Integration of PV system with SMES based on model predictive control for utility grid reliability improvement.

This paper describes the integration of a photovoltaic (PV) renewable energy source with a superconducting magnetic energy storage (SMES) system. The integrated system can improve the voltage stability of the utility grid and achieve power leveling. The control schemes employ model predictive control (MPC), which has gained significant attention in recent years because of its advantages such as fast response and simple implementation. The PV system provides maximum power at various irradiation levels using the incremental conductance technique (INC). The interfaced grid side converter of the SMES can control the grid voltage by regulating its injected reactive power to the grid, while the charge and discharge operation of the SMES coil can be managed by the system operator to inject/absorb active power to/from the grid to achieve the power leveling strategy. Simulation results based on MATLAB/Simulink® software prove the fast response of the system control objectives in tracking the setpoints at different loading scenarios and PV irradiance levels, while the SMES injects/absorbs active and reactive power to/from the grid during various events to improve the voltage response and achieve power leveling strategy.     

Performance of Pile-Supported Bridge Approach Slabs

A large number of pile-supported bridge approach slabs in southeastern Louisiana were examined to identify the factors that affect their long-term performance. Design drawings and subsoil conditions at these sites as well as their traffic and maintenance records were compiled, and seven representative test sites were selected for thorough field investigation that included inspection of the approach slabs, bridge decks, bridge abutments, and roadway pavement. Field evaluation included walking profiler, falling-weight deflectometer (FWD), laser profiler, geodetic survey, soil borings, cone penetrometer, and nondestructive testing. Measurements made with the walking profiler agreed well with the geodetic survey. The FWD and nondestructive testing were effectively used to detect voids under the approach slab. Results of the study indicated that the current empirical methodology used by the Louisiana Department of Transportation and Development for design of pile-supported approach slabs yields inconsistent field performance. It was concluded that this inconsistent performance is primarily due to the differences in roadway embankment design and construction and in subsoil conditions, which in turn affect the negative skin friction (downdrag) loads imparted on the piles. Impact of other variables such as ramp type, speed limit, traffic volume, and so on was found to be insignificant. Results of the field study were used to develop a new rating system for approach slabs (IRIS) based on International Roughness Index (IRI) measurements obtained with the laser profiler.     

Detecting and classifying delay Data Exceptions on communication networks using rule based algorithms

Network performance monitoring is essential for managing a network efficiently and for ensuring reliable operation of the network. Monitored network performance changes reflect events in the network, such as faults, significant changes in usage patterns or planned alterations. Network managers are interested in how and when the performance of a network changes; however it is inefficient to analyse all the data resulting from the monitoring operation manually. In this paper a rule based algorithm to automate detection of the changes in one of the network performance parameters, namely delay, is presented and described in detail. The nature of the delay pattern in a commercial communication network was the key issue in developing this algorithm. The approach was tested with monitored delay data generated from three different networks and showed good results. Also, the algorithm was tested with sets of delay data which have been already input to a previously developed detector based on a different approach, and the results between the two detectors are compared. In addition to a noticeable improvement in detection performance, the new approach provides more generality and independency of the source of the delay data, making the approach generally applicable to other networks. Copyright © 2004 John Wiley & Sons, Ltd.     

Macroblock Level Bits Allocation for Depth Maps in 3-D Video Coding

For 3-D videos, one commonly used representation method is texture videos plus depth maps for several selected viewpoints, whereas the other viewpoints are synthesized based on the available texture videos and depth maps with the depth-image-based rendering (DIBR) technique. As both the quality of the texture videos and depth maps will affect the quality of the synthesized views, bits allocation for the depth maps become indispensable. The existing bits allocation approaches are either inaccurate or requiring pre-encoding and analyzing in temporal dimension, making them unsuitable for the real-time applications. Motivated by the fact that different regions of the depth maps have different impacts on the synthesized image quality, a real-time macroblock level bits allocation approach is proposed, where different macroblocks of the depth maps are encoded with different quantization parameters and coding modes. As the bits allocation granularity is fine, the R-D performance of the proposed approach outperforms other bits allocation approaches significantly, while no additional pre-encoding delay is caused. Specifically, it can save more than 10% overall bit rate comparing with Morvan’s full search approach, while maintaining the same synthesized view quality.     

Quantification of annular flow in lined pipelines

This paper attempts to quantify the amount of flow within the annular space that could exist between a polymeric liner and a deteriorated host pipe. Inadequate fit of the liner within sewer line segments is likely to cause annular flow that will result in a higher flow rate within the wastewater collection system. The results of full-scale field tests performed by the authors on 12 pipelines lined with four different deformed/reformed or fold-and-form (DR/FF) and cured-in-place-pipe (CIPP) liner products indicated that gaps of different sizes existed in all of the tested pipelines. These gaps have resulted in variable annular flow in the tested pipelines. Based on the results of the full-scale tests, a mathematical relationship was established between the annular flow in a lined pipeline and the annular space. The relationship between the annular flow rate and the average annular gap size depends on the difference in head between the entry and exit points along the pipeline. In turn, the average annular gap size depends on many factors including tolerances and imperfections in the host pipe and liner, conditions of the host pipe and the quality of liner installation. A third-order polynomial equation was found to best describe the relationship between the annular flow and average gap size under high differential heads (up to 3.0 m or 10 ft); whereas, a logarithmic relationship fits best under low differential heads for wider range of annular gap sizes (up to 17.8 mm or 0.70 in.). Based on the results of the full-scale tests, this is believed to be more representative of typical liner installations.     

Theoretical study of the circuit architecture of the basic CFOA and testing techniques

This paper examines the closed-loop characteristics of the basic Current-Feedback Operational Amplifier (CFOA), and in particular, the dynamic response. Additionally, it also examines the design and advantages of the CFOA regarding its ability to provide a significantly constant closed-loop bandwidth for closed-loop voltage gain. Secondly, the almost limitless slew–rate provided by the class AB input stage that makes it superior to the voltage-mode operational amplifier (VOA) counterpart. Additionally, this paper also concerns the definitions and measurements of the terminal parameters of the CFOA, regarded as a ‘black box’. It does not deal with the way that these parameters are related to the properties of the active passive and active components of a particular circuit configuration. Simulation is used in terminal parameter determination: this brings with it the facility of using test conditions that would not normally prevail in a laboratory test on silicon implementations of the CFOAs. Thus, we can apply 1mA and 1mV test signals from, respectively, infinite and zero source impedances that range in frequency from d.c to some tens of GHz. Also, we assume the existence of resistors with identical Ohmic value and very high value ideal capacitors. Where appropriate, practical test methods are referred to physical laboratory prototypes.     

Determination of Stoichiometry and Superconducting Properties of Tl-1234 and (Cu0.25Tl0.75)-1234 Phases Substituted by Erbium

Superconducting samples of type TlBa₂Ca_3?y Er _y Cu₄O_11?δ and Cu_0.25Tl_0.75Ba₂Ca_3?y Er _y Cu₄O_12?δ ,y ranging from 0.0 to 0.1, have been prepared by a single step of solid-state reaction technique at normal pressure using high-purity oxide elements. The lattice parameters, for prepared samples, have been estimated from X-ray powder diffraction (XRD). The elemental stoichiometry of the prepared samples has been determined using Particle Induced X-ray Emission (PIXE), whereas the oxygen-content has been determined using elastic backscattering spectroscopy at 3 MeV proton beam. The superconducting transition temperature T _c has been determined from the electrical resistivity measurements. The data of T _c , for TlBa₂Ca_3?y Er _y Cu₄O_11?δ , show enhancement in its value from 124.5 to 128.45 K as y (Er-content) increases from 0.0 to 0.05, whereas it began to suppress with further increase in y. T _c gradually suppresses with increase of yfor Cu_0.25Tl_0.75Ba₂Ca_3?y Er _y Cu₄O_12?δ . Finally, the applied magnetic field B=0.44 T shows enlargement in the transition width. The effect of magnetic field on Tl-1234 phase is a little higher than that on (Cu_0.25Tl_0.75)-1234, indicating that the anisotropy parameter Γ for Tl-1234 is slightly higher than that for (Cu_0.25Tl_0.75)-1234.     

Nickel oxide nanoparticles grown on mesoporous carbon as an efficient electrocatalyst for urea electro-oxidation

Nickel oxide nanoparticles were formed on mesoporous carbon (NiO/MC) through precipitating nickel hydroxide species followed by post annealing treatment. The as-prepared electrocatalysts were physically characterized using XRD, Raman, EDX, SEM, TEM and HRTEM analysis techniques. Very fine nanoparticles were shown in TEM image and their chemical identity was proved in XRD pattern by three crystal indices of nickel oxide species as (111), (200) and (220). The electrocatalytic activity of NiO/MC electrocatalysts was investigated for oxidizing urea molecules in 0.5 M NaOH solution. Adding variable nickel oxide loading values during the electrocatalyst preparation method appreciably affected the obtained oxidation current density. Increasing the deposited oxide weight percentage would enhance the activity of formed nanocomposite to attain its optimum performance at the electrocatalyst containing 17.5 wt% NiO. The effect of altering urea concentration and scan rate during the oxidation process on the resultant electrocatalyst activity was studied. Chronoamperograms displayed improved steady state oxidation current density values after 1800 s revealing stable nanocatalysts. This promising electrocatalytic behavior of NiO/MC elects its application as an active component for urea electro-oxidation in many potential applications including hydrogen production, fuel cells and water purification.     

Magneto-conductivity Analysis for GdBa2Cu3O7−δ Added with Nanosized Ferrite CoFe2O4

Superconducting samples of type (CoFe₂O₄) _x GdBa₂Cu₃O_7?δ , 0.0≤x≤0.1 wt.%, have been prepared by the conventional solid-state reaction technique and characterized using X-ray powder diffraction (XRD) and the scanning electron microscope (SEM). XRD analysis indicates that the orthorhombic structure of Gd-123 is not affected by the nanosized ferrite CoFe₂O₄ addition, whereas the volume fraction of Gd-123 increases with x up to 0.01 wt.%. Nanosized ferrite CoFe₂O₄ has been prepared by Co-precipitation method with grain size about 8 nm. The temperature dependence of electrical resistivity has been measured in zero and 0.44 T magnetic fields. Magneto-conductivity data has been analyzed in terms of Aslamazov–Larkin (AL) and Maki–Thompson (MT) models for layered superconductors, considering the orbital contribution. The superconducting parameters such as the coherence lengths along ab plane ξ _ab (0) and along c-direction ξ _c (0) at 0 K, anisotropic parameter Γ and phase breaking time τ _φ at 100 K have been determined as a function of nanosized ferrite CoFe₂O₄ contents. It is found that the low nanosized CoFe₂O₄ addition contents up to x=0.01 wt.% improves the physical properties of Gd-123, while for x>0.01 wt.% these properties are deteriorated.     

Hybrid model of clustering and kernel autoassociator for reliable vehicle type classification

Automatic vehicle classification is an important area of research for intelligent transportation, traffic surveillance and security. A working image-based vehicle classification system is proposed in this paper. The first component vehicle detection is implemented by applying histogram of oriented gradient features and SVM classifier. The second component vehicle classification, which is the emphasis of this paper, is accomplished by a hybrid model composed of clustering and kernel autoassociator (KAA). The KAA model is a generalization of auto-associative networks by training to recall the inputs through kernel subspace. As an effective one-class classification strategy, KAA has been proposed to implement classification with rejection, showing balanced error–rejection trade-off. With a large number of training samples, however, the training of KAA becomes problematic due to the difficulties involved with directly creating the kernel matrix. As a solution, a hybrid model consisting of self-organizing map (SOM) and KAM has been proposed to first acquire prototypes and then construct the KAA model, which has been proven efficient in internet intrusion detection. The hybrid model is further studied in this paper, with several clustering algorithms compared, including k-mean clustering, SOM and Neural Gas. Experimental results using more than 2,500 images from four types of vehicles (bus, light truck, car and van) demonstrated the effectiveness of the hybrid model. The proposed scheme offers a performance of accuracy over $95~\%$ with a rejection rate $8~\%$ and reliability over $98~\%$ with a rejection rate of $20~\%$ . This exhibits promising potentials for real-world applications.