Identification of Microturbine Model for Long-term Dynamic Analysis of Distribution Networks

As one of the most successfully commercialized distributed energy resources, the long-term effects of microturbines (MTs) on the distribution network has not been fully investigated due to the complex thermo-fluid-mechanical energy conversion processes. This is further complicated by the fact that the parameter and internal data of MTs are not always available to the electric utility, due to different ownerships and confidentiality concerns. To address this issue, a general modeling approach for MTs is proposed in this paper, which allows for the long-term simulation of the distribution network with multiple MTs. First, the feasibility of deriving a simplified MT model for long-term dynamic analysis of the distribution network is discussed, based on the physical understanding of dynamic processes that occurred within MTs. Then a three-stage identification method is developed in order to obtain a piecewise MT model and predict electro-mechanical system behaviors with saturation. Next, assisted with the electric power flow calculation tool, a fast simulation methodology is proposed to evaluate the long-term impact of multiple MTs on the distribution network. Finally, the model is verified by using Capstone C30 microturbine experiments, and further applied to the dynamic simulation of a modified IEEE 37-node test feeder with promising results.

Data-Driven Dynamic Prediction of Interrelated Heat and Electric Outputs of Microturbines

Microturbines are among the most successfully commercialized distributed energy resources, especially when they are used for combined heat and power generation. However, the interrelated thermal and electrical system dynamic behaviors have not been fully investigated. This is technically challenging due to the complex thermo-fluid-mechanical energy conversion processes which introduce multiple time-scale dynamics and strong nonlinearity into the analysis. To tackle this problem, this paper proposes a simplified model which can predict the coupled thermal and electric output dynamics of microturbines. Considering the time-scale difference of various dynamic processes occuring within microturbines, the electromechanical subsystem is treated as a fast quasi-linear process while the thermo-mechanical subsystem is treated as a slow process with high nonlinearity. A three-stage subspace identification method is utilized to capture the dominant dynamics and predict the electric power output. For the thermo-mechanical process, a radial basis function model trained by the particle swarm optimization method is employed to handle the strong nonlinear characteristics. Experimental tests on a Capstone C30 microturbine show that the proposed modeling method can well capture the system dynamics and produce a good prediction of the coupled thermal and electric outputs in various operating modes.

Integrated Optimal Power Flow for Distribution Networks in Local and Urban Scales

This paper develops an integrated optimal power flow (OPF) tool for distribution networks in two spatial scales. In the local scale, the distribution network, the natural gas network, and the heat system are coordinated as a microgrid. In the urban scale, the impact of natural gas network is considered as constraints for the distribution network operation. The proposed approach incorporates unbalance three-phase electrical systems, natural gas systems, and combined cooling, heating, and power systems. The interactions among the above three energy systems are described by energy hub model combined with components capacity constraints. In order to efficiently accommodate the nonlinear constraint optimization problem, particle swarm optimization algorithm is employed to set the control variables in the OPF problem. Numerical studies indicate that by using the OPF method, the distribution network can be economically operated. Also, the tie-line power can be effectively managed.

Fuzzy logic-based implicit authentication for mobile access control

In order to address the increasing compromise of user privacy on mobile devices, a Fuzzy Logic based implicit authentication scheme is proposed in this paper. The proposed scheme computes an aggregate score based on selected features and a threshold in real-time based on current and historic data depicting user routine. The tuned fuzzy system is then applied to the aggregated score and the threshold to determine the trust level of the current user. The proposed fuzzy-integrated implicit authentication scheme is designed to: operate adaptively and completely in the background, require minimal training period, enable high system accuracy while provide timely detection of abnormal activity. In this paper, we explore Fuzzy Logic based authentication in depth. Gaussian and triangle-based membership functions are investigated and compared using real data over several weeks from different Android phone users. The presented results show that our proposed Fuzzy Logic approach is a highly effective, and viable scheme for lightweight real-time implicit authentication on mobile devices.

Improved Real-time State-of-Charge Estimation of LiFePO4 Battery Based on a Novel Thermoelectric Model

Li-ion batteries have been widely used in electric vehicles, and battery internal state estimation plays an important role in the battery management system. However, it is technically challenging, in particular, for the estimation of the battery internal temperature and state-ofcharge (SOC), which are two key state variables affecting the battery performance. In this paper, a novel method is proposed for realtime simultaneous estimation of these two internal states, thus leading to a significantly improved battery model for realtime SOC estimation. To achieve this, a simplified battery thermoelectric model is firstly built, which couples a thermal submodel and an electrical submodel. The interactions between the battery thermal and electrical behaviours are captured, thus offering a comprehensive description of the battery thermal and electrical behaviour. To achieve more accurate internal state estimations, the model is trained by the simulation error minimization method, and model parameters are optimized by a hybrid optimization method combining a meta-heuristic algorithm and the least square approach. Further, timevarying model parameters under different heat dissipation conditions are considered, and a joint extended Kalman filter is used to simultaneously estimate both the battery internal states and time-varying model parameters in realtime. Experimental results based on the testing data of LiFePO4 batteries confirm the efficacy of the proposed method.

Epitaxial growth of molecular crystals on van der Waals substrates for high-performance organic electronics

Epitaxial van der Waals (vdW) heterostructures of organic and layered materials are demonstrated to create high-performance organic electronic devices. High-quality rubrene films with large single-crystalline domains are grown on h-BN dielectric layers via vdW epitaxy. In addition, high carrier mobility comparable to free-standing single-crystal counterparts is achieved by forming interfacial electrical contacts with graphene electrodes.

Aerosol ion concentrations and oxygen-17 excess data for samples collected during the Malaspina and Xue-Long cruises

The dataset contains aerosol ion concentrations and oxygen-17 excess data for samples collected during the Malaspina and Xue-Long cruises. This is the data used for the study "Isotopic constraints on the role of hypohalous acids in sulfate aerosol formation in the remote marine boundary layer" in ACPD by Chen et al., 2016.

The Effects of High Steady State Auxin Levels on Root Cell Elongation in Brachypodium.

The long-standing Acid Growth Theory of plant cell elongation posits that auxin promotes cell elongation by stimulating cell wall acidification and thus expansin action. To date, the paucity of pertinent genetic materials has precluded thorough analysis of the importance of this concept in roots. The recent isolation of mutants of the model grass species Brachypodium distachyon with dramatically enhanced root cell elongation due to increased cellular auxin levels has allowed us to address this question. We found that the primary transcriptomic effect associated with elevated steady state auxin concentration in elongating root cells is upregulation of cell wall remodeling factors, notably expansins, while plant hormone signaling pathways maintain remarkable homeostasis. These changes are specifically accompanied by reduced cell wall arabinogalactan complexity but not by increased proton excretion. On the contrary, we observed a tendency for decreased rather than increased proton extrusion from root elongation zones with higher cellular auxin levels. Moreover, similar to Brachypodium, root cell elongation is, in general, robustly buffered against external pH fluctuation in Arabidopsis thaliana However, forced acidification through artificial proton pump activation inhibits root cell elongation. Thus, the interplay between auxin, proton pump activation, and expansin action may be more flexible in roots than in shoots.

Angler Perception and Population Dynamics of the Northern Snakehead (Channa argus) in the Potomac River & Tributaries

Our research sought to address the extent to which the northern snakehead (Channa argus), an invasive fish species, represents a threat to the Potomac River ecosystem. The first goal of our research was to survey the perceptions and opinions of recreational anglers on the effects of the snakehead population in the Potomac River ecosystem. To determine angler perceptions, we created and administered 113 surveys from June – September 2014 at recreational boat ramps along the Potomac River. Our surveys were designed to expand information collected during previous surveys conducted by the U.S. Fish and Wildlife Service. Our results indicated recreational anglers perceive that abundances and catch rates of target species, specifically largemouth bass, have declined since snakehead became established in the river. The second goal of our research was to determine the genetic diversity and potential of the snakehead population to expand in the Potomac River. We hypothesized that the effective genetic population size would be much less than the census size of the snakehead population in the Potomac River. We collected tissue samples (fin clippings) from 79 snakehead collected in a recreational tournament held between Fort Washington and Wilson’s Landing, MD on the Potomac River and from electrofishing sampling conducted by the Maryland Department of Natural Resources in Pomonkey Creek, a tributary of the Potomac River. DNA was extracted from the tissue samples and scored for 12 microsatellite markers, which had previously been identified for Potomac River snakehead. Microsatellite allele frequency data were recorded and analyzed in the software programs GenAlEx and NeEstimator to estimate heterozygosity and effective genetic population size. Resampling simulations indicated that the number of microsatellites and the number of fish analyzed provided sufficient precision. Simulations indicated that the effective population size estimate would expect to stabilize for samples > 70 individual snakehead. Based on a sample of 79 fish scored for 12 microsatellites, we calculated an Ne of 15.3 individuals. This is substantially smaller than both the sample size and estimated population size. We conclude that genetic diversity in the snakehead population in the Potomac River is low because the population has yet to recover from a genetic bottleneck associated with a founder effect due to their recent introduction into the system.

Investigating the Diabetic Brain: The Effects of Pioglitazone and Insulin on the Cellular Processes and Pathology of Alzheimer's Disease

Alzheimer’s disease (AD) is the sixth leading cause of death in the US. Some researchers refer to AD as “Type III Diabetes” because of reported glucose metabolism dysfunction. Preclinical studies suggest increasing insulin decreases AD pathology, although the mechanism remains unclear. To sensitize insulin signaling, this study activated Peroxisome Proliferator-Activated Receptor Gamma using intranasal co-administration of pioglitazone (PGZ) and insulin. This method targeted the site of action to reduce peripheral effects and to maximize impact in transgenic mice expressing AD pathology. Data from GC-MS fluxomics analysis suggested that PGZ+Insulin increased glucose metabolism in the brain. Immunohistochemistry with relevant antibodies was used to identify AD pathological markers in the subiculum, indicating that PGZ+Insulin decreased pathology compared to Insulin and Saline. This suggests that increasing glucose uptake in the brain alleviated AD pathology, further clarifying the role of insulin signaling in AD pathology.Gemstone

PREPARATION OF POLYELECTROLYTE MEMBRANES EMBEDDED WITH ZEOLITE NANOPARTICLES FOR ENHANCED PERFORMANCE IN FORWARD OSMOSIS

Water scarcity is a global issue that has already affected every continent. Membrane technology is considered as one of the most promising candidates for resolving this worsening issue. Among all the membrane processes, the emerging forward osmosis (FO) membrane process is osmotically-driven and has unique advantages compared with other traditional pressure-driven membrane processes. One of the major challenges to advancing the FO membrane process is the lack of a suitable membrane. Polyelectrolyte thin film prepared via layer-by-layer (LbL) technique has demonstrated its excellent performance in many applications including electronics, optics, sensors, etc. Recent studies have revealed the potential of polyelectrolyte thin films in acting as the active separation layer of FO membranes, but significant efforts are still needed to improve the membrane performance and understand the transport mechanisms. This dissertation introduces a novel approach to prepare a zeolite-embedded polyelectrolyte composite membrane for enhanced FO performance. This membrane takes advantages of the versatile LbL process to unprecedentedly incorporate high loading of zeolite nanoparticles, which are anticipated to facilitate water transport due to the uniquely interconnected structure of zeolites. Major topics discussed in this dissertation include: (1) the synthesis and evaluation of the polyelectrolyte-zeolite composite FO membrane, (2) the examination of the fouling resistance to identify its technical limitations, (3) the demonstration of the membrane regenerability as an effective strategy for membrane fouling control, and (4) the investigation of crosslinking effects on the membrane performance to elucidate the transport mechanisms involved in the zeolite-embedded polyelectrolyte membranes. Comparative studies have been made between polyelectrolyte membranes with and without zeolite incorporation. The findings suggest that the zeolite-embedded membrane, although slightly more susceptible to silica scaling, has demonstrated enhanced water flux and separation capability, good resistance to organic fouling, and complete regenerability for fouling control. Additionally, the embedded zeolite nanoparticles are proved to be able to create fast pathways for water transport. Overall, this work provides a novel strategy to create zeolite-polymer composite membranes with enhanced separation performance and unique fouling mitigation properties.

The whole-cell immobilization of D-hydantoinase-engineered Escherichia coli for D-CpHPG biosynthesis

Background: D-Hydroxyphenylglycine is considered to be an important chiral molecular building-block of antibiotic reagents such as pesticides, and β-lactam antibiotics. The process of its production is catalyzed by D-hydantoinase and D-carbamoylase in a two-step enzyme reaction. How to enhance the catalytic potential of the two enzymes is valuable for industrial application. In this investigation, an Escherichia coli strain genetically engineered with D-hydantoinase was immobilized by calcium alginate with certain adjuncts to evaluate the optimal condition for the biosynthesis of D-carbamoyl-p-hydroxyphenylglycine (D-CpHPG), the compound further be converted to D-hydroxyphenylglycine (D-HPG) by carbamoylase. Result: The optimal medium to produce D-CpHPG by whole-cell immobilization was a modified Luria-Bertani (LB) added with 3.0% (W/V) alginate, 1.5% (W/V) diatomite, 0.05% (W/V) CaCl2 and 1.00 mM MnCl2. The optimized diameter of immobilized beads for the whole-cell biosynthesis here was 2.60 mm. The maximized production rates of D-CpHPG were up to 76%, and the immobilized beads could be reused for 12 batches. Conclusions: This investigation not only provides an effective procedure for biological production of D-CpHPG, but gives an insight into the whole-cell immobilization technology. © 2016 Pontificia Universidad Católica de Valparaíso. Production and hosting by Elsevier B.V. All rights reserved.

FOOD FOR THE CITY: CULTIVATING COMMUNITY IN BALTIMORE CITY

One in four residents of Baltimore City live in a food desert. Food desert disproportionately affects the low income neighborhoods more than the neighborhoods with financial stability. Throughout history, food became a commodity that depends on and dictates the market force. Food sources were being eliminated in the inner city while the suburbs saw rising development of grocery stores. Without grocery stores and other food retailers, communities are missing gathering and commercial hubs that make neighborhoods livable and help the local economy sustain and thrive. This thesis studies why food was further displaced from suffering communities and how an inclusive sustainable urban food system can help create a hub of neighborhood revitalization and promote health, social, safety, stability, and economic well-being of the community.