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School of Civil and Environmental Engineering

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https://hdl.handle.net/1853/70760

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College of Engineering

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Georgia Water Resources Institute

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Georgia Transportation Institute

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Environmental Microbial Genomics Laboratory

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https://finding-aids.library.gatech.edu/agents/corporate_entities/385

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Publication Search Results

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ORGANIC CONTAMINANTS DESTRUCTION USING THE UV/FREE CHLORINE PROCESS: MECHANISMS AND MODELING

(Georgia Institute of Technology, 2019-12-16) Zhang, Weiqiu

Advanced oxidation processes (AOPs) are effective technologies to oxidize recalcitrant organic contaminants in the aqueous phase. The UV/free chlorine process has gained attention as a promising AOP technology, and it generates various reactive radicals (i.e. HO∙, Cl∙, Cl2-∙ and ClO∙) at room temperature and pressure. These electrophilic radicals eventually mineralize refractory organic contaminants into CO2 and H2O. Compared with other common AOPs (e.g. UV/H2O2 and UV/Persulfate processes), the UV/free chlorine process has many advantages, for example (1) it has much lower chemical reagent costs; (2) it has higher energy efficiency; (3) it is only slightly impacted by chloride ions (Cl-) (We found Cl- significantly inhibits the effectiveness of the UV/Persulfate process). For large scale applications, understanding the degradation mechanisms is critical to the design of the UV/free chlorine process that has the lowest energy consumption and greatest toxicity reduction. A number of related studies have shed light on the degradation of some selected organic compounds (e.g., atrazine, naproxen, etc.). However, these previous studies of the UV/free chlorine process have not comprehensively examined the mechanistically complex radicals-initiated chain reactions. Many researches have conducted experiments to determine the degradation mechanisms. However, these experimental studies are very time consuming and expensive. With respect to developing kinetic models that can simulate the reaction pathways in the UV/free chlorine process, most studies have used simplified lumped reactions or invoked the simplified pseudo steady state assumption because the rate constants between reactive radicals and organic compounds are unknown. Accordingly, conducting experiments and developing simplified kinetic models would be impossible to fully elucidate the oxidation mechanisms of all organic contaminants that may be found in the aqueous phase (Chemical Abstracts Service lists about more than 147 million compounds). To overcome the above-mentioned challenges, we developed a first principles-based kinetic model to predict the oxidation of organic compounds in the UV/free chlorine process. First, we collected photolysis and chemical reactions that describe the oxidation of target organic compounds from literature. Second, we developed a rate constants estimator to predict the rarely reported second-order rate constants between reactive radicals and organic compounds (i.e. kHO∙/R, kCl∙/R, kCl2-∙/R and kClO∙/R). kHO∙/R was estimated by the group contribution method (GCM). kCl∙/R, kCl2-∙/R and kClO∙/R were estimated by using the genetic algorithm that was fit to our experimental data (i.e. experimental observed time-dependent concentration profiles of target organic compounds). Third, we developed a stiff ordinary differential equations solver using Gear’s method to predict the time-dependent concentration profiles of target organic compounds, and our prediction results agreed with our experimental data for various operational conditions. Accordingly, our first principles-based kinetic model was successfully verified using our experimental data. Based on our UV/free chlorine kinetic model, we developed four quantitative structure activity relationships using Hammett constants of organic compounds and our predicted rate constants. We then determined relative contribution of these reactive radicals and photolysis, and, we found ClO∙ was the dominant radicals for organic contaminants oxidation. We also optimized the operational conditions (i.e. UV intensity and free chlorine dosage) that has the lowest energy consumption. Furthermore, we successfully implemented graph theory to develop a computerized pathway generator, which was built based on the predefined reaction mechanisms from experimental observations. The pathway generator can automatically predict all possible reactions and byproducts/intermediates that are involved in the degradation of target organic contaminants during the UV/free chlorine process (e.g. the degradation of TCE involves more than 200 byproducts /intermediates and more than 1,000 reactions). Therefore, the pathway generator significantly advances our understanding about the degradation pathways. However, we have noticed that it is difficult to estimate the rate constants of all possible involved reactions at current stage, because we only have very limited amount of experimental data (e.g., we do not have data on peroxyl radicals reactions) to develop a GCM. Consequently, future work will mainly focus on developing new methods (e.g. quantum chemistry) to estimate the rate constants of all possible involved reactions, and then predicting the time-dependent concentration profiles of byproducts. Finally, we investigated the disinfection byproducts (DBPs) and disinfection byproducts formation potentials (DBPFPs) in the UV/free chlorine process. In practical applications, natural organic matter can react with residual free chlorine to produce toxic DBPs. As a result, both the micropollutants and the DBPFPs must be decreased. Therefore, we need determine the controlling factor (i.e., organic contaminant destruction or DBPFPs reduction) in the design of the UV/free chlorine system. Overall, our study can be used to design the most cost-effective UV/free chlorine process.
Behavior of straight skewed I-girder bridge with skew index approaching 0.3

(Georgia Institute of Technology, 2019-12-12) Kamath, Ajit Manohar

Refined methods of analysis – 2D grid, plate and eccentric beam or 3D FEA – often are employed for design of I-girder bridges having significant skew. Traditionally, many of these structures have been designed using 1D line girder analysis (LGA). This research presents results from comparative parametric 3D FEA and LGA on a suite of 26 bridges that have a skew index up to and slightly larger than 0.3. Results of the comparative studies are presented for various key response quantities. Recommendations are provided for application of 1D LGA to the design of skewed I-girder bridge structures.
Transformation elasticity and anelasticity

(Georgia Institute of Technology, 2019-12-12) Golgoon, Ashkan

We present a theoretical framework for studying a large class of elastic and anelastic problems in nonlinear solids. We specifically use the transformation properties of nonlinear and linearized elasticity in this theory. Given an anelastic deformation, a non-vanishing strain does not correspond to a non-vanishing stress. That part of strain that is related to the corresponding stress is called elastic strain. The remaining part of strain is called eigenstrain or pre-strain. Eigenstrains (or anelastic sources) such as inclusions, defects, growth, phase transformations, and nonuniform temperature changes can cause residual stresses. The relaxed (natural) configuration of a residually-stressed body is a non-Euclidean manifold that cannot be isometrically embedded in the Euclidean ambient space. Using transformation anelasticity, one can construct the Riemannian material manifold of the body. In particular, the material metric explicitly depends on the distribution of eigenstrains. In this PhD thesis we utilize transformation anelasticity to study the induced elastic fields of a circumferentially-symmetric distribution of finite eigenstrains in nonlinear elastic wedges; the stress field of a nonlinear elastic solid torus with a toroidal inclusion; nonlinear elastic inclusions in anisotropic solids as well as distributed line and point defects in nonlinear anisotropic solids. The goal in transformation elasticity is to transform the nonlinear or linearized boundary-value (or initial-boundary-value) problem of an elastic body to that of another elastic body using a diffeomorphism (or a smooth mapping). The diffeomorphism, in turn, explicitly determines how the different elastic fields (and elastic parameters) of the two bodies are related. In particular, it is noted that the two boundary-value problems are not related by push-forward or pull-back under the diffeomorphism. We apply this theory to formulate the nonlinear and linearized elastodynamic transformation cloaking problem in the context of the classical elasticity, the small-on-large theory of elasticity, i.e., linearized elasticity with respect to an initially stressed configuration, and in solids with microstructure, namely gradient and (generalized) Cosserat solids. In particular, we note that a cloaking transformation is neither a spatial nor a referential change of coordinates (frame). Rather, a cloaking map transforms the boundary-value problem of an isotropic and homogeneous elastic body (virtual problem) to that of an anisotropic and inhomogeneous elastic body with a finite hole covered by a cloak that is to be designed (physical problem). The virtual body has a desired mechanical (wave-guiding) response, whereas the physical body is designed such that the same response is mimicked outside the cloak using a cloaking transformation. Finally, starting from nonlinear shell theory, we utilize transformation elasticity to formulate the transformation cloaking problem for Kirchhoff-Love plates and for elastic plates with both the in-plane and the out-of-plane displacements.
"Assessment of oxidative potential of ambient water-soluble and insoluble of PM2.5

(Georgia Institute of Technology, 2019-12-11) Gao, Dong

Oxidative stress has been proposed as a major mechanism responsible for adverse health effects associated with particulate matter (PM) pollution. Various methods have been developed to measure PM oxidative potential (OP), the potential for particles to generate reactive oxygen species and elicit oxidative stress. But no consensus has been reached as to the best OP assay. Both water-soluble and insoluble PM components contribute to PM OP, but the water-insoluble OP fraction has been less studied. This dissertation aims to characterize water-soluble PM OP measured by different OP assays and water-insoluble OP in terms of temporal variability and chemical determinants. This dissertation provides a direct inter-comparison between two health-relevant acellular OP assays, the synthetic respiratory tract lining fluid (RTLF) assay and the dithiothreitol (DTT) assay. These assays were used to measure the water-soluble OP of ambient fine PM collected in urban Atlanta over a year-long period. The results showed that these assays were driven by different groups of aerosol species, ranging from organic species to transition metal ions. The OP responses in the RTLF assay were affected by the composition of synthetic lung fluid, which emphasizes the importance of developing a “standard” technique for OP assays. Multivariate regression models for these OP metrics capture interactions among species, expanding our understanding of the relationships among species in the OP assessment. To develop a method for quantifying total PM OP, we compared three commonly used extraction methods for total OP assessment, involving methanol extraction (1) with or (2) without filtering the extracts, followed by solvent removal and reconstitution with water, and (3) water extraction without removing the particle-laden filter. The results indicated that performing the OP assay directly on the water extracts that still contained the particle-laden filter was a more effective way to capture water-insoluble OP compared to organic solvent extraction. An automated system was developed based on the DTT assay to facilitate the total OP analysis. The water-soluble and total OP of ambient particles collected at two urban sites and one roadside site were analyzed, with water-insoluble OP determined by difference. The results clearly demonstrated a measurable OP contribution from water-insoluble PM, which accounted for 20–35 % of total OP. The spatial and temporal variations in OP measures suggested that the insoluble OP contributors were largely secondary and related to biomass burning emissions. Multivariate regression analyses indicated that water-insoluble OP was related to incomplete combustion products and surface properties of soot and water-insoluble metals. Overall, assessing water-insoluble or total PM OP may provide important information in elucidating the health risks related to PM exposure and ultimately in promulgating effective control strategies to protect public health.
Pollutant exposure studies of emerging modes of transportation

(Georgia Institute of Technology, 2019-12-06) Schaffer, Kaitlyn Greer

The Center for Advancing Research in Transportation Emissions, Energy, and Health (CARTEEH) has invested in exposure studies and other similar initiatives that focus on the impact of transportation emissions on human health. CARTEEH’s research program includes a collaborative program that funds joint projects conducted by consortium members and competitive programs. Two of the funded projects led by the Georgia Institute of Technology include a paratransit transport exposure study and an urban cyclist exposure study. The work presented in this thesis includes the experimental procedures and findings from the paratransit exposure study and urban cyclist exposure study, accompanied by a literature review. The literature review consists of four main topics: (1) adverse health effects from particulate matter (PM) exposure, (2) factors that affect air quality and contribute to varying particulate concentrations, (3) methodologies for measuring human exposure to PM for different modes of transportation, and (4) an overview of low-cost air quality sensors. The findings from these initial experiments confirm the impact of transportation networks and the design of associated infrastructure on users’ health. Users’ health is negatively impacted by prolonged or repetitive exposure to particulate matter. These studies are the initial step to characterize the particulate matter exposure of paratransit and cycling in urban environments. Understanding users’ exposure is the first step to identify strategies to reduce exposure to harmful pollutants.
Challenges and practices of design professional liability policies in design-build projects

(Georgia Institute of Technology, 2019-12-04) Zhou, Yuxin

This study identifies emerging issues regarding design liabilities and explores the state-of-the-art practices in design professional liability insurance (DPLI) policy for design–build (DB) highway construction projects. The main objective of the research undertaken is to study the significant issues and challenges regarding design liability in the DB environment and state of the practices in DPLI across various state departments of transportation (DOTs). The research aims to identify important trends, best practices, and recommendations. The research assignment began with an in-depth analysis of the current literature in terms of published academic papers, federal and state reports, and conference presentations associated with professional associations. These resources include federal and state reports published by various organizations such as the National Cooperative Highway Research Program (NCHRP) and General Accounting Office (GAO); numerous state DOTs’ design–build agreement, master contracts, and requests for proposals (RFPs); and presentations and other published records from professional associations such as the Design–Build Institute of America (DBIA). Following the literature review stage, the research methodology continued with a survey and interviews with question-and-answer sessions with subject-matter experts across the country. This stage included a questionnaire survey, email interviews, telephonic conversations and meetings, and presentations during relevant conferences, such as the Transportation Research Board (TRB) and DBIA conferences. The first half of the research was performed to identify design liability. The major findings of the first step of the research were (1) key issues of design claims in DB environment; and (2) use of design professional liability insurance in the DB environment. In light of these developments, several challenges were identified: volume of design claims in DB and design–bid–build (DBB); project phases when design claims occur and insurance company’s involvement; gaps of DPLI coverage as to heightened standard of care; types of DPLI in DB; and influence of DB on changes in DPLI policy. The second half of the research effort was to examine emerging trends of state DOT practice of DPLI and identify best practices in consideration of DPLI that influence the selection of DPLI policy requirements in the DB environment. The results of the email interview process and review of state DOTs’ design–build agreements and RFPs helped identify several important areas that can be considered for enhancing the state of the practice for DPLI in DB as follows: different types of DPLI; significant elements under DPLI; considerations in selection of DPLI types; and considerations in determining coverage amount requirements.
Next generation electric vehicle energy modeling in transportation networks

(Georgia Institute of Technology, 2019-11-12) Xu, Xiaodan

Electric vehicles (EVs) will play a central role in future energy-efficient and sustainable transportation systems. Predicting the energy use for EVs is a complex issue because the onboard vehicle systems are trying to balance the provision of power to the wheels as well as manage the state of charge (SOC) of the battery pack. Traditional modeling methodologies for estimating real-world EV energy consumption either depend on numerical analysis of laboratory or on-road vehicle test data or the use of full-system EV simulation tools. Unfortunately, full-system simulation tools suffer from scaling problems in the context of large transportation network, necessitating the development of approaches that supports large transportation network projections of modal EV operations and applicable energy use rates. This study introduces an activity-based, bottom-up modeling approach to estimate EV energy consumption under the expected range of on-road operating conditions. The proposed system integrates outputs from a full EV simulation model called Autonomie. Three analytical efforts were undertaken to develop the activity-based approach for EV fleets using Autonomie simulation outputs. First, a sample of EV technologies was configured in Autonomie, and various operating conditions were simulated in Autonomie to generate a library for on-road operations by technology. Second, a grey box model design, referred to a Bayesian Network method in this study, was used to develop energy consumption models for the variety of EV technologies. This approach combines vehicle performance knowledge and data-driven energy inferences with on-road vehicle operation as inputs. Finally, the proposed EV energy models were verified using a separate testing dataset developed from Autonomie simulation results of another set of driving profiles. In addition, the real-world observed operation and energy use data were collected from select EV models using on-board diagnostic (OBD) devices to verify the energy prediction from the proposed model. The verification results suggested that the proposed model can predict energy use patterns under most driving conditions. The proposed approach was applied at aggregated-level, to a regional-level network, and at individual-level, to households and persons traveling within a region. The scalability of the proposed energy model framework was demonstrated in an Atlanta, GA case study. The results demonstrated that if 6.2% of urban VMT and 4.9% of rural VMT are driven by EVs, the network-level fuel savings are around 4.0% for a normal travel day in 2024. The energy model was also applied to daily trips predicted by the regional travel demand model. The results suggest the actual benefits of EV adoption depends on household travel patterns across deployment scenarios, as well as charger availability, electricity and fuel cost, and ambient environment conditions.
Stochastic approaches for quantification of near- and long-term structural reliability

(Georgia Institute of Technology, 2019-11-12) Saini, Ajay Singh Singh

The quantification of structural reliability is an important problem in civil engineering, affecting decisions in design, maintenance, retrofit, and rehabilitation of structures. As structural monitoring data increases, there is the desire to use this data to better estimate and predict the performance of structures, both under extreme loadings such as earthquakes, and over longer time horizons. The first part of this thesis concentrates on estimating and predicting the near-term reliability of structures under earthquake loading. We propose a methodology based on dynamic Bayesian networks and Kalman filter estimators to utilize building-mounted accelerometer data in real time to estimate the maximum nonlinear response of a structure and quantify the reliability in terms of the distribution of the maximum response under the earthquake. We extend this methodology from real-time estimation to prediction to predict the maximum structural response of a structure for an impending earthquake. We develop a time-sensitive, computationally efficient, and sufficiently accurate methodology to predict the maximum response of the structure. We verify the methodologies for the estimation and prediction of maximum response based on experimental data from laboratory tests and show close correspondence between the experimental and theoretical results. The second part of this thesis focuses on the quantification of long-term structural reliability. We propose a stochastic degradation model for structures and evaluate the effect of environmental and climate parameters on structural reliability based on changes in the rate of degradation and occurrence frequency and intensity of loadings. Finally, we propose a method to predict reliability to optimize the repair of a structure over its lifetime. We use the reliability and repair projections to quantify the structural resilience over longer time horizons. The projected resilience is used to analyze the performance of both an individual structure and a network of structures after a shock event.
Estimating the Health Risks Posed by Intermittent Water Supply Using Quantitative Microbial Risk Assessment

(Georgia Institute of Technology, 2019-11-12) Bivins, Aaron W.

Intermittent water supply (IWS) is a prevalent deficiency in piped water supplies. Microbiological and epidemiological evidence indicates that in some contexts IWS is associated with increased levels of fecal contamination and increased risk of waterborne diarrheal disease. In our initial quantitative microbial risk assessment (QMRA) using E. coli counts observed at IWS taps and pathogen to E. coli ratios in sewage, we estimated that IWS could account for 17.2 million infections causing 4.52 million cases of diarrhea, 109,000 DALYs, and 1,560 deaths among the 925 million exposed to IWS globally. Subsequently, we used dead-end ultrafiltation and droplet digital PCR to perform microbial sampling of two IWSs in India and QMRA to estimate the risks to human health attributable to IWS in India. During our microbial sampling in Jaipur, we detected gene targets associated with Cryptosporidium spp., Giardia duodenalis, and enterotoxigenic E. coli (ETEC) concurrently with culturable E. coli in groundwater samples from tube wells. In Nagpur, we observed a significant increase in the proportion of samples positive for culturable E. coli and gene targets associated with waterborne pathogens at household taps served by IWS compared to those served by CWS. At household taps served by IWS we detected genes associated with ETEC, Shigella spp., norovirus GI and GII, adenovirus, Cryptosporidium spp., and Giardia duodenalis. Our QMRA estimates that the daily risks of infection for Giardia, Cryptosporidium, norovirus, adenovirus, and Shigella exceed the US EPA acceptable annual threshold of 1 in 10,000 at the 10th percentile. Collectively, the results of our work indicate that, even given large uncertainty and variability, the public health risks associated with IWS likely exceed acceptable risk levels established by the WHO and US EPA.
Multi-scale analyses of granular flows for disaster resilience enhancement

(Georgia Institute of Technology, 2019-11-12) Liu, Fangzhou

A study that overlaps the fundamentals of granular flows with human responses to disasters at the community or regional scale is considered to be a strategic approach that advances existing methods in natural and human-induced hazard research in light of global-scale changes in earth systems. This study aims to improve the understanding: 1) on the mechanical behaviors of fluidized loess flowslide using centrifuge modeling as well as in-house designed laboratory testing and elastic wave characterization techniques (i.e. natural systems), and 2) on the cascading impacts of geohazards on local communities, assessing disaster resilience associated with reconstruction strategies and the performance of debris flow mitigation systems (i.e. natural-human systems interactions). The current work reveals the state-dependent effects of structure on flow behavior of loess and proposes modified criteria to predict the flow behavior. Laboratory tests show the changes in the mechanical behavior due to decementation of loess and indicate the needs to study loess within the scope of geotechnical analysis. The failure mechanism of loess flowslide is better understood from the study on the deformation process that shows the compounding effects of increasing pore-water pressure and reducing confining stresses on static liquefaction. The earthquake and post-earthquake impacts are documented after the 2008 Wenchuan earthquake, which permits a pilot study on quantifying the recovery processes of two communities of different reconstruction modes in light of Bayesian-based learning method. The design and performance of post-earthquake debris flow mitigation systems are reviewed; it offers a simple and robust data-driven approach to evaluate the effectiveness of debris flow mitigation systems at the regional scale.