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Optimization-based network modeling of the chemical and refining industry
Get PDFThe U.S. energy landscape has changed drastically in the past years, not only solidifying the country as a key player in the global energy markets, but also having profound effects on the chemical and refining industries, by providing an abundance of Natural Gas Liquids (NGLs) that serve as versatile feedstocks. The evolving role of these industries and their complex interdependence necessitate advanced tools for modeling and optimization. The first part of this dissertation develops a comprehensive superstructure network model of the entire U.S. chemical and refining industry. This model aims to predict potential future trajectories of these industries under various scenarios related to the availability and utilization of fossil fuels. The model could serve as a crucial tool for forecasting shifts in chemical manufacturing considering specific constraints or technological innovations that capitalize on NGLs or alternative fuels. The second part focuses on regional, spatially-resolved network models to evaluate new chemical production technologies. Focusing on the Marcellus Shale region, the model identifies the optimal locations and maximum adoption costs for new technologies, with a case study on chemical plants that produce gasoline from ethylene. Time resolution is added to this model to provide a dynamic perspective, addressing questions around the potential for new chemical processing technologies to replace or supplement existing infrastructures. In the final part, the dissertation explores the integration of renewable energy into chemical processing networks. As the shift towards lower carbon emissions continues, assessing the impact of variable renewable energy on the profitability and emissions of chemical processing networks is paramount. The developed model investigates optimal decisions concerning renewable energy infrastructure and battery storage. Taken together, this dissertation offers a thorough exploration of network modeling as a tool for optimizing and understanding the increasingly interwoven chemical and refining industries. The models and analyses presented can serve as key resources for stakeholders, policy-makers, and industry practitioners seeking to navigate these industries' future complexities and opportunities.Chemical Engineerin
Why wearing a yellow hat is impossible : Chinese and U.S. Children’s developing possibility conceptions
Get PDFWhen thinking about possibility, one can consider epistemic or deontic principles (i.e., physical possibility or permissibility). Cultures differing in independence and interdependence weigh epistemic and deontic obligations differently; children in these cultures may conceive of possibility differently. A growing body of research on children’s possibility conceptions has consistently replicated a robust finding: though children as young as 4 recognize events that violate physical laws as impossible, these children also deny the possibility of events that are physically possible nevertheless improbable. From ages 4-8, children increasingly acknowledge the possibility of these events (e.g., Shtulman & Carey, 2007). However, these replications have occurred within the U.S. and Canada. The current dissertation takes this research to China, asking whether this pattern holds in an independent culture, and explores potential cultural influences on possibility judgments of ordinary events (i.e., physical regularities), impossible events (i.e., physical violations), and improbable events (i.e., physical irregularities). Study 1 explores the effect of consensus testimony on 8-year-olds possibility judgments in Austin, TX and Wuhan, China. Study 2 explores the developmental trajectory of children’s possibility judgments in Austin and Wuhan, and Study 3 asks whether children from Austin and five different Chinese cities use epistemic constraints to make possibility judgments. This research suggests that culture influences not only what children judge to be possible, but also how children reason about possibility. These findings underscore the complex exchange between culture and cognitive development and reinforce the need for more cross-cultural research with varied populations in diverse locations when studying conceptual development.Psycholog
Nickel oxide nanocrystals and vanadium oxide composites for electrochromic smart windows
Get PDFThis report investigates the synthesis, characterization, and electrochromic performance of nickel oxide (NiO) nanocrystals (NCs) and vanadium oxide (V₂O₅) composites for smart window applications. NiO NCs were synthesized through a colloidal nanocrystal process while V₂O₅ films were prepared via a simple oxidative deposition from a vanadium chloride precursor. The structural analyses revealed 4 – 7 nm flowery clusters of NiO NCs and dense amorphous V₂O₅ films, each contributing uniquely to the composite's electrochromic properties. In-situ spectroelectrochemical measurements demonstrated a maximum transmittance modulation of 55% for NiO NC films, for films tested from ~400 nm thick to ~1.2 μm thick, which highlights the limitations to our fabrication technique. We present NiO films overlayed onto amorphous V₂O₅ which exhibited a two-stage oxidation process, attributed to the sequential charging of V₂O₅ and NiO layers, offering enhanced control over optical properties without requiring additional electrodes. These studies underscore the potential of NiO/V₂O₅ composites for smart windows.Chemical Engineerin
Socio-technical systems engineering and design : a meso-level network-based approach
Get PDFDifferent from traditional engineering systems design, which is keen on the design and optimization of technical artifacts, the design of socio-technical systems (STS) is guided by fundamentally understanding the complex interactions between social and technical aspects. This has posed significant challenges when applying existing systems engineering (SE) and design approaches to STS. For example, classical top-down design methodologies, such as the Waterfall model and the SE Vee model, are not appropriate for the engineering and design of large-scale STS with spontaneous interactions among individual entities or components. Although existing bottom-up design approaches are adaptable to the system scale, they primarily focus on understanding the behaviors and interactions between individual entities at the micro-level and their impact on system performance at the macro-level. In my dissertation research, the central hypothesis is that subsystems at the meso level (e.g., small clusters of individual entities) serve as critical links in system structures and could influence both macro-level performance and micro-level interactions, and thus deserve scientific investigation in STS engineering and design. However, there is a knowledge gap in understanding what meaningful subsystem information at the meso-level is and how it can be extracted and used to guide the design of an STS system to achieve the desired system performance. To fill this gap, my research objective is to develop a novel meso-level network-based framework for STS engineering and design. This dissertation is driven by answering three research questions: 1) RQ1 : How can significant meso-level system structures be identified? 2) RQ2 : What are the influences of the significant meso-level subsystems on the system performance at the macro level and the interaction mechanism at the micro level? 3) RQ3 : How can meso-level structural information be used to design an STS to achieve desired macro-level performance and micro-level functionality? The methodologies proposed to address these questions are validated through two case studies: shared mobility systems and customer-product market systems. For shared mobility systems, a network motif-based robust design framework is proposed to improve the robustness and resilience of socio-technical systems against seasonal effects. Within this framework, trip motif mining addresses RQ1, while trip motif-based system robustness metrics tackle RQ2. Formulating and solving optimization problems serves to address RQ3. Additionally, a graph neural network-based (GNN-based) link prediction (LP) model is introduced to support STS design decision-making and validation. The GNN-based model leverages local network information to enhance prediction accuracy, addressing RQ2, while implementing the LP model for design strategy validation contributes to addressing RQ3. In the context of customer-product market systems, a socio-technical system data collection framework integrating information retrieval and survey design methods is proposed to tackle the data scarcity issue in STSs. Furthermore, a novel micro-level entity design framework of STS, considering meso-level dependencies, is proposed, marking the first attempt to solve the inverse problem. This framework contributes to addressing RQ1, RQ2, and RQ3 by incorporating network motif mining, quantification of subsystem-based individual entity functionality, and entity optimization design within a unified framework. Lastly, a preliminary exploration of meso-level temporal network motifs in STS is conducted, encompassing solutions to the dynamic data scarcity issue, dynamic network modeling, and significant temporal subnetwork mining and empirical interpretation. This exploration contributes to answering RQ1 and RQ2 when considering the time dimension. Regarding the key findings and conclusions of this dissertation, we first show the effectiveness of combining information retrieval and survey design to tackle the data accessibility challenge in STS network data. Additionally, our survey study, for the first time, gathered customers' social network data alongside their purchase decision-making data, aiding in the examination of social factors influencing customers' decision-making. Moreover, while survey studies are time-consuming, leveraging named entity recognition (NER) models for mining online text data offers a viable alternative for supporting entity relationship data collection. Then, when working on the shared mobility system case study, we find that: 1) An STS's seasonal sensitivity is closely tied to imbalanced capacity planning within its subsystems. Therefore, balancing the capacity of meso-level service systems is beneficial to enhancing STS robustness against seasonal demand fluctuations; 2) The outperformance of the GNN-based predictive model, which incorporates local network information, compared to a simple neural network model lacking such consideration, demonstrates the importance of local network information in demand prediction between stations in shared mobility networks. Moreover, this outperformance persists even when network structures and density change significantly. Next, in the study of design for customer-product systems, the inter-brand triadic competition closure competition, where three products from different brands form a closed triangle competition, emerges as a significant pattern in the vacuum cleaner market system. Identifying these meso-level patterns offers a means to quantify product competitiveness. Integrating this information with network predictive models and metaheuristic approaches, like the genetic algorithm, facilitates the inclusion of local competition data in the product design process. In the study of STS dynamic analysis, we demonstrate that increasing undersampling ratios improves predictive performance, particularly in moderately imbalanced systems, enhancing the GNN-based LP model. However, in extremely imbalanced systems, a tuning process is necessary to balance computational efficiency and model performance, with the threshold-based postprocessing method consistently outperforming the rank-based method. Additionally, six temporal competition motifs are interpreted, aiding in tracking market system dynamics. In summary, my dissertation contributes to the systems science literature by introducing a novel meso-level network-based framework for STS engineering and design, thus addressing the knowledge gap pertaining to the identification and interpretation of statistically significant subsystem structures (i.e., meso-level structures formed within a complex system) and the use of such structures for STS engineering and design. The findings presented herein shed light on the importance of treating significant subsystems as crucial functional units and building blocks of STSs and underscore the need to consider them in both macro-level system design and micro-level individual entity design for optimizing system performance and entity functionality. Beyond enriching systems science from the meso-level subsystem perspective, this dissertation is expected to generate broader impacts in: 1) Addressing imbalanced source allocations in societal infrastructure systems, such as uneven distribution of public resources in urban areas. By treating local communities as meso-level subsystems and utilizing their information, this research offers policymakers actionable insights for more efficient resource distribution; 2) showing the potential to inform robust design strategies for large networked physical systems like power grids and transportation networks, the meso-level subsystem-based approach facilitates the identification of critical functional units within these systems. Subsequently, system optimization design can be guided by preserving the functionality of these identified subsystems. 3) enhancing interdisciplinary collaboration between engineering and social sciences. The frameworks proposed in this dissertation are extensible to incorporate societal analytical models. For example, in the case study of customer-product market systems, a more advanced network model that integrates customer social networks into the proposed product competition network can be easily generated to support a more in-depth analysis. By bridging the gap between technical systems engineering and social aspects, it fosters a holistic approach to addressing complex societal challenges.Mechanical Engineerin
Surfactant enhanced oil recovery in high temperature high pressure sandstone reservoir with mobility control
Get PDFSurfactant is one of the various important chemicals used for enhanced oil recovery (EOR) methods. Surfactant can be injected into oil reservoirs to reduce the interfacial tension (IFT) between the aqueous and oleic phases or to alter the rock's wettability in a favorable way, both of which increase displacement efficiency. However, in many cases, surfactant is injected with other components to control the mobility of the aqueous phase, such as polymer in SP flooding or gas in LTG flooding. Even in surfactant EOR methods, mobility control is crucial for ensuring effective sweep efficiency and oil recovery.
This thesis presents a comparative study of Surfactant-Polymer (SP) flooding and Low-Tension Gas (LTG) flooding, two advanced surfactant EOR techniques for high-temperature sandstone reservoirs. Both methods rely on ultra-low IFT to improve oil recovery, but their effectiveness also hinges on mobility control, formulation optimization, and reservoir conditions. The study also examined the optimum salinity for both surrogate and live oil, proposing a mass fraction based mixing rule to match the equivalent alkane carbon number (EACN) and optimize the salinity for microemulsion phase behavior.
For SP flooding, the research optimized microemulsion phase behavior under harsh conditions, including 100°C and high salinity (582 ppm divalent cations), using anionic surfactant formulations like TDA carboxylate and C20-24 IOS with a co-solvent. LTG flooding, involving the co-injection of surfactant and methane, generated strong foams that provided superior sweep efficiency, particularly in intermediate-permeability regions (70 mD), where SP may experience permeability reduction and reduced oil recovery.
Both SP and LTG methods achieved over 90% recovery of the original oil in place (OOIP) with live oil under well-optimized conditions. LTG requires larger chemical slugs and more time than SP but offers better mobility control in low-permeability reservoirs. SP, however, is faster and more environmentally favorable due to lower surfactant retention. The choice between SP and LTG depends on factors like permeability, operation time, and environmental impact. While SP is more time-efficient, LTG excels in low-permeability conditions, with similar overall chemical costs but higher facility expenses for LTG due to gas injection.Petroleum and Geosystems Engineerin
Energy efficient and area efficient integrated circuits design for implantable devices
Get PDFImplantable medical devices (IMDs) play crucial roles in various clinical applications. They facilitate diagnosis, deliver therapeutic interventions, and promote regenerative processes. Furthermore, IMDs are revolutionizing scientific approaches and methodologies, particularly in neuroscience research. Cutting-edge IMDs designed for neural interfaces should be able to support vital signal monitoring and advanced neuromodulation. Additionally, it is important to implement a wirelessly powered IMD with a data transmission link to eliminate the need for tethers and batteries, thus overcoming limitations in clinical use. Despite all these they can do, the IMDs are still facing several challenges, such as device miniaturization, power reduction, and closing the loop. In this dissertation, several application-specific integrated circuits (ASICs) have been developed for next-generation IMDs. In addition, in these ASICs, several circuit-level and system-level techniques have been proposed to address the aforementioned challenges. In the first ASIC design, a wireless opto-electro neural interface is developed to support simultaneous optical stimulation and neural recording. In addition, a novel voltage-boosting switched-capacitor-based stimulation (VB-SCS) and a continuous-time discrete-time (CT-DT) delta-sigma modulator-based (ΔΣM) neural recording front-end is proposed. The second ASIC design includes a novel linear-charging SCS (LC-SCS) and a CT ΔΣM neural recording front-end, for the first time, enabling a dual-modal miniaturized neural interface device. The third design presents a wireless, multi-modal physiological monitoring ASIC for animal health monitoring injectable devices. The ASIC includes an electrocardiogram (ECG), photoplethysmography (PPG), and body temperature sensing. This dissertation also explored a novel method to power the device efficiently and wirelessly. In the fourth ASIC, an ultrasound energy harvesting circuit was proposed. The ASIC is able to harvest acoustic power from a pre-charged capacitive micromachined ultrasonic transducers (CMUT) and provides the CMUT with a 4-44V bias voltage to dynamically optimize its efficiency. In the last design, an switched-capacitor-based DCDC boost converter with optimal efficiency tracking scheme is proposed to facilitate the self-powered health monitoring devices.Electrical and Computer Engineerin
The influence of music on cognitive function in people with type 2 diabetes
Get PDFPeople with type 2 diabetes (T2DM) are at risk of cognitive impairment. This dissertation aimed to examine how music impacts cognitive function of people with T2DM. A systematic review of people with mild cognitive impairment was conducted to examine the effects of music interventions on cognitive function and to identify gaps in the literature. The systematic review indicated that various music interventions (e.g., dancing, listening to music, musical improvisation) improve global cognitive function, verbal fluency, executive function, and spatial function. The review also highlighted existing gaps in the literature regarding the effects of music interventions on specific cognitive domains and their impact on disease-related cognitive impairment. In addition, secondary analyses on people with T2DM were carried out to investigate the influence of music on their cognitive function. The first study used path analysis to examine the relationships among musical activity engagement, depressive symptoms, physical activity, and cognitive function. The path model revealed that musical activity engagement had a significant indirect effect on subjective cognitive function through physical activity, with physical activity fully mediating this relationship. The second study employed multiple regression to identify the significant musical reward factor predicting cognitive function. Results showed that mood regulation reward had a significant positive association with subjective cognitive function. The findings of the dissertation provide preliminary evidence on the effects of music on cognitive function in people with T2DM. Continued and more rigorous research is necessary to establish strong evidence for the beneficial effects of music and its application in clinical practice. Implications for future research and nursing practice were discussed.Nursin
Regulation of manganese efflux transporter SLC30A10 for maintaining manganese homeostasis
No full textManganese is an essential metal that induces neurotoxicity at elevated levels. Animal studies dating back to the 1920s highlight the importance of hepatic and intestinal manganese excretion for maintaining physiological body manganese levels. However, the molecular mechanism of manganese excretion is only now being elucidated following the discovery of hereditary forms of manganese toxicity linked to homozygous loss-of-function mutations in SLC30A10. Our previous studies identified SLC30A10 as a manganese efflux transporter that is crucial for mediating manganese excretion in the liver and intestines and preventing toxicity. Whereas the disease-causing, yet very rare SLC30A10 loss-of-function mutations are now well characterized, the effects of modest changes in SLC30A10 activity or expression on manganese homeostasis and pathophysiology for general public health are poorly understood. These changes can be caused by genetic factors, such as less severe SLC30A10 polymorphisms, or as a homeostatic response to factors, such as elevated manganese levels. Indeed, several highly frequent, non-coding SLC30A10 SNPs, as well as a coding SNP have been associated with modest manganese level increases, neuromotor deficits, or elevated liver disease markers. In addition, our lab has recently characterized the manganese-induced SLC30A10 upregulation by hypoxia-inducible factors (HIF). This work aimed to build upon these recent findings to: [1] determine the effects of coding SLC30A10 SNP associated with liver disease markers (variant T95I) on SLC30A10 activity; and [2] characterize mismetallation and inhibition of Prolyl Hydroxylase Domain 2 (PHD2) as the homeostatic manganese sensing mechanism that activates HIF signaling and SLC30A10 upregulation. In Chapter 2, liver disease-associated SLC30A10 variant T95I is shown to retain Mn efflux activity comparable to wild-type (WT) SLC30A10 in cell culture assays, suggestive of a minor deficit in SLC30A10 activity that may only present a pathological phenotype in conjunction with other disease factors. In Chapter 3, the mismetallation and inhibition of PHD2 enzyme by elevated manganese are characterized as the homeostatic Mn sensing mechanism that activates HIF signaling and upregulates SLC30A10. Altogether, these results substantially advance our understanding of SLC30A10 regulation in response to elevated manganese and have implications for identifying genetic susceptibilities to manganese pathophysiologies.Cellular and Molecular Biolog
Context Matters. Raising children with a serious condition can sometimes take a toll on a mother’s long-term physical health.
No full textThis study examined how three dimensions of parenting intensity shaped physical health among mothers who care for a child with a serious condition. Fixed-effects modeling of panel data showed all three dimensions predicted poorer health over time. Associations were weaker when mothers had higher incomes or worked for pay.Population Research Cente
Master's thesis recital (mezzo soprano)
No full textVittoria mio core / Giacomo Carissimi -- Thy hand, Belinda ; When I am laid / Henry Purcell -- Che faro senza Euridice / Gluck -- Amorosi miei giorni / Stefano Donaudy -- Der Tod und das Mädchen / Schubert -- Ah! Mon fils! : from Le prophète / Meyerbeer -- Hold fast to dreams / Langston Hughes [text], Rosephanye Powell -- Afraid, am I afraid? : from The Medium / Menotti -- The water is wide / arr. Jay Althouse -- Amoung the fuchscias / Burleigh -- Nobody knows de trouble I seen / arr. Clarence Cameron White -- City called heaven / arr. Hall Johnson -- Memory : from Cats / Andrew Lloyd Webber -- Send in the clowns : from A little night music / Stephen Sondheim -- Gimmie gimmie : from Thoroughly modern Millie / Jeanie Tesori, Dick Scanlan.MusicName of supervisor not provided