Civil & Environmental Engineering Doctoral Work

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ADYTrack: A Model for Structural Analysis of Railroad Trackbed Using Random Finite Element Method
(North Dakota State University, 2019) Arshid, Asif
Railroads are playing pivotal role to the economic growth of United States and trackbeds ensure their safe and smooth operations. However, reliable trackbed performance prediction has always been challenging due to many reasons, for instance materials characterization, deteriorations of materials and geometries due to railways operation and environmental changes etc. All these factors exhibit varying levels of intrinsic variabilities and uncertainties. These variations and uncertainties are completely ignored in most of the state-of-the-practice problems due to lack of availability of robust models that can characterize variations in materials, geometries, and/or loadings. In this study, a Random Finite Element based three-dimensional numerical model, named ADYTrack, is developed for structural analysis of railroad trackbeds. Uniqueness of this model is the inclusion of materials’ intrinsic variabilities, geometric imperfections and/or uncertainties in axle loadings. The ADYTrack results, when compared with the analytical solution of a cantilever beam model, produced a maximum percentage difference of 0.7%; and 6% difference when compared with ANSYS software results for a single layer trackbed model; and a range of 5-20% difference was observed when validated against the actual field measurements. Sensitivity studies using RFEM based ADYTrack revealed that with the increasing variations in input parameters, measured by coefficient of variations (COV), the variations in output parameter also increased, and generally followed a bilinear trend with first linear component relatively insensitive up to around 30% COV of input parameters. However, beyond this limit, a considerable increase was observed in COVs of output parameters. For a COV of 80% in subgrade resilient modulus, a COV of 65% in vertical stress at the top of subgrade layer was observed. Additionally, the performance of any substructure layer found to be more sensitive to the variations in its own resilient modulus values. Furthermore, resilient modulus of subgrade layer was found to be the most influential input parameter, as revealed by many other studies, and so was its variations. To conclude, ADYTrack model can serve as a robust supplemental tool for railroad trackbed analysis, especially at locations that exhibit higher degrees of uncertainties and thus pose higher risk of public or infrastructure safety.
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.
Analysis on Structural Modeling for Recycled Asphalt Pavement used as a Base Layer
(North Dakota State University, 2015) Noureldin, Ehab Magdy Salah
Reusing RAP in the base layer became a common practice in the last decade. However, some crucial issues must be resolved to succeed in using RAP satisfying the standard specifications as a base layer. The most important unknown factor is the mechanistic behavior of RAP. This question may be satisfied by understanding the role of RAP in terms of whether it just behaves as a black rock or has a stabilizing effect with traditional aggregates used for base layer. The first stage of this study is modeling the structural behavior of RAP via prediction MR. This stage then comprises comparing the predicted results to actual measured data under several field conditions. The second stage focuses on the modeling behavior of PD. This stage takes in consideration two sets of data, the first is for the measured PD data calculated from MR test. While another traditional set of measured data for PD from repeated tri-axial loading (RTL) test either single or multi-stage is collected for the same RAP sources used in the first stage. The third stage concerns on MR-PD relationship. It indicates the typical relationship for the MR-PD behavior that can be understood for the RAP in base layer. The fourth and last stage is essential to investigate the Poisson’s ratio of RAP blends and its effectiveness on both parameters MR and PD. This ratio is measured during un-confined compression test. Two main testing conditions: various water and RAP contents are taken in consideration during this measurement for different RAP/Aggregate sources. This study proves that both prediction models used in the MEPDG for prediction of both parameters MR and PD are totally significant for RAP/Aggregate blends used for pavement base layer. The prediction is at the highest accuracy at water content levels close to OMC%, MDD and with 50% to 75% RAP content. In addition, it is proved that Poisson’s ratio is an effective parameter on both MR and PD parameters especially with variation of water content. This conclusion recommends to take in consideration Poisson’s ratio as an effective parameter in MR and PD prediction models used in MEPDG software.
Artificial Intelligence-Empowered Structural Health Monitoring, Damage Diagnosis, and Prognosis of Metallic Structures
(North Dakota State University, 2022) Zhang, Zi
etallic structures are the key backbone of the society and economy, which are often subjected to different types of loadings resulting cracking, corrosion, and other material discontinuity, and affecting structural integrity and safety. Therefore, ultrasonic guided wave (UGW) has been widely used for structural health monitoring (SHM) to gain a deep understanding of structural performance, assess the current state of structural conditions, and avoid potential catastrophic events. Despite advances in technologies and methods in data process, microdamage detection still posts great challenges in their detectability. Different from conventional physics-based methods, artificial intelligence and machine learning (AI/ML) has recently fueled profound automation solutions toward signal process and data fusion, thereby dramatically overcoming the limits. Along this vein, this study aims to propose AI-empowered SHM framework by decoding the UGW to uncover complex interconnected information among data, models, uncertainty, and risk for enhanced structural diagnosis and prognosis to improve metallic structural integrity and safety. Several structural cases, from one-dimensional plates/rods to three-dimensional pipes, were deliberately selected to demonstrate the real-world applications. Three different levels of the AI/ML approaches, from shallow learning to deep learning, are used to explore the effectiveness of the data fusion and data representation. Meanwhile, noise interference and structurally initial nonlinearity as typical structural uncertainty are included in data collection to understand the effects of data quality and uncertainty on the robustness of the proposed methods. The results showed that the proposed method was an efficient and accuracy way to identify the damage characteristics. Results from the shallow learning demonstrated that different features had certain levels of sensitivity to damage, while the feature selection method in the shallow learning revealed that time-frequency features and wavelet coefficients exhibited the highest damage-sensitivity. However, with the increase of noise level, the shallow learning failed in detectability. By taking advantage of higher automation in feature extraction, the deep learning exhibited significant improvement in accuracy, robustness, and reliability for structural diagnosis and prognosis. Particularly, the higher-layer architecture could outperform the shallow learning in terms of higher effective and efficient data fusion, and enhanced their capability in decoding information over noise interference and structural uncertainty.
Bonding Performances of Epoxy-Based Composites Reinforced by Carbon Nanotubes
(North Dakota State University, 2022) Zhang, Dawei
Epoxy resin has been exclusively used in many civil engineering applications such as adhesive joints and anti-corrosive coatings, but most of the usages of epoxy resin highly rely on a solid adhesive bonding between the epoxy matrix and the substrate material. In order to improve the bonding performance of epoxy resin, carbon nanotubes (CNTs) are incorporated into the epoxy resin due to their extraordinary mechanical properties. Although CNTs are expected to be promising additives for epoxy resin, the reinforcing efficiency of CNTs is still far from satisfactory, the bonding performance of CNT reinforced epoxy composites remains an essential research issue. In this dissertation, a systematic study was carried out to investigate the bonding performances of epoxy-based composites reinforced using CNTs. The influences of two main influential parameters (surface roughness and bondline thickness) on the bonding performance of epoxy-based composites were examined. It was found that rougher steel substrates or thinner epoxy bondlines yielded better bonding performances for both unreinforced and CNT reinforced epoxy composites. However, according to the SEM image analyses, the reinforcing efficiency of CNTs was restricted by the non-uniform dispersion of CNTs in the epoxy matrix resulted from CNT agglomeration and entanglement. Given that the great variances of CNT geometries may inevitably result in extensive differences on CNT dispersion status and reinforcing efficiencies in CNT reinforced epoxy composites, the dispersion characterizations and bonding performance of CNT reinforced epoxy composites with different CNT geometries were studied. The experimental results indicated that CNTs with larger diameter (50-100 nm) had a greater ability to achieve more uniform dispersion which further led to better bonding performance. Although CNT length did not have an evident effect on the CNT dispersion, epoxy-based composites reinforced by normal-length CNTs (5-20 μm) had higher bonding strength and toughness than those by shorter CNTs (0.5-2 μm). To further improve the dispersion effectiveness of CNTs, a novel CNT mixing method using carboxymethyl cellulose (CMC) was proposed. It was proved that better CNT dispersion resulted from the CMC surface treatment significantly improved the bonding performance of CNT reinforced epoxy composites.
Bounding Surface Approach to the Fatigue Modeling of Engineering Materials with Applications to Woven Fabric Composites and Concrete
(North Dakota State University, 2011) Wen, Chao
It has been known that the nucleation and growth of cracks and defects dominate the fatigue damage process in brittle or quasi-brittle materials, such as woven fabric composites and concrete. The behaviors of these materials under multiaxial tensile or compression fatigue loading conditions are quite complex, necessitating a unified approach based on principles of mechanics and thermodynamics that offers good predictive capabilities while maintaining simplicity for robust engineering calculations. A unified approach has been proposed in this dissertation to simulate the change of mechanical properties of the woven fabric composite and steel fiber reinforced concrete under uniaxial and biaxial fatigue loading. The boundary surface theory is used to describe the effect of biaxial fatigue loading. A fourth-order response tensor is used to reflect the high directionality of the damage development, and a second-order response tensor is used to describe the evolution of inelastic deformation due to damage. A direction function is used to capture the strength anisotropic property of the woven fabric composite. The comparisons between model prediction results and experimental data show the good prediction capability of models proposed in this dissertation.
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.
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.
Corrosion Risk Assessment System For Coated Pipeline System
(North Dakota State University, 2018) Deng, Fodan
Steel is widely used as building material for large-scale structures, such as oil and gas pipelines, due to its high strength-to-weight ratio. However, corrosion attack has been long recognized as one of the major reasons of steel pipeline degradation and brings great threat to safety in normal operation of structure. To mitigate the corrosion attacks, coatings are generally applied to protect steel pipelines against corrosion and improve durability of the associated structures for longer service life. Although have higher corrosion resistance, coated pipelines will still get corroded in a long run, as coatings may subject to damages such as cracks. Cracks on coatings could lower the effectiveness of protection for associated structures. Timely updates of up-to-date corrosion rate, corrosion location, and coating conditions to the pipeline risk management model and prompt repairs on these damaged coatings would significantly improve the reliability of protected structures against deterioration and failure. In this study, a corrosion risk analysis system is developed to detect and locate the corrosion induced coating cracks on coated steel using embedded fiber Bragg grating (FBG) sensors. The coatings investigated include high velocity oxygen fuel (HVOF) thermal sprayed Al-Bronze coating, wire arc sprayed Al-Zn coating, and soft coating. Theoretical models of corrosion risk assessment system were carried out followed by systematic laboratory experiments, which shows that the developed system can quantitatively detect corrosion rate, corrosion propagations, and accurately locate the cracks initialized in the coating in real time. This real-time corrosion information can be integrated into pipeline risk management model to optimize the corrosion related risk analysis for resource allocation. To place the sensing units of the system in the most needed locations along the huge pipeline systems for an effective corrosion risk assessment, an example case study is conducted in this study to show how to locate the most critical sensor placement locations along the pipeline using worst case oil and gas discharge analysis. Further applications of the developed system can be integrated with pipeline management system for better maintenance resource allocations.
Crack-Dependent Response of Structural Steel Members Repaired with CFRP
(North Dakota State University, 2014) Hmidan, Amer
Cracking of the lower flange in steel-girder bridges is a critical consideration because it will influence flexural behavior such as load-carrying capacity. Timely rehabilitation will save long-term repair costs and warrant sustainable performance. Carbon-fiber-reinforced polymer (CFRP) is a promising material to repair damaged steel members. This non-metallic reinforcement provides a number of benefits when compared to traditional repair materials (e.g., welded steel plates) for deteriorated steel girders: for example, a favorable strength-to-weight ratio, resistance to corrosion and fatigue, rapid installation in practice, and reduced long-term maintenance expenses. Although applying CFRP to steel members has recently attracted the rehabilitation community, its contribution to the behavior of repaired members is not fully understood. Very limited information about the interaction between the level of initial damage in steel girders and CFRP-repair is available, and also, scant research about the long-term performance and environmental durability for such repaired members has been done. This study addresses these identified research gaps based on a two-phase experimental program. The first phase focuses on CFRP-repaired steel beams having various levels of initial damage (representing multiple stages of fatigue crack propagation). The second phase is focused on testing the repaired beams when subjected to various levels of sustained intensity and cold temperature. A three-dimensional non-linear finite element (FE) model is developed to predict the flexural behavior of CFRP-repaired beams, including CFRP debonding and crack propagation across the critical section of the repaired beams. Also, the FE method is used and regression equations are proposed to predict the static strength of standard steel W Shapes repaired with CFRP, taking into consideration the material and geometric properties.
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.
Dynamic Interaction of Vehicle and Bridge Subjected to Prestress Force Loss and Foundation Settlement
(North Dakota State University, 2016) Zhong, Hai
Plenty of bridges in U.S. are suffering from prestress force loss and foundation settlements. The loss of prestress force in bridge load-carrying members such as girders may lead to the malfunction and even failure of the prestressed bridges that comprises more than 55% of all new and replaced bridges built in US between the year 2000 and 2012. Settlement of foundations supporting the bridge piers and abutments impairs the superstructure integrity and serviceability of the bridge, or even collapses the bridge if the settlement is over a certain limit. In present study, the dynamic interaction between vehicles and the bridges subjected to prestress force loss and foundation settlement has been investigated. Based on modal superposition technique and principal of virtual works, new bridge-vehicle interaction models have been created to take the effects of prestress and foundation settlement on dynamic bridge and vehicle responses into account. With the developed models, numerical simulations have been performed to show that the prestress force makes the distribution of impact factors along the bridge unbalanced and the existence of foundation settlement may couple with road surface roughness of the bridge deck to possess an aggregated overall effect amplifying the bridge responses. In general, the vehicle responses are vulnerable to the prestress force loss and foundation settlement, which harms the riding comfort of passengers. The existed direct and indirect methods used for prestress loss identification are all based on the measurement collected from sensors deployed on the outside or inside of the bridge, which is not only costly but also inconvenient. The current study proposes to detect the prestress force loss of the bridge through the analysis of vehicle responses. Through simulations, it is found that light, low-frequency vehicles moving at low speeds have a better performance in detecting the bridge prestress loss than the heavy, high-frequency vehicles with high speeds. The advantage of the proposed method is that it only needs a few sensors installed on the vehicle, and works without interrupting the ongoing traffic, which is efficient and cost-effective.
Enhancement of Dispersibility of Zero-Valent Iron Nanoparticles for Environmental Remediation: Entrapment and Surface Modification with Polymers
(North Dakota State University, 2012) Krajangpan, Sita
Nanoscale zero-valent iron (NZVI) particles have been surface modified and used for contaminant remediation. NZVI tend to agglomerate due to magnetic and van der Waals forces and form larger particles that settle down in aqeous media. Agglomerated particles increase in size and have decreased specific surface area and that lead to decrease in their reactivity. In this research, polymer-based surface modifiers were used to increase dispersibility of NZVI for environmental remediation applications. Ca-alginate was selected to entrap NZVI in beads and used to remove aqueous nitrate. The two-way ANOVA test indicates that there was no significant difference between reactivities (towards nitrate) of entrapped NZVI and bare NZVI. While the reactivity of entrapped NZVI was comparable to bare NZVI, the NZVI particles were found to remain agglomerated or clustered together within the alginate beads. A novel amphiphilic polysiloxane graft copolymers (APGC) was designed, synthesized and used to coat NZVI in an attempt to overcome the agglomeration problem. APGC was composed of hydrophobic polysilosin, hydrophilic polyethylene glycol (PEG), and carboxylic acid. The APGC was successfully adsorbed onto the NZVI surfaces via the carboxylic acid anchoring groups and PEG grafts provided dispersibility in water. Coating of NZVI particles with APGC was found to enhance their colloidal stability in water. The APGC possessing the highest concentration of carboxylic acid anchoring group (AA) provided the highest colloidal stability. It was also found that the colloidal stability of the APGC coated NZVI remained effectively unchanged up to 12 months. The sedimentation characteristics of APGC coated NZVI (CNZVI) under different ionic strength conditions (0-10 mM NaCl and CaCl2) did not change significantly. Degradation studies were conducted with trichloroethylene (TCE) and arsenic(V) [As(V)] as the model contaminants. TCE degradation rates with CNZVI were determined to be higher as compared to bare NZVI. Shelf-life studies indicated no change on TCE degradation by CNZVI over a 6-month period. As(V) removal batch studies with CNZVI were conducted to in both aerobic and anaerobic conditions. Increase in arsenic removal efficiency was observed with CNZVI as compare to bare NZVI in both aerobic and anaerobic conditions. Ionic strengths showed minimal inhibiting effect on arsenic removal by CNZVI.
Enhancing the Performance of Crumb Rubber Modified Asphalt through Controlling the Internal Network Structure Developed
(North Dakota State University, 2016) Ragab, Mohyeldin
Sustainability presents a pathway for future generations to have a better life. Cradle to cradle methodology is the essence of sustainability. In cradle to cradle approach, we aim to reuti-lize a given waste instead of disposing or landfilling it. Each year, millions of waste tires are dis-posed of in landfills. This poses a major challenge environmentally and economically. Environ-mentally, those tires become prone to fire hazards as well as being a place for rodents and mos-quitos to reside at. Economically, on the other hand, each tire has an average of about 50% valu-able polymers as well as oily components. One of the methods to utilize the valuable raw materi-als in waste tires is to recycle it in the form of ground tire rubber also known as crumb rubber modifier (CRM). Although CRM has been widely used as an asphalt modifier, however, due to the complexity of asphalt as well as the waste nature of CRM, the full understanding of the CRM modification mechanism with asphalt has not been fully understood. Understanding of the modi-fication mechanisms involved in the CRM interaction with asphalt would enable us to produce a crumb rubber modified asphalt (CRMA) with enhanced properties. In the current research work, an attempt is made to better understand the mechanism of interaction between CRM and asphalt and the nature of components from asphalt and CRM that take part in the interaction between them. In addition, we investigate the effectiveness of CRM as a modifier for asphalt on the mac-ro and microscale aspects. Another part of the current research work deals with a second waste material; used motor oil. Used motor oil (UMO) presents yet another challenge to environment. With the ever increas-ing motor vehicles produced with advanced technologies and increased advanced motor oil de-mand. This presents a burden on the environment, with the continuous production of UMO. In the current research work, we investigated the feasibility of utilizing UMO as a modifier for asphalt and CRMA. We also investigated the effect of UMO on the micro and macroscale aspects of asphalt.
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.
Exploring Chemically Treated Fiber Reinforced Pervious Concrete Through Image Based Micromechanical Modeling
(North Dakota State University, 2019) Akand, Lutfur
Pervious concrete has been widely used in parking lots and airport fields. However, past experience has shown durability and strength of the pervious concrete remains a challenge for adopting them in wider applications, as the binding material proportion is low and the use of fine aggregates is nearly zero. The position, size and shape distribution of voids in the pervious concrete microstructure control the overall behavior of the material. In this research, the influence of the distribution of voids on the strength, stiffness, and permeability of pervious concrete microstructure is studied by 2D image analysis and finite element modeling through MATLAB and ANSYS Parametric Design Language (APDL). The effect of the sample size of 2D microstructures is studied by varying the section size and a possible representative volume element (RVE) is therefore found. Predicted stress-strain plots are generated for the 2D specimen under compressive load and the obtained results, including stiffness, strength and permeability are compared with the results from the experiments conducted following ASTM standards. In order to enhance bonding between reinforcement fiber and cement matrix, chemical treatment is adopted and applied on short polypropylene fibers when used in pervious concrete as reinforcement. The change in fiber surface due to the treatment is determined through fiber wettability test and Atomic Force Microscopy (AFM). Single fiber pullout tests are conducted to study the effect of the treatment type on fiber-cement interface properties. Treated fibers are then put into pervious concrete matrix for compressive and flexural strength tests. With the chemical treated fibers, 2D microstructures of fiber reinforced pervious concrete are generated and cohesive zone technique is used to model the interface between fiber and concrete matrix, with its interface properties extracted from single fiber pullout tests. Load-displacement plots are generated in ANSYS for specimen under compression for different mixes. Through the validated micromechanical model and its modeling results of different fiber reinforced pervious concrete mix, an optimization method is developed to provide a useful tool for mix design of reinforced pervious concrete with chemically treated fibers.
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.
Fate and Transformation of a Conjugated Natural Hormone 17β-Estradiol-3-Glucuronide in Soil-Water Systems
(North Dakota State University, 2011) Shrestha, Suman Lal
The objectives of the study were to investigate the sorption and degradation of a glucuronide conjugated natural hormone, 17β-estradio1-3-glucuronide (E2-3G), and its estrogenic metabolites in soil-water systems. Radiolabeled E2-3G was first synthesized in the laboratory. Soil-water batch experiments were then conducted using natural and sterilized topsoil (0-6 cm) and subsoil (18-24 cm) with the radiolabeled E2-3G to investigate the effects of soil organic matter content and microbial activity. The aqueous dissipation of 14C in the batch experiments followed a biphasic pattern with an initial rapid dissipation phase followed by a second slower phase. Significant differences in total aqueous 14C dissipation were observed for the different initial concentrations for both soils, with greater persistence of intact E2-3G at higher initial concentrations.
GFRP Bars in Concrete toward Corrosion-free RC Structures: Bond Behavior, Characterization, and Long-term Durability Prediction
(North Dakota State University, 2016) Yan, Fei
Corrosion of steel reinforcements is the leading causes of malfunction or even failures of reinforced concrete (RC) structures nationwide and worldwide for many decades. This arises up to substantial economic burden on repairs and rehabilitations to maintain and extend their service life of those RC public projects. The inherent natures of glass fiber-reinforced polymers (GFRP) bars, from their superior corrosion resistance to high strength-to-weight ratio, have promoted their acceptance as a viable alternative for steel reinforcement in civil infrastructures. Comprehensive understanding of the bond between GFRP bars and concrete, in particular under in-service conditions or extremely severe events, enables scientists and engineers to provide their proper design, assessment and long-term predictions, and ultimately to implement them toward the corrosion-free concrete products. This research aims to develop a holistic framework through an experimental, analytical and numerical study to gain deep understanding of the bond mechanism, behavior, and its long-term durability under harsh environments. The bond behavior and failure modes of GFRP bar to concrete are investigated through the accelerated aging tests with various environmental conditions, including alkaline and/or saline solutions, freezing-thawing cycles. The damage evolution of the bond is formulated from Damage Mechanics, while detailed procedures using the Arrhenius law and time shift factor approach are developed to predict the long-term bond degradation over time. Besides, the machine learning techniques of the artificial neural network integrated with the genetic algorithm are used for bond strength prediction and anchorage reliability assessment. Clearly, test data allow further calibration and verification of the analytical models and the finite element simulation. Bond damage evolution using the secant modulus of the bond-slip curves could effectively evaluate the interface degradation against slip and further identify critical factors that affect the bond design and assessment under the limit states. Long-term prediction reveals that the moisture content and elevated temperature could impact the material degradation of GFRP bars, thereby affecting their service life. In addition, the new attempt of the Data-to-Information concept using the machine learning techniques could yield valuable insight into the bond strength prediction and anchorage reliability analysis for their applications in RC structures.
Hygrothermal Effects of Air Cavities Behind Claddings on Building Envelopes
(North Dakota State University, 2022) Xie, Yanmei
Air cavity behind claddings within building envelope provides an approach to mitigating building moisture-related issues as well as improving the building’s thermal performance. However, studies in literature commonly assume the cavity air as still and thus neglect the influence of mixed convection on the performance of building envelope. In addition, the drying performance of the air cavities remains unknown, and commonly a rectangular unicellular cavity is improperly assumed to simplify the investigation of the hygrothermal performance of a cladding system. Moreover, the literature lacks a study of the effect of humid air in the air cavity on heat and mass transfer. Therefore, it necessitates advanced problem formulation and solving to comprehensively study the effects of air cavities behind claddings on the performance of building envelope. The specific objectives are to 1) investigate potential of self-drying siding with raised air cavities for building envelopes; 2) study the effects of the cavity depth in mixed convection of air cavity for building envelopes; 3) analyze the effects of humid air in an air cavity on mass and heat transfer with phase change at the wall. To achieve these objectives, firstly, this study redefines the drying potential of air cavity taking into account the air cavity depth related to the shape irregularity and the inlet and outlet uncertainties. Then the formulated problems of mixed convection of air cavities behind sidings are solved with a perturbation method and SIMPLER algorithm. The results show that the drying performance is found to be heavily dependent on the cavity depth. Further, increasing the ratio of the siding depth to the air cavity depth amplifies the cavity air’s velocity, temperature, and mass fraction at cavity walls, as well as the heat and mass transfer across cavities. Consequently, this study demonstrated that humid air with the phase change and the cavity depth have the significant effects on the hygrothermal performance of building envelopes. The outcome of this study provides valuable guidance on the thermal performance evaluation of air cavity and has the potential of improving the design of claddings for the overall hygrothermal performance of building envelope.

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