A. James Clark School of Engineering

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The collections in this community comprise faculty research works, as well as graduate theses and dissertations.

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Now showing 1 - 6 of 6
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    Electricity Generation Using Sediment Microbial Fuel Cells with a Manganese Dioxide Cathode Catalyst
    (2014) Tatinclaux, Maia; Torrents, Alba; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Wastewater treatment plants employ an energetically costly aerobic unit process to remove organic matter from municipal wastewater; this process is known as activated sludge. Microbial fuel cells (MFCs) present an anaerobic, energy-saving approach to wastewater treatment that results in electricity generation. However, MFCs are often limited by internal resistance from membrane fouling and slow cathodic oxygen reduction. This work examined an option to overcome these limitations-- adapting membrane-less sediment microbial fuel cells (SMFCs) for use with wastewater as an organic substrate by using floating carbon cloth air cathodes coated with an oxygen reduction reaction (ORR) catalyst. The performance of a platinum ORR catalyst at the cathode was compared to a manganese dioxide ORR catalyst and several additional cathode materials and reactor configurations were tested to optimize SMFC performance. The MnO2 catalyst, though significantly cheaper than platinum, was unable to sustain consistent high cathode potentials in wastewater over time.
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    Multi-Period Natural Gas Market Modeling - Applications, Stochastic Extensions and Solution Approaches
    (2010) Egging, Rudolf Gerardus; Gabriel, Steven A; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    This dissertation develops deterministic and stochastic multi-period mixed complementarity problems (MCP) for the global natural gas market, as well as solution approaches for large-scale stochastic MCP. The deterministic model is unique in the combination of the level of detail of the actors in the natural gas markets and the transport options, the detailed regional and global coverage, the multi-period approach with endogenous capacity expansions for transportation and storage infrastructure, the seasonal variation in demand and the representation of market power according to Nash-Cournot theory. The model is applied to several scenarios for the natural gas market that cover the formation of a cartel by the members of the Gas Exporting Countries Forum, a low availability of unconventional gas in the United States, and cost reductions in long-distance gas transportation. The results provide insights in how different regions are affected by various developments, in terms of production, consumption, traded volumes, prices and profits of market participants. The stochastic MCP is developed and applied to a global natural gas market problem with four scenarios for a time horizon until 2050 with nineteen regions and containing 78,768 variables. The scenarios vary in the possibility of a gas market cartel formation and varying depletion rates of gas reserves in the major gas importing regions. Outcomes for hedging decisions of market participants show some significant shifts in the timing and location of infrastructure investments, thereby affecting local market situations. A first application of Benders decomposition (BD) is presented to solve a large-scale stochastic MCP for the global gas market with many hundreds of first-stage capacity expansion variables and market players exerting various levels of market power. The largest problem solved successfully using BD contained 47,373 variables of which 763 first-stage variables, however using BD did not result in shorter solution times relative to solving the extensive-forms. Larger problems, up to 117,481 variables, were solved in extensive-form, but not when applying BD due to numerical issues. It is discussed how BD could significantly reduce the solution time of large-scale stochastic models, but various challenges remain and more research is needed to assess the potential of Benders decomposition for solving large-scale stochastic MCP.
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    Design and testing of a microbial fuel cell for the conversion of lignocellulosic biomass into electricity
    (2010) Gregoire, Kyla Patricia; Becker, Jennifer; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Previous research has demonstrated that microbial fuel cells (MFCs) have the ability to degrade soluble substrates such as wastewater; however, very few studies have attempted the conversion particulate biomass to electricity in an MFC. A single-chamber, air cathode MFC was developed using a solid, lignocellulosic substrate (corncob pellets) as the electron donor. The first trial, using a prototype reactor with a graphite rod anode, ran for 415 hours, and generated a maximum open circuit voltage and current of 0.67 V and 0.25 mA, respectively. The second trial employed graphite brush anodes and multiple microbial inocula. A pasteurized soil inoculum resulted in negligible power (P = 0.144 mW/m3). The addition of rumen fluid, which naturally contains cellulose-degrading microorganisms, and Geobacter metallireducens, resulted in Pmax values of 77 mW/m3 and 159 mW/m3, respectively. Analysis of hydrogen, methane, organic acids, and the mass of substrate consumed provided insight into the relationship between cellulose oxidation, methanogenesis, and power production.
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    NANOPOROUS AAO: A PLATFORM FOR REGULAR HETEROGENEOUS NANOSTRUCTURES AND ENERGY STORAGE DEVICES
    (2009) Perez, Israel; Rubloff, Gary W; Material Science and Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Nanoporous anodic aluminum oxide (AAO) has vast implications as a tool for nanoscience research and as a nanostructure in which nanoscale devices can be fabricated because of its regular and ordered nanopores. Self-assembly plays a critical role in pore ordering, causing nanopores to grow parallel with one another in high density. The mild electrochemical conditions in which porous AAO grows along with its relatively cheap starting materials makes this nanomaterial a cost effective alternative to advanced photolithography techniques for forming high surface area nanostructures over large areas. In this research, atomic layer deposition (ALD) was used to deposit conformal films within in nanoporous AAO with hopes to 1) develop methodologies to characterize ALD depositions within its high aspect ratio nanopores and 2) to better understand how to use nanoporous AAO templates as a scaffold for energy devices, specifically Metal-Insulator-Metal (MIM) capacitors. Using the nanotube template synthesis method, ALD films were deposited onto nanoporous AAO, later removing the films deposited within the templates nanopores for characterization in TEM. This nanotube metrology characterization involves first obtaining images of full length ALD-AAO nanotubes, and then measuring wall thickness as a function of depth within the nanopore. MIM nanocapacitors were also constructed in vertical AAO nanopores by deposition of multilayer ALD films. MIM stacks were patterned into micro-scale capacitors for electrical characterization.
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    MINIMUM ENERGY DESIGN OF SEAWATER HEAT EXCHANGERS
    (2009) Luckow, Patrick Wass; Bar-Cohen, Avram; Rodgers, Peter; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Industrial cooling with seawater, particularly natural gas liquefaction in arid environments, places large strains on existing heat exchanger designs. High temperature, high salinity water damages metals and leads to devices with a short useful life. Cost effective, corrosion resistant heat exchangers are required to fully utilize available saline water resources. Thermally conductive polymer composites, using carbon fiber fillers to enhance conductivity, are a promising material. This Thesis provides a characterization, analysis, and optimization of heat exchangers built of anisotropic thermally conductive polymers. The energy content of such polymers is compared to several other materials, and the required content of carbon-fiber fillers is studied for optimum conductivity enhancement. A methodology for the optimization of low thermal conductivity fins, and subsequently heat exchangers, is presented. Finally, the thermal performance of a prototype thermally enhanced polymer heat exchanger is experimentally verified, and compared to numerical and analytical results.
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    CASPER: An Integrated Energy-Driven Approach for Task Graph Scheduling on Distributed Embedded Systems
    (IEEE, 2005-07) Kianzad, Vida; Bhattacharyya, Shuvra S.; Qu, Gang
    For multiprocessor embedded systems, the dynamic voltage scaling (DVS) technique can be applied to scheduled applications for energy reduction. DVS utilizes slack in the schedule to slow down processes and save energy. Therefore, it is generally believed that the maximal energy saving is achieved on a schedule with the minimum makespan (maximal slack). Most current approaches treat task assignment, scheduling, and DVS separately. In this paper, we present a framework called CASPER (Combined Assignment, Scheduling, and PowER-management) that challenges this common belief by integrating task scheduling and DVS under a single iterative optimization loop via genetic algorithm. We have conducted extensive experiments to validate the energy efficiency of CASPER. For homogeneous multiprocessor systems (in which all processors are of the same type), we consider a recently proposed slack distribution algorithm (PDP-SPM) [3]: applying PDP-SPM on the schedule with the minimal makespan gives an average of 53.8% energy saving; CASPER finds schedules with slightly larger makespan but a 57.3% energy saving, a 7.8% improvement. For heterogeneous systems, we consider the power variation DVS (PV-DVS) algorithm [13], CASPER improves its energy efficiency by 8.2%. Finally, our results also show that the proposed single loop CASPER framework saves 23.3% more energy over GMA+EE-GLSA [12], the only other known integrated approach with a nested loop that combines scheduling and power management in the inner loop but leaves assignment in the outer loop.