Measurement-based Method for Wind Farm Power System Oscillations Monitoring

The global increase in the penetration of renewable energy is pushing electrical power systems into uncharted territory, especially in terms of transient and dynamic stability. In particular, the greater penetration of wind generation in European power networks is, at times, displacing a significant capacity of conventional synchronous generation with fixed-speed induction generation and now more commonly, doubly fed induction generators. The impact of such changes in the generation mix requires careful monitoring to assess the impact on transient and dynamic stability. This study presents a measurement-based method for the early detection of power system oscillations, with consideration of mode damping, in order to raise alarms and develop strategies to actively improve power system dynamic stability and security. A method is developed based on wavelet-based support vector data description (SVDD) to detect oscillation modes in wind farm output power, which may excite dynamic instabilities in the wider system. The wavelet transform is used as a filter to identify oscillations in frequency bands, whereas the SVDD method is used to extract dominant features from different scales and generate an assessment boundary according to the extracted features. Poorly damped oscillations of a large magnitude, or that are resonant, can be alarmed to the system operator, to reduce the risk of system instability. The proposed method is exemplified using measured data from a chosen wind farm site.

Modelling the mechanical response of the reed-mouthpiece-lip system of a clarinet. Part II: A lumped model approximation

A non-linear lumped model of the reed-mouthpiece-lip system of a clarinet is formulated, in which the lumped parameters are derived from numerical experiments with a finite-difference simulation based on a distributed reed model. The effective stiffness per unit area is formulated as a function of the pressure signal driving the reed, in order to simulate the effects of the reed bending against the lay, and mass and damping terms are added as a first approximation to the dynamic behaviour of the reed. A discrete-time formulation is presented, and its response is compared to that of the distributed model. In addition, the lumped model is applied in the simulation of clarinet tones, enabling the analysis of the effects of using a pressure-dependent stiffness per unit area on sustained oscillations. The analysed effects and features are in qualitative agreement with players' experiences and experimental results obtained in prior studies.

Digital Musical Interactions: Performer-System Relationships and their Perception by Spectators

This article adopts an ecological view of digital musical interactions, first considering the relationship between performers and digital systems, and then spectators’ perception of these interactions. We provide evidence that the relationships between performers and digital music systems are not necessarily instrumental in the same was as they are with acoustic systems, and nor should they always strive to be. Furthermore, we report results of a study suggesting that spectators may not perceive such interactions in the same way as performances with musical instruments. We present implications for the design of digital musical interactions, suggesting that designers should embrace the reality that digital systems are malleable and dynamic, and may engage performers and spectators in different modalities, sometimes simultaneously.

Automated nonlinear system modelling with multiple neural networks

This article discusses the identification of nonlinear dynamic systems using multi-layer perceptrons (MLPs). It focuses on both structure uncertainty and parameter uncertainty, which have been widely explored in the literature of nonlinear system identification. The main contribution is that an integrated analytic framework is proposed for automated neural network structure selection, parameter identification and hysteresis network switching with guaranteed neural identification performance. First, an automated network structure selection procedure is proposed within a fixed time interval for a given network construction criterion. Then, the network parameter updating algorithm is proposed with guaranteed bounded identification error. To cope with structure uncertainty, a hysteresis strategy is proposed to enable neural identifier switching with guaranteed network performance along the switching process. Both theoretic analysis and a simulation example show the efficacy of the proposed method.

Dynamic Linear Precoding for the Exploitation of Known Interference in MIMO Broadcast Systems

This paper introduces a novel channel inversion (CI) precoding scheme for the downlink of phase shift keying (PSK)-based multiple input multiple output (MIMO) systems. In contrast to common practice where knowledge of the interference is used to eliminate it, the main idea proposed here is to use this knowledge to glean benefit from the interference. It will be shown that the system performance can be enhanced by exploiting some of the existent inter-channel interference (ICI). This is achieved by applying partial channel inversion such that the constructive part of ICI is preserved and exploited while the destructive part is eliminated by means of CI precoding. By doing so, the effective signal to interference-plus-noise ratio (SINR) delivered to the mobile unit (MU) receivers is enhanced without the need to invest additional transmitted signal power at the MIMO base station (BS). It is shown that the trade-off to this benefit is a minor increase in the complexity of the BS processing. The presented theoretical analysis and simulations demonstrate that due to the SINR enhancement, significant performance and throughput gains are offered by the proposed MIMO precoding technique compared to its conventional counterparts.

Dynamic pricing for used products in remanufacturing with back orders(ABS 3* Journal, Accepted with Revision on 2nd December 2011).

In remanufacturing, the supply of used products and the demand for remanufactured products are usually mismatched because of the great uncertainties on both sides. In this paper, we propose a dynamic pricing policy to balance this uncertain supply and demand. Specifically, we study a remanufacturer’s problem of pricing a single class of cores with random price-dependent returns and random demand for the remanufactured products with backlogs. We model this pricing task as a continuous-time Markov decision process, which addresses both the finite and infinite horizon problems, and provide managerial insights by analyzing the structural properties of the optimal policy. We then use several computational examples to illustrate the impacts of particular system parameters on pricing policy.

A Theoretical and Experimental Study of Resonance in a High Performance Engine Intake System: Part 1

The unsteady gas dynamic phenomena in engine intake systems of the type found in racecars have been examined. In particular, the resonant tuning effects, including cylinder-to-cylinder power variations, which can occur as a result of the interaction between an engine and its airbox have been considered. Frequency analysis of the output from a Virtual 4-Stroke 1D engine simulation was used to characterise the forcing function applied by an engine to an airbox. A separate computational frequency sweeping technique, which employed the CFD package FLUENT, was used to determine the natural frequencies of virtual airboxes in isolation from an engine. Using this technique, an airbox with a natural frequency at 75 Hz was designed for a Yamaha R6 4-cylinder motorcycle engine. The existence of an airbox natural frequency at 75 Hz was subsequently confirmed by an experimental frequency sweeping technique carried out on the engine test bed. A coupled 1D/3D analysis which employed the engine simulation package Virtual 4-Stroke and the CFD package FLUENT, was used to model the combined engine and airbox system. The coupled 1D/3D analysis predicted a 75 Hz resonance of the airbox at an engine speed of 9000 rpm. This frequency was the induction frequency for a single cylinder. An airbox was fabricated and tested on the engine. Static pressure was recorded at a grid of points in the airbox as the engine was swept through a speed range of 3000 to 10000 rpm. The measured engine speed corresponding to resonance in the airbox agreed well with the predicted values. There was also good correlation between the amplitude and phase of the pressure traces recorded within the airbox and the 1D/3D predictions.

Nuclear activation as a high dynamic range diagnostic of laser-plasma interactions

Proton imaging has become a common diagnostic technique for use in laser-plasma research experiments due to their ability to diagnose electric field effects and to resolve small density differences caused through shock effects. These interactions are highly dependent on the use of radiochromic film (RCF) as a detection system for the particle probe, and produces very high-resolution images. However, saturation effects, and in many cases, damage to the film limits the usefulness of this technique for high-flux particle probing. This paper outlines the use of a new technique using contact radiography of (p,n)-generated isotopes in activation samples to produce high dynamic range 2D images with high spatial resolution and extremely high dynamic range, whilst maintaining both energy resolution and absolute flux measurements. (C)007 Elsevier B.V. All rights reserved.

Real-space mapping of dynamic phenomena during hysteresis loop measurements: Dynamic switching spectroscopy piezoresponse force microscopy

Dynamic switching spectroscopy piezoresponse force microscopy is developed to separate thermodynamic and kinetic effects in local bias-induced phase transitions. The approaches for visualization and analysis of five-dimensional data are discussed. The spatial and voltage variability of relaxation behavior of the a-c domain lead zirconate-titanate surface suggest the interpretation in terms of surface charge dynamics. This approach is applicable to local studies of dynamic behavior in any system with reversible bias-induced phase transitions ranging from ferroelectrics and multiferroics to ionic systems such as batteries, fuel cells, and electroresistive materials. (C) 2011 American Institute of Physics. [doi:10.1063/1.3590919]

A Theoretical and Experimental Study of Resonance in a High Performance Engine Intake System: Part 2

The unsteady gas dynamic phenomena in a racecar airbox have been examined, and resonant tuning effects have been considered. A coupled 1D/3D analysis, using the engine simulation package Virtual 4-Stroke and the CFD package FLUENT, was used to model the engine and airbox. The models were experimentally validated. An airbox was designed with a natural frequency in the region of 75 Hz. A coupled 1D/3D analysis of the airbox and a Yamaha R6 4 cylinder engine predicted resonance at the single-cylinder induction frequency; 75 Hz at an engine speed of 9000 rpm.

Addressing Selective Polypharmacology of Antipsychotic Drugs Targeting the Bioaminergic Receptors through the Receptor Dynamic Conformational Ensembles

Selective polypharmacology, where a drug acts on multiple rather than single molecular targets involved in a disease, emerges to develop a structure-based system biology approach to design drugs selectively targeting a disease-active protein network. We focus on the bioaminergic receptors that belong to the group of integral membrane signalling proteins coupled to the G protein and represent targets for therapeutic agents against schizophrenia and depression. Among them, it has been shown that the serotonin (5-HT2A and 5-HT6), dopamine (D2 and D3) receptors induce a cognition-enhancing effect (group 1), while the histamine (H1) and serotonin (5-HT2C) receptors lead to metabolic side effects and the 5-HT2B serotonin receptor causes pulmonary hypertension (group 2). Thus, the problem arises to develop an approach that allows identifying drugs targeting only the disease-active receptors, i.e. group 1. The recent release of several crystal structures of the bioaminergic receptors, involving the D3 and H1 receptors provides the possibility to model the structures of all receptors and initiate a study of the structural and dynamic context of selective polypharmacology. In this work, we use molecular dynamics simulations to generate a conformational space of the receptors and subsequently characterize its binding properties applying molecular probe mapping. All-against-all comparison of the generated probe maps of the selected diverse conformations of all receptors with the Tanimoto similarity coefficient (Tc) enable to separate the receptors of group 1 from group 2. The pharmacophore built based on the Tc-selected receptor conformations, using the multiple probe maps discovers structural features that can be used to design molecules selective towards the receptors of group 1. The importance of several predicted residues to ligand selectivity is supported by the available mutagenesis and ligand structure-activity relationships studies. In addition, the Tc-selected conformations of the receptors for group 1 show good performance in isolation of known ligands from a random decoy. Our computational structure-based protocol to tackle selective polypharmacology of antipsychotic drugs could be applied for other diseases involving multiple drug targets, such as oncologic and infectious disorders.

BDDT: Block-level Dynamic Dependence Analysis for Task-Based Parallelism

We present BDDT, a task-parallel runtime system that dynamically discovers and resolves dependencies among parallel tasks. BDDT allows the programmer to specify detailed task footprints on any memory address range, multidimensional array tile or dynamic region. BDDT uses a block-based dependence analysis with arbitrary granularity. The analysis is applicable to existing C programs without having to restructure object or array allocation, and provides flexibility in array layouts and tile dimensions.
We evaluate BDDT using a representative set of benchmarks, and we compare it to SMPSs (the equivalent runtime system in StarSs) and OpenMP. BDDT performs comparable to or better than SMPSs and is able to cope with task granularity as much as one order of magnitude finer than SMPSs. Compared to OpenMP, BDDT performs up to 3.9× better for benchmarks that benefit from dynamic dependence analysis. BDDT provides additional data annotations to bypass dependence analysis. Using these annotations, BDDT outperforms OpenMP also in benchmarks where dependence analysis does not discover additional parallelism, thanks to a more efficient implementation of the runtime system.

Multi-detection of Paralytic, Diarrheic and Amnesic Shellfish Toxins by an Inhibition Immunoassay Using a Microsphere-Flow Cytometry System

The presence of paralytic shellfish poisoning (PSP), diarrheic shellfish poisoning (DSP) and amnesic shellfish poisoning (ASP) toxins in seafood is a severe and growing threat to human health. In order to minimize the risks of human exposure, the maximum content of these toxins in seafood has been limited by legal regulations worldwide. The regulated limits are established in equivalents of the main representatives of the groups: saxitoxin (STX), okadaic acid (OA) and domoic acid (DA), for PSP, DSP and ASP, respectively. In this study a multi-detection method to screen shellfish samples for the presence of these toxins simultaneously was developed. Multiplexing was achieved using a solid-phase microsphere assay coupled to flow-fluorimetry detection, based on the Luminex xMap technology. The multi-detection method consists of three simultaneous competition immunoassays. Free toxins in solution compete with STX, OA or DA immobilized on the surface of three different classes of microspheres for binding to specific monoclonal antibodies. The IC50 obtained in buffer was similar in single- and multi-detection: 5.6 ± 1.1 ng/mL for STX, 1.1 ± 0.03 ng/mL for OA and 1.9 ± 0.1 ng/mL for DA. The sample preparation protocol was optimized for the simultaneous extraction of STX, OA and DA with a mixture of methanol and acetate buffer. The three immunoassays performed well with mussel and scallop matrixes displaying adequate dynamic ranges and recovery rates (around 90 % for STX, 80 % for OA and 100 % for DA). This microsphere-based multi-detection immunoassay provides an easy and rapid screening method capable of detecting simultaneously in the same sample three regulated groups of marine toxins.

Investigating autonomic control of the cardiovascular system: a battery of simple tests

Sympathetic and parasympathetic divisions of the autonomic nervous system constantly control the heart (sympathetic and parasympathetic divisions) and blood vessels (predominantly the sympathetic division) to maintain appropriate blood pressure and organ blood flow over sometimes widely varying conditions. This can be adversely affected by pathological conditions that can damage one or both branches of autonomic control. The set of teaching laboratory activities outlined here uses various interventions, namely, 1) the heart rate response to deep breathing, 2) the heart rate response to a Valsalva maneuver, 3) the heart rate response to standing, and 4) the blood pressure response to standing, that cause fairly predictable disturbances in cardiovascular parameters in normal circumstances, which serve to demonstrate the dynamic control of the cardiovascular system by autonomic nerves. These tests are also used clinically to help investigate potential damage to this control.

Dynamic Buffer Management for Multimedia Services in Beyond 3G Wireless Networks

This paper investigates a dynamic buffer man-agement scheme for QoS control of multimedia services in be-yond 3G wireless systems. The scheme is studied in the context of the state-of-the-art 3.5G system i.e. the High Speed Downlink Packet Access (HSDPA) which enhances 3G UMTS to support high-speed packet switched services. Unlike earlier systems, UMTS-evolved systems from HSDPA and beyond incorporate mechanisms such as packet scheduling and HARQ in the base station necessitating data buffering at the air interface. This introduces a potential bottleneck to end-to-end communication. Hence, buffer management at the air interface is crucial for end-to-end QoS support of multimedia services with multi-plexed parallel diverse flows such as video and data in the same end-user session. The dynamic buffer management scheme for HSDPA multimedia sessions with aggregated real-time and non real-time flows is investigated via extensive HSDPA simulations. The impact of the scheme on end-to-end traffic performance is evaluated with an example multimedia session comprising a real-time streaming flow concurrent with TCP-based non real-time flow. Results demonstrate that the scheme can guar-antee the end-to-end QoS of the real-time streaming flow, whilst simultaneously protecting the non real-time flow from starva-tion resulting in improved end-to-end throughput performance