Recent Submissions

  • Compartmentalization and grain-fabric alignments in mixed carbonate-siliciclastics mass-transport deposits: the Cutoff formation, Permian Basin, Texas

    Wood, Lesli J.; Jobe, Zane R.; Simabrata, Hanaga; Trudgill, Bruce, 1964-; Sarg, J. F. (J. Frederick); Cardona, Sebastian; Hurd, Gregory (Colorado School of Mines. Arthur Lakes Library, 2022)
    Mass-transport deposits (MTDs) comprise complex, multi-scale deformation that renders them unique compared to sediments of other depositional origins. The topics of this research entail compartmentalization (outcrops) and grain-fabric modifications (thin sections) in MTDs developed during the emplacement processes, which can significantly impact formation heterogeneity and anisotropy. Our research emphasizes on (1) the recognition criteria of sub-seismic MTD compartments and (2) qualitative and quantitative characterizations of grain-fabric alignments, both of which utilize the well-exposed Cutoff MTDs in the Permian Basin, Texas. Our study shows that sub-seismic compartments in MTDs can be predicted from the intersegment contrasts of lithofacies, deformation types, and deformation orientations. Using these recognition criteria in conjunction increases the likelihood of identifying MTD compartments. Thin section analysis over 29.000 elongated grains (predominantly sponge spicules) reveals that grain-fabric alignments in MTDs are heterogeneous in multiple scales, and are likely controlled by grain lengths (with constant aspect ratio) and matrix types. The results of this study contribute in the following fields: (1) identification of sub-seismic MTD compartments, which can serve as barriers or conduit to fluid flow, (2) anisotropy prediction of petrophysical (e.g., permeability) and mechanical (elastic moduli) properties, (3) the kinematic of MTD evolution during emplacement, including the origins of MTD compartments and the prediction of paleotransport directions.
  • Effect of casting conditions and clogging on fluid flow in metal delivery system and thermo-mechanical behavior of solidifying shell in continuous casting of steel

    Thomas, Brian G.; Olia, Hamed; De Moor, Emmanuel; Asle Zaeem, Mohsen; Berger, John R. (Colorado School of Mines. Arthur Lakes Library, 2022)
    In continuous casting of steel, it is very important to quantify the pressure distribution and flow rate in the metal delivery system, which starts from the tundish, then into the Upper Tundish Nozzel (UTN), Submerged Entry Nozzle (SEN), and finally to the mold. It is, also, crucial to understand the effect of turbulent flow on thermo-mechanical characteristics of the solidifying shell inside the mold, since both can directly affect the quality of the final product. To that end, two MATLAB-based state-of-the-art one-dimensional pressure energy models are developed and applied in this work to calculate pressure distribution and flow rate in slide-gate, PFSG, and stopper-rod nozzle systems, PFSR, for argon-molten steel flow systems by solving a 1D system of Bernoulli equations which can be used in commercial steel casters and water models. Both models are validated and verified with experimental plant measurements and computational fluid dynamics simulations with errors of less than 8 pct. Additionally, PFSG is used to investigate the effect of different casting conditions on the flow rate and pressure distribution. It is shown that increasing some casting conditions such as tundish height and nozzle bore diameter can decrease minimum pressure in the system, which in turn increases the possibility of air aspiration. As for the PFSR, it is concluded that two more phenomena, cavitation and non-primed flow, are needed to capture the real physics existing in the plant. Finally, a transient thermo-mechanical model is developed to understand the strength of the turbulent flow on the solidifying shell inside the mold in continuous casting of steel using ABAQUS. The model is able to account for the superheat flux, which is the heat transfer across the interface near the solidification front between the turbulent flowing liquid and the solidifying steel shell. The predictions of the model include temperature distribution, shell growth, stress, and strain (including elastic, inelastic, thermal, and fluid components) distribution for temperature-varying thermo-mechanical and composition-based properties. It is, then, verified with existing models, CON1D and analytical solutions, and validated with experiments. Ultimately, a case study is conducted to investigate the effect of the turbulent flow caused by the asymmetric clogging inside one of the ports on the thermo-mechanical behavior of the solidifying shell inside the mold. It is shown that the effect of mold heat flux is far more important than the superheat flux.
  • Explaining soil biogeochemical responses after fire

    Spear, John R.; Honeyman, Alexander Schroeder; Ranville, James F.; Rhoades, Charles; Navarre-Sitchler, Alexis K.; Munakata Marr, Junko; Kleiber, William (Colorado School of Mines. Arthur Lakes Library, 2022)
    Wildfires are a perennial event globally and the biogeochemical underpinnings of soil responses at relevant spatial and temporal scales are unclear. Soil biogeochemical processes regulate plant growth and nutrient losses that affect water quality, yet the response of soil after variable intensity fire is difficult to explain and predict. To address this issue, we investigated fire-impacted soil through two independent lenses. First, we examined two wildfires in Colorado, USA across the first and second post-fire years and leveraged Statistical Learning (SL) to predict and explain biogeochemical responses. We found that SL predicts biogeochemical responses in soil after wildfire with surprising accuracy. Of the 13 biogeochemical analytes analyzed in this study, 9 are best explained with a hybrid microbiome + biogeochemical SL model. Biogeochemical-only models best explain 3 features, and 1 feature is explained equally well with hybrid or biogeochemical-only models. In some cases, microbiome-only SL models are also effective (such as predicting NH4+). Whenever a microbiome component is employed, selected features always involve uncommon soil microbiota (i.e., the 'rare biosphere', existing at < 1% relative abundance). Second, an excavated soil cube was burned in the laboratory with a butane torch (~ 1300 °C). Using optical chemical sensing with planar ‘optodes’, pH and dissolved O2 concentration were tracked spatially (depth and width) with a resolution of 360 µm per pixel for 72 hours. We show that imaging data from planar optodes can be correlated with microbial activity as quantified via high-throughput sequencing of RNA transcripts. Of the 28 carbon, nitrogen, and sulfur metabolism pathways (sets of genes) or individual genes investigated in this study, only two correlated significantly with soil depth postfire (which covaries with postfire soil temperature). In contrast, postfire pH negatively correlated with four of the 28 pathways or genes, and dissolved O2 negatively correlated with 10 of 28. Results demonstrate that postfire soils are spatially complex on a mm scale and that using optode-based chemical imaging as a chemical navigator for transcript sampling is effective.
  • Identification of advanced die coatings, their failure mechanisms, and progress towards lube-free aluminum high pressure die casting

    Kaufman, Michael J.; Midson, Stephen; Delfino de Campos Neto, Nelson; Clarke, Kester; Bourne, Gerald; Squier, Jeff A.; Korenyi-Both, Andras L. (Colorado School of Mines. Arthur Lakes Library, 2022)
    In this work, the effects of Al/(Al+Cr) ratio, nanolayering with TiCN, surface roughness of the coated H13 steel, and coating defect population were evaluated for five different AlCrN-based PVD coatings (Chapter 2). In addition, the failure mechanisms of core pins coated with Si-DLC by plasma-assisted chemical vapor deposition, or with AlCrN/TiCN or Al2O3 by PVD and positioned directly in front of the gate of a die used to produce large automotive die castings were investigated (Chapter 3). Regardless of coating type, five failure mechanisms were observed including mechanical erosion, chemical soldering, gross chemical soldering, build-up on coating, and thermal spalling, although the extent of each mechanism did vary with coating type. Selection maps were created by combining the wear resistance and the fraction of the core pin surfaces experiencing soldering and used to determine the best coatings for avoiding chemical and mechanical degradation leading to soldering. Successful lube-free aluminum HPDC can be achieved (Chapter 4) using two simple dies that were coated with an AlCrN PVD coating but contained no core pins or other features that were non-perpendicular to the ejection direction. It was possible to run both of these dies in the lube-free condition and produce over 200 lube-free castings. It was observed that aluminum build-up on the die surface was an intermittent phenomenon as it did not lead to chemical soldering. There was no chemical reaction or intermetallic formation in the interface regions between the aluminum and the H13 steel, or between the aluminum and the AlCrN coating. A mechanistic lube-free model was developed to understand the correlation between surface roughness, wetting angle and pressure and explain why lube-free aluminum HPDC was possible for these simple geometries and why it becomes challenging for more complex geometries.
  • Hydrothermal technologies for destruction of per- and polyfluoroalkyl substances (PFASS) in aqueous film-forming foam (AFFF) and AFFF-impacted wastes

    Strathmann, Timothy J.; Higgins, Christopher P.; HAO, SHILAI; Sharp, Jonathan O.; Bellona, Christopher; Vyas, Shubham (Colorado School of Mines. Arthur Lakes Library, 2022)
    Per- and polyfluoroalkyl substances (PFASs) are a family of chemicals with at least one perfluoroalkyl moiety (CnF2n+1-) used in a variety of industries and consumer products since the 1940s. The ubiquity of PFASs in the environment, wildlife, and humans has raised significant concerns and calls for action globally. One of the major sources of PFAS contamination is the use of aqueous film-forming foam (AFFF), water-based mixtures of fluorinated and hydrocarbon surfactants that are applied to rapidly extinguish hydrocarbon and solvent-based fires. Groundwater and soil at many sites in the U.S. have been reported to be impacted by the historic use of AFFF. Current treatment technologies mostly focus on separation (e.g., activated carbon, membrane separation), and there remain few options for achieving destruction and defluorination of the full range of PFASs in AFFF-impacted matrices (e.g., groundwater and soil). Thus, there remains a critical need to develop a rapid, effective, and robust treatment method for the destruction of PFASs. This thesis advanced the understanding and application of hydrothermal alkaline treatment (HALT) technologies for the destruction of PFASs in contaminated environmental and concentrate matrices, and key findings provide guidance on the integration of HALT within treatment trains that will be applied for real-world site remediation. Initially, I evaluated the effectiveness of HALT for destruction and defluorination of PFASs identified in AFFFs produced by suppliers via electrochemical fluorination- (ECF) and fluorotelomerization (FT) processes. Quantitative and semi-quantitative high-resolution mass spectrometry was used to track a wide range of PFAS structures during treatment with HALT. Results demonstrated rapid degradation of all 109 PFASs identified in two AFFFs when the solutions were amended with alkali (e.g., 1-5 M NaOH) at near-critical temperatures and pressures (350 °C, 16.5 MPa). This includes perfluoroalkyl acids (PFAAs) and a range of polyfluoroalkyl precursors. Most PFASs were degraded to non-detectable levels within 15 min. Perfluoroalkyl sulfonates (PFSAs) were the most recalcitrant class of PFASs, but these were degraded to non-detectable levels within 30 min when treated with 5 M NaOH. 19F-NMR spectroscopic analysis and fluoride ion analysis confirmed that destruction was accompanied by near-complete defluorination of PFASs in both dilute and concentrated AFFF mixtures (total fluorine up to 0.36 M), and no stable volatile organofluorine species were detected in reactor headspace gases analyzed by gas chromatography with mass spectrometry (GC-MS) detection. The application of the HALT was then extended to AFFF-impacted groundwater and soil matrices. Results showed that 148 PFASs identified in the collected field samples (2 groundwater samples, 3 soils), including 10 cationic, 98 anionic, and 40 zwitterionic PFASs, were mostly degraded to non-detectable levels within 90 min when treated with 5 M NaOH at 350 °C. The near-complete defluorination, as evidenced by fluoride release measurements, confirmed the complete destruction of PFASs. Rates of PFSA destruction in groundwater samples were similar to those measured in laboratory water solutions, but reactions in soil were slowed, attributed to base-neutralizing properties of the soil (e.g., reaction with silicate minerals). Further, the degradation of PFASs in groundwaters and soils was found to be a function of reaction temperature, NaOH concentration, and reaction times. The dissolution of soil minerals during HALT presents a challenge to direct soil treatment applications and suggests the need for future research to optimize PFAS destruction while minimizing soil matrix reactions. To reduce the overall energy requirements for treatment and destruction of PFASs, I then examined application of HALT for treatment of PFAS concentrates produced by foam fractionation (FF) processes being developed for groundwater remediation. Results showed that all 62 PFASs identified in two FF-derived concentrates were degraded by >90% within 90 min when treated with 1 M NaOH at 350 °C; concentrations were reduced below the detection limit when treated with 5 M NaOH for the same reaction time. The foam concentrate matrix, including elevated dissolved organic carbon (DOC; up to 4.5 g/L) did not significantly affect reaction kinetics for the most recalcitrant PFSAs. Efforts were included to characterize and track organic constituents during treatment, with results showing partial reduction of bulk DOC, but complete degradation of 43 hydrocarbon surfactants identified in an ECF-derived AFFF concentrate. An initial analysis of energy requirements for an integrated process coupling FF with HALT was estimated to be ~0.7 kWh/m3 groundwater, with the HALT step being a negligible contributor to the overall treatment process due to the small volume of concentrate requiring treatment. Studies were also conducted using ultra-short chain perfluoroalkyl acids (PFAAs) to better understand the mechanisms responsible for PFAA destruction and defluorination during HALT. Reactions were conducted with trifluoroacetic acetate (TFA) and trifluoromethanesulfonate (TFMS; triflate). Results confirmed the destruction and defluorination through HRMS, nuclear magnetic resonance (NMR), and fluoride ion measurement. TFMS showed much lower reactivity (~95 fold lower) than TFA, consistent with measurements of longer chain analogues. The carbon atoms of TFA and TFMS were converted to a mixture of formate and dissolved carbonate species, and the sulfonate group of TFMS was converted stoichiometrically to sulfate. Experiments also show TFMS defluorination could be mediated by the addition of alternative nucleophiles (iodide, bisulfide) in place of hydroxide. Results support a proposed stepwise nucleophilic substitution mechanism that destabilizes the alkyl chain within PFASs, leading to complete defluorination and partial carbon mineralization. Overall, this thesis demonstrated that HALT is a rapid, effective, and robust treatment method for the destruction of the full range of PFASs identified in water-containing environmental matrices and concentrates. A proposed nucleophile substitution mechanism produces inorganic fluoride ion as the sole product with no evidence for formation of undesirable volatile fluorinated products that can be produced by other thermal treatment processes, including incineration. Therefore, results support a conclusion that HALT has significant potential for addressing remediation and industrial treatment needs at a growing number of sites.
  • Fractional integrable nonlinear systems

    Carr, Lincoln D.; Ablowitz, Mark J.; Been, Joel B.; Martin, P. A.; Flournoy, Alex (Colorado School of Mines. Arthur Lakes Library, 2022)
    Nonlinear equations and fractional calculus have become important mathematical descriptions of physical applications. We provide context for the intersection of these two mathematical theories with our discovery of integrable, i.e., exactly solvable, fractional nonlinear evolution equations. Using a general method which can be applied to any integrable system with sufficient structure, we derive the first known fractional integrable equations with nonlocal fractional operators, the fractional Korteweg-deVries and fractional nonlinear Schr\"odinger equations. For these equations, we find the general solution for decaying initial data in terms of a set of linear integral equations. Like other integrable equations, these fractional integrable equations have solitonic solutions, an infinite number of conservation laws, and elastic soliton-soliton interactions. The soliton solutions to these equations have velocities related to their amplitudes by a power law, a simple physical prediction common to these fractional integrable equations known as anomalous dispersion. The method of finding these fractional integrable equations involves three key mathematical ingredients: power law dispersion, completeness of squared eigenfunctions, and the inverse scattering transform. All of these elements together allow us to define the nonlinear fractional operators underlying these fractional integrable equations through spectral theory, just as Fourier transforms can be used to define fractional derivatives. If any integrable system admits these three structural elements, it will have fractional integrable equations associated to it. Once these fractional integrable equations are found, we solve them using the inverse scattering transform. The inverse scattering transform is an analytical solution method that linearizes certain nonlinear evolution equations; such equations are called integrable. The method associates an integrable equations to a scattering problem, e.g., the time-independent Schr\"odinger equation to solve the Korteweg-deVries equation. The solutions to this scattering problem are used to map the nonlinear equation into scattering space, where time evolution is simple. Then, recovering the solution to the nonlinear equation in physical space is performed by inverse scattering which involves solving a set of linear integral equations. The solutions to these integrable problems have radiation and $N$-soliton components where the solitons have elastic collisions. We linearize the fractional Korteweg-deVries by association to the time-independent Schr\"odinger equation and the nonlinear Schr\"odinger equations by the Ablowitz-Kaup-Newell-Segur scattering system. We then apply this method to derive fractional extensions to the modified Korteweg-deVries, sine-Gordon, and sinh-Gordon equations, reviewing the inverse scattering theory in detail required to define and solve these equations. The scattering equation associated to these three fractional integrable equations is a scalar reduction of the Ablowitz-Kaup-Newell-Segur scattering system given a certain symmetry condition. We show how completeness for the Ablowitz-Kaup-Newell-Segur scattering system reduces to completeness for the scalar scattering problem and use this to define the relevant nonlinear fractional operators. Then, using this completeness relation, we verify explicitly that the one-soliton solutions to these equations are indeed solutions. As with the fractional Korteweg-deVries and nonlinear Schr\"odinger equations, these soliton solutions exhibit anomalous dispersion. We then showed that this method can be applied to discrete systems by defining and solving the fractional integrable discrete nonlinear Schr\"odinger equation, whose solution is defined on a lattice, i.e., on discrete points on the real line, but still depends continuously on time. As with the other fractional equations, we demonstrated how the three key mathematical ingredients lead to an explicit form for the equation and how the inverse scattering transform can be used to linearize the problem. However, unlike the continuous fractional integrable equations, the one-soliton solution admits a peak velocity related to its amplitude in a much more complicated manner than in anomalous dispersion, allowing for potentially unexpected behavior. In particular, we demonstrate that the velocity can exhibit a turning point where it switches from increasing to decreasing with the fractional parameter at a certain value of the fractional parameter. We also show how some of the characteristics of these fractional integrable equations reach beyond integrable equations by comparing this discrete integrable equation to the fractional averaged discrete nonlinear Schr\"odiner equation. This equation is closely related to its integrable counterpart, but has a much simpler mathematical form. Using a Fourier split step method, we numerically integrate the fractional averaged equation and find solitary wave solutions. By studying the emitted radiation, peak position, averaged amplitude, velocity, and form of the solitary waves, we demonstrate that these waves have similar characteristics to the integrable solitons and that these similarities are accentuated for positive fractional parameter and small amplitude waves. This work invites further research into fractional integrable and nonintegrable nonlinear system and exploration of their many potential applications.
  • Developing a quantitative framework for assessing and reporting mining's contributions to sustainable development

    Smith, Nicole M..; Düzgün, H. Sebnem; Perdeli Demirkan, Cansu; Battalora, Linda Ann; Bazilian, Morgan D.; Nakagawa, Masami (Colorado School of Mines. Arthur Lakes Library, 2022)
    With the establishment of the United Nations Sustainable Development Goals (SDGs) in 2015, the UN called on the private sector to further engage in responsible business practices to contribute to the achievement of sustainable development and acknowledged the mining industry as one of the leading industries to advance the SDGs. In the past three decades, the mining industry has been making efforts to adopt more sustainable and responsible practices and measure their outcomes in accordance with global and industry sustainability targets. However, evaluating a mining company’s contribution to sustainable development across their operations is challenging because of the varied spatial and temporal scales at which they take place. At the temporal scale, there are significant operational differences between the phases of a mining operation. At the spatial scale, there is significant variation due to the adopted mining method, the size of the operation, the characteristics of the ore body, and the geological and geographical settings. Current sustainability assessment and reporting approaches of mining companies are unable to capture how their contributions to sustainable development change throughout the mining life cycle and across their operations. Thus, there is a disconnect between the reported contributions of mining companies to sustainable development at the corporate level, and the contributions at the site or operation levels. Better assessment and reporting of the mining industry’s contribution to sustainable development is essential for the mining industry to be able to manage the challenges related to contributions to the SDGs, social license to operate, stakeholder pressure, and becoming greener investments. To do this, sustainability assessment frameworks that capture the spatio-temporal scale of mining operations and that can be applied across different scales is necessary. In an attempt to meet these needs, this research develops an indicator-based quantitative framework for capturing mining’s contributions to sustainable development at three different scales and aligns these contributions to the SDGs. This dissertation composes three research articles which seek to answer the following research questions: 1. What are the trends, strengths, and weaknesses in sustainability reporting of the mining industry? How does sustainability reporting in the mining industry compare to that in the oil and gas industry? 2. How can quantification be used to assess the mining industry’s contributions to sustainable development at different spatial and temporal scales? 3. What indicators relate to the closure/post-closure phase of the mining life cycle? How do different stakeholders prioritize these indicators? 4. What indicators relate to the production phase of the mining life cycle, and specifically for low-carbon haulage technologies? 5. How does the contribution of mining to the SDGs compare for the closure/post-closure and production phases? How does the contribution of mining to the SDGs compare at the operation-, site-, and corporate-levels? This dissertation informs these questions with three research activities: An investigation of the baseline of what companies are reporting at the corporate level: This research examines the scope and consistency of sustainability indicators used in the sustainability reports of eight oil and gas and eight mining companies from 2012 to 2018. This research demonstrates that extractive industries’ sustainability reporting practices are not consistent over time and that internal issues are better represented than external issues, in particular transportation and supply chain issues. It identifies the strengths and areas for improvement in sustainability reporting practices of the two industries and aligns the strengths and areas for improvement in terms of demonstrating their contributions to the related SDGs. An analysis of mining’s contributions to sustainable development at the site level for the closure/post-closure phase: This research uses stakeholder input to evaluate and compare three different repurposing alternatives for the tailings dam area of a mine that is approaching closure. With a primary focus on people, and more specifically the stakeholders, this research examines different stakeholder perspectives on sustainable development in the context of mine closure and repurposing based on environmental, social, and economic sustainability indicators. The research shows which alternative better reflects stakeholder preferences and provides the most sustainable outcome. It contends that integrating stakeholder views into mine closure design and repurposing can lead to more responsible and sustainable mine closure that is unique to a particular setting and stakeholder needs. Applying this methodology also highlights strengths for contributing to the SDGs. An analysis of mining’s contributions to sustainable development at the operation level for the production phase: Autonomous haulage trucks (AHT) are listed among the top low-carbon strategies by large iron ore companies. This research investigates AHT’s potential for a lower carbon footprint for haulage by proposing an emission estimation methodology based on the Time Usage Model (TUM) and applying it to a surface iron ore mine in Australia. It finds that AHT result in higher overall emissions per ton of material moved compared to their conventional counterparts, while decreasing the emissions generated from non-productive activities, such as through standby or operating delay. It also finds that there is still very limited reporting of Scope 1 emissions at the site-level, and reporting is not transparent in terms of how it relates to specific processes like drilling or hauling. Although this research primarily focuses on the environment, and specifically emissions, it also discusses the broader socio-economic implications of AHT on workers and communities and identifies the related strengths and areas for improvement for the SDGs. Collectively these studies identify very different focus areas, and hence very different strengths and areas for improvement for contributing to the SDGs for the corporate, site, and operation-levels. This indicates that the varied spatial and temporal scales of mining are complementary to each other in contributing to sustainable development and the SDGs. In tracking and assessing their progress towards achieving the SDGs, mining companies should review the whole system (i.e., the corporate-level) together with its subsystems (i.e., site-level and operation-level). The findings of this dissertation inform a discussion of the usefulness of systems-based methodologies for tracking progress towards sustainable development. By approaching different scales with different assessment methods, this research was able to arrive at a more robust assessment of the mining industry’s contributions to sustainable development.
  • Theorizing the "social" in sociotechnical, community-based engineering: incorporating a rapid assessment procedure in educational and field-based studies on Colombian artisanal and small-scale gold mining

    Smith, Jessica, 1980-; Smits, Kathleen M.; Gibson, Casey; Lucena, Juan C.; Restrepo Baena, Oscar Jaime (Colorado School of Mines. Arthur Lakes Library, 2022)
    Engineering and scientific fields now widely recognize how crucial it is to understand and incorporate “social” factors to conceptualize complex systems, inform design, and guide projects. However, most engineers and natural scientists are not trained to analyze social factors as comprehensively as technical ones. Thus, the overarching aim of this thesis was to help diverse, technically-minded audiences rethink the “social” dimensions of sociotechnical systems by drawing from established social science, social justice, community-based research, and humanitarian engineering frameworks. Moreover, this thesis sought to ground these theoretical ideals with concrete educational and field-based tools and case studies centered on challenges within the Colombian artisanal and small-scale gold mining (ASGM) sector–a rural livelihood with significant environmental, political, technical, and social entanglements. The broad research questions focused on assessing the opportunities and barriers for implementing transdisciplinary tools, as well as analyzing what these tools could reveal about sociotechnical ASGM systems. This thesis includes two cases for different audiences: 1) an educational study for systems engineers in which we taught an anthropological Rapid Assessment Procedure (RAP) to students to help them conduct front-end stakeholder needs analysis with ASGM community members; 2) a field-based study for socio-hydrologists in which we applied RAP in an ASGM community to characterize the qualitative mechanisms driving coupled human-water systems. In both studies, we contributed to ongoing theoretical discussions on the current limits and opportunities for enhancing “social” aspects of transdisciplinary work by synthesizing literature from humanitarian engineering and social science. In the applied portions of this thesis, we found that RAP was a helpful tool in both educational and field-based settings. In the RAP workshop, students perceived practical benefits from RAP and demonstrated positive learning outcomes in analyzing ASGM stakeholder needs. In the field in Colombia, RAP allowed us to identify patterns of hydrological-risk-based livelihood decisions in ASGM and agricultural sectors that paradoxically threatened the very water resources that these livelihoods depended on, ultimately revealing critical points of intervention for sustainable water resource management. These findings indicate the need for further theoretical and applied research on how engineering and natural science disciplines can fruitfully collaborate with social science fields to take people more effectively into account in sociotechnical problem definition and solving.
  • Gas hydrate deposition & remediation during continuous/transient operations

    Koh, Carolyn A. (Carolyn Ann); Zerpa, Luis E.; Pickarts, Marshall A.; Yin, Xiaolong; Wu, Ning; Carreon, Moises; Grasso, Giovanny A.; Estanga, Douglas (Colorado School of Mines. Arthur Lakes Library, 2022)
    Within hydrocarbon production, gas hydrates present a significant issue preventing safe and reliable operation. Plugs from these compounds develop within hours to days from jamming, agglomeration, and deposition processes. In particular, deposition comprises an outstanding and difficult subject to address due to the terminology’s broad coverage of various mechanisms, which include aggregate bedding, particle impingement, liquid splashing, and condensation. This thesis focuses on its potential mitigation with a surface treatment as well as its significance during transient shut-in/restart operations. Efforts began with a bench-scale evaluation of a smooth, omniphobic surface treatment on its interaction with multiple pipeline liquids and solids. A benchtop interfacial tensiometer, rocking cell, flowloop, and mechanical shear device demonstrated reduced/prevented wetting, deposition, formation, and adhesion of water, crude oil, gas hydrates, asphaltenes, and waxes. This work showed one surface treatment provided passive protection from multiple flow assurance issues. A scientific understanding of gas hydrate deposition prevention with the surface treatment ensued. Induction time, rocking cell, and flowloop trials highlighted surface roughness/energy controlling effects on gas hydrate nucleation, condensation-driven growth, and aggregate deposition. For optimal prevention, treatments required both smoothened and low energy features, which reduced physical/chemical interactions between fluids and the wall. Next, the surface treatment application scaled to a laboratory flowloop for transient oil-dominated gas hydrate experiments. Baseline tests displayed a prevalence of aggregate bedding. High volume, low conversion deposits, which formed rapidly after cold restart, dominated plugging. Then, application of the omniphobic surface treatment to only 15% of the flowline rectified this problem. The system avoided significant stenosis and thus plugging. The surface treatment successfully scaled to fully flow systems, matching results from benchtop apparatuses. Further transient gas hydrate experimentation transpired on a pilot-scale flowloop with an attached riser. Despite the different setup, analogous plugging mechanisms to the baseline lab-scale flowloop trials occurred. A bedding-based deposition process controlled plugging. Furthermore, possible severe slugging in the riser arose and perpetuated due to the presence of the solid slurry. The riser’s presence emphasized the importance of geometry in laboratory testing setups. Lastly, collected flowloop observations combined with research from key operators and academic groups to generate a conceptual picture for gas hydrate plugging during transient operations. This illustration created a basis for the unresolved modeling efforts of these scenarios. Overall, the scientific impact of this work emanates from identifying the wall features preventing gas hydrate formation/deposition, connecting solids presence to possible severe slugging, and developing a novel illustration of gas hydrate plugging through deposition during pipeline restart. This information aids researchers in the design of future surface treatment formulations for desired gas hydrate formation and deposition prevention properties. Furthermore, once directly verified, it presents a previously unknown expansion to the envelope of severe slugging occurrence by considering gas hydrates. The thesis work ends by formulating a modeling pathway during highly-complex transient flow conditions for predictive tools. Though each area involved the first recorded instance of such descriptions, the general conclusions applied broadly enough to appropriate scenarios to extend beyond the limited conditions shown in this thesis.
  • Numerical techniques for the simulation of reverse osmosis systems with complicated geometries

    Tilton, Nils; Cath, Tzahi Y.; Johnston, Jacob R.; Ryan, Jennifer K.; Bogin, Gregory E.; DeCaluwe, Steven C. (Colorado School of Mines. Arthur Lakes Library, 2022)
    Reverse osmosis (RO) is a membrane desalination process with important applications to seawater desalination and advanced water treatment. RO, however, is an inherently energy intensive process due to the large pressures required to operate these systems. One major technical problem for RO that leads to further energy demands and performance losses is called concentration polarization. Concentration polarization refers to the accumulation of solutes near the membrane surface. The fundamentals of this process are complicated because of unsteady mixing and solute transport and because the flow regimes in RO systems are not fully understood. More recently, computational fluid dynamics (CFD) has been used as an investigative tool to study mass transport and polarization phenomena in RO. However, numerical challenges arise in RO systems due to complicated interactions between solute boundary layers and unsteady vortical flow structures generated by feed spacers. Feed spacers are mesh-like materials that support the membrane and separate the membrane sheets. Furthermore, these flow structures also interact with semipermeable membranes through which the permeate flow depends on the local pressure. Additionally, many simulations of spacers currently rely on body-fitted grids that require considerable time to generate. This work addresses these challenges by developing a suite of numerical methods tailored to the efficient and accurate simulation of RO systems with feed spacers. We first develop an immersed boundary method capable of simulating spacers without body-fitted grids. We show that, using these methods, we can recover second-order spatial accuracy for both Dirichlet and Neumann type boundary conditions for the spacer filaments. We then explore the application of two projection methods to the accuracy of RO simulations. We found that traditional projection methods can produce lower temporal accuracy for the pressure field as well as the velocity fields. We then develop a modified projection method that recovers second-order accuracy. Using our methods, we perform a parametric CFD study of concentration polarization in RO system with three different spacer arrangements over a broad range of Reynolds numbers, $50 \le Re \le 500$. We then propose and investigate a reduced order model that mimics the impact of spacers on the near-membrane velocity field and demonstrate its ability to reproduce important CFD results to high accuracy.
  • Symmetry protected subspaces in quantum simulations

    Kapit, Eliot; Rotello, Caleb G.; Mehta, Dinesh P.; Gong, Zhexuan; Hadi, Mohammed (Colorado School of Mines. Arthur Lakes Library, 2022)
    This work demonstrates an efficient algorithm which leverages transitive closure on graphs to identify symmetry protected subspaces of quantum unitary operators in the σz basis. The algorithm’s time complexity is linear to the size of the subspace. This subspace constrains states in quantum time evolution to a smaller subspace. If this subspace is small enough, a classical computer can complete the quantum simulation task; however, if this subspace has exponential scaling and is thus infeasible to calculate, a quantum computer is required to complete the same simulation task. In this regime, the symmetry protected subspace is leveraged to reduce quantum computation errors with post-selection. To do this, a probabilistic algorithm is presented which can determine if a measured state is within the subspace in polynomial time. Both algorithms are benchmarked on three quantum simulations: the Heisenberg XXX Hamiltonian, T2 Quantum Cellular Automata (QCA), and F4 QCA. QCA simulations are implemented as update rules which define quantum time evolution. Finally, the paper concludes by implementing post-selection on a quantum circuit emulator with noise with the three aforementioned simulations.
  • Practical applications of machine learning to quantum computing and quantum simulation

    Gong, Zhexuan; Lidiak, Alexander G.; Wu, Bo; Carr, Lincoln D.; Diniz Behn, Cecilia (Colorado School of Mines. Arthur Lakes Library, 2022)
    The understanding of quantum many-body systems is at the core of various quantum technologies that could revolutionize our society, including quantum computing and quantum simulation in particular. This thesis focuses on practical applications of machine learning to the simulation, control, and understanding of quantum manybody systems. First, variational learning using artificial neural networks is leveraged to achieve efficient classical simulation of quantum many-body systems and is further developed to allow GPU accelerated computing. Second, a machine learning based quantum optimal control algorithm is developed to design speed-optimized quantum gates for a superconducting qubit based quantum computer. Its advantage over conventional algorithms is demonstrated both theoretically and experimentally. Third, unsupervised machine learning is applied to identify complex quantum phase transitions. A specific method known as diffusion map is shown to be capable of learning a wide range of non-trivial quantum phases and is applicable to state-of-art quantum simulation experiments. Finally, a new quantum state tomography protocol based on supervised machine learning is developed, which outperforms many existing protocols especially for states generated by one-dimensional noisy quantum computers. Each of these achievements is integral to the development of quantum technologies in realistic settings.
  • Extracting neural network models via contention-based side channel attacks on shared memory system-on-chips

    Belviranli, Mehmet E.; Cieslewicz, Alexander W.; Yue, Chuan; Wu, Bo (Colorado School of Mines. Arthur Lakes Library, 2022)
    Shared Memory System-on-Chip (SM-SoC) devices are used in a multitude of environments in order to execute sensitive and critical operations. Some of these operations include the execution of deep neural networks (DNN). Several side-channel attacks that extract neural network information have previously been proposed. However the side-channel vector used by these attacks assumes a high level of access to the target system. In this work, we propose a novel side-channel attack for SM-SoCs used in mobile platforms. Our attack relies on a unique memory contention leakage detection (MCLD) mechanism that minimizes the level of privilege an attacker requires to execute a DNN extraction attack. MCLD generates an artificial memory traffic on the CPU and observes the contention exerted on the shared memory bus in order to gather information about a target process. MCLD’s implementation requires no physical access or elevated permissions on the target system. Using MCLD, the paper further implements and end-to-end DNN model used to extract the information from the victim DNN. Our experimental results performed on a state-of-the-art mobile/edge SM-SoC and popular neural networks showed that our proposed scheme can predict the neural network topology of critical workloads with average layer error rate, i.e. percentage of mispredicted layers, of 5%.
  • Catalyst design strategy to logically control product selectivity by tailoring void environments around active sites

    Kwon, Stephanie; Bian, Yingxue; Wu, Ning; Gómez-Gualdrón, Diego A. (Colorado School of Mines. Arthur Lakes Library, 2022)
    Selectivity, activity, and stability are the most crucial criteria for screening catalysts for catalytic reactions. Porous materials such as zeolites and metal-organic frameworks have been studied to understand the role of the microporous environment on reaction rates, and previous research has reported that the different sizes of microporous void environments enable selective uptake of molecules and modification of product selectivity, while the transition state leading to desired products was close to the void size. Therefore, we aim to explore a design strategy to create zeo-type catalysts with desired microstructures, and depending on the size of the microporous structure, these catalysts are able to control product selectivity for plenty of reactions. This work demonstrates a bottom-up synthesis method of tailoring the microporous SiO2 void environments around the active sites on TiO2 catalysts, which controls product selectivity for aldol condensation catalysis. We showed that microporous SiO2 layers can prevent unwanted parallel esterification reactions by destabilizing the relevant transition state that leads to esterification products and suppressing unwanted sequential reactions that form bulkier products by imposing steric barriers. This work provides a methodological framework for controlling product selectivity via a bottom-up design strategy, which can be applied to other catalytic applications in a broader area.
  • Understanding and protecting the privacy of main users and bystanders in smart homes

    Yue, Chuan; Gilbert, Benjamin; Alshehri, Ahmed; Yang, Dejun; Han, Qi (Colorado School of Mines. Arthur Lakes Library, 2022)
    Privacy is considered among the fundamental human rights recognized by the United Nations (UN). It has become a main concern for the public as technologies have advanced and become more accessible. Among the new technologies are smart homes which have been adopted by many people in recent years. Along with the great benefits of these smart home devices, new privacy threats have appeared. According to McKinsey 2020 report regarding the smart home market, 70% of potential consumers are hesitant to buy smart home devices due to privacy concerns. These privacy concerns slow down growth and innovations for smart home technologies. This was our motivation to further explore the privacy issues in smart homes and how we can improve privacy protections. It is important to consider that privacy in smart homes affects more than primary users (owners or main users) of the devices. Secondary users (e.g., visiting family members, friends, or domestic workers) can be impacted as well. We investigate the privacy issues in smart homes for two main groups: the privacy of owners in Chapter 2, and the privacy of bystanders in Chapter 3. Bystanders’ privacy protections might conflict with the smart home utility. For example, if a bystander wants to protect their privacy by asking the owner to turn off the smart camera, the main utility of the camera to increase home safety is defeated. Thus, a form of agreement is needed to protect bystanders’ privacy while preserving the smart home utility. As a result, We investigate how owners and bystanders can negotiate over smart home data practices when they coexist in Chapter 4.
  • Multiphysics simulation of the electrical signature of dual-domain mass transfer in a pore-scale microfluidics experiment

    Singha, Kamini; Dorchester, Charles Leland, III; Navarre-Sitchler, Alexis K.; Li, Yaoguo (Colorado School of Mines. Arthur Lakes Library, 2022)
    Dual-porosity models are often used to describe solute transport in heterogeneous media, but the parameters within these models are difficult to identify experimentally or relate to measurable quantities. Here, we developed synthetic, pore-scale microfluidics experiments that coupled fluid flow, solute transport, and electrical resistivity (ER) measurements to explore relations between dual-porosity model parameters and the hydrogeologic system. A conductive-tracer test and the associated geoelectrical signatures were simulated for four flow rates in two distinct pore-scale model scenarios: one with intergranular porosity, and a second with an intragranular porosity also defined. With these models, we explore how the effective characteristic-length scale estimated from a best-fit DDMT model compares to geometric aspects of the flow field. In both model scenarios we find that: (1) mobile domains and immobile domains are interpreted to exist in a DDMT system even in a system that is explicitly defined with one domain; (2) the ratio of immobile to mobile porosity is larger at faster flow rates as is the mass transfer rate; and (3) a comparison of length scales associated with the mass-transfer rate (Lα) and those associated with calculation of the Peclet number (LPe) show LPe is commonly larger than Lα. These results suggest that estimated immobile porosities from a DDMT model are not only a function of physically mobile or immobile pore space, but also are a function of advective versus diffusive transport defined by the average linear pore water velocity, whereas the mass-transfer rates between mobile and immobile pore space are a function of the average linear pore water velocity. This work demonstrates that the definition of “immobile” is a function of the relation between pore water velocity and domain geometry (i.e., stagnant zones around pore constrictions), where physical obstructions to flow can drive the interpretation of immobile porosity even in single-porosity domains.
  • Optimization of processing, microstructure, and performance of Q&P steels

    Speer, J. G.; Findley, Kip Owen; Gilliams, Casey M. F.; Clarke, Kester; Bourne, Gerald (Colorado School of Mines. Arthur Lakes Library, 2022)
    Quenched and partitioned (Q&P) steels are third generation advanced high strength steels (AHSS) designed to maintain (or increase) strength and improve ductility (relative to the second generation of AHSS) while utilizing leaner alloyed steels. Q&P steels are of particular interest in the automotive industry as a way to improve safety and produce lighter weight vehicles that are more fuel efficient. Though there is an abundance of studies that attempt to maximize retained austenite contents in Q&P steels, as retained austenite has been shown to promote promising combinations of strength and ductility, few sources are available that take into consideration the influence of chemical and morphological characteristics (such as morphology, stability, and size) of the retained austenite on performance. In this work, consideration of retained austenite characteristics and the influence of prior processing (hot band thickness, cold reduction, and coiling temperature), and thus prior microstructure, on the heat-treating response, resulting microstructures, and property performance of Q&P steels are investigated in a 0.17C-2.8Mn-1.5Si steel through modeling, dilation simulations, and mechanical testing. The Koistinen-Marburger (KM) relationship was modified to incorporate variations in composition and austenite grain size to model optimal quench temperatures. Through the explicit incorporation of grain size, it was implied that austenite could be fully stabilized at higher quench temperatures, dependent on the applied heat treatment and parameters used. Dilation experiments exploring the effect of quench temperature and partitioning time, involving careful monitoring of secondary martensite formation during final quenching, were performed. It was found that a general Q&P heat treatment could be applied to a material of the same composition but with variations in the prior processing and result in similar microstructures and amounts of retained austenite. Heat treatment parameters as determined by the dilation experiments were applied to sub-size ASTM E8 tensile specimens and mechanically tested. Substantial variation in tensile properties were found in the different processing conditions. These variations are not fully understood and may have arisen due to inconsistent temperature control during heat treatment.
  • Novel approaches in electromagnetic methods using reparameterization and machine learning with application to monitoring geological CO₂ storage sites

    Li, Yaoguo; Kohnke, Colton J.; Wakin, Michael B.; Swidinsky, Andrei; Ganesh, Mahadevan; Shragge, Jeffrey (Colorado School of Mines. Arthur Lakes Library, 2022)
    Generalized geophysical inversion is a powerful tool to construct physical property models of the subsurface from measurements of different fields, such as electromagnetic or potential fields, at receiver locations. Geophysical inversion methods are computationally expensive in terms of memory, storage, and computational time. These limitations make inversion an impractical method to enhance geophysical surveys in real time, such as in determining where future receivers should be located during a field campaign, or when an answer is needed quickly, as in problems related to decisions about well operations. Within this thesis, I make use of unique model parameterizations and data characteristics to limit the computational cost and perform a rapid inversion of electromagnetics data for subsurface properties. The method of zero-level curves aids in determining the location and primitive shape of a compact conductor in the subsurface, and can be used to make operation decisions in real time. The zero-level curve can also be used to approximate a resistive body in a conductive media, such as a CO_2 plume in a saline reservoir. I then focus on the feasibility of monitoring supercritical CO_2 that has been injected into a conductive reservoir for a fictitious scenario based on the Kemper CarbonSAFE site in Mississippi. In CO_2 monitoring there is a push for low-cost geophysical methods to be part of the larger monitoring plan, making electromagnetics an attractive choice. Furthermore, focusing on the magnetic field from such surveys offers additional flexibility to monitoring due to the advent of drone-based sensors. I model electric dipole sources in the frequency domain, a time-domain current loop, and magnetotellurics to determine if the current generation of sensor technology is sensitive enough to measure the resulting secondary magnetic fields. I find that electric dipole sources and magnetotellurics produce measurable fields, but a time-domain current loop does not for this particular site. Finally, I apply a convolutional neural network to automatically invert magnetotelluric tipper data for a parameterized model of the CO_2 plume in a conductive reservoir. Parameterizing the model of the CO_2 allows the network to train faster when compared to methods that solve for a full conductivity model of the subsurface. The network is also applied in classification mode to determine if the CO_2 is contained in the reservoir layer, or if it has escaped the seal, however, the network fails to distinguish between these cases, likely due to the limited vertical resolution offered by magnetotelluric tipper data.
  • Structural assessment and platform actuation of a novel semi-submersible floating offshore wind turbine substructure

    Johnson, Kathryn E.; Damiani, Rick; Dinius, James D.; Bogin, Gregory E.; Braun, Robert J. (Colorado School of Mines. Arthur Lakes Library, 2022)
    Floating offshore wind turbines (FOWTs) represent a valuable resource as governments plan how to transition from fossil fuels to renewables. However, there are both technical and economic challenges to overcome before floating offshore wind becomes a commercially viable option. Due to high deployment, capital, and development costs (due to the relative novelty of the technology), floating offshore wind currently has a much higher energy cost than other renewable options such as fixed bottom offshore or land-based wind turbines. The design of FOWTs also presents many engineering hurdles, such as maintaining platform stability without excessive system mass and cost, keeping the Levelized Cost of Energy (LCOE) competitive with other energy production methods, and ensuring the structure can withstand environmental loading from waves, wind, and turbine actions. SpiderFLOAT is a novel semi-submersible floating offshore wind substructure designed by the USFLOWT team under the ARPA-E ATLANTIS program. SpiderFLOAT is a flexible substructure consisting of a central column with three legs attached by moment-free connections and supported by tensioned stay-cables. Buoyancy cans are attached at the ends of the legs. This structure is designed to shed loading via structural compliance, reducing the structural requirements to sustain wind and wave loading in an offshore environment. This keeps system mass, and by extension material costs, lower than other FOWT substructure designs. This thesis investigates a few SpiderFLOAT substructure alterations to the design to mitigate loading and improve system stability while keeping system mass low. Two types of design alterations were considered: alterations to the structural geometry and the introduction of substructure actuation mechanisms. Structural alterations included system draft, buoyancy can size, stay cable attachment points, and the number of legs. Actuation mechanisms included the tension of the stay cables, the ballast level in the buoyancy cans, and adjustments in mooring-line length and thus tension.
  • Integrating complex human dimensions into residential demand flexibility program design

    Gilbert, Benjamin; Reyna, Janet L.; Olawale, Opeoluwa Wonuola; Tabares-Velasco, Paulo Cesar; Landis, Amy E.; Sen, Pankaj K.; Wilson, Eric J. H. (Colorado School of Mines. Arthur Lakes Library, 2022)
    The United States residential buildings sector with its over 135 million customers contributes 48% of peak energy demand and about 1 billion tons of carbon emissions. Peak energy demand reduction via demand flexibility (DF) is critical to increasing grid-integrated renewable energy and reducing carbon emissions. Yet, DF does not meet its peak demand reduction goal by over 60% due to low participation rates (<8% in the residential sector) and high attrition rates (>30% override rates). Complex diverse human behavior and evolving comfort priorities, especially with climate change, further complicate predicting peak energy demand and DF adoption rates. Anticipating and predicting DF overrides and accounting for different customer types in peak demand estimates are also critical to successful DF program design. Existing residential occupant behavior and building energy models (BEM) relevant to peak demand predictions and DF technology prioritization do not suffice in reducing peak demand uncertainties, understanding how occupants interact with DF, or predicting how different residential customers might adopt DF. This dissertation fills these gaps by delineating the key factors that impact what people do to drive peak demand (behavior). It also answers why people override signals from DF programs (interactions) and how these might affect DF estimates (modeling) based on population demographics. The methods in this dissertation combine econometric/statistical and BEM approaches via supervised machine learning models, statistical significance tests, big data analytics, and large-scale physics-based building stock energy model development to create new DF-relevant datasets. For instance, low-income groups may refrain from DF enrollment due to price shocks (up to 8 times greater peak energy burdens relative to high-income groups) if a uniform price-based demand flexibility scheme is signaled. The overarching goal is to influence robust DF program designs that can fully integrate clean energy grid solutions while including underserved communities in the United States.

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