Flue Gas Desulfurization sludge (FGD, CaSO4·2H2O, CaSO3·1/2H2O) is a waste by-product produced when sorbent slurry is passed through wet scrubbers. FGD contains higher concentrations of Ca, S, Si, Fe, Al and Br making it of great environmental concern. Presently only 16% of 24 million metric tons (MT) of FGD sludge produced is being recycled; the rest is disposed in landfills. This research was focused towards stabilizing FGD sludge with Portland Type II cement and Class C fly ash to produce lightweight fill material to be used in the construction of coastal devices. The specific objectives included the development of a FGD briquette composition that under submerged conditions: 1) maintained physical integrity, 2) has minimal dissolution of Ca2+ and SO42- to the surroundings 3) demonstrates acceptable engineering properties of a fill material and 4) economical to fabricate. The leaching behavior of all the FGD composites was found to be similar and the effective diffusion coefficients from the 77-day dynamic leaching test ranged 4.877.01 x 10-13 m2·s-1and 0.67 3.71 x 10-13 m2·s-1, for calcium and sulfate respectively. The metal concentrations in the TCLP leachate were well below the USEPA toxicity characteristics limits. The engineering properties test results indicated that the composite material could be classified as well-graded gravel or well-graded sand with little or no fines. The USCS classification would also qualify FGD briquettes as a potential fill material in embankment construction having excellent workability and shear angle of 48° to 49°. For all the tests conducted the 63%:35%:2% briquette fabricated in small size performed better than the large size briquette. Among the selected four 77%: 20%: 03%, 69%: 30%:01%, 67%: 30%:03%. and 64%: 35%: 1% FGD: Class C fly ash: Portland Type II cement composites the 77%: 20%: 3% FGD: Class C fly ash composite showed promising results with lowest diffusion coefficients for Ca2+, SO42-, no signs of degradation after eight months of field submergence and lowest production cost of $11.35·ton-1 (year 2003).

Structural materials display a strong size-dependence when deformed non-uniformly into the inelastic range: smaller is stronger. This effect has important implications for an increasing number of applications in structural failure, electronics, functional coatings, composites, micro-electro-mechanical systems (MEMS), nanostructured materials, micro/nanometer fabrication technologies, etc. The mechanical behavior of these applications cannot be characterized by classical (local) continuum theories because they incorporate no material length scales and consequently predict no size effects. On the other hand, it is still not possible to perform quantum and atomistic simulations on realistic time and structures. It is therefore necessary to develop a scale-dependent continuum theory bridging the gap between the classical continuum theories and the atomistic simulations in order to be able to design the size-dependent structures of modern technology. Nonlocal rate-dependent and gradient-dependent theories of plasticity and damage are developed in this work for this purpose. We adopt a multi-scale, hierarchical thermodynamic consistent framework to construct the material constitutive relations for the scale-dependent plasticity/damage behavior. Material length scales are implicitly and explicitly introduced into the governing equations through material rate-dependency (viscosity) and coefficients of spatial higher-order gradients of one or more material state variables, respectively. The proposed framework is implemented into the commercially well-known finite element software ABAQUS. The finite element simulations of material instability problems converge to meaningful results upon further refinement of the finite element mesh, since the width of the fracture process zone (shear band) is determined by the intrinsic material length scale; while the classical continuum theories fail to address this problem. It is also shown that the proposed theory is successful for the interpretation of indentation size effects in micro/nano-hardness when using pyramidal and spherical indenters and gives sound interpretations of the size effects in micro-torsion of thin wires and micro-bending of thin beams. Future studies should be directed toward incorporation of the size effects into design procedures and code recommendations of modern engineering structures (e.g. for MEMS, NEMS, coatings, thin films), fiber composites (e.g. for aircrafts and ships), etc.

Microscopic simulation models are more and more widely used to support real-time control and management functions in the field of transportation engineering. However, even with today¡¯s advancement in computing power, microscopic simulation modeling remains a computationally intensive process that imposes limitations on its potential use for modeling large-scale transportation networks. While microscopic features of a simulated system collectively define the overall system characteristics, it is argued here that the simulation process itself is not necessarily free of redundancy which, if reduced, could substantially improve the computational efficiency of simulation processes without substantially compromising the overall integrity of the simulation process. The idea of this research is to explore the concept of scalability for microscopic traffic simulation systems in order to improve their computational efficiency and cost-effectiveness. In an attempt to strike the balance between simulation performance and computational resources, we present an optimized downsampling procedure to transform the full-scale simulation system into an equivalent reduced-scale system. The primary goal of this research is to maximize the fidelity to microscopic simulation properties while maintaining the same macroscopic properties, such as flow rate, speed, and density. Experimental analysis was conducted on a homogeneous freeway corridor to examine the behavioral scalability of sophisticated nonlinear car-following models. A methodology to address lane-changing scalability is also included in this research study.

Lauryl Alkylbenzene Sulfonate (LAS) is the major anionic surfactant used worldwide in detergent and household cleaning product formulations. Its biodegradation and removal has been extensively studied in wastewater treatment facilities and laboratory-scale tests at low concentrations (<10 mg/L) typical of those encountered in municipal wastewater treatment plants. Less effort, however, has been expended investigating degradation of higher concentrations of LAS representative of those expected in wastewater generated at LAS manufacturing operations. The research described in this thesis was conducted to study biological processes for treating wastewaters containing high concentrations (e.g., 400 mg/L) of LAS. Initial experiments were carried out using a respirometry technique, and subsequently, three different laboratory-scale bioreactor systems. The three systems studied were a Sequencing Batch Reactor (SBR), a Sequencing Batch Biofilm Reactor (SBBR), and an Intermittent Cycle Extension Aeration System (ICEAS). The SBR and ICEAS were operated on a five-day cycle basis with a hydraulic retention time of four days. The SBBR was operated mainly in a two-day cycle having a hydraulic retention time of ten days as well, and polyurethane foam cubes were used as a support medium for attached biomass growth. The three systems were compared on their ability to remove LAS measured in terms of total organic carbon (TOC) and methylene blue active substances (MBAS). The reactors were also compared on the basis of foam production. The ICEAS showed the best performance in terms of controllable foam production while exhibiting a capacity for effectively dealing with transient periods of elevated loading. When a short Fill period was used, the SBR and SBBR had the disadvantage of producing excessive foaming, and an intermittent aeration strategy was required avoid overflow.

The ability of removing toxic organic compounds in natural systems is important due to the capacity of these toxicants to increase risk of diseases when they are ingested by humans. This study developed a mechanistic model to estimate the removal efficiency of toxic organics in wetlands using the tanks-in-series model. Sensitivity analyses were performed for different values of the hydraulic loading rate and two kinds of wetlands: bottomland hardwood forest and freshwater marsh. It was observed the effect in the removal efficiency by the number of cell in series was principally perceived for values of N between 1 and 4; that for both kind of wetlands. The most hydraulic loading rate, the less removal of organic compounds was observed in both kinds of wetlands and for the different values of N. For the same value of hydraulic loading rate, number of sections considered (N) and the same kind of wetland, soluble organics (low K_ow) as naphthalene were more assimilated than hydrophobic organics (high K_ow) as hexachlorobenzene. Two zones were well defined on the logarithmic space defined by Sorption versus Henry's Constant for two conditions total recycle and no recycle: Air zone and sediment zone. Removal efficiency went down when the value of DOC in the water column went up for insoluble organics as hexachlorobenzene. For soluble organics as naphthalene no effect was observed. That was observed in both kinds of wetlands. Removal efficiency has no a large dependence of the value of DOC in the sediment bed, in both kinds of wetlands and for both kind of compounds (lower and higher K_ow value). The higher K_w of the pollutant, the higher removal in both of the kind of wetlands was observed in this analysis. It was observed that removal efficiency is higher when the sediment bed depth is higher until determined values depending of the kind of pollutant. It was observed that removal efficiency is higher for soluble organics as naphthalene than for hydrophobic organics as hexachlorobenzene, and in addition higher removal efficiency is observed in bottomland hardwood forest wetlands than in freshwater marshes.

Little attention has been given to estimating dynamic travel demand in transportation planning in the past. However, when factors influencing travel are changing significantly over time such as with an approaching hurricane - dynamic demand and the resulting variation in traffic flow on the network become important. In this study, dynamic travel demand models for hurricane evacuation were developed with two methodologies: survival analysis and sequential choice model. Using survival analysis, the time before evacuation from a pending hurricane is modeled with those that do not evacuate considered as censored observations. A Cox proportional hazards regression model with time-dependent variables and a Piecewise Exponential model were estimated. In the sequential choice model the decision to evacuate in the face of an oncoming hurricane is considered as a series of binary choices over time. A sequential logit model and a sequential complementary log-log model were developed. Each model is capable of predicting the probability of a household evacuating at each time period before hurricane landfall as a function of the households socio-economic characteristics, the characteristics of the hurricane (such as distance to the storm), and policy decisions (such as the issuing of evacuation orders). Three datasets were used in this study. They were data from Southwest Louisiana collected following Hurricane Andrew, data from South Carolina collected following Hurricane Floyd, and stated preference survey data collected from New Orleans area. Based on the analysis, the sequential logit model was found to be the best alternative for modeling dynamic travel demand for hurricane evacuation. The sequential logit model produces predictions which are superior to those of current evacuation participation rate models with response curves. Transfer of the sequential logit model estimated on the Floyd data to the Andrew data demonstrated that the sequential logit model is capable of estimating dynamic travel demand in a different environment than the one in which it was estimated, with reasonable accuracy. However, more study is required on the transferability of models of this type, as well as the development of procedures that would allow the updating of transferred model parameters to better reflect local evacuation behavior.

Because of the potential for serious train-vehicle accidents at or near railroad-highway grade crossings, preemption of traffic signals is a very important supplement to an active warning system. Preemption is the transfer of normal signal phasing to a special control mode with the purpose of clearing any vehicles that are queued within the dynamic envelope as the train approaches, and prohibiting signal phases that would allow additional vehicles in the track area while the train is present. The focus of this research was the determination of the Clear Track Green Interval (or the Queue Clearance Time). The clear track green interval is the most important component of the preemption process because this is the time allotted to clear any vehicles that are queued within the track dynamic envelope. The estimation of the amount of time needed for the Clear Track Green Interval is often left to the discretion of the traffic engineer. To date, the Louisiana Department of Transportation and Development has no explicit guidelines for the traffic engineers in their design of railroad preemption for traffic signals. This research describes the evaluation of three methodologies that can be used to acquire the clear track green interval for an intersection. The study provides a comparison of the calculated values versus the field (or observed) values with the objective being to show if the calculated times are adequate or if they provide too much time for the action thereby causing adverse affects to the intersection. The second objective of this research is to provide guidance to the traffic engineers in the design of railroad preemption for traffic signals. Based on the results and analysis of this research, the field observed method yielded a lower clear track green interval 71% of the time. Out of the remaining two methods, the Marshall/Berg method yielded lower results 29% of the time and the Northwestern method always yielded a longer time because of its conservative approach. The instances when the Marshall/Berg method yielded lower results has varying causes. The reasons included: intersections where the side approaches shared the phasing causing the track side approach to have to compete with the other approach to move beyond the track, red light runners causing the drivers to hesitate before proceeding out into the intersection, and geometry issues.

The use of high-speed data acquisition systems, inexpensive and reliable transducers, and better models of interpretation have combined to make elastic wave tomographic imaging of geotechnical engineering systems easier to accomplish both in the laboratory and in the field. An important application of these developments is that the evaluation of states of effective stress in soils using images of elastic wave velocity distribution. As a consequence, it is possible to experimentally estimate the state of induced and in-situ effective stresses and to compare these results with established models of stress distribution based on the theory of elasticity (e.g., Boussinesqs solution). The effective stress versus shear wave velocity relationship follows a Hertz model. The parameters for this relationship are calibrated by testing the dry sand in both a modified triaxial cell and an oedometer cell hosting bender elements. The long term objective of this research is to obtain a tomographic image of the states of in-situ and induced stresses in clean, dry sand underneath a model footing. The post calibration test program consists of a test cell that is capable of yielding a Ko-state of stress condition while allowing independent control of simulated overburden pressure and bearing pressure. The elastic waves will be generated and received using bender elements (i.e., bimorph piezoceramic crystals). Justification of the travel time data from the test cell is made possible by a numerical integration of the Boussinesq solution for our stress conditions. Furthermore, velocity field images are presented as well as recommendations for improvements.

This dissertation details the results of recent investigations concerning non-colloidal particulate matter found in urban rainfall-runoff and urban snowmelt. Three forms of the power law model (PLM) were used to model particle number density. It was found that significant model error could be introduced into PLMs when the median diameter particle was used to estimate the number of particles per interval, but the SSE of continuous PLMs could be significantly reduced through the use of correction factors when the sieve interval was large (P<0.05). Additionally, a multiple PLM analysis may be more appropriate than a single PLM analysis when changes in particle population occur within a single gradation. PLMs were also used to model the relationship between cumulative granulometric mass and cumulative particulate-bound metal mass. The use of such calibrated PLMs provided considerable cost reduction when compared to conventional direct measurements of particulate-bound metal mass. A first flush analysis indicated that only events with average volumetric flow rates approaching 1 L/min/m of drainage width exhibit a rapid depletion of particulate matter consistent with the concentration-based definition of the first flush. An analysis of particle separation mechanisms indicated that 90% of these particles, by mass, could be removed from the discharge with detention times of 30 min and 120 min for snowmelt and rainfall-runoff, respectively, in a typical roadside drainage system. It was also found that the kinematic wave model could accurately model significant aspects of rainfall-runoff events in traffic-impacted watersheds provided that abstractions were incorporated into the modeling process. For this watershed the source of abstraction was attributable to vehicular traffic. For high-intensity events with more than 10 vehicles per runoff volume (VPV) the runoff coefficient varied between 0.6 and 0.9 while for low-intensity events with fewer than 10 VPV the coefficient ranged between 0.2 and 0.4.

Geotechnical engineering materials are inherently variable, which leads to many simplifications when trying to model their behavior. The materials must always be characterized prior to any design work so that the engineer knows which direction he must progress to have a reliable design. Although subsurface characterization techniques and geotechnical design steadily improve, they are by no means infallible. The combination of geotechnical subsurface characterization along with geophysical techniques for improved design and construction monitoring has begun to surface as a viable alternative to the standard techniques in geotechnical engineering. This is important because there is a lack of Quality Control/Quality Assurance during the construction stage of a project, which further compounds the problems inherent from the complexity of the subsurface. Geophysical techniques based on elastic wave propagation provide an excellent combination of characterization and monitoring for the observation of geotechnical engineering projects. Elastic wave propagation provides coverage between traditional boreholes and it helps infer changes in the state of stresses. Unfortunately, sensors for this type of monitoring have typically been expensive, and the use of elastic wave propagation for characterization and monitoring has just begun to become to be implemented. The application of elastic wave tomography needs an inexpensive set of sensors to help justify its inclusion in the broad area of construction monitoring and characterization systems. This set of inexpensive sensors has arrived on the market developed from Miniature Electro-Mechanical Systems (MEMs) technology. This research developed the Analog Devices ADXL250 MEMS accelerometer to determine its limitations and its range of applications. In addition, a packaging system developed to allow for a broader range of applications in geotechnical engineering. Once the sensor was fully calibrated, a long-term goal for the research was to utilize the instrument in a laboratory experiment to obtain a tomographic image of the state of stress within a model. While the sensor was utilized in a model in this study, the final reasoning for its use within the model was simply to show its capabilities and areas of application. Simple velocity distributions are given as well as inferences made about the driving factors for these behaviors.