Evaluation of wind-induced internal pressure in low-rise buildings: A multi scale experimental and numerical approach

Hurricane is one of the most destructive and costly natural hazard to the built environment and its impact on low-rise buildings, particularity, is beyond acceptable. The major objective of this research was to perform a parametric evaluation of internal pressure (IP) for wind-resistant design of low-rise buildings and wind-driven natural ventilation applications. For this purpose, a multi-scale experimental, i.e. full-scale at Wall of Wind (WoW) and small-scale at Boundary Layer Wind Tunnel (BLWT), and a Computational Fluid Dynamics (CFD) approach was adopted. This provided new capability to assess wind pressures realistically on internal volumes ranging from small spaces formed between roof tiles and its deck to attic to room partitions. Effects of sudden breaching, existing dominant openings on building envelopes as well as compartmentalization of building interior on the IP were systematically investigated. Results of this research indicated: (i) for sudden breaching of dominant openings, the transient overshooting response was lower than the subsequent steady state peak IP and internal volume correction for low-wind-speed testing facilities was necessary. For example a building without volume correction experienced a response four times faster and exhibited 30–40% lower mean and peak IP; (ii) for existing openings, vent openings uniformly distributed along the roof alleviated, whereas one sided openings aggravated the IP; (iii) larger dominant openings exhibited a higher IP on the building envelope, and an off-center opening on the wall exhibited (30–40%) higher IP than center located openings; (iv) compartmentalization amplified the intensity of IP and; (v) significant underneath pressure was measured for field tiles, warranting its consideration during net pressure evaluations. The study aimed at wind driven natural ventilation indicated: (i) the IP due to cross ventilation was 1.5 to 2.5 times higher for Ainlet/Aoutlet>1 compared to cases where Ainlet/Aoutlet<1, this in effect reduced the mixing of air inside the building and hence the ventilation effectiveness; (ii) the presence of multi-room partitioning increased the pressure differential and consequently the air exchange rate. Overall good agreement was found between the observed large-scale, small-scale and CFD based IP responses. Comparisons with ASCE 7-10 consistently demonstrated that the code underestimated peak positive and suction IP.

Development of an integrated surface and subsurface model of Everglades National Park

An integrated surface-subsurface hydrological model of Everglades National Park (ENP) was developed using MIKE SHE and MIKE 11 modeling software. The model has a resolution of 400 meters, covers approximately 1050 square miles of ENP, includes 110 miles of drainage canals with a variety of hydraulic structures, and processes hydrological information, such as evapotranspiration, precipitation, groundwater levels, canal discharges and levels, and operational schedules. Calibration was based on time series and probability of exceedance for water levels and discharges in the years 1987 through 1997. Model verification was then completed for the period of 1998 through 2005. Parameter sensitivity in uncertainty analysis showed that the model was most sensitive to the hydraulic conductivity of the regional Surficial Aquifer System, the Manning's roughness coefficient, and the leakage coefficient, which defines the canal-subsurface interaction. The model offers an enhanced predictive capability, compared to other models currently available, to simulate the flow regime in ENP and to forecast the impact of topography, water flows, and modifying operation schedules.

A methodology to estimate time varying user responses to travel time and travel time reliability in a road pricing environment

Road pricing has emerged as an effective means of managing road traffic demand while simultaneously raising additional revenues to transportation agencies. Research on the factors that govern travel decisions has shown that user preferences may be a function of the demographic characteristics of the individuals and the perceived trip attributes. However, it is not clear what are the actual trip attributes considered in the travel decision- making process, how these attributes are perceived by travelers, and how the set of trip attributes change as a function of the time of the day or from day to day. In this study, operational Intelligent Transportation Systems (ITS) archives are mined and the aggregated preferences for a priced system are extracted at a fine time aggregation level for an extended number of days. The resulting information is related to corresponding time-varying trip attributes such as travel time, travel time reliability, charged toll, and other parameters. The time-varying user preferences and trip attributes are linked together by means of a binary choice model (Logit) with a linear utility function on trip attributes. The trip attributes weights in the utility function are then dynamically estimated for each time of day by means of an adaptive, limited-memory discrete Kalman filter (ALMF). The relationship between traveler choices and travel time is assessed using different rules to capture the logic that best represents the traveler perception and the effect of the real-time information on the observed preferences. The impact of travel time reliability on traveler choices is investigated considering its multiple definitions. It can be concluded based on the results that using the ALMF algorithm allows a robust estimation of time-varying weights in the utility function at fine time aggregation levels. The high correlations among the trip attributes severely constrain the simultaneous estimation of their weights in the utility function. Despite the data limitations, it is found that, the ALMF algorithm can provide stable estimates of the choice parameters for some periods of the day. Finally, it is found that the daily variation of the user sensitivities for different periods of the day resembles a well-defined normal distribution.

The effect of iron oxide nanoparticles on the fate and transformation of arsenic in aquatic environments

Iron oxides and arsenic are prevalent in the environment. With the increase interest in the use of iron oxide nanoparticles (IONPs) for contaminant remediation and the high toxicity of arsenic, it is crucial that we evaluate the interactions between IONPs and arsenic. The goal was to understand the environmental behavior of IONPs in regards to their particle size, aggregation and stability, and to determine how this behavior influences IONPs-arsenic interactions. ^ A variety of dispersion techniques were investigated to disperse bare commercial IONPs. Vortex was able to disperse commercial hematite nanoparticles into unstable dispersions with particles in the micrometer size range while probe ultrasonication dispersed the particles into stable dispersions of nanometer size ranges for a prolonged period of time. Using probe ultrasonication and vortex to prepare IONPs suspensions of different particle sizes, the adsorption of arsenite and arsenate to bare hematite nanoparticles and hematite aggregates were investigated. To understand the difference in the adsorptive behavior, adsorption kinetics and isotherm parameters were determined. Both arsenite and arsenate were capable of adsorbing to hematite nanoparticles and hematite aggregates but the rate and capacity of adsorption is dependent upon the hematite particle size, the stability of the dispersion and the type of sorbed arsenic species. Once arsenic was adsorbed onto the hematite surface, both iron and arsenic can undergo redox transformation both microbially and photochemically and these processes can be intertwined. Arsenic speciation studies in the presence of hematite particles were performed and the effect of light on the redox process was preliminary quantified. The redox behavior of arsenite and arsenate were different depending on the hematite particle size, the stability of the suspension and the presence of environmental factors such as microbes and light. The results from this study are important and have significant environmental implications as arsenic mobility and bioavailability can be affected by its adsorption to hematite particles and by its surface mediated redox transformation. Moreover, this study furthers our understanding on how the particle size influences the interactions between IONPs and arsenic thereby clarifying the role of IONPs in the biogeochemical cycling of arsenic.^

Fractal analysis of flocs formed in edible oil -water emulsions by image analysis techniques

Edible oil is an important contaminant in water and wastewater. Oil droplets smaller than 40 μm may remain in effluent as an emulsion and combine with other contaminants in water. Coagulation/flocculation processes are used to remove oil droplets from water and wastewater. By adding a polymer at proper dose, small oil droplets can be flocculated and separated from water. The purpose of this study was to characterize and analyze the morphology of flocs and floc formation in edible oil-water emulsions by using microscopic image analysis techniques. The fractal dimension, concentration of polymer, effect of pH and temperature are investigated and analyzed to develop a fractal model of the flocs. Three types of edible oil (corn, olive, and sunflower oil) at concentrations of 600 ppm (by volume) were used to determine the optimum polymer dosage and effect of pH and temperature. To find the optimum polymer dose, polymer was added to the oil-water emulsions at concentration of 0.5, 1.0, 1.5, 2.0, 3.0 and 3.5 ppm (by volume). The clearest supernatants obtained from flocculation of corn, olive, and sunflower oil were achieved at polymer dosage of 3.0 ppm producing turbidities of 4.52, 12.90, and 13.10 NTU, respectively. This concentration of polymer was subsequently used to study the effect of pH and temperature on flocculation. The effect of pH was studied at pH 5, 7, 9, and 11 at 30°C. Microscopic image analysis was used to investigate the morphology of flocs in terms of fractal dimension, radius of oil droplets trapped in floc, floc size, and histograms of oil droplet distribution. Fractal dimension indicates the density of oil droplets captured in flocs. By comparison of fractal dimensions, pH was found to be one of the most important factors controlling droplet flocculation. Neutral pH or pH 7 showed the highest degree of flocculation, while acidic (pH 5) and basic pH (pH 9 and pH 11) showed low efficiency of flocculation. The fractal dimensions achieved from flocculation of corn, olive, and sunflower oil at pH 7 and temperature 30°C were 1.2763, 1.3592, and 1.4413, respectively. The effect of temperature was explored at temperatures 20°, 30°, and 40°C and pH 7. The results of flocculation of oil at pH 7 and different temperatures revealed that temperature significantly affected flocculation. The fractal dimension of flocs formed in corn, olive and sunflower oil emulsion at pH 7 and temperature 20°, 30°, and 40°C were 1.82, 1.28, 1.29, 1.62, 1.36, 1.42, 1.36, 1.44, and 1.28, respectively. After comparison of fractal dimension, radius of oil droplets captured, and floc length in each oil type, the optimal flocculation temperature was determined to be 30°C. ^

Reliability analysis of encapsulation methods for lead -based paint through an accelerated life testing

The adverse health effects of long-term exposure to lead are well established, with major uptake into the human body occurring mainly through oral ingestion by young children. Lead-based paint was frequently used in homes built before 1978, particularly in inner-city areas. Minority populations experience the effects of lead poisoning disproportionately. ^ Lead-based paint abatement is costly. In the United States, residents of about 400,000 homes, occupied by 900,000 young children, lack the means to correct lead-based paint hazards. The magnitude of this problem demands research on affordable methods of hazard control. One method is encapsulation, defined as any covering or coating that acts as a permanent barrier between the lead-based paint surface and the environment. ^ Two encapsulants were tested for reliability and effective life span through an accelerated lifetime experiment that applied stresses exceeding those encountered under normal use conditions. The resulting time-to-failure data were used to extrapolate the failure time under conditions of normal use. Statistical analysis and models of the test data allow forecasting of long-term reliability relative to the 20-year encapsulation requirement. Typical housing material specimens simulating walls and doors coated with lead-based paint were overstressed before encapsulation. A second, un-aged set was also tested. Specimens were monitored after the stress test with a surface chemical testing pad to identify the presence of lead breaking through the encapsulant. ^ Graphical analysis proposed by Shapiro and Meeker and the general log-linear model developed by Cox were used to obtain results. Findings for the 80% reliability time to failure varied, with close to 21 years of life under normal use conditions for encapsulant A. The application of product A on the aged gypsum and aged wood substrates yielded slightly lower times. Encapsulant B had an 80% reliable life of 19.78 years. ^ This study reveals that encapsulation technologies can offer safe and effective control of lead-based paint hazards and may be less expensive than other options. The U.S. Department of Health and Human Services and the CDC are committed to eliminating childhood lead poisoning by 2010. This ambitious target is feasible, provided there is an efficient application of innovative technology, a goal to which this study aims to contribute. ^

Chlorine contribution to quantitative structure and activity relationship models of disinfection by -products' quantum chemical descriptors and toxicities

Quantitative Structure-Activity Relationship (QSAR) has been applied extensively in predicting toxicity of Disinfection By-Products (DBPs) in drinking water. Among many toxicological properties, acute and chronic toxicities of DBPs have been widely used in health risk assessment of DBPs. These toxicities are correlated with molecular properties, which are usually correlated with molecular descriptors. The primary goals of this thesis are: (1) to investigate the effects of molecular descriptors (e.g., chlorine number) on molecular properties such as energy of the lowest unoccupied molecular orbital (E LUMO) via QSAR modelling and analysis; (2) to validate the models by using internal and external cross-validation techniques; (3) to quantify the model uncertainties through Taylor and Monte Carlo Simulation. One of the very important ways to predict molecular properties such as ELUMO is using QSAR analysis. In this study, number of chlorine (NCl ) and number of carbon (NC) as well as energy of the highest occupied molecular orbital (EHOMO) are used as molecular descriptors. There are typically three approaches used in QSAR model development: (1) Linear or Multi-linear Regression (MLR); (2) Partial Least Squares (PLS); and (3) Principle Component Regression (PCR). In QSAR analysis, a very critical step is model validation after QSAR models are established and before applying them to toxicity prediction. The DBPs to be studied include five chemical classes: chlorinated alkanes, alkenes, and aromatics. In addition, validated QSARs are developed to describe the toxicity of selected groups (i.e., chloro-alkane and aromatic compounds with a nitro- or cyano group) of DBP chemicals to three types of organisms (e.g., Fish, T. pyriformis, and P.pyosphoreum) based on experimental toxicity data from the literature. The results show that: (1) QSAR models to predict molecular property built by MLR, PLS or PCR can be used either to select valid data points or to eliminate outliers; (2) The Leave-One-Out Cross-Validation procedure by itself is not enough to give a reliable representation of the predictive ability of the QSAR models, however, Leave-Many-Out/K-fold cross-validation and external validation can be applied together to achieve more reliable results; (3) E LUMO are shown to correlate highly with the NCl for several classes of DBPs; and (4) According to uncertainty analysis using Taylor method, the uncertainty of QSAR models is contributed mostly from NCl for all DBP classes.

Study on Pore Distribution and Formation Rule of Sepiolite Mineral Nanomaterials

Theoretical research and specific surface area analysis of nitrogen adsorption indicated that a lot of structural micropores exist in sepiolite minerals fibers. However, the microporous size, existing form, and the distribution relationship between microporous structures were not proved yet. In this paper, the section TEM samples of nanofibers were prepared on the basis of the metal embedding and cutting technique, and the inner structure of sepiolite nanofibers was observed by TEM. The results showed that sepiolite fibers have multiplayer structure similar to concentric circles, and many micropores with the size of about 2–5 nm are normal and parallel to the -axis. The reason for the previously mentioned phenomenon was explained by using BET analysis and X-ray diffraction analysis results.

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.^

Multi-media filtration for removal of petroleum contamination

A pilot scale multi-media filtration system was used to evaluate the effectiveness of filtration in removing petroleum hydrocarbons from a source water contaminated with diesel fuel. Source water was artificially prepared by mixing bentonite clay and tap water to produce a turbidity range of 10-15 NTU. Diesel fuel concentrations of 150 ppm or 750 ppm were used to contaminate the source water. The coagulants used included Cat Floc K-10 and Cat Floc T-2. The experimental phase was conducted under direct filtration conditions at constant head and constant rate filtration at 8.0 gpm. Filtration experiments were run until the filter reached its clogging point as noted by a measured peak pressure loss of 10 psi. The experimental variables include type of coagulant, oil concentration and source water. Filtration results were evaluated based on turbidity removal and petroleum hydrocarbon (PHC) removal efficiency as measured by gas chromatography. Experiments indicated that clogging was controlled by the clay loading on the filter and that inadequate destabilization of the contaminated water by the coagulant limited the PHC removal. ^

The effect of weathering processes on the vertical turbulent dispersion characteristics of crude oil spilled on the sea

Since the Exxon Valdez accident in 1987, renewed interest has come forth to better understand and predict the fate and transport of crude oil lost to marine environments. The short-term fate of an Arabian Crude oil was simulated in laboratory experiments using artificial seawater. The time-dependent changes in the rheological and chemical properties of the oil under the influence of natural weathering processes were characterized, including dispersion behavior of the oil under simulated ocean turbulence. Methodology included monitoring the changes in the chemical composition of the oil by Gas Chromatography/Mass Spectrometry (GCMS), toxicity evaluations for the oil dispersions by Microtox analysis, and quantification of dispersed soluble aromatics by fluorescence spectrometry. Results for this oil show a sharp initial increase in viscosity, due to evaporative losses of lower molecular weight hydrocarbons, with the formation of stable water-in-oil emulsions occurring within one week. Toxicity evaluations indicate a decreased EC-50 value (higher toxicity) occurring after the oil has weathered eight hours, with maximum toxicity being observed after weathering seven days. Particle charge distributions, determined by electrophoretic techniques using a Coulter DELSA 440, reveal that an unstable oil dispersion exists within the size range of 1.5 to 2.5 um, with recombination processes being observed between sequential laser runs of a single sample.

Surfactant solubilization and subsequent bioavailability of phenanthrene

Contamination of soil, sediment and groundwater by hydrophobic organic compounds (HOCs) is a matter of growing concern because groundwater is a valuable and limited resource, and because such contamination is difficult to address. This investigation involved an experimental evaluation of the addition of several surfactant solutions to aqueous and soil-water systems contaminated with phenanthrene, a selected HOC. The results are presented in terms of: * phenanthrene solubilization achieved through surfactant addition * observed effects of surfactant addition on the mineralization of phenanthrene * estimation of relative toxicities of various surfactants using toxicity assays * literature-reported biodegradability/persistence of selected surfactants * surfactant sorption/precipitation onto soil and its impacts on proposed use of surfactant-amended remediation Surfactants were observed to facilitate the transfer of phenanthrene from the soil-sorbed phase to the aqueous pseudophase, however, surfactant solubilization did not translate into enhanced phenanthrene biodegradation.

Mitigation of High Alkalinity in Leachates of Aged Steel Slag

Steel slag, an abundant by-product of the steel-making industry, after it is aged, has a huge potential for use as an aggregate in road construction. However, the high pH of steel slag seepage (pH≥12) is a major impediment in its beneficial use. Analyses on aged steel slag samples demonstrated that the alkalinity producing capacity of aged steel slag samples strongly correlated to Ca(OH)2 dissolution and that prolonged aging periods have marginal effects on overall alkalinity. Treatment methods that included bitumen-coating, bathing in Al(III) solutions and addition of an alum-based drinking water treatment residual (WTR) were evaluated based on reduction in pH levels and leachate alkalinity. 10% (wt./wt.) alum-based drinking water treatment residual (WTR) addition to slag was determined to be the most successful mitigation method, providing 65−70% reduction in alkalinity both in batch-type and column leach tests, but final leachate pH was only 0.5−1 units lower and leachates were contaminated by dissolved Al(+III) (≥3−4 mM). Based on the interpretation of calculated saturation indices and SEM and EDX analyses, formation of calcium sulfoaluminate phases (i.e., ettringite and monosulfate) was suggested as the mechanism behind alkalinity mitigation upon WTR-modification. The residual alkalinity in WTR-amended slag leachates was able to be completely eliminated utilizing a biosolids compost with high base neutralization capacity. In column leach tests, effluent pH levels below 7 were maintained for 58−74 pore volumes worth of WTR-amended slag leachate using 0.13 kg compost (dry wt.) per 1 kg WTR-amended slag on average; also, dissolved Al(+III) was strongly retained on the compost.

THE DEVELOPMENT EFFECTIVENESS OF INTERNATIONAL WATER AND SANITATION INFRASTRUCTURE PROJECTS: DEFINING “QUALITY AT ENTRY” OF WORLD BANK PROJECTS.

Over the past 15 years, the number of international development projects aimed at combating global poverty has increased significantly. Within the water and sanitation sector however, and despite heightened global attention and an increase in the number of infrastructure projects, over 800 million people remain without access to appropriate water and sanitation facilities. The majority of donor aid in the water supply and sanitation sector of developing countries is delivered through standalone projects. The quality of projects at the design and preparation stage is a critical determinant in meeting project objectives. The quality of projects at early stage of design, widely referred to as quality at entry (QAE), however remains unquantified and largely subjective. This research argues that water and sanitation infrastructure projects in the developing world tend to be designed in the absence of a specific set of actions that ensure high QAE, and consequently have relatively high rates of failure. This research analyzes 32 cases of water and sanitation infrastructure projects implemented with partial or full World Bank financing globally from 2000 – 2010. The research uses categorical data analysis, regression analysis and descriptive analysis to examine perceived linkages between project QAE and project development outcomes and determines which upstream project design factors are likely to impact the QAE of international development projects in water supply and sanitation. The research proposes a number of specific design stage actions that can be incorporated into the formal review process of water and sanitation projects financed by the World Bank or other international development partners.

ELECTROCATALYTIC PROCESSING OF RENEWABLE BIOMASS-DERIVED COMPOUNDS FOR PRODUCTION OF CHEMICALS, FUELS AND ELECTRICITY

The dual problems of sustaining the fast growth of human society and preserving the environment for future generations urge us to shift our focus from exploiting fossil oils to researching and developing more affordable, reliable and clean energy sources. Human beings had a long history that depended on meeting our energy demands with plant biomass, and the modern biorefinery technologies realize the effective conversion of biomass to production of transportation fuels, bulk and fine chemicals so to alleviate our reliance on fossil fuel resources of declining supply. With the aim of replacing as much non-renewable carbon from fossil oils with renewable carbon from biomass as possible, innovative R&D activities must strive to enhance the current biorefinery process and secure our energy future. Much of my Ph.D. research effort is centered on the study of electrocatalytic conversion of biomass-derived compounds to produce value-added chemicals, biofuels and electrical energy on model electrocatalysts in AEM/PEM-based continuous flow electrolysis cell and fuel cell reactors. High electricity generation performance was obtained when glycerol or crude glycerol was employed as fuels in AEMFCs. The study on selective electrocatalytic oxidation of glycerol shows an electrode potential-regulated product distribution where tartronate and mesoxalate can be selectively produced with electrode potential switch. This finding then led to the development of AEMFCs with selective production of valuable tartronate or mesoxalate with high selectivity and yield and cogeneration of electricity. Reaction mechanisms of electrocatalytic oxidation of ethylene glycol and 1,2-propanediol were further elucidated by means of an on-line sample collection technique and DFT modeling. Besides electro-oxidation of biorenewable alcohols to chemicals and electricity, electrocatalytic reduction of keto acids (e.g. levulinic acid) was also studied for upgrading biomass-based feedstock to biofuels while achieving renewable electricity storage. Meanwhile, ORR that is often coupled in AEMFCs on the cathode was investigated on non-PGM electrocatalyst with comparable activity to commercial Pt/C. The electro-biorefinery process could be coupled with traditional biorefinery operation and will play a significant role in our energy and chemical landscape.