Environmental and Economic Assessment of Carbon Dioxide Recovery and Mitigation in the Industrial and Energy Sectors.

Anthropogenic carbon dioxide (CO₂) is a global pollutant that needs urgent control to prevent large-scale vitiation of ecosystems. Generally speaking, anthropogenic CO2 emissions can be reduced through (1) CO2 capture for long-term sequestration or use in other applications, (2) renewable and low-carbon energy sources and technologies, and (3) demand reduction of carbon-intensive services and products through reduced consumption and efficiency improvements. The first two approaches constitute the “supply-side” of carbon abatement measures, and are the focus of this dissertation in which I examine the environmental and economic attributes of CO2 recovery and mitigation technologies in the U.S. industrial and energy sectors. Starting by developing a comprehensive picture of the recovered CO2 supply chain, this dissertation provides process-based emissions inventories for recovering and purifying CO2 from combustion flue gases and higher purity point sources for sequestration and use in industrial applications. The strong influence of CO2 quality on the emissions, energy consumption, and costs of carbon capture found through this analysis warrants deeper scientific and economic analyses of carbon capture and sequestration as a carbon abatement option. To estimate the marginal emissions from use of recovered CO2 in industrial applications, a market-based allocation methodology is developed in a consequential life cycle assessment framework, along with new greenhouse gas accounting procedures that incorporate reuse and sequestration as fates for CO2. This methodology is presented with results from experimental studies on recovered CO2-based metalworking fluids, and motivates further exploration of applications employing the thermal and chemical properties of CO2 for pollution prevention and carbon abatement. The dissertation concludes with an examination of carbon mitigation strategies from the standpoint of CO2 prevention in the U.S. electric and automotive sectors. By creating a stock-and-flow model of the U.S. automotive and power generation fleets, and considering the evolution of all major technologies in both sectors in an optimization framework, cost-minimizing technology trajectories are identified, which collectively cut about 55 gigatons of CO2 emissions by 2050. The analysis reveals that despite anticipated advancements and cost reductions in carbon abatement technologies with time, the technological costs of carbon abatement are likely to increase markedly with delay in climate-action.PhDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/111423/1/supekar_1.pd

Developmental Maturation of Dynamic Causal Control Signals in Higher-Order Cognition: A Neurocognitive Network Model

Cognitive skills undergo protracted developmental changes resulting in proficiencies that are a hallmark of human cognition. One skill that develops over time is the ability to problem solve, which in turn relies on cognitive control and attention abilities. Here we use a novel multimodal neurocognitive network-based approach combining task-related fMRI, resting-state fMRI and diffusion tensor imaging (DTI) to investigate the maturation of control processes underlying problem solving skills in 7–9 year-old children. Our analysis focused on two key neurocognitive networks implicated in a wide range of cognitive tasks including control: the insula-cingulate salience network, anchored in anterior insula (AI), ventrolateral prefrontal cortex and anterior cingulate cortex, and the fronto-parietal central executive network, anchored in dorsolateral prefrontal cortex and posterior parietal cortex (PPC). We found that, by age 9, the AI node of the salience network is a major causal hub initiating control signals during problem solving. Critically, despite stronger AI activation, the strength of causal regulatory influences from AI to the PPC node of the central executive network was significantly weaker and contributed to lower levels of behavioral performance in children compared to adults. These results were validated using two different analytic methods for estimating causal interactions in fMRI data. In parallel, DTI-based tractography revealed weaker AI-PPC structural connectivity in children. Our findings point to a crucial role of AI connectivity, and its causal cross-network influences, in the maturation of dynamic top-down control signals underlying cognitive development. Overall, our study demonstrates how a unified neurocognitive network model when combined with multimodal imaging enhances our ability to generalize beyond individual task-activated foci and provides a common framework for elucidating key features of brain and cognitive development. The quantitative approach developed is likely to be useful in investigating neurodevelopmental disorders, in which control processes are impaired, such as autism and ADHD

A NOTE ON PARTIALLY ORDERED FUZZY METRIC SPACE VIA COUPLED COINCIDENCE POINTS

In this paper, we prove a coupled coincidence point theorem in partially ordered fuzzy metric space using Ï•-contractive condition

Supercritical Carbon Dioxide in Microelectronics Manufacturing: Marginal Cradle-to-grave Emissions

AbstractThis paper presents and discusses the marginal cradle-to-grave environmental impacts of using VLSI grade supercritical carbon dioxide (scCO2) as a rinsing agent in place of ultrapure water (UPW) in semiconductor fabrication. Impacts are estimated using a consequential life cycle assessment framework for recovered CO2. Upon factoring the cumulative yields of the CO2 recovery and purification processes, compressor energy use (566kJ/kg CO2 output) together with refrigeration (540kJ/kg CO2 output) accounts for about 90% of total on-site electricity use. Upstream emissions from production of propylene carbonate co-solvent contribute to more than 50% of the life cycle impacts of scCO2-based wafer cleaning. Overall impacts of scCO2-wafer cleaning, particularly water and energy use, are found to be significantly lower than UPW

Translating and squirming cylinders in a viscoplastic fluid

Three related problems of viscoplastic flow around cylinders are considered. First, translating cylinders with no-slip surfaces appear to generate adjacent rotating plugs in the limit where the translation speed becomes vanishingly small. In this plastic limit, analytical results are available from plasticity theory (slipline theory) which indicate that no such plugs should exist. Using a combination of numerical computations and asymptotic analysis, we show that the plugs of the viscoplastic theory actually disappear in the plastic limit, albeit very slowly. Second, when the boundary condition on the cylinder is replaced by one that permits sliding, the plastic limit corresponds to a partially rough cylinder. In this case, no plasticity solution has been previously established; we provide evidence from numerical computations and slipline theory that a previously proposed upper bound (Martin & Randolph, Geotechnique, vol. 56, 2006, pp. 141–145) is actually the true plastic solution. Third, we consider how a prescribed surface velocity field can propel cylindrical squirmers through a viscoplastic fluid. We determine swimming speeds and contrast the results with those from the corresponding Newtonian problem

Linearly forced fluid flow on a rotating sphere

We investigate generalized Navier-Stokes (GNS) equations that couple nonlinear advection with a generic linear instability. This analytically tractable minimal model for fluid flows driven by internal active stresses has recently been shown to permit exact solutions on a stationary two-dimensional sphere. Here, we extend the analysis to linearly driven flows on rotating spheres. We derive exact solutions of the GNS equations corresponding to time-independent zonal jets and superposed westward-propagating Rossby waves, qualitatively similar to those seen in planetary atmospheres. Direct numerical simulations with large rotation rates obtain statistically stationary states close to these exact solutions. The measured phase speeds of waves in the GNS simulations agree with analytical predictions for Rossby waves.Comment: 13 pages, 6 figure

Comparing energy and water use of aqueous and gas‐based metalworking fluids

Gas‐based metalworking fluids (MWFs) have been proposed as alternative coolants and lubricants in machining operations to mitigate concerns surrounding water use and pollution, industrial hygiene, occupational health, and performance limitations associated with water‐based (aqueous) MWFs that are ubiquitously used in the metals manufacturing industry. This study compares the primary energy and water use associated with the consumptive use, delivery, and disposal of aqueous MWFs with three gas‐based MWFs in the literature—minimum quantity lubricant‐in‐compressed air (MQL), liquid/gaseous N2, and liquid/supercritical CO2. The comparison accounts for reported differences in machining performance in peer‐reviewed experimental studies across several machining processes and materials. The analysis shows that despite the reported improvement in tool life with N2 and CO2‐based MWFs, the electricity‐ and water‐intensive separation and purification processes for N2 and CO2 lead to their higher primary energy and water use per volume of material machined relative to water‐based MWFs. Although MQL is found to have lower primary energy use, significant consumptive water use associated with the vegetable oil commonly used with this MWF leads to higher overall water use than aqueous MWF, which is operated in a recirculative system. Gas‐based MWFs thus shift the water use upstream of the manufacturing plant. Primary energy and water use of gas‐based MWFs could be reduced by focusing on achieving higher material removal rates and throughput compared to aqueous MWF instead of solely targeting improvements in tool life. Additionally, the consumptive use of CO2 and N2 MWFs could be minimized by optimizing their flow rates and delivery to precisely meet the cooling and lubrication needs of specific machining processes instead of flooding the tool and workpiece with these gases. This article met the requirements for a gold–gold JIE data openness badge described at http://jie.click/badges.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/163496/3/jiec12992.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/163496/2/jiec12992-sup-0001-SuppMat.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/163496/1/jiec12992_am.pd