Numerical Investigation of Optimal Pin Actuator Location on a Supersonic Projectile

The flowfield around a supersonic projectile using a pin actuator control method has been predicted using computational fluid dynamics. It has been predicted using both viscous and inviscid methods for a number of positions. Both methods showed that an optimal longitudinal position exists. However, the inviscid model over-predicted the lateral acceleration due to the difference in shock formation around the pin between the two approaches. The optimal location was predicted independent of solver, however the higher-fidelity solver predicted lower achievable lateral accelerations. This is due to the viscous interactions caused by the pin. The effect of projectile orientation has shown that shielding the pin leads to reduced effectiveness due to the wake of the fin enveloping the pin. When the pin is exposed to onset flow, the forces achieved are increased. There is also an increase in the achievable forces and moments with increasing Mach number.

Power Stored and Quality Factors in Frequency Selective Surfaces at THz Frequencies

A study of the external, loaded and unloaded quality factors for frequency selective surfaces (FSSs) is presented. The study is focused on THz frequencies between 5 and 30 THz, where ohmic losses arising from the conductors become important. The influence of material properties, such as metal thickness, conductivity dispersion and surface roughness, is investigated. An equivalent circuit that models the FSS in the presence of ohmic losses is introduced and validated by means of full-wave results. Using both full-wave methods as well as a circuit model, the reactive energy stored in the vicinity of the FSS at resonance upon plane-wave incidence is presented. By studying a doubly periodic array of aluminium strips, it is revealed that the reactive power stored at resonance increases rapidly with increasing periodicity. Moreover, it is demonstrated that arrays with larger periodicity-and therefore less metallisation per unit area-exhibit stronger thermal absorption. Despite this absorption, arrays with higher periodicities produce higher unloaded quality factors. Finally, experimental results of a fabricated prototype operating at 14 THz are presented.

Ocular blood flow analysis detects microvascular abnormalities in impaired glucose tolerance.

Objective: Waveform analysis has been used to assess vascular resistance and predict cardiovascular events. We aimed to identify microvascular abnormalities in patients with impaired glucose tolerance (IGT) using ocular waveform analysis. The effects of pioglitazone were also assessed. Methods: Forty patients with IGT and twenty-four controls were studied. Doppler velocity recordings were obtained from the central retinal, ophthalmic and common carotid arteries, and sampled at 200 Hz. A discrete wavelet-based analysis method was employed to quantify waveforms. The resistive index (RI),was also determined. Patients with IGT were randomised to pioglitazone or placebo and measurements repeated after 12 weeks treatment. Results: In the ocular waveforms, significant differences in power spectra were observed in frequency band four (corresponding to frequencies between 6.25 and 12.50 Hz) between groups (p

Nonlinear time series prediction based on a power-law noise model

In this paper we investigate the influence of a power-law noise model, also called noise, on the performance of a feed-forward neural network used to predict time series. We introduce an optimization procedure that optimizes the parameters the neural networks by maximizing the likelihood function based on the power-law model. We show that our optimization procedure minimizes the mean squared leading to an optimal prediction. Further, we present numerical results applying method to time series from the logistic map and the annual number of sunspots demonstrate that a power-law noise model gives better results than a Gaussian model.

Prediction-Based Power-Performance Adaptation of Multithreaded Scientific Codes

Computing has recently reached an inflection point with the introduction of multicore processors. On-chip thread-level parallelism is doubling approximately every other year. Concurrency lends itself naturally to allowing a program to trade performance for power savings by regulating the number of active cores; however, in several domains, users are unwilling to sacrifice performance to save power. We present a prediction model for identifying energy-efficient operating points of concurrency in well-tuned multithreaded scientific applications and a runtime system that uses live program analysis to optimize applications dynamically. We describe a dynamic phase-aware performance prediction model that combines multivariate regression techniques with runtime analysis of data collected from hardware event counters to locate optimal operating points of concurrency. Using our model, we develop a prediction-driven phase-aware runtime optimization scheme that throttles concurrency so that power consumption can be reduced and performance can be set at the knee of the scalability curve of each program phase. The use of prediction reduces the overhead of searching the optimization space while achieving near-optimal performance and power savings. A thorough evaluation of our approach shows a reduction in power consumption of 10.8 percent, simultaneous with an improvement in performance of 17.9 percent, resulting in energy savings of 26.7 percent.

Assessment Method for a Power Analysis to Identify Differentially Expressed Pathways

Gene expression data can provide a very rich source of information for elucidating the biological function on the pathway level if the experimental design considers the needs of the statistical analysis methods. The purpose of this paper is to provide a comparative analysis of statistical methods for detecting the differentially expression of pathways (DEP). In contrast to many other studies conducted so far, we use three novel simulation types, producing a more realistic correlation structure than previous simulation methods. This includes also the generation of surrogate data from two large-scale microarray experiments from prostate cancer and ALL. As a result from our comprehensive analysis of 41,004 parameter configurations, we find that each method should only be applied if certain conditions of the data from a pathway are met. Further, we provide method-specific estimates for the optimal sample size for microarray experiments aiming to identify DEP in order to avoid an underpowered design. Our study highlights the sensitivity of the studied methods on the parameters of the system. © 2012 Tripahti and Emmert-Streib.

Development of a five-plex flow cytometric immunoassay for the simultaneous detection of six coccidiostats in feed and eggs

Coccidiostats are the only veterinary drugs still permitted to be used as feed additives to treat poultry for coccidiosis. To protect consumers, maximum levels for their presence in food and feed have been set by the European Union (EU). To monitor these coccidiostats, a rapid and inexpensive screening method would be a useful tool. The development of such a screening method, using a flow cytometry-based immunoassay, is described. The assay uses five sets of colour-coded paramagnetic microspheres for the detection of six selected priority coccidiostats. Different coccidiostats, with and without carrier proteins, were covalently coupled onto different bead sets and tested in combination with polyclonal antisera and with a fluorescent-labelled secondary antibody. The five optimal combinations were selected for this multiplex and a simple-to-use sample extraction method was applied for screening blank and spiked eggs and feed samples. A very good correlation (r ranging from 0.995 to 0.999) was obtained with the responses obtained in two different flow cytometers (Luminex 100 and FLEXMAP 3D). The sensitivities obtained were in accordance with the levels set by the EU as the measured limits of detection for narasin/salinomycin, lasalocid, diclazuril, nicarbazin (4,4'-dinitrocarbanilide) and monensin in eggs were 0.01, 0.1, 0.5, 53 and 0.1 µg/kg and in feed 0.1, 0.2, 0.3, 9 and 1.5 µg/kg, respectively.

Effect of Turbine Inlet Temperature on Rotor Blade Tip Leakage Flow and Heat Transfer

One of the most critical gas turbine engine components, the rotor blade tip and casing, is exposed to high thermal load. It becomes a significant design challenge to protect the turbine materials from this severe situation. The purpose of this paper is to study numerically the effect of turbine inlet temperature on the tip leakage flow structure and heat transfer. In this paper, the effect of turbine inlet temperature on the tip leakage flow structure and heat transfer has been studied numerically. Uniform low (LTIT: 444 K) and high (HTIT: 800 K) turbine inlet temperature, as well as non-uniform inlet temperature have been considered. The results showed the higher turbine inlet temperature yields the higher velocity and temperature variations in the leakage flow aerodynamics and heat transfer. For a given turbine geometry and on-design operating conditions, the turbine power output can be increased by 1.33 times, when the turbine inlet temperature increases 1.80 times. Whereas the averaged heat fluxes on the casing and the blade tip become 2.71 and 2.82 times larger, respectively. Therefore, about 2.8 times larger cooling capacity is required to keep the same turbine material temperature. Furthermore, the maximum heat flux on the blade tip of high turbine inlet temperature case reaches up to 3.348 times larger than that of LTIT case. The effect of the interaction of stator and rotor on heat transfer features is also explored using unsteady simulations. The non-uniform turbine inlet temperature enhances the heat flux fluctuation on the blade tip and casing.

The effect of sub-optimal control and the spectral wave climate on the performance of wave energy converter arrays

A linear hydrodynamic model is used to assess the sensitivity of the performance of a wave energy converter (WEC) array to control parameters. It is found that WEC arrays have a much smaller tolerance to imprecision of the control parameters than isolated WECs and that the increase in power capture of WEC arrays is only achieved with larger amplitudes of motion of the individual WECs. The WEC array radiation pattern is found to provide useful insight into the array hydrodynamics. The linear hydrodynamic model is used, together with the wave climate at the European Marine Energy Centre (EMEC), to assess the maximum annual average power capture of a WEC array. It is found that the maximum annual average power capture is significantly reduced compared to the maximum power capture for regular waves and that the optimum array configuration is also significantly modified. It is concluded that the optimum configuration of a WEC array will be as much influenced by factors such as mooring layout, device access and power smoothing as it is by the theoretical optimum hydrodynamic configuration. © 2009 Elsevier Ltd.

The Impact of Vehicle-to-Grid on Electric Power Systems: A Review

Environmental concerns and fossil fuel shortage put pressure on both power and transportation systems. Electric vehicles (EVs) are thought to be a good solution to these problems. With EV adoption, energy flow is two way: from grid to vehicle and from vehicle to grid, which is known as vehicle-to-grid (V2G) today. This paper considers electric power systems and provides a review of the impact of V2G on power system stability. The concept and basics of V2G technology are introduced at first, followed by a description of EV application in the world. Several technical issues are detailed in V2G modeling and capacity forecasting, steady-state analysis and stability analysis. Research trends of such topics are declared at last.

Phillips-Heffron Power System Model for SmartPark and Suppression of Interarea Oscillations

This paper investigates the use of plug-in parking lots (SmartPark) as integral energy storage to improve small-signal stability using plug-in electric vehicles (PEV). The paper establishes the Phillips-Heffron model of a power system for a SmartPark solution. Based on this model, SmartPark-based stabilisers have been designed based using phase compensation to improve power system oscillation stability. The effectiveness of stabilisation superimposed on the active and reactive power regulators is verified by simulations obtained from a multi-machine power system model with SmartPark and a large-scale wind farm inclusion.

Day-Ahead Optimal Charging/Discharging Scheduling for Electric Vehicles in Micro-Grids

A micro-grid is an autonomous system which can be operated and connected to an external system or isolated with the help of energy storage systems (ESSs). While the daily output of distributed generators (DGs) strongly depends on the temporal distribution of natural resources such as wind and solar, unregulated electric vehicle (EV) charging demand will deteriorate the imbalance between the daily load and generation curves. In this paper, a statistical model is presented to describe daily EV charging/discharging behaviour. An optimisation problem is proposed to obtain economic operation for the micro-grid based on this model. In day-ahead scheduling, with estimated information of power generation and load demand, optimal charging/discharging of EVs during 24 hours is obtained. A series of numerical optimization solutions in different scenarios is achieved by serial quadratic programming. The results show that optimal charging/discharging of EVs, a daily load curve can better track the generation curve and the network loss and required ESS capacity are both decreased. The paper also demonstrates cost benefits for EVs and operators.

Analysis of Load Impact on Small-signal Stability based on Load Active Power Sensitivity

While load flow conditions vary with different loads, the small-signal stability of the entire system is closely related with to the locations, capacities and models of loads. In this paper, load impacts with different capacities and models on the small-signal stability are analysed. In the real large-scale power system case, the load sensitivity which denotes the sensitivity of the eigenvalue with respect to the load active power is introduced and applied to rank the loads. The loads with high sensitivity are also considered.

Optimization of FRT Active Power Performance of a DFIG during Transient Grid Faults

Optimal fault ride-through (FRT) conditions for a doubly-fed induction generator (DFIG) during a transient grid fault are analyzed with special emphasis on improving the active power generation profile. The transition states due to crowbar activation during transient faults are investigated to exploit the maximum power during the fault and post-fault period. It has been identified that operating slip, severity of fault and crowbar resistance have a direct impact on the power capability of a DFIG, and crowbar resistance can be chosen to optimize the power capability. It has been further shown that an extended crowbar period can deliver enhanced inertial response following the transient fault. The converter protection and drive train dynamics have also been analyzed while choosing the optimum crowbar resistance and delivering enhanced inertial support for an extended crowbar period.

Harnessing the power of personality assessment:Subjective assessment predicts behaviour in horses

Objective assessment of animal personality is typically time consuming, requiring the repeated measure of behavioural responses. By contrast, subjective assessment of personality allows information to be collected quickly by experienced caregivers. However, subjective assessment must predict behaviour to be valid. Comparisons of subjective assessments and behaviour have been made but often with methodological weaknesses and thus, limited success. Here we test the validity of a subjective assessment against a battery of behaviour tests in 146 horses (Equus caballus). Our first aim was to determine if subjective personality assessment could predict behaviour during behaviour testing. We made specific a priori predictions for how subjectively measured personality should relate to behaviour testing. We found that Extroversion predicted time to complete a handling test and refusal behaviour during this test. It also predicted minimum distance to a novel object. Neuroticism predicted how reactive an individual was to a sudden visual stimulus but not how quickly it recovered from this. Agreeableness did not predict any behaviour during testing. There were several unpredicted correlations between subjective measures and behaviour tests which we explore further. Our second aim was to combine data from the subjective assessment and behaviour tests to gain a more comprehensive understanding of personality. We found that the combination of methods provides new insights into horse behaviour. Furthermore, our data are consistent with the idea of horses showing different coping styles, a novel finding for this species. © 2013 Elsevier B.V.