Modeling long correlation times using additive binary Markov chains: Applications to wind generation time series.

PubMed

Weber, Juliane; Zachow, Christopher; Witthaut, Dirk

2018-03-01

Wind power generation exhibits a strong temporal variability, which is crucial for system integration in highly renewable power systems. Different methods exist to simulate wind power generation but they often cannot represent the crucial temporal fluctuations properly. We apply the concept of additive binary Markov chains to model a wind generation time series consisting of two states: periods of high and low wind generation. The only input parameter for this model is the empirical autocorrelation function. The two-state model is readily extended to stochastically reproduce the actual generation per period. To evaluate the additive binary Markov chain method, we introduce a coarse model of the electric power system to derive backup and storage needs. We find that the temporal correlations of wind power generation, the backup need as a function of the storage capacity, and the resting time distribution of high and low wind events for different shares of wind generation can be reconstructed.

Modeling long correlation times using additive binary Markov chains: Applications to wind generation time series

NASA Astrophysics Data System (ADS)

Weber, Juliane; Zachow, Christopher; Witthaut, Dirk

2018-03-01

Wind power generation exhibits a strong temporal variability, which is crucial for system integration in highly renewable power systems. Different methods exist to simulate wind power generation but they often cannot represent the crucial temporal fluctuations properly. We apply the concept of additive binary Markov chains to model a wind generation time series consisting of two states: periods of high and low wind generation. The only input parameter for this model is the empirical autocorrelation function. The two-state model is readily extended to stochastically reproduce the actual generation per period. To evaluate the additive binary Markov chain method, we introduce a coarse model of the electric power system to derive backup and storage needs. We find that the temporal correlations of wind power generation, the backup need as a function of the storage capacity, and the resting time distribution of high and low wind events for different shares of wind generation can be reconstructed.

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.

A perturbative approach to the redshift space correlation function: beyond the Standard Model

NASA Astrophysics Data System (ADS)

Bose, Benjamin; Koyama, Kazuya

2017-08-01

We extend our previous redshift space power spectrum code to the redshift space correlation function. Here we focus on the Gaussian Streaming Model (GSM). Again, the code accommodates a wide range of modified gravity and dark energy models. For the non-linear real space correlation function used in the GSM we use the Fourier transform of the RegPT 1-loop matter power spectrum. We compare predictions of the GSM for a Vainshtein screened and Chameleon screened model as well as GR. These predictions are compared to the Fourier transform of the Taruya, Nishimichi and Saito (TNS) redshift space power spectrum model which is fit to N-body data. We find very good agreement between the Fourier transform of the TNS model and the GSM predictions, with <= 6% deviations in the first two correlation function multipoles for all models for redshift space separations in 50Mpch <= s <= 180Mpc/h. Excellent agreement is found in the differences between the modified gravity and GR multipole predictions for both approaches to the redshift space correlation function, highlighting their matched ability in picking up deviations from GR. We elucidate the timeliness of such non-standard templates at the dawn of stage-IV surveys and discuss necessary preparations and extensions needed for upcoming high quality data.

Cross-Layer Modeling Framework for Energy-Efficient Resilience

DTIC Science & Technology

2014-04-01

functional block diagram of the software architecture of PEARL, which stands for: Power Efficient and Resilient Embedded Processing with Real - Time ... DVFS ). The goal of the run- time manager is to minimize power consumption, while maintaining system resilience targets (on average) and meeting... real - time performance targets. The integrated performance, power and resilience models are nothing but the analytical modeling toolkit described in

Perspective Space as a Model for Distance and Size Perception.

PubMed

Erkelens, Casper J

2017-01-01

In the literature, perspective space has been introduced as a model of visual space. Perspective space is grounded on the perspective nature of visual space during both binocular and monocular vision. A single parameter, that is, the distance of the vanishing point, transforms the geometry of physical space into that of perspective space. The perspective-space model predicts perceived angles, distances, and sizes. The model is compared with other models for distance and size perception. Perspective space predicts that perceived distance and size as a function of physical distance are described by hyperbolic functions. Alternatively, power functions have been widely used to describe perceived distance and size. Comparison of power and hyperbolic functions shows that both functions are equivalent within the range of distances that have been judged in experiments. Two models describing perceived distance on the ground plane appear to be equivalent with the perspective-space model too. The conclusion is that perspective space unifies a number of models of distance and size perception.

Perspective Space as a Model for Distance and Size Perception

PubMed Central

2017-01-01

In the literature, perspective space has been introduced as a model of visual space. Perspective space is grounded on the perspective nature of visual space during both binocular and monocular vision. A single parameter, that is, the distance of the vanishing point, transforms the geometry of physical space into that of perspective space. The perspective-space model predicts perceived angles, distances, and sizes. The model is compared with other models for distance and size perception. Perspective space predicts that perceived distance and size as a function of physical distance are described by hyperbolic functions. Alternatively, power functions have been widely used to describe perceived distance and size. Comparison of power and hyperbolic functions shows that both functions are equivalent within the range of distances that have been judged in experiments. Two models describing perceived distance on the ground plane appear to be equivalent with the perspective-space model too. The conclusion is that perspective space unifies a number of models of distance and size perception. PMID:29225765

Computer-Aided Modeling and Analysis of Power Processing Systems (CAMAPPS). Phase 1: Users handbook

NASA Technical Reports Server (NTRS)

Kim, S.; Lee, J.; Cho, B. H.; Lee, F. C.

1986-01-01

The EASY5 macro component models developed for the spacecraft power system simulation are described. A brief explanation about how to use the macro components with the EASY5 Standard Components to build a specific system is given through an example. The macro components are ordered according to the following functional group: converter power stage models, compensator models, current-feedback models, constant frequency control models, load models, solar array models, and shunt regulator models. Major equations, a circuit model, and a program listing are provided for each macro component.

Primordial black holes and uncertainties in the choice of the window function

NASA Astrophysics Data System (ADS)

Ando, Kenta; Inomata, Keisuke; Kawasaki, Masahiro

2018-05-01

Primordial black holes (PBHs) can be produced by the perturbations that exit the horizon during the inflationary phase. While inflation models predict the power spectrum of the perturbations in Fourier space, the PBH abundance depends on the probability distribution function of density perturbations in real space. To estimate the PBH abundance in a given inflation model, we must relate the power spectrum in Fourier space to the probability density function in real space by coarse graining the perturbations with a window function. However, there are uncertainties on what window function should be used, which could change the relation between the PBH abundance and the power spectrum. This is particularly important in considering PBHs with mass 30 M⊙, which account for the LIGO events because the required power spectrum is severely constrained by the observations. In this paper, we investigate how large an influence the uncertainties on the choice of a window function has over the power spectrum required for LIGO PBHs. As a result, it is found that the uncertainties significantly affect the prediction for the stochastic gravitational waves induced by the second-order effect of the perturbations. In particular, the pulsar timing array constraints on the produced gravitational waves could disappear for the real-space top-hat window function.

Determination of Strength Exercise Intensities Based on the Load-Power-Velocity Relationship

PubMed Central

Jandačka, Daniel; Beremlijski, Petr

2011-01-01

The velocity of movement and applied load affect the production of mechanical power output and subsequently the extent of the adaptation stimulus in strength exercises. We do not know of any known function describing the relationship of power and velocity and load in the bench press exercise. The objective of the study is to find a function modeling of the relationship of relative velocity, relative load and mechanical power output for the bench press exercise and to determine the intensity zones of the exercise for specifically focused strength training of soccer players. Fifteen highly trained soccer players at the start of a competition period were studied. The subjects of study performed bench presses with the load of 0, 10, 30, 50, 70 and 90% of the predetermined one repetition maximum with maximum possible speed of movement. The mean measured power and velocity for each load (kg) were used to develop a multiple linear regression function which describes the quadratic relationship between the ratio of power (W) to maximum power (W) and the ratios of the load (kg) to one repetition maximum (kg) and the velocity (m•s−1) to maximal velocity (m•s−1). The quadratic function of two variables that modeled the searched relationship explained 74% of measured values in the acceleration phase and 75% of measured values from the entire extent of the positive power movement in the lift. The optimal load for reaching maximum power output suitable for the dynamics effort strength training was 40% of one repetition maximum, while the optimal mean velocity would be 75% of maximal velocity. Moreover, four zones: maximum power, maximum velocity, velocity-power and strength-power were determined on the basis of the regression function. PMID:23486484

Determination of strength exercise intensities based on the load-power-velocity relationship.

PubMed

Jandačka, Daniel; Beremlijski, Petr

2011-06-01

The velocity of movement and applied load affect the production of mechanical power output and subsequently the extent of the adaptation stimulus in strength exercises. We do not know of any known function describing the relationship of power and velocity and load in the bench press exercise. The objective of the study is to find a function modeling of the relationship of relative velocity, relative load and mechanical power output for the bench press exercise and to determine the intensity zones of the exercise for specifically focused strength training of soccer players. Fifteen highly trained soccer players at the start of a competition period were studied. The subjects of study performed bench presses with the load of 0, 10, 30, 50, 70 and 90% of the predetermined one repetition maximum with maximum possible speed of movement. The mean measured power and velocity for each load (kg) were used to develop a multiple linear regression function which describes the quadratic relationship between the ratio of power (W) to maximum power (W) and the ratios of the load (kg) to one repetition maximum (kg) and the velocity (m•s(-1)) to maximal velocity (m•s(-1)). The quadratic function of two variables that modeled the searched relationship explained 74% of measured values in the acceleration phase and 75% of measured values from the entire extent of the positive power movement in the lift. The optimal load for reaching maximum power output suitable for the dynamics effort strength training was 40% of one repetition maximum, while the optimal mean velocity would be 75% of maximal velocity. Moreover, four zones: maximum power, maximum velocity, velocity-power and strength-power were determined on the basis of the regression function.

The three-point function as a probe of models for large-scale structure

NASA Astrophysics Data System (ADS)

Frieman, Joshua A.; Gaztanaga, Enrique

1994-04-01

We analyze the consequences of models of structure formation for higher order (n-point) galaxy correlation functions in the mildly nonlinear regime. Several variations of the standard Omega = 1 cold dark matter model with scale-invariant primordial perturbations have recently been introduced to obtain more power on large scales, Rp is approximately 20/h Mpc, e.g., low matter-density (nonzero cosmological constant) models, 'tilted' primordial spectra, and scenarios with a mixture of cold and hot dark matter. They also include models with an effective scale-dependent bias, such as the cooperative galaxy formation scenario of Bower et al. We show that higher-order (n-point) galaxy correlation functions can provide a useful test of such models and can discriminate between models with true large-scale power in the density field and those where the galaxy power arises from scale-dependent bias: a bias with rapid scale dependence leads to a dramatic decrease of the the hierarchical amplitudes QJ at large scales, r is greater than or approximately Rp. Current observational constraints on the three-point amplitudes Q3 and S3 can place limits on the bias parameter(s) and appear to disfavor, but not yet rule out, the hypothesis that scale-dependent bias is responsible for the extra power observed on large scales.

Probability density function characterization for aggregated large-scale wind power based on Weibull mixtures

DOE PAGES

Gomez-Lazaro, Emilio; Bueso, Maria C.; Kessler, Mathieu; ...

2016-02-02

Here, the Weibull probability distribution has been widely applied to characterize wind speeds for wind energy resources. Wind power generation modeling is different, however, due in particular to power curve limitations, wind turbine control methods, and transmission system operation requirements. These differences are even greater for aggregated wind power generation in power systems with high wind penetration. Consequently, models based on one-Weibull component can provide poor characterizations for aggregated wind power generation. With this aim, the present paper focuses on discussing Weibull mixtures to characterize the probability density function (PDF) for aggregated wind power generation. PDFs of wind power datamore » are firstly classified attending to hourly and seasonal patterns. The selection of the number of components in the mixture is analyzed through two well-known different criteria: the Akaike information criterion (AIC) and the Bayesian information criterion (BIC). Finally, the optimal number of Weibull components for maximum likelihood is explored for the defined patterns, including the estimated weight, scale, and shape parameters. Results show that multi-Weibull models are more suitable to characterize aggregated wind power data due to the impact of distributed generation, variety of wind speed values and wind power curtailment.« less

On the Power of Multivariate Latent Growth Curve Models to Detect Correlated Change

ERIC Educational Resources Information Center

Hertzog, Christopher; Lindenberger, Ulman; Ghisletta, Paolo; Oertzen, Timo von

2006-01-01

We evaluated the statistical power of single-indicator latent growth curve models (LGCMs) to detect correlated change between two variables (covariance of slopes) as a function of sample size, number of longitudinal measurement occasions, and reliability (measurement error variance). Power approximations following the method of Satorra and Saris…

Optimal cycling time trial position models: aerodynamics versus power output and metabolic energy.

PubMed

Fintelman, D M; Sterling, M; Hemida, H; Li, F-X

2014-06-03

The aerodynamic drag of a cyclist in time trial (TT) position is strongly influenced by the torso angle. While decreasing the torso angle reduces the drag, it limits the physiological functioning of the cyclist. Therefore the aims of this study were to predict the optimal TT cycling position as function of the cycling speed and to determine at which speed the aerodynamic power losses start to dominate. Two models were developed to determine the optimal torso angle: a 'Metabolic Energy Model' and a 'Power Output Model'. The Metabolic Energy Model minimised the required cycling energy expenditure, while the Power Output Model maximised the cyclists׳ power output. The input parameters were experimentally collected from 19 TT cyclists at different torso angle positions (0-24°). The results showed that for both models, the optimal torso angle depends strongly on the cycling speed, with decreasing torso angles at increasing speeds. The aerodynamic losses outweigh the power losses at cycling speeds above 46km/h. However, a fully horizontal torso is not optimal. For speeds below 30km/h, it is beneficial to ride in a more upright TT position. The two model outputs were not completely similar, due to the different model approaches. The Metabolic Energy Model could be applied for endurance events, while the Power Output Model is more suitable in sprinting or in variable conditions (wind, undulating course, etc.). It is suggested that despite some limitations, the models give valuable information about improving the cycling performance by optimising the TT cycling position. Copyright © 2014 Elsevier Ltd. All rights reserved.

An optimal strategy for functional mapping of dynamic trait loci.

PubMed

Jin, Tianbo; Li, Jiahan; Guo, Ying; Zhou, Xiaojing; Yang, Runqing; Wu, Rongling

2010-02-01

As an emerging powerful approach for mapping quantitative trait loci (QTLs) responsible for dynamic traits, functional mapping models the time-dependent mean vector with biologically meaningful equations and are likely to generate biologically relevant and interpretable results. Given the autocorrelation nature of a dynamic trait, functional mapping needs the implementation of the models for the structure of the covariance matrix. In this article, we have provided a comprehensive set of approaches for modelling the covariance structure and incorporated each of these approaches into the framework of functional mapping. The Bayesian information criterion (BIC) values are used as a model selection criterion to choose the optimal combination of the submodels for the mean vector and covariance structure. In an example for leaf age growth from a rice molecular genetic project, the best submodel combination was found between the Gaussian model for the correlation structure, power equation of order 1 for the variance and the power curve for the mean vector. Under this combination, several significant QTLs for leaf age growth trajectories were detected on different chromosomes. Our model can be well used to study the genetic architecture of dynamic traits of agricultural values.

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

Modeling of Autovariator Operation as Power Components Adjuster in Adaptive Machine Drives

NASA Astrophysics Data System (ADS)

Balakin, P. D.; Belkov, V. N.; Shtripling, L. O.

2018-01-01

Full application of the available power and stationary mode preservation for the power station (engine) operation of the transport machine under the conditions of variable external loading, are topical issues. The issues solution is possible by means of mechanical drives with the autovaried rate transfer function and nonholonomic constraint of the main driving mediums. Additional to the main motion, controlled motion of the driving mediums is formed by a variable part of the transformed power flow and is implemented by the integrated control loop, functioning only on the basis of the laws of motion. The mathematical model of the mechanical autovariator operation is developed using Gibbs function, acceleration energy; the study results are presented; on their basis, the design calculations of the autovariator driving mediums and constraints, including its automatic control loop, are possible.

Computer-Aided Modeling and Analysis of Power Processing Systems (CAMAPPS), phase 1

NASA Technical Reports Server (NTRS)

Kim, S.; Lee, J.; Cho, B. H.; Lee, F. C.

1986-01-01

The large-signal behaviors of a regulator depend largely on the type of power circuit topology and control. Thus, for maximum flexibility, it is best to develop models for each functional block a independent modules. A regulator can then be configured by collecting appropriate pre-defined modules for each functional block. In order to complete the component model generation for a comprehensive spacecraft power system, the following modules were developed: solar array switching unit and control; shunt regulators; and battery discharger. The capability of each module is demonstrated using a simplified Direct Energy Transfer (DET) system. Large-signal behaviors of solar array power systems were analyzed. Stability of the solar array system operating points with a nonlinear load is analyzed. The state-plane analysis illustrates trajectories of the system operating point under various conditions. Stability and transient responses of the system operating near the solar array's maximum power point are also analyzed. The solar array system mode of operation is described using the DET spacecraft power system. The DET system is simulated for various operating conditions. Transfer of the software program CAMAPPS (Computer Aided Modeling and Analysis of Power Processing Systems) to NASA/GSFC (Goddard Space Flight Center) was accomplished.

Time-domain comparisons of power law attenuation in causal and noncausal time-fractional wave equations

PubMed Central

Zhao, Xiaofeng; McGough, Robert J.

2016-01-01

The attenuation of ultrasound propagating in human tissue follows a power law with respect to frequency that is modeled by several different causal and noncausal fractional partial differential equations. To demonstrate some of the similarities and differences that are observed in three related time-fractional partial differential equations, time-domain Green's functions are calculated numerically for the power law wave equation, the Szabo wave equation, and for the Caputo wave equation. These Green's functions are evaluated for water with a power law exponent of y = 2, breast with a power law exponent of y = 1.5, and liver with a power law exponent of y = 1.139. Simulation results show that the noncausal features of the numerically calculated time-domain response are only evident very close to the source and that these causal and noncausal time-domain Green's functions converge to the same result away from the source. When noncausal time-domain Green's functions are convolved with a short pulse, no evidence of noncausal behavior remains in the time-domain, which suggests that these causal and noncausal time-fractional models are equally effective for these numerical calculations. PMID:27250193

A perturbative approach to the redshift space correlation function: beyond the Standard Model

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

Bose, Benjamin; Koyama, Kazuya, E-mail: benjamin.bose@port.ac.uk, E-mail: kazuya.koyama@port.ac.uk

We extend our previous redshift space power spectrum code to the redshift space correlation function. Here we focus on the Gaussian Streaming Model (GSM). Again, the code accommodates a wide range of modified gravity and dark energy models. For the non-linear real space correlation function used in the GSM we use the Fourier transform of the RegPT 1-loop matter power spectrum. We compare predictions of the GSM for a Vainshtein screened and Chameleon screened model as well as GR. These predictions are compared to the Fourier transform of the Taruya, Nishimichi and Saito (TNS) redshift space power spectrum model whichmore » is fit to N-body data. We find very good agreement between the Fourier transform of the TNS model and the GSM predictions, with ≤ 6% deviations in the first two correlation function multipoles for all models for redshift space separations in 50Mpc h ≤ s ≤ 180Mpc/ h . Excellent agreement is found in the differences between the modified gravity and GR multipole predictions for both approaches to the redshift space correlation function, highlighting their matched ability in picking up deviations from GR. We elucidate the timeliness of such non-standard templates at the dawn of stage-IV surveys and discuss necessary preparations and extensions needed for upcoming high quality data.« less

Optimization Scheduling Model for Wind-thermal Power System Considering the Dynamic penalty factor

NASA Astrophysics Data System (ADS)

PENG, Siyu; LUO, Jianchun; WANG, Yunyu; YANG, Jun; RAN, Hong; PENG, Xiaodong; HUANG, Ming; LIU, Wanyu

2018-03-01

In this paper, a new dynamic economic dispatch model for power system is presented.Objective function of the proposed model presents a major novelty in the dynamic economic dispatch including wind farm: introduced the “Dynamic penalty factor”, This factor could be computed by using fuzzy logic considering both the variable nature of active wind power and power demand, and it could change the wind curtailment cost according to the different state of the power system. Case studies were carried out on the IEEE30 system. Results show that the proposed optimization model could mitigate the wind curtailment and the total cost effectively, demonstrate the validity and effectiveness of the proposed model.

A fully implantable pacemaker for the mouse: from battery to wireless power.

PubMed

Laughner, Jacob I; Marrus, Scott B; Zellmer, Erik R; Weinheimer, Carla J; MacEwan, Matthew R; Cui, Sophia X; Nerbonne, Jeanne M; Efimov, Igor R

2013-01-01

Animal models have become a popular platform for the investigation of the molecular and systemic mechanisms of pathological cardiovascular physiology. Chronic pacing studies with implantable pacemakers in large animals have led to useful models of heart failure and atrial fibrillation. Unfortunately, molecular and genetic studies in these large animal models are often prohibitively expensive or not available. Conversely, the mouse is an excellent species for studying molecular mechanisms of cardiovascular disease through genetic engineering. However, the large size of available pacemakers does not lend itself to chronic pacing in mice. Here, we present the design for a novel, fully implantable wireless-powered pacemaker for mice capable of long-term (>30 days) pacing. This design is compared to a traditional battery-powered pacemaker to demonstrate critical advantages achieved through wireless inductive power transfer and control. Battery-powered and wireless-powered pacemakers were fabricated from standard electronic components in our laboratory. Mice (n = 24) were implanted with endocardial, battery-powered devices (n = 14) and epicardial, wireless-powered devices (n = 10). Wireless-powered devices were associated with reduced implant mortality and more reliable device function compared to battery-powered devices. Eight of 14 (57.1%) mice implanted with battery-powered pacemakers died following device implantation compared to 1 of 10 (10%) mice implanted with wireless-powered pacemakers. Moreover, device function was achieved for 30 days with the wireless-powered device compared to 6 days with the battery-powered device. The wireless-powered pacemaker system presented herein will allow electrophysiology studies in numerous genetically engineered mouse models as well as rapid pacing-induced heart failure and atrial arrhythmia in mice.

The invariant of the stiffness filter function with the weight filter function of the power function form

NASA Astrophysics Data System (ADS)

Shang, Zhen; Sui, Yun-Kang

2012-12-01

Based on the independent, continuous and mapping (ICM) method and homogenization method, a research model is constructed to propose and deduce a theorem and corollary from the invariant between the weight filter function and the corresponding stiffness filter function of the form of power function. The efficiency in searching for optimum solution will be raised via the choice of rational filter functions, so the above mentioned results are very important to the further study of structural topology optimization.

Research on Operation Strategy for Bundled Wind-thermal Generation Power Systems Based on Two-Stage Optimization Model

NASA Astrophysics Data System (ADS)

Sun, Congcong; Wang, Zhijie; Liu, Sanming; Jiang, Xiuchen; Sheng, Gehao; Liu, Tianyu

2017-05-01

Wind power has the advantages of being clean and non-polluting and the development of bundled wind-thermal generation power systems (BWTGSs) is one of the important means to improve wind power accommodation rate and implement “clean alternative” on generation side. A two-stage optimization strategy for BWTGSs considering wind speed forecasting results and load characteristics is proposed. By taking short-term wind speed forecasting results of generation side and load characteristics of demand side into account, a two-stage optimization model for BWTGSs is formulated. By using the environmental benefit index of BWTGSs as the objective function, supply-demand balance and generator operation as the constraints, the first-stage optimization model is developed with the chance-constrained programming theory. By using the operation cost for BWTGSs as the objective function, the second-stage optimization model is developed with the greedy algorithm. The improved PSO algorithm is employed to solve the model and numerical test verifies the effectiveness of the proposed strategy.

Cost and performance model for redox flow batteries

NASA Astrophysics Data System (ADS)

Viswanathan, Vilayanur; Crawford, Alasdair; Stephenson, David; Kim, Soowhan; Wang, Wei; Li, Bin; Coffey, Greg; Thomsen, Ed; Graff, Gordon; Balducci, Patrick; Kintner-Meyer, Michael; Sprenkle, Vincent

2014-02-01

A cost model is developed for all vanadium and iron-vanadium redox flow batteries. Electrochemical performance modeling is done to estimate stack performance at various power densities as a function of state of charge and operating conditions. This is supplemented with a shunt current model and a pumping loss model to estimate actual system efficiency. The operating parameters such as power density, flow rates and design parameters such as electrode aspect ratio and flow frame channel dimensions are adjusted to maximize efficiency and minimize capital costs. Detailed cost estimates are obtained from various vendors to calculate cost estimates for present, near-term and optimistic scenarios. The most cost-effective chemistries with optimum operating conditions for power or energy intensive applications are determined, providing a roadmap for battery management systems development for redox flow batteries. The main drivers for cost reduction for various chemistries are identified as a function of the energy to power ratio of the storage system. Levelized cost analysis further guide suitability of various chemistries for different applications.

Nonlinear GARCH model and 1 / f noise

NASA Astrophysics Data System (ADS)

Kononovicius, A.; Ruseckas, J.

2015-06-01

Auto-regressive conditionally heteroskedastic (ARCH) family models are still used, by practitioners in business and economic policy making, as a conditional volatility forecasting models. Furthermore ARCH models still are attracting an interest of the researchers. In this contribution we consider the well known GARCH(1,1) process and its nonlinear modifications, reminiscent of NGARCH model. We investigate the possibility to reproduce power law statistics, probability density function and power spectral density, using ARCH family models. For this purpose we derive stochastic differential equations from the GARCH processes in consideration. We find the obtained equations to be similar to a general class of stochastic differential equations known to reproduce power law statistics. We show that linear GARCH(1,1) process has power law distribution, but its power spectral density is Brownian noise-like. However, the nonlinear modifications exhibit both power law distribution and power spectral density of the 1 /fβ form, including 1 / f noise.

Note: The full function test explosive generator.

PubMed

Reisman, D B; Javedani, J B; Griffith, L V; Ellsworth, G F; Kuklo, R M; Goerz, D A; White, A D; Tallerico, L J; Gidding, D A; Murphy, M J; Chase, J B

2010-03-01

We have conducted three tests of a new pulsed power device called the full function test. These tests represented the culmination of an effort to establish a high energy pulsed power capability based on high explosive pulsed power (HEPP) technology. This involved an extensive computational modeling, engineering, fabrication, and fielding effort. The experiments were highly successful and a new U.S. record for magnetic energy was obtained.

A new parameterization of an empirical model for wind/ocean scatterometry

NASA Technical Reports Server (NTRS)

Woiceshyn, P. M.; Wurtele, M. G.; Boggs, D. H.; Mcgoldrick, L. F.; Peteherych, S.

1984-01-01

The power law form of the SEASAT A Scatterometer System (SASS) empirical backscatter-to-wind model function does not uniformly meet the instrument performance over the range 4 to 24 /ms. Analysis indicates that the horizontal polarization (H-Pol) and vertical polarization (V-Pol) components of the benchmark SASS1 model function yield self-consistent results only for a small mid-range of speeds at larger incidence angles, and for a somewhat larger range of speeds at smaller incidence angles. Comparison of SASS1 to in situ data over the Gulf of Alaska region further underscores the shortcomings of the power law form. Finally, a physically based empirical SASS model is proposed which corrects some of the deficiencies of power law models like SASS1. The new model allows the mutual determination of sea surface wind stress and wind speed in a consistent manner from SASS backscatter measurements.

Radiation Losses Due to Tapering of a Double-Core Optical Waveguide

NASA Technical Reports Server (NTRS)

Lyons, Donald R.; Khet, Myat; Pencil, Eric (Technical Monitor)

2001-01-01

The theoretical model we designed parameterizes the power losses as a function of .the profile shape for a tapered, single mode, optical dielectric coupler. The focus of this project is to produce a working model that determines the power losses experienced by the fibers when light crosses a taper region. This phenomenon can be examined using coupled mode theory. The optical directional coupler consists of a parallel, dual-channel, waveguide with minimal spacing between the channels to permit energy exchange. Thus, power transfer is essentially a function of the taper profile. To find the fields in the fibers, the approach used was that of solving the Helmholtz equation in cylindrical coordinates involving Bessel and modified Bessel functions depending on the location.

Wind Tunnel Database Development using Modern Experiment Design and Multivariate Orthogonal Functions

NASA Technical Reports Server (NTRS)

Morelli, Eugene A.; DeLoach, Richard

2003-01-01

A wind tunnel experiment for characterizing the aerodynamic and propulsion forces and moments acting on a research model airplane is described. The model airplane called the Free-flying Airplane for Sub-scale Experimental Research (FASER), is a modified off-the-shelf radio-controlled model airplane, with 7 ft wingspan, a tractor propeller driven by an electric motor, and aerobatic capability. FASER was tested in the NASA Langley 12-foot Low-Speed Wind Tunnel, using a combination of traditional sweeps and modern experiment design. Power level was included as an independent variable in the wind tunnel test, to allow characterization of power effects on aerodynamic forces and moments. A modeling technique that employs multivariate orthogonal functions was used to develop accurate analytic models for the aerodynamic and propulsion force and moment coefficient dependencies from the wind tunnel data. Efficient methods for generating orthogonal modeling functions, expanding the orthogonal modeling functions in terms of ordinary polynomial functions, and analytical orthogonal blocking were developed and discussed. The resulting models comprise a set of smooth, differentiable functions for the non-dimensional aerodynamic force and moment coefficients in terms of ordinary polynomials in the independent variables, suitable for nonlinear aircraft simulation.

Non-parametric model selection for subject-specific topological organization of resting-state functional connectivity.

PubMed

Ferrarini, Luca; Veer, Ilya M; van Lew, Baldur; Oei, Nicole Y L; van Buchem, Mark A; Reiber, Johan H C; Rombouts, Serge A R B; Milles, J

2011-06-01

In recent years, graph theory has been successfully applied to study functional and anatomical connectivity networks in the human brain. Most of these networks have shown small-world topological characteristics: high efficiency in long distance communication between nodes, combined with highly interconnected local clusters of nodes. Moreover, functional studies performed at high resolutions have presented convincing evidence that resting-state functional connectivity networks exhibits (exponentially truncated) scale-free behavior. Such evidence, however, was mostly presented qualitatively, in terms of linear regressions of the degree distributions on log-log plots. Even when quantitative measures were given, these were usually limited to the r(2) correlation coefficient. However, the r(2) statistic is not an optimal estimator of explained variance, when dealing with (truncated) power-law models. Recent developments in statistics have introduced new non-parametric approaches, based on the Kolmogorov-Smirnov test, for the problem of model selection. In this work, we have built on this idea to statistically tackle the issue of model selection for the degree distribution of functional connectivity at rest. The analysis, performed at voxel level and in a subject-specific fashion, confirmed the superiority of a truncated power-law model, showing high consistency across subjects. Moreover, the most highly connected voxels were found to be consistently part of the default mode network. Our results provide statistically sound support to the evidence previously presented in literature for a truncated power-law model of resting-state functional connectivity. Copyright © 2010 Elsevier Inc. All rights reserved.

The three-point function as a probe of models for large-scale structure

NASA Technical Reports Server (NTRS)

Frieman, Joshua A.; Gaztanaga, Enrique

1993-01-01

The consequences of models of structure formation for higher-order (n-point) galaxy correlation functions in the mildly non-linear regime are analyzed. Several variations of the standard Omega = 1 cold dark matter model with scale-invariant primordial perturbations were recently introduced to obtain more power on large scales, R(sub p) is approximately 20 h(sup -1) Mpc, e.g., low-matter-density (non-zero cosmological constant) models, 'tilted' primordial spectra, and scenarios with a mixture of cold and hot dark matter. They also include models with an effective scale-dependent bias, such as the cooperative galaxy formation scenario of Bower, etal. It is shown that higher-order (n-point) galaxy correlation functions can provide a useful test of such models and can discriminate between models with true large-scale power in the density field and those where the galaxy power arises from scale-dependent bias: a bias with rapid scale-dependence leads to a dramatic decrease of the hierarchical amplitudes Q(sub J) at large scales, r is approximately greater than R(sub p). Current observational constraints on the three-point amplitudes Q(sub 3) and S(sub 3) can place limits on the bias parameter(s) and appear to disfavor, but not yet rule out, the hypothesis that scale-dependent bias is responsible for the extra power observed on large scales.

Power-Law Dynamics of Membrane Conductances Increase Spiking Diversity in a Hodgkin-Huxley Model.

PubMed

Teka, Wondimu; Stockton, David; Santamaria, Fidel

2016-03-01

We studied the effects of non-Markovian power-law voltage dependent conductances on the generation of action potentials and spiking patterns in a Hodgkin-Huxley model. To implement slow-adapting power-law dynamics of the gating variables of the potassium, n, and sodium, m and h, conductances we used fractional derivatives of order η≤1. The fractional derivatives were used to solve the kinetic equations of each gate. We systematically classified the properties of each gate as a function of η. We then tested if the full model could generate action potentials with the different power-law behaving gates. Finally, we studied the patterns of action potential that emerged in each case. Our results show the model produces a wide range of action potential shapes and spiking patterns in response to constant current stimulation as a function of η. In comparison with the classical model, the action potential shapes for power-law behaving potassium conductance (n gate) showed a longer peak and shallow hyperpolarization; for power-law activation of the sodium conductance (m gate), the action potentials had a sharp rise time; and for power-law inactivation of the sodium conductance (h gate) the spikes had wider peak that for low values of η replicated pituitary- and cardiac-type action potentials. With all physiological parameters fixed a wide range of spiking patterns emerged as a function of the value of the constant input current and η, such as square wave bursting, mixed mode oscillations, and pseudo-plateau potentials. Our analyses show that the intrinsic memory trace of the fractional derivative provides a negative feedback mechanism between the voltage trace and the activity of the power-law behaving gate variable. As a consequence, power-law behaving conductances result in an increase in the number of spiking patterns a neuron can generate and, we propose, expand the computational capacity of the neuron.

From non-trivial geometries to power spectra and vice versa

NASA Astrophysics Data System (ADS)

Brooker, D. J.; Tsamis, N. C.; Woodard, R. P.

2018-04-01

We review a recent formalism which derives the functional forms of the primordial—tensor and scalar—power spectra of scalar potential inflationary models. The formalism incorporates the case of geometries with non-constant first slow-roll parameter. Analytic expressions for the power spectra are given that explicitly display the dependence on the geometric properties of the background. Moreover, we present the full algorithm for using our formalism, to reconstruct the model from the observed power spectra. Our techniques are applied to models possessing "features" in their potential with excellent agreement.

A Smoothed Eclipse Model for Solar Electric Propulsion Trajectory Optimization

NASA Technical Reports Server (NTRS)

Aziz, Jonathan D.; Scheeres, Daniel J.; Parker, Jeffrey S.; Englander, Jacob A.

2017-01-01

Solar electric propulsion (SEP) is the dominant design option for employing low-thrust propulsion on a space mission. Spacecraft solar arrays power the SEP system but are subject to blackout periods during solar eclipse conditions. Discontinuity in power available to the spacecraft must be accounted for in trajectory optimization, but gradient-based methods require a differentiable power model. This work presents a power model that smooths the eclipse transition from total eclipse to total sunlight with a logistic function. Example trajectories are computed with differential dynamic programming, a second-order gradient-based method.

Knowledge-based and integrated monitoring and diagnosis in autonomous power systems

NASA Technical Reports Server (NTRS)

Momoh, J. A.; Zhang, Z. Z.

1990-01-01

A new technique of knowledge-based and integrated monitoring and diagnosis (KBIMD) to deal with abnormalities and incipient or potential failures in autonomous power systems is presented. The KBIMD conception is discussed as a new function of autonomous power system automation. Available diagnostic modelling, system structure, principles and strategies are suggested. In order to verify the feasibility of the KBIMD, a preliminary prototype expert system is designed to simulate the KBIMD function in a main electric network of the autonomous power system.

Maximizing photovoltaic power generation of a space-dart configured satellite

NASA Astrophysics Data System (ADS)

Lee, Dae Young; Cutler, James W.; Mancewicz, Joe; Ridley, Aaron J.

2015-06-01

Many small satellites are power constrained due to their minimal solar panel area and the eclipse environment of low-Earth orbit. As with larger satellites, these small satellites, including CubeSats, use deployable power arrays to increase power production. This presents a design opportunity to develop various objective functions related to energy management and methods for optimizing these functions over a satellite design. A novel power generation model was created, and a simulation system was developed to evaluate various objective functions describing energy management for complex satellite designs. The model uses a spacecraft-body-fixed spherical coordinate system to analyze the complex geometry of a satellite's self-induced shadowing with computation provided by the Open Graphics Library. As an example design problem, a CubeSat configured as a space-dart with four deployable panels is optimized. Due to the fast computation speed of the solution, an exhaustive search over the design space is used to find the solar panel deployment angles which maximize total power generation. Simulation results are presented for a variety of orbit scenarios. The method is extendable to a variety of complex satellite geometries and power generation systems.

Analytical time-domain Green’s functions for power-law media

PubMed Central

Kelly, James F.; McGough, Robert J.; Meerschaert, Mark M.

2008-01-01

Frequency-dependent loss and dispersion are typically modeled with a power-law attenuation coefficient, where the power-law exponent ranges from 0 to 2. To facilitate analytical solution, a fractional partial differential equation is derived that exactly describes power-law attenuation and the Szabo wave equation [“Time domain wave-equations for lossy media obeying a frequency power-law,” J. Acoust. Soc. Am. 96, 491–500 (1994)] is an approximation to this equation. This paper derives analytical time-domain Green’s functions in power-law media for exponents in this range. To construct solutions, stable law probability distributions are utilized. For exponents equal to 0, 1∕3, 1∕2, 2∕3, 3∕2, and 2, the Green’s function is expressed in terms of Dirac delta, exponential, Airy, hypergeometric, and Gaussian functions. For exponents strictly less than 1, the Green’s functions are expressed as Fox functions and are causal. For exponents greater than or equal than 1, the Green’s functions are expressed as Fox and Wright functions and are noncausal. However, numerical computations demonstrate that for observation points only one wavelength from the radiating source, the Green’s function is effectively causal for power-law exponents greater than or equal to 1. The analytical time-domain Green’s function is numerically verified against the material impulse response function, and the results demonstrate excellent agreement. PMID:19045774

A Fully Implantable Pacemaker for the Mouse: From Battery to Wireless Power

PubMed Central

Zellmer, Erik R.; Weinheimer, Carla J.; MacEwan, Matthew R.; Cui, Sophia X.; Nerbonne, Jeanne M.; Efimov, Igor R.

2013-01-01

Animal models have become a popular platform for the investigation of the molecular and systemic mechanisms of pathological cardiovascular physiology. Chronic pacing studies with implantable pacemakers in large animals have led to useful models of heart failure and atrial fibrillation. Unfortunately, molecular and genetic studies in these large animal models are often prohibitively expensive or not available. Conversely, the mouse is an excellent species for studying molecular mechanisms of cardiovascular disease through genetic engineering. However, the large size of available pacemakers does not lend itself to chronic pacing in mice. Here, we present the design for a novel, fully implantable wireless-powered pacemaker for mice capable of long-term (>30 days) pacing. This design is compared to a traditional battery-powered pacemaker to demonstrate critical advantages achieved through wireless inductive power transfer and control. Battery-powered and wireless-powered pacemakers were fabricated from standard electronic components in our laboratory. Mice (n = 24) were implanted with endocardial, battery-powered devices (n = 14) and epicardial, wireless-powered devices (n = 10). Wireless-powered devices were associated with reduced implant mortality and more reliable device function compared to battery-powered devices. Eight of 14 (57.1%) mice implanted with battery-powered pacemakers died following device implantation compared to 1 of 10 (10%) mice implanted with wireless-powered pacemakers. Moreover, device function was achieved for 30 days with the wireless-powered device compared to 6 days with the battery-powered device. The wireless-powered pacemaker system presented herein will allow electrophysiology studies in numerous genetically engineered mouse models as well as rapid pacing-induced heart failure and atrial arrhythmia in mice. PMID:24194832

Control aspects of the Schuchuli Village stand-alone photovoltaic power system

NASA Astrophysics Data System (ADS)

Groumpos, P. P.; Culler, J. E.; Delombard, R.

1984-11-01

A photovoltaic power system in an Arizona Indian village was installed. The control subsystem of this photovoltaic power system was analyzed. The four major functions of the control subsystem are: (1) voltage regulation; (2) load management; (3) water pump control; and (4) system protection. The control subsystem functions flowcharts for the control subsystem operation, and a computer program that models the control subsystem are presented.

Control aspects of the Schuchuli Village stand-alone photovoltaic power system

NASA Technical Reports Server (NTRS)

Groumpos, P. P.; Culler, J. E.; Delombard, R.

1984-01-01

A photovoltaic power system in an Arizona Indian village was installed. The control subsystem of this photovoltaic power system was analyzed. The four major functions of the control subsystem are: (1) voltage regulation; (2) load management; (3) water pump control; and (4) system protection. The control subsystem functions flowcharts for the control subsystem operation, and a computer program that models the control subsystem are presented.

Improved GART neural network model for pattern classification and rule extraction with application to power systems.

PubMed

Yap, Keem Siah; Lim, Chee Peng; Au, Mau Teng

2011-12-01

Generalized adaptive resonance theory (GART) is a neural network model that is capable of online learning and is effective in tackling pattern classification tasks. In this paper, we propose an improved GART model (IGART), and demonstrate its applicability to power systems. IGART enhances the dynamics of GART in several aspects, which include the use of the Laplacian likelihood function, a new vigilance function, a new match-tracking mechanism, an ordering algorithm for determining the sequence of training data, and a rule extraction capability to elicit if-then rules from the network. To assess the effectiveness of IGART and to compare its performances with those from other methods, three datasets that are related to power systems are employed. The experimental results demonstrate the usefulness of IGART with the rule extraction capability in undertaking classification problems in power systems engineering.

Market Mechanism Design for Renewable Energy based on Risk Theory

NASA Astrophysics Data System (ADS)

Yang, Wu; Bo, Wang; Jichun, Liu; Wenjiao, Zai; Pingliang, Zeng; Haobo, Shi

2018-02-01

Generation trading between renewable energy and thermal power is an efficient market means for transforming supply structure of electric power into sustainable development pattern. But the trading is hampered by the output fluctuations of renewable energy and the cost differences between renewable energy and thermal power at present. In this paper, the external environmental cost (EEC) is defined and the EEC is introduced into the generation cost. At same time, the incentive functions of renewable energy and low-emission thermal power are designed, which are decreasing functions of EEC. On these bases, for the market risks caused by the random variability of EEC, the decision-making model of generation trading between renewable energy and thermal power is constructed according to the risk theory. The feasibility and effectiveness of the proposed model are verified by simulation results.

Modelling altered revenue function based on varying power consumption distribution and electricity tariff charge using data analytics framework

NASA Astrophysics Data System (ADS)

Zainudin, W. N. R. A.; Ramli, N. A.

2017-09-01

In 2010, Energy Commission (EC) had introduced Incentive Based Regulation (IBR) to ensure sustainable Malaysian Electricity Supply Industry (MESI), promotes transparent and fair returns, encourage maximum efficiency and maintains policy driven end user tariff. To cater such revolutionary transformation, a sophisticated system to generate policy driven electricity tariff structure is in great need. Hence, this study presents a data analytics framework that generates altered revenue function based on varying power consumption distribution and tariff charge function. For the purpose of this study, the power consumption distribution is being proxy using proportion of household consumption and electricity consumed in KwH and the tariff charge function is being proxy using three-tiered increasing block tariff (IBT). The altered revenue function is useful to give an indication on whether any changes in the power consumption distribution and tariff charges will give positive or negative impact to the economy. The methodology used for this framework begins by defining the revenue to be a function of power consumption distribution and tariff charge function. Then, the proportion of household consumption and tariff charge function is derived within certain interval of electricity power. Any changes in those proportion are conjectured to contribute towards changes in revenue function. Thus, these changes can potentially give an indication on whether the changes in power consumption distribution and tariff charge function are giving positive or negative impact on TNB revenue. Based on the finding of this study, major changes on tariff charge function seems to affect altered revenue function more than power consumption distribution. However, the paper concludes that power consumption distribution and tariff charge function can influence TNB revenue to some great extent.

Modeling and Analysis of Power Processing Systems (MAPPS). Volume 1: Technical report

NASA Technical Reports Server (NTRS)

Lee, F. C.; Rahman, S.; Carter, R. A.; Wu, C. H.; Yu, Y.; Chang, R.

1980-01-01

Computer aided design and analysis techniques were applied to power processing equipment. Topics covered include: (1) discrete time domain analysis of switching regulators for performance analysis; (2) design optimization of power converters using augmented Lagrangian penalty function technique; (3) investigation of current-injected multiloop controlled switching regulators; and (4) application of optimization for Navy VSTOL energy power system. The generation of the mathematical models and the development and application of computer aided design techniques to solve the different mathematical models are discussed. Recommendations are made for future work that would enhance the application of the computer aided design techniques for power processing systems.

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

System-wide emissions implications of increased wind power penetration.

PubMed

Valentino, Lauren; Valenzuela, Viviana; Botterud, Audun; Zhou, Zhi; Conzelmann, Guenter

2012-04-03

This paper discusses the environmental effects of incorporating wind energy into the electric power system. We present a detailed emissions analysis based on comprehensive modeling of power system operations with unit commitment and economic dispatch for different wind penetration levels. First, by minimizing cost, the unit commitment model decides which thermal power plants will be utilized based on a wind power forecast, and then, the economic dispatch model dictates the level of production for each unit as a function of the realized wind power generation. Finally, knowing the power production from each power plant, the emissions are calculated. The emissions model incorporates the effects of both cycling and start-ups of thermal power plants in analyzing emissions from an electric power system with increasing levels of wind power. Our results for the power system in the state of Illinois show significant emissions effects from increased cycling and particularly start-ups of thermal power plants. However, we conclude that as the wind power penetration increases, pollutant emissions decrease overall due to the replacement of fossil fuels.

Modeling Geomagnetically Induced Currents From Magnetometer Measurements: Spatial Scale Assessed With Reference Measurements

NASA Astrophysics Data System (ADS)

Butala, Mark D.; Kazerooni, Maryam; Makela, Jonathan J.; Kamalabadi, Farzad; Gannon, Jennifer L.; Zhu, Hao; Overbye, Thomas J.

2017-10-01

Solar-driven disturbances generate geomagnetically induced currents (GICs) that can result in power grid instability and, in the most extreme cases, even failure. Magnetometers provide direct measurements of the geomagnetic disturbance (GMD) effect on the surface magnetic field and GIC response can be determined from the power grid topology and engineering parameters. This paper considers this chain of models: transforming surface magnetic field disturbance to induced surface electric field through an electromagnetic transfer function and, then, induced surface electric field to GIC using the PowerWorld simulator to model a realistic power grid topology. Comparisons are made to transformer neutral current reference measurements provided by the American Transmission Company. Three GMD intervals are studied, with the Kp index reaching 8- on 2 October 2013, 7 on 1 June 2013, and 6- on 9 October 2013. Ultimately, modeled to measured GIC correlations are analyzed as a function of magnetometer to GIC sensor distance. Results indicate that modeling fidelity during the three studied GMD intervals is strongly dependent on both magnetometer to substation transformer baseline distance and GMD intensity.

Individual differences in long-range time representation.

PubMed

Agostino, Camila S; Caetano, Marcelo S; Balci, Fuat; Claessens, Peter M E; Zana, Yossi

2017-04-01

On the basis of experimental data, long-range time representation has been proposed to follow a highly compressed power function, which has been hypothesized to explain the time inconsistency found in financial discount rate preferences. The aim of this study was to evaluate how well linear and power function models explain empirical data from individual participants tested in different procedural settings. The line paradigm was used in five different procedural variations with 35 adult participants. Data aggregated over the participants showed that fitted linear functions explained more than 98% of the variance in all procedures. A linear regression fit also outperformed a power model fit for the aggregated data. An individual-participant-based analysis showed better fits of a linear model to the data of 14 participants; better fits of a power function with an exponent β > 1 to the data of 12 participants; and better fits of a power function with β < 1 to the data of the remaining nine participants. Of the 35 volunteers, the null hypothesis β = 1 was rejected for 20. The dispersion of the individual β values was approximated well by a normal distribution. These results suggest that, on average, humans perceive long-range time intervals not in a highly compressed, biased manner, but rather in a linear pattern. However, individuals differ considerably in their subjective time scales. This contribution sheds new light on the average and individual psychophysical functions of long-range time representation, and suggests that any attribution of deviation from exponential discount rates in intertemporal choice to the compressed nature of subjective time must entail the characterization of subjective time on an individual-participant basis.

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.

Power and Sample Size Calculations for Logistic Regression Tests for Differential Item Functioning

ERIC Educational Resources Information Center

Li, Zhushan

2014-01-01

Logistic regression is a popular method for detecting uniform and nonuniform differential item functioning (DIF) effects. Theoretical formulas for the power and sample size calculations are derived for likelihood ratio tests and Wald tests based on the asymptotic distribution of the maximum likelihood estimators for the logistic regression model.…

ARMAX-Based Transfer Function Model Identification Using Wide-Area Measurement for Adaptive and Coordinated Damping Control

DOE PAGES

Liu, Hesen; Zhu, Lin; Pan, Zhuohong; ...

2015-09-14

One of the main drawbacks of the existing oscillation damping controllers that are designed based on offline dynamic models is adaptivity to the power system operating condition. With the increasing availability of wide-area measurements and the rapid development of system identification techniques, it is possible to identify a measurement-based transfer function model online that can be used to tune the oscillation damping controller. Such a model could capture all dominant oscillation modes for adaptive and coordinated oscillation damping control. our paper describes a comprehensive approach to identify a low-order transfer function model of a power system using a multi-input multi-outputmore » (MIMO) autoregressive moving average exogenous (ARMAX) model. This methodology consists of five steps: 1) input selection; 2) output selection; 3) identification trigger; 4) model estimation; and 5) model validation. The proposed method is validated by using ambient data and ring-down data in the 16-machine 68-bus Northeast Power Coordinating Council system. Our results demonstrate that the measurement-based model using MIMO ARMAX can capture all the dominant oscillation modes. Compared with the MIMO subspace state space model, the MIMO ARMAX model has equivalent accuracy but lower order and improved computational efficiency. The proposed model can be applied for adaptive and coordinated oscillation damping control.« less

Derivation of linearized transfer functions for switching-mode regulations. Phase A: Current step-up and voltage step-up converters

NASA Technical Reports Server (NTRS)

Wong, R. C.; Owen, H. A., Jr.; Wilson, T. G.

1981-01-01

Small-signal models are derived for the power stage of the voltage step-up (boost) and the current step-up (buck) converters. The modeling covers operation in both the continuous-mmf mode and the discontinuous-mmf mode. The power stage in the regulated current step-up converter on board the Dynamics Explorer Satellite is used as an example to illustrate the procedures in obtaining the small-signal functions characterizing a regulated converter.

Day-Ahead Short-Term Forecasting Electricity Load via Approximation

NASA Astrophysics Data System (ADS)

Khamitov, R. N.; Gritsay, A. S.; Tyunkov, D. A.; E Sinitsin, G.

2017-04-01

The method of short-term forecasting of a power consumption which can be applied to short-term forecasting of power consumption is offered. The offered model is based on sinusoidal function for the description of day and night cycles of power consumption. Function coefficients - the period and amplitude are set up is adaptive, considering dynamics of power consumption with use of an artificial neural network. The presented results are tested on real retrospective data of power supply company. The offered method can be especially useful if there are no opportunities of collection of interval indications of metering devices of consumers, and the power supply company operates with electrical supply points. The offered method can be used by any power supply company upon purchase of the electric power in the wholesale market. For this purpose, it is necessary to receive coefficients of approximation of sinusoidal function and to have retrospective data on power consumption on an interval not less than one year.

Optimal Transmission Line Switching under Geomagnetic Disturbances

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

Lu, Mowen; Nagarajan, Harsha; Yamangil, Emre

Recently, there have been increasing concerns about how geomagnetic disturbances (GMDs) impact electrical power systems. Geomagnetically-induced currents (GICs) can saturate transformers, induce hot spot heating and increase reactive power losses. These effects can potentially cause catastrophic damage to transformers and severely impact the ability of a power system to deliver power. To address this problem, we develop a model of GIC impacts to power systems that includes 1) GIC thermal capacity of transformers as a function of normal Alternating Current (AC) and 2) reactive power losses as a function of GIC. We also use this model to derive an optimizationmore » problem that protects power systems from GIC impacts through line switching, generator dispatch, and load shedding. We then employ state-of-the-art convex relaxations of AC power flow equations to lower bound the objective. We demonstrate the approach on a modified RTS96 system and UIUC 150-bus system and show that line switching is an effective means to mitigate GIC impacts. We also provide a sensitivity analysis of decisions with respect to GMD direction.« less

Optimal Transmission Line Switching under Geomagnetic Disturbances

DOE PAGES

Lu, Mowen; Nagarajan, Harsha; Yamangil, Emre; ...

2017-10-11

Recently, there have been increasing concerns about how geomagnetic disturbances (GMDs) impact electrical power systems. Geomagnetically-induced currents (GICs) can saturate transformers, induce hot spot heating and increase reactive power losses. These effects can potentially cause catastrophic damage to transformers and severely impact the ability of a power system to deliver power. To address this problem, we develop a model of GIC impacts to power systems that includes 1) GIC thermal capacity of transformers as a function of normal Alternating Current (AC) and 2) reactive power losses as a function of GIC. We also use this model to derive an optimizationmore » problem that protects power systems from GIC impacts through line switching, generator dispatch, and load shedding. We then employ state-of-the-art convex relaxations of AC power flow equations to lower bound the objective. We demonstrate the approach on a modified RTS96 system and UIUC 150-bus system and show that line switching is an effective means to mitigate GIC impacts. We also provide a sensitivity analysis of decisions with respect to GMD direction.« less

Resolving power for the diffusion orientation distribution function.

PubMed

Jensen, Jens H; Helpern, Joseph A

2016-08-01

The diffusion orientation distribution function (dODF) is primarily used for white matter fiber tractography. Here the resolving power of the dODF is investigated for a simple diffusion model of two intersecting axonal fiber bundles. The resolving power for the dODF is evaluated using the Sparrow criterion. This is determined for the exact dODF and also for q-space imaging (QSI), q-ball, and kurtosis approximations. Based on theoretical and numerical calculations, the resolving power is found to depend on the eigenvalues of the diffusion model and on the degree of radial weighting for the dODF. The resolving powers of the QSI and q-ball dODFs improve with increased b-value. The kurtosis dODF has a resolving power similar to that of the exact dODF. The dODFs, whether exact or approximate, have finite resolving powers that limit their sensitivity to fiber crossings. The resolving powers for the different dODFs considered here provide convenient benchmarks for assessing and comparing their performance. Magn Reson Med 76:679-688, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Simulation program for estimating statistical power of Cox's proportional hazards model assuming no specific distribution for the survival time.

PubMed

Akazawa, K; Nakamura, T; Moriguchi, S; Shimada, M; Nose, Y

1991-07-01

Small sample properties of the maximum partial likelihood estimates for Cox's proportional hazards model depend on the sample size, the true values of regression coefficients, covariate structure, censoring pattern and possibly baseline hazard functions. Therefore, it would be difficult to construct a formula or table to calculate the exact power of a statistical test for the treatment effect in any specific clinical trial. The simulation program, written in SAS/IML, described in this paper uses Monte-Carlo methods to provide estimates of the exact power for Cox's proportional hazards model. For illustrative purposes, the program was applied to real data obtained from a clinical trial performed in Japan. Since the program does not assume any specific function for the baseline hazard, it is, in principle, applicable to any censored survival data as long as they follow Cox's proportional hazards model.

Rolling scheduling of electric power system with wind power based on improved NNIA algorithm

NASA Astrophysics Data System (ADS)

Xu, Q. S.; Luo, C. J.; Yang, D. J.; Fan, Y. H.; Sang, Z. X.; Lei, H.

2017-11-01

This paper puts forth a rolling modification strategy for day-ahead scheduling of electric power system with wind power, which takes the operation cost increment of unit and curtailed wind power of power grid as double modification functions. Additionally, an improved Nondominated Neighbor Immune Algorithm (NNIA) is proposed for solution. The proposed rolling scheduling model has further improved the operation cost of system in the intra-day generation process, enhanced the system’s accommodation capacity of wind power, and modified the key transmission section power flow in a rolling manner to satisfy the security constraint of power grid. The improved NNIA algorithm has defined an antibody preference relation model based on equal incremental rate, regulation deviation constraints and maximum & minimum technical outputs of units. The model can noticeably guide the direction of antibody evolution, and significantly speed up the process of algorithm convergence to final solution, and enhance the local search capability.

Reliability analysis using an exponential power model with bathtub-shaped failure rate function: a Bayes study.

PubMed

Shehla, Romana; Khan, Athar Ali

2016-01-01

Models with bathtub-shaped hazard function have been widely accepted in the field of reliability and medicine and are particularly useful in reliability related decision making and cost analysis. In this paper, the exponential power model capable of assuming increasing as well as bathtub-shape, is studied. This article makes a Bayesian study of the same model and simultaneously shows how posterior simulations based on Markov chain Monte Carlo algorithms can be straightforward and routine in R. The study is carried out for complete as well as censored data, under the assumption of weakly-informative priors for the parameters. In addition to this, inference interest focuses on the posterior distribution of non-linear functions of the parameters. Also, the model has been extended to include continuous explanatory variables and R-codes are well illustrated. Two real data sets are considered for illustrative purposes.

Hydraulic geometry of the Platte River in south-central Nebraska

USGS Publications Warehouse

Eschner, T.R.

1982-01-01

At-a-station hydraulic-geometry of the Platte River in south-central Nebraska is complex. The range of exponents of simple power-function relations is large, both between different reaches of the river, and among different sections within a given reach. The at-a-station exponents plot in several fields of the b-f-m diagram, suggesting that morphologic and hydraulic changes with increasing discharge vary considerably. Systematic changes in the plotting positions of the exponents with time indicate that in general, the width exponent has decreased, although trends are not readily apparent in the other exponents. Plots of the hydraulic-geometry relations indicate that simple power functions are not the proper model in all instances. For these sections, breaks in the slopes of the hydraulic geometry relations serve to partition the data sets. Power functions fit separately to the partitioned data described the width-, depth-, and velocity-discharge relations more accurately than did a single power function. Plotting positions of the exponents from hydraulic geometry relations of partitioned data sets on b-f-m diagrams indicate that much of the apparent variations of plotting positions of single power functions results because the single power functions compromise both subsets of partitioned data. For several sections, the shape of the channel primarily accounts for the better fit of two-power functions to partitioned data than a single power function over the entire range of data. These non-log linear relations may have significance for channel maintenance. (USGS)

Smart caching based on mobile agent of power WebGIS platform.

PubMed

Wang, Xiaohui; Wu, Kehe; Chen, Fei

2013-01-01

Power information construction is developing towards intensive, platform, distributed direction with the expansion of power grid and improvement of information technology. In order to meet the trend, power WebGIS was designed and developed. In this paper, we first discuss the architecture and functionality of power WebGIS, and then we study caching technology in detail, which contains dynamic display cache model, caching structure based on mobile agent, and cache data model. We have designed experiments of different data capacity to contrast performance between WebGIS with the proposed caching model and traditional WebGIS. The experimental results showed that, with the same hardware environment, the response time of WebGIS with and without caching model increased as data capacity growing, while the larger the data was, the higher the performance of WebGIS with proposed caching model improved.

Computing the Power-Density Spectrum for an Engineering Model

NASA Technical Reports Server (NTRS)

Dunn, H. J.

1982-01-01

Computer program for calculating of power-density spectrum (PDS) from data base generated by Advanced Continuous Simulation Language (ACSL) uses algorithm that employs fast Fourier transform (FFT) to calculate PDS of variable. Accomplished by first estimating autocovariance function of variable and then taking FFT of smoothed autocovariance function to obtain PDS. Fast-Fourier-transform technique conserves computer resources.

Joint pricing and production management: a geometric programming approach with consideration of cubic production cost function

NASA Astrophysics Data System (ADS)

Sadjadi, Seyed Jafar; Hamidi Hesarsorkh, Aghil; Mohammadi, Mehdi; Bonyadi Naeini, Ali

2015-06-01

Coordination and harmony between different departments of a company can be an important factor in achieving competitive advantage if the company corrects alignment between strategies of different departments. This paper presents an integrated decision model based on recent advances of geometric programming technique. The demand of a product considers as a power function of factors such as product's price, marketing expenditures, and consumer service expenditures. Furthermore, production cost considers as a cubic power function of outputs. The model will be solved by recent advances in convex optimization tools. Finally, the solution procedure is illustrated by numerical example.

Application of Autonomous Smart Inverter Volt-VAR Function for Voltage Reduction Energy Savings and Power Quality in Electric Distribution Systems: Preprint

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

Ding, Fei; Nagarajan, Adarsh; Baggu, Murali

This paper evaluated the impact of smart inverter Volt-VAR function on voltage reduction energy saving and power quality in electric power distribution systems. A methodology to implement the voltage reduction optimization was developed by controlling the substation LTC and capacitor banks, and having smart inverters participate through their autonomous Volt-VAR control. In addition, a power quality scoring methodology was proposed and utilized to quantify the effect on power distribution system power quality. All of these methodologies were applied to a utility distribution system model to evaluate the voltage reduction energy saving and power quality under various PV penetrations and smartmore » inverter densities.« less

Duality in Power-Law Localization in Disordered One-Dimensional Systems

NASA Astrophysics Data System (ADS)

Deng, X.; Kravtsov, V. E.; Shlyapnikov, G. V.; Santos, L.

2018-03-01

The transport of excitations between pinned particles in many physical systems may be mapped to single-particle models with power-law hopping, 1 /ra . For randomly spaced particles, these models present an effective peculiar disorder that leads to surprising localization properties. We show that in one-dimensional systems almost all eigenstates (except for a few states close to the ground state) are power-law localized for any value of a >0 . Moreover, we show that our model is an example of a new universality class of models with power-law hopping, characterized by a duality between systems with long-range hops (a <1 ) and short-range hops (a >1 ), in which the wave function amplitude falls off algebraically with the same power γ from the localization center.

Application of viscoelastic, viscoplastic, and rate-and-state friction constitutive laws to the deformation of unconsolidated sands

NASA Astrophysics Data System (ADS)

Hagin, Paul N.

Laboratory experiments on dry, unconsolidated sands from the Wilmington field, CA, reveal significant viscous creep strain under a variety of loading conditions. In hydrostatic compression tests between 10 and 50 MPa of pressure, the creep strain exceeds the magnitude of the instantaneous strain and follows a power law function of time. Interestingly, the viscous effects only appear when loading a sample beyond its preconsolidation pressure. Cyclic loading tests (at quasi-static frequencies of 10-6 to 10 -2 Hz) show that the bulk modulus increases by a factor of two with increasing frequency while attenuation remains constant. I attempt to fit these observations using three classes of models: linear viscoelastic, viscoplastic, and rate-and-state friction models. For the linear viscoelastic modeling, I investigated two types of models; spring-dashpot (exponential) and power law models. I find that a combined power law-Maxwell solid creep model adequately fits all of the data. Extrapolating the power law-Maxwell creep model out to 30 years (to simulate the lifetime of a reservoir) predicts that the static bulk modulus is 25% of the dynamic modulus, in good agreement with field observations. Laboratory studies also reveal that a large portion of the deformation is permanent, suggesting that an elastic-plastic model is appropriate. However, because the viscous component of deformation is significant, an elastic-viscoplastic model is necessary. An appropriate model for unconsolidated sands is developed by incorporating Perzyna (power law) viscoplasticity theory into the modified Cambridge clay cap model. Hydrostatic compression tests conducted as a function of volumetric strain rate produced values for the required model parameters. As a result, by using an end cap model combined with power law viscoplasticity theory, changes in porosity in both the elastic and viscoplastic regimes can be predicted as a function of both stress path and strain rate. To test whether rate-and-state friction laws can be used to model creep strain, I expand the rate-and-state formulation to include deformation under hydrostatic stress boundary conditions. Results show that the expanded rate-and-state formulation successfully describes the creep strain of unconsolidated sand. Finally, I show that the viscoplastic end cap and rate-and-state models are mathematically similar.

Aerobic power and lean mass are indicators of competitive sprint performance among elite female cross-country skiers.

PubMed

Carlsson, Tomas; Tonkonogi, Michail; Carlsson, Magnus

2016-01-01

The purpose of this study was to establish the optimal allometric models to predict International Ski Federation's ski-ranking points for sprint competitions (FISsprint) among elite female cross-country skiers based on maximal oxygen uptake ( [Formula: see text]) and lean mass (LM). Ten elite female cross-country skiers (age: 24.5±2.8 years [mean ± SD]) completed a treadmill roller-skiing test to determine [Formula: see text] (ie, aerobic power) using the diagonal stride technique, whereas LM (ie, a surrogate indicator of anaerobic capacity) was determined by dual-emission X-ray anthropometry. The subjects' FISsprint were used as competitive performance measures. Power function modeling was used to predict the skiers' FISsprint based on [Formula: see text], LM, and body mass. The subjects' test and performance data were as follows: [Formula: see text], 4.0±0.3 L min -1 ; LM, 48.9±4.4 kg; body mass, 64.0±5.2 kg; and FISsprint, 116.4±59.6 points. The following power function models were established for the prediction of FISsprint: [Formula: see text] and 6.95 × 10 10 · LM -5.25 ; these models explained 66% ( P =0.0043) and 52% ( P =0.019), respectively, of the variance in the FISsprint. Body mass failed to contribute to both models; hence, the models are based on [Formula: see text] and LM expressed absolutely. The results demonstrate that the physiological variables that reflect aerobic power and anaerobic capacity are important indicators of competitive sprint performance among elite female skiers. To accurately indicate performance capability among elite female skiers, the presented power function models should be used. Skiers whose [Formula: see text] differs by 1% will differ in their FISsprint by 5.8%, whereas the corresponding 1% difference in LM is related to an FISsprint difference of 5.1%, where both differences are in favor of the skier with higher [Formula: see text] or LM. It is recommended that coaches use the absolute expression of these variables to monitor skiers' performance-related training adaptations linked to changes in aerobic power and anaerobic capacity.

Gain and power optimization of the wireless optical system with multilevel modulation.

PubMed

Liu, Xian

2008-06-01

When used in an outdoor environment to expedite networking access, the performance of wireless optical communication systems is affected by transmitter sway. In the design of such systems, much attention has been paid to developing power-efficient schemes. However, the bandwidth efficiency is also an important issue. One of the most natural approaches to promote bandwidth efficiency is to use multilevel modulation. This leads to multilevel pulse amplitude modulation in the context of intensity modulation and direct detection. We develop a model based on the four-level pulse amplitude modulation. We show that the model can be formulated as an optimization problem in terms of the transmitter power, bit error probability, transmitter gain, and receiver gain. The technical challenges raised by modeling and solving the problem include the analytical and numerical treatments for the improper integrals of the Gaussian functions coupled with the erfc function. The results demonstrate that, at the optimal points, the power penalty paid to the doubled bandwidth efficiency is around 3 dB.

Analyzing Small Signal Stability of Power System based on Online Data by Use of SMES

NASA Astrophysics Data System (ADS)

Ishikawa, Hiroyuki; Shirai, Yasuyuki; Nitta, Tanzo; Shibata, Katsuhiko

The purpose of this study is to estimate eigen-values and eigen-vectors of a power system from on-line data to evaluate the power system stability. Power system responses due to the small power modulation of known pattern from SMES (Superconducting Magnetic Energy Storage) were analyzed, and the transfer functions between the power modulation and power oscillations of generators were obtained. Eigen-values and eigen-vectors were estimated from the transfer functions. Experiments were carried out by use of a model SMES and Advanced Power System Analyzer (APSA), which is an analogue type power system simulator of Kansai Electric Power Company Inc., Japan. Changes in system condition were observed by the estimated eigen-values and eigen-vectors. Result agreed well with the resent report and digital simulation. This method gives a new application for SMES, which will be installed for improving electric power quality.

Evaluation of concentrated space solar arrays using computer modeling. [for spacecraft propulsion and power supplies

NASA Technical Reports Server (NTRS)

Rockey, D. E.

1979-01-01

A general approach is developed for predicting the power output of a concentrator enhanced photovoltaic space array. A ray trace routine determines the concentrator intensity arriving at each solar cell. An iterative calculation determines the cell's operating temperature since cell temperature and cell efficiency are functions of one another. The end result of the iterative calculation is that the individual cell's power output is determined as a function of temperature and intensity. Circuit output is predicted by combining the individual cell outputs using the single diode model of a solar cell. Concentrated array characteristics such as uniformity of intensity and operating temperature at various points across the array are examined using computer modeling techniques. An illustrative example is given showing how the output of an array can be enhanced using solar concentration techniques.

Research on Power System Scheduling Improving Wind Power Accommodation Considering Thermal Energy Storage and Flexible Load

NASA Astrophysics Data System (ADS)

Zou, Chenlu; Cui, Xue; Wang, Heng; Zhou, Bin; Liu, Yang

2018-01-01

In the case of rapid development of wind power and heavy wind curtailment, the study of wind power accommodation of combined heat and power system has become the focus of attention. A two-stage scheduling model contains of wind power, thermal energy storage, CHP unit and flexible load were constructed. This model with the objective function of minimizing wind curtailment and the operation cost of units while taking into account of the total coal consumption of units, constraint of thermal energy storage and electricity-heat characteristic of CHP. This paper uses MICA to solve the problem of too many constraints and make the solution more feasible. A numerical example showed that the two stage decision scheduling model can consume more wind power, and it could provide a reference for combined heat and power system short-term operation

Efficient Operation of a Multi-purpose Reservoir in Chile: Integration of Economic Water Value for Irrigation and Hydropower

NASA Astrophysics Data System (ADS)

Olivares, M. A.; Gonzalez Cabrera, J. M., Sr.; Moreno, R.

2016-12-01

Operation of hydropower reservoirs in Chile is prescribed by an Independent Power System Operator. This study proposes a methodology that integrates power grid operations planning with basin-scale multi-use reservoir operations planning. The aim is to efficiently manage a multi-purpose reservoir, in which hydroelectric generation is competing with other water uses, most notably irrigation. Hydropower and irrigation are competing water uses due to a seasonality mismatch. Currently, the operation of multi-purpose reservoirs with substantial power capacity is prescribed as the result of a grid-wide cost-minimization model which takes irrigation requirements as constraints. We propose advancing in the economic co-optimization of reservoir water use for irrigation and hydropower at the basin level, by explicitly introducing the economic value of water for irrigation represented by a demand function for irrigation water. The proposed methodology uses the solution of a long-term grid-wide operations planning model, a stochastic dual dynamic program (SDDP), to obtain the marginal benefit function for water use in hydropower. This marginal benefit corresponds to the energy price in the power grid as a function of the water availability in the reservoir and the hydrologic scenarios. This function allows capture technical and economic aspects to the operation of hydropower reservoir in the power grid and is generated with the dual variable of the power-balance constraint, the optimal reservoir operation and the hydrologic scenarios used in SDDP. The economic value of water for irrigation and hydropower are then integrated into a basin scale stochastic dynamic program, from which stored water value functions are derived. These value functions are then used to re-optimize reservoir operations under several inflow scenarios.

Development of a Dynamic Visco-elastic Vehicle-Soil Interaction Model for Rut Depth, and Power Determinations

DTIC Science & Technology

2011-09-06

Presentation Outline A) Review of Soil Model governing equations B) Development of pedo -transfer functions (terrain database to engineering properties) C...lateral earth pressure) UNCLASSIFIED B) Development of pedo -transfer functions Engineering parameters needed by soil model - compression index - rebound...inches, RCI for fine- grained soils, CI for coarse-grained soils. UNCLASSIFIED Pedo -transfer function • Need to transfer existing terrain database

Power System Transient Stability Improvement by the Interline Power Flow Controller (IPFC)

NASA Astrophysics Data System (ADS)

Zhang, Jun; Yokoyama, Akihiko

This paper presents a study on the power system transient stability improvement by means of interline power flow controller (IPFC). The power injection model of IPFC in transient analysis is proposed and can be easily incorporated into existing power systems. Based on the energy function analysis, the operation of IPFC should guarantee that the time derivative of the global energy of the system is not greater than zero in order to damp the electromechanical oscillations. Accordingly, control laws of IPFC are proposed for its application to the single-machine infinite-bus (SMIB) system and the multimachine systems, respectively. Numerical simulations on the corresponding model power systems are presented to demonstrate their effectiveness in improving power system transient stability.

A Design of a Network Model to the Electric Power Trading System Using Web Services

NASA Astrophysics Data System (ADS)

Maruo, Tomoaki; Matsumoto, Keinosuke; Mori, Naoki; Kitayama, Masashi; Izumi, Yoshio

Web services are regarded as a new application paradigm in the world of the Internet. On the other hand, many business models of a power trading system has been proposed to aim at load reduction by consumers cooperating with electric power suppliers in an electric power market. Then, we propose a network model of power trading system using Web service in this paper. The adaptability of Web services to power trading system was checked in the prototype of our network model and we got good results for it. Each server provides functions as a SOAP server, and it is coupled loosely with each other through SOAP. Storing SOAP message in HTTP packet can establish the penetration communication way that is not conscious of a firewall. Switching of a dynamic server is possible by means of rewriting the server point information on WSDL at the time of obstacle generating.

Toward an operant model of power in organizations

PubMed Central

Goltz, Sonia M.

2003-01-01

The purpose of this paper is to suggest that behavior analysis can help to explain social power. In this approach, an individual's potential for influence is thought to be partially a function of his or her access to stimuli that can be used as consequences. This access can occur either through direct authority or indirectly through social networks and exchanges. Social power is also thought to be a function of an individual's skill in delivering the stimuli in ways that will have the most impact on behavior. A number of predictions about power based on an operant approach are offered. PMID:22478398

A power function profile of a ski jumping in-run hill.

PubMed

Zanevskyy, Ihor

2011-01-01

The aim of the research was to find a function of the curvilinear segment profile which could make possible to avoid an instantaneous increasing of a curvature and to replace a circle arc segment on the in-run of a ski jump without any correction of the angles of inclination and the length of the straight-line segments. The methods of analytical geometry and trigonometry were used to calculate an optimal in-run hill profile. There were two fundamental conditions of the model: smooth borders between a curvilinear segment and straight-line segments of an in-run hill and concave of the curvilinear segment. Within the framework of this model, the problem has been solved with a reasonable precision. Four functions of a curvilinear segment profile of the in-run hill were investigated: circle arc, inclined quadratic parabola, inclined cubic parabola, and power function. The application of a power function to the in-run profile satisfies equal conditions for replacing a circle arc segment. Geometrical parameters of 38 modern ski jumps were investigated using the methods proposed.

Analytical simulation of SPS system performance, volume 3, phase 3

NASA Technical Reports Server (NTRS)

Kantak, A. V.; Lindsey, W. C.

1980-01-01

The simulation model for the Solar Power Satellite spaceantenna and the associated system imperfections are described. Overall power transfer efficiency, the key performance issue, is discussed as a function of the system imperfections. Other system performance measures discussed include average power pattern, mean beam gain reduction, and pointing error.

Neural system modeling and simulation using Hybrid Functional Petri Net.

PubMed

Tang, Yin; Wang, Fei

2012-02-01

The Petri net formalism has been proved to be powerful in biological modeling. It not only boasts of a most intuitive graphical presentation but also combines the methods of classical systems biology with the discrete modeling technique. Hybrid Functional Petri Net (HFPN) was proposed specially for biological system modeling. An array of well-constructed biological models using HFPN yielded very interesting results. In this paper, we propose a method to represent neural system behavior, where biochemistry and electrical chemistry are both included using the Petri net formalism. We built a model for the adrenergic system using HFPN and employed quantitative analysis. Our simulation results match the biological data well, showing that the model is very effective. Predictions made on our model further manifest the modeling power of HFPN and improve the understanding of the adrenergic system. The file of our model and more results with their analysis are available in our supplementary material.

Electrical cable utilization for wave energy converters

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

Bull, Diana; Baca, Michael; Schenkman, Benjamin

Here, this paper investigates the suitability of sizing the electrical export cable based on the rating of the contributing WECs within a farm. These investigations have produced a new methodology to evaluate the probabilities associated with peak power values on an annual basis. It has been shown that the peaks in pneumatic power production will follow an exponential probability function for a linear model. A methodology to combine all the individual probability functions into an annual view has been demonstrated on pneumatic power production by a Backward Bent Duct Buoy (BBDB). These investigations have also resulted in a highly simplifiedmore » and perfunctory model of installed cable cost as a function of voltage and conductor cross-section. This work solidifies the need to determine electrical export cable rating based on expected energy delivery as opposed to device rating as small decreases in energy delivery can result in cost savings.« less

Electrical cable utilization for wave energy converters

DOE PAGES

Bull, Diana; Baca, Michael; Schenkman, Benjamin

2018-04-27

Here, this paper investigates the suitability of sizing the electrical export cable based on the rating of the contributing WECs within a farm. These investigations have produced a new methodology to evaluate the probabilities associated with peak power values on an annual basis. It has been shown that the peaks in pneumatic power production will follow an exponential probability function for a linear model. A methodology to combine all the individual probability functions into an annual view has been demonstrated on pneumatic power production by a Backward Bent Duct Buoy (BBDB). These investigations have also resulted in a highly simplifiedmore » and perfunctory model of installed cable cost as a function of voltage and conductor cross-section. This work solidifies the need to determine electrical export cable rating based on expected energy delivery as opposed to device rating as small decreases in energy delivery can result in cost savings.« less

Primordial power spectrum features and consequences

NASA Astrophysics Data System (ADS)

Goswami, G.

2014-03-01

The present Cosmic Microwave Background (CMB) temperature and polarization anisotropy data is consistent with not only a power law scalar primordial power spectrum (PPS) with a small running but also with the scalar PPS having very sharp features. This has motivated inflationary models with such sharp features. Recently, even the possibility of having nulls in the power spectrum (at certain scales) has been considered. The existence of these nulls has been shown in linear perturbation theory. What shall be the effect of higher order corrections on such nulls? Inspired by this question, we have attempted to calculate quantum radiative corrections to the Fourier transform of the 2-point function in a toy field theory and address the issue of how these corrections to the power spectrum behave in models in which the tree-level power spectrum has a sharp dip (but not a null). In particular, we have considered the possibility of the relative enhancement of radiative corrections in a model in which the tree-level spectrum goes through a dip in power at a certain scale. The mode functions of the field (whose power spectrum is to be evaluated) are chosen such that they undergo the kind of dynamics that leads to a sharp dip in the tree level power spectrum. Next, we have considered the situation in which this field has quartic self interactions, and found one loop correction in a suitably chosen renormalization scheme. Thus, we have attempted to answer the following key question in the context of this toy model (which is as important in the realistic case): In the chosen renormalization scheme, can quantum radiative corrections be enhanced relative to tree-level power spectrum at scales, at which sharp dips appear in the tree-level spectrum?

Smart Caching Based on Mobile Agent of Power WebGIS Platform

PubMed Central

Wang, Xiaohui; Wu, Kehe; Chen, Fei

2013-01-01

Power information construction is developing towards intensive, platform, distributed direction with the expansion of power grid and improvement of information technology. In order to meet the trend, power WebGIS was designed and developed. In this paper, we first discuss the architecture and functionality of power WebGIS, and then we study caching technology in detail, which contains dynamic display cache model, caching structure based on mobile agent, and cache data model. We have designed experiments of different data capacity to contrast performance between WebGIS with the proposed caching model and traditional WebGIS. The experimental results showed that, with the same hardware environment, the response time of WebGIS with and without caching model increased as data capacity growing, while the larger the data was, the higher the performance of WebGIS with proposed caching model improved. PMID:24288504

Peculiar velocity effect on galaxy correlation functions in nonlinear clustering regime

NASA Astrophysics Data System (ADS)

Matsubara, Takahiko

1994-03-01

We studied the distortion of the apparent distribution of galaxies in redshift space contaminated by the peculiar velocity effect. Specifically we obtained the expressions for N-point correlation functions in redshift space with given functional form for velocity distribution f(v) and evaluated two- and three-point correlation functions quantitatively. The effect of velocity correlations is also discussed. When the two-point correlation function in real space has a power-law form, Xir(r) is proportional to r(-gamma), the redshift-space counterpart on small scales also has a power-law form but with an increased power-law index: Xis(s) is proportional to s(1-gamma). When the three-point correlation function has the hierarchical form and the two-point correlation function has the power-law form in real space, the hierarchical form of the three-point correlation function is almost preserved in redshift space. The above analytic results are compared with the direct analysis based on N-body simulation data for cold dark matter models. Implications on the hierarchical clustering ansatz are discussed in detail.

Dynamic study for performance improvements of a thermo-mechanically bistable heat engine

NASA Astrophysics Data System (ADS)

Boughaleb, J.; Arnaud, A.; Monfray, S.; Cottinet, P. J.; Quenard, S.; Pitone, G.; Boeuf, F.; Guyomar, D.; Skotnicki, T.

2015-12-01

This paper focuses on a thermal study of a thermal energy harvester based on the coupling of a bimetallic strip heat engine with a piezoelectric membrane for wasted heat scavenging. Such a harvester is dedicated to power autonomous systems such as wireless sensor nodes. For a better understanding of the working principle of the system, it is compulsory to have a good understanding of the thermal specificities and phenomenon taking place inside the harvester. Attention is consequently focused on the thermal modeling of the harvester in static mode using the equivalence between the electrical and thermal quantities. This first modeling step allowed the improvement of the thermal properties inside the system by increasing the thermal gradient across it. However, the bimetal being the active part of the system has not been taken into account in this model and shadow zones persisted regarding the bimetal operation windows as a function of its snapping temperatures and hysteresis. To overcome this, a dynamic model is proposed in this paper taking into account the bimetal as a switched capacitance alternatively in contact with the hot source and the cold surface. This last model completed the static one by predicting the bimetal's operation windows in function of its intrinsic properties and the operation range evolution in function of the snapping temperature first and then in function of the bimetal thermal hysteresis. Moreover, experimental measurements enable to validate the proposed model and to point out the most powerful bimetals for scavenging higher amounts of power.

On the running of the spectral index to all orders: a new model-dependent approach to constrain inflationary models

NASA Astrophysics Data System (ADS)

Zarei, Moslem

2016-06-01

In conventional model-independent approaches, the power spectrum of primordial perturbations is characterized by such free parameters as the spectral index, its running, the running of running, and the tensor-to-scalar ratio. In this work we show that, at least for simple inflationary potentials, one can find the primordial scalar and tensor power spectra exactly by resumming over all the running terms. In this model-dependent method, we expand the power spectra about the pivot scale to find the series terms as functions of the e-folding number for some single field models of inflation. Interestingly, for the viable models studied here, one can sum over all the terms and evaluate the exact form of the power spectra. This in turn gives more accurate parametrization of the specific models studied in this work. We finally compare our results with recent cosmic microwave background data to find that our new power spectra are in good agreement with the data.

Mechanical analysis of non-uniform bi-directional functionally graded intelligent micro-beams using modified couple stress theory

NASA Astrophysics Data System (ADS)

Bakhshi Khaniki, Hossein; Rajasekaran, Sundaramoorthy

2018-05-01

This study develops a comprehensive investigation on mechanical behavior of non-uniform bi-directional functionally graded beam sensors in the framework of modified couple stress theory. Material variation is modelled through both length and thickness directions using power-law, sigmoid and exponential functions. Moreover, beam is assumed with linear, exponential and parabolic cross-section variation through the length using power-law and sigmoid varying functions. Using these assumptions, a general model for microbeams is presented and formulated by employing Hamilton’s principle. Governing equations are solved using a mixed finite element method with Lagrangian interpolation technique, Gaussian quadrature method and Wilson’s Lagrangian multiplier method. It is shown that by using bi-directional functionally graded materials in nonuniform microbeams, mechanical behavior of such structures could be affected noticeably and scale parameter has a significant effect in changing the rigidity of nonuniform bi-directional functionally graded beams.

Battery model for electrical power system energy balance

NASA Technical Reports Server (NTRS)

Hafen, D. P.

1983-01-01

A model to simulate nickel-cadmium battery performance and response in a spacecraft electrical power system energy balance calculation was developed. The voltage of the battery is given as a function of temperature, operating depth-of-charge (DOD), and battery state-of-charge. Also accounted for is charge inefficiency. A battery is modeled by analysis of the results of a multiparameter battery cycling test at various temperatures and DOD's.

Operations research investigations of satellite power stations

NASA Technical Reports Server (NTRS)

Cole, J. W.; Ballard, J. L.

1976-01-01

A systems model reflecting the design concepts of Satellite Power Stations (SPS) was developed. The model is of sufficient scope to include the interrelationships of the following major design parameters: the transportation to and between orbits; assembly of the SPS; and maintenance of the SPS. The systems model is composed of a set of equations that are nonlinear with respect to the system parameters and decision variables. The model determines a figure of merit from which alternative concepts concerning transportation, assembly, and maintenance of satellite power stations are studied. A hybrid optimization model was developed to optimize the system's decision variables. The optimization model consists of a random search procedure and the optimal-steepest descent method. A FORTRAN computer program was developed to enable the user to optimize nonlinear functions using the model. Specifically, the computer program was used to optimize Satellite Power Station system components.

Fluidic Energy Harvester Optimization in Grid Turbulence

NASA Astrophysics Data System (ADS)

Danesh-Yazdi, Amir; Elvin, Niell; Andreopoulos, Yiannis

2017-11-01

Even though it is omnipresent in nature, there has not been a great deal of research in the literature involving turbulence as an energy source for piezoelectric fluidic harvesters. In the present work, a grid-generated turbulence forcing function model which we derived previously is employed in the single degree-of-freedom electromechanical equations to find the power output and tip displacement of piezoelectric cantilever beams. Additionally, we utilize simplified, deterministic models of the turbulence forcing function to obtain closed-form expressions for the power output. These theoretical models are studied using experiments that involve separately placing a hot-wire anemometer probe and a short PVDF beam in flows where turbulence is generated by means of passive and semi-passive grids. From a parametric study on the deterministic models, we show that the white noise forcing function best mimics the experimental data. Furthermore, our parametric study of the response spectrum of a generic fluidic harvester in grid-generated turbulent flow shows that optimum power output is attained for beams placed closer to the grid with a low natural frequency and damping ratio and a large electromechanical coupling coefficient. NSF Grant No. CBET 1033117.

Adaptive control method for core power control in TRIGA Mark II reactor

NASA Astrophysics Data System (ADS)

Sabri Minhat, Mohd; Selamat, Hazlina; Subha, Nurul Adilla Mohd

2018-01-01

The 1MWth Reactor TRIGA PUSPATI (RTP) Mark II type has undergone more than 35 years of operation. The existing core power control uses feedback control algorithm (FCA). It is challenging to keep the core power stable at the desired value within acceptable error bands to meet the safety demand of RTP due to the sensitivity of nuclear research reactor operation. Currently, the system is not satisfied with power tracking performance and can be improved. Therefore, a new design core power control is very important to improve the current performance in tracking and regulate reactor power by control the movement of control rods. In this paper, the adaptive controller and focus on Model Reference Adaptive Control (MRAC) and Self-Tuning Control (STC) were applied to the control of the core power. The model for core power control was based on mathematical models of the reactor core, adaptive controller model, and control rods selection programming. The mathematical models of the reactor core were based on point kinetics model, thermal hydraulic models, and reactivity models. The adaptive control model was presented using Lyapunov method to ensure stable close loop system and STC Generalised Minimum Variance (GMV) Controller was not necessary to know the exact plant transfer function in designing the core power control. The performance between proposed adaptive control and FCA will be compared via computer simulation and analysed the simulation results manifest the effectiveness and the good performance of the proposed control method for core power control.

Simulation model of a variable-speed pumped-storage power plant in unstable operating conditions in pumping mode

NASA Astrophysics Data System (ADS)

Martínez-Lucas, G.; Pérez-Díaz, J. I.; Sarasúa, J. I.; Cavazzini, G.; Pavesi, G.; Ardizzon, G.

2017-04-01

This paper presents a dynamic simulation model of a laboratory-scale pumped-storage power plant (PSPP) operating in pumping mode with variable speed. The model considers the dynamic behavior of the conduits by means of an elastic water column approach, and synthetically generates both pressure and torque pulsations that reproduce the operation of the hydraulic machine in its instability region. The pressure and torque pulsations are generated each from a different set of sinusoidal functions. These functions were calibrated from the results of a CFD model, which was in turn validated from experimental data. Simulation model results match the numerical results of the CFD model with reasonable accuracy. The pump-turbine model (the functions used to generate pressure and torque pulsations inclusive) was up-scaled by hydraulic similarity according to the design parameters of a real PSPP and included in a dynamic simulation model of the said PSPP. Preliminary conclusions on the impact of unstable operation conditions on the penstock fatigue were obtained by means of a Monte Carlo simulation-based fatigue analysis.

Continuous-Time Finance and the Waiting Time Distribution: Multiple Characteristic Times

NASA Astrophysics Data System (ADS)

Fa, Kwok Sau

2012-09-01

In this paper, we model the tick-by-tick dynamics of markets by using the continuous-time random walk (CTRW) model. We employ a sum of products of power law and stretched exponential functions for the waiting time probability distribution function; this function can fit well the waiting time distribution for BUND futures traded at LIFFE in 1997.

Asymptotic correlation functions and FFLO signature for the one-dimensional attractive Hubbard model

NASA Astrophysics Data System (ADS)

Cheng, Song; Jiang, Yuzhu; Yu, Yi-Cong; Batchelor, Murray T.; Guan, Xi-Wen

2018-04-01

We study the long-distance asymptotic behavior of various correlation functions for the one-dimensional (1D) attractive Hubbard model in a partially polarized phase through the Bethe ansatz and conformal field theory approaches. We particularly find the oscillating behavior of these correlation functions with spatial power-law decay, of which the pair (spin) correlation function oscillates with a frequency ΔkF (2 ΔkF). Here ΔkF = π (n↑ -n↓) is the mismatch in the Fermi surfaces of spin-up and spin-down particles. Consequently, the pair correlation function in momentum space has peaks at the mismatch k = ΔkF, which has been observed in recent numerical work on this model. These singular peaks in momentum space together with the spatial oscillation suggest an analog of the Fulde-Ferrell-Larkin-Ovchinnikov (FFLO) state in the 1D Hubbard model. The parameter β representing the lattice effect becomes prominent in critical exponents which determine the power-law decay of all correlation functions. We point out that the backscattering of unpaired fermions and bound pairs within their own Fermi points gives a microscopic origin of the FFLO pairing in 1D.

Approximating lens power.

PubMed

Kaye, Stephen B

2009-04-01

To provide a scalar measure of refractive error, based on geometric lens power through principal, orthogonal and oblique meridians, that is not limited to the paraxial and sag height approximations. A function is derived to model sections through the principal meridian of a lens, followed by rotation of the section through orthogonal and oblique meridians. Average focal length is determined using the definition for the average of a function. Average univariate power in the principal meridian (including spherical aberration), can be computed from the average of a function over the angle of incidence as determined by the parameters of the given lens, or adequately computed from an integrated series function. Average power through orthogonal and oblique meridians, can be similarly determined using the derived formulae. The widely used computation for measuring refractive error, the spherical equivalent, introduces non-constant approximations, leading to a systematic bias. The equations proposed provide a good univariate representation of average lens power and are not subject to a systematic bias. They are particularly useful for the analysis of aggregate data, correlating with biological treatment variables and for developing analyses, which require a scalar equivalent representation of refractive power.

Value function in economic growth model

NASA Astrophysics Data System (ADS)

Bagno, Alexander; Tarasyev, Alexandr A.; Tarasyev, Alexander M.

2017-11-01

Properties of the value function are examined in an infinite horizon optimal control problem with an unlimited integrand index appearing in the quality functional with a discount factor. Optimal control problems of such type describe solutions in models of economic growth. Necessary and sufficient conditions are derived to ensure that the value function satisfies the infinitesimal stability properties. It is proved that value function coincides with the minimax solution of the Hamilton-Jacobi equation. Description of the growth asymptotic behavior for the value function is provided for the logarithmic, power and exponential quality functionals and an example is given to illustrate construction of the value function in economic growth models.

Saturn systems holddown acoustic efficiency and normalized acoustic power spectrum.

NASA Technical Reports Server (NTRS)

Gilbert, D. W.

1972-01-01

Saturn systems field acoustic data are used to derive mid- and far-field prediction parameters for rocket engine noise. The data were obtained during Saturn vehicle launches at the Kennedy Space Center. The data base is a sorted set of acoustic data measured during the period 1961 through 1971 for Saturn system launches SA-1 through AS-509. The model assumes hemispherical radiation from a simple source located at the intersection of the longitudinal axis of each booster and the engine exit plane. The model parameters are evaluated only during vehicle holddown. The acoustic normalized power spectrum and efficiency for each system are isolated as a composite from the data using linear numerical methods. The specific definitions of each allows separation. The resulting power spectra are nondimensionalized as a function of rocket engine parameters. The nondimensional Saturn system acoustic spectrum and efficiencies are compared as a function of Strouhal number with power spectra from other systems.

On the Spike Train Variability Characterized by Variance-to-Mean Power Relationship.

PubMed

Koyama, Shinsuke

2015-07-01

We propose a statistical method for modeling the non-Poisson variability of spike trains observed in a wide range of brain regions. Central to our approach is the assumption that the variance and the mean of interspike intervals are related by a power function characterized by two parameters: the scale factor and exponent. It is shown that this single assumption allows the variability of spike trains to have an arbitrary scale and various dependencies on the firing rate in the spike count statistics, as well as in the interval statistics, depending on the two parameters of the power function. We also propose a statistical model for spike trains that exhibits the variance-to-mean power relationship. Based on this, a maximum likelihood method is developed for inferring the parameters from rate-modulated spike trains. The proposed method is illustrated on simulated and experimental spike trains.

The γ-ray emission produced by protons that escape from supernova remnant G349.7+0.2

NASA Astrophysics Data System (ADS)

Zhang, Xiao; Li, Hui; Chen, Yang

2016-10-01

G349.7+0.2 is an interacting supernova remnant (SNR) expanding in a dense medium. Recently, a very strong γ-ray source coincident with this SNR has been revealed by Fermi-LAT and H.E.S.S. observations which shows a broken power-law-like spectrum. An escaping-diffusion model, including the power-law and δ-function injection, is applied to this source which can naturally explain the spectral feature in both the GeV and TeV regime. We use the Markov Chain Monte Carlo method to constrain the model parameters and find that the correction factor of slow diffusion around this SNR, χ ˜ 0.01 for power-law injection and χ ˜ 0.1 for δ-function injection, can fit the data best with reasonable molecular cloud mass. This slow diffusion is also consistent with previous results from both phenomenological models and theoretical predication.

Thermodynamic and themoeconomic optimization of isothermal endoreversible chemical engine models

NASA Astrophysics Data System (ADS)

Ocampo-García, A.; Barranco-Jiménez, M. A.; Angulo-Brown, F.

2017-12-01

A branch of finite-time thermodynamics (FTT) is the thermoeconomical analysis of simplified power plant models. The most studied models are those of the Curzon-Ahlborn (CA) and Novikov-Chambadal types. In the decade of 90's of the past century, the FTT analysis of thermal engines was extended to chemical engines. In the present paper we made a thermoeconomical analysis of heat engines and chemical engines of the CA and Novikov types. This study is carried out for isothermal endoreversible chemical engine models with a linear mass transfer law and under three different modes of thermodynamic performance (maximum power, maximum ecological function and maximum efficient power).

Fourier band-power E/B-mode estimators for cosmic shear

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

Becker, Matthew R.; Rozo, Eduardo

We introduce new Fourier band-power estimators for cosmic shear data analysis and E/B-mode separation. We consider both the case where one performs E/B-mode separation and the case where one does not. The resulting estimators have several nice properties which make them ideal for cosmic shear data analysis. First, they can be written as linear combinations of the binned cosmic shear correlation functions. Secondly, they account for the survey window function in real-space. Thirdly, they are unbiased by shape noise since they do not use correlation function data at zero separation. Fourthly, the band-power window functions in Fourier space are compactmore » and largely non-oscillatory. Fifthly, they can be used to construct band-power estimators with very efficient data compression properties. In particular, we find that all of the information on the parameters Ωm, σ8 and ns in the shear correlation functions in the range of ~10–400 arcmin for single tomographic bin can be compressed into only three band-power estimates. Finally, we can achieve these rates of data compression while excluding small-scale information where the modelling of the shear correlation functions and power spectra is very difficult. Given these desirable properties, these estimators will be very useful for cosmic shear data analysis.« less

Analysis of the Multi Strategy Goal Programming for Micro-Grid Based on Dynamic ant Genetic Algorithm

NASA Astrophysics Data System (ADS)

Qiu, J. P.; Niu, D. X.

Micro-grid is one of the key technologies of the future energy supplies. Take economic planning. reliability, and environmental protection of micro grid as a basis for the analysis of multi-strategy objective programming problems for micro grid which contains wind power, solar power, and battery and micro gas turbine. Establish the mathematical model of each power generation characteristics and energy dissipation. and change micro grid planning multi-objective function under different operating strategies to a single objective model based on AHP method. Example analysis shows that in combination with dynamic ant mixed genetic algorithm can get the optimal power output of this model.

Optimization of the time series NDVI-rainfall relationship using linear mixed-effects modeling for the anti-desertification area in the Beijing and Tianjin sandstorm source region

NASA Astrophysics Data System (ADS)

Wang, Jin; Sun, Tao; Fu, Anmin; Xu, Hao; Wang, Xinjie

2018-05-01

Degradation in drylands is a critically important global issue that threatens ecosystem and environmental in many ways. Researchers have tried to use remote sensing data and meteorological data to perform residual trend analysis and identify human-induced vegetation changes. However, complex interactions between vegetation and climate, soil units and topography have not yet been considered. Data used in the study included annual accumulated Moderate Resolution Imaging Spectroradiometer (MODIS) 250 m normalized difference vegetation index (NDVI) from 2002 to 2013, accumulated rainfall from September to August, digital elevation model (DEM) and soil units. This paper presents linear mixed-effect (LME) modeling methods for the NDVI-rainfall relationship. We developed linear mixed-effects models that considered the random effects of sample points nested in soil units for nested two-level modeling and single-level modeling of soil units and sample points, respectively. Additionally, three functions, including the exponential function (exp), the power function (power), and the constant plus power function (CPP), were tested to remove heterogeneity, and an additional three correlation structures, including the first-order autoregressive structure [AR(1)], a combination of first-order autoregressive and moving average structures [ARMA(1,1)] and the compound symmetry structure (CS), were used to address the spatiotemporal correlations. It was concluded that the nested two-level model considering both heteroscedasticity with (CPP) and spatiotemporal correlation with [ARMA(1,1)] showed the best performance (AMR = 0.1881, RMSE = 0.2576, adj- R 2 = 0.9593). Variations between soil units and sample points that may have an effect on the NDVI-rainfall relationship should be included in model structures, and linear mixed-effects modeling achieves this in an effective and accurate way.

The power of yeast to model diseases of the powerhouse of the cell

PubMed Central

Baile, Matthew G.; Claypool, Steven M

2013-01-01

Mitochondria participate in a variety of cellular functions. As such, mitochondrial diseases exhibit numerous clinical phenotypes. Because mitochondrial functions are highly conserved between humans and Saccharomyces cerevisiae, yeast are an excellent model to study mitochondrial disease, providing insight into both physiological and pathophysiological processes. PMID:23276920

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.

Distribution function approach to redshift space distortions. Part IV: perturbation theory applied to dark matter

NASA Astrophysics Data System (ADS)

Vlah, Zvonimir; Seljak, Uroš; McDonald, Patrick; Okumura, Teppei; Baldauf, Tobias

2012-11-01

We develop a perturbative approach to redshift space distortions (RSD) using the phase space distribution function approach and apply it to the dark matter redshift space power spectrum and its moments. RSD can be written as a sum over density weighted velocity moments correlators, with the lowest order being density, momentum density and stress energy density. We use standard and extended perturbation theory (PT) to determine their auto and cross correlators, comparing them to N-body simulations. We show which of the terms can be modeled well with the standard PT and which need additional terms that include higher order corrections which cannot be modeled in PT. Most of these additional terms are related to the small scale velocity dispersion effects, the so called finger of god (FoG) effects, which affect some, but not all, of the terms in this expansion, and which can be approximately modeled using a simple physically motivated ansatz such as the halo model. We point out that there are several velocity dispersions that enter into the detailed RSD analysis with very different amplitudes, which can be approximately predicted by the halo model. In contrast to previous models our approach systematically includes all of the terms at a given order in PT and provides a physical interpretation for the small scale dispersion values. We investigate RSD power spectrum as a function of μ, the cosine of the angle between the Fourier mode and line of sight, focusing on the lowest order powers of μ and multipole moments which dominate the observable RSD power spectrum. Overall we find considerable success in modeling many, but not all, of the terms in this expansion. This is similar to the situation in real space, but predicting power spectrum in redshift space is more difficult because of the explicit influence of small scale dispersion type effects in RSD, which extend to very large scales.

Design of an Adaptive Power Regulation Mechanism and a Nozzle for a Hydroelectric Power Plant Turbine Test Rig

NASA Astrophysics Data System (ADS)

Mert, Burak; Aytac, Zeynep; Tascioglu, Yigit; Celebioglu, Kutay; Aradag, Selin; ETU Hydro Research Center Team

2014-11-01

This study deals with the design of a power regulation mechanism for a Hydroelectric Power Plant (HEPP) model turbine test system which is designed to test Francis type hydroturbines up to 2 MW power with varying head and flow(discharge) values. Unlike the tailor made regulation mechanisms of full-sized, functional HEPPs; the design for the test system must be easily adapted to various turbines that are to be tested. In order to achieve this adaptability, a dynamic simulation model is constructed in MATLAB/Simulink SimMechanics. This model acquires geometric data and hydraulic loading data of the regulation system from Autodesk Inventor CAD models and Computational Fluid Dynamics (CFD) analysis respectively. The dynamic model is explained and case studies of two different HEPPs are performed for validation. CFD aided design of the turbine guide vanes, which is used as input for the dynamic model, is also presented. This research is financially supported by Turkish Ministry of Development.

Prevalence and factors associated with recent intimate partner violence and relationships between disability and depression in post-partum women in one clinic in eThekwini Municipality, South Africa.

PubMed

Gibbs, Andrew; Carpenter, Bradley; Crankshaw, Tamaryn; Hannass-Hancock, Jill; Smit, Jennifer; Tomlinson, Mark; Butler, Lisa

2017-01-01

Intimate partner violence (IPV) experienced by pregnant and post-partum women has negative health effects for women, as well as the foetus, and the new-born child. In this study we sought to assess the prevalence and factors associated with recent IPV amongst post-partum women in one clinic in eThekwini Municipality, South Africa, and explore the relationship between IPV, depression and functional limitations/disabilities. Past 12 month IPV-victimisation was 10.55%. Logistic regression modelled relationships between IPV, functional limitations, depressive symptoms, socio-economic measures, and sexual relationship power. In logistic regression models, overall severity of functional limitations were not associated with IPV-victimisation when treated as a continuous overall score. In this model relationship power (aOR0.22, p = 0.001) and depressive symptoms (aOR1.26, p = 0.001) were significant. When the different functional limitations were separated out in a second model, significant factors were relationship power (aOR0.20, p = 0.001), depressive symptoms (aOR1.20, p = 0.011) and mobility limitations (aOR2.96, p = 0.024). The study emphasises that not all functional limitations are associated with IPV-experience, that depression and disability while overlapping can also be considered different drivers of vulnerability, and that women's experience of IPV is not dependent on pregnancy specific factors, but rather wider social factors that all women experience.

Modification of the gravity model and application to the metropolitan Seoul subway system.

PubMed

Goh, Segun; Lee, Keumsook; Park, Jong Soo; Choi, M Y

2012-08-01

The Metropolitan Seoul Subway system is examined through the use of the gravity model. Exponents describing the power-law dependence on the time distance between stations are obtained, which reveals a universality for subway lines of the same topology. In the short (time) distance regime the number of passengers between stations does not grow with the decrease in the distance, thus deviating from the power-law behavior. It is found that such reduction in passengers is well described by the Hill function. Further, temporal fluctuations in the passenger flow data, fitted to the gravity model modified by the Hill function, are analyzed to reveal the Yule-type nature inherent in the structure of Seoul.

Functionally relevant climate variables for arid lands: Aclimatic water deficit approach for modelling desert shrub distributions

Treesearch

Thomas E. Dilts; Peter J. Weisberg; Camie M. Dencker; Jeanne C. Chambers

2015-01-01

We have three goals. (1) To develop a suite of functionally relevant climate variables for modelling vegetation distribution on arid and semi-arid landscapes of the Great Basin, USA. (2) To compare the predictive power of vegetation distribution models based on mechanistically proximate factors (water deficit variables) and factors that are more mechanistically removed...

Computer Code for Interpreting 13C NMR Relaxation Measurements with Specific Models of Molecular Motion: The Rigid Isotropic and Symmetric Top Rotor Models and the Flexible Symmetric Top Rotor Model

DTIC Science & Technology

2017-01-01

unlimited. 13. SUPPLEMENTARY NOTES 14. ABSTRACT: Carbon-13 nuclear magnetic resonance (13C NMR) spectroscopy is a powerful technique for...FLEXIBLE SYMMETRIC TOP ROTOR MODEL 1. INTRODUCTION Nuclear magnetic resonance (NMR) spectroscopy is a tremendously powerful technique for...application of NMR spectroscopy concerns the property of molecular motion, which is related to many physical, and even biological, functions of molecules in

A Multiobjective Interval Programming Model for Wind-Hydrothermal Power System Dispatching Using 2-Step Optimization Algorithm

PubMed Central

Jihong, Qu

2014-01-01

Wind-hydrothermal power system dispatching has received intensive attention in recent years because it can help develop various reasonable plans to schedule the power generation efficiency. But future data such as wind power output and power load would not be accurately predicted and the nonlinear nature involved in the complex multiobjective scheduling model; therefore, to achieve accurate solution to such complex problem is a very difficult task. This paper presents an interval programming model with 2-step optimization algorithm to solve multiobjective dispatching. Initially, we represented the future data into interval numbers and simplified the object function to a linear programming problem to search the feasible and preliminary solutions to construct the Pareto set. Then the simulated annealing method was used to search the optimal solution of initial model. Thorough experimental results suggest that the proposed method performed reasonably well in terms of both operating efficiency and precision. PMID:24895663

A multiobjective interval programming model for wind-hydrothermal power system dispatching using 2-step optimization algorithm.

PubMed

Ren, Kun; Jihong, Qu

2014-01-01

Wind-hydrothermal power system dispatching has received intensive attention in recent years because it can help develop various reasonable plans to schedule the power generation efficiency. But future data such as wind power output and power load would not be accurately predicted and the nonlinear nature involved in the complex multiobjective scheduling model; therefore, to achieve accurate solution to such complex problem is a very difficult task. This paper presents an interval programming model with 2-step optimization algorithm to solve multiobjective dispatching. Initially, we represented the future data into interval numbers and simplified the object function to a linear programming problem to search the feasible and preliminary solutions to construct the Pareto set. Then the simulated annealing method was used to search the optimal solution of initial model. Thorough experimental results suggest that the proposed method performed reasonably well in terms of both operating efficiency and precision.

Understanding the determinants of volatility clustering in terms of stationary Markovian processes

NASA Astrophysics Data System (ADS)

Miccichè, S.

2016-11-01

Volatility is a key variable in the modeling of financial markets. The most striking feature of volatility is that it is a long-range correlated stochastic variable, i.e. its autocorrelation function decays like a power-law τ-β for large time lags. In the present work we investigate the determinants of such feature, starting from the empirical observation that the exponent β of a certain stock's volatility is a linear function of the average correlation of such stock's volatility with all other volatilities. We propose a simple approach consisting in diagonalizing the cross-correlation matrix of volatilities and investigating whether or not the diagonalized volatilities still keep some of the original volatility stylized facts. As a result, the diagonalized volatilities result to share with the original volatilities either the power-law decay of the probability density function and the power-law decay of the autocorrelation function. This would indicate that volatility clustering is already present in the diagonalized un-correlated volatilities. We therefore present a parsimonious univariate model based on a non-linear Langevin equation that well reproduces these two stylized facts of volatility. The model helps us in understanding that the main source of volatility clustering, once volatilities have been diagonalized, is that the economic forces driving volatility can be modeled in terms of a Smoluchowski potential with logarithmic tails.

A theoretical study on the impact of particle scattering on the channel characteristics of underwater optical communication system

NASA Astrophysics Data System (ADS)

Sahu, Sanjay Kumar; Shanmugam, Palanisamy

2018-02-01

Scattering by water molecules and particulate matters determines the path and distance of photon propagation in underwater medium. Consequently, photon angle of scattering (given by scattering phase function) requires to be considered in addition to the extinction coefficient of the aquatic medium governed by the absorption and scattering coefficients in channel characterization for an underwater wireless optical communication (UWOC) system. This study focuses on analyzing the received signal power and impulse response of UWOC channel based on Monte-Carlo simulations for different water types, link distances, link geometries and transceiver parameters. A newly developed scattering phase function (referred to as SS phase function), which represents the real water types more accurately like the Petzold phase function, is considered for quantification of the channel characteristics along with the effects of absorption and scattering coefficients. A comparison between the results simulated using various phase function models and the experimental measurements of Petzold revealed that the SS phase function model predicts values closely matching with the actual values of the Petzold's phase function, which further establishes the importance of using a correct scattering phase function model while estimating the channel capacity of UWOC system in terms of the received power and channel impulse response. Results further demonstrate a great advantage of considering the nonzero probability of receiving scattered photons in estimating channel capacity rather than considering the reception of only ballistic photons as in Beer's Law, which severely underestimates the received power and affects the range of communication especially in the scattering water column. The received power computed based on the Monte-Carlo method by considering the receiver aperture sizes and field of views in different water types are further analyzed and discussed. These results are essential for evaluating the underwater link budget and constructing different system and design parameters for an UWOC system.

Power Plant Model Validation Tool

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

The PPMV is used to validate generator model using disturbance recordings. The PPMV tool contains a collection of power plant models and model validation studies, as well as disturbance recordings from a number of historic grid events. The user can import data from a new disturbance into the database, which converts PMU and SCADA data into GE PSLF format, and then run the tool to validate (or invalidate) the model for a specific power plant against its actual performance. The PNNL PPMV tool enables the automation of the process of power plant model validation using disturbance recordings. The tool usesmore » PMU and SCADA measurements as input information. The tool automatically adjusts all required EPCL scripts and interacts with GE PSLF in the batch mode. The main tool features includes: The tool interacts with GE PSLF; The tool uses GE PSLF Play-In Function for generator model validation; Database of projects (model validation studies); Database of the historic events; Database of the power plant; The tool has advanced visualization capabilities; and The tool automatically generates reports« less

Reducing Cascading Failure Risk by Increasing Infrastructure Network Interdependence.

PubMed

Korkali, Mert; Veneman, Jason G; Tivnan, Brian F; Bagrow, James P; Hines, Paul D H

2017-03-20

Increased interconnection between critical infrastructure networks, such as electric power and communications systems, has important implications for infrastructure reliability and security. Others have shown that increased coupling between networks that are vulnerable to internetwork cascading failures can increase vulnerability. However, the mechanisms of cascading in these models differ from those in real systems and such models disregard new functions enabled by coupling, such as intelligent control during a cascade. This paper compares the robustness of simple topological network models to models that more accurately reflect the dynamics of cascading in a particular case of coupled infrastructures. First, we compare a topological contagion model to a power grid model. Second, we compare a percolation model of internetwork cascading to three models of interdependent power-communication systems. In both comparisons, the more detailed models suggest substantially different conclusions, relative to the simpler topological models. In all but the most extreme case, our model of a "smart" power network coupled to a communication system suggests that increased power-communication coupling decreases vulnerability, in contrast to the percolation model. Together, these results suggest that robustness can be enhanced by interconnecting networks with complementary capabilities if modes of internetwork failure propagation are constrained.

Reducing Cascading Failure Risk by Increasing Infrastructure Network Interdependence

NASA Astrophysics Data System (ADS)

Korkali, Mert; Veneman, Jason G.; Tivnan, Brian F.; Bagrow, James P.; Hines, Paul D. H.

2017-03-01

Increased interconnection between critical infrastructure networks, such as electric power and communications systems, has important implications for infrastructure reliability and security. Others have shown that increased coupling between networks that are vulnerable to internetwork cascading failures can increase vulnerability. However, the mechanisms of cascading in these models differ from those in real systems and such models disregard new functions enabled by coupling, such as intelligent control during a cascade. This paper compares the robustness of simple topological network models to models that more accurately reflect the dynamics of cascading in a particular case of coupled infrastructures. First, we compare a topological contagion model to a power grid model. Second, we compare a percolation model of internetwork cascading to three models of interdependent power-communication systems. In both comparisons, the more detailed models suggest substantially different conclusions, relative to the simpler topological models. In all but the most extreme case, our model of a “smart” power network coupled to a communication system suggests that increased power-communication coupling decreases vulnerability, in contrast to the percolation model. Together, these results suggest that robustness can be enhanced by interconnecting networks with complementary capabilities if modes of internetwork failure propagation are constrained.

Reducing Cascading Failure Risk by Increasing Infrastructure Network Interdependence

PubMed Central

Korkali, Mert; Veneman, Jason G.; Tivnan, Brian F.; Bagrow, James P.; Hines, Paul D. H.

2017-01-01

Increased interconnection between critical infrastructure networks, such as electric power and communications systems, has important implications for infrastructure reliability and security. Others have shown that increased coupling between networks that are vulnerable to internetwork cascading failures can increase vulnerability. However, the mechanisms of cascading in these models differ from those in real systems and such models disregard new functions enabled by coupling, such as intelligent control during a cascade. This paper compares the robustness of simple topological network models to models that more accurately reflect the dynamics of cascading in a particular case of coupled infrastructures. First, we compare a topological contagion model to a power grid model. Second, we compare a percolation model of internetwork cascading to three models of interdependent power-communication systems. In both comparisons, the more detailed models suggest substantially different conclusions, relative to the simpler topological models. In all but the most extreme case, our model of a “smart” power network coupled to a communication system suggests that increased power-communication coupling decreases vulnerability, in contrast to the percolation model. Together, these results suggest that robustness can be enhanced by interconnecting networks with complementary capabilities if modes of internetwork failure propagation are constrained. PMID:28317835

The correlation function for density perturbations in an expanding universe. IV - The evolution of the correlation function. [galaxy distribution

NASA Technical Reports Server (NTRS)

Mcclelland, J.; Silk, J.

1979-01-01

The evolution of the two-point correlation function for the large-scale distribution of galaxies in an expanding universe is studied on the assumption that the perturbation densities lie in a Gaussian distribution centered on any given mass scale. The perturbations are evolved according to the Friedmann equation, and the correlation function for the resulting distribution of perturbations at the present epoch is calculated. It is found that: (1) the computed correlation function gives a satisfactory fit to the observed function in cosmological models with a density parameter (Omega) of approximately unity, provided that a certain free parameter is suitably adjusted; (2) the power-law slope in the nonlinear regime reflects the initial fluctuation spectrum, provided that the density profile of individual perturbations declines more rapidly than the -2.4 power of distance; and (3) both positive and negative contributions to the correlation function are predicted for cosmological models with Omega less than unity.

A Hierarchical Modeling for Reactive Power Optimization With Joint Transmission and Distribution Networks by Curve Fitting

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

Ding, Tao; Li, Cheng; Huang, Can

Here, in order to solve the reactive power optimization with joint transmission and distribution networks, a hierarchical modeling method is proposed in this paper. It allows the reactive power optimization of transmission and distribution networks to be performed separately, leading to a master–slave structure and improves traditional centralized modeling methods by alleviating the big data problem in a control center. Specifically, the transmission-distribution-network coordination issue of the hierarchical modeling method is investigated. First, a curve-fitting approach is developed to provide a cost function of the slave model for the master model, which reflects the impacts of each slave model. Second,more » the transmission and distribution networks are decoupled at feeder buses, and all the distribution networks are coordinated by the master reactive power optimization model to achieve the global optimality. Finally, numerical results on two test systems verify the effectiveness of the proposed hierarchical modeling and curve-fitting methods.« less

A Hierarchical Modeling for Reactive Power Optimization With Joint Transmission and Distribution Networks by Curve Fitting

DOE PAGES

Ding, Tao; Li, Cheng; Huang, Can; ...

2017-01-09

Here, in order to solve the reactive power optimization with joint transmission and distribution networks, a hierarchical modeling method is proposed in this paper. It allows the reactive power optimization of transmission and distribution networks to be performed separately, leading to a master–slave structure and improves traditional centralized modeling methods by alleviating the big data problem in a control center. Specifically, the transmission-distribution-network coordination issue of the hierarchical modeling method is investigated. First, a curve-fitting approach is developed to provide a cost function of the slave model for the master model, which reflects the impacts of each slave model. Second,more » the transmission and distribution networks are decoupled at feeder buses, and all the distribution networks are coordinated by the master reactive power optimization model to achieve the global optimality. Finally, numerical results on two test systems verify the effectiveness of the proposed hierarchical modeling and curve-fitting methods.« less

Essays in market power mitigation and supply function equilibrium

NASA Astrophysics Data System (ADS)

Subramainam, Thiagarajah Natchie

Market power mitigation has been an integral part of wholesale electricity markets since deregulation. In wholesale electricity markets, different regions in the US take different approaches to regulating market power. While the exercise of market power has received considerable attention in the literature, the issue of market power mitigation has attracted scant attention. In the first chapter, I examine the market power mitigation rules used in New York ISO (Independent System Operator) and California ISO (CAISO) with respect to day-ahead and real-time energy markets. I test whether markups associated with New York in-city generators would be lower with an alternative approach to mitigation, the CAISO approach. Results indicate the difference in markups between these two mitigation rules is driven by the shape of residual demand curves for suppliers. Analysis of residual demand curves faced by New York in-city suppliers show similar markups under both mitigation rules when no one supplier is necessary to meet the demand (i.e., when no supplier is pivotal). However, when some supplier is crucial for the market to clear, the mitigation rule adopted by the NYISO consistently leads to higher markups than would the CAISO rule. This result suggest that market power episodes in New York is confined to periods where some supplier is pivotal. As a result, I find that applying the CAISOs' mitigation rules to the New York market could lower wholesale electricity prices by 18%. The second chapter of my dissertation focuses on supply function equilibrium. In power markets, suppliers submit offer curves in auctions, indicating their willingness to supply at different price levels. Although firms are allowed to submit different offer curves for different time periods, surprisingly many firms stick to a single offer curve for the entire day. This essentially means that firms are submitting a single offer curve for multiple demand realizations. A suitable framework to analyze such oligopolistic competition between power market suppliers is supply function equilibrium models. Using detailed bidding data, I develop equilibrium in supply functions by restricting supplier offers to a class of supply functions. By collating equilibrium supply functions corresponding to different realizations of demand, I obtain a single optimal supply function for the entire day. Then I compare the resulting supply function with actual day-ahead offers in New York. In addition to supply function equilibrium, I also develop a conservative bidding approach in which each firm assumes that rivals bid at marginal costs. Results show that the supply functions derived from equilibrium bidding model in this paper is not consistent with actual bidding in New York. This result is mainly driven by the class of supply functions used in this study to generate the equilibrium. Further, actual offers do not resemble offers generated by the conservative bidding algorithm.

Population patterns in World’s administrative units

PubMed Central

Miramontes, Pedro; Cocho, Germinal

2017-01-01

Whereas there has been an extended discussion concerning city population distribution, little has been said about that of administrative divisions. In this work, we investigate the population distribution of second-level administrative units of 150 countries and territories and propose the discrete generalized beta distribution (DGBD) rank-size function to describe the data. After testing the balance between the goodness of fit and number of parameters of this function compared with a power law, which is the most common model for city population, the DGBD is a good statistical model for 96% of our datasets and preferred over a power law in almost every case. Moreover, the DGBD is preferred over a power law for fitting country population data, which can be seen as the zeroth-level administrative unit. We present a computational toy model to simulate the formation of administrative divisions in one dimension and give numerical evidence that the DGBD arises from a particular case of this model. This model, along with the fitting of the DGBD, proves adequate in reproducing and describing local unit evolution and its effect on the population distribution. PMID:28791153

Neutronic design studies of a conceptual DCLL fusion reactor for a DEMO and a commercial power plant

NASA Astrophysics Data System (ADS)

Palermo, I.; Veredas, G.; Gómez-Ros, J. M.; Sanz, J.; Ibarra, A.

2016-01-01

Neutronic analyses or, more widely, nuclear analyses have been performed for the development of a dual-coolant He/LiPb (DCLL) conceptual design reactor. A detailed three-dimensional (3D) model has been examined and optimized. The design is based on the plasma parameters and functional materials of the power plant conceptual studies (PPCS) model C. The initial radial-build for the detailed model has been determined according to the dimensions established in a previous work on an equivalent simplified homogenized reactor model. For optimization purposes, the initial specifications established over the simplified model have been refined on the detailed 3D design, modifying material and dimension of breeding blanket, shield and vacuum vessel in order to fulfil the priority requirements of a fusion reactor in terms of the fundamental neutronic responses. Tritium breeding ratio, energy multiplication factor, radiation limits in the TF coils, helium production and displacements per atom (dpa) have been calculated in order to demonstrate the functionality and viability of the reactor design in guaranteeing tritium self-sufficiency, power efficiency, plasma confinement, and re-weldability and structural integrity of the components. The paper describes the neutronic design improvements of the DCLL reactor, obtaining results for both DEMO and power plant operational scenarios.

Incorporation of stochastic engineering models as prior information in Bayesian medical device trials.

PubMed

Haddad, Tarek; Himes, Adam; Thompson, Laura; Irony, Telba; Nair, Rajesh

2017-01-01

Evaluation of medical devices via clinical trial is often a necessary step in the process of bringing a new product to market. In recent years, device manufacturers are increasingly using stochastic engineering models during the product development process. These models have the capability to simulate virtual patient outcomes. This article presents a novel method based on the power prior for augmenting a clinical trial using virtual patient data. To properly inform clinical evaluation, the virtual patient model must simulate the clinical outcome of interest, incorporating patient variability, as well as the uncertainty in the engineering model and in its input parameters. The number of virtual patients is controlled by a discount function which uses the similarity between modeled and observed data. This method is illustrated by a case study of cardiac lead fracture. Different discount functions are used to cover a wide range of scenarios in which the type I error rates and power vary for the same number of enrolled patients. Incorporation of engineering models as prior knowledge in a Bayesian clinical trial design can provide benefits of decreased sample size and trial length while still controlling type I error rate and power.

Modeling the expenditure and reconstitution of work capacity above critical power.

PubMed

Skiba, Philip Friere; Chidnok, Weerapong; Vanhatalo, Anni; Jones, Andrew M

2012-08-01

The critical power (CP) model includes two constants: the CP and the W' [P = (W' / t) + CP]. The W' is the finite work capacity available above CP. Power output above CP results in depletion of the W' complete depletion of the W' results in exhaustion. Monitoring the W' may be valuable to athletes during training and competition. Our purpose was to develop a function describing the dynamic state of the W' during intermittent exercise. After determination of V˙O(2max), CP, and W', seven subjects completed four separate exercise tests on a cycle ergometer on different days. Each protocol comprised a set of intervals: 60 s at a severe power output, followed by 30-s recovery at a lower prescribed power output. The intervals were repeated until exhaustion. These data were entered into a continuous equation predicting balance of W' remaining, assuming exponential reconstitution of the W'. The time constant was varied by an iterative process until the remaining modeled W' = 0 at the point of exhaustion. The time constants of W' recharge were negatively correlated with the difference between sub-CP recovery power and CP. The relationship was best fit by an exponential (r = 0.77). The model-predicted W' balance correlated with the temporal course of the rise in V˙O(2) (r = 0.82-0.96). The model accurately predicted exhaustion of the W' in a competitive cyclist during a road race. We have developed a function to track the dynamic state of the W' during intermittent exercise. This may have important implications for the planning and real-time monitoring of athletic performance.

A new smooth-k space filter approach to calculate halo abundances

NASA Astrophysics Data System (ADS)

Leo, Matteo; Baugh, Carlton M.; Li, Baojiu; Pascoli, Silvia

2018-04-01

We propose a new filter, a smooth-k space filter, to use in the Press-Schechter approach to model the dark matter halo mass function which overcomes shortcomings of other filters. We test this against the mass function measured in N-body simulations. We find that the commonly used sharp-k filter fails to reproduce the behaviour of the halo mass function at low masses measured from simulations of models with a sharp truncation in the linear power spectrum. We show that the predictions with our new filter agree with the simulation results over a wider range of halo masses for both damped and undamped power spectra than is the case with the sharp-k and real-space top-hat filters.

Electrical Transport Properties of Liquid Sn-Sb Binary Alloys

NASA Astrophysics Data System (ADS)

Thakore, B. Y.; Suthar, P. H.; Khambholja, S. G.; Jani, A. R.

2010-06-01

The study of electrical transport properties viz. electrical resistivity, thermo electrical power and thermal conductivity of liquid Sn-Sb binary alloys have been made by our well recognized single parametric model potential. In the present work, screening functions due to Hartree, Taylor, Ichimaru et al.. Farid et al.. and Sarkar et al.. have been employed to incorporate the exchange and correlation effects. The liquid alloy is studied as a function of its composition at temperature 823 K according to the Faber-Ziman model. Further, thermoelectric power and thermal conductivity have been predicted. The values of electrical resistivity of binary alloys computed with Ichimaru et al. and Farid et al.. screening function are in good agreement with the experimental data.

A class of simple bouncing and late-time accelerating cosmologies in f(R) gravity

NASA Astrophysics Data System (ADS)

Kuiroukidis, A.

We consider the field equations for a flat FRW cosmological model, given by Eq. (??), in an a priori generic f(R) gravity model and cast them into a, completely normalized and dimensionless, system of ODEs for the scale factor and the function f(R), with respect to the scalar curvature R. It is shown that under reasonable assumptions, namely for power-law functional form for the f(R) gravity model, one can produce simple analytical and numerical solutions describing bouncing cosmological models where in addition there are late-time accelerating. The power-law form for the f(R) gravity model is typically considered in the literature as the most concrete, reasonable, practical and viable assumption [see S. D. Odintsov and V. K. Oikonomou, Phys. Rev. D 90 (2014) 124083, arXiv:1410.8183 [gr-qc

Augmented twin-nonlinear two-box behavioral models for multicarrier LTE power amplifiers.

PubMed

Hammi, Oualid

2014-01-01

A novel class of behavioral models is proposed for LTE-driven Doherty power amplifiers with strong memory effects. The proposed models, labeled augmented twin-nonlinear two-box models, are built by cascading a highly nonlinear memoryless function with a mildly nonlinear memory polynomial with cross terms. Experimental validation on gallium nitride based Doherty power amplifiers illustrates the accuracy enhancement and complexity reduction achieved by the proposed models. When strong memory effects are observed, the augmented twin-nonlinear two-box models can improve the normalized mean square error by up to 3 dB for the same number of coefficients when compared to state-of-the-art twin-nonlinear two-box models. Furthermore, the augmented twin-nonlinear two-box models lead to the same performance as previously reported twin-nonlinear two-box models while requiring up to 80% less coefficients.

Dynamical analysis for a scalar-tensor model with kinetic and nonminimal couplings

NASA Astrophysics Data System (ADS)

Granda, L. N.; Jimenez, D. F.

We study the autonomous system for a scalar-tensor model of dark energy with nonminimal coupling to curvature and nonminimal kinetic coupling to the Einstein tensor. The critical points describe important stable asymptotic scenarios including quintessence, phantom and de Sitter attractor solutions. Two functional forms for the coupling functions and the scalar potential were considered: power-law and exponential functions of the scalar field. For power-law couplings, the restrictions on stable quintessence and phantom solutions lead to asymptotic freedom regime for the gravitational interaction. For the exponential functions, the stable quintessence, phantom or de Sitter solutions allow asymptotic behaviors where the effective Newtonian coupling can reach either the asymptotic freedom regime or constant value. The phantom solutions could be realized without appealing to ghost degrees of freedom. Transient inflationary and radiation dominated phases can also be described.

Statistical properties of a filtered Poisson process with additive random noise: distributions, correlations and moment estimation

NASA Astrophysics Data System (ADS)

Theodorsen, A.; E Garcia, O.; Rypdal, M.

2017-05-01

Filtered Poisson processes are often used as reference models for intermittent fluctuations in physical systems. Such a process is here extended by adding a noise term, either as a purely additive term to the process or as a dynamical term in a stochastic differential equation. The lowest order moments, probability density function, auto-correlation function and power spectral density are derived and used to identify and compare the effects of the two different noise terms. Monte-Carlo studies of synthetic time series are used to investigate the accuracy of model parameter estimation and to identify methods for distinguishing the noise types. It is shown that the probability density function and the three lowest order moments provide accurate estimations of the model parameters, but are unable to separate the noise types. The auto-correlation function and the power spectral density also provide methods for estimating the model parameters, as well as being capable of identifying the noise type. The number of times the signal crosses a prescribed threshold level in the positive direction also promises to be able to differentiate the noise type.

Statistical power as a function of Cronbach alpha of instrument questionnaire items.

PubMed

Heo, Moonseong; Kim, Namhee; Faith, Myles S

2015-10-14

In countless number of clinical trials, measurements of outcomes rely on instrument questionnaire items which however often suffer measurement error problems which in turn affect statistical power of study designs. The Cronbach alpha or coefficient alpha, here denoted by C(α), can be used as a measure of internal consistency of parallel instrument items that are developed to measure a target unidimensional outcome construct. Scale score for the target construct is often represented by the sum of the item scores. However, power functions based on C(α) have been lacking for various study designs. We formulate a statistical model for parallel items to derive power functions as a function of C(α) under several study designs. To this end, we assume fixed true score variance assumption as opposed to usual fixed total variance assumption. That assumption is critical and practically relevant to show that smaller measurement errors are inversely associated with higher inter-item correlations, and thus that greater C(α) is associated with greater statistical power. We compare the derived theoretical statistical power with empirical power obtained through Monte Carlo simulations for the following comparisons: one-sample comparison of pre- and post-treatment mean differences, two-sample comparison of pre-post mean differences between groups, and two-sample comparison of mean differences between groups. It is shown that C(α) is the same as a test-retest correlation of the scale scores of parallel items, which enables testing significance of C(α). Closed-form power functions and samples size determination formulas are derived in terms of C(α), for all of the aforementioned comparisons. Power functions are shown to be an increasing function of C(α), regardless of comparison of interest. The derived power functions are well validated by simulation studies that show that the magnitudes of theoretical power are virtually identical to those of the empirical power. Regardless of research designs or settings, in order to increase statistical power, development and use of instruments with greater C(α), or equivalently with greater inter-item correlations, is crucial for trials that intend to use questionnaire items for measuring research outcomes. Further development of the power functions for binary or ordinal item scores and under more general item correlation strutures reflecting more real world situations would be a valuable future study.

An objective function exploiting suboptimal solutions in metabolic networks

PubMed Central

2013-01-01

Background Flux Balance Analysis is a theoretically elegant, computationally efficient, genome-scale approach to predicting biochemical reaction fluxes. Yet FBA models exhibit persistent mathematical degeneracy that generally limits their predictive power. Results We propose a novel objective function for cellular metabolism that accounts for and exploits degeneracy in the metabolic network to improve flux predictions. In our model, regulation drives metabolism toward a region of flux space that allows nearly optimal growth. Metabolic mutants deviate minimally from this region, a function represented mathematically as a convex cone. Near-optimal flux configurations within this region are considered equally plausible and not subject to further optimizing regulation. Consistent with relaxed regulation near optimality, we find that the size of the near-optimal region predicts flux variability under experimental perturbation. Conclusion Accounting for suboptimal solutions can improve the predictive power of metabolic FBA models. Because fluctuations of enzyme and metabolite levels are inevitable, tolerance for suboptimality may support a functionally robust metabolic network. PMID:24088221

Brayton Power Conversion System Parametric Design Modelling for Nuclear Electric Propulsion

NASA Technical Reports Server (NTRS)

Ashe, Thomas L.; Otting, William D.

1993-01-01

The parametrically based closed Brayton cycle (CBC) computer design model was developed for inclusion into the NASA LeRC overall Nuclear Electric Propulsion (NEP) end-to-end systems model. The code is intended to provide greater depth to the NEP system modeling which is required to more accurately predict the impact of specific technology on system performance. The CBC model is parametrically based to allow for conducting detailed optimization studies and to provide for easy integration into an overall optimizer driver routine. The power conversion model includes the modeling of the turbines, alternators, compressors, ducting, and heat exchangers (hot-side heat exchanger and recuperator). The code predicts performance to significant detail. The system characteristics determined include estimates of mass, efficiency, and the characteristic dimensions of the major power conversion system components. These characteristics are parametrically modeled as a function of input parameters such as the aerodynamic configuration (axial or radial), turbine inlet temperature, cycle temperature ratio, power level, lifetime, materials, and redundancy.

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.

SNPSAM - Space Nuclear Power System Analysis Model

NASA Astrophysics Data System (ADS)

El-Genk, Mohamed S.; Seo, Jong T.

The current version of SNPSAM is described, and the results of the integrated thermoeletric SP-100 system performance studies using SNPSAM are reported. The electric power output, conversion efficiency, coolant temperatures, and specific pumping power of the system are calculated as functions of the reactor thermal power and the liquid metal coolant type (Li or NaK-78) during steady state operation. The transient behavior of the system is also discussed.

Economic modeling and energy policy planning. [technology transfer, market research

NASA Technical Reports Server (NTRS)

Thompson, R. G.; Schwartz, A., Jr.; Lievano, R. J.; Stone, J. C.

1974-01-01

A structural economic model is presented for estimating the demand functions for natural gas and crude oil in industry and in steam electric power generation. Extensions of the model to other commodities are indicated.

Reflection and emission models for deserts derived from Nimbus-7 ERB scanner measurements

NASA Technical Reports Server (NTRS)

Staylor, W. F.; Suttles, J. T.

1986-01-01

Broadband shortwave and longwave radiance measurements obtained from the Nimbus-7 Earth Radiation Budget scanner were used to develop reflectance and emittance models for the Sahara-Arabian, Gibson, and Saudi Deserts. The models were established by fitting the satellite measurements to analytic functions. For the shortwave, the model function is based on an approximate solution to the radiative transfer equation. The bidirectional-reflectance function was obtained from a single-scattering approximation with a Rayleigh-like phase function. The directional-reflectance model followed from integration of the bidirectional model and is a function of the sum and product of cosine solar and viewing zenith angles, thus satisfying reciprocity between these angles. The emittance model was based on a simple power-law of cosine viewing zenith angle.

Gene-Based Association Analysis for Censored Traits Via Fixed Effect Functional Regressions.

PubMed

Fan, Ruzong; Wang, Yifan; Yan, Qi; Ding, Ying; Weeks, Daniel E; Lu, Zhaohui; Ren, Haobo; Cook, Richard J; Xiong, Momiao; Swaroop, Anand; Chew, Emily Y; Chen, Wei

2016-02-01

Genetic studies of survival outcomes have been proposed and conducted recently, but statistical methods for identifying genetic variants that affect disease progression are rarely developed. Motivated by our ongoing real studies, here we develop Cox proportional hazard models using functional regression (FR) to perform gene-based association analysis of survival traits while adjusting for covariates. The proposed Cox models are fixed effect models where the genetic effects of multiple genetic variants are assumed to be fixed. We introduce likelihood ratio test (LRT) statistics to test for associations between the survival traits and multiple genetic variants in a genetic region. Extensive simulation studies demonstrate that the proposed Cox RF LRT statistics have well-controlled type I error rates. To evaluate power, we compare the Cox FR LRT with the previously developed burden test (BT) in a Cox model and sequence kernel association test (SKAT), which is based on mixed effect Cox models. The Cox FR LRT statistics have higher power than or similar power as Cox SKAT LRT except when 50%/50% causal variants had negative/positive effects and all causal variants are rare. In addition, the Cox FR LRT statistics have higher power than Cox BT LRT. The models and related test statistics can be useful in the whole genome and whole exome association studies. An age-related macular degeneration dataset was analyzed as an example. © 2016 WILEY PERIODICALS, INC.

Gene-based Association Analysis for Censored Traits Via Fixed Effect Functional Regressions

PubMed Central

Fan, Ruzong; Wang, Yifan; Yan, Qi; Ding, Ying; Weeks, Daniel E.; Lu, Zhaohui; Ren, Haobo; Cook, Richard J; Xiong, Momiao; Swaroop, Anand; Chew, Emily Y.; Chen, Wei

2015-01-01

Summary Genetic studies of survival outcomes have been proposed and conducted recently, but statistical methods for identifying genetic variants that affect disease progression are rarely developed. Motivated by our ongoing real studies, we develop here Cox proportional hazard models using functional regression (FR) to perform gene-based association analysis of survival traits while adjusting for covariates. The proposed Cox models are fixed effect models where the genetic effects of multiple genetic variants are assumed to be fixed. We introduce likelihood ratio test (LRT) statistics to test for associations between the survival traits and multiple genetic variants in a genetic region. Extensive simulation studies demonstrate that the proposed Cox RF LRT statistics have well-controlled type I error rates. To evaluate power, we compare the Cox FR LRT with the previously developed burden test (BT) in a Cox model and sequence kernel association test (SKAT) which is based on mixed effect Cox models. The Cox FR LRT statistics have higher power than or similar power as Cox SKAT LRT except when 50%/50% causal variants had negative/positive effects and all causal variants are rare. In addition, the Cox FR LRT statistics have higher power than Cox BT LRT. The models and related test statistics can be useful in the whole genome and whole exome association studies. An age-related macular degeneration dataset was analyzed as an example. PMID:26782979

76 FR 35736 - Special Conditions: Gulfstream Aerospace LP (GALP) Model G250 Airplane Automatic Power Reserve...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-06-20

... novel or unusual design feature associated with go-around performance credit for use of Automatic Power... docket in person, go to the address in the ADDRESSES section of this preamble between 7:30 a.m. and 4 p.m... proposing to use the APR function of the Model G250 airplane during go-around and is requesting approach...

Effects of Long Period Ocean Tides on the Earth's Rotation

NASA Technical Reports Server (NTRS)

Gross, Richard S.; Chao, Ben F.; Desai, Shailen D.

1996-01-01

The spectra of polar motion excitation functions exhibit enhanced power in the fortnightly tidal band. This enhanced power is attributed to ocean tidal excitation. Ocean tide models predict polar motion excitation effects that differ with each other, and with observations, by factors as large as 2-3. There is a need for inproved models for the effect of long-period ocean tides on Earth's rotation.

Reactive Power Compensation Method Considering Minimum Effective Reactive Power Reserve

NASA Astrophysics Data System (ADS)

Gong, Yiyu; Zhang, Kai; Pu, Zhang; Li, Xuenan; Zuo, Xianghong; Zhen, Jiao; Sudan, Teng

2017-05-01

According to the calculation model of minimum generator reactive power reserve of power system voltage stability under the premise of the guarantee, the reactive power management system with reactive power compensation combined generator, the formation of a multi-objective optimization problem, propose a reactive power reserve is considered the minimum generator reactive power compensation optimization method. This method through the improvement of the objective function and constraint conditions, when the system load growth, relying solely on reactive power generation system can not meet the requirement of safe operation, increase the reactive power reserve to solve the problem of minimum generator reactive power compensation in the case of load node.

Coupled Effects of non-Newtonian Rheology and Aperture Variability on Flow in a Single Fracture

NASA Astrophysics Data System (ADS)

Di Federico, V.; Felisa, G.; Lauriola, I.; Longo, S.

2017-12-01

Modeling of non-Newtonian flow in fractured media is essential in hydraulic fracturing and drilling operations, EOR, environmental remediation, and to understand magma intrusions. An important step in the modeling effort is a detailed understanding of flow in a single fracture, as the fracture aperture is spatially variable. A large bibliography exists on Newtonian and non-Newtonian flow in variable aperture fractures. Ultimately, stochastic or deterministic modeling leads to the flowrate under a given pressure gradient as a function of the parameters describing the aperture variability and the fluid rheology. Typically, analytical or numerical studies are performed adopting a power-law (Oswald-de Waele) model. Yet the power-law model, routinely used e.g. for hydro-fracturing modeling, does not characterize real fluids at low and high shear rates. A more appropriate rheological model is provided by e.g. the four-parameter Carreau constitutive equation, which is in turn approximated by the more tractable truncated power-law model. Moreover, fluids of interest may exhibit yield stress, which requires the Bingham or Herschel-Bulkely model. This study employs different rheological models in the context of flow in variable aperture fractures, with the aim of understanding the coupled effect of rheology and aperture spatial variability with a simplified model. The aperture variation, modeled within a stochastic or deterministic framework, is taken to be one-dimensional and i) perpendicular; ii) parallel to the flow direction; for stochastic modeling, the influence of different distribution functions is examined. Results for the different rheological models are compared with those obtained for the pure power-law. The adoption of the latter model leads to overestimation of the flowrate, more so for large aperture variability. The presence of yield stress also induces significant changes in the resulting flowrate for assigned external pressure gradient.

Power law versus exponential state transition dynamics: application to sleep-wake architecture.

PubMed

Chu-Shore, Jesse; Westover, M Brandon; Bianchi, Matt T

2010-12-02

Despite the common experience that interrupted sleep has a negative impact on waking function, the features of human sleep-wake architecture that best distinguish sleep continuity versus fragmentation remain elusive. In this regard, there is growing interest in characterizing sleep architecture using models of the temporal dynamics of sleep-wake stage transitions. In humans and other mammals, the state transitions defining sleep and wake bout durations have been described with exponential and power law models, respectively. However, sleep-wake stage distributions are often complex, and distinguishing between exponential and power law processes is not always straightforward. Although mono-exponential distributions are distinct from power law distributions, multi-exponential distributions may in fact resemble power laws by appearing linear on a log-log plot. To characterize the parameters that may allow these distributions to mimic one another, we systematically fitted multi-exponential-generated distributions with a power law model, and power law-generated distributions with multi-exponential models. We used the Kolmogorov-Smirnov method to investigate goodness of fit for the "incorrect" model over a range of parameters. The "zone of mimicry" of parameters that increased the risk of mistakenly accepting power law fitting resembled empiric time constants obtained in human sleep and wake bout distributions. Recognizing this uncertainty in model distinction impacts interpretation of transition dynamics (self-organizing versus probabilistic), and the generation of predictive models for clinical classification of normal and pathological sleep architecture.

Probability density functions of power-in-bucket and power-in-fiber for an infrared laser beam propagating in the maritime environment.

PubMed

Nelson, Charles; Avramov-Zamurovic, Svetlana; Korotkova, Olga; Malek-Madani, Reza; Sova, Raymond; Davidson, Frederic

2013-11-01

Irradiance fluctuations of an infrared laser beam from a shore-to-ship data link ranging from 5.1 to 17.8 km are compared to lognormal (LN), gamma-gamma (GG) with aperture averaging, and gamma-Laguerre (GL) distributions. From our data analysis, the LN and GG probability density function (PDF) models were generally in good agreement in near-weak to moderate fluctuations. This was also true in moderate to strong fluctuations when the spatial coherence radius was smaller than the detector aperture size, with the exception of the 2.54 cm power-in-bucket (PIB) where the LN PDF model fit best. For moderate to strong fluctuations, the GG PDF model tended to outperform the LN PDF model when the spatial coherence radius was greater than the detector aperture size. Additionally, the GL PDF model had the best or next to best overall fit in all cases with the exception of the 2.54 cm PIB where the scintillation index was highest. The GL PDF model also appears to be robust for off-of-beam center laser beam applications.

Implementation of a Sage-Based Stirling Model Into a System-Level Numerical Model of the Fission Power System Technology Demonstration Unit

NASA Technical Reports Server (NTRS)

Briggs, Maxwell H.

2011-01-01

The Fission Power System (FPS) project is developing a Technology Demonstration Unit (TDU) to verify the performance and functionality of a subscale version of the FPS reference concept in a relevant environment, and to verify component and system models. As hardware is developed for the TDU, component and system models must be refined to include the details of specific component designs. This paper describes the development of a Sage-based pseudo-steady-state Stirling convertor model and its implementation into a system-level model of the TDU.

Performance of wind turbines in a turbulent atmosphere

NASA Technical Reports Server (NTRS)

Sundar, R. M.; Sullivan, J. P.

1981-01-01

The effect of atmospheric turbulence on the power fluctuations of large wind turbines was studied. The significance of spatial non-uniformities of the wind is emphasized. The turbulent wind with correlation in time and space is simulated on the computer by Shinozukas method. The wind turbulence is modelled according to the Davenport spectrum with an exponential spatial correlation function. The rotor aerodynamics is modelled by simple blade element theory. Comparison of the spectrum of power output signal between 1-D and 3-D turbulence, shows the significant power fluctuations centered around the blade passage frequency.

Application of the MNA design method to a nonlinear turbofan engine. [multivariable Nyquist array method

NASA Technical Reports Server (NTRS)

Leininger, G. G.

1981-01-01

Using nonlinear digital simulation as a representative model of the dynamic operation of the QCSEE turbofan engine, a feedback control system is designed by variable frequency design techniques. Transfer functions are generated for each of five power level settings covering the range of operation from approach power to full throttle (62.5% to 100% full power). These transfer functions are then used by an interactive control system design synthesis program to provide a closed loop feedback control using the multivariable Nyquist array and extensions to multivariable Bode diagrams and Nichols charts.

Probability density function evolution of power systems subject to stochastic variation of renewable energy

NASA Astrophysics Data System (ADS)

Wei, J. Q.; Cong, Y. C.; Xiao, M. Q.

2018-05-01

As renewable energies are increasingly integrated into power systems, there is increasing interest in stochastic analysis of power systems.Better techniques should be developed to account for the uncertainty caused by penetration of renewables and consequently analyse its impacts on stochastic stability of power systems. In this paper, the Stochastic Differential Equations (SDEs) are used to represent the evolutionary behaviour of the power systems. The stationary Probability Density Function (PDF) solution to SDEs modelling power systems excited by Gaussian white noise is analysed. Subjected to such random excitation, the Joint Probability Density Function (JPDF) solution to the phase angle and angular velocity is governed by the generalized Fokker-Planck-Kolmogorov (FPK) equation. To solve this equation, the numerical method is adopted. Special measure is taken such that the generalized FPK equation is satisfied in the average sense of integration with the assumed PDF. Both weak and strong intensities of the stochastic excitations are considered in a single machine infinite bus power system. The numerical analysis has the same result as the one given by the Monte Carlo simulation. Potential studies on stochastic behaviour of multi-machine power systems with random excitations are discussed at the end.

Linear mixed-effects models to describe individual tree crown width for China-fir in Fujian Province, southeast China.

PubMed

Hao, Xu; Yujun, Sun; Xinjie, Wang; Jin, Wang; Yao, Fu

2015-01-01

A multiple linear model was developed for individual tree crown width of Cunninghamia lanceolata (Lamb.) Hook in Fujian province, southeast China. Data were obtained from 55 sample plots of pure China-fir plantation stands. An Ordinary Linear Least Squares (OLS) regression was used to establish the crown width model. To adjust for correlations between observations from the same sample plots, we developed one level linear mixed-effects (LME) models based on the multiple linear model, which take into account the random effects of plots. The best random effects combinations for the LME models were determined by the Akaike's information criterion, the Bayesian information criterion and the -2logarithm likelihood. Heteroscedasticity was reduced by three residual variance functions: the power function, the exponential function and the constant plus power function. The spatial correlation was modeled by three correlation structures: the first-order autoregressive structure [AR(1)], a combination of first-order autoregressive and moving average structures [ARMA(1,1)], and the compound symmetry structure (CS). Then, the LME model was compared to the multiple linear model using the absolute mean residual (AMR), the root mean square error (RMSE), and the adjusted coefficient of determination (adj-R2). For individual tree crown width models, the one level LME model showed the best performance. An independent dataset was used to test the performance of the models and to demonstrate the advantage of calibrating LME models.

Guest Editorial High Performance Computing (HPC) Applications for a More Resilient and Efficient Power Grid

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

Huang, Zhenyu Henry; Tate, Zeb; Abhyankar, Shrirang

The power grid has been evolving over the last 120 years, but it is seeing more changes in this decade and next than it has seen over the past century. In particular, the widespread deployment of intermittent renewable generation, smart loads and devices, hierarchical and distributed control technologies, phasor measurement units, energy storage, and widespread usage of electric vehicles will require fundamental changes in methods and tools for the operation and planning of the power grid. The resulting new dynamic and stochastic behaviors will demand the inclusion of more complexity in modeling the power grid. Solving such complex models inmore » the traditional computing environment will be a major challenge. Along with the increasing complexity of power system models, the increasing complexity of smart grid data further adds to the prevailing challenges. In this environment, the myriad of smart sensors and meters in the power grid increase by multiple orders of magnitude, so do the volume and speed of the data. The information infrastructure will need to drastically change to support the exchange of enormous amounts of data as smart grid applications will need the capability to collect, assimilate, analyze and process the data, to meet real-time grid functions. High performance computing (HPC) holds the promise to enhance these functions, but it is a great resource that has not been fully explored and adopted for the power grid domain.« less

Direct mechanical torque sensor for model wind turbines

NASA Astrophysics Data System (ADS)

Kang, Hyung Suk; Meneveau, Charles

2010-10-01

A torque sensor is developed to measure the mechanical power extracted by model wind turbines. The torque is measured by mounting the model generator (a small dc motor) through ball bearings to the hub and by preventing its rotation by the deflection of a strain-gauge-instrumented plate. By multiplying the measured torque and rotor angular velocity, a direct measurement of the fluid mechanical power extracted from the flow is obtained. Such a measurement is more advantageous compared to measuring the electrical power generated by the model generator (dc motor), since the electrical power is largely affected by internal frictional, electric and magnetic losses. Calibration experiments are performed, and during testing, the torque sensor is mounted on a model wind turbine in a 3 rows × 3 columns array of wind turbines in a wind tunnel experiment. The resulting electrical and mechanical powers are quantified and compared over a range of applied loads, for three different incoming wind velocities. Also, the power coefficients are obtained as a function of the tip speed ratio. Significant differences between the electrical and mechanical powers are observed, which highlights the importance of using the direct mechanical power measurement for fluid dynamically meaningful results. A direct calibration with the measured current is also explored. The new torque sensor is expected to contribute to more accurate model wind tunnel tests which should provide added flexibility in model studies of the power that can be harvested from wind turbines and wind-turbine farms.

A simplified model to evaluate the effect of fluid rheology on non-Newtonian flow in variable aperture fractures

NASA Astrophysics Data System (ADS)

Felisa, Giada; Ciriello, Valentina; Longo, Sandro; Di Federico, Vittorio

2017-04-01

Modeling of non-Newtonian flow in fractured media is essential in hydraulic fracturing operations, largely used for optimal exploitation of oil, gas and thermal reservoirs. Complex fluids interact with pre-existing rock fractures also during drilling operations, enhanced oil recovery, environmental remediation, and other natural phenomena such as magma and sand intrusions, and mud volcanoes. A first step in the modeling effort is a detailed understanding of flow in a single fracture, as the fracture aperture is typically spatially variable. A large bibliography exists on Newtonian flow in single, variable aperture fractures. Ultimately, stochastic modeling of aperture variability at the single fracture scale leads to determination of the flowrate under a given pressure gradient as a function of the parameters describing the variability of the aperture field and the fluid rheological behaviour. From the flowrate, a flow, or 'hydraulic', aperture can then be derived. The equivalent flow aperture for non-Newtonian fluids of power-law nature in single, variable aperture fractures has been obtained in the past both for deterministic and stochastic variations. Detailed numerical modeling of power-law fluid flow in a variable aperture fracture demonstrated that pronounced channelization effects are associated to a nonlinear fluid rheology. The availability of an equivalent flow aperture as a function of the parameters describing the fluid rheology and the aperture variability is enticing, as it allows taking their interaction into account when modeling flow in fracture networks at a larger scale. A relevant issue in non-Newtonian fracture flow is the rheological nature of the fluid. The constitutive model routinely used for hydro-fracturing modeling is the simple, two-parameter power-law. Yet this model does not characterize real fluids at low and high shear rates, as it implies, for shear-thinning fluids, an apparent viscosity which becomes unbounded for zero shear rate and tends to zero for infinite shear rate. On the contrary, the four-parameter Carreau constitutive equation includes asymptotic values of the apparent viscosity at those limits; in turn, the Carreau rheological equation is well approximated by the more tractable truncated power-law model. Results for flow of such fluids between parallel walls are already available. This study extends the adoption of the truncated power-law model to variable aperture fractures, with the aim of understanding the joint influence of rheology and aperture spatial variability. The aperture variation, modeled within a stochastic or deterministic framework, is taken to be one-dimensional and perpendicular to the flow direction; for stochastic modeling, the influence of different distribution functions is examined. Results are then compared with those obtained for pure power-law fluids for different combinations of model parameters. It is seen that the adoption of the pure power law model leads to significant overestimation of the flowrate with respect to the truncated model, more so for large external pressure gradient and/or aperture variability.

Weighted functional linear regression models for gene-based association analysis.

PubMed

Belonogova, Nadezhda M; Svishcheva, Gulnara R; Wilson, James F; Campbell, Harry; Axenovich, Tatiana I

2018-01-01

Functional linear regression models are effectively used in gene-based association analysis of complex traits. These models combine information about individual genetic variants, taking into account their positions and reducing the influence of noise and/or observation errors. To increase the power of methods, where several differently informative components are combined, weights are introduced to give the advantage to more informative components. Allele-specific weights have been introduced to collapsing and kernel-based approaches to gene-based association analysis. Here we have for the first time introduced weights to functional linear regression models adapted for both independent and family samples. Using data simulated on the basis of GAW17 genotypes and weights defined by allele frequencies via the beta distribution, we demonstrated that type I errors correspond to declared values and that increasing the weights of causal variants allows the power of functional linear models to be increased. We applied the new method to real data on blood pressure from the ORCADES sample. Five of the six known genes with P < 0.1 in at least one analysis had lower P values with weighted models. Moreover, we found an association between diastolic blood pressure and the VMP1 gene (P = 8.18×10-6), when we used a weighted functional model. For this gene, the unweighted functional and weighted kernel-based models had P = 0.004 and 0.006, respectively. The new method has been implemented in the program package FREGAT, which is freely available at https://cran.r-project.org/web/packages/FREGAT/index.html.

Multiple scattering corrections to the Beer-Lambert law. 2: Detector with a variable field of view.

PubMed

Zardecki, A; Tam, W G

1982-07-01

The multiple scattering corrections to the Beer-Lambert law in the case of a detector with a variable field of view are analyzed. We introduce transmission functions relating the received radiant power to reference power levels relevant to two different experimental situations. In the first case, the transmission function relates the received power to a reference power level appropriate to a nonattenuating medium. In the second case, the reference power level is established by bringing the receiver to the close-up position with respect to the source. To examine the effect of the variation of the detector field of view the behavior of the gain factor is studied. Numerical results modeling the laser beam propagation in fog, cloud, and rain are presented.

Manual of phosphoric acid fuel cell power plant optimization model and computer program

NASA Technical Reports Server (NTRS)

Lu, C. Y.; Alkasab, K. A.

1984-01-01

An optimized cost and performance model for a phosphoric acid fuel cell power plant system was derived and developed into a modular FORTRAN computer code. Cost, energy, mass, and electrochemical analyses were combined to develop a mathematical model for optimizing the steam to methane ratio in the reformer, hydrogen utilization in the PAFC plates per stack. The nonlinear programming code, COMPUTE, was used to solve this model, in which the method of mixed penalty function combined with Hooke and Jeeves pattern search was chosen to evaluate this specific optimization problem.

Augmented Twin-Nonlinear Two-Box Behavioral Models for Multicarrier LTE Power Amplifiers

PubMed Central

2014-01-01

A novel class of behavioral models is proposed for LTE-driven Doherty power amplifiers with strong memory effects. The proposed models, labeled augmented twin-nonlinear two-box models, are built by cascading a highly nonlinear memoryless function with a mildly nonlinear memory polynomial with cross terms. Experimental validation on gallium nitride based Doherty power amplifiers illustrates the accuracy enhancement and complexity reduction achieved by the proposed models. When strong memory effects are observed, the augmented twin-nonlinear two-box models can improve the normalized mean square error by up to 3 dB for the same number of coefficients when compared to state-of-the-art twin-nonlinear two-box models. Furthermore, the augmented twin-nonlinear two-box models lead to the same performance as previously reported twin-nonlinear two-box models while requiring up to 80% less coefficients. PMID:24624047

Use case driven approach to develop simulation model for PCS of APR1400 simulator

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

Dong Wook, Kim; Hong Soo, Kim; Hyeon Tae, Kang

2006-07-01

The full-scope simulator is being developed to evaluate specific design feature and to support the iterative design and validation in the Man-Machine Interface System (MMIS) design of Advanced Power Reactor (APR) 1400. The simulator consists of process model, control logic model, and MMI for the APR1400 as well as the Power Control System (PCS). In this paper, a use case driven approach is proposed to develop a simulation model for PCS. In this approach, a system is considered from the point of view of its users. User's view of the system is based on interactions with the system and themore » resultant responses. In use case driven approach, we initially consider the system as a black box and look at its interactions with the users. From these interactions, use cases of the system are identified. Then the system is modeled using these use cases as functions. Lower levels expand the functionalities of each of these use cases. Hence, starting from the topmost level view of the system, we proceeded down to the lowest level (the internal view of the system). The model of the system thus developed is use case driven. This paper will introduce the functionality of the PCS simulation model, including a requirement analysis based on use case and the validation result of development of PCS model. The PCS simulation model using use case will be first used during the full-scope simulator development for nuclear power plant and will be supplied to Shin-Kori 3 and 4 plant. The use case based simulation model development can be useful for the design and implementation of simulation models. (authors)« less

Long-time tail in the two-wave model

NASA Astrophysics Data System (ADS)

Hatori, T.; Abe, Y.; Irie, H.; Kaufman, A. N.

1984-07-01

The velocity time correlation function is found, both theoretically and numerically, to decay with the power law for the chaotic orbit governed by a Hamiltonian, H = v to 2nd power/2 - Mcosx - Pcos k(x-t) , M, P and k are the parameters.

Creation of Power Reserves Under the Market Economy Conditions

NASA Astrophysics Data System (ADS)

Mahnitko, A.; Gerhards, J.; Lomane, T.; Ribakov, S.

2008-09-01

The main task of the control over an electric power system (EPS) is to ensure reliable power supply at the least cost. In this case, requirements to the electric power quality, power supply reliability and cost limitations on the energy resources must be observed. The available power reserve in an EPS is the necessary condition to keep it in operation with maintenance of normal operating variables (frequency, node voltage, power flows via the transmission lines, etc.). The authors examine possibilities to create power reserves that could be offered for sale by the electric power producer. They consider a procedure of price formation for the power reserves and propose a relevant mathematical model for a united EPS, the initial data being the fuel-cost functions for individual systems, technological limitations on the active power generation and consumers' load. As the criterion of optimization the maximum profit for the producer is taken. The model is exemplified by a concentrated EPS. The computations have been performed using the MATLAB program.

Turbulent Equilibria for Charged Particles in Space

NASA Astrophysics Data System (ADS)

Yoon, Peter

2017-04-01

The solar wind electron distribution function is apparently composed of several components including non-thermal tail population. The electron distribution that contains energetic tail feature is well fitted with the kappa distribution function. The solar wind protons also possess quasi power-law tail distribution function that is well fitted with an inverse power law model. The present paper discusses the latest theoretical development regarding the dynamical steady-state solution of electrons and Langmuir turbulence that are in turbulent equilibrium. According to such a theory, the Maxwellian and kappa distribution functions for the electrons emerge as the only two possible solution that satisfy the steady-state weak turbulence plasma kinetic equation. For the proton inverse power-law tail problem, a similar turbulent equilibrium solution can be conceived of, but instead of high-frequency Langmuir fluctuation, the theory involves low-frequency kinetic Alfvenic turbulence. The steady-state solution of the self-consistent proton kinetic equation and wave kinetic equation for Alfvenic waves can be found in order to obtain a self-consistent solution for the inverse power law tail distribution function.

Research on multi - channel interactive virtual assembly system for power equipment under the “VR+” era

NASA Astrophysics Data System (ADS)

Ren, Yilong; Duan, Xitong; Wu, Lei; He, Jin; Xu, Wu

2017-06-01

With the development of the “VR+” era, the traditional virtual assembly system of power equipment has been unable to satisfy our growing needs. In this paper, based on the analysis of the traditional virtual assembly system of electric power equipment and the application of VR technology in the virtual assembly system of electric power equipment in our country, this paper puts forward the scheme of establishing the virtual assembly system of power equipment: At first, we should obtain the information of power equipment, then we should using OpenGL and multi texture technology to build 3D solid graphics library. After the completion of three-dimensional modeling, we can use the dynamic link library DLL package three-dimensional solid graphics generation program to realize the modularization of power equipment model library and power equipment model library generated hidden algorithm. After the establishment of 3D power equipment model database, we set up the virtual assembly system of 3D power equipment to separate the assembly operation of the power equipment from the space. At the same time, aiming at the deficiency of the traditional gesture recognition algorithm, we propose a gesture recognition algorithm based on improved PSO algorithm for BP neural network data glove. Finally, the virtual assembly system of power equipment can really achieve multi-channel interaction function.

Two parametric voice source models and their asymptotic analysis

NASA Astrophysics Data System (ADS)

Leonov, A. S.; Sorokin, V. N.

2014-05-01

The paper studies the asymptotic behavior of the function for the area of the glottis near moments of its opening and closing for two mathematical voice source models. It is shown that in the first model, the asymptotics of the area function obeys a power law with an exponent of no less that 1. Detailed analysis makes it possible to refine these limits depending on the relative sizes of the intervals of a closed and open glottis. This work also studies another parametric model of the area of the glottis, which is based on a simplified physical-geometrical representation of vocal-fold vibration processes. This is a special variant of the well-known two-mass model and contains five parameters: the period of the main tone, equivalent masses on the lower and upper edge of vocal folds, the coefficient of elastic resistance of the lower vocal fold, and the delay time between openings of the upper and lower folds. It is established that the asymptotics of the obtained function for the area of the glottis obey a power law with an exponent of 1 both for opening and closing.

A method for the estimation of the significance of cross-correlations in unevenly sampled red-noise time series

NASA Astrophysics Data System (ADS)

Max-Moerbeck, W.; Richards, J. L.; Hovatta, T.; Pavlidou, V.; Pearson, T. J.; Readhead, A. C. S.

2014-11-01

We present a practical implementation of a Monte Carlo method to estimate the significance of cross-correlations in unevenly sampled time series of data, whose statistical properties are modelled with a simple power-law power spectral density. This implementation builds on published methods; we introduce a number of improvements in the normalization of the cross-correlation function estimate and a bootstrap method for estimating the significance of the cross-correlations. A closely related matter is the estimation of a model for the light curves, which is critical for the significance estimates. We present a graphical and quantitative demonstration that uses simulations to show how common it is to get high cross-correlations for unrelated light curves with steep power spectral densities. This demonstration highlights the dangers of interpreting them as signs of a physical connection. We show that by using interpolation and the Hanning sampling window function we are able to reduce the effects of red-noise leakage and to recover steep simple power-law power spectral densities. We also introduce the use of a Neyman construction for the estimation of the errors in the power-law index of the power spectral density. This method provides a consistent way to estimate the significance of cross-correlations in unevenly sampled time series of data.

Physical and cognitive effort discounting across different reward magnitudes: Tests of discounting models

PubMed Central

Ostaszewski, Paweł

2017-01-01

The effort required to obtain a rewarding outcome is an important factor in decision-making. Describing the reward devaluation by increasing effort intensity is substantial to understanding human preferences, because every action and choice that we make is in itself effortful. To investigate how reward valuation is affected by physical and cognitive effort, we compared mathematical discounting functions derived from research on discounting. Seven discounting models were tested across three different reward magnitudes. To test the models, data were collected from a total of 114 participants recruited from the general population. For one-parameter models (hyperbolic, exponential, and parabolic), the data were explained best by the exponential model as given by a percentage of explained variance. However, after introducing an additional parameter, data obtained in the cognitive and physical effort conditions were best described by the power function model. Further analysis, using the second order Akaike and Bayesian Information Criteria, which account for model complexity, allowed us to identify the best model among all tested. We found that the power function best described the data, which corresponds to conventional analyses based on the R2 measure. This supports the conclusion that the function best describing reward devaluation by physical and cognitive effort is a concave one and is different from those that describe delay or probability discounting. In addition, consistent magnitude effects were observed that correspond to those in delay discounting research. PMID:28759631

Dynamic modeling and parameter estimation of a radial and loop type distribution system network

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

Jun Qui; Heng Chen; Girgis, A.A.

1993-05-01

This paper presents a new identification approach to three-phase power system modeling and model reduction taking power system network as multi-input, multi-output (MIMO) processes. The model estimate can be obtained in discrete-time input-output form, discrete- or continuous-time state-space variable form, or frequency-domain impedance transfer function matrix form. An algorithm for determining the model structure of this MIMO process is described. The effect of measurement noise on the approach is also discussed. This approach has been applied on a sample system and simulation results are also presented in this paper.

Make-up wells drilling cost in financial model for a geothermal project

NASA Astrophysics Data System (ADS)

Oktaviani Purwaningsih, Fitri; Husnie, Ruly; Afuar, Waldy; Abdurrahman, Gugun

2017-12-01

After commissioning of a power plant, geothermal reservoir will encounter pressure decline, which will affect wells productivity. Therefore, further drilling is carried out to enhance steam production. Make-up wells are production wells drilled inside an already confirmed reservoir to maintain steam production in a certain level. Based on Sanyal (2004), geothermal power cost consists of three components, those are capital cost, O&M cost and make-up drilling cost. The make-up drilling cost component is a major part of power cost which will give big influence in a whole economical value of the project. The objective of this paper it to analyse the make-up wells drilling cost component in financial model of a geothermal power project. The research will calculate make-up wells requirements, drilling costs as a function of time and how they influence the financial model and affect the power cost. The best scenario in determining make-up wells strategy in relation with the project financial model would be the result of this research.

Estimated power quality for line commutated photovoltaic residential system

NASA Astrophysics Data System (ADS)

McNeill, B. W.; Mirza, M. A.

1983-10-01

A residential photovoltaic system using a line commutated inverter is modeled using a single diode model for the solar cells and a four switch model for the inverter. The model predicts power factor and total harmonic distortion as a function of solar radiation, array voltage, inverter output voltage, and inverter filter capacitor and inductor size. The model was run using parameter values appropriate for the John F. Long PV System and the predicted results compared well with measured results from the system. The model shows that improvements in total harmonic distortion are made at the expense of the power factor. The harmonic distortion is least when the inverter is operating at just continuous conduction. The total harmonic distortion can be kept to less than 0.17 all day if a variable inductor is used in the inverter's input filters.

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.

Hybrid power supplies: A capacitor-assisted battery

NASA Astrophysics Data System (ADS)

Catherino, Henry A.; Burgel, Joseph F.; Shi, Peter L.; Rusek, Andrew; Zou, Xiulin

A hybrid electrochemical power supply is a concept that circumvents the need for designing any single power source to meet some extraordinary application requirement. A hybrid allows using components designed for near optimal operation without having to make unnecessary performance sacrifices. In many cases some additional synergistic effects appear. In this study, an electrochemical capacitor was employed as a power assist for a battery. An engine starting load was numerically modeled in the time domain and simulations were carried out. Actual measurements were then taken on the cranking of a diesel engine removed from a 5.0-tonne military truck and cranked in an environmental chamber. The cranking currents delivered by each power source were measured in the accessible current loops. This permitted the model parameters to be identified and, by doing that, studies using the analytical model demonstrated the merit of this hybrid application. The general system response of the battery/capacitor configuration was then modeled as a function of temperature. Doing this revealed electrical the interaction between the hybrid components. This study illustrates another case for advocating hybridized power systems.

Application of small-signal modeling and measurement techniques to the stability analysis of an integrated switching-mode power system. [onboard Dynamics Explorer Satellite

NASA Technical Reports Server (NTRS)

Wong, R. C.; Owen, H. A., Jr.; Wilson, T. G.; Rodriguez, G. E.

1980-01-01

Small-signal modeling techniques are used in a system stability analysis of a breadboard version of a complete functional electrical power system. The system consists of a regulated switching dc-to-dc converter, a solar-cell-array simulator, a solar-array EMI filter, battery chargers and linear shunt regulators. Loss mechanisms in the converter power stage, including switching-time effects in the semiconductor elements, are incorporated into the modeling procedure to provide an accurate representation of the system without requiring frequency-domain measurements to determine the damping factor. The small-signal system model is validated by the use of special measurement techniques which are adapted to the poor signal-to-noise ratio encountered in switching-mode systems. The complete electrical power system with the solar-array EMI filter is shown to be stable over the intended range of operation.

Ankle and Midfoot Power During Walking and Stair Ascent in Healthy Adults.

PubMed

DiLiberto, Frank E; Nawoczenski, Deborah A; Houck, Jeff

2018-02-27

Ankle power dominates forward propulsion of gait, but midfoot power generation is also important for successful push off. However, it is unclear if midfoot power generation increases or stays the same in response to propulsive activities that induce larger external loads and require greater ankle power. The purpose of this study was to examine ankle and midfoot power in healthy adults during progressively more demanding functional tasks. Multi-segment foot motion (tibia, calcaneus, forefoot) and ground reaction forces were recorded as participants (N=12) walked, ascended a standard step, and ascended a high step. Ankle and midfoot positive peak power and total power, and the proportion of midfoot to ankle total power were calculated. One-way repeated measures ANOVAs were conducted to evaluate differences across tasks. Main effects were found for ankle and midfoot peak and total powers (all p < .001), but not for the proportion of midfoot to ankle total power (p = .331). Ankle and midfoot power significantly increased across each task. Midfoot power increased in proportion to ankle power and in congruence to the external load of a task. Study findings may serve to inform multi-segment foot modeling applications and internal mechanistic theories of normal and pathological foot function.

A non-local structural derivative model for characterization of ultraslow diffusion in dense colloids

NASA Astrophysics Data System (ADS)

Liang, Yingjie; Chen, Wen

2018-03-01

Ultraslow diffusion has been observed in numerous complicated systems. Its mean squared displacement (MSD) is not a power law function of time, but instead a logarithmic function, and in some cases grows even more slowly than the logarithmic rate. The distributed-order fractional diffusion equation model simply does not work for the general ultraslow diffusion. Recent study has used the local structural derivative to describe ultraslow diffusion dynamics by using the inverse Mittag-Leffler function as the structural function, in which the MSD is a function of inverse Mittag-Leffler function. In this study, a new stretched logarithmic diffusion law and its underlying non-local structural derivative diffusion model are proposed to characterize the ultraslow diffusion in aging dense colloidal glass at both the short and long waiting times. It is observed that the aging dynamics of dense colloids is a class of the stretched logarithmic ultraslow diffusion processes. Compared with the power, the logarithmic, and the inverse Mittag-Leffler diffusion laws, the stretched logarithmic diffusion law has better precision in fitting the MSD of the colloidal particles at high densities. The corresponding non-local structural derivative diffusion equation manifests clear physical mechanism, and its structural function is equivalent to the first-order derivative of the MSD.

Detecting biodiversity hotspots by species-area relationships: a case study of Mediterranean beetles.

PubMed

Fattorini, Simone

2006-08-01

Any method of identifying hotspots should take into account the effect of area on species richness. I examined the importance of the species-area relationship in determining tenebrionid (Coleoptera: Tenebrionidae) hotspots on the Aegean Islands (Greece). Thirty-two islands and 170 taxa (species and subspecies) were included in this study. I tested several species-area relationship models with linear and nonlinear regressions, including power exponential, negative exponential, logistic, Gompertz, Weibull, Lomolino, and He-Legendre functions. Islands with positive residuals were identified as hotspots. I also analyzed the values of the C parameter of the power function and the simple species-area ratios. Species richness was significantly correlated with island area for all models. The power function model was the most convenient one. Most functions, however identified certain islands as hotspots. The importance of endemics in insular biotas should be evaluated carefully because they are of high conservation concern. The simple use of the species-area relationship can be problematic when areas with no endemics are included. Therefore the importance of endemics should be evaluated according to different methods, such as percentages, to take into account different levels of endemism and different kinds of "endemics" (e.g., endemic to single islands vs. endemic to the archipelago). Because the species-area relationship is a key pattern in ecology, my findings can be applied at broader scales.

Bispectrum supersample covariance

NASA Astrophysics Data System (ADS)

Chan, Kwan Chuen; Moradinezhad Dizgah, Azadeh; Noreña, Jorge

2018-02-01

Modes with wavelengths larger than the survey window can have significant impact on the covariance within the survey window. The supersample covariance has been recognized as an important source of covariance for the power spectrum on small scales, and it can potentially be important for the bispectrum covariance as well. In this paper, using the response function formalism, we model the supersample covariance contributions to the bispectrum covariance and the cross-covariance between the power spectrum and the bispectrum. The supersample covariances due to the long-wavelength density and tidal perturbations are investigated, and the tidal contribution is a few orders of magnitude smaller than the density one because in configuration space the bispectrum estimator involves angular averaging and the tidal response function is anisotropic. The impact of the super-survey modes is quantified using numerical measurements with periodic box and sub-box setups. For the matter bispectrum, the ratio between the supersample covariance correction and the small-scale covariance—which can be computed using a periodic box—is roughly an order of magnitude smaller than that for the matter power spectrum. This is because for the bispectrum, the small-scale non-Gaussian covariance is significantly larger than that for the power spectrum. For the cross-covariance, the supersample covariance is as important as for the power spectrum covariance. The supersample covariance prediction with the halo model response function is in good agreement with numerical results.

Normative data and predictors of leg muscle function and postural control in children.

PubMed

Hazell, Tom J; Sharma, Atul K; Vanstone, Catherine A; Gagnon, Isabelle; Pham, Thu Trang; Finch, Sarah L; Weiler, Hope A; Rodd, Celia J

2014-11-01

At the present there are limited tools available to measure muscle function in young children. Ground reaction force plates measure lower-body function and postural control in older children and adults. The purpose of this study was threefold: 1) develop normative data for evaluating global muscle development; 2) determine the reproducibility of ground reaction force plates for assessing muscle function in preschool-age children; and 3) identify predictors of skeletal muscle function. Children's (n = 81, 1.8 to 6.0 yr; M = 52%) muscle function and postural control was measured for jump (JMP), sit-to-stand (STS), and both undistracted and distracted body sway tests using a ground reaction force plate (Kistler 9200A). Whole body composition used dual-energy x-ray absorptiometry (Hologic 4500A Discovery Series). Plasma 25-hydroxyvitamin D [25(OH)D] and parathyroid hormone concentrations were measured by chemiluminescence (Liaison, Diasorin, Mississauga, ON, Canada) as well as ionized calcium (ABL80 FLEX, Radiometer Medical A/S). Demographics, and anthropometry were collected. ANOVA and linear regression were used to identify predictors. Reproducibility was assessed by intersubject coefficient of variation. Age was a consistent predictor in all models; body size or fat and lean mass were important predictors in 3 of the models - STS peak force, STS peak power, and JMP peak power. STS was the most reproducible maneuver (average coefficient of variation =15.7%). Distracted body sway testing was not appropriate in these youngsters. The novel data presented in this study demonstrate a clear age (developmental) effect without any effect of sex on muscle function and postural control in young children. Lean muscle mass was important in some models (STS peak force and JMP peak power). The STS test was the best of the 4 maneuvers.

Across-Platform Imputation of DNA Methylation Levels Incorporating Nonlocal Information Using Penalized Functional Regression.

PubMed

Zhang, Guosheng; Huang, Kuan-Chieh; Xu, Zheng; Tzeng, Jung-Ying; Conneely, Karen N; Guan, Weihua; Kang, Jian; Li, Yun

2016-05-01

DNA methylation is a key epigenetic mark involved in both normal development and disease progression. Recent advances in high-throughput technologies have enabled genome-wide profiling of DNA methylation. However, DNA methylation profiling often employs different designs and platforms with varying resolution, which hinders joint analysis of methylation data from multiple platforms. In this study, we propose a penalized functional regression model to impute missing methylation data. By incorporating functional predictors, our model utilizes information from nonlocal probes to improve imputation quality. Here, we compared the performance of our functional model to linear regression and the best single probe surrogate in real data and via simulations. Specifically, we applied different imputation approaches to an acute myeloid leukemia dataset consisting of 194 samples and our method showed higher imputation accuracy, manifested, for example, by a 94% relative increase in information content and up to 86% more CpG sites passing post-imputation filtering. Our simulated association study further demonstrated that our method substantially improves the statistical power to identify trait-associated methylation loci. These findings indicate that the penalized functional regression model is a convenient and valuable imputation tool for methylation data, and it can boost statistical power in downstream epigenome-wide association study (EWAS). © 2016 WILEY PERIODICALS, INC.

Evaluation model of distribution network development based on ANP and grey correlation analysis

NASA Astrophysics Data System (ADS)

Ma, Kaiqiang; Zhan, Zhihong; Zhou, Ming; Wu, Qiang; Yan, Jun; Chen, Genyong

2018-06-01

The existing distribution network evaluation system cannot scientifically and comprehensively reflect the distribution network development status. Furthermore, the evaluation model is monotonous and it is not suitable for horizontal analysis of many regional power grids. For these reason, this paper constructs a set of universal adaptability evaluation index system and model of distribution network development. Firstly, distribution network evaluation system is set up by power supply capability, power grid structure, technical equipment, intelligent level, efficiency of the power grid and development benefit of power grid. Then the comprehensive weight of indices is calculated by combining the AHP with the grey correlation analysis. Finally, the index scoring function can be obtained by fitting the index evaluation criterion to the curve, and then using the multiply plus operator to get the result of sample evaluation. The example analysis shows that the model can reflect the development of distribution network and find out the advantages and disadvantages of distribution network development. Besides, the model provides suggestions for the development and construction of distribution network.

Analytical and experimental comparisons of electromechanical vibration response of a piezoelectric bimorph beam for power harvesting

NASA Astrophysics Data System (ADS)

Lumentut, M. F.; Howard, I. M.

2013-03-01

Power harvesters that extract energy from vibrating systems via piezoelectric transduction show strong potential for powering smart wireless sensor devices in applications of health condition monitoring of rotating machinery and structures. This paper presents an analytical method for modelling an electromechanical piezoelectric bimorph beam with tip mass under two input base transverse and longitudinal excitations. The Euler-Bernoulli beam equations were used to model the piezoelectric bimorph beam. The polarity-electric field of the piezoelectric element is excited by the strain field caused by base input excitation, resulting in electrical charge. The governing electromechanical dynamic equations were derived analytically using the weak form of the Hamiltonian principle to obtain the constitutive equations. Three constitutive electromechanical dynamic equations based on independent coefficients of virtual displacement vectors were formulated and then further modelled using the normalised Ritz eigenfunction series. The electromechanical formulations include both the series and parallel connections of the piezoelectric bimorph. The multi-mode frequency response functions (FRFs) under varying electrical load resistance were formulated using Laplace transformation for the multi-input mechanical vibrations to provide the multi-output dynamic displacement, velocity, voltage, current and power. The experimental and theoretical validations reduced for the single mode system were shown to provide reasonable predictions. The model results from polar base excitation for off-axis input motions were validated with experimental results showing the change to the electrical power frequency response amplitude as a function of excitation angle, with relevance for practical implementation.

Approximate Bayesian Computation Using Markov Chain Monte Carlo Simulation: Theory, Concepts, and Applications

NASA Astrophysics Data System (ADS)

Sadegh, M.; Vrugt, J. A.

2013-12-01

The ever increasing pace of computational power, along with continued advances in measurement technologies and improvements in process understanding has stimulated the development of increasingly complex hydrologic models that simulate soil moisture flow, groundwater recharge, surface runoff, root water uptake, and river discharge at increasingly finer spatial and temporal scales. Reconciling these system models with field and remote sensing data is a difficult task, particularly because average measures of model/data similarity inherently lack the power to provide a meaningful comparative evaluation of the consistency in model form and function. The very construction of the likelihood function - as a summary variable of the (usually averaged) properties of the error residuals - dilutes and mixes the available information into an index having little remaining correspondence to specific behaviors of the system (Gupta et al., 2008). The quest for a more powerful method for model evaluation has inspired Vrugt and Sadegh [2013] to introduce "likelihood-free" inference as vehicle for diagnostic model evaluation. This class of methods is also referred to as Approximate Bayesian Computation (ABC) and relaxes the need for an explicit likelihood function in favor of one or multiple different summary statistics rooted in hydrologic theory that together have a much stronger and compelling diagnostic power than some aggregated measure of the size of the error residuals. Here, we will introduce an efficient ABC sampling method that is orders of magnitude faster in exploring the posterior parameter distribution than commonly used rejection and Population Monte Carlo (PMC) samplers. Our methodology uses Markov Chain Monte Carlo simulation with DREAM, and takes advantage of a simple computational trick to resolve discontinuity problems with the application of set-theoretic summary statistics. We will also demonstrate a set of summary statistics that are rather insensitive to errors in the forcing data. This enhances prospects of detecting model structural deficiencies.

A statistical framework for genetic association studies of power curves in bird flight

PubMed Central

Lin, Min; Zhao, Wei

2006-01-01

How the power required for bird flight varies as a function of forward speed can be used to predict the flight style and behavioral strategy of a bird for feeding and migration. A U-shaped curve was observed between the power and flight velocity in many birds, which is consistent to the theoretical prediction by aerodynamic models. In this article, we present a general genetic model for fine mapping of quantitative trait loci (QTL) responsible for power curves in a sample of birds drawn from a natural population. This model is developed within the maximum likelihood context, implemented with the EM algorithm for estimating the population genetic parameters of QTL and the simplex algorithm for estimating the QTL genotype-specific parameters of power curves. Using Monte Carlo simulation derived from empirical observations of power curves in the European starling (Sturnus vulgaris), we demonstrate how the underlying QTL for power curves can be detected from molecular markers and how the QTL detected affect the most appropriate flight speeds used to design an optimal migration strategy. The results from our model can be directly integrated into a conceptual framework for understanding flight origin and evolution. PMID:17066123

Relationship between cardiac autonomic function and cognitive function in Alzheimer's disease.

PubMed

Nonogaki, Zen; Umegaki, Hiroyuki; Makino, Taeko; Suzuki, Yusuke; Kuzuya, Masafumi

2017-01-01

Alzheimer's disease (AD) affects many central nervous structures and neurotransmitter systems. These changes affect not only cognitive function, but also cardiac autonomic function. However, the functional relationship between cardiac autonomic function and cognition in AD has not yet been investigated. The objective of the present study was to evaluate the association between cardiac autonomic function measured by heart rate variability and cognitive function in AD. A total of 78 AD patients were recruited for this study. Cardiac autonomic function was evaluated using heart rate variability analysis. Multiple linear regression analysis was used to model the association between heart rate variability and cognitive function (global cognitive function, memory, executive function and processing speed), after adjustment for covariates. Global cognitive function was negatively associated with sympathetic modulation (low-to-high frequency power ratio). Memory performance was positively associated with parasympathetic modulation (high frequency power) and negatively associated with sympathetic modulation (low-to-high frequency power ratio). These associations were independent of age, sex, educational years, diabetes, hypertension and cholinesterase inhibitor use. Cognitive function, especially in the areas of memory, is associated with cardiac autonomic function in AD. Specifically, lower cognitive performance was found to be associated with significantly higher cardiac sympathetic and lower parasympathetic function in AD. Geriatr Gerontol Int 2017; 17: 92-98. © 2015 Japan Geriatrics Society.

Spaceborne power systems preference analyses. Volume 1: Summary

NASA Technical Reports Server (NTRS)

Smith, J. H.; Feinberg, A.; Miles, R. F., Jr.

1985-01-01

Sixteen alternative spaceborne nuclear power system concepts were ranked using multiattribute decision analysis to identify promising concepts for further technology development. Four groups interviewed were: safety, systems definition and design, technology assessment, and mission analysis. The ranking results were consistent from group and for different utility function models for individuals.

Dual learning processes underlying human decision-making in reversal learning tasks: functional significance and evidence from the model fit to human behavior

PubMed Central

Bai, Yu; Katahira, Kentaro; Ohira, Hideki

2014-01-01

Humans are capable of correcting their actions based on actions performed in the past, and this ability enables them to adapt to a changing environment. The computational field of reinforcement learning (RL) has provided a powerful explanation for understanding such processes. Recently, the dual learning system, modeled as a hybrid model that incorporates value update based on reward-prediction error and learning rate modulation based on the surprise signal, has gained attention as a model for explaining various neural signals. However, the functional significance of the hybrid model has not been established. In the present study, we used computer simulation in a reversal learning task to address functional significance in a probabilistic reversal learning task. The hybrid model was found to perform better than the standard RL model in a large parameter setting. These results suggest that the hybrid model is more robust against the mistuning of parameters compared with the standard RL model when decision-makers continue to learn stimulus-reward contingencies, which can create abrupt changes. The parameter fitting results also indicated that the hybrid model fit better than the standard RL model for more than 50% of the participants, which suggests that the hybrid model has more explanatory power for the behavioral data than the standard RL model. PMID:25161635

Modeling Framework and Validation of a Smart Grid and Demand Response System for Wind Power Integration

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

Broeer, Torsten; Fuller, Jason C.; Tuffner, Francis K.

2014-01-31

Electricity generation from wind power and other renewable energy sources is increasing, and their variability introduces new challenges to the power system. The emergence of smart grid technologies in recent years has seen a paradigm shift in redefining the electrical system of the future, in which controlled response of the demand side is used to balance fluctuations and intermittencies from the generation side. This paper presents a modeling framework for an integrated electricity system where loads become an additional resource. The agent-based model represents a smart grid power system integrating generators, transmission, distribution, loads and market. The model incorporates generatormore » and load controllers, allowing suppliers and demanders to bid into a Real-Time Pricing (RTP) electricity market. The modeling framework is applied to represent a physical demonstration project conducted on the Olympic Peninsula, Washington, USA, and validation simulations are performed using actual dynamic data. Wind power is then introduced into the power generation mix illustrating the potential of demand response to mitigate the impact of wind power variability, primarily through thermostatically controlled loads. The results also indicate that effective implementation of Demand Response (DR) to assist integration of variable renewable energy resources requires a diversity of loads to ensure functionality of the overall system.« less

Novel Analog For Muscle Deconditioning

NASA Technical Reports Server (NTRS)

Ploutz-Snyder, Lori; Ryder, Jeff; Buxton, Roxanne; Redd, Elizabeth; Scott-Pandorf, Melissa; Hackney, Kyle; Fiedler, James; Bloomberg, Jacob

2010-01-01

Existing models of muscle deconditioning are cumbersome and expensive (ex: bedrest). We propose a new model utilizing a weighted suit to manipulate strength, power or endurance (function) relative to body weight (BW). Methods: 20 subjects performed 7 occupational astronaut tasks while wearing a suit weighted with 0-120% of BW. Models of the full relationship between muscle function/BW and task completion time were developed using fractional polynomial regression and verified by the addition of pre- and post-flight astronaut performance data using the same tasks. Spline regression was used to identify muscle function thresholds below which task performance was impaired. Results: Thresholds of performance decline were identified for each task. Seated egress & walk (most difficult task) showed thresholds of: leg press (LP) isometric peak force/BW of 18 N/kg, LP power/BW of 18 W/kg, LP work/ BW of 79 J/kg, knee extension (KE) isokinetic/BW of 6 Nm/Kg and KE torque/BW of 1.9 Nm/kg. Conclusions: Laboratory manipulation of strength / BW has promise as an appropriate analog for spaceflight-induced loss of muscle function for predicting occupational task performance and establishing operationally relevant exercise targets.

Novel Analog For Muscle Deconditioning

NASA Technical Reports Server (NTRS)

Ploutz-Snyder, Lori; Ryder, Jeff; Buxton, Roxanne; Redd. Elizabeth; Scott-Pandorf, Melissa; Hackney, Kyle; Fiedler, James; Ploutz-Snyder, Robert; Bloomberg, Jacob

2011-01-01

Existing models (such as bed rest) of muscle deconditioning are cumbersome and expensive. We propose a new model utilizing a weighted suit to manipulate strength, power, or endurance (function) relative to body weight (BW). Methods: 20 subjects performed 7 occupational astronaut tasks while wearing a suit weighted with 0-120% of BW. Models of the full relationship between muscle function/BW and task completion time were developed using fractional polynomial regression and verified by the addition of pre-and postflightastronaut performance data for the same tasks. Splineregression was used to identify muscle function thresholds below which task performance was impaired. Results: Thresholds of performance decline were identified for each task. Seated egress & walk (most difficult task) showed thresholds of leg press (LP) isometric peak force/BW of 18 N/kg, LP power/BW of 18 W/kg, LP work/BW of 79 J/kg, isokineticknee extension (KE)/BW of 6 Nm/kg, and KE torque/BW of 1.9 Nm/kg.Conclusions: Laboratory manipulation of relative strength has promise as an appropriate analog for spaceflight-induced loss of muscle function, for predicting occupational task performance and establishing operationally relevant strength thresholds.

Halo Substructure and the Power Spectrum

NASA Astrophysics Data System (ADS)

Zentner, Andrew R.; Bullock, James S.

2003-11-01

We present a semianalytic model to investigate the merger history, destruction rate, and survival probability of substructure in hierarchically formed dark matter halos and use it to study the substructure content of halos as a function of input primordial power spectrum. For a standard cold dark matter ``concordance'' cosmology (ΛCDM n=1, σ8=0.95) we successfully reproduce the subhalo velocity function and radial distribution profile seen in N-body simulations and determine that the rate of merging and disruption peaks ~10-12 Gyr in the past for Milky Way-like halos, while surviving substructures are typically accreted within the last ~0-8 Gyr. We explore power spectra with normalizations and spectral ``tilts'' spanning the ranges σ8~=1-0.65 and n~=1-0.8, and include a ``running-index'' model with dn/dlnk=-0.03 similar to the best-fit model discussed in the first-year Wilkinson Microwave Anisotropy Probe (WMAP) report. We investigate spectra with truncated small-scale power, including a broken-scale inflation model and three warm dark matter cases with mW=0.75-3.0 keV. We find that the mass fraction in substructure is relatively insensitive to the tilt and overall normalization of the primordial power spectrum. All of the CDM-type models yield projected substructure mass fractions that are consistent with, but on the low side, of published estimates from strong lens systems: f9=0.4%-1.5% (64th percentile) for subhalos smaller than 109 Msolar within projected cylinders of radius r<10 kpc. Truncated models produce significantly smaller fractions, f9=0.02%-0.2% for mW~=1 keV, and are disfavored by lensing estimates. This suggests that lensing and similar probes can provide a robust test of the CDM paradigm and a powerful constraint on broken-scale inflation/warm particle masses, including masses larger than the ~1 keV upper limits of previous studies. We compare our predicted subhalo velocity functions with the dwarf satellite population of the Milky Way. Assuming that dwarfs have isotropic velocity dispersions, we find that the standard n=1 model overpredicts the number of Milky Way satellites at Vmax<~35 km s-1, as expected. Models with less small-scale power do better because subhalos are less concentrated and the mapping between observed velocity dispersion and halo Vmax is significantly altered. The running-index model, or a fixed tilt with σ8~0.75, can account for the local dwarfs without the need for differential feedback (for Vmax>~20 km s-1) however, these comparisons depend sensitively on the assumption of isotropic velocities in satellite galaxies.

Control and prediction for blackouts caused by frequency collapse in smart grids.

PubMed

Wang, Chengwei; Grebogi, Celso; Baptista, Murilo S

2016-09-01

The electric power system is one of the cornerstones of modern society. One of its most serious malfunctions is the blackout, a catastrophic event that may disrupt a substantial portion of the system, playing havoc to human life and causing great economic losses. Thus, understanding the mechanisms leading to blackouts and creating a reliable and resilient power grid has been a major issue, attracting the attention of scientists, engineers, and stakeholders. In this paper, we study the blackout problem in power grids by considering a practical phase-oscillator model. This model allows one to simultaneously consider different types of power sources (e.g., traditional AC power plants and renewable power sources connected by DC/AC inverters) and different types of loads (e.g., consumers connected to distribution networks and consumers directly connected to power plants). We propose two new control strategies based on our model, one for traditional power grids and another one for smart grids. The control strategies show the efficient function of the fast-response energy storage systems in preventing and predicting blackouts in smart grids. This work provides innovative ideas which help us to build up a robuster and more economic smart power system.

Control and prediction for blackouts caused by frequency collapse in smart grids

NASA Astrophysics Data System (ADS)

Wang, Chengwei; Grebogi, Celso; Baptista, Murilo S.

2016-09-01

The electric power system is one of the cornerstones of modern society. One of its most serious malfunctions is the blackout, a catastrophic event that may disrupt a substantial portion of the system, playing havoc to human life and causing great economic losses. Thus, understanding the mechanisms leading to blackouts and creating a reliable and resilient power grid has been a major issue, attracting the attention of scientists, engineers, and stakeholders. In this paper, we study the blackout problem in power grids by considering a practical phase-oscillator model. This model allows one to simultaneously consider different types of power sources (e.g., traditional AC power plants and renewable power sources connected by DC/AC inverters) and different types of loads (e.g., consumers connected to distribution networks and consumers directly connected to power plants). We propose two new control strategies based on our model, one for traditional power grids and another one for smart grids. The control strategies show the efficient function of the fast-response energy storage systems in preventing and predicting blackouts in smart grids. This work provides innovative ideas which help us to build up a robuster and more economic smart power system.

Case studies on optimization problems in MATLAB and COMSOL multiphysics by means of the livelink

NASA Astrophysics Data System (ADS)

Ozana, Stepan; Pies, Martin; Docekal, Tomas

2016-06-01

LiveLink for COMSOL is a tool that integrates COMSOL Multiphysics with MATLAB to extend one's modeling with scripting programming in the MATLAB environment. It allows user to utilize the full power of MATLAB and its toolboxes in preprocessing, model manipulation, and post processing. At first, the head script launches COMSOL with MATLAB and defines initial value of all parameters, refers to the objective function J described in the objective function and creates and runs the defined optimization task. Once the task is launches, the COMSOL model is being called in the iteration loop (from MATLAB environment by use of API interface), changing defined optimization parameters so that the objective function is minimized, using fmincon function to find a local or global minimum of constrained linear or nonlinear multivariable function. Once the minimum is found, it returns exit flag, terminates optimization and returns the optimized values of the parameters. The cooperation with MATLAB via LiveLink enhances a powerful computational environment with complex multiphysics simulations. The paper will introduce using of the LiveLink for COMSOL for chosen case studies in the field of technical cybernetics and bioengineering.

Conditional Spectral Analysis of Replicated Multiple Time Series with Application to Nocturnal Physiology.

PubMed

Krafty, Robert T; Rosen, Ori; Stoffer, David S; Buysse, Daniel J; Hall, Martica H

2017-01-01

This article considers the problem of analyzing associations between power spectra of multiple time series and cross-sectional outcomes when data are observed from multiple subjects. The motivating application comes from sleep medicine, where researchers are able to non-invasively record physiological time series signals during sleep. The frequency patterns of these signals, which can be quantified through the power spectrum, contain interpretable information about biological processes. An important problem in sleep research is drawing connections between power spectra of time series signals and clinical characteristics; these connections are key to understanding biological pathways through which sleep affects, and can be treated to improve, health. Such analyses are challenging as they must overcome the complicated structure of a power spectrum from multiple time series as a complex positive-definite matrix-valued function. This article proposes a new approach to such analyses based on a tensor-product spline model of Cholesky components of outcome-dependent power spectra. The approach exibly models power spectra as nonparametric functions of frequency and outcome while preserving geometric constraints. Formulated in a fully Bayesian framework, a Whittle likelihood based Markov chain Monte Carlo (MCMC) algorithm is developed for automated model fitting and for conducting inference on associations between outcomes and spectral measures. The method is used to analyze data from a study of sleep in older adults and uncovers new insights into how stress and arousal are connected to the amount of time one spends in bed.

Average focal length and power of a section of any defined surface.

PubMed

Kaye, Stephen B

2010-04-01

To provide a method to allow calculation of the average focal length and power of a lens through a specified meridian of any defined surface, not limited to the paraxial approximations. University of Liverpool, Liverpool, United Kingdom. Functions were derived to model back-vertex focal length and representative power through a meridian containing any defined surface. Average back-vertex focal length was based on the definition of the average of a function, using the angle of incidence as an independent variable. Univariate functions allowed determination of average focal length and power through a section of any defined or topographically measured surface of a known refractive index. These functions incorporated aberrations confined to the section. The proposed method closely approximates the average focal length, and by inference power, of a section (meridian) of a surface to a single or scalar value. It is not dependent on the paraxial and other nonconstant approximations and includes aberrations confined to that meridian. A generalization of this method to include all orthogonal and oblique meridians is needed before a comparison with measured wavefront values can be made. Copyright (c) 2010 ASCRS and ESCRS. Published by Elsevier Inc. All rights reserved.

Geometric Heat Engines Featuring Power that Grows with Efficiency.

PubMed

Raz, O; Subaşı, Y; Pugatch, R

2016-04-22

Thermodynamics places a limit on the efficiency of heat engines, but not on their output power or on how the power and efficiency change with the engine's cycle time. In this Letter, we develop a geometrical description of the power and efficiency as a function of the cycle time, applicable to an important class of heat engine models. This geometrical description is used to design engine protocols that attain both the maximal power and maximal efficiency at the fast driving limit. Furthermore, using this method, we also prove that no protocol can exactly attain the Carnot efficiency at nonzero power.

Modeling and Economic Analysis of Power Grid Operations in a Water Constrained System

NASA Astrophysics Data System (ADS)

Zhou, Z.; Xia, Y.; Veselka, T.; Yan, E.; Betrie, G.; Qiu, F.

2016-12-01

The power sector is the largest water user in the United States. Depending on the cooling technology employed at a facility, steam-electric power stations withdrawal and consume large amounts of water for each megawatt hour of electricity generated. The amounts are dependent on many factors, including ambient air and water temperatures, cooling technology, etc. Water demands from most economic sectors are typically highest during summertime. For most systems, this coincides with peak electricity demand and consequently a high demand for thermal power plant cooling water. Supplies however are sometimes limited due to seasonal precipitation fluctuations including sporadic droughts that lead to water scarcity. When this occurs there is an impact on both unit commitments and the real-time dispatch. In this work, we model the cooling efficiency of several different types of thermal power generation technologies as a function of power output level and daily temperature profiles. Unit specific relationships are then integrated in a power grid operational model that minimizes total grid production cost while reliably meeting hourly loads. Grid operation is subject to power plant physical constraints, transmission limitations, water availability and environmental constraints such as power plant water exit temperature limits. The model is applied to a standard IEEE-118 bus system under various water availability scenarios. Results show that water availability has a significant impact on power grid economics.

University Administration on a Political Model.

ERIC Educational Resources Information Center

Walker, Donald E.

1979-01-01

It is suggested that recognizing the university as a political community may lead to better management and organization. The patriarchal role, the president as hero, dispersed power, how the university really functions, and a political model are described. (MLW)

Interaction Models for Functional Regression.

PubMed

Usset, Joseph; Staicu, Ana-Maria; Maity, Arnab

2016-02-01

A functional regression model with a scalar response and multiple functional predictors is proposed that accommodates two-way interactions in addition to their main effects. The proposed estimation procedure models the main effects using penalized regression splines, and the interaction effect by a tensor product basis. Extensions to generalized linear models and data observed on sparse grids or with measurement error are presented. A hypothesis testing procedure for the functional interaction effect is described. The proposed method can be easily implemented through existing software. Numerical studies show that fitting an additive model in the presence of interaction leads to both poor estimation performance and lost prediction power, while fitting an interaction model where there is in fact no interaction leads to negligible losses. The methodology is illustrated on the AneuRisk65 study data.

Burst and inter-burst duration statistics as empirical test of long-range memory in the financial markets

NASA Astrophysics Data System (ADS)

Gontis, V.; Kononovicius, A.

2017-10-01

We address the problem of long-range memory in the financial markets. There are two conceptually different ways to reproduce power-law decay of auto-correlation function: using fractional Brownian motion as well as non-linear stochastic differential equations. In this contribution we address this problem by analyzing empirical return and trading activity time series from the Forex. From the empirical time series we obtain probability density functions of burst and inter-burst duration. Our analysis reveals that the power-law exponents of the obtained probability density functions are close to 3 / 2, which is a characteristic feature of the one-dimensional stochastic processes. This is in a good agreement with earlier proposed model of absolute return based on the non-linear stochastic differential equations derived from the agent-based herding model.

Modeling laser brightness from cross Porro prism resonators

NASA Astrophysics Data System (ADS)

Forbes, Andrew; Burger, Liesl; Litvin, Igor Anatolievich

2006-08-01

Laser brightness is a parameter often used to compare high power laser beam delivery from various sources, and incorporates both the power contained in the particular mode, as well as the propagation of that mode through the beam quality factor, M2. In this study a cross Porro prism resonator is considered; crossed Porro prism resonators have been known for some time, but until recently have not been modeled as a complete physical optics system that allows the modal output to be determined as a function of the rotation angle of the prisms. In this paper we consider the diffraction losses as a function of the prism rotation angle relative to one another, and combine this with the propagation of the specific modes to determine the laser output brightness as a function of the prism orientation.

Multilayered models for electromagnetic reflection amplitudes

NASA Technical Reports Server (NTRS)

Linlor, W. I.

1976-01-01

The remote sensing of snowpack characteristics with surface installations or with an airborne system could have important applications in water resource management and flood prediction. To derive some insight into such applications, the electromagnetic response of multilayer snow models is analyzed. Normally incident plane waves are assumed at frequencies ranging from 10 to the 6th power to 10 to the 10th power Hz, and amplitude reflection coefficients are calculated for models having various snow-layer combinations, including ice sheets. Layers are defined by a thickness, permittivity, and conductivity; the electrical parameters are constant or prescribed functions of frequency. To illustrate the effect of various layering combinations, results are given in the form of curves of amplitude reflection coefficients, versus frequency for a variety of models. Under simplifying assumptions, the snow thickness and effective dielectric constant can be estimated from the reflection coefficient variations as a function of frequency.

Harvesting Vibrational Energy Using Material Work Functions

PubMed Central

Varpula, Aapo; Laakso, Sampo J.; Havia, Tahvo; Kyynäräinen, Jukka; Prunnila, Mika

2014-01-01

Vibration energy harvesters scavenge energy from mechanical vibrations to energise low power electronic devices. In this work, we report on vibration energy harvesting scheme based on the charging phenomenon occurring naturally between two bodies with different work functions. Such work function energy harvester (WFEH) is similar to electrostatic energy harvester with the fundamental distinction that neither external power supplies nor electrets are needed. A theoretical model and description of different operation modes of WFEHs are presented. The WFEH concept is tested with macroscopic experiments, which agree well with the model. The feasibility of miniaturizing WFEHs is shown by simulating a realistic MEMS device. The WFEH can be operated as a charge pump that pushes charge and energy into an energy storage element. We show that such an operation mode is highly desirable for applications and that it can be realised with either a charge shuttle or with switches. The WFEH is shown to give equal or better output power in comparison to traditional electrostatic harvesters. Our findings indicate that WFEH has great potential in energy harvesting applications. PMID:25348004

Using "StorAge Selection" functions and high resolution isotope data to unravel travel time distributions in headwater catchments

NASA Astrophysics Data System (ADS)

Benettin, Paolo; Soulsby, Chris; Birkel, Christian; Tetzlaff, Doerthe; Botter, Gianluca; Rinaldo, Andrea

2017-04-01

We use high resolution tracer data from the Bruntland Burn catchment (UK) to test theoretical approaches that integrate catchment-scale flow and transport processes in a unified framework centered on selective age sampling by streamflow and evapotranspiration fluxes. Hydrologic transport is here described through StorAge Selection (SAS) functions, parametrized as simple power laws. By representing the way in which catchment storage generates outflows composed by water of different ages, the main mechanism regulating the tracer composition of runoff is clearly identified. The calibrated numerical model provides simulations that convincingly reproduce complex measured signals of daily deuterium content in stream waters during wet and dry periods. The results for the catchment under consideration are consistent with other recent studies indicating a tendency for natural catchments to preferentially release younger available water. The model allows estimating transient water age and its related uncertainty, as well as the total catchment storage. This study shows that power-law SAS functions prove a powerful tool to explain catchment-scale transport processes that also has potential in less intensively monitored sites.

Large-Scale Clustering of Galaxies in the CFA Survey

NASA Astrophysics Data System (ADS)

Park, Changbom

1992-03-01

The power spectrum of the galaxy distribution is accuarately measured up to wavelengths over 100h-1 Mpc from the CfA 1 and 2 catalogs. We find that our results agree with power spectra calculated by others from smaller samples of optical, radio and infrared galaxies. The power spectrum of an open CDM model (Omega h = 0.2 and delta8 = 1; see below for definitions) best approximates the observed power spectrum. The power spectrum of the standard CDM model(Omega h = 0.5 and delta8 = 1) is inconsistent with the observed one at the 99% confidence level. Our best estimation of the corresponding correlation function in real space is Xi(r) = (r/6.2h-1 Mpc)^-1.8 for r < 20h-1 Mpc.

The Exoplanet Mass-Ratio Function From the MOA-II Survey: Discovery of a Break and Likely Peak at a Neptune Mass

NASA Technical Reports Server (NTRS)

Suzuki, D.; Bennett, D. P.; Sumi, T.; Bond, I. A.; Rogers, L. A.; Abe, F.; Asakura, Y.; Bhattacharya, A.; Donachie, M.; Freeman, M.;

Fitting and forecasting coupled dark energy in the non-linear regime

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

Casas, Santiago; Amendola, Luca; Pettorino, Valeria

2016-01-01

We consider cosmological models in which dark matter feels a fifth force mediated by the dark energy scalar field, also known as coupled dark energy. Our interest resides in estimating forecasts for future surveys like Euclid when we take into account non-linear effects, relying on new fitting functions that reproduce the non-linear matter power spectrum obtained from N-body simulations. We obtain fitting functions for models in which the dark matter-dark energy coupling is constant. Their validity is demonstrated for all available simulations in the redshift range 0z=–1.6 and wave modes below 0k=1 h/Mpc. These fitting formulas can be used tomore » test the predictions of the model in the non-linear regime without the need for additional computing-intensive N-body simulations. We then use these fitting functions to perform forecasts on the constraining power that future galaxy-redshift surveys like Euclid will have on the coupling parameter, using the Fisher matrix method for galaxy clustering (GC) and weak lensing (WL). We find that by using information in the non-linear power spectrum, and combining the GC and WL probes, we can constrain the dark matter-dark energy coupling constant squared, β{sup 2}, with precision smaller than 4% and all other cosmological parameters better than 1%, which is a considerable improvement of more than an order of magnitude compared to corresponding linear power spectrum forecasts with the same survey specifications.« less

Limit order placement as an utility maximization problem and the origin of power law distribution of limit order prices

NASA Astrophysics Data System (ADS)

Lillo, F.

2007-02-01

I consider the problem of the optimal limit order price of a financial asset in the framework of the maximization of the utility function of the investor. The analytical solution of the problem gives insight on the origin of the recently empirically observed power law distribution of limit order prices. In the framework of the model, the most likely proximate cause of this power law is a power law heterogeneity of traders' investment time horizons.

Continuous time random walk model with asymptotical probability density of waiting times via inverse Mittag-Leffler function

NASA Astrophysics Data System (ADS)

Liang, Yingjie; Chen, Wen

2018-04-01

The mean squared displacement (MSD) of the traditional ultraslow diffusion is a logarithmic function of time. Recently, the continuous time random walk model is employed to characterize this ultraslow diffusion dynamics by connecting the heavy-tailed logarithmic function and its variation as the asymptotical waiting time density. In this study we investigate the limiting waiting time density of a general ultraslow diffusion model via the inverse Mittag-Leffler function, whose special case includes the traditional logarithmic ultraslow diffusion model. The MSD of the general ultraslow diffusion model is analytically derived as an inverse Mittag-Leffler function, and is observed to increase even more slowly than that of the logarithmic function model. The occurrence of very long waiting time in the case of the inverse Mittag-Leffler function has the largest probability compared with the power law model and the logarithmic function model. The Monte Carlo simulations of one dimensional sample path of a single particle are also performed. The results show that the inverse Mittag-Leffler waiting time density is effective in depicting the general ultraslow random motion.

Perturbed generalized multicritical one-matrix models

NASA Astrophysics Data System (ADS)

Ambjørn, J.; Chekhov, L.; Makeenko, Y.

2018-03-01

We study perturbations around the generalized Kazakov multicritical one-matrix model. The multicritical matrix model has a potential where the coefficients of zn only fall off as a power 1 /n s + 1. This implies that the potential and its derivatives have a cut along the real axis, leading to technical problems when one performs perturbations away from the generalized Kazakov model. Nevertheless it is possible to relate the perturbed partition function to the tau-function of a KdV hierarchy and solve the model by a genus expansion in the double scaling limit.

Fate of ethanol during cooking of liquid foods prepared with alcoholic beverages: Theory and experimental studies.

PubMed

Snitkjær, Pia; Ryapushkina, Julia; Skovenborg, Erik; Astrup, Arne; Bech, Lene Mølskov; Jensen, Morten Georg; Risbo, Jens

2017-09-01

To obtain an understanding of the ethanol loss during cooking of liquid foods containing alcoholic beverages, ethanol concentration was measured as a function of time and remaining volume in meat stocks prepared with wine and beer. A mathematical model describing the decline in volatile compounds during heating of simple liquid foods was derived. The experimental results and the model show that concentration of ethanol at any given time is determined by the initial concentration and a power law function of the remaining volume fraction. The power law function is found to be independent of factors like pot dimensions and temperature. When using a lid to cover the pot during cooking, the model was still valid but the ethanol concentrations decreased more steeply, corresponding to a higher exponent. The results provide a theoretical and empirical guideline for predicting the ethanol concentration in cooked liquid foods. Copyright © 2017 Elsevier Ltd. All rights reserved.

On the probability distribution function of the mass surface density of molecular clouds. I

NASA Astrophysics Data System (ADS)

Fischera, Jörg

2014-05-01

The probability distribution function (PDF) of the mass surface density is an essential characteristic of the structure of molecular clouds or the interstellar medium in general. Observations of the PDF of molecular clouds indicate a composition of a broad distribution around the maximum and a decreasing tail at high mass surface densities. The first component is attributed to the random distribution of gas which is modeled using a log-normal function while the second component is attributed to condensed structures modeled using a simple power-law. The aim of this paper is to provide an analytical model of the PDF of condensed structures which can be used by observers to extract information about the condensations. The condensed structures are considered to be either spheres or cylinders with a truncated radial density profile at cloud radius rcl. The assumed profile is of the form ρ(r) = ρc/ (1 + (r/r0)2)n/ 2 for arbitrary power n where ρc and r0 are the central density and the inner radius, respectively. An implicit function is obtained which either truncates (sphere) or has a pole (cylinder) at maximal mass surface density. The PDF of spherical condensations and the asymptotic PDF of cylinders in the limit of infinite overdensity ρc/ρ(rcl) flattens for steeper density profiles and has a power law asymptote at low and high mass surface densities and a well defined maximum. The power index of the asymptote Σ- γ of the logarithmic PDF (ΣP(Σ)) in the limit of high mass surface densities is given by γ = (n + 1)/(n - 1) - 1 (spheres) or by γ = n/ (n - 1) - 1 (cylinders in the limit of infinite overdensity). Appendices are available in electronic form at http://www.aanda.org

Functionality, Complexity, and Approaches to Assessment of Resilience Under Constrained Energy and Information

DTIC Science & Technology

2015-03-26

albeit powerful , method available for exploring CAS. As discussed above, there are many useful mathematical tools appropriate for CAS modeling. Agent-based...cells, tele- phone calls, and sexual contacts approach power -law distributions. [48] Networks in general are robust against random failures, but...targeted failures can have powerful effects – provided the targeter has a good understanding of the network structure. Some argue (convincingly) that all

Impact of thermal energy storage properties on solar dynamic space power conversion system mass

NASA Technical Reports Server (NTRS)

Juhasz, Albert J.; Coles-Hamilton, Carolyn E.; Lacy, Dovie E.

1987-01-01

A 16 parameter solar concentrator/heat receiver mass model is used in conjunction with Stirling and Brayton Power Conversion System (PCS) performance and mass computer codes to determine the effect of thermal energy storage (TES) material property changes on overall PCS mass as a function of steady state electrical power output. Included in the PCS mass model are component masses as a function of thermal power for: concentrator, heat receiver, heat exchangers (source unless integral with heat receiver, heat sink, regenerator), heat engine units with optional parallel redundancy, power conditioning and control (PC and C), PC and C radiator, main radiator, and structure. Critical TES properties are: melting temperature, heat of fusion, density of the liquid phase, and the ratio of solid-to-liquid density. Preliminary results indicate that even though overalll system efficiency increases with TES melting temperature up to 1400 K for concentrator surface accuracies of 1 mrad or better, reductions in the overall system mass beyond that achievable with lithium fluoride (LiF) can be accomplished only if the heat of fusion is at least 800 kJ/kg and the liquid density is comparable to that of LiF (1880 kg/cu m.

Impact of thermal energy storage properties on solar dynamic space power conversion system mass

NASA Technical Reports Server (NTRS)

Juhasz, Albert J.; Coles-Hamilton, Carolyn E.; Lacy, Dovie E.

1987-01-01

A 16 parameter solar concentrator/heat receiver mass model is used in conjunction with Stirling and Brayton Power Conversion System (PCS) performance and mass computer codes to determine the effect of thermal energy storage (TES) material property changes on overall PCS mass as a function of steady state electrical power output. Included in the PCS mass model are component masses as a function of thermal power for: concentrator, heat receiver, heat exchangers (source unless integral with heat receiver, heat sink, regenerator), heat engine units with optional parallel redundancy, power conditioning and control (PC and C), PC and C radiator, main radiator, and structure. Critical TES properties are: melting temperature, heat of fusion, density of the liquid phase, and the ratio of solid-to-liquid density. Preliminary results indicate that even though overall system efficiency increases with TES melting temperature up to 1400 K for concentrator surface accuracies of 1 mrad or better, reductions in the overall system mass beyond that achievable with lithium fluoride (LiF) can be accomplished only if the heat of fusion is at least 800 kJ/kg and the liquid density is comparable to that of LiF (1800 kg/cu m).

Energy Optimization for a Weak Hybrid Power System of an Automobile Exhaust Thermoelectric Generator

NASA Astrophysics Data System (ADS)

Fang, Wei; Quan, Shuhai; Xie, Changjun; Tang, Xinfeng; Ran, Bin; Jiao, Yatian

2017-11-01

An integrated starter generator (ISG)-type hybrid electric vehicle (HEV) scheme is proposed based on the automobile exhaust thermoelectric generator (AETEG). An eddy current dynamometer is used to simulate the vehicle's dynamic cycle. A weak ISG hybrid bench test system is constructed to test the 48 V output from the power supply system, which is based on engine exhaust-based heat power generation. The thermoelectric power generation-based system must ultimately be tested when integrated into the ISG weak hybrid mixed power system. The test process is divided into two steps: comprehensive simulation and vehicle-based testing. The system's dynamic process is simulated for both conventional and thermoelectric powers, and the dynamic running process comprises four stages: starting, acceleration, cruising and braking. The quantity of fuel available and battery pack energy, which are used as target vehicle energy functions for comparison with conventional systems, are simplified into a single energy target function, and the battery pack's output current is used as the control variable in the thermoelectric hybrid energy optimization model. The system's optimal battery pack output current function is resolved when its dynamic operating process is considered as part of the hybrid thermoelectric power generation system. In the experiments, the system bench is tested using conventional power and hybrid thermoelectric power for the four dynamic operation stages. The optimal battery pack curve is calculated by functional analysis. In the vehicle, a power control unit is used to control the battery pack's output current and minimize energy consumption. Data analysis shows that the fuel economy of the hybrid power system under European Driving Cycle conditions is improved by 14.7% when compared with conventional systems.

Toward Balance Recovery With Leg Prostheses Using Neuromuscular Model Control

PubMed Central

Geyer, Hartmut

2016-01-01

Objective Lower limb amputees are at high risk of falling as current prosthetic legs provide only limited functionality for recovering balance after unexpected disturbances. For instance, the most established control method used on powered leg prostheses tracks local joint impedance functions without taking the global function of the leg in balance recovery into account. Here we explore an alternative control policy for powered transfemoral prostheses that considers the global leg function and is based on a neuromuscular model of human locomotion. Methods We adapt this model to describe and simulate an amputee walking with a powered prosthesis using the proposed control, and evaluate the gait robustness when confronted with rough ground and swing leg disturbances. We then implement and partially evaluate the resulting controller on a leg prosthesis prototype worn by a non-amputee user. Results In simulation, the proposed prosthesis control leads to gaits that are more robust than those obtained by the impedance control method. The initial hardware experiments with the prosthesis prototype show that the proposed control reproduces normal walking patterns qualitatively and effectively responds to disturbances in early and late swing. However, the response to mid-swing disturbances neither replicates human responses nor averts falls. Conclusions The neuromuscular model control is a promising alternative to existing prosthesis controls, although further research will need to improve on the initial implementation and determine how well these results transfer to amputee gait. Significance This work provides a potential avenue for future development of control policies that help improve amputee balance recovery. PMID:26315935

Load allocation of power plant using multi echelon economic dispatch

NASA Astrophysics Data System (ADS)

Wahyuda, Santosa, Budi; Rusdiansyah, Ahmad

2017-11-01

In this paper, the allocation of power plant load which is usually done with a single echelon as in the load flow calculation, is expanded into a multi echelon. A plant load allocation model based on the integration of economic dispatch and multi-echelon problem is proposed. The resulting model is called as Single Objective Multi Echelon Economic Dispatch (SOME ED). This model allows the distribution of electrical power in more detail in the transmission and distribution substations along the existing network. Considering the interconnection system where the distance between the plant and the load center is usually far away, therefore the loss in this model is seen as a function of distance. The advantages of this model is its capability of allocating electrical loads properly, as well as economic dispatch information with the flexibility of electric power system as a result of using multi-echelon. In this model, the flexibility can be viewed from two sides, namely the supply and demand sides, so that the security of the power system is maintained. The model was tested on a small artificial data. The results demonstrated a good performance. It is still very open to further develop the model considering the integration with renewable energy, multi-objective with environmental issues and applied to the case with a larger scale.

Electromagnetic Compatibility Testing Studies

NASA Technical Reports Server (NTRS)

Trost, Thomas F.; Mitra, Atindra K.

1996-01-01

This report discusses the results on analytical models and measurement and simulation of statistical properties from a study of microwave reverberation (mode-stirred) chambers performed at Texas Tech University. Two analytical models of power transfer vs. frequency in a chamber, one for antenna-to-antenna transfer and the other for antenna to D-dot sensor, were experimentally validated in our chamber. Two examples are presented of the measurement and calculation of chamber Q, one for each of the models. Measurements of EM power density validate a theoretical probability distribution on and away from the chamber walls and also yield a distribution with larger standard deviation at frequencies below the range of validity of the theory. Measurements of EM power density at pairs of points which validate a theoretical spatial correlation function on the chamber walls and also yield a correlation function with larger correlation length, R(sub corr), at frequencies below the range of validity of the theory. A numerical simulation, employing a rectangular cavity with a moving wall shows agreement with the measurements. The determination that the lowest frequency at which the theoretical spatial correlation function is valid in our chamber is considerably higher than the lowest frequency recommended by current guidelines for utilizing reverberation chambers in EMC testing. Two suggestions have been made for future studies related to EMC testing.

Insight into RF power requirements and B1 field homogeneity for human MRI via rigorous FDTD approach.

PubMed

Ibrahim, Tamer S; Tang, Lin

2007-06-01

To study the dependence of radiofrequency (RF) power deposition on B(0) field strength for different loads and excitation mechanisms. Studies were performed utilizing a finite difference time domain (FDTD) model that treats the transmit array and the load as a single system. Since it was possible to achieve homogenous excitations across the human head model by varying the amplitudes/phases of the voltages driving the transmit array, studies of the RF power/B(0) field strength (frequency) dependence were achievable under well-defined/fixed/homogenous RF excitation. Analysis illustrating the regime in which the RF power is dependent on the square of the operating frequency is presented. Detailed studies focusing on the RF power requirements as a function of number of excitation ports, driving mechanism, and orientations/positioning within the load are presented. With variable phase/amplitude excitation, as a function of frequency, the peak-then-decrease relation observed in the upper axial slices of brain with quadrature excitation becomes more evident in the lower slices as well. Additionally, homogeneity optimization targeted at minimizing the ratio of maximum/minimum B(1) (+) field intensity within the region of interest, typically results in increased RF power requirements (standard deviation was not considered in this study). Increasing the number of excitation ports, however, can result in significant RF power reduction. (c) 2007 Wiley-Liss, Inc.

The Singularity Mystery Associated with a Radially Continuous Maxwell Viscoelastic Structure

NASA Technical Reports Server (NTRS)

Fang, Ming; Hager, Bradford H.

1995-01-01

The singularity problem associated with a radially continuous Maxwell viscoclastic structure is investigated. A special tool called the isolation function is developed. Results calculated using the isolation function show that the discrete model assumption is no longer valid when the viscoelastic parameter becomes a continuous function of radius. Continuous variations in the upper mantle viscoelastic parameter are especially powerful in destroying the mode-like structures. The contribution to the load Love numbers of the singularities is sensitive to the convexity of the viscoelastic parameter models. The difference between the vertical response and the horizontal response found in layered viscoelastic parameter models remains with continuous models.

Balancing reliability and cost to choose the best power subsystem

NASA Technical Reports Server (NTRS)

Suich, Ronald C.; Patterson, Richard L.

1991-01-01

A mathematical model is presented for computing total (spacecraft) subsystem cost including both the basic subsystem cost and the expected cost due to the failure of the subsystem. This model is then used to determine power subsystem cost as a function of reliability and redundancy. Minimum cost and maximum reliability and/or redundancy are not generally equivalent. Two example cases are presented. One is a small satellite, and the other is an interplanetary spacecraft.

[Spectral quantitative analysis by nonlinear partial least squares based on neural network internal model for flue gas of thermal power plant].

PubMed

Cao, Hui; Li, Yao-Jiang; Zhou, Yan; Wang, Yan-Xia

2014-11-01

To deal with nonlinear characteristics of spectra data for the thermal power plant flue, a nonlinear partial least square (PLS) analysis method with internal model based on neural network is adopted in the paper. The latent variables of the independent variables and the dependent variables are extracted by PLS regression firstly, and then they are used as the inputs and outputs of neural network respectively to build the nonlinear internal model by train process. For spectra data of flue gases of the thermal power plant, PLS, the nonlinear PLS with the internal model of back propagation neural network (BP-NPLS), the non-linear PLS with the internal model of radial basis function neural network (RBF-NPLS) and the nonlinear PLS with the internal model of adaptive fuzzy inference system (ANFIS-NPLS) are compared. The root mean square error of prediction (RMSEP) of sulfur dioxide of BP-NPLS, RBF-NPLS and ANFIS-NPLS are reduced by 16.96%, 16.60% and 19.55% than that of PLS, respectively. The RMSEP of nitric oxide of BP-NPLS, RBF-NPLS and ANFIS-NPLS are reduced by 8.60%, 8.47% and 10.09% than that of PLS, respectively. The RMSEP of nitrogen dioxide of BP-NPLS, RBF-NPLS and ANFIS-NPLS are reduced by 2.11%, 3.91% and 3.97% than that of PLS, respectively. Experimental results show that the nonlinear PLS is more suitable for the quantitative analysis of glue gas than PLS. Moreover, by using neural network function which can realize high approximation of nonlinear characteristics, the nonlinear partial least squares method with internal model mentioned in this paper have well predictive capabilities and robustness, and could deal with the limitations of nonlinear partial least squares method with other internal model such as polynomial and spline functions themselves under a certain extent. ANFIS-NPLS has the best performance with the internal model of adaptive fuzzy inference system having ability to learn more and reduce the residuals effectively. Hence, ANFIS-NPLS is an accurate and useful quantitative thermal power plant flue gas analysis method.

Power in the Classroom VI: Verbal Control Strategies, Nonverbal Immediacy and Affective Learning.

ERIC Educational Resources Information Center

Plax, Timothy G.; And Others

Recognizing that nonverbal behaviors typically provide the framework for interpreting verbal messages, this project (the sixth in a series of projects designed to examine teacher power in the classroom) proposed and sequentially tested a heuristic model of student affective learning as a function of behavior alteration techniques and teacher…

An Experiment on Salience as a Function of the Discriminatory Power of an Attribute.

ERIC Educational Resources Information Center

Finn, Michael S.

Carter's model of affective relations (1965) and Chaffee's research on cognitive discrepancies and communication (1959) are used to test the hypotheses that increasing an attribute's discriminatory power will increase attribute salience and that increasing the exclusiveness of an object's attributes will increase objective salience. The current…

Second Magnetoplasmadynamic Thruster Workshop

NASA Technical Reports Server (NTRS)

1992-01-01

The meeting focused on progress made in establishing performance and lifetime expectations of magnetoplasmadynamic (MPD) thrusters as functions of power, propellant, and design; models for the plasma flow and electrode components; viability and transportability of quasi-steady thruster testing; engineering requirements for high power, long life thrusters; and facilities and their requirements for performance and life testing.

A Graphical Systems Model and Tissue-specific Functional Gene Sets to Aid Transcriptomic Analysis of Chemical Impacts on the Female Teleost Reproductive Axis

EPA Science Inventory

Oligonucleotide microarrays and other ‘omics’ approaches are powerful tools for unsupervised analysis of chemical impacts on biological systems. However, the lack of well annotated biological pathways for many aquatic organisms, including fish, and the poor power of microarray-b...

First quantitative measurements of charged-particle stopping and its dependence on electron temperature and density in Inertial-Confinement-Fusion plasmas

NASA Astrophysics Data System (ADS)

Frenje, J.; Li, C. K.; Séguin, F.; Zylstra, A.; Rinderknecht, H.; Petrasso, R.; Delettrez, J.; Glebov, V.; Sangster, T.

2013-10-01

We report on the first quantitative measurements of charged-particle stopping in Inertial-Confinement-Fusion (ICF) plasmas at various conditions. In these experiments, four charged fusion products from the DD and D3He reactions in D3He gas-filled filled implosions were used to determine the stopping power of ICF plasmas at electron temperatures (Te) , ion temperatures (Ti) , and areal densities (ρR) in the range of 0.6-4.0 keV, 3-14 keV and 2-10 mg/cm2, respectively. The resulting data, in the form of measured energy downshift of the charged fusion products, clearly indicate that the stopping-power function depends strongly on Te. It was also observed that the stopping-power function change in characteristics for higher-density implosions in which ions and electrons equilibrate faster, resulting in higher Te relative to Ti and higher ρR s. These results will be modelled by Landau-Spitzer theory and contrasted to different stopping-power models. This work was partially supported by the US DOE, NLUF, LLE, and GA.

Modeling the resilience of critical infrastructure: the role of network dependencies.

PubMed

Guidotti, Roberto; Chmielewski, Hana; Unnikrishnan, Vipin; Gardoni, Paolo; McAllister, Therese; van de Lindt, John

2016-01-01

Water and wastewater network, electric power network, transportation network, communication network, and information technology network are among the critical infrastructure in our communities; their disruption during and after hazard events greatly affects communities' well-being, economic security, social welfare, and public health. In addition, a disruption in one network may cause disruption to other networks and lead to their reduced functionality. This paper presents a unified theoretical methodology for the modeling of dependent/interdependent infrastructure networks and incorporates it in a six-step probabilistic procedure to assess their resilience. Both the methodology and the procedure are general, can be applied to any infrastructure network and hazard, and can model different types of dependencies between networks. As an illustration, the paper models the direct effects of seismic events on the functionality of a potable water distribution network and the cascading effects of the damage of the electric power network (EPN) on the potable water distribution network (WN). The results quantify the loss of functionality and delay in the recovery process due to dependency of the WN on the EPN. The results show the importance of capturing the dependency between networks in modeling the resilience of critical infrastructure.

Modeling the resilience of critical infrastructure: the role of network dependencies

PubMed Central

Guidotti, Roberto; Chmielewski, Hana; Unnikrishnan, Vipin; Gardoni, Paolo; McAllister, Therese; van de Lindt, John

2017-01-01

Water and wastewater network, electric power network, transportation network, communication network, and information technology network are among the critical infrastructure in our communities; their disruption during and after hazard events greatly affects communities’ well-being, economic security, social welfare, and public health. In addition, a disruption in one network may cause disruption to other networks and lead to their reduced functionality. This paper presents a unified theoretical methodology for the modeling of dependent/interdependent infrastructure networks and incorporates it in a six-step probabilistic procedure to assess their resilience. Both the methodology and the procedure are general, can be applied to any infrastructure network and hazard, and can model different types of dependencies between networks. As an illustration, the paper models the direct effects of seismic events on the functionality of a potable water distribution network and the cascading effects of the damage of the electric power network (EPN) on the potable water distribution network (WN). The results quantify the loss of functionality and delay in the recovery process due to dependency of the WN on the EPN. The results show the importance of capturing the dependency between networks in modeling the resilience of critical infrastructure. PMID:28825037

ATF neutral beam injection: optimization of beam alignment and aperturing

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

Morris, R.N.; Fowler, R.H.; Rome, J.A.

1985-12-01

The application of the existing Impurity Study Experiment (ISX-B) neutral beam injectors for the Advanced Toroidal Facility (ATF) is studied. It is determined that with the practical considerations of beam aperturing, ATF vacuum vessel complexity, and realistic beam modeling, the power absorbed by the plasma will be approximately 57% of the extracted neutral beam power, which corresponds to an injected power of about 1.5 MW. By reducing the beam divergence to a 1/sup 0/ Gaussian distribution, the absorbed power could be increased to 93%. The power delivered to the plasma is found to be a strong function of the beammore » divergence but only a weak function of the beam focal length. Shinethrough can be a serious problem if very low density startups are necessary. Preliminary calculations indicate that there will be no excessive fast-ion losses. 12 refs., 17 figs., 1 tab.« less

Two solar proton fluence models based on ground level enhancement observations

NASA Astrophysics Data System (ADS)

Raukunen, Osku; Vainio, Rami; Tylka, Allan J.; Dietrich, William F.; Jiggens, Piers; Heynderickx, Daniel; Dierckxsens, Mark; Crosby, Norma; Ganse, Urs; Siipola, Robert

2018-01-01

Solar energetic particles (SEPs) constitute an important component of the radiation environment in interplanetary space. Accurate modeling of SEP events is crucial for the mitigation of radiation hazards in spacecraft design. In this study we present two new statistical models of high energy solar proton fluences based on ground level enhancement (GLE) observations during solar cycles 19-24. As the basis of our modeling, we utilize a four parameter double power law function (known as the Band function) fits to integral GLE fluence spectra in rigidity. In the first model, the integral and differential fluences for protons with energies between 10 MeV and 1 GeV are calculated using the fits, and the distributions of the fluences at certain energies are modeled with an exponentially cut-off power law function. In the second model, we use a more advanced methodology: by investigating the distributions and relationships of the spectral fit parameters we find that they can be modeled as two independent and two dependent variables. Therefore, instead of modeling the fluences separately at different energies, we can model the shape of the fluence spectrum. We present examples of modeling results and show that the two methodologies agree well except for a short mission duration (1 year) at low confidence level. We also show that there is a reasonable agreement between our models and three well-known solar proton models (JPL, ESP and SEPEM), despite the differences in both the modeling methodologies and the data used to construct the models.

Design of a portable powered seat lift

NASA Technical Reports Server (NTRS)

Weddendorf, Bruce

1993-01-01

People suffering from degenerative hip or knee joints find sitting and rising from a seated position very difficult. These people can rely on large stationary chairs at home, but must ask others for assistance when rising from any other chair. An orthopedic surgeon identified to the MSFC Technology Utilization Office the need for development of a portable device that could perform a similar function to the stationary lift chairs. The MSFC Structural Development Branch answered the Technology Utilization Office's request for design of a portable powered seat lift. The device is a seat cushion that opens under power, lifting the user to near-standing positions. The largest challenge was developing a mechanism to provide a stable lift over the large range of motion needed, and fold flat enough to be comfortable to sit on. CAD 3-D modeling was used to generate complete drawings for the prototype, and a full-scale working model of the Seat lift was made based on the drawings. The working model is of low strength, but proves the function of the mechanism and the concept.

Uncertainty Propagation in OMFIT

NASA Astrophysics Data System (ADS)

Smith, Sterling; Meneghini, Orso; Sung, Choongki

2017-10-01

A rigorous comparison of power balance fluxes and turbulent model fluxes requires the propagation of uncertainties in the kinetic profiles and their derivatives. Making extensive use of the python uncertainties package, the OMFIT framework has been used to propagate covariant uncertainties to provide an uncertainty in the power balance calculation from the ONETWO code, as well as through the turbulent fluxes calculated by the TGLF code. The covariant uncertainties arise from fitting 1D (constant on flux surface) density and temperature profiles and associated random errors with parameterized functions such as a modified tanh. The power balance and model fluxes can then be compared with quantification of the uncertainties. No effort is made at propagating systematic errors. A case study will be shown for the effects of resonant magnetic perturbations on the kinetic profiles and fluxes at the top of the pedestal. A separate attempt at modeling the random errors with Monte Carlo sampling will be compared to the method of propagating the fitting function parameter covariant uncertainties. Work supported by US DOE under DE-FC02-04ER54698, DE-FG2-95ER-54309, DE-SC 0012656.

Phenomenological model of nuclear primary air showers

NASA Technical Reports Server (NTRS)

Tompkins, D. R., Jr.; Saterlie, S. F.

1976-01-01

The development of proton primary air showers is described in terms of a model based on a hadron core plus an electromagnetic cascade. The muon component is neglected. The model uses three parameters: a rate at which hadron core energy is converted into electromagnetic cascade energy and a two-parameter sea-level shower-age function. By assuming an interaction length for the primary nucleus, the model is extended to nuclear primaries. Both models are applied over the energy range from 10 to the 13th power to 10 to the 21st power eV. Both models describe the size and age structure (neglecting muons) from a depth of 342 to 2052 g/sq cm.

Mobility of power-law and Carreau fluids through fibrous media.

PubMed

Shahsavari, Setareh; McKinley, Gareth H

2015-12-01

The flow of generalized Newtonian fluids with a rate-dependent viscosity through fibrous media is studied, with a focus on developing relationships for evaluating the effective fluid mobility. Three methods are used here: (i) a numerical solution of the Cauchy momentum equation with the Carreau or power-law constitutive equations for pressure-driven flow in a fiber bed consisting of a periodic array of cylindrical fibers, (ii) an analytical solution for a unit cell model representing the flow characteristics of a periodic fibrous medium, and (iii) a scaling analysis of characteristic bulk parameters such as the effective shear rate, the effective viscosity, geometrical parameters of the system, and the fluid rheology. Our scaling analysis yields simple expressions for evaluating the transverse mobility functions for each model, which can be used for a wide range of medium porosity and fluid rheological parameters. While the dimensionless mobility is, in general, a function of the Carreau number and the medium porosity, our results show that for porosities less than ɛ≃0.65, the dimensionless mobility becomes independent of the Carreau number and the mobility function exhibits power-law characteristics as a result of the high shear rates at the pore scale. We derive a suitable criterion for determining the flow regime and the transition from a constant viscosity Newtonian response to a power-law regime in terms of a new Carreau number rescaled with a dimensionless function which incorporates the medium porosity and the arrangement of fibers.

Self-discharge analysis and characterization of supercapacitors for environmentally powered wireless sensor network applications

NASA Astrophysics Data System (ADS)

Yang, Hengzhao; Zhang, Ying

2011-10-01

A new approach is presented to characterize the variable leakage resistance, a parameter in the variable leakage resistance model we developed to model supercapacitors used in environmentally powered wireless sensor network applications. Based on an analysis of the supercapacitor terminal behavior during the self-discharge, the variable leakage resistance is modeled as a function of the supercapacitor terminal voltage instead of the self-discharge time, which is more practical for an environmentally powered wireless sensor node. The new characterization approach is implemented and validated using MATLAB Simulink with a 10 F supercapacitor as an example. In addition, effects of initial voltages and temperatures on the supercapacitor self-discharge rate and the variable leakage resistance value are explored.

Dynamic intersectoral models with power-law memory

NASA Astrophysics Data System (ADS)

Tarasova, Valentina V.; Tarasov, Vasily E.

2018-01-01

Intersectoral dynamic models with power-law memory are proposed. The equations of open and closed intersectoral models, in which the memory effects are described by the Caputo derivatives of non-integer orders, are derived. We suggest solutions of these equations, which have the form of linear combinations of the Mittag-Leffler functions and which are characterized by different effective growth rates. Examples of intersectoral dynamics with power-law memory are suggested for two sectoral cases. We formulate two principles of intersectoral dynamics with memory: the principle of changing of technological growth rates and the principle of domination change. It has been shown that in the input-output economic dynamics the effects of fading memory can change the economic growth rate and dominant behavior of economic sectors.

Tachyon with an inverse power-law potential in a braneworld cosmology

NASA Astrophysics Data System (ADS)

Bilić, Neven; Domazet, Silvije; Djordjevic, Goran S.

2017-08-01

We study a tachyon cosmological model based on the dynamics of a 3-brane in the bulk of the second Randall-Sundrum model extended to more general warp functions. A well known prototype of such a generalization is the bulk with a selfinteracting scalar field. As a consequence of a generalized bulk geometry the cosmology on the observer brane is modified by the scale dependent four-dimensional gravitational constant. In particular, we study a power law warp factor which generates an inverse power-law potential V\\propto \\varphi-n of the tachyon field φ. We find a critical power n cr that divides two subclasses with distinct asymptotic behaviors: a dust universe for n>n_cr and a quasi de Sitter universe for 0.

Regularized lattice Boltzmann model for immiscible two-phase flows with power-law rheology

NASA Astrophysics Data System (ADS)

Ba, Yan; Wang, Ningning; Liu, Haihu; Li, Qiang; He, Guoqiang

2018-03-01

In this work, a regularized lattice Boltzmann color-gradient model is developed for the simulation of immiscible two-phase flows with power-law rheology. This model is as simple as the Bhatnagar-Gross-Krook (BGK) color-gradient model except that an additional regularization step is introduced prior to the collision step. In the regularization step, the pseudo-inverse method is adopted as an alternative solution for the nonequilibrium part of the total distribution function, and it can be easily extended to other discrete velocity models no matter whether a forcing term is considered or not. The obtained expressions for the nonequilibrium part are merely related to macroscopic variables and velocity gradients that can be evaluated locally. Several numerical examples, including the single-phase and two-phase layered power-law fluid flows between two parallel plates, and the droplet deformation and breakup in a simple shear flow, are conducted to test the capability and accuracy of the proposed color-gradient model. Results show that the present model is more stable and accurate than the BGK color-gradient model for power-law fluids with a wide range of power-law indices. Compared to its multiple-relaxation-time counterpart, the present model can increase the computing efficiency by around 15%, while keeping the same accuracy and stability. Also, the present model is found to be capable of reasonably predicting the critical capillary number of droplet breakup.

Research and exploration of product innovative design for function

NASA Astrophysics Data System (ADS)

Wang, Donglin; Wei, Zihui; Wang, Youjiang; Tan, Runhua

2009-07-01

Products innovation is under the prerequisite of realizing the new function, the realization of the new function must solve the contradiction. A new process model of new product innovative design was proposed based on Axiomatic Design (AD) Theory and Functional Structure Analysis (FSA), imbedded Principle of Solving Contradiction. In this model, employ AD Theory to guide FSA, determine the contradiction for the realization of the principle solution. To provide powerful support for innovative design tools in principle solution, Principle of Solving Contradiction in the model were imbedded, so as to boost up the innovation of principle solution. As a case study, an innovative design of button battery separator paper punching machine has been achieved with application of the proposed model.

Detectability of large-scale power suppression in the galaxy distribution

NASA Astrophysics Data System (ADS)

Gibelyou, Cameron; Huterer, Dragan; Fang, Wenjuan

2010-12-01

Suppression in primordial power on the Universe’s largest observable scales has been invoked as a possible explanation for large-angle observations in the cosmic microwave background, and is allowed or predicted by some inflationary models. Here we investigate the extent to which such a suppression could be confirmed by the upcoming large-volume redshift surveys. For definiteness, we study a simple parametric model of suppression that improves the fit of the vanilla ΛCDM model to the angular correlation function measured by WMAP in cut-sky maps, and at the same time improves the fit to the angular power spectrum inferred from the maximum likelihood analysis presented by the WMAP team. We find that the missing power at large scales, favored by WMAP observations within the context of this model, will be difficult but not impossible to rule out with a galaxy redshift survey with large-volume (˜100Gpc3). A key requirement for success in ruling out power suppression will be having redshifts of most galaxies detected in the imaging survey.

The relationship between movement speed and duration during soccer matches.

PubMed

Roecker, Kai; Mahler, Hubert; Heyde, Christian; Röll, Mareike; Gollhofer, Albert

2017-01-01

The relationship between the time duration of movement (t(dur)) and related maximum possible power output has been studied and modeled under many conditions. Inspired by the so-called power profiles known for discontinuous endurance sports like cycling, and the critical power concept of Monod and Scherrer, the aim of this study was to evaluate the numerical characteristics of the function between maximum horizontal movement velocity (HSpeed) and t(dur) in soccer. To evaluate this relationship, GPS data from 38 healthy soccer players and 82 game participations (≥30 min active playtime) were used to select maximum HSpeed for 21 distinct t(dur) values (between 0.3 s and 2,700 s) based on moving medians with an incremental t(dur) window-size. As a result, the relationship between HSpeed and Log(t(dur)) appeared reproducibly as a sigmoidal decay function, and could be fitted to a five-parameter equation with upper and lower asymptotes, and an inflection point, power and decrease rate. Thus, the first three parameters described individual characteristics if evaluated using mixed-model analysis. This study shows for the first time the general numerical relationship between t(dur) and HSpeed in soccer games. In contrast to former descriptions that have evaluated speed against power, HSpeed against t(dur) always yields a sigmoidal shape with a new upper asymptote. The evaluated curve fit potentially describes the maximum moving speed of individual players during the game, and allows for concise interpretations of the functional state of team sports athletes.

The relationship between movement speed and duration during soccer matches

PubMed Central

Mahler, Hubert; Heyde, Christian; Röll, Mareike; Gollhofer, Albert

2017-01-01

The relationship between the time duration of movement (t(dur)) and related maximum possible power output has been studied and modeled under many conditions. Inspired by the so-called power profiles known for discontinuous endurance sports like cycling, and the critical power concept of Monod and Scherrer, the aim of this study was to evaluate the numerical characteristics of the function between maximum horizontal movement velocity (HSpeed) and t(dur) in soccer. To evaluate this relationship, GPS data from 38 healthy soccer players and 82 game participations (≥30 min active playtime) were used to select maximum HSpeed for 21 distinct t(dur) values (between 0.3 s and 2,700 s) based on moving medians with an incremental t(dur) window-size. As a result, the relationship between HSpeed and Log(t(dur)) appeared reproducibly as a sigmoidal decay function, and could be fitted to a five-parameter equation with upper and lower asymptotes, and an inflection point, power and decrease rate. Thus, the first three parameters described individual characteristics if evaluated using mixed-model analysis. This study shows for the first time the general numerical relationship between t(dur) and HSpeed in soccer games. In contrast to former descriptions that have evaluated speed against power, HSpeed against t(dur) always yields a sigmoidal shape with a new upper asymptote. The evaluated curve fit potentially describes the maximum moving speed of individual players during the game, and allows for concise interpretations of the functional state of team sports athletes. PMID:28742832

Stochastic multi-objective model for optimal energy exchange optimization of networked microgrids with presence of renewable generation under risk-based strategies.

PubMed

Gazijahani, Farhad Samadi; Ravadanegh, Sajad Najafi; Salehi, Javad

2018-02-01

The inherent volatility and unpredictable nature of renewable generations and load demand pose considerable challenges for energy exchange optimization of microgrids (MG). To address these challenges, this paper proposes a new risk-based multi-objective energy exchange optimization for networked MGs from economic and reliability standpoints under load consumption and renewable power generation uncertainties. In so doing, three various risk-based strategies are distinguished by using conditional value at risk (CVaR) approach. The proposed model is specified as a two-distinct objective function. The first function minimizes the operation and maintenance costs, cost of power transaction between upstream network and MGs as well as power loss cost, whereas the second function minimizes the energy not supplied (ENS) value. Furthermore, the stochastic scenario-based approach is incorporated into the approach in order to handle the uncertainty. Also, Kantorovich distance scenario reduction method has been implemented to reduce the computational burden. Finally, non-dominated sorting genetic algorithm (NSGAII) is applied to minimize the objective functions simultaneously and the best solution is extracted by fuzzy satisfying method with respect to risk-based strategies. To indicate the performance of the proposed model, it is performed on the modified IEEE 33-bus distribution system and the obtained results show that the presented approach can be considered as an efficient tool for optimal energy exchange optimization of MGs. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Dynamical Correlation In Some Liquid Alkaline Earth Metals Near Melting

NASA Astrophysics Data System (ADS)

Thakore, B. Y.; Suthar, P. H.; Khambholja, S. G.; Gajjar, P. N.; Jani, A. R.

2010-12-01

The study of dynamical variables: velocity autocorrelation function (VACF) and power spectrum of liquid alkaline earth metals (Ca, Sr, and Ba) have been presented based on the static harmonic well approximation. The effective interatomic potential for liquid metals is computed using our well recognized model potential with the exchange correlation functions due to Hartree, Taylor, Ichimaru and Utsumi, Farid et al. and Sarkar et al. It is observed that the VACF computed using Sarkar et al. gives the good agreement with available molecular dynamics simulation (MD) results [Phys Rev. B 62, 14818 (2000)]. The shoulder of the power spectrum depends upon the type of local field correlation function used.

Optimum dimensions of power solenoids for magnetic suspension

NASA Technical Reports Server (NTRS)

Kaznacheyev, B. A.

1985-01-01

Design optimization of power solenoids for controllable and stabilizable magnetic suspensions with force compensation in a wind tunnel is shown. It is assumed that the model of a levitating body is a sphere of ferromagnetic material with constant magnetic permeability. This sphere, with a radius much smaller than its distance from the solenoid above, is to be maintained in position on the solenoid axis by balance of the vertical electromagnetic force and the force of gravitation. The necessary vertical (axial) force generated by the solenoid is expressed as a function of relevant system dimensions, solenoid design parameters, and physical properties of the body. Three families of curves are obtained which depict the solenoid power for a given force as a function of the solenoid length with either outside radius or inside radius as a variable parameter and as a function of the outside radius with inside radius as a variable parameter. The curves indicate the optimum solenoid length and outside radius, for minimum power, corresponding to a given outside radius and inside radius, respectively.

Creating of structure of facts for the knowledge base of an expert system for wind power plant's equipment diagnosis

NASA Astrophysics Data System (ADS)

Duer, Stanisław; Wrzesień, Paweł; Duer, Radosław

2017-10-01

This article describes rules and conditions for making a structure (a set) of facts for an expert knowledge base of the intelligent system to diagnose Wind Power Plants' equipment. Considering particular operational conditions of a technical object, that is a set of Wind Power Plant's equipment, this is a significant issue. A structural model of Wind Power Plant's equipment is developed. Based on that, a functional - diagnostic model of Wind Power Plant's equipment is elaborated. That model is a basis for determining primary elements of the object structure, as well as for interpreting a set of diagnostic signals and their reference signals. The key content of this paper is a description of rules for building of facts on the basis of developed analytical dependence. According to facts, their dependence is described by rules for transferring of a set of pieces of diagnostic information into a specific set of facts. The article consists of four chapters that concern particular issues on the subject.

Contingency Analysis Post-Processing With Advanced Computing and Visualization

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

Chen, Yousu; Glaesemann, Kurt; Fitzhenry, Erin

Contingency analysis is a critical function widely used in energy management systems to assess the impact of power system component failures. Its outputs are important for power system operation for improved situational awareness, power system planning studies, and power market operations. With the increased complexity of power system modeling and simulation caused by increased energy production and demand, the penetration of renewable energy and fast deployment of smart grid devices, and the trend of operating grids closer to their capacity for better efficiency, more and more contingencies must be executed and analyzed quickly in order to ensure grid reliability andmore » accuracy for the power market. Currently, many researchers have proposed different techniques to accelerate the computational speed of contingency analysis, but not much work has been published on how to post-process the large amount of contingency outputs quickly. This paper proposes a parallel post-processing function that can analyze contingency analysis outputs faster and display them in a web-based visualization tool to help power engineers improve their work efficiency by fast information digestion. Case studies using an ESCA-60 bus system and a WECC planning system are presented to demonstrate the functionality of the parallel post-processing technique and the web-based visualization tool.« less

Explanation of power law behavior of autoregressive conditional duration processes based on the random multiplicative process

NASA Astrophysics Data System (ADS)

Sato, Aki-Hiro

2004-04-01

Autoregressive conditional duration (ACD) processes, which have the potential to be applied to power law distributions of complex systems found in natural science, life science, and social science, are analyzed both numerically and theoretically. An ACD(1) process exhibits the singular second order moment, which suggests that its probability density function (PDF) has a power law tail. It is verified that the PDF of the ACD(1) has a power law tail with an arbitrary exponent depending on a model parameter. On the basis of theory of the random multiplicative process a relation between the model parameter and the power law exponent is theoretically derived. It is confirmed that the relation is valid from numerical simulations. An application of the ACD(1) to intervals between two successive transactions in a foreign currency market is shown.

Explanation of power law behavior of autoregressive conditional duration processes based on the random multiplicative process.

PubMed

Sato, Aki-Hiro

2004-04-01

Autoregressive conditional duration (ACD) processes, which have the potential to be applied to power law distributions of complex systems found in natural science, life science, and social science, are analyzed both numerically and theoretically. An ACD(1) process exhibits the singular second order moment, which suggests that its probability density function (PDF) has a power law tail. It is verified that the PDF of the ACD(1) has a power law tail with an arbitrary exponent depending on a model parameter. On the basis of theory of the random multiplicative process a relation between the model parameter and the power law exponent is theoretically derived. It is confirmed that the relation is valid from numerical simulations. An application of the ACD(1) to intervals between two successive transactions in a foreign currency market is shown.

The power laws of nanoscale forces in ambient conditions

NASA Astrophysics Data System (ADS)

Chiesa, Matteo; Santos, Sergio; Lai, Chia-Yun

Power laws are ubiquitous in the physical sciences and indispensable to qualitatively and quantitatively describe physical phenomena. A nanoscale force law that accurately describes the phenomena observed in ambient conditions at several nm or fractions of a nm above a surface however is still lacking. Here we report a power law derived from experimental data and describing the interaction between an atomic force microscope AFM tip modelled as a sphere and a surface in ambient conditions. By employing a graphite surface as a model system the resulting effective power is found to be a function of the tip radius and the distance. The data suggest a nano to mesoscale transition in the power law that results in relative agreement with the distance-dependencies predicted by the Hamaker and Lifshitz theories for van der Waals forces for the larger tip radii only

New tools for the analysis of glial cell biology in Drosophila.

PubMed

Awasaki, Takeshi; Lee, Tzumin

2011-09-01

Because of its genetic, molecular, and behavioral tractability, Drosophila has emerged as a powerful model system for studying molecular and cellular mechanisms underlying the development and function of nervous systems. The Drosophila nervous system has fewer neurons and exhibits a lower glia:neuron ratio than is seen in vertebrate nervous systems. Despite the simplicity of the Drosophila nervous system, glial organization in flies is as sophisticated as it is in vertebrates. Furthermore, fly glial cells play vital roles in neural development and behavior. In addition, powerful genetic tools are continuously being created to explore cell function in vivo. In taking advantage of these features, the fly nervous system serves as an excellent model system to study general aspects of glial cell development and function in vivo. In this article, we review and discuss advanced genetic tools that are potentially useful for understanding glial cell biology in Drosophila. Copyright © 2011 Wiley-Liss, Inc.

Stochastic methods for analysis of power flow in electric networks

NASA Astrophysics Data System (ADS)

1982-09-01

The modeling and effects of probabilistic behavior on steady state power system operation were analyzed. A solution to the steady state network flow equations which adhere both to Kirchoff's Laws and probabilistic laws, using either combinatorial or functional approximation techniques was obtained. The development of sound techniques for producing meaningful data to serve as input is examined. Electric demand modeling, equipment failure analysis, and algorithm development are investigated. Two major development areas are described: a decomposition of stochastic processes which gives stationarity, ergodicity, and even normality; and a powerful surrogate probability approach using proportions of time which allows the calculation of joint events from one dimensional probability spaces.

Power Hardware-in-the-Loop Evaluation of PV Inverter Grid Support on Hawaiian Electric Feeders: Preprint

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

Nelson, Austin; Prabakar, Kumaraguru; Nagarajan, Adarsh

As more grid-connected photovoltaic (PV) inverters become compliant with evolving interconnections requirements, there is increased interest from utilities in understanding how to best deploy advanced grid-support functions (GSF) in the field. One efficient and cost-effective method to examine such deployment options is to leverage power hardware-in-the-loop (PHIL) testing methods. Two Hawaiian Electric feeder models were converted to real-time models in the OPAL-RT real-time digital testing platform, and integrated with models of GSF capable PV inverters that were modeled from characterization test data. The integrated model was subsequently used in PHIL testing to evaluate the effects of different fixed power factormore » and volt-watt control settings on voltage regulation of the selected feeders. The results of this study were provided as inputs for field deployment and technical interconnection requirements for grid-connected PV inverters on the Hawaiian Islands.« less

An asymptotic theory for cross-correlation between auto-correlated sequences and its application on neuroimaging data.

PubMed

Zhou, Yunyi; Tao, Chenyang; Lu, Wenlian; Feng, Jianfeng

2018-04-20

Functional connectivity is among the most important tools to study brain. The correlation coefficient, between time series of different brain areas, is the most popular method to quantify functional connectivity. Correlation coefficient in practical use assumes the data to be temporally independent. However, the time series data of brain can manifest significant temporal auto-correlation. A widely applicable method is proposed for correcting temporal auto-correlation. We considered two types of time series models: (1) auto-regressive-moving-average model, (2) nonlinear dynamical system model with noisy fluctuations, and derived their respective asymptotic distributions of correlation coefficient. These two types of models are most commonly used in neuroscience studies. We show the respective asymptotic distributions share a unified expression. We have verified the validity of our method, and shown our method exhibited sufficient statistical power for detecting true correlation on numerical experiments. Employing our method on real dataset yields more robust functional network and higher classification accuracy than conventional methods. Our method robustly controls the type I error while maintaining sufficient statistical power for detecting true correlation in numerical experiments, where existing methods measuring association (linear and nonlinear) fail. In this work, we proposed a widely applicable approach for correcting the effect of temporal auto-correlation on functional connectivity. Empirical results favor the use of our method in functional network analysis. Copyright © 2018. Published by Elsevier B.V.

Functional and Physical Outcomes following Use of a Flexible CO2 Laser Fiber and Bipolar Electrocautery in Close Proximity to the Rat Sciatic Nerve with Correlation to an In Vitro Thermal Profile Model

PubMed Central

Robinson, A. M.; Fishman, A. J.; Bendok, B. R.; Richter, C.-P.

2015-01-01

This study compared functional and physical collateral damage to a nerve when operating a Codman MALIS Bipolar Electrosurgical System CMC-III or a CO2 laser coupled to a laser, with correlation to an in vitro model of heating profiles created by the devices in thermochromic ink agarose. Functional damage of the rat sciatic nerve after operating the MALIS or CO2 laser at various power settings and proximities to the nerve was measured by electrically evoked nerve action potentials, and histology of the nerve was used to assess physical damage. Thermochromic ink dissolved in agarose was used to model the spatial and temporal profile of the collateral heating zone of the electrosurgical system and the laser ablation cone. We found that this laser can be operated at 2 W directly above the nerve with minimal damage, while power settings of 5 W and 10 W resulted in acute functional and physical nerve damage, correlating with the maximal heating cone in the thermochromic ink model. MALIS settings up to 40 (11 W) did not result in major functional or physical nerve damage until the nerve was between the forceps tips, correlating with the hottest zone, localized discretely between the tips. PMID:25699266

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

Solar Power Satellite (SPS) solid-state antenna power combiner

NASA Technical Reports Server (NTRS)

1980-01-01

A low loss power-combining microstrip antenna suitable for solid state solar power satellite (SPS) application was developed. A unique approach for performing both the combining and radiating function in a single cavity-type circuit was verified, representing substantial refinements over previous demonstration models in terms of detailed geometry to obtain good matching and adequate bandwidth at the design frequency. The combiner circuit was designed, built, and tested and the overall results support the view that the solid state power-combining antenna approach is a viable candidate for a solid state SPS antenna building block.

Design and implementation of a simple nuclear power plant simulator

NASA Astrophysics Data System (ADS)

Miller, William H.

1983-02-01

A simple PWR nuclear power plant simulator has been designed and implemented on a minicomputer system. The system is intended for students use in understanding the power operation of a nuclear power plant. A PDP-11 minicomputer calculates reactor parameters in real time, uses a graphics terminal to display the results and a keyboard and joystick for control functions. Plant parameters calculated by the model include the core reactivity (based upon control rod positions, soluble boron concentration and reactivity feedback effects), the total core power, the axial core power distribution, the temperature and pressure in the primary and secondary coolant loops, etc.

Galaxy power spectrum in redshift space: Combining perturbation theory with the halo model

NASA Astrophysics Data System (ADS)

Okumura, Teppei; Hand, Nick; Seljak, Uroš; Vlah, Zvonimir; Desjacques, Vincent

2015-11-01

Theoretical modeling of the redshift-space power spectrum of galaxies is crucially important to correctly extract cosmological information from galaxy redshift surveys. The task is complicated by the nonlinear biasing and redshift space distortion (RSD) effects, which change with halo mass, and by the wide distribution of halo masses and their occupations by galaxies. One of the main modeling challenges is the existence of satellite galaxies that have both radial distribution inside the halos and large virial velocities inside halos, a phenomenon known as the Finger-of-God (FoG) effect. We present a model for the redshift-space power spectrum of galaxies in which we decompose a given galaxy sample into central and satellite galaxies and relate different contributions to the power spectrum to 1-halo and 2-halo terms in a halo model. Our primary goal is to ensure that any parameters that we introduce have physically meaningful values, and are not just fitting parameters. For the lowest order 2-halo terms we use the previously developed RSD modeling of halos in the context of distribution function and perturbation theory approach. This term needs to be multiplied by the effect of radial distances and velocities of satellites inside the halo. To this one needs to add the 1-halo terms, which are nonperturbative. We show that the real space 1-halo terms can be modeled as almost constant, with the finite extent of the satellites inside the halo inducing a small k2R2 term over the range of scales of interest, where R is related to the size of the halo given by its halo mass. We adopt a similar model for FoG in redshift space, ensuring that FoG velocity dispersion is related to the halo mass. For FoG k2 type expansions do not work over the range of scales of interest and FoG resummation must be used instead. We test several simple damping functions to model the velocity dispersion FoG effect. Applying the formalism to mock galaxies modeled after the "CMASS" sample of the BOSS survey, we find that our predictions for the redshift-space power spectra are accurate up to k ≃0.4 h Mpc-1 within 1% if the halo power spectrum is measured using N -body simulations and within 3% if it is modeled using perturbation theory.

A stochastic fault model. 2. Time-dependent case.

USGS Publications Warehouse

Andrews, D.J.

1981-01-01

A random model of fault motion in an earthquake is formulated by assuming that the slip velocity is a random function of position and time truncated at zero, so that it does not have negative values. This random function is chosen to be self-affine; that is, on change of length scale, the function is multiplied by a scale factor but is otherwise unchanged statistically. A snapshot of slip velocity at a given time resembles a cluster of islands with rough topography; the final slip function is a smoother island or cluster of islands. In the Fourier transform domain, shear traction on the fault equals the slip velocity times an impedance function. The fact that this impedance function has a pole at zero frequency implies that traction and slip velocity cannot have the same spectral dependence in space and time. To describe stress fluctuations of the order of 100 bars when smoothed over a length of kilometers and of the order of kilobars at the grain size, shear traction must have a one-dimensional power spectrum is space proportional to the reciprocal wave number. Then the one-dimensional power spectrum for the slip velocity is proportional to the reciprocal wave number squared and for slip to its cube. If slip velocity has the same power law spectrum in time as in space, then the spectrum of ground acceleration with be flat (white noise) both on the fault and in the far field.-Author

Waveform Design for Wireless Power Transfer

NASA Astrophysics Data System (ADS)

Clerckx, Bruno; Bayguzina, Ekaterina

2016-12-01

Far-field Wireless Power Transfer (WPT) has attracted significant attention in recent years. Despite the rapid progress, the emphasis of the research community in the last decade has remained largely concentrated on improving the design of energy harvester (so-called rectenna) and has left aside the effect of transmitter design. In this paper, we study the design of transmit waveform so as to enhance the DC power at the output of the rectenna. We derive a tractable model of the non-linearity of the rectenna and compare with a linear model conventionally used in the literature. We then use those models to design novel multisine waveforms that are adaptive to the channel state information (CSI). Interestingly, while the linear model favours narrowband transmission with all the power allocated to a single frequency, the non-linear model favours a power allocation over multiple frequencies. Through realistic simulations, waveforms designed based on the non-linear model are shown to provide significant gains (in terms of harvested DC power) over those designed based on the linear model and over non-adaptive waveforms. We also compute analytically the theoretical scaling laws of the harvested energy for various waveforms as a function of the number of sinewaves and transmit antennas. Those scaling laws highlight the benefits of CSI knowledge at the transmitter in WPT and of a WPT design based on a non-linear rectenna model over a linear model. Results also motivate the study of a promising architecture relying on large-scale multisine multi-antenna waveforms for WPT. As a final note, results stress the importance of modeling and accounting for the non-linearity of the rectenna in any system design involving wireless power.

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

Vlah, Zvonimir; Seljak, Uroš; Baldauf, Tobias

We develop a perturbative approach to redshift space distortions (RSD) using the phase space distribution function approach and apply it to the dark matter redshift space power spectrum and its moments. RSD can be written as a sum over density weighted velocity moments correlators, with the lowest order being density, momentum density and stress energy density. We use standard and extended perturbation theory (PT) to determine their auto and cross correlators, comparing them to N-body simulations. We show which of the terms can be modeled well with the standard PT and which need additional terms that include higher order correctionsmore » which cannot be modeled in PT. Most of these additional terms are related to the small scale velocity dispersion effects, the so called finger of god (FoG) effects, which affect some, but not all, of the terms in this expansion, and which can be approximately modeled using a simple physically motivated ansatz such as the halo model. We point out that there are several velocity dispersions that enter into the detailed RSD analysis with very different amplitudes, which can be approximately predicted by the halo model. In contrast to previous models our approach systematically includes all of the terms at a given order in PT and provides a physical interpretation for the small scale dispersion values. We investigate RSD power spectrum as a function of μ, the cosine of the angle between the Fourier mode and line of sight, focusing on the lowest order powers of μ and multipole moments which dominate the observable RSD power spectrum. Overall we find considerable success in modeling many, but not all, of the terms in this expansion. This is similar to the situation in real space, but predicting power spectrum in redshift space is more difficult because of the explicit influence of small scale dispersion type effects in RSD, which extend to very large scales.« less

Model studies of laser absorption computed tomography for remote air pollution measurement

NASA Technical Reports Server (NTRS)

Wolfe, D. C., Jr.; Byer, R. L.

1982-01-01

Model studies of the potential of laser absorption-computed tomography are presented which demonstrate the possibility of sensitive remote atmospheric pollutant measurements, over kilometer-sized areas, with two-dimensional resolution, at modest laser source powers. An analysis of this tomographic reconstruction process as a function of measurement SNR, laser power, range, and system geometry, shows that the system is able to yield two-dimensional maps of pollutant concentrations at ranges and resolutions superior to those attainable with existing, direct-detection laser radars.

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.

Analysis of Solar Cell Efficiency for Venus Atmosphere and Surface Missions

NASA Technical Reports Server (NTRS)

Landis, Geoffrey A.; Haag, Emily

2013-01-01

A simplified model of solar power in the Venus environment is developed, in which the solar intensity, solar spectrum, and temperature as a function of altitude is applied to a model of photovoltaic performance, incorporating the temperature and intensity dependence of the open-circuit voltage and the temperature dependence of the bandgap and spectral response of the cell. We use this model to estimate the performance of solar cells for both the surface of Venus and for atmospheric probes at altitudes from the surface up to 60 km. The model shows that photovoltaic cells will produce power even at the surface of Venus.

The statistical overlap theory of chromatography using power law (fractal) statistics.

PubMed

Schure, Mark R; Davis, Joe M

2011-12-30

The chromatographic dimensionality was recently proposed as a measure of retention time spacing based on a power law (fractal) distribution. Using this model, a statistical overlap theory (SOT) for chromatographic peaks is developed that estimates the number of peak maxima as a function of the chromatographic dimension, saturation and scale. Power law models exhibit a threshold region whereby below a critical saturation value no loss of peak maxima due to peak fusion occurs as saturation increases. At moderate saturation, behavior is similar to the random (Poisson) peak model. At still higher saturation, the power law model shows loss of peaks nearly independent of the scale and dimension of the model. The physicochemical meaning of the power law scale parameter is discussed and shown to be equal to the Boltzmann-weighted free energy of transfer over the scale limits. The scale is discussed. Small scale range (small β) is shown to generate more uniform chromatograms. Large scale range chromatograms (large β) are shown to give occasional large excursions of retention times; this is a property of power laws where "wild" behavior is noted to occasionally occur. Both cases are shown to be useful depending on the chromatographic saturation. A scale-invariant model of the SOT shows very simple relationships between the fraction of peak maxima and the saturation, peak width and number of theoretical plates. These equations provide much insight into separations which follow power law statistics. Copyright © 2011 Elsevier B.V. All rights reserved.

Reduced power processor requirements for the 30-cm diameter HG ion thruster

NASA Technical Reports Server (NTRS)

Rawlin, V. K.

1979-01-01

The characteristics of power processors strongly impact the overall performance and cost of electric propulsion systems. A program was initiated to evaluate simplifications of the thruster-power processor interface requirements. The power processor requirements are mission dependent with major differences arising for those missions which require a nearly constant thruster operating point (typical of geocentric and some inbound planetary missions) and those requiring operation over a large range of input power (such as outbound planetary missions). This paper describes the results of tests which have indicated that as many as seven of the twelve power supplies may be eliminated from the present Functional Model Power Processor used with 30-cm diameter Hg ion thrusters.

Evaluation of hydrogen bond networks in cellulose Iβ and II crystals using density functional theory and Car-Parrinello molecular dynamics.

PubMed

Hayakawa, Daichi; Nishiyama, Yoshiharu; Mazeau, Karim; Ueda, Kazuyoshi

2017-09-08

Crystal models of cellulose Iβ and II, which contain various hydrogen bonding (HB) networks, were analyzed using density functional theory and Car-Parrinello molecular dynamics (CPMD) simulations. From the CPMD trajectories, the power spectra of the velocity correlation functions of hydroxyl groups involved in hydrogen bonds were calculated. For the Iβ allomorph, HB network A, which is dominant according to the neutron diffraction data, was stable, and the power spectrum represented the essential features of the experimental IR spectra. In contrast, network B, which is a minor structure, was unstable because its hydroxymethyl groups reoriented during the CPMD simulation, yielding a different crystal structure to that determined by experiments. For the II allomorph, a HB network A is proposed based on diffraction data, whereas molecular modeling identifies an alternative network B. Our simulations showed that the interaction energies of the cellulose II (B) model are slightly more favorable than model II(A). However, the evaluation of the free energy should be waited for the accurate determination from the energy point of view. For the IR calculation, cellulose II (B) model reproduces the spectra better than model II (A). Copyright © 2017 Elsevier Ltd. All rights reserved.

Gabor-based kernel PCA with fractional power polynomial models for face recognition.

PubMed

Liu, Chengjun

2004-05-01

This paper presents a novel Gabor-based kernel Principal Component Analysis (PCA) method by integrating the Gabor wavelet representation of face images and the kernel PCA method for face recognition. Gabor wavelets first derive desirable facial features characterized by spatial frequency, spatial locality, and orientation selectivity to cope with the variations due to illumination and facial expression changes. The kernel PCA method is then extended to include fractional power polynomial models for enhanced face recognition performance. A fractional power polynomial, however, does not necessarily define a kernel function, as it might not define a positive semidefinite Gram matrix. Note that the sigmoid kernels, one of the three classes of widely used kernel functions (polynomial kernels, Gaussian kernels, and sigmoid kernels), do not actually define a positive semidefinite Gram matrix either. Nevertheless, the sigmoid kernels have been successfully used in practice, such as in building support vector machines. In order to derive real kernel PCA features, we apply only those kernel PCA eigenvectors that are associated with positive eigenvalues. The feasibility of the Gabor-based kernel PCA method with fractional power polynomial models has been successfully tested on both frontal and pose-angled face recognition, using two data sets from the FERET database and the CMU PIE database, respectively. The FERET data set contains 600 frontal face images of 200 subjects, while the PIE data set consists of 680 images across five poses (left and right profiles, left and right half profiles, and frontal view) with two different facial expressions (neutral and smiling) of 68 subjects. The effectiveness of the Gabor-based kernel PCA method with fractional power polynomial models is shown in terms of both absolute performance indices and comparative performance against the PCA method, the kernel PCA method with polynomial kernels, the kernel PCA method with fractional power polynomial models, the Gabor wavelet-based PCA method, and the Gabor wavelet-based kernel PCA method with polynomial kernels.

Issues of Power and Equity in Two Models of Self-Assessment

ERIC Educational Resources Information Center

Taras, Maddalena

2008-01-01

The two models of self-assessment examined in this paper serve different functions and provide different skills and points of focus for both learners and tutors. The standard model focuses students on their own resources and knowledge in an essentially formative assessment context. Taras' model focuses on students' understanding, using the tutor's…

Mathematical modelling of the growth of human fetus anatomical structures.

PubMed

Dudek, Krzysztof; Kędzia, Wojciech; Kędzia, Emilia; Kędzia, Alicja; Derkowski, Wojciech

2017-09-01

The goal of this study was to present a procedure that would enable mathematical analysis of the increase of linear sizes of human anatomical structures, estimate mathematical model parameters and evaluate their adequacy. Section material consisted of 67 foetuses-rectus abdominis muscle and 75 foetuses- biceps femoris muscle. The following methods were incorporated to the study: preparation and anthropologic methods, image digital acquisition, Image J computer system measurements and statistical analysis method. We used an anthropologic method based on age determination with the use of crown-rump length-CRL (V-TUB) by Scammon and Calkins. The choice of mathematical function should be based on a real course of the curve presenting growth of anatomical structure linear size Ύ in subsequent weeks t of pregnancy. Size changes can be described with a segmental-linear model or one-function model with accuracy adequate enough for clinical purposes. The interdependence of size-age is described with many functions. However, the following functions are most often considered: linear, polynomial, spline, logarithmic, power, exponential, power-exponential, log-logistic I and II, Gompertz's I and II and von Bertalanffy's function. With the use of the procedures described above, mathematical models parameters were assessed for V-PL (the total length of body) and CRL body length increases, rectus abdominis total length h, its segments hI, hII, hIII, hIV, as well as biceps femoris length and width of long head (LHL and LHW) and of short head (SHL and SHW). The best adjustments to measurement results were observed in the exponential and Gompertz's models.

Cross-frequency power coupling between hierarchically organized face-selective areas.

PubMed

Furl, Nicholas; Coppola, Richard; Averbeck, Bruno B; Weinberger, Daniel R

2014-09-01

Neural oscillations are linked to perception and behavior and may reflect mechanisms for long-range communication between brain areas. We developed a causal model of oscillatory dynamics in the face perception network using magnetoencephalographic data from 51 normal volunteers. This model predicted induced responses to faces by estimating oscillatory power coupling between source locations corresponding to bilateral occipital and fusiform face areas (OFA and FFA) and the right superior temporal sulcus (STS). These sources showed increased alpha and theta and decreased beta power as well as selective responses to fearful facial expressions. We then used Bayesian model comparison to compare hypothetical models, which were motivated by previous connectivity data and a well-known theory of temporal lobe function. We confirmed this theory in detail by showing that the OFA bifurcated into 2 independent, hierarchical, feedforward pathways, with fearful expressions modulating power coupling only in the more dorsal (STS) pathway. The power coupling parameters showed a common pattern over connections. Low-frequency bands showed same-frequency power coupling, which, in the dorsal pathway, was modulated by fearful faces. Also, theta power showed a cross-frequency suppression of beta power. This combination of linear and nonlinear mechanisms could reflect computational mechanisms in hierarchical feedforward networks. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

A simulator for evaluating methods for the detection of lesion-deficit associations

NASA Technical Reports Server (NTRS)

Megalooikonomou, V.; Davatzikos, C.; Herskovits, E. H.

2000-01-01

Although much has been learned about the functional organization of the human brain through lesion-deficit analysis, the variety of statistical and image-processing methods developed for this purpose precludes a closed-form analysis of the statistical power of these systems. Therefore, we developed a lesion-deficit simulator (LDS), which generates artificial subjects, each of which consists of a set of functional deficits, and a brain image with lesions; the deficits and lesions conform to predefined distributions. We used probability distributions to model the number, sizes, and spatial distribution of lesions, to model the structure-function associations, and to model registration error. We used the LDS to evaluate, as examples, the effects of the complexities and strengths of lesion-deficit associations, and of registration error, on the power of lesion-deficit analysis. We measured the numbers of recovered associations from these simulated data, as a function of the number of subjects analyzed, the strengths and number of associations in the statistical model, the number of structures associated with a particular function, and the prior probabilities of structures being abnormal. The number of subjects required to recover the simulated lesion-deficit associations was found to have an inverse relationship to the strength of associations, and to the smallest probability in the structure-function model. The number of structures associated with a particular function (i.e., the complexity of associations) had a much greater effect on the performance of the analysis method than did the total number of associations. We also found that registration error of 5 mm or less reduces the number of associations discovered by approximately 13% compared to perfect registration. The LDS provides a flexible framework for evaluating many aspects of lesion-deficit analysis.

Analyzing Effects of Turbulence on Power Generation Using Wind Plant Monitoring Data: Preprint

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

Zhang, J.; Chowdhury, S.; Hodge, B. M.

2014-01-01

In this paper, a methodology is developed to analyze how ambient and wake turbulence affects the power generation of a single wind turbine within an array of turbines. Using monitoring data from a wind power plant, we selected two sets of wind and power data for turbines on the edge of the wind plant that resemble (i) an out-of-wake scenario (i.e., when the turbine directly faces incoming winds) and (ii) an in-wake scenario (i.e., when the turbine is under the wake of other turbines). For each set of data, two surrogate models were then developed to represent the turbine powermore » generation (i) as a function of the wind speed; and (ii) as a function of the wind speed and turbulence intensity. Support vector regression was adopted for the development of the surrogate models. Three types of uncertainties in the turbine power generation were also investigated: (i) the uncertainty in power generation with respect to the published/reported power curve, (ii) the uncertainty in power generation with respect to the estimated power response that accounts for only mean wind speed; and (iii) the uncertainty in power generation with respect to the estimated power response that accounts for both mean wind speed and turbulence intensity. Results show that (i) under the same wind conditions, the turbine generates different power between the in-wake and out-of-wake scenarios, (ii) a turbine generally produces more power under the in-wake scenario than under the out-of-wake scenario, (iii) the power generation is sensitive to turbulence intensity even when the wind speed is greater than the turbine rated speed, and (iv) there is relatively more uncertainty in the power generation under the in-wake scenario than under the out-of-wake scenario.« less

Pattern, growth, and aging in aggregation kinetics of a Vicsek-like active matter model

NASA Astrophysics Data System (ADS)

Das, Subir K.

2017-01-01

Via molecular dynamics simulations, we study kinetics in a Vicsek-like phase-separating active matter model. Quantitative results, for isotropic bicontinuous pattern, are presented on the structure, growth, and aging. These are obtained via the two-point equal-time density-density correlation function, the average domain length, and the two-time density autocorrelation function. Both the correlation functions exhibit basic scaling properties, implying self-similarity in the pattern dynamics, for which the average domain size exhibits a power-law growth in time. The equal-time correlation has a short distance behavior that provides reasonable agreement between the corresponding structure factor tail and the Porod law. The autocorrelation decay is a power-law in the average domain size. Apart from these basic similarities, the overall quantitative behavior of the above-mentioned observables is found to be vastly different from those of the corresponding passive limit of the model which also undergoes phase separation. The functional forms of these have been quantified. An exceptionally rapid growth in the active system occurs due to fast coherent motion of the particles, mean-squared-displacements of which exhibit multiple scaling regimes, including a long time ballistic one.

Cosmological models with a hybrid scale factor in an extended gravity theory

NASA Astrophysics Data System (ADS)

Mishra, B.; Tripathy, S. K.; Tarai, Sankarsan

2018-03-01

A general formalism to investigate Bianchi type V Ih universes is developed in an extended theory of gravity. A minimally coupled geometry and matter field is considered with a rescaled function of f(R,T) substituted in place of the Ricci scalar R in the geometrical action. Dynamical aspects of the models are discussed by using a hybrid scale factor (HSF) that behaves as power law in an initial epoch and as an exponential form at late epoch. The power law behavior and the exponential behavior appear as two extreme cases of the present model.

Halo modelling in chameleon theories

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

Lombriser, Lucas; Koyama, Kazuya; Li, Baojiu, E-mail: lucas.lombriser@port.ac.uk, E-mail: kazuya.koyama@port.ac.uk, E-mail: baojiu.li@durham.ac.uk

2014-03-01

We analyse modelling techniques for the large-scale structure formed in scalar-tensor theories of constant Brans-Dicke parameter which match the concordance model background expansion history and produce a chameleon suppression of the gravitational modification in high-density regions. Thereby, we use a mass and environment dependent chameleon spherical collapse model, the Sheth-Tormen halo mass function and linear halo bias, the Navarro-Frenk-White halo density profile, and the halo model. Furthermore, using the spherical collapse model, we extrapolate a chameleon mass-concentration scaling relation from a ΛCDM prescription calibrated to N-body simulations. We also provide constraints on the model parameters to ensure viability on localmore » scales. We test our description of the halo mass function and nonlinear matter power spectrum against the respective observables extracted from large-volume and high-resolution N-body simulations in the limiting case of f(R) gravity, corresponding to a vanishing Brans-Dicke parameter. We find good agreement between the two; the halo model provides a good qualitative description of the shape of the relative enhancement of the f(R) matter power spectrum with respect to ΛCDM caused by the extra attractive gravitational force but fails to recover the correct amplitude. Introducing an effective linear power spectrum in the computation of the two-halo term to account for an underestimation of the chameleon suppression at intermediate scales in our approach, we accurately reproduce the measurements from the N-body simulations.« less

Field data-based mathematical modeling by Bode equations and vector fitting algorithm for renewable energy applications.

PubMed

Sabry, A H; W Hasan, W Z; Ab Kadir, M Z A; Radzi, M A M; Shafie, S

2018-01-01

The power system always has several variations in its profile due to random load changes or environmental effects such as device switching effects when generating further transients. Thus, an accurate mathematical model is important because most system parameters vary with time. Curve modeling of power generation is a significant tool for evaluating system performance, monitoring and forecasting. Several numerical techniques compete to fit the curves of empirical data such as wind, solar, and demand power rates. This paper proposes a new modified methodology presented as a parametric technique to determine the system's modeling equations based on the Bode plot equations and the vector fitting (VF) algorithm by fitting the experimental data points. The modification is derived from the familiar VF algorithm as a robust numerical method. This development increases the application range of the VF algorithm for modeling not only in the frequency domain but also for all power curves. Four case studies are addressed and compared with several common methods. From the minimal RMSE, the results show clear improvements in data fitting over other methods. The most powerful features of this method is the ability to model irregular or randomly shaped data and to be applied to any algorithms that estimating models using frequency-domain data to provide state-space or transfer function for the model.

Field data-based mathematical modeling by Bode equations and vector fitting algorithm for renewable energy applications

PubMed Central

W. Hasan, W. Z.

2018-01-01

The power system always has several variations in its profile due to random load changes or environmental effects such as device switching effects when generating further transients. Thus, an accurate mathematical model is important because most system parameters vary with time. Curve modeling of power generation is a significant tool for evaluating system performance, monitoring and forecasting. Several numerical techniques compete to fit the curves of empirical data such as wind, solar, and demand power rates. This paper proposes a new modified methodology presented as a parametric technique to determine the system’s modeling equations based on the Bode plot equations and the vector fitting (VF) algorithm by fitting the experimental data points. The modification is derived from the familiar VF algorithm as a robust numerical method. This development increases the application range of the VF algorithm for modeling not only in the frequency domain but also for all power curves. Four case studies are addressed and compared with several common methods. From the minimal RMSE, the results show clear improvements in data fitting over other methods. The most powerful features of this method is the ability to model irregular or randomly shaped data and to be applied to any algorithms that estimating models using frequency-domain data to provide state-space or transfer function for the model. PMID:29351554

Energy-harvesting potential of automobile suspension

NASA Astrophysics Data System (ADS)

Múčka, Peter

2016-12-01

This study is aimed quantify dissipated power in a damper of automobile suspension to predict energy harvesting potential of a passenger car more accurately. Field measurements of power dissipation in a regenerative damper are still rare. The novelty is in using the broad database of real road profiles, a 9 degrees-of-freedom full-car model with real parameters, and a tyre-enveloping contact model. Results were presented as a function of road surface type, velocity and road roughness characterised by International Roughness Index. Results were calculated for 1600 test sections of a total length about 253.5 km. Root mean square of a dissipated power was calculated from 19 to 46 W for all four suspension dampers and velocity 60 km/h and from 24 to 58 W for velocity 90 km/h. Results were compared for a full-car model with a tyre-enveloping road contact, full-car and quarter-car models with a tyre-road point contact. Mean difference among three models in calculated power was a few per cent.

smoothG

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

Barker, Andrew T.; Gelever, Stephan A.; Lee, Chak S.

2017-12-12

smoothG is a collection of parallel C++ classes/functions that algebraically constructs reduced models of different resolutions from a given high-fidelity graph model. In addition, smoothG also provides efficient linear solvers for the reduced models. Other than pure graph problem, the software finds its application in subsurface flow and power grid simulations in which graph Laplacians are found

Cluster-cluster clustering

NASA Technical Reports Server (NTRS)

Barnes, J.; Dekel, A.; Efstathiou, G.; Frenk, C. S.

1985-01-01

The cluster correlation function xi sub c(r) is compared with the particle correlation function, xi(r) in cosmological N-body simulations with a wide range of initial conditions. The experiments include scale-free initial conditions, pancake models with a coherence length in the initial density field, and hybrid models. Three N-body techniques and two cluster-finding algorithms are used. In scale-free models with white noise initial conditions, xi sub c and xi are essentially identical. In scale-free models with more power on large scales, it is found that the amplitude of xi sub c increases with cluster richness; in this case the clusters give a biased estimate of the particle correlations. In the pancake and hybrid models (with n = 0 or 1), xi sub c is steeper than xi, but the cluster correlation length exceeds that of the points by less than a factor of 2, independent of cluster richness. Thus the high amplitude of xi sub c found in studies of rich clusters of galaxies is inconsistent with white noise and pancake models and may indicate a primordial fluctuation spectrum with substantial power on large scales.

Improved Evolutionary Programming with Various Crossover Techniques for Optimal Power Flow Problem

NASA Astrophysics Data System (ADS)

Tangpatiphan, Kritsana; Yokoyama, Akihiko

This paper presents an Improved Evolutionary Programming (IEP) for solving the Optimal Power Flow (OPF) problem, which is considered as a non-linear, non-smooth, and multimodal optimization problem in power system operation. The total generator fuel cost is regarded as an objective function to be minimized. The proposed method is an Evolutionary Programming (EP)-based algorithm with making use of various crossover techniques, normally applied in Real Coded Genetic Algorithm (RCGA). The effectiveness of the proposed approach is investigated on the IEEE 30-bus system with three different types of fuel cost functions; namely the quadratic cost curve, the piecewise quadratic cost curve, and the quadratic cost curve superimposed by sine component. These three cost curves represent the generator fuel cost functions with a simplified model and more accurate models of a combined-cycle generating unit and a thermal unit with value-point loading effect respectively. The OPF solutions by the proposed method and Pure Evolutionary Programming (PEP) are observed and compared. The simulation results indicate that IEP requires less computing time than PEP with better solutions in some cases. Moreover, the influences of important IEP parameters on the OPF solution are described in details.

OpenSoC Fabric

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

2014-08-21

Recent advancements in technology scaling have shown a trend towards greater integration with large-scale chips containing thousands of processors connected to memories and other I/O devices using non-trivial network topologies. Software simulation proves insufficient to study the tradeoffs in such complex systems due to slow execution time, whereas hardware RTL development is too time-consuming. We present OpenSoC Fabric, an on-chip network generation infrastructure which aims to provide a parameterizable and powerful on-chip network generator for evaluating future high performance computing architectures based on SoC technology. OpenSoC Fabric leverages a new hardware DSL, Chisel, which contains powerful abstractions provided by itsmore » base language, Scala, and generates both software (C++) and hardware (Verilog) models from a single code base. The OpenSoC Fabric2 infrastructure is modeled after existing state-of-the-art simulators, offers large and powerful collections of configuration options, and follows object-oriented design and functional programming to make functionality extension as easy as possible.« less

USING TIME VARIANT VOLTAGE TO CALCULATE ENERGY CONSUMPTION AND POWER USE OF BUILDING SYSTEMS

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

Makhmalbaf, Atefe; Augenbroe , Godfried

2015-12-09

Buildings are the main consumers of electricity across the world. However, in the research and studies related to building performance assessment, the focus has been on evaluating the energy efficiency of buildings whereas the instantaneous power efficiency has been overlooked as an important aspect of total energy consumption. As a result, we never developed adequate models that capture both thermal and electrical characteristics (e.g., voltage) of building systems to assess the impact of variations in the power system and emerging technologies of the smart grid on buildings energy and power performance and vice versa. This paper argues that the powermore » performance of buildings as a function of electrical parameters should be evaluated in addition to systems’ mechanical and thermal behavior. The main advantage of capturing electrical behavior of building load is to better understand instantaneous power consumption and more importantly to control it. Voltage is one of the electrical parameters that can be used to describe load. Hence, voltage dependent power models are constructed in this work and they are coupled with existing thermal energy models. Lack of models that describe electrical behavior of systems also adds to the uncertainty of energy consumption calculations carried out in building energy simulation tools such as EnergyPlus, a common building energy modeling and simulation tool. To integrate voltage-dependent power models with thermal models, the thermal cycle (operation mode) of each system was fed into the voltage-based electrical model. Energy consumption of systems used in this study were simulated using EnergyPlus. Simulated results were then compared with estimated and measured power data. The mean square error (MSE) between simulated, estimated, and measured values were calculated. Results indicate that estimated power has lower MSE when compared with measured data than simulated results. Results discussed in this paper will illustrate the significance of enhancing building energy models with electrical characteristics. This would support different studies such as those related to modernization of the power system that require micro scale building-grid interaction, evaluating building energy efficiency with power efficiency considerations, and also design and control decisions that rely on accuracy of building energy simulation results.« less

Joint resonant CMB power spectrum and bispectrum estimation

NASA Astrophysics Data System (ADS)

Meerburg, P. Daniel; Münchmeyer, Moritz; Wandelt, Benjamin

2016-02-01

We develop the tools necessary to assess the statistical significance of resonant features in the CMB correlation functions, combining power spectrum and bispectrum measurements. This significance is typically addressed by running a large number of simulations to derive the probability density function (PDF) of the feature-amplitude in the Gaussian case. Although these simulations are tractable for the power spectrum, for the bispectrum they require significant computational resources. We show that, by assuming that the PDF is given by a multivariate Gaussian where the covariance is determined by the Fisher matrix of the sine and cosine terms, we can efficiently produce spectra that are statistically close to those derived from full simulations. By drawing a large number of spectra from this PDF, both for the power spectrum and the bispectrum, we can quickly determine the statistical significance of candidate signatures in the CMB, considering both single frequency and multifrequency estimators. We show that for resonance models, cosmology and foreground parameters have little influence on the estimated amplitude, which allows us to simplify the analysis considerably. A more precise likelihood treatment can then be applied to candidate signatures only. We also discuss a modal expansion approach for the power spectrum, aimed at quickly scanning through large families of oscillating models.

Separability of spatiotemporal spectra of image sequences. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Eckert, Michael P.; Buchsbaum, Gershon; Watson, Andrew B.

1992-01-01

The spatiotemporal power spectrum was calculated of 14 image sequences in order to determine the degree to which the spectra are separable in space and time, and to assess the validity of the commonly used exponential correlation model found in the literature. The spectrum was expanded by a Singular Value Decomposition into a sum of separable terms and an index was defined of spatiotemporal separability as the fraction of the signal energy that can be represented by the first (largest) separable term. All spectra were found to be highly separable with an index of separability above 0.98. The power spectra of the sequences were well fit by a separable model. The power spectrum model corresponds to a product of exponential autocorrelation functions separable in space and time.

A representation of an NTCP function for local complication mechanisms

NASA Astrophysics Data System (ADS)

Alber, M.; Nüsslin, F.

2001-02-01

A mathematical formalism was tailored for the description of mechanisms complicating radiation therapy with a predominantly local component. The functional representation of an NTCP function was developed based on the notion that it has to be robust against population averages in order to be applicable to experimental data. The model was required to be invariant under scaling operations of the dose and the irradiated volume. The NTCP function was derived from the model assumptions that the complication is a consequence of local tissue damage and that the probability of local damage in a small reference volume is independent of the neighbouring volumes. The performance of the model was demonstrated with an animal model which has been published previously (Powers et al 1998 Radiother. Oncol. 46 297-306).

Bread dough rheology: Computing with a damage function model

NASA Astrophysics Data System (ADS)

Tanner, Roger I.; Qi, Fuzhong; Dai, Shaocong

2015-01-01

We describe an improved damage function model for bread dough rheology. The model has relatively few parameters, all of which can easily be found from simple experiments. Small deformations in the linear region are described by a gel-like power-law memory function. A set of large non-reversing deformations - stress relaxation after a step of shear, steady shearing and elongation beginning from rest, and biaxial stretching, is used to test the model. With the introduction of a revised strain measure which includes a Mooney-Rivlin term, all of these motions can be well described by the damage function described in previous papers. For reversing step strains, larger amplitude oscillatory shearing and recoil reasonable predictions have been found. The numerical methods used are discussed and we give some examples.

A Simplified GCS-DCSK Modulation and Its Performance Optimization

NASA Astrophysics Data System (ADS)

Xu, Weikai; Wang, Lin; Chi, Chong-Yung

2016-12-01

In this paper, a simplified Generalized Code-Shifted Differential Chaos Shift Keying (GCS-DCSK) whose transmitter never needs any delay circuits, is proposed. However, its performance is deteriorated because the orthogonality between substreams cannot be guaranteed. In order to optimize its performance, the system model of the proposed GCS-DCSK with power allocations on substreams is presented. An approximate bit error rate (BER) expression of the proposed model, which is a function of substreams’ power, is derived using Gaussian Approximation. Based on the BER expression, an optimal power allocation strategy between information substreams and reference substream is obtained. Simulation results show that the BER performance of the proposed GCS-DCSK with the optimal power allocation can be significantly improved when the number of substreams M is large.

Accounting for subordinate perceptions of supervisor power: an identity-dependence model.

PubMed

Farmer, Steven M; Aguinis, Herman

2005-11-01

The authors present a model that explains how subordinates perceive the power of their supervisors and the causal mechanisms by which these perceptions translate into subordinate outcomes. Drawing on identity and resource-dependence theories, the authors propose that supervisors have power over their subordinates when they control resources needed for the subordinates' enactment and maintenance of current and desired identities. The joint effect of perceptions of supervisor power and supervisor intentions to provide such resources leads to 4 conditions ranging from highly functional to highly dysfunctional: confirmation, hope, apathy, and progressive withdrawal. Each of these conditions is associated with specific outcomes such as the quality of the supervisor-subordinate relationship, turnover, and changes in the type and centrality of various subordinate identities. ((c) 2005 APA, all rights reserved).

Multiple perspective vulnerability analysis of the power network

NASA Astrophysics Data System (ADS)

Wang, Shuliang; Zhang, Jianhua; Duan, Na

2018-02-01

To understand the vulnerability of the power network from multiple perspectives, multi-angle and multi-dimensional vulnerability analysis as well as community based vulnerability analysis are proposed in this paper. Taking into account of central China power grid as an example, correlation analysis of different vulnerability models is discussed. Then, vulnerabilities produced by different vulnerability metrics under the given vulnerability models and failure scenarios are analyzed. At last, applying the community detecting approach, critical areas of central China power grid are identified, Vulnerable and robust communities on both topological and functional perspective are acquired and analyzed. The approach introduced in this paper can be used to help decision makers develop optimal protection strategies. It will be also useful to give a multiple vulnerability analysis of the other infrastructure systems.

Battery-powered thin film deposition process for coating telescope mirrors in space

NASA Astrophysics Data System (ADS)

Sheikh, David A.

2016-07-01

Aluminum films manufactured in the vacuum of space may increase the broadband reflectance response of a space telescope operating in the EUV (50-nm to 115-nm) by eliminating absorbing metal-fluorides and metal-oxides, which significantly reduce aluminum's reflectance below 115-nm. Recent developments in battery technology allow small lithium batteries to rapidly discharge large amounts of energy. It is therefore conceivable to power an array of resistive evaporation filaments in a space environment, using a reasonable mass of batteries and other hardware. This paper presents modeling results for coating thickness as a function of position, for aluminum films made with a hexagonal array of battery powered evaporation sources. The model is based on measured data from a single battery-powered evaporation source.

The scalar-scalar-tensor inflationary three-point function in the axion monodromy model

NASA Astrophysics Data System (ADS)

Chowdhury, Debika; Sreenath, V.; Sriramkumar, L.

2016-11-01

The axion monodromy model involves a canonical scalar field that is governed by a linear potential with superimposed modulations. The modulations in the potential are responsible for a resonant behavior which gives rise to persisting oscillations in the scalar and, to a smaller extent, in the tensor power spectra. Interestingly, such spectra have been shown to lead to an improved fit to the cosmological data than the more conventional, nearly scale invariant, primordial power spectra. The scalar bi-spectrum in the model too exhibits continued modulations and the resonance is known to boost the amplitude of the scalar non-Gaussianity parameter to rather large values. An analytical expression for the scalar bi-spectrum had been arrived at earlier which, in fact, has been used to compare the model with the cosmic microwave background anisotropies at the level of three-point functions involving scalars. In this work, with future applications in mind, we arrive at a similar analytical template for the scalar-scalar-tensor cross-correlation. We also analytically establish the consistency relation (in the squeezed limit) for this three-point function. We conclude with a summary of the main results obtained.

On the Asymptotic Behavior of the Kernel Function in the Generalized Langevin Equation: A One-Dimensional Lattice Model

NASA Astrophysics Data System (ADS)

Chu, Weiqi; Li, Xiantao

2018-01-01

We present some estimates for the memory kernel function in the generalized Langevin equation, derived using the Mori-Zwanzig formalism from a one-dimensional lattice model, in which the particles interactions are through nearest and second nearest neighbors. The kernel function can be explicitly expressed in a matrix form. The analysis focuses on the decay properties, both spatially and temporally, revealing a power-law behavior in both cases. The dependence on the level of coarse-graining is also studied.

Comparison of P&O and INC Methods in Maximum Power Point Tracker for PV Systems

NASA Astrophysics Data System (ADS)

Chen, Hesheng; Cui, Yuanhui; Zhao, Yue; Wang, Zhisen

2018-03-01

In the context of renewable energy, the maximum power point tracker (MPPT) is often used to increase the solar power efficiency, taking into account the randomness and volatility of solar energy due to changes in temperature and photovoltaic. In all MPPT techniques, perturb & observe and incremental conductance are widely used in MPPT controllers, because of their simplicity and ease of operation. According to the internal structure of the photovoltaic cell and the output volt-ampere characteristic, this paper established the circuit model and establishes the dynamic simulation model in Matlab/Simulink with the preparation of the s function. The perturb & observe MPPT method and the incremental conductance MPPT method were analyzed and compared by the theoretical analysis and digital simulation. The simulation results have shown that the system with INC MPPT method has better dynamic performance and improves the output power of photovoltaic power generation.

Wireless power using magnetic resonance coupling for neural sensing applications

NASA Astrophysics Data System (ADS)

Yoon, Hargsoon; Kim, Hyunjung; Choi, Sang H.; Sanford, Larry D.; Geddis, Demetris; Lee, Kunik; Kim, Jaehwan; Song, Kyo D.

2012-04-01

Various wireless power transfer systems based on electromagnetic coupling have been investigated and applied in many biomedical applications including functional electrical stimulation systems and physiological sensing in humans and animals. By integrating wireless power transfer modules with wireless communication devices, electronic systems can deliver data and control system operation in untethered freely-moving conditions without requiring access through the skin, a potential source of infection. In this presentation, we will discuss a wireless power transfer module using magnetic resonance coupling that is specifically designed for neural sensing systems and in-vivo animal models. This research presents simple experimental set-ups and circuit models of magnetic resonance coupling modules and discusses advantages and concerns involved in positioning and sizing of source and receiver coils compared to conventional inductive coupling devices. Furthermore, the potential concern of tissue heating in the brain during operation of the wireless power transfer systems will also be addressed.

Predictive analysis of beer quality by correlating sensory evaluation with higher alcohol and ester production using multivariate statistics methods.

PubMed

Dong, Jian-Jun; Li, Qing-Liang; Yin, Hua; Zhong, Cheng; Hao, Jun-Guang; Yang, Pan-Fei; Tian, Yu-Hong; Jia, Shi-Ru

2014-10-15

Sensory evaluation is regarded as a necessary procedure to ensure a reproducible quality of beer. Meanwhile, high-throughput analytical methods provide a powerful tool to analyse various flavour compounds, such as higher alcohol and ester. In this study, the relationship between flavour compounds and sensory evaluation was established by non-linear models such as partial least squares (PLS), genetic algorithm back-propagation neural network (GA-BP), support vector machine (SVM). It was shown that SVM with a Radial Basis Function (RBF) had a better performance of prediction accuracy for both calibration set (94.3%) and validation set (96.2%) than other models. Relatively lower prediction abilities were observed for GA-BP (52.1%) and PLS (31.7%). In addition, the kernel function of SVM played an essential role of model training when the prediction accuracy of SVM with polynomial kernel function was 32.9%. As a powerful multivariate statistics method, SVM holds great potential to assess beer quality. Copyright © 2014 Elsevier Ltd. All rights reserved.

Modeling diffusion and reaction in soils: 9. The Buckingham-Burdine-Campbell equation for gas diffusivity in undisturbed soil

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

Moldrup, P.; Olesen, T.; Yamaguchi, T.

1999-08-01

Accurate description of gas diffusivity (ratio of gas diffusion coefficients in soil and free air, D{sub s}/D{sub 0}) in undisturbed soils is a prerequisite for predicting in situ transport and fate of volatile organic chemicals and greenhouse gases. Reference point gas diffusivities (R{sub p}) in completely dry soil were estimated for 20 undisturbed soils by assuming a power function relation between gas diffusivity and air-filled porosity ({epsilon}). Among the classical gas diffusivity models, the Buckingham (1904) expression, equal to the soil total porosity squared, best described R{sub p}. Inasmuch, as their previous works implied a soil-type dependency of D{sub s}/D{submore » 0}({epsilon}) in undisturbed soils, the Buckingham R{sub p} expression was inserted in two soil-type-dependent D{sub s}/D{sub 0}({epsilon}) models. One D{sub s}/D{sub 0}({epsilon}) model is a function of pore-size distribution (the Campbell water retention parameter used in a modified Burdine capillary tube model), and the other is a calibrated, empirical function of soil texture (silt + sand fraction). Both the Buckingham-Burdine-Campbell (BBC) and the Buckingham/soil texture-based D{sub s}/D{sub 0}({epsilon}) models described well the observed soil type effects on gas diffusivity and gave improved predictions compared with soil type independent models when tested against an independent data set for six undisturbed surface soils. This study emphasizes that simple but soil-type-dependent power function D{sub s}/D{sub 0}({epsilon}) models can adequately describe and predict gas diffusivity in undisturbed soil. The authors recommend the new BBC model as basis for modeling gas transport and reactions in undisturbed soil systems.« less

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.

The complex contribution of sociodemographics to decision-making power in gay male couples.

PubMed

Perry, Nicholas S; Huebner, David M; Baucom, Brian R W; Hoff, Colleen C

2016-12-01

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) and 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. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Bayesian Inference for Functional Dynamics Exploring in fMRI Data.

PubMed

Guo, Xuan; Liu, Bing; Chen, Le; Chen, Guantao; Pan, Yi; Zhang, Jing

2016-01-01

This paper aims to review state-of-the-art Bayesian-inference-based methods applied to functional magnetic resonance imaging (fMRI) data. Particularly, we focus on one specific long-standing challenge in the computational modeling of fMRI datasets: how to effectively explore typical functional interactions from fMRI time series and the corresponding boundaries of temporal segments. Bayesian inference is a method of statistical inference which has been shown to be a powerful tool to encode dependence relationships among the variables with uncertainty. Here we provide an introduction to a group of Bayesian-inference-based methods for fMRI data analysis, which were designed to detect magnitude or functional connectivity change points and to infer their functional interaction patterns based on corresponding temporal boundaries. We also provide a comparison of three popular Bayesian models, that is, Bayesian Magnitude Change Point Model (BMCPM), Bayesian Connectivity Change Point Model (BCCPM), and Dynamic Bayesian Variable Partition Model (DBVPM), and give a summary of their applications. We envision that more delicate Bayesian inference models will be emerging and play increasingly important roles in modeling brain functions in the years to come.

Predictive Power Estimation Algorithm (PPEA) - A New Algorithm to Reduce Overfitting for Genomic Biomarker Discovery

PubMed Central

Liu, Jiangang; Jolly, Robert A.; Smith, Aaron T.; Searfoss, George H.; Goldstein, Keith M.; Uversky, Vladimir N.; Dunker, Keith; Li, Shuyu; Thomas, Craig E.; Wei, Tao

2011-01-01

Toxicogenomics promises to aid in predicting adverse effects, understanding the mechanisms of drug action or toxicity, and uncovering unexpected or secondary pharmacology. However, modeling adverse effects using high dimensional and high noise genomic data is prone to over-fitting. Models constructed from such data sets often consist of a large number of genes with no obvious functional relevance to the biological effect the model intends to predict that can make it challenging to interpret the modeling results. To address these issues, we developed a novel algorithm, Predictive Power Estimation Algorithm (PPEA), which estimates the predictive power of each individual transcript through an iterative two-way bootstrapping procedure. By repeatedly enforcing that the sample number is larger than the transcript number, in each iteration of modeling and testing, PPEA reduces the potential risk of overfitting. We show with three different cases studies that: (1) PPEA can quickly derive a reliable rank order of predictive power of individual transcripts in a relatively small number of iterations, (2) the top ranked transcripts tend to be functionally related to the phenotype they are intended to predict, (3) using only the most predictive top ranked transcripts greatly facilitates development of multiplex assay such as qRT-PCR as a biomarker, and (4) more importantly, we were able to demonstrate that a small number of genes identified from the top-ranked transcripts are highly predictive of phenotype as their expression changes distinguished adverse from nonadverse effects of compounds in completely independent tests. Thus, we believe that the PPEA model effectively addresses the over-fitting problem and can be used to facilitate genomic biomarker discovery for predictive toxicology and drug responses. PMID:21935387

Four-body correlation embedded in antisymmetrized geminal power wave function.

PubMed

Kawasaki, Airi; Sugino, Osamu

2016-12-28

We extend the Coleman's antisymmetrized geminal power (AGP) to develop a wave function theory that can incorporate up to four-body correlation in a region of strong correlation. To facilitate the variational determination of the wave function, the total energy is rewritten in terms of the traces of geminals. This novel trace formula is applied to a simple model system consisting of one dimensional Hubbard ring with a site of strong correlation. Our scheme significantly improves the result obtained by the AGP-configuration interaction scheme of Uemura et al. and also achieves more efficient compression of the degrees of freedom of the wave function. We regard the result as a step toward a first-principles wave function theory for a strongly correlated point defect or adsorbate embedded in an AGP-based mean-field medium.

Research on unit commitment with large-scale wind power connected power system

NASA Astrophysics Data System (ADS)

Jiao, Ran; Zhang, Baoqun; Chi, Zhongjun; Gong, Cheng; Ma, Longfei; Yang, Bing

2017-01-01

Large-scale integration of wind power generators into power grid brings severe challenges to power system economic dispatch due to its stochastic volatility. Unit commitment including wind farm is analyzed from the two parts of modeling and solving methods. The structures and characteristics can be summarized after classification has been done according to different objective function and constraints. Finally, the issues to be solved and possible directions of research and development in the future are discussed, which can adapt to the requirements of the electricity market, energy-saving power generation dispatching and smart grid, even providing reference for research and practice of researchers and workers in this field.

Fractional Gaussian model in global optimization

NASA Astrophysics Data System (ADS)

Dimri, V. P.; Srivastava, R. P.

2009-12-01

Earth system is inherently non-linear and it can be characterized well if we incorporate no-linearity in the formulation and solution of the problem. General tool often used for characterization of the earth system is inversion. Traditionally inverse problems are solved using least-square based inversion by linearizing the formulation. The initial model in such inversion schemes is often assumed to follow posterior Gaussian probability distribution. It is now well established that most of the physical properties of the earth follow power law (fractal distribution). Thus, the selection of initial model based on power law probability distribution will provide more realistic solution. We present a new method which can draw samples of posterior probability density function very efficiently using fractal based statistics. The application of the method has been demonstrated to invert band limited seismic data with well control. We used fractal based probability density function which uses mean, variance and Hurst coefficient of the model space to draw initial model. Further this initial model is used in global optimization inversion scheme. Inversion results using initial models generated by our method gives high resolution estimates of the model parameters than the hitherto used gradient based liner inversion method.

Preliminary Chaotic Model of Snapover on High Voltage Solar Cells

NASA Technical Reports Server (NTRS)

Mackey, Willie R.

1995-01-01

High voltage power systems in space will interact with the space plasma in a variety of ways. One of these, Snapover, is characterized by a sudden enlargement of the electron current collection area across normally insulating surfaces. A power drain on solar array power systems will results from this enhanced current collection. Optical observations of the snapover phenomena in the laboratory indicates a functional relation between bia potential and surface glow area. This paper shall explore the potential benefits of modeling the relation between current and bia potential as an aspect of bifurcation analysis in chaos theory. Successful characterizations of snapover as a chaotic phenomena may provide a means of snapover prevention and control through chaotic synchronization.

Principle, design and validation of a power-generated magnetorheological energy absorber with velocity self-sensing capability

NASA Astrophysics Data System (ADS)

Bai, Xian-Xu; Zhong, Wei-Min; Zou, Qi; Zhu, An-Ding; Sun, Jun

2018-07-01

Based on the structural design concept of ‘functional integration’, this paper proposes the principle of a power-generated magnetorheological energy absorber with velocity self-sensing capability (PGMREA), which realizes the integration of controllable damping mechanism and mechanical energy-electrical energy conversion mechanism in structure profile and multiple functions in function profile, including controllable damping, power generation and velocity self-sensing. The controllable damping mechanism consists of an annular gap and a ball screw. The annular gap fulfilled with MR fluid that operates in pure shear mode under controllable electromagnetic field. The rotational damping torque generated from the controllable damping mechanism is translated to a linear damping force via the ball screw. The mechanical energy-electrical energy conversion mechanism is realized by the ball screw and a generator composed of a permanent magnet rotor and a generator stator. The ball screw based mechanical energy-electrical energy conversion mechanism converts the mechanical energy of excitations to electrical energy for storage or directly to power the controllable damping mechanism of the PGMREA. The velocity self-sensing capability of the PGMREA is achieved via signal processing using the mechanical energy-electrical energy conversion information. Based on the principle of the proposed PGMREA, the mathematical model of the PGMREA is established, including the damping force, generated power and self-sensing velocity. The electromagnetic circuit of the PGMREA is simulated and verified via a finite element analysis software ANSYS. The developed PGMREA prototype is experimentally tested on a servo-hydraulic testing system. The model-based predicted results and the experimental results are compared and analyzed.

Qualitative modeling of silica plasma etching using neural network

NASA Astrophysics Data System (ADS)

Kim, Byungwhan; Kwon, Kwang Ho

2003-01-01

An etching of silica thin film is qualitatively modeled by using a neural network. The process was characterized by a 23 full factorial experiment plus one center point, in which the experimental factors and ranges include 100-800 W radio-frequency source power, 100-400 W bias power and gas flow rate ratio CHF3/CF4. The gas flow rate ratio varied from 0.2 to 5.0. The backpropagation neural network (BPNN) was trained on nine experiments and tested on six experiments, not pertaining to the original training data. The prediction ability of the BPNN was optimized as a function of the training parameters. Prediction errors are 180 Å/min and 1.33, for the etch rate and anisotropy models, respectively. Physical etch mechanisms were estimated from the three-dimensional plots generated from the optimized models. Predicted response surfaces were consistent with experimentally measured etch data. The dc bias was correlated to the etch responses to evaluate its contribution. Both the source power (plasma density) and bias power (ion directionality) strongly affected the etch rate. The source power was the most influential factor for the etch rate. A conflicting effect between the source and bias powers was noticed with respect to the anisotropy. The dc bias played an important role in understanding or separating physical etch mechanisms.

Numerical model of solar dynamic radiator for parametric analysis

NASA Technical Reports Server (NTRS)

Rhatigan, Jennifer L.

1989-01-01

Growth power requirements for Space Station Freedom will be met through addition of 25 kW solar dynamic (SD) power modules. The SD module rejects waste heat from the power conversion cycle to space through a pumped-loop, multi-panel, deployable radiator. The baseline radiator configuration was defined during the Space Station conceptual design phase and is a function of the state point and heat rejection requirements of the power conversion unit. Requirements determined by the overall station design such as mass, system redundancy, micrometeoroid and space debris impact survivability, launch packaging, costs, and thermal and structural interaction with other station components have also been design drivers for the radiator configuration. Extensive thermal and power cycle modeling capabilities have been developed which are powerful tools in Station design and analysis, but which prove cumbersome and costly for simple component preliminary design studies. In order to aid in refining the SD radiator to the mature design stage, a simple and flexible numerical model was developed. The model simulates heat transfer and fluid flow performance of the radiator and calculates area mass and impact survivability for many combinations of flow tube and panel configurations, fluid and material properties, and environmental and cycle variations. A brief description and discussion of the numerical model, it's capabilities and limitations, and results of the parametric studies performed is presented.

An empirical comparison of SPM preprocessing parameters to the analysis of fMRI data.

PubMed

Della-Maggiore, Valeria; Chau, Wilkin; Peres-Neto, Pedro R; McIntosh, Anthony R

2002-09-01

We present the results from two sets of Monte Carlo simulations aimed at evaluating the robustness of some preprocessing parameters of SPM99 for the analysis of functional magnetic resonance imaging (fMRI). Statistical robustness was estimated by implementing parametric and nonparametric simulation approaches based on the images obtained from an event-related fMRI experiment. Simulated datasets were tested for combinations of the following parameters: basis function, global scaling, low-pass filter, high-pass filter and autoregressive modeling of serial autocorrelation. Based on single-subject SPM analysis, we derived the following conclusions that may serve as a guide for initial analysis of fMRI data using SPM99: (1) The canonical hemodynamic response function is a more reliable basis function to model the fMRI time series than HRF with time derivative. (2) Global scaling should be avoided since it may significantly decrease the power depending on the experimental design. (3) The use of a high-pass filter may be beneficial for event-related designs with fixed interstimulus intervals. (4) When dealing with fMRI time series with short interstimulus intervals (<8 s), the use of first-order autoregressive model is recommended over a low-pass filter (HRF) because it reduces the risk of inferential bias while providing a relatively good power. For datasets with interstimulus intervals longer than 8 seconds, temporal smoothing is not recommended since it decreases power. While the generalizability of our results may be limited, the methods we employed can be easily implemented by other scientists to determine the best parameter combination to analyze their data.

Probabilistic Wind Power Ramp Forecasting Based on a Scenario Generation Method

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

Wang, Qin; Florita, Anthony R; Krishnan, Venkat K

Wind power ramps (WPRs) are particularly important in the management and dispatch of wind power and currently drawing the attention of balancing authorities. With the aim to reduce the impact of WPRs for power system operations, this paper develops a probabilistic ramp forecasting method based on a large number of simulated scenarios. An ensemble machine learning technique is first adopted to forecast the basic wind power forecasting scenario and calculate the historical forecasting errors. A continuous Gaussian mixture model (GMM) is used to fit the probability distribution function (PDF) of forecasting errors. The cumulative distribution function (CDF) is analytically deduced.more » The inverse transform method based on Monte Carlo sampling and the CDF is used to generate a massive number of forecasting error scenarios. An optimized swinging door algorithm is adopted to extract all the WPRs from the complete set of wind power forecasting scenarios. The probabilistic forecasting results of ramp duration and start-time are generated based on all scenarios. Numerical simulations on publicly available wind power data show that within a predefined tolerance level, the developed probabilistic wind power ramp forecasting method is able to predict WPRs with a high level of sharpness and accuracy.« less

Functional specifications for AI software tools for electric power applications. Final report

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

Faught, W.S.

1985-08-01

The principle barrier to the introduction of artificial intelligence (AI) technology to the electric power industry has not been a lack of interest or appropriate problems, for the industry abounds in both. Like most others, however, the electric power industry lacks the personnel - knowledge engineers - with the special combination of training and skills AI programming demands. Conversely, very few AI specialists are conversant with electric power industry problems and applications. The recent availability of sophisticated AI programming environments is doing much to alleviate this shortage. These products provide a set of powerful and usable software tools that enablemore » even non-AI scientists to rapidly develop AI applications. The purpose of this project was to develop functional specifications for programming tools that, when integrated with existing general-purpose knowledge engineering tools, would expedite the production of AI applications for the electric power industry. Twelve potential applications, representative of major problem domains within the nuclear power industry, were analyzed in order to identify those tools that would be of greatest value in application development. Eight tools were specified, including facilities for power plant modeling, data base inquiry, simulation and machine-machine interface.« less

Probabilistic Wind Power Ramp Forecasting Based on a Scenario Generation Method: Preprint

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

Wang, Qin; Florita, Anthony R; Krishnan, Venkat K

2017-08-31

Wind power ramps (WPRs) are particularly important in the management and dispatch of wind power, and they are currently drawing the attention of balancing authorities. With the aim to reduce the impact of WPRs for power system operations, this paper develops a probabilistic ramp forecasting method based on a large number of simulated scenarios. An ensemble machine learning technique is first adopted to forecast the basic wind power forecasting scenario and calculate the historical forecasting errors. A continuous Gaussian mixture model (GMM) is used to fit the probability distribution function (PDF) of forecasting errors. The cumulative distribution function (CDF) ismore » analytically deduced. The inverse transform method based on Monte Carlo sampling and the CDF is used to generate a massive number of forecasting error scenarios. An optimized swinging door algorithm is adopted to extract all the WPRs from the complete set of wind power forecasting scenarios. The probabilistic forecasting results of ramp duration and start time are generated based on all scenarios. Numerical simulations on publicly available wind power data show that within a predefined tolerance level, the developed probabilistic wind power ramp forecasting method is able to predict WPRs with a high level of sharpness and accuracy.« less

An analytic formula for the supercluster mass function

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

Lim, Seunghwan; Lee, Jounghun, E-mail: slim@astro.umass.edu, E-mail: jounghun@astro.snu.ac.kr

2014-03-01

We present an analytic formula for the supercluster mass function, which is constructed by modifying the extended Zel'dovich model for the halo mass function. The formula has two characteristic parameters whose best-fit values are determined by fitting to the numerical results from N-body simulations for the standard ΛCDM cosmology. The parameters are found to be independent of redshifts and robust against variation of the key cosmological parameters. Under the assumption that the same formula for the supercluster mass function is valid for non-standard cosmological models, we show that the relative abundance of the rich superclusters should be a powerful indicatormore » of any deviation of the real universe from the prediction of the standard ΛCDM model.« less

Functional Regression Models for Epistasis Analysis of Multiple Quantitative Traits.

PubMed

Zhang, Futao; Xie, Dan; Liang, Meimei; Xiong, Momiao

2016-04-01

To date, most genetic analyses of phenotypes have focused on analyzing single traits or analyzing each phenotype independently. However, joint epistasis analysis of multiple complementary traits will increase statistical power and improve our understanding of the complicated genetic structure of the complex diseases. Despite their importance in uncovering the genetic structure of complex traits, the statistical methods for identifying epistasis in multiple phenotypes remains fundamentally unexplored. To fill this gap, we formulate a test for interaction between two genes in multiple quantitative trait analysis as a multiple functional regression (MFRG) in which the genotype functions (genetic variant profiles) are defined as a function of the genomic position of the genetic variants. We use large-scale simulations to calculate Type I error rates for testing interaction between two genes with multiple phenotypes and to compare the power with multivariate pairwise interaction analysis and single trait interaction analysis by a single variate functional regression model. To further evaluate performance, the MFRG for epistasis analysis is applied to five phenotypes of exome sequence data from the NHLBI's Exome Sequencing Project (ESP) to detect pleiotropic epistasis. A total of 267 pairs of genes that formed a genetic interaction network showed significant evidence of epistasis influencing five traits. The results demonstrate that the joint interaction analysis of multiple phenotypes has a much higher power to detect interaction than the interaction analysis of a single trait and may open a new direction to fully uncovering the genetic structure of multiple phenotypes.

Population pharmacokinetics of paracetamol across the human age-range from (pre)term neonates, infants, children to adults.

PubMed

Wang, Chenguang; Allegaert, Karel; Tibboel, Dick; Danhof, Meindert; van der Marel, Caroline D; Mathot, Ron A A; Knibbe, Catherijne A J

2014-06-01

In order to characterize the variation in pharmacokinetics of paracetamol across the human age span, we performed a population pharmacokinetic analysis from preterm neonates to adults with specific focus on clearance. Concentration-time data obtained in 220 neonates (post-natal age 1-76 days, gestational age 27-42 weeks), infants (0.11-1.33 yrs), children (2-7 yrs) and adults (19-34 yrs) were analyzed using NONMEM 7.2. In the covariate analysis, linear functions, power functions, and a power function with a bodyweight-dependent exponent were tested. Between preterm neonates and adults, linear bodyweight functions were identified for Q2, Q3, V1, V2, and V3, while for CL a power function with a bodyweight-dependent exponent k was identified (CLi  = CLp  × (BW/70)(k) ). The exponent k was found to decrease in a sigmoidal manner with bodyweight from 1.2 to 0.75, with half the decrease in exponent reached at 12.2 kg. No other covariates such as age were identified. A pharmacokinetic model for paracetamol characterizing changes in pharmacokinetic parameters across the pediatric age-range was developed. Clearance was found to change in a nonlinear manner with bodyweight. Based on the final model, dosing guidelines are proposed from preterm neonates to adolescents resulting in similar exposure across all age ranges. © 2014, The American College of Clinical Pharmacology.

Regression-based reduced-order models to predict transient thermal output for enhanced geothermal systems

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

Mudunuru, Maruti Kumar; Karra, Satish; Harp, Dylan Robert

Reduced-order modeling is a promising approach, as many phenomena can be described by a few parameters/mechanisms. An advantage and attractive aspect of a reduced-order model is that it is computational inexpensive to evaluate when compared to running a high-fidelity numerical simulation. A reduced-order model takes couple of seconds to run on a laptop while a high-fidelity simulation may take couple of hours to run on a high-performance computing cluster. The goal of this paper is to assess the utility of regression-based reduced-order models (ROMs) developed from high-fidelity numerical simulations for predicting transient thermal power output for an enhanced geothermal reservoirmore » while explicitly accounting for uncertainties in the subsurface system and site-specific details. Numerical simulations are performed based on equally spaced values in the specified range of model parameters. Key sensitive parameters are then identified from these simulations, which are fracture zone permeability, well/skin factor, bottom hole pressure, and injection flow rate. We found the fracture zone permeability to be the most sensitive parameter. The fracture zone permeability along with time, are used to build regression-based ROMs for the thermal power output. The ROMs are trained and validated using detailed physics-based numerical simulations. Finally, predictions from the ROMs are then compared with field data. We propose three different ROMs with different levels of model parsimony, each describing key and essential features of the power production curves. The coefficients in the proposed regression-based ROMs are developed by minimizing a non-linear least-squares misfit function using the Levenberg–Marquardt algorithm. The misfit function is based on the difference between numerical simulation data and reduced-order model. ROM-1 is constructed based on polynomials up to fourth order. ROM-1 is able to accurately reproduce the power output of numerical simulations for low values of permeabilities and certain features of the field-scale data. ROM-2 is a model with more analytical functions consisting of polynomials up to order eight, exponential functions and smooth approximations of Heaviside functions, and accurately describes the field-data. At higher permeabilities, ROM-2 reproduces numerical results better than ROM-1, however, there is a considerable deviation from numerical results at low fracture zone permeabilities. ROM-3 consists of polynomials up to order ten, and is developed by taking the best aspects of ROM-1 and ROM-2. ROM-1 is relatively parsimonious than ROM-2 and ROM-3, while ROM-2 overfits the data. ROM-3 on the other hand, provides a middle ground for model parsimony. Based on R 2-values for training, validation, and prediction data sets we found that ROM-3 is better model than ROM-2 and ROM-1. For predicting thermal drawdown in EGS applications, where high fracture zone permeabilities (typically greater than 10 –15 m 2) are desired, ROM-2 and ROM-3 outperform ROM-1. As per computational time, all the ROMs are 10 4 times faster when compared to running a high-fidelity numerical simulation. In conclusion, this makes the proposed regression-based ROMs attractive for real-time EGS applications because they are fast and provide reasonably good predictions for thermal power output.« less

Regression-based reduced-order models to predict transient thermal output for enhanced geothermal systems

DOE PAGES

Mudunuru, Maruti Kumar; Karra, Satish; Harp, Dylan Robert; ...

2017-07-10

Reduced-order modeling is a promising approach, as many phenomena can be described by a few parameters/mechanisms. An advantage and attractive aspect of a reduced-order model is that it is computational inexpensive to evaluate when compared to running a high-fidelity numerical simulation. A reduced-order model takes couple of seconds to run on a laptop while a high-fidelity simulation may take couple of hours to run on a high-performance computing cluster. The goal of this paper is to assess the utility of regression-based reduced-order models (ROMs) developed from high-fidelity numerical simulations for predicting transient thermal power output for an enhanced geothermal reservoirmore » while explicitly accounting for uncertainties in the subsurface system and site-specific details. Numerical simulations are performed based on equally spaced values in the specified range of model parameters. Key sensitive parameters are then identified from these simulations, which are fracture zone permeability, well/skin factor, bottom hole pressure, and injection flow rate. We found the fracture zone permeability to be the most sensitive parameter. The fracture zone permeability along with time, are used to build regression-based ROMs for the thermal power output. The ROMs are trained and validated using detailed physics-based numerical simulations. Finally, predictions from the ROMs are then compared with field data. We propose three different ROMs with different levels of model parsimony, each describing key and essential features of the power production curves. The coefficients in the proposed regression-based ROMs are developed by minimizing a non-linear least-squares misfit function using the Levenberg–Marquardt algorithm. The misfit function is based on the difference between numerical simulation data and reduced-order model. ROM-1 is constructed based on polynomials up to fourth order. ROM-1 is able to accurately reproduce the power output of numerical simulations for low values of permeabilities and certain features of the field-scale data. ROM-2 is a model with more analytical functions consisting of polynomials up to order eight, exponential functions and smooth approximations of Heaviside functions, and accurately describes the field-data. At higher permeabilities, ROM-2 reproduces numerical results better than ROM-1, however, there is a considerable deviation from numerical results at low fracture zone permeabilities. ROM-3 consists of polynomials up to order ten, and is developed by taking the best aspects of ROM-1 and ROM-2. ROM-1 is relatively parsimonious than ROM-2 and ROM-3, while ROM-2 overfits the data. ROM-3 on the other hand, provides a middle ground for model parsimony. Based on R 2-values for training, validation, and prediction data sets we found that ROM-3 is better model than ROM-2 and ROM-1. For predicting thermal drawdown in EGS applications, where high fracture zone permeabilities (typically greater than 10 –15 m 2) are desired, ROM-2 and ROM-3 outperform ROM-1. As per computational time, all the ROMs are 10 4 times faster when compared to running a high-fidelity numerical simulation. In conclusion, this makes the proposed regression-based ROMs attractive for real-time EGS applications because they are fast and provide reasonably good predictions for thermal power output.« less

Experimental Effects of Propulsive Jets and Afterbody Configurations on the Zero-lift Drag of Bodies of Revolution at a Mach Number of 1.59

NASA Technical Reports Server (NTRS)

De Moraes, Carlos A; Nowitzky, Albin M

1954-01-01

The present investigation was made at a free-stream Mach number of 1.59 to compare the afterbody drags to a series of conical boattailed models at zero angle of attack. Afterbody drags were obtained for both the power-off and the power-on conditions. Power-on drags were obtained as a function of afterbody fineness ratio, jet pressure ratio and divergence, and jet Mach number.

Investigation of the laser pumping power impact on the operating regimes of a laser passively Q-switched by a saturated absorber

NASA Astrophysics Data System (ADS)

Benarab, Mustapha; Mokdad, Rabah; Djellout, Hocine; Benfdila, Arezki; Lamrous, Omar; Meyrueis, Patrick

2011-09-01

We have adapted the point model for the study of an all-fiber laser doped with Nd3+ and Q-switched by a saturable fiber absorber doped with Cr4+. Calculations of the output power of the 1084 nm laser are considered as a function of the pump power supplied by a 790 nm laser diode. The analysis of the simulation results reveals the existence of pulsed, sinusoidal, and dc operating regimes.

Social Modeling Influences on Pain Experience and Behaviour.

ERIC Educational Resources Information Center

Craig, Kenneth D.

The impact of exposure to social models displaying variably tolerant pain behaviour on observers' expressions of pain is examined. Findings indicate substantial effects on verbal reports of pain, avoidance behaviour, psychophysiological indices, power function parameters, and sensory decision theory indices. Discussion centers on how social models…

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).

Small scale clustering of late forming dark matter

NASA Astrophysics Data System (ADS)

Agarwal, S.; Corasaniti, P.-S.; Das, S.; Rasera, Y.

2015-09-01

We perform a study of the nonlinear clustering of matter in the late-forming dark matter (LFDM) scenario in which dark matter results from the transition of a nonminimally coupled scalar field from radiation to collisionless matter. A distinct feature of this model is the presence of a damped oscillatory cutoff in the linear matter power spectrum at small scales. We use a suite of high-resolution N-body simulations to study the imprints of LFDM on the nonlinear matter power spectrum, the halo mass and velocity functions and the halo density profiles. The model largely satisfies high-redshift matter power spectrum constraints from Lyman-α forest measurements, while it predicts suppressed abundance of low-mass halos (˜109- 1010 h-1 M⊙ ) at all redshifts compared to a vanilla Λ CDM model. The analysis of the LFDM halo velocity function shows a better agreement than the Λ CDM prediction with the observed abundance of low-velocity galaxies in the local volume. Halos with mass M ≳1011 h-1 M⊙ show minor departures of the density profiles from Λ CDM expectations, while smaller-mass halos are less dense, consistent with the fact that they form later than their Λ CDM counterparts.

Wind farm density and harvested power in very large wind farms: A low-order model

NASA Astrophysics Data System (ADS)

Cortina, G.; Sharma, V.; Calaf, M.

2017-07-01

In this work we create new understanding of wind turbine wakes recovery process as a function of wind farm density using large-eddy simulations of an atmospheric boundary layer diurnal cycle. Simulations are forced with a constant geostrophic wind and a time varying surface temperature extracted from a selected period of the Cooperative Atmospheric Surface Exchange Study field experiment. Wind turbines are represented using the actuator disk model with rotation and yaw alignment. A control volume analysis around each turbine has been used to evaluate wind turbine wake recovery and corresponding harvested power. Results confirm the existence of two dominant recovery mechanisms, advection and flux of mean kinetic energy, which are modulated by the background thermal stratification. For the low-density arrangements advection dominates, while for the highly loaded wind farms the mean kinetic energy recovers through fluxes of mean kinetic energy. For those cases in between, a smooth balance of both mechanisms exists. From the results, a low-order model for the wind farms' harvested power as a function of thermal stratification and wind farm density has been developed, which has the potential to be used as an order-of-magnitude assessment tool.

Research and development of energy harvesting from vibrations and human motions (Conference Presentation)

NASA Astrophysics Data System (ADS)

Liao, Wei-Hsin

2017-04-01

Most of the ambient energy, which was regarded useless in the past, now is under the spotlight. With the rapid developments on low power electronics, future personal mobile devices and remote sensing systems might become self-powered by scavenging energy in different forms from their surroundings. Kinetic energy is one of the promising energy forms in our living environment, e.g., human motions and vibrations. We have proposed an energy flow to clarify the functions of piezoelectric energy harvesting, dissipation, and their effects on the structural damping of vibrating structures. Impedance modeling and analysis were performed. We have designed an improved self-powered switching interface for piezoelectric energy harvesting circuits. With electromagnetic transduction, we also proposed a knee-mounted energy harvester that could convert the mechanical power from knee joints into electricity during walking. On the other hand, we have developed magnetorheological (MR) fluid devices with multiple functions, including rotary actuators and linear dampers. Multifunctional rotary actuator was designed to integrate motor/generator part and MR fluids into a single device. The actuator could function as motor, generator, clutch and brake, with compact size and good energy efficiency. In addition, novel self-sensing MR dampers with power generation, so as to integrate the dynamic sensing, controllable damping and power generation functions, were developed and investigated. Prototypes were fabricated and tested. The developed actuators were promising for various applications. In this paper, related research in energy harvesting done at The Chinese University of Hong Kong and key results will be presented.

A path integral approach to asset-liability management

NASA Astrophysics Data System (ADS)

Decamps, Marc; De Schepper, Ann; Goovaerts, Marc

2006-05-01

Functional integrals constitute a powerful tool in the investigation of financial models. In the recent econophysics literature, this technique was successfully used for the pricing of a number of derivative securities. In the present contribution, we introduce this approach to the field of asset-liability management. We work with a representation of cash flows by means of a two-dimensional delta-function perturbation, in the case of a Brownian model and a geometric Brownian model. We derive closed-form solutions for a finite horizon ALM policy. The results are numerically and graphically illustrated.

Price dynamics and market power in an agent-based power exchange

NASA Astrophysics Data System (ADS)

Cincotti, Silvano; Guerci, Eric; Raberto, Marco

2005-05-01

This paper presents an agent-based model of a power exchange. Supply of electric power is provided by competing generating companies, whereas demand is assumed to be inelastic with respect to price and is constant over time. The transmission network topology is assumed to be a fully connected graph and no transmission constraints are taken into account. The price formation process follows a common scheme for real power exchanges: a clearing house mechanism with uniform price, i.e., with price set equal across all matched buyer-seller pairs. A single class of generating companies is considered, characterized by linear cost function for each technology. Generating companies compete for the sale of electricity through repeated rounds of the uniform auction and determine their supply functions according to production costs. However, an individual reinforcement learning algorithm characterizes generating companies behaviors in order to attain the expected maximum possible profit in each auction round. The paper investigates how the market competitive equilibrium is affected by market microstructure and production costs.

Wire array Z-pinch insights for enhanced x-ray production

NASA Astrophysics Data System (ADS)

Sanford, T. W. L.; Mock, R. C.; Spielman, R. B.; Haines, M. G.; Chittenden, J. P.; Whitney, K. G.; Apruzese, J. P.; Peterson, D. L.; Greenly, J. B.; Sinars, D. B.; Reisman, D. B.; Mosher, D.

1999-05-01

Comparisons of measured total radiated x-ray power from annular wire-array z-pinches with a variety of models as a function of wire number, array mass, and load radius are reviewed. The data, which are comprehensive, have provided important insights into the features of wire-array dynamics that are critical for high x-ray power generation. Collectively, the comparisons of the data with the model calculations suggest that a number of underlying dynamical mechanisms involving cylindrical asymmetries and plasma instabilities contribute to the measured characteristics. For example, under the general assumption that the measured risetime of the total-radiated-power pulse is related to the thickness of the plasma shell formed on axis, the Heuristic Model [IEEE Trans. Plasma Sci. 26, 1275 (1998)] agrees with the measured risetime under a number of specific assumptions about the way the breakdown of the wires, the wire-plasma expansion, and the Rayleigh-Taylor instability in the r-z plane, develop. Likewise, in the high wire-number regime (where the wires are calculated to form a plasma shell prior to significant radial motion of the shell) the comparisons show that the variation in the power of the radiation generated as a function of load mass and array radius can be simulated by the two-dimensional Eulerian-radiation- magnetohydrodynamics code (E-RMHC) [Phys. Plasmas 3, 368 (1996)], using a single random-density perturbation that seeds the Rayleigh-Taylor instability in the r-z plane. For a given pulse-power generator, the comparisons suggest that (1) the smallest interwire gaps compatible with practical load construction and (2) the minimum implosion time consistent with the optimum required energy coupling of the generator to the load should produce the highest total-radiated-power levels.

Power-law decay of the spatial correlation function in exciton-polariton condensates

PubMed Central

Roumpos, Georgios; Lohse, Michael; Nitsche, Wolfgang H.; Keeling, Jonathan; Szymańska, Marzena Hanna; Littlewood, Peter B.; Löffler, Andreas; Höfling, Sven; Worschech, Lukas; Forchel, Alfred; Yamamoto, Yoshihisa

2012-01-01

We create a large exciton-polariton condensate and employ a Michelson interferometer setup to characterize the short- and long-distance behavior of the first order spatial correlation function. Our experimental results show distinct features of both the two-dimensional and nonequilibrium characters of the condensate. We find that the gaussian short-distance decay is followed by a power-law decay at longer distances, as expected for a two-dimensional condensate. The exponent of the power law is measured in the range 0.9–1.2, larger than is possible in equilibrium. We compare the experimental results to a theoretical model to understand the features required to observe a power law and to clarify the influence of external noise on spatial coherence in nonequilibrium phase transitions. Our results indicate that Berezinskii–Kosterlitz–Thouless-like phase order survives in open-dissipative systems. PMID:22496595

Robust Electrical Transfer System (RETS) for Solar Array Drive Mechanism SlipRing Assembly

NASA Astrophysics Data System (ADS)

Bommottet, Daniel; Bossoney, Luc; Schnyder, Ralph; Howling, Alan; Hollenstein, Christoph

2013-09-01

Demands for robust and reliable power transmission systems for sliprings for SADM (Solar Array Drive Mechanism) are increasing steadily. As a consequence, it is required to know their performances regarding the voltage breakdown limit.An understanding of the overall shape of the breakdown voltage versus pressure curve is established, based on experimental measurements of DC (Direct Current) gas breakdown in complex geometries compared with a numerical simulation model.In addition a detailed study was made of the functional behaviour of an entire wing of satellite in a like- operational mode, comprising the solar cells, the power transmission lines, the SRA (SlipRing Assembly), the power S3R (Sequential Serial/shunt Switching Regulators) and the satellite load to simulate the electrical power consumption.A test bench able to measure automatically the: a)breakdown voltage versus pressure curve and b)the functional switching performances, was developed and validated.

Specification and testing for power by wire aircraft

NASA Technical Reports Server (NTRS)

Hansen, Irving G.; Kenney, Barbara H.

1993-01-01

A power by wire aircraft is one in which all active functions other than propulsion are implemented electrically. Other nomenclature are 'all electric airplane,' or 'more electric airplane.' What is involved is the task of developing and certifying electrical equipment to replace existing hydraulics and pneumatics. When such functions, however, are primary flight controls which are implemented electrically, new requirements are imposed that were not anticipated by existing power system designs. Standards of particular impact are the requirements of ultra-high reliability, high peak transient bi-directional power flow, and immunity to electromagnetic interference and lightning. Not only must the electromagnetic immunity of the total system be verifiable, but box level tests and meaningful system models must be established to allow system evaluation. This paper discusses some of the problems, the system modifications involved, and early results in establishing wiring harness and interface susceptibility requirements.

Are we there yet? Tracking the development of new model systems

Treesearch

A. Abzhanov; C. Extavour; A. Groover; S. Hodges; H. Hoekstra; E. Kramer; A. Monteiro

2008-01-01

It is increasingly clear that additional ‘model’ systems are needed to elucidate the genetic and developmental basis of organismal diversity. Whereas model system development previously required enormous investment, recent advances including the decreasing cost of DNA sequencing and the power of reverse genetics to study gene function are greatly facilitating...

Functional Abstraction from Structure in VLSI Simulation Models,

DTIC Science & Technology

1987-05-01

wide vari- ety of powerful tools, designed around the Y model proposed by Gajski and Kuhn [11]. The heart of the system is the data representation...34Fuictional Models for VLSI Design", 20th IEEE Design Automation Conference (DAC󈨗), 1983, paper 32.2, pp. 506-514. * 21 [11] Gajski , Daniel D., Kuhn, Robert H

The Role of Atmospheric Measurements in Wind Power Statistical Models

NASA Astrophysics Data System (ADS)

Wharton, S.; Bulaevskaya, V.; Irons, Z.; Newman, J. F.; Clifton, A.

2015-12-01

The simplest wind power generation curves model power only as a function of the wind speed at turbine hub-height. While the latter is an essential predictor of power output, it is widely accepted that wind speed information in other parts of the vertical profile, as well as additional atmospheric variables including atmospheric stability, wind veer, and hub-height turbulence are also important factors. The goal of this work is to determine the gain in predictive ability afforded by adding additional atmospheric measurements to the power prediction model. In particular, we are interested in quantifying any gain in predictive ability afforded by measurements taken from a laser detection and ranging (lidar) instrument, as lidar provides high spatial and temporal resolution measurements of wind speed and direction at 10 or more levels throughout the rotor-disk and at heights well above. Co-located lidar and meteorological tower data as well as SCADA power data from a wind farm in Northern Oklahoma will be used to train a set of statistical models. In practice, most wind farms continue to rely on atmospheric measurements taken from less expensive, in situ instruments mounted on meteorological towers to assess turbine power response to a changing atmospheric environment. Here, we compare a large suite of atmospheric variables derived from tower measurements to those taken from lidar to determine if remote sensing devices add any competitive advantage over tower measurements alone to predict turbine power response.

Random medium model for cusping of plane waves.

PubMed

Li, Jia; Korotkova, Olga

2017-09-01

We introduce a model for a three-dimensional (3D) Schell-type stationary medium whose degree of potential's correlation satisfies the Fractional Multi-Gaussian (FMG) function. Compared with the scattered profile produced by the Gaussian Schell-model (GSM) medium, the Fractional Multi-Gaussian Schell-model (FMGSM) medium gives rise to a sharp concave intensity apex in the scattered field. This implies that the FMGSM medium also accounts for a larger than Gaussian's power in the bucket (PIB) in the forward scattering direction, hence being a better candidate than the GSM medium for generating highly-focused (cusp-like) scattered profiles in the far zone. Compared to other mathematical models for the medium's correlation function which can produce similar cusped scattered profiles the FMG function offers unprecedented tractability being the weighted superposition of Gaussian functions. Our results provide useful applications to energy counter problems and particle manipulation by weakly scattered fields.

Validity of linear encoder measurement of sit-to-stand performance power in older people.

PubMed

Lindemann, U; Farahmand, P; Klenk, J; Blatzonis, K; Becker, C

2015-09-01

To investigate construct validity of linear encoder measurement of sit-to-stand performance power in older people by showing associations with relevant functional performance and physiological parameters. Cross-sectional study. Movement laboratory of a geriatric rehabilitation clinic. Eighty-eight community-dwelling, cognitively unimpaired older women (mean age 78 years). Sit-to-stand performance power and leg power were assessed using a linear encoder and the Nottingham Power Rig, respectively. Gait speed was measured on an instrumented walkway. Maximum quadriceps and hand grip strength were assessed using dynamometers. Mid-thigh muscle cross-sectional area of both legs was measured using magnetic resonance imaging. Associations of sit-to-stand performance power with power assessed by the Nottingham Power Rig, maximum gait speed and muscle cross-sectional area were r=0.646, r=0.536 and r=0.514, respectively. A linear regression model explained 50% of the variance in sit-to-stand performance power including muscle cross-sectional area (p=0.001), maximum gait speed (p=0.002), and power assessed by the Nottingham Power Rig (p=0.006). Construct validity of linear encoder measurement of sit-to-stand power was shown at functional level and morphological level for older women. This measure could be used in routine clinical practice as well as in large-scale studies. DRKS00003622. Copyright © 2015 Chartered Society of Physiotherapy. Published by Elsevier Ltd. All rights reserved.

Pleiotropy Analysis of Quantitative Traits at Gene Level by Multivariate Functional Linear Models

PubMed Central

Wang, Yifan; Liu, Aiyi; Mills, James L.; Boehnke, Michael; Wilson, Alexander F.; Bailey-Wilson, Joan E.; Xiong, Momiao; Wu, Colin O.; Fan, Ruzong

2015-01-01

In genetics, pleiotropy describes the genetic effect of a single gene on multiple phenotypic traits. A common approach is to analyze the phenotypic traits separately using univariate analyses and combine the test results through multiple comparisons. This approach may lead to low power. Multivariate functional linear models are developed to connect genetic variant data to multiple quantitative traits adjusting for covariates for a unified analysis. Three types of approximate F-distribution tests based on Pillai–Bartlett trace, Hotelling–Lawley trace, and Wilks’s Lambda are introduced to test for association between multiple quantitative traits and multiple genetic variants in one genetic region. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and optimal sequence kernel association test (SKAT-O). Extensive simulations were performed to evaluate the false positive rates and power performance of the proposed models and tests. We show that the approximate F-distribution tests control the type I error rates very well. Overall, simultaneous analysis of multiple traits can increase power performance compared to an individual test of each trait. The proposed methods were applied to analyze (1) four lipid traits in eight European cohorts, and (2) three biochemical traits in the Trinity Students Study. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and SKAT-O for the three biochemical traits. The approximate F-distribution tests of the proposed functional linear models are more sensitive than those of the traditional multivariate linear models that in turn are more sensitive than SKAT-O in the univariate case. The analysis of the four lipid traits and the three biochemical traits detects more association than SKAT-O in the univariate case. PMID:25809955

Pleiotropy analysis of quantitative traits at gene level by multivariate functional linear models.

PubMed

Wang, Yifan; Liu, Aiyi; Mills, James L; Boehnke, Michael; Wilson, Alexander F; Bailey-Wilson, Joan E; Xiong, Momiao; Wu, Colin O; Fan, Ruzong

2015-05-01

In genetics, pleiotropy describes the genetic effect of a single gene on multiple phenotypic traits. A common approach is to analyze the phenotypic traits separately using univariate analyses and combine the test results through multiple comparisons. This approach may lead to low power. Multivariate functional linear models are developed to connect genetic variant data to multiple quantitative traits adjusting for covariates for a unified analysis. Three types of approximate F-distribution tests based on Pillai-Bartlett trace, Hotelling-Lawley trace, and Wilks's Lambda are introduced to test for association between multiple quantitative traits and multiple genetic variants in one genetic region. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and optimal sequence kernel association test (SKAT-O). Extensive simulations were performed to evaluate the false positive rates and power performance of the proposed models and tests. We show that the approximate F-distribution tests control the type I error rates very well. Overall, simultaneous analysis of multiple traits can increase power performance compared to an individual test of each trait. The proposed methods were applied to analyze (1) four lipid traits in eight European cohorts, and (2) three biochemical traits in the Trinity Students Study. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and SKAT-O for the three biochemical traits. The approximate F-distribution tests of the proposed functional linear models are more sensitive than those of the traditional multivariate linear models that in turn are more sensitive than SKAT-O in the univariate case. The analysis of the four lipid traits and the three biochemical traits detects more association than SKAT-O in the univariate case. © 2015 WILEY PERIODICALS, INC.

Self-consistent fluid modeling and simulation on a pulsed microwave atmospheric-pressure argon plasma jet

NASA Astrophysics Data System (ADS)

Chen, Zhaoquan; Yin, Zhixiang; Chen, Minggong; Hong, Lingli; Xia, Guangqing; Hu, Yelin; Huang, Yourui; Liu, Minghai; Kudryavtsev, A. A.

2014-10-01

In present study, a pulsed lower-power microwave-driven atmospheric-pressure argon plasma jet has been introduced with the type of coaxial transmission line resonator. The plasma jet plume is with room air temperature, even can be directly touched by human body without any hot harm. In order to study ionization process of the proposed plasma jet, a self-consistent hybrid fluid model is constructed in which Maxwell's equations are solved numerically by finite-difference time-domain method and a fluid model is used to study the characteristics of argon plasma evolution. With a Guass type input power function, the spatio-temporal distributions of the electron density, the electron temperature, the electric field, and the absorbed power density have been simulated, respectively. The simulation results suggest that the peak values of the electron temperature and the electric field are synchronous with the input pulsed microwave power but the maximum quantities of the electron density and the absorbed power density are lagged to the microwave power excitation. In addition, the pulsed plasma jet excited by the local enhanced electric field of surface plasmon polaritons should be the discharge mechanism of the proposed plasma jet.

Model systems: how chemical biologists study RNA

PubMed Central

Rios, Andro C.; Tor, Yitzhak

2009-01-01

Ribonucleic acids are structurally and functionally sophisticated biomolecules and the use of models, frequently truncated or modified sequences representing functional domains of the natural systems, is essential to their exploration. Functional non-coding RNAs such as miRNAs, riboswitches, and, in particular, ribozymes, have changed the view of RNA’s role in biology and its catalytic potential. The well-known truncated hammerhead model has recently been refined and new data provide a clearer molecular picture of the elements responsible for its catalytic power. A model for the spliceosome, a massive and highly intricate ribonucleoprotein, is also emerging, although its true utility is yet to be cemented. Such catalytic model systems could also serve as “chemo-paleontological” tools, further refining the RNA world hypothesis and its relevance to the origin and evolution of life. PMID:19879179

Cylindrically symmetric Green's function approach for modeling the crystal growth morphology of ice.

PubMed

Libbrecht, K G

1999-08-01

We describe a front-tracking Green's function approach to modeling cylindrically symmetric crystal growth. This method is simple to implement, and with little computer power can adequately model a wide range of physical situations. We apply the method to modeling the hexagonal prism growth of ice crystals, which is governed primarily by diffusion along with anisotropic surface kinetic processes. From ice crystal growth observations in air, we derive measurements of the kinetic growth coefficients for the basal and prism faces as a function of temperature, for supersaturations near the water saturation level. These measurements are interpreted in the context of a model for the nucleation and growth of ice, in which the growth dynamics are dominated by the structure of a disordered layer on the ice surfaces.

Item selection via Bayesian IRT models.

PubMed

Arima, Serena

2015-02-10

With reference to a questionnaire that aimed to assess the quality of life for dysarthric speakers, we investigate the usefulness of a model-based procedure for reducing the number of items. We propose a mixed cumulative logit model, which is known in the psychometrics literature as the graded response model: responses to different items are modelled as a function of individual latent traits and as a function of item characteristics, such as their difficulty and their discrimination power. We jointly model the discrimination and the difficulty parameters by using a k-component mixture of normal distributions. Mixture components correspond to disjoint groups of items. Items that belong to the same groups can be considered equivalent in terms of both difficulty and discrimination power. According to decision criteria, we select a subset of items such that the reduced questionnaire is able to provide the same information that the complete questionnaire provides. The model is estimated by using a Bayesian approach, and the choice of the number of mixture components is justified according to information criteria. We illustrate the proposed approach on the basis of data that are collected for 104 dysarthric patients by local health authorities in Lecce and in Milan. Copyright © 2014 John Wiley & Sons, Ltd.

Safe Lock

NASA Technical Reports Server (NTRS)

1991-01-01

The Model 1150 electronic spring latch, which provides controlled and timed access to a safe, was developed by Burnett Electronics Lab, Inc., San Diego, CA, and is marketed by KeyOne, Inc. also of San Diego. The Model 1150 is a spinoff from a spinoff. The original spinoff, the acoustic pinger, is an underwater transmitting device developed by Langley Research Center and the Navy for location and recovery of sounding rocket research payloads from the ocean. Long functioning life is a vital requirement for both the acoustic pinger and the Model 1150. The electronic spring latch employs the pinger power management technology to get long life out of the battery power source.

Neutral Evolution of Duplicated DNA: An Evolutionary Stick-Breaking Process Causes Scale-Invariant Behavior

NASA Astrophysics Data System (ADS)

Massip, Florian; Arndt, Peter F.

2013-04-01

Recently, an enrichment of identical matching sequences has been found in many eukaryotic genomes. Their length distribution exhibits a power law tail raising the question of what evolutionary mechanism or functional constraints would be able to shape this distribution. Here we introduce a simple and evolutionarily neutral model, which involves only point mutations and segmental duplications, and produces the same statistical features as observed for genomic data. Further, we extend a mathematical model for random stick breaking to analytically show that the exponent of the power law tail is -3 and universal as it does not depend on the microscopic details of the model.

Optimal positions and parameters of translational and rotational mass dampers in beams subjected to random excitation

NASA Astrophysics Data System (ADS)

Łatas, Waldemar

2018-01-01

The problem of vibrations of the beam with the attached system of translational and rotational dynamic mass dampers subjected to random excitations with peaked power spectral densities, is presented in the hereby paper. The Euler-Bernoulli beam model is applied, while for solving the equation of motion the Galerkin method and the Laplace time transform are used. The obtained transfer functions allow to determine power spectral densities of the beam deflection and other dependent variables. Numerical examples present simple optimization problems of mass dampers parameters for local and global objective functions.

A Tool for Model-Based Generation of Scenario-driven Electric Power Load Profiles

NASA Technical Reports Server (NTRS)

Rozek, Matthew L.; Donahue, Kenneth M.; Ingham, Michel D.; Kaderka, Justin D.

2015-01-01

Power consumption during all phases of spacecraft flight is of great interest to the aerospace community. As a result, significant analysis effort is exerted to understand the rates of electrical energy generation and consumption under many operational scenarios of the system. Previously, no standard tool existed for creating and maintaining a power equipment list (PEL) of spacecraft components that consume power, and no standard tool existed for generating power load profiles based on this PEL information during mission design phases. This paper presents the Scenario Power Load Analysis Tool (SPLAT) as a model-based systems engineering tool aiming to solve those problems. SPLAT is a plugin for MagicDraw (No Magic, Inc.) that aids in creating and maintaining a PEL, and also generates a power and temporal variable constraint set, in Maple language syntax, based on specified operational scenarios. The constraint set can be solved in Maple to show electric load profiles (i.e. power consumption from loads over time). SPLAT creates these load profiles from three modeled inputs: 1) a list of system components and their respective power modes, 2) a decomposition hierarchy of the system into these components, and 3) the specification of at least one scenario, which consists of temporal constraints on component power modes. In order to demonstrate how this information is represented in a system model, a notional example of a spacecraft planetary flyby is introduced. This example is also used to explain the overall functionality of SPLAT, and how this is used to generate electric power load profiles. Lastly, a cursory review of the usage of SPLAT on the Cold Atom Laboratory project is presented to show how the tool was used in an actual space hardware design application.

Mathematical Modeling of Optical Radiation Emission as a Function of Welding Power during Gas Shielded Metal Arc Welding.

PubMed

Bauer, Stefan; Janßen, Marco; Schmitz, Martin; Ott, Günter

2017-11-01

Arc welding is accompanied by intense optical radiation emission that can be detrimental not only for the welder himself but also for people working nearby or for passersby. Technological progress advances continuously in the field of joining, so an up-to-date radiation database is necessary. Additionally, many literature irradiance data have been measured for a few welding currents or for parts of the optical spectral region only. Within this paper, a comprehensive study of contemporary metal active gas, metal inert gas, and cold metal transfer welding is presented covering optical radiation emission from 200 up to 2,700 nm by means of (spectro-) radiometric measurements. The investigated welding currents range from 70 to 350 A, reflecting values usually applied in industry. Based upon these new irradiance data, three mathematical models were derived in order to describe optical radiation emission as a function of welding power. The linear, exponential, and sigmoidal emission models depend on the process variant (standard or pulsed) as well as on the welding material (mild and stainless steel, aluminum). In conjunction with the corresponding exposure limit values for incoherent optical radiation maximum permissible exposure durations were calculated as a function of welding power. Typical times are shorter than 1 s for the ultraviolet spectral region and range from 1 to 10 s for visible radiation. For the infrared regime, exposure durations are of the order of minutes to hours. Finally, a validation of the metal active gas emission models was carried out with manual arc welding.

Spectral Modeling of the EGRET 3EG Gamma Ray Sources Near the Galactic Plane

NASA Technical Reports Server (NTRS)

Bertsch, D. L.; Hartman, R. C.; Hunter, S. D.; Thompson, D. J.; Lin, Y. C.; Kniffen, D. A.; Kanbach, G.; Mayer-Hasselwander, H. A.; Reimer, O.; Sreekumar, P.

1999-01-01

The third EGRET catalog lists 84 sources within 10 deg of the Galactic Plane. Five of these are well-known spin-powered pulsars, 2 and possibly 3 others are blazars, and the remaining 74 are classified as unidentified, although 6 of these are likely to be artifacts of nearby strong sources. Several of the remaining 68 unidentified sources have been noted as having positional agreement with supernovae remnants and OB associations. Others may be radio-quiet pulsars like Geminga, and still others may belong to a totally new class of sources. The question of the energy spectral distributions of these sources is an important clue to their identification. In this paper, the spectra of the sources within 10 deg of Galactic Plane are fit with three different functional forms; a single power law, two power laws, and a power law with an exponential cutoff. Where possible, the best fit is selected with statistical tests. Twelve, and possibly an additional 5 sources, are found to have spectra that are fit by a breaking power law or by the power law with exponential cutoff function.

Optical remote sensing and correlation of office equipment functional state and stress levels via power quality disturbances inefficiencies

NASA Astrophysics Data System (ADS)

Sternberg, Oren; Bednarski, Valerie R.; Perez, Israel; Wheeland, Sara; Rockway, John D.

2016-09-01

Non-invasive optical techniques pertaining to the remote sensing of power quality disturbances (PQD) are part of an emerging technology field typically dominated by radio frequency (RF) and invasive-based techniques. Algorithms and methods to analyze and address PQD such as probabilistic neural networks and fully informed particle swarms have been explored in industry and academia. Such methods are tuned to work with RF equipment and electronics in existing power grids. As both commercial and defense assets are heavily power-dependent, understanding electrical transients and failure events using non-invasive detection techniques is crucial. In this paper we correlate power quality empirical models to the observed optical response. We also empirically demonstrate a first-order approach to map household, office and commercial equipment PQD to user functions and stress levels. We employ a physics-based image and signal processing approach, which demonstrates measured non-invasive (remote sensing) techniques to detect and map the base frequency associated with the power source to the various PQD on a calibrated source.

MADGiC: a model-based approach for identifying driver genes in cancer

PubMed Central

Korthauer, Keegan D.; Kendziorski, Christina

2015-01-01

Motivation: Identifying and prioritizing somatic mutations is an important and challenging area of cancer research that can provide new insights into gene function as well as new targets for drug development. Most methods for prioritizing mutations rely primarily on frequency-based criteria, where a gene is identified as having a driver mutation if it is altered in significantly more samples than expected according to a background model. Although useful, frequency-based methods are limited in that all mutations are treated equally. It is well known, however, that some mutations have no functional consequence, while others may have a major deleterious impact. The spatial pattern of mutations within a gene provides further insight into their functional consequence. Properly accounting for these factors improves both the power and accuracy of inference. Also important is an accurate background model. Results: Here, we develop a Model-based Approach for identifying Driver Genes in Cancer (termed MADGiC) that incorporates both frequency and functional impact criteria and accommodates a number of factors to improve the background model. Simulation studies demonstrate advantages of the approach, including a substantial increase in power over competing methods. Further advantages are illustrated in an analysis of ovarian and lung cancer data from The Cancer Genome Atlas (TCGA) project. Availability and implementation: R code to implement this method is available at http://www.biostat.wisc.edu/ kendzior/MADGiC/. Contact: kendzior@biostat.wisc.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25573922

Mixed Effects Models for Resampled Network Statistics Improves Statistical Power to Find Differences in Multi-Subject Functional Connectivity

PubMed Central

Narayan, Manjari; Allen, Genevera I.

2016-01-01

Many complex brain disorders, such as autism spectrum disorders, exhibit a wide range of symptoms and disability. To understand how brain communication is impaired in such conditions, functional connectivity studies seek to understand individual differences in brain network structure in terms of covariates that measure symptom severity. In practice, however, functional connectivity is not observed but estimated from complex and noisy neural activity measurements. Imperfect subject network estimates can compromise subsequent efforts to detect covariate effects on network structure. We address this problem in the case of Gaussian graphical models of functional connectivity, by proposing novel two-level models that treat both subject level networks and population level covariate effects as unknown parameters. To account for imperfectly estimated subject level networks when fitting these models, we propose two related approaches—R2 based on resampling and random effects test statistics, and R3 that additionally employs random adaptive penalization. Simulation studies using realistic graph structures reveal that R2 and R3 have superior statistical power to detect covariate effects compared to existing approaches, particularly when the number of within subject observations is comparable to the size of subject networks. Using our novel models and methods to study parts of the ABIDE dataset, we find evidence of hypoconnectivity associated with symptom severity in autism spectrum disorders, in frontoparietal and limbic systems as well as in anterior and posterior cingulate cortices. PMID:27147940

NCWin — A Component Object Model (COM) for processing and visualizing NetCDF data

USGS Publications Warehouse

Liu, Jinxun; Chen, J.M.; Price, D.T.; Liu, S.

2005-01-01

NetCDF (Network Common Data Form) is a data sharing protocol and library that is commonly used in large-scale atmospheric and environmental data archiving and modeling. The NetCDF tool described here, named NCWin and coded with Borland C + + Builder, was built as a standard executable as well as a COM (component object model) for the Microsoft Windows environment. COM is a powerful technology that enhances the reuse of applications (as components). Environmental model developers from different modeling environments, such as Python, JAVA, VISUAL FORTRAN, VISUAL BASIC, VISUAL C + +, and DELPHI, can reuse NCWin in their models to read, write and visualize NetCDF data. Some Windows applications, such as ArcGIS and Microsoft PowerPoint, can also call NCWin within the application. NCWin has three major components: 1) The data conversion part is designed to convert binary raw data to and from NetCDF data. It can process six data types (unsigned char, signed char, short, int, float, double) and three spatial data formats (BIP, BIL, BSQ); 2) The visualization part is designed for displaying grid map series (playing forward or backward) with simple map legend, and displaying temporal trend curves for data on individual map pixels; and 3) The modeling interface is designed for environmental model development by which a set of integrated NetCDF functions is provided for processing NetCDF data. To demonstrate that the NCWin can easily extend the functions of some current GIS software and the Office applications, examples of calling NCWin within ArcGIS and MS PowerPoint for showing NetCDF map animations are given.

Power law-based local search in spider monkey optimisation for lower order system modelling

NASA Astrophysics Data System (ADS)

Sharma, Ajay; Sharma, Harish; Bhargava, Annapurna; Sharma, Nirmala

2017-01-01

The nature-inspired algorithms (NIAs) have shown efficiency to solve many complex real-world optimisation problems. The efficiency of NIAs is measured by their ability to find adequate results within a reasonable amount of time, rather than an ability to guarantee the optimal solution. This paper presents a solution for lower order system modelling using spider monkey optimisation (SMO) algorithm to obtain a better approximation for lower order systems and reflects almost original higher order system's characteristics. Further, a local search strategy, namely, power law-based local search is incorporated with SMO. The proposed strategy is named as power law-based local search in SMO (PLSMO). The efficiency, accuracy and reliability of the proposed algorithm is tested over 20 well-known benchmark functions. Then, the PLSMO algorithm is applied to solve the lower order system modelling problem.

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.

High-Density Signal Interface Electromagnetic Radiation Prediction for Electromagnetic Compatibility Evaluation.

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

Halligan, Matthew

Radiated power calculation approaches for practical scenarios of incomplete high- density interface characterization information and incomplete incident power information are presented. The suggested approaches build upon a method that characterizes power losses through the definition of power loss constant matrices. Potential radiated power estimates include using total power loss information, partial radiated power loss information, worst case analysis, and statistical bounding analysis. A method is also proposed to calculate radiated power when incident power information is not fully known for non-periodic signals at the interface. Incident data signals are modeled from a two-state Markov chain where bit state probabilities aremore » derived. The total spectrum for windowed signals is postulated as the superposition of spectra from individual pulses in a data sequence. Statistical bounding methods are proposed as a basis for the radiated power calculation due to the statistical calculation complexity to find a radiated power probability density function.« less

Hierarchical Bayesian Models of Subtask Learning

ERIC Educational Resources Information Center

Anglim, Jeromy; Wynton, Sarah K. A.

2015-01-01

The current study used Bayesian hierarchical methods to challenge and extend previous work on subtask learning consistency. A general model of individual-level subtask learning was proposed focusing on power and exponential functions with constraints to test for inconsistency. To study subtask learning, we developed a novel computer-based booking…

Forgetting Curves: Implications for Connectionist Models

ERIC Educational Resources Information Center

Sikstrom, Sverker

2002-01-01

Forgetting in long-term memory, as measured in a recall or a recognition test, is faster for items encoded more recently than for items encoded earlier. Data on forgetting curves fit a power function well. In contrast, many connectionist models predict either exponential decay or completely flat forgetting curves. This paper suggests a…

78 FR 58492 - Generator Verification Reliability Standards

Federal Register 2010, 2011, 2012, 2013, 2014

2013-09-24

... Control Functions), MOD-027-1 (Verification of Models and Data for Turbine/Governor and Load Control or...), MOD-027-1 (Verification of Models and Data for Turbine/Governor and Load Control or Active Power... Category B and C contingencies, as required by wind generators in Order No. 661, or that those generators...

The Increased Pluralism and Politicization of Public Education--Coping with Conflict.

ERIC Educational Resources Information Center

Coleman, Peter

Power, or influence, in educational governance is increasingly becoming diffused. Everyone in education now feels relatively powerless. A political model of decision-making, emphasizing consultation with representatives of interest groups is now appropriate. In this model, the school board functions as "meta-mediator." This modifies the…

Galaxy power spectrum in redshift space: Combining perturbation theory with the halo model

DOE PAGES

Okumura, Teppei; Hand, Nick; Seljak, Uros; ...

2015-11-19

Theoretical modeling of the redshift-space power spectrum of galaxies is crucially important to correctly extract cosmological information from galaxy redshift surveys. The task is complicated by the nonlinear biasing and redshift space distortion (RSD) effects, which change with halo mass, and by the wide distribution of halo masses and their occupations by galaxies. One of the main modeling challenges is the existence of satellite galaxies that have both radial distribution inside the halos and large virial velocities inside halos, a phenomenon known as the Finger-of-God (FoG) effect. We present a model for the redshift-space power spectrum of galaxies in whichmore » we decompose a given galaxy sample into central and satellite galaxies and relate different contributions to the power spectrum to 1-halo and 2-halo terms in a halo model. Our primary goal is to ensure that any parameters that we introduce have physically meaningful values, and are not just fitting parameters. For the lowest order 2-halo terms we use the previously developed RSD modeling of halos in the context of distribution function and perturbation theory approach. This term needs to be multiplied by the effect of radial distances and velocities of satellites inside the halo. To this one needs to add the 1-halo terms, which are nonperturbative. We show that the real space 1-halo terms can be modeled as almost constant, with the finite extent of the satellites inside the halo inducing a small k 2R 2 term over the range of scales of interest, where R is related to the size of the halo given by its halo mass. Furthermore, we adopt a similar model for FoG in redshift space, ensuring that FoG velocity dispersion is related to the halo mass. For FoG k 2 type expansions do not work over the range of scales of interest and FoG resummation must be used instead. We test several simple damping functions to model the velocity dispersion FoG effect. Applying the formalism to mock galaxies modeled after the “CMASS” sample of the BOSS survey, we find that our predictions for the redshift-space power spectra are accurate up to k ≃ 0.4 h Mpc –1 within 1% if the halo power spectrum is measured using N-body simulations and within 3% if it is modeled using perturbation theory.« less

Cosmic microwave background constraints for global strings and global monopoles

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

Lopez-Eiguren, Asier; Lizarraga, Joanes; Urrestilla, Jon

We present the first cosmic microwave background (CMB) power spectra from numerical simulations of the global O( N ) linear σ-model, with N =2,3, which have global strings and monopoles as topological defects. In order to compute the CMB power spectra we compute the unequal time correlators (UETCs) of the energy-momentum tensor, showing that they fall off at high wave number faster than naive estimates based on the geometry of the defects, indicating non-trivial (anti-)correlations between the defects and the surrounding Goldstone boson field. We obtain source functions for Einstein-Boltzmann solvers from the UETCs, using a recently developed method thatmore » improves the modelling at the radiation-matter transition. We show that the interpolation function that mimics the transition is similar to other defect models, but not identical, confirming the non-universality of the interpolation function. The CMB power spectra for global strings and global monopoles have the same overall shape as those obtained using the non-linear σ-model approximation, which is well captured by a large- N calculation. However, the amplitudes are larger than the large- N calculation would naively predict, and in the case of global strings much larger: a factor of 20 at the peak. Finally we compare the CMB power spectra with the latest CMB data in other to put limits on the allowed contribution to the temperature power spectrum at multipole l = 10 of 1.7% for global strings and 2.4% for global monopoles. These limits correspond to symmetry-breaking scales of 2.9× 10{sup 15} GeV (6.3× 10{sup 14} GeV with the expected logarithmic scaling of the effective string tension between the simulation time and decoupling) and 6.4× 10{sup 15} GeV respectively. The bound on global strings is a significant one for the ultra-light axion scenario with axion masses m {sub a} ∼< 10{sup −28} eV . These upper limits indicate that gravitational waves from global topological defects will not be observable at the gravitational wave observatory LISA.« less

Power-law viscous materials for analogue experiments: New data on the rheology of highly-filled silicone polymers

NASA Astrophysics Data System (ADS)

Boutelier, D.; Schrank, C.; Cruden, A.

2008-03-01

The selection of appropriate analogue materials is a central consideration in the design of realistic physical models. We investigate the rheology of highly-filled silicone polymers in order to find materials with a power-law strain-rate softening rheology suitable for modelling rock deformation by dislocation creep and report the rheological properties of the materials as functions of the filler content. The mixtures exhibit strain-rate softening behaviour but with increasing amounts of filler become strain-dependent. For the strain-independent viscous materials, flow laws are presented while for strain-dependent materials the relative importance of strain and strain rate softening/hardening is reported. If the stress or strain rate is above a threshold value some highly-filled silicone polymers may be considered linear visco-elastic (strain independent) and power-law strain-rate softening. The power-law exponent can be raised from 1 to ˜3 by using mixtures of high-viscosity silicone and plasticine. However, the need for high shear strain rates to obtain the power-law rheology imposes some restrictions on the usage of such materials for geodynamic modelling. Two simple shear experiments are presented that use Newtonian and power-law strain-rate softening materials. The results demonstrate how materials with power-law rheology result in better strain localization in analogue experiments.

Countermovement depth - a variable which clarifies the relationship between the maximum power output and height of a vertical jump.

PubMed

Gajewski, Jan; Michalski, Radosław; Buśko, Krzysztof; Mazur-Różycka, Joanna; Staniak, Zbigniew

2018-01-01

The aim of this study was to identify the determinants of peak power achieved during vertical jumps in order to clarify relationship between the height of jump and the ability to exert maximum power. One hundred young (16.8±1.8 years) sportsmen participated in the study (body height 1.861 ± 0.109 m, body weight 80.3 ± 9.2 kg). Each participant performed three jump tests: countermovement jump (CMJ), akimbo countermovement jump (ACMJ), and spike jump (SPJ). A force plate was used to measure ground reaction force and to determine peak power output. The following explanatory variables were included in the model: jump height, body mass, and the lowering of the centre of mass before launch (countermovement depth). A model was created using multiple regression analysis and allometric scaling. The model was used to calculate the expected power value for each participant, which correlated strongly with real values. The value of the coefficient of determination R2 equalled 0.89, 0.90 and 0.98, respectively, for the CMJ, ACMJ, and SPJ jumps. The countermovement depth proved to be a variable strongly affecting the maximum power of jump. If the countermovement depth remains constant, the relative peak power is a simple function of jump height. The results suggest that the jump height of an individual is an exact indicator of their ability to produce maximum power. The presented model has a potential to be utilized under field condition for estimating the maximum power output of vertical jumps.

The Use of Artificial Neural Networks for Forecasting the Electric Demand of Stand-Alone Consumers

NASA Astrophysics Data System (ADS)

Ivanin, O. A.; Direktor, L. B.

2018-05-01

The problem of short-term forecasting of electric power demand of stand-alone consumers (small inhabited localities) situated outside centralized power supply areas is considered. The basic approaches to modeling the electric power demand depending on the forecasting time frame and the problems set, as well as the specific features of such modeling, are described. The advantages and disadvantages of the methods used for the short-term forecast of the electric demand are indicated, and difficulties involved in the solution of the problem are outlined. The basic principles of arranging artificial neural networks are set forth; it is also shown that the proposed method is preferable when the input information necessary for prediction is lacking or incomplete. The selection of the parameters that should be included into the list of the input data for modeling the electric power demand of residential areas using artificial neural networks is validated. The structure of a neural network is proposed for solving the problem of modeling the electric power demand of residential areas. The specific features of generation of the training dataset are outlined. The results of test modeling of daily electric demand curves for some settlements of Kamchatka and Yakutia based on known actual electric demand curves are provided. The reliability of the test modeling has been validated. A high value of the deviation of the modeled curve from the reference curve obtained in one of the four reference calculations is explained. The input data and the predicted power demand curves for the rural settlement of Kuokuiskii Nasleg are provided. The power demand curves were modeled for four characteristic days of the year, and they can be used in the future for designing a power supply system for the settlement. To enhance the accuracy of the method, a series of measures based on specific features of a neural network's functioning are proposed.

The 2-10 keV unabsorbed luminosity function of AGN from the LSS, CDFS, and COSMOS surveys

NASA Astrophysics Data System (ADS)

Ranalli, P.; Koulouridis, E.; Georgantopoulos, I.; Fotopoulou, S.; Hsu, L.-T.; Salvato, M.; Comastri, A.; Pierre, M.; Cappelluti, N.; Carrera, F. J.; Chiappetti, L.; Clerc, N.; Gilli, R.; Iwasawa, K.; Pacaud, F.; Paltani, S.; Plionis, E.; Vignali, C.

2016-05-01

The XMM-Large scale structure (XMM-LSS), XMM-Cosmological evolution survey (XMM-COSMOS), and XMM-Chandra deep field south (XMM-CDFS) surveys are complementary in terms of sky coverage and depth. Together, they form a clean sample with the least possible variance in instrument effective areas and point spread function. Therefore this is one of the best samples available to determine the 2-10 keV luminosity function of active galactic nuclei (AGN) and their evolution. The samples and the relevant corrections for incompleteness are described. A total of 2887 AGN is used to build the LF in the luminosity interval 1042-1046 erg s-1 and in the redshift interval 0.001-4. A new method to correct for absorption by considering the probability distribution for the column density conditioned on the hardness ratio is presented. The binned luminosity function and its evolution is determined with a variant of the Page-Carrera method, which is improved to include corrections for absorption and to account for the full probability distribution of photometric redshifts. Parametric models, namely a double power law with luminosity and density evolution (LADE) or luminosity-dependent density evolution (LDDE), are explored using Bayesian inference. We introduce the Watanabe-Akaike information criterion (WAIC) to compare the models and estimate their predictive power. Our data are best described by the LADE model, as hinted by the WAIC indicator. We also explore the recently proposed 15-parameter extended LDDE model and find that this extension is not supported by our data. The strength of our method is that it provides unabsorbed, non-parametric estimates, credible intervals for luminosity function parameters, and a model choice based on predictive power for future data. Based on observations obtained with XMM-Newton, an ESA science mission with instruments and contributions directly funded by ESA member states and NASA.Tables with the samples of the posterior probability distributions are only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/590/A80

Unified Sequence-Based Association Tests Allowing for Multiple Functional Annotations and Meta-analysis of Noncoding Variation in Metabochip Data.

PubMed

He, Zihuai; Xu, Bin; Lee, Seunggeun; Ionita-Laza, Iuliana

2017-09-07

Substantial progress has been made in the functional annotation of genetic variation in the human genome. Integrative analysis that incorporates such functional annotations into sequencing studies can aid the discovery of disease-associated genetic variants, especially those with unknown function and located outside protein-coding regions. Direct incorporation of one functional annotation as weight in existing dispersion and burden tests can suffer substantial loss of power when the functional annotation is not predictive of the risk status of a variant. Here, we have developed unified tests that can utilize multiple functional annotations simultaneously for integrative association analysis with efficient computational techniques. We show that the proposed tests significantly improve power when variant risk status can be predicted by functional annotations. Importantly, when functional annotations are not predictive of risk status, the proposed tests incur only minimal loss of power in relation to existing dispersion and burden tests, and under certain circumstances they can even have improved power by learning a weight that better approximates the underlying disease model in a data-adaptive manner. The tests can be constructed with summary statistics of existing dispersion and burden tests for sequencing data, therefore allowing meta-analysis of multiple studies without sharing individual-level data. We applied the proposed tests to a meta-analysis of noncoding rare variants in Metabochip data on 12,281 individuals from eight studies for lipid traits. By incorporating the Eigen functional score, we detected significant associations between noncoding rare variants in SLC22A3 and low-density lipoprotein and total cholesterol, associations that are missed by standard dispersion and burden tests. Copyright © 2017 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Deployment strategy for battery energy storage system in distribution network based on voltage violation regulation

NASA Astrophysics Data System (ADS)

Wu, H.; Zhou, L.; Xu, T.; Fang, W. L.; He, W. G.; Liu, H. M.

2017-11-01

In order to improve the situation of voltage violation caused by the grid-connection of photovoltaic (PV) system in a distribution network, a bi-level programming model is proposed for battery energy storage system (BESS) deployment. The objective function of inner level programming is to minimize voltage violation, with the power of PV and BESS as the variables. The objective function of outer level programming is to minimize the comprehensive function originated from inner layer programming and all the BESS operating parameters, with the capacity and rated power of BESS as the variables. The differential evolution (DE) algorithm is applied to solve the model. Based on distribution network operation scenarios with photovoltaic generation under multiple alternative output modes, the simulation results of IEEE 33-bus system prove that the deployment strategy of BESS proposed in this paper is well adapted to voltage violation regulation invariable distribution network operation scenarios. It contributes to regulating voltage violation in distribution network, as well as to improve the utilization of PV systems.

Testing relativistic electron acceleration mechanisms

NASA Astrophysics Data System (ADS)

Green, Janet Carol

2002-09-01

This dissertation tests models of relativistic electron acceleration in the earth's outer radiation belt. The models fall into two categories: external and internal. External acceleration models transport and accelerate electrons from a source region in the outer magnetosphere to the inner magnetosphere. Internal acceleration models accelerate a population of electrons already present in the inner magnetosphere. In this dissertation, we test one specific external acceleration mechanism, perform a general test that differentiates between internal and external acceleration models, and test one promising internal acceleration model. We test the models using Polar-HIST data that we transform into electron phase space density (PSD) as a function of adiabatic invariants. We test the ultra low frequency (ULF) wave enhanced radial diffusion external acceleration mechanism by looking for a causal relationship between increased wave power and increased electron PSD at three L* values. One event with increased wave power at two L* values and no subsequent PSD increase does not support the model suggesting that ULF wave power alone is not sufficient to cause an electron response. Excessive loss of electrons and the duration of wave power do not explain the lack of a PSD enhancement at low L*. We differentiate between internal and external acceleration mechanisms by examining the radial profile of electron PSD. We observe PSD profiles that depend on local time. Nightside profiles are highly dependent on the magnetic field model used to calculate PSD as a function of adiabatic invariants and are not reliable. Dayside PSD profiles are more robust and consistent with internal acceleration of electrons. We test one internal acceleration model, the whistler/electromagnetic ion cyclotron wave model, by comparing observed pitch angle distributions to those predicted by the model using a superposed epoch analysis. The observations show pitch angle distributions corresponding to electrons with energy >=4.0 MeV becoming more peaked at 90° during the storm recovery phase. The observation is consistent with but does not confirm the model. Our tests indicate that relativistic electrons are accelerated by an internal source acceleration mechanism but we do not identify a unique mechanism.

Prediction of silicon oxynitride plasma etching using a generalized regression neural network

NASA Astrophysics Data System (ADS)

Kim, Byungwhan; Lee, Byung Teak

2005-08-01

A prediction model of silicon oxynitride (SiON) etching was constructed using a neural network. Model prediction performance was improved by means of genetic algorithm. The etching was conducted in a C2F6 inductively coupled plasma. A 24 full factorial experiment was employed to systematically characterize parameter effects on SiON etching. The process parameters include radio frequency source power, bias power, pressure, and C2F6 flow rate. To test the appropriateness of the trained model, additional 16 experiments were conducted. For comparison, four types of statistical regression models were built. Compared to the best regression model, the optimized neural network model demonstrated an improvement of about 52%. The optimized model was used to infer etch mechanisms as a function of parameters. The pressure effect was noticeably large only as relatively large ion bombardment was maintained in the process chamber. Ion-bombardment-activated polymer deposition played the most significant role in interpreting the complex effect of bias power or C2F6 flow rate. Moreover, [CF2] was expected to be the predominant precursor to polymer deposition.

A Structural Equation Model of the Factors Associated with Influence and Power of IT Departments and Their Relationship to Firm's IT Orientation and Business Performance

ERIC Educational Resources Information Center

Kowshik, Raghu V.

2010-01-01

Although few firms can function without an information technology (IT) department, senior executives often consider IT as secondary. Historically, studies have found IT departments to have low influence and power status compared to other departments. Few, if any, studies have investigated what factors contribute to this subservient position. Three…

Relationship of Sit-to-Stand Lower-Body Power With Functional Fitness Measures Among Older Adults With and Without Sarcopenia.

PubMed

Glenn, Jordan M; Gray, Michelle; Binns, Ashley

When evaluating health in older adults, batteries of tests are typically utilized to assess functional fitness. Unfortunately, physician's visits are time-sensitive, and it may be important to develop faster methods to assess functional fitness that can be utilized in professional or clinical settings. Therefore, the purpose of this investigation was to examine the relationship of sit-to-stand (STS) power generated through the STS task with previously established measures of functional fitness, specifically strength, endurance, speed, agility, and flexibility in older adults with and without sarcopenia. This study consisted of 57 community-dwelling older adults (n = 16 males; n = 41 females). Functional fitness was assessed using the Short Physical Performance Battery (SPPB), Senior Fitness Test, handgrip, gait speed (habitual and maximal), balance, and STS power generated via the Tendo Weightlifting Analyzer. On the basis of data distribution, second-degree polynomial (quadratic) curvilinear models (lines of best fit) were applied for the relationships of 5-time STS time with average and peak power. Zero-order correlations were evaluated between STS power and all other functional fitness measures. Older adults with sarcopenia were also identified (n = 15), and relationships were reevaluated within this subset. STS power (average and peak) was significantly (P ≤ .01) correlated with physical performance measured via previously established assessments. For average power, this was observed during the senior fitness test (6-minute walk [r = 0.39], 8-ft up-and-go [r = -0.46], arm curl [r = 0.46], and chair stand [r = 0.55]), SPPB (5-time STS time [r = -0.63] and 8-ft walk [r = -0.32]), and other independent functional fitness measures (grip strength [r = 0.65] and maximal gait speed [r = -0.31]). Similar results were observed for peak power during the senior fitness test (6-minute walk [r = 0.39], 8-ft up-and-go [r = -0.46], arm curl [r = 0.45], chair stand [r = 0.52], and sit-and-reach [r = -0.27]), SPPB (5-time STS time [r = -0.60] and 8-ft walk [r = -0.33]), and other independent functional fitness measures (grip strength [r = 0.70] and maximal gait speed [r = -0.32]). Within the sarcopenic subset, for average and peak power, respectively, significant relationships were still retained for handgrip strength (r = 0.57 and r = 0.57), 6-minute walk (r = 0.55 and r = 0.61), chair stand (r = 0.76 and r = 0.81), and 5-time STS time (r = -0.76 and r = -0.80) tests. STS power generated via the STS task significantly relates to commonly administered functional fitness measures. These relationships also appear to exist when evaluating these relationships in older adults with sarcopenia. STS power may be utilized as an independent measure of functional fitness that is feasible to incorporate in clinical settings where time and space are often limiting factors.

Power Laws are Disguised Boltzmann Laws

NASA Astrophysics Data System (ADS)

Richmond, Peter; Solomon, Sorin

Using a previously introduced model on generalized Lotka-Volterra dynamics together with some recent results for the solution of generalized Langevin equations, we derive analytically the equilibrium mean field solution for the probability distribution of wealth and show that it has two characteristic regimes. For large values of wealth, it takes the form of a Pareto style power law. For small values of wealth, w<=wm, the distribution function tends sharply to zero. The origin of this law lies in the random multiplicative process built into the model. Whilst such results have been known since the time of Gibrat, the present framework allows for a stable power law in an arbitrary and irregular global dynamics, so long as the market is ``fair'', i.e., there is no net advantage to any particular group or individual. We further show that the dynamics of relative wealth is independent of the specific nature of the agent interactions and exhibits a universal character even though the total wealth may follow an arbitrary and complicated dynamics. In developing the theory, we draw parallels with conventional thermodynamics and derive for the system some new relations for the ``thermodynamics'' associated with the Generalized Lotka-Volterra type of stochastic dynamics. The power law that arises in the distribution function is identified with new additional logarithmic terms in the familiar Boltzmann distribution function for the system. These are a direct consequence of the multiplicative stochastic dynamics and are absent for the usual additive stochastic processes.

Power of the wingbeat: modelling the effects of flapping wings in vertebrate flight.

PubMed

Heerenbrink, M Klein; Johansson, L C; Hedenström, A

2015-05-08

Animal flight performance has been studied using models developed for man-made aircraft. For an aeroplane with fixed wings, the energetic cost as a function of flight speed can be expressed in terms of weight, wing span, wing area and body area, where more details are included in proportionality coefficients. Flying animals flap their wings to produce thrust. Adopting the fixed wing flight model implicitly incorporates the effects of wing flapping in the coefficients. However, in practice, these effects have been ignored. In this paper, the effects of reciprocating wing motion on the coefficients of the fixed wing aerodynamic power model for forward flight are explicitly formulated in terms of thrust requirement, wingbeat frequency and stroke-plane angle, for optimized wingbeat amplitudes. The expressions are obtained by simulating flights over a large parameter range using an optimal vortex wake method combined with a low-level blade element method. The results imply that previously assumed acceptable values for the induced power factor might be strongly underestimated. The results also show the dependence of profile power on wing kinematics. The expressions introduced in this paper can be used to significantly improve animal flight models.

Power of the wingbeat: modelling the effects of flapping wings in vertebrate flight

PubMed Central

Heerenbrink, M. Klein; Johansson, L. C.; Hedenström, A.

2015-01-01

Animal flight performance has been studied using models developed for man-made aircraft. For an aeroplane with fixed wings, the energetic cost as a function of flight speed can be expressed in terms of weight, wing span, wing area and body area, where more details are included in proportionality coefficients. Flying animals flap their wings to produce thrust. Adopting the fixed wing flight model implicitly incorporates the effects of wing flapping in the coefficients. However, in practice, these effects have been ignored. In this paper, the effects of reciprocating wing motion on the coefficients of the fixed wing aerodynamic power model for forward flight are explicitly formulated in terms of thrust requirement, wingbeat frequency and stroke-plane angle, for optimized wingbeat amplitudes. The expressions are obtained by simulating flights over a large parameter range using an optimal vortex wake method combined with a low-level blade element method. The results imply that previously assumed acceptable values for the induced power factor might be strongly underestimated. The results also show the dependence of profile power on wing kinematics. The expressions introduced in this paper can be used to significantly improve animal flight models. PMID:27547098

Shot model parameters for Cygnus X-1 through phase portrait fitting

NASA Technical Reports Server (NTRS)

Lochner, James C.; Swank, J. H.; Szymkowiak, A. E.

1991-01-01

Shot models for systems having about 1/f power density spectrum are developed by utilizing a distribution of shot durations. Parameters of the distribution are determined by fitting the power spectrum either with analytic forms for the spectrum of a shot model with a given shot profile, or with the spectrum derived from numerical realizations of trial shot models. The shot fraction is specified by fitting the phase portrait, which is a plot of intensity at a given time versus intensity at a delayed time and in principle is sensitive to different shot profiles. These techniques have been extensively applied to the X-ray variability of Cygnus X-1, using HEAO 1 A-2 and an Exosat ME observation. The power spectra suggest models having characteristic shot durations lasting from milliseconds to a few seconds, while the phase portrait fits give shot fractions of about 50 percent. Best fits to the portraits are obtained if the amplitude of the shot is a power-law function of the duration of the shot. These fits prefer shots having a symmetric exponential rise and decay. Results are interpreted in terms of a distribution of magnetic flares in the accretion disk.

Broadband changes in the cortical surface potential track activation of functionally diverse neuronal populations

PubMed Central

Miller, Kai J; Honey, Christopher J; Hermes, Dora; Rao, Rajesh PN; denNijs, Marcel; Ojemann, Jeffrey G

2013-01-01

We illustrate a general principal of electrical potential measurements from the surface of the cerebral cortex, by revisiting and reanalyzing experimental work from the visual, language and motor systems. A naïve decomposition technique of electrocorticographic power spectral measurements reveals that broadband spectral changes reliably track task engagement. These broadband changes are shown to be a generic correlate of local cortical function across a variety of brain areas and behavioral tasks. Furthermore, they fit a power-law form that is consistent with simple models of the dendritic integration of asynchronous local population firing. Because broadband spectral changes covary with diverse perceptual and behavioral states on the timescale of 20–50ms, they provide a powerful and widely applicable experimental tool. PMID:24018305

A Method of Dynamic Extended Reactive Power Optimization in Distribution Network Containing Photovoltaic-Storage System

NASA Astrophysics Data System (ADS)

Wang, Wu; Huang, Wei; Zhang, Yongjun

2018-03-01

The grid-integration of Photovoltaic-Storage System brings some undefined factors to the network. In order to make full use of the adjusting ability of Photovoltaic-Storage System (PSS), this paper puts forward a reactive power optimization model, which are used to construct the objective function based on power loss and the device adjusting cost, including energy storage adjusting cost. By using Cataclysmic Genetic Algorithm to solve this optimization problem, and comparing with other optimization method, the result proved that: the method of dynamic extended reactive power optimization this article puts forward, can enhance the effect of reactive power optimization, including reducing power loss and device adjusting cost, meanwhile, it gives consideration to the safety of voltage.

Constructing topological models by symmetrization: A projected entangled pair states study

NASA Astrophysics Data System (ADS)

Fernández-González, Carlos; Mong, Roger S. K.; Landon-Cardinal, Olivier; Pérez-García, David; Schuch, Norbert

2016-10-01

Symmetrization of topologically ordered wave functions is a powerful method for constructing new topological models. Here we study wave functions obtained by symmetrizing quantum double models of a group G in the projected entangled pair states (PEPS) formalism. We show that symmetrization naturally gives rise to a larger symmetry group G ˜ which is always non-Abelian. We prove that by symmetrizing on sufficiently large blocks, one can always construct wave functions in the same phase as the double model of G ˜. In order to understand the effect of symmetrization on smaller patches, we carry out numerical studies for the toric code model, where we find strong evidence that symmetrizing on individual spins gives rise to a critical model which is at the phase transitions of two inequivalent toric codes, obtained by anyon condensation from the double model of G ˜.

Critical Concavity of a Drainage Basin for Steady-State

NASA Astrophysics Data System (ADS)

Byun, Jongmin; Paik, Kyungrock

2015-04-01

Longitudinal profiles of natural streams are known to show concave forms. Saying A as drainage area, channel gradient S can be expressed as the power-law, S≈A-θ (Flint, 1974), which is one of the scale-invariant features of drainage basin. According to literature, θ of most natural streams falls into a narrow range (0.4 < θ < 0.7) (Tucker and Whipple, 2002). It leads to fundamental questions: 'Why does θ falls into such narrow range?' and 'How is this related with other power-law scaling relationships reported in natural drainage basins?' To answer above questions, we analytically derive θ for a steady-state drainage basin following Lane's equilibrium (Lane, 1955) throughout the corridor and named this specific case as the 'critical concavity'. In the derivation, sediment transport capacity is estimated by unit stream power model (Yang, 1976), yielding a power function of upstream area. Stability of channel at a local point occurs when incoming flux equals outgoing flux at the point. Therefore, given the drainage at steady-state where all channel beds are stable, the exponent of the power function should be zero. From this, we can determine the critical concavity. Considering ranges of variables associated in this derivation, critical concavity cannot be resolved as a single definite value, rather a range of critical concavity is suggested. This range well agrees with the widely reported range of θ (0.4 < θ < 0.7) in natural streams. In this theoretical study, inter-relationships between power-laws such as hydraulic geometry (Leopold and Maddock, 1953), dominant discharge-drainage area (Knighton et al., 1999), and concavity, are coupled into the power-law framework of stream power sediment transport model. This allows us to explore close relationships between their power-law exponents: their relative roles and sensitivity. Detailed analysis and implications will be presented. References Flint, J. J., 1974, Stream gradient as a function of order, magnitude, and discharge, Water Resources Research, 10, 969-973. Knighton, A. D., 1999, Downstream variation in stream power, Geomorphology, 29, 293-306. Lane, E. W., 1955, The importance of fluvial morphology in hydraulic engineering, American Society of Civil Engineers, Proceedings, 81, 1-17 Leopold, L. B., Maddock, T., 1953, The hydraulic geometry of stream channels and some physiographic implications, United States Government Printing Office, 1953. Tucker, G. E., Whipple, K. X., 2002, Topographic outcomes predicted by stream erosion models: Sensitivity analysis and intermodel comparison, Journal of Geophysical Research, 107(B9), 2179, doi:10.1029/2001JB000162, 2002. Yang, C. T., 1976, Minimum unit stream power and fluvial hydraulics, Journal of Hydraulics Division, ASCE 102, 919-934.

Oceanographic and meteorological research based on the data products of SEASAT

NASA Technical Reports Server (NTRS)

Pierson, W. J., Jr.

1985-01-01

Reservations were expressed concerning the sum of squares wind recovery algorithm and the power law model function. The SAS sum of squares (SOS) method for recovering winds from backscatter data leads to inconsistent results when V pol and H pol winds are compared. A model function that does not use a power law and that accounts for sea surface temperature is needed and is under study both theoretically and by means of the SASS mode 4 data. Aspects of the determination of winds by means of scatterometry and of the utilization of vector wind data for meteorological forecasts are elaborated. The operational aspect of an intermittent assimilation scheme currently utilized for the specification of the initial value field is considered with focus on quantifying the absolute 12-hour linear displacement error of the movement of low centers.

Universal Expression of Efficiency at Maximum Power: A Quantum-Mechanical Brayton Engine Working with a Single Particle Confined in a Power-Law Trap

NASA Astrophysics Data System (ADS)

Ye, Zhuo-Lin; Li, Wei-Sheng; Lai, Yi-Ming; He, Ji-Zhou; Wang, Jian-Hui

2015-12-01

We propose a quantum-mechanical Brayton engine model that works between two superposed states, employing a single particle confined in an arbitrary power-law trap as the working substance. Applying the superposition principle, we obtain the explicit expressions of the power and efficiency, and find that the efficiency at maximum power is bounded from above by the function: η+ = θ/(θ + 1), with θ being a potential-dependent exponent. Supported by the National Natural Science Foundation of China under Grant Nos. 11505091, 11265010, and 11365015, and the Jiangxi Provincial Natural Science Foundation under Grant No. 20132BAB212009

Quality engineering tools focused on high power LED driver design using boost power stages in switch mode

NASA Astrophysics Data System (ADS)

Ileana, Ioan; Risteiu, Mircea; Marc, Gheorghe

2016-12-01

This paper is a part of our research dedicated to high power LED lamps designing. The boost-up selected technology wants to meet driver producers' tendency in the frame of efficiency and disturbances constrains. In our work we used modeling and simulation tools for implementing scenarios of the driver work when some controlling functions are executed (output voltage/ current versus input voltage and fixed switching frequency, input and output electric power transfer versus switching frequency, transient inductor voltage analysis, and transient out capacitor analysis). Some electrical and thermal stress conditions are also analyzed. Based on these aspects, a high reliable power LED driver has been designed.

Quantitative Characterization of Shear-Induced Platelet Receptor Shedding: Glycoprotein Ibα, Glycoprotein VI, and Glycoprotein IIb/IIIa.

PubMed

Chen, Zengsheng; Koenig, Steven C; Slaughter, Mark S; Griffith, Bartley P; Wu, Zhongjun J

2017-11-07

The structural integrity of platelet receptors is essential for platelets to play the normal hemostatic function. The high non-physiologic shear stress (NPSS) commonly exists in blood-contacting medical devices and has been shown to cause platelet receptor shedding. The loss of platelet receptors may impair the normal hemostatic function of platelets. The aim of this study was to quantify NPSS-induced shedding of three key receptors on the platelet surface. Human blood was subjected to the matrix of well-defined shear stresses and exposure times, generated by using a custom-designed blood-shearing device. The expression of three key platelet receptors, glycoprotein (GP) Ibα, GPVI, and GPIIb/IIIa, in sheared blood was quantified using flow cytometry. The quantitative relationship between the loss of each of the three receptors on the platelet surface and shear condition (shear stress level and exposure time) was explored. It was found that these relationships followed well the power law functional form. The coefficients of the power law models for the shear-induced shedding of these platelet receptors were derived with coefficients of determination (R) of 0.77, 0.73, and 0.78, respectively. The power law models with these coefficients may be potentially used to predict the shear-induced platelet receptor shedding of human blood.

Generation of 1/f noise from a broken-symmetry model for the arbitrary absolute pitch of musical melodies.

PubMed

Grant, Martin; Faghihi, Niloufar

2017-11-01

A model is presented to generate power spectrum noise with intensity proportional to 1/f  as a function of frequency f. The model arises from a broken-symmetry variable, which corresponds to absolute pitch, where fluctuations occur in an attempt to restore that symmetry, influenced by interactions in the creation of musical melodies.

Learning in engineered multi-agent systems

NASA Astrophysics Data System (ADS)

Menon, Anup

Consider the problem of maximizing the total power produced by a wind farm. Due to aerodynamic interactions between wind turbines, each turbine maximizing its individual power---as is the case in present-day wind farms---does not lead to optimal farm-level power capture. Further, there are no good models to capture the said aerodynamic interactions, rendering model based optimization techniques ineffective. Thus, model-free distributed algorithms are needed that help turbines adapt their power production on-line so as to maximize farm-level power capture. Motivated by such problems, the main focus of this dissertation is a distributed model-free optimization problem in the context of multi-agent systems. The set-up comprises of a fixed number of agents, each of which can pick an action and observe the value of its individual utility function. An individual's utility function may depend on the collective action taken by all agents. The exact functional form (or model) of the agent utility functions, however, are unknown; an agent can only measure the numeric value of its utility. The objective of the multi-agent system is to optimize the welfare function (i.e. sum of the individual utility functions). Such a collaborative task requires communications between agents and we allow for the possibility of such inter-agent communications. We also pay attention to the role played by the pattern of such information exchange on certain aspects of performance. We develop two algorithms to solve this problem. The first one, engineered Interactive Trial and Error Learning (eITEL) algorithm, is based on a line of work in the Learning in Games literature and applies when agent actions are drawn from finite sets. While in a model-free setting, we introduce a novel qualitative graph-theoretic framework to encode known directed interactions of the form "which agents' action affect which others' payoff" (interaction graph). We encode explicit inter-agent communications in a directed graph (communication graph) and, under certain conditions, prove convergence of agent joint action (under eITEL) to the welfare optimizing set. The main condition requires that the union of interaction and communication graphs be strongly connected; thus the algorithm combines an implicit form of communication (via interactions through utility functions) with explicit inter-agent communications to achieve the given collaborative goal. This work has kinship with certain evolutionary computation techniques such as Simulated Annealing; the algorithm steps are carefully designed such that it describes an ergodic Markov chain with a stationary distribution that has support over states where agent joint actions optimize the welfare function. The main analysis tool is perturbed Markov chains and results of broader interest regarding these are derived as well. The other algorithm, Collaborative Extremum Seeking (CES), uses techniques from extremum seeking control to solve the problem when agent actions are drawn from the set of real numbers. In this case, under the assumption of existence of a local minimizer for the welfare function and a connected undirected communication graph between agents, a result regarding convergence of joint action to a small neighborhood of a local optimizer of the welfare function is proved. Since extremum seeking control uses a simultaneous gradient estimation-descent scheme, gradient information available in the continuous action space formulation is exploited by the CES algorithm to yield improved convergence speeds. The effectiveness of this algorithm for the wind farm power maximization problem is evaluated via simulations. Lastly, we turn to a different question regarding role of the information exchange pattern on performance of distributed control systems by means of a case study for the vehicle platooning problem. In the vehicle platoon control problem, the objective is to design distributed control laws for individual vehicles in a platoon (or a road-train) that regulate inter-vehicle distances at a specified safe value while the entire platoon follows a leader-vehicle. While most of the literature on the problem deals with some inadequacy in control performance when the information exchange is of the nearest neighbor-type, we consider an arbitrary graph serving as information exchange pattern and derive a relationship between how a certain indicator of control performance is related to the information pattern. Such analysis helps in understanding qualitative features of the `right' information pattern for this problem.

Reconstruction of halo power spectrum from redshift-space galaxy distribution: cylinder-grouping method and halo exclusion effect

NASA Astrophysics Data System (ADS)

Okumura, Teppei; Takada, Masahiro; More, Surhud; Masaki, Shogo

2017-07-01

The peculiar velocity field measured by redshift-space distortions (RSD) in galaxy surveys provides a unique probe of the growth of large-scale structure. However, systematic effects arise when including satellite galaxies in the clustering analysis. Since satellite galaxies tend to reside in massive haloes with a greater halo bias, the inclusion boosts the clustering power. In addition, virial motions of the satellite galaxies cause a significant suppression of the clustering power due to non-linear RSD effects. We develop a novel method to recover the redshift-space power spectrum of haloes from the observed galaxy distribution by minimizing the contamination of satellite galaxies. The cylinder-grouping method (CGM) we study effectively excludes satellite galaxies from a galaxy sample. However, we find that this technique produces apparent anisotropies in the reconstructed halo distribution over all the scales which mimic RSD. On small scales, the apparent anisotropic clustering is caused by exclusion of haloes within the anisotropic cylinder used by the CGM. On large scales, the misidentification of different haloes in the large-scale structures, aligned along the line of sight, into the same CGM group causes the apparent anisotropic clustering via their cross-correlation with the CGM haloes. We construct an empirical model for the CGM halo power spectrum, which includes correction terms derived using the CGM window function at small scales as well as the linear matter power spectrum multiplied by a simple anisotropic function at large scales. We apply this model to a mock galaxy catalogue at z = 0.5, designed to resemble Sloan Digital Sky Survey-III Baryon Oscillation Spectroscopic Survey (BOSS) CMASS galaxies, and find that our model can predict both the monopole and quadrupole power spectra of the host haloes up to k < 0.5 {{h Mpc^{-1}}} to within 5 per cent.

A simple method for assessment of muscle force, velocity, and power producing capacities from functional movement tasks.

PubMed

Zivkovic, Milena Z; Djuric, Sasa; Cuk, Ivan; Suzovic, Dejan; Jaric, Slobodan

2017-07-01

A range of force (F) and velocity (V) data obtained from functional movement tasks (e.g., running, jumping, throwing, lifting, cycling) performed under variety of external loads have typically revealed strong and approximately linear F-V relationships. The regression model parameters reveal the maximum F (F-intercept), V (V-intercept), and power (P) producing capacities of the tested muscles. The aim of the present study was to evaluate the level of agreement between the routinely used "multiple-load model" and a simple "two-load model" based on direct assessment of the F-V relationship from only 2 external loads applied. Twelve participants were tested on the maximum performance vertical jumps, cycling, bench press throws, and bench pull performed against a variety of different loads. All 4 tested tasks revealed both exceptionally strong relationships between the parameters of the 2 models (median R = 0.98) and a lack of meaningful differences between their magnitudes (fixed bias below 3.4%). Therefore, addition of another load to the standard tests of various functional tasks typically conducted under a single set of mechanical conditions could allow for the assessment of the muscle mechanical properties such as the muscle F, V, and P producing capacities.

Temporal dependence of transient dark counts in an avalanche photodiode: A solution for power-law behavior of afterpulsing

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

Akiba, M., E-mail: akiba@nict.go.jp; Tsujino, K.

This paper offers a theoretical explanation of the temperature and temporal dependencies of transient dark count rates (DCRs) measured for a linear-mode silicon avalanche photodiode (APD) and the dependencies of afterpulsing that were measured in Geiger-mode Si and InGaAs/InP APDs. The temporal dependencies exhibit power-law behavior, at least to some extent. For the transient DCR, the value of the DCR for a given time period increases with decreases in temperature, while the power-law behavior remains unchanged. The transient DCR is attributed to electron emissions from traps in the multiplication layer of the APD with a high electric field, and itsmore » temporal dependence is explained by a continuous change in the electron emission rate as a function of the electric field strength. The electron emission rate is calculated using a quantum model for phonon-assisted tunnel emission. We applied the theory to the temporal dependence of afterpulsing that was measured for Si and InGaAs/InP APDs. The power-law temporal dependence is attributed to the power-law function of the electron emission rate from the traps as a function of their position across the p–n junction of the APD. Deviations from the power-law temporal dependence can be derived from the upper and lower limits of the electric field strength.« less

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

Okumura, Teppei; Hand, Nick; Seljak, Uros

Theoretical modeling of the redshift-space power spectrum of galaxies is crucially important to correctly extract cosmological information from galaxy redshift surveys. The task is complicated by the nonlinear biasing and redshift space distortion (RSD) effects, which change with halo mass, and by the wide distribution of halo masses and their occupations by galaxies. One of the main modeling challenges is the existence of satellite galaxies that have both radial distribution inside the halos and large virial velocities inside halos, a phenomenon known as the Finger-of-God (FoG) effect. We present a model for the redshift-space power spectrum of galaxies in whichmore » we decompose a given galaxy sample into central and satellite galaxies and relate different contributions to the power spectrum to 1-halo and 2-halo terms in a halo model. Our primary goal is to ensure that any parameters that we introduce have physically meaningful values, and are not just fitting parameters. For the lowest order 2-halo terms we use the previously developed RSD modeling of halos in the context of distribution function and perturbation theory approach. This term needs to be multiplied by the effect of radial distances and velocities of satellites inside the halo. To this one needs to add the 1-halo terms, which are nonperturbative. We show that the real space 1-halo terms can be modeled as almost constant, with the finite extent of the satellites inside the halo inducing a small k 2R 2 term over the range of scales of interest, where R is related to the size of the halo given by its halo mass. Furthermore, we adopt a similar model for FoG in redshift space, ensuring that FoG velocity dispersion is related to the halo mass. For FoG k 2 type expansions do not work over the range of scales of interest and FoG resummation must be used instead. We test several simple damping functions to model the velocity dispersion FoG effect. Applying the formalism to mock galaxies modeled after the “CMASS” sample of the BOSS survey, we find that our predictions for the redshift-space power spectra are accurate up to k ≃ 0.4 h Mpc –1 within 1% if the halo power spectrum is measured using N-body simulations and within 3% if it is modeled using perturbation theory.« less

Effects of variability of X-ray binaries on the X-ray luminosity functions of Milky Way

NASA Astrophysics Data System (ADS)

Islam, Nazma; Paul, Biswajit

2016-08-01

The X-ray luminosity functions of galaxies have become a useful tool for population studies of X-ray binaries in them. The availability of long term light-curves of X-ray binaries with the All Sky X-ray Monitors opens up the possibility of constructing X-ray luminosity functions, by also including the intensity variation effects of the galactic X-ray binaries. We have constructed multiple realizations of the X-ray luminosity functions (XLFs) of Milky Way, using the long term light-curves of sources obtained in the 2-10 keV energy band with the RXTE-ASM. The observed spread seen in the value of slope of both HMXB and LMXB XLFs are due to inclusion of variable luminosities of X-ray binaries in construction of these XLFs as well as finite sample effects. XLFs constructed for galactic HMXBs in the luminosity range 1036-1039 erg/sec is described by a power-law model with a mean power-law index of -0.48 and a spread due to variability of HMXBs as 0.19. XLFs constructed for galactic LMXBs in the luminosity range 1036-1039 erg/sec has a shape of cut-off power-law with mean power-law index of -0.31 and a spread due to variability of LMXBs as 0.07.

Modelling and control synthesis of a micro-combined heat and power interface for a concentrating solar power system in off-grid rural power applications

NASA Astrophysics Data System (ADS)

Prinsloo, Gerro; Dobson, Robert; Brent, Alan; Mammoli, Andrea

2016-05-01

Concentrating solar power co-generation systems have been identified as potential stand-alone solar energy supply solutions in remote rural energy applications. This study describes the modelling and synthesis of a combined heat and power Stirling CSP system in order to evaluate its potential performance in small off-grid rural village applications in Africa. This Stirling micro-Combined Heat and Power (micro-CHP) system has a 1 kW electric capacity, with 3 kW of thermal generation capacity which is produced as waste heat recovered from the solar power generation process. As part of the development of an intelligent microgrid control and distribution solution, the Trinum micro-CHP system and other co-generation systems are systematically being modelled on the TRNSYS simulation platform. This paper describes the modelling and simulation of the Trinum micro-CHP configuration on TRNSYS as part of the process to develop the control automation solution for the smart rural microgrid in which the Trinum will serve as a solar powerpack. The results present simulated performance outputs for the Trinum micro-CHP system for a number of remote rural locations in Africa computed from real-time TRNSYS solar irradiation and weather data (yearly, monthly, daily) for the relevant locations. The focus of this paper is on the parametric modelling of the Trinum Stirling micro-CHP system, with specific reference to this system as a TRNSYS functional block in the microgrid simulation. The model is used to forecast the solar energy harvesting potential of the Trinum micro-CHP unit at a number of remote rural sites in Africa.

On the mass function of stars growing in a flocculent medium

NASA Astrophysics Data System (ADS)

Maschberger, Th.

2013-12-01

Stars form in regions of very inhomogeneous densities and may have chaotic orbital motions. This leads to a time variation of the accretion rate, which will spread the masses over some mass range. We investigate the mass distribution functions that arise from fluctuating accretion rates in non-linear accretion, ṁ ∝ mα. The distribution functions evolve in time and develop a power-law tail attached to a lognormal body, like in numerical simulations of star formation. Small fluctuations may be modelled by a Gaussian and develop a power-law tail ∝ m-α at the high-mass side for α > 1 and at the low-mass side for α < 1. Large fluctuations require that their distribution is strictly positive, for example, lognormal. For positive fluctuations the mass distribution function develops the power-law tail always at the high-mass hand side, independent of α larger or smaller than unity. Furthermore, we discuss Bondi-Hoyle accretion in a supersonically turbulent medium, the range of parameters for which non-linear stochastic growth could shape the stellar initial mass function, as well as the effects of a distribution of initial masses and growth times.

Quantifying uncertainty in partially specified biological models: how can optimal control theory help us?

PubMed

Adamson, M W; Morozov, A Y; Kuzenkov, O A

2016-09-01

Mathematical models in biology are highly simplified representations of a complex underlying reality and there is always a high degree of uncertainty with regards to model function specification. This uncertainty becomes critical for models in which the use of different functions fitting the same dataset can yield substantially different predictions-a property known as structural sensitivity. Thus, even if the model is purely deterministic, then the uncertainty in the model functions carries through into uncertainty in model predictions, and new frameworks are required to tackle this fundamental problem. Here, we consider a framework that uses partially specified models in which some functions are not represented by a specific form. The main idea is to project infinite dimensional function space into a low-dimensional space taking into account biological constraints. The key question of how to carry out this projection has so far remained a serious mathematical challenge and hindered the use of partially specified models. Here, we propose and demonstrate a potentially powerful technique to perform such a projection by using optimal control theory to construct functions with the specified global properties. This approach opens up the prospect of a flexible and easy to use method to fulfil uncertainty analysis of biological models.

Bulk heating effects as tests for collapse models

NASA Astrophysics Data System (ADS)

Adler, Stephen L.; Vinante, Andrea

2018-05-01

We discuss limits on the noise strength parameter in mass-proportional-coupled wave-function collapse models implied by bulk heating effects and examine the role of the noise power spectrum in comparing experiments of different types. This comparison utilizes a calculation of the rate of heating through phonon excitation implied by a general noise power spectrum λ (ω ) . We find that, in the standard heating formula, the reduction rate λ is replaced by λeff=2/3 π3 /2 ∫d3w e-w⃗2w⃗2λ ( ωL(w ⃗/rc) ) , with ωL(q ⃗) being the longitudinal acoustic-phonon frequency as a function of wave number q ⃗, and with rC being the noise correlation length. Hence if the noise power spectrum is cut off below ωL(| q ⃗|˜rc-1) , the bulk heating rate is sharply reduced, allowing compatibility with current experimental results. We suggest possible new bulk heating experiments that can be performed subject to limits placed by natural heating from radioactivity and cosmic rays. The proposed experiments exploit the vanishing of thermal transport in the low-temperature limit.

Seismic isolation device having charging function by a transducer

NASA Astrophysics Data System (ADS)

Yamaguchi, Takashi; Miura, Nanako; Takahashi, Masaki

2016-04-01

In late years, many base isolated structures are planned as the seismic design, because they suppress vibration response significantly against large earthquake. To achieve greater safety, semi-active or active vibration control system is installed in the structures as earthquake countermeasures. Semi-active and active vibration control systems are more effective than passive vibration control system to large earthquake in terms of vibration reduction. However semi-active and active vibration control system cannot operate as required when external power supply is cut off. To solve the problem of energy consumption, we propose a self-powered active seismic isolation floor which achieve active control system using regenerated vibration energy. This device doesn't require external energy to produce control force. The purpose of this study is to propose the seismic isolation device having charging function and to optimize the control system and passive elements such as spring coefficients and damping coefficients using genetic algorithm. As a result, optimized model shows better performance in terms of vibration reduction and electric power regeneration than the previous model. At the end of this paper, the experimental specimen of the proposed isolation device is shown.

A COSMIC COINCIDENCE: THE POWER-LAW GALAXY CORRELATION FUNCTION

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

Watson, Douglas F.; Berlind, Andreas A.; Zentner, Andrew R.

We model the evolution of galaxy clustering through cosmic time to investigate the nature of the power-law shape of {xi}(r), the galaxy two-point correlation function. While {xi}(r) at large scales is set by primordial fluctuations, departures from a power law are governed by galaxy pair counts at small scales, subject to nonlinear dynamics. We assume that galaxies reside within dark matter halos and subhalos. Therefore, the shape of the correlation function at small scales depends on the amount of halo substructure. We use a semi-analytic substructure evolution model to study subhalo populations within host halos. We find that tidal massmore » loss and, to a lesser extent, dynamical friction dramatically deplete the number of subhalos within larger host halos over time, resulting in a {approx}90% reduction by z = 0 compared to the number of distinct mergers that occur during the assembly of a host halo. We show that these nonlinear processes resulting in this depletion are essential for achieving a power law {xi}(r). We investigate how the shape of {xi}(r) depends on subhalo mass (or luminosity) and redshift. We find that {xi}(r) breaks from a power law at high masses, implying that only galaxies of luminosities {approx}< L{sub *} should exhibit power-law clustering. Moreover, we demonstrate that {xi}(r) evolves from being far from a power law at high redshift, toward a near power-law shape at z = 0. We argue that {xi}(r) will once again evolve away from a power law in the future. This is in large part caused by the evolving competition between the accretion and destruction rates of subhalos over time, which happen to strike just the right balance at z {approx} 0. We then investigate the conditions required for {xi}(r) to be a power law in a general context. We use the halo model, along with simple parameterizations of the halo occupation distribution, to probe galaxy occupation at various masses and redshifts. We show that the key ingredients determining the shape of {xi}(r) are the fraction of galaxies that are satellites, the relative difference in mass between the halos of isolated galaxies and halos that contain a single satellite on average, and the rareness of halos that host galaxies. These pieces are intertwined and we find no simple, universal rule for which a power law {xi}(r) will occur. However, we do show that the physics responsible for setting the galaxy content of halos do not care about the conditions needed to achieve a power law {xi}(r) and that these conditions are met only in a narrow mass and redshift range. We conclude that the power-law nature of {xi}(r) for L{sub *} and fainter galaxy samples at low redshift is a cosmic coincidence.« less

Mesoscopic fluctuations and intermittency in aging dynamics

NASA Astrophysics Data System (ADS)

Sibani, P.

2006-01-01

Mesoscopic aging systems are characterized by large intermittent noise fluctuations. In a record dynamics scenario (Sibani P. and Dall J., Europhys. Lett., 64 (2003) 8) these events, quakes, are treated as a Poisson process with average αln (1 + t/tw), where t is the observation time, tw is the age and α is a parameter. Assuming for simplicity that quakes constitute the only source of de-correlation, we present a model for the probability density function (PDF) of the configuration autocorrelation function. Beside α, the model has the average quake size 1/q as a parameter. The model autocorrelation PDF has a Gumbel-like shape, which approaches a Gaussian for large t/tw and becomes sharply peaked in the thermodynamic limit. Its average and variance, which are given analytically, depend on t/tw as a power law and a power law with a logarithmic correction, respectively. Most predictions are in good agreement with data from the literature and with the simulations of the Edwards-Anderson spin-glass carried out as a test.

Design and testing of a regenerative magnetorheological actuator for assistive knee braces

NASA Astrophysics Data System (ADS)

Ma, Hao; Chen, Bing; Qin, Ling; Liao, Wei-Hsin

2017-03-01

In this paper, a multifunctional magneto-rheological actuator with power regeneration capability, named regenerative magnetorheological actuator (RMRA), is designed for gait assistance in the knee joint. RMRA has motor and magnetorheological (MR) brake parts working in parallel that can harvest energy through regenerative braking. This novel design provides multiple functions with good energy efficiency. The configuration and basic design of the RMRA are first introduced. Then geometrical optimization of the MR brake is conducted based on a parameterized model, and multiple factors are considered in the design objectives: braking torque, weight, and power consumption. After the optimal design is obtained, an RMRA prototype is fabricated and associated driver circuits are designed. Finally, multiple functions of the RMRA, especially three different braking modes, are modeled and tested. Experimental results of RMRA output performances in all working modes match the modeling and simulation. Assistive knee braces with the developed RMRA are promising for future applications in gait assistance and rehabilitation.

Modeling of Yb3+/Er3+-codoped microring resonators

NASA Astrophysics Data System (ADS)

Vallés, Juan A.; Gălătuş, Ramona

2015-03-01

The performance of a highly Yb3+/Er3+-codoped phosphate glass add-drop microring resonator is numerically analyzed. The model assumes resonant behaviour of both pump and signal powers and the dependences of pump intensity build-up inside the microring resonator and of the signal transfer functions to the device through and drop ports are evaluated. Detailed equations for the evolution of the rare-earth ions levels population densities and the propagation of the optical powers inside the microring resonator are included in the model. Moreover, due to the high dopant concentrations considered, the microscopic statistical formalism based on the statistical average of the excitation probability of the Er3+ ion in a microscopic level has been used to describe energy-transfer inter-atomic mechanisms. Realistic parameters and working conditions are used for the calculations. Requirements to achieve amplification and laser oscillation within these devices are obtainable as a function of rare earth ions concentration and coupling losses.

The Large Local Hole in the Galaxy Distribution: The 2MASS Galaxy Angular Power Spectrum

NASA Astrophysics Data System (ADS)

Frith, W. J.; Outram, P. J.; Shanks, T.

2005-06-01

We present new evidence for a large deficiency in the local galaxy distribution situated in the ˜4000 deg2 APM survey area. We use models guided by the 2dF Galaxy Redshift Survey (2dFGRS) n(z) as a probe of the underlying large-scale structure. We first check the usefulness of this technique by comparing the 2dFGRS n(z) model prediction with the K-band and B-band number counts extracted from the 2MASS and 2dFGRS parent catalogues over the 2dFGRS Northern and Southern declination strips, before turning to a comparison with the APM counts. We find that the APM counts in both the B and K-bands indicate a deficiency in the local galaxy distribution of ˜30% to z ≈ 0.1 over the entire APM survey area. We examine the implied significance of such a large local hole, considering several possible forms for the real-space correlation function. We find that such a deficiency in the APM survey area indicates an excess of power at large scales over what is expected from the correlation function observed in 2dFGRS correlation function or predicted from ΛCDM Hubble Volume mock catalogues. In order to check further the clustering at large scales in the 2MASS data, we have calculated the angular power spectrum for 2MASS galaxies. Although in the linear regime (l<30), ΛCDM models can give a good fit to the 2MASS angular power spectrum, over a wider range (l<100) the power spectrum from Hubble Volume mock catalogues suggests that scale-dependent bias may be needed for ΛCDM to fit. However, the modest increase in large-scale power observed in the 2MASS angular power spectrum is still not enough to explain the local hole. If the APM survey area really is 25% deficient in galaxies out to z≈0.1, explanations for the disagreement with observed galaxy clustering statistics include the possibilities that the galaxy clustering is non-Gaussian on large scales or that the 2MASS volume is still too small to represent a `fair sample' of the Universe. Extending the 2dFGRS redshift survey over the whole APM area would resolve many of the remaining questions about the existence and interpretation of this local hole.

From Bacteria to Whales: Using Functional Size Spectra to Model Marine Ecosystems.

PubMed

Blanchard, Julia L; Heneghan, Ryan F; Everett, Jason D; Trebilco, Rowan; Richardson, Anthony J

2017-03-01

Size-based ecosystem modeling is emerging as a powerful way to assess ecosystem-level impacts of human- and environment-driven changes from individual-level processes. These models have evolved as mechanistic explanations for observed regular patterns of abundance across the marine size spectrum hypothesized to hold from bacteria to whales. Fifty years since the first size spectrum measurements, we ask how far have we come? Although recent modeling studies capture an impressive range of sizes, complexity, and real-world applications, ecosystem coverage is still only partial. We describe how this can be overcome by unifying functional traits with size spectra (which we call functional size spectra) and highlight the key knowledge gaps that need to be filled to model ecosystems from bacteria to whales. Copyright © 2017 Elsevier Ltd. All rights reserved.

Development of an Atmospheric Dispersion Model for Heavier-Than-Air Gas Mixtures. Volume 3. DEGADIS User’s Manual.

DTIC Science & Technology

1985-05-01

interpolates between a pair of points based on a list of supplied values (C-2). () ALP estimates the ambient wind profile power a by minimizing the integral...Typical Values of Surface Roughness 7 1.2. Representative Konin-Obukhov Lengths arnd Power Law Exponents for Different Atmospheric Stabilities 8 IV.1...a constant in power law wind profile 0 constant in a correlation r gama function 𔄁 ratio of (p - pa)/Cc 6 constant in a correlation y AMonin-Obukhov

Electron Heating and Quasiparticle Tunnelling in Superconducting Charge Qubits

NASA Technical Reports Server (NTRS)

Shaw, M. D.; Bueno, J.; Delsing, P.; Echternach, P. M.

2008-01-01

We have directly measured non-equilibrium quasiparticle tunnelling in the time domain as a function of temperature and RF carrier power for a pair of charge qubits based on the single Cooper-pair box, where the readout is performed with a multiplexed quantum capacitance technique. We have extracted an effective electron temperature for each applied RF power, using the data taken at the lowest power as a reference curve. This data has been fit to a standard T? electron heating model, with a reasonable correspondence with established material parameters.

Two Regimes of Turbulent Fragmentation and the Stellar Initial Mass Function from Primordial to Present-Day Star Formation

NASA Astrophysics Data System (ADS)

Padoan, Paolo; Nordlund, Åke; Kritsuk, Alexei G.; Norman, Michael L.; Li, Pak Shing

2007-06-01

The Padoan and Nordlund model of the stellar initial mass function (IMF) is derived from low-order statistics of supersonic turbulence, neglecting gravity (e.g., gravitational fragmentation, accretion, and merging). In this work, the predictions of that model are tested using the largest numerical experiments of supersonic hydrodynamic (HD) and magnetohydrodynamic (MHD) turbulence to date (~10003 computational zones) and three different codes (Enzo, Zeus, and the Stagger code). The model predicts a power-law distribution for large masses, related to the turbulence-energy power-spectrum slope and the shock-jump conditions. This power-law mass distribution is confirmed by the numerical experiments. The model also predicts a sharp difference between the HD and MHD regimes, which is recovered in the experiments as well, implying that the magnetic field, even below energy equipartition on the large scale, is a crucial component of the process of turbulent fragmentation. These results suggest that the stellar IMF of primordial stars may differ from that in later epochs of star formation, due to differences in both gas temperature and magnetic field strength. In particular, we find that the IMF of primordial stars born in turbulent clouds may be narrowly peaked around a mass of order 10 Msolar, as long as the column density of such clouds is not much in excess of 1022 cm-2.

Anthropogenic and technogenic factors of operational risk at hazardous industrial objects of fuel-power complex

NASA Astrophysics Data System (ADS)

Magid, S. I.; Arkhipova, E. N.; Kulichikhin, V. V.; Zagretdinov, I. Sh.

2016-12-01

Technogenic and anthropogenic accidence at hazardous industrial objects (HIO) in the Russian Federation has been considered. The accidence level at HIO, including power plants and network enterprises, is determined by anthropogenic reasons, so-called "human factor", in 70% of all cases. The analysis of incidents caused by personnel has shown that errors occur most often during accidental situations, launches, holdups, routine switches, and other effects on equipment controls. It has been demonstrated that skills needed to perform type and routine switches can be learned, to certain limits, on real operating equipment, while combating emergency and accidental situations can be learned only with the help of modern training simulators developed based on information technologies. Problems arising during the following processes have been considered: development of mathematical and software support of modern training equipment associated, in one way or another, with adequate power-generating object modeling in accordance with human operator specifics; modeling and/or simulation of the corresponding control and management systems; organization of the education system (functional supply of the instructor, education and methodological resources (EMR)); organization of the program-technical, scalable and adaptable, platform for modeling of the main and secondary functions of the training simulator. It has been concluded that the systemic approach principle on the necessity and sufficiency in the applied methodology allows to reproduce all technological characteristics of the equipment, its topological completeness, as well as to achieve the acceptable counting rate. The initial "rough" models of processes in the equipment are based on the normative techniques and equation coefficients taken from the normative materials as well. Then, the synthesis of "fine" models has been carried out following the global practice in modeling and training simulator building, i.e., verification of "rough" models based on experimental data available to the developer. Finally, the last stage of modeling is adaptation (validation) of "fine" models to the prototype object using experimental data on the power-generating object and tests of these models with operating and maintaining personnel. These stages determine adequacy of the used mathematical model for a particular training simulator and, thus, its compliance with such modern scientific criteria as objectivity and experimental verifiability.

Machine Learning Based Multi-Physical-Model Blending for Enhancing Renewable Energy Forecast -- Improvement via Situation Dependent Error Correction

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

Lu, Siyuan; Hwang, Youngdeok; Khabibrakhmanov, Ildar

With increasing penetration of solar and wind energy to the total energy supply mix, the pressing need for accurate energy forecasting has become well-recognized. Here we report the development of a machine-learning based model blending approach for statistically combining multiple meteorological models for improving the accuracy of solar/wind power forecast. Importantly, we demonstrate that in addition to parameters to be predicted (such as solar irradiance and power), including additional atmospheric state parameters which collectively define weather situations as machine learning input provides further enhanced accuracy for the blended result. Functional analysis of variance shows that the error of individual modelmore » has substantial dependence on the weather situation. The machine-learning approach effectively reduces such situation dependent error thus produces more accurate results compared to conventional multi-model ensemble approaches based on simplistic equally or unequally weighted model averaging. Validation over an extended period of time results show over 30% improvement in solar irradiance/power forecast accuracy compared to forecasts based on the best individual model.« less

Modeling the microstructure of surface by applying BRDF function

NASA Astrophysics Data System (ADS)

Plachta, Kamil

2017-06-01

The paper presents the modeling of surface microstructure using a bidirectional reflectance distribution function. This function contains full information about the reflectance properties of the flat surfaces - it is possible to determine the share of the specular, directional and diffuse components in the reflected luminous stream. The software is based on the authorial algorithm that uses selected elements of this function models, which allows to determine the share of each component. Basing on obtained data, the surface microstructure of each material can be modeled, which allows to determine the properties of this materials. The concentrator directs the reflected solar radiation onto the photovoltaic surface, increasing, at the same time, the value of the incident luminous stream. The paper presents an analysis of selected materials that can be used to construct the solar concentrator system. The use of concentrator increases the power output of the photovoltaic system by up to 17% as compared to the standard solution.

Extended operating range of the 30-cm ion thruster with simplified power processor requirements

NASA Technical Reports Server (NTRS)

Rawlin, V. K.

1981-01-01

A two grid 30 cm diameter mercury ion thruster was operated with only six power supplies over the baseline J series thruster power throttle range with negligible impact on thruster performance. An analysis of the functional model power processor showed that the component mass and parts count could be reduced considerably and the electrical efficiency increased slightly by only replacing power supplies with relays. The input power, output thrust, and specific impulse of the thruster were then extended, still using six supplies, from 2660 watts, 0.13 newtons, and 2980 seconds to 9130 watts, 0.37 newtons, and 3820 seconds, respectively. Increases in thrust and power density enable reductions in the number of thrusters and power processors required for most missions. Preliminary assessments of the impact of thruster operation at increased thrust and power density on the discharge characteristics, performance, and lifetime of the thruster were also made.

Transportation and dynamic networks: Models, theory, and applications to supply chains, electric power, and financial networks

NASA Astrophysics Data System (ADS)

Liu, Zugang

Network systems, including transportation and logistic systems, electric power generation and distribution networks as well as financial networks, provide the critical infrastructure for the functioning of our societies and economies. The understanding of the dynamic behavior of such systems is also crucial to national security and prosperity. The identification of new connections between distinct network systems is the inspiration for the research in this dissertation. In particular, I answer two questions raised by Beckmann, McGuire, and Winsten (1956) and Copeland (1952) over half a century ago, which are, respectively, how are electric power flows related to transportation flows and does money flow like water or electricity? In addition, in this dissertation, I achieve the following: (1) I establish the relationships between transportation networks and three other classes of complex network systems: supply chain networks, electric power generation and transmission networks, and financial networks with intermediation. The establishment of such connections provides novel theoretical insights as well as new pricing mechanisms, and efficient computational methods. (2) I develop new modeling frameworks based on evolutionary variational inequality theory that capture the dynamics of such network systems in terms of the time-varying flows and incurred costs, prices, and, where applicable, profits. This dissertation studies the dynamics of such network systems by addressing both internal competition and/or cooperation, and external changes, such as varying costs and demands. (3) I focus, in depth, on electric power supply chains. By exploiting the relationships between transportation networks and electric power supply chains, I develop a large-scale network model that integrates electric power supply chains and fuel supply markets. The model captures both the economic transactions as well as the physical transmission constraints. The model is then applied to the New England electric power supply chain consisting of 6 states, 5 fuel types, 82 power generators, with a total of 573 generating units, and 10 demand markets. The empirical case study demonstrates that the regional electricity prices simulated by the model match very well the actual electricity prices in New England. I also utilize the model to study interactions between electric power supply chains and energy fuel markets.

Qualitative Variation in Constructive Alignment in Curriculum Design

ERIC Educational Resources Information Center

Trigwell, Keith; Prosser, Michael

2014-01-01

Constructive alignment has emerged as a powerful curriculum design idea, but little is known of the extent to which the effectiveness of this idea is a function of qualitative variation. This article introduces a model of qualitative variation in constructive alignment, and uses the results from known alignment studies to test the model. The…

Presidential and bureaucratic policy-making: The case of Mexican oil policy

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

de la Luz Valverde Rocha, M.

1991-01-01

A close examination of the literature yielded two different, but vague models of Mexican policy-making: (1) closed presidential policy-making and (2) open presidential policy-making. These two models are tested by identifying the regime's policy-making structures and by explaining the manner in which they operated to produce oil policy in two presidential administrations. To attain these goals, the oil policy-making process was divided into several stages. The policy roles played by different actors in the various stages of policy-making were analyzed. The process they engaged in to produce oil policy was also examined. The findings lend strong support to the openmore » presidential policy-making model. The most salient features of this model are: (1) the president and different members of the Mexican federal bureaucracy share policy-making functions, power, and influence; (2) policymakers engage in a political process of persuasion, coalition building, information functions, power, and influence; and (3) policymakers engage in these and other political techniques to produce government decisions and actions.« less

Anode power in a quasi-steady MPD thruster. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Saber, A. J.

1974-01-01

Local anode heat flux in a quasi-steady MPD thruster is measured by thermocouples attached to the inside surface of a shell anode. Over a range of arc currents J from 5.5 to 44 kiloamperes and argon propellant mass flows m from 1 to 48 g/sec, with the ratio J2/m held constant, the fraction of arc power deposited in the anode is found to decrease with increasing arc power. Specifically, this anode power fraction decreases from 50% at 200 kW arc power, to 10% at 20 MW. In an effort to account for this functional behavior, the current density, plasma potential, and electron temperature in the plasma adjacent to the anode are measured with probes, and the results are used in a theoretical anode heat flux model. The model asserts that energy exchange between electrons and heavy particles in the plasma near the anode occur over distances greater than the anode sheath thickness.

Analysis of temporal transcription expression profiles reveal links between protein function and developmental stages of Drosophila melanogaster.

PubMed

Wan, Cen; Lees, Jonathan G; Minneci, Federico; Orengo, Christine A; Jones, David T

2017-10-01

Accurate gene or protein function prediction is a key challenge in the post-genome era. Most current methods perform well on molecular function prediction, but struggle to provide useful annotations relating to biological process functions due to the limited power of sequence-based features in that functional domain. In this work, we systematically evaluate the predictive power of temporal transcription expression profiles for protein function prediction in Drosophila melanogaster. Our results show significantly better performance on predicting protein function when transcription expression profile-based features are integrated with sequence-derived features, compared with the sequence-derived features alone. We also observe that the combination of expression-based and sequence-based features leads to further improvement of accuracy on predicting all three domains of gene function. Based on the optimal feature combinations, we then propose a novel multi-classifier-based function prediction method for Drosophila melanogaster proteins, FFPred-fly+. Interpreting our machine learning models also allows us to identify some of the underlying links between biological processes and developmental stages of Drosophila melanogaster.

Photo-detachment of negative ions in Ar-CO2 dc discharge employing Langmuir probe

NASA Astrophysics Data System (ADS)

Rodríguez, Jannet; Yousif, Farook Bashir; Fuentes, Beatriz E.; Vázquez, Federico; Rivera, Marco; López-Patiño, J.; Figueroa, Aldo; Martínez, Horacio

2018-05-01

The electronegativity of the A r - C O 2 gas mixture was investigated, and the total relative negative oxygen ion density O2- + O- in the bulk of a dc discharge has been determined employing Langmuir probe assisted laser photo-detachment. The relative electron density and absolute temperature were obtained for the mixture at discharge powers between 200 and 3000 mW and pressures between 0.2 and 0.6 mbar, employing the collisional radiative model for several Ar gas mixtures. The absolute metastable number density for 1s3 and 1s5 levels was measured, and both showed an increasing trend as a function of pressure and power. The absolute number density of the 1s5 level was found to be higher than that of the 1s3 level. Electronegativity was found to decrease as a function of power and as a function of the increasing Ar percentage in the gas mixture.

Density matrix embedding in an antisymmetrized geminal power bath

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

Tsuchimochi, Takashi; Welborn, Matthew; Van Voorhis, Troy, E-mail: tvan@mit.edu

2015-07-14

Density matrix embedding theory (DMET) has emerged as a powerful tool for performing wave function-in-wave function embedding for strongly correlated systems. In traditional DMET, an accurate calculation is performed on a small impurity embedded in a mean field bath. Here, we extend the original DMET equations to account for correlation in the bath via an antisymmetrized geminal power (AGP) wave function. The resulting formalism has a number of advantages. First, it allows one to properly treat the weak correlation limit of independent pairs, which DMET is unable to do with a mean-field bath. Second, it associates a size extensive correlationmore » energy with a given density matrix (for the models tested), which AGP by itself is incapable of providing. Third, it provides a reasonable description of charge redistribution in strongly correlated but non-periodic systems. Thus, AGP-DMET appears to be a good starting point for describing electron correlation in molecules, which are aperiodic and possess both strong and weak electron correlation.« less

An Update on Statistical Boosting in Biomedicine.

PubMed

Mayr, Andreas; Hofner, Benjamin; Waldmann, Elisabeth; Hepp, Tobias; Meyer, Sebastian; Gefeller, Olaf

2017-01-01

Statistical boosting algorithms have triggered a lot of research during the last decade. They combine a powerful machine learning approach with classical statistical modelling, offering various practical advantages like automated variable selection and implicit regularization of effect estimates. They are extremely flexible, as the underlying base-learners (regression functions defining the type of effect for the explanatory variables) can be combined with any kind of loss function (target function to be optimized, defining the type of regression setting). In this review article, we highlight the most recent methodological developments on statistical boosting regarding variable selection, functional regression, and advanced time-to-event modelling. Additionally, we provide a short overview on relevant applications of statistical boosting in biomedicine.

Decoding genes with coexpression networks and metabolomics - 'majority report by precogs'.

PubMed

Saito, Kazuki; Hirai, Masami Y; Yonekura-Sakakibara, Keiko

2008-01-01

Following the sequencing of whole genomes of model plants, high-throughput decoding of gene function is a major challenge in modern plant biology. In view of remarkable technical advances in transcriptomics and metabolomics, integrated analysis of these 'omics' by data-mining informatics is an excellent tool for prediction and identification of gene function, particularly for genes involved in complicated metabolic pathways. The availability of Arabidopsis public transcriptome datasets containing data of >1000 microarrays reinforces the potential for prediction of gene function by transcriptome coexpression analysis. Here, we review the strategy of combining transcriptome and metabolome as a powerful technology for studying the functional genomics of model plants and also crop and medicinal plants.

Modeling of high composition AlGaN channel high electron mobility transistors with large threshold voltage

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

Bajaj, Sanyam, E-mail: bajaj.10@osu.edu; Hung, Ting-Hsiang; Akyol, Fatih

2014-12-29

We report on the potential of high electron mobility transistors (HEMTs) consisting of high composition AlGaN channel and barrier layers for power switching applications. Detailed two-dimensional (2D) simulations show that threshold voltages in excess of 3 V can be achieved through the use of AlGaN channel layers. We also calculate the 2D electron gas mobility in AlGaN channel HEMTs and evaluate their power figures of merit as a function of device operating temperature and Al mole fraction in the channel. Our models show that power switching transistors with AlGaN channels would have comparable on-resistance to GaN-channel based transistors for the samemore » operation voltage. The modeling in this paper shows the potential of high composition AlGaN as a channel material for future high threshold enhancement mode transistors.« less

KTX circuit model and discharge waveform prediction

NASA Astrophysics Data System (ADS)

Bai, Wei; Lan, T.; Mao, W. Z.; You, W.; Li, H.; Liu, A. D.; Xie, J. L.; Wan, S. D.; Liu, W. D.; Yang, L.; Fu, P.; Xiao, C. J.; Ding, W. X.

2013-10-01

The Keda Torus eXperiment (KTX) is a constructing reversed field pinch (RFP) device in University of Science and Technology of China. The KTX power supply system includes the Ohmic heating, field shaping and toroidal power supply systems, which produce the Ohmic field, equilibrium field and toroidal field, respectively. The detailed circuit model will be introduced in this poster. Another purpose is to predict its discharge waveforms using the modified Bessel function mode (MBFM), which describes the evolution of plasma current and magnetic flux in RFP base on Taylor theory. Furthermore, the power supply requirements of external field shaping winding are also predicted in the model, which will be very helpful for the design of plasma equilibrium controlling system. Supported by ITER-China program (No. 2011GB106000), NNSFC (Nos. 10990210, 10990211, 10335060 and 10905057), CPSF (No. 20080440104), YIF (No. WK2030040019) and KIPCAS (No. kjcx-yw-n28).

Multiphysics Modeling of an Annular Linear Induction Pump With Applications to Space Nuclear Power Systems

NASA Technical Reports Server (NTRS)

Kilbane, J.; Polzin, K. A.

2014-01-01

An annular linear induction pump (ALIP) that could be used for circulating liquid-metal coolant in a fission surface power reactor system is modeled in the present work using the computational COMSOL Multiphysics package. The pump is modeled using a two-dimensional, axisymmetric geometry and solved under conditions similar to those used during experimental pump testing. Real, nonlinear, temperature-dependent material properties can be incorporated into the model for both the electrically-conducting working fluid in the pump (NaK-78) and structural components of the pump. The intricate three-phase coil configuration of the pump is implemented in the model to produce an axially-traveling magnetic wave that is qualitatively similar to the measured magnetic wave. The model qualitatively captures the expected feature of a peak in efficiency as a function of flow rate.

Fusing modeling techniques to support domain analysis for reuse opportunities identification

NASA Technical Reports Server (NTRS)

Hall, Susan Main; Mcguire, Eileen

1993-01-01

Functional modeling techniques or object-oriented graphical representations, which are more useful to someone trying to understand the general design or high level requirements of a system? For a recent domain analysis effort, the answer was a fusion of popular modeling techniques of both types. By using both functional and object-oriented techniques, the analysts involved were able to lean on their experience in function oriented software development, while taking advantage of the descriptive power available in object oriented models. In addition, a base of familiar modeling methods permitted the group of mostly new domain analysts to learn the details of the domain analysis process while producing a quality product. This paper describes the background of this project and then provides a high level definition of domain analysis. The majority of this paper focuses on the modeling method developed and utilized during this analysis effort.

Semiparametric Identification of Human Arm Dynamics for Flexible Control of a Functional Electrical Stimulation Neuroprosthesis

PubMed Central

Schearer, Eric M.; Liao, Yu-Wei; Perreault, Eric J.; Tresch, Matthew C.; Memberg, William D.; Kirsch, Robert F.; Lynch, Kevin M.

2016-01-01

We present a method to identify the dynamics of a human arm controlled by an implanted functional electrical stimulation neuroprosthesis. The method uses Gaussian process regression to predict shoulder and elbow torques given the shoulder and elbow joint positions and velocities and the electrical stimulation inputs to muscles. We compare the accuracy of torque predictions of nonparametric, semiparametric, and parametric model types. The most accurate of the three model types is a semiparametric Gaussian process model that combines the flexibility of a black box function approximator with the generalization power of a parameterized model. The semiparametric model predicted torques during stimulation of multiple muscles with errors less than 20% of the total muscle torque and passive torque needed to drive the arm. The identified model allows us to define an arbitrary reaching trajectory and approximately determine the muscle stimulations required to drive the arm along that trajectory. PMID:26955041

Measurement and analysis of applied power, forces and material response in friction stir welding of aluminum alloy 6061

NASA Astrophysics Data System (ADS)

Avila, Ricardo E.

The process of Friction Stir Welding (FSW) 6061 aluminum alloy is investigated, with focus on the forces and power being applied in the process and the material response. The main objective is to relate measurements of the forces and power applied in the process with mechanical properties of the material during the dynamic process, based on mathematical modeling and aided by computer simulations, using the LS-DYNA software for finite element modeling. Results of measurements of applied forces and power are presented. The result obtained for applied power is used in the construction of a mechanical variational model of FSW, in which minimization of a functional for the applied torque is sought, leading to an expression for shear stress in the material. The computer simulations are performed by application of the Smoothed Particle Hydrodynamics (SPH) method, in which no structured finite element mesh is used to construct a spatial discretization of the model. The current implementation of SPH in LS-DYNA allows a structural solution using a plastic kinematic material model. This work produces information useful to improve understanding of the material flow in the process, and thus adds to current knowledge about the behavior of materials under processes of severe plastic deformation, particularly those processes in which deformation occurs mainly by application of shear stress, aided by thermoplastic strain localization and dynamic recrystallization.

Numerical approach to optimal portfolio in a power utility regime-switching model

NASA Astrophysics Data System (ADS)

Gyulov, Tihomir B.; Koleva, Miglena N.; Vulkov, Lubin G.

2017-12-01

We consider a system of weakly coupled degenerate semi-linear parabolic equations of optimal portfolio in a regime-switching with power utility function, derived by A.R. Valdez and T. Vargiolu [14]. First, we discuss some basic properties of the solution of this system. Then, we develop and analyze implicit-explicit, flux limited finite difference schemes for the differential problem. Numerical experiments are discussed.

Simulating flaring events in complex active regions driven by observed magnetograms

NASA Astrophysics Data System (ADS)

Dimitropoulou, M.; Isliker, H.; Vlahos, L.; Georgoulis, M. K.

2011-05-01

Context. We interpret solar flares as events originating in active regions that have reached the self organized critical state, by using a refined cellular automaton model with initial conditions derived from observations. Aims: We investigate whether the system, with its imposed physical elements, reaches a self organized critical state and whether well-known statistical properties of flares, such as scaling laws observed in the distribution functions of characteristic parameters, are reproduced after this state has been reached. Methods: To investigate whether the distribution functions of total energy, peak energy and event duration follow the expected scaling laws, we first applied a nonlinear force-free extrapolation that reconstructs the three-dimensional magnetic fields from two-dimensional vector magnetograms. We then locate magnetic discontinuities exceeding a threshold in the Laplacian of the magnetic field. These discontinuities are relaxed in local diffusion events, implemented in the form of cellular automaton evolution rules. Subsequent loading and relaxation steps lead the system to self organized criticality, after which the statistical properties of the simulated events are examined. Physical requirements, such as the divergence-free condition for the magnetic field vector, are approximately imposed on all elements of the model. Results: Our results show that self organized criticality is indeed reached when applying specific loading and relaxation rules. Power-law indices obtained from the distribution functions of the modeled flaring events are in good agreement with observations. Single power laws (peak and total flare energy) are obtained, as are power laws with exponential cutoff and double power laws (flare duration). The results are also compared with observational X-ray data from the GOES satellite for our active-region sample. Conclusions: We conclude that well-known statistical properties of flares are reproduced after the system has reached self organized criticality. A significant enhancement of our refined cellular automaton model is that it commences the simulation from observed vector magnetograms, thus facilitating energy calculation in physical units. The model described in this study remains consistent with fundamental physical requirements, and imposes physically meaningful driving and redistribution rules.

Effect of high energy electrons on H⁻ production and destruction in a high current DC negative ion source for cyclotron.

PubMed

Onai, M; Etoh, H; Aoki, Y; Shibata, T; Mattei, S; Fujita, S; Hatayama, A; Lettry, J

2016-02-01

Recently, a filament driven multi-cusp negative ion source has been developed for proton cyclotrons in medical applications. In this study, numerical modeling of the filament arc-discharge source plasma has been done with kinetic modeling of electrons in the ion source plasmas by the multi-cusp arc-discharge code and zero dimensional rate equations for hydrogen molecules and negative ions. In this paper, main focus is placed on the effects of the arc-discharge power on the electron energy distribution function and the resultant H(-) production. The modelling results reasonably explains the dependence of the H(-) extraction current on the arc-discharge power in the experiments.

An environmental testing facility for Space Station Freedom power management and distribution hardware

NASA Technical Reports Server (NTRS)

Jackola, Arthur S.; Hartjen, Gary L.

1992-01-01

The plans for a new test facility, including new environmental test systems, which are presently under construction, and the major environmental Test Support Equipment (TSE) used therein are addressed. This all-new Rocketdyne facility will perform space simulation environmental tests on Power Management and Distribution (PMAD) hardware to Space Station Freedom (SSF) at the Engineering Model, Qualification Model, and Flight Model levels of fidelity. Testing will include Random Vibration in three axes - Thermal Vacuum, Thermal Cycling and Thermal Burn-in - as well as numerous electrical functional tests. The facility is designed to support a relatively high throughput of hardware under test, while maintaining the high standards required for a man-rated space program.

Design analysis and computer-aided performance evaluation of shuttle orbiter electrical power system. Volume 1: Summary

NASA Technical Reports Server (NTRS)

1974-01-01

Studies were conducted to develop appropriate space shuttle electrical power distribution and control (EPDC) subsystem simulation models and to apply the computer simulations to systems analysis of the EPDC. A previously developed software program (SYSTID) was adapted for this purpose. The following objectives were attained: (1) significant enhancement of the SYSTID time domain simulation software, (2) generation of functionally useful shuttle EPDC element models, and (3) illustrative simulation results in the analysis of EPDC performance, under the conditions of fault, current pulse injection due to lightning, and circuit protection sizing and reaction times.

Simulating the effect of high column density absorbers on the one-dimensional Lyman α forest flux power spectrum

NASA Astrophysics Data System (ADS)

Rogers, Keir K.; Bird, Simeon; Peiris, Hiranya V.; Pontzen, Andrew; Font-Ribera, Andreu; Leistedt, Boris

2018-03-01

We measure the effect of high column density absorbing systems of neutral hydrogen (H I) on the one-dimensional (1D) Lyman α forest flux power spectrum using cosmological hydrodynamical simulations from the Illustris project. High column density absorbers (which we define to be those with H I column densities N(H I) > 1.6 × 10^{17} atoms cm^{-2}) cause broadened absorption lines with characteristic damping wings. These damping wings bias the 1D Lyman α forest flux power spectrum by causing absorption in quasar spectra away from the location of the absorber itself. We investigate the effect of high column density absorbers on the Lyman α forest using hydrodynamical simulations for the first time. We provide templates as a function of column density and redshift, allowing the flexibility to accurately model residual contamination, i.e. if an analysis selectively clips out the largest damping wings. This flexibility will improve cosmological parameter estimation, for example, allowing more accurate measurement of the shape of the power spectrum, with implications for cosmological models containing massive neutrinos or a running of the spectral index. We provide fitting functions to reproduce these results so that they can be incorporated straightforwardly into a data analysis pipeline.

The ACS Survey of Galactic Globular Clusters. VIII. Effects of Environment on Globular Cluster Global Mass Functions

NASA Astrophysics Data System (ADS)

Paust, Nathaniel E. Q.; Reid, I. Neill; Piotto, Giampaolo; Aparicio, Antonio; Anderson, Jay; Sarajedini, Ata; Bedin, Luigi R.; Chaboyer, Brian; Dotter, Aaron; Hempel, Maren; Majewski, Steven; Marín-Franch, A.; Milone, Antonino; Rosenberg, Alfred; Siegel, Michael

2010-02-01

We have used observations obtained as part of the Hubble Space Telescope/ACS Survey of Galactic Globular Clusters to construct global present-day mass functions for 17 globular clusters utilizing multi-mass King models to extrapolate from our observations to the global cluster behavior. The global present-day mass functions for these clusters are well matched by power laws from the turnoff, ≈0.8 M sun, to 0.2-0.3 M sun on the lower main sequence. The slopes of those power-law fits, α, have been correlated with an extensive set of intrinsic and extrinsic cluster properties to investigate which parameters may influence the form of the present-day mass function. We do not confirm previous suggestions of correlations between α and either metallicity or Galactic location. However, we do find a strong statistical correlation with the related parameters central surface brightness, μ V , and inferred central density, ρ0. The correlation is such that clusters with denser cores (stronger binding energy) tend to have steeper mass functions (a higher proportion of low-mass stars), suggesting that dynamical evolution due to external interactions may have played a key role in determining α. Thus, the present-day mass function may owe more to nurture than to nature. Detailed modeling of external dynamical effects is therefore a requisite for determining the initial mass function for Galactic globular clusters.

The possible consequences for cognitive functions of external electric fields at power line frequency on hippocampal CA1 pyramidal neurons.

PubMed

Migliore, Rosanna; De Simone, Giada; Leinekugel, Xavier; Migliore, Michele

2017-04-01

The possible effects on cognitive processes of external electric fields, such as those generated by power line pillars and household appliances are of increasing public concern. They are difficult to study experimentally, and the relatively scarce and contradictory evidence make it difficult to clearly assess these effects. In this study, we investigate how, why and to what extent external perturbations of the intrinsic neuronal activity, such as those that can be caused by generation, transmission and use of electrical energy can affect neuronal activity during cognitive processes. For this purpose, we used a morphologically and biophysically realistic three-dimensional model of CA1 pyramidal neurons. The simulation findings suggest that an electric field oscillating at power lines frequency, and environmentally measured strength, can significantly alter both the average firing rate and temporal spike distribution properties of a hippocampal CA1 pyramidal neuron. This effect strongly depends on the specific and instantaneous relative spatial location of the neuron with respect to the field, and on the synaptic input properties. The model makes experimentally testable predictions on the possible functional consequences for normal hippocampal functions such as object recognition and spatial navigation. The results suggest that, although EF effects on cognitive processes may be difficult to occur in everyday life, their functional consequences deserve some consideration, especially when they constitute a systematic presence in living environments. © 2016 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

The relationship between perceived discomfort of static posture holding and posture holding time.

PubMed

Ogutu, Jack; Park, Woojin

2015-01-01

Few studies have investigated mathematical characteristics of the discomfort-time relationship during prolonged static posture holding (SPH) on an individual basis. Consequently, the discomfort-time relationship is not clearly understood at individual trial level. The objective of this study was to examine discomfort-time sequence data obtained from a large number of maximum-duration SPH trials to understand the perceived discomfort-posture holding time relationship at the individual SPH trial level. Thirty subjects (15 male, 15 female) participated in this study as paid volunteers. The subjects performed maximum-duration SPH trials employing 12 different wholebody static postures. The hand-held load for all the task trials was a ``generic'' box weighing 2 kg. Three mathematical functions, that is, linear, logarithmic and power functions were examined as possible mathematical models for representing individual discomfort-time profiles of SPH trials. Three different time increase patterns (negatively accelerated, linear and positively accelerated) were observed in the discomfort-time sequences data. The power function model with an additive constant term was found to adequately fit most (96.4%) of the observed discomfort-time sequences, and thus, was recommended as a general mathematical representation of the perceived discomfort-posture holding time relationship in SPH. The new knowledge on the nature of the discomfort-time relationship in SPH and the power function representation found in this study will facilitate analyzing discomfort-time data of SPH and developing future posture analysis tools for work-related discomfort control.

Secure provision of reactive power ancillary services in competitive electricity markets

NASA Astrophysics Data System (ADS)

El-Samahy, Ismael

The research work presented in this thesis discusses various complex issues associated with reactive power management and pricing in the context of new operating paradigms in deregulated power systems, proposing appropriate policy solutions. An integrated two-level framework for reactive power management is set forth, which is both suitable for a competitive market and ensures a secure and reliable operation of the associated power system. The framework is generic in nature and can be adopted for any electricity market structure. The proposed hierarchical reactive power market structure comprises two stages: procurement of reactive power resources on a seasonal basis, and real-time reactive power dispatch. The main objective of the proposed framework is to provide appropriate reactive power support from service providers at least cost, while ensuring a secure operation of the power system. The proposed procurement procedure is based on a two-step optimization model. First, the marginal benefits of reactive power supply from each provider, with respect to system security, are obtained by solving a loadability-maximization problem subject to transmission security constraints imposed by voltage and thermal limits. Second, the selected set of generators is determined by solving an optimal power flow (OPF)-based auction. This auction maximizes a societal advantage function comprising generators' offers and their corresponding marginal benefits with respect to system security, and considering all transmission system constraints. The proposed procedure yields the selected set of generators and zonal price components, which would form the basis for seasonal contracts between the system operator and the selected reactive power service providers. The main objective of the proposed reactive power dispatch model is to minimize the total payment burden on the Independent System Operator (ISO), which is associated with reactive power dispatch. The real power generation is decoupled and assumed to be fixed during the reactive power dispatch procedures; however, the effect of reactive power on real power is considered in the model by calculating the required reduction in real power output of a generator due to an increase in its reactive power supply. In this case, real power generation is allowed to be rescheduled, within given limits, from the already dispatched levels obtained from the energy market clearing process. The proposed dispatch model achieves the main objective of an ISO in a competitive electricity market, which is to provide the required reactive power support from generators at least cost while ensuring a secure operation of the power system. The proposed reactive power procurement and dispatch models capture both the technical and economic aspects of power system operation in competitive electricity markets; however, from an optimization point of view, these models represent non-convex mixed integer non-linear programming (MINLP) problems due to the presence of binary variables associated with the different regions of reactive power operation in a synchronous generator. Such MINLP optimization problems are difficult to solve, especially for an actual power system. A novel Generator Reactive Power Classification (GRPC) algorithm is proposed in this thesis to address this issue, with the advantage of iteratively solving the optimization models as a series of non-linear programming (NLP) sub-problems. The proposed reactive power procurement and dispatch models are implemented and tested on the CIGRE 32-bus system, with several case studies that represent different practical operating scenarios. The developed models are also compared with other approaches for reactive power provision, and the results demonstrate the robustness and effectiveness of the proposed model. The results clearly reveal the main features of the proposed models for optimal provision of reactive power ancillary service, in order to suit the requirements of an ISO under today's stressed system conditions in a competitive market environment.

Analytical Characterization of SPM Impact on XPM-Induced Degradation in Dispersion-Compensated WDM Systems

NASA Astrophysics Data System (ADS)

Luís, Ruben S.; Cartaxo, Adolfo V. T.

2005-03-01

This paper proposes the definition of a cross-phase modulation (XPM)-induced power penalty for intensity modulation/direct detection (IM-DD) systems as a function of the normalized variance of the XPM-induced IM. This allows the definition of 1-dB power penalty reference values. New expressions of the equivalent linear model transfer functions for the XPM-induced IM and phase modulation (PM) that include the influence of self-phase modulation (SPM) as well as group-velocity dispersion are derived. The new expressions allow a significant extension for higher powers and dispersion parameters of expressions derived in previous papers for single-segment and multisegment fiber systems with dispersion compensation. Good agreement between analytical results and numerical simulations is obtained. Consistency with work performed numerically and experimentally by other authors is shown, validating the proposed model. Using the proposed model, the influence of residual dispersion and SPM on the limitations imposed by XPM on the performance of dispersion-compensated systems is assessed. It is shown that inline residual dispersion may lead to performance improvement for a properly tuned total residual dispersion. The influence of SPM is shown to degrade the system performance when nonzero-dispersion-shifted fiber is used. However, systems using standard single-mode fiber may benefit from the presence of SPM.

Anesthesia modifies subthreshold critical slowing down in a stochastic Hodgkin-Huxley-like model with inhibitory synaptic input

NASA Astrophysics Data System (ADS)

Bukoski, Alex; Steyn-Ross, D. A.; Pickett, Ashley F.; Steyn-Ross, Moira L.

2018-06-01

The dynamics of a stochastic type-I Hodgkin-Huxley-like point neuron model exposed to inhibitory synaptic noise are investigated as a function of distance from spiking threshold and the inhibitory influence of the general anesthetic agent propofol. The model is biologically motivated and includes the effects of intrinsic ion-channel noise via a stochastic differential equation description as well as inhibitory synaptic noise modeled as multiple Poisson-distributed impulse trains with saturating response functions. The effect of propofol on these synapses is incorporated through this drug's principal influence on fast inhibitory neurotransmission mediated by γ -aminobutyric acid (GABA) type-A receptors via reduction of the synaptic response decay rate. As the neuron model approaches spiking threshold from below, we track membrane voltage fluctuation statistics of numerically simulated stochastic trajectories. We find that for a given distance from spiking threshold, increasing the magnitude of anesthetic-induced inhibition is associated with augmented signatures of critical slowing: fluctuation amplitudes and correlation times grow as spectral power is increasingly focused at 0 Hz. Furthermore, as a function of distance from threshold, anesthesia significantly modifies the power-law exponents for variance and correlation time divergences observable in stochastic trajectories. Compared to the inverse square root power-law scaling of these quantities anticipated for the saddle-node bifurcation of type-I neurons in the absence of anesthesia, increasing anesthetic-induced inhibition results in an observable exponent <-0.5 for variance and >-0.5 for correlation time divergences. However, these behaviors eventually break down as distance from threshold goes to zero with both the variance and correlation time converging to common values independent of anesthesia. Compared to the case of no synaptic input, linearization of an approximating multivariate Ornstein-Uhlenbeck model reveals these effects to be the consequence of an additional slow eigenvalue associated with synaptic activity that competes with those of the underlying point neuron in a manner that depends on distance from spiking threshold.

Estimating radiofrequency power deposition in body NMR imaging.

PubMed

Bottomley, P A; Redington, R W; Edelstein, W A; Schenck, J F

1985-08-01

Simple theoretical estimates of the average, maximum, and spatial variation of the radiofrequency power deposition (specific absorption rate) during hydrogen nuclear magnetic resonance imaging are deduced for homogeneous spheres and for cylinders of biological tissue with a uniformly penetrating linear rf field directed axially and transverse to the cylindrical axis. These are all simple scalar multiples of the expression for the cylinder in an axial field published earlier (Med. Phys. 8, 510 (1981]. Exact solutions for the power deposition in the cylinder with axial (Phys. Med. Biol. 23, 630 (1978] and transversely directed rf field are also presented, and the spatial variation of power deposition in head and body models is examined. In the exact models, the specific absorption rates decrease rapidly and monotonically with decreasing radius despite local increases in rf field amplitude. Conversion factors are provided for calculating the power deposited by Gaussian and sinc-modulated rf pulses used for slice selection in NMR imaging, relative to rectangular profiled pulses. Theoretical estimates are compared with direct measurements of the total power deposited in the bodies of nine adult males by a 63-MHz body-imaging system with transversely directed field, taking account of cable and NMR coil losses. The results for the average power deposition agree within about 20% for the exact model of the cylinder with axial field, when applied to the exposed torso volume enclosed by the rf coil. The average values predicted by the simple spherical and cylindrical models with axial fields, the exact cylindrical model with transverse field, and the simple truncated cylinder model with transverse field were about two to three times that measured, while the simple model consisting of an infinitely long cylinder with transverse field gave results about six times that measured. The surface power deposition measured by observing the incremental power as a function of external torso radius was comparable to the average value. This is consistent with the presence of a variable thickness peripheral adipose layer which does not substantially increase surface power deposition with increasing torso radius. The absence of highly localized intensity artifacts in 63-MHz body images does not suggest anomalously intense power deposition at localized internal sites, although peak power is difficult to measure.

An architecture for object-oriented intelligent control of power systems in space

NASA Technical Reports Server (NTRS)

Holmquist, Sven G.; Jayaram, Prakash; Jansen, Ben H.

1993-01-01

A control system for autonomous distribution and control of electrical power during space missions is being developed. This system should free the astronauts from localizing faults and reconfiguring loads if problems with the power distribution and generation components occur. The control system uses an object-oriented simulation model of the power system and first principle knowledge to detect, identify, and isolate faults. Each power system component is represented as a separate object with knowledge of its normal behavior. The reasoning process takes place at three different levels of abstraction: the Physical Component Model (PCM) level, the Electrical Equivalent Model (EEM) level, and the Functional System Model (FSM) level, with the PCM the lowest level of abstraction and the FSM the highest. At the EEM level the power system components are reasoned about as their electrical equivalents, e.g, a resistive load is thought of as a resistor. However, at the PCM level detailed knowledge about the component's specific characteristics is taken into account. The FSM level models the system at the subsystem level, a level appropriate for reconfiguration and scheduling. The control system operates in two modes, a reactive and a proactive mode, simultaneously. In the reactive mode the control system receives measurement data from the power system and compares these values with values determined through simulation to detect the existence of a fault. The nature of the fault is then identified through a model-based reasoning process using mainly the EEM. Compound component models are constructed at the EEM level and used in the fault identification process. In the proactive mode the reasoning takes place at the PCM level. Individual components determine their future health status using a physical model and measured historical data. In case changes in the health status seem imminent the component warns the control system about its impending failure. The fault isolation process uses the FSM level for its reasoning base.

Enhanced representations of lithium-ion batteries in power systems models and their effect on the valuation of energy arbitrage applications

NASA Astrophysics Data System (ADS)

Sakti, Apurba; Gallagher, Kevin G.; Sepulveda, Nestor; Uckun, Canan; Vergara, Claudio; de Sisternes, Fernando J.; Dees, Dennis W.; Botterud, Audun

2017-02-01

We develop three novel enhanced mixed integer-linear representations of the power limit of the battery and its efficiency as a function of the charge and discharge power and the state of charge of the battery, which can be directly implemented in large-scale power systems models and solved with commercial optimization solvers. Using these battery representations, we conduct a techno-economic analysis of the performance of a 10 MWh lithium-ion battery system testing the effect of a 5-min vs. a 60-min price signal on profits using real time prices from a selected node in the MISO electricity market. Results show that models of lithium-ion batteries where the power limits and efficiency are held constant overestimate profits by 10% compared to those obtained from an enhanced representation that more closely matches the real behavior of the battery. When the battery system is exposed to a 5-min price signal, the energy arbitrage profitability improves by 60% compared to that from hourly price exposure. These results indicate that a more accurate representation of li-ion batteries as well as the market rules that govern the frequency of electricity prices can play a major role on the estimation of the value of battery technologies for power grid applications.

Interpreting single jet measurements in Pb$+$Pb collisions at the LHC

DOE PAGES

Spousta, Martin; Cole, Brian

2016-01-27

Results are presented from a phenomenological analysis of recent measurements of jet suppression and modifications of jet fragmentation functions in Pb+Pb collisions at the LHC. Particular emphasis is placed on the impact of the differences between quark and gluon jet quenching on the transverse momentum (p jet T) dependence of the jet R AA and on the fragmentation functions, D(z). Primordial quark and gluon parton distributions were obtained from PYTHIA8 and were parameterized using simple power-law functions and extensions to the power-law function which were found to better describe the PYTHIA8 parton spectra. A simple model for the quark energymore » loss based on the shift formalism is used to model R AA and D(z) using both analytic results and using direct Monte-Carlo sampling of the PYTHIA parton spectra. The model is capable of describing the full p jet T, rapidity, and centrality dependence of the measured jet R AA using three effective parameters. A key result from the analysis is that the D(z) modifications observed in the data, excluding the enhancement at low-z, may result primarily from the different quenching of the quarks and gluons. Furthermore, the model is also capable of reproducing the charged hadron R AA at high transverse momentum. Predictions are made for the jet R AA at large rapidities where it has not yet been measured and for the rapidity dependence of D(z).« less

Better Resolved Low Frequency Dispersions by the Apt Use of Kramers-Kronig Relations, Differential Operators, and All-In-1 Modeling

PubMed Central

van Turnhout, J.

2016-01-01

The dielectric spectra of colloidal systems often contain a typical low frequency dispersion, which usually remains unnoticed, because of the presence of strong conduction losses. The KK relations offer a means for converting ε′ into ε″ data. This allows us to calculate conduction free ε″ spectra in which the l.f. dispersion will show up undisturbed. This interconversion can be done on line with a moving frame of logarithmically spaced ε′ data. The coefficients of the conversion frames were obtained by kernel matching and by using symbolic differential operators. Logarithmic derivatives and differences of ε′ and ε″ provide another option for conduction free data analysis. These difference-based functions actually derived from approximations to the distribution function, have the additional advantage of improving the resolution power of dielectric studies. A high resolution is important because of the rich relaxation structure of colloidal suspensions. The development of all-in-1 modeling facilitates the conduction free and high resolution data analysis. This mathematical tool allows the apart-together fitting of multiple data and multiple model functions. It proved also useful to go around the KK conversion altogether. This was achieved by the combined approximating ε′ and ε″ data with a complex rational fractional power function. The all-in-1 minimization turned out to be also highly useful for the dielectric modeling of a suspension with the complex dipolar coefficient. It guarantees a secure correction for the electrode polarization, so that the modeling with the help of the differences ε′ and ε″ can zoom in on the genuine colloidal relaxations. PMID:27242997

Modelling the luminosity function of long gamma-ray bursts using Swift and Fermi

NASA Astrophysics Data System (ADS)

Paul, Debdutta

2018-01-01

I have used a sample of long gamma-ray bursts (GRBs) common to both Swift and Fermi to re-derive the parameters of the Yonetoku correlation. This allowed me to self-consistently estimate pseudo-redshifts of all the bursts with unknown redshifts. This is the first time such a large sample of GRBs from these two instruments is used, both individually and in conjunction, to model the long GRB luminosity function. The GRB formation rate is modelled as the product of the cosmic star formation rate and a GRB formation efficiency for a given stellar mass. An exponential cut-off power-law luminosity function fits the data reasonably well, with ν = 0.6 and Lb = 5.4 × 1052 ergs- 1, and does not require a cosmological evolution. In the case of a broken power law, it is required to incorporate a sharp evolution of the break given by Lb ∼ 0.3 × 1052(1 + z)2.90 erg s- 1, and the GRB formation efficiency (degenerate up to a beaming factor of GRBs) decreases with redshift as ∝ (1 + z)-0.80. However, it is not possible to distinguish between the two models. The derived models are then used as templates to predict the distribution of GRBs detectable by CZT Imager onboard AstroSat as a function of redshift and luminosity. This demonstrates that via a quick localization and redshift measurement of even a few CZT Imager GRBs, AstroSat will help in improving the statistics of GRBs both typical and peculiar.

Power and energy dissipation in subsequent return strokes as predicted by a new return stroke model

NASA Technical Reports Server (NTRS)

Cooray, Vernon

1991-01-01

Recently, Cooray introduced a new return stroke model which is capable of predicting the temporal behavior of the return stroke current and the return stroke velocity as a function of the height along the return stroke channel. The authors employed this model to calculate the power and energy dissipation in subsequent return strokes. The results of these calculations are presented here. It was concluded that a large fraction of the total energy available for the dart leader-subsequent stroke process is dissipated in the dart leader stage. The peak power per unit length dissipated in a subsequent stroke channel element decreases with increasing height of that channel element from ground level. For a given channel element, the peak power dissipation increases with increasing current in that channel element. The peak electrical power dissipation in a typical subsequent return stroke is about 1.5 times 10(exp 11) W. The energy dissipation in a subsequent stroke increases with increasing current in the return stroke channel, and for a typical subsequent stroke, the energy dissipation per unit length is about 5.0 times 10(exp 3) J/m.

Modeling and design of a capacitive microwave power sensor for X-band applications based on GaAs technology

NASA Astrophysics Data System (ADS)

Cui, Yan; Liao, Xiaoping

2012-05-01

In the work, modeling and design of a capacitive microwave power sensor employing the MEMS plate with clamped-clamped and free-free edges are presented. A novel analytical model of the sensor is established in detail. Through the function of mode shapes presented, the natural frequency can be solved by the Rayleigh-Ritz method. And based on the generalized coordinate introduced, the displacement of the plate with the irradiation of microwave power can be solved. Furthermore, the sensitivity for the power is also derived. Then the detailed consideration of the design and simulation of the microwave characteristic of the sensor are also presented. The linearly graded ground planar in the coplanar waveguide is employed to avoid step discontinuity. The fabrication process is compatible with GaAs MMIC technology completely, also described in detail. The measurement of the proposed sensor indicates a sensitivity of 7.2 fF W-1 and superior return and insertion losses (S11 and S21), less than -22.16 dB and -0.25 dB, respectively, up to 12 GHz, suggesting that it can be available for microwave power detecting in the X-band frequency range.

Estimation of parameters of constant elasticity of substitution production functional model

NASA Astrophysics Data System (ADS)

Mahaboob, B.; Venkateswarlu, B.; Sankar, J. Ravi

2017-11-01

Nonlinear model building has become an increasing important powerful tool in mathematical economics. In recent years the popularity of applications of nonlinear models has dramatically been rising up. Several researchers in econometrics are very often interested in the inferential aspects of nonlinear regression models [6]. The present research study gives a distinct method of estimation of more complicated and highly nonlinear model viz Constant Elasticity of Substitution (CES) production functional model. Henningen et.al [5] proposed three solutions to avoid serious problems when estimating CES functions in 2012 and they are i) removing discontinuities by using the limits of the CES function and its derivative. ii) Circumventing large rounding errors by local linear approximations iii) Handling ill-behaved objective functions by a multi-dimensional grid search. Joel Chongeh et.al [7] discussed the estimation of the impact of capital and labour inputs to the gris output agri-food products using constant elasticity of substitution production function in Tanzanian context. Pol Antras [8] presented new estimates of the elasticity of substitution between capital and labour using data from the private sector of the U.S. economy for the period 1948-1998.

[Models for biomass estimation of four shrub species planted in urban area of Xi'an city, Northwest China].

PubMed

Yao, Zheng-Yang; Liu, Jian-Jun

2014-01-01

Four common greening shrub species (i. e. Ligustrum quihoui, Buxus bodinieri, Berberis xinganensis and Buxus megistophylla) in Xi'an City were selected to develop the highest correlation and best-fit estimation models for the organ (branch, leaf and root) and total biomass against different independent variables. The results indicated that the organ and total biomass optimal models of the four shrubs were power functional model (CAR model) except for the leaf biomass model of B. megistophylla which was logarithmic functional model (VAR model). The independent variables included basal diameter, crown diameter, crown diameter multiplied by height, canopy area and canopy volume. B. megistophylla significantly differed from the other three shrub species in the independent variable selection, which were basal diameter and crown-related factors, respectively.

A one-dimensional model of solid-earth electrical resistivity beneath Florida

USGS Publications Warehouse

Blum, Cletus; Love, Jeffrey J.; Pedrie, Kolby; Bedrosian, Paul A.; Rigler, E. Joshua

2015-11-19

An estimated one-dimensional layered model of electrical resistivity beneath Florida was developed from published geological and geophysical information. The resistivity of each layer is represented by plausible upper and lower bounds as well as a geometric mean resistivity. Corresponding impedance transfer functions, Schmucker-Weidelt transfer functions, apparent resistivity, and phase responses are calculated for inducing geomagnetic frequencies ranging from 10−5 to 100 hertz. The resulting one-dimensional model and response functions can be used to make general estimates of time-varying electric fields associated with geomagnetic storms such as might represent induction hazards for electric-power grid operation. The plausible upper- and lower-bound resistivity structures show the uncertainty, giving a wide range of plausible time-varying electric fields.

Analysis of a model race car

NASA Astrophysics Data System (ADS)

Coletta, Vincent P.; Evans, Jonathan

2008-10-01

We analyze the motion of a gravity powered model race car on a downhill track of variable slope. Using a simple algebraic function to approximate the height of the track as a function of the distance along the track, and taking account of the rotational energy of the wheels, rolling friction, and air resistance, we obtain analytic expressions for the velocity and time of the car as functions of the distance traveled along the track. Photogates are used to measure the time at selected points along the track, and the measured values are in excellent agreement with the values predicted from theory. The design and analysis of model race cars provides a good application of principles of mechanics and suggests interesting projects for classes in introductory and intermediate mechanics.

Tweedie convergence: a mathematical basis for Taylor's power law, 1/f noise, and multifractality.

PubMed

Kendal, Wayne S; Jørgensen, Bent

2011-12-01

Plants and animals of a given species tend to cluster within their habitats in accordance with a power function between their mean density and the variance. This relationship, Taylor's power law, has been variously explained by ecologists in terms of animal behavior, interspecies interactions, demographic effects, etc., all without consensus. Taylor's law also manifests within a wide range of other biological and physical processes, sometimes being referred to as fluctuation scaling and attributed to effects of the second law of thermodynamics. 1/f noise refers to power spectra that have an approximately inverse dependence on frequency. Like Taylor's law these spectra manifest from a wide range of biological and physical processes, without general agreement as to cause. One contemporary paradigm for 1/f noise has been based on the physics of self-organized criticality. We show here that Taylor's law (when derived from sequential data using the method of expanding bins) implies 1/f noise, and that both phenomena can be explained by a central limit-like effect that establishes the class of Tweedie exponential dispersion models as foci for this convergence. These Tweedie models are probabilistic models characterized by closure under additive and reproductive convolution as well as under scale transformation, and consequently manifest a variance to mean power function. We provide examples of Taylor's law, 1/f noise, and multifractality within the eigenvalue deviations of the Gaussian unitary and orthogonal ensembles, and show that these deviations conform to the Tweedie compound Poisson distribution. The Tweedie convergence theorem provides a unified mathematical explanation for the origin of Taylor's law and 1/f noise applicable to a wide range of biological, physical, and mathematical processes, as well as to multifractality.

Bianchi Type-II String Cosmological Model with Magnetic Field in f ( R, T) Gravity

NASA Astrophysics Data System (ADS)

Sharma, N. K.; Singh, J. K.

2014-09-01

The spatially homogeneous and totally anisotropic Bianchi type-II cosmological solutions of massive strings have been investigated in the presence of the magnetic field in the framework of f( R, T) gravity proposed by Harko et al. (Phys Rev D 84:024020, 2011). With the help of special law of variation for Hubble's parameter proposed by Berman (Nuovo Cimento B 74:182, 1983) cosmological model is obtained in this theory. We consider f( R, T) model and investigate the modification R+ f( T) in Bianchi type-II cosmology with an appropriate choice of a function f( T)= μ T. We use the power law relation between average Hubble parameter H and average scale factor R to find the solution. The assumption of constant deceleration parameter leads to two models of universe, i.e. power law model and exponential model. Some physical and kinematical properties of the model are also discussed.

Wind-Friendly Flexible Ramping Product Design in Multi-Timescale Power System Operations

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

Cui, Mingjian; Zhang, Jie; Wu, Hongyu

With increasing wind power penetration in the electricity grid, system operators are recognizing the need for additional flexibility, and some are implementing new ramping products as a type of ancillary service. However, wind is generally thought of as causing the need for ramping services, not as being a potential source for the service. In this paper, a multi-timescale unit commitment and economic dispatch model is developed to consider the wind power ramping product (WPRP). An optimized swinging door algorithm with dynamic programming is applied to identify and forecast wind power ramps (WPRs). Designed as positive characteristics of WPRs, the WPRPmore » is then integrated into the multi-timescale dispatch model that considers new objective functions, ramping capacity limits, active power limits, and flexible ramping requirements. Numerical simulations on the modified IEEE 118-bus system show the potential effectiveness of WPRP in increasing the economic efficiency of power system operations with high levels of wind power penetration. It is found that WPRP not only reduces the production cost by using less ramping reserves scheduled by conventional generators, but also possibly enhances the reliability of power system operations. Moreover, wind power forecasts play an important role in providing high-quality WPRP service.« less

Relaxation model of radiation-induced conductivity in polymers

NASA Astrophysics Data System (ADS)

Zhutayeva, Yu. R.; Khatipov, S. A.

1999-05-01

The paper suggests a relaxation model of radiation-induced conductivity (RIC) in polymers. According to the model, the transfer of charges generated in the polymer volume by ionizing radiation takes place with the participation of molecular relaxation processes. The mechanism of electron transport consists in the transfer of the charge directly between traps when they draw close to one another due to the rotation of macromolecule segments. The numerical solutions of the corresponding kinetic equations for different distribution functions Q( τ) of the times of molecular relaxation and for different functions of the probability P( τ, τ') of charge transfer in the `overlapping' regions of the diffusion spheres of the segments are analyzed. The relaxation model provides an explanation of the non-Arrhenius behavior of the RIC temperature dependence, the power dependence of RIC on the dose rate with a power index in the interval 0.5-1.0, the appearance of maxima in the curves of the RIC temporal dependence and their irreversible character in the region of large dose rates (more than 1 Gy/s). The model can be used for interpreting polymer RIC in conditions of kinetic mobility of macromolecules.

Removing an intersubject variance component in a general linear model improves multiway factoring of event-related spectral perturbations in group EEG studies.

PubMed

Spence, Jeffrey S; Brier, Matthew R; Hart, John; Ferree, Thomas C

2013-03-01

Linear statistical models are used very effectively to assess task-related differences in EEG power spectral analyses. Mixed models, in particular, accommodate more than one variance component in a multisubject study, where many trials of each condition of interest are measured on each subject. Generally, intra- and intersubject variances are both important to determine correct standard errors for inference on functions of model parameters, but it is often assumed that intersubject variance is the most important consideration in a group study. In this article, we show that, under common assumptions, estimates of some functions of model parameters, including estimates of task-related differences, are properly tested relative to the intrasubject variance component only. A substantial gain in statistical power can arise from the proper separation of variance components when there is more than one source of variability. We first develop this result analytically, then show how it benefits a multiway factoring of spectral, spatial, and temporal components from EEG data acquired in a group of healthy subjects performing a well-studied response inhibition task. Copyright © 2011 Wiley Periodicals, Inc.

Focus expansion and stability of the spread parameter estimate of the power law model for dispersal gradients

PubMed Central

Gent, David H.; Mehra, Lucky K.; Christie, David; Magarey, Roger

2017-01-01

Empirical and mechanistic modeling indicate that pathogens transmitted via aerially dispersed inoculum follow a power law, resulting in dispersive epidemic waves. The spread parameter (b) of the power law model, which is an indicator of the distance of the epidemic wave front from an initial focus per unit time, has been found to be approximately 2 for several animal and plant diseases over a wide range of spatial scales under conditions favorable for disease spread. Although disease spread and epidemic expansion can be influenced by several factors, the stability of the parameter b over multiple epidemic years has not been determined. Additionally, the size of the initial epidemic area is expected to be strongly related to the final epidemic extent for epidemics, but the stability of this relationship is also not well established. Here, empirical data of cucurbit downy mildew epidemics collected from 2008 to 2014 were analyzed using a spatio-temporal model of disease spread that incorporates logistic growth in time with a power law function for dispersal. Final epidemic extent ranged from 4.16 ×108 km2 in 2012 to 6.44 ×108 km2 in 2009. Current epidemic extent became significantly associated (P < 0.0332; 0.56 < R2 < 0.99) with final epidemic area beginning near the end of April, with the association increasing monotonically to 1.0 by the end of the epidemic season in July. The position of the epidemic wave-front became exponentially more distant with time, and epidemic velocity increased linearly with distance. Slopes from the temporal and spatial regression models varied with about a 2.5-fold range across epidemic years. Estimates of b varied substantially ranging from 1.51 to 4.16 across epidemic years. We observed a significant b ×time (or distance) interaction (P < 0.05) for epidemic years where data were well described by the power law model. These results suggest that the spread parameter b may not be stable over multiple epidemic years. However, b ≈ 2 may be considered the lower limit of the distance traveled by epidemic wave-fronts for aerially transmitted pathogens that follow a power law dispersal function. PMID:28649473

Development Status of the NSTAR Ion Propulsion System Power Processor

NASA Technical Reports Server (NTRS)

Hamley, John A.; Pinero, Luis R.; Rawlin, Vincent K.; Miller, John R.; Cartier, Kevin C.; Bowers, Glen E.

1995-01-01

A 0.5-2.3 kW xenon ion propulsion system is presently being developed under the NASA Solar Electric Propulsion Technology Application Readiness (NSTAR) program. This propulsion system includes a 30 cm diameter xenon ion thruster, a Digital Control Interface Unit, a xenon feed system, and a power processing unit (PPU). The PPU consists of the power supply assemblies which operate the thruster neutralizer, main discharge chamber, and ion optics. Also included are recycle logic and a digital microcontroller. The neutralizer and discharge power supplies employ a dual use configuration which combines the functions of two power supplies into one, significantly simplifying the PPU. Further simplification was realized by implementing a single thruster control loop which regulates the beam current via the discharge current. Continuous throttling is possible over a 0.5-2.3 kW output power range. All three power supplies have been fabricated and tested with resistive loads, and have been combined into a single breadboard unit with the recycle logic and microcontroller. All line and load regulation test results show the power supplies to be within the NSTAR flight PPU specified power output of 1.98 kW. The overall efficiency of the PPU, calculated as the combined efficiencies of the power supplies and controller, at 2.3 kW delivered to resistive loads was 0.90. The component was 6.16 kg. Integration testing of the neutralizer and discharge power supplies with a functional model thruster revealed no issues with discharge ignition or steady state operation.

Long-term effects of psychosocial work stress in midlife on health functioning after labor market exit--results from the GAZEL study.

PubMed

Wahrendorf, Morten; Sembajwe, Grace; Zins, Marie; Berkman, Lisa; Goldberg, Marcel; Siegrist, Johannes

2012-07-01

To study long-term effects of psychosocial work stress in mid-life on health functioning after labor market exit using two established work stress models. In the frame of the prospective French Gazel cohort study, data on psychosocial work stress were assessed using the full questionnaires measuring the demand-control-support model (in 1997 and 1999) and the effort-reward imbalance model (in 1998). In 2007, health functioning was assessed, using the Short Form 36 mental and physical component scores. Multivariate regressions were calculated to predict health functioning in 2007, controlling for age, gender, social position, and baseline self-perceived health. Consistent effects of both work stress models and their single components on mental and physical health functioning during retirement were observed. Effects remained significant after adjustment including baseline self-perceived health. Whereas the predictive power of both work stress models was similar in the case of the physical composite score, in the case of the mental health score, values of model fit were slightly higher for the effort-reward imbalance model (R(2): 0.13) compared with the demand-control model (R²: 0.11). Findings underline the importance of working conditions in midlife not only for health in midlife but also for health functioning after labor market exit.

The decline and fall of Type II error rates

Treesearch

Steve Verrill; Mark Durst

2005-01-01

For general linear models with normally distributed random errors, the probability of a Type II error decreases exponentially as a function of sample size. This potentially rapid decline reemphasizes the importance of performing power calculations.

Gradient flow of O(N) nonlinear sigma model at large N

DOE PAGES

Aoki, Sinya; Kikuchi, Kengo; Onogi, Tetsuya

2015-04-28

Here, we study the gradient flow equation for the O(N) nonlinear sigma model in two dimensions at large N. We parameterize solution of the field at flow time t in powers of bare fields by introducing the coefficient function X n for the n-th power term (n = 1, 3, ··· ). Reducing the flow equation by keeping only the contributions at leading order in large N, we obtain a set of equations for X n ’s, which can be solved iteratively starting from n = 1. For n = 1 case, we find an explicit form of the exactmore » solution. Using this solution, we show that the two point function at finite flow time t is finite. As an application, we obtain the non-perturbative running coupling defined from the energy density. We also discuss the solution for n = 3 case.« less

Developing the Polynomial Expressions for Fields in the ITER Tokamak

NASA Astrophysics Data System (ADS)

Sharma, Stephen

2017-10-01

The two most important problems to be solved in the development of working nuclear fusion power plants are: sustained partial ignition and turbulence. These two phenomena are the subject of research and investigation through the development of analytic functions and computational models. Ansatz development through Gaussian wave-function approximations, dielectric quark models, field solutions using new elliptic functions, and better descriptions of the polynomials of the superconducting current loops are the critical theoretical developments that need to be improved. Euler-Lagrange equations of motion in addition to geodesic formulations generate the particle model which should correspond to the Dirac dispersive scattering coefficient calculations and the fluid plasma model. Feynman-Hellman formalism and Heaviside step functional forms are introduced to the fusion equations to produce simple expressions for the kinetic energy and loop currents. Conclusively, a polynomial description of the current loops, the Biot-Savart field, and the Lagrangian must be uncovered before there can be an adequate computational and iterative model of the thermonuclear plasma.

Expressions for Fields in the ITER Tokamak

NASA Astrophysics Data System (ADS)

Sharma, Stephen

2017-10-01

The two most important problems to be solved in the development of working nuclear fusion power plants are: sustained partial ignition and turbulence. These two phenomenon are the subject of research and investigation through the development of analytic functions and computational models. Ansatz development through Gaussian wave-function approximations, dielectric quark models, field solutions using new elliptic functions, and better descriptions of the polynomials of the superconducting current loops are the critical theoretical developments that need to be improved. Euler-Lagrange equations of motion in addition to geodesic formulations generate the particle model which should correspond to the Dirac dispersive scattering coefficient calculations and the fluid plasma model. Feynman-Hellman formalism and Heaviside step functional forms are introduced to the fusion equations to produce simple expressions for the kinetic energy and loop currents. Conclusively, a polynomial description of the current loops, the Biot-Savart field, and the Lagrangian must be uncovered before there can be an adequate computational and iterative model of the thermonuclear plasma.

Multivariate Heteroscedasticity Models for Functional Brain Connectivity.

PubMed

Seiler, Christof; Holmes, Susan

2017-01-01

Functional brain connectivity is the co-occurrence of brain activity in different areas during resting and while doing tasks. The data of interest are multivariate timeseries measured simultaneously across brain parcels using resting-state fMRI (rfMRI). We analyze functional connectivity using two heteroscedasticity models. Our first model is low-dimensional and scales linearly in the number of brain parcels. Our second model scales quadratically. We apply both models to data from the Human Connectome Project (HCP) comparing connectivity between short and conventional sleepers. We find stronger functional connectivity in short than conventional sleepers in brain areas consistent with previous findings. This might be due to subjects falling asleep in the scanner. Consequently, we recommend the inclusion of average sleep duration as a covariate to remove unwanted variation in rfMRI studies. A power analysis using the HCP data shows that a sample size of 40 detects 50% of the connectivity at a false discovery rate of 20%. We provide implementations using R and the probabilistic programming language Stan.

Red, Straight, no bends: primordial power spectrum reconstruction from CMB and large-scale structure

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

Ravenni, Andrea; Verde, Licia; Cuesta, Antonio J., E-mail: andrea.ravenni@pd.infn.it, E-mail: liciaverde@icc.ub.edu, E-mail: ajcuesta@icc.ub.edu

2016-08-01

We present a minimally parametric, model independent reconstruction of the shape of the primordial power spectrum. Our smoothing spline technique is well-suited to search for smooth features such as deviations from scale invariance, and deviations from a power law such as running of the spectral index or small-scale power suppression. We use a comprehensive set of the state-of the art cosmological data: Planck observations of the temperature and polarisation anisotropies of the cosmic microwave background, WiggleZ and Sloan Digital Sky Survey Data Release 7 galaxy power spectra and the Canada-France-Hawaii Lensing Survey correlation function. This reconstruction strongly supports the evidencemore » for a power law primordial power spectrum with a red tilt and disfavours deviations from a power law power spectrum including small-scale power suppression such as that induced by significantly massive neutrinos. This offers a powerful confirmation of the inflationary paradigm, justifying the adoption of the inflationary prior in cosmological analyses.« less

Red, Straight, no bends: primordial power spectrum reconstruction from CMB and large-scale structure

NASA Astrophysics Data System (ADS)

Ravenni, Andrea; Verde, Licia; Cuesta, Antonio J.

2016-08-01

We present a minimally parametric, model independent reconstruction of the shape of the primordial power spectrum. Our smoothing spline technique is well-suited to search for smooth features such as deviations from scale invariance, and deviations from a power law such as running of the spectral index or small-scale power suppression. We use a comprehensive set of the state-of the art cosmological data: Planck observations of the temperature and polarisation anisotropies of the cosmic microwave background, WiggleZ and Sloan Digital Sky Survey Data Release 7 galaxy power spectra and the Canada-France-Hawaii Lensing Survey correlation function. This reconstruction strongly supports the evidence for a power law primordial power spectrum with a red tilt and disfavours deviations from a power law power spectrum including small-scale power suppression such as that induced by significantly massive neutrinos. This offers a powerful confirmation of the inflationary paradigm, justifying the adoption of the inflationary prior in cosmological analyses.

Intertemporal consumption with directly measured welfare functions and subjective expectations

PubMed Central

Kapteyn, Arie; Kleinjans, Kristin J.; van Soest, Arthur

2010-01-01

Euler equation estimation of intertemporal consumption models requires many, often unverifiable assumptions. These include assumptions on expectations and preferences. We aim at reducing some of these requirements by using direct subjective information on respondents’ preferences and expectations. The results suggest that individually measured welfare functions and expectations have predictive power for the variation in consumption across households. Furthermore, estimates of the intertemporal elasticity of substitution based on the estimated welfare functions are plausible and of a similar order of magnitude as other estimates found in the literature. The model favored by the data only requires cross-section data for estimation. PMID:20442798

Using the Drosophila Nephrocyte to Model Podocyte Function and Disease

PubMed Central

Helmstädter, Martin; Huber, Tobias B.; Hermle, Tobias

2017-01-01

Glomerular disorders are a major cause of end-stage renal disease and effective therapies are often lacking. Nephrocytes are considered to be part of the Drosophila excretory system and form slit diaphragms across cellular membrane invaginations. Nehphrocytes have been shown to share functional, morphological, and molecular features with podocytes, which form the glomerular filter in vertebrates. Here, we report the progress and the evolving tool-set of this model system. Combining a functional, accessible slit diaphragm with the power of the genetic tool-kit in Drosophila, the nephrocyte has the potential to greatly advance our understanding of the glomerular filtration barrier in health and disease. PMID:29270398

Double Parton Fragmentation Function and its Evolution in Quarkonium Production

NASA Astrophysics Data System (ADS)

Kang, Zhong-Bo

2014-01-01

We summarize the results of a recent study on a new perturbative QCD factorization formalism for the production of heavy quarkonia of large transverse momentum pT at collider energies. Such a new factorization formalism includes both the leading power (LP) and next-to-leading power (NLP) contributions to the cross section in the mQ2/p_T^2 expansion for heavy quark mass mQ. For the NLP contribution, the so-called double parton fragmentation functions are involved, whose evolution equations have been derived. We estimate fragmentation functions in the non-relativistic QCD formalism, and found that their contribution reproduce the bulk of the large enhancement found in explicit NLO calculations in the color singlet model. Heavy quarkonia produced from NLP channels prefer longitudinal polarization, in contrast to the single parton fragmentation function. This might shed some light on the heavy quarkonium polarization puzzle.

Implications of Transitioning from De Facto to Engineered Water Reuse for Power Plant Cooling.

PubMed

Barker, Zachary A; Stillwell, Ashlynn S

2016-05-17

Thermoelectric power plants demand large quantities of cooling water, and can use alternative sources like treated wastewater (reclaimed water); however, such alternatives generate many uncertainties. De facto water reuse, or the incidental presence of wastewater effluent in a water source, is common at power plants, representing baseline conditions. In many cases, power plants would retrofit open-loop systems to cooling towers to use reclaimed water. To evaluate the feasibility of reclaimed water use, we compared hydrologic and economic conditions at power plants under three scenarios: quantified de facto reuse, de facto reuse with cooling tower retrofits, and modeled engineered reuse conditions. We created a genetic algorithm to estimate costs and model optimal conditions. To assess power plant performance, we evaluated reliability metrics for thermal variances and generation capacity loss as a function of water temperature. Applying our analysis to the greater Chicago area, we observed high de facto reuse for some power plants and substantial costs for retrofitting to use reclaimed water. Conversely, the gains in reliability and performance through engineered reuse with cooling towers outweighed the energy investment in reclaimed water pumping. Our analysis yields quantitative results of reclaimed water feasibility and can inform sustainable management of water and energy.

Prediction of a Francis turbine prototype full load instability from investigations on the reduced scale model

NASA Astrophysics Data System (ADS)

Alligné, S.; Maruzewski, P.; Dinh, T.; Wang, B.; Fedorov, A.; Iosfin, J.; Avellan, F.

2010-08-01

The growing development of renewable energies combined with the process of privatization, lead to a change of economical energy market strategies. Instantaneous pricings of electricity as a function of demand or predictions, induces profitable peak productions which are mainly covered by hydroelectric power plants. Therefore, operators harness more hydroelectric facilities at full load operating conditions. However, the Francis Turbine features an axi-symmetric rope leaving the runner which may act under certain conditions as an internal energy source leading to instability. Undesired power and pressure fluctuations are induced which may limit the maximum available power output. BC Hydro experiences such constraints in a hydroelectric power plant consisting of four 435 MW Francis Turbine generating units, which is located in Canada's province of British Columbia. Under specific full load operating conditions, one unit experiences power and pressure fluctuations at 0.46 Hz. The aim of the paper is to present a methodology allowing prediction of this prototype's instability frequency from investigations on the reduced scale model. A new hydro acoustic vortex rope model has been developed in SIMSEN software, taking into account the energy dissipation due to the thermodynamic exchange between the gas and the surrounding liquid. A combination of measurements, CFD simulations and computation of eigenmodes of the reduced scale model installed on test rig, allows the accurate calibration of the vortex rope model parameters at the model scale. Then, transposition of parameters to the prototype according to similitude laws is applied and stability analysis of the power plant is performed. The eigenfrequency of 0.39 Hz related to the first eigenmode of the power plant is determined to be unstable. Predicted frequency of the full load power and pressure fluctuations at the unit unstable operating point is found to be in general agreement with the prototype measurements.

Interactions between different EEG frequency bands and their effect on alpha-fMRI correlations.

PubMed

de Munck, J C; Gonçalves, S I; Mammoliti, R; Heethaar, R M; Lopes da Silva, F H

2009-08-01

In EEG/fMRI correlation studies it is common to consider the fMRI BOLD as filtered version of the EEG alpha power. Here the question is addressed whether other EEG frequency components may affect the correlation between alpha and BOLD. This was done comparing the statistical parametric maps (SPMs) of three different filter models wherein either the free or the standard hemodynamic response functions (HRF) were used in combination with the full spectral bandwidth of the EEG. EEG and fMRI were co-registered in a 30 min resting state condition in 15 healthy young subjects. Power variations in the delta, theta, alpha, beta and gamma bands were extracted from the EEG and used as regressors in a general linear model. Statistical parametric maps (SPMs) were computed using three different filter models, wherein either the free or the standard hemodynamic response functions (HRF) were used in combination with the full spectral bandwidth of the EEG. Results show that the SPMs of different EEG frequency bands, when significant, are very similar to that of the alpha rhythm. This is true in particular for the beta band, despite the fact that the alpha harmonics were discarded. It is shown that inclusion of EEG frequency bands as confounder in the fMRI-alpha correlation model has a large effect on the resulting SPM, in particular when for each frequency band the HRF is extracted from the data. We conclude that power fluctuations of different EEG frequency bands are mutually highly correlated, and that a multi frequency model is required to extract the SPM of the frequency of interest from EEG/fMRI data. When no constraints are put on the shapes of the HRFs of the nuisance frequencies, the correlation model looses so much statistical power that no correlations can be detected.

Optimal Operation of Energy Storage in Power Transmission and Distribution

NASA Astrophysics Data System (ADS)

Akhavan Hejazi, Seyed Hossein

In this thesis, we investigate optimal operation of energy storage units in power transmission and distribution grids. At transmission level, we investigate the problem where an investor-owned independently-operated energy storage system seeks to offer energy and ancillary services in the day-ahead and real-time markets. We specifically consider the case where a significant portion of the power generated in the grid is from renewable energy resources and there exists significant uncertainty in system operation. In this regard, we formulate a stochastic programming framework to choose optimal energy and reserve bids for the storage units that takes into account the fluctuating nature of the market prices due to the randomness in the renewable power generation availability. At distribution level, we develop a comprehensive data set to model various stochastic factors on power distribution networks, with focus on networks that have high penetration of electric vehicle charging load and distributed renewable generation. Furthermore, we develop a data-driven stochastic model for energy storage operation at distribution level, where the distribution of nodal voltage and line power flow are modelled as stochastic functions of the energy storage unit's charge and discharge schedules. In particular, we develop new closed-form stochastic models for such key operational parameters in the system. Our approach is analytical and allows formulating tractable optimization problems. Yet, it does not involve any restricting assumption on the distribution of random parameters, hence, it results in accurate modeling of uncertainties. By considering the specific characteristics of random variables, such as their statistical dependencies and often irregularly-shaped probability distributions, we propose a non-parametric chance-constrained optimization approach to operate and plan energy storage units in power distribution girds. In the proposed stochastic optimization, we consider uncertainty from various elements, such as solar photovoltaic , electric vehicle chargers, and residential baseloads, in the form of discrete probability functions. In the last part of this thesis we address some other resources and concepts for enhancing the operation of power distribution and transmission systems. In particular, we proposed a new framework to determine the best sites, sizes, and optimal payment incentives under special contracts for committed-type DG projects to offset distribution network investment costs. In this framework, the aim is to allocate DGs such that the profit gained by the distribution company is maximized while each DG unit's individual profit is also taken into account to assure that private DG investment remains economical.

Identifying and exploiting trait-relevant tissues with multiple functional annotations in genome-wide association studies

PubMed Central

Zhang, Shujun

2018-01-01

Genome-wide association studies (GWASs) have identified many disease associated loci, the majority of which have unknown biological functions. Understanding the mechanism underlying trait associations requires identifying trait-relevant tissues and investigating associations in a trait-specific fashion. Here, we extend the widely used linear mixed model to incorporate multiple SNP functional annotations from omics studies with GWAS summary statistics to facilitate the identification of trait-relevant tissues, with which to further construct powerful association tests. Specifically, we rely on a generalized estimating equation based algorithm for parameter inference, a mixture modeling framework for trait-tissue relevance classification, and a weighted sequence kernel association test constructed based on the identified trait-relevant tissues for powerful association analysis. We refer to our analytic procedure as the Scalable Multiple Annotation integration for trait-Relevant Tissue identification and usage (SMART). With extensive simulations, we show how our method can make use of multiple complementary annotations to improve the accuracy for identifying trait-relevant tissues. In addition, our procedure allows us to make use of the inferred trait-relevant tissues, for the first time, to construct more powerful SNP set tests. We apply our method for an in-depth analysis of 43 traits from 28 GWASs using tissue-specific annotations in 105 tissues derived from ENCODE and Roadmap. Our results reveal new trait-tissue relevance, pinpoint important annotations that are informative of trait-tissue relationship, and illustrate how we can use the inferred trait-relevant tissues to construct more powerful association tests in the Wellcome trust case control consortium study. PMID:29377896

Unscheduled load flow effect due to large variation in the distributed generation in a subtransmission network

NASA Astrophysics Data System (ADS)

Islam, Mujahidul

A sustainable energy delivery infrastructure implies the safe and reliable accommodation of large scale penetration of renewable sources in the power grid. In this dissertation it is assumed there will be no significant change in the power transmission and distribution structure currently in place; except in the operating strategy and regulatory policy. That is to say, with the same old structure, the path towards unveiling a high penetration of switching power converters in the power system will be challenging. Some of the dimensions of this challenge are power quality degradation, frequent false trips due to power system imbalance, and losses due to a large neutral current. The ultimate result is the reduced life of many power distribution components - transformers, switches and sophisticated loads. Numerous ancillary services are being developed and offered by the utility operators to mitigate these problems. These services will likely raise the system's operational cost, not only from the utility operators' end, but also reflected on the Independent System Operators and by the Regional Transmission Operators (RTO) due to an unforeseen backlash of frequent variation in the load-side generation or distributed generation. The North American transmission grid is an interconnected system similar to a large electrical circuit. This circuit was not planned but designed over 100 years. The natural laws of physics govern the power flow among loads and generators except where control mechanisms are installed. The control mechanism has not matured enough to withstand the high penetration of variable generators at uncontrolled distribution ends. Unlike a radial distribution system, mesh or loop networks can alleviate complex channels for real and reactive power flow. Significant variation in real power injection and absorption on the distribution side can emerge as a bias signal on the routing reactive power in some physical links or channels that are not distinguishable from the vast network. A path tracing methodology is developed to identify the power lines that are vulnerable to an unscheduled flow effect in the sub-transmission network. It is much harder to aggregate power system network sensitivity information or data from measuring load flow physically than to simulate in software. System dynamics is one of the key factors to determine an appropriate dynamic control mechanism at an optimum network location. Once a model of deterministic but variable power generator is used, the simulation can be meaningful in justifying this claim. The method used to model the variable generator is named the two-components phase distortion model. The model was validated from the high resolution data collected from three pilot photovoltaic sites in Florida - two in the city of St. Petersburg and one in the city of Tampa. The high resolution data was correlated with weather radar closest to the sites during the design stage of the model. Technically the deterministic model cannot replicate a stochastic model which is more realistically applicable for solar isolation and involves a Markov chain. The author justified the proposition based on the fact that for analysis of the response functions of different systems, the excitation function should be common for comparison. Moreover, there could be many possible simulation scenarios but fewer worst cases. Almost all commercial systems are protected against potential faults and contingencies to a certain extent. Hence, the proposed model for worst case studies was designed within a reasonable limit. The simulation includes steady state and transient mode using multiple software modules including MatlabRTM, PSCADRTM and Paladin Design BaseRTM. It is shown that by identifying vulnerable or sensitive branches in the network, the control mechanisms can be coordinated reliably. In the long run this can save money by preventing unscheduled power flow in the network and eventually stabilizing the energy market.

Fixed-speed and Variable-speed Pumped Storage Dispatch Model in Power Systems with High Renewable Penetration

NASA Astrophysics Data System (ADS)

Yuan, Bo; Zong, Jin; Xu, Zhicheng

2018-06-01

According to different operating characteristics of pumped storage fixed speed unit and variable speed unit, a joint dispatching model of pumped storage unit and other types of units based on mixed integer linear optimization is constructed. The model takes into account the operating conditions, reservoir capacity, cycle type and other pumped storage unit constraints, but also consider the frequent start and stop and the stability of the operation of the unit caused by the loss. Using the Cplex solver to solve the model, the empirical example of the provincial power grid shows that the model can effectively arrange the pumping storage speed and the dispatching operation of the variable speed unit under the precondition of economic life of the unit, and give full play to the function of peak shaving and accommodating new energy. Because of its more flexible regulation characteristics of power generation and pumping conditions, the variable speed unit can better improve the operating conditions of other units in the system and promote the new energy dissipation.

Light extraction in planar light-emitting diode with nonuniform current injection: model and simulation.

PubMed

Khmyrova, Irina; Watanabe, Norikazu; Kholopova, Julia; Kovalchuk, Anatoly; Shapoval, Sergei

2014-07-20

We develop an analytical and numerical model for performing simulation of light extraction through the planar output interface of the light-emitting diodes (LEDs) with nonuniform current injection. Spatial nonuniformity of injected current is a peculiar feature of the LEDs in which top metal electrode is patterned as a mesh in order to enhance the output power of light extracted through the top surface. Basic features of the model are the bi-plane computation domain, related to other areas of numerical grid (NG) cells in these two planes, representation of light-generating layer by an ensemble of point light sources, numerical "collection" of light photons from the area limited by acceptance circle and adjustment of NG-cell areas in the computation procedure by the angle-tuned aperture function. The developed model and procedure are used to simulate spatial distributions of the output optical power as well as the total output power at different mesh pitches. The proposed model and simulation strategy can be very efficient in evaluation of the output optical performance of LEDs with periodical or symmetrical configuration of the electrodes.