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.

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.

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.

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.

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.

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.

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%.

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.

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.

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.