Showing papers by "Missouri University of Science and Technology published in 2008"

Particle Swarm Optimization: Basic Concepts, Variants and Applications in Power Systems

Abstract: Many areas in power systems require solving one or more nonlinear optimization problems. While analytical methods might suffer from slow convergence and the curse of dimensionality, heuristics-based swarm intelligence can be an efficient alternative. Particle swarm optimization (PSO), part of the swarm intelligence family, is known to effectively solve large-scale nonlinear optimization problems. This paper presents a detailed overview of the basic concepts of PSO and its variants. Also, it provides a comprehensive survey on the power system applications that have benefited from the powerful nature of PSO as an optimization technique. For each application, technical details that are required for applying PSO, such as its type, particle formulation (solution representation), and the most efficient fitness functions are also discussed.

Double-Tiered Switched-Capacitor Battery Charge Equalization Technique

Abstract: The automobile industry is progressing toward hybrid, plug-in hybrid, and fully electric vehicles in their future car models. The energy storage unit is one of the most important blocks in the power train of future electric-drive vehicles. Batteries and/or ultracapacitors are the most prominent storage systems utilized so far. Hence, their reliability during the lifetime of the vehicle is of great importance. Charge equalization of series-connected batteries or ultracapacitors is essential due to the capacity imbalances stemming from manufacturing, ensuing driving environment, and operational usage. Double-tiered capacitive charge shuttling technique is introduced and applied to a battery system in order to balance the battery-cell voltages. Parameters in the system are varied, and their effects on the performance of the system are determined. Results are compared to a single-tiered approach. MATLAB simulation shows a substantial improvement in charge transport using the new topology. Experimental results verifying simulation are presented.

Temperature-insensitive miniaturized fiber inline Fabry-Perot interferometer for highly sensitive refractive index measurement

Abstract: We report a miniaturized fiber inline Fabry-Perot interferometer (FPI), with an open micro-notch cavity fabricated by one-step fs laser micromachining, for highly sensitive refractive index measurement. The device was tested for measurement of the refractive indices of various liquids including isopropanol, acetone and methanol at room temperature, as well as the temperature-dependent refractive index of deionized water from 3 to 90 degrees C. The sensitivity for measurement of refractive index change of water was 1163 nm/RIU at the wavelength of 1550 nm. The temperature cross-sensitivity of the device was about 1.1x10(-6) RIU/degrees C. The small size, all-fiber structure, small temperature dependence, linear response and high sensitivity, make the device attractive for chemical and biological sensing.

Structure-property correlations in Al 7050 and Al 7055 high-strength aluminum alloys

Abstract: The 7XXX series age-hardenable high-strength aluminum alloys find useful applications in the field of aerospace engineering. Constant efforts are being made to tailor the mechanical and corrosion properties of these alloys as per requirements for a particular application. These properties are a function of factors like microstructure, chemical composition and processing parameters. An effort has been made to collate the information available from different studies conducted on alloys Al 7050 and Al 7055. Databases were created to consolidate the information about microstructure, mechanical properties and corrosion behavior for the two alloys. Existing models were utilized to predict strength and fracture toughness for these alloys and these models were validated using experimental values and a qualitative evaluation was made for the corrosion behavior of these alloys. Available data were utilized to prepare maps that are intended to serve as guides to design aluminum alloys with desired combination of properties.

Border detection in dermoscopy images using statistical region merging.

Abstract: Malignant melanoma has consistently had one of the most rapidly increasing incidence of all cancers, with 59,940 new cases and 8110 deaths estimated in the United States in 2007 (1). Early diagnosis is particularly important because melanoma can be cured with a simple excision if detected early. Dermoscopy is a non-invasive skin imaging technique that uses optical magnification and either liquid immersion and low angle-of-incidence lighting or cross-polarized lighting to make the contact area translucent, making subsurface structures more easily visible when compared with conventional macroscopic (clinical) images. Dermoscopy allows the identification of dozens of morphological features such as pigment networks, dots/globules, streaks, blue-white areas, and blotches (2). This reduces screening errors, and provides greater differentiation between difficult lesions such as pigmented Spitz nevi and small, clinically equivocal lesions (3). However, it has been demonstrated that dermoscopy may actually lower the diagnostic accuracy in the hands of inexperienced dermatologists (4). Therefore, due to the lack of reproducibility and subjectivity of human interpretation, the development of computerized image analysis techniques is of paramount importance (5). The first step in the computerized analysis of skin lesion images is the detection of the lesion borders. The importance of border detection for the analysis is two-fold. First, the border structure provides important information for accurate diagnosis. Many clinical features such as asymmetry, border irregularity, and abrupt border cutoff are calculated from the border. Second, the extraction of other important clinical features such as atypical pigment networks, globules, and blue-white areas critically depends on the accuracy of border detection. Automated border detection in dermoscopy images is a challenging task due to several reasons: (i) low contrast between the lesion and the surrounding skin; (ii) irregular and fuzzy lesion borders; (iii) artifacts such as skin lines, air bubbles and hairs; and (iv) variegated coloring inside the lesion. Numerous methods have been developed for border detection in pigmented skin lesion images earlier; most of these dealt with clinical images (6). However, recent research has focused more on dermoscopy images. Gao et al. (7) proposed two methods: one based on stabilized inverse diffusion equations, a form of non-linear diffusion and another one based on Markov random fields in which the model parameters are estimated using the mean field theory. Pagadala (8) described a method based on optimized histogram thresholding. Schmid (6) developed a technique based on color clustering. First, a 2D histogram is calculated from the first two principal components of the CIE L*u*v* color space. The histogram is then smoothed and initial cluster centers are determined from the peaks using a perceptron classifier. Finally, the lesion image is segmented using a modified version of the fuzzy c-means (FCM) clustering algorithm. Donadey et al. (9) presented a supervised method based on intensity radial profiles calculated from the I (intensity) component of the HSI space. Cucchiara et al. (10) presented a recursive FCM clustering technique that augments Schmid’s method using topological information. Erkol et al. (11) proposed a method based on the gradient vector flow (GVF) snakes with an automatic initialization. Iyatomi et al. (12) described a method called the dermatologist-like tumor extraction algorithm (DTEA) that is based on thresholding followed by iterative region growing. Melli et al. (13) compared four different color clustering algorithms: median cut, k-means, FCM, and meanshift. They concluded that the meanshift algorithm gave the best results. Celebi et al. (14) developed a method based on the JSEG segmentation algorithm. Their method involves an algorithm for approximate lesion localization that reduces the computational time and improves the accuracy by focusing the border detection process on the immediate neighborhood of the lesion rather than the whole image. In this paper, we present an unsupervised approach to border detection in dermoscopy images based on the statistical region merging (SRM) algorithm (15). The SRM algorithm is adapted to this problem due to its simplicity, computational efficiency, and excellent performance in a variety of image domains.

An experimental study on ubiquitous commerce adoption: Impact of personalization and privacy concerns

Abstract: U-commerce represents “anytime, anywhere” commerce. U-commerce can provide a high level of personalization, which can bring significant benefits to customers. However, customers’ privacy is a major concern and obstacle to the adoption of u-commerce. As customers’ intention to adopt u-commerce is based on the aggregate effect of perceived benefits and risk exposure (e.g., privacy concerns), this research examines how personalization and context can impact on customers’ perceived benefits and privacy concerns, and how this aggregated effect in turn affects u-commerce adoption intention.

Thermophysical Properties of ZrB2 and ZrB2–SiC Ceramics

Abstract: Thermophysical properties were investigated for zirconium diboride (ZrB2) and ZrB2–30 vol% silicon carbide (SiC) ceramics. Thermal conductivities were calculated from measured thermal diffusivities, heat capacities, and densities. The thermal conductivity of ZrB2 increased from 56 W (m K)−1 at room temperature to 67 W (m K)−1 at 1675 K, whereas the thermal conductivity of ZrB2–SiC decreased from 62 to 56 W (m K)−1 over the same temperature range. Electron and phonon contributions to thermal conductivity were determined using electrical resistivity measurements and were used, along with grain size models, to explain the observed trends. The results are compared with previously reported thermal conductivities for ZrB2 and ZrB2–SiC.

Effects of Ionic Strength, Temperature, and pH on Degradation of Selected Antibiotics

Abstract: Aqueous degradation rates, which include hydrolysis and epimerization, for chlortetracycline (CTC), oxytetracycline (OTC), tetracycline (TET), lincomycin (LNC), sulfachlorpyridazine (SCP), sulfadimethoxine (SDM), sulfathiazole (STZ), trimethoprim (TRM), and tylosin A (TYL) were studied as a function of ionic strength (0.0015, 0.050, or 0.084 mg/L as Na(2)HPO(4)), temperature (7, 22, and 35 degrees C), and pH (2, 5, 7, 9, and 11). Multiple linear regression revealed that ionic strength did not significantly affect (alpha = 0.05) degradation rates for all compounds, but temperature and pH affected rates for CTC, OTC, and TET significantly (alpha = 0.05). Degradation also was observed for TYL at pH 2 and 11. No significant degradation was observed for LNC, SCP, SDM, STZ, TRM, and TYL (pH 5, 7, and 9) under study conditions. Pseudo first-order rate constants, half-lives, and Arrhenius coefficients were calculated where appropriate. In general, hydrolysis rates for CTC, OTC, and TET increased as pH and temperature increased following Arrhenius relationships. Known degradation products were used to confirm that degradation had occurred, but these products were not quantified. Half-lives ranged from less than 6 h up to 9.7 wk for the tetracyclines and for TYL (pH 2 and 11), but no degradation of LIN, the sulfonamides, or TRM was observed during the study period. These results indicate that tetracyclines and TYL at pH 2 and 11 are prone to pH-mediated transformation and hydrolysis in some cases, but not the sulfonamides, LIN nor TRM are inclined to degrade under study conditions. This indicates that with the exception of CTC, OTC, and TET, pH-mediated reactions such as hydrolysis and epimerization are not likely removal mechanisms in surface water, anaerobic swine lagoons, wastewater, and ground water.

Phase Transitions in LaFeAsO: Structural, Magnetic, Elastic, and Transport Properties, Heat Capacity and Mössbauer Spectra

Abstract: We present results from a detailed experimental investigation of LaFeAsO, the parent material in the series of ``FeAs'' based oxypnictide superconductors. Upon cooling, this material undergoes a tetragonal-orthorhombic crystallographic phase transition at $\ensuremath{\sim}160\text{ }\text{K}$ followed closely by an antiferromagnetic ordering near 145 K. Analysis of these phase transitions using temperature dependent powder x-ray and neutron-diffraction measurements is presented. A magnetic moment of $\ensuremath{\sim}0.35{\ensuremath{\mu}}_{B}$ per iron is derived from M\"ossbauer spectra in the low-temperature phase. Evidence of the structural transition is observed at temperatures well above the transition temperature (up to near 200 K) in the diffraction data as well as the polycrystalline elastic moduli probed by resonant ultrasound spectroscopy measurements. The effects of the two phase transitions on the transport properties (resistivity, thermal conductivity, Seebeck coefficient, and Hall coefficient), heat capacity, and magnetization of LaFeAsO are also reported, including a dramatic increase in the magnitude of the Hall coefficient below 160 K. The results suggest that the structural distortion leads to a localization of carriers on Fe, producing small local magnetic moments which subsequently order antiferromagnetically upon further cooling. Evidence of strong electron-phonon interactions in the high-temperature tetragonal phase is also observed.

Miniaturized fiber inline Fabry-Perot interferometer fabricated with a femtosecond laser.

Abstract: We report a miniaturized inline Fabry-Perot interferometer directly fabricated on a single-mode optical fiber with a femtosecond laser. The device had a loss of 16 dB and an interference visibility exceeding 14 dB. The device was tested and survived in high temperatures up to 1100°C. With an accessible cavity and all-glass structure, the new device is attractive for sensing applications in high-temperature harsh environments.

Intelligent Scheduling of Hybrid and Electric Vehicle Storage Capacity in a Parking Lot for Profit Maximization in Grid Power Transactions

Abstract: This paper proposes an intelligent method for scheduling usage of available energy storage capacity from plug-in hybrid electric vehicles (PHEV) and electric vehicles (EV) The batteries on these vehicles can either provide power to the grid when parked, known as vehicle-to-grid (V2G) concept or take power from the grid to charge the batteries on the vehicles A scalable parking lot model is developed with different parameters assigned to fleets of vehicles The size of the parking lot is assumed to be large enough to accommodate the number of vehicles performing grid transactions In order to figure out the appropriate charge and discharge times throughout the day, binary particle swarm optimization is applied Price curves from the California ISO database are used in this study to have realistic price fluctuations Finding optimal solutions that maximize profits to vehicle owners while satisfying system and vehicle owners constraints is the objective of this study Different fleets of vehicles are used to approximate varying customer base and demonstrate the scalability of parking lots for V2G The results are compared for consistency and scalability Discussions on how this technique can be applied to other grid issues such as peaking power are included at the end

Unified Uncertainty Analysis by the First Order Reliability Method

Abstract: Two types of uncertainty exist in engineering. Aleatory uncertainty comes from inherent variations while epistemic uncertainty derives from ignorance or incomplete information. The former is usually modeled by the probability theory and has been widely researched. The latter can be modeled by the probability theory or nonprobability theories and is much more difficult to deal with. In this work, the effects of both types of uncertainty are quantified with belief and plausibility measures (lower and upper probabilities) in the context of the evidence theory. Input parameters with aleatory uncertainty are modeled with probability distributions by the probability theory. Input parameters with epistemic uncertainty are modeled with basic probability assignments by the evidence theory. A computational method is developed to compute belief and plausibility measures for black-box performance functions. The proposed method involves the nested probabilistic analysis and interval analysis. To handle black-box functions, we employ the first order reliability method for probabilistic analysis and nonlinear optimization for interval analysis. Two example problems are presented to demonstrate the proposed method.

Multiple Reference Frame-Based Control of Three-Phase PWM Boost Rectifiers under Unbalanced and Distorted Input Conditions

Abstract: Many control algorithms and circuits for three-phase pulse width modulation active rectifiers have been proposed in the past decades. In most of the research, it is often assumed that the input voltages are balanced or contain only fundamental frequency components. In this paper, a selective harmonic compensation method is proposed based on an improved multiple reference frame algorithm, which decouples signals of different frequencies before reference frame transformation. This technique eliminates interactions between the fundamental-frequency positive-sequence components and harmonic and/or negative-sequence components in the input currents, so that fast and accurate regulation of harmonic and unbalanced currents can be achieved. A decoupled phase-locked loop algorithm is used for proper synchronization with the utility voltage, which also benefits from the multiple reference frame technique. The proposed control method leads to considerable reduction in low-order harmonic contents in the rectifier input current and achieves almost zero steady-state error through feedback loops. Extensive experimental tests based on a fixed-point digital signal processor controlled 2 kW prototype are used to verify the effectiveness of the proposed ideas.

Pressureless Sintering of Zirconium Diboride: Particle Size and Additive Effects

Abstract: Zirconium diboride (ZrB 2 ) was densified by pressureless sintering using <4-wt% boron carbide and/or carbon as sintering aids. As-received ZrB 2 with an average particle size of ∼ 2 μm could be sintered to ∼ 100% density at 1900°C using a combination of boron carbide and carbon to react with and remove the surface oxide impurities. Even though particle size reduction increased the oxygen content of the powders from ∼ 0.9 wt% for the as-received powder to ∼ 2.0 wt%, the reduction in particle size enhanced the sinterability of the powder. Attrition-milled ZrB 2 with an average particle size of <0.5 μm was sintered to nearly full density at 1850°C using either boron carbide or a combination of boride carbide and carbon. Regardless of the starting particle size, densification of ZrB 2 was not possible without the removal of oxygen-based impurities on the particle surfaces by a chemical reaction.

Emerging trends in M-government

Abstract: Considering the advantages and implications of increased usage of wireless connectivity for governmental information and services.

Generalized Hamilton–Jacobi–Bellman Formulation -Based Neural Network Control of Affine Nonlinear Discrete-Time Systems

Abstract: In this paper, we consider the use of nonlinear networks towards obtaining nearly optimal solutions to the control of nonlinear discrete-time (DT) systems. The method is based on least squares successive approximation solution of the generalized Hamilton-Jacobi-Bellman (GHJB) equation which appears in optimization problems. Successive approximation using the GHJB has not been applied for nonlinear DT systems. The proposed recursive method solves the GHJB equation in DT on a well-defined region of attraction. The definition of GHJB, pre-Hamiltonian function, HJB equation, and method of updating the control function for the affine nonlinear DT systems under small perturbation assumption are proposed. A neural network (NN) is used to approximate the GHJB solution. It is shown that the result is a closed-loop control based on an NN that has been tuned a priori in offline mode. Numerical examples show that, for the linear DT system, the updated control laws will converge to the optimal control, and for nonlinear DT systems, the updated control laws will converge to the suboptimal control.

3-D Virtual Worlds in Education: Applications, Benefits, Issues, and Opportunities

Abstract: Three-dimensional virtual world environments are providing new opportunities to develop engaging, interactive experiences in education. These virtual worlds are unique in that they allow individuals to interact with others through their avatars and with objects in the environment, and can create experiences that are not necessarily possible in the real world. To assess the impact that these virtual worlds are currently having on education, a literature review is conducted to identify current applications, benefits being realized, as well as issues faced. Based on this review, virtual world capabilities, experiences, and factors associated with educational opportunities are presented as well as gaps in meeting pedagogical objectives. Practical and research implications are then addressed. Virtual worlds are proving to provide unique educational experiences, with its potential only at the cusp of being explored.

Sequential optimization and reliability assessment for multidisciplinary systems design

Abstract: With higher reliability and safety requirements, reliability-based design has been increasingly applied in multidisciplinary design optimization (MDO). A direct integration of reliability-based design and MDO may present tremendous implementation and numerical difficulties. In this work, a methodology of sequential optimization and reliability assessment for MDO is proposed to improve the efficiency of reliability-based MDO. The central idea is to decouple the reliability analysis from MDO with sequential cycles of reliability analysis and deterministic MDO. The reliability analysis is based on the first-order reliability method (FORM). In the proposed method, the reliability analysis and the deterministic MDO use two MDO strategies, the multidisciplinary feasible approach and the individual disciplinary feasible approach. The effectiveness of the proposed method is illustrated with two example problems.

Freeze casting of porous hydroxyapatite scaffolds. I. Processing and general microstructure.

Abstract: Freeze casting of aqueous suspensions on a cold substrate was investigated as a method for preparing hydroxyapatite (HA) scaffolds with unidirectional porosity. In the present paper, we report on the ability to manipulate the microstructure of freeze-cast constructs by controlling the processing parameters. Constructs prepared from aqueous suspensions (5-20 volume percent particles) on a steel substrate at -20 degrees C had a lamellar-type microstructure, consisting of plate-like HA and unidirectional pores oriented in the direction of freezing. Sintering for 3 h at 1350 degrees C produced constructs with dense HA lamellas, porosity of approximately 50%, and inter-lamellar pore widths of 5-30 microm. The thickness of the HA lamellas decreased but the width of the pores increased with decreasing particle concentration. Decreasing the substrate temperature from -20 degrees C to -196 degrees C produced a finer lamellar microstructure. The use of water-glycerol mixtures (20 wt % glycerol) as the solvent in the suspension resulted in the production of finer pores (1-10 microm) and a larger number of dendritic growth connecting the HA lamellas. On the other hand, the use of water-dioxane mixtures (60 wt % dioxane) produced a cellular-type microstructure with larger pores (90-110 microm). The ability to produce a uniaxial microstructure and its manipulation by controlling the processing parameters indicate the potential of the present freeze casting route for the production of scaffolds for bone tissue engineering applications.

Smart Structures: Innovative Systems for Seismic Response Control

Abstract: Preface Acknowledgements About the Authors Basic Concept of Smart Structure Systems Introduction Basic Principles of Smart Structure Technology for Seismic Response Control History of Smart Structure Technology for Seismic Response Control Base Isolation Systems Passive Energy Dissipation Systems Semi-Active Damper Systems Active Control Systems Hybrid Control Systems Base Isolation Systems Basic Concepts of Seismically Isolated Building Structures Base Isolator Mechanical Characteristics and Computer Modeling Techniques Code Requirements for Design of Seismically Isolated Structures Dynamic Analysis Procedure Design Examples Testing Verification and Determination of Isolator Properties Damping Systems Basic Concepts of Building Structures with Damping Systems Analysis Procedures and Code Requirements Design Examples Testing Verification and Determination of Damping Device Properties Smart Seismic Structures Using Active Control Systems Analytical Model of Smart Seismic Structures with Active Control Classical Optimal Control Algorithms for Smart Seismic Structures Development of Active Control Algorithms for Seismic Smart Structures Concluding Remarks Smart Seismic Structures Using Semiactive and Hybrid Control Systems Dynamic Model of Control Devices for Semiactive and Hybrid Systems Dynamic Model of Smart Seismic Structures with Semiactive or Hybrid Control Control Strategy and System Stability Effectiveness of HDABC System for Seismic Response Control Implementation of Hybrid Control for Smart Seismic Structures Sensing and Data Acquisition Systems for Smart Seismic Structures Common Sensors for Smart Seismic Structures Sensing, Data Acquisition, and Digital Control Systems Seismic Observer Technique Optimal Device Placement for Smart Seismic Structures Introduction Optimal Actuator Placement for Smart Seismic Structures with Active Control Statistical Method for Optimal Device Placement of Smart Seismic Structures Summary Active Control Considering Soil-Structure Interaction Motion Equation of Actively Controlled Structure with Soil-Structure Interaction State Equation of SSI-Model and Solution Technique Generalized Optimal Active Control Algorithm for the SSI System Soil Properties and Wave Equations Stiffness Coefficients of Horizontal Layer and Half Plane Dynamic-Stiffness Matrices of Ground System Numerical Illustrations Computer Solutions for Building Structures with and without Control Summary and Concluding Remarks Hybrid Control of Structures on Shallow Foundation with Existing and Generated Earthquakes Introduction Structural Formulation with HDABC State Space Formulation of HDABC Systems with and without SSI Numerical Examples Using MATLAB Extreme Value Distribution Ground Motion Generation Case Studies Using Generated Earthquakes Concluding Remarks Appendix A: MATLAB Appendix B: Green's Function Appendix C: Element Stiffness and Mass Coefficients

Comparison of ultracapacitor electric circuit models

Abstract: Due to ultracapacitorspsila unique features, the electrical performances and reliabilities of electrical systems using ultracapacitors can be improved. It is important to have a good ultracapacitor model for simulation and assisting electrical system design and product development. Several kinds of ultracapacitor models are given these years. Especially, electric circuit models are the interested ones for electrical engineers. This paper concentrates on the electric circuit model. Three basic RC network models are discussed in detail, including modeling ideas, circuit formation, linear/nonlinear factors and evaluations of each model. The general electric circuit model considering the inductance and leakage current effects are given. Model selection depends on the specific applications of ultracapacitor. Based on the analysis in this paper, recommendations of ultracapacitor selection strategies are provided.