermal profiles. Laboratory test results showed pavement density and SCB Jc values correlated strongly with the temperatures measured prior to compaction. LWT, and IDT|E*| test results showed a decreasing trend in rut depth and stiffness with increasing TD severity level. Furthermore, IR-bar temperature readings were used to measure consistency by defining one qualitative (standard deviation) and one quantitative (%severity levels) parameter. Comparisons with construction factors showed that use of MTV increased consistency in temperature. Based on the results of this study, IR-bar system was found useful to monitor consistency in laydown temperatures. However temperature monitoring at breakdown compaction was observed to present actual effect of temperature differential on pavement performance. To ensure that asphalt mixture gets compacted at target temperature, it was strongly advised to instruct breakdown compactor operator to follow the paver closely. Additionally, the use of tarps over un-compacted portion of asphalt mat is strongly advised to prevent significant temperature loss during paver stops.

Healing by means of induction heating is promising, however the effectiveness of this technology is yet to be demonstrated due to limited studies on cracking damage and fracture resistance property recoveries after healing. The objective of this study was to test the hypothesis that a new generation of asphaltic materials could be artificially healed while in-service by embedding metallic fibers in the mix and by applying a magnetic field at the surface. To achieve this objective, an open-graded friction course (OGFC) was successfully designed and prepared to incorporate up to 5% steel and aluminum fibers by weight of the mix. Based on results of the study, it was found that the control mix and the mix prepared with aluminum fibers exhibited a greater ultimate load at failure prior to healing, than those specimens with steel fibers. Yet, differences were not statistically significant. The induction heating experiment was conducted successfully and showed the feasibility of inducing Eddy current in the metallic fibers without contact to the specimens. After healing, the control mix displayed the highest ultimate load after healing, although unsuccessfully heated through Eddy current; yet neither were these differences statistically significant. These outcomes indicate that other healing mechanisms were present due to the recovery period, which allowed the control specimens to heal during the rest period. Healing efficiency showed the highest results for the control specimen that approached 85%. The healing efficiency for the specimen with aluminum and steel fibers was 72 and 62%, respectively. Microscopic image analysis demonstrated that induced cracks healed efficiently during the healing period. Additionally, Loaded Wheel Track (LWT) test was conducted to analyze the rutting performance of the asphalt mixtures with steel and aluminum fibers. The results indicated that the mixture with a high percentage of steel fibers (5.0%) performed better than the ones with less content, while the mixtures with aluminum fibers did not perform well.

Coastal deltaic floodplains provide an important ecosystem service by removing or retaining nitrate from enriched riverine water. Wetland plants, soils, and microbes within these floodplains use nitrate through uptake, burial, and denitrification, thereby reducing the impact of nitrate on algal blooms and hypoxia in the Gulf of Mexico. However, these processes depend on the physical, biological, and chemical conditions within the floodplain. Understanding and characterizing the hydrodynamics of these systems and the relative impact of river, tide, and wind forcings are the first steps in understanding the biogeochemical processes controlling nitrate removal. Motivated by the desire to identify biogeochemical hotspots within coastal deltaic floodplains, this project focuses on modeling the hydrodynamics of these complex wetland ecosystems. Biogeochemical hotspots occur where anaerobic soils, sufficient organic carbon supply, longer residence times, and warmer water temperatures create optimal conditions for processes such as denitrification. The latter two conditions are strongly controlled by the hydrodynamics of the system. A Delft3D-FLOW model is developed for Wax Lake Delta, an actively prograding delta in southeastern Louisiana, in order to simulate daily and seasonal changes in water temperature and residence time within different hydrogeomoprhic zones of coastal deltaic floodplains. From January to March 2015, intertidal floodplains have warmer temperatures and longer residence times (up to 2.5 days) than subtidal floodplains (up to 1.5 days). However, when river discharge increases during spring floods, connectivity between channels and floodplains increases and residence times within all zones decreases as water is flushed more quickly to the Gulf of Mexico. Correctly simulating residence time of water within floodplains is essential to future efforts to model the transformation of nitrate in these systems.

Non-structural factors such as surface distresses and ride quality have been commonly used as the main indicators of in-service pavement conditions. In the last decade, the concept of implementing a structural condition index in Pavement Management System (PMS) to complement functional condition indices has become an important goal for many highway agencies. The Rolling Wheel Deflectometer (RWD) provides the ability to measure pavement deflection while operating at the posted speed limits causing no user delays. The objective of this study was two-fold. First, this study developed a model to predict pavement structural capacity at a length interval of 0.16 km (0.1 mi.) based on RWD measurements and assessed its effectiveness in identifying structurally deficient pavement sections. Second, this study introduced a framework, along with the required implementation tools, for incorporating pavement structural conditions into the Louisiana PMS decision matrix at the network level. The proposed framework aims at filling the gap between network level and project level decisions and eventually, allowing more accurate budget estimation. To achieve these objectives, RWD data collected from 153 road sections (more than 1,600 km) in District 05 of Louisiana were utilized in this study. The predicted Structural Number (SNRWD0.1) showed an acceptable accuracy with a Root Mean Square Error (RMSE) of 0.8 and coefficient of determination (R2) of 0.80 in the validation stage. Core samples showed that sections that were predicted to be structurally-deficient suffered from asphalt stripping and material deterioration distresses. Results support that the developed model is a valuable tool that could be used in PMS at the network level to predict pavement structural condition with an acceptable level of accuracy. With respect to the implementation of RWD in Louisiana PMS, two enhanced decision trees, for collectors and arterials, were developed, such that both functional and structural pavement conditions are considered in the decision-making process. Implementation of RWD in the decision-making process is demonstrated and is expected to improve the overall performance of the pavement network. Furthermore, the enhanced decision trees are expected to reduce the total maintenance and rehabilitation (M&R) construction costs if applied to relatively high volume roads (e.g., Interstates, Arterials, and Major Collectors). Based on the results of this study, a one-step enhanced decision-making tool, which considers both structural and functional pavement conditions in treatment selection, was developed. In the developed tool, the predicted structural number based on RWD measurements was utilized to calculate a pavement structural health indicator known as the Structural Condition Index (SCI). Finally, an Artificial Neural Network (ANN)-based pattern recognition system was trained and validated using pavement condition data and RWD measurements-based SN to arrive at the most optimum maintenance and rehabilitation (M&R) decisions.

This study presents a series of numerical studies of laterally loaded batter pile groups based on data of the full-scale lateral load test on M19 eastbound pier foundation of the new I-10 Twin Span Bridge, Louisiana. The numerical studies include several continuum-based 3D finite element analyses on batter/vertical pile/pile groups and a FB-MultiPier analysis of the pile foundation. The Anisotropic Modified Cam Clay Model, has been implemented into UMAT and applied for describing clay behavior in all FE models. The explicit substepping scheme with modified Euler algorithm is selected to implement the model in ABAQUS software. The resultant UMAT shows good accuracy compared to the ABAQUS in-built Modified Cam Clay model. Also it exhibits wonderful computational stability and efficiency in the pile group analyses, which greatly accelerated the whole research processes. The results of FE analyses were compared with the measured field data from lateral load test and those predicted by FB-MultiPier. All of them showing good agreement on lateral deformation profiles and bending moment profiles. The comparison of the lateral deflection, bending moment, soil resistance and lateral/ vertical load distributions between different spacing batter/ vertical pile groups and single isolated pile illustrate that small spacing and the vertical piles will produce intensified group effect. The concept of trapezoidal zone is firstly proposed to explain the axial load distribution pattern of batter pile group foundation. An additional coupled pore fluid diffusion and stress analysis on a single pile model demonstrated that the resultant excessive pore pressure caused by lateral loads has limited influence on the result of FE analyses.