Showing papers by "Missouri University of Science and Technology published in 2014"

Battery Energy Storage System (BESS) and Battery Management System (BMS) for Grid-Scale Applications

Abstract: The current electric grid is an inefficient system that wastes significant amounts of the electricity it produces because there is a disconnect between the amount of energy consumers require and the amount of energy produced from generation sources. Power plants typically produce more power than necessary to ensure adequate power quality. By taking advantage of energy storage within the grid, many of these inefficiencies can be removed. When using battery energy storage systems (BESS) for grid storage, advanced modeling is required to accurately monitor and control the storage system. A battery management system (BMS) controls how the storage system will be used and a BMS that utilizes advanced physics-based models will offer for much more robust operation of the storage system. The paper outlines the current state of the art for modeling in BMS and the advanced models required to fully utilize BMS for both lithium-ion batteries and vanadium redox-flow batteries. In addition, system architecture and how it can be useful in monitoring and control is discussed. A pathway for advancing BMS to better utilize BESS for grid-scale applications is outlined.

Gamification of Education: A Review of Literature

Abstract: We synthesized the literature on gamification of education by conducting a review of the literature on gamification in the educational and learning context Based on our review, we identified several game design elements that are used in education These game design elements include points, levels/stages, badges, leaderboards, prizes, progress bars, storyline, and feedback We provided examples from the literature to illustrate the application of gamification in the educational context

Secure k-nearest neighbor query over encrypted data in outsourced environments

Abstract: For the past decade, query processing on relational data has been studied extensively, and many theoretical and practical solutions to query processing have been proposed under various scenarios. With the recent popularity of cloud computing, users now have the opportunity to outsource their data as well as the data management tasks to the cloud. However, due to the rise of various privacy issues, sensitive data (e.g., medical records) need to be encrypted before outsourcing to the cloud. In addition, query processing tasks should be handled by the cloud; otherwise, there would be no point to outsource the data at the first place. To process queries over encrypted data without the cloud ever decrypting the data is a very challenging task. In this paper, we focus on solving the k-nearest neighbor (kNN) query problem over encrypted database outsourced to a cloud: a user issues an encrypted query record to the cloud, and the cloud returns the k closest records to the user. We first present a basic scheme and demonstrate that such a naive solution is not secure. To provide better security, we propose a secure kNN protocol that protects the confidentiality of the data, user's input query, and data access patterns. Also, we empirically analyze the efficiency of our protocols through various experiments. These results indicate that our secure protocol is very efficient on the user end, and this lightweight scheme allows a user to use any mobile device to perform the kNN query.

Joint decisions on inventory replenishment and emission reduction investment under different emission regulations

Abstract: Carbon emission regulation policies have emerged as mechanisms to control firms’ carbon emissions. To meet regulatory requirements, firms can make changes in their production planning decisions or invest in green technologies. In this study, we analyse a retailer’s joint decisions on inventory replenishment and carbon emission reduction investment under three carbon emission regulation policies. Particularly, we extend the economic order quantity model to consider carbon emissions reduction investment availability under carbon cap, tax and cap-and-trade policies. We analytically show that carbon emission reduction investment opportunities, additional to reducing emissions as per regulations, further reduce carbon emissions while reducing costs. We also provide an analytical comparison between various investment opportunities and compare different carbon emission regulation policies in terms of costs and emissions. We document the results of a numerical study to further illustrate the effects of investment...

Sensor Cloud: A Cloud of Virtual Sensors

Abstract: Newer models for interacting with wireless sensors such as Internet of Things and Sensor Cloud aim to overcome restricted resources and efficiency. The Missouri S&T (science and technology) sensor cloud enables different networks, spread in a huge geographical area, to connect together and be employed simultaneously by multiple users on demand. Virtual sensors, which are at the core of this sensor cloud architecture, assist in creating a multiuser environment on top of resource-constrained physical wireless sensors and can help in supporting multiple applications.

An Accurate Small-Signal Model of Inverter- Dominated Islanded Microgrids Using $dq$ Reference Frame

Abstract: In the islanded mode operation of a microgrid, a part of the distributed network becomes electrically separated from the main grid, while loads are supported by local sources. Such distributed energy sources (DERs) are typically power electronic based, making the full system complex to study. A method for analyzing such a complicated system is discussed in this paper. A microgrid system with two inverters working as DERs is proposed. The controllers for the inverters are designed in the dq reference frame. Nonlinear equations are derived to reflect the system dynamics. These equations are linearized around steady-state operating points to develop a state-space model of the microgrid. An averaged model is used in the derivation of the mathematical model that results in a simplified system of equations. An eigenvalue analysis is completed using the linearized model to determine the small-signal stability of the system. A simulation of the proposed microgrid system consisting of two inverter based DERs, passive loads, and a distribution line is performed. An experimental testbed is designed to investigate the system's dynamics during load perturbation. Results obtained from the simulation and hardware experiment are compared with those predicted by the mathematical model to verify its accuracy.

The structure and properties of amorphous indium oxide

Abstract: A series of In2O3 thin films, ranging from X-ray diffraction amorphous to highly crystalline, were grown on amorphous silica substrates using pulsed laser deposition by varying the film growth temperature. The amorphous-to-crystalline transition and the structure of amorphous In2O3 were investigated by grazing angle X-ray diffraction (GIXRD), Hall transport measurement, high resolution transmission electron microscopy (HRTEM), electron diffraction, extended X-ray absorption fine structure (EXAFS), and ab initio molecular dynamics (MD) liquid-quench simulation. On the basis of excellent agreement between the EXAFS and MD results, a model of the amorphous oxide structure as a network of InO x polyhedra was constructed. Mechanisms for the transport properties observed in the crystalline, amorphous-to-crystalline, and amorphous deposition regions are presented, highlighting a unique structure-property relationship.

QoS Aware Geographic Opportunistic Routing in Wireless Sensor Networks

Abstract: QoS routing is an important research issue in wireless sensor networks (WSNs), especially for mission-critical monitoring and surveillance systems which requires timely and reliable data delivery. Existing work exploits multipath routing to guarantee both reliability and delay QoS constraints in WSNs. However, the multipath routing approach suffers from a significant energy cost. In this work, we exploit the geographic opportunistic routing (GOR) for QoS provisioning with both end-to-end reliability and delay constraints in WSNs. Existing GOR protocols are not efficient for QoS provisioning in WSNs, in terms of the energy efficiency and computation delay at each hop. To improve the efficiency of QoS routing in WSNs, we define the problem of efficient GOR for multiconstrained QoS provisioning in WSNs, which can be formulated as a multiobjective multiconstraint optimization problem. Based on the analysis and observations of different routing metrics in GOR, we then propose an Efficient QoS-aware GOR (EQGOR) protocol for QoS provisioning in WSNs. EQGOR selects and prioritizes the forwarding candidate set in an efficient manner, which is suitable for WSNs in respect of energy efficiency, latency, and time complexity. We comprehensively evaluate EQGOR by comparing it with the multipath routing approach and other baseline protocols through ns-2 simulation and evaluate its time complexity through measurement on the MicaZ node. Evaluation results demonstrate the effectiveness of the GOR approach for QoS provisioning in WSNs. EQGOR significantly improves both the end-to-end energy efficiency and latency, and it is characterized by the low time complexity.

Parallel, non-iterative, multi-physics domain decomposition methods for time-dependent Stokes-Darcy systems

Abstract: Two parallel, non-iterative, multi-physics, domain decomposition methods are proposed to solve a coupled time-dependent Stokes-Darcy system with the Beavers-Joseph-Saffman-Jones interface condition. For both methods, spatial discretization is effected using finite element methods. The backward Euler method and a three-step backward differentiation method are used for the temporal discretization. Results obtained at previous time steps are used to approximate the coupling information on the interface between the Darcy and Stokes subdomains at the current time step. Hence, at each time step, only a single Stokes and a single Darcy problem need be solved; as these are uncoupled, they can be solved in parallel. The unconditional stability and convergence of the first method is proved and also illustrated through numerical experiments. The improved temporal convergence and unconditional stability of the second method is also illustrated through numerical experiments.

Effect of weak magnetic field on arsenate and arsenite removal from water by zerovalent iron: an XAFS investigation.

Abstract: In this study, a weak magnetic field (WMF), superimposed with a permanent magnet, was utilized to improve ZVI corrosion and thereby enhance As(V)/As(III) removal by ZVI at pHini 3.0–9.0. The experiment with real arsenic-bearing groundwater revealed that WMF could greatly improve arsenic removal by ZVI even in the presence of various cations and anions. The WMF-induced improvement in As(V)/As(III) removal by ZVI should be primarily associated with accelerated ZVI corrosion, as evidenced by the pH variation, Fe2+ release, and the formation of corrosion products as characterized with X-ray absorption fine structure spectroscopy. The arsenic species analysis in solution/solid phases at pHini 3.0 revealed that As(III) oxidation to As(V) in aqueous phase preceded its subsequent sequestration by the newly formed iron (hydr)oxides. However, both As(V) adsorption following As(III) oxidation to As(V) in solution and As(III) adsorption preceding its conversion to As(V) in solid phase were observed at pHini 5.0–9.0. ...

Artificial Neural Networks for Control of a Grid-Connected Rectifier/Inverter Under Disturbance, Dynamic and Power Converter Switching Conditions

Abstract: Three-phase grid-connected converters are widely used in renewable and electric power system applications. Traditionally, grid-connected converters are controlled with standard decoupled d-q vector control mechanisms. However, recent studies indicate that such mechanisms show limitations in their applicability to dynamic systems. This paper investigates how to mitigate such restrictions using a neural network to control a grid-connected rectifier/inverter. The neural network implements a dynamic programming algorithm and is trained by using backpropagation through time. To enhance performance and stability under disturbance, additional strategies are adopted, including the use of integrals of error signals to the network inputs and the introduction of grid disturbance voltage to the outputs of a well-trained network. The performance of the neural-network controller is studied under typical vector control conditions and compared against conventional vector control methods, which demonstrates that the neural vector control strategy proposed in this paper is effective. Even in dynamic and power converter switching environments, the neural vector controller shows strong ability to trace rapidly changing reference commands, tolerate system disturbances, and satisfy control requirements for a faulted power system.

Enhancing Intensity and Refractive Index Sensing Capability with Infrared Plasmonic Perfect Absorbers

Abstract: An infrared refractive index sensor based on plasmonic perfect absorbers for glucose concentration sensing is experimentally demonstrated. Utilizing substantial absorption contrast between a perfect absorber (∼98% at normal incidence) and a non-perfect absorber upon the refractive index change, a maximum value of figure of merit (FOM*) about 55 and a bulk wavelength sensitivity about 590 nm/RIU are achieved. The demonstrated sensing platform provides great potential in improving the performance of plasmonic refractive index sensors and developing future surface enhanced infrared spectroscopy.

Evaluation of borate bioactive glass scaffolds as a controlled delivery system for copper ions in stimulating osteogenesis and angiogenesis in bone healing

Abstract: Biocompatible synthetic scaffolds with enhanced osteogenic and angiogenic capacity are of great interest for the repair of large (critical size) bone defects In this study, we investigated an approach based on the controlled delivery of copper (Cu) ions from borate bioactive glass scaffolds for stimulating angiogenesis and osteogenesis in a rodent calvarial defect model Borate glass scaffolds (pore size = 200–400 μm) doped with varying amounts of Cu (0–30 wt% CuO) were created using a polymer foam replication technique When immersed in simulated body fluid (SBF) in vitro, the scaffolds released Cu ions into the medium at a rate that was dependent on the amount of Cu in the glass and simultaneously converted to hydroxyapatite (HA) At the concentrations used, the Cu in the glass was not cytotoxic to human bone marrow derived stem cells (hBMSCs) cultured on the scaffolds and the alkaline phosphatase activity of the hBMSCs increased with increasing Cu in the glass When implanted in rat calvarial defects for 8 weeks, the scaffolds doped with 3 wt% CuO showed a significantly better capacity to stimulate angiogenesis and regenerate bone when compared to the undoped glass scaffolds Together, these results indicate that the controlled delivery of Cu ions from borate bioactive glass implants is a promising approach in healing bone defects

Piecewise and Wiener Filter-Based SAR Techniques for Monostatic Microwave Imaging of Layered Structures

Abstract: In this paper, two new techniques for microwave imaging of layered structures are introduced. These techniques were developed to address the limiting issues associated with classical synthetic aperture radar (SAR) imaging techniques in generating focused and properly-positioned images of embedded objects in generally layered dielectric structures. The first method, referred to as piecewise SAR (PW-SAR), is a natural extension of the classical SAR technique, and considers physical and electrical properties of each individual layer and the discontinuity among them. Although this method works well with low loss dielectric media, its applicability to lossy media is limited. This is due to the fact that this method does not consider signal attenuation. Moreover, multiple reflections within each layer are not incorporated. To improve imaging performance in which these important phenomena are included, a second method was developed that utilizes the Green's function of the layered structure and casts the imaging approach into a deconvolution procedure. Subsequently, a Wiener filter-based deconvolution technique is used to solve the problem. The technique is referred to as Wiener filter-based layered SAR (WL-SAR). The performance and efficacy of these SAR based imaging techniques are demonstrated using simulations and corresponding measurements of several different layered media.

Radiated Two-Stage Method for LTE MIMO User Equipment Performance Evaluation

Abstract: Two-stage method for long-term-evolution (LTE) multiple-input-multiple-output (MIMO) wireless user equipment (UE) performance evaluation is one of the methods proposed for standard organizations. However, the conducted two-stage method has been challenged for its lack of support for “over-the-air” (OTA) as well as for its negligence of the self-interference in the device under test (DUT) in the throughput test. Self-interference in DUT such as cell phones could significantly reduce receiver sensitivity, thus, if not properly included in the test setup, could affect the test accuracy. In order to solve the problems, a radiated two-stage (RTS) test method for LTE MIMO UE test is presented in this paper. By applying an invert calibration matrix to the input signal of the throughput test, the proposed method performs OTA second-stage test, which eliminates the problems of connecting an RF cable directly to the DUT receiver. The RTS OTA MIMO test method can be executed in a standard single-input-single-output anechoic chamber, reduces overall system cost, and offers high reliability and repeatability. Meanwhile, the measurement provides extensive subcomponent-level performance information and makes it an ideal solution for both research and development (R&D) and certification test.

Integrated inventory control and transportation decisions under carbon emissions regulations: LTL vs. TL carriers

Abstract: This study analyzes an integrated inventory control and transportation planning problem with carbon emissions regulations. We investigate the economic order quantity model with less-than-truckload (LTL) and truckload (TL) transportation under carbon cap, cap and trade, cap and offset, and taxing policies. We find the retailer’s optimal order quantity under each regulation with LTL and TL carriers. Analytical and numerical results comparing LTL and TL carriers are documented. We illustrate that the retailer’s carrier preference depends on regulation parameters. The tools provided enable analyzing the effects of regulations, transportation costs and emissions on the retailer’s costs and emissions with each carrier.

A versatile tripodal Cu(I) reagent for C-N bond construction via nitrene-transfer chemistry: catalytic perspectives and mechanistic insights on C-H aminations/amidinations and olefin aziridinations.

Abstract: A CuI catalyst (1), supported by a framework of strongly basic guanidinato moieties, mediates nitrene-transfer from PhI═NR sources to a wide variety of aliphatic hydrocarbons (C–H amination or amidination in the presence of nitriles) and olefins (aziridination). Product profiles are consistent with a stepwise rather than concerted C–N bond formation. Mechanistic investigations with the aid of Hammett plots, kinetic isotope effects, labeled stereochemical probes, and radical traps and clocks allow us to conclude that carboradical intermediates play a major role and are generated by hydrogen-atom abstraction from substrate C–H bonds or initial nitrene-addition to one of the olefinic carbons. Subsequent processes include solvent-caged radical recombination to afford the major amination and aziridination products but also one-electron oxidation of diffusively free carboradicals to generate amidination products due to carbocation participation. Analyses of metal- and ligand-centered events by variable temperat...