Effective energy conservation and management in the building sector : the answer to the energy predicament

Modern civilization has developed principally through man's harnessing of forces. For centuries man had to rely on wind, water and animal force as principal sources of power. The advent of the industrial revolution, electrification and the development of new technologies led to the application of wood, coal, gas, petroleum, and uranium to fuel new industries, produce goods and means of transportation, and generate the electrical energy which has become such an integral part of our lives. The geometric growth in energy consumption, coupled with the world's unrestricted growth in population, has caused a disproportionate use of these limited natural resources. The resulting energy predicament could have serious consequences within the next half century unless we commit ourselves to the philosophy of effective energy conservation and management. National legislation, along with the initiative of private industry and growing interest in the private sector has played a major role in stimulating the adoption of energy-conserving laws, technologies, measures, and practices. It is a matter of serious concern in the United States, where ninety-five percent of the commercial and industrial facilities which will be standing in the year 2000 - many in need of retrofit - are currently in place. To conserve energy, it is crucial to first understand how a facility consumes energy, how its users' needs are met, and how all internal and external elements interrelate. To this purpose, the major thrust of this report will be to emphasize the need to develop an energy conservation plan that incorporates energy auditing and surveying techniques. Numerous energy-saving measures and practices will be presented ranging from simple no-cost opportunities to capital intensive investments.

Understanding Immigrants' Travel Behavior in Florida: Neighborhood Effects and Behavioral Assimilation

The goal of this study was to develop Multinomial Logit models for the mode choice behavior of immigrants, with key focuses on neighborhood effects and behavioral assimilation. The first aspect shows the relationship between social network ties and immigrants’ chosen mode of transportation, while the second aspect explores the gradual changes toward alternative mode usage with regard to immigrants’ migrating period in the United States (US). Mode choice models were developed for work, shopping, social, recreational, and other trip purposes to evaluate the impacts of various land use patterns, neighborhood typology, socioeconomic-demographic and immigrant related attributes on individuals’ travel behavior. Estimated coefficients of mode choice determinants were compared between each alternative mode (i.e., high-occupancy vehicle, public transit, and non-motorized transport) with single-occupant vehicles. The model results revealed the significant influence of neighborhood and land use variables on the usage of alternative modes among immigrants. Incorporating these indicators into the demand forecasting process will provide a better understanding of the diverse travel patterns for the unique composition of population groups in Florida.

Water Demand and Allocation in the Mara River Basin, Kenya/Tanzania in the Face of Land Use Dynamics and Climate Variability

The Mara River Basin (MRB) is endowed with pristine biodiversity, socio-cultural heritage and natural resources. The purpose of my study is to develop and apply an integrated water resource allocation framework for the MRB based on the hydrological processes, water demand and economic factors. The basin was partitioned into twelve sub-basins and the rainfall runoff processes was modeled using the Soil and Water Assessment Tool (SWAT) after satisfactory Nash-Sutcliff efficiency of 0.68 for calibration and 0.43 for validation at Mara Mines station. The impact and uncertainty of climate change on the hydrology of the MRB was assessed using SWAT and three scenarios of statistically downscaled outputs from twenty Global Circulation Models. Results predicted the wet season getting more wet and the dry season getting drier, with a general increasing trend of annual rainfall through 2050. Three blocks of water demand (environmental, normal and flood) were estimated from consumptive water use by human, wildlife, livestock, tourism, irrigation and industry. Water demand projections suggest human consumption is expected to surpass irrigation as the highest water demand sector by 2030. Monthly volume of water was estimated in three blocks of current minimum reliability, reserve (>95%), normal (80–95%) and flood (40%) for more than 5 months in a year. The assessment of water price and marginal productivity showed that current water use hardly responds to a change in price or productivity of water. Finally, a water allocation model was developed and applied to investigate the optimum monthly allocation among sectors and sub-basins by maximizing the use value and hydrological reliability of water. Model results demonstrated that the status on reserve and normal volumes can be improved to ‘low’ or ‘moderate’ by updating the existing reliability to meet prevailing demand. Flow volumes and rates for four scenarios of reliability were presented. Results showed that the water allocation framework can be used as comprehensive tool in the management of MRB, and possibly be extended similar watersheds.

Integration of a Sedimentation Module to a Hydrologic Model and its Application to a Mercury TMDL Analysis

This research is part of continued efforts to correlate the hydrology of East Fork Poplar Creek (EFPC) and Bear Creek (BC) with the long term distribution of mercury within the overland, subsurface, and river sub-domains. The main objective of this study was to add a sedimentation module (ECO Lab) capable of simulating the reactive transport mercury exchange mechanisms within sediments and porewater throughout the watershed. The enhanced model was then applied to a Total Maximum Daily Load (TMDL) mercury analysis for EFPC. That application used historical precipitation, groundwater levels, river discharges, and mercury concentrations data that were retrieved from government databases and input to the model. The model was executed to reduce computational time, predict flow discharges, total mercury concentration, flow duration and mercury mass rate curves at key monitoring stations under various hydrological and environmental conditions and scenarios. The computational results provided insight on the relationship between discharges and mercury mass rate curves at various stations throughout EFPC, which is important to best understand and support the management mercury contamination and remediation efforts within EFPC.

Variable Speed Limit Strategies to Reduce the Impacts of Traffic Flow Breakdown at Recurrent Freeway Bottlenecks

Variable Speed Limit (VSL) strategies identify and disseminate dynamic speed limits that are determined to be appropriate based on prevailing traffic conditions, road surface conditions, and weather conditions. This dissertation develops and evaluates a shockwave-based VSL system that uses a heuristic switching logic-based controller with specified thresholds of prevailing traffic flow conditions. The system aims to improve operations and mobility at critical bottlenecks. Before traffic breakdown occurrence, the proposed VSL’s goal is to prevent or postpone breakdown by decreasing the inflow and achieving uniform distribution in speed and flow. After breakdown occurrence, the VSL system aims to dampen traffic congestion by reducing the inflow traffic to the congested area and increasing the bottleneck capacity by deactivating the VSL at the head of the congested area. The shockwave-based VSL system pushes the VSL location upstream as the congested area propagates upstream. In addition to testing the system using infrastructure detector-based data, this dissertation investigates the use of Connected Vehicle trajectory data as input to the shockwave-based VSL system performance. Since the field Connected Vehicle data are not available, as part of this research, Vehicle-to-Infrastructure communication is modeled in the microscopic simulation to obtain individual vehicle trajectories. In this system, wavelet transform is used to analyze aggregated individual vehicles’ speed data to determine the locations of congestion. The currently recommended calibration procedures of simulation models are generally based on the capacity, volume and system-performance values and do not specifically examine traffic breakdown characteristics. However, since the proposed VSL strategies are countermeasures to the impacts of breakdown conditions, considering breakdown characteristics in the calibration procedure is important to have a reliable assessment. Several enhancements were proposed in this study to account for the breakdown characteristics at bottleneck locations in the calibration process. In this dissertation, performance of shockwave-based VSL is compared to VSL systems with different fixed VSL message sign locations utilizing the calibrated microscopic model. The results show that shockwave-based VSL outperforms fixed-location VSL systems, and it can considerably decrease the maximum back of queue and duration of breakdown while increasing the average speed during breakdown.

Reducing Uncertainties in Estimation of Wind Effects on Tall Buildings Using Aerodynamic Wind Tunnel Tests

Tall buildings are wind-sensitive structures and could experience high wind-induced effects. Aerodynamic boundary layer wind tunnel testing has been the most commonly used method for estimating wind effects on tall buildings. Design wind effects on tall buildings are estimated through analytical processing of the data obtained from aerodynamic wind tunnel tests. Even though it is widely agreed that the data obtained from wind tunnel testing is fairly reliable the post-test analytical procedures are still argued to have remarkable uncertainties. This research work attempted to assess the uncertainties occurring at different stages of the post-test analytical procedures in detail and suggest improved techniques for reducing the uncertainties. Results of the study showed that traditionally used simplifying approximations, particularly in the frequency domain approach, could cause significant uncertainties in estimating aerodynamic wind-induced responses. Based on identified shortcomings, a more accurate dual aerodynamic data analysis framework which works in the frequency and time domains was developed. The comprehensive analysis framework allows estimating modal, resultant and peak values of various wind-induced responses of a tall building more accurately. Estimating design wind effects on tall buildings also requires synthesizing the wind tunnel data with local climatological data of the study site. A novel copula based approach was developed for accurately synthesizing aerodynamic and climatological data up on investigating the causes of significant uncertainties in currently used synthesizing techniques. Improvement of the new approach over the existing techniques was also illustrated with a case study on a 50 story building. At last, a practical dynamic optimization approach was suggested for tuning structural properties of tall buildings towards attaining optimum performance against wind loads with less number of design iterations.

Emergence and Fate of Siloxanes in Waste Streams: Release Mechanisms, Partitioning and Persistence in Three Environmental Compartments

Siloxanes are widely used in personal care and industrial products due to their low surface tension, thermal stability, antimicrobial and hydrophobic properties, among other characteristics. Volatile methyl siloxanes (VMS) have been detected both in landfill gas and biogas from anaerobic digesters at wastewater treatment plants. As a result, they are released to gas phase during waste decomposition and wastewater treatment. During transformation processes of digester or landfill gas to energy, siloxanes are converted to silicon oxides, leaving abrasive deposits on engine components. These deposits cause increased maintenance costs and in some cases complete engine overhauls become necessary. The objectives of this study were to compare the VMS types and levels present in biogas generated in the anaerobic digesters and landfills and evaluate the energetics of siloxane transformations under anaerobic conditions. Siloxane emissions, resulting from disposal of silicone-based materials, are expected to increase by 29% within the next 10 years. Estimated concentrations and the risk factors of exposure to siloxanes were evaluated based on the initial concentrations, partitioning characteristics and persistence. It was determined that D4 has the highest risk factor associated to bioaccumulation in liquid and solid phase, whereas D5 was highest in gas phase. Additionally, as siloxanes are combusted, the particle size range causes them to be potentially hazardous to human health. When inhaled, they may affix onto the alveoli of the lungs and may lead to development of silicosis. Siloxane-based COD-loading was evaluated and determined to be an insignificant factor concerning COD limits in wastewater. Removal of siloxane compounds is recommended prior to land application of biosolids or combustion of biogas. A comparison of estimated costs was made between maintenance practices for removal of siloxane deposits and installation/operation of fixed-bed carbon absorption systems. In the majority of cases, the installation of fixed-bed adsorption systems would not be a feasible option for the sole purpose of siloxane removal. However they may be utilized to remove additional compounds simultaneously.

Flood risk analysis of the White Oak Creek watershed in Oak Ridge, Tennessee using MIKE SHE and MIKE 11 software

The purpose of this study was to determine the flooding potential of contaminated areas within the White Oak Creek watershed in the Oak Ridge Reservation in Tennessee. The watershed was analyzed with an integrated surface and subsurface numerical model based on MIKE SHE/MIKE 11 software. The model was calibrated and validated using five decades of historical data. A series of simulations were conducted to determine the watershed response to 25 year, 100 year and 500 year precipitation forecasts; flooding maps were generated for those events. Predicted flood events were compared to Log Pearson III flood flow frequency values for validation. This investigation also provides an improved understanding of the water fluxes between the surface and subsurface subdomains as they affect flood frequencies. In sum, this study presents crucial information to further assess the environmental risks of potential mobilization of contaminants of concern during extreme precipitation events.

Lumps and balls in high-slump concrete: reasons and remedy

The objective of this research was to investigate the reason lumps occur in high-slump concrete and develop adequate batching procedures for a lumps-free high-slump ready-mix concrete mix used by the Florida Department of Transportation. Cement balls are round lumps of cement, sand, and coarse aggregate, typically about the size of a baseball that frequently occur in high-slump concrete. Such lumps or balls jeopardize the structural integrity of structural members. Experiments were conducted at the CSR Rinker concrete plant in Miami, Florida, based on a protocol developed by a team of Florida Department of Transportation (FDOT) concrete engineers, Rinker personnel, and Florida International University faculty. A total of seventeen truckloads were investigated in two phases, between April 2001 and March 2002. The tests consisted of gathering data by varying load size, discharge rate, headwater content, and mixing revolutions. The major finding was that a usual load size and discharge rate, an initial headwater ratio of 30%, and an initial number of revolutions of 100 at 12 revolutions per minute seem to produce a lump-free high-slump concrete. It was concluded that inadequate mixing and batching procedures caused cement lumps. Recommendations regarding specific load size, discharge rates, number of mixing revolutions, and initial water content are made. Clear guidelines for a high-slump concrete batching protocol can be developed, with further testing based on these research conclusions.

Advanced Methodologies in Dynamic Traffic Assignment Modeling of Managed Lanes

Managed lane strategies are innovative road operation schemes for addressing congestion problems. These strategies operate a lane (lanes) adjacent to a freeway that provides congestion-free trips to eligible users, such as transit or toll-payers. To ensure the successful implementation of managed lanes, the demand on these lanes need to be accurately estimated. Among different approaches for predicting this demand, the four-step demand forecasting process is most common. Managed lane demand is usually estimated at the assignment step. Therefore, the key to reliably estimating the demand is the utilization of effective assignment modeling processes. Managed lanes are particularly effective when the road is functioning at near-capacity. Therefore, capturing variations in demand and network attributes and performance is crucial for their modeling, monitoring and operation. As a result, traditional modeling approaches, such as those used in static traffic assignment of demand forecasting models, fail to correctly predict the managed lane demand and the associated system performance. The present study demonstrates the power of the more advanced modeling approach of dynamic traffic assignment (DTA), as well as the shortcomings of conventional approaches, when used to model managed lanes in congested environments. In addition, the study develops processes to support an effective utilization of DTA to model managed lane operations. Static and dynamic traffic assignments consist of demand, network, and route choice model components that need to be calibrated. These components interact with each other, and an iterative method for calibrating them is needed. In this study, an effective standalone framework that combines static demand estimation and dynamic traffic assignment has been developed to replicate real-world traffic conditions. With advances in traffic surveillance technologies collecting, archiving, and analyzing traffic data is becoming more accessible and affordable. The present study shows how data from multiple sources can be integrated, validated, and best used in different stages of modeling and calibration of managed lanes. Extensive and careful processing of demand, traffic, and toll data, as well as proper definition of performance measures, result in a calibrated and stable model, which closely replicates real-world congestion patterns, and can reasonably respond to perturbations in network and demand properties.

Effect of gamma-irradiation on total organic carbon and trihalomethane formation potential

This research was conducted to study the use of radiation in water treatment as an alternative to chlorination which has caused health concerns due to the formation of harmful disinfection by-products. Groundwater solutions from the Biscayne aquifer were radiated with Cobalt-60 gamma radiation and studied for changes in dissolved organic carbon (DOC), UV absorbance at 254 nm (UV254), fluorescence and trihalomethane formation potential (THMFP). Molecular fractionations were conducted by ultrafiltration. Effect of the combination of radiation/peroxide was studied for DOC and UV254. Radiation showed significant removal in DOC and THMFP. Similar results were seen in the fluorescence and UV absorbance experiments. Radiation/peroxide did not improve the DOC removal. Radiation of the groundwater samples broke the larger molecular weight fractions in to smaller fractions.

Developing brownfields ranking models using decision analytic methods

The redevelopment of Brownfields has taken off in the 1990s, supported by federal and state incentives, and largely accomplished by local initiatives. Brownfields redevelopment has several associated benefits. These include the revitalization of inner-city neighborhoods, creation of jobs, stimulation of tax revenues, greater protection of public health and natural resources, the renewal and reuse existing civil infrastructure and Greenfields protection. While these benefits are numerous, the obstacles to Brownfields redevelopment are also very much alive. Redevelopment issues typically embrace a host of financial and legal liability concerns, technical and economic constraints, competing objectives, and uncertainties arising from inadequate site information. Because the resources for Brownfields redevelopment are usually limited, local programs will require creativity in addressing these existing obstacles in a manner that extends their limited resources for returning Brownfields to productive uses. Such programs may benefit from a structured and defensible decision framework to prioritize sites for redevelopment: one that incorporates the desired objectives, corresponding variables and uncertainties associated with Brownfields redevelopment. This thesis demonstrates the use of a decision analytic tool, Bayesian Influence Diagrams, and related decision analytic tools in developing quantitative decision models to evaluate and rank Brownfields sites on the basis of their redevelopment potential.

Evaluating the effectiveness of signal timing optimization based on microscopic simulation evaluation

The optimization of the timing parameters of traffic signals provides for efficient operation of traffic along a signalized transportation system. Optimization tools with macroscopic simulation models have been used to determine optimal timing plans. These plans have been, in some cases, evaluated and fine tuned using microscopic simulation tools. A number of studies show inconsistencies between optimization tool results based on macroscopic simulation and the results obtained from microscopic simulation. No attempts have been made to determine the reason behind these inconsistencies. This research investigates whether adjusting the parameters of macroscopic simulation models to correspond to the calibrated microscopic simulation model parameters can reduce said inconsistencies. The adjusted parameters include platoon dispersion model parameters, saturation flow rates, and cruise speeds. The results from this work show that adjusting cruise speeds and saturation flow rates can have significant impacts on improving the optimization/macroscopic simulation results as assessed by microscopic simulation models.

Improved Criteria for Estimating Calibration Factors for Highway Safety Manual (HSM) Applications

The Highway Safety Manual (HSM) estimates roadway safety performance based on predictive models that were calibrated using national data. Calibration factors are then used to adjust these predictive models to local conditions for local applications. The HSM recommends that local calibration factors be estimated using 30 to 50 randomly selected sites that experienced at least a total of 100 crashes per year. It also recommends that the factors be updated every two to three years, preferably on an annual basis. However, these recommendations are primarily based on expert opinions rather than data-driven research findings. Furthermore, most agencies do not have data for many of the input variables recommended in the HSM. This dissertation is aimed at determining the best way to meet three major data needs affecting the estimation of calibration factors: (1) the required minimum sample sizes for different roadway facilities, (2) the required frequency for calibration factor updates, and (3) the influential variables affecting calibration factors. In this dissertation, statewide segment and intersection data were first collected for most of the HSM recommended calibration variables using a Google Maps application. In addition, eight years (2005-2012) of traffic and crash data were retrieved from existing databases from the Florida Department of Transportation. With these data, the effect of sample size criterion on calibration factor estimates was first studied using a sensitivity analysis. The results showed that the minimum sample sizes not only vary across different roadway facilities, but they are also significantly higher than those recommended in the HSM. In addition, results from paired sample t-tests showed that calibration factors in Florida need to be updated annually. To identify influential variables affecting the calibration factors for roadway segments, the variables were prioritized by combining the results from three different methods: negative binomial regression, random forests, and boosted regression trees. Only a few variables were found to explain most of the variation in the crash data. Traffic volume was consistently found to be the most influential. In addition, roadside object density, major and minor commercial driveway densities, and minor residential driveway density were also identified as influential variables.

An integrated multi-agent framework for optimizing time, cost and environmental impact of construction processes

Environmentally conscious construction has received a significant amount of research attention during the last decades. Even though construction literature is rich in studies that emphasize the importance of environmental impact during the construction phase, most of the previous studies failed to combine environmental analysis with other project performance criteria in construction. This is mainly because most of the studies have overlooked the multi-objective nature of construction projects. In order to achieve environmentally conscious construction, multi-objectives and their relationships need to be successfully analyzed in the complex construction environment. The complex construction system is composed of changing project conditions that have an impact on the relationship between time, cost and environmental impact (TCEI) of construction operations. Yet, this impact is still unknown by construction professionals. Studying this impact is vital to fulfill multiple project objectives and achieve environmentally conscious construction. This research proposes an analytical framework to analyze the impact of changing project conditions on the relationship of TCEI. This study includes green house gas (GHG) emissions as an environmental impact category. The methodology utilizes multi-agent systems, multi-objective optimization, analytical network process, and system dynamics tools to study the relationships of TCEI and support decision-making under the influence of project conditions. Life cycle assessment (LCA) is applied to the evaluation of environmental impact in terms of GHG. The mixed method approach allowed for the collection and analysis of qualitative and quantitative data. Structured interviews of professionals in the highway construction field were conducted to gain their perspectives in decision-making under the influence of certain project conditions, while the quantitative data were collected from the Florida Department of Transportation (FDOT) for highway resurfacing projects. The data collected were used to test the framework. The framework yielded statistically significant results in simulating project conditions and optimizing TCEI. The results showed that the change in project conditions had a significant impact on the TCEI optimal solutions. The correlation between TCEI suggested that they affected each other positively, but in different strengths. The findings of the study will assist contractors to visualize the impact of their decision on the relationship of TCEI.