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Fate and Characteristics of Dissolved Organic Nitrogen through Wastewater Treatment Systems
(North Dakota State University, 2012) Simsek, Halis
Dissolved organic nitrogen (DON) represents a significant portion (25-80%) of total dissolved nitrogen in the final effluent of wastewater treatment plants (WWTPs). DON in treated wastewater, once degraded, causes oxygen depletion and/or eutrophication in receiving waters and should be reduced prior to discharge. Biodegradability, bioavailability, and photodegradability are important characteristics of wastewater derived DON and are subjects of research in this dissertation. Four research tasks were performed. In the first task, laboratory-scale chemostat experiments were conducted to examine whether solids retention time (SRT) could be used to control DON and biodegradable DON (BDON) in treated wastewater. Nine different SRTs from 0.3 to 13 were studied. There was no correlation between effluent DON and SRTs. However, BDONs at SRTs of 0.3 to 4 days were comparable and had a decreasing trend with SRTs after that. These results indicate the benefit of high SRTs in term of producing effluent with less BDON. The second task was a comprehensive year-round data collection to study the fate of DON and BDON through the treatment train of a trickling filter (TF) WWTP. The plant removed substantial amounts of DON (62%) and BDON (76%) mainly through the biological process. However, the discharged concentrations in the effluent were still high enough to be critical for a stringent total nitrogen discharge limit (below 5 mg-N/L). Evolution of bioavailable DON (ABDON) along the treatment trains of activated sludge (AS) and TF WWTPs and relationship between ABDON and BDON were examined in the third task. ABDON exerted from a combination of bacteria and algae inocula was higher than algae inoculated ABDON and bacteria inoculated BDON suggesting the use of algae as a treatment organism along with bacteria to minimize effluent DON. The TF and AS WWTPs removed 88% and 64% of ABDON, respectively. In the last task, photodegradable DON (PDON) in primary wastewater and final effluent from TF and AS WWTPs was studied. PDON and BDON fractions of DON data in the final effluent of TF and AS WWTP samples elucidate that photodegradation is as critically important as biodegradation when mineralization of effluent DON is a concern in receiving waters.
Building Envelope Containing Phase Change Materials for Energy-Efficient Buildings
(North Dakota State University, 2021) Li, Mingli
Energy consumption in the building sector has increased dramatically over the past two decades. The incorporation of phase change materials (PCMs) into building envelopes is considered as effective thermal energy storage to improve building thermal performance and reduce space heating/cooling load. Despite significant efforts in PCMs technologies and their application to buildings, how to select proper PCMs for buildings and maximize the activation of their latent heat to effectively improve building energy efficiency still post great challenges. The lack of systematic and comprehensive studies in these gaps hinders their broad applications in the building sector. This study aims to develop a holistic framework through experimental and numerical studies to gain a deep understanding of the thermal property of PCM and the heat transfer mechanism of the exterior wall integrated with PCM. A novel shape-stabilized paraffin/expanded graphite(EG) composite is prepared and its thermal behavior is investigated through thermal energy storage and heat transfer test. The impact of critical design parameters including the location, thickness, latent heat, melting point, and thermal conductivity of PCM on the thermal performance of a multilayer wall is explored using COMSOL Multiphysics® software. The thermal storage and heat transfer test show that EG can significantly enhance the heat transfer rate of paraffin. In addition, the paraffin/EG composite possesses favorable thermal energy storage ability to decrease the indoor temperature fluctuation and shift the peak load. Among the aforementioned design parameters, melting point of PCM is critical to significantly influence the building thermal performance. To effectively account for melting point of PCM and enhance the service efficiency of PCM, a new wall configuration containing PCM with hybrid melting points is proposed. The proposed wall assembly is found to benefit the indoor thermal comfort and the activation of the latent heat of PCM when the ambient temperature covers cold, mild, and hot loading conditions for the long term. Moreover, coupling vacuum insulation panels (VIP) with extremely low thermal conductivity and PCMs with a large amount of latent heat in the building envelope is another solution to further enhance building thermal performance due to the increased thermal insulation and thermal inertia.
Development of Improved Methods for Watershed-Scale Topographic Analysis and Hydrologic Modeling
(North Dakota State University, 2020) Wang, Ning
Surface depressions are one of the significant topographic characteristics in depression-dominated areas and can retain runoff and break the hydrologic continuity in watersheds. In traditional semi-distributed models, the entire area of a watershed is assumed to be well connected to its associated outlet and depressions are often lumped as a single depth to control runoff water release. Consequently, hydrologic processes related to depressions cannot be directly simulated. The overall goal of this dissertation research is to analyze and quantify the topographic characteristics of surface depressions and their impacts on hydrologic processes in depression-dominated areas. The specific objectives of this research are: (1) to improve watershed delineation to further reveal the topographic characteristics and hydrologic connectivity within watersheds, (2) to analyze the impact of depressions on runoff processes during rainfall events and the mechanism of water release from depressions, and (3) to analyze the functionalities of depressions in continuous simulation of hydrologic processes and connectivity. A new algorithm was developed for hydrologic unit delineation of depressions and channels (HUD-DC), in which a unique method was proposed to identify depression- and channel-associated hydrologic units and their connections. The HUD-DC delineation results highlighted the significance of depressions and the complex connectivity in depression-dominated areas. Additionally, the delineation under different filling conditions provided helpful guidance for the identification of filling thresholds to remove artifacts in digital elevation models. To achieve the second objective, a depression-oriented, event-based hydrologic model (HYDROL-D) was developed with considering separate modeling for depressional and non-depressional areas, and hierarchical control thresholds for water release from depressions. The HYDROL-D modeling results for a watershed in North Dakota revealed the intrinsic threshold behavior of surface runoff over the watershed and the effectiveness of the hierarchical control thresholds. A depression-oriented hydrologic model with accounting for dynamic hydrologic connectivity (HYDROL-DC) was further developed to continuously track runoff unit by unit. The application of HYDROL-DC in a depression-dominated watershed showed that depressions had not only retention but also acceleration capabilities in surface runoff generation. Additionally, the spatial distribution of depressions exhibited dynamic influences on hydrologic connectivity and the related threshold behavior of runoff processes.
Post-Fire Damage and Corrosion in Structural Steels: Characterization and Prevention
(North Dakota State University, 2021) Sajid, Hizb Ullah
Steel structures frequently experience extreme service conditions such as fire accidents, corrosion, etc., resulting in significant deterioration, reduced service life, and increased maintenance cost. Almost 0.5 million structural fire accidents are reported annually in the U.S., inflicting a considerable toll on infrastructure. Similarly, corrosion-induced deterioration is the leading cause of premature failure in infrastructure and costs $22.6 billion in infrastructure maintenance annually. The bridge infrastructure vulnerability to these extreme service conditions is compounded by the aging bridge inventory (42% of the 617,000 bridges in the U.S. are 50 years or older). To improve the resilience and the “C-” infrastructure grade, it is vital to understand the material-scale damages and mechanisms induced by such extreme service conditions and develop efficient mitigation strategies. This dissertation adopts a two-prong approach to understand and predict the material-scale damage after exposure to fire accidents in steel structures and mitigate corrosion damage in steel/RC structures. Specifically, it aims to improve our current understanding of the post-fire mechanical behavior of steels and propose a microstructure-based approach for forensic analysis of fire-affected steel structures in phase-I. It further aims to mitigate corrosion in steel/RC structures by employing agriculturally-derived non-toxic materials and surface treatments in phase-II. Post-fire mechanical and microstructural investigations conducted in phase-I revealed that stress concentrations and fire-extinguishing methods significantly affect the post-fire mechanical behavior of structural steels, and post-fire steel microstructure can be utilized to accurately estimate the mechanical strength of structural steels without the knowledge of fire temperatures. The outcomes of phase-I of this dissertation can lead to accurate forensic fire investigations and usability determination of the fire-affected steel structures. The results obtained from phase-II of this dissertation revealed the role of surface treatments in improving the corrosion resistance and validated the performance of the agriculturally-derived materials such as corn-derived inhibitors and soy-protein coatings in lowering the corrosion damage in structural steels and embedded rebars by up to 90% without compromising the integrity of cement-based materials. These outcomes will lead to mitigating corrosion-induced deterioration in aging and new infrastructure. Overall, the outcomes of this dissertation contribute to improving infrastructure resilience and reducing maintenance costs.
Analyses of Highway Project Construction Risks, Performance, and Contingency
(North Dakota State University, 2010) Diab, Mohamed F.
Past studies have highlighted the importance of risk assessment and management in construction projects and transportation industry, and have identified cost and time as the most important risks that transportation professionals want to understand and manage. The main focus of this study is to comprehensively analyze transportation construction risk drivers and identify the correlation of the significant risk drivers with project characteristics, cost growth, schedule growth, and project contingency. This study has adopted 31 relevant and significant programmatic and project-specific risk drivers from different past studies. These risk drivers have been analyzed and evaluated using survey responses from professionals in the context of highway transportation projects. Risk assessments including rating of the encountered risk drivers and their correlation with project characteristics have been carried out within the context of highway construction projects in the United States. Correlations of the construction project performance or risk measures, cost growth percentage, and schedule growth percentage, with the rating values of identified risk drivers values have enabled a better understanding of the impacts of risks and the risk assessment process for highway transportation projects. The impact of significant risk drivers on reported construction cost contingency amounts has also been analyzed. The purpose of this effort was to assess impact of ratings for cost impact, schedule impact, and relative importance of the identified risk drivers on contingency amounts. Predetermined method is the common way to calculate contingency amount in transportation projects. In this study parametric modeling has been used to analyze the relationship between predetermined contingency amounts in transportation projects with perceived risk rating values in order to understand how the expert judgments regarding risk ratings can be used in determination of contingency amounts.
Estimation of the Capacity of a Basic Freeway and Weaving Segment Under Traditional, Autonomous, and Connected Autonomous Vehicles, Using Oversaturated Traffic Condition Data
(North Dakota State University, 2022) Saha, Niloy
Autonomous vehicles (AVs) and connected autonomous vehicles (CAVs) will be the standard in transportation in the future. The use of such vehicles could minimize traffic oscillation and travel time and boost safety and mobility on freeways. An AV is a self-driving vehicle that can make decisions by itself in any situation. CAVs include all the characteristics of AVs and additional communication with other vehicles or the infrastructure (signal system). The use of AVs and CAVs will substantially increase motorway capacity in upcoming decades. Moreover, vehicle dynamics will change as technology and algorithms become more commonplace. In the short term, capacity may have a negative impact on talent; however, as the algorithms become more aggressive, the results will improve. Highway Capacity Manual (HCM) may need to be updated if freeway system capacity changes. As a result, the manual should focus on enhancing two freeway segments: the fundamental freeway portion and the weaving part (case study on U.S. 101 in Los Angeles, California). A microsimulation program developed by the Planung Transport Verkehr (PTV) in Karlsruhe, Germany, was used to calibrate and evaluate Wiedemann's behavioral car-following model (CFM). The Coexist project from Europe created three types of autonomous cars: AV-cautious, AV-normal, and AV all-knowing. CFMs are vital because they measure the distance between vehicles. This is crucial for capacity. The capacity of AV cautious vehicles is decreased at all levels and penetrations. When AV-cautious autonomy evolves into AV all-knowing autonomy, the capacity of the weaving section and the BFS may rise by 33% and 36%, respectively. This study provides a method for evaluating the capacity of freeways, which we estimate using AV levels and penetrations. Transportation planners and traffic engineers may utilize these capabilities to design better traffic planning and traffic-management technology in the future. For example, highway capacity will be restricted if the AV mix is largely AV-cautious. However, the solution is likely not to expand capacity but to find ways to manage traffic as new technology develops and moves to CAVs. This research aids in the planning and design of how to bring AVs and CAVs to market.
Safety Effectiveness and Safety-Based Volume Warrants of Right-Turn Lanes at Unsignalized Intersections and Driveways on Two-Lane Roadways
(North Dakota State University, 2012) Ale, Gom Bahadur
Disagreements regarding to what degree right-turn lanes improve or worsen the safety of intersections and driveways provided the motivation and the need for this study. The objectives of this study were to: a) carry out an in-depth study to determine the safety impacts of right-turn movements in different contexts, and b) develop safety-based volume warrants for right-turn lanes if safety indeed improves. Lack of adequate study on the applicability of past warrants and guidelines for the specific context of right-turn movements made from major uncontrolled approaches at unsignalized intersections, and particularly driveways, on two-lane roadways provided the scope for this study. Five-year historical data of statewide traffic crashes reported on Minnesota’s twolane trunk highways were analyzed using binary/multinomial logistic regressions. Conflicts due to right turns were analyzed by fitting least squares conflict prediction models based on the data obtained from field surveys and traffic simulations. The safety impacts of rightturn lanes were determined through crash-conflict relationships, crash injury severity, and crash and construction costs. The study found that the probabilities of right-turn movement related crash ranged from 1.6 to 17.2% at intersections and from 7.8 to 38.7% at driveways. Rear-end, samedirection- sideswipe, right-angle and right-turn crash types constituted 96% of right-turn movement related crashes. Rear-end crash probabilities varied from 13.7 to 46.4% at approaches with right-turn lanes and from 37.9 to 76.9% otherwise. The ratios of rearend/ same-direction-sideswipe crashes to conflicts were 0.759 x 10^6 at approaches with right-turn lanes and 1.547 x 10^6 otherwise. Overall, right-turn lanes reduced right-turn movement related crash occurrences and conflicts by 85% and 80%, respectively. Right-turn lanes also reduced crash injury severity, hence, reducing the economic cost by 26%. Safety benefits, in dollars, realized with the use of right-turn lanes at driveways were 29% and 7% higher compared to those at intersections at low and high speed conditions respectively for similar traffic conditions. Depending on roadway conditions, interest rate and construction costs, the safety-based volume thresholds ranged from 3 to 200 right turns per hour during the design hour at intersection approaches, and from 2 to 175 right turns at driveway approaches.
Characterization of Activities of Crumb Rubber in Interaction with Asphalt and its Effect on Final Properties
(North Dakota State University, 2015) Ghavibazoo, Amir
Recycling of millions of scrap tires produced everyday is crucial challenge encountered by waste management systems. Recycling tire rubbers in form of ground tire rubber, known as crumb rubber modifier (CRM), in asphalt industry was introduced in early 1960's and is proved as an effective recycling method. Interaction between CRM and asphalt is physical in nature which happens mainly due to exchange of components between CRM and asphalt and enhances the time temperature dependant properties of asphalt. In this work, the interaction between CRM and asphalt was evaluated through monitoring the evolutions of CRM in asphalt in macro and micro-level. The mechanism and extent of CRM dissolution were monitored under several interaction conditions. The composition of materials released from CRM was investigated using thermo-gravimetric analysis (TGA). The molecular status of the released components were studied using gel permeation chromatography (GPC) analysis. The composition analysis indicated that the CRM start releasing its polymeric components into the asphalt matrix at dissolutions higher than 20%. The released polymeric component of CRM alters the microstructure of the asphalt and creates an internal network at certain interaction temperatures according to viscoelastic analysis. At these temperatures, the released polymeric components are at their highest molecular weight based on GPC results. The effect of released components of CRM on the time temperature dependent properties of asphalt and its glass transition kinetic was monitored using dynamic shear rheometer (DSR) and differential scanning calorimetry (DSC), respectively. The DSC results showed that the intensity of glass transition of the asphalt binder which is mainly defined by the aromatic components in asphalt reduced by absorption of these components by CRM. The evolution of CRM was investigated during short-term aging of the modified asphalt binder. In addition, the effect of presence of CRM and release of its component on oxidization of asphalt binder was evaluated using Fourier transform infrared spectroscopy (FTIR). The results revealed that CRM continue absorbing the aromatic components of asphalt during aging which stiffen the asphalt binder. Also, it was observed that release of oily components of the CRM, which contain antioxidant, reduces oxidization rate of asphalt significantly.
A Stochastic Bayesian Update and Logistic Growth Mapping of Travel-Time Flow Relationship
(North Dakota State University, 2017) Molla, Mohammad Mofigul Islam
The travel-time flow relationship is not always increasing in nature, it is very difficult to predict precisely. Traditional method fails to replicate this unique conditions. Until millennium, although various researchers and practitioners have given much attention to develop travel-time flow relationships, the advancement to improve travel-time flow relationships was not substantial. The knowledge about the travel-time flow relationship is not commensurate with or parallel to the advancement of new knowledge in other fields. After millennium, most investigators did not devote enough attention to create new knowledge, except for application and performance evaluation of the existing knowledge. Therefore, it is necessary to provide a new theoretical and methodological advancement in travel-time flow relationship. Consequentially, this research proposes a new methodology, which considers stochastic behavior of travel-time flow relationship with probabilistic Bayesian statistics and logistic growth mapping techniques. This research moderately improves the travel-time flow relationship. The unique contribution of this research is that the proposed methods outperforms the existing traditional travel-time flow theory, assumptions, and modeling techniques. The results shows that the proposed model is considerably a good candidate for travel-time predictions. The proposed model performs 36 percent better and accurate travel-time predictions in compared to the existing models. Furthermore, travel-time flow relationship need capacity and free-flow speed estimations. Traditionally, practice of capacity estimation is mostly practical, subjective, and not steady-state capacity. Therefore, a robust and stable capacity-estimation method was developed to eliminate the subjectivity of capacity estimation. The proposed model shows robust and capable of replicating steady-state capacity estimation. The free-flow speed estimation should relate to the traffic-flow speed model while the density is zero. Therefore, this research investigates the existing deterministic speed-density models and recommends a better methodology in free-flow speed estimation. This research presents how the undefined practice of free-flow speed selection can be sensitive. Additionally, finding suitable concurrent travel-time data and traffic volume is crucial and very challenging. To collect concurrent data, this research investigates and develops several technologies such as crowdsource, web app, virtual sensor method, test vehicle, smartphone, global positioning system, and utilized several state and local agencies data collection efforts. Keywords: Travel-Time Flow, Travel-Time Delay, Volume-Delay Function, Travel Time, Origin-Destination Survey, Travel Demand Model, Travel Data Collection, Transportation Survey, Internet Sensor, Crowdsourcing, Virtual Sensor Method, VSM, Transportation Planning, GPS, Smartphone, Loop Detector, Travel -Time Prediction, Travel-Speed Prediction, TDM, Bayesian Inference, Logistic Growth Function.
Optimizing Selection and Implementation Protocols of Lean Construction Tools and Techniques for Rapid Initial Successes
(North Dakota State University, 2021) Aslam, Mughees
Lean construction (LC) has been considered as one of the most promising project management philosophies to overcome low productivity and excessive waste issues impacting the construction industry. Despite strong philosophies and some successful implementations, the uptake of LC in the construction industry is very low due to convoluted implementing strategies. Specifically, the construction industry lacks effective evaluation criteria, selection framework, and integrated applications of LC principles, tools, and techniques. Moreover, there is a strong need for a practical framework and associated validation process for LC implementation. Therefore, the purpose of this research is to optimize the selection and implementation protocols of LC tools and techniques for rapid initial successes. The methodology used for this research includes (1) a systematic literature review (SLR), (2) an initial survey of LC practitioners, (3) development of selection and implementation frameworks, and (4) framework validation survey and analysis. Uniquely, interpretative structural modeling (ISM) was used to develop the initial LC implementation framework and structural equation modeling (SEM) was used for framework modification and validation. As a result of the study, an effective selection framework has been developed with recommended LC tools and techniques to achieve integrated LC. The study has also identified critical factors for rapid initial LC project success and developed a robust LC implementation framework and an innovative integrated Last Planner System (ILPS). The validated LC implementation framework can predict approximately 65% of the variance in the project outcomes based on eight performance outcome measures. The major contribution of this study is that the construction industry can efficiently select and implement LC tools and techniques allowing them to significantly reduce waste and improve project performance. Additionally, the well-structured validation process developed in this study has been proven efficient and valid and therefore can be used widely for other research in the future.

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