A vibrational spectroscopic study of the phosphate mineral lulzacite Sr2Fe2+(Fe2+,Mg)2Al4(PO4)4(OH)10

The mineral lulzacite from Saint-Aubin des Chateaux mine, France, with theoretical formula Sr2Fe2+(Fe2+,Mg)2Al4(PO4)4(OH)10 has been studied using a combination of electron microscopy with EDX and vibrational spectroscopic techniques. Chemical analysis shows a Sr, Fe, Al phosphate with minor amounts of Ga, Ba and Mg. Raman spectroscopy identifies an intense band at 990 cm�1 with an additional band at 1011 cm�1. These bands are attributed to the PO3� 4 m1 symmetric stretching mode. The m3 antisymmetric stretching modes are observed by a large number of Raman bands. The Raman bands at 1034, 1051, 1058, 1069 and 1084 together with the Raman bands at 1098, 1116, 1133, 1155 and 1174 cm�1 are assigned to the m3 antisymmetric stretching vibrations of PO3� 4 and the HOPO2� 3 units. The observation of these multiple Raman bands in the symmetric and antisymmetric stretching region gives credence to the concept that both phosphate and hydrogen phosphate units exist in the structure of lulzacite. The series of Raman bands at 567, 582, 601, 644, 661, 673 and 687 cm�1 are assigned to the PO3� 4 m2 bending modes. The series of Raman bands at 437, 468, 478, 491, 503 cm�1 are attributed to the PO3� 4 and HOPO2� 3 m4 bending modes. No Raman bands of lulzacite which could be attributed to the hydroxyl stretching unit were observed. Infrared bands at 3511 and 3359 cm�1 are ascribed to the OH stretching vibration of the OH units. Very broad bands at 3022 and 3299 cm�1 are attributed to the OH stretching vibrations of water. Vibrational spectroscopy offers insights into the molecular structure of the phosphate mineral lulzacite.

Hybrid genetic algorithm for elimination of severe stress concentration in railhead ends

This paper presents a computational method for eliminating severe stress concentration at the unsupported railhead ends in rail joints through innovative shape optimization of the contact zone, which is complex due to near field nonlinear contact. With a view to minimizing the computational efforts, hybrid genetic algorithm method coupled with parametric finite element has been developed and compared with the traditional genetic algorithm (GA). The shape of railhead top surface where the wheel contacts nonlinearly was optimized using the hybridized GA method. Comparative study of the optimal result and the search efficiency between the traditional and hybrid GA methods has shown that the hybridized GA provides the optimal shape in fewer computational cycles without losing accuracy. The method will be beneficial to solving complex engineering problems involving contact nonlinearity.

From nucleation to nanowires : a single-step process in reactive plasmas

This feature article introduces a deterministic approach for the rapid, single-step, direct synthesis of metal oxide nanowires. This approach is based on the exposure of thin metal samples to reactive oxygen plasmas and does not require any intervening processing or external substrate heating. The critical roles of the reactive oxygen plasmas, surface processes, and plasma-surface interactions that enable this growth are critically examined by using a deterministic viewpoint. The essentials of the experimental procedures and reactor design are presented and related to the key process requirements. The nucleation and growth kinetics is discussed for typical solid-liquid-solid and vapor-solid-solid mechanisms related to the synthesis of the oxide nanowires of metals with low (Ga, Cd) and high (Fe) melting points, respectively. Numerical simulations are focused on the possibility to predict the nanowire nucleation points through the interaction of the plasma radicals and ions with the nanoscale morphological features on the surface, as well as to control the localized 'hot spots' that in turn determine the nanowire size and shape. This generic approach can be applied to virtually any oxide nanoscale system and further confirms the applicability of the plasma nanoscience approaches for deterministic nanoscale synthesis and processing.

Grid-side cascade inverter system as an interface for wind energy storage

Additional converters that are used to interface energy storage devices incur power losses as well as increased system cost and complexity. The need for additional converters can be eliminated if the grid side inverter can itself be effectively used as the interface for energy storage. This paper therefore proposes a technique whereby the grid side inverter can also be used as an interface to connect a supercapacitor energy storage for wind energy conversion systems. The proposed grid side inverter is formed by cascading a 3-level inverter and a 2-level inverter through a coupling transformer. The three-level inverter is the main inverter and it is powered by the rectified output of the wind turbine coupled AC generator while the 2-level auxiliary inverter is connected to the super capacitor bank that is used to compensate short term power fluctuations. Novel modulation and control techniques are proposed to address the problems associated with non-integer and dynamically-changing dc-link voltage ratio, which is caused by the random nature of wind. Simulation results are presented to verify the efficacy of the proposed system in suppressing short term wind power fluctuations.

A Battery Energy Storage interface for wind power systems with the use of grid side inverter

This paper presents a novel concept of Energy Storage System (ESS) interfacing with the grid side inverter in wind energy conversion systems. The inverter system used here is formed by cascading a 2-level inverter and a three level inverter through a coupling transformer. The constituent inverters are named as the “main inverter” and the “auxiliary inverter” respectively. The main inverter is connected with the rectified output of the wind generator while the auxiliary inverter is attached to a Battery Energy Storage System (BESS). The BESS ensures constant power dispatch to the grid irrespective of change in wind condition. Furthermore, this unique combination of BESS and inverter eliminates the need of additional dc-dc converters. Novel modulation and control techniques are proposed to address the problem of non-integer, dynamically-changing dc-link voltage ratio, which is due to random wind changes. Strategies used to handle auxiliary inverter dc-link voltage imbalances and controllers used to charge batteries at different rates are explained in detail. Simulation results are presented to verify the efficacy of the proposed modulation and control techniques in suppressing random wind power fluctuations.

A business perspective of legacy systems

Abstract Legacy information systems evolved incrementally in response to changes in business strategy and information technology. Organizations are now being forced to change much more radically and quickly than previously and this change places new demands on information systems. Legacy information systems are usually considered from a technical perspective, addressing issues such as age, complexity, maintainability, design and technology. We wish to demonstrate that the business dimension to legacy information systems, represented by the organisation structure, business processes and procedures that are bound up in the design and operation of the existing IT systems, is also significant. This paper identifies the important role of legacy information systems in the formation of new strategies. We show that the move away from a stable to an unstable business environment accelerates the rate of change. Furthermore, the gap between what the legacy information systems can deliver and the strategic vision of the organization widens when the legacy information systems are unable to adapt to meet the new requirements. An analysis of fifteen case studies provides evidence that legacy information systems include business and technical dimensions and that the systems can present problems when there is a misalignment between the strategic vision of the business, the IT legacy and the old business model embodied in the legacy.

Building energy simulation and parallel computing : opportunities and challenges

Increased focus on energy cost savings and carbon footprint reduction efforts improved the visibility of building energy simulation, which became a mandatory requirement of several building rating systems. Despite developments in building energy simulation algorithms and user interfaces, there are some major challenges associated with building energy simulation; an important one is the computational demands and processing time. In this paper, we analyze the opportunities and challenges associated with this topic while executing a set of 275 parametric energy models simultaneously in EnergyPlus using a High Performance Computing (HPC) cluster. Successful parallel computing implementation of building energy simulations will not only improve the time necessary to get the results and enable scenario development for different design considerations, but also might enable Dynamic-Building Information Modeling (BIM) integration and near real-time decision-making. This paper concludes with the discussions on future directions and opportunities associated with building energy modeling simulations.

Hardware design and implementation of a MAVLink interface for an FPGA-based autonomous UAV flight control system

This paper details the initial design and planning of a Field Programmable Gate Array (FPGA) implemented control system that will enable a path planner to interact with a MAVLink based flight computer. The design is aimed at small Unmanned Aircraft Vehicles (UAV) under autonomous operation which are typically subject to constraints arising from limited on-board processing capabilities, power and size. An FPGA implementation for the de- sign is chosen for its potential to address such limitations through low power and high speed in-hardware computation. The MAVLink protocol offers a low bandwidth interface for the FPGA implemented path planner to communicate with an on-board flight computer. A control system plan is presented that is capable of accepting a string of GPS waypoints generated on-board from a previously developed in- hardware Genetic Algorithm (GA) path planner and feeding them to the open source PX4 autopilot, while simultaneously respond- ing with flight status information.

Reliable Fault Diagnosis for Low-Speed Bearings Using Individually Trained Support Vector Machines With Kernel Discriminative Feature Analysis

This paper proposes a highly reliable fault diagnosis approach for low-speed bearings. The proposed approach first extracts wavelet-based fault features that represent diverse symptoms of multiple low-speed bearing defects. The most useful fault features for diagnosis are then selected by utilizing a genetic algorithm (GA)-based kernel discriminative feature analysis cooperating with one-against-all multicategory support vector machines (OAA MCSVMs). Finally, each support vector machine is individually trained with its own feature vector that includes the most discriminative fault features, offering the highest classification performance. In this study, the effectiveness of the proposed GA-based kernel discriminative feature analysis and the classification ability of individually trained OAA MCSVMs are addressed in terms of average classification accuracy. In addition, the proposedGA- based kernel discriminative feature analysis is compared with four other state-of-the-art feature analysis approaches. Experimental results indicate that the proposed approach is superior to other feature analysis methodologies, yielding an average classification accuracy of 98.06% and 94.49% under rotational speeds of 50 revolutions-per-minute (RPM) and 80 RPM, respectively. Furthermore, the individually trained MCSVMs with their own optimal fault features based on the proposed GA-based kernel discriminative feature analysis outperform the standard OAA MCSVMs, showing an average accuracy of 98.66% and 95.01% for bearings under rotational speeds of 50 RPM and 80 RPM, respectively.

Dual-functional gum arabic binder for silicon anodes in lithium ion batteries

Si has attracted enormous research and manufacturing attention as an anode material for lithium ion batteries (LIBs) because of its high specific capacity. The lack of a low cost and effective mechanism to prevent the pulverization of Si electrodes during the lithiation/ delithiation process has been a major barrier in the mass production of Si anodes. Naturally abundant gum arabic (GA), composed of polysaccharides and glycoproteins, is applied as a dualfunction binder to address this dilemma. Firstly, the hydroxyl groups of the polysaccharide in GA are crucial in ensuring strong binding to Si. Secondly, similar to the function of fiber in fiberreinforced concrete (FRC), the long chain glycoproteins provide further mechanical tolerance to dramatic volume expansion by Si nanoparticles. The resultant Si anodes present an outstanding capacity of ca. 2000 mAh/g at a 1 C rate and 1000 mAh/g at 2 C rate, respectively, throughout 500 cycles. Excellent long-term stability is demonstrated by the maintenance of 1000 mAh/g specific capacity at 1 C rate for over 1000 cycles. This low cost, naturally abundant and environmentally benign polymer is a promising binder for LIBs in the future.

Systematic constellations of neurons are activated in lateral amygdala following Pavlovian fear conditioning

How memory is organized within neural networks is a fundamental question in neuroscience. We used Pavlovian fear conditioning to study the discrete organization patterns of neurons activated in an associative memory paradigm. In Pavlovian fear conditioning a neutral stimulus, such as an auditory tone, is temporally paired with an aversive unconditioned stimulus (US), such as a foot shock...

Afferent specific regulation of cortical and subcortical synaptic input to the lateral amygdala by norepinephrine

The lateral amygdala (LA) has been extensively implicated in the neurobiology of conditioned fear paradigms. Norepinepherine (NE), especially its beta receptors, has been implicated in consolidation, reconsolidation and extinction of fear memories, and has been proposed as a potential treatment for PTSD (Berlau and McGaugh, NLM, 2006; Debiec and LeDoux, N, 2005)...

A recurrent network in the lateral amygdala: A mechanism for temporal coincidence detection

The dorsal lateral amygdala (LAd) is a vital nucleus for the formation of associations between aversive unconditioned stimuli (US) and neutral stimuli, such as auditory tones, which can become conditioned (CS) to the US through temporal pairing. Important aspects of CS-US associations are believed to occur within the LAd, however relatively little is known about the temporal behavior of local LAd networks. Information about the CS and US enters the LA via a rapid and direct thalamic input and a longer latency cortical path...

Different approaches of applying single-objective binary genetic algorithm on the wind farm design

This paper discusses three different ways of applying the single-objective binary genetic algorithm into designing the wind farm. The introduction of different applications is through altering the binary encoding methods in GA codes. The first encoding method is the traditional one with fixed wind turbine positions. The second involves varying the initial positions from results of the first method, and it is achieved by using binary digits to represent the coordination of wind turbine on X or Y axis. The third is the mixing of the first encoding method with another one, which is by adding four more binary digits to represent one of the unavailable plots. The goal of this paper is to demonstrate how the single-objective binary algorithm can be applied and how the wind turbines are distributed under various conditions with best fitness. The main emphasis of discussion is focused on the scenario of wind direction varying from 0° to 45°. Results show that choosing the appropriate position of wind turbines is more significant than choosing the wind turbine numbers, considering that the former has a bigger influence on the whole farm fitness than the latter. And the farm has best performance of fitness values, farm efficiency, and total power with the direction between 20°to 30°.

Structural identification of a laboratory-based steel through truss cantilevered bridge with suspended span using a layered genetic algorithm with patternsearch step (GAPS)

Structural identification (St-Id) can be considered as the process of updating a finite element (FE) model of a structural system to match the measured response of the structure. This paper presents the St-Id of a laboratory-based steel through-truss cantilevered bridge with suspended span. There are a total of 600 degrees of freedom (DOFs) in the superstructure plus additional DOFs in the substructure. The St-Id of the bridge model used the modal parameters from a preliminary modal test in the objective function of a global optimisation technique using a layered genetic algorithm with patternsearch step (GAPS). Each layer of the St-Id process involved grouping of the structural parameters into a number of updating parameters and running parallel optimisations. The number of updating parameters was increased at each layer of the process. In order to accelerate the optimisation and ensure improved diversity within the population, a patternsearch step was applied to the fittest individuals at the end of each generation of the GA. The GAPS process was able to replicate the mode shapes for the first two lateral sway modes and the first vertical bending mode to a high degree of accuracy and, to a lesser degree, the mode shape of the first lateral bending mode. The mode shape and frequency of the torsional mode did not match very well. The frequencies of the first lateral bending mode, the first longitudinal mode and the first vertical mode matched very well. The frequency of the first sway mode was lower and that of the second sway mode was higher than the true values, indicating a possible problem with the FE model. Improvements to the model and the St-Id process will be presented at the upcoming conference and compared to the results presented in this paper. These improvements will include the use of multiple FE models in a multi-layered, multi-solution, GAPS St-Id approach.