Theses for the College of Engineering & Mines

Recent Submissions

  • Passively encouraging offline networking in small, concentrated communities through UI/UX design

    Mitchell, Addeline; Metzgar, Jonathan; Lawlor, Orion; Chappell, Glenn (2019-05)
    The goal of this project is to identify whether it is possible to encourage users to communicate with one an other face-to-face through User Interface (UI) and User Experience (UX) design. It is well known that users can be maliciously manipulated by design elements and that concerns have been raised about the effects o f social media on interpersonal communication. The key is to find non-harmful means of guiding users to the desired action of speaking face-to-face with others. User testing for a custom web app was conducted for the purposes of this project. It is hoped that the results will provide developers with new consideration for UI and UX design.
  • Implementation of various bed load transport equations at monitoring sites along the Sagavanirktok River

    Laurio, Jenah C.; Toniolo, Horacio; Barnes, Dave; Stuefer, Svetlana (2019-05)
    In May 2015, the Sagavanirktok River in Alaska flooded, spilling over the Dalton Highway and destroying several sections of the road near the community of Deadhorse. The Alaska Department of Transportation and Public Facilities made repairs to the road and funded the University of Alaska Fairbanks, Water and Environmental Research Center (WERC), to conduct a multiyear study of hydro-sedimentological conditions on the Sagavanirktok River. Personnel from the WERC installed four monitoring stations for research purposes. The first monitoring station (DSS1) is located near Deadhorse at Milepost (MP) 405 of the Dalton Highway, the second (DSS2) is located below the Ivishak River (MP 368), the third (DSS3) is located in Happy Valley (MP 335), and the fourth (DSS4) is located at MP 318. Near each monitoring station, large pits were excavated to trap bed sediment as it moves downstream. Researchers involved in the Sagavanirktok River study have been collecting bathymetry measurements from the sediment pits since fall of 2015. The following document discusses a research project that focused on bed load transport along the Sagavanirktok River at monitoring sites DSS1, DSS2, and DSS3. Monitoring site DSS4 was not included in this study due to difficulties retrieving sediment data caused by high water levels. Sediment transport volumes measured from the test pits were compared with volume estimations calculated using Acronym (a computer program), and applying the bed load equations of Meyer-Peter and Muller, Wong and Parker, Ashida and Michue, Fernandez Luque and Van Beek, Engelund and Fredsoe, the Parker fit to Einstein’s relation, Lajeunesse et al., and Wilson, with a critical Shields value ( t #) of 0.06 and 0.03. The study results showed that in all cases the bed load transport volumes measured at sites DSS2 and DSS3 were far smaller than those calculated using the bed load transport equations. For monitoring site DSS1, a few of the bed load transport equations estimated volumes were close to those measured. The Acronym program was used only for sites DSS2 and DSS3 due to difficulties creating the grain size distribution curve at DSS1. Data show that the volumes calculated by Acronym are greater than those measured at both sites. The bed load transport equations used for the project were not applicable to the Sagavanirktok River.
  • Infrared video tracking of UAVs: Guided landing in the absence of GPS signals

    Graves, Logan W.; Hatfield, Michael C.; Lawlor, Orion; Raskovic, Dejan (2019-05)
    Unmanned Aerial Vehicles (UAVs) use Global Positioning System (GPS) signals to determine their position for automated flight. The GPS signals require an unobstructed view of the sky in order to obtain position information. When inside without a clear view of the sky, such as in a building or mine, other methods are necessary to obtain the relative position of the UAV. For obstacle avoidance a LIDAR/SONAR system is sufficient to ensure automated flight, but for precision landing the LIDAR/SONAR system is insufficient for effectively identifying the location of the landing platform and providing flight control inputs to guide the UAV to the landing platform. This project was developed in order to solve this problem by creating a guidance system utilizing an infrared (IR) camera to track an IR LED and blue LEDs mounted on the UAV from a RaspberryPI 3 Model B+. The RaspberryPI, using OpenCV libraries, can effectively track the position of the LED lights mounted on the UAV, determine rotational and lateral corrections based on this tracking, and, using Dronekit-Python libraries, command the UAV to position itself and land on the platform of the Husky UGV (Unmanned Ground Vehicle).
  • The practical application of a hydraulic power recovery turbine at the Valdez Marine Terminal

    Bruns, Brendon; Dandekar, Abhijit; Heimke, David; Wies, Richard (2019-05)
    A hydraulic power recovery turbine (HPRT) is a machine designed to capture energy from the pressure differential of a fluid. The HPRT recovers energy that would otherwise be lost to entropy in flowing fluid processes. When the shaft of the HPRT is coupled to an electric generator, the electricity produced can be employed for practical purposes. At the terminus of the Trans-Alaska Pipeline System (TAPS) in Valdez, favorable hydraulic conditions and electrical infrastructure exists for the application of an HPRT to generate significant power. This project will study the practical application of an HPRT as a source of clean, reliable electricity to the VMT. Installation of an HPRT has the potential to reduce diesel consumption and emissions of air pollutants at the VMT.
  • Analysis of IPR curves in North Slope horizontal producers supported by waterflood and water alternating gas EOR processes

    Abel, Alan; Awoleke, Obadare; Zhang, Yin; Dandekar, Abhijit (2019-05)
    The shape and behavior of IPR curves in waterflooded reservoirs has not previously been defined despite their common use for optimization activities in such systems. This work begins to define the behavior of IPR curves in both water flood and water‐alternating‐gas EOR systems using a fine scale model of the Alpine A‐sand. The behavior of IPRs is extended to 3 additional reservoir systems with differing mobility ratios. Traditionally derived (Vogel, Fetkovich) IPR curves are found to be poor representations of well performance and are shown to lead to non‐optimal gas lift allocations in compression limited production networks. Additionally, the seemingly trivial solution to gas lift optimization in an unconstrained system is shown to be more complex than simply minimizing the bottom hole pressure of the producing well; maximized economic value is achieved at FBHPs greater than zero psi.
  • Closest pair optimization on modern hardware

    Bright, Jason; Chappell, Glenn G.; Lawlor, Orion; Hartman, Chris (2019-05)
    In this project we examine the performance of several algorithms for finding the closest pair of points out of a given set of points in a plane. We look at four algorithms, including brute force, recursive, non-recursive, and a random expected linear time for numbers of points ranging from one hundred to one billion. In our examination, we find that on average the non-recursive is the fastest, except for limited cases of 100 points for the brute force, and 32 bit spaces for the random expected linear.
  • Laboratory investigation of infiltration process of nonnewtonian fluids through porous media in a non-isothermal flow regime for effective remediation of adsorbed contaminants

    Naseer, Fawad; Misra, Debasmita; Metz, Paul; Awoleke, Obadare; Najm, Majdi Abou (2019-12)
    Contamination of soil and groundwater have serious health implications for man and environment. The overall goal of this research is to study a methodology of using nonNewtonian fluids for effective remediation of adsorbed contaminants in porous media under nonisothermal flow regimes. Non-Newtonian fluids (Guar gum and Xanthan gum solutions) provide a high viscous solution at low concentration and these fluids adjust their viscosities with applied shear rate and change in temperature. Adjustment of viscosity with an applied rate of shear is vital for contaminant remediation because non-Newtonian shear thinning fluids can penetrate to low permeability zones in subsurface by decreasing their viscosities due to high shear rates offered by low permeability zones. The application of non-Newtonian shear thinning fluids for contaminant remediation required the improvement in understanding of rheology and how the factors such as concentration, temperature and change in shear rate impacted the rheology of fluids. In order to study the rheology, we studied the changes in rheological characteristics (viscosity and contact angle) of non-Newtonian fluids of different concentrations (i.e., 0.5g/l, 1g/l, 3g/l, 6g/l and 7g/l) at different temperatures ranging from 0 ºC to 30 ºC. OFITE model 900 viscometer and Tantec contact angle meter were used to record the changes in viscosity of fluids for an applied range of shear rate (i.e., 17.02 s⁻¹ to 1021.38 s⁻¹) and contact angles, respectively, for different concentrations of non-Newtonian fluids. Understanding the flow characteristic of non-Newtonian fluids under low temperature conditions could help in developing methods to effectively remediate contaminants from soils. Results of rheological tests manifested an increase in the viscosity of both polymers with concentration and decrease in temperature. Mid (i.e., 3g/l) to high (i.e., 6g/l and 7g/l) concentrations of polymers manifested higher viscosities compared to 0.5g/l for both polymers. Flow of high viscous solutions required more force to pass through a glass-tube-bundle setup which represented a synthetic porous media to study the flow characteristic and effectiveness of Newtonian and non-Newtonian fluids for contaminant remediation. Low concentrations of 0.5g/l were selected for flow and remediation experiments because this concentration can flow through porous media easily without application of force. The 0.5g/l of Xanthan gum and de-ionized water were used to conduct the infiltration experiments to study the flow characteristics of Newtonian and non-Newtonian fluids at 0.6°C, 5°C and 19°C in synthetic porous media. Infiltration depth of both Newtonian and non-Newtonian fluids would decrease with the decrease in temperature because of the change in their properties like dynamic viscosity, density and angle of contact. The result of comparison of Newtonian and non-Newtonian fluids showed water to be more effective in remediating a surrogate adsorbent contaminant (Dichlobenil) from the synthetic porous media at 19°C. This result was counter-intuitive to what we began with as our hypothesis. However, it was also observed later that 0.5 g/l concentration of Guar gum behaved more like a Newtonian fluid and 0.5 g/l concentration of Xanthan gum had not shown strong non-Newtonian behavior compared to higher concentrations of Xanthan gum. Hence more analysis needs to be done to determine what concentration of non-Newtonian fluid should be more effective for remediation.
  • Retrodirective phased array antenna for nanosatellites

    Long, Justin W.; Thorsen, Denise; Kegege, Obadiah; Hawkins, Joseph; Mayer, Charles (2019-12)
    This thesis presents a S-band phased array antenna for CubeSat applications. Existing state-of the-art high gain antenna systems are not well suited to the majority of CubeSats, those that fall within the 1U (10 cm x 10 cm x 10 cm) to 3U (10 cm x 10 cm x 30 cm) size ranges and in Low Earth Orbit (LEO). The system presented in this thesis is designed specifically to meet the needs of those satellites. This system is designed to fit on the 1U face (10 cm x 10 cm) of a CubeSat and requires no deployables. The use of beamforming and retrodirective algorithms reduces the pointing requirements of the antenna, easing the strict requirements that high gain antennas typically force on a CubeSat mission. Additionally, this design minimizes volume and uses low cost Commercial-off-the-Shelf (COTS) parts. This thesis discusses the theoretical background of phased array theory and retrodirective algorithms. Analysis are presented that show the characteristics and advantages of retrodirective phased antenna systems. Preliminary trade studies and design analyses show the feasibility and expected performance of a system utilizing existing COTS parts. The preliminary analysis shows that an antenna system can be achieved with ≥8.5 dBi of gain, 27dB of transmitted signal gain, 20% Power Added Efficiency (PAE) within a 1 W to 2 W power output, and an 80° effective beamwidth. Simulation results show an example antenna array that achieves 8.14 dBi of gain and an 82° effective beamwidth. Testing results on a prototype of the front-end electronics show that with minimal calibration, the beamforming and scanning error can be reduced to 5°. The power consumption and signal gain of the electronics is also verified through testing. The CubeSat Communications Platform, a CubeSat mission funded through the Air Force Research Laboratory is in Phase A design to demonstrate this antenna system, along with other experimental payloads. This thesis includes a discussion of interface control, mission requirements, operations, and a recommended experiment sequence to test and verify the antenna system on orbit.
  • Classification and signal processing of radio backscatter from meteors

    Klemm, Jared; Thorsen, Denise; Bossert, Katrina; Collins, Richard; Mayer, Charlie (2019-12)
    Ground-based radar systems are routinely used to detect the trails of ionized particles that are formed by meteoroids falling through Earth's atmosphere. The most common use for these meteor radar systems is for atmospheric wind studies of the mesosphere and lower thermosphere (80-100 km altitude). Because these meteor trails are embedded in the background winds of the middle atmosphere, atmospheric winds in that region can be measured by observing the radial velocities of the trails. There has also been a considerable amount of research over the last few decades into estimation of neutral atmospheric temperatures using the measured decay time of meteor trails. Several methods exist for estimating atmospheric temperature using meteor radar observations, but there are limitations to these approaches. This thesis focuses on examining aspects of meteor radar signal and data processing, specifically interferometry and echo classification. Interferometry using the measured signal phase differences between antennas allows for the location of meteor trails to be unambiguously determined. Classification schemes are used to identify which echoes can be modeled as underdense meteors, overdense meteors, or other potentially non-meteor echoes. Finally, based on the proposed classification scheme, this thesis examines several temperature estimation methods for both underdense and overdense echoes and discusses the current issues in this area. Preliminary results from a newly installed meteor radar at Poker Flat Research Range are also presented.
  • The role of tundra vegetation in the Arctic water cycle

    Clark, Jason A.; Tape, Ken; Schnabel, William; Euskirchen, Eugénie; Ruess, Roger (2019-12)
    Vegetation plays many roles in Arctic ecosystems, and the role of vegetation in linking the terrestrial system to the atmosphere through evapotranspiration is likely important. Through the acquisition and use of water, vegetation cycles water back to the atmosphere and modifies the local environment. Evapotranspiration is the collective term used to describe the transfer of water from vascular plants (transpiration) and non-vascular plants and surfaces (evaporation) to the atmosphere. Evapotranspiration is known to return large portions of the annual precipitation back to the atmosphere, and it is thus a major component of the terrestrial Arctic hydrologic budget. However, the relative contributions of dominant Arctic vegetation types to total evapotranspiration is unknown. This dissertation addresses the role of vegetation in the tundra water cycle in three chapters: (1) woody shrub stem water content and storage, (2) woody shrub transpiration, and (3) partitioning ecosystem evapotranspiration into major vegetation components. In Chapter 1 I present a method to continuously monitor Arctic shrub water content. The water content of three species (Salix alaxensis, Salix pulchra, Betula nana) was measured over two years to quantify seasonal patterns of stem water content. I found that spring uptake of snowmelt water and stem water storage was minimal relative to the precipitation and evapotranspiration water fluxes. In Chapter 2, I focused on water fluxes by measuring shrub transpiration at two contrasting sites in the arctic tundra of northern Alaska to provide a fundamental understanding of water and energy fluxes. The two sites contrasted moist acidic shrub tundra with a riparian tall shrub community having greater shrub density and biomass. The much greater total shrub transpiration at the riparian site reflected the 12-fold difference in leaf area between the sites. I developed a statistical model using vapor pressure deficit, net radiation, and leaf area, which explained >80% of the variation in hourly shrub transpiration. Transpiration was approximately 10% of summer evapotranspiration in the tundra shrub community and a possible majority of summer evapotranspiration in the riparian shrub community. At the tundra shrub site, the other plant species in that watershed apparently accounted for a much larger proportion of evapotranspiration than the measured shrubs. In Chapter 3, I therefore measured partitioned evapotranspiration from dominant vegetation types in a small Arctic watershed. I used weighing micro-lysimeters to isolate evapotranspiration contributions from moss, sedge tussocks, and mixed vascular plant assemblages. I found that mosses and sedge tussocks are the major constituents of overall evapotranspiration, with the mixed vascular plants making up a minor component. The potential shrub transpiration contribution to overall evapotranspiration covers a huge range and depends on leaf area. Predicted increases in shrub abundance and biomass due to climate change are likely to alter components of the Arctic hydrologic budget. The thermal and hydraulic properties of the moss and organic layer regulate energy fluxes, permafrost stability, and future hydrologic function in the Arctic tundra. Shifts in the composition and cover of mosses and vascular plants will not only alter tundra evapotranspiration dynamics, but will also affect the significant role that mosses, their thick organic layers, and vascular plants play in the thermodynamics of Arctic soils and in the resilience of permafrost.
  • A novel virtual reality-based system for remote environmental monitoring and control using an activity modulated wireless sensor network

    Montz, Benjamin; Raskovic, Dejan; Mayer, Charles E.; Thorsen, Denise (2019-08)
    The ability to monitor and control a home environment remotely has improved considerably in recent years due to improvements in the computational power, reduction in physical size, reduced implementation cost, and widespread use of both wireless sensor networks and smart home systems. This thesis presents a remote environment management system that integrated a custom wireless sensor network that monitored environmental factors in multiple locations, a smart system that controlled those factors, and a virtual reality system that functioned as a remote interface with the environment. The resulting system enabled a user to efficiently interact with a distant environment using an immersive virtual reality experience. The user was able to interact with the remote environments by issuing voice commands, performing hand gestures, and interacting with virtual objects. This type of system has applications in many fields ranging from healthcare to the industrial sector. The case study system that was designed in this thesis monitored and controlled the environments of several rooms in a home. A novel approach to modulating the activity of the wireless sensor network was implemented in this system. The rate at which the sensor nodes collected and transmitted data was modulated based on the visibility of the virtual objects called VSNs. These virtual sensor nodes displayed the sensor node measurements in virtual reality. This method was expanded upon using a motion prediction algorithm that was used to predict if the virtual sensor nodes were going to be visible to the user. This prediction was then used to modulate the activity of the wireless sensor network. These activity modulation algorithms were used to reduce the power consumption of the wireless sensor network and thus increasing its operational lifespan, while simultaneously reducing unnecessary RF signals in the environment that can interfere with the operation of other wireless systems. These algorithms would be crucial for systems monitoring complex sensor-rich environments where reducing the data transmitted and extending the system's lifespan was paramount, such as managing the environments of many rooms in a large industrial park or controlling the environments of spacecraft from Mission Control on Earth.
  • Alaska Arctic coastal plain gravel pad hydrology: impacts to dismantlement removal and restoration operations ; a study on the human - hydrology relationship in Arctic environments

    Miller, Ori; Barnes, David L.; Stuefer, Svetlana L.; Shur, Yuri (2019-08)
    To guard against thawing permafrost and associated thaw subsidence, the oil facilities in the Arctic are constructed on gravel pads placed on top of the existing arctic tundra, however the impacts of this infrastructure to the sensitive hydrology are not fully understood. Production in some of the older fields is on the decline; however oil exploration in the Arctic Coastal Plain is resulting in the discovery and development of new reserves. In the coming years, old sites will need to be decommissioned as production transitions to new sites. New facilities will also need to be designed and constructed. Oil companies in Alaska have historically conducted operations under leases issued through the Alaska Department of Natural Resources. The leases stipulate that once resource extraction operations are completed, the facilities must be decommissioned and the sites restored, however they are often vague in their requirements and are variable in their specifics from lease to lease. As the oil companies transition to the new sites, decisions must be made regarding what should be done with vacated gravel pads. The construction of gravel pads essentially destroys underlying arctic tundra. In undisturbed areas in the Arctic, the tundra itself creates an insulating layer that limits the seasonal thaw depth to around 0.5 m. Removal of this layer causes thaw depths to greatly increase impacting the stability of the ground and the hydrology of the surrounding area. Because of this impact, other possible restoration techniques are being considered, such as vegetating and leaving the pads in place. Water movement is one of the major driving factors in the arctic contributing to permafrost degradation. Groundwater carries with it heat, which is transferred to the soil as the groundwater moves. Therefore, hydrology plays a major role in the stability of the arctic environment. This is especially relevant in areas where gravel pads exist. Gravel pads are anthropogenic structures that have significant water storage potential. Because of the unique conditions in the Arctic, pore-water flow through these gravel pads is not yet well understood. The purpose of this study is to develop a more complete scientific understanding of the driving forces behind pad pore-water movement. This study expands on fieldwork from a prior hydrological field study conducted by others. The prior study is expanded through this work by developing an associated groundwater model to the gravel pad from the field study to examine the flow through it and the controlling factors for this flow. The study site used for this project is located in Prudhoe Bay and is the pad constructed for the very first production well in Prudhoe Bay in 1968. This study demonstrates that it is the topography of the silt layer beneath the gravel pads that is the most significant factor controlling pad pore-water movement. The results from the modeling study will assist engineers and environmental scientists in better understanding the groundwater flow. This understanding will aid in the decommissioning and restoration process and help inform decision making in regards to the future of the existing pads. The results may also be used to inform the development of new infrastructure such that any new pads which are built may be constructed with their relationship to the local hydrology more in mind.
  • Probabilistic decline curve analysis in unconventional reservoirs using Bayesian and approximate Bayesian inference

    Korde, Anand A.; Awoleke, Obadare; Goddard, Scott; Dandekar, Abhijit (2019-08)
    In this work, a probabilistic methodology for Decline Curve Analysis (DCA) in unconventional reservoirs is presented using a combination of Bayesian statistical methods and deterministic models. Accurate reserve estimation and uncertainty quantification are the primary objectives of this study. The Bayesian inferencing techniques described in this work utilizes three sampling mechanisms, namely the Gibbs Sampling (implemented in OpenBUGS), the Metropolis Algorithm, and Approximate Bayesian Computation (ABC) to sample parameter values from their posterior distributions. These different sampling mechanisms are applied in conjunction with DCA models like Arps, Power Law Exponential (PLE), Stretched Exponential Production Decline (SEPD), Duong and Logistic Growth Analysis (LGA) to estimate prediction intervals. Production is forecasted, and uncertainty bounds are established using these prediction intervals. A complete workflow and the summary steps for each of the sampling techniques are provided to permit readers to replicate results. To examine the reliability, the methodology was tested over 74 oil and gas wells located in the three main sub plays of the Permian Basin, namely, the Delaware play, the Central Basin Platform, and the Midland play. Results show that the examined DCA-Bayesian models are successful in providing a high coverage rate, low production prediction errors and narrow uncertainty bounds for the production history data sets. The methodology was also successfully applied to unconventional reservoirs with as low as 6 months of available production history. Depending on the amount of production history available, the combined deterministic-stochastic model that provides the best fit can vary. It is therefore recommended that all possible combinations of the deterministic and stochastic models be applied to the available production history data. This is in order to obtain more confidence in the conclusions related to the reserve estimates and uncertainty bounds. The novelty of this methodology relies in using multiple combinations of DCA-Bayesian models to achieve accurate reserve estimates and narrow uncertainty bounds. The paper can help assess shale plays as most of the shale plays are in the early stages of production when the reserve estimations are carried out.
  • Testing and analysis of a ground source heat pump in Interior Alaska

    Garber-Slaght, Robbin; Das, Debendra K.; Marsik, Tomas; Lin, Chuen-Sen (2019-08)
    Ground source heat pumps (GSHPs) can be an efficient heating and cooling system in much of the world. However, their ability to work in extreme cold climates is not well studied. In a heating-dominated cold climate, the heat extracted from the soil is not actively replaced in the summer because there is very little space cooling. A ground source heat pump was installed at the Cold Climate Housing Research Center (CCHRC) in Fairbanks, Alaska with the intent to collect data on its performance and effects on the soil for at least ten years. Analysis shows GSHPs are viable in the Fairbanks climate; however, their performance may degrade over time. According to two previous finite element models, the CCHRC heat pump seems to reach equilibrium in the soil at a COP of about 2.5 in five to seven years. Data from the first four heating seasons of the ground source heat pump at CCHRC is evaluated. The efficiency of the heat pump degraded from an average coefficient of performance (COP) of 3.7 to a mediocre 2.8 over the first four heating seasons. Nanofluids are potential heat transfer fluids that could be used to enhance the heat transfer in the ground heat exchanger. Improved heat transfer could lower installation costs by making the ground heat exchanger smaller. A theoretical analysis of adding nanoparticles to the fluid in the ground heat exchanger is conducted. Two nanofluids are evaluated to verify improved heat transfer and potential performance of the heat pump system. Data from the CCHRC heat pump system has also been used to analyze a 2-dimensional finite element model of the system's interaction with the soil. A model based on the first four years of data is developed using Temp/W software evaluates the ground heat exchanger for a thirty-year period. This model finds that the ground heat exchanger does not lower the ground temperature in the long term.
  • Establishing and testing detection methods for anti-icing and deicing chemicals using spectral data

    Fulton, Gabriel; Belz, Nathan; Meyer, Franz; Stuefer, Svetlana (2019-08)
    Snow and ice accumulation on pavement reduce roadway surface friction and consequently result in diminished vehicle maneuverability, slower travel speeds, reduced roadway capacity, and increased crash risk. Though the use of chlorides and other freeze-inhibiting substances have been shown to reduce these negative factors, methods to quantify and analyze snow and ice remediation methods as well as the imposed loss of material are needed to allow state and municipal agencies to better allocate winter maintenance resources and funding. The use and application of chlorides, sand, and their related mixtures have proven to be highly effective for controlling or removing the development of ice on the roadway surface. However, if the amount of salt in solution becomes too dilute, then it no longer retains the capacity to control the development of, or to melt, ice on the roadway and may prove to be more detrimental by allowing the previously melted material to refreeze with a smoother (i.e., more slippery) surface state. The goal of this project was to determine to what extent winter roadway surfaces can be analyzed using spectrometry to determine the longevity and coverage of various types of applications. Using a systematically paired analysis of changes in spectrometric curves as solution concentrations change, relationships were generated which detected change in deicing and anti-icing compounds reliably in a lab setting. Field results were less reliable, suggesting that further comparisons and a more in-depth spectral library are needed.
  • Snowmelt hydrology in the upper Kuparuk watershed, Alaska: observations and modeling

    Dean, Kelsey M.; Stuefer, Svetlana; Verbyla, David; Schnabel, William (2019-08)
    The Fourth National Climate Assessment Report (2018) indicates that Alaska has been warming at a rate two times greater than the global average with the Arctic continuing to be experiencing higher rates of warming. Snowmelt driven runoff is the largest hydrologic event of the year in many Alaska Arctic river systems. Changes to air temperature, permafrost, and snow cover impact the timing and magnitude of snowmelt runoff. This thesis examines the variability in hydrometeorological variables associated with snowmelt to better understand the timing and magnitude of snowmelt runoff in headwater streams of Arctic Alaska. The objectives of this thesis are to: (1) use observational data to evaluate trends in air temperature, precipitation, snow accumulation, and snowmelt runoff data; (2) relate precipitation, snow cover, and air temperature to snowmelt runoff using the physically-based Snowmelt Runoff Model (SRM) to test the applicability of the model for headwater streams in the Arctic. The focus of this study is the Upper Kuparuk watershed area, located in Alaska on the north side of the Brooks Range, where several monitoring programs have operated long enough to generate a 20-year climate record, 1993-2017. Long-term air temperature, precipitation, and streamflow data collected by the University of Alaska Fairbanks at the Water and Environmental Research Center and other agencies were used for statistical analysis and modeling. While no statistically significant trends in snow accumulation and snowmelt runoff were identified during 1993-2017, observations highlight large year-to-year variability and include extreme years. Snow water equivalent ranges from 5.4 to 17.6 cm (average 11.0 cm), peak snowmelt runoff ranges from 3.84 to 50.0 cms (average 22.4 cms), and snowmelt peak occurrence date ranges from May 13 to June 5 for the Upper Kuparuk period of record. The spring of 2015 stands out as the warmest, snowiest year on record in the Upper Kuparuk. To further investigate the runoff response to snowmelt in 2015, remote sensing snow data was analyzed and recommended parameters were developed for SRM use in the Upper Kuparuk watershed. Recommended parameters were then applied to 2013 snowmelt runoff as a test year. Model results varied between the two years and provide good first-order approximation of snowmelt runoff for headwater rivers in the Alaska Arctic.
  • Enhancement of algorithm for detection of gold strip circuit vessel sensor errors

    de Melo, Eduardo Pimenta; Ganguli, Rajive; Ghosh, Tathagata; Arya, Sampurna (2019-08)
    Sensors are used to understand the condition and flow of mineral processes. Having accurate and precise information is fundamental for proper operation. Even small errors are relevant to cost when considering the operational span of a mine. Finding small errors is hard; few algorithms can detect them and fewer still, when considering errors on the scale of 2% in magnitude. Some tools have recently been developed using data mining techniques for detecting small errors. Rambabu Pothina (2017) created an algorithm for detecting small errors in strip vessel temperature sensors in the carbon stripping circuit in Pogo mine. The algorithm performed well and was able to detect small magnitude errors without disrupting the industrial process. This thesis improves the understanding of the performance of the algorithm, while also making some minor changes. First, a statistical analysis of the results of the algorithm on baseline data revealed an inherent difference in how the carbon strip process was run with respect to the two strip vessels. This discovery provided insight into the algorithm, and how its performance depended on process characteristics. Second, the error detection algorithm was tested under scenarios different from Pothina (2017). Three separate types of errors were artificially added to real data: a) a fixed 2% ("fixed" error increase) b) a fixed 2% decrease ("fixed" error decrease) and c) an error with a mean value of 2% of magnitude ("noisy" error). Additionally, error was added to temperature data from each strip vessel (rather than just one), though only one at a time. The algorithm was tested under each scenario for each of the four years, 2015, 2016, 2017 and 2018. The time to detect errors ranged from 19 to 73 days. The time to detect was very high (53 to 73 days) in 2017 since there were large data gaps that year. In general, time to detect was about 30 days. The performance under noisy error were not that far below fixed error scenario. The algorithm took 10% more time to detect errors under noisy error scenario compared to fixed error scenario. On average, the algorithm detected an error after 25 cycles, regardless of the time span this represents. This is consistent in years with plentiful data, such as 2015, as well as years with less data, 2017 and 2018. In years with data gaps, 25 cycles represent a longer time period. Seeded errors that decreased vessel temperature have very similar results to its equivalent increase, i.e. the decrease in 2% of S2 has results similar to the increase of 2% in S1 and vice versa. In conclusion, these additional testing and analysis helped develop a more comprehensive understanding of the behavior of the data and the algorithms. These results validate and strengthen the findings of Pothina (2017).
  • Intelligent traffic monitoring and control system

    Ch, Nabil Al Nahin; Raskovic, Dejan; Thorsen, Denise; Hatfield, Michael (2019-08)
    This thesis presents an intelligent system for monitoring and controlling traffic by sensing vehicles' attributes and using communication between vehicles and roadside infrastructures. The goal of this system is to improve the safety of the commuters and help the drivers in making better decisions by providing them with additional information about the traffic conditions. A prototype system consisting of a roadside unit (RSU) and an on-board unit (OBU) was developed to test the functionalities of the proposed system. The RSU consists of sensors for detecting vehicles and estimating their attributes and a radio for communicating with the OBU. The OBU also has a radio for communication purpose. Afterward, a vehicle was used to test the functionalities of the system and the communication between OBU and RSU was evaluated by emulating the presence of a vehicle. A protocol for exchanging messages between the RSU and the OBU was developed to support effective communication. The efficiency of the communication process was further improved by varying the transmission range of different messages. A format for the message was proposed to convey all the necessary information efficiently. The process of collecting vehicle data, processing them and extracting useful information from the data was discussed here along with some limitations of the proposed system.
  • Using rate transient analysis and bayesian algorithms for reservoir characterization in hydraulically fractured horizontal gas wells during linear flow

    Yuhun, Pirayu; Awoleke, Obadare; Ahmadi, Mohabbat; Hanks, Catherine (2019-05)
    Multi-stage hydraulically fractured horizontal wells (MFHWs) are currently a popular method of developing shale gas and oil reservoirs. The performance of MFHWs can be analyzed by an approach called Rate transient analysis (RTA). However, the predicted outcomes are often inaccurate and provide non-unique results. Therefore, the main objective of this thesis is to couple Bayesian Algorithms with a current production analysis method, that is, rate transient analysis, to generate probabilistic credible interval ranges for key reservoir and completion variables. To show the legitimacy of the RTA-Bayesian method, synthetic production data from a multistage hydraulically fractured horizontal completion in a reservoir modeled after Marcellus shale reservoir was generated using a reservoir (CMG) model. The synthetic production data was analyzed using a combination of rate transient analysis with Bayesian techniques. Firstly, the traditional log-log plot was produced to identify the linear flow production regime, which is usually the dominant regime in shale reservoirs. Using the linear flow production data and traditional rate transient analysis equations, Bayesian inversion was carried out using likelihood-based and likelihood-free Bayesian methods. The rjags and EasyABC packages in statistical software R were used for the likelihood-based and likelihood-free inversion respectively. Model priors were based (1) on information available about the Marcellus shale from technical literature and (2) hydraulic fracture design parameters. Posterior distributions and prediction intervals were developed for the fracture length, matrix permeability, and skin factor. These predicted credible intervals were then compared with actual synthetic reservoir and hydraulic fracture data. The methodology was also repeated for an actual case in the Barnett shale for a validation. The most substantial finding was that for all the investigated cases, including complicated scenarios (such as finite fracture conductivity, fracturing fluid flowback, heterogeneity of fracture length, and pressure-dependent reservoir), the combined RTA-Bayesian model provided a reasonable prediction interval that encompassed the actual/observed values of the reservoir/hydraulic fracture variables. The R-squared value of predicted values over true values was more than 0.5 in all cases. For the base case in this study, the choice of the prior distribution did not affect the posterior distribution/prediction interval in a significant manner in as much as the prior distribution was partially informative. However, the use of noninformative priors resulted in a loss of precision. Also, a comparison of the Approximate Bayesian Computation (ABC) and the traditional Bayesian algorithms showed that the ABC algorithm reduced computational time with minimal loss of accuracy by at least an order of magnitude by bypassing the complicated step of having to compute the likelihood function. In addition, the production time, number of iterations and tolerance of fitting had a minimal impact on the posterior distribution after an optimum point--which was at least one-year production, 10,000 iterations and 0.001 respectively. In summary, the RTA-Bayesian production analysis method implemented in relatively easy computational platforms, like R and Excel, provided good characterization of all key variables such as matrix permeability, fracture length and skin when compared to results obtained from analytical methods. This probabilistic characterization has the potential to enable better understanding of well performance, improved identification of optimization opportunities and ultimately improved ultimate recovery from shale gas resources.
  • Pre-stress loss due to creep in precast concrete decked bulb-tee girders under cold climate conditions

    Vandermeer, Drew E.; Ahn, Il-Sang; Liu, Juanyu (2019-05)
    This report presents guidelines for estimating pre-stress loss in high-strength precast pretensioned concrete Decked Bulb-Tee (DBT) bridge girders in cold climate regions. The guidelines incorporate procedures yielding more accurate predictions of shrinkage and concrete creep than current 2017 American Association of State Highway and Transportation Officials (AASHTO) specifications. The results of this report will be of particular interest to researchers and cold climate bridge design engineers in improved predictions of design life and durability. The use of high-strength concrete in pre-tensioned bridge girders has increased in popularity among many state highway agencies. This fact is due to its many beneficial economic and constructability aspects. The overall cost of longer girders with increased girder spacing in a bridge that is precast with high strength concrete can be significantly reduced through the proper estimating factors. Recent research indicates that the current provisions used for calculating prestress losses in cold regions for high-strength concrete bridge girders may not provide reliable estimates. Therefore, additional research is needed to evaluate the applicability of the current provisions for estimating pre-stress losses in high-strength concrete DBT girders. Accurate estimations of pre-stress losses in design of pre-tensioned concrete girders are affected by factors such as mix design, curing, concrete strength, and service exposure conditions. The development of improved guidelines for better estimating these losses assists bridge design engineers for such girders and provide a sense of security in terms of safety and longevity. The research includes field measurements of an environmentally exposed apparatus set up to measure shrinkage, creep and strain in cylinders loaded under constant pressure for a full calendar year.

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