Wind power prediction based on genetic neural network

NASA Astrophysics Data System (ADS)

Zhang, Suhan

2017-04-01

The scale of grid connected wind farms keeps increasing. To ensure the stability of power system operation, make a reasonable scheduling scheme and improve the competitiveness of wind farm in the electricity generation market, it's important to accurately forecast the short-term wind power. To reduce the influence of the nonlinear relationship between the disturbance factor and the wind power, the improved prediction model based on genetic algorithm and neural network method is established. To overcome the shortcomings of long training time of BP neural network and easy to fall into local minimum and improve the accuracy of the neural network, genetic algorithm is adopted to optimize the parameters and topology of neural network. The historical data is used as input to predict short-term wind power. The effectiveness and feasibility of the method is verified by the actual data of a certain wind farm as an example.

Low Power Operation of Temperature-Modulated Metal Oxide Semiconductor Gas Sensors.

PubMed

Burgués, Javier; Marco, Santiago

2018-01-25

Mobile applications based on gas sensing present new opportunities for low-cost air quality monitoring, safety, and healthcare. Metal oxide semiconductor (MOX) gas sensors represent the most prominent technology for integration into portable devices, such as smartphones and wearables. Traditionally, MOX sensors have been continuously powered to increase the stability of the sensing layer. However, continuous power is not feasible in many battery-operated applications due to power consumption limitations or the intended intermittent device operation. This work benchmarks two low-power, duty-cycling, and on-demand modes against the continuous power one. The duty-cycling mode periodically turns the sensors on and off and represents a trade-off between power consumption and stability. On-demand operation achieves the lowest power consumption by powering the sensors only while taking a measurement. Twelve thermally modulated SB-500-12 (FIS Inc. Jacksonville, FL, USA) sensors were exposed to low concentrations of carbon monoxide (0-9 ppm) with environmental conditions, such as ambient humidity (15-75% relative humidity) and temperature (21-27 °C), varying within the indicated ranges. Partial Least Squares (PLS) models were built using calibration data, and the prediction error in external validation samples was evaluated during the two weeks following calibration. We found that on-demand operation produced a deformation of the sensor conductance patterns, which led to an increase in the prediction error by almost a factor of 5 as compared to continuous operation (2.2 versus 0.45 ppm). Applying a 10% duty-cycling operation of 10-min periods reduced this prediction error to a factor of 2 (0.9 versus 0.45 ppm). The proposed duty-cycling powering scheme saved up to 90% energy as compared to the continuous operating mode. This low-power mode may be advantageous for applications that do not require continuous and periodic measurements, and which can tolerate slightly higher prediction errors.

Predicting homeowners' approval of fuel management at the wild-urban interface using the theory of reasoned action.

Treesearch

Christine A. Vogt; Greg Winter; Jeremy S. Fried

2005-01-01

Social science models are increasingly needed as a framework for explaining and predicting how members of the public respond to the natural environment and their communities. The theory of reasoned action is widely used in human dimensions research on natural resource problems and work is ongoing to increase the predictive power of models based on this theory. This...

An Integrated Software Package to Enable Predictive Simulation Capabilities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Yousu; Fitzhenry, Erin B.; Jin, Shuangshuang

The power grid is increasing in complexity due to the deployment of smart grid technologies. Such technologies vastly increase the size and complexity of power grid systems for simulation and modeling. This increasing complexity necessitates not only the use of high-performance-computing (HPC) techniques, but a smooth, well-integrated interplay between HPC applications. This paper presents a new integrated software package that integrates HPC applications and a web-based visualization tool based on a middleware framework. This framework can support the data communication between different applications. Case studies with a large power system demonstrate the predictive capability brought by the integrated software package,more » as well as the better situational awareness provided by the web-based visualization tool in a live mode. Test results validate the effectiveness and usability of the integrated software package.« less

ESB-based Sensor Web integration for the prediction of electric power supply system vulnerability.

PubMed

Stoimenov, Leonid; Bogdanovic, Milos; Bogdanovic-Dinic, Sanja

2013-08-15

Electric power supply companies increasingly rely on enterprise IT systems to provide them with a comprehensive view of the state of the distribution network. Within a utility-wide network, enterprise IT systems collect data from various metering devices. Such data can be effectively used for the prediction of power supply network vulnerability. The purpose of this paper is to present the Enterprise Service Bus (ESB)-based Sensor Web integration solution that we have developed with the purpose of enabling prediction of power supply network vulnerability, in terms of a prediction of defect probability for a particular network element. We will give an example of its usage and demonstrate our vulnerability prediction model on data collected from two different power supply companies. The proposed solution is an extension of the GinisSense Sensor Web-based architecture for collecting, processing, analyzing, decision making and alerting based on the data received from heterogeneous data sources. In this case, GinisSense has been upgraded to be capable of operating in an ESB environment and combine Sensor Web and GIS technologies to enable prediction of electric power supply system vulnerability. Aside from electrical values, the proposed solution gathers ambient values from additional sensors installed in the existing power supply network infrastructure. GinisSense aggregates gathered data according to an adapted Omnibus data fusion model and applies decision-making logic on the aggregated data. Detected vulnerabilities are visualized to end-users through means of a specialized Web GIS application.

ESB-Based Sensor Web Integration for the Prediction of Electric Power Supply System Vulnerability

PubMed Central

Stoimenov, Leonid; Bogdanovic, Milos; Bogdanovic-Dinic, Sanja

2013-01-01

Electric power supply companies increasingly rely on enterprise IT systems to provide them with a comprehensive view of the state of the distribution network. Within a utility-wide network, enterprise IT systems collect data from various metering devices. Such data can be effectively used for the prediction of power supply network vulnerability. The purpose of this paper is to present the Enterprise Service Bus (ESB)-based Sensor Web integration solution that we have developed with the purpose of enabling prediction of power supply network vulnerability, in terms of a prediction of defect probability for a particular network element. We will give an example of its usage and demonstrate our vulnerability prediction model on data collected from two different power supply companies. The proposed solution is an extension of the GinisSense Sensor Web-based architecture for collecting, processing, analyzing, decision making and alerting based on the data received from heterogeneous data sources. In this case, GinisSense has been upgraded to be capable of operating in an ESB environment and combine Sensor Web and GIS technologies to enable prediction of electric power supply system vulnerability. Aside from electrical values, the proposed solution gathers ambient values from additional sensors installed in the existing power supply network infrastructure. GinisSense aggregates gathered data according to an adapted Omnibus data fusion model and applies decision-making logic on the aggregated data. Detected vulnerabilities are visualized to end-users through means of a specialized Web GIS application. PMID:23955435

DOE Office of Scientific and Technical Information (OSTI.GOV)

Newman, Jennifer F.; Clifton, Andrew

Currently, cup anemometers on meteorological towers are used to measure wind speeds and turbulence intensity to make decisions about wind turbine class and site suitability; however, as modern turbine hub heights increase and wind energy expands to complex and remote sites, it becomes more difficult and costly to install meteorological towers at potential sites. As a result, remote-sensing devices (e.g., lidars) are now commonly used by wind farm managers and researchers to estimate the flow field at heights spanned by a turbine. Although lidars can accurately estimate mean wind speeds and wind directions, there is still a large amount ofmore » uncertainty surrounding the measurement of turbulence using these devices. Errors in lidar turbulence estimates are caused by a variety of factors, including instrument noise, volume averaging, and variance contamination, in which the magnitude of these factors is highly dependent on measurement height and atmospheric stability. As turbulence has a large impact on wind power production, errors in turbulence measurements will translate into errors in wind power prediction. The impact of using lidars rather than cup anemometers for wind power prediction must be understood if lidars are to be considered a viable alternative to cup anemometers.In this poster, the sensitivity of power prediction error to typical lidar turbulence measurement errors is assessed. Turbulence estimates from a vertically profiling WINDCUBE v2 lidar are compared to high-resolution sonic anemometer measurements at field sites in Oklahoma and Colorado to determine the degree of lidar turbulence error that can be expected under different atmospheric conditions. These errors are then incorporated into a power prediction model to estimate the sensitivity of power prediction error to turbulence measurement error. Power prediction models, including the standard binning method and a random forest method, were developed using data from the aeroelastic simulator FAST for a 1.5 MW turbine. The impact of lidar turbulence error on the predicted power from these different models is examined to determine the degree of turbulence measurement accuracy needed for accurate power prediction.« less

Comparative study of electrical and switch-skipping mechanical switch for self-powered SSHI in medium coupled piezoelectric vibration energy harvesters

NASA Astrophysics Data System (ADS)

Asanuma, H.; Sakamoto, K.; Komatsuzaki, T.; Iwata, Y.

2018-07-01

To increase output power for piezoelectric vibration energy harvesters, considerable attention has recently been focused on a self-powered synchronized switch harvesting on inductor (SSHI) technique employing an electrical and mechanical switch. However, there are two technical issues: in a medium or highly coupled harvester, the piezoelectric coupling force, which increases as the SSHI’s voltage increases, will reduce the harvester’s displacement and the resulting output power, and there are few reports comparing the performance of electrical switch SSHI (ESS) and mechanical switch SSHI (MSS) that include consideration of the piezoelectric coupling force. We developed a simulation technique that allows us to evaluate the output power considering the piezoelectric coupling force, and investigated the performance of stopper-based MSS and ESS, both numerically and experimentally. The numerical investigation predicted the following: (1) the output power for the ESS is lower than that for the MSS at acceleration lower than 3.5 m s‑2 and (2) intriguingly, the output power for the MSS continues to increase, whereas the peak–peak displacement remains constant. The experimental results showed behaviour similar to that of the numerical predictions. The results are attributed to the different switching strategies: the MSS turns on only when the harvester’s displacement exceeds the gap distance, while the ESS turns on at every maximum/minimum displacement.

An extended fatty liver index to predict non-alcoholic fatty liver disease.

PubMed

Kantartzis, K; Rettig, I; Staiger, H; Machann, J; Schick, F; Scheja, L; Gastaldelli, A; Bugianesi, E; Peter, A; Schulze, M B; Fritsche, A; Häring, H-U; Stefan, N

2017-06-01

In clinical practice, there is a strong interest in non-invasive markers of non-alcoholic fatty liver disease (NAFLD). Our hypothesis was that the fold-change in plasma triglycerides (TG) during a 2-h oral glucose tolerance test (fold-change TG OGTT ) in concert with blood glucose and lipid parameters, and the rs738409 C>G single nucleotide polymorphism (SNP) in PNPLA3 might improve the power of the widely used fatty liver index (FLI) to predict NAFLD. The liver fat content of 330 subjects was quantified by 1 H-magnetic resonance spectroscopy. Blood parameters were measured during fasting and after a 2-h OGTT. A subgroup of 213 subjects underwent these measurements before and after 9 months of a lifestyle intervention. The fold-change TG OGTT was closely associated with liver fat content (r=0.51, P<0.0001), but had less power to predict NAFLD (AUROC=0.75) than the FLI (AUROC=0.79). Not only was the fold-change TG OGTT independently associated with liver fat content and NAFLD, but so also were the 2-h blood glucose level and rs738409 C>G SNP in PNPLA3. In fact, a novel index (extended FLI) generated from these and the usual FLI parameters considerably increased its power to predict NAFLD (AUROC=0.79-0.86). The extended FLI also increased the power to predict changes in liver fat content with a lifestyle intervention (n=213; standardized beta coefficient: 0.23-0.29). This study has provided novel data confirming that the OGTT-derived fold-change TG OGTT and 2-h glucose level, together with the rs738409 C>G SNP in PNPLA3, allow calculation of an extended FLI that considerably improves its power to predict NAFLD. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

The rate of transient beta frequency events predicts behavior across tasks and species

PubMed Central

Law, Robert; Tsutsui, Shawn; Moore, Christopher I; Jones, Stephanie R

2017-01-01

Beta oscillations (15-29Hz) are among the most prominent signatures of brain activity. Beta power is predictive of healthy and abnormal behaviors, including perception, attention and motor action. In non-averaged signals, beta can emerge as transient high-power 'events'. As such, functionally relevant differences in averaged power across time and trials can reflect changes in event number, power, duration, and/or frequency span. We show that functionally relevant differences in averaged beta power in primary somatosensory neocortex reflect a difference in the number of high-power beta events per trial, i.e. event rate. Further, beta events occurring close to the stimulus were more likely to impair perception. These results are consistent across detection and attention tasks in human magnetoencephalography, and in local field potentials from mice performing a detection task. These results imply that an increased propensity of beta events predicts the failure to effectively transmit information through specific neocortical representations. PMID:29106374

Predicted impact of thermal power generation emission control measures in the Beijing-Tianjin-Hebei region on air pollution over Beijing, China.

PubMed

Wang, Liqiang; Li, Pengfei; Yu, Shaocai; Mehmood, Khalid; Li, Zhen; Chang, Shucheng; Liu, Weiping; Rosenfeld, Daniel; Flagan, Richard C; Seinfeld, John H

2018-01-17

Widespread economic growth in China has led to increasing episodes of severe air pollution, especially in major urban areas. Thermal power plants represent a particularly important class of emissions. Here we present an evaluation of the predicted effectiveness of a series of recently proposed thermal power plant emission controls in the Beijing-Tianjin-Hebei (BTH) region on air quality over Beijing using the Community Multiscale Air Quality(CMAQ) atmospheric chemical transport model to predict CO, SO 2 , NO 2 , PM 2.5 , and PM 10 levels. A baseline simulation of the hypothetical removal of all thermal power plants in the BTH region is predicted to lead to 38%, 23%, 23%, 24%, and 24% reductions in current annual mean levels of CO, SO 2 , NO 2 , PM 2.5 , and PM 10 in Beijing, respectively. Similar percentage reductions are predicted in the major cities in the BTH region. Simulations of the air quality impact of six proposed thermal power plant emission reduction strategies over the BTH region provide an estimate of the potential improvement in air quality in the Beijing metropolitan area, as a function of the time of year.

A Complete Procedure for Predicting and Improving the Performance of HAWT's

NASA Astrophysics Data System (ADS)

Al-Abadi, Ali; Ertunç, Özgür; Sittig, Florian; Delgado, Antonio

2014-06-01

A complete procedure for predicting and improving the performance of the horizontal axis wind turbine (HAWT) has been developed. The first process is predicting the power extracted by the turbine and the derived rotor torque, which should be identical to that of the drive unit. The BEM method and a developed post-stall treatment for resolving stall-regulated HAWT is incorporated in the prediction. For that, a modified stall-regulated prediction model, which can predict the HAWT performance over the operating range of oncoming wind velocity, is derived from existing models. The model involves radius and chord, which has made it more general in applications for predicting the performance of different scales and rotor shapes of HAWTs. The second process is modifying the rotor shape by an optimization process, which can be applied to any existing HAWT, to improve its performance. A gradient- based optimization is used for adjusting the chord and twist angle distribution of the rotor blade to increase the extraction of the power while keeping the drive torque constant, thus the same drive unit can be kept. The final process is testing the modified turbine to predict its enhanced performance. The procedure is applied to NREL phase-VI 10kW as a baseline turbine. The study has proven the applicability of the developed model in predicting the performance of the baseline as well as the optimized turbine. In addition, the optimization method has shown that the power coefficient can be increased while keeping same design rotational speed.

Nuclear Power Systems for Manned Mission to Mars

DTIC Science & Technology

2004-12-01

Brayton Cycle ..........................................................................30 c. Stirling Cycle ...specific mass as the power level increases. This graph also shows the upward scalability of Brayton and Rankine cycles , predicting that higher...Orbit, 1985), 79. 47Joseph A. Angelo, Jr. and David Buden, Space Nuclear Power, (Malabar, Florida: Orbit, 1985), 80. 30 b. Brayton Cycle

Social goals, aggression, peer preference, and popularity: longitudinal links during middle school.

PubMed

Ojanen, Tiina; Findley-Van Nostrand, Danielle

2014-08-01

Social goals are associated with behaviors and adjustment among peers. However, it remains unclear whether goals predict adolescent social development. We examined prospective associations among goals, physical and relational aggression, social preference, and popularity during middle school (N = 384 participants, ages 12-14 years). Agentic (status, power) goals predicted increased relational aggression and communal (closeness) goals predicted decreased physical aggression. Popularity predicted increases and preference predicted decreases in both forms of aggression. Goals moderated longitudinal links between aggression and popularity: Aggression predicted increases in popularity and vice versa for youth with higher agentic goals, and popularity predicted increases in physical aggression for youth with higher agentic and lower communal goals. Implications for research on social goals, aggression, and popularity are discussed. PsycINFO Database Record (c) 2014 APA, all rights reserved.

When More Power Makes Actors Worse off: Turning a Profit in the American Economy

ERIC Educational Resources Information Center

Piskorski, Mikolaj Jan; Casciaro, Tiziana

2006-01-01

We propose a theory which predicts that an increase in an actor's relative power reduces the actor's rewards in high mutual dependence dyads. Our argument is based on the premise that higher relative power gives the more powerful actor a greater share of surplus, but it also reduces dyadic exchange frequency, which lowers the expected magnitude of…

Integrated Wind Power Planning Tool

NASA Astrophysics Data System (ADS)

Rosgaard, Martin; Giebel, Gregor; Skov Nielsen, Torben; Hahmann, Andrea; Sørensen, Poul; Madsen, Henrik

2013-04-01

This poster presents the current state of the public service obligation (PSO) funded project PSO 10464, with the title "Integrated Wind Power Planning Tool". The goal is to integrate a mesoscale numerical weather prediction (NWP) model with purely statistical tools in order to assess wind power fluctuations, with focus on long term power system planning for future wind farms as well as short term forecasting for existing wind farms. Currently, wind power fluctuation models are either purely statistical or integrated with NWP models of limited resolution. Using the state-of-the-art mesoscale NWP model Weather Research & Forecasting model (WRF) the forecast error is sought quantified in dependence of the time scale involved. This task constitutes a preparative study for later implementation of features accounting for NWP forecast errors in the DTU Wind Energy maintained Corwind code - a long term wind power planning tool. Within the framework of PSO 10464 research related to operational short term wind power prediction will be carried out, including a comparison of forecast quality at different mesoscale NWP model resolutions and development of a statistical wind power prediction tool taking input from WRF. The short term prediction part of the project is carried out in collaboration with ENFOR A/S; a Danish company that specialises in forecasting and optimisation for the energy sector. The integrated prediction model will allow for the description of the expected variability in wind power production in the coming hours to days, accounting for its spatio-temporal dependencies, and depending on the prevailing weather conditions defined by the WRF output. The output from the integrated short term prediction tool constitutes scenario forecasts for the coming period, which can then be fed into any type of system model or decision making problem to be solved. The high resolution of the WRF results loaded into the integrated prediction model will ensure a high accuracy data basis is available for use in the decision making process of the Danish transmission system operator. The need for high accuracy predictions will only increase over the next decade as Denmark approaches the goal of 50% wind power based electricity in 2025 from the current 20%.

Modelling sheet erosion on steep slopes in the loess region of China

NASA Astrophysics Data System (ADS)

Wu, Bing; Wang, Zhanli; Zhang, Qingwei; Shen, Nan; Liu, June

2017-10-01

The relationship of sheet erosion rate (SE), slope gradient (S) and rainfall intensity (I), and hydraulic parameters, such as flow velocity (V), shear stress (τ), stream power (Ω) and unit stream power (P), was investigated to derive an accurate experimental model. The experiment was conducted at slopes of 12.23%, 17.63%, 26.8%, 36.4%, 40.4% and 46.63% under I of 48, 60, 90, 120, 138 and 150 mm h-1, respectively, using simulated rainfall. Results showed that sheet erosion rate increased as a power function with rainfall intensity and slope gradient with R2 = 0.95 and Nash-Sutcliffe model efficiency (NSE) = 0.87. Sheet erosion rate was more sensitive to rainfall intensity than to slope gradient. It increased as a power function with flow velocity, which was satisfactory for predicting sheet erosion rate with R2 = 0.95 and NSE = 0.81. Shear stress and stream power could be used to predict sheet erosion rate accurately with a linear function equation. Stream power (R2 = 0.97, NSE = 0.97) was a better predictor of sheet erosion rather than shear stress (R2 = 0.90, NSE = 0.89). However, a prediction based on unit stream power was poor. The new equation (i.e. SE = 7.5 ×1012S1.43I3.04 and SE = 0.06 Ω - 0.0003 and SE = 0.011 τ - 0.01) would improve water erosion estimation on loess hillslopes of China.

A summary of wind power prediction methods

NASA Astrophysics Data System (ADS)

Wang, Yuqi

2018-06-01

The deterministic prediction of wind power, the probability prediction and the prediction of wind power ramp events are introduced in this paper. Deterministic prediction includes the prediction of statistical learning based on histor ical data and the prediction of physical models based on NWP data. Due to the great impact of wind power ramp events on the power system, this paper also introduces the prediction of wind power ramp events. At last, the evaluation indicators of all kinds of prediction are given. The prediction of wind power can be a good solution to the adverse effects of wind power on the power system due to the abrupt, intermittent and undulation of wind power.

Prediction of power requirements for a longwall armored face conveyor

DOE Office of Scientific and Technical Information (OSTI.GOV)

Broadfoot, A.R.; Betz, R.E.

1995-12-31

Longwall armored face conveyors (AFC`s) have traditionally been designed using a combination of heuristics and simple models. However, as longwalls increase in length these design procedures are proving to be inadequate. The result has either been costly loss of production due to AFC stalling or component failure, or larger than necessary capital investment due to overdesign. In order to allow accurate estimation of the power requirements for an AFC this paper develops a comprehensive model of all the friction forces associated with the AFC. Power requirement predictions obtained from these models are then compared with measurements from two mine faces.

Effects of rhythmic stimulus presentation on oscillatory brain activity: the physiology of cueing in Parkinson’s disease

PubMed Central

te Woerd, Erik S.; Oostenveld, Robert; Bloem, Bastiaan R.; de Lange, Floris P.; Praamstra, Peter

2015-01-01

The basal ganglia play an important role in beat perception and patients with Parkinson’s disease (PD) are impaired in perception of beat-based rhythms. Rhythmic cues are nonetheless beneficial in gait rehabilitation, raising the question how rhythm improves movement in PD. We addressed this question with magnetoencephalography recordings during a choice response task with rhythmic and non-rhythmic modes of stimulus presentation. Analyses focused on (i) entrainment of slow oscillations, (ii) the depth of beta power modulation, and (iii) whether a gain in modulation depth of beta power, due to rhythmicity, is of predictive or reactive nature. The results show weaker phase synchronisation of slow oscillations and a relative shift from predictive to reactive movement-related beta suppression in PD. Nonetheless, rhythmic stimulus presentation increased beta modulation depth to the same extent in patients and controls. Critically, this gain selectively increased the predictive and not reactive movement-related beta power suppression. Operation of a predictive mechanism, induced by rhythmic stimulation, was corroborated by a sensory gating effect in the sensorimotor cortex. The predictive mode of cue utilisation points to facilitation of basal ganglia-premotor interactions, contrasting with the popular view that rhythmic stimulation confers a special advantage in PD, based on recruitment of alternative pathways. PMID:26509117

Prediction and measurement of the electromagnetic environment of high-power medium-wave and short-wave broadcast antennas in far field.

PubMed

Tang, Zhanghong; Wang, Qun; Ji, Zhijiang; Shi, Meiwu; Hou, Guoyan; Tan, Danjun; Wang, Pengqi; Qiu, Xianbo

2014-12-01

With the increasing city size, high-power electromagnetic radiation devices such as high-power medium-wave (MW) and short-wave (SW) antennas have been inevitably getting closer and closer to buildings, which resulted in the pollution of indoor electromagnetic radiation becoming worsened. To avoid such radiation exceeding the exposure limits by national standards, it is necessary to predict and survey the electromagnetic radiation by MW and SW antennas before constructing the buildings. In this paper, a modified prediction method for the far-field electromagnetic radiation is proposed and successfully applied to predict the electromagnetic environment of an area close to a group of typical high-power MW and SW wave antennas. Different from currently used simplified prediction method defined in the Radiation Protection Management Guidelines (H J/T 10. 3-1996), the new method in this article makes use of more information such as antennas' patterns to predict the electromagnetic environment. Therefore, it improves the prediction accuracy significantly by the new feature of resolution at different directions. At the end of this article, a comparison between the prediction data and the measured results is given to demonstrate the effectiveness of the proposed new method. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Resting-state sensorimotor rhythm (SMR) power predicts the ability to up-regulate SMR in an EEG-instrumental conditioning paradigm.

PubMed

Reichert, Johanna Louise; Kober, Silvia Erika; Neuper, Christa; Wood, Guilherme

2015-11-01

Instrumental conditioning of EEG activity (EEG-IC) is a promising method for improvement and rehabilitation of cognitive functions. However, it has been found that even healthy adults are not always able to learn how to regulate their brain activity during EEG-IC. In the present study, the role of a neurophysiological predictor of EEG-IC learning performance, the resting-state power of sensorimotor rhythm (rs-SMR, 12-15Hz), was investigated. Eyes-open and eyes-closed rs-SMR power was assessed before N=28 healthy adults underwent 10 training sessions of instrumental SMR conditioning (ISC), in which participants should learn to voluntarily increase their SMR power by means of audio-visual feedback. A control group of N=19 participants received gamma (40-43Hz) or sham EEG-IC. N=19 of the ISC participants could be classified as "responders" as they were able to increase SMR power during training sessions, while N=9 participants ("non-responders") were not able to increase SMR power. Rs-SMR power in responders before start of ISC was higher in widespread parieto-occipital areas than in non-responders. A discriminant analysis indicated that eyes-open rs-SMR power in a central brain region specifically predicted later ISC performance, but not an increase of SMR in the control group. Together, these findings indicate that rs-SMR power is a specific and easy-to-measure predictor of later ISC learning performance. The assessment of factors that influence the ability to regulate brain activity is of high relevance, as it could be used to avoid potentially frustrating and expensive EEG-IC training sessions for participants who have a low chance of success. Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Wind Power predictability a risk factor in the design, construction and operation of Wind Generation Turbines

NASA Astrophysics Data System (ADS)

Thiesen, J.; Gulstad, L.; Ristic, I.; Maric, T.

2010-09-01

Summit: The wind power predictability is often a forgotten decision and planning factor for most major wind parks, both onshore and offshore. The results of the predictability are presented after having examined a number of European offshore and offshore parks power predictability by using three(3) mesoscale model IRIE_GFS and IRIE_EC and WRF. Full description: It is well known that the potential wind production is changing with latitude and complexity in terrain, but how big are the changes in the predictability and the economic impacts on a project? The concept of meteorological predictability has hitherto to some degree been neglected as a risk factor in the design, construction and operation of wind power plants. Wind power plants are generally built in places where the wind resources are high, but these are often also sites where the predictability of the wind and other weather parameters is comparatively low. This presentation addresses the question of whether higher predictability can outweigh lower average wind speeds with regard to the overall economy of a wind power project. Low predictability also tends to reduce the value of the energy produced. If it is difficult to forecast the wind on a site, it will also be difficult to predict the power production. This, in turn, leads to increased balance costs and a less reduced carbon emission from the renewable source. By investigating the output from three(3) mesoscale models IRIE and WRF, using ECMWF and GFS as boundary data over a forecasting period of 3 months for 25 offshore and onshore wind parks in Europe, the predictability are mapped. Three operational mesoscale models with two different boundary data have been chosen in order to eliminate the uncertainty with one mesoscale model. All mesoscale models are running in a 10 km horizontal resolution. The model output are converted into "day a head" wind turbine generation forecasts by using a well proven advanced physical wind power model. The power models are using a number of weather parameters like wind speed in different heights, friction velocity and DTHV. The 25 wind sites are scattered around in Europe and contains 4 offshore parks and 21 onshore parks in various terrain complexity. The "day a head" forecasts are compared with production data and predictability for the period February 2010-April 2010 are given in Mean Absolute Errors (MAE) and Root Mean Squared Errors (RMSE). The power predictability results are mapped for each turbine giving a clear picture of the predictability in Europe. . Finally a economic analysis are shown for each wind parks in different regimes of predictability will be compared with regard to the balance costs that result from errors in the wind power prediction. Analysis shows that it may very well be profitable to place wind parks in regions of lower, but more predictable wind ressource. Authors: Ivan Ristic, CTO Weather2Umberlla D.O.O Tomislav Maric, Meteorologist at Global Flow Solutions Vestas Wind Technology R&D Line Gulstad, Manager Global Flow Solutions Vestas Wind Technology R&D Jesper Thiesen, CEO ConWx ApS

A signature inferred from Drosophila mitotic genes predicts survival of breast cancer patients.

PubMed

Damasco, Christian; Lembo, Antonio; Somma, Maria Patrizia; Gatti, Maurizio; Di Cunto, Ferdinando; Provero, Paolo

2011-02-28

The classification of breast cancer patients into risk groups provides a powerful tool for the identification of patients who will benefit from aggressive systemic therapy. The analysis of microarray data has generated several gene expression signatures that improve diagnosis and allow risk assessment. There is also evidence that cell proliferation-related genes have a high predictive power within these signatures. We thus constructed a gene expression signature (the DM signature) using the human orthologues of 108 Drosophila melanogaster genes required for either the maintenance of chromosome integrity (36 genes) or mitotic division (72 genes). The DM signature has minimal overlap with the extant signatures and is highly predictive of survival in 5 large breast cancer datasets. In addition, we show that the DM signature outperforms many widely used breast cancer signatures in predictive power, and performs comparably to other proliferation-based signatures. For most genes of the DM signature, an increased expression is negatively correlated with patient survival. The genes that provide the highest contribution to the predictive power of the DM signature are those involved in cytokinesis. This finding highlights cytokinesis as an important marker in breast cancer prognosis and as a possible target for antimitotic therapies.

Wind power application research on the fusion of the determination and ensemble prediction

NASA Astrophysics Data System (ADS)

Lan, Shi; Lina, Xu; Yuzhu, Hao

2017-07-01

The fused product of wind speed for the wind farm is designed through the use of wind speed products of ensemble prediction from the European Centre for Medium-Range Weather Forecasts (ECMWF) and professional numerical model products on wind power based on Mesoscale Model5 (MM5) and Beijing Rapid Update Cycle (BJ-RUC), which are suitable for short-term wind power forecasting and electric dispatch. The single-valued forecast is formed by calculating the different ensemble statistics of the Bayesian probabilistic forecasting representing the uncertainty of ECMWF ensemble prediction. Using autoregressive integrated moving average (ARIMA) model to improve the time resolution of the single-valued forecast, and based on the Bayesian model averaging (BMA) and the deterministic numerical model prediction, the optimal wind speed forecasting curve and the confidence interval are provided. The result shows that the fusion forecast has made obvious improvement to the accuracy relative to the existing numerical forecasting products. Compared with the 0-24 h existing deterministic forecast in the validation period, the mean absolute error (MAE) is decreased by 24.3 % and the correlation coefficient (R) is increased by 12.5 %. In comparison with the ECMWF ensemble forecast, the MAE is reduced by 11.7 %, and R is increased 14.5 %. Additionally, MAE did not increase with the prolongation of the forecast ahead.

Increased prognostic accuracy of TBI when a brain electrical activity biomarker is added to loss of consciousness (LOC).

PubMed

Hack, Dallas; Huff, J Stephen; Curley, Kenneth; Naunheim, Roseanne; Ghosh Dastidar, Samanwoy; Prichep, Leslie S

2017-07-01

Extremely high accuracy for predicting CT+ traumatic brain injury (TBI) using a quantitative EEG (QEEG) based multivariate classification algorithm was demonstrated in an independent validation trial, in Emergency Department (ED) patients, using an easy to use handheld device. This study compares the predictive power using that algorithm (which includes LOC and amnesia), to the predictive power of LOC alone or LOC plus traumatic amnesia. ED patients 18-85years presenting within 72h of closed head injury, with GSC 12-15, were study candidates. 680 patients with known absence or presence of LOC were enrolled (145 CT+ and 535 CT- patients). 5-10min of eyes closed EEG was acquired using the Ahead 300 handheld device, from frontal and frontotemporal regions. The same classification algorithm methodology was used for both the EEG based and the LOC based algorithms. Predictive power was evaluated using area under the ROC curve (AUC) and odds ratios. The QEEG based classification algorithm demonstrated significant improvement in predictive power compared with LOC alone, both in improved AUC (83% improvement) and odds ratio (increase from 4.65 to 16.22). Adding RGA and/or PTA to LOC was not improved over LOC alone. Rapid triage of TBI relies on strong initial predictors. Addition of an electrophysiological based marker was shown to outperform report of LOC alone or LOC plus amnesia, in determining risk of an intracranial bleed. In addition, ease of use at point-of-care, non-invasive, and rapid result using such technology suggests significant value added to standard clinical prediction. Copyright © 2017 Elsevier Inc. All rights reserved.

Prestimulus EEG Power Predicts Conscious Awareness But Not Objective Visual Performance

PubMed Central

Veniero, Domenica

2017-01-01

Abstract Prestimulus oscillatory neural activity has been linked to perceptual outcomes during performance of psychophysical detection and discrimination tasks. Specifically, the power and phase of low frequency oscillations have been found to predict whether an upcoming weak visual target will be detected or not. However, the mechanisms by which baseline oscillatory activity influences perception remain unclear. Recent studies suggest that the frequently reported negative relationship between α power and stimulus detection may be explained by changes in detection criterion (i.e., increased target present responses regardless of whether the target was present/absent) driven by the state of neural excitability, rather than changes in visual sensitivity (i.e., more veridical percepts). Here, we recorded EEG while human participants performed a luminance discrimination task on perithreshold stimuli in combination with single-trial ratings of perceptual awareness. Our aim was to investigate whether the power and/or phase of prestimulus oscillatory activity predict discrimination accuracy and/or perceptual awareness on a trial-by-trial basis. Prestimulus power (3–28 Hz) was inversely related to perceptual awareness ratings (i.e., higher ratings in states of low prestimulus power/high excitability) but did not predict discrimination accuracy. In contrast, prestimulus oscillatory phase did not predict awareness ratings or accuracy in any frequency band. These results provide evidence that prestimulus α power influences the level of subjective awareness of threshold visual stimuli but does not influence visual sensitivity when a decision has to be made regarding stimulus features. Hence, we find a clear dissociation between the influence of ongoing neural activity on conscious awareness and objective performance. PMID:29255794

Early Prediction of Student Dropout and Performance in MOOCSs Using Higher Granularity Temporal Information

ERIC Educational Resources Information Center

Ye, Cheng; Biswas, Gautam

2014-01-01

Our project is motivated by the early dropout and low completion rate problem in MOOCs. We have extended traditional features for MOOC analysis with richer and higher granularity information to make more accurate predictions of dropout and performance. The results show that finer-grained temporal information increases the predictive power in the…

Voltage collapse in complex power grids

PubMed Central

Simpson-Porco, John W.; Dörfler, Florian; Bullo, Francesco

2016-01-01

A large-scale power grid's ability to transfer energy from producers to consumers is constrained by both the network structure and the nonlinear physics of power flow. Violations of these constraints have been observed to result in voltage collapse blackouts, where nodal voltages slowly decline before precipitously falling. However, methods to test for voltage collapse are dominantly simulation-based, offering little theoretical insight into how grid structure influences stability margins. For a simplified power flow model, here we derive a closed-form condition under which a power network is safe from voltage collapse. The condition combines the complex structure of the network with the reactive power demands of loads to produce a node-by-node measure of grid stress, a prediction of the largest nodal voltage deviation, and an estimate of the distance to collapse. We extensively test our predictions on large-scale systems, highlighting how our condition can be leveraged to increase grid stability margins. PMID:26887284

Effects of nonverbal behavior on perceptions of a female employee's power bases.

PubMed

Aguinis, H; Henle, C A

2001-08-01

The authors extended a previous examination of the effects of nonverbal behavior on perceptions of a male employee's power bases (H. Aguinis, M. M. Simonsen, & C. A. Pierce, 1998) by examining the effects of nonverbal behavior on perceptions of a female employee's power bases. U.S. undergraduates read vignettes describing a female employee engaging in 3 types of nonverbal behavior (i.e., eye contact, facial expression, body posture) and rated their perceptions of the woman's power bases (i.e., reward, coercive, legitimate, referent, expert, credibility). As predicted, (a) direct eye contact increased perceptions of coercive power, and (b) a relaxed facial expression decreased perceptions of all 6 power bases. Also as predicted, the present results differed markedly from those of Aguinis et al. (1998) regarding a male employee. The authors discuss implications for theory, future research, and the advancement of female employees.

High Pressure Regenerative Turbine Engine: 21st Century Propulsion

NASA Technical Reports Server (NTRS)

Lear, W. E.; Laganelli, A. L.; Senick, Paul (Technical Monitor)

2001-01-01

A novel semi-closed cycle gas turbine engine was demonstrated and was found to meet the program goals. The proof-of-principle test of the High Pressure Regenerative Turbine Engine produced data that agreed well with models, enabling more confidence in designing future prototypes based on this concept. Emission levels were significantly reduced as predicted as a natural attribute of this power cycle. Engine testing over a portion of the operating range allowed verification of predicted power increases compared to the baseline.

Prediction of power requirements for a longwall armored face conveyor

DOE Office of Scientific and Technical Information (OSTI.GOV)

Broadfoot, A.R.; Betz, R.E.

1997-01-01

Longwall armored face conveyors (AFC`s) have traditionally been designed using a combination of heuristics and simple models. However, as longwalls increase in length, these design procedures are proving to be inadequate. The result has either been a costly loss of production due to AFC stalling or component failure, or larger than necessary capital investment due to overdesign. In order to allow accurate estimation of the power requirements for an AFC, this paper develops a comprehensive model of all the friction forces associated with the AFC. Power requirement predictions obtained from these models are then compared with measurements from two minemore » faces.« less

The wind power prediction research based on mind evolutionary algorithm

NASA Astrophysics Data System (ADS)

Zhuang, Ling; Zhao, Xinjian; Ji, Tianming; Miao, Jingwen; Cui, Haina

2018-04-01

When the wind power is connected to the power grid, its characteristics of fluctuation, intermittent and randomness will affect the stability of the power system. The wind power prediction can guarantee the power quality and reduce the operating cost of power system. There were some limitations in several traditional wind power prediction methods. On the basis, the wind power prediction method based on Mind Evolutionary Algorithm (MEA) is put forward and a prediction model is provided. The experimental results demonstrate that MEA performs efficiently in term of the wind power prediction. The MEA method has broad prospect of engineering application.

Social Power Increases Interoceptive Accuracy

PubMed Central

Moeini-Jazani, Mehrad; Knoeferle, Klemens; de Molière, Laura; Gatti, Elia; Warlop, Luk

2017-01-01

Building on recent psychological research showing that power increases self-focused attention, we propose that having power increases accuracy in perception of bodily signals, a phenomenon known as interoceptive accuracy. Consistent with our proposition, participants in a high-power experimental condition outperformed those in the control and low-power conditions in the Schandry heartbeat-detection task. We demonstrate that the effect of power on interoceptive accuracy is not explained by participants’ physiological arousal, affective state, or general intention for accuracy. Rather, consistent with our reasoning that experiencing power shifts attentional resources inward, we show that the effect of power on interoceptive accuracy is dependent on individuals’ chronic tendency to focus on their internal sensations. Moreover, we demonstrate that individuals’ chronic sense of power also predicts interoceptive accuracy similar to, and independent of, how their situationally induced feeling of power does. We therefore provide further support on the relation between power and enhanced perception of bodily signals. Our findings offer a novel perspective–a psychophysiological account–on how power might affect judgments and behavior. We highlight and discuss some of these intriguing possibilities for future research. PMID:28824501

Hypertriglyceridemic waist might be an alternative to metabolic syndrome for predicting future diabetes mellitus.

PubMed

He, Sen; Zheng, Yi; Shu, Yan; He, Jiyun; Wang, Yong; Chen, Xiaoping

2013-01-01

In some cross-sectional studies, hypertriglyceridemic waist (HTGW) has been recommended as an alternative to metabolic syndrome (MetS) for screening individuals at high risk for diabetes mellitus (DM). However, little information is about the predictive power of HTGW for future DM. The aims of the study were to assess the DM predictive power of HTGW compared with MetS based on the follow-up data over 15 years collected from a general Chinese population. And Findings: The data were collected in 1992 and then again in 2007 from the same group of 687 individuals without DM in 1992. For the whole population (n =687), multivariate analysis showed presence of HTGW was associated with a 4.1-fold (95%CI: 2.4-7.0, p < 0.001) increased risk and presence of MetS was associated with a 3.7-fold (95%CI: 2.2-6.2, p < 0.001) increased risk for future DM. For the population without elevated fasting plasma glucose (n = 650), multivariate analysis showed presence of HTGW was associated with a 3.9-fold (95%CI: 2.2-7.0, p < 0.001) increased risk and presence of MetS was associated with a 3.7-fold (95%CI: 2.1-6.6, p < 0.001) increased risk for future DM. HTGW could predict future DM independently, and the predictive power was similar to MetS. HTGW might be an alternative to MetS for predicting future DM. For simpler and fewer components, HTGW might be more practical than MetS, and it might be recommended in most clinical practices. This finding might be more useful for the individuals who only have elevated WC and TG. Although these individuals are without MetS, they are still at high risk for future DM, similarly to the individuals with MetS.

Predictability of depression severity based on posterior alpha oscillations.

PubMed

Jiang, H; Popov, T; Jylänki, P; Bi, K; Yao, Z; Lu, Q; Jensen, O; van Gerven, M A J

2016-04-01

We aimed to integrate neural data and an advanced machine learning technique to predict individual major depressive disorder (MDD) patient severity. MEG data was acquired from 22 MDD patients and 22 healthy controls (HC) resting awake with eyes closed. Individual power spectra were calculated by a Fourier transform. Sources were reconstructed via beamforming technique. Bayesian linear regression was applied to predict depression severity based on the spatial distribution of oscillatory power. In MDD patients, decreased theta (4-8 Hz) and alpha (8-14 Hz) power was observed in fronto-central and posterior areas respectively, whereas increased beta (14-30 Hz) power was observed in fronto-central regions. In particular, posterior alpha power was negatively related to depression severity. The Bayesian linear regression model showed significant depression severity prediction performance based on the spatial distribution of both alpha (r=0.68, p=0.0005) and beta power (r=0.56, p=0.007) respectively. Our findings point to a specific alteration of oscillatory brain activity in MDD patients during rest as characterized from MEG data in terms of spectral and spatial distribution. The proposed model yielded a quantitative and objective estimation for the depression severity, which in turn has a potential for diagnosis and monitoring of the recovery process. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

A large-eddy simulation based power estimation capability for wind farms over complex terrain

NASA Astrophysics Data System (ADS)

Senocak, I.; Sandusky, M.; Deleon, R.

2017-12-01

There has been an increasing interest in predicting wind fields over complex terrain at the micro-scale for resource assessment, turbine siting, and power forecasting. These capabilities are made possible by advancements in computational speed from a new generation of computing hardware, numerical methods and physics modelling. The micro-scale wind prediction model presented in this work is based on the large-eddy simulation paradigm with surface-stress parameterization. The complex terrain is represented using an immersed-boundary method that takes into account the parameterization of the surface stresses. Governing equations of incompressible fluid flow are solved using a projection method with second-order accurate schemes in space and time. We use actuator disk models with rotation to simulate the influence of turbines on the wind field. Data regarding power production from individual turbines are mostly restricted because of proprietary nature of the wind energy business. Most studies report percentage drop of power relative to power from the first row. There have been different approaches to predict power production. Some studies simply report available wind power in the upstream, some studies estimate power production using power curves available from turbine manufacturers, and some studies estimate power as torque multiplied by rotational speed. In the present work, we propose a black-box approach that considers a control volume around a turbine and estimate the power extracted from the turbine based on the conservation of energy principle. We applied our wind power prediction capability to wind farms over flat terrain such as the wind farm over Mower County, Minnesota and the Horns Rev offshore wind farm in Denmark. The results from these simulations are in good agreement with published data. We also estimate power production from a hypothetical wind farm in complex terrain region and identify potential zones suitable for wind power production.

Cassini RTG acceptance test results and RTG performance on Galileo and Ulysses

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kelly, C.E.; Klee, P.M.

Flight acceptance testing has been completed for the RTGs to be used on the Cassini spacecraft which is scheduled for an October 6, 1997 launch to Saturn. The acceptance test program includes vibration tests, magnetic field measurements, mass properties (weight and c.g.) and thermal vacuum test. This paper presents the thermal vacuum test results. Three RTGs are to be used, F-2, F-6, and F-7. F-5 is the backup RTG, as it was for the Galileo and Ulysses missions launched in 1989 and 1990, respectively. RTG performance measured during the thermal vacuum tests carried out at the Mound Laboratory facility metmore » all specification requirements. Beginning of mission (BOM) and end of mission (EOM) power predictions have been made based on these tests results. BOM power is predicted to be 888 watts compared to the minimum requirement of 826 watts. Degradation models predict the EOM power after 16 years is to be 640 watts compared to a minimum requirement of 596 watts. Results of small scale module tests are also shown. The modules contain couples from the qualification and flight production runs. The tests have exceeded 28,000 hours (3.2 years) and are continuing to provide increased confidence in the predicted long term performance of the Cassini RTGs. All test results indicate that the power requirements of the Cassini spacecraft will be met. BOM and EOM power margins of over 5% are predicted. Power output from telemetry for the two Galileo RTGs are shown from the 1989 launch to the recent Jupiter encounter. Comparisons of predicted, measured and required performance are shown. Telemetry data are also shown for the RTG on the Ulysses spacecraft which completed its planned mission in 1995 and is now in the extended mission.« less

Cassini RTG acceptance test results and RTG performance on Galileo and Ulysses

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kelly, C.E.; Klee, P.M.

Flight acceptance testing has been completed for the RTGs to be used on the Cassini spacecraft which is scheduled for an October 6, 1997 launch to Saturn. The acceptance test program includes vibration tests, magnetic field measurements, properties (weight and c.g.) and thermal vacuum test. This paper presents The thermal vacuum test results. Three RTGs are to be used, F-2, F-6, and F-7. F-5 is tile back-up RTG, as it was for the Galileo and Ulysses missions launched in 1989 and 1990, respectively. RTG performance measured during the thermal vacuum tests carried out at die Mound Laboratory facility met allmore » specification requirements. Beginning of mission (BOM) and end of mission (EOM) power predictions have been made based on than tests results. BOM power is predicted to be 888 watts compared to the minimum requirement of 826 watts. Degradation models predict the EOM power after 16 years is to be 640 watts compared to a minimum requirement of 596 watts. Results of small scale module tests are also showing. The modules contain couples from the qualification and flight production runs. The tests have exceeded 28,000 hours (3.2 years) and are continuing to provide increased confidence in the predicted long term performance of the Cassini RTGs. All test results indicate that the power requirements of the Cassini spacecraft will be met. BOM and EOM power margins of over five percent are predicted. Power output from telemetry for the two Galileo RTGs are shown from the 1989 launch to the recent Jupiter encounter. Comparisons of predicted, measured and required performance are shown. Telemetry data are also shown for the RTG on the Ulysses spacecraft which completed its planned mission in 1995 and is now in the extended mission.« less

Cassini RTG Acceptance Test Results and RTG Performance on Galileo and Ulysses

DOE R&D Accomplishments Database

Kelly, C. E.; Klee, P. M.

1997-06-01

Flight acceptance testing has been completed for the RTGs to be used on the Cassini spacecraft which is scheduled for an October 6, 1997 launch to Saturn. The acceptance test program includes vibration tests, magnetic field measurements, properties (weight and c.g.) and thermal vacuum test. This paper presents The thermal vacuum test results. Three RTGs are to be used, F 2, F 6, and F 7. F 5 is tile back up RTG, as it was for the Galileo and Ulysses missions launched in 1989 and 1990, respectively. RTG performance measured during the thermal vacuum tests carried out at die Mound Laboratory facility met all specification requirements. Beginning of mission (BOM) and end of mission (EOM) power predictions have been made based on than tests results. BOM power is predicted to be 888 watts compared to the minimum requirement of 826 watts. Degradation models predict the EOM power after 16 years is to be 640 watts compared to a minimum requirement of 596 watts. Results of small scale module tests are also showing. The modules contain couples from the qualification and flight production runs. The tests have exceeded 28,000 hours (3.2 years) and are continuing to provide increased confidence in the predicted long term performance of the Cassini RTGs. All test results indicate that the power requirements of the Cassini spacecraft will be met. BOM and EOM power margins of over five percent are predicted. Power output from telemetry for the two Galileo RTGs are shown from the 1989 launch to the recent Jupiter encounter. Comparisons of predicted, measured and required performance are shown. Telemetry data are also shown for the RTG on the Ulysses spacecraft which completed its planned mission in 1995 and is now in the extended mission.

Prevalence of diseases and statistical power of the Japan Nurses' Health Study.

PubMed

Fujita, Toshiharu; Hayashi, Kunihiko; Katanoda, Kota; Matsumura, Yasuhiro; Lee, Jung Su; Takagi, Hirofumi; Suzuki, Shosuke; Mizunuma, Hideki; Aso, Takeshi

2007-10-01

The Japan Nurses' Health Study (JNHS) is a long-term, large-scale cohort study investigating the effects of various lifestyle factors and healthcare habits on the health of Japanese women. Based on currently limited statistical data regarding the incidence of disease among Japanese women, our initial sample size was tentatively set at 50,000 during the design phase. The actual number of women who agreed to participate in follow-up surveys was approximately 18,000. Taking into account the actual sample size and new information on disease frequency obtained during the baseline component, we established the prevalence of past diagnoses of target diseases, predicted their incidence, and calculated the statistical power for JNHS follow-up surveys. For all diseases except ovarian cancer, the prevalence of a past diagnosis increased markedly with age, and incidence rates could be predicted based on the degree of increase in prevalence between two adjacent 5-yr age groups. The predicted incidence rate for uterine myoma, hypercholesterolemia, and hypertension was > or =3.0 (per 1,000 women, per year), while the rate of thyroid disease, hepatitis, gallstone disease, and benign breast tumor was predicted to be > or =1.0. For these diseases, the statistical power to detect risk factors with a relative risk of 1.5 or more within ten years, was 70% or higher.

CFD code calibration and inlet-fairing effects on a 3D hypersonic powered-simulation model

NASA Technical Reports Server (NTRS)

Huebner, Lawrence D.; Tatum, Kenneth E.

1993-01-01

A three-dimensional (3D) computational study has been performed addressing issues related to the wind tunnel testing of a hypersonic powered-simulation model. The study consisted of three objectives. The first objective was to calibrate a state-of-the-art computational fluid dynamics (CFD) code in its ability to predict hypersonic powered-simulation flows by comparing CFD solutions with experimental surface pressure dam. Aftbody lower surface pressures were well predicted, but lower surface wing pressures were less accurately predicted. The second objective was to determine the 3D effects on the aftbody created by fairing over the inlet; this was accomplished by comparing the CFD solutions of two closed-inlet powered configurations with a flowing-inlet powered configuration. Although results at four freestream Mach numbers indicate that the exhaust plume tends to isolate the aftbody surface from most forebody flowfield differences, a smooth inlet fairing provides the least aftbody force and moment variation compared to a flowing inlet. The final objective was to predict and understand the 3D characteristics of exhaust plume development at selected points on a representative flight path. Results showed a dramatic effect of plume expansion onto the wings as the freestream Mach number and corresponding nozzle pressure ratio are increased.

CFD Code Calibration and Inlet-Fairing Effects On a 3D Hypersonic Powered-Simulation Model

NASA Technical Reports Server (NTRS)

Huebner, Lawrence D.; Tatum, Kenneth E.

1993-01-01

A three-dimensional (3D) computational study has been performed addressing issues related to the wind tunnel testing of a hypersonic powered-simulation model. The study consisted of three objectives. The first objective was to calibrate a state-of-the-art computational fluid dynamics (CFD) code in its ability to predict hypersonic powered-simulation flows by comparing CFD solutions with experimental surface pressure data. Aftbody lower surface pressures were well predicted, but lower surface wing pressures were less accurately predicted. The second objective was to determine the 3D effects on the aftbody created by fairing over the inlet; this was accomplished by comparing the CFD solutions of two closed-inlet powered configurations with a flowing- inlet powered configuration. Although results at four freestream Mach numbers indicate that the exhaust plume tends to isolate the aftbody surface from most forebody flow- field differences, a smooth inlet fairing provides the least aftbody force and moment variation compared to a flowing inlet. The final objective was to predict and understand the 3D characteristics of exhaust plume development at selected points on a representative flight path. Results showed a dramatic effect of plume expansion onto the wings as the freestream Mach number and corresponding nozzle pressure ratio are increased.

A Gaussian Processes Technique for Short-term Load Forecasting with Considerations of Uncertainty

NASA Astrophysics Data System (ADS)

Ohmi, Masataro; Mori, Hiroyuki

In this paper, an efficient method is proposed to deal with short-term load forecasting with the Gaussian Processes. Short-term load forecasting plays a key role to smooth power system operation such as economic load dispatching, unit commitment, etc. Recently, the deregulated and competitive power market increases the degree of uncertainty. As a result, it is more important to obtain better prediction results to save the cost. One of the most important aspects is that power system operator needs the upper and lower bounds of the predicted load to deal with the uncertainty while they require more accurate predicted values. The proposed method is based on the Bayes model in which output is expressed in a distribution rather than a point. To realize the model efficiently, this paper proposes the Gaussian Processes that consists of the Bayes linear model and kernel machine to obtain the distribution of the predicted value. The proposed method is successively applied to real data of daily maximum load forecasting.

Lessons Learned from the Wide Field Camera 3 Flight Correlation

NASA Technical Reports Server (NTRS)

Peabody, Hume L.; Stavely, Richard A.; Townsend, Jackie; Abel, Josh; Mandi, Joe; Bast, William

2010-01-01

The Wide Field Camera 3 (WFC3) instrument was installed into the Hubble Space Telescope (HST) as part of the activities for STS (Space Transportation System)-125 (HST Servicing Mission 4). Initial model predictions for power and radiator temperature were not in good agreement with flight data during a relatively hot, stable period, with the flight power and temperatures being significantly higher than predictions. Significant efforts were undertaken to identify the causes of the discrepancies and to resolve the flight model correlation problems as the thermal vacuum test correlation indicated good agreement. The WFC3 thermal design performance has proven difficult to accurately predict, since the power dissipation on the radiator typically increases as the radiator temperature increases, due to a Thermo Electric Cooler (TEC) attached to the this radiator. This self beating continues until the radiative emissive capability is met for a given temperature, and only then does the system find a quasi-steady regime. Various other factors may also contribute to the radiator temperature, such as backloadlng from the observatory itself and the planet, local high-absorptivity regions near fasteners/holes, and temperature varying parasitic heat leaks from the instrument itself to the radiator. Each of these effects in turn may increase the radiator temperature, and furthermore the demand on the TEC.

Power Relative to Body Mass Best Predicts Change in Core Temperature During Exercise-Heat Stress.

PubMed

Gibson, Oliver R; Willmott, Ashley G B; James, Carl A; Hayes, Mark; Maxwell, Neil S

2017-02-01

Gibson, OR, Willmott, AGB, James, CA, Hayes, M, and Maxwell, NS. Power relative to body mass best predicts change in core temperature during exercise-heat stress. J Strength Cond Res 31(2): 403-414, 2017-Controlling internal temperature is crucial when prescribing exercise-heat stress, particularly during interventions designed to induce thermoregulatory adaptations. This study aimed to determine the relationship between the rate of rectal temperature (Trec) increase, and various methods for prescribing exercise-heat stress, to identify the most efficient method of prescribing isothermic heat acclimation (HA) training. Thirty-five men cycled in hot conditions (40° C, 39% R.H.) for 29 ± 2 minutes. Subjects exercised at 60 ± 9% V[Combining Dot Above]O2peak, with methods for prescribing exercise retrospectively observed for each participant. Pearson product moment correlations were calculated for each prescriptive variable against the rate of change in Trec (° C·h), with stepwise multiple regressions performed on statistically significant variables (p ≤ 0.05). Linear regression identified the predicted intensity required to increase Trec by 1.0-2.0° C between 20- and 45-minute periods and the duration taken to increase Trec by 1.5° C in response to incremental intensities to guide prescription. Significant (p ≤ 0.05) relationships with the rate of change in Trec were observed for prescriptions based on relative power (W·kg; r = 0.764), power (%Powermax; r = 0.679), rating of perceived exertion (RPE) (r = 0.577), V[Combining Dot Above]O2 (%V[Combining Dot Above]O2peak; r = 0.562), heart rate (HR) (%HRmax; r = 0.534), and thermal sensation (r = 0.311). Stepwise multiple regressions observed relative power and RPE as variables to improve the model (r = 0.791), with no improvement after inclusion of any anthropometric variable. Prescription of exercise under heat stress using power (W·kg or %Powermax) has the strongest relationship with the rate of change in Trec with no additional requirement to correct for body composition within a normal range. Practitioners should therefore prescribe exercise intensity using relative power during isothermic HA training to increase Trec efficiently and maximize adaptation.

Single crystals and nonlinear process for outstanding vibration-powered electrical generators.

PubMed

Badel, Adrien; Benayad, Abdelmjid; Lefeuvre, Elie; Lebrun, Laurent; Richard, Claude; Guyomar, Daniel

2006-04-01

This paper compares the performances of vibration-powered electrical generators using a piezoelectric ceramic and a piezoelectric single crystal associated to several power conditioning circuits. A new approach of the piezoelectric power conversion based on a nonlinear voltage processing is presented, leading to three novel high performance power conditioning interfaces. Theoretical predictions and experimental results show that the nonlinear processing technique may increase the power harvested by a factor of 8 compared to standard techniques. Moreover, it is shown that, for a given energy harvesting technique, generators using single crystals deliver 20 times more power than generators using piezoelectric ceramics.

Abundance matters: a field experiment testing the more individuals hypothesis for richness–productivity relationships

PubMed Central

Yee, D. A.; Juliano, S. A.

2007-01-01

The more individuals hypothesis (MIH) postulates that productivity increases species richness by increasing mean equilibrium population size, thereby reducing the probability of local extinction. We tested the MIH for invertebrates colonizing microcosms that simulated tree holes by manipulating productivity through additions of leaf or animal detritus and subsequently determining the relationships among richness, total abundance, abundance per species, and measures of productivity. We quantified productivity as the rate of microorganism protein synthesis, microorganism metabolic rate, nutrient ion concentration, and type and amount of detritus. Microcosms with animal detritus attracted more species, more individuals per species, and more total individuals than did microcosms with similar amounts of leaf detritus. Relationships between richness or abundance and productivity varied with date. Richness in June increased as a linear function of productivity, whereas the power function predicted by the MIH fit best in July. Abundance in June and July was best described by a power function of productivity, but the linear function predicted by the MIH fit best in September. Abundance per species was best described by a power function of productivity in June and July. Path analysis showed that the indirect effect of productivity through abundance on richness that is predicted by MIH was important in all months, and that direct links between productivity and richness were unnecessary. Our results support many of the predictions of the MIH, but they also suggest that the effects of abundance on richness may be more complex than expected. PMID:17401581

Local Burn-Up Effects in the NBSR Fuel Element

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brown N. R.; Hanson A.; Diamond, D.

2013-01-31

This study addresses the over-prediction of local power when the burn-up distribution in each half-element of the NBSR is assumed to be uniform. A single-element model was utilized to quantify the impact of axial and plate-wise burn-up on the power distribution within the NBSR fuel elements for both high-enriched uranium (HEU) and low-enriched uranium (LEU) fuel. To validate this approach, key parameters in the single-element model were compared to parameters from an equilibrium core model, including neutron energy spectrum, power distribution, and integral U-235 vector. The power distribution changes significantly when incorporating local burn-up effects and has lower power peakingmore » relative to the uniform burn-up case. In the uniform burn-up case, the axial relative power peaking is over-predicted by as much as 59% in the HEU single-element and 46% in the LEU single-element with uniform burn-up. In the uniform burn-up case, the plate-wise power peaking is over-predicted by as much as 23% in the HEU single-element and 18% in the LEU single-element. The degree of over-prediction increases as a function of burn-up cycle, with the greatest over-prediction at the end of Cycle 8. The thermal flux peak is always in the mid-plane gap; this causes the local cumulative burn-up near the mid-plane gap to be significantly higher than the fuel element average. Uniform burn-up distribution throughout a half-element also causes a bias in fuel element reactivity worth, due primarily to the neutronic importance of the fissile inventory in the mid-plane gap region.« less

GABAergic modulation of visual gamma and alpha oscillations and its consequences for working memory performance.

PubMed

Lozano-Soldevilla, Diego; ter Huurne, Niels; Cools, Roshan; Jensen, Ole

2014-12-15

Impressive in vitro research in rodents and computational modeling has uncovered the core mechanisms responsible for generating neuronal oscillations. In particular, GABAergic interneurons play a crucial role for synchronizing neural populations. Do these mechanistic principles apply to human oscillations associated with function? To address this, we recorded ongoing brain activity using magnetoencephalography (MEG) in healthy human subjects participating in a double-blind pharmacological study receiving placebo, 0.5 mg and 1.5 mg of lorazepam (LZP; a benzodiazepine upregulating GABAergic conductance). Participants performed a demanding visuospatial working memory (WM) task. We found that occipital gamma power associated with WM recognition increased with LZP dosage. Importantly, the frequency of the gamma activity decreased with dosage, as predicted by models derived from the rat hippocampus. A regionally specific gamma increase correlated with the drug-related performance decrease. Despite the system-wide pharmacological intervention, gamma power drug modulations were specific to visual cortex: sensorimotor gamma power and frequency during button presses remained unaffected. In contrast, occipital alpha power modulations during the delay interval decreased parametrically with drug dosage, predicting performance impairment. Consistent with alpha oscillations reflecting functional inhibition, LZP affected alpha power strongly in early visual regions not required for the task demonstrating a regional specific occipital impairment. GABAergic interneurons are strongly implicated in the generation of gamma and alpha oscillations in human occipital cortex where drug-induced power modulations predicted WM performance. Our findings bring us an important step closer to linking neuronal dynamics to behavior by embracing established animal models. Copyright © 2014 Elsevier Ltd. All rights reserved.

Diabetes and Impaired Fasting Glucose Prediction Using Anthropometric Indices in Adults from Maracaibo City, Venezuela.

PubMed

Bermúdez, Valmore; Salazar, Juan; Rojas, Joselyn; Calvo, María; Rojas, Milagros; Chávez-Castillo, Mervin; Añez, Roberto; Cabrera, Mayela

2016-12-01

To determine the predictive power of various anthropometric indices for the identification of dysglycemic states in Maracaibo, Venezuela. A cross-sectional study with randomized, multi-staged sampling was realized in 2230 adult subjects of both genders who had their body mass index (BMI), waist circumference (WC) and waist-height ratio (WHR) determined. Diagnoses of type 2 diabetes mellitus (DM2) and impaired fasting glucose (IFG) were made following ADA 2015 criteria. ROC curves were used to evaluate the predictive power of each anthropometric parameter. Area under the curve (AUC) values were compared through Delong's test. Of the total 2230 individuals (52.6 % females), 8.4 % were found to have DM2, and 19.5 % had IFG. Anthropometric parameters displayed greater predictive power regarding newly diagnosed diabetics, where WHR was the most important predictor in both females (AUC = 0.808; CI 95 % 0.715-0.900. Sensitivity: 82.8 %; specificity: 76.2 %) and males (AUC = 0.809; CI 95 % 0.736-0.882. Sensitivity: 78.6 %; specificity: 68.1 %), although all three parameters appeared to have comparable predictive power in this subset. In previously diagnosed diabetic subjects, WHR was superior to both WC and BMI in females, and WHR and WC were both superior to BMI in males. Lower predictive values were found for IFG in both genders. Accumulation of various altered anthropometric measurements was associated with increased odds ratios for both newly and previously diagnosed DM2. The predictive power of anthropometric measurements was greater for DM2 than IFG. We suggest assessment of as many available parameters as possible in the clinical setting.

Accuracy of three-dimensional multislice view Doppler in diagnosis of morbid adherent placenta

PubMed Central

Abdel Moniem, Alaa M.; Ibrahim, Ahmed; Akl, Sherif A.; Aboul-Enen, Loay; Abdelazim, Ibrahim A.

2015-01-01

Objective To detect the accuracy of the three-dimensional multislice view (3D MSV) Doppler in the diagnosis of morbid adherent placenta (MAP). Material and Methods Fifty pregnant women at ≥28 weeks gestation with suspected MAP were included in this prospective study. Two dimensional (2D) trans-abdominal gray-scale ultrasound scan was performed for the subjects to confirm the gestational age, placental location, and findings suggestive of MAP, followed by the 3D power Doppler and then the 3D MSV Doppler to confirm the diagnosis of MAP. Intraoperative findings and histopathology results of removed uteri in cases managed by emergency hysterectomy were compared with preoperative sonographic findings to detect the accuracy of the 3D MSV Doppler in the diagnosis of MAP. Results The 3D MSV Doppler increased the accuracy and predictive values of the diagnostic criteria of MAP compared with the 3D power Doppler. The sensitivity and negative predictive value (NPV) (79.6% and 82.2%, respectively) of crowded vessels over the peripheral sub-placental zone to detect difficult placental separation and considerable intraoperative blood loss in cases of MAP using the 3D power Doppler was increased to 82.6% and 84%, respectively, using the 3D MSV Doppler. In addition, the sensitivity, specificity, and positive predictive value (PPV) (90.9%, 68.8%, and 47%, respectively) of the disruption of the uterine serosa-bladder interface for the detection of emergency hysterectomy in cases of MAP using the 3D power Doppler was increased to 100%, 71.8%, and 50%, respectively, using the 3D MSV Doppler. Conclusion The 3D MSV Doppler is a useful adjunctive tool to the 3D power Doppler or color Doppler to refine the diagnosis of MAP. PMID:26401104

The Power Spectrum of Ionic Nanopore Currents: The Role of Ion Correlations.

PubMed

Zorkot, Mira; Golestanian, Ramin; Bonthuis, Douwe Jan

2016-04-13

We calculate the power spectrum of electric-field-driven ion transport through nanometer-scale membrane pores using both linearized mean-field theory and Langevin dynamics simulations. Remarkably, the linearized mean-field theory predicts a plateau in the power spectral density at low frequency ω, which is confirmed by the simulations at low ion concentration. At high ion concentration, however, the power spectral density follows a power law that is reminiscent of the 1/ω(α) dependence found experimentally at low frequency. On the basis of simulations with and without ion-ion interactions, we attribute the low-frequency power-law dependence to ion-ion correlations. We show that neither a static surface charge density, nor an increased pore length, nor an increased ion valency have a significant effect on the shape of the power spectral density at low frequency.

Sixty-five years of the long march in protein secondary structure prediction: the final stretch?

PubMed Central

Yang, Yuedong; Gao, Jianzhao; Wang, Jihua; Heffernan, Rhys; Hanson, Jack; Paliwal, Kuldip; Zhou, Yaoqi

2018-01-01

Abstract Protein secondary structure prediction began in 1951 when Pauling and Corey predicted helical and sheet conformations for protein polypeptide backbone even before the first protein structure was determined. Sixty-five years later, powerful new methods breathe new life into this field. The highest three-state accuracy without relying on structure templates is now at 82–84%, a number unthinkable just a few years ago. These improvements came from increasingly larger databases of protein sequences and structures for training, the use of template secondary structure information and more powerful deep learning techniques. As we are approaching to the theoretical limit of three-state prediction (88–90%), alternative to secondary structure prediction (prediction of backbone torsion angles and Cα-atom-based angles and torsion angles) not only has more room for further improvement but also allows direct prediction of three-dimensional fragment structures with constantly improved accuracy. About 20% of all 40-residue fragments in a database of 1199 non-redundant proteins have <6 Å root-mean-squared distance from the native conformations by SPIDER2. More powerful deep learning methods with improved capability of capturing long-range interactions begin to emerge as the next generation of techniques for secondary structure prediction. The time has come to finish off the final stretch of the long march towards protein secondary structure prediction. PMID:28040746

An augmented classical least squares method for quantitative Raman spectral analysis against component information loss.

PubMed

Zhou, Yan; Cao, Hui

2013-01-01

We propose an augmented classical least squares (ACLS) calibration method for quantitative Raman spectral analysis against component information loss. The Raman spectral signals with low analyte concentration correlations were selected and used as the substitutes for unknown quantitative component information during the CLS calibration procedure. The number of selected signals was determined by using the leave-one-out root-mean-square error of cross-validation (RMSECV) curve. An ACLS model was built based on the augmented concentration matrix and the reference spectral signal matrix. The proposed method was compared with partial least squares (PLS) and principal component regression (PCR) using one example: a data set recorded from an experiment of analyte concentration determination using Raman spectroscopy. A 2-fold cross-validation with Venetian blinds strategy was exploited to evaluate the predictive power of the proposed method. The one-way variance analysis (ANOVA) was used to access the predictive power difference between the proposed method and existing methods. Results indicated that the proposed method is effective at increasing the robust predictive power of traditional CLS model against component information loss and its predictive power is comparable to that of PLS or PCR.

Predicting Microbial Fuel Cell Biofilm Communities and Bioreactor Performance using Artificial Neural Networks.

PubMed

Lesnik, Keaton Larson; Liu, Hong

2017-09-19

The complex interactions that occur in mixed-species bioelectrochemical reactors, like microbial fuel cells (MFCs), make accurate predictions of performance outcomes under untested conditions difficult. While direct correlations between any individual waste stream characteristic or microbial community structure and reactor performance have not been able to be directly established, the increase in sequencing data and readily available computational power enables the development of alternate approaches. In the current study, 33 MFCs were evaluated under a range of conditions including eight separate substrates and three different wastewaters. Artificial Neural Networks (ANNs) were used to establish mathematical relationships between wastewater/solution characteristics, biofilm communities, and reactor performance. ANN models that incorporated biotic interactions predicted reactor performance outcomes more accurately than those that did not. The average percent error of power density predictions was 16.01 ± 4.35%, while the average percent error of Coulombic efficiency and COD removal rate predictions were 1.77 ± 0.57% and 4.07 ± 1.06%, respectively. Predictions of power density improved to within 5.76 ± 3.16% percent error through classifying taxonomic data at the family versus class level. Results suggest that the microbial communities and performance of bioelectrochemical systems can be accurately predicted using data-mining, machine-learning techniques.

The in-training examination: an analysis of its predictive value on performance on the general pediatrics certification examination.

PubMed

Althouse, Linda A; McGuinness, Gail A

2008-09-01

This study investigates the predictive validity of the In-Training Examination (ITE). Although studies have confirmed the predictive validity of ITEs in other medical specialties, no study has been done for general pediatrics. Each year, residents in accredited pediatric training programs take the ITE as a self-assessment instrument. The ITE is similar to the American Board of Pediatrics General Pediatrics Certifying Examination. First-time takers of the certifying examination over a 5-year period who took at least 1 ITE examination were included in the sample. Regression models analyzed the predictive value of the ITE. The predictive power of the ITE in the first training year is minimal. However, the predictive power of the ITE increases each year, providing the greatest power in the third year of training. Even though ITE scores provide information regarding the likelihood of passing the certification examination, the data should be used with caution, particularly in the first training year. Other factors also must be considered when predicting performance on the certification examination. This study continues to support the ITE as an assessment tool for program directors, as well as a means of providing residents with feedback regarding their acquisition of pediatric knowledge.

Learning temporal context shapes prestimulus alpha oscillations and improves visual discrimination performance.

PubMed

Toosi, Tahereh; K Tousi, Ehsan; Esteky, Hossein

2017-08-01

Time is an inseparable component of every physical event that we perceive, yet it is not clear how the brain processes time or how the neuronal representation of time affects our perception of events. Here we asked subjects to perform a visual discrimination task while we changed the temporal context in which the stimuli were presented. We collected electroencephalography (EEG) signals in two temporal contexts. In predictable blocks stimuli were presented after a constant delay relative to a visual cue, and in unpredictable blocks stimuli were presented after variable delays relative to the visual cue. Four subsecond delays of 83, 150, 400, and 800 ms were used in the predictable and unpredictable blocks. We observed that predictability modulated the power of prestimulus alpha oscillations in the parieto-occipital sites: alpha power increased in the 300-ms window before stimulus onset in the predictable blocks compared with the unpredictable blocks. This modulation only occurred in the longest delay period, 800 ms, in which predictability also improved the behavioral performance of the subjects. Moreover, learning the temporal context shaped the prestimulus alpha power: modulation of prestimulus alpha power grew during the predictable block and correlated with performance enhancement. These results suggest that the brain is able to learn the subsecond temporal context of stimuli and use this to enhance sensory processing. Furthermore, the neural correlate of this temporal prediction is reflected in the alpha oscillations. NEW & NOTEWORTHY It is not well understood how the uncertainty in the timing of an external event affects its processing, particularly at subsecond scales. Here we demonstrate how a predictable timing scheme improves visual processing. We found that learning the predictable scheme gradually shaped the prestimulus alpha power. These findings indicate that the human brain is able to extract implicit subsecond patterns in the temporal context of events. Copyright © 2017 the American Physiological Society.

What can nuclear energy do for society?

NASA Technical Reports Server (NTRS)

Rom, F. E.

1971-01-01

The utilization of nuclear energy and the predicted impact of future uses of nuclear energy are discussed. Areas of application in electric power production and transportation methods are described. It is concluded that the need for many forms of nuclear energy will become critical as the requirements for power to supply an increasing population are met.

A simulation of cross-country skiing on varying terrain by using a mathematical power balance model

PubMed Central

Moxnes, John F; Sandbakk, Øyvind; Hausken, Kjell

2013-01-01

The current study simulated cross-country skiing on varying terrain by using a power balance model. By applying the hypothetical inductive deductive method, we compared the simulated position along the track with actual skiing on snow, and calculated the theoretical effect of friction and air drag on skiing performance. As input values in the model, air drag and friction were estimated from the literature, whereas the model included relationships between heart rate, metabolic rate, and work rate based on the treadmill roller-ski testing of an elite cross-country skier. We verified this procedure by testing four models of metabolic rate against experimental data on the treadmill. The experimental data corresponded well with the simulations, with the best fit when work rate was increased on uphill and decreased on downhill terrain. The simulations predicted that skiing time increases by 3%–4% when either friction or air drag increases by 10%. In conclusion, the power balance model was found to be a useful tool for predicting how various factors influence racing performance in cross-country skiing. PMID:24379718

A simulation of cross-country skiing on varying terrain by using a mathematical power balance model.

PubMed

Moxnes, John F; Sandbakk, Oyvind; Hausken, Kjell

2013-01-01

The current study simulated cross-country skiing on varying terrain by using a power balance model. By applying the hypothetical inductive deductive method, we compared the simulated position along the track with actual skiing on snow, and calculated the theoretical effect of friction and air drag on skiing performance. As input values in the model, air drag and friction were estimated from the literature, whereas the model included relationships between heart rate, metabolic rate, and work rate based on the treadmill roller-ski testing of an elite cross-country skier. We verified this procedure by testing four models of metabolic rate against experimental data on the treadmill. The experimental data corresponded well with the simulations, with the best fit when work rate was increased on uphill and decreased on downhill terrain. The simulations predicted that skiing time increases by 3%-4% when either friction or air drag increases by 10%. In conclusion, the power balance model was found to be a useful tool for predicting how various factors influence racing performance in cross-country skiing.

Preliminary power train design for a state-of-the-art electric vehicle

NASA Technical Reports Server (NTRS)

Ross, J. A.; Wooldridge, G. A.

1978-01-01

The state-of-the-art (SOTA) of electric vehicles built since 1965 was reviewed to establish a base for the preliminary design of a power train for a SOTA electric vehicle. The performance of existing electric vehicles were evaluated to establish preliminary specifications for a power train design using state-of-the-art technology and commercially available components. Power train components were evaluated and selected using a computer simulation of the SAE J227a Schedule D driving cycle. Predicted range was determined for a number of motor and controller combinations in conjunction with the mechanical elements of power trains and a battery pack of sixteen lead-acid batteries - 471.7 kg at 0.093 MJ/Kg (1040 lbs. at 11.7 Whr/lb). On the basis of maximum range and overall system efficiency using the Schedule D cycle, an induction motor and 3 phase inverter/controller was selected as the optimum combination when used with a two-speed transaxle and steel belted radial tires. The predicted Schedule D range is 90.4 km (56.2 mi). Four near term improvements to the SOTA were identified, evaluated, and predicted to increase range approximately 7%.

Discrete Element Model for Simulations of Early-Life Thermal Fracturing Behaviors in Ceramic Nuclear Fuel Pellets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hai Huang; Ben Spencer; Jason Hales

2014-10-01

A discrete element Model (DEM) representation of coupled solid mechanics/fracturing and heat conduction processes has been developed and applied to explicitly simulate the random initiations and subsequent propagations of interacting thermal cracks in a ceramic nuclear fuel pellet during initial rise to power and during power cycles. The DEM model clearly predicts realistic early-life crack patterns including both radial cracks and circumferential cracks. Simulation results clearly demonstrate the formation of radial cracks during the initial power rise, and formation of circumferential cracks as the power is ramped down. In these simulations, additional early-life power cycles do not lead to themore » formation of new thermal cracks. They do, however clearly indicate changes in the apertures of thermal cracks during later power cycles due to thermal expansion and shrinkage. The number of radial cracks increases with increasing power, which is consistent with the experimental observations.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hoke, Anderson; Shirazi, Mariko; Chakraborty, Sudipta

As deployment of power electronic coupled generation such as photovoltaic (PV) systems increases, grid operators have shown increasing interest in calling on inverter-coupled generation to help mitigate frequency contingency events by rapidly surging active power into the grid. When responding to contingency events, the faster the active power is provided, the more effective it may be for arresting the frequency event. This paper proposes a predictive PV inverter control method for very fast and accurate control of active power. This rapid active power control method will increase the effectiveness of various higher-level controls designed to mitigate grid frequency contingency events,more » including fast power-frequency droop, inertia emulation, and fast frequency response, without the need for energy storage. The rapid active power control method, coupled with a maximum power point estimation method, is implemented in a prototype PV inverter connected to a PV array. The prototype inverter's response to various frequency events is experimentally confirmed to be fast (beginning within 2 line cycles and completing within 4.5 line cycles of a severe test event) and accurate (below 2% steady-state error).« less

High serum total cholesterol is a long-term cause of osteoporotic fracture.

PubMed

Trimpou, P; Odén, A; Simonsson, T; Wilhelmsen, L; Landin-Wilhelmsen, K

2011-05-01

Risk factors for osteoporotic fractures were evaluated in 1,396 men and women for a period of 20 years. Serum total cholesterol was found to be an independent osteoporotic fracture risk factor whose predictive power improves with time. The purpose of this study was to evaluate long-term risk factors for osteoporotic fracture. A population random sample of men and women aged 25-64 years (the Gothenburg WHO MONICA project, N = 1,396, 53% women) was studied prospectively. The 1985 baseline examination recorded physical activity at work and during leisure time, psychological stress, smoking habits, coffee consumption, BMI, waist/hip ratio, blood pressure, total, HDL and LDL cholesterol, triglycerides, and fibrinogen. Osteoporotic fractures over a period of 20 years were retrieved from the Gothenburg hospital registers. Poisson regression was used to analyze the predictive power for osteoporotic fracture of each risk factor. A total number of 258 osteoporotic fractures occurred in 143 participants (10.2%). As expected, we found that previous fracture, smoking, coffee consumption, and lower BMI each increase the risk for osteoporotic fracture independently of age and sex. More unexpectedly, we found that the gradient of risk of serum total cholesterol to predict osteoporotic fracture significantly increases over time (p = 0.0377). Serum total cholesterol is an independent osteoporotic fracture risk factor whose predictive power improves with time. High serum total cholesterol is a long-term cause of osteoporotic fracture.

Correlation between molecular secondary ion yield and cluster ion sputtering for samples with different stopping powers

NASA Astrophysics Data System (ADS)

Heile, A.; Muhmann, C.; Lipinsky, D.; Arlinghaus, H. F.

2012-07-01

In static SIMS, the secondary ion yield, defined as detected ions per primary ion, can be increased by altering several primary ion parameters. For many years, no quantitative predictions could be made for the secondary ion yield enhancement of molecular ions. For thick samples of organic compounds, a power dependency of the secondary ion yield on the sputtering yield was shown. For this article, samples with thick molecular layers and (sub-)monolayers composed of various molecules were prepared on inorganic substrates such as silicon, silver, and gold, and subsequently analyzed. For primary ion bombardment, monoatomic (Ne+, Ar+, Ga+, Kr+, Xe+, Bi+) as well as polyatomic (Bin+, Bin++) primary ions were used within an energy range of 10-50 keV. The power dependency was found to hold true for the different samples; however, the exponent decreased with increasing stopping power. Based on these findings, a rule of thumb is proposed for the prediction of the lower limit of the secondary ion yield enhancement as a function of the primary ion species. Additionally, effects caused by the variation of the energy deposition are discussed, including the degree of molecular fragmentation and the non-linear increase of the secondary ion yield when polyatomic primary ions are used.

Thermodynamics Analysis of Binary Plant Generating Power from Low-Temperature Geothermal Resource

NASA Astrophysics Data System (ADS)

Maksuwan, A.

2018-05-01

The purpose in this research was to predict tendency of increase Carnot efficiency of the binary plant generating power from low-temperature geothermal resource. Low-temperature geothermal resources or less, are usually exploited by means of binary-type energy conversion systems. The maximum efficiency is analyzed for electricity production of the binary plant generating power from low-temperature geothermal resource becomes important. By using model of the heat exchanger equivalent to a power plant together with the calculation of the combined heat and power (CHP) generation. The CHP was solved in detail with appropriate boundary originating an idea from the effect of temperature of source fluid inlet-outlet and cooling fluid supply. The Carnot efficiency from the CHP calculation was compared between condition of increase temperature of source fluid inlet-outlet and decrease temperature of cooling fluid supply. Result in this research show that the Carnot efficiency for binary plant generating power from low-temperature geothermal resource has tendency increase by decrease temperature of cooling fluid supply.

Integrated Wind Power Planning Tool

NASA Astrophysics Data System (ADS)

Rosgaard, M. H.; Giebel, G.; Nielsen, T. S.; Hahmann, A.; Sørensen, P.; Madsen, H.

2012-04-01

This poster presents the current state of the public service obligation (PSO) funded project PSO 10464, with the working title "Integrated Wind Power Planning Tool". The project commenced October 1, 2011, and the goal is to integrate a numerical weather prediction (NWP) model with purely statistical tools in order to assess wind power fluctuations, with focus on long term power system planning for future wind farms as well as short term forecasting for existing wind farms. Currently, wind power fluctuation models are either purely statistical or integrated with NWP models of limited resolution. With regard to the latter, one such simulation tool has been developed at the Wind Energy Division, Risø DTU, intended for long term power system planning. As part of the PSO project the inferior NWP model used at present will be replaced by the state-of-the-art Weather Research & Forecasting (WRF) model. Furthermore, the integrated simulation tool will be improved so it can handle simultaneously 10-50 times more turbines than the present ~ 300, as well as additional atmospheric parameters will be included in the model. The WRF data will also be input for a statistical short term prediction model to be developed in collaboration with ENFOR A/S; a danish company that specialises in forecasting and optimisation for the energy sector. This integrated prediction model will allow for the description of the expected variability in wind power production in the coming hours to days, accounting for its spatio-temporal dependencies, and depending on the prevailing weather conditions defined by the WRF output. The output from the integrated prediction tool constitute scenario forecasts for the coming period, which can then be fed into any type of system model or decision making problem to be solved. The high resolution of the WRF results loaded into the integrated prediction model will ensure a high accuracy data basis is available for use in the decision making process of the Danish transmission system operator, and the need for high accuracy predictions will only increase over the next decade as Denmark approaches the goal of 50% wind power based electricity in 2020, from the current 20%.

Application of the aeroacoustic analogy to a shrouded, subsonic, radial fan

NASA Astrophysics Data System (ADS)

Buccieri, Bryan M.; Richards, Christopher M.

2016-12-01

A study was conducted to investigate the predictive capability of computational aeroacoustics with respect to a shrouded, subsonic, radial fan. A three dimensional unsteady fluid dynamics simulation was conducted to produce aerodynamic data used as the acoustic source for an aeroacoustics simulation. Two acoustic models were developed: one modeling the forces on the rotating fan blades as a set of rotating dipoles located at the center of mass of each fan blade and one modeling the forces on the stationary fan shroud as a field of distributed stationary dipoles. Predicted acoustic response was compared to experimental data measured at two operating speeds using three different outlet restrictions. The blade source model predicted overall far field sound power levels within 5 dB averaged over the six different operating conditions while the shroud model predicted overall far field sound power levels within 7 dB averaged over the same conditions. Doubling the density of the computational fluids mesh and using a scale adaptive simulation turbulence model increased broadband noise accuracy. However, computation time doubled and the accuracy of the overall sound power level prediction improved by only 1 dB.

Power decreases trust in social exchange

PubMed Central

Schilke, Oliver; Reimann, Martin; Cook, Karen S.

2015-01-01

How does lacking vs. possessing power in a social exchange affect people’s trust in their exchange partner? An answer to this question has broad implications for a number of exchange settings in which dependence plays an important role. Here, we report on a series of experiments in which we manipulated participants’ power position in terms of structural dependence and observed their trust perceptions and behaviors. Over a variety of different experimental paradigms and measures, we find that more powerful actors place less trust in others than less powerful actors do. Our results contradict predictions by rational actor models, which assume that low-power individuals are able to anticipate that a more powerful exchange partner will place little value on the relationship with them, thus tends to behave opportunistically, and consequently cannot be trusted. Conversely, our results support predictions by motivated cognition theory, which posits that low-power individuals want their exchange partner to be trustworthy and then act according to that desire. Mediation analyses show that, consistent with the motivated cognition account, having low power increases individuals’ hope and, in turn, their perceptions of their exchange partners’ benevolence, which ultimately leads them to trust. PMID:26438869

Power decreases trust in social exchange.

PubMed

Schilke, Oliver; Reimann, Martin; Cook, Karen S

2015-10-20

How does lacking vs. possessing power in a social exchange affect people's trust in their exchange partner? An answer to this question has broad implications for a number of exchange settings in which dependence plays an important role. Here, we report on a series of experiments in which we manipulated participants' power position in terms of structural dependence and observed their trust perceptions and behaviors. Over a variety of different experimental paradigms and measures, we find that more powerful actors place less trust in others than less powerful actors do. Our results contradict predictions by rational actor models, which assume that low-power individuals are able to anticipate that a more powerful exchange partner will place little value on the relationship with them, thus tends to behave opportunistically, and consequently cannot be trusted. Conversely, our results support predictions by motivated cognition theory, which posits that low-power individuals want their exchange partner to be trustworthy and then act according to that desire. Mediation analyses show that, consistent with the motivated cognition account, having low power increases individuals' hope and, in turn, their perceptions of their exchange partners' benevolence, which ultimately leads them to trust.

Identification and Management of Pump Thrombus in the HeartWare Left Ventricular Assist Device System: A Novel Approach Using Log File Analysis.

PubMed

Jorde, Ulrich P; Aaronson, Keith D; Najjar, Samer S; Pagani, Francis D; Hayward, Christopher; Zimpfer, Daniel; Schlöglhofer, Thomas; Pham, Duc T; Goldstein, Daniel J; Leadley, Katrin; Chow, Ming-Jay; Brown, Michael C; Uriel, Nir

2015-11-01

The study sought to characterize patterns in the HeartWare (HeartWare Inc., Framingham, Massachusetts) ventricular assist device (HVAD) log files associated with successful medical treatment of device thrombosis. Device thrombosis is a serious adverse event for mechanical circulatory support devices and is often preceded by increased power consumption. Log files of the pump power are easily accessible on the bedside monitor of HVAD patients and may allow early diagnosis of device thrombosis. Furthermore, analysis of the log files may be able to predict the success rate of thrombolysis or the need for pump exchange. The log files of 15 ADVANCE trial patients (algorithm derivation cohort) with 16 pump thrombus events treated with tissue plasminogen activator (tPA) were assessed for changes in the absolute and rate of increase in power consumption. Successful thrombolysis was defined as a clinical resolution of pump thrombus including normalization of power consumption and improvement in biochemical markers of hemolysis. Significant differences in log file patterns between successful and unsuccessful thrombolysis treatments were verified in 43 patients with 53 pump thrombus events implanted outside of clinical trials (validation cohort). The overall success rate of tPA therapy was 57%. Successful treatments had significantly lower measures of percent of expected power (130.9% vs. 196.1%, p = 0.016) and rate of increase in power (0.61 vs. 2.87, p < 0.0001). Medical therapy was successful in 77.7% of the algorithm development cohort and 81.3% of the validation cohort when the rate of power increase and percent of expected power values were <1.25% and 200%, respectively. Log file parameters can potentially predict the likelihood of successful tPA treatments and if validated prospectively, could substantially alter the approach to thrombus management. Copyright © 2015 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

New algorithm for toric intraocular lens power calculation considering the posterior corneal astigmatism.

PubMed

Canovas, Carmen; Alarcon, Aixa; Rosén, Robert; Kasthurirangan, Sanjeev; Ma, Joseph J K; Koch, Douglas D; Piers, Patricia

2018-02-01

To assess the accuracy of toric intraocular lens (IOL) power calculations of a new algorithm that incorporates the effect of posterior corneal astigmatism (PCA). Abbott Medical Optics, Inc., Groningen, the Netherlands. Retrospective case report. In eyes implanted with toric IOLs, the exact vergence formula of the Tecnis toric calculator was used to predict refractive astigmatism from preoperative biometry, surgeon-estimated surgically induced astigmatism (SIA), and implanted IOL power, with and without including the new PCA algorithm. For each calculation method, the error in predicted refractive astigmatism was calculated as the vector difference between the prediction and the actual refraction. Calculations were also made using postoperative keratometry (K) values to eliminate the potential effect of incorrect SIA estimates. The study comprised 274 eyes. The PCA algorithm significantly reduced the centroid error in predicted refractive astigmatism (P < .001). With the PCA algorithm, the centroid error reduced from 0.50 @ 1 to 0.19 @ 3 when using preoperative K values and from 0.30 @ 0 to 0.02 @ 84 when using postoperative K values. Patients who had anterior corneal against-the-rule, with-the-rule, and oblique astigmatism had improvement with the PCA algorithm. In addition, the PCA algorithm reduced the median absolute error in all groups (P < .001). The use of the new PCA algorithm decreased the error in the prediction of residual refractive astigmatism in eyes implanted with toric IOLs. Therefore, the new PCA algorithm, in combination with an exact vergence IOL power calculation formula, led to an increased predictability of toric IOL power. Copyright © 2018 ASCRS and ESCRS. Published by Elsevier Inc. All rights reserved.

Very-short-term wind power prediction by a hybrid model with single- and multi-step approaches

NASA Astrophysics Data System (ADS)

Mohammed, E.; Wang, S.; Yu, J.

2017-05-01

Very-short-term wind power prediction (VSTWPP) has played an essential role for the operation of electric power systems. This paper aims at improving and applying a hybrid method of VSTWPP based on historical data. The hybrid method is combined by multiple linear regressions and least square (MLR&LS), which is intended for reducing prediction errors. The predicted values are obtained through two sub-processes:1) transform the time-series data of actual wind power into the power ratio, and then predict the power ratio;2) use the predicted power ratio to predict the wind power. Besides, the proposed method can include two prediction approaches: single-step prediction (SSP) and multi-step prediction (MSP). WPP is tested comparatively by auto-regressive moving average (ARMA) model from the predicted values and errors. The validity of the proposed hybrid method is confirmed in terms of error analysis by using probability density function (PDF), mean absolute percent error (MAPE) and means square error (MSE). Meanwhile, comparison of the correlation coefficients between the actual values and the predicted values for different prediction times and window has confirmed that MSP approach by using the hybrid model is the most accurate while comparing to SSP approach and ARMA. The MLR&LS is accurate and promising for solving problems in WPP.

From Power to Inaction.

PubMed

Durso, Geoffrey R O; Briñol, Pablo; Petty, Richard E

2016-12-01

Research has shown that people who feel powerful are more likely to act than those who feel powerless, whereas people who feel ambivalent are less likely to act than those whose reactions are univalent (entirely positive or entirely negative). But what happens when powerful people also are ambivalent? On the basis of the self-validation theory of judgment, we hypothesized that power and ambivalence would interact to predict individuals' action. Because power can validate individuals' reactions, we reasoned that feeling powerful strengthens whatever reactions people have during a decision. It can strengthen univalent reactions and increase action orientation, as shown in past research. Among people who hold an ambivalent judgment, however, those who feel powerful would be less action oriented than those who feel powerless. Two experiments provide evidence for this hypothesized interactive effect of power and ambivalence on individuals' action tendencies during both positive decisions (promoting an employee; Experiment 1) and negative decisions (firing an employee; Experiment 2). In summary, when individuals' reactions are ambivalent, power increases the likelihood of inaction.

Investigation at supersonic and subsonic Mach numbers of auxiliary inlets supplying secondary air flow to ejector exhaust nozzles

NASA Technical Reports Server (NTRS)

Hearth, Donald P; Cubbison, Robert W

1956-01-01

The results indicated increases in auxiliary-inlet pressure recovery with increases in scoop height relative to the boundary-layer thickness. The pressure recovery increased at about the same rate as theoretically predicted for an inlet in a boundary layer having a one-seventh power profile, but was only about 0.68 to 0.75 of the theoretically obtainable values. Under some operating conditions, flow from the primary jet was exhausted through the auxiliary inlet. This phenomenon could be predicted from the ejector pumping characteristics.

A new framework to increase the efficiency of large-scale solar power plants.

NASA Astrophysics Data System (ADS)

Alimohammadi, Shahrouz; Kleissl, Jan P.

2015-11-01

A new framework to estimate the spatio-temporal behavior of solar power is introduced, which predicts the statistical behavior of power output at utility scale Photo-Voltaic (PV) power plants. The framework is based on spatio-temporal Gaussian Processes Regression (Kriging) models, which incorporates satellite data with the UCSD version of the Weather and Research Forecasting model. This framework is designed to improve the efficiency of the large-scale solar power plants. The results are also validated from measurements of the local pyranometer sensors, and some improvements in different scenarios are observed. Solar energy.

Models for 31-Mode PVDF Energy Harvester for Wearable Applications

PubMed Central

Zhao, Jingjing; You, Zheng

2014-01-01

Currently, wearable electronics are increasingly widely used, leading to an increasing need of portable power supply. As a clean and renewable power source, piezoelectric energy harvester can transfer mechanical energy into electric energy directly, and the energy harvester based on polyvinylidene difluoride (PVDF) operating in 31-mode is appropriate to harvest energy from human motion. This paper established a series of theoretical models to predict the performance of 31-mode PVDF energy harvester. Among them, the energy storage one can predict the collected energy accurately during the operation of the harvester. Based on theoretical study and experiments investigation, two approaches to improve the energy harvesting performance have been found. Furthermore, experiment results demonstrate the high accuracies of the models, which are better than 95%. PMID:25114981

Re-Evaluating Satellite Solar Power Systems for Earth

NASA Technical Reports Server (NTRS)

Landis, Geoffrey A.

2006-01-01

The Solar Power Satellite System is a concept to collect solar power in space, and then transport it to the surface of the Earth by microwave (or possibly laser) beam, where if is converted into electrical power for terrestrial use. The recent increase in energy costs, predictions of the near-term exhaustion of oil, and prominence of possible climate change due to the "greenhouse effect" from burning of fossil fuels has again brought alternative energy sources to public attention, and the time is certainly appropriate to reexamine the economics of space based power. Several new concepts for Satellite Power System designs were evaluated to make the concept more economically feasible.

Flight experience of Solar Mesosphere Explorer's two nickel-cadmium batteries

NASA Technical Reports Server (NTRS)

Faber, J.

1985-01-01

The performance of the power system on the solar mesosphere explorer (SME) since launch is discussed. Predictions for continued operation for the rest of the project mission are also discussed. The SME satellite's power system was characterized by both insufficient loading and excessive battery charging during the first year of the mission. These conditions affected battery performance and jeopardized the long-term mission. Increased loading on selected orbits has improved battery performance. Long term projections indicate steadily increasing temperatures for the remainder of the mission.

Streptococcal upper respiratory tract infections and psychosocial stress predict future tic and obsessive-compulsive symptom severity in children and adolescents with Tourette syndrome and/or obsessive-compulsive disorder

PubMed Central

Lin, Haiqun; Williams, Kyle A.; Katsovich, Liliya; Findley, Diane B.; Grantz, Heidi; Lombroso, Paul J.; King, Robert A.; Bessen, Debra E.; Johnson, Dwight; Kaplan, Edward L.; Landeros-Weisenberger, Angeli; Zhang, Heping; Leckman, James F.

2009-01-01

Background: One goal of this prospective longitudinal study was to identify new group A beta hemolytic streptococcal (GABHS) infections in children and adolescents with Tourette syndrome (TS) and/or obsessive-compulsive disorder (OCD) compared to healthy control subjects. We then examined the power of GABHS infections and measures of psychosocial stress to predict future tic, obsessive-compulsive (OC), and depressive symptom severity. Methods: Consecutive ratings of tic, OC and depressive symptom severity were obtained for 45 cases and 41 matched control subjects over a two-year period. Clinical raters were blinded to the results of laboratory tests. Laboratory personnel were blinded to case or control status and clinical ratings. Structural equation modeling for unbalanced repeated measures was used to assess the sequence of new GABHS infections and psychosocial stress and their impact on future symptom severity. Results: Increases in tic and OC symptom severity did not occur after every new GABHS infection. However, the structural equation model found that these newly diagnosed infections were predictive of modest increases in future tic and OC symptom severity, but did not predict future depressive symptom severity. In addition, the inclusion of new infections in the model greatly enhanced, by a factor of three, the power of psychosocial stress in predicting future tic and OC symptom severity. Conclusions: Our data suggest that a minority of children with TS and early-onset OCD were sensitive to antecedent GABHS infections. These infections also enhanced the predictive power of current psychosocial stress on future tic and OC symptom severity. PMID:19833320

Spatially resolved measurement of the core temperature in a high-power thulium fiber system

NASA Astrophysics Data System (ADS)

Walbaum, Till; Heinzig, Matthias; Beier, Franz; Liem, Andreas; Schreiber, Thomas; Eberhardt, Ramona; Tünnermann, Andreas

2016-03-01

We present measurements of the temperature increase inside the active fiber of a thulium fiber amplifier during high power operation. At a pump power of over 100 W at a wavelength of 793 nm, we measure the core temperature distribution along the first section of a large mode area (LMA) highly thulium doped active fiber by use of an optical backscatter reflectometer. A mode field adaptor is used to maintain single mode operation in the LMA fiber. An increase in temperature of over 100 K can be observed in spite of conductive cooling, located at the pumped fiber end and jeopardizing the fiber coating. The recoated splice can be clearly identified as the hottest fiber region. This allows us to estimate the maximum thermally acceptable pump power for this amplifier. We also observe that the temperature can be decreased by increasing the seed power, which is in agreement with theoretical predictions on the increase of cross relaxation efficiency by depletion of the upper laser level. This underlines the role of power scaling of the respective seed power of a thulium amplifier stage as a means of thermal management.

Interdisciplinary challenges in the study of power grid resilience and stability and their relation to extreme weather events

NASA Astrophysics Data System (ADS)

Heitzig, J.; Fujiwara, N.; Aihara, K.; Kurths, J.

2014-10-01

This topical issue collects contributions to the interdisciplinary study of power grid stability in face of increasing volatility of energy production and consumption due to increasing renewable energy infeed and changing climatic conditions. The individual papers focus on different aspects of this field and bring together modern achievements from various disciplines, in particular complex systems science, nonlinear data analysis, control theory, electrical engineering, and climatology. Main topics considered here are prediction and volatility of renewable infeed, modelling and theoretical analysis of power grid topology, dynamics and stability, relationships between stability and complex network topology, and improvements via topological changes or control. Impacts for the design of smart power grids are discussed in detail.

The Anisotropy of the Microwave Background to l = 3500: Deep Field Observations with the Cosmic Background Imager

NASA Technical Reports Server (NTRS)

Mason, B. S.; Pearson, T. J.; Readhead, A. C. S.; Shepherd, M. C.; Sievers, J.; Udomprasert, P. S.; Cartwright, J. K.; Farmer, A. J.; Padin, S.; Myers, S. T.;

Effect of walking velocity on hindlimb kinetics during stance in normal horses.

PubMed

Khumsap, S; Clayton, H M; Lanovaz, J L

2001-04-01

The objectives of this study were to measure the effect of walking velocity on net joint moments and joint powers in the hindlimb during stance and to use the data to predict these variables at different walking velocities. Videographic and force data were collected synchronously from 5 sound horses walking over a force plate at a range of velocities. Force and kinematic data from 56 trials were combined using an inverse dynamic solution to determine net joint moments and joint powers. Analysis by simple regression and correlation (P < 0.05, r2 > or = 0.30, r > 0.50) showed that, in early stance, there were significant velocity-dependent increases in the peak magnitudes of the following variables: extensor moment and positive power at the hip, flexor moment and positive power at the stifle, extensor moment, negative and positive power at the tarsus, and flexor moment and negative power at the fetlock. In late stance, there were significant velocity-dependent increases in the peak magnitudes of the following variables: flexor moment at the hip, negative power at the stifle and flexor moment and positive power at the tarsus. As velocity increased, the hip showed an increase in energy generation, whereas the tarsus showed increases in both energy generation and absorption. It is concluded that an increase in walking velocity is associated with increases in peak magnitudes of the net joint moments and joint powers in the hindlimb; and that energy generation at the hip makes the largest contribution to the increase in velocity.

Evidence of Non-Corresponsive Causal Relationships Between Personality Traits and Social Power Over Time.

PubMed

Wood, Dustin; Harms, P D

2017-01-01

Although the effects of personality traits on social environments are regularly thought to mirror the effects of social environments on personality traits, the causal dynamics existing between personality traits and social power may represent an important exception. Using a sample of 181 fraternity and sorority members surveyed over a year, we show that agentic traits are more likely to show cross-sectional associations with social power, and may increase from the experience of social power. However, increases in social power over a year are predicted better by communal characteristics. The findings are consistent with the understanding that social power acts as a disinhibitor allowing people to enact their desires with less risk and greater efficacy, but is differentially afforded to individuals perceived as likely to promote the goals of others. We discuss the conditions that may need to exist for personality traits and environments to show corresponsive relationships more generally.

Piezoelectric Power Requirements for Active Vibration Control

NASA Technical Reports Server (NTRS)

Brennan, Matthew C.; McGowan, Anna-Maria Rivas

1997-01-01

This paper presents a method for predicting the power consumption of piezoelectric actuators utilized for active vibration control. Analytical developments and experimental tests show that the maximum power required to control a structure using surface-bonded piezoelectric actuators is independent of the dynamics between the piezoelectric actuator and the host structure. The results demonstrate that for a perfectly-controlled system, the power consumption is a function of the quantity and type of piezoelectric actuators and the voltage and frequency of the control law output signal. Furthermore, as control effectiveness decreases, the power consumption of the piezoelectric actuators decreases. In addition, experimental results revealed a non-linear behavior in the material properties of piezoelectric actuators. The material non- linearity displayed a significant increase in capacitance with an increase in excitation voltage. Tests show that if the non-linearity of the capacitance was accounted for, a conservative estimate of the power can easily be determined.

Research on power source structure optimization for East China Power Grid

NASA Astrophysics Data System (ADS)

Xu, Lingjun; Sang, Da; Zhang, Jianping; Tang, Chunyi; Xu, Da

2017-05-01

The structure of east china power grid is not reasonable for the coal power takes a much higher proportion than hydropower, at present the coal power takes charge of most peak load regulation, and the pressure of peak load regulation cannot be ignored. The nuclear power, wind power, photovoltaic, other clean energy and hydropower, coal power and wind power from outside will be actively developed in future, which increases the pressure of peak load regulation. According to development of economic and social, Load status and load prediction, status quo and planning of power source and the characteristics of power source, the peak load regulation balance is carried out and put forward a reasonable plan of power source allocation. The ultimate aim is to optimize the power source structure and to provide reference for power source allocation in east china.

Seasonal thermoregulatory responses in mammals.

PubMed

Lovegrove, Barry G

2005-05-01

This study examined the proportional seasonal winter adjustments of total and mass-specific basal power (watts and watts g-1, respectively), thermal conductance (watts g-1 degrees C-1), non-shivering thermogenesis capacity (ratio of NST/basal power), body temperature ( degrees C), and body mass (g) of mammals. The responses are best summarized for three different body size classes; small mammals (<100 g), intermediate-sized mammals (0.1-10 kg), and large mammals (>10 kg). The principal adjustments of the small mammals center on energy conservation, especially the Dehnel Effect, the winter reduction in body size of as much as 50%, accompanied by reductions in mass-specific basal power. On average, these reductions reduce the total basal power approximately in direct proportion to the mass reductions. Reductions in mass-specific basal power are matched by concomitant reductions in conductance to maintain the setpoint body temperature during winter. The overall thermoregulatory adjustments in small mammals serve to (a) lower overall winter power consumption, (b) maintain the setpoint body temperature, and (c) lower the lower critical limit of thermoneutrality and hence thermoregulatory costs. In intermediate-size mammals, the seasonal response is centered more on increasing thermogenic capacity by increasing basal power and NST capacity, accompanied by predictable and large reductions in conductance. The Dehnel effect is negligible. Very large mammals undergo the largest reductions in total and mass-specific basal power and conductance. However, there are too few data to resolve whether the reductions in total basal power can be attributed to the Dehnel effect, because the moderate decreases in body mass may also be caused by nutritional stress. Apart from the seasonal changes in basal power, these observations are consistent with the predictions of Heldmaier's seasonal acclimatization model.

Impacts of past and future climate change on wind energy resources in the United States

NASA Astrophysics Data System (ADS)

McCaa, J. R.; Wood, A.; Eichelberger, S.; Westrick, K.

2009-12-01

The links between climate change and trends in wind energy resources have important potential implications for the wind energy industry, and have received significant attention in recent studies. We have conducted two studies that provide insights into the potential for climate change to affect future wind power production. In one experiment, we projected changes in power capacity for a hypothetical wind farm located near Kennewick, Washington, due to greenhouse gas-induced climate change, estimated using a set of regional climate model simulations. Our results show that the annual wind farm power capacity is projected to decrease 1.3% by 2050. In a wider study focusing on wind speed instead of power, we analyzed projected changes in wind speed from 14 different climate simulations that were performed in support of the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR4). Our results show that the predicted ensemble mean changes in annual mean wind speeds are expected to be modest. However, seasonal changes and changes predicted by individual models are large enough to affect the profitability of existing and future wind projects. The majority of the model simulations reveal that near-surface wind speed values are expected to shift poleward in response to the IPCC A2 emission scenario, particularly during the winter season. In the United States, most models agree that the mean annual wind speed values will increase in a region extending from the Great Lakes southward across the Midwest and into Texas. Decreased values, though, are predicted across most of the western United States. However, these predicted changes have a strong seasonal dependence, with wind speed increases over most of the United States during the winter and decreases over the northern United States during the summer.

Validation of finite element and boundary element methods for predicting structural vibration and radiated noise

NASA Technical Reports Server (NTRS)

Seybert, A. F.; Wu, X. F.; Oswald, Fred B.

1992-01-01

Analytical and experimental validation of methods to predict structural vibration and radiated noise are presented. A rectangular box excited by a mechanical shaker was used as a vibrating structure. Combined finite element method (FEM) and boundary element method (BEM) models of the apparatus were used to predict the noise radiated from the box. The FEM was used to predict the vibration, and the surface vibration was used as input to the BEM to predict the sound intensity and sound power. Vibration predicted by the FEM model was validated by experimental modal analysis. Noise predicted by the BEM was validated by sound intensity measurements. Three types of results are presented for the total radiated sound power: (1) sound power predicted by the BEM modeling using vibration data measured on the surface of the box; (2) sound power predicted by the FEM/BEM model; and (3) sound power measured by a sound intensity scan. The sound power predicted from the BEM model using measured vibration data yields an excellent prediction of radiated noise. The sound power predicted by the combined FEM/BEM model also gives a good prediction of radiated noise except for a shift of the natural frequencies that are due to limitations in the FEM model.

Model Predictive Control techniques with application to photovoltaic, DC Microgrid, and a multi-sourced hybrid energy system

NASA Astrophysics Data System (ADS)

Shadmand, Mohammad Bagher

Renewable energy sources continue to gain popularity. However, two major limitations exist that prevent widespread adoption: availability and variability of the electricity generated and the cost of the equipment. The focus of this dissertation is Model Predictive Control (MPC) for optimal sized photovoltaic (PV), DC Microgrid, and multi-sourced hybrid energy systems. The main considered applications are: maximum power point tracking (MPPT) by MPC, droop predictive control of DC microgrid, MPC of grid-interaction inverter, MPC of a capacitor-less VAR compensator based on matrix converter (MC). This dissertation firstly investigates a multi-objective optimization technique for a hybrid distribution system. The variability of a high-penetration PV scenario is also studied when incorporated into the microgrid concept. Emerging (PV) technologies have enabled the creation of contoured and conformal PV surfaces; the effect of using non-planar PV modules on variability is also analyzed. The proposed predictive control to achieve maximum power point for isolated and grid-tied PV systems speeds up the control loop since it predicts error before the switching signal is applied to the converter. The low conversion efficiency of PV cells means we want to ensure always operating at maximum possible power point to make the system economical. Thus the proposed MPPT technique can capture more energy compared to the conventional MPPT techniques from same amount of installed solar panel. Because of the MPPT requirement, the output voltage of the converter may vary. Therefore a droop control is needed to feed multiple arrays of photovoltaic systems to a DC bus in microgrid community. Development of a droop control technique by means of predictive control is another application of this dissertation. Reactive power, denoted as Volt Ampere Reactive (VAR), has several undesirable consequences on AC power system network such as reduction in power transfer capability and increase in transmission loss if not controlled appropriately. Inductive loads which operate with lagging power factor consume VARs, thus load compensation techniques by capacitor bank employment locally supply VARs needed by the load. Capacitors are highly unreliable components due to their failure modes and aging inherent. Approximately 60% of power electronic devices failure such as voltage-source inverter based static synchronous compensator (STATCOM) is due to the use of aluminum electrolytic DC capacitors. Therefore, a capacitor-less VAR compensation is desired. This dissertation also investigates a STATCOM capacitor-less reactive power compensation that uses only inductors combined with predictive controlled matrix converter.

Analysis of significant factors for dengue fever incidence prediction.

PubMed

Siriyasatien, Padet; Phumee, Atchara; Ongruk, Phatsavee; Jampachaisri, Katechan; Kesorn, Kraisak

2016-04-16

Many popular dengue forecasting techniques have been used by several researchers to extrapolate dengue incidence rates, including the K-H model, support vector machines (SVM), and artificial neural networks (ANN). The time series analysis methodology, particularly ARIMA and SARIMA, has been increasingly applied to the field of epidemiological research for dengue fever, dengue hemorrhagic fever, and other infectious diseases. The main drawback of these methods is that they do not consider other variables that are associated with the dependent variable. Additionally, new factors correlated to the disease are needed to enhance the prediction accuracy of the model when it is applied to areas of similar climates, where weather factors such as temperature, total rainfall, and humidity are not substantially different. Such drawbacks may consequently lower the predictive power for the outbreak. The predictive power of the forecasting model-assessed by Akaike's information criterion (AIC), Bayesian information criterion (BIC), and the mean absolute percentage error (MAPE)-is improved by including the new parameters for dengue outbreak prediction. This study's selected model outperforms all three other competing models with the lowest AIC, the lowest BIC, and a small MAPE value. The exclusive use of climate factors from similar locations decreases a model's prediction power. The multivariate Poisson regression, however, effectively forecasts even when climate variables are slightly different. Female mosquitoes and seasons were strongly correlated with dengue cases. Therefore, the dengue incidence trends provided by this model will assist the optimization of dengue prevention. The present work demonstrates the important roles of female mosquito infection rates from the previous season and climate factors (represented as seasons) in dengue outbreaks. Incorporating these two factors in the model significantly improves the predictive power of dengue hemorrhagic fever forecasting models, as confirmed by AIC, BIC, and MAPE.

Sexual relationship power and depression among HIV-infected women in Rural Uganda.

PubMed

Hatcher, Abigail M; Tsai, Alexander C; Kumbakumba, Elias; Dworkin, Shari L; Hunt, Peter W; Martin, Jeffrey N; Clark, Gina; Bangsberg, David R; Weiser, Sheri D

2012-01-01

Depression is associated with increased HIV transmission risk, increased morbidity, and higher risk of HIV-related death among HIV-infected women. Low sexual relationship power also contributes to HIV risk, but there is limited understanding of how it relates to mental health among HIV-infected women. Participants were 270 HIV-infected women from the Uganda AIDS Rural Treatment Outcomes study, a prospective cohort of individuals initiating antiretroviral therapy (ART) in Mbarara, Uganda. Our primary predictor was baseline sexual relationship power as measured by the Sexual Relationship Power Scale (SRPS). The primary outcome was depression severity, measured with the Hopkins Symptom Checklist (HSCL), and a secondary outcome was a functional scale for mental health status (MHS). Adjusted models controlled for socio-demographic factors, CD4 count, alcohol and tobacco use, baseline WHO stage 4 disease, social support, and duration of ART. The mean HSCL score was 1.34 and 23.7% of participants had HSCL scores consistent with probable depression (HSCL>1.75). Compared to participants with low SRPS scores, individuals with both moderate (coefficient b = -0.21; 95%CI, -0.36 to -0.07) and high power (b = -0.21; 95%CI, -0.36 to -0.06) reported decreased depressive symptomology. High SRPS scores halved the likelihood of women meeting criteria for probable depression (adjusted odds ratio = 0.44; 95%CI, 0.20 to 0.93). In lagged models, low SRPS predicted subsequent depression severity, but depression did not predict subsequent changes in SPRS. Results were similar for MHS, with lagged models showing SRPS predicts subsequent mental health, but not visa versa. Both Decision-Making Dominance and Relationship Control subscales of SRPS were associated with depression symptom severity. HIV-infected women with high sexual relationship power had lower depression and higher mental health status than women with low power. Interventions to improve equity in decision-making and control within dyadic partnerships are critical to prevent HIV transmission and to optimize mental health of HIV-infected women.

Univariate Time Series Prediction of Solar Power Using a Hybrid Wavelet-ARMA-NARX Prediction Method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nazaripouya, Hamidreza; Wang, Yubo; Chu, Chi-Cheng

This paper proposes a new hybrid method for super short-term solar power prediction. Solar output power usually has a complex, nonstationary, and nonlinear characteristic due to intermittent and time varying behavior of solar radiance. In addition, solar power dynamics is fast and is inertia less. An accurate super short-time prediction is required to compensate for the fluctuations and reduce the impact of solar power penetration on the power system. The objective is to predict one step-ahead solar power generation based only on historical solar power time series data. The proposed method incorporates discrete wavelet transform (DWT), Auto-Regressive Moving Average (ARMA)more » models, and Recurrent Neural Networks (RNN), while the RNN architecture is based on Nonlinear Auto-Regressive models with eXogenous inputs (NARX). The wavelet transform is utilized to decompose the solar power time series into a set of richer-behaved forming series for prediction. ARMA model is employed as a linear predictor while NARX is used as a nonlinear pattern recognition tool to estimate and compensate the error of wavelet-ARMA prediction. The proposed method is applied to the data captured from UCLA solar PV panels and the results are compared with some of the common and most recent solar power prediction methods. The results validate the effectiveness of the proposed approach and show a considerable improvement in the prediction precision.« less

RTG performance on Galileo and Ulysses and Cassini test results

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kelly, C. Edward; Klee, Paul M.

Power output from telemetry for the two Galileo RTGs are shown from the 1989 launch to the recent Jupiter encounter. Comparisons of predicted, measured and required performance are shown. Similar comparisons are made for the RTG on the Ulysses spacecraft which completed its planned mission in 1995. Also presented are test results from small scale thermoelectric modules and full scale converters performed for the Cassini program. The Cassini mission to Saturn is scheduled for an October 1997 launch. Small scale module test results on thermoelectric couples from the qualification and flight production runs are shown. These tests have exceeded 19,000more » hours are continuing to provide increased confidence in the predicted long term performance of the Cassini RTGs. Test results are presented for full scale units both ETGs (E-6, E-7) and RTGs (F-2, F-5) along with mission power predictions. F-5, fueled in 1985, served as a spare for the Galileo and Ulysses missions and plays the same role in the Cassini program. It has successfully completed all acceptance testing. The ten years storage between thermal vacuum tests is the longest ever experienced by an RTG. The data from this test are unique in providing the effects of long term low temperature storage on power output. All ETG and RTG test results to date indicate that the power requirements of the Cassini spacecraft will be met. BOM and EOM power margins of at least five percent are predicted.« less

Automated identification of RNA 3D modules with discriminative power in RNA structural alignments.

PubMed

Theis, Corinna; Höner Zu Siederdissen, Christian; Hofacker, Ivo L; Gorodkin, Jan

2013-12-01

Recent progress in predicting RNA structure is moving towards filling the 'gap' in 2D RNA structure prediction where, for example, predicted internal loops often form non-canonical base pairs. This is increasingly recognized with the steady increase of known RNA 3D modules. There is a general interest in matching structural modules known from one molecule to other molecules for which the 3D structure is not known yet. We have created a pipeline, metaRNAmodules, which completely automates extracting putative modules from the FR3D database and mapping of such modules to Rfam alignments to obtain comparative evidence. Subsequently, the modules, initially represented by a graph, are turned into models for the RMDetect program, which allows to test their discriminative power using real and randomized Rfam alignments. An initial extraction of 22 495 3D modules in all PDB files results in 977 internal loop and 17 hairpin modules with clear discriminatory power. Many of these modules describe only minor variants of each other. Indeed, mapping of the modules onto Rfam families results in 35 unique locations in 11 different families. The metaRNAmodules pipeline source for the internal loop modules is available at http://rth.dk/resources/mrm.

Mechanical work for step-to-step transitions is a major determinant of the metabolic cost of human walking.

PubMed

Donelan, J Maxwell; Kram, Rodger; Kuo, Arthur D

2002-12-01

In the single stance phase of walking, center of mass motion resembles that of an inverted pendulum. Theoretically, mechanical work is not necessary for producing the pendular motion, but work is needed to redirect the center of mass velocity from one pendular arc to the next during the transition between steps. A collision model predicts a rate of negative work proportional to the fourth power of step length. Positive work is required to restore the energy lost, potentially exacting a proportional metabolic cost. We tested these predictions with humans (N=9) walking over a range of step lengths (0.4-1.1 m) while keeping step frequency fixed at 1.8 Hz. We measured individual limb external mechanical work using force plates, and metabolic rate using indirect calorimetry. As predicted, average negative and positive external mechanical work rates increased with the fourth power of step length (from 1 W to 38 W; r(2)=0.96). Metabolic rate also increased with the fourth power of step length (from 7 W to 379 W; r(2)=0.95), and linearly with mechanical work rate. Mechanical work for step-to-step transitions, rather than pendular motion itself, appears to be a major determinant of the metabolic cost of walking.

Continuous wave power scaling in high power broad area quantum cascade lasers

NASA Astrophysics Data System (ADS)

Suttinger, M.; Leshin, J.; Go, R.; Figueiredo, P.; Shu, H.; Lyakh, A.

2018-02-01

Experimental and model results for high power broad area quantum cascade lasers are presented. Continuous wave power scaling from 1.62 W to 2.34 W has been experimentally demonstrated for 3.15 mm-long, high reflection-coated 5.6 μm quantum cascade lasers with 15 stage active region for active region width increased from 10 μm to 20 μm. A semi-empirical model for broad area devices operating in continuous wave mode is presented. The model uses measured pulsed transparency current, injection efficiency, waveguide losses, and differential gain as input parameters. It also takes into account active region self-heating and sub-linearity of pulsed power vs current laser characteristic. The model predicts that an 11% improvement in maximum CW power and increased wall plug efficiency can be achieved from 3.15 mm x 25 μm devices with 21 stages of the same design but half doping in the active region. For a 16-stage design with a reduced stage thickness of 300Å, pulsed roll-over current density of 6 kA/cm2 , and InGaAs waveguide layers; optical power increase of 41% is projected. Finally, the model projects that power level can be increased to 4.5 W from 3.15 mm × 31 μm devices with the baseline configuration with T0 increased from 140 K for the present design to 250 K.

Predictive power of food web models based on body size decreases with trophic complexity.

PubMed

Jonsson, Tomas; Kaartinen, Riikka; Jonsson, Mattias; Bommarco, Riccardo

2018-05-01

Food web models parameterised using body size show promise to predict trophic interaction strengths (IS) and abundance dynamics. However, this remains to be rigorously tested in food webs beyond simple trophic modules, where indirect and intraguild interactions could be important and driven by traits other than body size. We systematically varied predator body size, guild composition and richness in microcosm insect webs and compared experimental outcomes with predictions of IS from models with allometrically scaled parameters. Body size was a strong predictor of IS in simple modules (r 2  = 0.92), but with increasing complexity the predictive power decreased, with model IS being consistently overestimated. We quantify the strength of observed trophic interaction modifications, partition this into density-mediated vs. behaviour-mediated indirect effects and show that model shortcomings in predicting IS is related to the size of behaviour-mediated effects. Our findings encourage development of dynamical food web models explicitly including and exploring indirect mechanisms. © 2018 John Wiley & Sons Ltd/CNRS.

A Battery Health Monitoring Framework for Planetary Rovers

NASA Technical Reports Server (NTRS)

Daigle, Matthew J.; Kulkarni, Chetan Shrikant

2014-01-01

Batteries have seen an increased use in electric ground and air vehicles for commercial, military, and space applications as the primary energy source. An important aspect of using batteries in such contexts is battery health monitoring. Batteries must be carefully monitored such that the battery health can be determined, and end of discharge and end of usable life events may be accurately predicted. For planetary rovers, battery health estimation and prediction is critical to mission planning and decision-making. We develop a model-based approach utilizing computaitonally efficient and accurate electrochemistry models of batteries. An unscented Kalman filter yields state estimates, which are then used to predict the future behavior of the batteries and, specifically, end of discharge. The prediction algorithm accounts for possible future power demands on the rover batteries in order to provide meaningful results and an accurate representation of prediction uncertainty. The framework is demonstrated on a set of lithium-ion batteries powering a rover at NASA.

Post-mortem prediction of primal and selected retail cut weights of New Zealand lamb from carcass and animal characteristics.

PubMed

Ngo, L; Ho, H; Hunter, P; Quinn, K; Thomson, A; Pearson, G

2016-02-01

Post-mortem measurements (cold weight, grade and external carcass linear dimensions) as well as live animal data (age, breed, sex) were used to predict ovine primal and retail cut weights for 792 lamb carcases. Significant levels of variance could be explained using these predictors. The predictive power of those measurements on primal and retail cut weights was studied by using the results from principal component analysis and the absolute value of the t-statistics of the linear regression model. High prediction accuracy for primal cut weight was achieved (adjusted R(2) up to 0.95), as well as moderate accuracy for key retail cut weight: tenderloins (adj-R(2)=0.60), loin (adj-R(2)=0.62), French rack (adj-R(2)=0.76) and rump (adj-R(2)=0.75). The carcass cold weight had the best predictive power, with the accuracy increasing by around 10% after including the next three most significant variables. Copyright © 2015 Elsevier Ltd. All rights reserved.

The potential distribution of Phlebotomus papatasi (Diptera: Psychodidae) in Libya based on ecological niche model.

PubMed

Abdel-Dayem, M S; Annajar, B B; Hanafi, H A; Obenauer, P J

2012-05-01

The increased cases of cutaneous leishmaniasis vectored by Phlebotomus papatasi (Scopoli) in Libya have driven considerable effort to develop a predictive model for the potential geographical distribution of this disease. We collected adult P. papatasi from 17 sites in Musrata and Yefern regions of Libya using four different attraction traps. Our trap results and literature records describing the distribution of P. papatasi were incorporated into a MaxEnt algorithm prediction model that used 22 environmental variables. The model showed a high performance (AUC = 0.992 and 0.990 for training and test data, respectively). High suitability for P. papatasi was predicted to be largely confined to the coast at altitudes <600 m. Regions south of 300 degrees N latitude were calculated as unsuitable for this species. Jackknife analysis identified precipitation as having the most significant predictive power, while temperature and elevation variables were less influential. The National Leishmaniasis Control Program in Libya may find this information useful in their efforts to control zoonotic cutaneous leishmaniasis. Existing records are strongly biased toward a few geographical regions, and therefore, further sand fly collections are warranted that should include documentation of such factors as soil texture and humidity, land cover, and normalized difference vegetation index (NDVI) data to increase the model's predictive power.

Basal and dynamic relationships between implicit power motivation and estradiol in women.

PubMed

Stanton, Steven J; Schultheiss, Oliver C

2007-12-01

This study investigated basal and reciprocal relationships between implicit power motivation (n Power), a preference for having impact and dominance over others, and both salivary estradiol and testosterone in women. 49 participants completed the Picture Story Exercise, a measure of n Power. During a laboratory contest, participants competed in pairs on a cognitive task and contest outcome (win vs. loss) was experimentally varied. Estradiol and testosterone levels were determined in saliva samples collected at baseline and several times post-contest, including 1 day post-contest. n Power was positively associated with basal estradiol concentrations. The positive correlation between n Power and basal estradiol was stronger in single women, women not taking oral contraceptives, or in women with low-CV estradiol samples than in the overall sample of women. Women's estradiol responses to a dominance contest were influenced by the interaction of n Power and contest outcome: estradiol increased in power-motivated winners but decreased in power-motivated losers. For power-motivated winners, elevated levels of estradiol were still present the day after the contest. Lastly, n Power and estradiol did not correlate with self-reported dominance and correlated negatively with self-reported aggression. Self-reported dominance and aggression did not predict estradiol changes as a function of contest outcome. Overall, n Power did not predict basal testosterone levels or testosterone changes as a function of dominance contest outcome.

Validation of the FAST skating protocol to predict aerobic power in ice hockey players.

PubMed

Petrella, Nicholas J; Montelpare, William J; Nystrom, Murray; Plyley, Michael; Faught, Brent E

2007-08-01

Few studies have reported a sport-specific protocol to measure the aerobic power of ice hockey players using a predictive process. The purpose of our study was to validate an ice hockey aerobic field test on players of varying ages, abilities, and levels. The Faught Aerobic Skating Test (FAST) uses an on-ice continuous skating protocol on a course measuring 160 feet (48.8 m) using a CD to pace the skater with a beep signal to cross the starting line at each end of the course. The FAST incorporates the principle of increasing workload at measured time intervals during a continuous skating exercise. Step-wise multiple regression modelling was used to determine the estimate of aerobic power. Participants completed a maximal aerobic power test using a modified Bruce incremental treadmill protocol, as well as the on-ice FAST. Normative data were collected on 406 ice hockey players (291 males, 115 females) ranging in age from 9 to 25 y. A regression to predict maximum aerobic power was developed using body mass (kg), height (m), age (y), and maximum completed lengths of the FAST as the significant predictors of skating aerobic power (adjusted R2 = 0.387, SEE = 7.25 mL.kg-1.min-1, p < 0.0001). These results support the application of the FAST in estimating aerobic power among male and female competitive ice hockey players between the ages of 9 and 25 years.

Price dynamics in political prediction markets

PubMed Central

Majumder, Saikat Ray; Diermeier, Daniel; Rietz, Thomas A.; Amaral, Luís A. Nunes

2009-01-01

Prediction markets, in which contract prices are used to forecast future events, are increasingly applied to various domains ranging from political contests to scientific breakthroughs. However, the dynamics of such markets are not well understood. Here, we study the return dynamics of the oldest, most data-rich prediction markets, the Iowa Electronic Presidential Election “winner-takes-all” markets. As with other financial markets, we find uncorrelated returns, power-law decaying volatility correlations, and, usually, power-law decaying distributions of returns. However, unlike other financial markets, we find conditional diverging volatilities as the contract settlement date approaches. We propose a dynamic binary option model that captures all features of the empirical data and can potentially provide a tool with which one may extract true information events from a price time series. PMID:19155442

Optimal Parameter Selection for Support Vector Machine Based on Artificial Bee Colony Algorithm: A Case Study of Grid-Connected PV System Power Prediction.

PubMed

Gao, Xiang-Ming; Yang, Shi-Feng; Pan, San-Bo

2017-01-01

Predicting the output power of photovoltaic system with nonstationarity and randomness, an output power prediction model for grid-connected PV systems is proposed based on empirical mode decomposition (EMD) and support vector machine (SVM) optimized with an artificial bee colony (ABC) algorithm. First, according to the weather forecast data sets on the prediction date, the time series data of output power on a similar day with 15-minute intervals are built. Second, the time series data of the output power are decomposed into a series of components, including some intrinsic mode components IMFn and a trend component Res, at different scales using EMD. The corresponding SVM prediction model is established for each IMF component and trend component, and the SVM model parameters are optimized with the artificial bee colony algorithm. Finally, the prediction results of each model are reconstructed, and the predicted values of the output power of the grid-connected PV system can be obtained. The prediction model is tested with actual data, and the results show that the power prediction model based on the EMD and ABC-SVM has a faster calculation speed and higher prediction accuracy than do the single SVM prediction model and the EMD-SVM prediction model without optimization.

Optimal Parameter Selection for Support Vector Machine Based on Artificial Bee Colony Algorithm: A Case Study of Grid-Connected PV System Power Prediction

PubMed Central

2017-01-01

Predicting the output power of photovoltaic system with nonstationarity and randomness, an output power prediction model for grid-connected PV systems is proposed based on empirical mode decomposition (EMD) and support vector machine (SVM) optimized with an artificial bee colony (ABC) algorithm. First, according to the weather forecast data sets on the prediction date, the time series data of output power on a similar day with 15-minute intervals are built. Second, the time series data of the output power are decomposed into a series of components, including some intrinsic mode components IMFn and a trend component Res, at different scales using EMD. The corresponding SVM prediction model is established for each IMF component and trend component, and the SVM model parameters are optimized with the artificial bee colony algorithm. Finally, the prediction results of each model are reconstructed, and the predicted values of the output power of the grid-connected PV system can be obtained. The prediction model is tested with actual data, and the results show that the power prediction model based on the EMD and ABC-SVM has a faster calculation speed and higher prediction accuracy than do the single SVM prediction model and the EMD-SVM prediction model without optimization. PMID:28912803

Experimental evaluation of the power balance model of speed skating.

PubMed

de Koning, Jos J; Foster, Carl; Lampen, Joanne; Hettinga, Floor; Bobbert, Maarten F

2005-01-01

Prediction of speed skating performance with a power balance model requires assumptions about the kinetics of energy production, skating efficiency, and skating technique. The purpose of this study was to evaluate these parameters during competitive imitations for the purpose of improving model predictions. Elite speed skaters (n = 8) performed races and submaximal efficiency tests. External power output (P(o)) was calculated from movement analysis and aerodynamic models and ice friction measurements. Aerobic kinetics was calculated from breath-by-breath oxygen uptake (Vo(2)). Aerobic power (P(aer)) was calculated from measured skating efficiency. Anaerobic power (P(an)) kinetics was determined by subtracting P(aer) from P(o). We found gross skating efficiency to be 15.8% (1.8%). In the 1,500-m event, the kinetics of P(an) was characterized by a first-order system as P(an) = 88 + 556e(-0.0494t) (in W, where t is time). The rate constant for the increase in P(aer) was -0.153 s(-1), the time delay was 8.7 s, and the peak P(aer) was 234 W; P(aer) was equal to 234[1 - e(-0.153(t-8.7))] (in W). Skating position changed with preextension knee angle increasing and trunk angle decreasing throughout the event. We concluded the pattern of P(aer) to be quite similar to that reported during other competitive imitations, with the exception that the increase in P(aer) was more rapid. The pattern of P(an) does not appear to fit an "all-out" pattern, with near zero values during the last portion of the event, as assumed in our previous model (De Koning JJ, de Groot G, and van Ingen Schenau GJ. J Biomech 25: 573-580, 1992). Skating position changed in ways different from those assumed in our previous model. In addition to allowing improved predictions, the results demonstrate the importance of observations in unique subjects to the process of model construction.

Incorporating Psychological Predictors of Treatment Response into Health Economic Simulation Models: A Case Study in Type 1 Diabetes.

PubMed

Kruger, Jen; Pollard, Daniel; Basarir, Hasan; Thokala, Praveen; Cooke, Debbie; Clark, Marie; Bond, Rod; Heller, Simon; Brennan, Alan

2015-10-01

. Health economic modeling has paid limited attention to the effects that patients' psychological characteristics have on the effectiveness of treatments. This case study tests 1) the feasibility of incorporating psychological prediction models of treatment response within an economic model of type 1 diabetes, 2) the potential value of providing treatment to a subgroup of patients, and 3) the cost-effectiveness of providing treatment to a subgroup of responders defined using 5 different algorithms. . Multiple linear regressions were used to investigate relationships between patients' psychological characteristics and treatment effectiveness. Two psychological prediction models were integrated with a patient-level simulation model of type 1 diabetes. Expected value of individualized care analysis was undertaken. Five different algorithms were used to provide treatment to a subgroup of predicted responders. A cost-effectiveness analysis compared using the algorithms to providing treatment to all patients. . The psychological prediction models had low predictive power for treatment effectiveness. Expected value of individualized care results suggested that targeting education at responders could be of value. The cost-effectiveness analysis suggested, for all 5 algorithms, that providing structured education to a subgroup of predicted responders would not be cost-effective. . The psychological prediction models tested did not have sufficient predictive power to make targeting treatment cost-effective. The psychological prediction models are simple linear models of psychological behavior. Collection of data on additional covariates could potentially increase statistical power. . By collecting data on psychological variables before an intervention, we can construct predictive models of treatment response to interventions. These predictive models can be incorporated into health economic models to investigate more complex service delivery and reimbursement strategies. © The Author(s) 2015.

The stopping power and energy straggling of light ions in graphene oxide foils

NASA Astrophysics Data System (ADS)

Mikšová, R.; Macková, A.; Malinský, P.; Sofer, Z.

2017-09-01

Energy-loss and straggling experiments were performed using 2-4 MeV 1H+ and 7.4-9.0 MeV 4He2+ ions in graphene oxide foils by the transmission technique. The thickness of the graphene oxide foils was determined using a detailed image analysis of a graphene oxide cut, which was used to refine the graphene oxide density. The density was determined by the standard technique of micro-balance weighing. The stoichiometry of the graphene oxide foils before the irradiation was determined by Rutherford backscattering spectrometry (RBS) and elastic recoil detection analysis (ERDA) using 2 and 2.5 MeV 4He+. The measured energy stopping powers for hydrogen and helium ions in graphene oxide were compared with the predictions obtained from the SRIM-2013 code. The energy straggling was compared with that calculated using Bohr's, Bethe-Livingston and Yang predictions. The results show that the stopping power of graphene oxide foils irradiated by both ion species decreases with increasing energies, the differences between the measured and predicted values being below 3.8%. The energy straggling determined in our experiment is higher than Bohr's and Bethe-Livingston predicted values; the predictions by Yang are in better agreement with our experiment.

Exploring the predictive power of polygenic scores derived from genome-wide association studies: a study of 10 complex traits.

PubMed

So, Hon-Cheong; Sham, Pak C

2017-03-15

It is hoped that advances in our knowledge in disease genomics will contribute to personalized medicine such as individualized preventive strategies or early diagnoses of diseases. With the growth of genome-wide association studies (GWAS) in the past decade, how far have we reached this goal? In this study we explored the predictive ability of polygenic risk scores (PRSs) derived from GWAS for a range of complex disease and traits. We first proposed a new approach to evaluate predictive performances of PRS at arbitrary P -value thresholds. The method was based on corrected estimates of effect sizes, accounting for possible false positives and selection bias. This approach requires no distributional assumptions and only requires summary statistics as input. The validity of the approach was verified in simulations. We explored the predictive power of PRS for ten complex traits, including type 2 diabetes (DM), coronary artery disease (CAD), triglycerides, high- and low-density lipoprotein, total cholesterol, schizophrenia (SCZ), bipolar disorder (BD), major depressive disorder and anxiety disorders. We found that the predictive ability of PRS for CAD and DM were modest (best AUC = 0.608 and 0.607) while for lipid traits the prediction R-squared ranged from 16.1 to 29.8%. For psychiatric disorders, the predictive power for SCZ was estimated to be the highest (best AUC 0.820), followed by BD. Predictive performance of other psychiatric disorders ranged from 0.543 to 0.585. Psychiatric traits tend to have more gradual rise in AUC when significance thresholds increase and achieve the best predictive power at higher P -values than cardiometabolic traits. hcso@cuhk.edu.hk ; pcsham@hku.hk. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

The Payout Method: A Spending Policy That Enhances Return.

ERIC Educational Resources Information Center

Morrell, Louis R.

1991-01-01

College and university business officers are encouraged to implement an endowment distribution method that increases the amount distributed by a fixed annual percentage based on asset mix, inflation, and expected return. Such a payout system provides a predictable, steadily increasing level of endowment income yet maintains the purchasing power of…

Analysis of a turbulent boundary layer over a moving ground plane

NASA Technical Reports Server (NTRS)

Roper, A. T.; Gentry, G. L., Jr.

1972-01-01

Four methods of predicting the integral and friction parameters for a turbulent boundary layer over a moving ground plane were evaluated by using test information obtained in 76.2- by 50.8-centimeter tunnel. The tunnel was operated in the open sidewall configuration. These methods are (1) relative integral parameter method, (2) modified power law method, (3) relative power law method, and (4) modified law of the wall method. The modified law of the wall method predicts a more rapid decrease in skin friction with an increase in the ratio of belt velocity to free steam velocity than do methods (1) and (3).

Selenide isotope generator for the Galileo mission. SIG/Galileo contract compliance power prediction technique

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hammel, T.E.; Srinivas, V.

1978-11-01

This initial definition of the power degradation prediction technique outlines a model for predicting SIG/Galileo mean EOM power using component test data and data from a module power degradation demonstration test program. (LCL)

Reformation of PURPA contracts: Strategies for success in power marketing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Scalzo, P.J.

With the passage of the Energy Policy Act of 1992, real competition entered into the world of electric utilities. A slide presentations is given on reformation of Public Utility Regulatory Policies Act (PURPA) Contracts for success in power marketing strategies. Two ways to compete: Be the least cost provider or add value and `sell hard`. The PURPA vision was to increase efficiency in power generation, utilize renewable or waste fuels, and bolster the independent producers. Cogenerators and small power producers qualified. Utility planners predicted, avoided cost, utility loads, and oil and gas prices to increase. However, avoided costs, and oilmore » and gase prices declined. Two scenarios are discussed for contract reformation: Contract buyouts, and renegotiation of contracts. Options for for dealing with existing fuel agreements are presented.« less

Neonatal Sleep-Wake Analyses Predict 18-month Neurodevelopmental Outcomes.

PubMed

Shellhaas, Renée A; Burns, Joseph W; Hassan, Fauziya; Carlson, Martha D; Barks, John D E; Chervin, Ronald D

2017-11-01

The neurological examination of critically ill neonates is largely limited to reflexive behavior. The exam often ignores sleep-wake physiology that may reflect brain integrity and influence long-term outcomes. We assessed whether polysomnography and concurrent cerebral near-infrared spectroscopy (NIRS) might improve prediction of 18-month neurodevelopmental outcomes. Term newborns with suspected seizures underwent standardized neurologic examinations to generate Thompson scores and had 12-hour bedside polysomnography with concurrent cerebral NIRS. For each infant, the distribution of sleep-wake stages and electroencephalogram delta power were computed. NIRS-derived fractional tissue oxygen extraction (FTOE) was calculated across sleep-wake stages. At age 18-22 months, surviving participants were evaluated with Bayley Scales of Infant Development (Bayley-III), 3rd edition. Twenty-nine participants completed Bayley-III. Increased newborn time in quiet sleep predicted worse 18-month cognitive and motor scores (robust regression models, adjusted r2 = 0.22, p = .007, and 0.27, .004, respectively). Decreased 0.5-2 Hz electroencephalograph (EEG) power during quiet sleep predicted worse 18-month language and motor scores (adjusted r2 = 0.25, p = .0005, and 0.33, .001, respectively). Predictive values remained significant after adjustment for neonatal Thompson scores or exposure to phenobarbital. Similarly, an attenuated difference in FTOE, between neonatal wakefulness and quiet sleep, predicted worse 18-month cognitive, language, and motor scores in adjusted analyses (each p < .05). These prospective, longitudinal data suggest that inefficient neonatal sleep-as quantified by increased time in quiet sleep, lower electroencephalogram delta power during that stage, and muted differences in FTOE between quiet sleep and wakefulness-may improve prediction of adverse long-term outcomes for newborns with neurological dysfunction. © Sleep Research Society 2017. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.

Kinematic Mechanisms of How Power Training Improves Healthy Old Adults' Gait Velocity.

PubMed

Beijersbergen, Chantal M I; Granacher, Urs; Gäbler, Martijn; Devita, Paul; Hortobágyi, Tibor

2017-01-01

Slow gait predicts many adverse clinical outcomes in old adults, but the mechanisms of how power training can minimize the age-related loss of gait velocity is unclear. We examined the effects of 10 wk of lower extremity power training and detraining on healthy old adults' lower extremity muscle power and gait kinematics. As part of the Potsdam Gait Study, participants started with 10 wk of power training followed by 10 wk of detraining (n = 16), and participants started with a 10-wk control period followed by 10 wk of power training (n = 16). We measured gait kinematics (stride characteristic and joint kinematics) and isokinetic power of the ankle plantarflexor (20°·s, 40°·s, and 60°·s) and knee extensor and flexor (60°·s, 120°·s, and 180°·s) muscles at weeks 0, 10, and 20. Power training improved isokinetic muscle power by ~30% (P ≤ 0.001) and fast (5.9%, P < 0.05) but not habitual gait velocity. Ankle plantarflexor velocity measured during gait at fast pace decreased by 7.9% (P < 0.05). The changes isokinetic muscle power and joint kinematics did not correlate with increases in fast gait velocity. The mechanisms that increased fast gait velocity involved higher cadence (r = 0.86, P ≤ 0.001) rather than longer strides (r = 0.49, P = 0.066). Detraining did not reverse the training-induced increases in muscle power and fast gait velocity. Because increases in muscle power and modifications in joint kinematics did not correlate with increases in fast gait velocity, kinematic mechanisms seem to play a minor role in improving healthy old adults' fast gait velocity after power training.

Advanced Cloud Forecasting for Solar Energy’s Impact on Grid Modernization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Werth, D.; Nichols, R.

Solar energy production is subject to variability in the solar resource – clouds and aerosols will reduce the available solar irradiance and inhibit power production. The fact that solar irradiance can vary by large amounts at small timescales and in an unpredictable way means that power utilities are reluctant to assign to their solar plants a large portion of future energy demand – the needed power might be unavailable, forcing the utility to make costly adjustments to its daily portfolio. The availability and predictability of solar radiation therefore represent important research topics for increasing the power produced by renewable sources.

Cortical oscillatory activity and the induction of plasticity in the human motor cortex.

PubMed

McAllister, Suzanne M; Rothwell, John C; Ridding, Michael C

2011-05-01

Repetitive transcranial magnetic stimulation paradigms such as continuous theta burst stimulation (cTBS) induce long-term potentiation- and long-term depression-like plasticity in the human motor cortex. However, responses to cTBS are highly variable and may depend on the activity of the cortex at the time of stimulation. We investigated whether power in different electroencephalogram (EEG) frequency bands predicted the response to subsequent cTBS, and conversely whether cTBS had after-effects on the EEG. cTBS may utilize similar mechanisms of plasticity to motor learning; thus, we conducted a parallel set of experiments to test whether ongoing electroencephalography could predict performance of a visuomotor training task, and whether training itself had effects on the EEG. Motor evoked potentials (MEPs) provided an index of cortical excitability pre- and post-intervention. The EEG was recorded over the motor cortex pre- and post-intervention, and power spectra were computed. cTBS reduced MEP amplitudes; however, baseline power in the delta, theta, alpha or beta frequencies did not predict responses to cTBS or learning of the visuomotor training task. cTBS had no effect on delta, theta, alpha or beta power. In contrast, there was an increase in alpha power following visuomotor training that was positively correlated with changes in MEP amplitude post-training. The results suggest that the EEG is not a useful state-marker for predicting responses to plasticity-inducing paradigms. The correlation between alpha power and changes in corticospinal excitability following visuomotor training requires further investigation, but may be related to disengagement of the somatosensory system important for motor memory consolidation. © 2011 The Authors. European Journal of Neuroscience © 2011 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

Robust regression and posterior predictive simulation increase power to detect early bursts of trait evolution.

PubMed

Slater, Graham J; Pennell, Matthew W

2014-05-01

A central prediction of much theory on adaptive radiations is that traits should evolve rapidly during the early stages of a clade's history and subsequently slowdown in rate as niches become saturated--a so-called "Early Burst." Although a common pattern in the fossil record, evidence for early bursts of trait evolution in phylogenetic comparative data has been equivocal at best. We show here that this may not necessarily be due to the absence of this pattern in nature. Rather, commonly used methods to infer its presence perform poorly when when the strength of the burst--the rate at which phenotypic evolution declines--is small, and when some morphological convergence is present within the clade. We present two modifications to existing comparative methods that allow greater power to detect early bursts in simulated datasets. First, we develop posterior predictive simulation approaches and show that they outperform maximum likelihood approaches at identifying early bursts at moderate strength. Second, we use a robust regression procedure that allows for the identification and down-weighting of convergent taxa, leading to moderate increases in method performance. We demonstrate the utility and power of these approach by investigating the evolution of body size in cetaceans. Model fitting using maximum likelihood is equivocal with regards the mode of cetacean body size evolution. However, posterior predictive simulation combined with a robust node height test return low support for Brownian motion or rate shift models, but not the early burst model. While the jury is still out on whether early bursts are actually common in nature, our approach will hopefully facilitate more robust testing of this hypothesis. We advocate the adoption of similar posterior predictive approaches to improve the fit and to assess the adequacy of macroevolutionary models in general.

Power load prediction based on GM (1,1)

NASA Astrophysics Data System (ADS)

Wu, Di

2017-05-01

Currently, Chinese power load prediction is highly focused; the paper deeply studies grey prediction and applies it to Chinese electricity consumption during the recent 14 years; through after-test test, it obtains grey prediction which has good adaptability to medium and long-term power load.

Laser power beaming: an emerging technology for power transmission and propulsion in space

NASA Astrophysics Data System (ADS)

Bennett, Harold E.

1997-05-01

A ground based laser beam transmitted to space can be used as an electric utility for satellites. It can significantly increase the electric power available to operate a satellite or to transport it from low earth orbit (LEO) to mid earth or geosynchronous orbits. The increase in electrical power compared to that obtainable from the sun is as much as 1000% for the same size solar panels. An increase in satellite electric power is needed to meet the increasing demands for power caused by the advent of 'direct to home TV,' for increased telecommunications, or for other demands made by the burgeoning 'space highway.' Monetary savings as compared to putting up multiple satellites in the same 'slot' can be over half a billion dollars. To obtain propulsion, the laser power can be beamed through the atmosphere to an 'orbit transfer vehicle' (OTV) satellite which travels back and forth between LEO and higher earth orbits. The OTV will transport the satellite into orbit as does a rocket but does not require the heavy fuel load needed if rocket propulsion is used. Monetary savings of 300% or more in launch costs are predicted. Key elements in the proposed concept are a 100 to 200 kW free- electron laser operating at 0.84 m in the photographic infrared region of the spectrum and a novel adaptive optic telescope.

Effect of accuracy of wind power prediction on power system operator

NASA Technical Reports Server (NTRS)

Schlueter, R. A.; Sigari, G.; Costi, T.

1985-01-01

This research project proposed a modified unit commitment that schedules connection and disconnection of generating units in response to load. A modified generation control is also proposed that controls steam units under automatic generation control, fast responding diesels, gas turbines and hydro units under a feedforward control, and wind turbine array output under a closed loop array control. This modified generation control and unit commitment require prediction of trend wind power variation one hour ahead and the prediction of error in this trend wind power prediction one half hour ahead. An improved meter for predicting trend wind speed variation is developed. Methods for accurately simulating the wind array power from a limited number of wind speed prediction records was developed. Finally, two methods for predicting the error in the trend wind power prediction were developed. This research provides a foundation for testing and evaluating the modified unit commitment and generation control that was developed to maintain operating reliability at a greatly reduced overall production cost for utilities with wind generation capacity.

Incorporating Wind Power Forecast Uncertainties Into Stochastic Unit Commitment Using Neural Network-Based Prediction Intervals.

PubMed

Quan, Hao; Srinivasan, Dipti; Khosravi, Abbas

2015-09-01

Penetration of renewable energy resources, such as wind and solar power, into power systems significantly increases the uncertainties on system operation, stability, and reliability in smart grids. In this paper, the nonparametric neural network-based prediction intervals (PIs) are implemented for forecast uncertainty quantification. Instead of a single level PI, wind power forecast uncertainties are represented in a list of PIs. These PIs are then decomposed into quantiles of wind power. A new scenario generation method is proposed to handle wind power forecast uncertainties. For each hour, an empirical cumulative distribution function (ECDF) is fitted to these quantile points. The Monte Carlo simulation method is used to generate scenarios from the ECDF. Then the wind power scenarios are incorporated into a stochastic security-constrained unit commitment (SCUC) model. The heuristic genetic algorithm is utilized to solve the stochastic SCUC problem. Five deterministic and four stochastic case studies incorporated with interval forecasts of wind power are implemented. The results of these cases are presented and discussed together. Generation costs, and the scheduled and real-time economic dispatch reserves of different unit commitment strategies are compared. The experimental results show that the stochastic model is more robust than deterministic ones and, thus, decreases the risk in system operations of smart grids.

Study on mathematical model to predict aerated power consumption in a gas-liquid stirred tank

NASA Astrophysics Data System (ADS)

Luan, Deyu; Zhang, Shengfeng; Wei, Xing; Chen, Yiming

The aerated power consumption characteristics in a transparent tank with diameter of 0.3 m and flat bottom stirred by a Rushton impeller were investigated by means of experimental measurement. The test fluid used was tap water as liquid and air as gas. Based on Weibull model, the complete correlation of aerated power with aerated flow number was established through non-linear fit analysis. The effects of aerated rate and impeller speed on aerated power consumption were made an exploration. Results show that the changeable trend of the aerated power consumption is found to be similar under different impeller speeds and impeller diameters, i.e. the aerated power is close to dropping linear at the beginning of gas input, and then the drop tendency decreases as the aerated rate increases, at the end, the aerated power is a constant on the whole as the aerated rate reaches up the loading state. The non-linear fit curve is done using the software Origin based on the experimental data. The fairly high precision of data fit is obtained, which indicates that the mathematical model established can be used to accurately predict the aerated power consumption, comparatively. The proposed research provides a valuable instruction and reference for the design and enlargement of stirred vessel.

Examination of CRISPR/Cas9 design tools and the effect of target site accessibility on Cas9 activity.

PubMed

Lee, Ciaran M; Davis, Timothy H; Bao, Gang

2018-04-01

What is the topic of this review? In this review, we analyse the performance of recently described tools for CRISPR/Cas9 guide RNA design, in particular, design tools that predict CRISPR/Cas9 activity. What advances does it highlight? Recently, many tools designed to predict CRISPR/Cas9 activity have been reported. However, the majority of these tools lack experimental validation. Our analyses indicate that these tools have poor predictive power. Our preliminary results suggest that target site accessibility should be considered in order to develop better guide RNA design tools with improved predictive power. The recent adaptation of the clustered regulatory interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) system for targeted genome engineering has led to its widespread application in many fields worldwide. In order to gain a better understanding of the design rules of CRISPR/Cas9 systems, several groups have carried out large library-based screens leading to some insight into sequence preferences among highly active target sites. To facilitate CRISPR/Cas9 design, these studies have spawned a plethora of guide RNA (gRNA) design tools with algorithms based solely on direct or indirect sequence features. Here, we demonstrate that the predictive power of these tools is poor, suggesting that sequence features alone cannot accurately inform the cutting efficiency of a particular CRISPR/Cas9 gRNA design. Furthermore, we demonstrate that DNA target site accessibility influences the activity of CRISPR/Cas9. With further optimization, we hypothesize that it will be possible to increase the predictive power of gRNA design tools by including both sequence and target site accessibility metrics. © 2017 The Authors. Experimental Physiology © 2017 The Physiological Society.

Depression, Abuse, Relationship Power and Condom Use by Pregnant and Postpartum Women with Substance Abuse History.

PubMed

Dévieux, Jessy G; Jean-Gilles, Michèle; Rosenberg, Rhonda; Beck-Sagué, Consuelo; Attonito, Jennifer M; Saxena, Anshul; Stein, Judith A

2016-02-01

Substance-abusing pregnant and postpartum women are less likely to maintain consistent condom use and drug and alcohol abstinence, which is particularly concerning in high HIV-prevalence areas. Data from 224 pregnant and postpartum women in substance abuse treatment were analyzed to examine effects of history of substance use, child abuse, and mental health problems on current substance use and condom-use barriers. Mediators were depression, relationship power and social support. Most participants (72.9 %) evidenced current depression. Less social support (-0.17, p < 0.05) and relationship power (-0.48, p < 0.001), and greater depression (-0.16, p < 0.05) predicted more condom-use barriers. History of mental health problems predicted condom-use barriers, mediated by recent depression and relationship power (0.15, p < 0.001). These findings suggest depression and diminished relationship power limit highest-risk women's ability to negotiate condom use and abstain from substance use, increasing their risk of acute HIV infection and vertical transmission.

Modelling and Prediction of Spark-ignition Engine Power Performance Using Incremental Least Squares Support Vector Machines

NASA Astrophysics Data System (ADS)

Wong, Pak-kin; Vong, Chi-man; Wong, Hang-cheong; Li, Ke

2010-05-01

Modern automotive spark-ignition (SI) power performance usually refers to output power and torque, and they are significantly affected by the setup of control parameters in the engine management system (EMS). EMS calibration is done empirically through tests on the dynamometer (dyno) because no exact mathematical engine model is yet available. With an emerging nonlinear function estimation technique of Least squares support vector machines (LS-SVM), the approximate power performance model of a SI engine can be determined by training the sample data acquired from the dyno. A novel incremental algorithm based on typical LS-SVM is also proposed in this paper, so the power performance models built from the incremental LS-SVM can be updated whenever new training data arrives. With updating the models, the model accuracies can be continuously increased. The predicted results using the estimated models from the incremental LS-SVM are good agreement with the actual test results and with the almost same average accuracy of retraining the models from scratch, but the incremental algorithm can significantly shorten the model construction time when new training data arrives.

People, planning, predictions pull DP&L to pinnacle

DOE Office of Scientific and Technical Information (OSTI.GOV)

Beaty, W.; Warkentin, D.

Dayton Power and Light was chosen as the 26th utility to receive Electric Light and Power`s annual Utility of the Year award for investor-owned electric utilities. The award not only recognizes management for having guided the company to a high level of achievement, but to each employee for their contribution to the company`s success. Using its formula of three Ps to success - people, planning, and predict and prevent - this West Central Ohio utility plans on using its current plain vanilla approach to business to carve out its own pattern for the years ahead. DP&L`s employees have gone abovemore » and beyond the call of duty to serve its customers and shareholders. The utility`s operations are epitomized by the excellent fuel efficiency of its generating plants. DP&L has been in Electric Light & Power`s top 10 heat rate rankings for nine out of the past 10 years. Investor earnings per share increased from $1.15 in 1991 to $1.34 in 1992, with earnings per share rising by 6% to $1.42 in 1993.« less

RTG performance on Galileo and Ulysses and Cassini test results

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kelly, C.E.; Klee, P.M.

Power output from telemetry for the two Galileo RTGs are shown from the 1989 launch to the recent Jupiter encounter. Comparisons of predicted, measured and required performance are shown. Similar comparisons are made for the RTG on the Ulysses spacecraft which completed its planned mission in 1995. Also presented are test results from small scale thermoelectric modules and full scale converters performed for the Cassini program. The Cassini mission to Saturn is scheduled for an October 1997 launch. Small scale module test results on thermoelectric couples from the qualification and flight production runs are shown. These tests have exceeded 19,000more » hours are continuing to provide increased confidence in the predicted long term performance of the Cassini RTGs. Test results are presented for full scale units both ETGs (E-6, E-7) and RTGs (F-2, F-5) along with mission power predictions. F-5, fueled in 1985, served as a spare for the Galileo and Ulysses missions and plays the same role in the Cassini program. It has successfully completed all acceptance testing. The ten years storage between thermal vacuum tests is the longest ever experienced by an RTG. The data from this test are unique in providing the effects of long term low temperature storage on power output. All ETG and RTG test results to date indicate that the power requirements of the Cassini spacecraft will be met. BOM and EOM power margins of at least five percent are predicted. {copyright} {ital 1997 American Institute of Physics.}« less

Analytical modeling of helium turbomachinery using FORTRAN 77

NASA Astrophysics Data System (ADS)

Balaji, Purushotham

Advanced Generation IV modular reactors, including Very High Temperature Reactors (VHTRs), utilize helium as the working fluid, with a potential for high efficiency power production utilizing helium turbomachinery. Helium is chemically inert and nonradioactive which makes the gas ideal for a nuclear power-plant environment where radioactive leaks are a high concern. These properties of helium gas helps to increase the safety features as well as to decrease the aging process of plant components. The lack of sufficient helium turbomachinery data has made it difficult to study the vital role played by the gas turbine components of these VHTR powered cycles. Therefore, this research work focuses on predicting the performance of helium compressors. A FORTRAN77 program is developed to simulate helium compressor operation, including surge line prediction. The resulting design point and off design performance data can be used to develop compressor map files readable by Numerical Propulsion Simulation Software (NPSS). This multi-physics simulation software that was developed for propulsion system analysis has found applications in simulating power-plant cycles.

From damselflies to pterosaurs: how burst and sustainable flight performance scale with size.

PubMed

Marden, J H

1994-04-01

Recent empirical data for short-burst lift and power production of flying animals indicate that mass-specific lift and power output scale independently (lift) or slightly positively (power) with increasing size. These results contradict previous theory, as well as simple observation, which argues for degradation of flight performance with increasing size. Here, empirical measures of lift and power during short-burst exertion are combined with empirically based estimates of maximum muscle power output in order to predict how burst and sustainable performance scale with body size. The resulting model is used to estimate performance of the largest extant flying birds and insects, along with the largest flying animals known from fossils. These estimates indicate that burst flight performance capacities of even the largest extinct fliers (estimated mass 250 kg) would allow takeoff from the ground; however, limitations on sustainable power output should constrain capacity for continuous flight at body sizes exceeding 0.003-1.0 kg, depending on relative wing length and flight muscle mass.

Sensitivity to Referential Ambiguity in Discourse: The Role of Attention, Working Memory, and Verbal Ability

PubMed Central

Boudewyn, Megan A.; Long, Debra L.; Traxler, Matthew J.; Lesh, Tyler A.; Dave, Shruti; Mangun, George R.; Carter, Cameron S.; Swaab, Tamara Y.

2016-01-01

The establishment of reference is essential to language comprehension. The goal of this study was to examine listeners’ sensitivity to referential ambiguity as a function of individual variation in attention, working memory capacity, and verbal ability. Participants listened to stories in which two entities were introduced that were either very similar (e.g., two oaks) or less similar (e.g., one oak and one elm). The manipulation rendered an anaphor in a subsequent sentence (e.g., oak) ambiguous or unambiguous. EEG was recorded as listeners comprehended the story, after which participants completed tasks to assess working memory, verbal ability, and the ability to use context in task performance. Power in the alpha and theta frequency bands when listeners received critical information about the discourse entities (e.g., oaks) was used to index attention and the involvement of the working memory system in processing the entities. These measures were then used to predict an ERP component that is sensitive to referential ambiguity, the Nref, which was recorded when listeners received the anaphor. Nref amplitude at the anaphor was predicted by alpha power during the earlier critical sentence: Individuals with increased alpha power in ambiguous compared with unambiguous stories were less sensitive to the anaphor's ambiguity. Verbal ability was also predictive of greater sensitivity to referential ambiguity. Finally, increased theta power in the ambiguous compared with unambiguous condition was associated with higher working-memory span. These results highlight the role of attention and working memory in referential processing during listening comprehension. PMID:26401815

Sensitivity to Referential Ambiguity in Discourse: The Role of Attention, Working Memory, and Verbal Ability.

PubMed

Boudewyn, Megan A; Long, Debra L; Traxler, Matthew J; Lesh, Tyler A; Dave, Shruti; Mangun, George R; Carter, Cameron S; Swaab, Tamara Y

2015-12-01

The establishment of reference is essential to language comprehension. The goal of this study was to examine listeners' sensitivity to referential ambiguity as a function of individual variation in attention, working memory capacity, and verbal ability. Participants listened to stories in which two entities were introduced that were either very similar (e.g., two oaks) or less similar (e.g., one oak and one elm). The manipulation rendered an anaphor in a subsequent sentence (e.g., oak) ambiguous or unambiguous. EEG was recorded as listeners comprehended the story, after which participants completed tasks to assess working memory, verbal ability, and the ability to use context in task performance. Power in the alpha and theta frequency bands when listeners received critical information about the discourse entities (e.g., oaks) was used to index attention and the involvement of the working memory system in processing the entities. These measures were then used to predict an ERP component that is sensitive to referential ambiguity, the Nref, which was recorded when listeners received the anaphor. Nref amplitude at the anaphor was predicted by alpha power during the earlier critical sentence: Individuals with increased alpha power in ambiguous compared with unambiguous stories were less sensitive to the anaphor's ambiguity. Verbal ability was also predictive of greater sensitivity to referential ambiguity. Finally, increased theta power in the ambiguous compared with unambiguous condition was associated with higher working-memory span. These results highlight the role of attention and working memory in referential processing during listening comprehension.

Unified Performance and Power Modeling of Scientific Workloads

DOE Office of Scientific and Technical Information (OSTI.GOV)

Song, Shuaiwen; Barker, Kevin J.; Kerbyson, Darren J.

2013-11-17

It is expected that scientific applications executing on future large-scale HPC must be optimized not only in terms of performance, but also in terms of power consumption. As power and energy become increasingly constrained resources, researchers and developers must have access to tools that will allow for accurate prediction of both performance and power consumption. Reasoning about performance and power consumption in concert will be critical for achieving maximum utilization of limited resources on future HPC systems. To this end, we present a unified performance and power model for the Nek-Bone mini-application developed as part of the DOE's CESAR Exascalemore » Co-Design Center. Our models consider the impact of computation, point-to-point communication, and collective communication« less

Manufacturing of diamond windows for synchrotron radiation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schildkamp, W.; Nikitina, L.

2012-09-15

A new diamond window construction is presented and explicit manufacturing details are given. This window will increase the power dissipation by about a factor of 4 over present day state of the art windows to absorb 600 W of power. This power will be generated by in-vacuum undulators with the storage ring ALBA operating at a design current of 400 mA. Extensive finite element (FE) calculations are included to predict the windows behavior accompanied by explanations for the chosen boundary conditions. A simple linear model was used to cross-check the FE calculations.

A tale of four surveys:What have we learned about the variable sky?

NASA Astrophysics Data System (ADS)

Howell, S. B.

2008-03-01

Four tales concerning a set of photometric imaging surveys are spun. The reader is lead through a brief description of each survey and major results are presented. The four surveys are summarized in a few simple "rules": 1) The fraction of point sources that are variable with respect to those that are found to be constant, increases as a power law as the photometric precision of the survey improves, and 2) This fact can be simply formulated as a power law function granting the user a predictive power.

Thermospheric mass density model error variance as a function of time scale

NASA Astrophysics Data System (ADS)

Emmert, J. T.; Sutton, E. K.

2017-12-01

In the increasingly crowded low-Earth orbit environment, accurate estimation of orbit prediction uncertainties is essential for collision avoidance. Poor characterization of such uncertainty can result in unnecessary and costly avoidance maneuvers (false positives) or disregard of a collision risk (false negatives). Atmospheric drag is a major source of orbit prediction uncertainty, and is particularly challenging to account for because it exerts a cumulative influence on orbital trajectories and is therefore not amenable to representation by a single uncertainty parameter. To address this challenge, we examine the variance of measured accelerometer-derived and orbit-derived mass densities with respect to predictions by thermospheric empirical models, using the data-minus-model variance as a proxy for model uncertainty. Our analysis focuses mainly on the power spectrum of the residuals, and we construct an empirical model of the variance as a function of time scale (from 1 hour to 10 years), altitude, and solar activity. We find that the power spectral density approximately follows a power-law process but with an enhancement near the 27-day solar rotation period. The residual variance increases monotonically with altitude between 250 and 550 km. There are two components to the variance dependence on solar activity: one component is 180 degrees out of phase (largest variance at solar minimum), and the other component lags 2 years behind solar maximum (largest variance in the descending phase of the solar cycle).

A distributed big data storage and data mining framework for solar-generated electricity quantity forecasting

NASA Astrophysics Data System (ADS)

Wang, Jianzong; Chen, Yanjun; Hua, Rui; Wang, Peng; Fu, Jia

2012-02-01

Photovoltaic is a method of generating electrical power by converting solar radiation into direct current electricity using semiconductors that exhibit the photovoltaic effect. Photovoltaic power generation employs solar panels composed of a number of solar cells containing a photovoltaic material. Due to the growing demand for renewable energy sources, the manufacturing of solar cells and photovoltaic arrays has advanced considerably in recent years. Solar photovoltaics are growing rapidly, albeit from a small base, to a total global capacity of 40,000 MW at the end of 2010. More than 100 countries use solar photovoltaics. Driven by advances in technology and increases in manufacturing scale and sophistication, the cost of photovoltaic has declined steadily since the first solar cells were manufactured. Net metering and financial incentives, such as preferential feed-in tariffs for solar-generated electricity; have supported solar photovoltaics installations in many countries. However, the power that generated by solar photovoltaics is affected by the weather and other natural factors dramatically. To predict the photovoltaic energy accurately is of importance for the entire power intelligent dispatch in order to reduce the energy dissipation and maintain the security of power grid. In this paper, we have proposed a big data system--the Solar Photovoltaic Power Forecasting System, called SPPFS to calculate and predict the power according the real-time conditions. In this system, we utilized the distributed mixed database to speed up the rate of collecting, storing and analysis the meteorological data. In order to improve the accuracy of power prediction, the given neural network algorithm has been imported into SPPFS.By adopting abundant experiments, we shows that the framework can provide higher forecast accuracy-error rate less than 15% and obtain low latency of computing by deploying the mixed distributed database architecture for solar-generated electricity.

Is laughter a better vocal change detector than a growl?

PubMed

Pinheiro, Ana P; Barros, Carla; Vasconcelos, Margarida; Obermeier, Christian; Kotz, Sonja A

2017-07-01

The capacity to predict what should happen next and to minimize any discrepancy between an expected and an actual sensory input (prediction error) is a central aspect of perception. Particularly in vocal communication, the effective prediction of an auditory input that informs the listener about the emotionality of a speaker is critical. What is currently unknown is how the perceived valence of an emotional vocalization affects the capacity to predict and detect a change in the auditory input. This question was probed in a combined event-related potential (ERP) and time-frequency analysis approach. Specifically, we examined the brain response to standards (Repetition Positivity) and to deviants (Mismatch Negativity - MMN), as well as the anticipatory response to the vocal sounds (pre-stimulus beta oscillatory power). Short neutral, happy (laughter), and angry (growls) vocalizations were presented both as standard and deviant stimuli in a passive oddball listening task while participants watched a silent movie and were instructed to ignore the vocalizations. MMN amplitude was increased for happy compared to neutral and angry vocalizations. The Repetition Positivity was enhanced for happy standard vocalizations. Induced pre-stimulus upper beta power was increased for happy vocalizations, and predicted the modulation of the standard Repetition Positivity. These findings indicate enhanced sensory prediction for positive vocalizations such as laughter. Together, the results suggest that positive vocalizations are more effective predictors in social communication than angry and neutral ones, possibly due to their high social significance. Copyright © 2017 Elsevier Ltd. All rights reserved.

The extension of total gain (TG) statistic in survival models: properties and applications.

PubMed

Choodari-Oskooei, Babak; Royston, Patrick; Parmar, Mahesh K B

2015-07-01

The results of multivariable regression models are usually summarized in the form of parameter estimates for the covariates, goodness-of-fit statistics, and the relevant p-values. These statistics do not inform us about whether covariate information will lead to any substantial improvement in prediction. Predictive ability measures can be used for this purpose since they provide important information about the practical significance of prognostic factors. R (2)-type indices are the most familiar forms of such measures in survival models, but they all have limitations and none is widely used. In this paper, we extend the total gain (TG) measure, proposed for a logistic regression model, to survival models and explore its properties using simulations and real data. TG is based on the binary regression quantile plot, otherwise known as the predictiveness curve. Standardised TG ranges from 0 (no explanatory power) to 1 ('perfect' explanatory power). The results of our simulations show that unlike many of the other R (2)-type predictive ability measures, TG is independent of random censoring. It increases as the effect of a covariate increases and can be applied to different types of survival models, including models with time-dependent covariate effects. We also apply TG to quantify the predictive ability of multivariable prognostic models developed in several disease areas. Overall, TG performs well in our simulation studies and can be recommended as a measure to quantify the predictive ability in survival models.

Modeling of detachment experiments at DIII-D

DOE PAGES

Canik, John M.; Briesemeister, Alexis R.; Lasnier, C. J.; ...

2014-11-26

Edge fluid–plasma/kinetic–neutral modeling of well-diagnosed DIII-D experiments is performed in order to document in detail how well certain aspects of experimental measurements are reproduced within the model as the transition to detachment is approached. Results indicate, that at high densities near detachment onset, the poloidal temperature profile produced in the simulations agrees well with that measured in experiment. However, matching the heat flux in the model requires a significant increase in the radiated power compared to what is predicted using standard chemical sputtering rates. Lastly, these results suggest that the model is adequate to predict the divertor temperature, provided thatmore » the discrepancy in radiated power level can be resolved.« less

Using marketing muscle to sell fat: the rise of obesity in the modern economy.

PubMed

Zimmerman, Frederick J

2011-01-01

The large increase in obesity in the past 30 years has often been explained in rational choice terms; for example, a decline in food prices has engendered greater food consumption. On closer examination, this kind of explanation does not fit the facts of the current obesity epidemic. Instead, an unprecedented expansion in the scope, power, and ubiquity of food marketing has coincided with an unprecedented expansion in food consumption in predictable ways. Ongoing protestations that the causes of the recent increase in obesity are unknown may overstate the case. Ample evidence indicates that the obesity epidemic is, at least to a large degree, the result of increased marketing power over the American diet. Only by reigning in or countering marketing power can rationality be restored to the dietary choices of Americans.

Effect of nuclear power on CO₂ emission from power plant sector in Iran.

PubMed

Kargari, Nargess; Mastouri, Reza

2011-01-01

It is predicted that demand for electricity in Islamic Republic of Iran will continue to increase dramatically in the future due to the rapid pace of economic development leading to construction of new power plants. At the present time, most of electricity is generated by burning fossil fuels which result in emission of great deal of pollutants and greenhouse gases (GHG) such as SO₂, NOx, and CO₂. The power industry is the largest contributor to these emissions. Due to minimal emission of GHG by renewable and nuclear power plants, they are most suitable replacements for the fossil-fueled power plants. However, the nuclear power plants are more suitable than renewable power plants in providing baseload electricity. The Bushehr Nuclear Power Plant, the only nuclear power plant of Iran, is expected to start operation in 2010. This paper attempts to interpret the role of Bushehr nuclear power plant (BNPP) in CO₂ emission trend of power plant sector in Iran. In order to calculate CO₂ emissions from power plants, National CO₂ coefficients have been used. The National CO₂ emission coefficients are according to different fuels (natural gas, fuels gas, fuel oil). By operating Bushehr Nuclear Power Plant in 2010, nominal capacity of electricity generation in Iran will increase by about 1,000 MW, which increases the electricity generation by almost 7,000 MWh/year (it is calculated according to availability factor and nominal capacity of BNPP). Bushehr Nuclear Power Plant will decrease the CO₂ emission in Iran power sector, by about 3% in 2010.

Gaussian Processes for Prediction of Homing Pigeon Flight Trajectories

NASA Astrophysics Data System (ADS)

Mann, Richard; Freeman, Robin; Osborne, Michael; Garnett, Roman; Meade, Jessica; Armstrong, Chris; Biro, Dora; Guilford, Tim; Roberts, Stephen

2009-12-01

We construct and apply a stochastic Gaussian Process (GP) model of flight trajectory generation for pigeons trained to home from specific release sites. The model shows increasing predictive power as the birds become familiar with the sites, mirroring the animal's learning process. We show how the increasing similarity between successive flight trajectories can be used to infer, with increasing accuracy, an idealised route that captures the repeated spatial aspects of the bird's flight. We subsequently use techniques associated with reduced-rank GP approximations to objectively identify the key waypoints used by each bird to memorise its idiosyncratic habitual route between the release site and the home loft.

Nilsson's Power Model connecting speed and road trauma: applicability by road type and alternative models for urban roads.

PubMed

Cameron, M H; Elvik, R

2010-11-01

Nilsson (1981) proposed power relationships connecting changes in traffic speeds with changes in road crashes at various levels of injury severity. Increases in fatal crashes are related to the 4(th) power of the increase in mean speed, increases in serious casualty crashes (those involving death or serious injury) according to the 3(rd) power, and increases in casualty crashes (those involving death or any injury) according to the 2(nd) power. Increases in numbers of crash victims at cumulative levels of injury severity are related to the crash increases plus higher powers predicting the number of victims per crash. These relationships are frequently applied in OECD countries to estimate road trauma reductions resulting from expected speed reductions. The relationships were empirically derived based on speed changes resulting from a large number of rural speed limit changes in Sweden during 1967-1972. Nilsson (2004) noted that there had been very few urban speed limit changes studied to test his power model. This paper aims to test the assumption that the model is equally applicable in all road environments. It was found that the road environment is an important moderator of Nilsson's power model. While Nilsson's model appears satisfactory for rural highways and freeways, the model does not appear to be directly applicable to traffic speed changes on urban arterial roads. The evidence of monotonically increasing powers applicable to changes in road trauma at increasing injury severity levels with changes in mean speed is weak. The estimated power applicable to serious casualties on urban arterial roads was significantly less than that on rural highways, which was also significantly less than that on freeways. Alternative models linking the parameters of speed distributions with road trauma are reviewed and some conclusions reached for their use on urban roads instead of Nilsson's model. Further research is needed on the relationships between serious road trauma and urban speeds. 2010 Elsevier Ltd. All rights reserved.

Yoga Poses Increase Subjective Energy and State Self-Esteem in Comparison to ‘Power Poses’

PubMed Central

Golec de Zavala, Agnieszka; Lantos, Dorottya; Bowden, Deborah

2017-01-01

Research on beneficial consequences of yoga focuses on the effects of yogic breathing and meditation. Less is known about the psychological effects of performing yoga postures. The present study investigated the effects of yoga poses on subjective sense of energy and self-esteem. The effects of yoga postures were compared to the effects of ‘power poses,’ which arguably increase the sense of power and self-confidence due to their association with interpersonal dominance (Carney et al., 2010). The study tested the novel prediction that yoga poses, which are not associated with interpersonal dominance but increase bodily energy, would increase the subjective feeling of energy and therefore increase self-esteem compared to ‘high power’ and ‘low power’ poses. A two factorial, between participants design was employed. Participants performed either two standing yoga poses with open front of the body (n = 19), two standing yoga poses with covered front of the body (n = 22), two expansive, high power poses (n = 21), or two constrictive, low power poses (n = 20) for 1-min each. The results showed that yoga poses in comparison to ‘power poses’ increased self-esteem. This effect was mediated by an increased subjective sense of energy and was observed when baseline trait self-esteem was controlled for. These results suggest that the effects of performing open, expansive body postures may be driven by processes other than the poses’ association with interpersonal power and dominance. This study demonstrates that positive effects of yoga practice can occur after performing yoga poses for only 2 min. PMID:28553249

Influence of guide vane opening on the flow phenomena in a pump turbine during a fast transition from pump mode to generating mode

NASA Astrophysics Data System (ADS)

Stens, C.; Riedelbauch, S.

2017-04-01

Due to a more fluctuating energy production caused by renewable energies such as wind and solar power, the number of changes between operating points in pumped storage power plants has increased over the last years. To further increase available regulating power, it is desirable to speed up these changes of operation conditions in Hydro units. Previous studies showed that CFD is well capable of predicting the flow phenomena in the machine under unsteady conditions for a large guide vane opening angle. The present paper investigates the benefits of nearly closed guide vanes during the transition. Results are compared between the two different angles as well as between simulation and measurement.

Non-monotonic behavior of electron temperature in argon inductively coupled plasma and its analysis via novel electron mean energy equation

NASA Astrophysics Data System (ADS)

Zhao, Shu-Xia

2018-03-01

In this work, the behavior of electron temperature against the power in argon inductively coupled plasma is investigated by a fluid model. The model properly reproduces the non-monotonic variation of temperature with power observed in experiments. By means of a novel electron mean energy equation proposed for the first time in this article, this electron temperature behavior is interpreted. In the overall considered power range, the skin effect of radio frequency electric field results in localized deposited power density, responsible for an increase of electron temperature with power by means of one parameter defined as power density divided by electron density. At low powers, the rate fraction of multistep and Penning ionizations of metastables that consume electron energy two times significantly increases with power, which dominates over the skin effect and consequently leads to the decrease of temperature with power. In the middle power regime, a transition region of temperature is given by the competition between the ionizing effect of metastables and the skin effect of electric field. The power location where the temperature alters its trend moves to the low power end as increasing the pressure due to the lack of metastables. The non-monotonic curve of temperature is asymmetric at the short chamber due to the weak role of skin effect in increasing the temperature and tends symmetric when axially prolonging the chamber. Still, the validity of the fluid model in this prediction is estimated and the role of neutral gas heating is guessed. This finding is helpful for people understanding the different trends of temperature with power in the literature.

Short-term load and wind power forecasting using neural network-based prediction intervals.

PubMed

Quan, Hao; Srinivasan, Dipti; Khosravi, Abbas

2014-02-01

Electrical power systems are evolving from today's centralized bulk systems to more decentralized systems. Penetrations of renewable energies, such as wind and solar power, significantly increase the level of uncertainty in power systems. Accurate load forecasting becomes more complex, yet more important for management of power systems. Traditional methods for generating point forecasts of load demands cannot properly handle uncertainties in system operations. To quantify potential uncertainties associated with forecasts, this paper implements a neural network (NN)-based method for the construction of prediction intervals (PIs). A newly introduced method, called lower upper bound estimation (LUBE), is applied and extended to develop PIs using NN models. A new problem formulation is proposed, which translates the primary multiobjective problem into a constrained single-objective problem. Compared with the cost function, this new formulation is closer to the primary problem and has fewer parameters. Particle swarm optimization (PSO) integrated with the mutation operator is used to solve the problem. Electrical demands from Singapore and New South Wales (Australia), as well as wind power generation from Capital Wind Farm, are used to validate the PSO-based LUBE method. Comparative results show that the proposed method can construct higher quality PIs for load and wind power generation forecasts in a short time.

Modeling of flowing gas diode pumped alkali lasers: dependence of the operation on the gas velocity and on the nature of the buffer gas.

PubMed

Barmashenko, B D; Rosenwaks, S

2012-09-01

A simple, semi-analytical model of flowing gas diode pumped alkali lasers (DPALs) is presented. The model takes into account the rise of temperature in the lasing medium with increasing pump power, resulting in decreasing pump absorption and slope efficiency. The model predicts the dependence of power on the flow velocity in flowing gas DPALs and checks the effect of using a buffer gas with high molar heat capacity and large relaxation rate constant between the 2P3/2 and 2P1/2 fine-structure levels of the alkali atom. It is found that the power strongly increases with flow velocity and that by replacing, e.g., ethane by propane as a buffer gas the power may be further increased by up to 30%. Eight kilowatt is achievable for 20 kW pump at flow velocity of 20  m/s.

Towards a renewal of the propeller in aeronautics

NASA Technical Reports Server (NTRS)

Berger, D.; Jacquet, P.

1985-01-01

The reasons for reconsidering the propeller for aircraft propulsion, the areas of application, and necessary developments are considered. Rising fuel costs and an increasing theoretical and experimental data base for turboprop engines have demonstrated that significant cost savings can be realized by the use of propellers. Propellers are well-suited to powering aircraft traveling at speeds up to Mach 0.65. Work is progressing on the development of a 150 seat aircraft which has a cruise speed of Mach 0.8, powered by a turboprop attached to an engine of 15,000 shp. Aeroelasticity analyses ae necessary in order to characterize the behavior of thin profile propfan blades, particularly to predict the oscillations through the entire functional range. High-power reducers must be developed, and the level of cabin noise must be controlled to less than 90 dB. Commercial applications are predicted for turboprops in specific instances.

Simplified APC for Space Shuttle applications. [Adaptive Predictive Coding for speech transmission

NASA Technical Reports Server (NTRS)

Hutchins, S. E.; Batson, B. H.

1975-01-01

This paper describes an 8 kbps adaptive predictive digital speech transmission system which was designed for potential use in the Space Shuttle Program. The system was designed to provide good voice quality in the presence of both cabin noise on board the Shuttle and the anticipated bursty channel. Minimal increase in size, weight, and power over the current high data rate system was also a design objective.

Prediction of Wind Energy Resources (PoWER) Users Guide

DTIC Science & Technology

2016-01-01

ARL-TR-7573● JAN 2016 US Army Research Laboratory Prediction of Wind Energy Resources (PoWER) User’s Guide by David P Sauter...not return it to the originator. ARL-TR-7573 ● JAN 2016 US Army Research Laboratory Prediction of Wind Energy Resources (PoWER...2016 2. REPORT TYPE Final 3. DATES COVERED (From - To) 09/2015–11/2015 4. TITLE AND SUBTITLE Prediction of Wind Energy Resources (PoWER) User’s

Application and verification of ECMWF seasonal forecast for wind energy

NASA Astrophysics Data System (ADS)

Žagar, Mark; Marić, Tomislav; Qvist, Martin; Gulstad, Line

2015-04-01

A good understanding of long-term annual energy production (AEP) is crucial when assessing the business case of investing in green energy like wind power. The art of wind-resource assessment has emerged into a scientific discipline on its own, which has advanced at high pace over the last decade. This has resulted in continuous improvement of the AEP accuracy and, therefore, increase in business case certainty. Harvesting the full potential output of a wind farm or a portfolio of wind farms depends heavily on optimizing operation and management strategy. The necessary information for short-term planning (up to 14 days) is provided by standard weather and power forecasting services, and the long-term plans are based on climatology. However, the wind-power industry is lacking quality information on intermediate scales of the expected variability in seasonal and intra-annual variations and their geographical distribution. The seasonal power forecast presented here is designed to bridge this gap. The seasonal power production forecast is based on the ECMWF seasonal weather forecast and the Vestas' high-resolution, mesoscale weather library. The seasonal weather forecast is enriched through a layer of statistical post-processing added to relate large-scale wind speed anomalies to mesoscale climatology. The resulting predicted energy production anomalies, thus, include mesoscale effects not captured by the global forecasting systems. The turbine power output is non-linearly related to the wind speed, which has important implications for the wind power forecast. In theory, the wind power is proportional to the cube of wind speed. However, due to the nature of turbine design, this exponent is close to 3 only at low wind speeds, becomes smaller as the wind speed increases, and above 11-13 m/s the power output remains constant, called the rated power. The non-linear relationship between wind speed and the power output generally increases sensitivity of the forecasted power to the wind speed anomalies. On the other hand, in some cases and areas where turbines operate close to, or above the rated power, the sensitivity of power forecast is reduced. Thus, the seasonal power forecasting system requires good knowledge of the changes in frequency of events with sufficient wind speeds to have acceptable skill. The scientific background for the Vestas seasonal power forecasting system is described and the relationship between predicted monthly wind speed anomalies and observed wind energy production are investigated for a number of operating wind farms in different climate zones. Current challenges will be discussed and some future research and development areas identified.

Analysis and experimental evaluation of shunt active power filter for power quality improvement based on predictive direct power control.

PubMed

Aissa, Oualid; Moulahoum, Samir; Colak, Ilhami; Babes, Badreddine; Kabache, Nadir

2017-10-12

This paper discusses the use of the concept of classical and predictive direct power control for shunt active power filter function. These strategies are used to improve the active power filter performance by compensation of the reactive power and the elimination of the harmonic currents drawn by non-linear loads. A theoretical analysis followed by a simulation using MATLAB/Simulink software for the studied techniques has been established. Moreover, two test benches have been carried out using the dSPACE card 1104 for the classic and predictive DPC control to evaluate the studied methods in real time. Obtained results are presented and compared in this paper to confirm the superiority of the predictive technique. To overcome the pollution problems caused by the consumption of fossil fuels, renewable energies are the alternatives recommended to ensure green energy. In the same context, the tested predictive filter can easily be supplied by a renewable energy source that will give its impact to enhance the power quality.

A simple microbial fuel cell model for improvement of biomedical device powering times.

PubMed

Roxby, Daniel N; Tran, Nham; Nguyen, Hung T

2014-01-01

This study describes a Matlab based Microbial Fuel Cell (MFC) model for a suspended microbial population, in the anode chamber for the use of the MFC in powering biomedical devices. The model contains three main sections including microbial growth, microbial chemical uptake and secretion and electrochemical modeling. The microbial growth portion is based on a Continuously Stirred Tank Reactor (CSTR) model for the microbial growth with substrate and electron acceptors. Microbial stoichiometry is used to determine chemical concentrations and their rates of change and transfer within the MFC. These parameters are then used in the electrochemical modeling for calculating current, voltage and power. The model was tested for typically exhibited MFC characteristics including increased electrode distances and surface areas, overpotentials and operating temperatures. Implantable biomedical devices require long term powering which is the main objective for MFCs. Towards this end, our model was tested with different initial substrate and electron acceptor concentrations, revealing a four-fold increase in concentrations decreased the power output time by 50%. Additionally, the model also predicts that for a 35.7% decrease in specific growth rate, a 50% increase in power longevity is possible.

Prediction of Cerebral Hyperperfusion Syndrome with Velocity Blood Pressure Index.

PubMed

Lai, Zhi-Chao; Liu, Bao; Chen, Yu; Ni, Leng; Liu, Chang-Wei

2015-06-20

Cerebral hyperperfusion syndrome is an important complication of carotid endarterectomy (CEA). An >100% increase in middle cerebral artery velocity (MCAV) after CEA is used to predict the cerebral hyperperfusion syndrome (CHS) development, but the accuracy is limited. The increase in blood pressure (BP) after surgery is a risk factor of CHS, but no study uses it to predict CHS. This study was to create a more precise parameter for prediction of CHS by combined the increase of MCAV and BP after CEA. Systolic MCAV measured by transcranial Doppler and systematic BP were recorded preoperatively; 30 min postoperatively. The new parameter velocity BP index (VBI) was calculated from the postoperative increase ratios of MCAV and BP. The prediction powers of VBI and the increase ratio of MCAV (velocity ratio [VR]) were compared for predicting CHS occurrence. Totally, 6/185 cases suffered CHS. The best-fit cut-off point of 2.0 for VBI was identified, which had 83.3% sensitivity, 98.3% specificity, 62.5% positive predictive value and 99.4% negative predictive value for CHS development. This result is significantly better than VR (33.3%, 97.2%, 28.6% and 97.8%). The area under the curve (AUC) of receiver operating characteristic: AUC(VBI) = 0.981, 95% confidence interval [CI] 0.949-0.995; AUC(VR) = 0.935, 95% CI 0.890-0.966, P = 0.02. The new parameter VBI can more accurately predict patients at risk of CHS after CEA. This observation needs to be validated by larger studies.

Gender, status, and psychiatric labels.

PubMed

Kroska, Amy; Harkness, Sarah K; Brown, Ryan P; Thomas, Lauren S

2015-11-01

We examine a key modified labeling theory proposition-that a psychiatric label increases vulnerability to competence-based criticism and rejection-within task- and collectively oriented dyads comprised of same-sex individuals with equivalent education. Drawing on empirical work that approximates these conditions, we expect the proposition to hold only among men. We also expect education, operationalized with college class standing, to moderate the effects of gender by reducing men's and increasing women's criticism and rejection. But, we also expect the effect of education to weaken when men work with a psychiatric patient. As predicted, men reject suggestions from teammates with a psychiatric history more frequently than they reject suggestions from other teammates, while women's resistance to influence is unaffected by their teammate's psychiatric status. Men also rate psychiatric patient teammates as less powerful but no lower in status than other teammates, while women's teammate assessments are unaffected by their teammate's psychiatric status. Also as predicted, education reduces men's resistance to influence when their teammate has no psychiatric history. Education also increases men's ratings of their teammate's power, as predicted, but has no effect on women's resistance to influence or teammate ratings. We discuss the implications of these findings for the modified labeling theory of mental illness and status characteristics theory. Copyright © 2015 Elsevier Inc. All rights reserved.

Model calculations of kinetic and fluid dynamic processes in diode pumped alkali lasers

NASA Astrophysics Data System (ADS)

Barmashenko, Boris D.; Rosenwaks, Salman; Waichman, Karol

2013-10-01

Kinetic and fluid dynamic processes in diode pumped alkali lasers (DPALs) are analyzed in detail using a semianalytical model, applicable to both static and flowing-gas devices. The model takes into account effects of temperature rise, excitation of neutral alkali atoms to high lying electronic states and their losses due to ionization and chemical reactions, resulting in a decrease of the pump absorption, slope efficiency and lasing power. Effects of natural convection in static DPALs are also taken into account. The model is applied to Cs DPALs and the results are in good agreement with measurements in a static [B.V. Zhdanov, J. Sell and R.J. Knize, Electron. Lett. 44, 582 (2008)] and 1-kW flowing-gas [A.V. Bogachev et al., Quantum Electron. 42, 95 (2012)] DPALs. It predicts the dependence of power on the flow velocity in flowing-gas DPALs and on the buffer gas composition. The maximum values of the laser power can be substantially increased by optimization of the flowing-gas DPAL parameters. In particular for the aforementioned 1 kW DPAL, 6 kW maximum power is achievable just by increasing the pump power and the temperature of the wall and the gas at the flow inlet (resulting in increase of the alkali saturated vapor density). Dependence of the lasing power on the pump power is non-monotonic: the power first increases, achieves its maximum and then decreases. The decrease of the lasing power with increasing pump power at large values of the latter is due to the rise of the aforementioned losses of the alkali atoms as a result of ionization. Work in progress applying two-dimensional computational fluid dynamics modeling of flowing-gas DPALs is also reported.

Power scaling and experimentally fitted model for broad area quantum cascade lasers in continuous wave operation

NASA Astrophysics Data System (ADS)

Suttinger, Matthew; Go, Rowel; Figueiredo, Pedro; Todi, Ankesh; Shu, Hong; Leshin, Jason; Lyakh, Arkadiy

2018-01-01

Experimental and model results for 15-stage broad area quantum cascade lasers (QCLs) are presented. Continuous wave (CW) power scaling from 1.62 to 2.34 W has been experimentally demonstrated for 3.15-mm long, high reflection-coated QCLs for an active region width increased from 10 to 20 μm. A semiempirical model for broad area devices operating in CW mode is presented. The model uses measured pulsed transparency current, injection efficiency, waveguide losses, and differential gain as input parameters. It also takes into account active region self-heating and sublinearity of pulsed power versus current laser characteristic. The model predicts that an 11% improvement in maximum CW power and increased wall-plug efficiency can be achieved from 3.15 mm×25 μm devices with 21 stages of the same design, but half doping in the active region. For a 16-stage design with a reduced stage thickness of 300 Å, pulsed rollover current density of 6 kA/cm2, and InGaAs waveguide layers, an optical power increase of 41% is projected. Finally, the model projects that power level can be increased to ˜4.5 W from 3.15 mm×31 μm devices with the baseline configuration with T0 increased from 140 K for the present design to 250 K.

Conceptual design of a 500 watt solar AMTEC space power system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ivanenok, J.F. III; Sievers, R.K.; Harty, R.B.

1995-12-31

Numerous design studies have been completed on Radioisotope powered Alkali Metal Thermal to Electric Converter (RAMTEC) power systems demonstrating their substantial increase in performance. Prior to recent advances in AMTEC technology and Thermal Energy Storage (TES), coupling AMTEC converters with a solar concentrator did not increase the performance of solar powered space power systems. This paper describes a conceptual design of an innovative, low cost, reliable, low mass, long life 500 watt Solar AMTEC (SAMTEC) power system, and the predicted system performance. The concept uses innovative, high voltage AMTEC cells, each containing 7 to 9 small electrolyte tubes, integrated withmore » an individual TES unit. These multi-tube AMTEC cells are identical to the AMTEC cells designed for radioisotope powered systems. The TES used in this conceptual design is the LiF-22%CaF{sub 2} unit currently being developed at NASA Lewis Research Center (LeRC) for the Solar Dynamic Ground Test Demonstration (SDGTD) Program. The system was designed to provide 500 watts of electrical power at 28 volts to a payload in Low Earth Orbit (LEO, 800 km, 28.5{degree} inclination) for a minimum lifetime of 5 years. The SAMTEC power system is predicted to have a specific power k of 5.3 to 8.9 W(e)/kg (including the concentrator, receiver, AMTEC cells, gimbals and drives, structure, power processing and control, and a 30% mass contingency) at the 500 watt power level, and 12 to 17 W(e)/kg at the 5,000 watt power level. The SAMTEC system, including all of the components listed above, is anticipated to cost $1,000/W(e) once development is complete and production begins. The SAMTEC system provides 92% of its Beginning of Life (BOL) power after a 5 year period in LEO, and SAMTEC systems should provide 10 to 15 years of life in LEO. Current AMTEC cells have demonstrated 18% efficiency in the laboratory and have been heated radiatively, with propane flames and electrical resistance heaters.« less

Body size, performance and fitness in galapagos marine iguanas.

PubMed

Wikelski, Martin; Romero, L Michael

2003-07-01

Complex organismal traits such as body size are influenced by innumerable selective pressures, making the prediction of evolutionary trajectories for those traits difficult. A potentially powerful way to predict fitness in natural systems is to study the composite response of individuals in terms of performance measures, such as foraging or reproductive performance. Once key performance measures are identified in this top-down approach, we can determine the underlying physiological mechanisms and gain predictive power over long-term evolutionary processes. Here we use marine iguanas as a model system where body size differs by more than one order of magnitude between island populations. We identified foraging efficiency as the main performance measure that constrains body size. Mechanistically, foraging performance is determined by food pasture height and the thermal environment, influencing intake and digestion. Stress hormones may be a flexible way of influencing an individual's response to low-food situations that may be caused by high population density, famines, or anthropogenic disturbances like oil spills. Reproductive performance, on the other hand, increases with body size and is mediated by higher survival of larger hatchlings from larger females and increased mating success of larger males. Reproductive performance of males may be adjusted via plastic hormonal feedback mechanisms that allow individuals to assess their social rank annually within the current population size structure. When integrated, these data suggest that reproductive performance favors increased body size (influenced by reproductive hormones), with an overall limit imposed by foraging performance (influenced by stress hormones). Based on our mechanistic understanding of individual performances we predicted an evolutionary increase in maximum body size caused by global warming trends. We support this prediction using specimens collected during 1905. We also show in a common-garden experiment that body size may have a genetic component in iguanids. This 'performance paradigm' allows predictions about adaptive evolution in natural populations.

Silicon device performance measurements to support temperature range enhancement

NASA Technical Reports Server (NTRS)

Bromstead, James; Weir, Bennett; Nelms, R. Mark; Johnson, R. Wayne; Askew, Ray

1994-01-01

Silicon based power devices can be used at 200 C. The device measurements made during this program show a predictable shift in device parameters with increasing temperature. No catastrophic or abrupt changes occurred in the parameters over the temperature range. As expected, the most dramatic change was the increase in leakage currents with increasing temperature. At 200 C the leakage current was in the milliAmp range but was still several orders of magnitude lower than the on-state current capabilities of the devices under test. This increase must be considered in the design of circuits using power transistors at elevated temperature. Three circuit topologies have been prototyped using MOSFET's and IGBT's. The circuits were designed using zero current or zero voltage switching techniques to eliminate or minimize hard switching of the power transistors. These circuits have functioned properly over the temperature range. One thousand hour life data have been collected for two power supplies with no failures and no significant change in operating efficiency. While additional reliability testing should be conducted, the feasibility of designing soft switched circuits for operation at 200 C has been successfully demonstrated.

The aerodynamic cost of flight in the short-tailed fruit bat (Carollia perspicillata): comparing theory with measurement

PubMed Central

von Busse, Rhea; Waldman, Rye M.; Swartz, Sharon M.; Voigt, Christian C.; Breuer, Kenneth S.

2014-01-01

Aerodynamic theory has long been used to predict the power required for animal flight, but widely used models contain many simplifications. It has been difficult to ascertain how closely biological reality matches model predictions, largely because of the technical challenges of accurately measuring the power expended when an animal flies. We designed a study to measure flight speed-dependent aerodynamic power directly from the kinetic energy contained in the wake of bats flying in a wind tunnel. We compared these measurements with two theoretical predictions that have been used for several decades in diverse fields of vertebrate biology and to metabolic measurements from a previous study using the same individuals. A high-accuracy displaced laser sheet stereo particle image velocimetry experimental design measured the wake velocities in the Trefftz plane behind four bats flying over a range of speeds (3–7 m s−1). We computed the aerodynamic power contained in the wake using a novel interpolation method and compared these results with the power predicted by Pennycuick's and Rayner's models. The measured aerodynamic power falls between the two theoretical predictions, demonstrating that the models effectively predict the appropriate range of flight power, but the models do not accurately predict minimum power or maximum range speeds. Mechanical efficiency—the ratio of aerodynamic power output to metabolic power input—varied from 5.9% to 9.8% for the same individuals, changing with flight speed. PMID:24718450

Observations of single-pass ion cyclotron heating in a trans-sonic flowing plasma

NASA Astrophysics Data System (ADS)

Bering, E. A.; Díaz, F. R. Chang; Squire, J. P.; Glover, T. W.; Carter, M. D.; McCaskill, G. E.; Longmier, B. W.; Brukardt, M. S.; Chancery, W. J.; Jacobson, V. T.

2010-04-01

The VAriable Specific Impulse Magnetoplasma Rocket (VASIMR®) is a high power electric spacecraft propulsion system, capable of Isp/thrust modulation at constant power [F. R. Chang Díaz et al., Proceedings of the 39th AIAA Aerospace Sciences Meeting and Exhibit, Reno, NV, 8-11 Jan. 2001]. The VASIMR® uses a helicon discharge to generate plasma. This plasma is energized by an rf booster stage that uses left hand polarized slow mode waves launched from the high field side of the ion cyclotron resonance. In the experiments reported in this paper, the booster uses 2-4 MHz waves with up to 50 kW of power. This process is similar to the ion cyclotron heating (ICH) in tokamaks, but in the VASIMR® the ions only pass through the resonance region once. The rapid absorption of ion cyclotron waves has been predicted in recent theoretical studies. These theoretical predictions have been supported with several independent measurements in this paper. The single-pass ICH produced a substantial increase in ion velocity. Pitch angle distribution studies showed that this increase took place in the resonance region where the ion cyclotron frequency was roughly equal to the frequency on the injected rf waves. Downstream of the resonance region the perpendicular velocity boost should be converted to axial flow velocity through the conservation of the first adiabatic invariant as the magnetic field decreases in the exhaust region of the VASIMR®. This paper will review all of the single-pass ICH ion acceleration data obtained using deuterium in the first VASIMR® physics demonstrator machine, the VX-50. During these experiments, the available power to the helicon ionization stage increased from 3 to 20+ kW. The increased plasma density produced increased plasma loading of the ICH coupler. Starting with an initial demonstration of single-pass ion cyclotron acceleration, the experiments demonstrate significant improvements in coupler efficiency and in ion heating efficiency. In deuterium plasma, ≥80% efficient absorption of 20 kW of ICH input power was achieved. No clear evidence for power limiting instabilities in the exhaust beam has been observed.

Sexual Relationship Power and Depression among HIV-Infected Women in Rural Uganda

PubMed Central

Hatcher, Abigail M.; Tsai, Alexander C.; Kumbakumba, Elias; Dworkin, Shari L.; Hunt, Peter W.; Martin, Jeffrey N.; Clark, Gina; Bangsberg, David R.; Weiser, Sheri D.

2012-01-01

Background Depression is associated with increased HIV transmission risk, increased morbidity, and higher risk of HIV-related death among HIV-infected women. Low sexual relationship power also contributes to HIV risk, but there is limited understanding of how it relates to mental health among HIV-infected women. Methods Participants were 270 HIV-infected women from the Uganda AIDS Rural Treatment Outcomes study, a prospective cohort of individuals initiating antiretroviral therapy (ART) in Mbarara, Uganda. Our primary predictor was baseline sexual relationship power as measured by the Sexual Relationship Power Scale (SRPS). The primary outcome was depression severity, measured with the Hopkins Symptom Checklist (HSCL), and a secondary outcome was a functional scale for mental health status (MHS). Adjusted models controlled for socio-demographic factors, CD4 count, alcohol and tobacco use, baseline WHO stage 4 disease, social support, and duration of ART. Results The mean HSCL score was 1.34 and 23.7% of participants had HSCL scores consistent with probable depression (HSCL>1.75). Compared to participants with low SRPS scores, individuals with both moderate (coefficient b = −0.21; 95%CI, −0.36 to −0.07) and high power (b = −0.21; 95%CI, −0.36 to −0.06) reported decreased depressive symptomology. High SRPS scores halved the likelihood of women meeting criteria for probable depression (adjusted odds ratio = 0.44; 95%CI, 0.20 to 0.93). In lagged models, low SRPS predicted subsequent depression severity, but depression did not predict subsequent changes in SPRS. Results were similar for MHS, with lagged models showing SRPS predicts subsequent mental health, but not visa versa. Both Decision-Making Dominance and Relationship Control subscales of SRPS were associated with depression symptom severity. Conclusions HIV-infected women with high sexual relationship power had lower depression and higher mental health status than women with low power. Interventions to improve equity in decision-making and control within dyadic partnerships are critical to prevent HIV transmission and to optimize mental health of HIV-infected women. PMID:23300519

Value of Combining Left Atrial Diameter and Amino-terminal Pro-brain Natriuretic Peptide to the CHA2DS2-VASc Score for Predicting Stroke and Death in Patients with Sick Sinus Syndrome after Pacemaker Implantation.

PubMed

Mo, Bin-Feng; Lu, Qiu-Fen; Lu, Shang-Biao; Xie, Yu-Quan; Feng, Xiang-Fei; Li, Yi-Gang

2017-08-20

The CHA2DS2-VASc score is used clinically for stroke risk stratification in patients with atrial fibrillation (AF). We sought to investigate whether the CHA2DS2-VASc score predicts stroke and death in Chinese patients with sick sinus syndrome (SSS) after pacemaker implantation and to evaluate whether the predictive power of the CHA2DS2-VASc score could be improved by combining it with left atrial diameter (LAD) and amino-terminal pro-brain natriuretic peptide (NT-proBNP). A total of 481 consecutive patients with SSS who underwent pacemaker implantation from January 2004 to December 2014 in our department were included. The CHA2DS2-VASc scores were retrospectively calculated according to the hospital medical records before pacemaker implantation. The outcome data (stroke and death) were collected by pacemaker follow-up visits and telephonic follow-up until December 31, 2015. During 2151 person-years of follow-up, 46 patients (9.6%) suffered stroke and 52 (10.8%) died. The CHA2DS2-VASc score showed a significant association with the development of stroke (hazard ratio [HR] 1.45, 95% confidence interval [CI] 1.20-1.75, P< 0.001) and death (HR 1.45, 95% CI 1.22-1.71, P< 0.001). The combination of increased LAD and the CHA2DS2-VASc score improved the predictive power for stroke (C-stat 0.69, 95% CI 0.61-0.77 vs. C-stat 0.66, 95% CI 0.57-0.74, P= 0.013), and the combination of increased NT-proBNP and the CHA2DS2-VASc score improved the predictive power for death (C-stat 0.70, 95% CI 0.64-0.77 vs. C-stat 0.67, 95% CI 0.60--0.75, P= 0.023). CHA2DS2-VASc score is valuable for predicting stroke and death risk in patients with SSS after pacemaker implantation. The addition of LAD and NT-proBNP to the CHA2DS2-VASc score improved its predictive power for stroke and death, respectively, in this patient cohort. Future prospective studies are warranted to validate the benefit of adding LAD and NT-proBNP to the CHA2DS2-VASc score for predicting stroke and death risk in non-AF populations.

Neural mechanisms to predict subjective level of fatigue in the future: a magnetoencephalography study

PubMed Central

Ishii, Akira; Tanaka, Masaaki; Watanabe, Yasuyoshi

2016-01-01

Fatigue is a major contributor to workplace accidents, morbidity, and mortality. To prevent the disruption of homeostasis and to concurrently accomplish an assigned workload, it is essential to control the level of workload based on the subjective estimation of the level of fatigue that will be experienced in the near future. In this study, we aimed to clarify the neural mechanisms related to predicting subjective levels of fatigue that would be experienced 60 min later, using magnetoencephalography. Sixteen healthy male volunteers participated in this study. In relation to the prediction, a decrease of alpha band power in the right Brodmann’s area (BA) 40 and BA 9 at 1200 to 1350 ms and that in the right BA 9 at 1350 to 1500 ms, and a decrease of gamma band power in the right BA 10 at 1500 to 1650 ms were observed. In addition, the decreased level of alpha band power in BA 9 at 1200 to 1350 ms was positively associated with the daily level of fatigue. These findings may help increase our understanding of the neural mechanisms activated to indicate the need to take a rest based on the prediction of the subjective fatigue in the future. PMID:27112115

Increasing power generation in horizontal axis wind turbines using optimized flow control

NASA Astrophysics Data System (ADS)

Cooney, John A., Jr.

In order to effectively realize future goals for wind energy, the efficiency of wind turbines must increase beyond existing technology. One direct method for achieving increased efficiency is by improving the individual power generation characteristics of horizontal axis wind turbines. The potential for additional improvement by traditional approaches is diminishing rapidly however. As a result, a research program was undertaken to assess the potential of using distributed flow control to increase power generation. The overall objective was the development of validated aerodynamic simulations and flow control approaches to improve wind turbine power generation characteristics. BEM analysis was conducted for a general set of wind turbine models encompassing last, current, and next generation designs. This analysis indicated that rotor lift control applied in Region II of the turbine power curve would produce a notable increase in annual power generated. This was achieved by optimizing induction factors along the rotor blade for maximum power generation. In order to demonstrate this approach and other advanced concepts, the University of Notre Dame established the Laboratory for Enhanced Wind Energy Design (eWiND). This initiative includes a fully instrumented meteorological tower and two pitch-controlled wind turbines. The wind turbines are representative in their design and operation to larger multi-megawatt turbines, but of a scale that allows rotors to be easily instrumented and replaced to explore new design concepts. Baseline data detailing typical site conditions and turbine operation is presented. To realize optimized performance, lift control systems were designed and evaluated in CFD simulations coupled with shape optimization tools. These were integrated into a systematic design methodology involving BEM simulations, CFD simulations and shape optimization, and selected experimental validation. To refine and illustrate the proposed design methodology, a complete design cycle was performed for the turbine model incorporated in the wind energy lab. Enhanced power generation was obtained through passive trailing edge shaping aimed at reaching lift and lift-to-drag goals predicted to optimize performance. These targets were determined by BEM analysis to improve power generation characteristics and annual energy production (AEP) for the wind turbine. A preliminary design was validated in wind tunnel experiments on a 2D rotor section in preparation for testing in the full atmospheric environment of the eWiND Laboratory. These tests were performed for the full-scale geometry and atmospheric conditions. Upon making additional improvements to the shape optimization tools, a series of trailing edge additions were designed to optimize power generation. The trailing edge additions were predicted to increase the AEP by up to 4.2% at the White Field site. The pieces were rapid-prototyped and installed on the wind turbine in March, 2014. Field tests are ongoing.

Using Analog Ensemble to generate spatially downscaled probabilistic wind power forecasts

NASA Astrophysics Data System (ADS)

Delle Monache, L.; Shahriari, M.; Cervone, G.

2017-12-01

We use the Analog Ensemble (AnEn) method to generate probabilistic 80-m wind power forecasts. We use data from the NCEP GFS ( 28 km resolution) and NCEP NAM (12 km resolution). We use forecasts data from NAM and GFS, and analysis data from NAM which enables us to: 1) use a lower-resolution model to create higher-resolution forecasts, and 2) use a higher-resolution model to create higher-resolution forecasts. The former essentially increases computing speed and the latter increases forecast accuracy. An aggregated model of the former can be compared against the latter to measure the accuracy of the AnEn spatial downscaling. The AnEn works by taking a deterministic future forecast and comparing it with past forecasts. The model searches for the best matching estimates within the past forecasts and selects the predictand value corresponding to these past forecasts as the ensemble prediction for the future forecast. Our study is based on predicting wind speed and air density at more than 13,000 grid points in the continental US. We run the AnEn model twice: 1) estimating 80-m wind speed by using predictor variables such as temperature, pressure, geopotential height, U-component and V-component of wind, 2) estimating air density by using predictors such as temperature, pressure, and relative humidity. We use the air density values to correct the standard wind power curves for different values of air density. The standard deviation of the ensemble members (i.e. ensemble spread) will be used as the degree of difficulty to predict wind power at different locations. The value of the correlation coefficient between the ensemble spread and the forecast error determines the appropriateness of this measure. This measure is prominent for wind farm developers as building wind farms in regions with higher predictability will reduce the real-time risks of operating in the electricity markets.

Prediction of anaerobic power values from an abbreviated WAnT protocol.

PubMed

Stickley, Christopher D; Hetzler, Ronald K; Kimura, Iris F

2008-05-01

The traditional 30-second Wingate anaerobic test (WAnT) is a widely used anaerobic power assessment protocol. An abbreviated protocol has been shown to decrease the mild to severe physical discomfort often associated with the WAnT. Therefore, the purpose of this study was to determine whether a 20-second WAnT protocol could be used to accurately predict power values of a standard 30-second WAnT. In 96 college females, anaerobic power variables were assessed using a standard 30-second WAnT protocol. Maximum power values as well as instantaneous power at 10, 15, and 20 seconds were recorded. Based on these results, stepwise regression analysis was performed to determine the accuracy with which mean power, minimum power, 30-second power, and percentage of fatigue for a standard 30-second WAnT could be predicted from values obtained during the first 20 seconds of testing. Mean power values showed the highest level of predictability (R2 = 0.99) from the 20-second values. Minimum power, 30-second power, and percentage of fatigue also showed high levels of predictability (R2 = 0.91, 0.84, and 0.84, respectively) using only values obtained during the first 20 seconds of the protocol. An abbreviated (20-second) WAnT protocol appears to effectively predict results of a standard 30-second WAnT in college-age females, allowing for comparison of data to published norms. A shortened test may allow for a decrease in unwanted side effects associated with the traditional WAnT protocol.

Experimental Evaluation of a Method for Turbocharging Four-Stroke, Single Cylinder, Internal Combustion Engines

NASA Astrophysics Data System (ADS)

Buchman, Michael; Winter, Amos

2015-11-01

Turbocharging an engine increases specific power, improves fuel economy, reduces emissions, and lowers cost compared to a naturally aspirated engine of the same power output. These advantages make turbocharging commonplace for multi-cylinder engines. Single cylinder engineers are not commonly turbocharged due to the phase lag between the exhaust stroke, which powers the turbocharger, and the intake stroke, when air is pumped into the engine. Our proposed method of turbocharging single cylinder engines is to add an ``air capacitor'' to the intake manifold, an additional volume that acts as a buffer to store compressed air between the exhaust and intake strokes, and smooth out the pressure pulses from the turbocharger. This talk presents experimental results from a single cylinder, turbocharged diesel engine fit with various sized air capacitors. Power output from the engine was measured using a dynamometer made from a generator, with the electrical power dissipated with resistive heating elements. We found that intake air density increases with capacitor size as theoretically predicted, ranging from 40 to 60 percent depending on heat transfer. Our experiment was able to produce 29 percent more power compared to using natural aspiration. These results validated that an air capacitor and turbocharger may be a simple, cost effective means of increasing the power density of single cylinder engines.

Variation in aerosol nucleation and growth in coal-fired power plant plumes due to background aerosol, meteorology and emissions: sensitivity analysis and parameterization.

NASA Astrophysics Data System (ADS)

Stevens, R. G.; Lonsdale, C. L.; Brock, C. A.; Reed, M. K.; Crawford, J. H.; Holloway, J. S.; Ryerson, T. B.; Huey, L. G.; Nowak, J. B.; Pierce, J. R.

2012-04-01

New-particle formation in the plumes of coal-fired power plants and other anthropogenic sulphur sources may be an important source of particles in the atmosphere. It remains unclear, however, how best to reproduce this formation in global and regional aerosol models with grid-box lengths that are 10s of kilometres and larger. The predictive power of these models is thus limited by the resultant uncertainties in aerosol size distributions. In this presentation, we focus on sub-grid sulphate aerosol processes within coal-fired power plant plumes: the sub-grid oxidation of SO2 with condensation of H2SO4 onto newly-formed and pre-existing particles. Based on the results of the System for Atmospheric Modelling (SAM), a Large-Eddy Simulation/Cloud-Resolving Model (LES/CRM) with online TwO Moment Aerosol Sectional (TOMAS) microphysics, we develop a computationally efficient, but physically based, parameterization that predicts the characteristics of aerosol formed within coal-fired power plant plumes based on parameters commonly available in global and regional-scale models. Given large-scale mean meteorological parameters, emissions from the power plant, mean background condensation sink, and the desired distance from the source, the parameterization will predict the fraction of the emitted SO2 that is oxidized to H2SO4, the fraction of that H2SO4 that forms new particles instead of condensing onto preexisting particles, the median diameter of the newly-formed particles, and the number of newly-formed particles per kilogram SO2 emitted. We perform a sensitivity analysis of these characteristics of the aerosol size distribution to the meteorological parameters, the condensation sink, and the emissions. In general, new-particle formation and growth is greatly reduced during polluted conditions due to the large preexisting aerosol surface area for H2SO4 condensation and particle coagulation. The new-particle formation and growth rates are also a strong function of the amount of sunlight and NOx since both control OH concentrations. Decreases in NOx emissions without simultaneous decreases in SO2 emissions increase new-particle formation and growth due to increased oxidation of SO2. The parameterization we describe here should allow for more accurate predictions of aerosol size distributions and a greater confidence in the effects of aerosols in climate and health studies.

Ideal MHD Stability Prediction and Required Power for EAST Advanced Scenario

NASA Astrophysics Data System (ADS)

Chen, Junjie; Li, Guoqiang; Qian, Jinping; Liu, Zixi

2012-11-01

The Experimental Advanced Superconducting Tokamak (EAST) is the first fully superconducting tokamak with a D-shaped cross-sectional plasma presently in operation. The ideal magnetohydrodynamic (MHD) stability and required power for the EAST advanced tokamak (AT) scenario with negative central shear and double transport barrier (DTB) are investigated. With the equilibrium code TOQ and stability code GATO, the ideal MHD stability is analyzed. It is shown that a moderate ratio of edge transport barriers' (ETB) height to internal transport barriers' (ITBs) height is beneficial to ideal MHD stability. The normalized beta βN limit is about 2.20 (without wall) and 3.70 (with ideal wall). With the scaling law of energy confinement time, the required heating power for EAST AT scenario is calculated. The total heating power Pt increases as the toroidal magnetic field BT or the normalized beta βN is increased.

Improved Weather and Power Forecasts for Energy Operations - the German Research Project EWeLiNE

NASA Astrophysics Data System (ADS)

Lundgren, Kristina; Siefert, Malte; Hagedorn, Renate; Majewski, Detlev

2014-05-01

The German energy system is going through a fundamental change. Based on the energy plans of the German federal government, the share of electrical power production from renewables should increase to 35% by 2020. This means that, in the near future at certain times renewable energies will provide a major part of Germany's power production. Operating a power supply system with a large share of weather-dependent power sources in a secure way requires improved power forecasts. One of the most promising strategies to improve the existing wind power and PV power forecasts is to optimize the underlying weather forecasts and to enhance the collaboration between the meteorology and energy sectors. Deutscher Wetterdienst addresses these challenges in collaboration with Fraunhofer IWES within the research project EWeLiNE. The overarching goal of the project is to improve the wind and PV power forecasts by combining improved power forecast models and optimized weather forecasts. During the project, the numerical weather prediction models COSMO-DE and COSMO-DE-EPS (Ensemble Prediction System) by Deutscher Wetterdienst will be generally optimized towards improved wind power and PV forecasts. For instance, it will be investigated whether the assimilation of new types of data, e.g. power production data, can lead to improved weather forecasts. With regard to the probabilistic forecasts, the focus is on the generation of ensembles and ensemble calibration. One important aspect of the project is to integrate the probabilistic information into decision making processes by developing user-specified products. In this paper we give an overview of the project and present first results.

Exploring the Effects of Low Power Schemas in Mothers.

ERIC Educational Resources Information Center

Mills, Rosemary S. L.

1999-01-01

Assessed whether low perceived maternal power and temperamentally fearful preschool-aged daughters predicted subsequent maternal overcontrol and internalizing symptoms in daughters 2 years later. Found that low perceived maternal power predicted subsequent maternal overcontrol with initially fearful daughters but did not predict subsequent…

Accelerated Aging with Electrical Overstress and Prognostics for Power MOSFETs

NASA Technical Reports Server (NTRS)

Saha, Sankalita; Celaya, Jose Ramon; Vashchenko, Vladislav; Mahiuddin, Shompa; Goebel, Kai F.

2011-01-01

Power electronics play an increasingly important role in energy applications as part of their power converter circuits. Understanding the behavior of these devices, especially their failure modes as they age with nominal usage or sudden fault development is critical in ensuring efficiency. In this paper, a prognostics based health management of power MOSFETs undergoing accelerated aging through electrical overstress at the gate area is presented. Details of the accelerated aging methodology, modeling of the degradation process of the device and prognostics algorithm for prediction of the future state of health of the device are presented. Experiments with multiple devices demonstrate the performance of the model and the prognostics algorithm as well as the scope of application. Index Terms Power MOSFET, accelerated aging, prognostics

Experimental Challenges to Stiffness as a Transport Paradigm

NASA Astrophysics Data System (ADS)

Luce, T. C.

2017-10-01

Transport in plasmas is treated experimentally as a relationship between gradients and fluxes in analogy to the random-walk problem. Gyrokinetic models often predict strong increases in local flux for small increases in local gradient when above a threshold, holding all other parameters fixed. This has been named `stiffness'. The radial scalelength is then expected to vary little with source strength as a result of high stiffness. To probe the role of ExB shearing on stiffness in the DIII-D tokamak, two neutral beam injection power scans in H-mode plasmas were specially crafted-one with constant, low torque and one with increasing torque. The ion heat, electron heat, and ion toroidal momentum transport do not show expected signatures of stiffness, while the ion particle transport does. The ion heat transport shows the clearest discrepancy; the normalized heat flux drops with increasing inverse ion temperature scalelength. ExB shearing affects the transport magnitude, but not the scalelength dependence. Linear gyrofluid (TGLF) and nonlinear gyrokinetic (GYRO) predictions show stiff ion heat transport around the experimental profiles. The ion temperature gradient required to match the ion heat flux with increasing auxiliary power is not correctly described by TGLF, even when parameters are varied within the experimental uncertainties. TGLF also underpredicts transport at smaller radii, but overpredicts transport at larger radii. Independent of the theory/experiment comparison, it is not clear that the theoretical definition of stiffness yields any prediction about parameter scans such as the power scans here, because the quantities that must be held fixed to quantify stiffness are varied. A survey of recent literature indicated that profile resilience is routinely attributed to stiffness, but simple model calculations show profile resilience does not imply stiffness. Taken together, these observations challenge the use of local stiffness as a paradigm for explaining global transport behavior. Work supported by US DOE under DE-FC02-04ER54698.

Hydrodynamic effects of kinetic power extraction by in-stream tidal turbines

NASA Astrophysics Data System (ADS)

Polagye, Brian L.

The hydrodynamic effects of extracting kinetic power from tidal streams presents unique challenges to the development of in-stream tidal power. In-stream tidal turbines superficially resemble wind turbines and extract kinetic power from the ebb and flood of strong tidal currents. Extraction increases the resistance to flow, leading to changes in tidal range, transport, mixing, and the kinetic resource itself. These far-field changes have environmental, social, and economic implications that must be understood to develop the in-stream resource. This dissertation describes the development of a one-dimensional numerical channel model and its application to the study of these effects. The model is applied to determine the roles played by site geometry, network topology, tidal regime, and device dynamics. A comparison is also made between theoretical and modeled predictions for the maximum amount of power which could be extracted from a tidal energy site. The model is extended to a simulation of kinetic power extraction from Puget Sound, Washington. In general, extracting tidal energy will have a number of far-field effects, in proportion to the level of power extraction. At the theoretical limit, these effects can be very significant (e.g., 50% reduction in transport), but are predicted to be immeasurably small for pilot-scale projects. Depending on the specifics of the site, far-field effects may either augment or reduce the existing tidal regime. Changes to the tide, in particular, have significant spatial variability. Since tidal streams are generally subcritical, effects are felt throughout the estuary, not just at the site of extraction. The one dimensional numerical modeling is supported by a robust theory for predicting the performance characteristics of in-stream devices. The far-field effects of tidal power depend on the total power dissipated by turbines, rather than the power extracted. When the low-speed wake downstream of a turbine mixes with the free-stream, power is lost, such that the total power dissipated by the turbine is significantly greater than the power extracted. This dissertation concludes with a framework for three-dimensional numerical modeling of near-field extraction effects.

Increased exposure to pollutant aerosols under high voltage power lines.

PubMed

Fews, A P; Henshaw, D L; Keitch, P A; Close, J J; Wilding, R J

1999-12-01

To assess increased exposure to airborne pollutants near power lines by investigating theoretically and experimentally the behaviour of 222Rn decay product marker aerosols in the 50 Hz electric field under power lines. The behaviour of aerosols in outdoor air including those carrying 222Rn decay products was modelled theoretically in the presence of an AC field. TASTRAK alpha-particle spectroscopy was used to characterize 218Po and 214Po aerosols outdoors. Sampling points were chosen along a line at right angles up to 200 m from a number of high voltage power (transmission) lines. Each sampling point comprised an arrangement of mutually orthogonal TASTRAK detectors. Exposures were carried out at different power line locations in various weather conditions. The model predicts a two- to three-fold increase in deposition of aerosols on spherical surfaces mimicking the human head under high voltage power lines. Experimental measurements using detectors mounted on grounded metal spheres showed an enhanced deposition of both 218Po and 214Po aerosols. Enhanced 218Po deposition on 400 kV lines ranged from 1.96+/-0.15 to 2.86+/-0.32. Enhanced 214Po deposition on 275 kV and 132 kV lines were 1.43+/-0.07 and 1.11+/-0.21, respectively, where the latter value was not significant. The observations demonstrate a mode of increased exposure to pollutant aerosols under high voltage power lines by increased deposition on the body. The total (indoor + outdoor) 218Po and 214Po dose to the basal layer of facial skin is estimated to be increased by between 1.2 and 2.0 for 10% of time spent outdoors under high voltage power lines.

Wind Turbine Wakes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kelley, Christopher Lee; Maniaci, David Charles; Resor, Brian R.

2015-10-01

The total energy produced by a wind farm depends on the complex interaction of many wind turbines operating in proximity with the turbulent atmosphere. Sometimes, the unsteady forces associated with wind negatively influence power production, causing damage and increasing the cost of producing energy associated with wind power. Wakes and the motion of air generated by rotating blades need to be better understood. Predicting wakes and other wind forces could lead to more effective wind turbine designs and farm layouts, thereby reducing the cost of energy, allowing the United States to increase the installed capacity of wind energy. The Windmore » Energy Technologies Department at Sandia has collaborated with the University of Minnesota to simulate the interaction of multiple wind turbines. By combining the validated, large-eddy simulation code with Sandia’s HPC capability, this consortium has improved its ability to predict unsteady forces and the electrical power generated by an array of wind turbines. The array of wind turbines simulated were specifically those at the Sandia Scaled Wind Farm Testbed (SWiFT) site which aided the design of new wind turbine blades being manufactured as part of the National Rotor Testbed project with the Department of Energy.« less

Model predictive direct power control for active power decoupled single-phase quasi- Z -source inverter

DOE PAGES

Liu, Yushan; Ge, Baoming; Abu-Rub, Haitham; ...

2016-06-14

In this study, the active power filter (APF) that consists of a half-bridge leg and an ac capacitor is integrated in the single-phase quasi-Z-source inverter (qZSI) in this paper to avoid the second harmonic power flowing into the dc side. The capacitor of APF buffers the second harmonic power of the load, and the ac capacitor allows highly pulsating ac voltage, so that the capacitances of both dc and ac sides can be small. A model predictive direct power control (DPC) is further proposed to achieve the purpose of this newtopology through predicting the capacitor voltage of APF at eachmore » sampling period and ensuring the APF power to track the second harmonic power of single-phase qZSI. Simulation and experimental results verify the model predictive DPC for the APF-integrated single-phase qZSI.« less

Potentiality Prediction of Electric Power Replacement Based on Power Market Development Strategy

NASA Astrophysics Data System (ADS)

Miao, Bo; Yang, Shuo; Liu, Qiang; Lin, Jingyi; Zhao, Le; Liu, Chang; Li, Bin

2017-05-01

The application of electric power replacement plays an important role in promoting the development of energy conservation and emission reduction in our country. To exploit the potentiality of regional electric power replacement, the regional GDP (gross domestic product) and energy consumption are taken as potentiality evaluation indicators. The principal component factors are extracted with PCA (principal component analysis), and the integral potentiality analysis is made to the potentiality of electric power replacement in the national various regions; a region is taken as a research object, and the potentiality of electric power replacement is defined and quantified. The analytical model for the potentiality of multi-scenario electric power replacement is developed, and prediction is made to the energy consumption with the grey prediction model. The relevant theoretical research is utilized to realize prediction analysis on the potentiality amount of multi-scenario electric power replacement.

Model predictive direct power control for active power decoupled single-phase quasi- Z -source inverter

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Yushan; Ge, Baoming; Abu-Rub, Haitham

In this study, the active power filter (APF) that consists of a half-bridge leg and an ac capacitor is integrated in the single-phase quasi-Z-source inverter (qZSI) in this paper to avoid the second harmonic power flowing into the dc side. The capacitor of APF buffers the second harmonic power of the load, and the ac capacitor allows highly pulsating ac voltage, so that the capacitances of both dc and ac sides can be small. A model predictive direct power control (DPC) is further proposed to achieve the purpose of this newtopology through predicting the capacitor voltage of APF at eachmore » sampling period and ensuring the APF power to track the second harmonic power of single-phase qZSI. Simulation and experimental results verify the model predictive DPC for the APF-integrated single-phase qZSI.« less

Bayesian predictive power: choice of prior and some recommendations for its use as probability of success in drug development.

PubMed

Rufibach, Kaspar; Burger, Hans Ulrich; Abt, Markus

2016-09-01

Bayesian predictive power, the expectation of the power function with respect to a prior distribution for the true underlying effect size, is routinely used in drug development to quantify the probability of success of a clinical trial. Choosing the prior is crucial for the properties and interpretability of Bayesian predictive power. We review recommendations on the choice of prior for Bayesian predictive power and explore its features as a function of the prior. The density of power values induced by a given prior is derived analytically and its shape characterized. We find that for a typical clinical trial scenario, this density has a u-shape very similar, but not equal, to a β-distribution. Alternative priors are discussed, and practical recommendations to assess the sensitivity of Bayesian predictive power to its input parameters are provided. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Correlation between use time of machine and decline curve for emerging enterprise information systems

NASA Astrophysics Data System (ADS)

Chang, Yao-Chung; Lai, Chin-Feng; Chuang, Chi-Cheng; Hou, Cheng-Yu

2018-04-01

With the progress of science and technology, more and more machines are adpot to help human life better and more convenient. When the machines have been used for a longer period of time so that the machine components are getting old, the amount of power comsumption will increase and easily cause the machine to overheat. This also causes a waste of invisible resources. If the Internet of Everything (IoE) technologies are able to be applied into the enterprise information systems for monitoring the machines use time, it can not only make energy can be effectively used, but aslo create a safer living environment. To solve the above problem, the correlation predict model is established to collect the data of power consumption converted into power eigenvalues. This study takes the power eigenvalue as the independent variable and use time as the dependent variable in order to establish the decline curve. Ultimately, the scoring and estimation modules are employed to seek the best power eigenvalue as the independent variable. To predict use time, the correlation is discussed between the use time and the decline curve to improve the entire behavioural analysis of the facilitate recognition of the use time of machines.

The relationship between blood pressure and the structures of Pender's health promotion model in rural hypertensive patients.

PubMed

Kamran, Aziz; Azadbakht, Leila; Sharifirad, Gholamreza; Mahaki, Behzad; Mohebi, Siamak

2015-01-01

Perception is the most important predictor of behavior and there is a strong relation and correlation between behavior and believes. Thus, to improve self-care behaviors of patients, it is required to fully understand their perceptions about behavior. This paper aimed to assess the prediction power of health promotion model of systolic blood pressure (SBP) as the result of self-care behavior in rural hypertensive. This cross-sectional study has been carried out through random multistage sampling on 671 rural patients under the coverage of health center of Ardebil city in 2013. Data were collected through reliable and valid questionnaire based on the health promotion model in eight sectors. For data analysis, Pearson correlation statistical tests, multivariate linear regression, ANOVA and independent t-test were used and for confirmatory factor analysis, SPSS 18 and AMOS 18 (SPSS Inc., Chicago, IL, USA) were used. The results showed significant negative correlation between self-efficacy, perceived benefits, situational influences, affects related to behavior and commitment to action structures with SBP and showed a positive significant correlation between perceived barriers and SBP. Furthermore, age and body mass had direct significant relation with SBP. The age of patients showed inverse significant correlation with self-efficacy, perceived benefits, affects related to behavior, interpersonal influences and commitment and showed a direct significant correlation with perceived barriers, means that by increase of age, the perceived barriers also increased. The structures of health promotion model have in overall the prediction power of 71.4% of SBP changes. The diet perceptions of patients, the same as health promotion model, has good predictive power of SBP, especially the structures of perceived benefits and self-efficacy have inverse meaningful relation with systole blood pressure and predicted a higher percentage of this variable.

An on-time power-aware scheduling scheme for medical sensor SoC-based WBAN systems.

PubMed

Hwang, Tae-Ho; Kim, Dong-Sun; Kim, Jung-Guk

2012-12-27

The focus of many leading technologies in the field of medical sensor systems is on low power consumption and robust data transmission. For example, the implantable cardioverter-defibrillator (ICD), which is used to maintain the heart in a healthy state, requires a reliable wireless communication scheme with an extremely low duty-cycle, high bit rate, and energy-efficient media access protocols. Because such devices must be sustained for over 5 years without access to battery replacement, they must be designed to have extremely low power consumption in sleep mode. Here, an on-time, energy-efficient scheduling scheme is proposed that performs power adjustments to minimize the sleep-mode current. The novelty of this scheduler is that it increases the determinacy of power adjustment and the predictability of scheduling by employing non-pre-emptible dual priority scheduling. This predictable scheduling also guarantees the punctuality of important periodic tasks based on their serialization, by using their worst case execution time) and the power consumption optimization. The scheduler was embedded into a system on chip (SoC) developed to support the wireless body area network-a wakeup-radio and wakeup-timer for implantable medical devices. This scheduling system is validated by the experimental results of its performance when used with life-time extensions of ICD devices.

An On-Time Power-Aware Scheduling Scheme for Medical Sensor SoC-Based WBAN Systems

PubMed Central

Hwang, Tae-Ho; Kim, Dong-Sun; Kim, Jung-Guk

2013-01-01

The focus of many leading technologies in the field of medical sensor systems is on low power consumption and robust data transmission. For example, the implantable cardioverter-defibrillator (ICD), which is used to maintain the heart in a healthy state, requires a reliable wireless communication scheme with an extremely low duty-cycle, high bit rate, and energy-efficient media access protocols. Because such devices must be sustained for over 5 years without access to battery replacement, they must be designed to have extremely low power consumption in sleep mode. Here, an on-time, energy-efficient scheduling scheme is proposed that performs power adjustments to minimize the sleep-mode current. The novelty of this scheduler is that it increases the determinacy of power adjustment and the predictability of scheduling by employing non-pre-emptible dual priority scheduling. This predictable scheduling also guarantees the punctuality of important periodic tasks based on their serialization, by using their worst case execution time) and the power consumption optimization. The scheduler was embedded into a system on chip (SoC) developed to support the wireless body area network—a wakeup-radio and wakeup-timer for implantable medical devices. This scheduling system is validated by the experimental results of its performance when used with life-time extensions of ICD devices. PMID:23271602

Power maximization of a point absorber wave energy converter using improved model predictive control

NASA Astrophysics Data System (ADS)

Milani, Farideh; Moghaddam, Reihaneh Kardehi

2017-08-01

This paper considers controlling and maximizing the absorbed power of wave energy converters for irregular waves. With respect to physical constraints of the system, a model predictive control is applied. Irregular waves' behavior is predicted by Kalman filter method. Owing to the great influence of controller parameters on the absorbed power, these parameters are optimized by imperialist competitive algorithm. The results illustrate the method's efficiency in maximizing the extracted power in the presence of unknown excitation force which should be predicted by Kalman filter.

Power technologies and the space future

NASA Technical Reports Server (NTRS)

Faymon, Karl A.; Fordyce, J. Stuart; Brandhorst, Henry W., Jr.

1991-01-01

Advancements in space power and energy technologies are critical to serve space development needs and help solve problems on Earth. The availability of low cost power and energy in space will be the hallmark of this advance. Space power will undergo a dramatic change for future space missions. The power systems which have served the U.S. space program so well in the past will not suffice for the missions of the future. This is especially true if the space commercialization is to become a reality. New technologies, and new and different space power architectures and topologies will replace the lower power, low-voltage systems of the past. Efficiencies will be markedly improved, specific powers will be greatly increased, and system lifetimes will be markedly extended. Space power technology is discussed - its past, its current status, and predictions about where it will go in the future. A key problem for power and energy is its cost of affordability. Power must be affordable or it will not serve future needs adequately. This aspect is also specifically addressed.

Powerful Voter Selection for Making Multistep Delegate Ballot Fair

NASA Astrophysics Data System (ADS)

Yamakawa, Hiroshi

For decision by majority, each voter often exercises his right by delegating to trustable other voters. Multi-step delegates rule allows indirect delegating through more than one voter, and this helps each voter finding his delegate voters. In this paper, we propose powerful voter selection method depending on the multi-step delegate rule. This method sequentially selects voters who is most delegated indirectly. Multi-agent simulation demonstrate that we can achieve highly fair poll results from small number of vote by using proposed method. Here, fairness is prediction accuracy to sum of all voters preferences for choices. In simulation, each voter selects choices arranged on one dimensional preference axis for voting. Acquaintance relationships among voters were generated as a random network, and each voter delegates some of his acquaintances who has similar preferences. We obtained simulation results from various acquaintance networks, and then averaged these results. Firstly, if each voter has enough acquaintances in average, proposed method can help predicting sum of all voters' preferences of choices from small number of vote. Secondly, if the number of each voter's acquaintances increases corresponding to an increase in the number of voters, prediction accuracy (fairness) from small number of vote can be kept in appropriate level.

Zinc Bromide Flow Battery Installation for Islanding and Backup Power

DTIC Science & Technology

2017-08-09

predictably is in place. The ability to control generation has become more difficult with the increase of RE systems such as solar PV and wind turbines ...Both PV and wind systems generate power based on unpredictable cycles of nature. At very low levels of RE penetration the grid can be balanced by...Page Intentionally Left Blank 15 5.0 TEST DESIGN This goal of this demonstration was to solve two main problems . The first

A mathematical model of the maximum power density attainable in an alkaline hydrogen/oxygen fuel cell

NASA Technical Reports Server (NTRS)

Kimble, Michael C.; White, Ralph E.

1991-01-01

A mathematical model of a hydrogen/oxygen alkaline fuel cell is presented that can be used to predict the polarization behavior under various power loads. The major limitations to achieving high power densities are indicated and methods to increase the maximum attainable power density are suggested. The alkaline fuel cell model describes the phenomena occurring in the solid, liquid, and gaseous phases of the anode, separator, and cathode regions based on porous electrode theory applied to three phases. Fundamental equations of chemical engineering that describe conservation of mass and charge, species transport, and kinetic phenomena are used to develop the model by treating all phases as a homogeneous continuum.

Applying Precision Medicine to Trial Design Using Physiology. Extracorporeal CO2 Removal for Acute Respiratory Distress Syndrome.

PubMed

Goligher, Ewan C; Amato, Marcelo B P; Slutsky, Arthur S

2017-09-01

In clinical trials of therapies for acute respiratory distress syndrome (ARDS), the average treatment effect in the study population may be attenuated because individual patient responses vary widely. This inflates sample size requirements and increases the cost and difficulty of conducting successful clinical trials. One solution is to enrich the study population with patients most likely to benefit, based on predicted patient response to treatment (predictive enrichment). In this perspective, we apply the precision medicine paradigm to the emerging use of extracorporeal CO 2 removal (ECCO 2 R) for ultraprotective ventilation in ARDS. ECCO 2 R enables reductions in tidal volume and driving pressure, key determinants of ventilator-induced lung injury. Using basic physiological concepts, we demonstrate that dead space and static compliance determine the effect of ECCO 2 R on driving pressure and mechanical power. This framework might enable prediction of individual treatment responses to ECCO 2 R. Enriching clinical trials by selectively enrolling patients with a significant predicted treatment response can increase treatment effect size and statistical power more efficiently than conventional enrichment strategies that restrict enrollment according to the baseline risk of death. To support this claim, we simulated the predicted effect of ECCO 2 R on driving pressure and mortality in a preexisting cohort of patients with ARDS. Our computations suggest that restricting enrollment to patients in whom ECCO 2 R allows driving pressure to be decreased by 5 cm H 2 O or more can reduce sample size requirement by more than 50% without increasing the total number of patients to be screened. We discuss potential implications for trial design based on this framework.

Hearing and seeing meaning in noise: Alpha, beta, and gamma oscillations predict gestural enhancement of degraded speech comprehension.

PubMed

Drijvers, Linda; Özyürek, Asli; Jensen, Ole

2018-05-01

During face-to-face communication, listeners integrate speech with gestures. The semantic information conveyed by iconic gestures (e.g., a drinking gesture) can aid speech comprehension in adverse listening conditions. In this magnetoencephalography (MEG) study, we investigated the spatiotemporal neural oscillatory activity associated with gestural enhancement of degraded speech comprehension. Participants watched videos of an actress uttering clear or degraded speech, accompanied by a gesture or not and completed a cued-recall task after watching every video. When gestures semantically disambiguated degraded speech comprehension, an alpha and beta power suppression and a gamma power increase revealed engagement and active processing in the hand-area of the motor cortex, the extended language network (LIFG/pSTS/STG/MTG), medial temporal lobe, and occipital regions. These observed low- and high-frequency oscillatory modulations in these areas support general unification, integration and lexical access processes during online language comprehension, and simulation of and increased visual attention to manual gestures over time. All individual oscillatory power modulations associated with gestural enhancement of degraded speech comprehension predicted a listener's correct disambiguation of the degraded verb after watching the videos. Our results thus go beyond the previously proposed role of oscillatory dynamics in unimodal degraded speech comprehension and provide first evidence for the role of low- and high-frequency oscillations in predicting the integration of auditory and visual information at a semantic level. © 2018 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Hearing and seeing meaning in noise: Alpha, beta, and gamma oscillations predict gestural enhancement of degraded speech comprehension

PubMed Central

Özyürek, Asli; Jensen, Ole

2018-01-01

Abstract During face‐to‐face communication, listeners integrate speech with gestures. The semantic information conveyed by iconic gestures (e.g., a drinking gesture) can aid speech comprehension in adverse listening conditions. In this magnetoencephalography (MEG) study, we investigated the spatiotemporal neural oscillatory activity associated with gestural enhancement of degraded speech comprehension. Participants watched videos of an actress uttering clear or degraded speech, accompanied by a gesture or not and completed a cued‐recall task after watching every video. When gestures semantically disambiguated degraded speech comprehension, an alpha and beta power suppression and a gamma power increase revealed engagement and active processing in the hand‐area of the motor cortex, the extended language network (LIFG/pSTS/STG/MTG), medial temporal lobe, and occipital regions. These observed low‐ and high‐frequency oscillatory modulations in these areas support general unification, integration and lexical access processes during online language comprehension, and simulation of and increased visual attention to manual gestures over time. All individual oscillatory power modulations associated with gestural enhancement of degraded speech comprehension predicted a listener's correct disambiguation of the degraded verb after watching the videos. Our results thus go beyond the previously proposed role of oscillatory dynamics in unimodal degraded speech comprehension and provide first evidence for the role of low‐ and high‐frequency oscillations in predicting the integration of auditory and visual information at a semantic level. PMID:29380945

Geometry characteristics modeling and process optimization in coaxial laser inside wire cladding

NASA Astrophysics Data System (ADS)

Shi, Jianjun; Zhu, Ping; Fu, Geyan; Shi, Shihong

2018-05-01

Coaxial laser inside wire cladding method is very promising as it has a very high efficiency and a consistent interaction between the laser and wire. In this paper, the energy and mass conservation law, and the regression algorithm are used together for establishing the mathematical models to study the relationship between the layer geometry characteristics (width, height and cross section area) and process parameters (laser power, scanning velocity and wire feeding speed). At the selected parameter ranges, the predicted values from the models are compared with the experimental measured results, and there is minor error existing, but they reflect the same regularity. From the models, it is seen the width of the cladding layer is proportional to both the laser power and wire feeding speed, while it firstly increases and then decreases with the increasing of the scanning velocity. The height of the cladding layer is proportional to the scanning velocity and feeding speed and inversely proportional to the laser power. The cross section area increases with the increasing of feeding speed and decreasing of scanning velocity. By using the mathematical models, the geometry characteristics of the cladding layer can be predicted by the known process parameters. Conversely, the process parameters can be calculated by the targeted geometry characteristics. The models are also suitable for multi-layer forming process. By using the optimized process parameters calculated from the models, a 45 mm-high thin-wall part is formed with smooth side surfaces.

Comparison of the economic impact of different wind power forecast systems for producers

NASA Astrophysics Data System (ADS)

Alessandrini, S.; Davò, F.; Sperati, S.; Benini, M.; Delle Monache, L.

2014-05-01

Deterministic forecasts of wind production for the next 72 h at a single wind farm or at the regional level are among the main end-users requirement. However, for an optimal management of wind power production and distribution it is important to provide, together with a deterministic prediction, a probabilistic one. A deterministic forecast consists of a single value for each time in the future for the variable to be predicted, while probabilistic forecasting informs on probabilities for potential future events. This means providing information about uncertainty (i.e. a forecast of the PDF of power) in addition to the commonly provided single-valued power prediction. A significant probabilistic application is related to the trading of energy in day-ahead electricity markets. It has been shown that, when trading future wind energy production, using probabilistic wind power predictions can lead to higher benefits than those obtained by using deterministic forecasts alone. In fact, by using probabilistic forecasting it is possible to solve economic model equations trying to optimize the revenue for the producer depending, for example, on the specific penalties for forecast errors valid in that market. In this work we have applied a probabilistic wind power forecast systems based on the "analog ensemble" method for bidding wind energy during the day-ahead market in the case of a wind farm located in Italy. The actual hourly income for the plant is computed considering the actual selling energy prices and penalties proportional to the unbalancing, defined as the difference between the day-ahead offered energy and the actual production. The economic benefit of using a probabilistic approach for the day-ahead energy bidding are evaluated, resulting in an increase of 23% of the annual income for a wind farm owner in the case of knowing "a priori" the future energy prices. The uncertainty on price forecasting partly reduces the economic benefit gained by using a probabilistic energy forecast system.

A fundamental model of quasi-static wheelchair biomechanics.

PubMed

Leary, M; Gruijters, J; Mazur, M; Subic, A; Burton, M; Fuss, F K

2012-11-01

The performance of a wheelchair system is a function of user anatomy, including arm segment lengths and muscle parameters, and wheelchair geometry, in particular, seat position relative to the wheel hub. To quantify performance, researchers have proposed a number of predictive models. In particular, the model proposed by Richter is extremely useful for providing initial analysis as it is simple to apply and provides insight into the peak and transient joint torques required to achieve a given angular velocity. The work presented in this paper identifies and corrects a critical error; specifically that the Richter model incorrectly predicts that shoulder torque is due to an anteflexing muscle moment. This identified error was confirmed analytically, graphically and numerically. The authors have developed a corrected, fundamental model which identifies that the shoulder anteflexes only in the first half of the push phase and retroflexes in the second half. The fundamental model has been extended by the authors to obtain novel data on joint and net power as a function of push progress. These outcomes indicate that shoulder power is positive in the first half of the push phase (concentrically contracting anteflexors) and negative in the second half (eccentrically contracting retroflexors). As the eccentric contraction introduces adverse negative power, these considerations are essential when optimising wheelchair design in terms of the user's musculoskeletal system. The proposed fundamental model was applied to assess the effect of vertical seat position on joint torques and power. Increasing the seat height increases the peak positive (concentric) shoulder and elbow torques while reducing the associated (eccentric) peak negative torque. Furthermore, the transition from positive to negative shoulder torque (as well as from positive to negative power) occurs later in the push phase with increasing seat height. These outcomes will aid in the optimisation of manual wheelchair propulsion biomechanics by minimising adverse negative muscle power, and allow joint torques to be manipulated as required to minimise injury or aid in rehabilitation. Copyright © 2012. Published by Elsevier Ltd.

Multiple Kernel Learning with Random Effects for Predicting Longitudinal Outcomes and Data Integration

PubMed Central

Chen, Tianle; Zeng, Donglin

2015-01-01

Summary Predicting disease risk and progression is one of the main goals in many clinical research studies. Cohort studies on the natural history and etiology of chronic diseases span years and data are collected at multiple visits. Although kernel-based statistical learning methods are proven to be powerful for a wide range of disease prediction problems, these methods are only well studied for independent data but not for longitudinal data. It is thus important to develop time-sensitive prediction rules that make use of the longitudinal nature of the data. In this paper, we develop a novel statistical learning method for longitudinal data by introducing subject-specific short-term and long-term latent effects through a designed kernel to account for within-subject correlation of longitudinal measurements. Since the presence of multiple sources of data is increasingly common, we embed our method in a multiple kernel learning framework and propose a regularized multiple kernel statistical learning with random effects to construct effective nonparametric prediction rules. Our method allows easy integration of various heterogeneous data sources and takes advantage of correlation among longitudinal measures to increase prediction power. We use different kernels for each data source taking advantage of the distinctive feature of each data modality, and then optimally combine data across modalities. We apply the developed methods to two large epidemiological studies, one on Huntington's disease and the other on Alzheimer's Disease (Alzheimer's Disease Neuroimaging Initiative, ADNI) where we explore a unique opportunity to combine imaging and genetic data to study prediction of mild cognitive impairment, and show a substantial gain in performance while accounting for the longitudinal aspect of the data. PMID:26177419

Unsteady propulsion by an intermittent swimming gait

NASA Astrophysics Data System (ADS)

Akoz, Emre; Moored, Keith W.

2018-01-01

Inviscid computational results are presented on a self-propelled swimmer modeled as a virtual body combined with a two-dimensional hydrofoil pitching intermittently about its leading edge. Lighthill (1971) originally proposed that this burst-and-coast behavior can save fish energy during swimming by taking advantage of the viscous Bone-Lighthill boundary layer thinning mechanism. Here, an additional inviscid Garrick mechanism is discovered that allows swimmers to control the ratio of their added mass thrust-producing forces to their circulatory drag-inducing forces by decreasing their duty cycle, DC, of locomotion. This mechanism can save intermittent swimmers as much as 60% of the energy it takes to swim continuously at the same speed. The inviscid energy savings are shown to increase with increasing amplitude of motion, increase with decreasing Lighthill number, Li, and switch to an energetic cost above continuous swimming for sufficiently low DC. Intermittent swimmers are observed to shed four vortices per cycle that form into groups that are self-similar with the DC. In addition, previous thrust and power scaling laws of continuous self-propelled swimming are further generalized to include intermittent swimming. The key is that by averaging the thrust and power coefficients over only the bursting period then the intermittent problem can be transformed into a continuous one. Furthermore, the intermittent thrust and power scaling relations are extended to predict the mean speed and cost of transport of swimmers. By tuning a few coefficients with a handful of simulations these self-propelled relations can become predictive. In the current study, the mean speed and cost of transport are predicted to within 3% and 18% of their full-scale values by using these relations.

Periictal activity in cooled asphyxiated neonates with seizures.

PubMed

Major, Philippe; Lortie, Anne; Dehaes, Mathieu; Lodygensky, Gregory Anton; Gallagher, Anne; Carmant, Lionel; Birca, Ala

2017-04-01

Seizures are common in critically ill neonates. Both seizures and antiepileptic treatments may lead to short term complications and worsen the outcomes. Predicting the risks of seizure reoccurrence could enable individual treatment regimens and better outcomes. We aimed to identify EEG signatures of seizure reoccurrence by investigating periictal electrographic features and spectral power characteristics in hypothermic neonates with hypoxic-ischemic encephalopathy (HIE) with or without reoccurrence of seizures on rewarming. We recruited five consecutive HIE neonates, submitted to continuous EEG monitoring, with high seizure burden (>20% per hour) while undergoing therapeutic hypothermia. Two of them had reoccurrence of seizures on rewarming. We performed quantitative analysis of fifteen artifact-free consecutive seizures to appreciate spectral power changes between the interictal, preictal and ictal periods, separately for each patient. Visual analysis allowed description of electrographic features associated with ictal events. Every patient demonstrated a significant increase in overall spectral power from the interictal to preictal and ictal periods (p<0.01). Alpha power increase was more pronounced in the two patients with reoccurrence of seizures on rewarming and significant when comparing both interictal-to-preictal and interictal-to-ictal periods. This alpha activity increase could be also appreciated using visual analysis and distinguished neonates with and without seizure reoccurrence. This distinct alpha activity preceding ictal onset could represent a biomarker of propensity for seizure reoccurrence in neonates. Future studies should be performed to confirm whether quantitative periictal characteristics and electrographic features allow predicting the risks of seizure reoccurrence in HIE neonates and other critically ill patients. Copyright © 2017 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Development and design of photovoltaic power prediction system

NASA Astrophysics Data System (ADS)

Wang, Zhijia; Zhou, Hai; Cheng, Xu

2018-02-01

In order to reduce the impact of power grid safety caused by volatility and randomness of the energy produced in photovoltaic power plants, this paper puts forward a construction scheme on photovoltaic power generation prediction system, introducing the technical requirements, system configuration and function of each module, and discussing the main technical features of the platform software development. The scheme has been applied in many PV power plants in the northwest of China. It shows that the system can produce reasonable prediction results, providing a right guidance for dispatching and efficient running for PV power plant.

Predictive Trip Detection for Nuclear Power Plants

NASA Astrophysics Data System (ADS)

Rankin, Drew J.; Jiang, Jin

2016-08-01

This paper investigates the use of a Kalman filter (KF) to predict, within the shutdown system (SDS) of a nuclear power plant (NPP), whether safety parameter measurements have reached a trip set-point. In addition, least squares (LS) estimation compensates for prediction error due to system-model mismatch. The motivation behind predictive shutdown is to reduce the amount of time between the occurrence of a fault or failure and the time of trip detection, referred to as time-to-trip. These reductions in time-to-trip can ultimately lead to increases in safety and productivity margins. The proposed predictive SDS differs from conventional SDSs in that it compares point-predictions of the measurements, rather than sensor measurements, against trip set-points. The predictive SDS is validated through simulation and experiments for the steam generator water level safety parameter. Performance of the proposed predictive SDS is compared against benchmark conventional SDS with respect to time-to-trip. In addition, this paper analyzes: prediction uncertainty, as well as; the conditions under which it is possible to achieve reduced time-to-trip. Simulation results demonstrate that on average the predictive SDS reduces time-to-trip by an amount of time equal to the length of the prediction horizon and that the distribution of times-to-trip is approximately Gaussian. Experimental results reveal that a reduced time-to-trip can be achieved in a real-world system with unknown system-model mismatch and that the predictive SDS can be implemented with a scan time of under 100ms. Thus, this paper is a proof of concept for KF/LS-based predictive trip detection.

Two Machine Learning Approaches for Short-Term Wind Speed Time-Series Prediction.

PubMed

Ak, Ronay; Fink, Olga; Zio, Enrico

2016-08-01

The increasing liberalization of European electricity markets, the growing proportion of intermittent renewable energy being fed into the energy grids, and also new challenges in the patterns of energy consumption (such as electric mobility) require flexible and intelligent power grids capable of providing efficient, reliable, economical, and sustainable energy production and distribution. From the supplier side, particularly, the integration of renewable energy sources (e.g., wind and solar) into the grid imposes an engineering and economic challenge because of the limited ability to control and dispatch these energy sources due to their intermittent characteristics. Time-series prediction of wind speed for wind power production is a particularly important and challenging task, wherein prediction intervals (PIs) are preferable results of the prediction, rather than point estimates, because they provide information on the confidence in the prediction. In this paper, two different machine learning approaches to assess PIs of time-series predictions are considered and compared: 1) multilayer perceptron neural networks trained with a multiobjective genetic algorithm and 2) extreme learning machines combined with the nearest neighbors approach. The proposed approaches are applied for short-term wind speed prediction from a real data set of hourly wind speed measurements for the region of Regina in Saskatchewan, Canada. Both approaches demonstrate good prediction precision and provide complementary advantages with respect to different evaluation criteria.

Nonlinear model predictive control of a vortex-induced vibrations bladeless wind turbine

NASA Astrophysics Data System (ADS)

Azadi Yazdi, E.

2018-07-01

In this paper, a nonlinear model predictive controller (NMPC) is proposed for a vortex-induced vibrations bladeless wind turbine (BWT). The BWT consists of a long rigid cylinder mounted on a flexible beam. The nonlinear dynamic model of the transverse vibrations of the BWT is obtained under the fluctuating lift force due to periodically shedding vortices. The NMPC method is used to design a controller that achieves maximum energy production rate. It is observed that the power generation of the NMPC drops in high wind speeds due to a mismatch between the vortex shedding frequency and the structural natural frequency. Therefore, a secondary gain-scheduling (GS) controller is proposed to virtually increase the natural frequency of the structure to match the vortex shedding frequency for high winds. Although previous studies predicted the output power of the studied BWT to be less than 100 W, with the proposed GS-NMPC scheme the output power reaches the value of 1 kW. Therefore, the capability of the BWT as a renewable energy generation device was highly underestimated in the literature. The computed values of the aero-mechanical efficiency suggest the BWT as a major competitor to the conventional wind turbines.

Storm surge and tidal range energy

NASA Astrophysics Data System (ADS)

Lewis, Matthew; Angeloudis, Athanasios; Robins, Peter; Evans, Paul; Neill, Simon

2017-04-01

The need to reduce carbon-based energy sources whilst increasing renewable energy forms has led to concerns of intermittency within a national electricity supply strategy. The regular rise and fall of the tide makes prediction almost entirely deterministic compared to other stochastic renewable energy forms; therefore, tidal range energy is often stated as a predictable and firm renewable energy source. Storm surge is the term used for the non-astronomical forcing of tidal elevation, and is synonymous with coastal flooding because positive storm surges can elevate water-levels above the height of coastal flood defences. We hypothesis storm surges will affect the reliability of the tidal range energy resource; with negative surge events reducing the tidal range, and conversely, positive surge events increasing the available resource. Moreover, tide-surge interaction, which results in positive storm surges more likely to occur on a flooding tide, will reduce the annual tidal range energy resource estimate. Water-level data (2000-2012) at nine UK tide gauges, where the mean tidal amplitude is above 2.5m and thus suitable for tidal-range energy development (e.g. Bristol Channel), were used to predict tidal range power with a 0D modelling approach. Storm surge affected the annual resource estimate by between -5% to +3%, due to inter-annual variability. Instantaneous power output were significantly affected (Normalised Root Mean Squared Error: 3%-8%, Scatter Index: 15%-41%) with spatial variability and variability due to operational strategy. We therefore find a storm surge affects the theoretical reliability of tidal range power, such that a prediction system may be required for any future electricity generation scenario that includes large amounts of tidal-range energy; however, annual resource estimation from astronomical tides alone appears sufficient for resource estimation. Future work should investigate water-level uncertainties on the reliability and predictability of tidal range energy with 2D hydrodynamic models.

Managing PV Power on Mars - MER Rovers

NASA Technical Reports Server (NTRS)

Stella, Paul M.; Chin, Keith; Wood, Eric; Herman, Jennifer; Ewell, Richard

2009-01-01

The MER Rovers have recently completed over 5 years of operation! This is a remarkable demonstration of the capabilities of PV power on the Martian surface. The extended mission required the development of an efficient process to predict the power available to the rovers on a day-to-day basis. The performance of the MER solar arrays is quite unlike that of any other Space array and perhaps more akin to Terrestrial PV operation, although even severe by that comparison. The impact of unpredictable factors, such as atmospheric conditions and dust accumulation (and removal) on the panels limits the accurate prediction of array power to short time spans. Based on the above, it is clear that long term power predictions are not sufficiently accurate to allow for detailed long term planning. Instead, the power assessment is essentially a daily activity, effectively resetting the boundary points for the overall predictive power model. A typical analysis begins with the importing of the telemetry from each rover's previous day's power subsystem activities. This includes the array power generated, battery state-of-charge, rover power loads, and rover orientation, all as functions of time. The predicted performance for that day is compared to the actual performance to identify the extent of any differences. The model is then corrected for these changes. Details of JPL's MER power analysis procedure are presented, including the description of steps needed to provide the final prediction for the mission planners. A dust cleaning event of the solar array is also highlighted to illustrate the impact of Martian weather on solar array performance

GIS and crop simulation modelling applications in climate change research

USDA-ARS?s Scientific Manuscript database

The challenges that climate change presents humanity require an unprecedented ability to predict the responses of crops to environment and management. Geographic information systems (GIS) and crop simulation models are two powerful and highly complementary tools that are increasingly used for such p...

NASA's Prediction Of Worldwide Energy Resource (POWER) Project Unveils a New Geospatial Data Portal

Atmospheric Science Data Center

2018-03-16

NASA's Prediction Of Worldwide Energy Resource (POWER) Project Unveils a New Geospatial Data Portal ... current POWER home page. The new POWER will include improved solar and meteorological data with all parameters available on a 0.5-degree ...

Communal and Agentic Interpersonal and Intergroup Motives Predict Preferences for Status Versus Power.

PubMed

Locke, Kenneth D; Heller, Sonja

2017-01-01

Seven studies involving 1,343 participants showed how circumplex models of social motives can help explain individual differences in preferences for status (having others' admiration) versus power (controlling valuable resources). Studies 1 to 3 and 7 concerned interpersonal motives in workplace contexts, and found that stronger communal motives (to have mutual trust, support, and cooperation) predicted being more attracted to status (but not power) and achieving more workplace status, while stronger agentic motives (to be firm, decisive, and influential) predicted being more attracted to and achieving more workplace power, and experiencing a stronger connection between workplace power and job satisfaction. Studies 4 to 6 found similar effects for intergroup motives: Stronger communal motives predicted wanting one's ingroup (e.g., country) to have status-but not power-relative to other groups. Finally, most people preferred status over power, and this was especially true for women, which was partially explained by women having stronger communal motives.

The predictive power of local properties of financial networks

NASA Astrophysics Data System (ADS)

Caraiani, Petre

2017-01-01

The literature on analyzing the dynamics of financial networks has focused so far on the predictive power of global measures of networks like entropy or index cohesive force. In this paper, I show that the local network properties have similar predictive power. I focus on key network measures like average path length, average degree or cluster coefficient, and also consider the diameter and the s-metric. Using Granger causality tests, I show that some of these measures have statistically significant prediction power with respect to the dynamics of aggregate stock market. Average path length is most robust relative to the frequency of data used or specification (index or growth rate). Most measures are found to have predictive power only for monthly frequency. Further evidences that support this view are provided through a simple regression model.

Ensemble forecasting for renewable energy applications - status and current challenges for their generation and verification

NASA Astrophysics Data System (ADS)

Pinson, Pierre

2016-04-01

The operational management of renewable energy generation in power systems and electricity markets requires forecasts in various forms, e.g., deterministic or probabilistic, continuous or categorical, depending upon the decision process at hand. Besides, such forecasts may also be necessary at various spatial and temporal scales, from high temporal resolutions (in the order of minutes) and very localized for an offshore wind farm, to coarser temporal resolutions (hours) and covering a whole country for day-ahead power scheduling problems. As of today, weather predictions are a common input to forecasting methodologies for renewable energy generation. Since for most decision processes, optimal decisions can only be made if accounting for forecast uncertainties, ensemble predictions and density forecasts are increasingly seen as the product of choice. After discussing some of the basic approaches to obtaining ensemble forecasts of renewable power generation, it will be argued that space-time trajectories of renewable power production may or may not be necessitate post-processing ensemble forecasts for relevant weather variables. Example approaches and test case applications will be covered, e.g., looking at the Horns Rev offshore wind farm in Denmark, or gridded forecasts for the whole continental Europe. Eventually, we will illustrate some of the limitations of current frameworks to forecast verification, which actually make it difficult to fully assess the quality of post-processing approaches to obtain renewable energy predictions.

Predicting energy expenditure through hand rim propulsion power output in individuals who use wheelchairs.

PubMed

Conger, Scott A; Scott, Stacy N; Bassett, David R

2014-07-01

To examine the relationship between hand rim propulsion power and energy expenditure (EE) during wheelchair wheeling and to investigate whether adding other variables to the model could improve on the prediction of EE. Individuals who use manual wheelchairs (n=14) performed five different wheeling activities in a wheelchair with a PowerTap power meter hub built into the right rear wheel. Activities included wheeling on a smooth, level surface at three different speeds (4.5, 5.5 and 6.5 km/h), wheeling on a rubberised track at one speed (5.5 km/h) and wheeling on a sidewalk course that included uphill and downhill segments at a self-selected speed. EE was measured using a portable indirect calorimetry system. Stepwise linear regression was performed to predict EE from power output variables. A repeated-measures analysis of variance was used to compare the measured EE to the estimates from the power models. Bland-Altman plots were used to assess the agreement between the criterion values and the predicted values. EE and power were significantly correlated (r=0.694, p<0.001). Regression analysis yielded three significant prediction models utilising measured power; measured power and speed; and measured power, speed and heart rate. No significant differences were found between measured EE and any of the prediction models. EE can be accurately and precisely estimated based on hand rim propulsion power. These results indicate that power could be used as a method to assess EE in individuals who use wheelchairs. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Neural activity in the hippocampus during conflict resolution.

PubMed

Sakimoto, Yuya; Okada, Kana; Hattori, Minoru; Takeda, Kozue; Sakata, Shogo

2013-01-15

This study examined configural association theory and conflict resolution models in relation to hippocampal neural activity during positive patterning tasks. According to configural association theory, the hippocampus is important for responses to compound stimuli in positive patterning tasks. In contrast, according to the conflict resolution model, the hippocampus is important for responses to single stimuli in positive patterning tasks. We hypothesized that if configural association theory is applicable, and not the conflict resolution model, the hippocampal theta power should be increased when compound stimuli are presented. If, on the other hand, the conflict resolution model is applicable, but not configural association theory, then the hippocampal theta power should be increased when single stimuli are presented. If both models are valid and applicable in the positive patterning task, we predict that the hippocampal theta power should be increased by presentation of both compound and single stimuli during the positive patterning task. To examine our hypotheses, we measured hippocampal theta power in rats during a positive patterning task. The results showed that hippocampal theta power increased during the presentation of a single stimulus, but did not increase during the presentation of a compound stimulus. This finding suggests that the conflict resolution model is more applicable than the configural association theory for describing neural activity during positive patterning tasks. Copyright © 2012 Elsevier B.V. All rights reserved.

A citation-based assessment of the performance of U.S. boiling water reactors following extended power up-rates

NASA Astrophysics Data System (ADS)

Heidrich, Brenden J.

Nuclear power plants produce 20 percent of the electricity generated in the U.S. Nuclear generated electricity is increasingly valuable to a utility because it can be produced at a low marginal cost and it does not release any carbon dioxide. It can also be a hedge against uncertain fossil fuel prices. The construction of new nuclear power plants in the U.S. is cautiously moving forward, restrained by high capital costs. Since 1998, nuclear utilities have been increasing the power output of their reactors by implementing extended power up-rates. Power increases of up to 20 percent are allowed under this process. The equivalent of nine large power plants has been added via extended power up-rates. These up-rates require the replacement of large capital equipment and are often performed in concert with other plant life extension activities such as license renewals. This dissertation examines the effect of these extended power up-rates on the safety performance of U.S. boiling water reactors. Licensing event reports are submitted by the utilities to the Nuclear Regulatory Commission, the federal nuclear regulator, for a wide range of abnormal events. Two methods are used to examine the effect of extended power up-rates on the frequency of abnormal events at the reactors. The Crow/AMSAA model, a univariate technique is used to determine if the implementation of an extended power up-rate affects the rate of abnormal events. The method has a long history in the aerospace industry and in the military. At a 95-percent confidence level, the rate of events requiring the submission of a licensing event report decreases following the implementation of an extended power up-rate. It is hypothesized that the improvement in performance is tied to the equipment replacement and refurbishment that is performed as part of the up-rate process. The reactor performance is also analyzed using the proportional hazards model. This technique allows for the estimation of the effects of multiple independent variables on the event rate. Both the Cox and Weibull formulations were tested. The Cox formulation is more commonly used in survival analysis because of its flexibility. The best Cox model included fixed effects at the multi-reactor site level. The Weibull parametric formulation has the same base hazard rate as the Crow/AMSAA model. This theoretical connection was confirmed through a series of tests that demonstrated both models predicted the same base hazard rates. The Weibull formulation produced a model with most of the same statistically significant variables as the Cox model. The beneficial effect of extended power up-rates was predicted in the proportional hazards models as well as the Crow/AMSAA model. The Weibull model also indicated an effect that can be traced back to a plant’s construction. Performance was also found to improve in plants that had been divested from their original owners. This research developed a consistent evaluation toolkit for nuclear power plant performance using either a univariate method that allows for simple graphical evaluation at its heart or a more complex multivariate method that includes the effects of several independent variables with data that are available from public sources. Utilities or regulators with access to proprietary data may be able to expand upon this research with additional data that is not readily available to an academic researcher. Even without access to special data, the methods developed are valuable tools in evaluating and predicting nuclear power plant reliability performance.

Valuing hydrological forecasts for a pumped storage assisted hydro facility

NASA Astrophysics Data System (ADS)

Zhao, Guangzhi; Davison, Matt

2009-07-01

SummaryThis paper estimates the value of a perfectly accurate short-term hydrological forecast to the operator of a hydro electricity generating facility which can sell its power at time varying but predictable prices. The expected value of a less accurate forecast will be smaller. We assume a simple random model for water inflows and that the costs of operating the facility, including water charges, will be the same whether or not its operator has inflow forecasts. Thus, the improvement in value from better hydrological prediction results from the increased ability of the forecast using facility to sell its power at high prices. The value of the forecast is therefore the difference between the sales of a facility operated over some time horizon with a perfect forecast, and the sales of a similar facility operated over the same time horizon with similar water inflows which, though governed by the same random model, cannot be forecast. This paper shows that the value of the forecast is an increasing function of the inflow process variance and quantifies how much the value of this perfect forecast increases with the variance of the water inflow process. Because the lifetime of hydroelectric facilities is long, the small increase observed here can lead to an increase in the profitability of hydropower investments.

Electrical Generation for More-Electric Aircraft Using Solid Oxide Fuel Cells

DOE Office of Scientific and Technical Information (OSTI.GOV)

Whyatt, Greg A.; Chick, Lawrence A.

This report examines the potential for Solid-Oxide Fuel Cells (SOFC) to provide electrical generation on-board commercial aircraft. Unlike a turbine-based auxiliary power unit (APU) a solid oxide fuel cell power unit (SOFCPU) would be more efficient than using the main engine generators to generate electricity and would operate continuously during flight. The focus of this study is on more-electric aircraft which minimize bleed air extraction from the engines and instead use electrical power obtained from generators driven by the main engines to satisfy all major loads. The increased electrical generation increases the potential fuel savings obtainable through more efficient electricalmore » generation using a SOFCPU. However, the weight added to the aircraft by the SOFCPU impacts the main engine fuel consumption which reduces the potential fuel savings. To investigate these relationships the Boeing 787­8 was used as a case study. The potential performance of the SOFCPU was determined by coupling flowsheet modeling using ChemCAD software with a stack performance algorithm. For a given stack operating condition (cell voltage, anode utilization, stack pressure, target cell exit temperature), ChemCAD software was used to determine the cathode air rate to provide stack thermal balance, the heat exchanger duties, the gross power output for a given fuel rate, the parasitic power for the anode recycle blower and net power obtained from (or required by) the compressor/expander. The SOFC is based on the Gen4 Delphi planar SOFC with assumed modifications to tailor it to this application. The size of the stack needed to satisfy the specified condition was assessed using an empirically-based algorithm. The algorithm predicts stack power density based on the pressure, inlet temperature, cell voltage and anode and cathode inlet flows and compositions. The algorithm was developed by enhancing a model for a well-established material set operating at atmospheric pressure to reflect the effect of elevated pressure and to represent the expected enhancement obtained using a promising cell material set which has been tested in button cells but not yet used to produce full-scale stacks. The predictions for the effect of pressure on stack performance were based on literature. As part of this study, additional data were obtained on button cells at elevated pressure to confirm the validity of the predictions. The impact of adding weight to the 787-8 fuel consumption was determined as a function of flight distance using a PianoX model. A conceptual design for a SOFC power system for the Boeing 787 is developed and the weight estimated. The results indicate that the power density of the stacks must increase by at least a factor of 2 to begin saving fuel on the 787 aircraft. However, the conceptual design of the power system may still be useful for other applications which are less weight sensitive.« less

Lung Injury Prediction Score Is Useful in Predicting Acute Respiratory Distress Syndrome and Mortality in Surgical Critical Care Patients

PubMed Central

Bauman, Zachary M.; Gassner, Marika Y.; Coughlin, Megan A.; Mahan, Meredith; Watras, Jill

2015-01-01

Background. Lung injury prediction score (LIPS) is valuable for early recognition of ventilated patients at high risk for developing acute respiratory distress syndrome (ARDS). This study analyzes the value of LIPS in predicting ARDS and mortality among ventilated surgical patients. Methods. IRB approved, prospective observational study including all ventilated patients admitted to the surgical intensive care unit at a single tertiary center over 6 months. ARDS was defined using the Berlin criteria. LIPS were calculated for all patients and analyzed. Logistic regression models evaluated the ability of LIPS to predict development of ARDS and mortality. A receiver operator characteristic (ROC) curve demonstrated the optimal LIPS value to statistically predict development of ARDS. Results. 268 ventilated patients were observed; 141 developed ARDS and 127 did not. The average LIPS for patients who developed ARDS was 8.8 ± 2.8 versus 5.4 ± 2.8 for those who did not (p < 0.001). An ROC area under the curve of 0.79 demonstrates LIPS is statistically powerful for predicting ARDS development. Furthermore, for every 1-unit increase in LIPS, the odds of developing ARDS increase by 1.50 (p < 0.001) and odds of ICU mortality increase by 1.22 (p < 0.001). Conclusion. LIPS is reliable for predicting development of ARDS and predicting mortality in critically ill surgical patients. PMID:26301105

Conditional power and predictive power based on right censored data with supplementary auxiliary information.

PubMed

Sun, Libo; Wan, Ying

2018-04-22

Conditional power and predictive power provide estimates of the probability of success at the end of the trial based on the information from the interim analysis. The observed value of the time to event endpoint at the interim analysis could be biased for the true treatment effect due to early censoring, leading to a biased estimate of conditional power and predictive power. In such cases, the estimates and inference for this right censored primary endpoint are enhanced by incorporating a fully observed auxiliary variable. We assume a bivariate normal distribution of the transformed primary variable and a correlated auxiliary variable. Simulation studies are conducted that not only shows enhanced conditional power and predictive power but also can provide the framework for a more efficient futility interim analysis in terms of an improved accuracy in estimator, a smaller inflation in type II error and an optimal timing for such analysis. We also illustrated the new approach by a real clinical trial example. Copyright © 2018 John Wiley & Sons, Ltd.

Active Wake Redirection Control to Improve Energy Yield (Poster)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Churchfield, M. J.; Fleming, P.; DeGeorge, E.

Wake effects can dramatically reduce the efficiency of waked turbines relative to the unwaked turbines. Wakes can be deflected, or 'redirected,' by applying yaw misalignment to the turbines. Yaw misalignment causes part of the rotor thrust vector to be pointed in the cross-stream direction, deflecting the flow and the wake. Yaw misalignment reduces power production, but the global increase in wind plant power due to decreased wake effect creates a net increase in power production. It is also a fairly simple control idea to implement at existing or new wind plants. We performed high-fidelity computational fluid dynamics simulations of themore » wake flow of the proposed Fishermen's Atlantic City Windfarm (FACW) that predict that under certain waking conditions, wake redirection can increase plant efficiency by 10%. This means that by applying wake redirection control, for a given watersheet area, a wind plant can either produce more power, or the same amount of power can be produced with a smaller watersheet area. With the power increase may come increased loads, though, due to the yaw misalignment. If misalignment is applied properly, or if layered with individual blade pitch control, though, the load increase can be mitigated. In this talk we will discuss the concept of wake redirection through yaw misalignment and present our CFD results of the FACW project. We will also discuss the implications of wake redirection control on annual energy production, and finally we will discuss plans to implement wake redirection control at FACW when it is operational.« less

Transport phenomena governing nicotine emissions from electronic cigarettes: model formulation and experimental investigation

PubMed Central

Talih, Soha; Balhas, Zainab; Salman, Rola; El-Hage, Rachel; Karaoghlanian, Nareg; El-Hellani, Ahmad; Baassiri, Mohamad; Jaroudi, Ezzat; Eissenberg, Thomas; Saliba, Najat; Shihadeh, Alan

2017-01-01

Electronic cigarettes (ECIGs) electrically heat and aerosolize a liquid containing propylene glycol (PG), vegetable glycerin (VG), flavorants, water, and nicotine. ECIG effects and proposed methods to regulate them are controversial. One regulatory focal point involves nicotine emissions. We describe a mathematical model that predicts ECIG nicotine emissions. The model computes the vaporization rate of individual species by numerically solving the unsteady species and energy conservation equations. To validate model predictions, yields of nicotine, total particulate matter, PG, and VG were measured while manipulating puff topography, electrical power, and liquid composition across 100 conditions. Nicotine flux, the rate at which nicotine is emitted per unit time, was the primary outcome. Across conditions, the measured and computed nicotine flux were highly correlated (r = 0.85, p<.0001). As predicted, device power, nicotine concentration, PG/VG ratio, and puff duration influenced nicotine flux (p<.05), while water content and puff velocity did not. Additional empirical investigation revealed that PG/VG liquids act as ideal solutions, that liquid vaporization accounts for more than 95% of ECIG aerosol mass emissions, and that as device power increases the aerosol composition shifts towards the less volatile components of the parent liquid. To the extent that ECIG regulations focus on nicotine emissions, mathematical models like this one can be used to predict ECIG nicotine emissions and to test the effects of proposed regulation of factors that influence nicotine flux. PMID:28706340

A Comprehensive Prediction Model of Hydraulic Extended-Reach Limit Considering the Allowable Range of Drilling Fluid Flow Rate in Horizontal Drilling.

PubMed

Li, Xin; Gao, Deli; Chen, Xuyue

2017-06-08

Hydraulic extended-reach limit (HERL) model of horizontal extended-reach well (ERW) can predict the maximum measured depth (MMD) of the horizontal ERW. The HERL refers to the well's MMD when drilling fluid cannot be normally circulated by drilling pump. Previous model analyzed the following two constraint conditions, drilling pump rated pressure and rated power. However, effects of the allowable range of drilling fluid flow rate (Q min  ≤ Q ≤ Q max ) were not considered. In this study, three cases of HERL model are proposed according to the relationship between allowable range of drilling fluid flow rate and rated flow rate of drilling pump (Q r ). A horizontal ERW is analyzed to predict its HERL, especially its horizontal-section limit (L h ). Results show that when Q min  ≤ Q r  ≤ Q max (Case I), L h depends both on horizontal-section limit based on rated pump pressure (L h1 ) and horizontal-section limit based on rated pump power (L h2 ); when Q min  < Q max  < Q r (Case II), L h is exclusively controlled by L h1 ; while L h is only determined by L h2 when Q r  < Q min  < Q max (Case III). Furthermore, L h1 first increases and then decreases with the increase in drilling fluid flow rate, while L h2 keeps decreasing as the drilling fluid flow rate increases. The comprehensive model provides a more accurate prediction on HERL.

The prediction of the impact of climatic factors on short-term electric power load based on the big data of smart city

NASA Astrophysics Data System (ADS)

Qiu, Yunfei; Li, Xizhong; Zheng, Wei; Hu, Qinghe; Wei, Zhanmeng; Yue, Yaqin

2017-08-01

The climate changes have great impact on the residents’ electricity consumption, so the study on the impact of climatic factors on electric power load is of significance. In this paper, the effects of the data of temperature, rainfall and wind of smart city on short-term power load is studied to predict power load. The authors studied the relation between power load and daily temperature, rainfall and wind in the 31 days of January of one year. In the research, the authors used the Matlab neural network toolbox to establish the combinational forecasting model. The authors trained the original input data continuously to get the internal rules inside the data and used the rules to predict the daily power load in the next January. The prediction method relies on the accuracy of weather forecasting. If the weather forecasting is different from the actual weather, we need to correct the climatic factors to ensure accurate prediction.

Evaluating Upper-Body Strength and Power From a Single Test: The Ballistic Push-up.

PubMed

Wang, Ran; Hoffman, Jay R; Sadres, Eliahu; Bartolomei, Sandro; Muddle, Tyler W D; Fukuda, David H; Stout, Jeffrey R

2017-05-01

Wang, R, Hoffman, JR, Sadres, E, Bartolomei, S, Muddle, TWD, Fukuda, DH, and Stout, JR. Evaluating upper-body strength and power from a single test: the ballistic push-up. J Strength Cond Res 31(5): 1338-1345, 2017-The purpose of this study was to examine the reliability of the ballistic push-up (BPU) exercise and to develop a prediction model for both maximal strength (1 repetition maximum [1RM]) in the bench press exercise and upper-body power. Sixty recreationally active men completed a 1RM bench press and 2 BPU assessments in 3 separate testing sessions. Peak and mean force, peak and mean rate of force development, net impulse, peak velocity, flight time, and peak and mean power were determined. Intraclass correlation coefficients were used to examine the reliability of the BPU. Stepwise linear regression was used to develop 1RM bench press and power prediction equations. Intraclass correlation coefficient's ranged from 0.849 to 0.971 for the BPU measurements. Multiple regression analysis provided the following 1RM bench press prediction equation: 1RM = 0.31 × Mean Force - 1.64 × Body Mass + 0.70 (R = 0.837, standard error of the estimate [SEE] = 11 kg); time-based power prediction equation: Peak Power = 11.0 × Body Mass + 2012.3 × Flight Time - 338.0 (R = 0.658, SEE = 150 W), Mean Power = 6.7 × Body Mass + 1004.4 × Flight Time - 224.6 (R = 0.664, SEE = 82 W); and velocity-based power prediction equation: Peak Power = 8.1 × Body Mass + 818.6 × Peak Velocity - 762.0 (R = 0.797, SEE = 115 W); Mean Power = 5.2 × Body Mass + 435.9 × Peak Velocity - 467.7 (R = 0.838, SEE = 57 W). The BPU is a reliable test for both upper-body strength and power. Results indicate that the mean force generated from the BPU can be used to predict 1RM bench press, whereas peak velocity and flight time measured during the BPU can be used to predict upper-body power. These findings support the potential use of the BPU as a valid method to evaluate upper-body strength and power.

The Effect of Sex on Heart Rate Variability at High Altitude.

PubMed

Boos, Christopher John; Vincent, Emma; Mellor, Adrian; O'Hara, John; Newman, Caroline; Cruttenden, Richard; Scott, Phylip; Cooke, Mark; Matu, Jamie; Woods, David Richard

2017-12-01

There is evidence suggesting that high altitude (HA) exposure leads to a fall in heart rate variability (HRV) that is linked to the development of acute mountain sickness (AMS). The effects of sex on changes in HRV at HA and its relationship to AMS are unknown. HRV (5-min single-lead ECG) was measured in 63 healthy adults (41 men and 22 women) 18-56 yr of age at sea level (SL) and during a HA trek at 3619, 4600, and 5140 m, respectively. The main effects of altitude (SL, 3619 m, 4600 m, and 5140 m) and sex (men vs women) and their potential interaction were assessed using a factorial repeated-measures ANOVA. Logistic regression analyses were performed to assess the ability of HRV to predict AMS. Men and women were of similar age (31.2 ± 9.3 vs 31.7 ± 7.5 yr), ethnicity, and body and mass index. There was main effect for altitude on heart rate, SD of normal-to-normal (NN) intervals (SDNN), root mean square of successive differences (RMSSD), number of pairs of successive NN differing by >50 ms (NN50), NN50/total number of NN, very low-frequency power, low-frequency (LF) power, high-frequency (HF) power, and total power (TP). The most consistent effect on post hoc analysis was reduction in these HRV measures between 3619 and 5140 m at HA. Heart rate was significantly lower and SDNN, RMSSD, LF power, HF power, and TP were higher in men compared with women at HA. There was no interaction between sex and altitude for any of the HRV indices measured. HRV was not predictive of AMS development. Increasing HA leads to a reduction in HRV. Significant differences between men and women emerge at HA. HRV was not predictive of AMS.

Time series analysis of malaria in Afghanistan: using ARIMA models to predict future trends in incidence.

PubMed

Anwar, Mohammad Y; Lewnard, Joseph A; Parikh, Sunil; Pitzer, Virginia E

2016-11-22

Malaria remains endemic in Afghanistan. National control and prevention strategies would be greatly enhanced through a better ability to forecast future trends in disease incidence. It is, therefore, of interest to develop a predictive tool for malaria patterns based on the current passive and affordable surveillance system in this resource-limited region. This study employs data from Ministry of Public Health monthly reports from January 2005 to September 2015. Malaria incidence in Afghanistan was forecasted using autoregressive integrated moving average (ARIMA) models in order to build a predictive tool for malaria surveillance. Environmental and climate data were incorporated to assess whether they improve predictive power of models. Two models were identified, each appropriate for different time horizons. For near-term forecasts, malaria incidence can be predicted based on the number of cases in the four previous months and 12 months prior (Model 1); for longer-term prediction, malaria incidence can be predicted using the rates 1 and 12 months prior (Model 2). Next, climate and environmental variables were incorporated to assess whether the predictive power of proposed models could be improved. Enhanced vegetation index was found to have increased the predictive accuracy of longer-term forecasts. Results indicate ARIMA models can be applied to forecast malaria patterns in Afghanistan, complementing current surveillance systems. The models provide a means to better understand malaria dynamics in a resource-limited context with minimal data input, yielding forecasts that can be used for public health planning at the national level.

Developing strategies for predicting hyperkalemia in potassium-increasing drug-drug interactions.

PubMed

Eschmann, Emmanuel; Beeler, Patrick Emanuel; Schneemann, Markus; Blaser, Jürg

2017-01-01

To compare different strategies predicting hyperkalemia (serum potassium level ≥5.5 mEq/l) in hospitalized patients for whom medications triggering potassium-increasing drug-drug interactions (DDIs) were ordered. We investigated 5 strategies that combined prediction triggered at onset of DDI versus continuous monitoring and taking into account an increasing number of patient parameters. The considered patient parameters were identified using generalized additive models, and the thresholds of the prediction strategies were calculated by applying Youden's J statistic to receiver operation characteristic curves. Half of the data served as the calibration set, half as the validation set. We identified 132 incidences of hyperkalemia induced by 8413 potentially severe potassium-increasing DDIs among 76 467 patients. The positive predictive value (PPV) of those strategies predicting hyperkalemia at the onset of DDI ranged from 1.79% (undifferentiated anticipation of hyperkalemia due to the DDI) to 3.02% (additionally considering the baseline serum potassium) and 3.10% (including further patient parameters). Continuous monitoring significantly increased the PPV to 8.25% (considering the current serum potassium) and 9.34% (additional patient parameters). Continuous monitoring of the risk for hyperkalemia based on current potassium level shows a better predictive power than predictions triggered at the onset of DDI. This contrasts with efforts to improve DDI alerts by taking into account more patient parameters at the time of ordering. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Utilization of Model Predictive Control to Balance Power Absorption Against Load Accumulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Abbas, Nikhar; Tom, Nathan M

2017-06-03

Wave energy converter (WEC) control strategies have been primarily focused on maximizing power absorption. The use of model predictive control strategies allows for a finite-horizon, multiterm objective function to be solved. This work utilizes a multiterm objective function to maximize power absorption while minimizing the structural loads on the WEC system. Furthermore, a Kalman filter and autoregressive model were used to estimate and forecast the wave exciting force and predict the future dynamics of the WEC. The WEC's power-take-off time-averaged power and structural loads under a perfect forecast assumption in irregular waves were compared against results obtained from the Kalmanmore » filter and autoregressive model to evaluate model predictive control performance.« less

Utilization of Model Predictive Control to Balance Power Absorption Against Load Accumulation: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Abbas, Nikhar; Tom, Nathan

Wave energy converter (WEC) control strategies have been primarily focused on maximizing power absorption. The use of model predictive control strategies allows for a finite-horizon, multiterm objective function to be solved. This work utilizes a multiterm objective function to maximize power absorption while minimizing the structural loads on the WEC system. Furthermore, a Kalman filter and autoregressive model were used to estimate and forecast the wave exciting force and predict the future dynamics of the WEC. The WEC's power-take-off time-averaged power and structural loads under a perfect forecast assumption in irregular waves were compared against results obtained from the Kalmanmore » filter and autoregressive model to evaluate model predictive control performance.« less

X-33 XRS-2200 Linear Aerospike Engine Sea Level Plume Radiation

NASA Technical Reports Server (NTRS)

DAgostino, Mark G.; Lee, Young C.; Wang, Ten-See; Turner, Jim (Technical Monitor)

2001-01-01

Wide band plume radiation data were collected during ten sea level tests of a single XRS-2200 engine at the NASA Stennis Space Center in 1999 and 2000. The XRS-2200 is a liquid hydrogen/liquid oxygen fueled, gas generator cycle linear aerospike engine which develops 204,420 lbf thrust at sea level. Instrumentation consisted of six hemispherical radiometers and one narrow view radiometer. Test conditions varied from 100% to 57% power level (PL) and 6.0 to 4.5 oxidizer to fuel (O/F) ratio. Measured radiation rates generally increased with engine chamber pressure and mixture ratio. One hundred percent power level radiation data were compared to predictions made with the FDNS and GASRAD codes. Predicted levels ranged from 42% over to 7% under average test values.

Ultra-Short-Term Wind Power Prediction Using a Hybrid Model

NASA Astrophysics Data System (ADS)

Mohammed, E.; Wang, S.; Yu, J.

2017-05-01

This paper aims to develop and apply a hybrid model of two data analytical methods, multiple linear regressions and least square (MLR&LS), for ultra-short-term wind power prediction (WPP), for example taking, Northeast China electricity demand. The data was obtained from the historical records of wind power from an offshore region, and from a wind farm of the wind power plant in the areas. The WPP achieved in two stages: first, the ratios of wind power were forecasted using the proposed hybrid method, and then the transformation of these ratios of wind power to obtain forecasted values. The hybrid model combines the persistence methods, MLR and LS. The proposed method included two prediction types, multi-point prediction and single-point prediction. WPP is tested by applying different models such as autoregressive moving average (ARMA), autoregressive integrated moving average (ARIMA) and artificial neural network (ANN). By comparing results of the above models, the validity of the proposed hybrid model is confirmed in terms of error and correlation coefficient. Comparison of results confirmed that the proposed method works effectively. Additional, forecasting errors were also computed and compared, to improve understanding of how to depict highly variable WPP and the correlations between actual and predicted wind power.

Experimental validation of boundary element methods for noise prediction

NASA Technical Reports Server (NTRS)

Seybert, A. F.; Oswald, Fred B.

1992-01-01

Experimental validation of methods to predict radiated noise is presented. A combined finite element and boundary element model was used to predict the vibration and noise of a rectangular box excited by a mechanical shaker. The predicted noise was compared to sound power measured by the acoustic intensity method. Inaccuracies in the finite element model shifted the resonance frequencies by about 5 percent. The predicted and measured sound power levels agree within about 2.5 dB. In a second experiment, measured vibration data was used with a boundary element model to predict noise radiation from the top of an operating gearbox. The predicted and measured sound power for the gearbox agree within about 3 dB.

Predicting Rediated Noise With Power Flow Finite Element Analysis

DTIC Science & Technology

2007-02-01

Defence R&D Canada – Atlantic DEFENCE DÉFENSE & Predicting Rediated Noise With Power Flow Finite Element Analysis D. Brennan T.S. Koko L. Jiang J...PREDICTING RADIATED NOISE WITH POWER FLOW FINITE ELEMENT ANALYSIS D.P. Brennan T.S. Koko L. Jiang J.C. Wallace Martec Limited Martec Limited...model- or full-scale data before it is available for general use. Brennan, D.P., Koko , T.S., Jiang, L., Wallace, J.C. 2007. Predicting Radiated

Dynamic Modeling and Very Short-term Prediction of Wind Power Output Using Box-Cox Transformation

NASA Astrophysics Data System (ADS)

Urata, Kengo; Inoue, Masaki; Murayama, Dai; Adachi, Shuichi

2016-09-01

We propose a statistical modeling method of wind power output for very short-term prediction. The modeling method with a nonlinear model has cascade structure composed of two parts. One is a linear dynamic part that is driven by a Gaussian white noise and described by an autoregressive model. The other is a nonlinear static part that is driven by the output of the linear part. This nonlinear part is designed for output distribution matching: we shape the distribution of the model output to match with that of the wind power output. The constructed model is utilized for one-step ahead prediction of the wind power output. Furthermore, we study the relation between the prediction accuracy and the prediction horizon.

Vertical Jump and Leg Power Normative Data for Colombian Schoolchildren Aged 9-17.9 Years: The FUPRECOL Study.

PubMed

Ramírez-Vélez, Robinson; Correa-Bautista, Jorge E; Lobelo, Felipe; Cadore, Eduardo L; Alonso-Martinez, Alicia M; Izquierdo, Mikel

2017-04-01

Ramírez-Vélez, R, Correa-Bautista, JE, Lobelo, F, Cadore, EL, Alonso-Martinez, AM, and Izquierdo, M. Vertical jump and leg power normative data for Colombian schoolchildren aged 9-17.9 years: the FUPRECOL study. J Strength Cond Res 31(4): 990-998, 2017-The aims of the present study were to generate normative vertical jump height and predicted peak power (Ppeak) data for 9- to 17.9-year-olds and to investigate between-sex and age group differences in these measures. This was a cross-sectional study of 7,614 healthy schoolchildren (boys n = 3,258 and girls n = 4,356, mean [SD] age 12.8 [2.3] years). Each participant performed 2 countermovement jumps; jump height was calculated using a Takei 5414 Jump-DF Digital Vertical (Takei Scientific Instruments Co., Ltd.). The highest jump was used for analysis and in the calculation of predicted Ppeak. Centile smoothed curves, percentiles, and tables for the 3rd, 10th, 25th, 50th, 75th, 90th, and 97th percentiles were calculated using Cole's LMS (L [curve Box-Cox], M [curve median], and S [curve coefficient of variation]) method. The 2-way analysis of variance tests showed that maximum jump height (in centimeters) and predicted Ppeak (in watts) were higher in boys than in girls (p < 0.01). Post hoc analyses within sexes showed yearly increases in jump height and Ppeak in all ages. In boys, the maximum jump height and predicted Ppeak 50th percentile ranged from 24.0 to 38.0 cm and from 845.5 to 3061.6 W, respectively. In girls, the 50th percentile for jump height ranged from 22.3 to 27.0 cm, and the predicted Ppeak was 710.1-2036.4 W. For girls, jump height increased yearly from 9 to 17.9 years old. Our results provide, for the first time, sex- and age-specific vertical jump height and predicted Ppeak reference standards for Colombian schoolchildren aged 9-17.9 years.

Social motives and cognitive power-sex associations: predictors of aggressive sexual behavior.

PubMed

Zurbriggen, E L

2000-03-01

The present study investigated whether implicit social motives and cognitive power-sex associations would predict self-reports of aggressive sexual behavior. Participants wrote stories in response to Thematic Apperception Test pictures, which were scored for power and affiliation-intimacy motives. They also completed a lexical-decision priming task that provided an index of the strength of the cognitive association between the concepts of "power" and "sexuality." For men, high levels of power motivation and strong power-sex associations predicted more frequent aggression. There was also an interaction: Power motivation was unrelated to aggression for men with the weakest power-sex associations. For women, high levels of affiliation-intimacy motivation were associated with more frequent aggression. Strong power-sex associations were also predictive for women but only when affiliation-intimacy motivation was high.

Epileptic Seizure Prediction Using Big Data and Deep Learning: Toward a Mobile System.

PubMed

Kiral-Kornek, Isabell; Roy, Subhrajit; Nurse, Ewan; Mashford, Benjamin; Karoly, Philippa; Carroll, Thomas; Payne, Daniel; Saha, Susmita; Baldassano, Steven; O'Brien, Terence; Grayden, David; Cook, Mark; Freestone, Dean; Harrer, Stefan

2018-01-01

Seizure prediction can increase independence and allow preventative treatment for patients with epilepsy. We present a proof-of-concept for a seizure prediction system that is accurate, fully automated, patient-specific, and tunable to an individual's needs. Intracranial electroencephalography (iEEG) data of ten patients obtained from a seizure advisory system were analyzed as part of a pseudoprospective seizure prediction study. First, a deep learning classifier was trained to distinguish between preictal and interictal signals. Second, classifier performance was tested on held-out iEEG data from all patients and benchmarked against the performance of a random predictor. Third, the prediction system was tuned so sensitivity or time in warning could be prioritized by the patient. Finally, a demonstration of the feasibility of deployment of the prediction system onto an ultra-low power neuromorphic chip for autonomous operation on a wearable device is provided. The prediction system achieved mean sensitivity of 69% and mean time in warning of 27%, significantly surpassing an equivalent random predictor for all patients by 42%. This study demonstrates that deep learning in combination with neuromorphic hardware can provide the basis for a wearable, real-time, always-on, patient-specific seizure warning system with low power consumption and reliable long-term performance. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

3D thermal model of laser surface glazing for H13 tool steel

NASA Astrophysics Data System (ADS)

Kabir, I. R.; Yin, D.; Naher, S.

2017-10-01

In this work a three dimensional (3D) finite element model of laser surface glazing (LSG) process has been developed. The purpose of the 3D thermal model of LSG was to achieve maximum accuracy towards the predicted outcome for optimizing the process. A cylindrical geometry of 10mm diameter and 1mm length was used in ANSYS 15 software. Temperature distribution, depth of modified zone and cooling rates were analysed from the thermal model. Parametric study was carried out varying the laser power from 200W-300W with constant beam diameter and residence time which were 0.2mm and 0.15ms respectively. The maximum surface temperature 2554°K was obtained for power 300W and minimum surface temperature 1668°K for power 200W. Heating and cooling rates increased with increasing laser power. The depth of the laser modified zone attained for 300W power was 37.5µm and for 200W power was 30µm. No molten zone was observed at 200W power. Maximum surface temperatures obtained from 3D model increased 4% than 2D model presented in author's previous work. In order to verify simulation results an analytical solution of temperature distribution for laser surface modification was used. The surface temperature after heating was calculated for similar laser parameters which is 1689°K. The difference in maximum surface temperature is around 20.7°K between analytical and numerical analysis of LSG for power 200W.

The predictive power of physical function assessed by questionnaire and physical performance measures for subsequent disability.

PubMed

Hoshi, Masayuki; Hozawa, Atsushi; Kuriyama, Shinichi; Nakaya, Naoki; Ohmori-Matsuda, Kaori; Sone, Toshimasa; Kakizaki, Masako; Niu, Kaijun; Fujita, Kazuki; Ueki, Shouzoh; Haga, Hiroshi; Nagatomi, Ryoichi; Tsuji, Ichiro

2012-08-01

To compare the predictive power of physical function assessed by questionnaire and physical performance measures for subsequent disability in community-dwelling elderly persons. Prospective cohort study. Participants were 813 aged 70 years and older, elderly Japanese residing in the community, included in the Tsurugaya Project, who were not disabled at the baseline in 2003. Physical function was assessed by the questionnaire of "Motor Fitness Scale". Physical performance measures consisted of maximum walking velocity, timed up and go test (TUG), leg extension power, and functional reach test. The area under the curve (AUC) of the receiver operating characteristic curve for disability was used to compare screening accuracy between Motor Fitness Scale and physical performance measures. Incident disability, defined as certification for long-term care insurance, was used as the endpoint. We observed 135 cases of incident disability during follow-up. The third or fourth quartile for each measure was associated with a significantly increased risk of disability in comparison with the highest quartile. The AUC was 0.70, 0.72, 0.70, 0.68, 0.69 and 0.74, for Motor Fitness Scale, maxi- mum walking velocity, TUG, leg extension power, functional reach test, and total performance score, respectively. The predictive power of physical function assessed by the Motor Fitness Scale was equivalent to that assessed by physical performance measures. Since Motor Fitness Scale can evaluate physical function safely and simply in comparison with physical performance tests, it would be a practical tool for screening persons at high risk of disability.

Evaluation and prediction of solar radiation for energy management based on neural networks

NASA Astrophysics Data System (ADS)

Aldoshina, O. V.; Van Tai, Dinh

2017-08-01

Currently, there is a high rate of distribution of renewable energy sources and distributed power generation based on intelligent networks; therefore, meteorological forecasts are particularly useful for planning and managing the energy system in order to increase its overall efficiency and productivity. The application of artificial neural networks (ANN) in the field of photovoltaic energy is presented in this article. Implemented in this study, two periodically repeating dynamic ANS, that are the concentration of the time delay of a neural network (CTDNN) and the non-linear autoregression of a network with exogenous inputs of the NAEI, are used in the development of a model for estimating and daily forecasting of solar radiation. ANN show good productivity, as reliable and accurate models of daily solar radiation are obtained. This allows to successfully predict the photovoltaic output power for this installation. The potential of the proposed method for controlling the energy of the electrical network is shown using the example of the application of the NAEI network for predicting the electric load.

Convexity of Energy-Like Functions: Theoretical Results and Applications to Power System Operations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dvijotham, Krishnamurthy; Low, Steven; Chertkov, Michael

2015-01-12

Power systems are undergoing unprecedented transformations with increased adoption of renewables and distributed generation, as well as the adoption of demand response programs. All of these changes, while making the grid more responsive and potentially more efficient, pose significant challenges for power systems operators. Conventional operational paradigms are no longer sufficient as the power system may no longer have big dispatchable generators with sufficient positive and negative reserves. This increases the need for tools and algorithms that can efficiently predict safe regions of operation of the power system. In this paper, we study energy functions as a tool to designmore » algorithms for various operational problems in power systems. These have a long history in power systems and have been primarily applied to transient stability problems. In this paper, we take a new look at power systems, focusing on an aspect that has previously received little attention: Convexity. We characterize the domain of voltage magnitudes and phases within which the energy function is convex in these variables. We show that this corresponds naturally with standard operational constraints imposed in power systems. We show that power of equations can be solved using this approach, as long as the solution lies within the convexity domain. We outline various desirable properties of solutions in the convexity domain and present simple numerical illustrations supporting our results.« less

Distinct plasma lipids profiles of recurrent ovarian cancer by liquid chromatography-mass spectrometry

PubMed Central

Li, Ang; Cheng, Jinlong; Yang, Kai; Wang, Jingtao; Wang, Wenjie; Zhang, Fan; Li, Zhenzi; Dhillon, Harman S.; Openkova, Margarita S; Zhou, Xiaohua; Li, Kang; Hou, Yan

2017-01-01

Epithelial ovarian cancer (EOC) is the most deadly gynecologic malignancy worldwide due to its high recurrence rate after surgery and chemotherapy. There is a critical need for discovery of novel biomarkers for EOC recurrence providing higher prediction power than that of the present ones. Lipids have been reported to associate with development and progression of cancer. In the current study, we aim to identify and validate the lipids which were relevant to the ovarian cancer recurrence based on plasma lipidomics performed by ultra-performance liquid chromatography coupled with mass spectrometry. In order to fulfill this objective, plasma from 70 EOC patients with follow up information was obtained. The results revealed that patients with and without recurrence could be clearly distinguished based on their lipid profiles. Thirty-one lipid metabolites were identified as potential biomarkers for EOC recurrence. The AUC value of these metabolite combinations for predicting EOC recurrence was 0.897. In terms of clinical applicability, LysoPG(20:5) arose as a potential EOC recurrence predictive biomarker to increase the predictive power of clinical predictors from AUC value 0.739 to 0.875. Additionally, we still found that individuals with early relapses (< 6 months) had a distinctive metabolomic pattern compared with late EOC and non-EOC recurrence subjects. Interestingly, decreased levels of triglycerides (TGs) were found to be a specific metabolic feature foreshadowing an early relapse. In conclusion, plasma lipidomics study could be used for predicting EOC recurrences, as well as early and late recurrent cases. The lipid biomarker research improves the predictive power of clinical predictors and the identified biomarkers are of great prognostic and therapeutic potential. PMID:27564116

Combined Euler column vibration isolation and energy harvesting

NASA Astrophysics Data System (ADS)

Davis, R. B.; McDowell, M. D.

2017-05-01

A new device that combines vibration isolation and energy harvesting is modeled, simulated, and tested. The vibration isolating portion of the device uses post-buckled beams as its spring elements. Piezoelectric film is applied to the beams to harvest energy from their dynamic flexure. The entire device operates passively on applied base excitation and requires no external power or control system. The structural system is modeled using the elastica, and the structural response is applied as forcing on the electric circuit equation to predict the output voltage and the corresponding harvested power. The vibration isolation and energy harvesting performance is simulated across a large parameter space and the modeling approach is validated with experimental results. Experimental transmissibilities of 2% and harvested power levels of 0.36 μW are simultaneously demonstrated. Both theoretical and experimental data suggest that there is not necessarily a trade-off between vibration isolation and harvested power. That is, within the practical operational range of the device, improved vibration isolation will be accompanied by an increase in the harvested power as the forcing frequency is increased.

POWER Web Access Data

Atmospheric Science Data Center

2018-05-27

Description:  Obtain Prediction of Worldwide Energy Resource (POWER) data The Prediction of Worldwide Energy ... (POWER) project was initiated to improve upon the current renewable energy data set and to create new data sets from new satellite ...

1987 overview of free-piston Stirling technology for space power application

NASA Technical Reports Server (NTRS)

Slaby, Jack G.; Alger, Donald L.

1987-01-01

The Lewis Research Center program concerned with the development of a free-piston Stirling engine for space-power applications is examined. The system mass of a Stirling system is compared to that of a Brayton system for the same peak temperature and output power; the advantages of the Stirling system are discussed. The predicted and experimental performances of the 25 kWe opposed-piston space power demonstrator engine are evaluated. It is determined that in order to enhance performance the regenerator needs to be modified, and the gas bearing flow between the displacer and power piston needs to be isolated in order to increase the operating stroke. Identification and correction of the energy losses, the design and operation of the linear alternator, and heat exchange concepts are considered. The design parameters and conceptual design characteristics for a 25 kWe single-cylinder free-piston Stirling space-power converter are described.

Formation of visual memories controlled by gamma power phase-locked to alpha oscillations.

PubMed

Park, Hyojin; Lee, Dong Soo; Kang, Eunjoo; Kang, Hyejin; Hahm, Jarang; Kim, June Sic; Chung, Chun Kee; Jiang, Haiteng; Gross, Joachim; Jensen, Ole

2016-06-16

Neuronal oscillations provide a window for understanding the brain dynamics that organize the flow of information from sensory to memory areas. While it has been suggested that gamma power reflects feedforward processing and alpha oscillations feedback control, it remains unknown how these oscillations dynamically interact. Magnetoencephalography (MEG) data was acquired from healthy subjects who were cued to either remember or not remember presented pictures. Our analysis revealed that in anticipation of a picture to be remembered, alpha power decreased while the cross-frequency coupling between gamma power and alpha phase increased. A measure of directionality between alpha phase and gamma power predicted individual ability to encode memory: stronger control of alpha phase over gamma power was associated with better memory. These findings demonstrate that encoding of visual information is reflected by a state determined by the interaction between alpha and gamma activity.

Formation of visual memories controlled by gamma power phase-locked to alpha oscillations

PubMed Central

Park, Hyojin; Lee, Dong Soo; Kang, Eunjoo; Kang, Hyejin; Hahm, Jarang; Kim, June Sic; Chung, Chun Kee; Jiang, Haiteng; Gross, Joachim; Jensen, Ole

2016-01-01

Neuronal oscillations provide a window for understanding the brain dynamics that organize the flow of information from sensory to memory areas. While it has been suggested that gamma power reflects feedforward processing and alpha oscillations feedback control, it remains unknown how these oscillations dynamically interact. Magnetoencephalography (MEG) data was acquired from healthy subjects who were cued to either remember or not remember presented pictures. Our analysis revealed that in anticipation of a picture to be remembered, alpha power decreased while the cross-frequency coupling between gamma power and alpha phase increased. A measure of directionality between alpha phase and gamma power predicted individual ability to encode memory: stronger control of alpha phase over gamma power was associated with better memory. These findings demonstrate that encoding of visual information is reflected by a state determined by the interaction between alpha and gamma activity. PMID:27306959

Formation of visual memories controlled by gamma power phase-locked to alpha oscillations

NASA Astrophysics Data System (ADS)

Park, Hyojin; Lee, Dong Soo; Kang, Eunjoo; Kang, Hyejin; Hahm, Jarang; Kim, June Sic; Chung, Chun Kee; Jiang, Haiteng; Gross, Joachim; Jensen, Ole

2016-06-01

Neuronal oscillations provide a window for understanding the brain dynamics that organize the flow of information from sensory to memory areas. While it has been suggested that gamma power reflects feedforward processing and alpha oscillations feedback control, it remains unknown how these oscillations dynamically interact. Magnetoencephalography (MEG) data was acquired from healthy subjects who were cued to either remember or not remember presented pictures. Our analysis revealed that in anticipation of a picture to be remembered, alpha power decreased while the cross-frequency coupling between gamma power and alpha phase increased. A measure of directionality between alpha phase and gamma power predicted individual ability to encode memory: stronger control of alpha phase over gamma power was associated with better memory. These findings demonstrate that encoding of visual information is reflected by a state determined by the interaction between alpha and gamma activity.

Interpretation of body-mounted accelerometry in flying animals and estimation of biomechanical power

PubMed Central

Spivey, R. J.; Bishop, C. M.

2013-01-01

An idealized energy fluctuation model of a bird's body undergoing horizontal flapping flight is developed, focusing on the biomechanical power discernible to a body-mounted accelerometer. Expressions for flight body power constructed from root mean square dynamic body accelerations and wingstroke frequency are derived from first principles and presented in dimensionally appropriate units. As wingstroke frequency increases, the model generally predicts a gradual transition in power from a linear to an asymptotically cubic relationship. However, the onset of this transition and the degree to which this occurs depends upon whether and how forward vibrations are exploited for temporary energy storage and retrieval. While this may vary considerably between species and individual birds, it is found that a quadrature phase arrangement is generally advantageous during level flight. Gravity-aligned vertical acceleration always enters into the calculation of body power, but, whenever forward acceleration becomes relevant, its contribution is subtractive. Several novel kinematic measures descriptive of flapping flight are postulated, offering fresh insights into the processes involved in airborne locomotion. The limitations of the model are briefly discussed, and departures from its predictions during ascending and descending flight evaluated. These findings highlight how body-mounted accelerometers can offer a valuable, insightful and non-invasive technique for investigating the flight of free-ranging birds and bats. PMID:23883951

Interpretation of body-mounted accelerometry in flying animals and estimation of biomechanical power.

PubMed

Spivey, R J; Bishop, C M

2013-10-06

An idealized energy fluctuation model of a bird's body undergoing horizontal flapping flight is developed, focusing on the biomechanical power discernible to a body-mounted accelerometer. Expressions for flight body power constructed from root mean square dynamic body accelerations and wingstroke frequency are derived from first principles and presented in dimensionally appropriate units. As wingstroke frequency increases, the model generally predicts a gradual transition in power from a linear to an asymptotically cubic relationship. However, the onset of this transition and the degree to which this occurs depends upon whether and how forward vibrations are exploited for temporary energy storage and retrieval. While this may vary considerably between species and individual birds, it is found that a quadrature phase arrangement is generally advantageous during level flight. Gravity-aligned vertical acceleration always enters into the calculation of body power, but, whenever forward acceleration becomes relevant, its contribution is subtractive. Several novel kinematic measures descriptive of flapping flight are postulated, offering fresh insights into the processes involved in airborne locomotion. The limitations of the model are briefly discussed, and departures from its predictions during ascending and descending flight evaluated. These findings highlight how body-mounted accelerometers can offer a valuable, insightful and non-invasive technique for investigating the flight of free-ranging birds and bats.

Stillwater Hybrid Geo-Solar Power Plant Optimization Analyses

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wendt, Daniel S.; Mines, Gregory L.; Turchi, Craig S.

2015-09-02

The Stillwater Power Plant is the first hybrid plant in the world able to bring together a medium-enthalpy geothermal unit with solar thermal and solar photovoltaic systems. Solar field and power plant models have been developed to predict the performance of the Stillwater geothermal / solar-thermal hybrid power plant. The models have been validated using operational data from the Stillwater plant. A preliminary effort to optimize performance of the Stillwater hybrid plant using optical characterization of the solar field has been completed. The Stillwater solar field optical characterization involved measurement of mirror reflectance, mirror slope error, and receiver position error.more » The measurements indicate that the solar field may generate 9% less energy than the design value if an appropriate tracking offset is not employed. A perfect tracking offset algorithm may be able to boost the solar field performance by about 15%. The validated Stillwater hybrid plant models were used to evaluate hybrid plant operating strategies including turbine IGV position optimization, ACC fan speed and turbine IGV position optimization, turbine inlet entropy control using optimization of multiple process variables, and mixed working fluid substitution. The hybrid plant models predict that each of these operating strategies could increase net power generation relative to the baseline Stillwater hybrid plant operations.« less

Flow Accelerated Erosion-Corrosion (FAC) considerations for secondary side piping in the AP1000{sup R} nuclear power plant design

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vanderhoff, J. F.; Rao, G. V.; Stein, A.

2012-07-01

The issue of Flow Accelerated Erosion-Corrosion (FAC) in power plant piping is a known phenomenon that has resulted in material replacements and plant accidents in operating power plants. Therefore, it is important for FAC resistance to be considered in the design of new nuclear power plants. This paper describes the design considerations related to FAC that were used to develop a safe and robust AP1000{sup R} plant secondary side piping design. The primary FAC influencing factors include: - Fluid Temperature - Pipe Geometry/layout - Fluid Chemistry - Fluid Velocity - Pipe Material Composition - Moisture Content (in steam lines) Duemore » to the unknowns related to the relative impact of the influencing factors and the complexities of the interactions between these factors, it is difficult to accurately predict the expected wear rate in a given piping segment in a new plant. This paper provides: - a description of FAC and the factors that influence the FAC degradation rate, - an assessment of the level of FAC resistance of AP1000{sup R} secondary side system piping, - an explanation of options to increase FAC resistance and associated benefits/cost, - discussion of development of a tool for predicting FAC degradation rate in new nuclear power plants. (authors)« less

Thermomechanical modelling of laser surface glazing for H13 tool steel

NASA Astrophysics Data System (ADS)

Kabir, I. R.; Yin, D.; Tamanna, N.; Naher, S.

2018-03-01

A two-dimensional thermomechanical finite element (FE) model of laser surface glazing (LSG) has been developed for H13 tool steel. The direct coupling technique of ANSYS 17.2 (APDL) has been utilised to solve the transient thermomechanical process. A H13 tool steel cylindrical cross-section has been modelled for laser power 200 W and 300 W at constant 0.2 mm beam width and 0.15 ms residence time. The model can predict temperature distribution, stress-strain increments in elastic and plastic region with time and space. The crack formation tendency also can be assumed by analysing the von Mises stress in the heat-concentrated zone. Isotropic and kinematic hardening models have been applied separately to predict the after-yield phenomena. At 200 W laser power, the peak surface temperature achieved is 1520 K which is below the melting point (1727 K) of H13 tool steel. For laser power 300 W, the peak surface temperature is 2523 K. Tensile residual stresses on surface have been found after cooling, which are in agreement with literature. Isotropic model shows higher residual stress that increases with laser power. Conversely, kinematic model gives lower residual stress which decreases with laser power. Therefore, both plasticity models could work in LSG for H13 tool steel.

Multisensory stimuli elicit altered oscillatory brain responses at gamma frequencies in patients with schizophrenia

PubMed Central

Stone, David B.; Coffman, Brian A.; Bustillo, Juan R.; Aine, Cheryl J.; Stephen, Julia M.

2014-01-01

Deficits in auditory and visual unisensory responses are well documented in patients with schizophrenia; however, potential abnormalities elicited from multisensory audio-visual stimuli are less understood. Further, schizophrenia patients have shown abnormal patterns in task-related and task-independent oscillatory brain activity, particularly in the gamma frequency band. We examined oscillatory responses to basic unisensory and multisensory stimuli in schizophrenia patients (N = 46) and healthy controls (N = 57) using magnetoencephalography (MEG). Time-frequency decomposition was performed to determine regions of significant changes in gamma band power by group in response to unisensory and multisensory stimuli relative to baseline levels. Results showed significant behavioral differences between groups in response to unisensory and multisensory stimuli. In addition, time-frequency analysis revealed significant decreases and increases in gamma-band power in schizophrenia patients relative to healthy controls, which emerged both early and late over both sensory and frontal regions in response to unisensory and multisensory stimuli. Unisensory gamma-band power predicted multisensory gamma-band power differently by group. Furthermore, gamma-band power in these regions predicted performance in select measures of the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) test battery differently by group. These results reveal a unique pattern of task-related gamma-band power in schizophrenia patients relative to controls that may indicate reduced inhibition in combination with impaired oscillatory mechanisms in patients with schizophrenia. PMID:25414652

Novel fiber-MOPA-based high power blue laser

NASA Astrophysics Data System (ADS)

Engin, Doruk; Fouron, Jean-Luc; Chen, Youming; Huffman, Andromeda; Fitzpatrick, Fran; Burnham, Ralph; Gupta, Shantanu

2012-06-01

5W peak power at 911 nm is demonstrated with a pulsed Neodymium (Nd) doped fiber master oscillator power amplifier (MOPA). This result is the first reported high gain (16dB) fiber amplifier operation at 911nm. Pulse repetition frequency (PRF) and duty-cycle dependence of the all fiber system is characterized. Negligible performance degreadation is observed down to 1% duty cycle and 10 kHz PRF, where 2.5μJ of pulse energy is achieved. Continuous wave (CW) MOPA experiments achieved 55mW average power and 9dB gain with 15% optical to optical (o-o) efficiency. Excellent agreement is established between dynammic fiber MOPA simulation tool and experimental results in predicting output amplified spontaneous emission (ase) and signal pulse shapes. Using the simulation tool robust Stimulated Brillion Scattering (SBS) free operation is predicted out of a two stage all fiber system that generates over 10W's of peak power with 500 MHz line-width. An all fiber 911 nm pulsed laser source with >10W of peak power is expected to increase reliability and reduce complexity of high energy 455 nm laser system based on optical parametric amplification for udnerwater applications. The views expressed are thos of the author and do not reflect the official policy or position of the Department of Defense or the U.S. Government.

Prediction of near-term breast cancer risk using a Bayesian belief network

NASA Astrophysics Data System (ADS)

Zheng, Bin; Ramalingam, Pandiyarajan; Hariharan, Harishwaran; Leader, Joseph K.; Gur, David

2013-03-01

Accurately predicting near-term breast cancer risk is an important prerequisite for establishing an optimal personalized breast cancer screening paradigm. In previous studies, we investigated and tested the feasibility of developing a unique near-term breast cancer risk prediction model based on a new risk factor associated with bilateral mammographic density asymmetry between the left and right breasts of a woman using a single feature. In this study we developed a multi-feature based Bayesian belief network (BBN) that combines bilateral mammographic density asymmetry with three other popular risk factors, namely (1) age, (2) family history, and (3) average breast density, to further increase the discriminatory power of our cancer risk model. A dataset involving "prior" negative mammography examinations of 348 women was used in the study. Among these women, 174 had breast cancer detected and verified in the next sequential screening examinations, and 174 remained negative (cancer-free). A BBN was applied to predict the risk of each woman having cancer detected six to 18 months later following the negative screening mammography. The prediction results were compared with those using single features. The prediction accuracy was significantly increased when using the BBN. The area under the ROC curve increased from an AUC=0.70 to 0.84 (p<0.01), while the positive predictive value (PPV) and negative predictive value (NPV) also increased from a PPV=0.61 to 0.78 and an NPV=0.65 to 0.75, respectively. This study demonstrates that a multi-feature based BBN can more accurately predict the near-term breast cancer risk than with a single feature.

Theoretical Considerations for Improving the Pulse Power of a Battery through the Addition of a Second Electrochemically Active Material

DOE Office of Scientific and Technical Information (OSTI.GOV)

Knehr, K. W.; West, Alan C.

Here, porous electrode theory is used to conduct case studies for when the addition of a second electrochemically active material can improve the pulse-power performance of an electrode. Case studies are conducted for the positive electrode of a sodium metal-halide battery and the graphite negative electrode of a lithium “rocking chair” battery. The replacement of a fraction of the nickel chloride capacity with iron chloride in a sodium metal-halide electrode and the replacement of a fraction of the graphite capacity with carbon black in a lithium-ion negative electrode were both predicted to increase the maximum pulse power by up tomore » 40%. In general, whether or not a second electrochemically active material increases the pulse power depends on the relative importance of ohmic-to-charge transfer resistances within the porous structure, the capacity fraction of the second electrochemically active material, and the kinetic and thermodynamic parameters of the two active materials.« less

Theoretical Considerations for Improving the Pulse Power of a Battery through the Addition of a Second Electrochemically Active Material

DOE PAGES

Knehr, K. W.; West, Alan C.

2016-05-26

Here, porous electrode theory is used to conduct case studies for when the addition of a second electrochemically active material can improve the pulse-power performance of an electrode. Case studies are conducted for the positive electrode of a sodium metal-halide battery and the graphite negative electrode of a lithium “rocking chair” battery. The replacement of a fraction of the nickel chloride capacity with iron chloride in a sodium metal-halide electrode and the replacement of a fraction of the graphite capacity with carbon black in a lithium-ion negative electrode were both predicted to increase the maximum pulse power by up tomore » 40%. In general, whether or not a second electrochemically active material increases the pulse power depends on the relative importance of ohmic-to-charge transfer resistances within the porous structure, the capacity fraction of the second electrochemically active material, and the kinetic and thermodynamic parameters of the two active materials.« less

The Increasing Effects of Computers on Education.

ERIC Educational Resources Information Center

Gannon, John F.

Predicting that the teaching-learning process in American higher education is about to change drastically because of continuing innovations in computer-assisted technology, this paper argues that this change will be driven by inexpensive but powerful computer technology, and that it will manifest itself by reducing the traditional timing of…

Translating Learning into Numbers: A Generic Framework for Learning Analytics

ERIC Educational Resources Information Center

Greller, Wolfgang; Drachsler, Hendrik

2012-01-01

With the increase in available educational data, it is expected that Learning Analytics will become a powerful means to inform and support learners, teachers and their institutions in better understanding and predicting personal learning needs and performance. However, the processes and requirements behind the beneficial application of Learning…

Data Credibility: A Perspective from Systematic Reviews in Environmental Management

ERIC Educational Resources Information Center

Pullin, Andrew S.; Knight, Teri M.

2009-01-01

To use environmental program evaluation to increase effectiveness, predictive power, and resource allocation efficiency, evaluators need good data. Data require sufficient credibility in terms of fitness for purpose and quality to develop the necessary evidence base. The authors examine elements of data credibility using experience from critical…

Predictions of the near edge transport shortfall in DIII-D L-mode plasmas using the trapped gyro-Landau-fluid model [Predictions of the near edge transport shortfall in DIII-D L-mode plasmas using the TGLF model

DOE PAGES

Kinsey, Jon E.; Staebler, Gary M.; Candy, Jefferey M.; ...

2015-01-14

Previous studies of DIII-D L-mode plasmas have shown that a transport shortfall exists in that our current models of turbulent transport can significantly underestimate the energy transport in the near edge region. In this paper, the Trapped Gyro-Landau-Fluid (TGLF) drift wave transport model is used to simulate the near edge transport in a DIII-D L-mode experiment designed to explore the impact of varying the safety factor on the shortfall. We find that the shortfall systematically increases with increasing safety factor and is more pronounced for the electrons than for the ions. Within the shortfall dataset, a single high current casemore » has been found where no transport shortfall is predicted. Reduced neutral beam injection power has been identified as the key parameter separating this discharge from other discharges exhibiting a shortfall. Further analysis shows that the energy transport in the L-mode near edge region is not stiff according to TGLF. Unlike the H-mode core region, the predicted temperature profiles are relatively more responsive to changes in auxiliary heating power. In testing the fidelity of TGLF for the near edge region, we find that a recalibration of the collision model is warranted. A recalibration improves agreement between TGLF and nonlinear gyrokinetic simulations performed using the GYRO code with electron-ion collisions. As a result, the recalibration only slightly impacts the predicted shortfall.« less

Relationship Power, Sexual Decision Making, and HIV Risk Among Midlife and Older Women.

PubMed

Altschuler, Joanne; Rhee, Siyon

2015-01-01

The number of midlife and older women with HIV/AIDS is high and increasing, especially among women of color. This article addresses these demographic realities by reporting on findings about self-esteem, relationship power, and HIV risk from a pilot study of midlife and older women. A purposive sample (N = 110) of ethnically, economically, and educationally diverse women 40 years and older from the Greater Los Angeles Area was surveyed to determine their levels of self-esteem, general relationship power, sexual decision-making power, safer sex behaviors, and HIV knowledge. Women with higher levels of self-esteem exercised greater power in their relationships with their partner. Women with higher levels of general relationship power and self-esteem tend to exercise greater power in sexual decision making, such as having sex and choosing sexual acts. Income and sexual decision-making power were statistically significant in predicting the use of condoms. Implications and recommendations for future HIV/AIDS research and intervention targeting midlife and older women are presented.

Use of a machine learning algorithm to classify expertise: analysis of hand motion patterns during a simulated surgical task.

PubMed

Watson, Robert A

2014-08-01

To test the hypothesis that machine learning algorithms increase the predictive power to classify surgical expertise using surgeons' hand motion patterns. In 2012 at the University of North Carolina at Chapel Hill, 14 surgical attendings and 10 first- and second-year surgical residents each performed two bench model venous anastomoses. During the simulated tasks, the participants wore an inertial measurement unit on the dorsum of their dominant (right) hand to capture their hand motion patterns. The pattern from each bench model task performed was preprocessed into a symbolic time series and labeled as expert (attending) or novice (resident). The labeled hand motion patterns were processed and used to train a Support Vector Machine (SVM) classification algorithm. The trained algorithm was then tested for discriminative/predictive power against unlabeled (blinded) hand motion patterns from tasks not used in the training. The Lempel-Ziv (LZ) complexity metric was also measured from each hand motion pattern, with an optimal threshold calculated to separately classify the patterns. The LZ metric classified unlabeled (blinded) hand motion patterns into expert and novice groups with an accuracy of 70% (sensitivity 64%, specificity 80%). The SVM algorithm had an accuracy of 83% (sensitivity 86%, specificity 80%). The results confirmed the hypothesis. The SVM algorithm increased the predictive power to classify blinded surgical hand motion patterns into expert versus novice groups. With further development, the system used in this study could become a viable tool for low-cost, objective assessment of procedural proficiency in a competency-based curriculum.

Numerical analysis of radial inward flow turbine for CO2 based closed loop Brayton cycle

NASA Astrophysics Data System (ADS)

Kisan, Jadhav Amit; Govardhan, M.

2017-06-01

Last few decades have witnessed a phenomenal growth in the demand for power, which has driven the suppliers to find new sources of energy and increase the efficiency of power generation process. Power generation cycles are either steam based Rankine cycle or closed loop Brayton cycles providing an efficiency of 30 to 40%. An upcoming technology in this regard is the CO2 based Brayton cycle operating near the critical region which has applications in vast areas. Power generation of CO2 based Brayton cycle can vary from few kilowatts for waste heat recovery to hundreds of megawatts in sodium cooled fast reactors. A CO2 based Brayton cycle is being studied for power generation especially in mid-sized concentrated solar power plants by numerous research groups around the world. One of the main components of such a setting is its turbine. Simulating the flow conditions inside the turbine becomes very crucial in order to accurately predict the performance of the system. The flow inside radial inflow turbine is studied at various inlet temperatures and mass flow rates in order to predict the behavior of the turbine under various boundary conditions. The performance investigation of the turbine system is done on the basis of parameters such as total efficiency, pressure ratio, and power coefficient. Effect of different inlet stagnation temperature and exit mass flow rates on these parameters is also studied. Results obtained are encouraging for the use of CO2 as working fluid in Brayton cycle.

POWER/SSE Web Access Data

Atmospheric Science Data Center

2018-06-25

Description:  Obtain Prediction of Worldwide Energy Resource (POWER) data The Prediction of Worldwide Energy ... (POWER) project was initiated to improve upon the current renewable energy data set and to create new data sets from new satellite ...

Ensemble Data Assimilation of Photovoltaic Power Information in the Convection-permitting High-Resolution Model COSMO-DE

NASA Astrophysics Data System (ADS)

Declair, Stefan; Saint-Drenan, Yves-Marie; Potthast, Roland

2017-04-01

Determining the amount of weather dependent renewable energy is a demanding task for transmission system operators (TSOs) and wind and photovoltaic (PV) prediction errors require the use of reserve power, which generate costs and can - in extreme cases - endanger the security of supply. In the project EWeLiNE funded by the German government, the German Weather Service and the Fraunhofer Institute on Wind Energy and Energy System Technology develop innovative weather- and power forecasting models and tools for grid integration of weather dependent renewable energy. The key part in energy prediction process chains is the numerical weather prediction (NWP) system. Irradiation forecasts from NWP systems are however subject to several sources of error. For PV power prediction, weaknesses of the NWP model to correctly forecast i.e. low stratus, absorption of condensed water or aerosol optical depths are the main sources of errors. Inaccurate radiation schemes (i.e. the two-stream parametrization) are also known as a deficit of NWP systems with regard to irradiation forecast. To mitigate errors like these, latest observations can be used in a pre-processing technique called data assimilation (DA). In DA, not only the initial fields are provided, but the model is also synchronized with reality - the observations - and hence forecast errors are reduced. Besides conventional observation networks like radiosondes, synoptic observations or air reports of wind, pressure and humidity, the number of observations measuring meteorological information indirectly by means of remote sensing such as satellite radiances, radar reflectivities or GPS slant delays strongly increases. Numerous PV plants installed in Germany potentially represent a dense meteorological network assessing irradiation through their power measurements. Forecast accuracy may thus be enhanced by extending the observations in the assimilation by this new source of information. PV power plants can provide information on clouds, aerosol optical depth or low stratus in terms of remote sensing: the power output is strongly dependent on perturbations along the slant between sun position and PV panel. Since these data are not limited to the vertical column above or below the detector, it may thus complement satellite data and compensate weaknesses in the radiation scheme. In this contribution, the used DA technique (Local Ensemble Transform Kalman Filter, LETKF) is shortly sketched. Furthermore, the computation of the model power equivalents is described and first results are presented and discussed.

Development and Application of Advanced Weather Prediction Technologies for the Wind Energy Industry (Invited)

NASA Astrophysics Data System (ADS)

Mahoney, W. P.; Wiener, G.; Liu, Y.; Myers, W.; Johnson, D.

2010-12-01

Wind energy decision makers are required to make critical judgments on a daily basis with regard to energy generation, distribution, demand, storage, and integration. Accurate knowledge of the present and future state of the atmosphere is vital in making these decisions. As wind energy portfolios expand, this forecast problem is taking on new urgency because wind forecast inaccuracies frequently lead to substantial economic losses and constrain the national expansion of renewable energy. Improved weather prediction and precise spatial analysis of small-scale weather events are crucial for renewable energy management. In early 2009, the National Center for Atmospheric Research (NCAR) began a collaborative project with Xcel Energy Services, Inc. to perform research and develop technologies to improve Xcel Energy's ability to increase the amount of wind energy in their generation portfolio. The agreement and scope of work was designed to provide highly detailed, localized wind energy forecasts to enable Xcel Energy to more efficiently integrate electricity generated from wind into the power grid. The wind prediction technologies are designed to help Xcel Energy operators make critical decisions about powering down traditional coal and natural gas-powered plants when sufficient wind energy is predicted. The wind prediction technologies have been designed to cover Xcel Energy wind resources spanning a region from Wisconsin to New Mexico. The goal of the project is not only to improve Xcel Energy’s wind energy prediction capabilities, but also to make technological advancements in wind and wind energy prediction, expand our knowledge of boundary layer meteorology, and share the results across the renewable energy industry. To generate wind energy forecasts, NCAR is incorporating observations of current atmospheric conditions from a variety of sources including satellites, aircraft, weather radars, ground-based weather stations, wind profilers, and even wind sensors on individual wind turbines. The information is utilized by several technologies including: a) the Weather Research and Forecasting (WRF) model, which generates finely detailed simulations of future atmospheric conditions, b) the Real-Time Four-Dimensional Data Assimilation System (RTFDDA), which performs continuous data assimilation providing the WRF model with continuous updates of the initial atmospheric state, 3) the Dynamic Integrated Forecast System (DICast®), which statistically optimizes the forecasts using all predictors, and 4) a suite of wind-to-power algorithms that convert wind speed to power for a wide range of wind farms with varying real-time data availability capabilities. In addition to these core wind energy prediction capabilities, NCAR implemented a high-resolution (10 km grid increment) 30-member ensemble RTFDDA prediction system that provides information on the expected range of wind power over a 72-hour forecast period covering Xcel Energy’s service areas. This talk will include descriptions of these capabilities and report on several topics including initial results of next-day forecasts and nowcasts of wind energy ramp events, influence of local observations on forecast skill, and overall lessons learned to date.

Impact of the 4 April 2014 Saharan dust outbreak on the photovoltaic power generation in Germany

NASA Astrophysics Data System (ADS)

Rieger, Daniel; Steiner, Andrea; Bachmann, Vanessa; Gasch, Philipp; Förstner, Jochen; Deetz, Konrad; Vogel, Bernhard; Vogel, Heike

2017-11-01

The importance for reliable forecasts of incoming solar radiation is growing rapidly, especially for those countries with an increasing share in photovoltaic (PV) power production. The reliability of solar radiation forecasts depends mainly on the representation of clouds and aerosol particles absorbing and scattering radiation. Especially under extreme aerosol conditions, numerical weather prediction has a systematic bias in the solar radiation forecast. This is caused by the design of numerical weather prediction models, which typically account for the direct impact of aerosol particles on radiation using climatological mean values and the impact on cloud formation assuming spatially and temporally homogeneous aerosol concentrations. These model deficiencies in turn can lead to significant economic losses under extreme aerosol conditions. For Germany, Saharan dust outbreaks occurring 5 to 15 times per year for several days each are prominent examples for conditions, under which numerical weather prediction struggles to forecast solar radiation adequately. We investigate the impact of mineral dust on the PV-power generation during a Saharan dust outbreak over Germany on 4 April 2014 using ICON-ART, which is the current German numerical weather prediction model extended by modules accounting for trace substances and related feedback processes. We find an overall improvement of the PV-power forecast for 65 % of the pyranometer stations in Germany. Of the nine stations with very high differences between forecast and measurement, eight stations show an improvement. Furthermore, we quantify the direct radiative effects and indirect radiative effects of mineral dust. For our study, direct effects account for 64 %, indirect effects for 20 % and synergistic interaction effects for 16 % of the differences between the forecast including mineral dust radiative effects and the forecast neglecting mineral dust.

End-of-Discharge and End-of-Life Prediction in Lithium-Ion Batteries with Electrochemistry-Based Aging Models

NASA Technical Reports Server (NTRS)

Daigle, Matthew; Kulkarni, Chetan S.

2016-01-01

As batteries become increasingly prevalent in complex systems such as aircraft and electric cars, monitoring and predicting battery state of charge and state of health becomes critical. In order to accurately predict the remaining battery power to support system operations for informed operational decision-making, age-dependent changes in dynamics must be accounted for. Using an electrochemistry-based model, we investigate how key parameters of the battery change as aging occurs, and develop models to describe aging through these key parameters. Using these models, we demonstrate how we can (i) accurately predict end-of-discharge for aged batteries, and (ii) predict the end-of-life of a battery as a function of anticipated usage. The approach is validated through an experimental set of randomized discharge profiles.

Origin and Consequences of the Relationship between Protein Mean and Variance

PubMed Central

Vallania, Francesco Luigi Massimo; Sherman, Marc; Goodwin, Zane; Mogno, Ilaria; Cohen, Barak Alon; Mitra, Robi David

2014-01-01

Cell-to-cell variance in protein levels (noise) is a ubiquitous phenomenon that can increase fitness by generating phenotypic differences within clonal populations of cells. An important challenge is to identify the specific molecular events that control noise. This task is complicated by the strong dependence of a protein's cell-to-cell variance on its mean expression level through a power-law like relationship (σ2∝μ1.69). Here, we dissect the nature of this relationship using a stochastic model parameterized with experimentally measured values. This framework naturally recapitulates the power-law like relationship (σ2∝μ1.6) and accurately predicts protein variance across the yeast proteome (r2 = 0.935). Using this model we identified two distinct mechanisms by which protein variance can be increased. Variables that affect promoter activation, such as nucleosome positioning, increase protein variance by changing the exponent of the power-law relationship. In contrast, variables that affect processes downstream of promoter activation, such as mRNA and protein synthesis, increase protein variance in a mean-dependent manner following the power-law. We verified our findings experimentally using an inducible gene expression system in yeast. We conclude that the power-law-like relationship between noise and protein mean is due to the kinetics of promoter activation. Our results provide a framework for understanding how molecular processes shape stochastic variation across the genome. PMID:25062021

Effects of temperature and pressure on the performance of a solid oxide fuel cell running on steam reformate of kerosene

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chick, Lawrence A.; Marina, Olga A.; Coyle, Christopher A.

2013-08-15

A button solid oxide fuel cell with a La0.6Sr0.4Co0.2Fe0.8O3 cathode and a nickel-YSZ anode was tested over a range of temperatures from 650 to 800°C and a range of pressures from 101 to 724 kPa. The fuel was simulated steam-reformed kerosene and the oxidant was air. The observed increases in open circuit voltages (OCV) were accurately predicted by the Nernst equation. Kinetics also increased, although the power boost due to kinetics was about two thirds as large as the boost due to OCV. The total power boost in going from 101 to 724 kPa at 750°C and 0.8 volts wasmore » 66%. Impedance spectroscopy demonstrated a significant decrease in electrodic losses at elevated pressures. Complex impedance spectra were dominated by a combination of low frequency processes that decreased markedly with increasing pressure. A composite of high-frequency processes also decreased with pressure, but to a lesser extent. An empirical algorithm that accurately predicts the increased fuel cell performance at elevated pressures was developed for our results and was also suitable for some, but not all, data reported in the literature.« less

Complete set of deuteron analyzing powers from d ⃗p elastic scattering at 190 MeV/nucleon

NASA Astrophysics Data System (ADS)

Sekiguchi, K.; Witała, H.; Akieda, T.; Eto, D.; Kon, H.; Wada, Y.; Watanabe, A.; Chebotaryov, S.; Dozono, M.; Golak, J.; Kamada, H.; Kawakami, S.; Kubota, Y.; Maeda, Y.; Miki, K.; Milman, E.; Ohkura, A.; Sakai, H.; Sakaguchi, S.; Sakamoto, N.; Sasano, M.; Shindo, Y.; Skibiński, R.; Suzuki, H.; Tabata, M.; Uesaka, T.; Wakasa, T.; Yako, K.; Yamamoto, T.; Yanagisawa, Y.; Yasuda, J.

2017-12-01

All deuteron analyzing powers for elastic deuteron-proton (d p ) scattering have been measured with a polarized deuteron beam at 186.6 MeV/nucleon. They are compared with results of three-nucleon Faddeev calculations based on the standard, high-precision nucleon-nucleon (N N ) potentials alone or combined with commonly used three-nucleon force (3 N F ) models such as the Tucson-Melbourne '99 or the Urbana IX. Predicted 3 N F effects localized at backward angles are supported only partially by the data. The data are also compared to predictions based on locally regularized chiral N N potentials. An estimation of theoretical truncation uncertainties in the consecutive orders of chiral expansion suggests that the observed discrepancies between this modern theory and the data could probably be explained by including chiral 3 N F 's in future calculations. A systematic comparison to the deuteron analyzing power data previously taken at incident energies from 70 to 294 MeV/nucleon clearly shows that not only the cross section but also the analyzing powers reveal growing 3 N F effects when the three-nucleon system energy is increased.

Method for predicting water demand for crop uses in New Jersey in 1990, 2000, 2010, and 2020, and for estimating water use for livestock and selected sectors of the food-processing industry in New Jersey in 1987

USGS Publications Warehouse

Clawges, R.M.; Titus, E.O.

1993-01-01

A method was developed to predict water demand for crop uses in New Jersey. A separate method was developed to estimate water use for livestock and selected sectors of the food-processing industry in 1987. Predictions of water demand for field- grown crops in New Jersey were made for 1990, 2000, 2010, and 2020 under three climatological scenarios: (1) wet year, (2) average year, and (3) drought year. These estimates ranged from 4.10 times 10 to the 9th power to 16.82 times 10 to the 9th power gal (gallons). Irrigation amounts calculated for the three climatological scenarios by using a daily water-balance model were multiplied by predicted numbers of irrigated acreage. Irrigated acreage was predicted from historical crop-irrigation data and from predictions of harvested acreage produced by using a statistical model relating population to harvested acreage. Predictions of water demand for cranberries and container-grown nursery crops also were made for 1990, 2000, 2010, and 2020. Predictions of water demand under the three climatological scenarios were made for container- grown nursery crops, but not for cranberries, because water demand for cranberries varies little in response to climatological factors. Water demand for cranberries was predicted to remain constant at 4.43 times 10 to the 9th power gal through the year 2020. Predictions of water demand for container-grown nursery crops ranged from 1.89 times 10 to the 9th power to 3.63 times 10 to the 9th power gal. Water-use for livestock in 1987 was estimated to be 0.78 times 10 to the 9th power gal, and water use for selected sectors of the food-processing industry was estimated to be 3.75 times 10 to the 9th power gal.

Cardiovascular performance of adult breeding sows fails to obey allometric scaling laws.

PubMed

van Essen, G J; Vernooij, J C M; Heesterbeek, J A P; Anjema, D; Merkus, D; Duncker, D J

2011-02-01

In view of the remarkable decrease of the relative heart weight (HW) and the relative blood volume in growing pigs, we investigated whether HW, cardiac output (CO), and stroke volume (SV) of modern growing pigs are proportional to BW, as predicted by allometric scaling laws: HW (or CO or SV) = a·BW(b), in which a and b are constants, and constant b is a multiple of 0.25 (quarter-power scaling law). Specifically, we tested the hypothesis that both HW and CO scale with BW to the power of 0.75 (HW or CO = a·BW(0.75)) and SV scales with BW to the power of 1.00 (SV = a·BW(1.0)). For this purpose, 2 groups of pigs (group 1, consisting of 157 pigs of 50 ± 1 kg; group 2, consisting of 45 pigs of 268 ± 18 kg) were surgically instrumented with a flow probe or a thermodilution dilution catheter, under open-chest anesthetized conditions to measure CO and SV, after which HW was determined. The 95% confidence intervals of power-coefficient b for HW were 0.74 to 0.80, encompassing the predicted value of 0.75, suggesting that HW increased proportionally with BW, as predicted by the allometric scaling laws. In contrast, the 95% confidence intervals of power-coefficient b for CO and SV as measured with flow probes were 0.40 to 0.56 and 0.39 to 0.61, respectively, and values obtained with the thermodilution technique were 0.34 to 0.53 and 0.40 to 0.62, respectively. Thus, the 95% confidence limits failed to encompass the predicted values of b for CO and SV of 0.75 and 1.0, respectively. In conclusion, although adult breeding sows display normal heart growth, cardiac performance appears to be disproportionately low for BW. This raises concern regarding the health status of adult breeding sows.

Hurricane destructive power predictions based on historical storm and sea surface temperature data.

PubMed

Bogen, Kenneth T; Jones, Edwin D; Fischer, Larry E

2007-12-01

Forecasting destructive hurricane potential is complicated by substantial, unexplained intraannual variation in storm-specific power dissipation index (PDI, or integrated third power of wind speed), and interannual variation in annual accumulated PDI (APDI). A growing controversy concerns the recent hypothesis that the clearly positive trend in North Atlantic Ocean (NAO) sea surface temperature (SST) since 1970 explains increased hurricane intensities over this period, and so implies ominous PDI and APDI growth as global warming continues. To test this "SST hypothesis" and examine its quantitative implications, a combination of statistical and probabilistic methods were applied to National Hurricane Center HURDAT best-track data on NAO hurricanes during 1880-2002, and corresponding National Oceanographic and Atmospheric Administration Extended Reconstruction SST estimates. Notably, hurricane behavior was compared to corresponding hurricane-specific (i.e., spatiotemporally linked) SST; previous similar comparisons considered only SST averaged over large NAO regions. Contrary to the SST hypothesis, SST was found to vary in a monthly pattern inconsistent with that of corresponding PDI, and to be at best weakly associated with PDI or APDI despite strong correlation with corresponding mean latitude (R(2)= 0.55) or with combined mean location and a approximately 90-year periodic trend (R(2)= 0.70). Over the last century, the lower 75% of APDIs appear randomly sampled from a nearly uniform distribution, and the upper 25% of APDIs from a nearly lognormal distribution. From the latter distribution, a baseline (SST-independent) stochastic model was derived predicting that over the next half century, APDI will not likely exceed its maximum value over the last half century by more than a factor of 1.5. This factor increased to 2 using a baseline model modified to assume SST-dependence conditioned on an upper bound of the increasing NAO SST trend observed since 1970. An additional model was developed that predicts PDI statistics conditional on APDI. These PDI and APDI models can be used to estimate upper bounds on indices of hurricane power likely to be realized over the next century, under divergent assumptions regarding SST influence.

Fluid-Plasma-Combustion Coupling Effects on the Ignition of a Fuel Jet

NASA Astrophysics Data System (ADS)

Massa, Luca; Freund, Jonathan

2016-11-01

We analyze the effect of plasma-combustion coupling on the ignition and flame supported by a DBD interacting with a jet of H2 in a air cross-flow. We propose that plasma-combustion coupling is due to the strong temperature-dependence of specific collisional energy loss as predicted by the Boltzmann equation, and that e- transport can be modeled by assuming a form for the E-field pulse in microstreamers. We introduce a two-way coupling based on the Boltzmann equation and the charged species conservation. The addition of this mechanism to a hydrogen combustion scheme leads to an improvement of the ignition prediction and of the understanding of the effect of the plasma on the flow. The key points of the analysis are 1) explanation of the mechanism for the two-stage ignition and quenching observed experimentally, 2) explanation of the existence of a power threshold above which the plasma is beneficial to the ignition probability, 3) understanding of the increase in power absorbed by the plasma in burning conditions and the reduction in power absorbed with an increase in the cross velocity, 4) explanation of the non-symmetric emissions and the increase in luminescence at the rotovibrational H2O band. The model is validated in part against air-H2 flow experiments. This material is based in part upon work supported by the Department of Energy, National Nuclear Security Administration, under Award Number DE-NA0002374.

Corneal power evaluation after myopic corneal refractive surgery using artificial neural networks.

PubMed

Koprowski, Robert; Lanza, Michele; Irregolare, Carlo

2016-11-15

Efficacy and high availability of surgery techniques for refractive defect correction increase the number of patients who undergo to this type of surgery. Regardless of that, with increasing age, more and more patients must undergo cataract surgery. Accurate evaluation of corneal power is an extremely important element affecting the precision of intraocular lens (IOL) power calculation and errors in this procedure could affect quality of life of patients and satisfaction with the service provided. The available device able to measure corneal power have been tested to be not reliable after myopic refractive surgery. Artificial neural networks with error backpropagation and one hidden layer were proposed for corneal power prediction. The article analysed the features acquired from the Pentacam HR tomograph, which was necessary to measure the corneal power. Additionally, several billion iterations of artificial neural networks were conducted for several hundred simulations of different network configurations and different features derived from the Pentacam HR. The analysis was performed on a PC with Intel ® Xeon ® X5680 3.33 GHz CPU in Matlab ® Version 7.11.0.584 (R2010b) with Signal Processing Toolbox Version 7.1 (R2010b), Neural Network Toolbox 7.0 (R2010b) and Statistics Toolbox (R2010b). A total corneal power prediction error was obtained for 172 patients (113 patients forming the training set and 59 patients in the test set) with an average age of 32 ± 9.4 years, including 67% of men. The error was at an average level of 0.16 ± 0.14 diopters and its maximum value did not exceed 0.75 dioptres. The Pentacam parameters (measurement results) providing the above result are tangential anterial/posterior. The corneal net power and equivalent k-reading power. The analysis time for a single patient (a single eye) did not exceed 0.1 s, whereas the time of network training was about 3 s for 1000 iterations (the number of neurons in the hidden layer was 400).

Comparison of Non-Parabolic Hydrodynamic Simulations for Semiconductor Devices

NASA Technical Reports Server (NTRS)

Smith, A. W.; Brennan, K. F.

1996-01-01

Parabolic drift-diffusion simulators are common engineering level design tools for semiconductor devices. Hydrodynamic simulators, based on the parabolic band approximation, are becoming more prevalent as device dimensions shrink and energy transport effects begin to dominate device characteristic. However, band structure effects present in state-of-the-art devices necessitate relaxing the parabolic band approximation. This paper presents simulations of ballistic diodes, a benchmark device, of Si and GaAs using two different non-parabolic hydrodynamic formulations. The first formulation uses the Kane dispersion relationship in the derivation of the conservation equations. The second model uses a power law dispersion relation {(hk)(exp 2)/2m = xW(exp Y)}. Current-voltage relations show that for the ballistic diodes considered. the non-parabolic formulations predict less current than the parabolic case. Explanations of this will be provided by examination of velocity and energy profiles. At low bias, the simulations based on the Kane formulation predict greater current flow than the power law formulation. As the bias is increased this trend changes and the power law predicts greater current than the Kane formulation. It will be shown that the non-parabolicity and energy range of the hydrodynamic model based on the Kane dispersion relation are limited due to the binomial approximation which was utilized in the derivation.

The Predictive Effects of Protection Motivation Theory on Intention and Behaviour of Physical Activity in Patients with Type 2 Diabetes.

PubMed

Ali Morowatisharifabad, Mohammad; Abdolkarimi, Mahdi; Asadpour, Mohammad; Fathollahi, Mahmood Sheikh; Balaee, Parisa

2018-04-15

Theory-based education tailored to target behaviour and group can be effective in promoting physical activity. The purpose of this study was to examine the predictive power of Protection Motivation Theory on intent and behaviour of Physical Activity in Patients with Type 2 Diabetes. This descriptive study was conducted on 250 patients in Rafsanjan, Iran. To examine the scores of protection motivation theory structures, a researcher-made questionnaire was used. Its validity and reliability were confirmed. The level of physical activity was also measured by the International Short - form Physical Activity Inventory. Its validity and reliability were also approved. Data were analysed by statistical tests including correlation coefficient, chi-square, logistic regression and linear regression. The results revealed that there was a significant correlation between all the protection motivation theory constructs and the intention to do physical activity. The results showed that the Theory structures were able to predict 60% of the variance of physical activity intention. The results of logistic regression demonstrated that increase in the score of physical activity intent and self - efficacy increased the chance of higher level of physical activity by 3.4 and 1.5 times, respectively OR = (3.39, 1.54). Considering the ability of protection motivation theory structures to explain the physical activity behaviour, interventional designs are suggested based on the structures of this theory, especially to improve self -efficacy as the most powerful factor in predicting physical activity intention and behaviour.

Application of clustering analysis in the prediction of photovoltaic power generation based on neural network

NASA Astrophysics Data System (ADS)

Cheng, K.; Guo, L. M.; Wang, Y. K.; Zafar, M. T.

2017-11-01

In order to select effective samples in the large number of data of PV power generation years and improve the accuracy of PV power generation forecasting model, this paper studies the application of clustering analysis in this field and establishes forecasting model based on neural network. Based on three different types of weather on sunny, cloudy and rainy days, this research screens samples of historical data by the clustering analysis method. After screening, it establishes BP neural network prediction models using screened data as training data. Then, compare the six types of photovoltaic power generation prediction models before and after the data screening. Results show that the prediction model combining with clustering analysis and BP neural networks is an effective method to improve the precision of photovoltaic power generation.

Universal Inverse Power-Law Distribution for Fractal Fluctuations in Dynamical Systems: Applications for Predictability of Inter-Annual Variability of Indian and USA Region Rainfall

NASA Astrophysics Data System (ADS)

Selvam, A. M.

2017-01-01

Dynamical systems in nature exhibit self-similar fractal space-time fluctuations on all scales indicating long-range correlations and, therefore, the statistical normal distribution with implicit assumption of independence, fixed mean and standard deviation cannot be used for description and quantification of fractal data sets. The author has developed a general systems theory based on classical statistical physics for fractal fluctuations which predicts the following. (1) The fractal fluctuations signify an underlying eddy continuum, the larger eddies being the integrated mean of enclosed smaller-scale fluctuations. (2) The probability distribution of eddy amplitudes and the variance (square of eddy amplitude) spectrum of fractal fluctuations follow the universal Boltzmann inverse power law expressed as a function of the golden mean. (3) Fractal fluctuations are signatures of quantum-like chaos since the additive amplitudes of eddies when squared represent probability densities analogous to the sub-atomic dynamics of quantum systems such as the photon or electron. (4) The model predicted distribution is very close to statistical normal distribution for moderate events within two standard deviations from the mean but exhibits a fat long tail that are associated with hazardous extreme events. Continuous periodogram power spectral analyses of available GHCN annual total rainfall time series for the period 1900-2008 for Indian and USA stations show that the power spectra and the corresponding probability distributions follow model predicted universal inverse power law form signifying an eddy continuum structure underlying the observed inter-annual variability of rainfall. On a global scale, man-made greenhouse gas related atmospheric warming would result in intensification of natural climate variability, seen immediately in high frequency fluctuations such as QBO and ENSO and even shorter timescales. Model concepts and results of analyses are discussed with reference to possible prediction of climate change. Model concepts, if correct, rule out unambiguously, linear trends in climate. Climate change will only be manifested as increase or decrease in the natural variability. However, more stringent tests of model concepts and predictions are required before applications to such an important issue as climate change. Observations and simulations with climate models show that precipitation extremes intensify in response to a warming climate (O'Gorman in Curr Clim Change Rep 1:49-59, 2015).

Radial evolution of power spectra of interplanetary Alfvenic turbulence

NASA Technical Reports Server (NTRS)

Bavassano, B.; Dobrowolny, M.; Mariani, F.; Ness, N. F.

1981-01-01

The radial evolution of the power spectra of the MHD turbulence within the trailing edge of high speed streams in the solar wind was investigated with the magnetic field data of Helios 1 and 2 for heliocentric distance between 0.3 and 0.9 AU. In the analyzed frequency range (.00028 Hz to .0083 Hz) the computed spectra have, near the Earth, values of the spectral index close to that predicted for an incompressible hydromagnetic turbulence in a stationary state. Approaching the Sun the spectral slope remains unchanged for frequencies f or approximately .00 Hz, whereas at lower frequencies, a clear evolution toward a less steep fall off with frequency is found. The radial gradient of the power in Alfvenic fluctuations depends on frequency and it increases upon increasing frequency. For frequencies f or approximately .00 Hz, however, the radial gradient remains approximately the same. Possible theoretical implications of the observational features are discussed.

Warped linear mixed models for the genetic analysis of transformed phenotypes

PubMed Central

Fusi, Nicolo; Lippert, Christoph; Lawrence, Neil D.; Stegle, Oliver

2014-01-01

Linear mixed models (LMMs) are a powerful and established tool for studying genotype–phenotype relationships. A limitation of the LMM is that the model assumes Gaussian distributed residuals, a requirement that rarely holds in practice. Violations of this assumption can lead to false conclusions and loss in power. To mitigate this problem, it is common practice to pre-process the phenotypic values to make them as Gaussian as possible, for instance by applying logarithmic or other nonlinear transformations. Unfortunately, different phenotypes require different transformations, and choosing an appropriate transformation is challenging and subjective. Here we present an extension of the LMM that estimates an optimal transformation from the observed data. In simulations and applications to real data from human, mouse and yeast, we show that using transformations inferred by our model increases power in genome-wide association studies and increases the accuracy of heritability estimation and phenotype prediction. PMID:25234577

Warped linear mixed models for the genetic analysis of transformed phenotypes.

PubMed

Fusi, Nicolo; Lippert, Christoph; Lawrence, Neil D; Stegle, Oliver

2014-09-19

Linear mixed models (LMMs) are a powerful and established tool for studying genotype-phenotype relationships. A limitation of the LMM is that the model assumes Gaussian distributed residuals, a requirement that rarely holds in practice. Violations of this assumption can lead to false conclusions and loss in power. To mitigate this problem, it is common practice to pre-process the phenotypic values to make them as Gaussian as possible, for instance by applying logarithmic or other nonlinear transformations. Unfortunately, different phenotypes require different transformations, and choosing an appropriate transformation is challenging and subjective. Here we present an extension of the LMM that estimates an optimal transformation from the observed data. In simulations and applications to real data from human, mouse and yeast, we show that using transformations inferred by our model increases power in genome-wide association studies and increases the accuracy of heritability estimation and phenotype prediction.

Weather conditions and visits to the medical wing of emergency rooms in a metropolitan area during the warm season in Israel: a predictive model

NASA Astrophysics Data System (ADS)

Novikov, Ilya; Kalter-Leibovici, Ofra; Chetrit, Angela; Stav, Nir; Epstein, Yoram

2012-01-01

Global climate changes affect health and present new challenges to healthcare systems. The aim of the present study was to analyze the pattern of visits to the medical wing of emergency rooms (ERs) in public hospitals during warm seasons, and to develop a predictive model that will forecast the number of visits to ERs 2 days ahead. Data on daily visits to the ERs of the four largest medical centers in the Tel-Aviv metropolitan area during the warm months of the year (April-October, 2001-2004), the corresponding daily meteorological data, daily electrical power consumption (a surrogate marker for air-conditioning), air-pollution parameters, and calendar information were obtained and used in the analyses. The predictive model employed a time series analysis with transitional Poisson regression. The concise multivariable model was highly accurate ( r 2 = 0.819). The contribution of mean daily temperature was small but significant: an increase of 1°C in ambient temperature was associated with a 1.47% increase in the number of ER visits ( P < 0.001). An increase in electrical power consumption significantly attenuated the effect of weather conditions on ER visits by 4% per 1,000 MWh ( P < 0.001). Higher daily mean SO2 concentrations were associated with a greater number of ER visits (1% per 1 ppb increment; P = 0.017). Calendar data were the main predictors of ER visits ( r 2 = 0.794). The predictive model was highly accurate in forecasting the number of visits to ERs 2 days ahead. The marginal effect of temperature on the number of ER visits can be attributed to behavioral adaptations, including the use of air-conditioning.

Improved pump turbine transient behaviour prediction using a Thoma number-dependent hillchart model

NASA Astrophysics Data System (ADS)

Manderla, M.; Kiniger, K.; Koutnik, J.

2014-03-01

Water hammer phenomena are important issues for high head hydro power plants. Especially, if several reversible pump-turbines are connected to the same waterways there may be strong interactions between the hydraulic machines. The prediction and coverage of all relevant load cases is challenging and difficult using classical simulation models. On the basis of a recent pump-storage project, dynamic measurements motivate an improved modeling approach making use of the Thoma number dependency of the actual turbine behaviour. The proposed approach is validated for several transient scenarios and turns out to increase correlation between measurement and simulation results significantly. By applying a fully automated simulation procedure broad operating ranges can be covered which provides a consistent insight into critical load case scenarios. This finally allows the optimization of the closing strategy and hence the overall power plant performance.

Maximum predictive power and the superposition principle

NASA Technical Reports Server (NTRS)

Summhammer, Johann

1994-01-01

In quantum physics the direct observables are probabilities of events. We ask how observed probabilities must be combined to achieve what we call maximum predictive power. According to this concept the accuracy of a prediction must only depend on the number of runs whose data serve as input for the prediction. We transform each probability to an associated variable whose uncertainty interval depends only on the amount of data and strictly decreases with it. We find that for a probability which is a function of two other probabilities maximum predictive power is achieved when linearly summing their associated variables and transforming back to a probability. This recovers the quantum mechanical superposition principle.

Lateralization in Alpha-Band Oscillations Predicts the Locus and Spatial Distribution of Attention.

PubMed

Ikkai, Akiko; Dandekar, Sangita; Curtis, Clayton E

2016-01-01

Attending to a task-relevant location changes how neural activity oscillates in the alpha band (8-13Hz) in posterior visual cortical areas. However, a clear understanding of the relationships between top-down attention, changes in alpha oscillations in visual cortex, and attention performance are still poorly understood. Here, we tested the degree to which the posterior alpha power tracked the locus of attention, the distribution of attention, and how well the topography of alpha could predict the locus of attention. We recorded magnetoencephalographic (MEG) data while subjects performed an attention demanding visual discrimination task that dissociated the direction of attention from the direction of a saccade to indicate choice. On some trials, an endogenous cue predicted the target's location, while on others it contained no spatial information. When the target's location was cued, alpha power decreased in sensors over occipital cortex contralateral to the attended visual field. When the cue did not predict the target's location, alpha power again decreased in sensors over occipital cortex, but bilaterally, and increased in sensors over frontal cortex. Thus, the distribution and the topography of alpha reliably indicated the locus of covert attention. Together, these results suggest that alpha synchronization reflects changes in the excitability of populations of neurons whose receptive fields match the locus of attention. This is consistent with the hypothesis that alpha oscillations reflect the neural mechanisms by which top-down control of attention biases information processing and modulate the activity of neurons in visual cortex.

Light aircraft sound transmission studies - Noise reduction model

NASA Technical Reports Server (NTRS)

Atwal, Mahabir S.; Heitman, Karen E.; Crocker, Malcolm J.

1987-01-01

Experimental tests conducted on the fuselage of a single-engine Piper Cherokee light aircraft suggest that the cabin interior noise can be reduced by increasing the transmission loss of the dominant sound transmission paths and/or by increasing the cabin interior sound absorption. The validity of using a simple room equation model to predict the cabin interior sound-pressure level for different fuselage and exterior sound field conditions is also presented. The room equation model is based on the sound power flow balance for the cabin space and utilizes the measured transmitted sound intensity data. The room equation model predictions were considered good enough to be used for preliminary acoustical design studies.

Experimental observations of nonlinearly enhanced 2omega-UH electromagnetic radiation excited by steady-state colliding electron beams

NASA Technical Reports Server (NTRS)

Intrator, T.; Hershkowitz, N.; Chan, C.

1984-01-01

Counterstreaming large-diameter electron beams in a steady-state laboratory experiment are observed to generate transverse radiation at twice the upper-hybrid frequency (2omega-UH) with a quadrupole radiation pattern. The electromagnetic wave power density is nonlinearly enhanced over the power density obtained from a single beam-plasma system. Electromagnetic power density scales exponentially with beam energy and increases with ion mass. Weak turbulence theory can predict similar (but weaker) beam energy scaling but not the high power density, or the predominance of the 2omega-UH radiation peak over the omega-UH peak. Significant noise near the upper-hybrid and ion plasma frequencies is also measured, with normalized electrostatic wave energy density W(ES)/n(e)T(e) approximately 0.01.

Heat pipe cooling of power processing magnetics

NASA Technical Reports Server (NTRS)

Hansen, I. G.; Chester, M.

1979-01-01

The constant demand for increased power and reduced mass has raised the internal temperature of conventionally cooled power magnetics toward the upper limit of acceptability. The conflicting demands of electrical isolation, mechanical integrity, and thermal conductivity preclude significant further advancements using conventional approaches. However, the size and mass of multikilowatt power processing systems may be further reduced by the incorporation of heat pipe cooling directly into the power magnetics. Additionally, by maintaining lower more constant temperatures, the life and reliability of the magnetic devices will be improved. A heat pipe cooled transformer and input filter have been developed for the 2.4 kW beam supply of a 30-cm ion thruster system. This development yielded a mass reduction of 40% (1.76 kg) and lower mean winding temperature (20 C lower). While these improvements are significant, preliminary designs predict even greater benefits to be realized at higher power. This paper presents the design details along with the results of thermal vacuum operation and the component performance in a 3 kW breadboard power processor.

Frontal Theta Reflects Uncertainty and Unexpectedness during Exploration and Exploitation

PubMed Central

Figueroa, Christina M.; Cohen, Michael X; Frank, Michael J.

2012-01-01

In order to understand the exploitation/exploration trade-off in reinforcement learning, previous theoretical and empirical accounts have suggested that increased uncertainty may precede the decision to explore an alternative option. To date, the neural mechanisms that support the strategic application of uncertainty-driven exploration remain underspecified. In this study, electroencephalography (EEG) was used to assess trial-to-trial dynamics relevant to exploration and exploitation. Theta-band activities over middle and lateral frontal areas have previously been implicated in EEG studies of reinforcement learning and strategic control. It was hypothesized that these areas may interact during top-down strategic behavioral control involved in exploratory choices. Here, we used a dynamic reward–learning task and an associated mathematical model that predicted individual response times. This reinforcement-learning model generated value-based prediction errors and trial-by-trial estimates of exploration as a function of uncertainty. Mid-frontal theta power correlated with unsigned prediction error, although negative prediction errors had greater power overall. Trial-to-trial variations in response-locked frontal theta were linearly related to relative uncertainty and were larger in individuals who used uncertainty to guide exploration. This finding suggests that theta-band activities reflect prefrontal-directed strategic control during exploratory choices. PMID:22120491

The power of friendship: protection against an escalating cycle of peer victimization.

PubMed

Hodges, E V; Boivin, M; Vitaro, F; Bukowski, W M

1999-01-01

This study examined 2 aspects of friendship (presence and perceived qualities of a best friend) as moderators of behavioral antecedents and outcomes of peer victimization. A total of 393 children (188 boys and 205 girls) in the 4th and 5th grades (mean age = 10 years 7 months) participated during each of 2 waves of data collection in this 1-year longitudinal study. Results indicated that teacher-reported internalizing and externalizing behaviors predicted increases in peer-reported victimization, but the relation of internalizing behaviors to increases in victimization was attenuated for children with a protective friendship. Victimization predicted increases in internalizing and externalizing behaviors but only for children without a mutual best friendship. Results highlight the importance of peer friendships in preventing an escalating cycle of peer abuse.

Channel adjustment of an unstable coarse-grained stream: Opposing trends of boundary and critical shear stress, and the applicability of extremal hypotheses

USGS Publications Warehouse

Simon, Andrew; Thorne, Colin R.

1996-01-01

Channel adjustments in the North Fork Toutle River and the Toutle River main stem were initiated by deposition of a 2.5km3 debris avalanche and associated lahars that accompanied the catastrophic eruption of Mount St. Helens, Washington on 18 May 1980. Channel widening was the dominant process. In combination, adjustments caused average boundary shear stress to decrease non-linearly with time and critical shear stress to increase non-linearly with time. At the discharge that is equalled or exceeded 1 per cent of the time, these trends converged by 1991-1992 so that excess shear stress approached minimum values. Extremal hypotheses, such as minimization of unit stream power and minimization of the rate of energy dissipation (minimum stream power), are shown to be applicable to dynamic adjustments of the Toutle River system. Maximization of the Darcy-Weisbach friction factor did not occur, but increases in relative bed roughness, caused by the concomitant reduction in hydraulic depths and bed-material coarsening, were documented. Predictions of stable channel geometries using the minimum stream power approach were unsuccessful when compared to the 1991-1992 geometries and bed-material characteristics measured in the field. It is concluded that the predictions are not applicable because the study reaches are not truly stable and cannot become so until a new floodplain has been formed by renewed channel incision, retreat of stream-side hummocks, and establishment of riparian vegetation to limit the destabilizing effects of large floods. Further, prediction of energy slope (and consequently stream power) by the sediment transport equations is inaccurate because of the inability of the equations to account for significant contributions of finer grained (sand and gravel) bank materials (relative to the coarsened channel bed) from bank retreat and from upstream terrace erosion.

Meta-analysis of genome-wide association from genomic prediction models

USDA-ARS?s Scientific Manuscript database

A limitation of many genome-wide association studies (GWA) in animal breeding is that there are many loci with small effect sizes; thus, larger sample sizes (N) are required to guarantee suitable power of detection. To increase sample size, results from different GWA can be combined in a meta-analys...

Effect of wind speed on performance of a solar-pv array

USDA-ARS?s Scientific Manuscript database

Thousands of solar photovoltaic (PV) arrays have been installed over the past few years, but the effect of wind speed on the predicted performance of PV arrays is not usually considered by installers. An increase in wind speed will cool the PV array, and the electrical power of the PV modules will ...

Design and Operating Characteristics of High-Speed, Small-Bore Cylindrical-Roller Bearings

NASA Technical Reports Server (NTRS)

Pinel, Stanley, I.; Signer, Hans R.; Zaretsky, Erwin V.

2000-01-01

The computer program SHABERTH was used to analyze 35-mm-bore cylindrical roller bearings designed and manufactured for high-speed turbomachinery applications. Parametric tests of the bearings were conducted on a high-speed, high-temperature bearing tester and the results were compared with the computer predictions. Bearings with a channeled inner ring were lubricated through the inner ring, while bearings with a channeled outer ring were lubricated with oil jets. Tests were run with and without outer-ring cooling. The predicted bearing life decreased with increasing speed because of increased contact stresses caused by centrifugal load. Lower temperatures, less roller skidding, and lower power losses were obtained with channeled inner rings. Power losses calculated by the SHABERTH computer program correlated reasonably well with the test results. The Parker formula for XCAV (used in SHABERTH as a measure of oil volume in the bearing cavity) needed to be adjusted to reflect the prevailing operating conditions. The XCAV formula will need to be further refined to reflect roller bearing lubrication, ring design, cage design, and location of the cage-controlling land.

Using the Fire Weather Index (FWI) to improve the estimation of fire emissions from fire radiative power (FRP) observations

NASA Astrophysics Data System (ADS)

Di Giuseppe, Francesca; Rémy, Samuel; Pappenberger, Florian; Wetterhall, Fredrik

2018-04-01

The atmospheric composition analysis and forecast for the European Copernicus Atmosphere Monitoring Services (CAMS) relies on biomass-burning fire emission estimates from the Global Fire Assimilation System (GFAS). The GFAS is a global system and converts fire radiative power (FRP) observations from MODIS satellites into smoke constituents. Missing observations are filled in using persistence, whereby observed FRP values from the previous day are progressed in time until a new observation is recorded. One of the consequences of this assumption is an increase of fire duration, which in turn translates into an increase of emissions estimated from fires compared to what is available from observations. In this study persistence is replaced by modelled predictions using the Canadian Fire Weather Index (FWI), which describes how atmospheric conditions affect the vegetation moisture content and ultimately fire duration. The skill in predicting emissions from biomass burning is improved with the new technique, which indicates that using an FWI-based model to infer emissions from FRP is better than persistence when observations are not available.

Preliminary Empirical Models for Predicting Shrinkage, Part Geometry and Metallurgical Aspects of Ti-6Al-4V Shaped Metal Deposition Builds

NASA Astrophysics Data System (ADS)

Escobar-Palafox, Gustavo; Gault, Rosemary; Ridgway, Keith

2011-12-01

Shaped Metal Deposition (SMD) is an additive manufacturing process which creates parts layer by layer by weld depositions. In this work, empirical models that predict part geometry (wall thickness and outer diameter) and some metallurgical aspects (i.e. surface texture, portion of finer Widmanstätten microstructure) for the SMD process were developed. The models are based on an orthogonal fractional factorial design of experiments with four factors at two levels. The factors considered were energy level (a relationship between heat source power and the rate of raw material input.), step size, programmed diameter and travel speed. The models were validated using previous builds; the prediction error for part geometry was under 11%. Several relationships between the factors and responses were identified. Current had a significant effect on wall thickness; thickness increases with increasing current. Programmed diameter had a significant effect on percentage of shrinkage; this decreased with increasing component size. Surface finish decreased with decreasing step size and current.

Does Spontaneous Favorability to Power (vs. Universalism) Values Predict Spontaneous Prejudice and Discrimination?

PubMed

Souchon, Nicolas; Maio, Gregory R; Hanel, Paul H P; Bardin, Brigitte

2017-10-01

We conducted five studies testing whether an implicit measure of favorability toward power over universalism values predicts spontaneous prejudice and discrimination. Studies 1 (N = 192) and 2 (N = 86) examined correlations between spontaneous favorability toward power (vs. universalism) values, achievement (vs. benevolence) values, and a spontaneous measure of prejudice toward ethnic minorities. Study 3 (N = 159) tested whether conditioning participants to associate power values with positive adjectives and universalism values with negative adjectives (or inversely) affects spontaneous prejudice. Study 4 (N = 95) tested whether decision bias toward female handball players could be predicted by spontaneous attitude toward power (vs. universalism) values. Study 5 (N = 123) examined correlations between spontaneous attitude toward power (vs. universalism) values, spontaneous importance toward power (vs. universalism) values, and spontaneous prejudice toward Black African people. Spontaneous positivity toward power (vs. universalism) values was associated with spontaneous negativity toward minorities and predicted gender bias in a decision task, whereas the explicit measures did not. These results indicate that the implicit assessment of evaluative responses attached to human values helps to model value-attitude-behavior relations. © 2016 The Authors. Journal of Personality Published by Wiley Periodicals, Inc.

Overview of NASA Lewis Research Center free-piston Stirling engine technology activities applicable to space power systems

NASA Technical Reports Server (NTRS)

Slaby, J. G.

1986-01-01

Free piston Stirling technology is applicable for both solar and nuclear powered systems. As such, the Lewis Research Center serves as the project office to manage the newly initiated SP-100 Advanced Technology Program. This five year program provides the technology push for providing significant component and subsystem options for increased efficiency, reliability and survivability, and power output growth at reduced specific mass. One of the major elements of the program is the development of advanced power conversion concepts of which the Stirling cycle is a viable candidate. Under this program the research findings of the 25 kWe opposed piston Space Power Demonstrator Engine (SPDE) are presented. Included in the SPDE discussions are initial differences between predicted and experimental power outputs and power output influenced by variations in regenerators. Projections are made for future space power requirements over the next few decades. And a cursory comparison is presented showing the mass benefits that a Stirling system has over a Brayton system for the same peak temperature and output power.

Electric Power Engineering Cost Predicting Model Based on the PCA-GA-BP

NASA Astrophysics Data System (ADS)

Wen, Lei; Yu, Jiake; Zhao, Xin

2017-10-01

In this paper a hybrid prediction algorithm: PCA-GA-BP model is proposed. PCA algorithm is established to reduce the correlation between indicators of original data and decrease difficulty of BP neural network in complex dimensional calculation. The BP neural network is established to estimate the cost of power transmission project. The results show that PCA-GA-BP algorithm can improve result of prediction of electric power engineering cost.

Evaluation of Data-Driven Models for Predicting Solar Photovoltaics Power Output

DOE PAGES

Moslehi, Salim; Reddy, T. Agami; Katipamula, Srinivas

2017-09-10

This research was undertaken to evaluate different inverse models for predicting power output of solar photovoltaic (PV) systems under different practical scenarios. In particular, we have investigated whether PV power output prediction accuracy can be improved if module/cell temperature was measured in addition to climatic variables, and also the extent to which prediction accuracy degrades if solar irradiation is not measured on the plane of array but only on a horizontal surface. We have also investigated the significance of different independent or regressor variables, such as wind velocity and incident angle modifier in predicting PV power output and cell temperature.more » The inverse regression model forms have been evaluated both in terms of their goodness-of-fit, and their accuracy and robustness in terms of their predictive performance. Given the accuracy of the measurements, expected CV-RMSE of hourly power output prediction over the year varies between 3.2% and 8.6% when only climatic data are used. Depending on what type of measured climatic and PV performance data is available, different scenarios have been identified and the corresponding appropriate modeling pathways have been proposed. The corresponding models are to be implemented on a controller platform for optimum operational planning of microgrids and integrated energy systems.« less

Improved techniques for predicting spacecraft power

NASA Technical Reports Server (NTRS)

Chmielewski, A. B.

1987-01-01

Radioisotope Thermoelectric Generators (RTGs) are going to supply power for the NASA Galileo and Ulysses spacecraft now scheduled to be launched in 1989 and 1990. The duration of the Galileo mission is expected to be over 8 years. This brings the total RTG lifetime to 13 years. In 13 years, the RTG power drops more than 20 percent leaving a very small power margin over what is consumed by the spacecraft. Thus it is very important to accurately predict the RTG performance and be able to assess the magnitude of errors involved. The paper lists all the error sources involved in the RTG power predictions and describes a statistical method for calculating the tolerance.

Power quality analysis based on spatial correlation

NASA Astrophysics Data System (ADS)

Li, Jiangtao; Zhao, Gang; Liu, Haibo; Li, Fenghou; Liu, Xiaoli

2018-03-01

With the industrialization and urbanization, the status of electricity in the production and life is getting higher and higher. So the prediction of power quality is the more potential significance. Traditional power quality analysis methods include: power quality data compression, disturbance event pattern classification, disturbance parameter calculation. Under certain conditions, these methods can predict power quality. This paper analyses the temporal variation of power quality of one provincial power grid in China from time angle. The distribution of power quality was analyzed based on spatial autocorrelation. This paper tries to prove that the research idea of geography is effective for mining the potential information of power quality.

A community effort to assess and improve drug sensitivity prediction algorithms

PubMed Central

Costello, James C; Heiser, Laura M; Georgii, Elisabeth; Gönen, Mehmet; Menden, Michael P; Wang, Nicholas J; Bansal, Mukesh; Ammad-ud-din, Muhammad; Hintsanen, Petteri; Khan, Suleiman A; Mpindi, John-Patrick; Kallioniemi, Olli; Honkela, Antti; Aittokallio, Tero; Wennerberg, Krister; Collins, James J; Gallahan, Dan; Singer, Dinah; Saez-Rodriguez, Julio; Kaski, Samuel; Gray, Joe W; Stolovitzky, Gustavo

2015-01-01

Predicting the best treatment strategy from genomic information is a core goal of precision medicine. Here we focus on predicting drug response based on a cohort of genomic, epigenomic and proteomic profiling data sets measured in human breast cancer cell lines. Through a collaborative effort between the National Cancer Institute (NCI) and the Dialogue on Reverse Engineering Assessment and Methods (DREAM) project, we analyzed a total of 44 drug sensitivity prediction algorithms. The top-performing approaches modeled nonlinear relationships and incorporated biological pathway information. We found that gene expression microarrays consistently provided the best predictive power of the individual profiling data sets; however, performance was increased by including multiple, independent data sets. We discuss the innovations underlying the top-performing methodology, Bayesian multitask MKL, and we provide detailed descriptions of all methods. This study establishes benchmarks for drug sensitivity prediction and identifies approaches that can be leveraged for the development of new methods. PMID:24880487

A community effort to assess and improve drug sensitivity prediction algorithms.

PubMed

Costello, James C; Heiser, Laura M; Georgii, Elisabeth; Gönen, Mehmet; Menden, Michael P; Wang, Nicholas J; Bansal, Mukesh; Ammad-ud-din, Muhammad; Hintsanen, Petteri; Khan, Suleiman A; Mpindi, John-Patrick; Kallioniemi, Olli; Honkela, Antti; Aittokallio, Tero; Wennerberg, Krister; Collins, James J; Gallahan, Dan; Singer, Dinah; Saez-Rodriguez, Julio; Kaski, Samuel; Gray, Joe W; Stolovitzky, Gustavo

2014-12-01

Predicting the best treatment strategy from genomic information is a core goal of precision medicine. Here we focus on predicting drug response based on a cohort of genomic, epigenomic and proteomic profiling data sets measured in human breast cancer cell lines. Through a collaborative effort between the National Cancer Institute (NCI) and the Dialogue on Reverse Engineering Assessment and Methods (DREAM) project, we analyzed a total of 44 drug sensitivity prediction algorithms. The top-performing approaches modeled nonlinear relationships and incorporated biological pathway information. We found that gene expression microarrays consistently provided the best predictive power of the individual profiling data sets; however, performance was increased by including multiple, independent data sets. We discuss the innovations underlying the top-performing methodology, Bayesian multitask MKL, and we provide detailed descriptions of all methods. This study establishes benchmarks for drug sensitivity prediction and identifies approaches that can be leveraged for the development of new methods.

The effects of message recipients' power before and after persuasion: a self-validation analysis.

PubMed

Briñol, Pablo; Petty, Richard E; Valle, Carmen; Rucker, Derek D; Becerra, Alberto

2007-12-01

In the present research, the authors examined the effect of a message recipient's power on attitude change and introduced a new mechanism by which power can affect social judgment. In line with prior research that suggested a link between power and approach tendencies, the authors hypothesized that having power increases confidence relative to being powerless. After demonstrating this link in Experiment 1, in 4 additional studies, they examined the role of power in persuasion as a function of when power is infused into the persuasion process. On the basis of the idea that power validates whatever mental content is accessible, they hypothesized that power would have different effects on persuasion depending on when power was induced. Specifically, the authors predicted that making people feel powerful prior to a message would validate their existing views and thus reduce the perceived need to attend to subsequent information. However, it was hypothesized that inducing power after a message has been processed would validate one's recently generated thoughts and thus influence the extent to which people rely upon their thoughts in determining their attitudes. (c) 2007 APA, all rights reserved.

Jet Power vs. Black Hole Mass in Blazars: Exploring the Relationship in the Context of the B-Z Mechanism

NASA Astrophysics Data System (ADS)

Fernandes, Sunil; Schlegel, E.

2012-01-01

Recently, a tentative negative correlation between jet power and BH mass in a sample of GeV-TeV BL Lac objects(Zhang et al 2011). It was suggested that spin energy extraction could play a significant role in producing the jets and the jets are not purely accretion driven. Broderick et al (2011) recently explored the relationship between jet power and radio core luminosity building on Blanford et al (1979) theoretical work. Using this work we have studied the relationship between radio core luminosity (as a stand in for jet power) and black hole mass and have found a possible positive correlation in a sample of nearby BL Lac objects. The present poster attempts to explore this relationship in the context of the Blanford-Znajek mechanism which predicts jet power increases with black hole mass, spin rate, and accretion rate.

Energy-Efficient Integration of Continuous Context Sensing and Prediction into Smartwatches.

PubMed

Rawassizadeh, Reza; Tomitsch, Martin; Nourizadeh, Manouchehr; Momeni, Elaheh; Peery, Aaron; Ulanova, Liudmila; Pazzani, Michael

2015-09-08

As the availability and use of wearables increases, they are becoming a promising platform for context sensing and context analysis. Smartwatches are a particularly interesting platform for this purpose, as they offer salient advantages, such as their proximity to the human body. However, they also have limitations associated with their small form factor, such as processing power and battery life, which makes it difficult to simply transfer smartphone-based context sensing and prediction models to smartwatches. In this paper, we introduce an energy-efficient, generic, integrated framework for continuous context sensing and prediction on smartwatches. Our work extends previous approaches for context sensing and prediction on wrist-mounted wearables that perform predictive analytics outside the device. We offer a generic sensing module and a novel energy-efficient, on-device prediction module that is based on a semantic abstraction approach to convert sensor data into meaningful information objects, similar to human perception of a behavior. Through six evaluations, we analyze the energy efficiency of our framework modules, identify the optimal file structure for data access and demonstrate an increase in accuracy of prediction through our semantic abstraction method. The proposed framework is hardware independent and can serve as a reference model for implementing context sensing and prediction on small wearable devices beyond smartwatches, such as body-mounted cameras.

Energy-Efficient Integration of Continuous Context Sensing and Prediction into Smartwatches

PubMed Central

Rawassizadeh, Reza; Tomitsch, Martin; Nourizadeh, Manouchehr; Momeni, Elaheh; Peery, Aaron; Ulanova, Liudmila; Pazzani, Michael

2015-01-01

As the availability and use of wearables increases, they are becoming a promising platform for context sensing and context analysis. Smartwatches are a particularly interesting platform for this purpose, as they offer salient advantages, such as their proximity to the human body. However, they also have limitations associated with their small form factor, such as processing power and battery life, which makes it difficult to simply transfer smartphone-based context sensing and prediction models to smartwatches. In this paper, we introduce an energy-efficient, generic, integrated framework for continuous context sensing and prediction on smartwatches. Our work extends previous approaches for context sensing and prediction on wrist-mounted wearables that perform predictive analytics outside the device. We offer a generic sensing module and a novel energy-efficient, on-device prediction module that is based on a semantic abstraction approach to convert sensor data into meaningful information objects, similar to human perception of a behavior. Through six evaluations, we analyze the energy efficiency of our framework modules, identify the optimal file structure for data access and demonstrate an increase in accuracy of prediction through our semantic abstraction method. The proposed framework is hardware independent and can serve as a reference model for implementing context sensing and prediction on small wearable devices beyond smartwatches, such as body-mounted cameras. PMID:26370997

Predicting power-optimal kinematics of avian wings

PubMed Central

Parslew, Ben

2015-01-01

A theoretical model of avian flight is developed which simulates wing motion through a class of methods known as predictive simulation. This approach uses numerical optimization to predict power-optimal kinematics of avian wings in hover, cruise, climb and descent. The wing dynamics capture both aerodynamic and inertial loads. The model is used to simulate the flight of the pigeon, Columba livia, and the results are compared with previous experimental measurements. In cruise, the model unearths a vast range of kinematic modes that are capable of generating the required forces for flight. The most efficient mode uses a near-vertical stroke–plane and a flexed-wing upstroke, similar to kinematics recorded experimentally. In hover, the model predicts that the power-optimal mode uses an extended-wing upstroke, similar to hummingbirds. In flexing their wings, pigeons are predicted to consume 20% more power than if they kept their wings full extended, implying that the typical kinematics used by pigeons in hover are suboptimal. Predictions of climbing flight suggest that the most energy-efficient way to reach a given altitude is to climb as steeply as possible, subjected to the availability of power. PMID:25392398

Performance of comorbidity, risk adjustment, and functional status measures in expenditure prediction for patients with diabetes.

PubMed

Maciejewski, Matthew L; Liu, Chuan-Fen; Fihn, Stephan D

2009-01-01

To compare the ability of generic comorbidity and risk adjustment measures, a diabetes-specific measure, and a self-reported functional status measure to explain variation in health care expenditures for individuals with diabetes. This study included a retrospective cohort of 3,092 diabetic veterans participating in a multisite trial. Two comorbidity measures, four risk adjusters, a functional status measure, a diabetes complication count, and baseline expenditures were constructed from administrative and survey data. Outpatient, inpatient, and total expenditure models were estimated using ordinary least squares regression. Adjusted R(2) statistics and predictive ratios were compared across measures to assess overall explanatory power and explanatory power of low- and high-cost subgroups. Administrative data-based risk adjusters performed better than the comorbidity, functional status, and diabetes-specific measures in all expenditure models. The diagnostic cost groups (DCGs) measure had the greatest predictive power overall and for the low- and high-cost subgroups, while the diabetes-specific measure had the lowest predictive power. A model with DCGs and the diabetes-specific measure modestly improved predictive power. Existing generic measures can be useful for diabetes-specific research and policy applications, but more predictive diabetes-specific measures are needed.

Prediction of light aircraft interior sound pressure level using the room equation

NASA Technical Reports Server (NTRS)

Atwal, M.; Bernhard, R.

1984-01-01

The room equation is investigated for predicting interior sound level. The method makes use of an acoustic power balance, by equating net power flow into the cabin volume to power dissipated within the cabin using the room equation. The sound power level transmitted through the panels was calculated by multiplying the measured space averaged transmitted intensity for each panel by its surface area. The sound pressure level was obtained by summing the mean square sound pressures radiated from each panel. The data obtained supported the room equation model in predicting the cabin interior sound pressure level.

Multi-Temporal Decomposed Wind and Load Power Models for Electric Energy Systems

NASA Astrophysics Data System (ADS)

Abdel-Karim, Noha

This thesis is motivated by the recognition that sources of uncertainties in electric power systems are multifold and may have potentially far-reaching effects. In the past, only system load forecast was considered to be the main challenge. More recently, however, the uncertain price of electricity and hard-to-predict power produced by renewable resources, such as wind and solar, are making the operating and planning environment much more challenging. The near-real-time power imbalances are compensated by means of frequency regulation and generally require fast-responding costly resources. Because of this, a more accurate forecast and look-ahead scheduling would result in a reduced need for expensive power balancing. Similarly, long-term planning and seasonal maintenance need to take into account long-term demand forecast as well as how the short-term generation scheduling is done. The better the demand forecast, the more efficient planning will be as well. Moreover, computer algorithms for scheduling and planning are essential in helping the system operators decide what to schedule and planners what to build. This is needed given the overall complexity created by different abilities to adjust the power output of generation technologies, demand uncertainties and by the network delivery constraints. Given the growing presence of major uncertainties, it is likely that the main control applications will use more probabilistic approaches. Today's predominantly deterministic methods will be replaced by methods which account for key uncertainties as decisions are made. It is well-understood that although demand and wind power cannot be predicted at very high accuracy, taking into consideration predictions and scheduling in a look-ahead way over several time horizons generally results in more efficient and reliable utilization, than when decisions are made assuming deterministic, often worst-case scenarios. This change is in approach is going to ultimately require new electricity market rules capable of providing the right incentives to manage uncertainties and of differentiating various technologies according to the rate at which they can respond to ever changing conditions. Given the overall need for modeling uncertainties in electric energy systems, we consider in this thesis the problem of multi-temporal modeling of wind and demand power, in particular. Historic data is used to derive prediction models for several future time horizons. Short-term prediction models derived can be used for look-ahead economic dispatch and unit commitment, while the long-term annual predictive models can be used for investment planning. As expected, the accuracy of such predictive models depends on the time horizons over which the predictions are made, as well as on the nature of uncertain signals. It is shown that predictive models obtained using the same general modeling approaches result in different accuracy for wind than for demand power. In what follows, we introduce several models which have qualitatively different patterns, ranging from hourly to annual. We first transform historic time-stamped data into the Fourier Transform (Fr) representation. The frequency domain data representation is used to decompose the wind and load power signals and to derive predictive models relevant for short-term and long-term predictions using extracted spectral techniques. The short-term results are interpreted next as a Linear Prediction Coding Model (LPC) and its accuracy is analyzed. Next, a new Markov-Based Sensitivity Model (MBSM) for short term prediction has been proposed and the dispatched costs of uncertainties for different predictive models with comparisons have been developed. Moreover, the Discrete Markov Process (DMP) representation is applied to help assess probabilities of most likely short-, medium- and long-term states and the related multi-temporal risks. In addition, this thesis discusses operational impacts of wind power integration in different scenario levels by performing more than 9,000 AC Optimal Power Flow runs. The effects of both wind and load variations on system constraints and costs are presented. The limitations of DC Optimal Power Flow (DCOPF) vs. ACOPF are emphasized by means of system convergence problems due to the effect of wind power on changing line flows and net power injections. By studying the effect of having wind power on line flows, we found that the divergence problem applies in areas with high wind and hydro generation capacity share (cheap generations). (Abstract shortened by UMI.).

THE LONGEST TIMESCALE X-RAY VARIABILITY REVEALS EVIDENCE FOR ACTIVE GALACTIC NUCLEI IN THE HIGH ACCRETION STATE

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang Youhong, E-mail: youhong.zhang@mail.tsinghua.edu.cn

2011-01-01

The All Sky Monitor (ASM) on board the Rossi X-ray Timing Explorer has continuously monitored a number of active galactic nuclei (AGNs) with similar sampling rates for 14 years, from 1996 January to 2009 December. Utilizing the archival ASM data of 27 AGNs, we calculate the normalized excess variances of the 300-day binned X-ray light curves on the longest timescale (between 300 days and 14 years) explored so far. The observed variance appears to be independent of AGN black-hole mass and bolometric luminosity. According to the scaling relation of black-hole mass (and bolometric luminosity) from galactic black hole X-ray binariesmore » (GBHs) to AGNs, the break timescales that correspond to the break frequencies detected in the power spectral density (PSD) of our AGNs are larger than the binsize (300 days) of the ASM light curves. As a result, the singly broken power-law (soft-state) PSD predicts the variance to be independent of mass and luminosity. Nevertheless, the doubly broken power-law (hard-state) PSD predicts, with the widely accepted ratio of the two break frequencies, that the variance increases with increasing mass and decreases with increasing luminosity. Therefore, the independence of the observed variance on mass and luminosity suggests that AGNs should have soft-state PSDs. Taking into account the scaling of the break timescale with mass and luminosity synchronously, the observed variances are also more consistent with the soft-state than the hard-state PSD predictions. With the averaged variance of AGNs and the soft-state PSD assumption, we obtain a universal PSD amplitude of 0.030 {+-} 0.022. By analogy with the GBH PSDs in the high/soft state, the longest timescale variability supports the standpoint that AGNs are scaled-up GBHs in the high accretion state, as already implied by the direct PSD analysis.« less

How and when predictability interacts with accentuation in temporally selective attention during speech comprehension.

PubMed

Li, Xiaoqing; Lu, Yong; Zhao, Haiyan

2014-11-01

The present study used EEG to investigate how and when top-down prediction interacts with bottom-up acoustic signals in temporally selective attention during speech comprehension. Mandarin Chinese spoken sentences were used as stimuli. We systematically manipulated the predictability and de/accentuation of the critical words in the sentence context. Meanwhile, a linguistic attention probe 'ba' was presented concurrently with the critical words or not. The results showed that, first, words with a linguistic attention probe elicited a larger N1 than those without a probe. The latency of this N1 effect was shortened for accented or lowly predictable words, indicating more attentional resources allocated to these words. Importantly, prediction and accentuation showed a complementary interplay on the latency of this N1 effect, demonstrating that when the words had already attracted attention due to low predictability or due to the presence of pitch accent, the other factor did not modulate attention allocation anymore. Second, relative to the lowly predictable words, the highly predictable words elicited a reduced N400 and enhanced gamma-band power increases, especially under the accented conditions; moreover, under the accented conditions, shorter N1 peak-latency was found to correlate with larger gamma-band power enhancement, which indicates that a close relationship might exist between early selective attention and later semantic integration. Finally, the interaction between top-down selective attention (driven by prediction) and bottom-up selective attention (driven by accentuation) occurred before lexical-semantic processing, namely before the N400 effect evoked by predictability, which was discussed with regard to the language comprehension models. Copyright © 2014 Elsevier Ltd. All rights reserved.

The honeymoon effect in job performance - Temporal increases in the predictive power of achievement motivation

NASA Technical Reports Server (NTRS)

Helmreich, Robert L.; Sawin, Linda L.; Carsrud, Alan L.

1986-01-01

Correlations between a job performance criterion and personality measures reflecting achievement motivation and an interpersonal orientation were examined at three points in time after completion of job training for a sample of airline reservations agents. Although correlations between the personality predictors and performance were small and nonsignificant for the 3-month period after beginning the job, by the end of six and eight months a number of significant relationships had emerged. Implications for the utility of personality measures in selection and performance prediction are discussed.

Predictions of Critical Heat Flux in Annular Pipes with TRACEv4.160 code

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jasiulevicius, Audrius; Macian-Juan, Rafael

2006-07-01

This paper presents the assessment of TRACE (version v4.160) against the Critical Heat Flux (CHF) experiments in annular tubes performed at the Royal Institute of Technology (KTH) in Stockholm, Sweden. The experimental database includes data for coolant mass fluxes between 250 and 2500 kg/m{sup 2}s and inlet subcooling of 10 and 40 K at a pressure of 70 bar. The work presented in this paper supplements the calculations of single round tube experiments carried out earlier and provides a broader scope of validated geometries. In addition to the Biasi and CISE-GE CHF correlations available in the code, a number ofmore » experimental points at low flow conditions are available for the annular geometry experiments, which also permitted the assessment of the Biasi/Zuber CHF correlation used in TRACE v4.160 for low flow conditions. Experiments with different axial power distribution were simulated and the effects of the axial power profile and the coolant inlet subcooling on the TRACE predictions were investigated. The results of this work show that the Biasi/Zuber correlation provides good estimation of the CHF at 70 bar, and, for the same conditions, the simulation of the annular experiments resulted in the calculation of lower CHF values compared to single-tube experiments. The analysis of the performance of the standard TRACE CHF correlations shows that the CISE-GE correlation yields critical qualities (quality at CHF) closer to the experimental values at 70 bar than the Biasi correlation for annular flow conditions. Regarding the power profile, the results of the TRACE calculations seem to be very sensitive to its shape, since, depending on the profile, different accuracies in the predictions were noted while other system conditions remained constant. The inlet coolant subcooling was also an important factor in the accuracy of TRACE CHF predictions. Thus, an increase in the inlet subcooling led to a clear improvement in the estimation of the critical quality with both Biasi and CISE-GE correlations. To complement the work, three additional CHF correlations were implemented in TRACE v4.160, namely the Bowring, Tong W-3 and Levitan-Lantsman CHF models, in order to assess the applicability of these correlations to simulate the CHF in annular tubes. The improvement of CHF predictions for low coolant mass flows (up to 1500 kg/m{sup 2}s) is noted when applying Bowring CHF correlation. However, the increase in the inlet subcooling increases the error in predicted critical quality with the Bowring correlation. The Levitan-Lantsman and Tong-W-3 correlations provide results similar to the Biasi model. Therefore, the most correct CHF predictions among the investigated correlations were obtained using CISE-GE model in the standard TRAC v4.160 code. (authors)« less

Influence of the effective lens position, as predicted by axial length and keratometry, on the near add power of multifocal intraocular lenses.

PubMed

Savini, Giacomo; Hoffer, Kenneth J; Lombardo, Marco; Serrao, Sebastiano; Schiano-Lomoriello, Domenico; Ducoli, Pietro

2016-01-01

To calculate the near focal distance of different multifocal intraocular lenses (IOLs) as a function of the 2 parameters that are measured before cataract surgery; that is, axial length (AL) and refractive corneal power (keratometry [K]). GB Bietti Foundation IRCCS, Rome, Italy. Noninterventional theoretical study. The IOL power for emmetropia was first calculated in an eye model with the AL ranging from 20 to 30 mm and K from 38 to 48 diopters (D). Then, the predicted myopic refraction for any given IOL add power (from +1.5 to +4.0 D) was calculated, and from this value the near focal distance was obtained. Calculations were also performed for the average eye (K = 43.81 D; AL = 23.65 mm). The near focal distance increased with increasing values of K and AL for each near power add. The near focal distance ranged between 53 cm and 72 cm (21 inches and 28 inches) for a multifocal IOL with +2.50 D, between 44 cm and 60 cm (17 inches and 24 inches) for a multifocal IOL with +3.00 D add, and between 33 cm and 44 cm (13 inches and 18 inches) for a multifocal IOL with +4.00 D add. In the average eye, the near focal distance ranges between 36 cm (near add power = 4.00 D) and 99 cm (near add power = 1.5 D). Longer eyes with steeper corneas showed the longest near focal distance and could experience more difficulties in focusing near objects after surgery. The opposite was true for short hyperopic eyes. Dr. Hoffer receives licensing fees for the commercial use of the registered trademark Hoffer from all biometry manufacturers using the Hoffer Q formula to ensure that it is programmed correctly and book royalties from Slack, Inc., for the textbook IOL Power. None of the authors has a financial or proprietary interest in any material or method mentioned. Copyright © 2016 ASCRS and ESCRS. Published by Elsevier Inc. All rights reserved.

Wind farms production: Control and prediction

NASA Astrophysics Data System (ADS)

El-Fouly, Tarek Hussein Mostafa

Wind energy resources, unlike dispatchable central station generation, produce power dependable on external irregular source and that is the incident wind speed which does not always blow when electricity is needed. This results in the variability, unpredictability, and uncertainty of wind resources. Therefore, the integration of wind facilities to utility electrical grid presents a major challenge to power system operator. Such integration has significant impact on the optimum power flow, transmission congestion, power quality issues, system stability, load dispatch, and economic analysis. Due to the irregular nature of wind power production, accurate prediction represents the major challenge to power system operators. Therefore, in this thesis two novel models are proposed for wind speed and wind power prediction. One proposed model is dedicated to short-term prediction (one-hour ahead) and the other involves medium term prediction (one-day ahead). The accuracy of the proposed models is revealed by comparing their results with the corresponding values of a reference prediction model referred to as the persistent model. Utility grid operation is not only impacted by the uncertainty of the future production of wind farms, but also by the variability of their current production and how the active and reactive power exchange with the grid is controlled. To address this particular task, a control technique for wind turbines, driven by doubly-fed induction generators (DFIGs), is developed to regulate the terminal voltage by equally sharing the generated/absorbed reactive power between the rotor-side and the gridside converters. To highlight the impact of the new developed technique in reducing the power loss in the generator set, an economic analysis is carried out. Moreover, a new aggregated model for wind farms is proposed that accounts for the irregularity of the incident wind distribution throughout the farm layout. Specifically, this model includes the wake effect and the time delay of the incident wind speed of the different turbines on the farm, and to simulate the fluctuation in the generated power more accurately and more closer to real-time operation. Recently, wind farms with considerable output power ratings have been installed. Their integrating into the utility grid will substantially affect the electricity markets. This thesis investigates the possible impact of wind power variability, wind farm control strategy, wind energy penetration level, wind farm location, and wind power prediction accuracy on the total generation costs and close to real time electricity market prices. These issues are addressed by developing a single auction market model for determining the real-time electricity market prices.

Prediction of global solar irradiance based on time series analysis: Application to solar thermal power plants energy production planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Martin, Luis; Marchante, Ruth; Cony, Marco

2010-10-15

Due to strong increase of solar power generation, the predictions of incoming solar energy are acquiring more importance. Photovoltaic and solar thermal are the main sources of electricity generation from solar energy. In the case of solar thermal energy plants with storage energy system, its management and operation need reliable predictions of solar irradiance with the same temporal resolution as the temporal capacity of the back-up system. These plants can work like a conventional power plant and compete in the energy stock market avoiding intermittence in electricity production. This work presents a comparisons of statistical models based on time seriesmore » applied to predict half daily values of global solar irradiance with a temporal horizon of 3 days. Half daily values consist of accumulated hourly global solar irradiance from solar raise to solar noon and from noon until dawn for each day. The dataset of ground solar radiation used belongs to stations of Spanish National Weather Service (AEMet). The models tested are autoregressive, neural networks and fuzzy logic models. Due to the fact that half daily solar irradiance time series is non-stationary, it has been necessary to transform it to two new stationary variables (clearness index and lost component) which are used as input of the predictive models. Improvement in terms of RMSD of the models essayed is compared against the model based on persistence. The validation process shows that all models essayed improve persistence. The best approach to forecast half daily values of solar irradiance is neural network models with lost component as input, except Lerida station where models based on clearness index have less uncertainty because this magnitude has a linear behaviour and it is easier to simulate by models. (author)« less

Diagnostic potential of endotoxin scattering photometry for sepsis and septic shock.

PubMed

Shimizu, Tomoharu; Obata, Toru; Sonoda, Hiromichi; Akabori, Hiroya; Miyake, Tohru; Yamamoto, Hiroshi; Tabata, Takahisa; Eguchi, Yutaka; Tani, Tohru

2013-12-01

Endotoxin scattering photometry (ESP) is a novel Limulus amebocyte lysate (LAL) assay that uses a laser light-scattering particle-counting method. In the present study, we compared ESP, standard turbidimetric LAL assay, and procalcitonin assay for the evaluation of sepsis after emergency gastrointestinal surgery. A total of 174 samples were collected from 40 adult patients undergoing emergency gastrointestinal surgery and 10 patients with colorectal cancer undergoing elective surgery as nonseptic controls. Plasma endotoxin levels were measured with ESP and turbidimetric LAL assay, and plasma procalcitonin levels were assessed with a standard procalcitonin assay. Plasma endotoxin and procalcitonin levels increased corresponding to the degree of sepsis. Endotoxin scattering photometry significantly discriminated between patients with or without septic shock: sensitivity, 81.1%; specificity, 76.6%; positive predictive value, 48.4%; negative predictive value, 93.8%; and accuracy, 77.6%. The area under the receiver operating characteristic curve for septic shock with the ESP assay (endotoxin cutoff value, 23.8 pg/mL) was 0.8532 ± 0.0301 (95% confidence interval, 0.7841-0.9030; P < 0.0001). The predictive power of ESP was superior to that of turbidimetric assay (difference, 0.1965 ± 0.0588; 95% confidence interval, 0.0812-0.3117; P = 0.0008). There was no significant difference in predictive power between ESP and procalcitonin assay. Endotoxin scattering photometry also discriminated between patients with and without sepsis. Area under the receiver operating characteristic curve analysis showed that ESP had the best predictive power for diagnosing sepsis. In conclusion, compared with turbidimetric LAL assay, ESP more sensitively detected plasma endotoxin and significantly discriminated between sepsis and septic shock in patients undergoing gastrointestinal emergency surgery.

Memory Concerns, Memory Performance and Risk of Dementia in Patients with Mild Cognitive Impairment

PubMed Central

Wolfsgruber, Steffen; Wagner, Michael; Schmidtke, Klaus; Frölich, Lutz; Kurz, Alexander; Schulz, Stefanie; Hampel, Harald; Heuser, Isabella; Peters, Oliver; Reischies, Friedel M.; Jahn, Holger; Luckhaus, Christian; Hüll, Michael; Gertz, Hermann-Josef; Schröder, Johannes; Pantel, Johannes; Rienhoff, Otto; Rüther, Eckart; Henn, Fritz; Wiltfang, Jens; Maier, Wolfgang; Kornhuber, Johannes; Jessen, Frank

2014-01-01

Background Concerns about worsening memory (“memory concerns”; MC) and impairment in memory performance are both predictors of Alzheimer's dementia (AD). The relationship of both in dementia prediction at the pre-dementia disease stage, however, is not well explored. Refined understanding of the contribution of both MC and memory performance in dementia prediction is crucial for defining at-risk populations. We examined the risk of incident AD by MC and memory performance in patients with mild cognitive impairment (MCI). Methods We analyzed data of 417 MCI patients from a longitudinal multicenter observational study. Patients were classified based on presence (n = 305) vs. absence (n = 112) of MC. Risk of incident AD was estimated with Cox Proportional-Hazards regression models. Results Risk of incident AD was increased by MC (HR = 2.55, 95%CI: 1.33–4.89), lower memory performance (HR = 0.63, 95%CI: 0.56–0.71) and ApoE4-genotype (HR = 1.89, 95%CI: 1.18–3.02). An interaction effect between MC and memory performance was observed. The predictive power of MC was greatest for patients with very mild memory impairment and decreased with increasing memory impairment. Conclusions Our data suggest that the power of MC as a predictor of future dementia at the MCI stage varies with the patients' level of cognitive impairment. While MC are predictive at early stage MCI, their predictive value at more advanced stages of MCI is reduced. This suggests that loss of insight related to AD may occur at the late stage of MCI. PMID:25019225

Predictors of Mortality in the Critically Ill Cirrhotic Patient: Is the Model for End-Stage Liver Disease Enough?

PubMed

Annamalai, Alagappan; Harada, Megan Y; Chen, Melissa; Tran, Tram; Ko, Ara; Ley, Eric J; Nuno, Miriam; Klein, Andrew; Nissen, Nicholas; Noureddin, Mazen

2017-03-01

Critically ill cirrhotics require liver transplantation urgently, but are at high risk for perioperative mortality. The Model for End-stage Liver Disease (MELD) score, recently updated to incorporate serum sodium, estimates survival probability in patients with cirrhosis, but needs additional evaluation in the critically ill. The purpose of this study was to evaluate the predictive power of ICU admission MELD scores and identify clinical risk factors associated with increased mortality. This was a retrospective review of cirrhotic patients admitted to the ICU between January 2011 and December 2014. Patients who were discharged or underwent transplantation (survivors) were compared with those who died (nonsurvivors). Demographic characteristics, admission MELD scores, and clinical risk factors were recorded. Multivariate regression was used to identify independent predictors of mortality, and measures of model performance were assessed to determine predictive accuracy. Of 276 patients who met inclusion criteria, 153 were considered survivors and 123 were nonsurvivors. Survivor and nonsurvivor cohorts had similar demographic characteristics. Nonsurvivors had increased MELD, gastrointestinal bleeding, infection, mechanical ventilation, encephalopathy, vasopressors, dialysis, renal replacement therapy, requirement of blood products, and ICU length of stay. The MELD demonstrated low predictive power (c-statistic 0.73). Multivariate analysis identified MELD score (adjusted odds ratio [AOR] = 1.05), mechanical ventilation (AOR = 4.55), vasopressors (AOR = 3.87), and continuous renal replacement therapy (AOR = 2.43) as independent predictors of mortality, with stronger predictive accuracy (c-statistic 0.87). The MELD demonstrated relatively poor predictive accuracy in critically ill patients with cirrhosis and might not be the best indicator for prognosis in the ICU population. Prognostic accuracy is significantly improved when variables indicating organ support (mechanical ventilation, vasopressors, and continuous renal replacement therapy) are included in the model. Copyright © 2016. Published by Elsevier Inc.

Replacement of SSE (Release 6) with NASA's Prediction of Worldwide Energy Resource (POWER) Project GIS-enabled Web Data Portal:

Atmospheric Science Data Center

2018-03-15

... effort has been developed under the Prediction Of Worldwide Energy Resource (POWER) Project funded largely by NASA Earth Applied Sciences ... to NASA's satellite and modeling analysis for Renewable Energy, Sustainable Buildings and Agroclimatology applications.  A new POWER ...

POWER/SSE

Atmospheric Science Data Center

2018-06-15

... The Prediction of Worldwide Energy Resource (POWER) project was initiated to improve upon the current SSE ... continue to be focussed on the solar and wind Renewable Energy industry. New data sets will target Sustainable Buildings ... The Prediction of Worldwide Energy Resource (POWER) project was initiated to improve upon the current SSE ...

DOE Office of Scientific and Technical Information (OSTI.GOV)

O'Driscoll, M.

Power capacity additions in Asia will at least triple by 2010, and Arthur D. Little Inc. predicts natural gas can pick up a good 15 percent of that market. The study predicts Asia potentially will need 720 gigawatts of new power generation by 2010, of which 15 percent may be gas-based. This represents a market three times the size of the US market in the same period, and would require more than $1 trillion in investment to finance the power generation projects alone. Six forces are driving new market opportunities for natural gas in Asia, and have set the stagemore » for major investments in Asian gas-based power generation. They are: New technologies; growing environmental pressures; privatization; alternative energy pricing; gas availability; and continued economic growth. Japan, South Korea and Taiwan already have large, well-established markets for both gas and power that provide minimal opportunities for foreign investment. But the rest of Asia - specifically, India, Pakistan, the Philippines, Vietnam, Indonesia, Malaysia, the People's Republic of China, Thailand, Bangladesh and Myanmar - is still relatively undeveloped, the study said, and gas is emerging as an energy import substitute or export earner. The study found those countries will turn increased environmental awareness and concern into legislation as their economic prosperity grows, leading to a higher future value for natural gas relative to other fuels. Stricter emissions standards will favor gas over diesel, fuel oil and coal.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Gen; Lee, Martin A., E-mail: gjk44@wildcats.unh.edu

The effects of scatter-dominated interplanetary transport on the spectral properties of the differential fluence of large gradual solar energetic particle (SEP) events are investigated analytically. The model assumes for simplicity radial constant solar wind and radial magnetic field. The radial diffusion coefficient is calculated with quasilinear theory by assuming a spectrum of Alfvén waves propagating parallel to the magnetic field. Cross-field transport is neglected. The model takes into consideration several essential features of gradual event transport: nearly isotropic ion distributions, adiabatic deceleration in a divergent solar wind, and particle radial scattering mean free paths increasing with energy. Assuming an impulsivemore » and spherically symmetric injection of SEPs with a power-law spectrum near the Sun, the predicted differential fluence spectrum exhibits at 1 AU three distinctive power laws for different energy domains. The model naturally reproduces the spectral features of the double power-law proton differential fluence spectra that tend to be observed in extremely large SEP events. We select nine western ground-level events (GLEs) out of the 16 GLEs during Solar Cycle 23 and fit the observed double power-law spectra to the analytical predictions. The compression ratio of the accelerating shock wave, the power-law index of the ambient wave intensity, and the proton radial scattering mean free path are determined for the nine GLEs. The derived parameters are generally in agreement with the characteristic values expected for large gradual SEP events.« less

First and second generation antipsychotics influence hippocampal gamma oscillations by interactions with 5-HT3 and D3 receptors

PubMed Central

Schulz, Steffen B; Heidmann, Karin E; Mike, Arpad; Klaft, Zin-Juan; Heinemann, Uwe; Gerevich, Zoltan

2012-01-01

BACKGROUND AND PURPOSE Disturbed cortical gamma band oscillations (30–80 Hz) have been observed in schizophrenia: positive symptoms of the disease correlate with an increase in gamma oscillation power, whereas negative symptoms are associated with a decrease. EXPERIMENTAL APPROACH Here we investigated the effects of first and second generation antipsychotics (FGAs and SGAs, respectively) on gamma oscillations. The FGAs haloperidol, flupenthixol, chlorpromazine, chlorprothixene and the SGAs clozapine, risperidone, ziprasidone, amisulpride were applied on gamma oscillations induced by acetylcholine and physostigmine in the CA3 region of rat hippocampal slices. KEY RESULTS Antipsychotics inhibited the power of gamma oscillations and increased the bandwidth of the gamma band. Haloperidol and clozapine had the highest inhibitory effects. To determine which receptor is responsible for the alterations in gamma oscillations, the effects of the antipsychotics were plotted against their pKi values for 19 receptors and analysed for correlation. Our results indicated that 5-HT3 receptors have an enhancing effect on gamma oscillations whereas dopamine D3 receptors inhibit them. To test this prediction, m-chlorophenylbiguanide, PD 128907 and CP 809101, selective agonists at 5-HT3, D3 and 5-HT2C receptors were applied and revealed that 5-HT3 receptors indeed enhanced the gamma power whereas D3 receptors reduced it. As predicted, 5-HT2C receptors had no effects on gamma oscillations. CONCLUSION AND IMPLICATIONS Our data suggest that antipsychotics alter hippocampal gamma oscillations by interacting with 5-HT3 and dopamine D3 receptors. Moreover, a correlation of receptor affinities with the biological effects can be used to predict targets for the pharmacological effects of multi-target drugs. PMID:22817643

Cultural variation in seasonal depression: cross-national differences in winter versus summer patterns of seasonal affective disorder.

PubMed

Kasof, Joseph

2009-05-01

Research suggests that two dimensions of national culture, individualism-collectivism and power distance, predict affective responses to the seasonally varying levels of ambient sunlight that may underlie regular cycles of mood and behavior in Seasonal Affective Disorder (SAD). Specifically, negative affect is predicted by the diminished sunlight of fall-winter in countries higher in individualism and lower in power distance, and by the increased sunlight of spring-summer in countries lower in individualism and higher in power distance. This study tests whether individualism correlates positively, and power distance negatively, with the frequency of winter-SAD relative to that of summer-SAD. A search for studies reporting frequencies of both winter-SAD and summer-SAD identified 55 samples encompassing 18 countries and 38,408 participants, including 1931 with SAD. The frequency of winter-SAD, relative to that of summer-SAD, correlated positively with individualism (r=.67, p=.001) and negatively with power distance (r=-.72, p=.0001). Countries in which winter-SAD was more common than summer-SAD were significantly more individualistic and less power-distant than countries in which summer-SAD was more common than winter-SAD. Results survived various tests of threats to validity. The study is limited by the quantity, quality, diversity, and representativeness of the research under review and by its correlational design. Individualism and power distance are strongly related to the relative prevalence of winter-SAD and summer-SAD. Culture may play an important but previously overlooked role in the etiology of SAD.

Tidal current and tidal energy changes imposed by a dynamic tidal power system in the Taiwan Strait, China

NASA Astrophysics Data System (ADS)

Dai, Peng; Zhang, Jisheng; Zheng, Jinhai

2017-12-01

The Taiwan Strait has recently been proposed as a promising site for dynamic tidal power systems because of its shallow depth and strong tides. Dynamic tidal power is a new concept for extracting tidal potential energy in which a coast-perpendicular dike is used to create water head and generate electricity via turbines inserted in the dike. Before starting such a project, the potential power output and hydrodynamic impacts of the dike must be assessed. In this study, a two-dimensional numerical model based on the Delft3D-FLOW module is established to simulate tides in China. A dike module is developed to account for turbine processes and estimate power output by integrating a special algorithm into the model. The domain decomposition technique is used to divide the computational zone into two subdomains with grid refinement near the dike. The hydrodynamic processes predicted by the model, both with and without the proposed construction, are examined in detail, including tidal currents and tidal energy flux. The predicted time-averaged power yields with various opening ratios are presented. The results show that time-averaged power yield peaks at an 8% opening ratio. For semidiurnal tides, the flow velocity increases in front of the head of the dike and decreases on either side. For diurnal tides, these changes are complicated by the oblique incidence of tidal currents with respect to the dike as well as by bathymetric features. The dike itself blocks the propagation of tidal energy flux.

COMSAC: Computational Methods for Stability and Control. Part 2

NASA Technical Reports Server (NTRS)

Fremaux, C. Michael (Compiler); Hall, Robert M. (Compiler)

2004-01-01

The unprecedented advances being made in computational fluid dynamic (CFD) technology have demonstrated the powerful capabilities of codes in applications to civil and military aircraft. Used in conjunction with wind-tunnel and flight investigations, many codes are now routinely used by designers in diverse applications such as aerodynamic performance predictions and propulsion integration. Typically, these codes are most reliable for attached, steady, and predominantly turbulent flows. As a result of increasing reliability and confidence in CFD, wind-tunnel testing for some new configurations has been substantially reduced in key areas, such as wing trade studies for mission performance guarantees. Interest is now growing in the application of computational methods to other critical design challenges. One of the most important disciplinary elements for civil and military aircraft is prediction of stability and control characteristics. CFD offers the potential for significantly increasing the basic understanding, prediction, and control of flow phenomena associated with requirements for satisfactory aircraft handling characteristics.

European shags optimize their flight behavior according to wind conditions.

PubMed

Kogure, Yukihisa; Sato, Katsufumi; Watanuki, Yutaka; Wanless, Sarah; Daunt, Francis

2016-02-01

Aerodynamics results in two characteristic speeds of flying birds: the minimum power speed and the maximum range speed. The minimum power speed requires the lowest rate of energy expenditure per unit time to stay airborne and the maximum range speed maximizes air distance traveled per unit of energy consumed. Therefore, if birds aim to minimize the cost of transport under a range of wind conditions, they are predicted to fly at the maximum range speed. Furthermore, take-off is predicted to be strongly affected by wind speed and direction. To investigate the effect of wind conditions on take-off and cruising flight behavior, we equipped 14 European shags Phalacrocorax aristotelis with a back-mounted GPS logger to measure position and hence ground speed, and a neck-mounted accelerometer to record wing beat frequency and strength. Local wind conditions were recorded during the deployment period. Shags always took off into the wind regardless of their intended destination and take-off duration was correlated negatively with wind speed. We combined ground speed and direction during the cruising phase with wind speed and direction to estimate air speed and direction. Whilst ground speed was highly variable, air speed was comparatively stable, although it increased significantly during strong head winds, because of stronger wing beats. The increased air speeds in head winds suggest that birds fly at the maximum range speed, not at the minimum power speed. Our study demonstrates that European shags actively adjust their flight behavior to utilize wind power to minimize the costs of take-off and cruising flight. © 2016. Published by The Company of Biologists Ltd.

On the Path to SunShot: Advancing Concentrating Solar Power Technology Performance and Dispatchability.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mehos, Mark; Turchi, Craig; Jorgensen, Jennie

2016-03-01

Since the SunShot Vision Study (DOE 2012) was published, global deployment of concentrating solar power (CSP) has increased threefold to nearly 4,500 MW, with a similar threefold increase in operational capacity to 1,650 MW within the United States. Growth in U.S. CSP capacity has primarily been driven by policy support at the state and federal levels. State-driven renewable portfolio standards (RPSs), combined with a 30% federal investment tax credit (ITC) and federal loan guarantees, provided the opportunity for CSP developers to kick-start construction of CSP plants throughout the Southwest. Figure ES-1 demonstrates that deployment and private- and public-sector research andmore » development have led to dramatic cost reductions that have placed CSP well on the path to reaching the U.S. Department of Energy’s SunShot Initiative goal of 6 cents/kWh by 2020. In comparing the estimated capital costs from the SunShot Vision Study and the current analysis, we find that parabolic trough solar-field costs have fallen more rapidly than predicted, although the drop in solar-field costs was offset by the additional costs of moving from a wet-cooled power block in 2010 to a more expensive dry-cooled power block in 2015. The predicted 2015 decline in tower costs was in line with expectations, primarily driven by reduced heliostat costs. Figure ES-1 shows the reduction in levelized cost of electricity (LCOE) for both parabolic trough and tower systems, in addition to the projected 2020 SunShot target.« less

Modeling the complexity of acoustic emission during intermittent plastic deformation: Power laws and multifractal spectra

NASA Astrophysics Data System (ADS)

Kumar, Jagadish; Ananthakrishna, G.

2018-01-01

Scale-invariant power-law distributions for acoustic emission signals are ubiquitous in several plastically deforming materials. However, power-law distributions for acoustic emission energies are reported in distinctly different plastically deforming situations such as hcp and fcc single and polycrystalline samples exhibiting smooth stress-strain curves and in dilute metallic alloys exhibiting discontinuous flow. This is surprising since the underlying dislocation mechanisms in these two types of deformations are very different. So far, there have been no models that predict the power-law statistics for discontinuous flow. Furthermore, the statistics of the acoustic emission signals in jerky flow is even more complex, requiring multifractal measures for a proper characterization. There has been no model that explains the complex statistics either. Here we address the problem of statistical characterization of the acoustic emission signals associated with the three types of the Portevin-Le Chatelier bands. Following our recently proposed general framework for calculating acoustic emission, we set up a wave equation for the elastic degrees of freedom with a plastic strain rate as a source term. The energy dissipated during acoustic emission is represented by the Rayleigh-dissipation function. Using the plastic strain rate obtained from the Ananthakrishna model for the Portevin-Le Chatelier effect, we compute the acoustic emission signals associated with the three Portevin-Le Chatelier bands and the Lüders-like band. The so-calculated acoustic emission signals are used for further statistical characterization. Our results show that the model predicts power-law statistics for all the acoustic emission signals associated with the three types of Portevin-Le Chatelier bands with the exponent values increasing with increasing strain rate. The calculated multifractal spectra corresponding to the acoustic emission signals associated with the three band types have a maximum spread for the type C bands and decreasing with types B and A. We further show that the acoustic emission signals associated with Lüders-like band also exhibit a power-law distribution and multifractality.

Modeling the complexity of acoustic emission during intermittent plastic deformation: Power laws and multifractal spectra.

PubMed

Kumar, Jagadish; Ananthakrishna, G

2018-01-01

Scale-invariant power-law distributions for acoustic emission signals are ubiquitous in several plastically deforming materials. However, power-law distributions for acoustic emission energies are reported in distinctly different plastically deforming situations such as hcp and fcc single and polycrystalline samples exhibiting smooth stress-strain curves and in dilute metallic alloys exhibiting discontinuous flow. This is surprising since the underlying dislocation mechanisms in these two types of deformations are very different. So far, there have been no models that predict the power-law statistics for discontinuous flow. Furthermore, the statistics of the acoustic emission signals in jerky flow is even more complex, requiring multifractal measures for a proper characterization. There has been no model that explains the complex statistics either. Here we address the problem of statistical characterization of the acoustic emission signals associated with the three types of the Portevin-Le Chatelier bands. Following our recently proposed general framework for calculating acoustic emission, we set up a wave equation for the elastic degrees of freedom with a plastic strain rate as a source term. The energy dissipated during acoustic emission is represented by the Rayleigh-dissipation function. Using the plastic strain rate obtained from the Ananthakrishna model for the Portevin-Le Chatelier effect, we compute the acoustic emission signals associated with the three Portevin-Le Chatelier bands and the Lüders-like band. The so-calculated acoustic emission signals are used for further statistical characterization. Our results show that the model predicts power-law statistics for all the acoustic emission signals associated with the three types of Portevin-Le Chatelier bands with the exponent values increasing with increasing strain rate. The calculated multifractal spectra corresponding to the acoustic emission signals associated with the three band types have a maximum spread for the type C bands and decreasing with types B and A. We further show that the acoustic emission signals associated with Lüders-like band also exhibit a power-law distribution and multifractality.

Intelligent Prediction of Fan Rotation Stall in Power Plants Based on Pressure Sensor Data Measured In-Situ

PubMed Central

Xu, Xiaogang; Wang, Songling; Liu, Jinlian; Liu, Xinyu

2014-01-01

Blower and exhaust fans consume over 30% of electricity in a thermal power plant, and faults of these fans due to rotation stalls are one of the most frequent reasons for power plant outage failures. To accurately predict the occurrence of fan rotation stalls, we propose a support vector regression machine (SVRM) model that predicts the fan internal pressures during operation, leaving ample time for rotation stall detection. We train the SVRM model using experimental data samples, and perform pressure data prediction using the trained SVRM model. To prove the feasibility of using the SVRM model for rotation stall prediction, we further process the predicted pressure data via wavelet-transform-based stall detection. By comparison of the detection results from the predicted and measured pressure data, we demonstrate that the SVRM model can accurately predict the fan pressure and guarantee reliable stall detection with a time advance of up to 0.0625 s. This superior pressure data prediction capability leaves significant time for effective control and prevention of fan rotation stall faults. This model has great potential for use in intelligent fan systems with stall prevention capability, which will ensure safe operation and improve the energy efficiency of power plants. PMID:24854057

Size effects and charge transport in metals: Quantum theory of the resistivity of nanometric metallic structures arising from electron scattering by grain boundaries and by rough surfaces

NASA Astrophysics Data System (ADS)

Munoz, Raul C.; Arenas, Claudio

2017-03-01

We discuss recent progress regarding size effects and their incidence upon the coefficients describing charge transport (resistivity, magnetoresistance, and Hall effect) induced by electron scattering from disordered grain boundaries and from rough surfaces on metallic nanostructures; we review recent measurements of the magneto transport coefficients that elucidate the electron scattering mechanisms at work. We review as well theoretical developments regarding quantum transport theories that allow calculating the increase in resistivity induced by electron-rough surface scattering (in the absence of grain boundaries) from first principles—from the parameters that describe the surface roughness that can be measured with a Scanning Tunnelling Microscope (STM). We evaluate the predicting power of the quantum version of the Fuchs-Sondheimer theory and of the model proposed by Calecki, abandoning the method of parameter fitting used for decades, but comparing instead theoretical predictions with resistivity measured in thin films where surface roughness has also been measured with a STM, and where electron-grain boundary scattering can be neglected. We also review the theory of Mayadas and Shatzkes (MS) [Phys. Rev. B 1, 1382 (1970)] used for decades, and discuss its severe conceptual difficulties that arise out of the fact that: (i) MS employed plane waves to describe the electronic states within the metal sample having periodic grain boundaries, rather than the Bloch states known since the thirties to be the solutions of the Schrödinger equation describing electrons propagating through a Krönig-Penney [Proc. R. Soc. London Ser. A 130, 499 (1931)] periodic potential; (ii) MS ignored the fact that the wave functions describing electrons propagating through a 1-D disordered potential are expected to decay exponentially with increasing distance, a fact known since the work of Anderson [Phys. Rev. 109, 1492 (1958)] in 1958 for which he was awarded the Nobel Prize in 1977; (iii) The current in the sample should be proportional to TN, the probability that an electron traverses N consecutive (disordered) grains found along a mean free path; MS assumed that TN = 1. We review unpublished details of a quantum transport theory based upon a model of diffusive transport and Kubo's linear response formalism recently published [Arenas et al., Appl. Surf. Sci. 329, 184 (2015)], which permits estimating the increase in resistivity of a metallic specimen (over the bulk resistivity) under the combined effects of electron scattering by phonons, impurities, disordered grain boundaries, and rough surfaces limiting the sample. We evaluate the predicting power of both the MS theory and of the new quantum model on samples where the temperature dependence of the resistivity has been measured between 4 K and 300 K, and where surface roughness and grain size distribution has been measured on each sample via independent experiments. We find that the quantum theory does exhibit a predicting power, whereas the predicting power of the MS model as well as the significance and reliability of its fitting parameters seems questionable. We explore the power of the new theory by comparing, for the first time, the resistivity predicted and measured on nanometric Cu wires of (approximately) rectangular cross section employed in building integrated circuits, based upon a quantum description of electron motion.

Effect of the equivalent refractive index on intraocular lens power prediction with ray tracing after myopic laser in situ keratomileusis.

PubMed

Canovas, Carmen; van der Mooren, Marrie; Rosén, Robert; Piers, Patricia A; Wang, Li; Koch, Douglas D; Artal, Pablo

2015-05-01

To determine the impact of the equivalent refractive index (ERI) on intraocular lens (IOL) power prediction for eyes with previous myopic laser in situ keratomileusis (LASIK) using custom ray tracing. AMO B.V., Groningen, the Netherlands, and the Department of Ophthalmology, Baylor College of Medicine, Houston, Texas, USA. Retrospective data analysis. The ERI was calculated individually from the post-LASIK total corneal power. Two methods to account for the posterior corneal surface were tested; that is, calculation from pre-LASIK data or from post-LASIK data only. Four IOL power predictions were generated using a computer-based ray-tracing technique, including individual ERI results from both calculation methods, a mean ERI over the whole population, and the ERI for normal patients. For each patient, IOL power results calculated from the four predictions as well as those obtained with the Haigis-L were compared with the optimum IOL power calculated after cataract surgery. The study evaluated 25 patients. The mean and range of ERI values determined using post-LASIK data were similar to those determined from pre-LASIK data. Introducing individual or an average ERI in the ray-tracing IOL power calculation procedure resulted in mean IOL power errors that were not significantly different from zero. The ray-tracing procedure that includes an average ERI gave a greater percentage of eyes with an IOL power prediction error within ±0.5 diopter than the Haigis-L (84% versus 52%). For IOL power determination in post-LASIK patients, custom ray tracing including a modified ERI was an accurate procedure that exceeded the current standards for normal eyes. Copyright © 2015 ASCRS and ESCRS. Published by Elsevier Inc. All rights reserved.

The influence of impression management scales on the Personality Assessment Inventory in the epilepsy monitoring unit.

PubMed

Purdom, Catherine L; Kirlin, Kristin A; Hoerth, Matthew T; Noe, Katherine H; Drazkowski, Joseph F; Sirven, Joseph I; Locke, Dona E C

2012-12-01

The Somatic Complaints scale (SOM) and Conversion subscale (SOM-C) of the Personality Assessment Inventory perform best in classifying psychogenic non-epileptic seizures (PNES) from epileptic seizures (ES); however, the impact of positive impression management (PIM) and negative impression management (NIM) scales on SOM and SOM-C classification has not been examined. We studied 187 patients from an epilepsy monitoring unit with confirmed PNES or ES. On SOM, the best cut score was 72.5 T when PIM was elevated and 69.5 T when there was no bias. On SOM-C, when PIM was elevated, the best cut score was 67.5 T and 76.5 T when there was no bias. Negative impression management elevations (n=9) were too infrequent to analyze separately. Despite similarities in classification accuracy, there were differences in sensitivity and specificity with and without PIM, impacting positive and negative predictive values. The presence of PIM bias generally increases positive predictive power of SOM and SOM-C but decreases negative predictive power. Copyright © 2012 Elsevier Inc. All rights reserved.

Advancing solar energy forecasting through the underlying physics

NASA Astrophysics Data System (ADS)

Yang, H.; Ghonima, M. S.; Zhong, X.; Ozge, B.; Kurtz, B.; Wu, E.; Mejia, F. A.; Zamora, M.; Wang, G.; Clemesha, R.; Norris, J. R.; Heus, T.; Kleissl, J. P.

2017-12-01

As solar power comprises an increasingly large portion of the energy generation mix, the ability to accurately forecast solar photovoltaic generation becomes increasingly important. Due to the variability of solar power caused by cloud cover, knowledge of both the magnitude and timing of expected solar power production ahead of time facilitates the integration of solar power onto the electric grid by reducing electricity generation from traditional ancillary generators such as gas and oil power plants, as well as decreasing the ramping of all generators, reducing start and shutdown costs, and minimizing solar power curtailment, thereby providing annual economic value. The time scales involved in both the energy markets and solar variability range from intra-hour to several days ahead. This wide range of time horizons led to the development of a multitude of techniques, with each offering unique advantages in specific applications. For example, sky imagery provides site-specific forecasts on the minute-scale. Statistical techniques including machine learning algorithms are commonly used in the intra-day forecast horizon for regional applications, while numerical weather prediction models can provide mesoscale forecasts on both the intra-day and days-ahead time scale. This talk will provide an overview of the challenges unique to each technique and highlight the advances in their ongoing development which come alongside advances in the fundamental physics underneath.

Effect of genetic architecture on the prediction accuracy of quantitative traits in samples of unrelated individuals.

PubMed

Morgante, Fabio; Huang, Wen; Maltecca, Christian; Mackay, Trudy F C

2018-06-01

Predicting complex phenotypes from genomic data is a fundamental aim of animal and plant breeding, where we wish to predict genetic merits of selection candidates; and of human genetics, where we wish to predict disease risk. While genomic prediction models work well with populations of related individuals and high linkage disequilibrium (LD) (e.g., livestock), comparable models perform poorly for populations of unrelated individuals and low LD (e.g., humans). We hypothesized that low prediction accuracies in the latter situation may occur when the genetics architecture of the trait departs from the infinitesimal and additive architecture assumed by most prediction models. We used simulated data for 10,000 lines based on sequence data from a population of unrelated, inbred Drosophila melanogaster lines to evaluate this hypothesis. We show that, even in very simplified scenarios meant as a stress test of the commonly used Genomic Best Linear Unbiased Predictor (G-BLUP) method, using all common variants yields low prediction accuracy regardless of the trait genetic architecture. However, prediction accuracy increases when predictions are informed by the genetic architecture inferred from mapping the top variants affecting main effects and interactions in the training data, provided there is sufficient power for mapping. When the true genetic architecture is largely or partially due to epistatic interactions, the additive model may not perform well, while models that account explicitly for interactions generally increase prediction accuracy. Our results indicate that accounting for genetic architecture can improve prediction accuracy for quantitative traits.

Status of NASA's Stirling Space Power Converter Program

NASA Technical Reports Server (NTRS)

Dudenhoefer, James E.; Winter, Jerry M.

1991-01-01

An overview is presented of the NASA-Lewis Free-Piston Stirling Space Power Convertor Technology Program. The goal is to develop the technology base needed to meet the long duration, high capacity power requirements for future NASA space initiatives. Efforts are focused upon increasing system power output and system thermal and electric energy conversion efficiency at least fivefold over current SP-100 technology, and on achieving systems that are compatible with space nuclear reactors. Stirling experience in space and progress toward 1050 and 1300 K Stirling Space Power Converters is discussed. Fabrication is nearly completed for the 1050 K Component Test Power Converters (CTPC); results of motoring tests of cold end (525 K), are presented. The success of these and future designs is dependent upon supporting research and technology efforts including heat pipes, bearings, superalloy joining technologies, high efficiency alternators, life and reliability testing and predictive methodologies. An update is provided of progress in some of these technologies leading off with a discussion of free-piston Stirling experience in space.

Study on Battery Capacity for Grid-connection Power Planning with Forecasts in Clustered Photovoltaic Systems

NASA Astrophysics Data System (ADS)

Shimada, Takae; Kawasaki, Norihiro; Ueda, Yuzuru; Sugihara, Hiroyuki; Kurokawa, Kosuke

This paper aims to clarify the battery capacity required by a residential area with densely grid-connected photovoltaic (PV) systems. This paper proposes a planning method of tomorrow's grid-connection power from/to the external electric power system by using demand power forecasting and insolation forecasting for PV power predictions, and defines a operation method of the electricity storage device to control the grid-connection power as planned. A residential area consisting of 389 houses consuming 2390 MWh/year of electricity with 2390kW PV systems is simulated based on measured data and actual forecasts. The simulation results show that 8.3MWh of battery capacity is required in the conditions of half-hour planning and 1% or less of planning error ratio and PV output limiting loss ratio. The results also show that existing technologies of forecasting reduce required battery capacity to 49%, and increase the allowable installing PV amount to 210%.

An Overview of Different Approaches for Battery Lifetime Prediction

NASA Astrophysics Data System (ADS)

Zhang, Peng; Liang, Jun; Zhang, Feng

2017-05-01

With the rapid development of renewable energy and the continuous improvement of the power supply reliability, battery energy storage technology has been wildly used in power system. Battery degradation is a nonnegligible issue when battery energy storage system participates in system design and operation strategies optimization. The health assessment and remaining cycle life estimation of battery gradually become a challenge and research hotspot in many engineering areas. In this paper, the battery capacity falling and internal resistance increase are presented on the basis of chemical reactions inside the battery. The general life prediction models are analysed from several aspects. The characteristics of them as well as their application scenarios are discussed in the survey. In addition, a novel weighted Ah ageing model with the introduction of the Ragone curve is proposed to provide a detailed understanding of the ageing processes. A rigorous proof of the mathematical theory about the proposed model is given in the paper.

SINGLE NEURON ACTIVITY AND THETA MODULATION IN POSTRHINAL CORTEX DURING VISUAL OBJECT DISCRIMINATION

PubMed Central

Furtak, Sharon C.; Ahmed, Omar J.; Burwell, Rebecca D.

2012-01-01

Postrhinal cortex, the rodent homolog of the primate parahippocampal cortex, processes spatial and contextual information. Our hypothesis of postrhinal function is that it serves to encode context, in part, by forming representations that link objects to places. We recorded postrhinal neuronal activity and local field potentials (LFPs) in rats trained on a two-choice, visual discrimination task. As predicted, a large proportion of postrhinal neurons signaled object-location conjunctions. In addition, postrhinal LFPs exhibited strong oscillatory rhythms in the theta band, and many postrhinal neurons were phase locked to theta. Although correlated with running speed, theta power was lower than predicted by speed alone immediately before and after choice. However, theta power was significantly increased following incorrect decisions, suggesting a role in signaling error. These findings provide evidence that postrhinal cortex encodes representations that link objects to places and suggest that postrhinal theta modulation extends to cognitive as well as spatial functions. PMID:23217745

Enhanced thermoelectric performance of graphene nanoribbon-based devices

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hossain, Md Sharafat, E-mail: hossain@student.unimelb.edu.au; Huynh, Duc Hau; Nguyen, Phuong Duc

There have been numerous theoretical studies on exciting thermoelectric properties of graphene nano-ribbons (GNRs); however, most of these studies are mainly based on simulations. In this work, we measure and characterize the thermoelectric properties of GNRs and compare the results with theoretical predictions. Our experimental results verify that nano-structuring and patterning graphene into nano-ribbons significantly enhance its thermoelectric power, confirming previous predictions. Although patterning results in lower conductance (G), the overall power factor (S{sup 2}G) increases for nanoribbons. We demonstrate that edge roughness plays an important role in achieving such an enhanced performance and support it through first principles simulations.more » We show that uncontrolled edge roughness, which is considered detrimental in GNR-based electronic devices, leads to enhanced thermoelectric performance of GNR-based thermoelectric devices. The result validates previously reported theoretical studies of GNRs and demonstrates the potential of GNRs for the realization of highly efficient thermoelectric devices.« less

Predictability of Landslide Timing From Quasi-Periodic Precursory Earthquakes

NASA Astrophysics Data System (ADS)

Bell, Andrew F.

2018-02-01

Accelerating rates of geophysical signals are observed before a range of material failure phenomena. They provide insights into the physical processes controlling failure and the basis for failure forecasts. However, examples of accelerating seismicity before landslides are rare, and their behavior and forecasting potential are largely unknown. Here I use a Bayesian methodology to apply a novel gamma point process model to investigate a sequence of quasiperiodic repeating earthquakes preceding a large landslide at Nuugaatsiaq in Greenland in June 2017. The evolution in earthquake rate is best explained by an inverse power law increase with time toward failure, as predicted by material failure theory. However, the commonly accepted power law exponent value of 1.0 is inconsistent with the data. Instead, the mean posterior value of 0.71 indicates a particularly rapid acceleration toward failure and suggests that only relatively short warning times may be possible for similar landslides in future.

Research on regional numerical weather prediction

NASA Technical Reports Server (NTRS)

Kreitzberg, C. W.

1976-01-01

Extension of the predictive power of dynamic weather forecasting to scales below the conventional synoptic or cyclonic scales in the near future is assessed. Lower costs per computation, more powerful computers, and a 100 km mesh over the North American area (with coarser mesh extending beyond it) are noted at present. Doubling the resolution even locally (to 50 km mesh) would entail a 16-fold increase in costs (including vertical resolution and halving the time interval), and constraints on domain size and length of forecast. Boundary conditions would be provided by the surrounding 100 km mesh, and time-varying lateral boundary conditions can be considered to handle moving phenomena. More physical processes to treat, more efficient numerical techniques, and faster computers (improved software and hardware) backing up satellite and radar data could produce further improvements in forecasting in the 1980s. Boundary layer modeling, initialization techniques, and quantitative precipitation forecasting are singled out among key tasks.

The gravitational wave contribution to cosmic microwave background anisotropies and the amplitude of mass fluctuations from COBE results

NASA Technical Reports Server (NTRS)

Lucchin, Francesco; Matarrese, Sabino; Mollerach, Silvia

1992-01-01

A stochastic background of primordial gravitational waves may substantially contribute, via the Sachs-Wolfe effect, to the large-scale cosmic microwave background (CMB) anisotropies recently detected by COBE. This implies a bias in any resulting determination of the primordial amplitude of density fluctuations. We consider the constraints imposed on n is less than 1 ('tilted') power-law fluctuation spectra, taking into account the contribution from both scalar and tensor waves, as predicted by power-law inflation. The gravitational wave contribution to CMB anisotropies generally reduces the required rms level of mass fluctuation, thereby increasing the linear bias parameter, even in models where the spectral index is close to the Harrison-Zel'dovich value n = 1. This 'gravitational wave bias' helps to reconcile the predictions of CDM models with observations on pairwise galaxy velocity dispersion on small scales.

Clinical prediction and the idea of a population.

PubMed

Armstrong, David

2017-04-01

Using an analysis of the British Medical Journal over the past 170 years, this article describes how changes in the idea of a population have informed new technologies of medical prediction. These approaches have largely replaced older ideas of clinical prognosis based on understanding the natural histories of the underlying pathologies. The 19 th -century idea of a population, which provided a denominator for medical events such as births and deaths, was constrained in its predictive power by its method of enumerating individual bodies. During the 20 th century, populations were increasingly constructed through inferential techniques based on patient groups and samples seen to possess variable characteristics. The emergence of these new virtual populations created the conditions for the emergence of predictive algorithms that are used to foretell our medical futures.

Multiple high-intensity focused ultrasound probes for kidney-tissue ablation.

PubMed

Häcker, Axel; Chauhan, Sunita; Peters, Kristina; Hildenbrand, Ralf; Marlinghaus, Ernst; Alken, Peter; Michel, Maurice Stephan

2005-10-01

To investigate kidney-tissue ablation by high-intensity focused ultrasound (HIFU) using multiple and single probes. Ultrasound beams (1.75 MHz) produced by a piezoceramic element (focal distance 80 mm) were focused at the center of renal parenchyma. One of the three probes (mounted on a jig) could also be used for comparison with a single probe at comparable power ratings. Lesion dimensions were examined in perfused and unperfused ex vivo porcine kidneys at different power levels (40, 60, and 80 W) and treatment times (4, 6, and 8 seconds). At identical power levels, the lesions induced by multiple probes were larger than those induced by a single probe. Lesion size increased with increasing pulse duration and generator power. The sizes and shapes of the lesions were predictably repeatable in all samples. Lesions in perfused kidneys were smaller than those in unperfused kidneys. Ex vivo, kidney-tissue ablation by means of multiple HIFU probes offers significant advantages over single HIFU probes in respect of lesion size and formation. These advantages need to be confirmed by tests in vivo at higher energy levels.

Using Reanalysis Data for the Prediction of Seasonal Wind Turbine Power Losses Due to Icing

NASA Astrophysics Data System (ADS)

Burtch, D.; Mullendore, G. L.; Delene, D. J.; Storm, B.

2013-12-01

The Northern Plains region of the United States is home to a significant amount of potential wind energy. However, in winter months capturing this potential power is severely impacted by the meteorological conditions, in the form of icing. Predicting the expected loss in power production due to icing is a valuable parameter that can be used in wind turbine operations, determination of wind turbine site locations and long-term energy estimates which are used for financing purposes. Currently, losses due to icing must be estimated when developing predictions for turbine feasibility and financing studies, while icing maps, a tool commonly used in Europe, are lacking in the United States. This study uses the Modern-Era Retrospective Analysis for Research and Applications (MERRA) dataset in conjunction with turbine production data to investigate various methods of predicting seasonal losses (October-March) due to icing at two wind turbine sites located 121 km apart in North Dakota. The prediction of icing losses is based on temperature and relative humidity thresholds and is accomplished using three methods. For each of the three methods, the required atmospheric variables are determined in one of two ways: using industry-specific software to correlate anemometer data in conjunction with the MERRA dataset and using only the MERRA dataset for all variables. For each season, a percentage of the total expected generated power lost due to icing is determined and compared to observed losses from the production data. An optimization is performed in order to determine the relative humidity threshold that minimizes the difference between the predicted and observed values. Eight seasons of data are used to determine an optimal relative humidity threshold, and a further three seasons of data are used to test this threshold. Preliminary results have shown that the optimized relative humidity threshold for the northern turbine is higher than the southern turbine for all methods. For the three test seasons, the optimized thresholds tend to under-predict the icing losses. However, the threshold determined using boundary layer similarity theory most closely predicts the power losses due to icing versus the other methods. For the northern turbine, the average predicted power loss over the three seasons is 4.65 % while the observed power loss is 6.22 % (average difference of 1.57 %). For the southern turbine, the average predicted power loss and observed power loss over the same time period are 4.43 % and 6.16 %, respectively (average difference of 1.73 %). The three-year average, however, does not clearly capture the variability that exists season-to-season. On examination of each of the test seasons individually, the optimized relative humidity threshold methodology performs better than fixed power loss estimates commonly used in the wind energy industry.

Reservoir characterization of the Upper Jurassic geothermal target formations (Molasse Basin, Germany): role of thermofacies as exploration tool

NASA Astrophysics Data System (ADS)

Homuth, S.; Götz, A. E.; Sass, I.

2015-06-01

The Upper Jurassic carbonates of the southern German Molasse Basin are the target of numerous geothermal combined heat and power production projects since the year 2000. A production-orientated reservoir characterization is therefore of high economic interest. Outcrop analogue studies enable reservoir property prediction by determination and correlation of lithofacies-related thermo- and petrophysical parameters. A thermofacies classification of the carbonate formations serves to identify heterogeneities and production zones. The hydraulic conductivity is mainly controlled by tectonic structures and karstification, whilst the type and grade of karstification is facies related. The rock permeability has only a minor effect on the reservoir's sustainability. Physical parameters determined on oven-dried samples have to be corrected, applying reservoir transfer models to water-saturated reservoir conditions. To validate these calculated parameters, a Thermo-Triaxial-Cell simulating the temperature and pressure conditions of the reservoir is used and calorimetric and thermal conductivity measurements under elevated temperature conditions are performed. Additionally, core and cutting material from a 1600 m deep research drilling and a 4850 m (total vertical depth, measured depth: 6020 m) deep well is used to validate the reservoir property predictions. Under reservoir conditions a decrease in permeability of 2-3 magnitudes is observed due to the thermal expansion of the rock matrix. For tight carbonates the matrix permeability is temperature-controlled; the thermophysical matrix parameters are density-controlled. Density increases typically with depth and especially with higher dolomite content. Therefore, thermal conductivity increases; however the dominant factor temperature also decreases the thermal conductivity. Specific heat capacity typically increases with increasing depth and temperature. The lithofacies-related characterization and prediction of reservoir properties based on outcrop and drilling data demonstrates that this approach is a powerful tool for exploration and operation of geothermal reservoirs.

An increasing electromechanical window is a predictive marker of ventricular fibrillation in anesthetized rabbit with ischemic heart.

PubMed

Limprasutr, Vudhiporn; Pirintr, Prapawadee; Kijtawornrat, Anusak; Hamlin, Robert L

2018-05-10

The QTc interval is widely used in Safety Pharmacological studies to predict arrhythmia risk, and the electromechanical window (EMW) and short-term variability of QT intervals (STV QT ) have been studied as new biomarkers for drug-induced Torsades de Pointes (TdP). However, the use of EMW and STV QT to predict ventricular fibrillation (VF) has not been elucidated. This study aimed to evaluate EMW and STV QT to predict VF in anesthetized rabbit model of VF. VF was induced by ligation of the left anterior descending and a descending branch of the left circumflex coronary arteries in a sample population of rabbits (n=18). VF was developed 55.6% (10/18). In rabbit with VF, the EMW was significantly higher than in rabbits without VF (96.3 ± 15.6 ms and 49.5 ± 5.6 ms, respectively, P<0.05). STV QT had significantly increased before the onset of VF in rabbits that experienced VF, but not in rabbits that did not experience VF (11.7 ± 1.8 ms and 3.7 ± 0.4 ms, respectively, P<0.05). The EMW and STV QT had better predictive power for VF with higher sensitivity and specificity than the QTc measure. The result suggested that the increasing of EMW, as well as the elevation of STV QT , can potentially be used as biomarkers for predicting of VF.

Data processing and optimization system to study prospective interstate power interconnections

NASA Astrophysics Data System (ADS)

Podkovalnikov, Sergei; Trofimov, Ivan; Trofimov, Leonid

2018-01-01

The paper presents Data processing and optimization system for studying and making rational decisions on the formation of interstate electric power interconnections, with aim to increasing effectiveness of their functioning and expansion. The technologies for building and integrating a Data processing and optimization system including an object-oriented database and a predictive mathematical model for optimizing the expansion of electric power systems ORIRES, are described. The technology of collection and pre-processing of non-structured data collected from various sources and its loading to the object-oriented database, as well as processing and presentation of information in the GIS system are described. One of the approaches of graphical visualization of the results of optimization model is considered on the example of calculating the option for expansion of the South Korean electric power grid.

Improved accuracy of intraocular lens power calculation with the Zeiss IOLMaster.

PubMed

Olsen, Thomas

2007-02-01

This study aimed to demonstrate how the level of accuracy in intraocular lens (IOL) power calculation can be improved with optical biometry using partial optical coherence interferometry (PCI) (Zeiss IOLMaster) and current anterior chamber depth (ACD) prediction algorithms. Intraocular lens power in 461 consecutive cataract operations was calculated using both PCI and ultrasound and the accuracy of the results of each technique were compared. To illustrate the importance of ACD prediction per se, predictions were calculated using both a recently published 5-variable method and the Haigis 2-variable method and the results compared. All calculations were optimized in retrospect to account for systematic errors, including IOL constants and other off-set errors. The average absolute IOL prediction error (observed minus expected refraction) was 0.65 dioptres with ultrasound and 0.43 D with PCI using the 5-variable ACD prediction method (p < 0.00001). The number of predictions within +/- 0.5 D, +/- 1.0 D and +/- 2.0 D of the expected outcome was 62.5%, 92.4% and 99.9% with PCI, compared with 45.5%, 77.3% and 98.4% with ultrasound, respectively (p < 0.00001). The 2-variable ACD method resulted in an average error in PCI predictions of 0.46 D, which was significantly higher than the error in the 5-variable method (p < 0.001). The accuracy of IOL power calculation can be significantly improved using calibrated axial length readings obtained with PCI and modern IOL power calculation formulas incorporating the latest generation ACD prediction algorithms.

Potential role of liver enzymes levels as predictor markers of glucose metabolism disorders in Tunisian population.

PubMed

Bouhajja, Houda; Abdelhedi, Rania; Amouri, Ali; Hadj Kacem, Faten; Marrakchi, Rim; Safi, Wajdi; Mrabet, Houcem; Chtourou, Lassaad; Charfi, Nadia; Fourati, Mouna; Bensassi, Salwa; Jamoussi, Kamel; Abid, Mohamed; Ayadi, Hammadi; Feki, Mouna Mnif; Elleuch, Noura Bougacha

2018-03-10

The relationship between liver enzymes and type 2 diabetes (T2D) risk is inconclusive. We aimed to evaluate the association between liver markers and risk of carbohydrate metabolism disorders and their discriminatory power for T2D prediction. This cross-sectional study enrolled 216 participants classified as normoglycemic, prediabetes, newly-diagnosed diabetes and diagnosed diabetes. All participants underwent anthropometric and biochemical measurements. The relationship between hepatic enzymes and glucose metabolism markers was evaluated by ANCOVA analyses. The associations between liver enzymes and incident carbohydrate metabolism disorders were analyzed through logistic regression and their discriminatory capacity for T2D by receiver operating characteristic (ROC) analysis. High alkaline phosphatase (AP), alanine aminotransferase (ALT), γ-glutamyltransferase (γGT) and aspartate aminotrasferase (AST) levels were independently related to decreased insulin sensitivity. Interestingly, higher AP level was significantly associated with increased risk of prediabetes (p=0.017), newly-diagnosed diabetes (p=0.004) and T2D (p=0.007). Elevated γGT level was an independent risk factor for T2D (p=0.032) and undiagnosed-T2D (p=0.010) in prediabetic and normoglycemic subjects, respectively. In ROC analysis, AP was a powerful predictor of incident diabetes and significantly improved T2D prediction. Liver enzymes within normal range, specifically AP levels, are associated with increased risk of carbohydrate metabolism disorders and significantly improved T2D prediction.

Large eddy simulation for predicting turbulent heat transfer in gas turbines

PubMed Central

Tafti, Danesh K.; He, Long; Nagendra, K.

2014-01-01

Blade cooling technology will play a critical role in the next generation of propulsion and power generation gas turbines. Accurate prediction of blade metal temperature can avoid the use of excessive compressed bypass air and allow higher turbine inlet temperature, increasing fuel efficiency and decreasing emissions. Large eddy simulation (LES) has been established to predict heat transfer coefficients with good accuracy under various non-canonical flows, but is still limited to relatively simple geometries and low Reynolds numbers. It is envisioned that the projected increase in computational power combined with a drop in price-to-performance ratio will make system-level simulations using LES in complex blade geometries at engine conditions accessible to the design process in the coming one to two decades. In making this possible, two key challenges are addressed in this paper: working with complex intricate blade geometries and simulating high-Reynolds-number (Re) flows. It is proposed to use the immersed boundary method (IBM) combined with LES wall functions. A ribbed duct at Re=20 000 is simulated using the IBM, and a two-pass ribbed duct is simulated at Re=100 000 with and without rotation (rotation number Ro=0.2) using LES with wall functions. The results validate that the IBM is a viable alternative to body-conforming grids and that LES with wall functions reproduces experimental results at a much lower computational cost. PMID:25024418

Using a Guided Machine Learning Ensemble Model to Predict Discharge Disposition following Meningioma Resection.

PubMed

Muhlestein, Whitney E; Akagi, Dallin S; Kallos, Justiss A; Morone, Peter J; Weaver, Kyle D; Thompson, Reid C; Chambless, Lola B

2018-04-01

Objective  Machine learning (ML) algorithms are powerful tools for predicting patient outcomes. This study pilots a novel approach to algorithm selection and model creation using prediction of discharge disposition following meningioma resection as a proof of concept. Materials and Methods  A diversity of ML algorithms were trained on a single-institution database of meningioma patients to predict discharge disposition. Algorithms were ranked by predictive power and top performers were combined to create an ensemble model. The final ensemble was internally validated on never-before-seen data to demonstrate generalizability. The predictive power of the ensemble was compared with a logistic regression. Further analyses were performed to identify how important variables impact the ensemble. Results  Our ensemble model predicted disposition significantly better than a logistic regression (area under the curve of 0.78 and 0.71, respectively, p  = 0.01). Tumor size, presentation at the emergency department, body mass index, convexity location, and preoperative motor deficit most strongly influence the model, though the independent impact of individual variables is nuanced. Conclusion  Using a novel ML technique, we built a guided ML ensemble model that predicts discharge destination following meningioma resection with greater predictive power than a logistic regression, and that provides greater clinical insight than a univariate analysis. These techniques can be extended to predict many other patient outcomes of interest.

Career-Related Continuous Learning: Longitudinal Predictive Power of Employees' Job and Career Attitudes

ERIC Educational Resources Information Center

Rowold, Jens; Schilling, Jan

2006-01-01

Purpose: Within the framework of learning in organizations, the concept of career-related continuous learning (CRCL) has gained increasing attention from the research community. The purpose of the present study is to explore the combined effect of job- and career-related variables on formal CRCL activities. Design/methodology/approach: The study…

Hybrid robust predictive optimization method of power system dispatch

DOEpatents

Chandra, Ramu Sharat [Niskayuna, NY; Liu, Yan [Ballston Lake, NY; Bose, Sumit [Niskayuna, NY; de Bedout, Juan Manuel [West Glenville, NY

2011-08-02

A method of power system dispatch control solves power system dispatch problems by integrating a larger variety of generation, load and storage assets, including without limitation, combined heat and power (CHP) units, renewable generation with forecasting, controllable loads, electric, thermal and water energy storage. The method employs a predictive algorithm to dynamically schedule different assets in order to achieve global optimization and maintain the system normal operation.

Power capability evaluation for lithium iron phosphate batteries based on multi-parameter constraints estimation

NASA Astrophysics Data System (ADS)

Wang, Yujie; Pan, Rui; Liu, Chang; Chen, Zonghai; Ling, Qiang

2018-01-01

The battery power capability is intimately correlated with the climbing, braking and accelerating performance of the electric vehicles. Accurate power capability prediction can not only guarantee the safety but also regulate driving behavior and optimize battery energy usage. However, the nonlinearity of the battery model is very complex especially for the lithium iron phosphate batteries. Besides, the hysteresis loop in the open-circuit voltage curve is easy to cause large error in model prediction. In this work, a multi-parameter constraints dynamic estimation method is proposed to predict the battery continuous period power capability. A high-fidelity battery model which considers the battery polarization and hysteresis phenomenon is presented to approximate the high nonlinearity of the lithium iron phosphate battery. Explicit analyses of power capability with multiple constraints are elaborated, specifically the state-of-energy is considered in power capability assessment. Furthermore, to solve the problem of nonlinear system state estimation, and suppress noise interference, the UKF based state observer is employed for power capability prediction. The performance of the proposed methodology is demonstrated by experiments under different dynamic characterization schedules. The charge and discharge power capabilities of the lithium iron phosphate batteries are quantitatively assessed under different time scales and temperatures.

Field Measurement of the Acoustic Nonlinearity Parameter in Turbine Blades

NASA Technical Reports Server (NTRS)

Hinton, Yolanda L.; Na, Jeong K.; Yost, William T.; Kessel, Gregory L.

2000-01-01

Nonlinear acoustics techniques were used to measure fatigue in turbine blades in a power generation plant. The measurements were made in the field using a reference based measurement technique, and a reference sample previously measured in the laboratory. The acoustic nonlinearity parameter showed significant increase with fatigue in the blades, as indicated by service age and areas of increased stress. The technique shows promise for effectively measuring fatigue in field applications and predicting subsequent failures.

Balancing computation and communication power in power constrained clusters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Piga, Leonardo; Paul, Indrani; Huang, Wei

Systems, apparatuses, and methods for balancing computation and communication power in power constrained environments. A data processing cluster with a plurality of compute nodes may perform parallel processing of a workload in a power constrained environment. Nodes that finish tasks early may be power-gated based on one or more conditions. In some scenarios, a node may predict a wait duration and go into a reduced power consumption state if the wait duration is predicted to be greater than a threshold. The power saved by power-gating one or more nodes may be reassigned for use by other nodes. A cluster agentmore » may be configured to reassign the unused power to the active nodes to expedite workload processing.« less

The Usability of Noise Level from Rock Cutting for the Prediction of Physico-Mechanical Properties of Rocks

NASA Astrophysics Data System (ADS)

Delibalta, M. S.; Kahraman, S.; Comakli, R.

2015-11-01

Because the indirect tests are easier and cheaper than the direct tests, the prediction of rock properties from the indirect testing methods is important especially for the preliminary investigations. In this study, the predictability of the physico-mechanical rock properties from the noise level measured during cutting rock with diamond saw was investigated. Noise measurement test, uniaxial compressive strength (UCS) test, Brazilian tensile strength (BTS) test, point load strength (Is) test, density test, and porosity test were carried out on 54 different rock types in the laboratory. The results were statistically analyzed to derive estimation equations. Strong correlations between the noise level and the mechanical rock properties were found. The relations follow power functions. Increasing rock strength increases the noise level. Density and porosity also correlated strongly with the noise level. The relations follow linear functions. Increasing density increases the noise level while increasing porosity decreases the noise level. The developed equations are valid for the rocks with a compressive strength below 150 MPa. Concluding remark is that the physico-mechanical rock properties can reliably be estimated from the noise level measured during cutting the rock with diamond saw.

Testing mechanistic models of growth in insects.

PubMed

Maino, James L; Kearney, Michael R

2015-11-22

Insects are typified by their small size, large numbers, impressive reproductive output and rapid growth. However, insect growth is not simply rapid; rather, insects follow a qualitatively distinct trajectory to many other animals. Here we present a mechanistic growth model for insects and show that increasing specific assimilation during the growth phase can explain the near-exponential growth trajectory of insects. The presented model is tested against growth data on 50 insects, and compared against other mechanistic growth models. Unlike the other mechanistic models, our growth model predicts energy reserves per biomass to increase with age, which implies a higher production efficiency and energy density of biomass in later instars. These predictions are tested against data compiled from the literature whereby it is confirmed that insects increase their production efficiency (by 24 percentage points) and energy density (by 4 J mg(-1)) between hatching and the attainment of full size. The model suggests that insects achieve greater production efficiencies and enhanced growth rates by increasing specific assimilation and increasing energy reserves per biomass, which are less costly to maintain than structural biomass. Our findings illustrate how the explanatory and predictive power of mechanistic growth models comes from their grounding in underlying biological processes. © 2015 The Author(s).

Synchrophasor-Assisted Prediction of Stability/Instability of a Power System

NASA Astrophysics Data System (ADS)

Saha Roy, Biman Kumar; Sinha, Avinash Kumar; Pradhan, Ashok Kumar

2013-05-01

This paper presents a technique for real-time prediction of stability/instability of a power system based on synchrophasor measurements obtained from phasor measurement units (PMUs) at generator buses. For stability assessment the technique makes use of system severity indices developed using bus voltage magnitude obtained from PMUs and generator electrical power. Generator power is computed using system information and PMU information like voltage and current phasors obtained from PMU. System stability/instability is predicted when the indices exceeds a threshold value. A case study is carried out on New England 10-generator, 39-bus system to validate the performance of the technique.

Prediction of the effects of propeller operation on the static longitudinal stability of single-engine tractor monoplanes with flaps retracted

NASA Technical Reports Server (NTRS)

Weil, Joseph; Sleeman, William C , Jr

1949-01-01

The effects of propeller operation on the static longitudinal stability of single-engine tractor monoplanes are analyzed, and a simple method is presented for computing power-on pitching-moment curves for flap-retracted flight conditions. The methods evolved are based on the results of powered-model wind-tunnel investigations of 28 model configurations. Correlation curves are presented from which the effects of power on the downwash over the tail and the stabilizer effectiveness can be rapidly predicted. The procedures developed enable prediction of power-on longitudinal stability characteristics that are generally in very good agreement with experiment.

Improving Genomic Prediction in Cassava Field Experiments Using Spatial Analysis.

PubMed

Elias, Ani A; Rabbi, Ismail; Kulakow, Peter; Jannink, Jean-Luc

2018-01-04

Cassava ( Manihot esculenta Crantz) is an important staple food in sub-Saharan Africa. Breeding experiments were conducted at the International Institute of Tropical Agriculture in cassava to select elite parents. Taking into account the heterogeneity in the field while evaluating these trials can increase the accuracy in estimation of breeding values. We used an exploratory approach using the parametric spatial kernels Power, Spherical, and Gaussian to determine the best kernel for a given scenario. The spatial kernel was fit simultaneously with a genomic kernel in a genomic selection model. Predictability of these models was tested through a 10-fold cross-validation method repeated five times. The best model was chosen as the one with the lowest prediction root mean squared error compared to that of the base model having no spatial kernel. Results from our real and simulated data studies indicated that predictability can be increased by accounting for spatial variation irrespective of the heritability of the trait. In real data scenarios we observed that the accuracy can be increased by a median value of 3.4%. Through simulations, we showed that a 21% increase in accuracy can be achieved. We also found that Range (row) directional spatial kernels, mostly Gaussian, explained the spatial variance in 71% of the scenarios when spatial correlation was significant. Copyright © 2018 Elias et al.

A Neural Network Design for the Estimation of Nonlinear Behavior of a Magnetically-Excited Piezoelectric Harvester

NASA Astrophysics Data System (ADS)

Çelik, Emre; Uzun, Yunus; Kurt, Erol; Öztürk, Nihat; Topaloğlu, Nurettin

2018-01-01

An application of an artificial neural network (ANN) has been implemented in this article to model the nonlinear relationship of the harvested electrical power of a recently developed piezoelectric pendulum with respect to its resistive load R L and magnetic excitation frequency f. Prediction of harvested power for a wide range is a difficult task, because it increases dramatically when f gets closer to the natural frequency f 0 of the system. The neural model of the concerned system is designed upon the basis of a standard multi-layer network with a back propagation learning algorithm. Input data, termed input patterns, to present to the network and the respective output data, termed output patterns, describing desired network output that are carefully collected from the experiment under several conditions in order to train the developed network accurately. Results have indicated that the designed ANN is an effective means for predicting the harvested power of the piezoelectric harvester as functions of R L and f with a root mean square error of 6.65 × 10-3 for training and 1.40 for different test conditions. Using the proposed approach, the harvested power can be estimated reasonably without tackling the difficulty of experimental studies and complexity of analytical formulas representing the concerned system.

Nitrogen oxides emissions from thermal power plants in china: current status and future predictions.

PubMed

Tian, Hezhong; Liu, Kaiyun; Hao, Jiming; Wang, Yan; Gao, Jiajia; Qiu, Peipei; Zhu, Chuanyong

2013-10-01

Increasing emissions of nitrogen oxides (NOx) over the Chinese mainland have been of great concern due to their adverse impacts on regional air quality and public health. To explore and obtain the temporal and spatial characteristics of NOx emissions from thermal power plants in China, a unit-based method is developed. The method assesses NOx emissions based on detailed information on unit capacity, boiler and burner patterns, feed fuel types, emission control technologies, and geographical locations. The national total NOx emissions in 2010 are estimated at 7801.6 kt, of which 5495.8 kt is released from coal-fired power plant units of considerable size between 300 and 1000 MW. The top provincial emitter is Shandong where plants are densely concentrated. The average NOx-intensity is estimated at 2.28 g/kWh, markedly higher than that of developed countries, mainly owing to the inadequate application of high-efficiency denitrification devices such as selective catalytic reduction (SCR). Future NOx emissions are predicted by applying scenario analysis, indicating that a reduction of about 40% by the year 2020 can be achieved compared with emissions in 2010. These results suggest that NOx emissions from Chinese thermal power plants could be substantially mitigated within 10 years if reasonable control measures were implemented effectively.

An Operating Method Using Prediction of Photovoltaic Power for a Photovoltaic-Diesel Hybrid Power Generation System

NASA Astrophysics Data System (ADS)

Yamamoto, Shigehiro; Sumi, Kazuyoshi; Nishikawa, Eiichi; Hashimoto, Takeshi

This paper describes a novel operating method using prediction of photovoltaic (PV) power for a photovoltaic-diesel hybrid power generation system. The system is composed of a PV array, a storage battery, a bi-directional inverter and a diesel engine generator (DG). The proposed method enables the system to save fuel consumption by using PV energy effectively, reducing charge and discharge energy of the storage battery, and avoiding low-load operation of the DG. The PV power is simply predicted from a theoretical equation of solar radiation and the observed PV energy for a constant time before the prediction. The amount of fuel consumption of the proposed method is compared with that of other methods by a simulation based on measurement data of the PV power at an actual PV generation system for one year. The simulation results indicate that the amount of fuel consumption of the proposed method is smaller than that of any other methods, and is close to that of the ideal operation of the DG.

Laser cutting of various materials: Kerf width size analysis and life cycle assessment of cutting process

NASA Astrophysics Data System (ADS)

Yilbas, Bekir Sami; Shaukat, Mian Mobeen; Ashraf, Farhan

2017-08-01

Laser cutting of various materials including Ti-6Al-4V alloy, steel 304, Inconel 625, and alumina is carried out to assess the kerf width size variation along the cut section. The life cycle assessment is carried out to determine the environmental impact of the laser cutting in terms of the material waste during the cutting process. The kerf width size is formulated and predicted using the lump parameter analysis and it is measured from the experiments. The influence of laser output power and laser cutting speed on the kerf width size variation is analyzed using the analytical tools including scanning electron and optical microscopes. In the experiments, high pressure nitrogen assisting gas is used to prevent oxidation reactions in the cutting section. It is found that the kerf width size predicted from the lump parameter analysis agrees well with the experimental data. The kerf width size variation increases with increasing laser output power. However, this behavior reverses with increasing laser cutting speed. The life cycle assessment reveals that material selection for laser cutting is critical for the environmental protection point of view. Inconel 625 contributes the most to the environmental damages; however, recycling of the waste of the laser cutting reduces this contribution.

A Comparison between Bench Press Throw and Ballistic Push-Up tests to assess upper-body power in trained individuals.

PubMed

Bartolomei, Sandro; Nigro, Federico; Ruggeri, Sandro; Lanzoni, Ivan Malagoli; Ciacci, Simone; Merni, Franco; Sadres, Eliahu; Hoffman, Jay R; Semprini, Gabriele

2018-03-06

The purpose of the present study was to validate the ballistic push-up test performed with hands on a force plate (BPU) as a method to measure upper-body power. Twenty-eight experienced resistance trained men (age = 25.4 ± 5.2 y; body mass = 78.5 ± 9.0 kg; body height = 179.6 ± 7.8 cm) performed, two days apart, a bench press 1RM test and upper-body power tests. Mean power and peak power were assessed using the bench press throw test (BT) and the BPU test performed in randomized order. The area under the force/power curve (AUC) obtained at BT was also calculated. Power expressed at BPU was estimated using a time-based prediction equation. Mean force and the participant's body weight were used to predict the bench press 1RM. Pearson product moment correlations were used to examine relationships between the power assessment methods and between the predicted 1RM bench and the actual value. Large correlations (0.79; p < 0.001) were found between AUC and mean power expressed at BPU. Large correlations were also detected between mean power and peak power expressed at BT and BPU (0.75; p < 0.001 and 0.74; p < 0.001, respectively). Very large correlations (0.87; p < 0.001) were found between the 1RM bench and the 1RM predicted by the BPU. Results of the present study indicate that BPU represents a valid and reliable method to estimate the upper-body power in resistance-trained individuals.

A strategy for high specific power pyroelectric energy harvesting from a fluid source

NASA Astrophysics Data System (ADS)

Maheux, E.; Hrebtov, M. Yu.; Sukhorukov, G.; Kozyulin, N. N.; Bobrov, M. S.; Dobroselsky, K. G.; Chikishev, L. M.; Dulin, V. M.; Yudin, P. V.

2017-12-01

Conversion of waste heat into usable electricity is now one of the important strategies for saving natural resources and minimizing impact on the environment. In contrast to Seebeck devices, utilizing a temperature gradient, pyroelectric scavengers use temporal temperature oscillations. Here, optimal strategies for pyroelectric energy harvesting are theoretically investigated from the point of view of non-stationary heat exchange for the application-relevant case of harvesting with a pyroelectric lamella from a fluid heat source. It is shown that for a fixed lamella thickness by choosing appropriate phase shift between the temperature oscillations and the voltage on the pyroelectric lamella, one can effectively operate at high frequencies and achieve a two to three-fold increase in specific power with respect to the classical Olsen cycle. A further increase in specific power is achieved by thinning down the lamella. For devices with a thickness down to a few hundreds of nanometers, specific power linearly increases with the inverse thickness. Further scaling down of the device is hampered with the heat exchange in the boundary layer. Our simulations for a representative pyroelectric Pb(Zr0,5Ti0,5)O3 predict harvestable powers of the order of kW/kg for a device with a thickness in the range from 100 nm to 1 μm, operating at hundreds of Hz.

Development & experimental validation of a SINDA/FLUINT thermal/fluid/electrical model of a multi-tube AMTEC cell

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hendricks, T.J.; Borkowski, C.A.; Huang, C.

1998-01-01

AMTEC (Alkali Metal Thermal-to-Electric Conversion) cell development has received increased attention and funding in the space power community because of several desirable performance characteristics compared to current radioisotope thermoelectric generation and solar photovoltaic (PV) power generation. AMTEC cell development is critically dependent upon the ability to predict thermal, fluid dynamic and electrical performance of an AMTEC cell which has many complex thermal, fluid dynamic and electrical processes and interactions occurring simultaneously. Development of predictive capability is critical to understanding the complex processes and interactions within the AMTEC cell, and thereby creating the ability to design high-performance, cost-effective AMTEC cells. Amore » flexible, sophisticated thermal/fluid/electrical model of an operating AMTEC cell has been developed using the SINDA/FLUINT analysis software. This model can accurately simulate AMTEC cell performance at any hot side and cold side temperature combination desired, for any voltage and current conditions, and for a broad range of cell design parameters involving the cell dimensions, current collector and electrode design, electrode performance parameters, and cell wall and thermal shield emissivity. The model simulates the thermal radiation network within the AMTEC cell using RadCAD thermal radiation analysis; hot side, cold side and cell wall conductive and radiative coupling; BASE (Beta Alumina Solid Electrode) tube electrochemistry, including electrode over-potentials; the fluid dynamics of the low-pressure sodium vapor flow to the condenser and liquid sodium flow in the wick; sodium condensation at the condenser; and high-temperature sodium evaporation in the wick. The model predicts the temperature profiles within the AMTEC cell walls, the BASE tube temperature profiles, the sodium temperature profile in the artery return, temperature profiles in the evaporator, thermal energy flows throughout the AMTEC cell, all sodium pressure drops from hot BASE tubes to the condenser, the current, voltage, and power output from the cell, and the cell efficiency. This AMTEC cell model is so powerful and flexible that it is used in radioisotope AMTEC power system design, solar AMTEC power system design, and combustion-driven power system design on several projects at Advanced Modular Power Systems, Inc. (AMPS). The model has been successfully validated against actual cell experimental data and its performance predictions agree very well with experimental data on PX-5B cells and other test cells at AMPS. {copyright} {ital 1998 American Institute of Physics.}« less

Inertia may limit efficiency of slow flapping flight, but mayflies show a strategy for reducing the power requirements of loiter.

PubMed

Usherwood, James R

2009-03-01

Predictions from aerodynamic theory often match biological observations very poorly. Many insects and several bird species habitually hover, frequently flying at low advance ratios. Taking helicopter-based aerodynamic theory, wings functioning predominantly for hovering, even for quite small insects, should operate at low angles of attack. However, insect wings operate at very high angles of attack during hovering; reduction in angle of attack should result in considerable energetic savings. Here, I consider the possibility that selection of kinematics is constrained from being aerodynamically optimal due to the inertial power requirements of flapping. Potential increases in aerodynamic efficiency with lower angles of attack during hovering may be outweighed by increases in inertial power due to the associated increases in flapping frequency. For simple hovering, traditional rotary-winged helicopter-like micro air vehicles would be more efficient than their flapping biomimetic counterparts. However, flapping may confer advantages in terms of top speed and manoeuvrability. If flapping-winged micro air vehicles are required to hover or loiter more efficiently, dragonflies and mayflies suggest biomimetic solutions.

Studying the Power of the Integrative Weaning Index in Predicting the Success Rate of the Spontaneous Breathing Trial in Patients under Mechanical Ventilation.

PubMed

Ebrahimabadi, Sahar; Moghadam, Ahmad Bagheri; Vakili, Mohammadali; Modanloo, Mahnaz; Khoddam, Homeira

2017-08-01

The use of weaning predictive indicators can avoid early extubation and wrongful prolonged mechanical ventilation. This study aimed to determine the power of the integrative weaning index (IWI) in predicting the success rate of the spontaneous breathing trial (SBT) in patients under mechanical ventilation. In this prospective study, 105 patients undergoing mechanical ventilation for over 48 h were enrolled. Before weaning initiation, the IWI was calculated and based on the defined cutoff point (≥25), the success rate of the SBT was predicted. In case of weaning from the device, 2-h SBT was performed and the physiologic and respiratory indices were continuously studied while being intubated. If they were in the normal range besides the patient's tolerance, the test was considered as a success. The result was then compared with the IWI and further analyzed. The SBT was successful in 90 (85.7%) and unsuccessful in 15 (14.3%) cases. The difference between the true patient outcome after SBT, and the IWI prediction was 0.143 according to the Kappa agreement coefficient ( P < 0.001). Moreover, regarding the predictive power, IWI had high sensitivity (95.6%), specificity (40%), positive and negative predictive values (90.5% and 60), positive and negative likelihood ratios (1.59 and 0.11), and accuracy (86.7%). The IWI as a more objective indicator has acceptable accuracy and power for predicting the 2-h SBT result. Therefore, in addition to the reliable prediction of the final weaning outcome, it has favorable power to predict if the patient is ready to breathe spontaneously as the first step to weaning.

Studying the Power of the Integrative Weaning Index in Predicting the Success Rate of the Spontaneous Breathing Trial in Patients under Mechanical Ventilation

PubMed Central

Ebrahimabadi, Sahar; Moghadam, Ahmad Bagheri; Vakili, Mohammadali; Modanloo, Mahnaz; Khoddam, Homeira

2017-01-01

Background and Aims: The use of weaning predictive indicators can avoid early extubation and wrongful prolonged mechanical ventilation. This study aimed to determine the power of the integrative weaning index (IWI) in predicting the success rate of the spontaneous breathing trial (SBT) in patients under mechanical ventilation. Materials and Methods: In this prospective study, 105 patients undergoing mechanical ventilation for over 48 h were enrolled. Before weaning initiation, the IWI was calculated and based on the defined cutoff point (≥25), the success rate of the SBT was predicted. In case of weaning from the device, 2-h SBT was performed and the physiologic and respiratory indices were continuously studied while being intubated. If they were in the normal range besides the patient's tolerance, the test was considered as a success. The result was then compared with the IWI and further analyzed. Results: The SBT was successful in 90 (85.7%) and unsuccessful in 15 (14.3%) cases. The difference between the true patient outcome after SBT, and the IWI prediction was 0.143 according to the Kappa agreement coefficient (P < 0.001). Moreover, regarding the predictive power, IWI had high sensitivity (95.6%), specificity (40%), positive and negative predictive values (90.5% and 60), positive and negative likelihood ratios (1.59 and 0.11), and accuracy (86.7%). Conclusion: The IWI as a more objective indicator has acceptable accuracy and power for predicting the 2-h SBT result. Therefore, in addition to the reliable prediction of the final weaning outcome, it has favorable power to predict if the patient is ready to breathe spontaneously as the first step to weaning. PMID:28904477

Electronic stopping powers for heavy ions in SiC and SiO{sub 2}

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jin, K.; Xue, H.; Zhang, Y., E-mail: Zhangy1@ornl.gov

2014-01-28

Accurate information on electronic stopping power is fundamental for broad advances in materials science, electronic industry, space exploration, and sustainable energy technologies. In the case of slow heavy ions in light targets, current codes and models provide significantly inconsistent predictions, among which the Stopping and Range of Ions in Matter (SRIM) code is the most commonly used one. Experimental evidence, however, has demonstrated considerable errors in the predicted ion and damage profiles based on SRIM stopping powers. In this work, electronic stopping powers for Cl, Br, I, and Au ions are experimentally determined in two important functional materials, SiC andmore » SiO{sub 2}, based on a single ion technique, and new electronic stopping power values are derived over the energy regime from 0 to 15 MeV, where large deviations from the SRIM predictions are observed. As an experimental validation, Rutherford backscattering spectrometry (RBS) and secondary ion mass spectrometry (SIMS) are utilized to measure the depth profiles of implanted Au ions in SiC for energies from 700 keV to 15 MeV. The measured ion distributions by both RBS and SIMS are considerably deeper than the SRIM predictions, but agree well with predictions based on our derived stopping powers.« less

Electronic Stopping Powers For Heavy Ions In SiC And SiO2

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jin, Ke; Zhang, Y.; Zhu, Zihua

2014-01-24

Accurate information on electronic stopping power is fundamental for broad advances in materials science, electronic industry, space exploration, and sustainable energy technologies. In the case of slow heavy ions in light targets, current codes and models provide significantly inconsistent predictions, among which the Stopping and Range of Ions in Matter (SRIM) code is the most commonly used one. Experimental evidence, however, has demonstrated considerable errors in the predicted ion and damage profiles based on SRIM stopping powers. In this work, electronic stopping powers for Cl, Br, I, and Au ions are experimentally determined in two important functional materials, SiC andmore » SiO2, based on a single ion technique, and new electronic stopping power values are derived over the energy regime from 0 to 15 MeV, where large deviations from the SRIM predictions are observed. As an experimental validation, Rutherford backscattering spectrometry (RBS) and secondary ion mass spectrometry (SIMS) are utilized to measure the depth profiles of implanted Au ions in SiC for energies from 700 keV to 15MeV. The measured ion distributions by both RBS and SIMS are considerably deeper than the SRIM predictions, but agree well with predictions based on our derived stopping powers.« less

The electronic stopping powers and angular energy-loss dependence of helium and lithium ions in the silicon crystal

NASA Astrophysics Data System (ADS)

Mikšová, R.; Macková, A.; Malinský, P.

2017-09-01

We have measured the electronic stopping powers of helium and lithium ions in the channelling direction of the Si〈1 0 0〉 crystal. The energy range used (2.0-8.0 MeV) was changed by 200 and 400-keV steps. The ratio α between the channelling and random stopping powers was determined as a function of the angle for 2, 3 and 4 MeV 4He+ ions and for 3 and 6 MeV 7Li+,2+ ions. The measurements were carried out using the Rutherford backscattering spectrometry in the channelling mode (RBS-C) in a silicon-on-insulator material. The experimental channelling stopping-power values measured in the channelling direction were then discussed in the frame of the random energy stopping predictions calculated using SRIM-2013 code and the theoretical unitary convolution approximation (UCA) model. The experimental channelling stopping-power values decrease with increasing ion energy. The stopping-power difference between channelled and randomly moving ions increases with the enhanced initial ion energy. The ratio between the channelling and random ion stopping powers α as a function of the ion beam incoming angle for 2, 3 and 4 MeV He+ ions and for 3 and 6 MeV Li+,2+ ions was observed in the range 0.5-1.

Contribution of vertical strength and power to sprint performance in young male athletes.

PubMed

Meylan, C M P; Cronin, J; Oliver, J L; Hopkins, W G; Pinder, S

2014-08-01

The purpose of this study was to assess the possible contribution of 1RM leg-press strength and jump peak power to 20-m sprint time in young athletes in three maturity groups based on age relative to predicted age of peak height velocity (PHV): Pre (- 2.5 to -1.0 years; n=25), Mid (- 1.0 to 0.5 years; n=26) and Post (0.5 to 2.0 years; n=15). Allometric scaling factors, representing percent difference in 20-m time per percent difference in strength and peak power, were derived by linear regression and were similar in the three maturity groups (-0.16%/% and -0.20%/% for strength and peak power, respectively). The moderate increase in sprint performance Pre to Mid PHV (5.7%) reduced to small (1.9%) and trivial but unclear (0.9%) magnitudes after adjustment for 1RM and peak power, while the moderate increase Mid to Post PHV (4.6%) were still moderate (3.4 and 3.0%) after adjustment. Thus percent differences in strength or power explained most of the maturity-related improvements in sprint performance before PHV age but only some improvements after PHV age. Factors in addition to strength and power should be identified and monitored for development of speed in athletes during puberty. © Georg Thieme Verlag KG Stuttgart · New York.

The Predictive Effects of Protection Motivation Theory on Intention and Behaviour of Physical Activity in Patients with Type 2 Diabetes

PubMed Central

Ali Morowatisharifabad, Mohammad; Abdolkarimi, Mahdi; Asadpour, Mohammad; Fathollahi, Mahmood Sheikh; Balaee, Parisa

2018-01-01

INTRODUCTION: Theory-based education tailored to target behaviour and group can be effective in promoting physical activity. AIM: The purpose of this study was to examine the predictive power of Protection Motivation Theory on intent and behaviour of Physical Activity in Patients with Type 2 Diabetes. METHODS: This descriptive study was conducted on 250 patients in Rafsanjan, Iran. To examine the scores of protection motivation theory structures, a researcher-made questionnaire was used. Its validity and reliability were confirmed. The level of physical activity was also measured by the International Short - form Physical Activity Inventory. Its validity and reliability were also approved. Data were analysed by statistical tests including correlation coefficient, chi-square, logistic regression and linear regression. RESULTS: The results revealed that there was a significant correlation between all the protection motivation theory constructs and the intention to do physical activity. The results showed that the Theory structures were able to predict 60% of the variance of physical activity intention. The results of logistic regression demonstrated that increase in the score of physical activity intent and self - efficacy increased the chance of higher level of physical activity by 3.4 and 1.5 times, respectively OR = (3.39, 1.54). CONCLUSION: Considering the ability of protection motivation theory structures to explain the physical activity behaviour, interventional designs are suggested based on the structures of this theory, especially to improve self -efficacy as the most powerful factor in predicting physical activity intention and behaviour. PMID:29731945

Pneumococcal pneumonia - Are the new severity scores more accurate in predicting adverse outcomes?

PubMed

Ribeiro, C; Ladeira, I; Gaio, A R; Brito, M C

2013-01-01

The site-of-care decision is one of the most important factors in the management of patients with community-acquired pneumonia. The severity scores are validated prognostic tools for community-acquired pneumonia mortality and treatment site decision. The aim of this paper was to compare the discriminatory power of four scores - the classic PSI and CURB65 ant the most recent SCAP and SMART-COP - in predicting major adverse events: death, ICU admission, need for invasive mechanical ventilation or vasopressor support in patients admitted with pneumococcal pneumonia. A five year retrospective study of patients admitted for pneumococcal pneumonia. Patients were stratified based on admission data and assigned to low-, intermediate-, and high-risk classes for each score. Results were obtained comparing low versus non-low risk classes. We studied 142 episodes of hospitalization with 2 deaths and 10 patients needing mechanical ventilation and vasopressor support. The majority of patients were classified as low risk by all scores - we found high negative predictive values for all adverse events studied, the most negative value corresponding to the SCAP score. The more recent scores showed better accuracy for predicting ICU admission and need for ventilation or vasopressor support (mostly for the SCAP score with higher AUC values for all adverse events). The rate of all adverse outcomes increased directly with increasing risk class in all scores. The new gravity scores appear to have a higher discriminatory power in all adverse events in our study, particularly, the SCAP score. Copyright © 2012 Sociedade Portuguesa de Pneumologia. Published by Elsevier España. All rights reserved.

Relapse Risk Assessment for Schizophrenia Patients (RASP): A New Self-Report Screening Tool.

PubMed

Velligan, Dawn; Carpenter, William; Waters, Heidi C; Gerlanc, Nicole M; Legacy, Susan N; Ruetsch, Charles

2018-01-01

The Relapse Assessment for Schizophrenia Patients (RASP) was developed as a six-question self-report screener that measures indicators of Increased Anxiety and Social Isolation to assess patient stability and predict imminent relapse. This paper describes the development and psychometric characteristics of the RASP. The RASP and Positive and Negative Syndrome Scale (PANSS) were administered to patients with schizophrenia (n=166) three separate times. Chart data were collected on a subsample of patients (n=81). Psychometric analyses of RASP included tests of reliability, construct validity, and concurrent validity of items. Factors from RASP were correlated with subscales from PANSS (sensitivity to change and criterion validity [agreement between RASP and evidence of relapse]). Test-retest reliability returned modest to strong agreement at the item level and strong agreement at the questionnaire level. RASP showed good item response curves and internal consistency for the total instrument and within each of the two subscales (Increased Anxiety and Social Isolation). RASP Total Score and subscales showed good concurrent validity when correlated with PANSS Total Score, Positive, Excitement, and Anxiety subscales. RASP correctly predicted relapse in 67% of cases, with good specificity and negative predictive power and acceptable positive predictive power and sensitivity. The reliability and validity data presented support the use of RASP in settings where addition of a brief self-report assessment of relapse risk among patients with schizophrenia may be of benefit. Ease of use and scoring, and the ability to administer without clinical supervision allows for routine administration and assessment of relapse risk.

Radar observations of density gradients, electric fields, and plasma irregularities near polar cap patches in the context of the gradient-drift instability

NASA Astrophysics Data System (ADS)

Lamarche, Leslie J.; Makarevich, Roman A.

2017-03-01

We present observations of plasma density gradients, electric fields, and small-scale plasma irregularities near a polar cap patch made by the Super Dual Auroral Radar Network radar at Rankin Inlet (RKN) and the northern face of Resolute Bay Incoherent Scatter Radar (RISR-N). RKN echo power and occurrence are analyzed in the context of gradient-drift instability (GDI) theory, with a particular focus on the previously uninvestigated 2-D dependencies on wave propagation, electric field, and gradient vectors, with the latter two quantities evaluated directly from RISR-N measurements. It is shown that higher gradient and electric field components along the wave vector generally lead to the higher observed echo occurrence, which is consistent with the expected higher GDI growth rate, but the relationship with echo power is far less straightforward. The RKN echo power increases monotonically as the predicted linear growth rate approaches zero from negative values but does not continue this trend into positive growth rate values, in contrast with GDI predictions. The observed greater consistency of echo occurrence with GDI predictions suggests that GDI operating in the linear regime can control basic plasma structuring, but measured echo strength may be affected by other processes and factors, such as multistep or nonlinear processes or a shear-driven instability.

Improving accuracy and power with transfer learning using a meta-analytic database.

PubMed

Schwartz, Yannick; Varoquaux, Gaël; Pallier, Christophe; Pinel, Philippe; Poline, Jean-Baptiste; Thirion, Bertrand

2012-01-01

Typical cohorts in brain imaging studies are not large enough for systematic testing of all the information contained in the images. To build testable working hypotheses, investigators thus rely on analysis of previous work, sometimes formalized in a so-called meta-analysis. In brain imaging, this approach underlies the specification of regions of interest (ROIs) that are usually selected on the basis of the coordinates of previously detected effects. In this paper, we propose to use a database of images, rather than coordinates, and frame the problem as transfer learning: learning a discriminant model on a reference task to apply it to a different but related new task. To facilitate statistical analysis of small cohorts, we use a sparse discriminant model that selects predictive voxels on the reference task and thus provides a principled procedure to define ROIs. The benefits of our approach are twofold. First it uses the reference database for prediction, i.e., to provide potential biomarkers in a clinical setting. Second it increases statistical power on the new task. We demonstrate on a set of 18 pairs of functional MRI experimental conditions that our approach gives good prediction. In addition, on a specific transfer situation involving different scanners at different locations, we show that voxel selection based on transfer learning leads to higher detection power on small cohorts.

Nuclear option

DOE Office of Scientific and Technical Information (OSTI.GOV)

Olson, P.S.

The energy demand complexion of this country is always changing and promises to change in the future. The nuclear industry is responding to changing energy demands through standards writing activities. Since the oil embargo of 1973, there has been a change in the mix of fuels contributing to energy growth in this country; virtually all of the energy growth has come from coal and nuclear power. The predicted expansion of coal use by 1985, over 1977 level, is 37%, while the use of oil is expected to decline by 17%. Use of nuclear power is expected to increase 62% frommore » the 1977 level. The feasibility of using nuclear energy to meet the needs of the USA for electric power is discussed.« less

Lateralization in Alpha-Band Oscillations Predicts the Locus and Spatial Distribution of Attention

PubMed Central

Ikkai, Akiko; Dandekar, Sangita; Curtis, Clayton E.

2016-01-01

Attending to a task-relevant location changes how neural activity oscillates in the alpha band (8–13Hz) in posterior visual cortical areas. However, a clear understanding of the relationships between top-down attention, changes in alpha oscillations in visual cortex, and attention performance are still poorly understood. Here, we tested the degree to which the posterior alpha power tracked the locus of attention, the distribution of attention, and how well the topography of alpha could predict the locus of attention. We recorded magnetoencephalographic (MEG) data while subjects performed an attention demanding visual discrimination task that dissociated the direction of attention from the direction of a saccade to indicate choice. On some trials, an endogenous cue predicted the target’s location, while on others it contained no spatial information. When the target’s location was cued, alpha power decreased in sensors over occipital cortex contralateral to the attended visual field. When the cue did not predict the target’s location, alpha power again decreased in sensors over occipital cortex, but bilaterally, and increased in sensors over frontal cortex. Thus, the distribution and the topography of alpha reliably indicated the locus of covert attention. Together, these results suggest that alpha synchronization reflects changes in the excitability of populations of neurons whose receptive fields match the locus of attention. This is consistent with the hypothesis that alpha oscillations reflect the neural mechanisms by which top-down control of attention biases information processing and modulate the activity of neurons in visual cortex. PMID:27144717

Comparison and validation of statistical methods for predicting power outage durations in the event of hurricanes.

PubMed

Nateghi, Roshanak; Guikema, Seth D; Quiring, Steven M

2011-12-01

This article compares statistical methods for modeling power outage durations during hurricanes and examines the predictive accuracy of these methods. Being able to make accurate predictions of power outage durations is valuable because the information can be used by utility companies to plan their restoration efforts more efficiently. This information can also help inform customers and public agencies of the expected outage times, enabling better collective response planning, and coordination of restoration efforts for other critical infrastructures that depend on electricity. In the long run, outage duration estimates for future storm scenarios may help utilities and public agencies better allocate risk management resources to balance the disruption from hurricanes with the cost of hardening power systems. We compare the out-of-sample predictive accuracy of five distinct statistical models for estimating power outage duration times caused by Hurricane Ivan in 2004. The methods compared include both regression models (accelerated failure time (AFT) and Cox proportional hazard models (Cox PH)) and data mining techniques (regression trees, Bayesian additive regression trees (BART), and multivariate additive regression splines). We then validate our models against two other hurricanes. Our results indicate that BART yields the best prediction accuracy and that it is possible to predict outage durations with reasonable accuracy. © 2011 Society for Risk Analysis.

Performance of Comorbidity, Risk Adjustment, and Functional Status Measures in Expenditure Prediction for Patients With Diabetes

PubMed Central

Maciejewski, Matthew L.; Liu, Chuan-Fen; Fihn, Stephan D.

2009-01-01

OBJECTIVE—To compare the ability of generic comorbidity and risk adjustment measures, a diabetes-specific measure, and a self-reported functional status measure to explain variation in health care expenditures for individuals with diabetes. RESEARCH DESIGN AND METHODS—This study included a retrospective cohort of 3,092 diabetic veterans participating in a multisite trial. Two comorbidity measures, four risk adjusters, a functional status measure, a diabetes complication count, and baseline expenditures were constructed from administrative and survey data. Outpatient, inpatient, and total expenditure models were estimated using ordinary least squares regression. Adjusted R2 statistics and predictive ratios were compared across measures to assess overall explanatory power and explanatory power of low- and high-cost subgroups. RESULTS—Administrative data–based risk adjusters performed better than the comorbidity, functional status, and diabetes-specific measures in all expenditure models. The diagnostic cost groups (DCGs) measure had the greatest predictive power overall and for the low- and high-cost subgroups, while the diabetes-specific measure had the lowest predictive power. A model with DCGs and the diabetes-specific measure modestly improved predictive power. CONCLUSIONS—Existing generic measures can be useful for diabetes-specific research and policy applications, but more predictive diabetes-specific measures are needed. PMID:18945927

Migrants, health, and happiness: Evidence that health assessments travel with migrants and predict well-being.

PubMed

Ljunge, Martin

2016-09-01

Health assessments correlate with health outcomes and subjective well-being. Immigrants offer an opportunity to study persistent social influences on health where the social conditions are not endogenous to individual outcomes. This approach provides a clear direction of causality from social conditions to health, and in a second stage to well-being. Natives and immigrants from across the world residing in 30 European countries are studied using survey data. The paper applies within country analysis using both linear regressions and two stage least squares. Natives' and immigrants' individual characteristics have similar predictive power for health, except Muslim immigrants who experience a sizeable health penalty. Average health reports in the immigrant's birth country have a significant association with the immigrant's current health. Almost a quarter of the birth country health variation is brought by the immigrants, while conditioning on socioeconomic characteristics. There is no evidence of the birth country predictive power declining neither as the immigrant spends more time in the residence country nor over the life course. The second stage estimates indicate that a one standard deviation improvement in health predicts higher happiness by 1.72 point or 0.82 of a standard deviation, more than four times the happiness difference of changing employment status from unemployed to employed. Studying life satisfaction yields similar results. Health improvements predict substantial increases in individual happiness. Copyright © 2016 Elsevier B.V. All rights reserved.

A new solar power output prediction based on hybrid forecast engine and decomposition model.

PubMed

Zhang, Weijiang; Dang, Hongshe; Simoes, Rolando

2018-06-12

Regarding to the growing trend of photovoltaic (PV) energy as a clean energy source in electrical networks and its uncertain nature, PV energy prediction has been proposed by researchers in recent decades. This problem is directly effects on operation in power network while, due to high volatility of this signal, an accurate prediction model is demanded. A new prediction model based on Hilbert Huang transform (HHT) and integration of improved empirical mode decomposition (IEMD) with feature selection and forecast engine is presented in this paper. The proposed approach is divided into three main sections. In the first section, the signal is decomposed by the proposed IEMD as an accurate decomposition tool. To increase the accuracy of the proposed method, a new interpolation method has been used instead of cubic spline curve (CSC) fitting in EMD. Then the obtained output is entered into the new feature selection procedure to choose the best candidate inputs. Finally, the signal is predicted by a hybrid forecast engine composed of support vector regression (SVR) based on an intelligent algorithm. The effectiveness of the proposed approach has been verified over a number of real-world engineering test cases in comparison with other well-known models. The obtained results prove the validity of the proposed method. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Off-Ice Anaerobic Power Does Not Predict On-Ice Repeated Shift Performance in Hockey.

PubMed

Peterson, Ben J; Fitzgerald, John S; Dietz, Calvin C; Ziegler, Kevin S; Baker, Sarah E; Snyder, Eric M

2016-09-01

Peterson, BJ, Fitzgerald, JS, Dietz, CC, Ziegler, KS, Baker, SE, and Snyder, EM. Off-ice anaerobic power does not predict on-ice repeated shift performance in hockey. J Strength Cond Res 30(9): 2375-2381, 2016-Anaerobic power is a significant predictor of acceleration and top speed in team sport athletes. Historically, these findings have been applied to ice hockey although recent research has brought their validity for this sport into question. As ice hockey emphasizes the ability to repeatedly produce power, single bout anaerobic power tests should be examined to determine their ability to predict on-ice performance. We tested whether conventional off-ice anaerobic power tests could predict on-ice acceleration, top speed, and repeated shift performance. Forty-five hockey players, aged 18-24 years, completed anthropometric, off-ice, and on-ice tests. Anthropometric and off-ice testing included height, weight, body composition, vertical jump, and Wingate tests. On-ice testing consisted of acceleration, top speed, and repeated shift fatigue tests. Vertical jump (VJ) (r = -0.42; r = -0.58), Wingate relative peak power (WRPP) (r = -0.32; r = -0.43), and relative mean power (WRMP) (r = -0.34; r = -0.48) were significantly correlated (p ≤ 0.05) to on-ice acceleration and top speed, respectively. Conversely, none of the off-ice tests correlated with on-ice repeated shift performance, as measured by first gate, second gate, or total course fatigue; VJ (r = 0.06; r = 0.13; r = 0.09), WRPP (r = 0.06; r = 0.14; r = 0.10), or WRMP (r = -0.10; r = -0.01; r = -0.01). Although conventional off-ice anaerobic power tests predict single bout on-ice acceleration and top speed, they neither predict the repeated shift ability of the player, nor are good markers for performance in ice hockey.

Traction Drive Inverter Cooling with Submerged Liquid Jet Impingement on Microfinned Enhanced Surfaces (Presentation)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Waye, S.; Narumanchi, S.; Moreno, G.

Jet impingement is one means to improve thermal management for power electronics in electric-drive traction vehicles. Jet impingement on microfin-enhanced surfaces further augments heat transfer and thermal performance. A channel flow heat exchanger from a commercial inverter was characterized as a baseline system for comparison with two new prototype designs using liquid jet impingement on plain and microfinned enhanced surfaces. The submerged jets can target areas with the highest heat flux to provide local cooling, such as areas under insulated-gate bipolar transistors and diode devices. Low power experiments, where four diodes were powered, dissipated 105 W of heat and weremore » used to validate computational fluid dynamics modeling of the baseline and prototype designs. Experiments and modeling used typical automotive flow rates using water-ethylene glycol as a coolant (50%-50% by volume). The computational fluid dynamics model was used to predict full inverter power heat dissipation. The channel flow and jet impingement configurations were tested at full inverter power of 40 to 100 kW (output power) on a dynamometer, translating to an approximate heat dissipation of 1 to 2 kW. With jet impingement, the cold plate material is not critical for the thermal pathway. A high-temperature plastic was used that could eventually be injection molded or formed, with the jets formed from a basic aluminum plate with orifices acting as nozzles. Long-term reliability of the jet nozzles and impingement on enhanced surfaces was examined. For jet impingement on microfinned surfaces, thermal performance increased 17%. Along with a weight reduction of approximately 3 kg, the specific power (kW/kg) increased by 36%, with an increase in power density (kW/L) of 12% compared with the baseline channel flow configuration.« less

Understanding GPU Power. A Survey of Profiling, Modeling, and Simulation Methods

DOE PAGES

Bridges, Robert A.; Imam, Neena; Mintz, Tiffany M.

2016-09-01

Modern graphics processing units (GPUs) have complex architectures that admit exceptional performance and energy efficiency for high throughput applications.Though GPUs consume large amounts of power, their use for high throughput applications facilitate state-of-the-art energy efficiency and performance. Consequently, continued development relies on understanding their power consumption. Our work is a survey of GPU power modeling and profiling methods with increased detail on noteworthy efforts. Moreover, as direct measurement of GPU power is necessary for model evaluation and parameter initiation, internal and external power sensors are discussed. Hardware counters, which are low-level tallies of hardware events, share strong correlation to powermore » use and performance. Statistical correlation between power and performance counters has yielded worthwhile GPU power models, yet the complexity inherent to GPU architectures presents new hurdles for power modeling. Developments and challenges of counter-based GPU power modeling is discussed. Often building on the counter-based models, research efforts for GPU power simulation, which make power predictions from input code and hardware knowledge, provide opportunities for optimization in programming or architectural design. Noteworthy strides in power simulations for GPUs are included along with their performance or functional simulator counterparts when appropriate. Lastly, possible directions for future research are discussed.« less

Understanding GPU Power. A Survey of Profiling, Modeling, and Simulation Methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bridges, Robert A.; Imam, Neena; Mintz, Tiffany M.

Modern graphics processing units (GPUs) have complex architectures that admit exceptional performance and energy efficiency for high throughput applications.Though GPUs consume large amounts of power, their use for high throughput applications facilitate state-of-the-art energy efficiency and performance. Consequently, continued development relies on understanding their power consumption. Our work is a survey of GPU power modeling and profiling methods with increased detail on noteworthy efforts. Moreover, as direct measurement of GPU power is necessary for model evaluation and parameter initiation, internal and external power sensors are discussed. Hardware counters, which are low-level tallies of hardware events, share strong correlation to powermore » use and performance. Statistical correlation between power and performance counters has yielded worthwhile GPU power models, yet the complexity inherent to GPU architectures presents new hurdles for power modeling. Developments and challenges of counter-based GPU power modeling is discussed. Often building on the counter-based models, research efforts for GPU power simulation, which make power predictions from input code and hardware knowledge, provide opportunities for optimization in programming or architectural design. Noteworthy strides in power simulations for GPUs are included along with their performance or functional simulator counterparts when appropriate. Lastly, possible directions for future research are discussed.« less

Advanced Cloud Forecasting for Solar Energy Production

NASA Astrophysics Data System (ADS)

Werth, D. W.; Parker, M. J.

2017-12-01

A power utility must decide days in advance how it will allocate projected loads among its various generating sources. If the latter includes solar plants, the utility must predict how much energy the plants will produce - any shortfall will have to be compensated for by purchasing power as it is needed, when it is more expensive. To avoid this, utilities often err on the side of caution and assume that a relatively small amount of solar energy will be available, and allocate correspondingly more load to coal-fired plants. If solar irradiance can be predicted more accurately, utilities can be more confident that the predicted solar energy will indeed be available when needed, and assign solar plants a larger share of the future load. Solar power production is increasing in the Southeast, but is often hampered by irregular cloud fields, especially during high-pressure periods when rapid afternoon thunderstorm development can occur during what was predicted to be a clear day. We are currently developing an analog forecasting system to predict solar irradiance at the surface at the Savannah River Site in South Carolina, with the goal of improving predictions of available solar energy. Analog forecasting is based on the assumption that similar initial conditions will lead to similar outcomes, and involves the use of an algorithm to look through the weather patterns of the past to identify previous conditions (the analogs) similar to those of today. For our application, we select three predictor variables - sea-level pressure, 700mb geopotential, and 700mb humidity. These fields for the current day are compared to those from past days, and a weighted combination of the differences (defined by a cost function) is used to select the five best analog days. The observed solar irradiance values subsequent to the dates of those analogs are then combined to represent the forecast for the next day. We will explain how we apply the analog process, and compare it to existing solar forecasts.

Measured and predicted rotor performance for the SERI advanced wind turbine blades

NASA Astrophysics Data System (ADS)

Tangler, J.; Smith, B.; Kelley, N.; Jager, D.

1992-02-01

Measured and predicted rotor performance for the Solar Energy Research Institute (SERI) advanced wind turbine blades were compared to assess the accuracy of predictions and to identify the sources of error affecting both predictions and measurements. An awareness of these sources of error contributes to improved prediction and measurement methods that will ultimately benefit future rotor design efforts. Propeller/vane anemometers were found to underestimate the wind speed in turbulent environments such as the San Gorgonio Pass wind farm area. Using sonic or cup anemometers, good agreement was achieved between predicted and measured power output for wind speeds up to 8 m/sec. At higher wind speeds an optimistic predicted power output and the occurrence of peak power at wind speeds lower than measurements resulted from the omission of turbulence and yaw error. In addition, accurate two-dimensional (2-D) airfoil data prior to stall and a post stall airfoil data synthesization method that reflects three-dimensional (3-D) effects were found to be essential for accurate performance prediction.

NASA Lewis Stirling engine computer code evaluation

NASA Technical Reports Server (NTRS)

Sullivan, Timothy J.

1989-01-01

In support of the U.S. Department of Energy's Stirling Engine Highway Vehicle Systems program, the NASA Lewis Stirling engine performance code was evaluated by comparing code predictions without engine-specific calibration factors to GPU-3, P-40, and RE-1000 Stirling engine test data. The error in predicting power output was -11 percent for the P-40 and 12 percent for the Re-1000 at design conditions and 16 percent for the GPU-3 at near-design conditions (2000 rpm engine speed versus 3000 rpm at design). The efficiency and heat input predictions showed better agreement with engine test data than did the power predictions. Concerning all data points, the error in predicting the GPU-3 brake power was significantly larger than for the other engines and was mainly a result of inaccuracy in predicting the pressure phase angle. Analysis into this pressure phase angle prediction error suggested that improvements to the cylinder hysteresis loss model could have a significant effect on overall Stirling engine performance predictions.

Magnetic storm effects in electric power systems and prediction needs

NASA Technical Reports Server (NTRS)

Albertson, V. D.; Kappenman, J. G.

1979-01-01

Geomagnetic field fluctuations produce spurious currents in electric power systems. These currents enter and exit through points remote from each other. The fundamental period of these currents is on the order of several minutes which is quasi-dc compared to the normal 60 Hz or 50 Hz power system frequency. Nearly all of the power systems problems caused by the geomagnetically induced currents result from the half-cycle saturation of power transformers due to simultaneous ac and dc excitation. The effects produced in power systems are presented, current research activity is discussed, and magnetic storm prediction needs of the power industry are listed.

Power-constrained supercomputing

NASA Astrophysics Data System (ADS)

Bailey, Peter E.

As we approach exascale systems, power is turning from an optimization goal to a critical operating constraint. With power bounds imposed by both stakeholders and the limitations of existing infrastructure, achieving practical exascale computing will therefore rely on optimizing performance subject to a power constraint. However, this requirement should not add to the burden of application developers; optimizing the runtime environment given restricted power will primarily be the job of high-performance system software. In this dissertation, we explore this area and develop new techniques that extract maximum performance subject to a particular power constraint. These techniques include a method to find theoretical optimal performance, a runtime system that shifts power in real time to improve performance, and a node-level prediction model for selecting power-efficient operating points. We use a linear programming (LP) formulation to optimize application schedules under various power constraints, where a schedule consists of a DVFS state and number of OpenMP threads for each section of computation between consecutive message passing events. We also provide a more flexible mixed integer-linear (ILP) formulation and show that the resulting schedules closely match schedules from the LP formulation. Across four applications, we use our LP-derived upper bounds to show that current approaches trail optimal, power-constrained performance by up to 41%. This demonstrates limitations of current systems, and our LP formulation provides future optimization approaches with a quantitative optimization target. We also introduce Conductor, a run-time system that intelligently distributes available power to nodes and cores to improve performance. The key techniques used are configuration space exploration and adaptive power balancing. Configuration exploration dynamically selects the optimal thread concurrency level and DVFS state subject to a hardware-enforced power bound. Adaptive power balancing efficiently predicts where critical paths are likely to occur and distributes power to those paths. Greater power, in turn, allows increased thread concurrency levels, CPU frequency/voltage, or both. We describe these techniques in detail and show that, compared to the state-of-the-art technique of using statically predetermined, per-node power caps, Conductor leads to a best-case performance improvement of up to 30%, and an average improvement of 19.1%. At the node level, an accurate power/performance model will aid in selecting the right configuration from a large set of available configurations. We present a novel approach to generate such a model offline using kernel clustering and multivariate linear regression. Our model requires only two iterations to select a configuration, which provides a significant advantage over exhaustive search-based strategies. We apply our model to predict power and performance for different applications using arbitrary configurations, and show that our model, when used with hardware frequency-limiting in a runtime system, selects configurations with significantly higher performance at a given power limit than those chosen by frequency-limiting alone. When applied to a set of 36 computational kernels from a range of applications, our model accurately predicts power and performance; our runtime system based on the model maintains 91% of optimal performance while meeting power constraints 88% of the time. When the runtime system violates a power constraint, it exceeds the constraint by only 6% in the average case, while simultaneously achieving 54% more performance than an oracle. Through the combination of the above contributions, we hope to provide guidance and inspiration to research practitioners working on runtime systems for power-constrained environments. We also hope this dissertation will draw attention to the need for software and runtime-controlled power management under power constraints at various levels, from the processor level to the cluster level.

A variable capacitance based modeling and power capability predicting method for ultracapacitor

NASA Astrophysics Data System (ADS)

Liu, Chang; Wang, Yujie; Chen, Zonghai; Ling, Qiang

2018-01-01

Methods of accurate modeling and power capability predicting for ultracapacitors are of great significance in management and application of lithium-ion battery/ultracapacitor hybrid energy storage system. To overcome the simulation error coming from constant capacitance model, an improved ultracapacitor model based on variable capacitance is proposed, where the main capacitance varies with voltage according to a piecewise linear function. A novel state-of-charge calculation approach is developed accordingly. After that, a multi-constraint power capability prediction is developed for ultracapacitor, in which a Kalman-filter-based state observer is designed for tracking ultracapacitor's real-time behavior. Finally, experimental results verify the proposed methods. The accuracy of the proposed model is verified by terminal voltage simulating results under different temperatures, and the effectiveness of the designed observer is proved by various test conditions. Additionally, the power capability prediction results of different time scales and temperatures are compared, to study their effects on ultracapacitor's power capability.

The aerodynamic cost of flight in bats--comparing theory with measurement

NASA Astrophysics Data System (ADS)

von Busse, Rhea; Waldman, Rye M.; Swartz, Sharon M.; Breuer, Kenneth S.

2012-11-01

Aerodynamic theory has long been used to predict the aerodynamic power required for animal flight. However, even though the actuator disk model does not account for the flapping motion of a wing, it is used for lack of any better model. The question remains: how close are these predictions to reality? We designed a study to compare predicted aerodynamic power to measured power from the kinetic energy contained in the wake shed behind a bat flying in a wind tunnel. A high-accuracy displaced light-sheet stereo PIV system was used in the Trefftz plane to capture the wake behind four bats flown over a range of flight speeds (1-6m/s). The total power in the wake was computed from the wake vorticity and these estimates were compared with the power predicted using Pennycuick's model for bird flight as well as estimates derived from measurements of the metabolic cost of flight, previously acquired from the same individuals.

A new method of power load prediction in electrification railway

NASA Astrophysics Data System (ADS)

Dun, Xiaohong

2018-04-01

Aiming at the character of electrification railway, the paper mainly studies the problem of load prediction in electrification railway. After the preprocessing of data, and the similar days are separated on the basis of its statistical characteristics. Meanwhile the accuracy of different methods is analyzed. The paper provides a new thought of prediction and a new method of accuracy of judgment for the load prediction of power system.

Predictability of action sub-steps modulates motor system activation during the observation of goal-directed actions.

PubMed

Braukmann, Ricarda; Bekkering, Harold; Hidding, Margreeth; Poljac, Edita; Buitelaar, Jan K; Hunnius, Sabine

2017-08-01

Action perception and execution are linked in the human motor system, and researchers have proposed that this action-observation matching system underlies our ability to predict observed behavior. If the motor system is indeed involved in the generation of action predictions, activation should be modulated by the degree of predictability of an observed action. This study used EEG and eye-tracking to investigate whether and how predictability of an observed action modulates motor system activation as well as behavioral predictions in the form of anticipatory eye-movements. Participants were presented with object-directed actions (e.g., making a cup of tea) consisting of three action steps which increased in their predictability. While the goal of the first step was ambiguous (e.g., when making tea, one can first grab the teabag or the cup), the goals of the following steps became predictable over the course of the action. Motor system activation was assessed by measuring attenuation of sensorimotor mu- and beta-oscillations. We found that mu- and beta-power were attenuated during observation, indicating general activation of the motor system. Importantly, predictive motor system activation, indexed by beta-band attenuation, increased for each action step, showing strongest activation prior to the final (i.e. most predictable) step. Sensorimotor activity was related to participants' predictive eye-movements which also showed a modulation by action step. Our results demonstrate that motor system activity and behavioral predictions become stronger for more predictable action steps. The functional roles of sensorimotor oscillations in predicting other's actions are discussed. Copyright © 2017 Elsevier Ltd. All rights reserved.

A neural network based computational model to predict the output power of different types of photovoltaic cells.

PubMed

Xiao, WenBo; Nazario, Gina; Wu, HuaMing; Zhang, HuaMing; Cheng, Feng

2017-01-01

In this article, we introduced an artificial neural network (ANN) based computational model to predict the output power of three types of photovoltaic cells, mono-crystalline (mono-), multi-crystalline (multi-), and amorphous (amor-) crystalline. The prediction results are very close to the experimental data, and were also influenced by numbers of hidden neurons. The order of the solar generation power output influenced by the external conditions from smallest to biggest is: multi-, mono-, and amor- crystalline silicon cells. In addition, the dependences of power prediction on the number of hidden neurons were studied. For multi- and amorphous crystalline cell, three or four hidden layer units resulted in the high correlation coefficient and low MSEs. For mono-crystalline cell, the best results were achieved at the hidden layer unit of 8.

Relative value of diverse brain MRI and blood-based biomarkers for predicting cognitive decline in the elderly

NASA Astrophysics Data System (ADS)

Madsen, Sarah K.; Ver Steeg, Greg; Daianu, Madelaine; Mezher, Adam; Jahanshad, Neda; Nir, Talia M.; Hua, Xue; Gutman, Boris A.; Galstyan, Aram; Thompson, Paul M.

2016-03-01

Cognitive decline accompanies many debilitating illnesses, including Alzheimer's disease (AD). In old age, brain tissue loss also occurs along with cognitive decline. Although blood tests are easier to perform than brain MRI, few studies compare brain scans to standard blood tests to see which kinds of information best predict future decline. In 504 older adults from the Alzheimer's Disease Neuroimaging Initiative (ADNI), we first used linear regression to assess the relative value of different types of data to predict cognitive decline, including 196 blood panel biomarkers, 249 MRI biomarkers obtained from the FreeSurfer software, demographics, and the AD-risk gene APOE. A subset of MRI biomarkers was the strongest predictor. There was no specific blood marker that increased predictive accuracy on its own, we found that a novel unsupervised learning method, CorEx, captured weak correlations among blood markers, and the resulting clusters offered unique predictive power.

Developing a comprehensive training curriculum for integrated predictive maintenance

NASA Astrophysics Data System (ADS)

Wurzbach, Richard N.

2002-03-01

On-line equipment condition monitoring is a critical component of the world-class production and safety histories of many successful nuclear plant operators. From addressing availability and operability concerns of nuclear safety-related equipment to increasing profitability through support system reliability and reduced maintenance costs, Predictive Maintenance programs have increasingly become a vital contribution to the maintenance and operation decisions of nuclear facilities. In recent years, significant advancements have been made in the quality and portability of many of the instruments being used, and software improvements have been made as well. However, the single most influential component of the success of these programs is the impact of a trained and experienced team of personnel putting this technology to work. Changes in the nature of the power generation industry brought on by competition, mergers, and acquisitions, has taken the historically stable personnel environment of power generation and created a very dynamic situation. As a result, many facilities have seen a significant turnover in personnel in key positions, including predictive maintenance personnel. It has become the challenge for many nuclear operators to maintain the consistent contribution of quality data and information from predictive maintenance that has become important in the overall equipment decision process. These challenges can be met through the implementation of quality training to predictive maintenance personnel and regular updating and re-certification of key technology holders. The use of data management tools and services aid in the sharing of information across sites within an operating company, and with experts who can contribute value-added data management and analysis. The overall effectiveness of predictive maintenance programs can be improved through the incorporation of newly developed comprehensive technology training courses. These courses address the use of key technologies such as vibration analysis, infrared thermography, and oil analysis not as singular entities, but as a toolbox resource from which to address overall equipment and plant reliability in a structured program and decision environment.

Improved Rainfall Estimates and Predictions for 21st Century Drought Early Warning

NASA Technical Reports Server (NTRS)

Funk, Chris; Peterson, Pete; Shukla, Shraddhanand; Husak, Gregory; Landsfeld, Marty; Hoell, Andrew; Pedreros, Diego; Roberts, J. B.; Robertson, F. R.; Tadesse, Tsegae;

Initial Assessment of the Risk Assessment and Prediction Tool in a Heterogeneous Neurosurgical Patient Population.

PubMed

Piazza, Matthew; Sharma, Nikhil; Osiemo, Benjamin; McClintock, Scott; Missimer, Emily; Gardiner, Diana; Maloney, Eileen; Callahan, Danielle; Smith, J Lachlan; Welch, William; Schuster, James; Grady, M Sean; Malhotra, Neil R

2018-05-21

Bundled care payments are increasingly being explored for neurosurgical interventions. In this setting, skilled nursing facility (SNF) is less desirable from a cost perspective than discharge to home, underscoring the need for better preoperative prediction of postoperative disposition. To assess the capability of the Risk Assessment and Prediction Tool (RAPT) and other preoperative variables to determine expected disposition prior to surgery in a heterogeneous neurosurgical cohort, through observational study. Patients aged 50 yr or more undergoing elective neurosurgery were enrolled from June 2016 to February 2017 (n = 623). Logistic regression was used to identify preoperative characteristics predictive of discharge disposition. Results from multivariate analysis were used to create novel grading scales for the prediction of discharge disposition that were subsequently compared to the RAPT Score using Receiver Operating Characteristic analysis. Higher RAPT Score significantly predicted home disposition (P < .001). Age 65 and greater, dichotomized RAPT walk score, and spinal surgery below L2 were independent predictors of SNF discharge in multivariate analysis. A grading scale utilizing these variables had superior discriminatory power between SNF and home/rehab discharge when compared with RAPT score alone (P = .004). Our analysis identified age, lower lumbar/lumbosacral surgery, and RAPT walk score as independent predictors of discharge to SNF, and demonstrated superior predictive power compared with the total RAPT Score when combined in a novel grading scale. These tools may identify patients who may benefit from expedited discharge to subacute care facilities and decrease inpatient hospital resource utilization following surgery.

Ensemble Data Assimilation of Wind and Photovoltaic Power Information in the Convection-permitting High-Resolution Model COSMO-DE

NASA Astrophysics Data System (ADS)

Declair, Stefan; Saint-Drenan, Yves-Marie; Potthast, Roland

2016-04-01

Determining the amount of weather dependent renewable energy is a demanding task for transmission system operators (TSOs) and wind and photovoltaic (PV) prediction errors require the use of reserve power, which generate costs and can - in extreme cases - endanger the security of supply. In the project EWeLiNE funded by the German government, the German Weather Service and the Fraunhofer Institute on Wind Energy and Energy System Technology develop innovative weather- and power forecasting models and tools for grid integration of weather dependent renewable energy. The key part in energy prediction process chains is the numerical weather prediction (NWP) system. Wind speed and irradiation forecast from NWP system are however subject to several sources of error. The quality of the wind power prediction is mainly penalized by forecast error of the NWP model in the planetary boundary layer (PBL), which is characterized by high spatial and temporal fluctuations of the wind speed. For PV power prediction, weaknesses of the NWP model to correctly forecast i.e. low stratus, the absorption of condensed water or aerosol optical depth are the main sources of errors. Inaccurate radiation schemes (i.e. the two-stream parametrization) are also known as a deficit of NWP systems with regard to irradiation forecast. To mitigate errors like these, NWP model data can be corrected by post-processing techniques such as model output statistics and calibration using historical observational data. Additionally, latest observations can be used in a pre-processing technique called data assimilation (DA). In DA, not only the initial fields are provided, but the model is also synchronized with reality - the observations - and hence the model error is reduced in the forecast. Besides conventional observation networks like radiosondes, synoptic observations or air reports of wind, pressure and humidity, the number of observations measuring meteorological information indirectly such as satellite radiances, radar reflectivities or GPS slant delays strongly increases. The numerous wind farm and PV plants installed in Germany potentially represent a dense meteorological network assessing irradiation and wind speed through their power measurements. The accuracy of the NWP data may thus be enhanced by extending the observations in the assimilation by this new source of information. Wind power data can serve as indirect measurements of wind speed at hub height. The impact on the NWP model is potentially interesting since conventional observation network lacks measurements in this part of the PBL. Photovoltaic power plants can provide information on clouds, aerosol optical depth or low stratus in terms of remote sensing: the power output is strongly dependent on perturbations along the slant between sun position and PV panel. Additionally, since the latter kind of data is not limited to the vertical column above or below the detector. It may thus complement satellite data and compensate weaknesses in the radiation scheme. In this contribution, the DA method (Local Ensemble Transform Kalman Filter, LETKF) is shortly sketched. Furthermore, the computation of the model power equivalents is described and first assimilation results are presented and discussed.

Initial comparison of single cylinder Stirling engine computer model predictions with test results

NASA Technical Reports Server (NTRS)

Tew, R. C., Jr.; Thieme, L. G.; Miao, D.

1979-01-01

A NASA developed digital computer code for a Stirling engine, modelling the performance of a single cylinder rhombic drive ground performance unit (GPU), is presented and its predictions are compared to test results. The GPU engine incorporates eight regenerator/cooler units and the engine working space is modelled by thirteen control volumes. The model calculates indicated power and efficiency for a given engine speed, mean pressure, heater and expansion space metal temperatures and cooler water inlet temperature and flow rate. Comparison of predicted and observed powers implies that the reference pressure drop calculations underestimate actual pressure drop, possibly due to oil contamination in the regenerator/cooler units, methane contamination in the working gas or the underestimation of mechanical loss. For a working gas of hydrogen, the predicted values of brake power are from 0 to 6% higher than experimental values, and brake efficiency is 6 to 16% higher, while for helium the predicted brake power and efficiency are 2 to 15% higher than the experimental.

Evolution of the radial electric field in high-Te ECH heated plasmas on LHD

NASA Astrophysics Data System (ADS)

Pablant, Novimir; Bitter, Manfred; Delgado Aparicio, Luis F.; Dinklage, Andreas; Gates, David; Goto, Motoshi; Ido, Takeshi; Hill, Kenneth H.; Kubo, Shin; Morita, Shigeru; Nagaoka, Kenichi; Oishi, Tetsutarou; Satake, Shinsuke; Takahashi, Hiromi; Yokoyama, Masayuki; LHD Experiment Group Team

2014-10-01

A detailed study is presented on the evolution of the radial electric field (Er) under a range of densities and injected ECH powers on the Large Helical Device (LHD). These plasmas focused on high-electron temperature ECH heated plasmas which exhibit a transition of Er from the ion-root to the electron-root when either the density is reduced or the ECH power is increased. Measurements of poloidal rotation were achieved using the X-Ray Imaging Crystal Spectrometer (XICS) and are compared with neo-classical predictions of the radial electric field using the GSRAKE and FORTEC-3D codes. This study is based on a series of experiments on LHD which used fast modulation of the gyrotrons on LHD to produce a detailed power scan with a constant power deposition profile. This is a novel application of this technique to LHD, and has provided the most detailed study to date on dependence of the radial electric field on the injected power. Detailed scans of the density at constant injected power were also made, allowing a separation of the power and density dependence.

A phenomenological model of muscle fatigue and the power-endurance relationship.

PubMed

James, A; Green, S

2012-11-01

The relationship between power output and the time that it can be sustained during exercise (i.e., endurance) at high intensities is curvilinear. Although fatigue is implicit in this relationship, there is little evidence pertaining to it. To address this, we developed a phenomenological model that predicts the temporal response of muscle power during submaximal and maximal exercise and which was based on the type, contractile properties (e.g., fatiguability), and recruitment of motor units (MUs) during exercise. The model was first used to predict power outputs during all-out exercise when fatigue is clearly manifest and for several distributions of MU type. The model was then used to predict times that different submaximal power outputs could be sustained for several MU distributions, from which several power-endurance curves were obtained. The model was simultaneously fitted to two sets of human data pertaining to all-out exercise (power-time profile) and submaximal exercise (power-endurance relationship), yielding a high goodness of fit (R(2) = 0.96-0.97). This suggested that this simple model provides an accurate description of human power output during submaximal and maximal exercise and that fatigue-related processes inherent in it account for the curvilinearity of the power-endurance relationship.

Estimation of Power Consumption in the Circular Sawing of Stone Based on Tangential Force Distribution

NASA Astrophysics Data System (ADS)

Huang, Guoqin; Zhang, Meiqin; Huang, Hui; Guo, Hua; Xu, Xipeng

2018-04-01

Circular sawing is an important method for the processing of natural stone. The ability to predict sawing power is important in the optimisation, monitoring and control of the sawing process. In this paper, a predictive model (PFD) of sawing power, which is based on the tangential force distribution at the sawing contact zone, was proposed, experimentally validated and modified. With regard to the influence of sawing speed on tangential force distribution, the modified PFD (MPFD) performed with high predictive accuracy across a wide range of sawing parameters, including sawing speed. The mean maximum absolute error rate was within 6.78%, and the maximum absolute error rate was within 11.7%. The practicability of predicting sawing power by the MPFD with few initial experimental samples was proved in case studies. On the premise of high sample measurement accuracy, only two samples are required for a fixed sawing speed. The feasibility of applying the MPFD to optimise sawing parameters while lowering the energy consumption of the sawing system was validated. The case study shows that energy use was reduced 28% by optimising the sawing parameters. The MPFD model can be used to predict sawing power, optimise sawing parameters and control energy.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jin, Ke; Zhang, Yanwen; Zhu, Zihua

Accurate information of electronic stopping power is fundamental for broad advances in electronic industry, space exploration, national security, and sustainable energy technologies. The Stopping and Range of Ions in Matter (SRIM) code has been widely applied to predict stopping powers and ion distributions for decades. Recent experimental results have, however, shown considerable errors in the SRIM predictions for stopping of heavy ions in compounds containing light elements, indicating an urgent need to improve current stopping power models. The electronic stopping powers of 35Cl, 80Br, 127I, and 197Au ions are experimentally determined in two important functional materials, SiC and SiO2, frommore » tens to hundreds keV/u based on a single ion technique. By combining with the reciprocity theory, new electronic stopping powers are suggested in a region from 0 to 15 MeV, where large deviations from SRIM predictions are observed. For independent experimental validation of the electronic stopping powers we determined, Rutherford backscattering spectrometry (RBS) and secondary ion mass spectrometry (SIMS) are utilized to measure the depth profiles of implanted Au ions in SiC with energies from 700 keV to 15 MeV. The measured ion distributions from both RBS and SIMS are considerably deeper (up to ~30%) than the predictions from the commercial SRIM code. In comparison, the new electronic stopping power values are utilized in a modified TRIM-85 (the original version of the SRIM) code, M-TRIM, to predict ion distributions, and the results are in good agreement with the experimentally measured ion distributions.« less

The Applications of NASA Mission Technologies to the Greening of Human Impact

NASA Technical Reports Server (NTRS)

Sims, Michael H.

2009-01-01

I will give an overview talk about flight software systems, robotics technologies and modeling for energy minimization as applied to vehicles and buildings infrastructures. A dominant issue in both design and operations of robotic spacecraft is the minimization of energy use. In the design and building of spacecraft increased power is acquired only at the cost of additional mass and volumes and ultimately cost. Consequently, interplanetary spacecrafts are designed to have the minimum essential power and those designs often incorporate careful timing of all power use. Operationally, the availability of power is the most influential constraint for the use of planetary surface robots, such as the Mars Exploration Rovers. The amount of driving done, the amount of science accomplished and indeed the survivability of the spacecraft itself is determined by the power available for use. For the Mars Exploration Rovers there are four tools which are used: (1) models of the rover and it s thermal and power use (2) predictive environmental models of power input and thermal environment (3) fine grained manipulation of power use (4) optimization modeling and planning tools. In this talk I will discuss possible applications of this methodology to minimizing power use on Earth, especially in buildings.

NASA's Prediction Of Worldwide Energy Resource (POWER) Project Unveils a New Geospatial Data Portal

Atmospheric Science Data Center

2018-03-01

The Prediction Of Worldwide Energy Resource (POWER) Project facilitates access to NASA's satellite and modeling analysis for Renewable Energy, Sustainable Buildings and Agroclimatology applications.  A   new ...

Effects of aberrant gamma frequency oscillations on prepulse inhibition.

PubMed

Jones, Nigel C; Anderson, Paul; Rind, Gil; Sullivan, Caley; van den Buuse, Maarten; O'Brien, Terence J

2014-10-01

Emerging literature implicates abnormalities in gamma frequency oscillations in the pathophysiology of schizophrenia, with hypofunction of N-methyl-D-aspartate (NMDA) receptors implicated as a key factor. Prepulse inhibition (PPI) is a behavioural measure of sensorimotor gating, which is disrupted in schizophrenia. We studied relationships between ongoing and sensory-evoked gamma oscillations and PPI using pharmacological interventions designed to increase gamma oscillations (ketamine, MK-801); reduce gamma oscillations (LY379268); or disrupt PPI (amphetamine). We predicted that elevating ongoing gamma power would lead to increased 'neural noise' in cortical circuits, dampened sensory-evoked gamma responses and disrupted behaviour. Wistar rats were implanted with EEG recording electrodes. They received ketamine (5 mg/kg), MK-801 (0.16 mg/kg), amphetamine (0.5 mg/kg), LY379268 (3 mg/kg) or vehicle and underwent PPI sessions with concurrent EEG recording. Ketamine and MK-801 increased the power of ongoing gamma oscillations and caused time-matched disruptions of PPI, while amphetamine marginally affected ongoing gamma power. In contrast, LY379268 reduced ongoing gamma power, but had no effect on PPI. The sensory gamma response evoked by the prepulse was reduced following treatment with all psychotomimetics, associating with disruptions in PPI. This was most noticeable following treatment with NMDA receptor antagonists. We found that ketamine and MK-801 increase ongoing gamma power and reduce evoked gamma power, both of which are related to disruptions in sensorimotor gating. This appears to be due to antagonism of NMDA receptors, since amphetamine and LY379268 differentially impacted these outcomes and possess different neuropharmacological substrates. Aberrant gamma frequency oscillations caused by NMDA receptor hypofunction may mediate the sensory processing deficits observed in schizophrenia.

Effect of Adding McKenzie Syndrome, Centralization, Directional Preference, and Psychosocial Classification Variables to a Risk-Adjusted Model Predicting Functional Status Outcomes for Patients With Lumbar Impairments.

PubMed

Werneke, Mark W; Edmond, Susan; Deutscher, Daniel; Ward, Jason; Grigsby, David; Young, Michelle; McGill, Troy; McClenahan, Brian; Weinberg, Jon; Davidow, Amy L

2016-09-01

Study Design Retrospective cohort. Background Patient-classification subgroupings may be important prognostic factors explaining outcomes. Objectives To determine effects of adding classification variables (McKenzie syndrome and pain patterns, including centralization and directional preference; Symptom Checklist Back Pain Prediction Model [SCL BPPM]; and the Fear-Avoidance Beliefs Questionnaire subscales of work and physical activity) to a baseline risk-adjusted model predicting functional status (FS) outcomes. Methods Consecutive patients completed a battery of questionnaires that gathered information on 11 risk-adjustment variables. Physical therapists trained in Mechanical Diagnosis and Therapy methods classified each patient by McKenzie syndromes and pain pattern. Functional status was assessed at discharge by patient-reported outcomes. Only patients with complete data were included. Risk of selection bias was assessed. Prediction of discharge FS was assessed using linear stepwise regression models, allowing 13 variables to enter the model. Significant variables were retained in subsequent models. Model power (R(2)) and beta coefficients for model variables were estimated. Results Two thousand sixty-six patients with lumbar impairments were evaluated. Of those, 994 (48%), 10 (<1%), and 601 (29%) were excluded due to incomplete psychosocial data, McKenzie classification data, and missing FS at discharge, respectively. The final sample for analyses was 723 (35%). Overall R(2) for the baseline prediction FS model was 0.40. Adding classification variables to the baseline model did not result in significant increases in R(2). McKenzie syndrome or pain pattern explained 2.8% and 3.0% of the variance, respectively. When pain pattern and SCL BPPM were added simultaneously, overall model R(2) increased to 0.44. Although none of these increases in R(2) were significant, some classification variables were stronger predictors compared with some other variables included in the baseline model. Conclusion The small added prognostic capabilities identified when combining McKenzie or pain-pattern classifications with the SCL BPPM classification did not significantly improve prediction of FS outcomes in this study. Additional research is warranted to investigate the importance of classification variables compared with those used in the baseline model to maximize predictive power. Level of Evidence Prognosis, level 4. J Orthop Sports Phys Ther 2016;46(9):726-741. Epub 31 Jul 2016. doi:10.2519/jospt.2016.6266.

The effect on the transmission loss of a double wall panel of using helium gas in the gap

NASA Astrophysics Data System (ADS)

Atwal, M. S.; Crocker, M. J.

The possibility of increasing the sound-power transmission loss of a double panel by using helium gas in the gap is investigated. The transmission loss of a panel is defined as ten times the common logarithm of the ratio of the sound power incident on the panel to the sound power transmitted to the space on the other side of the panel. The work is associated with extensive research being done to develop new techniques for predicting the interior noise levels on board high-speed advanced turboprop aircraft and reducing the noise levels with a minimum weight penalty. Helium gas was chosen for its inert properties and its low impedance compared with air. With helium in the gap, the impedance mismatch experienced by the sound wave will be greater than that with air in the gap. It is seen that helium gas in the gap increases the transmission loss of the double panel over a wide range of frequencies.

The effect on the transmission loss of a double wall panel of using helium gas in the gap

NASA Technical Reports Server (NTRS)

Atwal, M. S.; Crocker, M. J.

1985-01-01

The possibility of increasing the sound-power transmission loss of a double panel by using helium gas in the gap is investigated. The transmission loss of a panel is defined as ten times the common logarithm of the ratio of the sound power incident on the panel to the sound power transmitted to the space on the other side of the panel. The work is associated with extensive research being done to develop new techniques for predicting the interior noise levels on board high-speed advanced turboprop aircraft and reducing the noise levels with a minimum weight penalty. Helium gas was chosen for its inert properties and its low impedance compared with air. With helium in the gap, the impedance mismatch experienced by the sound wave will be greater than that with air in the gap. It is seen that helium gas in the gap increases the transmission loss of the double panel over a wide range of frequencies.

Effect of makeup water properties on the condenser fouling in power planr cooling system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Safari, I.; Walker, M.; Abbasian, J.

2011-01-01

The thermoelectric power industry in the U.S. uses a large amount of fresh water. As available freshwater for use in thermoelectric power production becomes increasingly limited, use of nontraditional water sources is of growing interest. Utilization of nontraditional water, in cooling systems increases the potential for mineral precipitation on heat exchanger surfaces. In that regard, predicting the accelerated rate of scaling and fouling in condenser is crucial to evaluate the condenser performance. To achieve this goal, water chemistry should be incorporated in cooling system modeling and simulation. This paper addresses the effects of various makeup water properties on the coolingmore » system, namely pH and aqueous speciation, both of which are important factors affecting the fouling rate in the main condenser. Detailed modeling of the volatile species desorption (i.e. CO{sub 2} and NH{sub 3}), the formation of scale in the recirculating system, and the relationship between water quality and the corresponding fouling rates is presented.« less

Predictability of Brayton electric power system performance

NASA Technical Reports Server (NTRS)

Klann, J. L.; Hettel, H. J.

1972-01-01

Data from the first tests of the 2- to 15-kilowatt space power system in a vacuum chamber were compared with predictions of both a pretest analysis and a modified version of that analysis. The pretest analysis predicted test results with differences of no more than 9 percent of the largest measured value for each quantity. The modified analysis correlated measurements. Differences in conversion efficiency and power output were no greater than plus or minus 2.5 percent. This modified analysis was used to project space performance maps for the current test system.

Thermal Modeling for Pulsed Inductive FRC Plasmoid Thrusters

NASA Astrophysics Data System (ADS)

Pfaff, Michael

Due to the rising importance of space based infrastructure, long-range robotic space missions, and the need for active attitude control for spacecraft, research into Electric Propulsion is becoming increasingly important. Electric Propulsion (EP) systems utilize electric power to accelerate ions in order to produce thrust. Unlike traditional chemical propulsion, this means that thrust levels are relatively low. The trade-off is that EP thrusters have very high specific impulses (Isp), and can therefore make do with far less onboard propellant than cold gas, monopropellant, or bipropellant engines. As a consequence of the high power levels used to accelerate the ionized propellant, there is a mass and cost penalty in terms of solar panels and a power processing unit. Due to the large power consumption (and waste heat) from electric propulsion thrusters, accurate measurements and predictions of thermal losses are needed. Excessive heating in sensitive locations within a thruster may lead to premature failure of vital components. Between the fixed cost required to purchase these components, as well as the man-hours needed to assemble (or replace) them, attempting to build a high-power thruster without reliable thermal modeling can be expensive. This paper will explain the usage of FEM modeling and experimental tests in characterizing the ElectroMagnetic Plasmoid Thruster (EMPT) and the Electrodeless Lorentz Force (ELF) thruster at the MSNW LLC facility in Redmond, Washington. The EMPT thruster model is validated using an experimental setup, and steady state temperatures are predicted for vacuum conditions. Preliminary analysis of the ELF thruster indicates possible material failure in absence of an active cooling system for driving electronics and for certain power levels.

Self-heating in piezoresistive cantilevers

PubMed Central

Doll, Joseph C.; Corbin, Elise A.; King, William P.; Pruitt, Beth L.

2011-01-01

We report experiments and models of self-heating in piezoresistive microcantilevers that show how cantilever measurement resolution depends on the thermal properties of the surrounding fluid. The predicted cantilever temperature rise from a finite difference model is compared with detailed temperature measurements on fabricated devices. Increasing the fluid thermal conductivity allows for lower temperature operation for a given power dissipation, leading to lower force and displacement noise. The force noise in air is 76% greater than in water for the same increase in piezoresistor temperature. PMID:21731884

Self-heating in piezoresistive cantilevers.

PubMed

Doll, Joseph C; Corbin, Elise A; King, William P; Pruitt, Beth L

2011-05-30

We report experiments and models of self-heating in piezoresistive microcantilevers that show how cantilever measurement resolution depends on the thermal properties of the surrounding fluid. The predicted cantilever temperature rise from a finite difference model is compared with detailed temperature measurements on fabricated devices. Increasing the fluid thermal conductivity allows for lower temperature operation for a given power dissipation, leading to lower force and displacement noise. The force noise in air is 76% greater than in water for the same increase in piezoresistor temperature.

Numerical Predictions of Wind Turbine Power and Aerodynamic Loads for the NREL Phase II and IV Combined Experiment Rotor

NASA Technical Reports Server (NTRS)

Duque, Earl P. N.; Johnson, Wayne; vanDam, C. P.; Chao, David D.; Cortes, Regina; Yee, Karen

1999-01-01

Accurate, reliable and robust numerical predictions of wind turbine rotor power remain a challenge to the wind energy industry. The literature reports various methods that compare predictions to experiments. The methods vary from Blade Element Momentum Theory (BEM), Vortex Lattice (VL), to variants of Reynolds-averaged Navier-Stokes (RaNS). The BEM and VL methods consistently show discrepancies in predicting rotor power at higher wind speeds mainly due to inadequacies with inboard stall and stall delay models. The RaNS methodologies show promise in predicting blade stall. However, inaccurate rotor vortex wake convection, boundary layer turbulence modeling and grid resolution has limited their accuracy. In addition, the inherently unsteady stalled flow conditions become computationally expensive for even the best endowed research labs. Although numerical power predictions have been compared to experiment. The availability of good wind turbine data sufficient for code validation experimental data that has been extracted from the IEA Annex XIV download site for the NREL Combined Experiment phase II and phase IV rotor. In addition, the comparisons will show data that has been further reduced into steady wind and zero yaw conditions suitable for comparisons to "steady wind" rotor power predictions. In summary, the paper will present and discuss the capabilities and limitations of the three numerical methods and make available a database of experimental data suitable to help other numerical methods practitioners validate their own work.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Baroni, A.; Schiavilla, R.

Cross sections for inclusive neutrino scattering off deuteron induced by neutral and charge-changing weak currents are calculated from threshold up to 150 MeV energies in a chiral effective field theory including high orders in the power counting. The contributions beyond leading order (LO) in the weak current are found to be small, and increase the cross sections obtained with the LO transition operators by a couple of percent over the whole energy range (0--150) MeV. Furthermore, the cutoff dependence is negligible, and the predicted cross sections are within ~2% of, albeit consistently larger than, corresponding predictions obtained in conventional meson-exchangemore » frameworks.« less

Predicting the behavior of techno-social systems.

PubMed

Vespignani, Alessandro

2009-07-24

We live in an increasingly interconnected world of techno-social systems, in which infrastructures composed of different technological layers are interoperating within the social component that drives their use and development. Examples are provided by the Internet, the World Wide Web, WiFi communication technologies, and transportation and mobility infrastructures. The multiscale nature and complexity of these networks are crucial features in understanding and managing the networks. The accessibility of new data and the advances in the theory and modeling of complex networks are providing an integrated framework that brings us closer to achieving true predictive power of the behavior of techno-social systems.

From documentation to prediction: Raising the bar for thermokarst research

DOE PAGES

Rowland, Joel C.; Coon, Ethan T.

2015-11-12

Here we report that to date the majority of published research on thermokarst has been directed at documenting its form, occurrence, and rates of occurrence. The fundamental processes driving thermokarst have long been largely understood. However, the detailed physical couplings between, water, air, soil, and the thermal dynamics governing freeze-thaw and soil mechanics is less understood and not captured in models aimed at predicting the response of frozen soils to warming and thaw. As computational resources increase more sophisticated mechanistic models can be applied; these show great promise as predictive tools. These models will be capable of simulating the responsemore » of soil deformation to thawing/freezing cycles and the long-term, non-recoverable response of the land surface to the loss of ice. At the same time, advances in remote sensing of permafrost environments also show promise in providing detailed and spatially extensive estimates in the rates and patterns of subsidence. These datasets provide key constraints to calibrate and evaluate the predictive power of mechanistic models. In conclusion, in the coming decade, these emerging technologies will greatly increase our ability to predict when, where, and how thermokarst will occur in a changing climate.« less

Projected electric power demands for the Potomac Electric Power Company

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wilson, J.W.

1975-07-01

Included are chapters on the background of the Potomac Electric Power Company, forecasting future power demand, demand modeling, accuracy of market predictions, and total power system requirements. (DG)

Power law behavior of RR-interval variability in healthy middle-aged persons, patients with recent acute myocardial infarction, and patients with heart transplants

NASA Technical Reports Server (NTRS)

Bigger, J. T. Jr; Steinman, R. C.; Rolnitzky, L. M.; Fleiss, J. L.; Albrecht, P.; Cohen, R. J.

1996-01-01

BACKGROUND. The purposes of the present study were (1) to establish normal values for the regression of log(power) on log(frequency) for, RR-interval fluctuations in healthy middle-aged persons, (2) to determine the effects of myocardial infarction on the regression of log(power) on log(frequency), (3) to determine the effect of cardiac denervation on the regression of log(power) on log(frequency), and (4) to assess the ability of power law regression parameters to predict death after myocardial infarction. METHODS AND RESULTS. We studied three groups: (1) 715 patients with recent myocardial infarction; (2) 274 healthy persons age and sex matched to the infarct sample; and (3) 19 patients with heart transplants. Twenty-four-hour RR-interval power spectra were computed using fast Fourier transforms and log(power) was regressed on log(frequency) between 10(-4) and 10(-2) Hz. There was a power law relation between log(power) and log(frequency). That is, the function described a descending straight line that had a slope of approximately -1 in healthy subjects. For the myocardial infarction group, the regression line for log(power) on log(frequency) was shifted downward and had a steeper negative slope (-1.15). The transplant (denervated) group showed a larger downward shift in the regression line and a much steeper negative slope (-2.08). The correlation between traditional power spectral bands and slope was weak, and that with log(power) at 10(-4) Hz was only moderate. Slope and log(power) at 10(-4) Hz were used to predict mortality and were compared with the predictive value of traditional power spectral bands. Slope and log(power) at 10(-4) Hz were excellent predictors of all-cause mortality or arrhythmic death. To optimize the prediction of death, we calculated a log(power) intercept that was uncorrelated with the slope of the power law regression line. We found that the combination of slope and zero-correlation log(power) was an outstanding predictor, with a relative risk of > 10, and was better than any combination of the traditional power spectral bands. The combination of slope and log(power) at 10(-4) Hz also was an excellent predictor of death after myocardial infarction. CONCLUSIONS. Myocardial infarction or denervation of the heart causes a steeper slope and decreased height of the power law regression relation between log(power) and log(frequency) of RR-interval fluctuations. Individually and, especially, combined, the power law regression parameters are excellent predictors of death of any cause or arrhythmic death and predict these outcomes better than the traditional power spectral bands.

Peer Influence, Information Quality and Predictive Power of Stock Microblogs

ERIC Educational Resources Information Center

Oh, Chong Keat

2013-01-01

Due to the popularity of Web 2.0 and Social Media in the last decade, the percolation of user generated content (UGC) has rapidly increased. In the financial realm, this results in the emergence of virtual investing communities (VIC) to the investing public. There is an on-going debate among scholars and practitioners on whether such UGC contain…

From Single Words to Passages: Contextual Effects on Predictive Power of Vocabulary Measures for Assessing Reading Performance

ERIC Educational Resources Information Center

Qian, David D.

2008-01-01

In the last 15 years or so, language testing practitioners have increasingly favored assessing vocabulary in context. The discrete-point vocabulary measure used in the old version of the Test of English as a Foreign Language (TOEFL) has long been criticized for encouraging test candidates to memorize wordlists out of context although test items…

International Elite, or Global Citizens? Equity, Distinction and Power: The International Baccalaureate and the Rise of the South

ERIC Educational Resources Information Center

Gardner-McTaggart, Alexander

2016-01-01

The 2013 UN Human Development report predicts the middle classes of "The South" a five-fold increase by 2030. Globalisation has resulted in national conceptions of business: education and identity being in flux. Emerging middle classes of the South are already embracing international forms of education for instrumental reasons of…

Experimental validation of finite element and boundary element methods for predicting structural vibration and radiated noise

NASA Technical Reports Server (NTRS)

Seybert, A. F.; Wu, T. W.; Wu, X. F.

1994-01-01

This research report is presented in three parts. In the first part, acoustical analyses were performed on modes of vibration of the housing of a transmission of a gear test rig developed by NASA. The modes of vibration of the transmission housing were measured using experimental modal analysis. The boundary element method (BEM) was used to calculate the sound pressure and sound intensity on the surface of the housing and the radiation efficiency of each mode. The radiation efficiency of each of the transmission housing modes was then compared to theoretical results for a finite baffled plate. In the second part, analytical and experimental validation of methods to predict structural vibration and radiated noise are presented. A rectangular box excited by a mechanical shaker was used as a vibrating structure. Combined finite element method (FEM) and boundary element method (BEM) models of the apparatus were used to predict the noise level radiated from the box. The FEM was used to predict the vibration, while the BEM was used to predict the sound intensity and total radiated sound power using surface vibration as the input data. Vibration predicted by the FEM model was validated by experimental modal analysis; noise predicted by the BEM was validated by measurements of sound intensity. Three types of results are presented for the total radiated sound power: sound power predicted by the BEM model using vibration data measured on the surface of the box; sound power predicted by the FEM/BEM model; and sound power measured by an acoustic intensity scan. In the third part, the structure used in part two was modified. A rib was attached to the top plate of the structure. The FEM and BEM were then used to predict structural vibration and radiated noise respectively. The predicted vibration and radiated noise were then validated through experimentation.

Power transfer systems for future navy helicopters. Final report 25 Jun 70--28 Jun 72

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bossler, R.B. Jr.

1972-11-01

The purpose of this program was to conduct an analysis of helicopter power transfer systems (pts), both conventional and advanced concept type, with the objective of reducing specific weights and improving reliability beyond present values. The analysis satisfied requirements specified for a 200,000 pound cargo transport helicopter (CTH), a 70,000 pound heavy assault helicopter, and a 15,000 pound non-combat search and rescue helicopter. Four selected gearing systems (out of seven studied), optimized for lightest weight and equal reliability for the CTH, using component proportioning via stress and stiffness equations, had no significant difference between their aircraft payloads. All optimized ptsmore » were approximately 70% of statistically predicted weight. Reliability increase is predicted via gearbox derating using Weibull relationships. Among advanced concepts, the Turbine Integrated Geared Rotor was competitive for weight, technology availability and reliability increase but handicapped by a special engine requirement. The warm cycle system was found not competitive. Helicopter parametric weight analysis is shown. Advanced development Plans are presented for the pts for the CTH, including total pts system, selected pts components, and scale model flight testing in a Kaman HH2 helicopter.« less

Rotary engine performance limits predicted by a zero-dimensional model

NASA Technical Reports Server (NTRS)

Bartrand, Timothy A.; Willis, Edward A.

1992-01-01

A parametric study was performed to determine the performance limits of a rotary combustion engine. This study shows how well increasing the combustion rate, insulating, and turbocharging increase brake power and decrease fuel consumption. Several generalizations can be made from the findings. First, it was shown that the fastest combustion rate is not necessarily the best combustion rate. Second, several engine insulation schemes were employed for a turbocharged engine. Performance improved only for a highly insulated engine. Finally, the variability of turbocompounding and the influence of exhaust port shape were calculated. Rotary engines performance was predicted by an improved zero-dimensional computer model based on a model developed at the Massachusetts Institute of Technology in the 1980's. Independent variables in the study include turbocharging, manifold pressures, wall thermal properties, leakage area, and exhaust port geometry. Additions to the computer programs since its results were last published include turbocharging, manifold modeling, and improved friction power loss calculation. The baseline engine for this study is a single rotor 650 cc direct-injection stratified-charge engine with aluminum housings and a stainless steel rotor. Engine maps are provided for the baseline and turbocharged versions of the engine.

Program Predicts Nonlinear Inverter Performance

NASA Technical Reports Server (NTRS)

Al-Ayoubi, R. R.; Oepomo, T. S.

1985-01-01

Program developed for ac power distribution system on Shuttle orbiter predicts total load on inverters and node voltages at each of line replaceable units (LRU's). Mathematical model simulates inverter performance at each change of state in power distribution system.

A novel method for predicting the power outputs of wave energy converters

NASA Astrophysics Data System (ADS)

Wang, Yingguang

2018-03-01

This paper focuses on realistically predicting the power outputs of wave energy converters operating in shallow water nonlinear waves. A heaving two-body point absorber is utilized as a specific calculation example, and the generated power of the point absorber has been predicted by using a novel method (a nonlinear simulation method) that incorporates a second order random wave model into a nonlinear dynamic filter. It is demonstrated that the second order random wave model in this article can be utilized to generate irregular waves with realistic crest-trough asymmetries, and consequently, more accurate generated power can be predicted by subsequently solving the nonlinear dynamic filter equation with the nonlinearly simulated second order waves as inputs. The research findings demonstrate that the novel nonlinear simulation method in this article can be utilized as a robust tool for ocean engineers in their design, analysis and optimization of wave energy converters.

Operations of the External Conjugate-T Matching System for the A2 ICRH Antennas at JET

NASA Astrophysics Data System (ADS)

Monakhov, I.; Graham, M.; Blackman, T.; Mayoral, M.-L.; Nightingale, M.; Sheikh, H.; Whitehurst, A.

2009-11-01

The External Conjugate-T (ECT) matching system was successfully commissioned on two A2 ICRH antennas at JET in 2009. The system allows trip-free injection of RF power into ELMy H-mode plasmas in the 32-52 MHz band without antenna phasing restrictions. The ECT demonstrates robust and predictable performance and high load-tolerance during routine operations, injecting up to 4 MW average power into H-mode plasma with Type-I ELMs. The total power coupled to ELMy plasma by all the A2 antennas using the ECT and 3dB systems has been increased to 7 MW. Antenna arcing during ELMs has been identified as a new challenge to high-power ICRH operations in H-mode plasma. The implemented Advanced Wave Amplitude Comparison System (AWACS) has proven to be an efficient protection tool for the ECT scheme.

Optimization of power and energy densities in supercapacitors

NASA Astrophysics Data System (ADS)

Robinson, David B.

Supercapacitors use nanoporous electrodes to store large amounts of charge on their high surface areas, and use the ions in electrolytes to carry charge into the pores. Their high power density makes them a potentially useful complement to batteries. However, ion transport through long, narrow channels still limits power and efficiency in these devices. Proper design can mitigate this. Current collector geometry must also be considered once this is done. Here, De Levie's model for porous electrodes is applied to quantitatively predict device performance and to propose optimal device designs for given specifications. Effects unique to nanoscale pores are considered, including that pores may not have enough salt to fully charge. Supercapacitors are of value for electric vehicles, portable electronics, and power conditioning in electrical grids with distributed renewable sources, and that value will increase as new device fabrication methods are developed and proper design accommodates those improvements. Example design outlines for vehicle applications are proposed and compared.

Operations of the External Conjugate-T Matching System for the A2 ICRH Antennas at JET

DOE Office of Scientific and Technical Information (OSTI.GOV)

Monakhov, I.; Graham, M.; Blackman, T.

2009-11-26

The External Conjugate-T (ECT) matching system was successfully commissioned on two A2 ICRH antennas at JET in 2009. The system allows trip-free injection of RF power into ELMy H-mode plasmas in the 32-52 MHz band without antenna phasing restrictions. The ECT demonstrates robust and predictable performance and high load-tolerance during routine operations, injecting up to 4 MW average power into H-mode plasma with Type-I ELMs. The total power coupled to ELMy plasma by all the A2 antennas using the ECT and 3dB systems has been increased to 7 MW. Antenna arcing during ELMs has been identified as a new challengemore » to high-power ICRH operations in H-mode plasma. The implemented Advanced Wave Amplitude Comparison System (AWACS) has proven to be an efficient protection tool for the ECT scheme.« less

Piezoelectric diaphragm for vibration energy harvesting.

PubMed

Minazara, E; Vasic, D; Costa, F; Poulin, G

2006-12-22

This paper presents a technique of electric energy generation using a mechanically excited unimorph piezoelectric membrane transducer. The electrical characteristics of the piezoelectric power generator are investigated under dynamic conditions. The electromechanical model of the generator is presented and used to predict its electrical performances. The experiments was performed with a piezoelectric actuator (shaker) moving a macroscopic 25 mm diameter piezoelectric membrane. A power of 0.65 mW was generated at the resonance frequency (1.71 kHz) across a 5.6 kOmega optimal resistor and for a 80 N force. A special electronic circuit has been conceived in order to increase the power harvested by the piezoelectric transducer. This electrical converter applies the SSHI (synchronized switch harvesting on inductor) technique, and leads to remarkable results: under the same actuation conditions the generated power reaches 1.7 mW, which is sufficient to supply a large range of low consumption sensors.

The all-fiber cladding-pumped Yb-doped gain-switched laser.

PubMed

Larsen, C; Hansen, K P; Mattsson, K E; Bang, O

2014-01-27

Gain-switching is an alternative pulsing technique of fiber lasers, which is power scalable and has a low complexity. From a linear stability analysis of rate equations the relaxation oscillation period is derived and from it, the pulse duration is defined. Good agreement between the measured pulse duration and the theoretical prediction is found over a wide range of parameters. In particular we investigate the influence of an often present length of passive fiber in the cavity and show that it introduces a finite minimum in the achievable pulse duration. This minimum pulse duration is shown to occur at longer active fibers length with increased passive length of fiber in the cavity. The peak power is observed to depend linearly on the absorbed pump power and be independent of the passive fiber length. Given these conclusions, the pulse energy, duration, and peak power can be estimated with good precision.

Optimization principles and the figure of merit for triboelectric generators.

PubMed

Peng, Jun; Kang, Stephen Dongmin; Snyder, G Jeffrey

2017-12-01

Energy harvesting with triboelectric nanogenerators is a burgeoning field, with a growing portfolio of creative application schemes attracting much interest. Although power generation capabilities and its optimization are one of the most important subjects, a satisfactory elemental model that illustrates the basic principles and sets the optimization guideline remains elusive. We use a simple model to clarify how the energy generation mechanism is electrostatic induction but with a time-varying character that makes the optimal matching for power generation more restrictive. By combining multiple parameters into dimensionless variables, we pinpoint the optimum condition with only two independent parameters, leading to predictions of the maximum limit of power density, which allows us to derive the triboelectric material and device figure of merit. We reveal the importance of optimizing device capacitance, not only load resistance, and minimizing the impact of parasitic capacitance. Optimized capacitances can lead to an overall increase in power density of more than 10 times.

Highly Automated Module Production Incorporating Advanced Light Management

DOE Office of Scientific and Technical Information (OSTI.GOV)

Perelli-Minetti, Michael; Roof, Kyle

2015-08-11

The objective was to enable a high volume, cost effective solution for increasing the amount of light captured by PV modules through utilization of an advanced Light Re-directing Film and to follow a phased approach to develop and implement this new technology in order to achieve an expected power gain of up to 12 watts per module. Full size PV modules were manufactured using a new Light Redirecting Film (LRF) material applied to two different areas of PV modules in order to increase the amount of light captured by the modules. One configuration involved applying thin strips of LRF filmmore » over the tabbing ribbon on the cells in order to redirect the light that is normally absorbed by the tabbing ribbon to the active areas of the cells. A second configuration involved applying thin strips of LRF film over the white spaces between cells within a module in order to capture some of the light that is normally reflected from the white areas back through the front glass of the modules. Significant power increases of 1.4% (3.9 watts) and 1.0% (3.2 watts), respectively, compared to standard PV modules were measured under standard test conditions. The performance of PV modules with LRF applied to the tabbing ribbon was modeled. The results showed that the power increase provided by LRF depended greatly on the angle of incident light with the optimum performance only occurring when the light was within a narrow range of being perpendicular to the solar module. The modeling showed that most of the performance gain would be lost when the angle of incident light was greater than 28 degrees off axis. This effect made the orientation of modules with LRF applied to tabbing ribbons very important as modules mounted in “portrait” mode were predicted to provide little to no power gain from LRF under real world conditions. Based on these results, modules with LRF on tabbing ribbons would have to be mounted in “landscape” mode to realize a performance advantage. In addition, modeling showed that under diffuse lighting conditions such as when the sky is overcast, there would be no significant performance advantage for modules with LRF. Modules were sent to an outside contractor to measure the power performance under different angles of incident light in order to validate the modeling results. The measured data agreed very well with the modeling predictions and showed that the power gain for modules with LRF applied to tabbing ribbons was completely lost at an angle of 25 degrees off of perpendicular. At even larger angles, the power was lower than standard modules. From 35 degrees to 55 degrees off axis, the power loss was about 1.4% or equal to the power gain at the optimum condition of perfectly on-axis light.« less

A simulation model for predicting the temperature during the application of MR-guided focused ultrasound for stroke treatment using pulsed ultrasound

NASA Astrophysics Data System (ADS)

Hadjisavvas, V.; Damianou, C.

2011-09-01

In this paper a simulation model for predicting the temperature during the application of MR-guided focused ultrasound for stroke treatment using pulsed ultrasound is presented. A single element spherically focused transducer of 5 cm diameter, focusing at 10 cm and operating at either 0.5 MHz or 1 MHz was considered. The power field was estimated using the KZK model. The temperature was estimated using the bioheat equation. The goal was to extract the acoustic parameters (power, pulse duration, duty factor and pulse repetition frequency) that maintain a temperature increase of less than 1 °C during the application of a pulse ultrasound protocol. It was found that the temperature change increases linearly with duty factor. The higher the power, the lower the duty factor needed to keep the temperature change to the safe limit of 1 °C. The higher the frequency the lower the duty factor needed to keep the temperature change to the safe limit of 1 °C. Finally, the deeper the target, the higher the duty factor needed to keep the temperature change to the safe limit of 1 °C. The simulation model was tested in brain tissue during the application of pulse ultrasound and the measured temperature was in close agreement with the simulated temperature. This simulation model is considered to be very useful tool for providing acoustic parameters (frequency, power, duty factor, pulse repetition frequency) during the application of pulsed ultrasound at various depths in tissue so that a safe temperature is maintained during the treatment. This model could be tested soon during stroke clinical trials.

The complex contribution of sociodemographics to decision-making power in gay male couples

PubMed Central

Perry, Nicholas S.; Huebner, David M.; Baucom, Brian R. W.; Hoff, Colleen C.

2016-01-01

Relationship power is an important dyadic construct in close relationships that is associated with relationship health and partner’s individual health. Understanding what predicts power in heterosexual couples has proven difficult, and even less is known about gay couples. Resource models of power posit that demographic characteristics associated with social status (e.g., age, income) confer power within the relationship, which in turn shapes relationship outcomes. We tested this model in a sample of gay male couples (N=566 couples), and extended it by examining race and HIV status. Multilevel modeling was used to test associations between demographic bases of power and decision-making power. We also examined relative associations among demographic bases and decision-making power with relationship satisfaction, given the literature on power imbalances and overall relationship functioning. Results showed that individual income was positively associated with decision-making power, as was participant’s HIV status, with HIV-positive men reporting greater power. Age differences within the relationship interacted with relationship length to predict decision-making power, but not satisfaction. HIV-concordant positive couples were less satisfied than concordant negative couples. Higher power partners were less satisfied than lower power partners. Demographic factors contributing to decision-making power among same-sex male couples appear to share some similarities with heterosexual couples (e.g., income is associated with power), as well as have unique features (e.g., HIV status influences power). However, these same demographics did not reliably predict relationship satisfaction in the manner that existing power theories suggest. Findings indicate important considerations for theories of power among same-sex male couples. PMID:27606937

Mentoring Support and Power: A Three Year Predictive Field Study on Protege Networking and Career Success

ERIC Educational Resources Information Center

Blickle, Gerhard; Witzki, Alexander H.; Schneider, Paula B.

2009-01-01

Career success of early employees was analyzed from a power perspective and a developmental network perspective. In a predictive field study with 112 employees mentoring support and mentors' power were assessed in the first wave, employees' networking was assessed after two years, and career success (i.e. income and hierarchical position) and…

Measurement of the temperature distribution inside the power cable using distributed temperature system

NASA Astrophysics Data System (ADS)

Jaros, Jakub; Liner, Andrej; Papes, Martin; Vasinek, Vladimir; Mach, Veleslav; Hruby, David; Kajnar, Tomas; Perecar, Frantisek

2015-01-01

Nowadays, the power cables are manufactured to fulfill the following condition - the highest allowable temperature of the cable during normal operation and the maximum allowable temperature at short circuit conditions cannot exceed the condition of the maximum allowable internal temperature. The distribution of the electric current through the conductor leads to the increase of the amplitude of electrons in the crystal lattice of the cables material. The consequence of this phenomenon is the increase of friction and the increase of collisions between particles inside the material, which causes the temperature increase of the carrying elements. The temperature increase is unwanted phenomena, because it is causing losses. In extreme cases, the long-term overload leads to the cable damaging or fire. This paper deals with the temperature distribution measurement inside the power cables using distributed temperature system. With cooperation with Kabex company, the tube containing optical fibers was installed into the center of power cables. These fibers, except telecommunications purposes, can be also used as sensors in measurements carrying out with distributed temperature system. These systems use the optical fiber as a sensor and allow the continual measurement of the temperature along the whole cable in real time with spatial resolution 1 m. DTS systems are successfully deployed in temperature measurement applications in industry areas yet. These areas include construction, drainage, hot water etc. Their advantages are low cost, resistance to electromagnetic radiation and the possibility of real time monitoring at the distance of 8 km. The location of the optical fiber in the center of the power cable allows the measurement of internal distribution of the temperature during overloading the cable. This measurement method can be also used for prediction of short-circuit and its exact location.

Genomic predictive model for recurrence and metastasis development in head and neck squamous cell carcinoma patients.

PubMed

Ribeiro, Ilda Patrícia; Caramelo, Francisco; Esteves, Luísa; Menoita, Joana; Marques, Francisco; Barroso, Leonor; Miguéis, Jorge; Melo, Joana Barbosa; Carreira, Isabel Marques

2017-10-24

The head and neck squamous cell carcinoma (HNSCC) population consists mainly of high-risk for recurrence and locally advanced stage patients. Increased knowledge of the HNSCC genomic profile can improve early diagnosis and treatment outcomes. The development of models to identify consistent genomic patterns that distinguish HNSCC patients that will recur and/or develop metastasis after treatment is of utmost importance to decrease mortality and improve survival rates. In this study, we used array comparative genomic hybridization data from HNSCC patients to implement a robust model to predict HNSCC recurrence/metastasis. This predictive model showed a good accuracy (>80%) and was validated in an independent population from TCGA data portal. This predictive genomic model comprises chromosomal regions from 5p, 6p, 8p, 9p, 11q, 12q, 15q and 17p, where several upstream and downstream members of signaling pathways that lead to an increase in cell proliferation and invasion are mapped. The introduction of genomic predictive models in clinical practice might contribute to a more individualized clinical management of the HNSCC patients, reducing recurrences and improving patients' quality of life. The power of this genomic model to predict the recurrence and metastases development should be evaluated in other HNSCC populations.

Optic Nerve Sheath Diameter: Translating a Terrestrial Focused Technique into a Clinical Monitoring Tool for Spaceflight

NASA Technical Reports Server (NTRS)

Mason, Sara; Foy, Millennia; Sargsyan, Ashot; Garcia, Kathleen; Wear, Mary L.; Bedi, Deepak; Ernst, Randy; Van Baalen, Mary

2015-01-01

Ultrasonography is increasingly used to quickly measure optic nerve sheath diameter (ONSD) when increased intracranial pressure (ICP) is suspected. NASA Space and Clinical Operations Division has been using ground and on-orbit ultrasound since 2009 as a proxy for ICP in non-acute monitoring for space medicine purposes. In the terrestrial emergency room population, an ONSD greater than 0.59 cm is considered highly predictive of elevated intracranial pressure. However, this cut-off limit is not applicable to the spaceflight setting since over 50% of US Operating Segment (USOS) astronauts have an ONSD greater than 0.60 cm even before launch. Crew Surgeon clinical decision-making is complicated by the fact that many astronauts have history of previous spaceflights. Our data characterize the distribution of baseline ONSD in the astronaut corps, its longitudinal trends in long-duration spaceflight, and the predictive power of this measure related to increased ICP outcomes.

Power-Stepped HF Cross-Modulation Experiments: Simulations and Experimental Observations

NASA Astrophysics Data System (ADS)

Greene, S.; Moore, R. C.

2014-12-01

High frequency (HF) cross modulation experiments are a well established means for probing the HF-modified characteristics of the D-region ionosphere. The interaction between the heating wave and the probing pulse depends on the ambient and modified conditions of the D-region ionosphere. Cross-modulation observations are employed as a measure of the HF-modified refractive index. We employ an optimized version of Fejer's method that we developed during previous experiments. Experiments were performed in March 2013 at the High Frequency Active Auroral Research Program (HAARP) observatory in Gakona, Alaska. During these experiments, the power of the HF heating signal incrementally increased in order to determine the dependence of cross-modulation on HF power. We found that a simple power law relationship does not hold at high power levels, similar to previous ELF/VLF wave generation experiments. In this paper, we critically compare these experimental observations with the predictions of a numerical ionospheric HF heating model and demonstrate close agreement.

A Novel Approach of Battery Energy Storage for Improving Value of Wind Power in Deregulated Markets

NASA Astrophysics Data System (ADS)

Nguyen, Y. Minh; Yoon, Yong Tae

2013-06-01

Wind power producers face many regulation costs in deregulated environment, which remarkably lowers the value of wind power in comparison with the conventional sources. One of these costs is associated with the real-time variation of power output and being paid in frequency control market according to the variation band. In this regard, this paper presents a new approach to the scheduling and operation of battery energy storage installed in wind generation system. This approach depends on the statistic data of wind generation and the prediction of frequency control market prices to determine the optimal charging and discharging of batteries in real-time, which ultimately gives the minimum cost of frequency regulation for wind power producers. The optimization problem is formulated as the trade-off between the decrease in regulation payment and the increase in the cost of using battery energy storage. The approach is illustrated in the case study and the results of simulation show its effectiveness.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Imani, Mohammadreza F., E-mail: mohamad.imani@gmail.com; Grbic, Anthony

One of the obstacles preventing wireless power transfer from becoming ubiquitous is their leakage of power: high-amplitude electromagnetic fields that can interfere with other electronic devices, increase health concerns, or hinder power metering. In this paper, we present near-field plates (NFPs) as a novel method to tailor the electromagnetic fields generated by a wireless power transfer system while maintaining high efficiency. NFPs are modulated arrays or surfaces designed to form prescribed near-field patterns. The NFP proposed in this paper consists of an array of loaded loops that are designed to confine the electromagnetic fields of a resonant transmitting loop tomore » the desired direction (receiving loop) while suppressing fields in other directions. The step-by-step design procedure for this device is outlined. Two NFPs are designed and examined in full-wave simulation. Their performance is shown to be in close agreement with the design predictions, thereby verifying the proposed design and operation. A NFP is also fabricated and experimentally shown to form a unidirectional wireless power transfer link with high efficiency.« less

Unpredicted Pitch Modulates Beta Oscillatory Power during Rhythmic Entrainment to a Tone Sequence.

PubMed

Chang, Andrew; Bosnyak, Dan J; Trainor, Laurel J

2016-01-01

Extracting temporal regularities in external stimuli in order to predict upcoming events is an essential aspect of perception. Fluctuations in induced power of beta band (15-25 Hz) oscillations in auditory cortex are involved in predictive timing during rhythmic entrainment, but whether such fluctuations are affected by prediction in the spectral (frequency/pitch) domain remains unclear. We tested whether unpredicted (i.e., unexpected) pitches in a rhythmic tone sequence modulate beta band activity by recording EEG while participants passively listened to isochronous auditory oddball sequences with occasional unpredicted deviant pitches at two different presentation rates. The results showed that the power in low-beta (15-20 Hz) was larger around 200-300 ms following deviant tones compared to standard tones, and this effect was larger when the deviant tones were less predicted. Our results suggest that the induced beta power activities in auditory cortex are consistent with a role in sensory prediction of both "when" (timing) upcoming sounds will occur as well as the prediction precision error of "what" (spectral content in this case). We suggest, further, that both timing and content predictions may co-modulate beta oscillations via attention. These findings extend earlier work on neural oscillations by investigating the functional significance of beta oscillations for sensory prediction. The findings help elucidate the functional significance of beta oscillations in perception.

Unpredicted Pitch Modulates Beta Oscillatory Power during Rhythmic Entrainment to a Tone Sequence

PubMed Central

Chang, Andrew; Bosnyak, Dan J.; Trainor, Laurel J.

2016-01-01

Extracting temporal regularities in external stimuli in order to predict upcoming events is an essential aspect of perception. Fluctuations in induced power of beta band (15–25 Hz) oscillations in auditory cortex are involved in predictive timing during rhythmic entrainment, but whether such fluctuations are affected by prediction in the spectral (frequency/pitch) domain remains unclear. We tested whether unpredicted (i.e., unexpected) pitches in a rhythmic tone sequence modulate beta band activity by recording EEG while participants passively listened to isochronous auditory oddball sequences with occasional unpredicted deviant pitches at two different presentation rates. The results showed that the power in low-beta (15–20 Hz) was larger around 200–300 ms following deviant tones compared to standard tones, and this effect was larger when the deviant tones were less predicted. Our results suggest that the induced beta power activities in auditory cortex are consistent with a role in sensory prediction of both “when” (timing) upcoming sounds will occur as well as the prediction precision error of “what” (spectral content in this case). We suggest, further, that both timing and content predictions may co-modulate beta oscillations via attention. These findings extend earlier work on neural oscillations by investigating the functional significance of beta oscillations for sensory prediction. The findings help elucidate the functional significance of beta oscillations in perception. PMID:27014138

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moslehi, Salim; Reddy, T. Agami; Katipamula, Srinivas

This research was undertaken to evaluate different inverse models for predicting power output of solar photovoltaic (PV) systems under different practical scenarios. In particular, we have investigated whether PV power output prediction accuracy can be improved if module/cell temperature was measured in addition to climatic variables, and also the extent to which prediction accuracy degrades if solar irradiation is not measured on the plane of array but only on a horizontal surface. We have also investigated the significance of different independent or regressor variables, such as wind velocity and incident angle modifier in predicting PV power output and cell temperature.more » The inverse regression model forms have been evaluated both in terms of their goodness-of-fit, and their accuracy and robustness in terms of their predictive performance. Given the accuracy of the measurements, expected CV-RMSE of hourly power output prediction over the year varies between 3.2% and 8.6% when only climatic data are used. Depending on what type of measured climatic and PV performance data is available, different scenarios have been identified and the corresponding appropriate modeling pathways have been proposed. The corresponding models are to be implemented on a controller platform for optimum operational planning of microgrids and integrated energy systems.« less

Informative priors on fetal fraction increase power of the noninvasive prenatal screen.

PubMed

Xu, Hanli; Wang, Shaowei; Ma, Lin-Lin; Huang, Shuai; Liang, Lin; Liu, Qian; Liu, Yang-Yang; Liu, Ke-Di; Tan, Ze-Min; Ban, Hao; Guan, Yongtao; Lu, Zuhong

2017-11-09

PurposeNoninvasive prenatal screening (NIPS) sequences a mixture of the maternal and fetal cell-free DNA. Fetal trisomy can be detected by examining chromosomal dosages estimated from sequencing reads. The traditional method uses the Z-test, which compares a subject against a set of euploid controls, where the information of fetal fraction is not fully utilized. Here we present a Bayesian method that leverages informative priors on the fetal fraction.MethodOur Bayesian method combines the Z-test likelihood and informative priors of the fetal fraction, which are learned from the sex chromosomes, to compute Bayes factors. Bayesian framework can account for nongenetic risk factors through the prior odds, and our method can report individual positive/negative predictive values.ResultsOur Bayesian method has more power than the Z-test method. We analyzed 3,405 NIPS samples and spotted at least 9 (of 51) possible Z-test false positives.ConclusionBayesian NIPS is more powerful than the Z-test method, is able to account for nongenetic risk factors through prior odds, and can report individual positive/negative predictive values.Genetics in Medicine advance online publication, 9 November 2017; doi:10.1038/gim.2017.186.

Investigation of Rotor Performance and Loads of a UH-60A Individual Blade Control System

NASA Technical Reports Server (NTRS)

Yeo, Hyeonsoo; Romander, Ethan A.; Norman, Thomas R.

2011-01-01

Wind tunnel measurements of performance, loads, and vibration of a full-scale UH-60A Black Hawk main rotor with an individual blade control (IBC) system are compared with calculations obtained using the comprehensive helicopter analysis CAMRAD II and a coupled CAMRAD II/OVERFLOW 2 analysis. Measured data show a 5.1% rotor power reduction (8.6% rotor lift to effective-drag ratio increase) using 2/rev IBC actuation with 2.0 amplitude at = 0.4. At the optimum IBC phase for rotor performance, IBC actuator force (pitch link force) decreased, and neither flap nor chord bending moments changed significantly. CAMRAD II predicts the rotor power variations with the IBC phase reasonably well at = 0.35. However, the correlation degrades at = 0.4. Coupled CAMRAD II/OVERFLOW 2 shows excellent correlation with the measured rotor power variations with the IBC phase at both = 0.35 and = 0.4. Maximum reduction of IBC actuator force is better predicted with CAMRAD II, but general trends are better captured with the coupled analysis. The correlation of vibratory hub loads is generally poor by both methods, although the coupled analysis somewhat captures general trends.

Soil temperature extrema recovery rates after precipitation cooling

NASA Technical Reports Server (NTRS)

Welker, J. E.

1984-01-01

From a one dimensional view of temperature alone variations at the Earth's surface manifest themselves in two cyclic patterns of diurnal and annual periods, due principally to the effects of diurnal and seasonal changes in solar heating as well as gains and losses of available moisture. Beside these two well known cyclic patterns, a third cycle has been identified which occurs in values of diurnal maxima and minima soil temperature extrema at 10 cm depth usually over a mesoscale period of roughly 3 to 14 days. This mesoscale period cycle starts with precipitation cooling of soil and is followed by a power curve temperature recovery. The temperature recovery clearly depends on solar heating of the soil with an increased soil moisture content from precipitation combined with evaporation cooling at soil temperatures lowered by precipitation cooling, but is quite regular and universal for vastly different geographical locations, and soil types and structures. The regularity of the power curve recovery allows a predictive model approach over the recovery period. Multivariable linear regression models alloy predictions of both the power of the temperature recovery curve as well as the total temperature recovery amplitude of the mesoscale temperature recovery, from data available one day after the temperature recovery begins.

Investigation of Rotor Performance and Loads of a UH-60A Individual Blade Control System

NASA Technical Reports Server (NTRS)

Yeo, Hyeonsoo; Romander, Ethan A.; Norman, Thomas R.

2011-01-01

Wind tunnel measurements of performance, loads, and vibration of a full-scale UH-60A Black Hawk main rotor with an individual blade control (IBC) system are compared with calculations obtained using the comprehensive helicopter analysis CAMRAD II and a coupled CAMRAD II/OVERFLOW 2 analysis. Measured data show a 5.1% rotor power reduction (8.6% rotor lift to effective-drag ratio increase) using 2/rev IBC actuation with 2.0. amplitude at u = 0.4. At the optimum IBC phase for rotor performance, IBC actuator force (pitch link force) decreased, and neither flap nor chord bending moments changed significantly. CAMRAD II predicts the rotor power variations with IBC phase reasonably well at u = 0.35. However, the correlation degrades at u = 0.4. Coupled CAMRAD II/OVERFLOW 2 shows excellent correlation with the measured rotor power variations with IBC phase at both u = 0.35 and u = 0.4. Maximum reduction of IBC actuator force is better predicted with CAMRAD II, but general trends are better captured with the coupled analysis. The correlation of vibratory hub loads is generally poor by both methods, although the coupled analysis somewhat captures general trends.

Stick balancing, falls and Dragon-Kings

NASA Astrophysics Data System (ADS)

Cabrera, J. L.; Milton, J. G.

2012-05-01

The extent to which the occurrence of falls, the dominant feature of human attempts to balance a stick at their fingertip, can be predicted is examined in the context of the "Dragon-King" hypothesis. For skilled stick balancers, fluctuations in the controlled variable, namely the vertical displacement angle θ, exhibit power law behaviors. When stick balancing is made less stable by either decreasing the length of the stick or by requiring the subject to balance the stick on the surface of a table tennis racket, systematic departures from the power law behaviors are observed in the range of large θ. This observation raises the possibility that the presence of departures from the power law in the large length scale region, possibly Dragon-Kings, may identify situations in which the occurrence of a fall is more imminent. However, whether or not Dragon-Kings are observed, there is a Weibull-type survival function for stick falling. The possibility that increased risk of falling can, at least to some extent, be predicted from fluctuations in the controlled variable before the event occurs has important implications for the development of preventative strategies for the management of phenomena ranging from earthquakes to epileptic seizures to falls in the elderly.

Predictors of Parental Locus of Control in Mothers of Pre- and Early-Adolescents

PubMed Central

Freed, Rachel D.; Tompson, Martha C.

2016-01-01

Parental locus of control refers to parents’ perceived power and efficacy in child-rearing situations. This study explored parental locus of control and its correlates in 160 mothers of children ages 8–14 cross-sectionally and 1 year later. Maternal depression, maternal expressed emotion, and child internalizing and externalizing behavior were examined, along with a number of sociodemographic factors. Cross-sectional analyses indicated that external parental locus of control was associated with child externalizing behavior, maternal depression, less maternal education, lower income, and older maternal age. Longitudinal analyses showed that child age and externalizing behavior also predicted increases in external parental locus of control 1 year later. Finally, lower income and less parental perceived control predicted increases in child externalizing behavior over time. PMID:21229447

50 kHz bottom backscattering measurements from two types of artificially roughened sandy bottoms

NASA Astrophysics Data System (ADS)

Son, Su-Uk; Cho, Sungho; Choi, Jee Woong

2016-07-01

Laboratory measurements of 50 kHz bottom backscattering strengths as a function of grazing angle were performed on the sandy bottom of a water tank; two types of bottom roughnesses, a relatively smooth interface and a rough interface, were created on the bottom surface. The roughness profiles of the two interface types were measured directly using an ultrasound arrival time difference of 5 MHz and then were Fourier transformed to obtain the roughness power spectra. The measured backscattering strengths increased from -29 to 0 dB with increasing grazing angle from 35 to 86°, which were compared to theoretical backscattering model predictions. The comparison results implied that bottom roughness is a key factor in accurately predicting bottom scattering for a sandy bottom.

The origins of computer weather prediction and climate modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lynch, Peter

2008-03-20

Numerical simulation of an ever-increasing range of geophysical phenomena is adding enormously to our understanding of complex processes in the Earth system. The consequences for mankind of ongoing climate change will be far-reaching. Earth System Models are capable of replicating climate regimes of past millennia and are the best means we have of predicting the future of our climate. The basic ideas of numerical forecasting and climate modeling were developed about a century ago, long before the first electronic computer was constructed. There were several major practical obstacles to be overcome before numerical prediction could be put into practice. Amore » fuller understanding of atmospheric dynamics allowed the development of simplified systems of equations; regular radiosonde observations of the free atmosphere and, later, satellite data, provided the initial conditions; stable finite difference schemes were developed; and powerful electronic computers provided a practical means of carrying out the prodigious calculations required to predict the changes in the weather. Progress in weather forecasting and in climate modeling over the past 50 years has been dramatic. In this presentation, we will trace the history of computer forecasting through the ENIAC integrations to the present day. The useful range of deterministic prediction is increasing by about one day each decade, and our understanding of climate change is growing rapidly as Earth System Models of ever-increasing sophistication are developed.« less

The origins of computer weather prediction and climate modeling

NASA Astrophysics Data System (ADS)

Lynch, Peter

2008-03-01

Numerical simulation of an ever-increasing range of geophysical phenomena is adding enormously to our understanding of complex processes in the Earth system. The consequences for mankind of ongoing climate change will be far-reaching. Earth System Models are capable of replicating climate regimes of past millennia and are the best means we have of predicting the future of our climate. The basic ideas of numerical forecasting and climate modeling were developed about a century ago, long before the first electronic computer was constructed. There were several major practical obstacles to be overcome before numerical prediction could be put into practice. A fuller understanding of atmospheric dynamics allowed the development of simplified systems of equations; regular radiosonde observations of the free atmosphere and, later, satellite data, provided the initial conditions; stable finite difference schemes were developed; and powerful electronic computers provided a practical means of carrying out the prodigious calculations required to predict the changes in the weather. Progress in weather forecasting and in climate modeling over the past 50 years has been dramatic. In this presentation, we will trace the history of computer forecasting through the ENIAC integrations to the present day. The useful range of deterministic prediction is increasing by about one day each decade, and our understanding of climate change is growing rapidly as Earth System Models of ever-increasing sophistication are developed.

Core Noise - Increasing Importance

NASA Technical Reports Server (NTRS)

Hultgren, Lennart S.

2011-01-01

This presentation is a technical summary of and outlook for NASA-internal and NASA-sponsored external research on core (combustor and turbine) noise funded by the Fundamental Aeronautics Program Subsonic Fixed Wing (SFW) Project. Sections of the presentation cover: the SFW system-level noise metrics for the 2015, 2020, and 2025 timeframes; turbofan design trends and their aeroacoustic implications; the emerging importance of core noise and its relevance to the SFW Reduced-Perceived-Noise Technical Challenge; and the current research activities in the core-noise area, with additional details given about the development of a high-fidelity combustor-noise prediction capability as well as activities supporting the development of improved reduced-order, physics-based models for combustor-noise prediction. The need for benchmark data for validation of high-fidelity and modeling work and the value of a potential future diagnostic facility for testing of core-noise-reduction concepts are indicated. The NASA Fundamental Aeronautics Program has the principal objective of overcoming today's national challenges in air transportation. The SFW Reduced-Perceived-Noise Technical Challenge aims to develop concepts and technologies to dramatically reduce the perceived aircraft noise outside of airport boundaries. This reduction of aircraft noise is critical to enabling the anticipated large increase in future air traffic. Noise generated in the jet engine core, by sources such as the compressor, combustor, and turbine, can be a significant contribution to the overall noise signature at low-power conditions, typical of approach flight. At high engine power during takeoff, jet and fan noise have traditionally dominated over core noise. However, current design trends and expected technological advances in engine-cycle design as well as noise-reduction methods are likely to reduce non-core noise even at engine-power points higher than approach. In addition, future low-emission combustor designs could increase the combustion-noise component. The trend towards high-power-density cores also means that the noise generated in the low-pressure turbine will likely increase. Consequently, the combined result from these emerging changes will be to elevate the overall importance of turbomachinery core noise, which will need to be addressed in order to meet future noise goals.

Design and aero-acoustic analysis of a counter-rotating wind turbine

NASA Astrophysics Data System (ADS)

Agrawal, Vineesh V.

Wind turbines have become an integral part of the energy business because they are one of the most economical and reliable sources of renewable energy. Conventional wind turbines are capable of capturing less than half of the energy present in the wind. Hence, to make the wind turbines more efficient, it is important to increase their performance. A horizontal axis wind turbine with multiple rotors is one concept that can achieve a higher power conversion rate. Also, a concern for wind energy is the noise generated by wind turbines. Hence, an investigation into the acoustic behavior of a multi-rotor horizontal axis wind turbine is required. In response to the need of a wind turbine design with higher power coefficient, a unique design of a counter-rotating horizontal axis wind turbine (CR-HAWT) is proposed. The Blade Element Momentum (BEM) theory is used to aerodynamically design the blades of the two rotors. Modifications are made to the BEM theory to accommodate the interaction of the two rotors. The tower effect on the noise generation of the downwind rotor is investigated. Predictions are made for the total noise generated by the wind turbine at its design operating conditions. A total power coefficient of 65.2% is predicted for the proposed CR-HAWT design. A low tip speed ratio is chosen to minimize the noise generation. The aeroacoustic analysis of the CR-HAWT shows that the noise generated at its design operating conditions is within an acceptable range. Thus, the CR-HAWT is predicted to be a quiet wind turbine with a high power coefficient, making it highly desirable for small wind turbine applications.