Civil & Environmental Engineering

Permanent URI for this communityhdl:10365/32547

Research from the Department of Civil & Environmental Engineering. The department website may be found at https://www.ndsu.edu/ce/

The Civilian is the newsletter for the Department of Civil Engineering and can be found at https://hdl.handle.net/10365/28260

Browse

Now showing 1 - 20 of 27

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.
Analyses of Highway Project Construction Risks, Performance, and Contingency
(North Dakota State University, 2010) Mohamed, Fahmy Diab
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 and Evaluation of the Pedestrian Hybrid Beacon in School Zones
(North Dakota State University, 2010) Bittner, Michael Howard
Meeting dual objectives of pedestrian safety and motorist convenience at pedestrian crossings in school zones is an important and continuing challenge for all local communities. Pedestrian safety is influenced by pedestrian delays as well as motorist compliance of controls. Motorist convenience is influenced by the delay experienced by drivers. Conventional crosswalk control devices such as marked crosswalks and pedestrian signals are not always adequate or efficient in balancing these two crucial but conflicting objectives. The 2009 edition of the Manual on Uniform Traffic Control Devices (MUTCD) has paved the way for the use of a brand new crosswalk control device known as the pedestrian hybrid beacon (PHB). Previous research has provided evidence of this device's effectiveness in the area of motorist compliance and reduced motorist delay compared to traditional pedestrian signals. No prior research has been conducted on the PHB in the school zone context or on children pedestrians in general. This research has two objectives. The first objective was to analyze MUTCD Warrant 5 standards, which are designed for pedestrian signals in school zones, and the new PHB standards. This analysis will use pedestrian volume, vehicle volume, and gap availability on different test locations to conduct a comparative analysis of the two sets of standards. The purpose of this objective is to determine the transferability of the new MUTCD PHB standards in the school zone context. The second objective of this research was to evaluate three crosswalk control devices; marked crosswalks, pedestrian signals, and PHBs, for their ability to effectively address pedestrian safety and motorist convenience at school crossings. It was found that the PHB performed significantly better than traditional marked crosswalks but not markedly different than conventional pedestrian signals in the ability to balance the objectives of pedestrian safety and motorist convenience. The absence of improvements in performance of the PHB when compared to the pedestrian signal can be attributed to the fact that only 8.8% of motorists correctly utilized the PHB at the test location in Fargo, North Dakota. The most significant contribution of this thesis was finding that the current PHB standards in MUTCD are not transferable to the school zone context. For PHBs to be considered a viable option for engineers designing and controlling school crosswalks, it is essential that the MUTCD have school zone specific standards or guidance. The analysis carried out in this research provides insights into how such standards can be established and applied.
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.
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.
Comparisons of Energy Dissipation in Structural Devices with Foundation Soil During Seismic Loading
(North Dakota State University, 2010) Saravanathiiban, Duraisamy Soundararajan
The effectiveness of structural energy dissipation mechanisms such as passive energy dissipation devices and base isolation methods used in seismic design depends on their capacity, ductility, energy dissipation, isolation, and self-centering characteristics. Though rocking shallow foundations could also be designed to possess many of these desirable characteristics, current seismic design codes often avoid nonlinear behavior of soil and energy dissipation beneath foundations because of concerns about permanent deformations at foundation level. This thesis compares the effectiveness of energy dissipation in foundation soil with structural energy dissipation devices during seismic loading. Numerical simulations of structures with and without energy dissipation devices were carried out to systematically study the seismic energy dissipation in structural elements and energy dissipation devices. The numerical model was validated using shaking table experimental results on model frame structures with and without energy dissipation devices. The energy dissipation in the structure, drift ratio, and the force and displacement demands on the structure are compared with energy dissipation characteristics of rocking shallow foundations as observed in centrifuge experiments, where shallow foundations were allowed to rock on dry sandy soil stratum during dynamic loading. The comparisons of results clearly indicate that foundation (rocking) energy dissipation mechanism is as efficient as structural passive energy dissipation devices. For the structures with energy dissipating devices, about 70% to 90% of the seismic input energy is dissipated by energy dissipating devices, while foundation rocking dissipates about 30% to 90% of the total seismic input energy in foundation soil (depending on static factor of safety). Inclusion of energy dissipating braces increases the base shear force transmitted to the structure, while normalized base shear forces transmitted to the foundation during rocking are smaller than those of the structures with energy dissipating devices because of the isolation effect of rocking foundations. If properly designed (with reliable capacity and tolerable settlements), adverse effects of foundation rocking can be minimized while taking advantage of the favorable features of foundation rocking, and hence they can be used as efficient and economical seismic energy dissipation mechanisms in buildings and bridges.
Cumulative-Anticipative Car-Following Model for Enhanced Safety in Autonomous Vehicles
(North Dakota State University, 2020) Yang, Xinyi
As the rapid development of smart cities, autonomous vehicles are considered to be the future ground transportation measure which provides many benefits over traditional human-driving vehicles. However, there will be decades before the autonomous vehicles fully penetrate, during when human-drivers will share the same road systems with the autonomous vehicles, where the majority of accidents associated with autonomous vehicles are induced by the operation inconsistency of human drivers, which can be avoided if there is communication between the autonomous vehicles and the infrastructure (V2I). This study develops cumulative-anticipative car-following (CACF) model for autonomous vehicles based on the Cooperate Adaptive Cruise Control/ Adaptive Cruise Control (CACC/ACC) model by considering cumulative influences from multiple preceding vehicles. The simulation results from 128 simulation runs using the micro-simulator VISSIM showed that the CACF model can improve the safety and traffic congestions compared to the Wiedemann 99, the ACC, and the CACC models.
Detection of Two-Dimensional Internal Cracks in Concrete Using Point Strain Sensors
(North Dakota State University, 2020) Alshandah, Mohanad
Tensile cracking in the concrete can destroy the structural frame since it induces water penetration in structure and foundation. For instance, in concrete pavements, cracking increases the potential for pavement distress, the probability of accidents occurring, and the damages for vehicles. Therefore, monitoring techniques to detect hidden internal cracking in concrete such as bottom-up cracks are necessary to ensure the safety of the infrastructure by distinguishing early signs of excessive damage. This study presents an approach to detect internal concrete cracks especially bottom-up cracks using point strain sensors. The stress intensity principle is used in this study to locate and estimate the growth of the cracks. Based on the stress intensity principle, theoretical derivations have been conducted to use the point strain sensors in concrete structures to detect both single and multiple bottom-up cracks. For single crack detection, laboratory experiments showed an average measurement accuracy of 85.76%. For multiple cracks, laboratory tests performed using reinforced concrete beams and the average measurement accuracy was achieved to be over 80%. With the validation in the lab, future efforts are expected to be performed in the field to provide an alternative technique to detect hidden internal cracks in concrete structures, especially pavements.
Durability of Concrete Members Strengthened with CFRP Sheets under Harsh Environmental Conditions
(North Dakota State University, 2010) Hossain, Md. Mozahid
The deterioration of concrete structures 1s a maJor concern to the infrastructure community. Typical sources of deterioration may include aging,.incrcased service load, and environmental damage. Structural rehabilitation using carbon fiber reinforced polymer (CFRP) sheets has recently attracted attention to the infrastructure community because of the superior strengthening effects in comparison to conventional repair methods. The CFRP sheets may be bonded on the deteriorated concrete structure using bonding agents to enhance load-carrying capacity. The most important consideration in such a strengthening method may be the long term durability under harsh environmental conditions. Furthermore, premature debonding of bonded CFRP sheets may also cause significant losses of the strengthening effects. Although extensive research has been reported on the debonding mechanism of CFRP sheets, there is still lack of understanding on the durability of CFRPs subject to low temperature effects. This thesis presents some major findings of the durability performance of concrete members strengthened with CFRP sheets subjected to harsh environments.
Earthquake-induced inelastic displacement ratio in reinforced concrete box girder bridges in California
(North Dakota State University, 2024) Gyawali, Bigya
In conventionally designed bridges, the inelastic displacement is estimated using an amplification factor (R_d) suggested by AASHTO which was developed based on Single-Degree-of-Freedom system. This study models the nonlinear behavior in different components of bridge and presents an equation of inelastic displacement ratio, C_μ, that can better predict the inelastic displacement. While AASHTO R_d closely matches C_μ corresponding to average response of different earthquakes, it does not give a reliable estimation for a wide range of earthquakes. Two equations are developed based on mean + standard deviation (SD) and mean + 3×SD to incorporate the variability in C_μ due to dynamic nature of bridge and wide range of earthquake. Additionally, it examines the influence of connection of columns to the ground, column height, deck width, number of spans, and damping ratio on C_μ. Contrary to AASHTO suggestion, C_μ was found to be increasing with increase in damping ratio.
Evaluating the Effects of Rail Preemption Strategies on Highway Safety and Operations
(North Dakota State University, 2011) Bratlien, Andrew Lee
Previous research related to signal preemption near highway-rail grade crossings has emphasized safety considerations, which are paramount due to the severity of potential train-vehicle collisions. The purpose of this research was to quantify the safety and efficiency implications of several common preemption strategies using the conditions in a small urban context. The research evaluates several important characteristics of rail preemption, including track clearance time, advance preempt time, and dwell cycle strategy, particularly with regard to surface street operational efficiency, that current traffic engineering practice do not adequately address. The context and preemption strategies were modeled using simulation software VISSIM. The results identified two separate and potentially serious safety issues related to the interaction of advance preempt time, track clearance time, and existence of four-quadrant gates at railroad crossing. In addition, the research also highlighted the negative effect of excessive track clearance time and dwell cycle on adjacent surface street operations.
Evaluating the Safety and Mobility of the Cumulative-Anticipative Car-Following Model for Connected Autonomous Vehicles
(North Dakota State University, 2020) Ahmed, Hafiz Usman
The advancements of vehicle automation are progressively improving resulting in safer driving environments in addition to more efficient mobility and fuel cost savings. However, autonomous and connected autonomous vehicles (AVs, CAVs) require decades to achieve complete market penetration. It is important to investigate the coexistence of conventional and autonomous cars during such a transition period. Traditionally, adaptive cruise control (ACC) and cooperative ACC (CACC) models were used for the AVs to guide their car-following. Recently, the cumulative-anticipative car-following (CACF) model was developed with consideration of the cumulative influences from surrounding vehicles through vehicle-to-everything (V2X) communication. This study further evaluates the safety and mobility performances of the CACF model for CAVs in mixed traffic through various sensitivity tests using the VISSIM simulation platform. The results demonstrate that the CACF model has promising improvements in roadway safety and network performances compared with the Wiedemann 99 and CACC models in mixed environments.
Filamentous Growth in Entrapped Microbial Cell Reactor Treating Wastewater
(North Dakota State University, 2010) Sathyaseelan, Vinodgnanadrepan
The overgrowth of filamentous microorganisms in wastewater treatment systems is a common adversary condition leading to foaming, poor sludge settling problems, and reduction in organic removal efficiency. Entrapped microbial cell reactors have been investigated for their uses in wastewater treatment. However, their susceptibility to filamentous growth is not known. The objective of this study is to investigate the filamentous growth and its effect on the treatment performance of an entrapped microbial cell system treating wastewater. A typical activated sludge wastewater treatment system was included for comparative purpose. Both systems were operated at the same operating conditions using synthetic wastewater. Four different hydraulic retention times (HRT) (9, 6, 3, 1.5 hours), three different dissolved oxygen (DO) concentrations (2, 4.5 and 5.7 mg/1), and three different influent chemical oxygen demand (COD) concentrations ( 120, 206 and 300 mg/I) were investigated. Results showed that DO and organic loading rate (COD/HRT) did not have any effect on the organic (soluble COD and soluble biochemical oxygen demand at 5 days) removal efficiencies at high and medium HRT (9 and 6 hours), even when there was excessive filamentous growth in the entrapped microbial cell reactor. The organic removal efficiencies of the activated sludge system dropped for some cases at high and medium HRT because of excessive filamentous overgrowth. At low HRT (3 hours), there was abundant filamentous growth and a drop in the organic removal efficiencies in the entrapped microbial cell reactor. To determine the reason (between HRT and filamentous abundance) for the decreases in organic removal efficiencies by the entrapped microbial cell system at the low HRT, a very low HRT of 1.5 hours was applied. DO and organic loading rate did not affect organic removal efficiencies of the entrapped cell reactor. Reduction of the filamentous microorganisms was attempted by chlorination using sodium hypochlorite. Three different chlorine dosages, I, 0.25 and 0.50 g NaOCl/d, were applied. The dosage of 0.25 g NaOCl/d was found to be very effective in controlling the filamentous overgrowth in the entrapped microbial cell reactor. The reduction of filamentous organisms by chlorination did not result in improved organic removal efficiencies, suggesting that the very low HRT rather than the abundance of filamentous organisms was responsible for the poorer performance of the reactor. A cell morphology and organelle analysis indicated Sphaerotilus natans as the most frequently observed filamentous microorganism in the entrapped microbial cell reactor. A thick layer of biofilm was also observed on the entrapment matrix. The biofilm did not affect the performances of the reactor. These results suggested that the entrapped microbial cell reactor is subjected to filamentous overgrowth, but it has no effect on the performances of the reactor.
Fracture Initiating Mechanism in Additively Manufactured 17-4 Stainless Steel
(North Dakota State University, 2022) Anto, Anik Das
Additive manufacturing provides exceptional geometrical freedom to the designers and enables the production of parts that cannot be made through subtractive processes. Defects in additively manufactured (AM) metals are detrimental to the manufactured components. This study aims to understand the fracture initiation mechanism in as-built AM 17-4 stainless steel. Micro-computed tomography (micro-CT) analysis was conducted on the undeformed and fractured unnotched and notched specimens to characterize the defects in the as-printed specimens before and after deformation. The micro-CT analysis showed that the initial void count and volume fraction increased after the deformation indicating new void nucleation and dilation of voids. Furthermore, coalesced void colonies were noticed in the fractured specimens in the vicinity of the fracture surface. Evidence for void nucleation, dilation, and coalescence indicates ductile fracture to be the fracture initiation mechanism in AM 17-4 steel.
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.
Identification, Categorization, and Prediction of Drought in Cold Climate Regions
(North Dakota State University, 2021) Bazrkar, Mohammad Hadi
To mitigate drought losses, identification, categorization, and prediction of droughts are essential. The objectives of this dissertation research are (1) to improve drought identification in cold climate regions by developing a new hydroclimatic aggregate drought index (HADI) and a snow-based hydroclimatic aggregate drought index (SHADI), (2) to customize drought categorization by considering both spatial and temporal distributions of droughts, and (3) to improve drought prediction by modifying the traditional support vector regression (SVR). R-mode principal component analyses (PCA) are conducted for rainfall, snowmelt, surface runoff, and soil water storage to derive the HADI. Instead of rainfall and snowmelt in the HADI, precipitation and snowpack are used to estimate the SHADI for adding the capability of snow drought identification. Drought frequencies and classes form a bivariate distribution function by applying a joint probability distribution function. A conditional expectation is further used to estimate the probability of occurrence of droughts. To derive variable threshold levels for drought categorization, hierarchical K-means clustering is used. For drought prediction, a change point detection method is employed to split the non-stationary time series into multiple stationary time series. SVR is further performed on each stationary time series to predict drought. The new drought methods were applied to the Red River of the North Basin (RRB). The 1979-2010 and 2011-2016 data obtained from the North American land data assimilation system were used for training and testing, respectively. Precipitation, temperature, and evapotranspiration were selected as the predictors, and the target variables consisted of multivariate HADI and SHADI, bivariate standardized drought indices, and univariate standardized drought indices. The results showed that the new HADI and SHADI, together with the customized drought categorization, were able to provide more accurate drought identification and characterization, especially for cold climate regions. The comparison of the results of the traditional and modified SVR models in the RRB demonstrated better performance of the modified SVR, particularly when drought indices with higher sensitivity to temperature were used. The methodologies developed in this dissertation research can be used for improving drought identification, categorization, and prediction, as well as further mitigating the potential adverse impacts of droughts.
Image-Based Hybrid Structural Health Monitoring Through Artificial Intelligence
(North Dakota State University, 2022) Bai, Xin
Bridges are widely used in human life. Understanding structural performance, assessing structural conditions, and providing in-time decision are crucial components in structural health monitoring (SHM), to avoid catastrophic events and improve public safety. However, traditional SHM needs traffic closure, extensive sensor deployment, and in-contact measurements. The main purpose of this thesis is to develop a vision-based sensor of high accuracy that does not need artificial targets. When the vibration of the UAV itself is removed, the UAV is a convenient method to record video of the vibrations. Based on the recorded images and vibration data, a new deep learning method is developed and used to analyze vibrations of the structure and detect damage locations and conditions automatically. In the thesis, a non-contact vision sensor system for monitoring structural displacements with an advanced Zernike subpixel edge detection technique is first suggested. A new method to filter the effect of camera motions through background templates is proposed in the study. Several experiments on the MTS machine were performed with different frequencies and amplitudes to verify the method. The results show that filtering of vibrations of the camera significantly improves the displacement monitoring accuracy from 53.0% to 97.0%. Three translations and three rotations of the unmanned aerial vehicle (UAV) were derived through the suggested fast Normalized Cross Correlation (NCC) based template matching method, and their effect on the monitored structural displacement is analyzed. To verify the concept, a series of lab and field experiments were performed. Excellent precision and consistency were obtained for the UAV monitored displacement, the MTS piston motion, and the fixed camera derived displacement. Further in the thesis, a novel deep learning-based structural health monitoring method was developed, which could detect damages using both defects and vibration data. Two ABAQUS models on a beam and an ABAQUS model on a truss were conducted to test if the proposed CNN model could detect damages successfully. Seven transfer learning methods were compared on detecting crack images. From the outputs of the deep learning models, it is apparent that the AlexNet CNN model with defect images shows higher accuracy in estimating damage status.
Investigating the Influences of Ingredients, W/C Ratio and Dispersion Methods for CNT Modified Smart Concrete
(North Dakota State University, 2022) Jannat, Tofatun
Carbon nanotubes (CNT) have excellent electromechanical properties and can be added into cement using appropriate dispersive means to produce CNT-modified cement-based smart materials (CNTCS). This study investigates how the ingredients, W/C ratio and dispersion methods influence the sensing ability of the smart concrete. Three different dispersion methods were investigated: direct mixing, surfactant surface treated with NaDDBS, and the Carboxymethyl cellulose (CMC) surface modification. CMC surface modification method showed consistency for modified cement paste and cement-sand composite material. For CMC surface treatment method, 0.6 w/c ratio was found to be optimal compared to 0.4 and 0.5. Coarse aggregate was added with cement and sand for 0.6 w/c ratio, and consistent piezo electric response was observed under dynamic loading for CMC surface treated smart concrete. However, significant reduction of sensitivity was observed between the CMC surface treated CNT modified smart concrete compared to smart cement-sand composite and the smart cement paste.
An Investigation of the Kerogen-Mineral Interactions in Green River Oil Shale
(North Dakota State University, 2010) Alstadt, Kristin Nadiene
Green River oil shale contains minerals, kerogen, and bitumen and yields a significant amount of oil upon heating. Kerogen is the insoluble organic remains found in sedimentary materials. It is a precursor to crude oil and is one of the most abundant forms of carbonaceous materials on earth. The richest oil shale deposits in the world are found in the Green River Formation located in the states of Utah, Wyoming and Colorado in the United States with the potential to be a major national resource. Current extraction methods involve heating the shale to high temperatures in order to decompose and evaporate the shale oil. This method is very inefficient due to tremendous energy requirements and is environmentally unfriendly. Thus, the extraction of kerogen is commercially not viable in the United States at this time. My research at North Dakota State University has been focused on understanding how the kerogen is "locked" in the surrounding mineral matrix. The research involves experimental and modeling studies aimed at evaluating the molecular interactions in the oil shale. The focus of my study has been on the in situ chemical composition, mechanical properties, and the physical location of kerogen in Green River oil shale. Fourier Transform Infrared (FTIR) studies have been conducted using the photoacoustic step-scan method to investigate the molecular nature of light and dark colored areas of the oil shale core. This technique provided the means for in situ investigation of kerogenmineral interactions. Results show that light colored oil shale has a high kerogen content with spectra similar to that of isolated kerogen while dark colored oil shale has more mineral components. Kerogen band shifts occurred indicating interactions on the molecular scale between kerogen and the surrounding minerals. Scanning Electron Microscope (SEM) studies were performed in order to obtain information on the size and layout of pores, minerals, and kerogen in the shale. Energy Dispersive Spectroscopy (EDS) performed ort light and dark colored samples indicate that the light colored oil shale contains more kerogen associated with the minerals quartz, clay, and potassium-feldspar. Dark oil shale samples contained kerogen, clay, dolomite, calcite, pyrite, and analcite. SEM images perpendicular to the bedding plane of cross-sectional polished oil shale samples showed orientated layers and elongation consistent with compression over time. The absence of large kerogen regions in SEM images and nanoindentation results suggest that Green River kerogen is on the scale of tens of nanometers and is in close proximity to oil shale minerals. The mechanical properties of kerogen and oil shale minerals were found using nanoindentation techniques. Green River kerogen was found to have an elastic modulus of 9 GPa and hardness of 1 GPa.

Browse

Browsing Civil & Environmental Engineering by browse.metadata.department "Civil, Construction, and Environmental Engineering"