NASA Workshop on Distributed Parameter Modeling and Control of Flexible Aerospace Systems

NASA Technical Reports Server (NTRS)

Marks, Virginia B. (Compiler); Keckler, Claude R. (Compiler)

1994-01-01

Although significant advances have been made in modeling and controlling flexible systems, there remains a need for improvements in model accuracy and in control performance. The finite element models of flexible systems are unduly complex and are almost intractable to optimum parameter estimation for refinement using experimental data. Distributed parameter or continuum modeling offers some advantages and some challenges in both modeling and control. Continuum models often result in a significantly reduced number of model parameters, thereby enabling optimum parameter estimation. The dynamic equations of motion of continuum models provide the advantage of allowing the embedding of the control system dynamics, thus forming a complete set of system dynamics. There is also increased insight provided by the continuum model approach.

A short-term and high-resolution distribution system load forecasting approach using support vector regression with hybrid parameters optimization

DOE PAGES

Jiang, Huaiguang; Zhang, Yingchen; Muljadi, Eduard; ...

2016-01-01

This paper proposes an approach for distribution system load forecasting, which aims to provide highly accurate short-term load forecasting with high resolution utilizing a support vector regression (SVR) based forecaster and a two-step hybrid parameters optimization method. Specifically, because the load profiles in distribution systems contain abrupt deviations, a data normalization is designed as the pretreatment for the collected historical load data. Then an SVR model is trained by the load data to forecast the future load. For better performance of SVR, a two-step hybrid optimization algorithm is proposed to determine the best parameters. In the first step of themore » hybrid optimization algorithm, a designed grid traverse algorithm (GTA) is used to narrow the parameters searching area from a global to local space. In the second step, based on the result of the GTA, particle swarm optimization (PSO) is used to determine the best parameters in the local parameter space. After the best parameters are determined, the SVR model is used to forecast the short-term load deviation in the distribution system. The performance of the proposed approach is compared to some classic methods in later sections of the paper.« less

A Short-Term and High-Resolution System Load Forecasting Approach Using Support Vector Regression with Hybrid Parameters Optimization

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

Jiang, Huaiguang

This work proposes an approach for distribution system load forecasting, which aims to provide highly accurate short-term load forecasting with high resolution utilizing a support vector regression (SVR) based forecaster and a two-step hybrid parameters optimization method. Specifically, because the load profiles in distribution systems contain abrupt deviations, a data normalization is designed as the pretreatment for the collected historical load data. Then an SVR model is trained by the load data to forecast the future load. For better performance of SVR, a two-step hybrid optimization algorithm is proposed to determine the best parameters. In the first step of themore » hybrid optimization algorithm, a designed grid traverse algorithm (GTA) is used to narrow the parameters searching area from a global to local space. In the second step, based on the result of the GTA, particle swarm optimization (PSO) is used to determine the best parameters in the local parameter space. After the best parameters are determined, the SVR model is used to forecast the short-term load deviation in the distribution system.« less

Distributed weighted least-squares estimation with fast convergence for large-scale systems☆

PubMed Central

Marelli, Damián Edgardo; Fu, Minyue

2015-01-01

In this paper we study a distributed weighted least-squares estimation problem for a large-scale system consisting of a network of interconnected sub-systems. Each sub-system is concerned with a subset of the unknown parameters and has a measurement linear in the unknown parameters with additive noise. The distributed estimation task is for each sub-system to compute the globally optimal estimate of its own parameters using its own measurement and information shared with the network through neighborhood communication. We first provide a fully distributed iterative algorithm to asymptotically compute the global optimal estimate. The convergence rate of the algorithm will be maximized using a scaling parameter and a preconditioning method. This algorithm works for a general network. For a network without loops, we also provide a different iterative algorithm to compute the global optimal estimate which converges in a finite number of steps. We include numerical experiments to illustrate the performances of the proposed methods. PMID:25641976

Factorization and reduction methods for optimal control of distributed parameter systems

NASA Technical Reports Server (NTRS)

Burns, J. A.; Powers, R. K.

1985-01-01

A Chandrasekhar-type factorization method is applied to the linear-quadratic optimal control problem for distributed parameter systems. An aeroelastic control problem is used as a model example to demonstrate that if computationally efficient algorithms, such as those of Chandrasekhar-type, are combined with the special structure often available to a particular problem, then an abstract approximation theory developed for distributed parameter control theory becomes a viable method of solution. A numerical scheme based on averaging approximations is applied to hereditary control problems. Numerical examples are given.

Wall Shear Stress Distribution in a Patient-Specific Cerebral Aneurysm Model using Reduced Order Modeling

NASA Astrophysics Data System (ADS)

Han, Suyue; Chang, Gary Han; Schirmer, Clemens; Modarres-Sadeghi, Yahya

2016-11-01

We construct a reduced-order model (ROM) to study the Wall Shear Stress (WSS) distributions in image-based patient-specific aneurysms models. The magnitude of WSS has been shown to be a critical factor in growth and rupture of human aneurysms. We start the process by running a training case using Computational Fluid Dynamics (CFD) simulation with time-varying flow parameters, such that these parameters cover the range of parameters of interest. The method of snapshot Proper Orthogonal Decomposition (POD) is utilized to construct the reduced-order bases using the training CFD simulation. The resulting ROM enables us to study the flow patterns and the WSS distributions over a range of system parameters computationally very efficiently with a relatively small number of modes. This enables comprehensive analysis of the model system across a range of physiological conditions without the need to re-compute the simulation for small changes in the system parameters.

Robust automatic control system of vessel descent-rise device for plant with distributed parameters “cable – towed underwater vehicle”

NASA Astrophysics Data System (ADS)

Chupina, K. V.; Kataev, E. V.; Khannanov, A. M.; Korshunov, V. N.; Sennikov, I. A.

2018-05-01

The paper is devoted to a problem of synthesis of the robust control system for a distributed parameters plant. The vessel descent-rise device has a heave compensation function for stabilization of the towed underwater vehicle on a set depth. A sea state code, parameters of the underwater vehicle and cable vary during underwater operations, the vessel heave is a stochastic process. It means that the plant and external disturbances have uncertainty. That is why it is necessary to use the robust theory for synthesis of an automatic control system, but without use of traditional methods of optimization, because this cable has distributed parameters. The offered technique has allowed one to design an effective control system for stabilization of immersion depth of the towed underwater vehicle for various degrees of sea roughness and to provide its robustness to deviations of parameters of the vehicle and cable’s length.

Injection of Contaminants into a Simulated Water Distribution System Equipped with Continuous Multi-Parameter Water Monitors

EPA Science Inventory

The U.S. EPA’s Technology Testing and Evaluation Program has been charged by EPA to evaluate the performance of commercially available water security-related technologies. Multi-parameter water monitors for distributions systems have been evaluated as such a water security techn...

Geostatistical characterisation of geothermal parameters for a thermal aquifer storage site in Germany

NASA Astrophysics Data System (ADS)

Rodrigo-Ilarri, J.; Li, T.; Grathwohl, P.; Blum, P.; Bayer, P.

2009-04-01

The design of geothermal systems such as aquifer thermal energy storage systems (ATES) must account for a comprehensive characterisation of all relevant parameters considered for the numerical design model. Hydraulic and thermal conductivities are the most relevant parameters and its distribution determines not only the technical design but also the economic viability of such systems. Hence, the knowledge of the spatial distribution of these parameters is essential for a successful design and operation of such systems. This work shows the first results obtained when applying geostatistical techniques to the characterisation of the Esseling Site in Germany. In this site a long-term thermal tracer test (> 1 year) was performed. On this open system the spatial temperature distribution inside the aquifer was observed over time in order to obtain as much information as possible that yield to a detailed characterisation both of the hydraulic and thermal relevant parameters. This poster shows the preliminary results obtained for the Esseling Site. It has been observed that the common homogeneous approach is not sufficient to explain the observations obtained from the TRT and that parameter heterogeneity must be taken into account.

Distribution of rain height over subtropical region: Durban, South Africa for satellite communication systems

NASA Astrophysics Data System (ADS)

Olurotimi, E. O.; Sokoya, O.; Ojo, J. S.; Owolawi, P. A.

2018-03-01

Rain height is one of the significant parameters for prediction of rain attenuation for Earth-space telecommunication links, especially those operating at frequencies above 10 GHz. This study examines Three-parameter Dagum distribution of the rain height over Durban, South Africa. 5-year data were used to study the monthly, seasonal, and annual variations using the parameters estimated by the maximum likelihood of the distribution. The performance estimation of the distribution was determined using the statistical goodness of fit. Three-parameter Dagum distribution shows an appropriate distribution for the modeling of rain height over Durban with the Root Mean Square Error of 0.26. Also, the shape and scale parameters for the distribution show a wide variation. The probability exceedance of time for 0.01% indicates the high probability of rain attenuation at higher frequencies.

A distributed system for fast alignment of next-generation sequencing data.

PubMed

Srimani, Jaydeep K; Wu, Po-Yen; Phan, John H; Wang, May D

2010-12-01

We developed a scalable distributed computing system using the Berkeley Open Interface for Network Computing (BOINC) to align next-generation sequencing (NGS) data quickly and accurately. NGS technology is emerging as a promising platform for gene expression analysis due to its high sensitivity compared to traditional genomic microarray technology. However, despite the benefits, NGS datasets can be prohibitively large, requiring significant computing resources to obtain sequence alignment results. Moreover, as the data and alignment algorithms become more prevalent, it will become necessary to examine the effect of the multitude of alignment parameters on various NGS systems. We validate the distributed software system by (1) computing simple timing results to show the speed-up gained by using multiple computers, (2) optimizing alignment parameters using simulated NGS data, and (3) computing NGS expression levels for a single biological sample using optimal parameters and comparing these expression levels to that of a microarray sample. Results indicate that the distributed alignment system achieves approximately a linear speed-up and correctly distributes sequence data to and gathers alignment results from multiple compute clients.

Proceedings of the Workshop on Applications of Distributed System Theory to the Control of Large Space Structures

NASA Technical Reports Server (NTRS)

Rodriguez, G. (Editor)

1983-01-01

Two general themes in the control of large space structures are addressed: control theory for distributed parameter systems and distributed control for systems requiring spatially-distributed multipoint sensing and actuation. Topics include modeling and control, stabilization, and estimation and identification.

Control of Groundwater Remediation Process as Distributed Parameter System

NASA Astrophysics Data System (ADS)

Mendel, M.; Kovács, T.; Hulkó, G.

2014-12-01

Pollution of groundwater requires the implementation of appropriate solutions which can be deployed for several years. The case of local groundwater contamination and its subsequent spread may result in contamination of drinking water sources or other disasters. This publication aims to design and demonstrate control of pumping wells for a model task of groundwater remediation. The task consists of appropriately spaced soil with input parameters, pumping wells and control system. Model of controlled system is made in the program MODFLOW using the finitedifference method as distributed parameter system. Control problem is solved by DPS Blockset for MATLAB & Simulink.

Computational methods for the control of distributed parameter systems

NASA Technical Reports Server (NTRS)

Burns, J. A.; Cliff, E. M.; Powers, R. K.

1985-01-01

It is shown that care must be taken to ensure that finite dimensional approximations of distributed parameter systems preserve important system properties (i.e., controllability, observability, stabilizability, detectability, etc.). It is noted that, if the particular scheme used to construct the finite dimensional model does not take into account these system properties, the model may not be suitable for control design and analysis. These ideas are illustrated by a simple example, i.e., a cable-spring-mass system.

A fuzzy discrete harmony search algorithm applied to annual cost reduction in radial distribution systems

NASA Astrophysics Data System (ADS)

Ameli, Kazem; Alfi, Alireza; Aghaebrahimi, Mohammadreza

2016-09-01

Similarly to other optimization algorithms, harmony search (HS) is quite sensitive to the tuning parameters. Several variants of the HS algorithm have been developed to decrease the parameter-dependency character of HS. This article proposes a novel version of the discrete harmony search (DHS) algorithm, namely fuzzy discrete harmony search (FDHS), for optimizing capacitor placement in distribution systems. In the FDHS, a fuzzy system is employed to dynamically adjust two parameter values, i.e. harmony memory considering rate and pitch adjusting rate, with respect to normalized mean fitness of the harmony memory. The key aspect of FDHS is that it needs substantially fewer iterations to reach convergence in comparison with classical discrete harmony search (CDHS). To the authors' knowledge, this is the first application of DHS to specify appropriate capacitor locations and their best amounts in the distribution systems. Simulations are provided for 10-, 34-, 85- and 141-bus distribution systems using CDHS and FDHS. The results show the effectiveness of FDHS over previous related studies.

A unified framework for approximation in inverse problems for distributed parameter systems

NASA Technical Reports Server (NTRS)

Banks, H. T.; Ito, K.

1988-01-01

A theoretical framework is presented that can be used to treat approximation techniques for very general classes of parameter estimation problems involving distributed systems that are either first or second order in time. Using the approach developed, one can obtain both convergence and stability (continuous dependence of parameter estimates with respect to the observations) under very weak regularity and compactness assumptions on the set of admissible parameters. This unified theory can be used for many problems found in the recent literature and in many cases offers significant improvements to existing results.

Considering inventory distributions in a stochastic periodic inventory routing system

NASA Astrophysics Data System (ADS)

Yadollahi, Ehsan; Aghezzaf, El-Houssaine

2017-07-01

Dealing with the stochasticity of parameters is one of the critical issues in business and industry nowadays. Supply chain planners have difficulties in forecasting stochastic parameters of a distribution system. Demand rates of customers during their lead time are one of these parameters. In addition, holding a huge level of inventory at the retailers is costly and inefficient. To cover the uncertainty of forecasting demand rates, researchers have proposed the usage of safety stock to avoid stock-out. However, finding the precise level of safety stock depends on forecasting the statistical distribution of demand rates and their variations in different settings among the planning horizon. In this paper the demand rate distributions and its parameters are taken into account for each time period in a stochastic periodic IRP. An analysis of the achieved statistical distribution of the inventory and safety stock level is provided to measure the effects of input parameters on the output indicators. Different values for coefficient of variation are applied to the customers' demand rate in the optimization model. The outcome of the deterministic equivalent model of SPIRP is simulated in form of an illustrative case.

Study of the zinc-silver oxide battery system

NASA Technical Reports Server (NTRS)

Nanis, L.

1973-01-01

Theoretical and experimental models for the evaluation of current distribution in flooded, porous electrodes are discussed. An approximation for the local current distribution function was derived for conditions of a linear overpotential, a uniform concentration, and a very conductive matrix. By considering the porous electrode to be an analog of chemical catalyst structures, a dimensionless performance parameter was derived from the approximated current distribution function. In this manner the electrode behavior was characterized in terms of an electrochemical Thiele parameter and an effectiveness factor. It was shown that the electrochemical engineering approach makes possible the organizations of theoretical descriptions and of practical experience in the form of dimensionless parameters, such as the electrochemical Thiele parameters, and hence provides useful information for the design of new electrochemical systems.

Advances in parameter estimation techniques applied to flexible structures

NASA Technical Reports Server (NTRS)

Maben, Egbert; Zimmerman, David C.

1994-01-01

In this work, various parameter estimation techniques are investigated in the context of structural system identification utilizing distributed parameter models and 'measured' time-domain data. Distributed parameter models are formulated using the PDEMOD software developed by Taylor. Enhancements made to PDEMOD for this work include the following: (1) a Wittrick-Williams based root solving algorithm; (2) a time simulation capability; and (3) various parameter estimation algorithms. The parameter estimations schemes will be contrasted using the NASA Mini-Mast as the focus structure.

Chandrasekhar equations and computational algorithms for distributed parameter systems

NASA Technical Reports Server (NTRS)

Burns, J. A.; Ito, K.; Powers, R. K.

1984-01-01

The Chandrasekhar equations arising in optimal control problems for linear distributed parameter systems are considered. The equations are derived via approximation theory. This approach is used to obtain existence, uniqueness, and strong differentiability of the solutions and provides the basis for a convergent computation scheme for approximating feedback gain operators. A numerical example is presented to illustrate these ideas.

Reliability measurement for mixed mode failures of 33/11 kilovolt electric power distribution stations.

PubMed

Alwan, Faris M; Baharum, Adam; Hassan, Geehan S

2013-01-01

The reliability of the electrical distribution system is a contemporary research field due to diverse applications of electricity in everyday life and diverse industries. However a few research papers exist in literature. This paper proposes a methodology for assessing the reliability of 33/11 Kilovolt high-power stations based on average time between failures. The objective of this paper is to find the optimal fit for the failure data via time between failures. We determine the parameter estimation for all components of the station. We also estimate the reliability value of each component and the reliability value of the system as a whole. The best fitting distribution for the time between failures is a three parameter Dagum distribution with a scale parameter [Formula: see text] and shape parameters [Formula: see text] and [Formula: see text]. Our analysis reveals that the reliability value decreased by 38.2% in each 30 days. We believe that the current paper is the first to address this issue and its analysis. Thus, the results obtained in this research reflect its originality. We also suggest the practicality of using these results for power systems for both the maintenance of power systems models and preventive maintenance models.

Reliability Measurement for Mixed Mode Failures of 33/11 Kilovolt Electric Power Distribution Stations

PubMed Central

Alwan, Faris M.; Baharum, Adam; Hassan, Geehan S.

2013-01-01

The reliability of the electrical distribution system is a contemporary research field due to diverse applications of electricity in everyday life and diverse industries. However a few research papers exist in literature. This paper proposes a methodology for assessing the reliability of 33/11 Kilovolt high-power stations based on average time between failures. The objective of this paper is to find the optimal fit for the failure data via time between failures. We determine the parameter estimation for all components of the station. We also estimate the reliability value of each component and the reliability value of the system as a whole. The best fitting distribution for the time between failures is a three parameter Dagum distribution with a scale parameter and shape parameters and . Our analysis reveals that the reliability value decreased by 38.2% in each 30 days. We believe that the current paper is the first to address this issue and its analysis. Thus, the results obtained in this research reflect its originality. We also suggest the practicality of using these results for power systems for both the maintenance of power systems models and preventive maintenance models. PMID:23936346

Characterizing and Optimizing Photocathode Laser Distributions for Ultra-low Emittance Electron Beam Operations

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

Zhou, F.; Bohler, D.; Ding, Y.

2015-12-07

Photocathode RF gun has been widely used for generation of high-brightness electron beams for many different applications. We found that the drive laser distributions in such RF guns play important roles in minimizing the electron beam emittance. Characterizing the laser distributions with measurable parameters and optimizing beam emittance versus the laser distribution parameters in both spatial and temporal directions are highly desired for high-brightness electron beam operation. In this paper, we report systematic measurements and simulations of emittance dependence on the measurable parameters represented for spatial and temporal laser distributions at the photocathode RF gun systems of Linac Coherent Lightmore » Source. The tolerable parameter ranges for photocathode drive laser distributions in both directions are presented for ultra-low emittance beam operations.« less

Compounding approach for univariate time series with nonstationary variances

NASA Astrophysics Data System (ADS)

Schäfer, Rudi; Barkhofen, Sonja; Guhr, Thomas; Stöckmann, Hans-Jürgen; Kuhl, Ulrich

2015-12-01

A defining feature of nonstationary systems is the time dependence of their statistical parameters. Measured time series may exhibit Gaussian statistics on short time horizons, due to the central limit theorem. The sample statistics for long time horizons, however, averages over the time-dependent variances. To model the long-term statistical behavior, we compound the local distribution with the distribution of its parameters. Here, we consider two concrete, but diverse, examples of such nonstationary systems: the turbulent air flow of a fan and a time series of foreign exchange rates. Our main focus is to empirically determine the appropriate parameter distribution for the compounding approach. To this end, we extract the relevant time scales by decomposing the time signals into windows and determine the distribution function of the thus obtained local variances.

Compounding approach for univariate time series with nonstationary variances.

PubMed

Schäfer, Rudi; Barkhofen, Sonja; Guhr, Thomas; Stöckmann, Hans-Jürgen; Kuhl, Ulrich

2015-12-01

A defining feature of nonstationary systems is the time dependence of their statistical parameters. Measured time series may exhibit Gaussian statistics on short time horizons, due to the central limit theorem. The sample statistics for long time horizons, however, averages over the time-dependent variances. To model the long-term statistical behavior, we compound the local distribution with the distribution of its parameters. Here, we consider two concrete, but diverse, examples of such nonstationary systems: the turbulent air flow of a fan and a time series of foreign exchange rates. Our main focus is to empirically determine the appropriate parameter distribution for the compounding approach. To this end, we extract the relevant time scales by decomposing the time signals into windows and determine the distribution function of the thus obtained local variances.

Derivation of hydrous pyrolysis kinetic parameters from open-system pyrolysis

NASA Astrophysics Data System (ADS)

Tseng, Yu-Hsin; Huang, Wuu-Liang

2010-05-01

Kinetic information is essential to predict the temperature, timing or depth of hydrocarbon generation within a hydrocarbon system. The most common experiments for deriving kinetic parameters are mainly by open-system pyrolysis. However, it has been shown that the conditions of open-system pyrolysis are deviant from nature by its low near-ambient pressure and high temperatures. Also, the extrapolation of heating rates in open-system pyrolysis to geological conditions may be questionable. Recent study of Lewan and Ruble shows hydrous-pyrolysis conditions can simulate the natural conditions better and its applications are supported by two case studies with natural thermal-burial histories. Nevertheless, performing hydrous pyrolysis experiment is really tedious and requires large amount of sample, while open-system pyrolysis is rather convenient and efficient. Therefore, the present study aims at the derivation of convincing distributed hydrous pyrolysis Ea with only routine open-system Rock-Eval data. Our results unveil that there is a good correlation between open-system Rock-Eval parameter Tmax and the activation energy (Ea) derived from hydrous pyrolysis. The hydrous pyrolysis single Ea can be predicted from Tmax based on the correlation, while the frequency factor (A0) is estimated based on the linear relationship between single Ea and log A0. Because the Ea distribution is more rational than single Ea, we modify the predicted single hydrous pyrolysis Ea into distributed Ea by shifting the pattern of Ea distribution from open-system pyrolysis until the weight mean Ea distribution equals to the single hydrous pyrolysis Ea. Moreover, it has been shown that the shape of the Ea distribution is very much alike the shape of Tmax curve. Thus, in case of the absence of open-system Ea distribution, we may use the shape of Tmax curve to get the distributed hydrous pyrolysis Ea. The study offers a new approach as a simple method for obtaining distributed hydrous pyrolysis Ea with only routine open-system Rock-Eval data, which will allow for better estimating hydrocarbon generation.

A Bayesian approach to identifying structural nonlinearity using free-decay response: Application to damage detection in composites

USGS Publications Warehouse

Nichols, J.M.; Link, W.A.; Murphy, K.D.; Olson, C.C.

2010-01-01

This work discusses a Bayesian approach to approximating the distribution of parameters governing nonlinear structural systems. Specifically, we use a Markov Chain Monte Carlo method for sampling the posterior parameter distributions thus producing both point and interval estimates for parameters. The method is first used to identify both linear and nonlinear parameters in a multiple degree-of-freedom structural systems using free-decay vibrations. The approach is then applied to the problem of identifying the location, size, and depth of delamination in a model composite beam. The influence of additive Gaussian noise on the response data is explored with respect to the quality of the resulting parameter estimates.

Made-to-measure modelling of observed galaxy dynamics

NASA Astrophysics Data System (ADS)

Bovy, Jo; Kawata, Daisuke; Hunt, Jason A. S.

2018-01-01

Amongst dynamical modelling techniques, the made-to-measure (M2M) method for modelling steady-state systems is amongst the most flexible, allowing non-parametric distribution functions in complex gravitational potentials to be modelled efficiently using N-body particles. Here, we propose and test various improvements to the standard M2M method for modelling observed data, illustrated using the simple set-up of a one-dimensional harmonic oscillator. We demonstrate that nuisance parameters describing the modelled system's orientation with respect to the observer - e.g. an external galaxy's inclination or the Sun's position in the Milky Way - as well as the parameters of an external gravitational field can be optimized simultaneously with the particle weights. We develop a method for sampling from the high-dimensional uncertainty distribution of the particle weights. We combine this in a Gibbs sampler with samplers for the nuisance and potential parameters to explore the uncertainty distribution of the full set of parameters. We illustrate our M2M improvements by modelling the vertical density and kinematics of F-type stars in Gaia DR1. The novel M2M method proposed here allows full probabilistic modelling of steady-state dynamical systems, allowing uncertainties on the non-parametric distribution function and on nuisance parameters to be taken into account when constraining the dark and baryonic masses of stellar systems.

Electrical Distribution System (EDS) and Caution and Warning System (CWS)

NASA Technical Reports Server (NTRS)

Mcclung, T.

1975-01-01

An astronaut caution and warning system is described which monitors various life support system parameters and detects out-of-range parameter conditions. The warning system generates a warning tone and displays the malfunction condition to the astronaut along with the proper corrective procedures required.

Bluetooth-based distributed measurement system

NASA Astrophysics Data System (ADS)

Tang, Baoping; Chen, Zhuo; Wei, Yuguo; Qin, Xiaofeng

2007-07-01

A novel distributed wireless measurement system, which is consisted of a base station, wireless intelligent sensors and relay nodes etc, is established by combining of Bluetooth-based wireless transmission, virtual instrument, intelligent sensor, and network. The intelligent sensors mounted on the equipments to be measured acquire various parameters and the Bluetooth relay nodes get the acquired data modulated and sent to the base station, where data analysis and processing are done so that the operational condition of the equipment can be evaluated. The establishment of the distributed measurement system is discussed with a measurement flow chart for the distributed measurement system based on Bluetooth technology, and the advantages and disadvantages of the system are analyzed at the end of the paper and the measurement system has successfully been used in Daqing oilfield, China for measurement of parameters, such as temperature, flow rate and oil pressure at an electromotor-pump unit.

Control of complex dynamics and chaos in distributed parameter systems

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

Chakravarti, S.; Marek, M.; Ray, W.H.

This paper discusses a methodology for controlling complex dynamics and chaos in distributed parameter systems. The reaction-diffusion system with Brusselator kinetics, where the torus-doubling or quasi-periodic (two characteristic incommensurate frequencies) route to chaos exists in a defined range of parameter values, is used as an example. Poincare maps are used for characterization of quasi-periodic and chaotic attractors. The dominant modes or topos, which are inherent properties of the system, are identified by means of the Singular Value Decomposition. Tested modal feedback control schemas based on identified dominant spatial modes confirm the possibility of stabilization of simple quasi-periodic trajectories in themore » complex quasi-periodic or chaotic spatiotemporal patterns.« less

Volcanic Ash Data Assimilation System for Atmospheric Transport Model

NASA Astrophysics Data System (ADS)

Ishii, K.; Shimbori, T.; Sato, E.; Tokumoto, T.; Hayashi, Y.; Hashimoto, A.

2017-12-01

The Japan Meteorological Agency (JMA) has two operations for volcanic ash forecasts, which are Volcanic Ash Fall Forecast (VAFF) and Volcanic Ash Advisory (VAA). In these operations, the forecasts are calculated by atmospheric transport models including the advection process, the turbulent diffusion process, the gravitational fall process and the deposition process (wet/dry). The initial distribution of volcanic ash in the models is the most important but uncertain factor. In operations, the model of Suzuki (1983) with many empirical assumptions is adopted to the initial distribution. This adversely affects the reconstruction of actual eruption plumes.We are developing a volcanic ash data assimilation system using weather radars and meteorological satellite observation, in order to improve the initial distribution of the atmospheric transport models. Our data assimilation system is based on the three-dimensional variational data assimilation method (3D-Var). Analysis variables are ash concentration and size distribution parameters which are mutually independent. The radar observation is expected to provide three-dimensional parameters such as ash concentration and parameters of ash particle size distribution. On the other hand, the satellite observation is anticipated to provide two-dimensional parameters of ash clouds such as mass loading, top height and particle effective radius. In this study, we estimate the thickness of ash clouds using vertical wind shear of JMA numerical weather prediction, and apply for the volcanic ash data assimilation system.

Influence of water quality on nitrifier regrowth in two full-scale drinking water distribution systems.

PubMed

Scott, Daniel B; Van Dyke, Michele I; Anderson, William B; Huck, Peter M

2015-12-01

The potential for regrowth of nitrifying microorganisms was monitored in 2 full-scale chloraminated drinking water distribution systems in Ontario, Canada, over a 9-month period. Quantitative PCR was used to measure amoA genes from ammonia-oxidizing bacteria (AOB) and ammonia-oxidizing archaea (AOA), and these values were compared with water quality parameters that can influence nitrifier survival and growth, including total chlorine, ammonia, temperature, pH, and organic carbon. Although there were no severe nitrification episodes, AOB and AOA were frequently detected at low concentrations in samples collected from both distribution systems. A culture-based presence-absence test confirmed the presence of viable nitrifiers. AOB were usually present in similar or greater numbers than AOA in both systems. As well, AOB showed higher regrowth potential compared with AOA in both systems. Statistically significant correlations were measured between several water quality parameters of relevance to nitrification. Total chlorine was negatively correlated with both nitrifiers and heterotrophic plate count (HPC) bacteria, and ammonia levels were positively correlated with nitrifiers. Of particular importance was the strong correlation between HPC and AOB, which reinforced the usefulness of HPC as an operational parameter to measure general microbiological conditions in distribution systems.

Distributed parameter system coupled ARMA expansion identification and adaptive parallel IIR filtering - A unified problem statement. [Auto Regressive Moving-Average

NASA Technical Reports Server (NTRS)

Johnson, C. R., Jr.; Balas, M. J.

1980-01-01

A novel interconnection of distributed parameter system (DPS) identification and adaptive filtering is presented, which culminates in a common statement of coupled autoregressive, moving-average expansion or parallel infinite impulse response configuration adaptive parameterization. The common restricted complexity filter objectives are seen as similar to the reduced-order requirements of the DPS expansion description. The interconnection presents the possibility of an exchange of problem formulations and solution approaches not yet easily addressed in the common finite dimensional lumped-parameter system context. It is concluded that the shared problems raised are nevertheless many and difficult.

Estimating Age Distributions of Base Flow in Watersheds Underlain by Single and Dual Porosity Formations Using Groundwater Transport Simulation and Weighted Weibull Functions

NASA Astrophysics Data System (ADS)

Sanford, W. E.

2015-12-01

Age distributions of base flow to streams are important to estimate for predicting the timing of water-quality responses to changes in distributed inputs of nutrients or pollutants at the land surface. Simple models of shallow aquifers will predict exponential age distributions, but more realistic 3-D stream-aquifer geometries will cause deviations from an exponential curve. In addition, in fractured rock terrains the dual nature of the effective and total porosity of the system complicates the age distribution further. In this study shallow groundwater flow and advective transport were simulated in two regions in the Eastern United States—the Delmarva Peninsula and the upper Potomac River basin. The former is underlain by layers of unconsolidated sediment, while the latter consists of folded and fractured sedimentary rocks. Transport of groundwater to streams was simulated using the USGS code MODPATH within 175 and 275 watersheds, respectively. For the fractured rock terrain, calculations were also performed along flow pathlines to account for exchange between mobile and immobile flow zones. Porosities at both sites were calibrated using environmental tracer data (3H, 3He, CFCs and SF6) in wells and springs, and with a 30-year tritium record from the Potomac River. Carbonate and siliciclastic rocks were calibrated to have mobile porosity values of one and six percent, and immobile porosity values of 18 and 12 percent, respectively. The age distributions were fitted to Weibull functions. Whereas an exponential function has one parameter that controls the median age of the distribution, a Weibull function has an extra parameter that controls the slope of the curve. A weighted Weibull function was also developed that potentially allows for four parameters, two that control the median age and two that control the slope, one of each weighted toward early or late arrival times. For both systems the two-parameter Weibull function nearly always produced a substantially better fit to the data than the one-parameter exponential function. For the single porosity system it was found that the use of three parameters was often optimal for accurately describing the base-flow age distribution, whereas for the dual porosity system the fourth parameter was often required to fit the more complicated response curves.

Building Better Planet Populations for EXOSIMS

NASA Astrophysics Data System (ADS)

Garrett, Daniel; Savransky, Dmitry

2018-01-01

The Exoplanet Open-Source Imaging Mission Simulator (EXOSIMS) software package simulates ensembles of space-based direct imaging surveys to provide a variety of science and engineering yield distributions for proposed mission designs. These mission simulations rely heavily on assumed distributions of planetary population parameters including semi-major axis, planetary radius, eccentricity, albedo, and orbital orientation to provide heuristics for target selection and to simulate planetary systems for detection and characterization. The distributions are encoded in PlanetPopulation modules within EXOSIMS which are selected by the user in the input JSON script when a simulation is run. The earliest written PlanetPopulation modules available in EXOSIMS are based on planet population models where the planetary parameters are considered to be independent from one another. While independent parameters allow for quick computation of heuristics and sampling for simulated planetary systems, results from planet-finding surveys have shown that many parameters (e.g., semi-major axis/orbital period and planetary radius) are not independent. We present new PlanetPopulation modules for EXOSIMS which are built on models based on planet-finding survey results where semi-major axis and planetary radius are not independent and provide methods for sampling their joint distribution. These new modules enhance the ability of EXOSIMS to simulate realistic planetary systems and give more realistic science yield distributions.

Estimation of modal parameters using bilinear joint time frequency distributions

NASA Astrophysics Data System (ADS)

Roshan-Ghias, A.; Shamsollahi, M. B.; Mobed, M.; Behzad, M.

2007-07-01

In this paper, a new method is proposed for modal parameter estimation using time-frequency representations. Smoothed Pseudo Wigner-Ville distribution which is a member of the Cohen's class distributions is used to decouple vibration modes completely in order to study each mode separately. This distribution reduces cross-terms which are troublesome in Wigner-Ville distribution and retains the resolution as well. The method was applied to highly damped systems, and results were superior to those obtained via other conventional methods.

Parameters of Higher Education Quality Assessment System at Universities

ERIC Educational Resources Information Center

Savickiene, Izabela

2005-01-01

The article analyses the system of institutional quality assessment at universities and lays foundation to its functional, morphological and processual parameters. It also presents the concept of the system and discusses the distribution of systems into groups, defines information, accountability, improvement and benchmarking functions of higher…

Interpretation of environmental tracers in groundwater systems with stagnant water zones.

PubMed

Maloszewski, Piotr; Stichler, Willibald; Zuber, Andrzej

2004-03-01

Lumped-parameter models are commonly applied for determining the age of water from time records of transient environmental tracers. The simplest models (e.g. piston flow or exponential) are also applicable for dating based on the decay or accumulation of tracers in groundwater systems. The models are based on the assumption that the transit time distribution function (exit age distribution function) of the tracer particles in the investigated system adequately represents the distribution of flow lines and is described by a simple function. A chosen or fitted function (called the response function) describes the transit time distribution of a tracer which would be observed at the output (discharge area, spring, stream, or pumping wells) in the case of an instantaneous injection at the entrance (recharge area). Due to large space and time scales, response functions are not measurable in groundwater systems, therefore, functions known from other fields of science, mainly from chemical engineering, are usually used. The type of response function and the values of its parameters define the lumped-parameter model of a system. The main parameter is the mean transit time of tracer through the system, which under favourable conditions may represent the mean age of mobile water. The parameters of the model are found by fitting calculated concentrations to the experimental records of concentrations measured at the outlet. The mean transit time of tracer (often called the tracer age), whether equal to the mean age of water or not, serves in adequate combinations with other data for determining other useful parameters, e.g. the recharge rate or the content of water in the system. The transit time distribution and its mean value serve for confirmation or determination of the conceptual model of the system and/or estimation of its potential vulnerability to anthropogenic pollution. In the interpretation of environmental tracer data with the aid of the lumped-parameter models, the influence of diffusion exchange between mobile water and stagnant or quasi-stagnant water is seldom considered, though it leads to large differences between tracer and water ages. Therefore, the article is focused on the transit time distribution functions of the most common lumped-parameter models, particularly those applicable for the interpretation of environmental tracer data in double-porosity aquifers, or aquifers in which aquitard diffusion may play an important role. A case study is recalled for a confined aquifer in which the diffusion exchange with aquitard most probably strongly influenced the transport of environmental tracers. Another case study presented is related to the interpretation of environmental tracer data obtained from lysimeters installed in the unsaturated zone with a fraction of stagnant water.

Application of Statistically Derived CPAS Parachute Parameters

NASA Technical Reports Server (NTRS)

Romero, Leah M.; Ray, Eric S.

2013-01-01

The Capsule Parachute Assembly System (CPAS) Analysis Team is responsible for determining parachute inflation parameters and dispersions that are ultimately used in verifying system requirements. A model memo is internally released semi-annually documenting parachute inflation and other key parameters reconstructed from flight test data. Dispersion probability distributions published in previous versions of the model memo were uniform because insufficient data were available for determination of statistical based distributions. Uniform distributions do not accurately represent the expected distributions since extreme parameter values are just as likely to occur as the nominal value. CPAS has taken incremental steps to move away from uniform distributions. Model Memo version 9 (MMv9) made the first use of non-uniform dispersions, but only for the reefing cutter timing, for which a large number of sample was available. In order to maximize the utility of the available flight test data, clusters of parachutes were reconstructed individually starting with Model Memo version 10. This allowed for statistical assessment for steady-state drag area (CDS) and parachute inflation parameters such as the canopy fill distance (n), profile shape exponent (expopen), over-inflation factor (C(sub k)), and ramp-down time (t(sub k)) distributions. Built-in MATLAB distributions were applied to the histograms, and parameters such as scale (sigma) and location (mu) were output. Engineering judgment was used to determine the "best fit" distribution based on the test data. Results include normal, log normal, and uniform (where available data remains insufficient) fits of nominal and failure (loss of parachute and skipped stage) cases for all CPAS parachutes. This paper discusses the uniform methodology that was previously used, the process and result of the statistical assessment, how the dispersions were incorporated into Monte Carlo analyses, and the application of the distributions in trajectory benchmark testing assessments with parachute inflation parameters, drag area, and reefing cutter timing used by CPAS.

Control of Distributed Parameter Systems

DTIC Science & Technology

1990-08-01

vari- ant of the general Lotka - Volterra model for interspecific competition. The variant described the emergence of one subpopulation from another as a...distribut ion unlimited. I&. ARSTRACT (MAUMUnw2O1 A unified arioroximation framework for Parameter estimation In general linear POE models has been completed...unified approximation framework for parameter estimation in general linear PDE models. This framework has provided the theoretical basis for a number of

A distributed transmit beamforming synchronization strategy for multi-element radar systems

NASA Astrophysics Data System (ADS)

Xiao, Manlin; Li, Xingwen; Xu, Jikang

2017-02-01

The distributed transmit beamforming has recently been discussed as an energy-effective technique in wireless communication systems. A common ground of various techniques is that the destination node transmits a beacon signal or feedback to assist source nodes to synchronize signals. However, this approach is not appropriate for a radar system since the destination is a non-cooperative target of an unknown location. In our paper, we propose a novel synchronization strategy for a distributed multiple-element beamfoming radar system. Source nodes estimate parameters of beacon signals transmitted from others to get their local synchronization information. The channel information of the phase propagation delay is transmitted to nodes via the reflected beacon signals as well. Next, each node generates appropriate parameters to form a beamforming signal at the target. Transmit beamforming signals of all nodes will combine coherently at the target compensating for different propagation delay. We analyse the influence of the local oscillation accuracy and the parameter estimation errors on the performance of the proposed synchronization scheme. The results of numerical simulations illustrate that this synchronization scheme is effective to enable the transmit beamforming in a distributed multi-element radar system.

A self-organizing neural network for job scheduling in distributed systems

NASA Astrophysics Data System (ADS)

Newman, Harvey B.; Legrand, Iosif C.

2001-08-01

The aim of this work is to describe a possible approach for the optimization of the job scheduling in large distributed systems, based on a self-organizing Neural Network. This dynamic scheduling system should be seen as adaptive middle layer software, aware of current available resources and making the scheduling decisions using the "past experience." It aims to optimize job specific parameters as well as the resource utilization. The scheduling system is able to dynamically learn and cluster information in a large dimensional parameter space and at the same time to explore new regions in the parameters space. This self-organizing scheduling system may offer a possible solution to provide an effective use of resources for the off-line data processing jobs for future HEP experiments.

Systems and methods for optimal power flow on a radial network

DOEpatents

Low, Steven H.; Peng, Qiuyu

2018-04-24

Node controllers and power distribution networks in accordance with embodiments of the invention enable distributed power control. One embodiment includes a node controller including a distributed power control application; a plurality of node operating parameters describing the operating parameter of a node and a set of at least one node selected from the group consisting of an ancestor node and at least one child node; wherein send node operating parameters to nodes in the set of at least one node; receive operating parameters from the nodes in the set of at least one node; calculate a plurality of updated node operating parameters using an iterative process to determine the updated node operating parameters using the node operating parameters that describe the operating parameters of the node and the set of at least one node, where the iterative process involves evaluation of a closed form solution; and adjust node operating parameters.

Design of distributed systems of hydrolithosphere processes management. A synthesis of distributed management systems

NASA Astrophysics Data System (ADS)

Pershin, I. M.; Pervukhin, D. A.; Ilyushin, Y. V.; Afanaseva, O. V.

2017-10-01

The paper considers an important problem of designing distributed systems of hydrolithosphere processes management. The control actions on the hydrolithosphere processes under consideration are implemented by a set of extractive wells. The article shows the method of defining the approximation links for description of the dynamic characteristics of hydrolithosphere processes. The structure of distributed regulators, used in the management systems by the considered processes, is presented. The paper analyses the results of the synthesis of the distributed management system and the results of modelling the closed-loop control system by the parameters of the hydrolithosphere process.

Battery management system with distributed wireless sensors

DOEpatents

Farmer, Joseph C.; Bandhauer, Todd M.

2016-02-23

A system for monitoring parameters of an energy storage system having a multiplicity of individual energy storage cells. A radio frequency identification and sensor unit is connected to each of the individual energy storage cells. The radio frequency identification and sensor unit operates to sense the parameter of each individual energy storage cell and provides radio frequency transmission of the parameters of each individual energy storage cell. A management system monitors the radio frequency transmissions from the radio frequency identification and sensor units for monitoring the parameters of the energy storage system.

Star formation history: Modeling of visual binaries

NASA Astrophysics Data System (ADS)

Gebrehiwot, Y. M.; Tessema, S. B.; Malkov, O. Yu.; Kovaleva, D. A.; Sytov, A. Yu.; Tutukov, A. V.

2018-05-01

Most stars form in binary or multiple systems. Their evolution is defined by masses of components, orbital separation and eccentricity. In order to understand star formation and evolutionary processes, it is vital to find distributions of physical parameters of binaries. We have carried out Monte Carlo simulations in which we simulate different pairing scenarios: random pairing, primary-constrained pairing, split-core pairing, and total and primary pairing in order to get distributions of binaries over physical parameters at birth. Next, for comparison with observations, we account for stellar evolution and selection effects. Brightness, radius, temperature, and other parameters of components are assigned or calculated according to approximate relations for stars in different evolutionary stages (main-sequence stars, red giants, white dwarfs, relativistic objects). Evolutionary stage is defined as a function of system age and component masses. We compare our results with the observed IMF, binarity rate, and binary mass-ratio distributions for field visual binaries to find initial distributions and pairing scenarios that produce observed distributions.

Distributed traffic signal control using fuzzy logic

NASA Technical Reports Server (NTRS)

Chiu, Stephen

1992-01-01

We present a distributed approach to traffic signal control, where the signal timing parameters at a given intersection are adjusted as functions of the local traffic condition and of the signal timing parameters at adjacent intersections. Thus, the signal timing parameters evolve dynamically using only local information to improve traffic flow. This distributed approach provides for a fault-tolerant, highly responsive traffic management system. The signal timing at an intersection is defined by three parameters: cycle time, phase split, and offset. We use fuzzy decision rules to adjust these three parameters based only on local information. The amount of change in the timing parameters during each cycle is limited to a small fraction of the current parameters to ensure smooth transition. We show the effectiveness of this method through simulation of the traffic flow in a network of controlled intersections.

Architectures of Kepler Planet Systems with Approximate Bayesian Computation

NASA Astrophysics Data System (ADS)

Morehead, Robert C.; Ford, Eric B.

2015-12-01

The distribution of period normalized transit duration ratios among Kepler’s multiple transiting planet systems constrains the distributions of mutual orbital inclinations and orbital eccentricities. However, degeneracies in these parameters tied to the underlying number of planets in these systems complicate their interpretation. To untangle the true architecture of planet systems, the mutual inclination, eccentricity, and underlying planet number distributions must be considered simultaneously. The complexities of target selection, transit probability, detection biases, vetting, and follow-up observations make it impractical to write an explicit likelihood function. Approximate Bayesian computation (ABC) offers an intriguing path forward. In its simplest form, ABC generates a sample of trial population parameters from a prior distribution to produce synthetic datasets via a physically-motivated forward model. Samples are then accepted or rejected based on how close they come to reproducing the actual observed dataset to some tolerance. The accepted samples form a robust and useful approximation of the true posterior distribution of the underlying population parameters. We build on the considerable progress from the field of statistics to develop sequential algorithms for performing ABC in an efficient and flexible manner. We demonstrate the utility of ABC in exoplanet populations and present new constraints on the distributions of mutual orbital inclinations, eccentricities, and the relative number of short-period planets per star. We conclude with a discussion of the implications for other planet occurrence rate calculations, such as eta-Earth.

An Iterative Local Updating Ensemble Smoother for Estimation and Uncertainty Assessment of Hydrologic Model Parameters With Multimodal Distributions

NASA Astrophysics Data System (ADS)

Zhang, Jiangjiang; Lin, Guang; Li, Weixuan; Wu, Laosheng; Zeng, Lingzao

2018-03-01

Ensemble smoother (ES) has been widely used in inverse modeling of hydrologic systems. However, for problems where the distribution of model parameters is multimodal, using ES directly would be problematic. One popular solution is to use a clustering algorithm to identify each mode and update the clusters with ES separately. However, this strategy may not be very efficient when the dimension of parameter space is high or the number of modes is large. Alternatively, we propose in this paper a very simple and efficient algorithm, i.e., the iterative local updating ensemble smoother (ILUES), to explore multimodal distributions of model parameters in nonlinear hydrologic systems. The ILUES algorithm works by updating local ensembles of each sample with ES to explore possible multimodal distributions. To achieve satisfactory data matches in nonlinear problems, we adopt an iterative form of ES to assimilate the measurements multiple times. Numerical cases involving nonlinearity and multimodality are tested to illustrate the performance of the proposed method. It is shown that overall the ILUES algorithm can well quantify the parametric uncertainties of complex hydrologic models, no matter whether the multimodal distribution exists.

Age Distribution of Groundwater

NASA Astrophysics Data System (ADS)

Morgenstern, U.; Daughney, C. J.

2012-04-01

Groundwater at the discharge point comprises a mixture of water from different flow lines with different travel time and therefore has no discrete age but an age distribution. The age distribution can be assessed by measuring how a pulse shaped tracer moves through the groundwater system. Detection of the time delay and the dispersion of the peak in the groundwater compared to the tracer input reveals the mean residence time and the mixing parameter. Tritium from nuclear weapons testing in the early 1960s resulted in a peak-shaped tritium input to the whole hydrologic system on earth. Tritium is the ideal tracer for groundwater because it is an isotope of hydrogen and therefore is part of the water molecule. Tritium time series data that encompass the passage of the bomb tritium pulse through the groundwater system in all common hydrogeologic situations in New Zealand demonstrate a semi-systematic pattern between age distribution parameters and hydrologic situation. The data in general indicate high fraction of mixing, but in some cases also indicate high piston flow. We will show that still, 45 years after the peak of the bomb tritium, it is possible to assess accurately the parameters of age distributions by measuring the tail of the bomb tritium.

Theoretical study of the dependence of single impurity Anderson model on various parameters within distributional exact diagonalization method

NASA Astrophysics Data System (ADS)

Syaina, L. P.; Majidi, M. A.

2018-04-01

Single impurity Anderson model describes a system consisting of non-interacting conduction electrons coupled with a localized orbital having strongly interacting electrons at a particular site. This model has been proven successful to explain the phenomenon of metal-insulator transition through Anderson localization. Despite the well-understood behaviors of the model, little has been explored theoretically on how the model properties gradually evolve as functions of hybridization parameter, interaction energy, impurity concentration, and temperature. Here, we propose to do a theoretical study on those aspects of a single impurity Anderson model using the distributional exact diagonalization method. We solve the model Hamiltonian by randomly generating sampling distribution of some conducting electron energy levels with various number of occupying electrons. The resulting eigenvalues and eigenstates are then used to define the local single-particle Green function for each sampled electron energy distribution using Lehmann representation. Later, we extract the corresponding self-energy of each distribution, then average over all the distributions and construct the local Green function of the system to calculate the density of states. We repeat this procedure for various values of those controllable parameters, and discuss our results in connection with the criteria of the occurrence of metal-insulator transition in this system.

Blind Deconvolution for Distributed Parameter Systems with Unbounded Input and Output and Determining Blood Alcohol Concentration from Transdermal Biosensor Data.

PubMed

Rosen, I G; Luczak, Susan E; Weiss, Jordan

2014-03-15

We develop a blind deconvolution scheme for input-output systems described by distributed parameter systems with boundary input and output. An abstract functional analytic theory based on results for the linear quadratic control of infinite dimensional systems with unbounded input and output operators is presented. The blind deconvolution problem is then reformulated as a series of constrained linear and nonlinear optimization problems involving infinite dimensional dynamical systems. A finite dimensional approximation and convergence theory is developed. The theory is applied to the problem of estimating blood or breath alcohol concentration (respectively, BAC or BrAC) from biosensor-measured transdermal alcohol concentration (TAC) in the field. A distributed parameter model with boundary input and output is proposed for the transdermal transport of ethanol from the blood through the skin to the sensor. The problem of estimating BAC or BrAC from the TAC data is formulated as a blind deconvolution problem. A scheme to identify distinct drinking episodes in TAC data based on a Hodrick Prescott filter is discussed. Numerical results involving actual patient data are presented.

Optimization of design and operating parameters of a space-based optical-electronic system with a distributed aperture.

PubMed

Tcherniavski, Iouri; Kahrizi, Mojtaba

2008-11-20

Using a gradient optimization method with objective functions formulated in terms of a signal-to-noise ratio (SNR) calculated at given values of the prescribed spatial ground resolution, optimization problems of geometrical parameters of a distributed optical system and a charge-coupled device of a space-based optical-electronic system are solved for samples of the optical systems consisting of two and three annular subapertures. The modulation transfer function (MTF) of the distributed aperture is expressed in terms of an average MTF taking residual image alignment (IA) and optical path difference (OPD) errors into account. The results show optimal solutions of the optimization problems depending on diverse variable parameters. The information on the magnitudes of the SNR can be used to determine the number of the subapertures and their sizes, while the information on the SNR decrease depending on the IA and OPD errors can be useful in design of a beam combination control system to produce the necessary requirements to its accuracy on the basis of the permissible deterioration in the image quality.

The evolution of Zipf's law indicative of city development

NASA Astrophysics Data System (ADS)

Chen, Yanguang

2016-02-01

Zipf's law of city-size distributions can be expressed by three types of mathematical models: one-parameter form, two-parameter form, and three-parameter form. The one-parameter and one of the two-parameter models are familiar to urban scientists. However, the three-parameter model and another type of two-parameter model have not attracted attention. This paper is devoted to exploring the conditions and scopes of application of these Zipf models. By mathematical reasoning and empirical analysis, new discoveries are made as follows. First, if the size distribution of cities in a geographical region cannot be described with the one- or two-parameter model, maybe it can be characterized by the three-parameter model with a scaling factor and a scale-translational factor. Second, all these Zipf models can be unified by hierarchical scaling laws based on cascade structure. Third, the patterns of city-size distributions seem to evolve from three-parameter mode to two-parameter mode, and then to one-parameter mode. Four-year census data of Chinese cities are employed to verify the three-parameter Zipf's law and the corresponding hierarchical structure of rank-size distributions. This study is revealing for people to understand the scientific laws of social systems and the property of urban development.

Full Two-Body Problem Mass Parameter Observability Explored Through Doubly Synchronous Systems

NASA Astrophysics Data System (ADS)

Davis, Alex Benjamin; Scheeres, Daniel

2018-04-01

The full two-body problem (F2BP) is often used to model binary asteroid systems, representing the bodies as two finite mass distributions whose dynamics are influenced by their mutual gravity potential. The emergent behavior of the F2BP is highly coupled translational and rotational mutual motion of the mass distributions. For these systems the doubly synchronous equilibrium occurs when both bodies are tidally-locked and in a circular co-orbit. Stable oscillations about this equilibrium can be shown, for the nonplanar system, to be combinations of seven fundamental frequencies of the system and the mutual orbit rate. The fundamental frequencies arise as the linear periods of center manifolds identified about the equilibrium which are heavily influenced by each body’s mass parameters. We leverage these eight dynamical constraints to investigate the observability of binary asteroid mass parameters via dynamical observations. This is accomplished by proving the nonsingularity of the relationship between the frequencies and mass parameters for doubly synchronous systems. Thus we can invert the relationship to show that given observations of the frequencies, we can solve for the mass parameters of a target system. In so doing we are able to predict the estimation covariance of the mass parameters based on observation quality and define necessary observation accuracies for desired mass parameter certainties. We apply these tools to 617 Patroclus, a doubly synchronous Trojan binary and flyby target of the LUCY mission, as well as the Pluto and Charon system in order to predict mutual behaviors of these doubly synchronous systems and to provide observational requirements for these systems’ mass parameters

MARSnet: Mission-aware Autonomous Radar Sensor Network for Future Combat Systems

DTIC Science & Technology

2007-05-03

34Parameter estimation for 3-parameter log-logistic distribution (LLD3) by Porne ", Parameter estimation for 3-parameter log-logistic distribu- tion...section V we physical security, air traffic control, traffic monitoring, andvidefaconu s cribedy. video surveillance, industrial automation etc. Each

Superslow relaxation in identical phase oscillators with random and frustrated interactions

NASA Astrophysics Data System (ADS)

Daido, H.

2018-04-01

This paper is concerned with the relaxation dynamics of a large population of identical phase oscillators, each of which interacts with all the others through random couplings whose parameters obey the same Gaussian distribution with the average equal to zero and are mutually independent. The results obtained by numerical simulation suggest that for the infinite-size system, the absolute value of Kuramoto's order parameter exhibits superslow relaxation, i.e., 1/ln t as time t increases. Moreover, the statistics on both the transient time T for the system to reach a fixed point and the absolute value of Kuramoto's order parameter at t = T are also presented together with their distribution densities over many realizations of the coupling parameters.

Probability distribution functions for unit hydrographs with optimization using genetic algorithm

NASA Astrophysics Data System (ADS)

Ghorbani, Mohammad Ali; Singh, Vijay P.; Sivakumar, Bellie; H. Kashani, Mahsa; Atre, Atul Arvind; Asadi, Hakimeh

2017-05-01

A unit hydrograph (UH) of a watershed may be viewed as the unit pulse response function of a linear system. In recent years, the use of probability distribution functions (pdfs) for determining a UH has received much attention. In this study, a nonlinear optimization model is developed to transmute a UH into a pdf. The potential of six popular pdfs, namely two-parameter gamma, two-parameter Gumbel, two-parameter log-normal, two-parameter normal, three-parameter Pearson distribution, and two-parameter Weibull is tested on data from the Lighvan catchment in Iran. The probability distribution parameters are determined using the nonlinear least squares optimization method in two ways: (1) optimization by programming in Mathematica; and (2) optimization by applying genetic algorithm. The results are compared with those obtained by the traditional linear least squares method. The results show comparable capability and performance of two nonlinear methods. The gamma and Pearson distributions are the most successful models in preserving the rising and recession limbs of the unit hydographs. The log-normal distribution has a high ability in predicting both the peak flow and time to peak of the unit hydrograph. The nonlinear optimization method does not outperform the linear least squares method in determining the UH (especially for excess rainfall of one pulse), but is comparable.

Task allocation in a distributed computing system

NASA Technical Reports Server (NTRS)

Seward, Walter D.

1987-01-01

A conceptual framework is examined for task allocation in distributed systems. Application and computing system parameters critical to task allocation decision processes are discussed. Task allocation techniques are addressed which focus on achieving a balance in the load distribution among the system's processors. Equalization of computing load among the processing elements is the goal. Examples of system performance are presented for specific applications. Both static and dynamic allocation of tasks are considered and system performance is evaluated using different task allocation methodologies.

Maximum likelihood estimation for life distributions with competing failure modes

NASA Technical Reports Server (NTRS)

Sidik, S. M.

1979-01-01

Systems which are placed on test at time zero, function for a period and die at some random time were studied. Failure may be due to one of several causes or modes. The parameters of the life distribution may depend upon the levels of various stress variables the item is subject to. Maximum likelihood estimation methods are discussed. Specific methods are reported for the smallest extreme-value distributions of life. Monte-Carlo results indicate the methods to be promising. Under appropriate conditions, the location parameters are nearly unbiased, the scale parameter is slight biased, and the asymptotic covariances are rapidly approached.

Estimation and impact assessment of input and parameter uncertainty in predicting groundwater flow with a fully distributed model

NASA Astrophysics Data System (ADS)

Touhidul Mustafa, Syed Md.; Nossent, Jiri; Ghysels, Gert; Huysmans, Marijke

2017-04-01

Transient numerical groundwater flow models have been used to understand and forecast groundwater flow systems under anthropogenic and climatic effects, but the reliability of the predictions is strongly influenced by different sources of uncertainty. Hence, researchers in hydrological sciences are developing and applying methods for uncertainty quantification. Nevertheless, spatially distributed flow models pose significant challenges for parameter and spatially distributed input estimation and uncertainty quantification. In this study, we present a general and flexible approach for input and parameter estimation and uncertainty analysis of groundwater models. The proposed approach combines a fully distributed groundwater flow model (MODFLOW) with the DiffeRential Evolution Adaptive Metropolis (DREAM) algorithm. To avoid over-parameterization, the uncertainty of the spatially distributed model input has been represented by multipliers. The posterior distributions of these multipliers and the regular model parameters were estimated using DREAM. The proposed methodology has been applied in an overexploited aquifer in Bangladesh where groundwater pumping and recharge data are highly uncertain. The results confirm that input uncertainty does have a considerable effect on the model predictions and parameter distributions. Additionally, our approach also provides a new way to optimize the spatially distributed recharge and pumping data along with the parameter values under uncertain input conditions. It can be concluded from our approach that considering model input uncertainty along with parameter uncertainty is important for obtaining realistic model predictions and a correct estimation of the uncertainty bounds.

Post-processing procedure for industrial quantum key distribution systems

NASA Astrophysics Data System (ADS)

Kiktenko, Evgeny; Trushechkin, Anton; Kurochkin, Yury; Fedorov, Aleksey

2016-08-01

We present algorithmic solutions aimed on post-processing procedure for industrial quantum key distribution systems with hardware sifting. The main steps of the procedure are error correction, parameter estimation, and privacy amplification. Authentication of classical public communication channel is also considered.

Voronoi cell patterns: Theoretical model and applications

NASA Astrophysics Data System (ADS)

González, Diego Luis; Einstein, T. L.

2011-11-01

We use a simple fragmentation model to describe the statistical behavior of the Voronoi cell patterns generated by a homogeneous and isotropic set of points in 1D and in 2D. In particular, we are interested in the distribution of sizes of these Voronoi cells. Our model is completely defined by two probability distributions in 1D and again in 2D, the probability to add a new point inside an existing cell and the probability that this new point is at a particular position relative to the preexisting point inside this cell. In 1D the first distribution depends on a single parameter while the second distribution is defined through a fragmentation kernel; in 2D both distributions depend on a single parameter. The fragmentation kernel and the control parameters are closely related to the physical properties of the specific system under study. We use our model to describe the Voronoi cell patterns of several systems. Specifically, we study the island nucleation with irreversible attachment, the 1D car-parking problem, the formation of second-level administrative divisions, and the pattern formed by the Paris Métro stations.

A Modified Goodness-of-Fit Test for the Lognormal Distribution with Unknown Scale and Location Parameters.

DTIC Science & Technology

1986-12-01

Force and other branches of the military are placing an increased emphasis on system reliablity and maintainability. In studying current systems ...used in the research of proposed systems , by predicting MTTF and MTTR of the new parts and thus, predict the reliability of those parts. The statistics...effectiveness of new systems . Aitchison’s book on the lognormal distribution, printed and used by Cambridge University, highlighted the distributions

Decision Support for Renewal of Wastewater Collections and Water Distribution Systems

EPA Science Inventory

The decision of how to accomplish the renewal of existing wastewater collection and water distribution systems involves the evaluation of many criteria and parameters. These criteria must be evaluated thoroughly to determine the best way of rehabilitating or replacing these sys...

DECISION SUPPORT FOR RENEWAL OF WASTEWATER COLLECTIONS AND WATER DISTRIBUTION SYSTEMS

EPA Science Inventory

The decision of how to accomplish the renewal of existing wastewater collection and water distribution systems involves the evaluation of many criteria and parameters. These criteria must be evaluated thoroughly to determine the best way of rehabilitating or replacing these syste...

Flow Cytometry Total Cell Counts: A Field Study Assessing Microbiological Water Quality and Growth in Unchlorinated Drinking Water Distribution Systems

PubMed Central

Liu, G.; Van der Mark, E. J.; Verberk, J. Q. J. C.; Van Dijk, J. C.

2013-01-01

The objective of this study was to evaluate the application of flow cytometry total cell counts (TCCs) as a parameter to assess microbial growth in drinking water distribution systems and to determine the relationships between different parameters describing the biostability of treated water. A one-year sampling program was carried out in two distribution systems in The Netherlands. Results demonstrated that, in both systems, the biomass differences measured by ATP were not significant. TCC differences were also not significant in treatment plant 1, but decreased slightly in treatment plant 2. TCC values were found to be higher at temperatures above 15°C than at temperatures below 15°C. The correlation study of parameters describing biostability found no relationship among TCC, heterotrophic plate counts, and Aeromonas. Also no relationship was found between TCC and ATP. Some correlation was found between the subgroup of high nucleic acid content bacteria and ATP (R 2 = 0.63). Overall, the results demonstrated that TCC is a valuable parameter to assess the drinking water biological quality and regrowth; it can directly and sensitively quantify biomass, detect small changes, and can be used to determine the subgroup of active HNA bacteria that are related to ATP. PMID:23819117

Distribution-Connected PV's Response to Voltage Sags at Transmission-Scale

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

Mather, Barry; Ding, Fei

The ever increasing amount of residential- and commercial-scale distribution-connected PV generation being installed and operated on the U.S.'s electric power system necessitates the use of increased fidelity representative distribution system models for transmission stability studies in order to ensure the continued safe and reliable operation of the grid. This paper describes a distribution model-based analysis that determines the amount of distribution-connected PV that trips off-line for a given voltage sag seen at the distribution circuit's substation. Such sags are what could potentially be experienced over a wide area of an interconnection during a transmission-level line fault. The results of thismore » analysis show that the voltage diversity of the distribution system does cause different amounts of PV generation to be lost for differing severity of voltage sags. The variation of the response is most directly a function of the loading of the distribution system. At low load levels the inversion of the circuit's voltage profile results in considerable differences in the aggregated response of distribution-connected PV Less variation is seen in the response to specific PV deployment scenarios, unless pushed to extremes, and in the total amount of PV penetration attained. A simplified version of the combined CMPLDW and PVD1 models is compared to the results from the model-based analysis. Furthermore, the parameters of the simplified model are tuned to better match the determined response. The resulting tuning parameters do not match the expected physical model of the distribution system and PV systems and thus may indicate that another modeling approach would be warranted.« less

System statistical reliability model and analysis

NASA Technical Reports Server (NTRS)

Lekach, V. S.; Rood, H.

1973-01-01

A digital computer code was developed to simulate the time-dependent behavior of the 5-kwe reactor thermoelectric system. The code was used to determine lifetime sensitivity coefficients for a number of system design parameters, such as thermoelectric module efficiency and degradation rate, radiator absorptivity and emissivity, fuel element barrier defect constant, beginning-of-life reactivity, etc. A probability distribution (mean and standard deviation) was estimated for each of these design parameters. Then, error analysis was used to obtain a probability distribution for the system lifetime (mean = 7.7 years, standard deviation = 1.1 years). From this, the probability that the system will achieve the design goal of 5 years lifetime is 0.993. This value represents an estimate of the degradation reliability of the system.

Stochastic control system parameter identifiability

NASA Technical Reports Server (NTRS)

Lee, C. H.; Herget, C. J.

1975-01-01

The parameter identification problem of general discrete time, nonlinear, multiple input/multiple output dynamic systems with Gaussian white distributed measurement errors is considered. The knowledge of the system parameterization was assumed to be known. Concepts of local parameter identifiability and local constrained maximum likelihood parameter identifiability were established. A set of sufficient conditions for the existence of a region of parameter identifiability was derived. A computation procedure employing interval arithmetic was provided for finding the regions of parameter identifiability. If the vector of the true parameters is locally constrained maximum likelihood (CML) identifiable, then with probability one, the vector of true parameters is a unique maximal point of the maximum likelihood function in the region of parameter identifiability and the constrained maximum likelihood estimation sequence will converge to the vector of true parameters.

Distributed parameter modelling of flexible spacecraft: Where's the beef?

NASA Technical Reports Server (NTRS)

Hyland, D. C.

1994-01-01

This presentation discusses various misgivings concerning the directions and productivity of Distributed Parameter System (DPS) theory as applied to spacecraft vibration control. We try to show the need for greater cross-fertilization between DPS theorists and spacecraft control designers. We recommend a shift in research directions toward exploration of asymptotic frequency response characteristics of critical importance to control designers.

NWP model forecast skill optimization via closure parameter variations

NASA Astrophysics Data System (ADS)

Järvinen, H.; Ollinaho, P.; Laine, M.; Solonen, A.; Haario, H.

2012-04-01

We present results of a novel approach to tune predictive skill of numerical weather prediction (NWP) models. These models contain tunable parameters which appear in parameterizations schemes of sub-grid scale physical processes. The current practice is to specify manually the numerical parameter values, based on expert knowledge. We developed recently a concept and method (QJRMS 2011) for on-line estimation of the NWP model parameters via closure parameter variations. The method called EPPES ("Ensemble prediction and parameter estimation system") utilizes ensemble prediction infra-structure for parameter estimation in a very cost-effective way: practically no new computations are introduced. The approach provides an algorithmic decision making tool for model parameter optimization in operational NWP. In EPPES, statistical inference about the NWP model tunable parameters is made by (i) generating an ensemble of predictions so that each member uses different model parameter values, drawn from a proposal distribution, and (ii) feeding-back the relative merits of the parameter values to the proposal distribution, based on evaluation of a suitable likelihood function against verifying observations. In this presentation, the method is first illustrated in low-order numerical tests using a stochastic version of the Lorenz-95 model which effectively emulates the principal features of ensemble prediction systems. The EPPES method correctly detects the unknown and wrongly specified parameters values, and leads to an improved forecast skill. Second, results with an ensemble prediction system emulator, based on the ECHAM5 atmospheric GCM show that the model tuning capability of EPPES scales up to realistic models and ensemble prediction systems. Finally, preliminary results of EPPES in the context of ECMWF forecasting system are presented.

Quality parameters analysis of optical imaging systems with enhanced focal depth using the Wigner distribution function

PubMed

Zalvidea; Colautti; Sicre

2000-05-01

An analysis of the Strehl ratio and the optical transfer function as imaging quality parameters of optical elements with enhanced focal length is carried out by employing the Wigner distribution function. To this end, we use four different pupil functions: a full circular aperture, a hyper-Gaussian aperture, a quartic phase plate, and a logarithmic phase mask. A comparison is performed between the quality parameters and test images formed by these pupil functions at different defocus distances.

Computational system identification of continuous-time nonlinear systems using approximate Bayesian computation

NASA Astrophysics Data System (ADS)

Krishnanathan, Kirubhakaran; Anderson, Sean R.; Billings, Stephen A.; Kadirkamanathan, Visakan

2016-11-01

In this paper, we derive a system identification framework for continuous-time nonlinear systems, for the first time using a simulation-focused computational Bayesian approach. Simulation approaches to nonlinear system identification have been shown to outperform regression methods under certain conditions, such as non-persistently exciting inputs and fast-sampling. We use the approximate Bayesian computation (ABC) algorithm to perform simulation-based inference of model parameters. The framework has the following main advantages: (1) parameter distributions are intrinsically generated, giving the user a clear description of uncertainty, (2) the simulation approach avoids the difficult problem of estimating signal derivatives as is common with other continuous-time methods, and (3) as noted above, the simulation approach improves identification under conditions of non-persistently exciting inputs and fast-sampling. Term selection is performed by judging parameter significance using parameter distributions that are intrinsically generated as part of the ABC procedure. The results from a numerical example demonstrate that the method performs well in noisy scenarios, especially in comparison to competing techniques that rely on signal derivative estimation.

Distributed dual-parameter optical fiber sensor based on cascaded microfiber Fabry-Pérot interferometers

NASA Astrophysics Data System (ADS)

Xiang, Yang; Luo, Yiyang; Zhang, Wei; Liu, Deming; Sun, Qizhen

2017-04-01

We propose and demonstrate a distributed fiber sensor based on cascaded microfiber Fabry-Perot interferometers (MFPI) for simultaneous refractive index (SRI) and temperature measurement. By employing MFPI which is fabricated by taper-drawing the center of a uniform fiber Bragg grating (FBG) on standard fiber into a section of microfiber, dual parameters including SRI and temperature can be detected through demodulating the reflection spectrum of the MFPI. Further, wavelength-division-multiplexing (WDM) is applied to realize distributed dual-parameter fiber sensor by using cascaded MFPIs with different Bragg wavelengths. A prototype sensor system with 5 cascaded MFPIs is constructed to experimentally demonstrate the sensing performance.

Improving control and estimation for distributed parameter systems utilizing mobile actuator-sensor network.

PubMed

Mu, Wenying; Cui, Baotong; Li, Wen; Jiang, Zhengxian

2014-07-01

This paper proposes a scheme for non-collocated moving actuating and sensing devices which is unitized for improving performance in distributed parameter systems. By Lyapunov stability theorem, each moving actuator/sensor agent velocity is obtained. To enhance state estimation of a spatially distributes process, two kinds of filters with consensus terms which penalize the disagreement of the estimates are considered. Both filters can result in the well-posedness of the collective dynamics of state errors and can converge to the plant state. Numerical simulations demonstrate that the effectiveness of such a moving actuator-sensor network in enhancing system performance and the consensus filters converge faster to the plant state when consensus terms are included. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

New model for distributed multimedia databases and its application to networking of museums

NASA Astrophysics Data System (ADS)

Kuroda, Kazuhide; Komatsu, Naohisa; Komiya, Kazumi; Ikeda, Hiroaki

1998-02-01

This paper proposes a new distributed multimedia data base system where the databases storing MPEG-2 videos and/or super high definition images are connected together through the B-ISDN's, and also refers to an example of the networking of museums on the basis of the proposed database system. The proposed database system introduces a new concept of the 'retrieval manager' which functions an intelligent controller so that the user can recognize a set of image databases as one logical database. A user terminal issues a request to retrieve contents to the retrieval manager which is located in the nearest place to the user terminal on the network. Then, the retrieved contents are directly sent through the B-ISDN's to the user terminal from the server which stores the designated contents. In this case, the designated logical data base dynamically generates the best combination of such a retrieving parameter as a data transfer path referring to directly or data on the basis of the environment of the system. The generated retrieving parameter is then executed to select the most suitable data transfer path on the network. Therefore, the best combination of these parameters fits to the distributed multimedia database system.

Lumped versus distributed thermoregulatory control: results from a three-dimensional dynamic model.

PubMed

Werner, J; Buse, M; Foegen, A

1989-01-01

In this study we use a three-dimensional model of the human thermal system, the spatial grid of which is 0.5 ... 1.0 cm. The model is based on well-known physical heat-transfer equations, and all parameters of the passive system have definite physical values. According to the number of substantially different areas and organs, 54 spatially different values are attributed to each physical parameter. Compatibility of simulation and experiment was achieved solely on the basis of physical considerations and physiological basic data. The equations were solved using a modification of the alternating direction implicit method. On the basis of this complex description of the passive system close to reality, various lumped and distributed parameter control equations were tested for control of metabolic heat production, blood flow and sweat production. The simplest control equations delivering results on closed-loop control compatible with experimental evidence were determined. It was concluded that it is essential to take into account the spatial distribution of heat production, blood flow and sweat production, and that at least for control of shivering, distributed controller gains different from the pattern of distribution of muscle tissue are required. For sweat production this is not so obvious, so that for simulation of sweating control after homogeneous heat load a lumped parameter control may be justified. Based on these conclusions three-dimensional temperature profiles for cold and heat load and the dynamics for changes of the environmental conditions were computed. In view of the exact simulation of the passive system and the compatibility with experimentally attainable variables there is good evidence that those values extrapolated by the simulation are adequately determined. The model may be used both for further analysis of the real thermoregulatory mechanisms and for special applications in environmental and clinical health care.

Extended Czjzek model applied to NMR parameter distributions in sodium metaphosphate glass

NASA Astrophysics Data System (ADS)

Vasconcelos, Filipe; Cristol, Sylvain; Paul, Jean-François; Delevoye, Laurent; Mauri, Francesco; Charpentier, Thibault; Le Caër, Gérard

2013-06-01

The extended Czjzek model (ECM) is applied to the distribution of NMR parameters of a simple glass model (sodium metaphosphate, NaPO3) obtained by molecular dynamics (MD) simulations. Accurate NMR tensors, electric field gradient (EFG) and chemical shift anisotropy (CSA) are calculated from density functional theory (DFT) within the well-established PAW/GIPAW framework. The theoretical results are compared to experimental high-resolution solid-state NMR data and are used to validate the considered structural model. The distributions of the calculated coupling constant CQ ∝ |Vzz| and the asymmetry parameter ηQ that characterize the quadrupolar interaction are discussed in terms of structural considerations with the help of a simple point charge model. Finally, the ECM analysis is shown to be relevant for studying the distribution of CSA tensor parameters and gives new insight into the structural characterization of disordered systems by solid-state NMR.

Extended Czjzek model applied to NMR parameter distributions in sodium metaphosphate glass.

PubMed

Vasconcelos, Filipe; Cristol, Sylvain; Paul, Jean-François; Delevoye, Laurent; Mauri, Francesco; Charpentier, Thibault; Le Caër, Gérard

2013-06-26

The extended Czjzek model (ECM) is applied to the distribution of NMR parameters of a simple glass model (sodium metaphosphate, NaPO3) obtained by molecular dynamics (MD) simulations. Accurate NMR tensors, electric field gradient (EFG) and chemical shift anisotropy (CSA) are calculated from density functional theory (DFT) within the well-established PAW/GIPAW framework. The theoretical results are compared to experimental high-resolution solid-state NMR data and are used to validate the considered structural model. The distributions of the calculated coupling constant C(Q) is proportional to |V(zz)| and the asymmetry parameter η(Q) that characterize the quadrupolar interaction are discussed in terms of structural considerations with the help of a simple point charge model. Finally, the ECM analysis is shown to be relevant for studying the distribution of CSA tensor parameters and gives new insight into the structural characterization of disordered systems by solid-state NMR.

Draft Genome Sequences of Six Mycobacterium immunogenum, Strains Obtained from a Chloraminated Drinking Water Distribution System Simulator

EPA Science Inventory

We report the draft genome sequences of six Mycobacterium immunogenum isolated from a chloraminated drinking water distribution system simulator subjected to changes in operational parameters. M. immunogenum, a rapidly growing mycobacteria previously reported as the cause of hyp...

Integrating machine learning to achieve an automatic parameter prediction for practical continuous-variable quantum key distribution

NASA Astrophysics Data System (ADS)

Liu, Weiqi; Huang, Peng; Peng, Jinye; Fan, Jianping; Zeng, Guihua

2018-02-01

For supporting practical quantum key distribution (QKD), it is critical to stabilize the physical parameters of signals, e.g., the intensity, phase, and polarization of the laser signals, so that such QKD systems can achieve better performance and practical security. In this paper, an approach is developed by integrating a support vector regression (SVR) model to optimize the performance and practical security of the QKD system. First, a SVR model is learned to precisely predict the time-along evolutions of the physical parameters of signals. Second, such predicted time-along evolutions are employed as feedback to control the QKD system for achieving the optimal performance and practical security. Finally, our proposed approach is exemplified by using the intensity evolution of laser light and a local oscillator pulse in the Gaussian modulated coherent state QKD system. Our experimental results have demonstrated three significant benefits of our SVR-based approach: (1) it can allow the QKD system to achieve optimal performance and practical security, (2) it does not require any additional resources and any real-time monitoring module to support automatic prediction of the time-along evolutions of the physical parameters of signals, and (3) it is applicable to any measurable physical parameter of signals in the practical QKD system.

An approximation theory for the identification of nonlinear distributed parameter systems

NASA Technical Reports Server (NTRS)

Banks, H. T.; Reich, Simeon; Rosen, I. G.

1988-01-01

An abstract approximation framework for the identification of nonlinear distributed parameter systems is developed. Inverse problems for nonlinear systems governed by strongly maximal monotone operators (satisfying a mild continuous dependence condition with respect to the unknown parameters to be identified) are treated. Convergence of Galerkin approximations and the corresponding solutions of finite dimensional approximating identification problems to a solution of the original finite dimensional identification problem is demonstrated using the theory of nonlinear evolution systems and a nonlinear analog of the Trotter-Kato approximation result for semigroups of bounded linear operators. The nonlinear theory developed here is shown to subsume an existing linear theory as a special case. It is also shown to be applicable to a broad class of nonlinear elliptic operators and the corresponding nonlinear parabolic partial differential equations to which they lead. An application of the theory to a quasilinear model for heat conduction or mass transfer is discussed.

The Impact of Uncertain Physical Parameters on HVAC Demand Response

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

Sun, Yannan; Elizondo, Marcelo A.; Lu, Shuai

HVAC units are currently one of the major resources providing demand response (DR) in residential buildings. Models of HVAC with DR function can improve understanding of its impact on power system operations and facilitate the deployment of DR technologies. This paper investigates the importance of various physical parameters and their distributions to the HVAC response to DR signals, which is a key step to the construction of HVAC models for a population of units with insufficient data. These parameters include the size of floors, insulation efficiency, the amount of solid mass in the house, and efficiency of the HVAC units.more » These parameters are usually assumed to follow Gaussian or Uniform distributions. We study the effect of uncertainty in the chosen parameter distributions on the aggregate HVAC response to DR signals, during transient phase and in steady state. We use a quasi-Monte Carlo sampling method with linear regression and Prony analysis to evaluate sensitivity of DR output to the uncertainty in the distribution parameters. The significance ranking on the uncertainty sources is given for future guidance in the modeling of HVAC demand response.« less

Review of probabilistic analysis of dynamic response of systems with random parameters

NASA Technical Reports Server (NTRS)

Kozin, F.; Klosner, J. M.

1989-01-01

The various methods that have been studied in the past to allow probabilistic analysis of dynamic response for systems with random parameters are reviewed. Dynamic response may have been obtained deterministically if the variations about the nominal values were small; however, for space structures which require precise pointing, the variations about the nominal values of the structural details and of the environmental conditions are too large to be considered as negligible. These uncertainties are accounted for in terms of probability distributions about their nominal values. The quantities of concern for describing the response of the structure includes displacements, velocities, and the distributions of natural frequencies. The exact statistical characterization of the response would yield joint probability distributions for the response variables. Since the random quantities will appear as coefficients, determining the exact distributions will be difficult at best. Thus, certain approximations will have to be made. A number of techniques that are available are discussed, even in the nonlinear case. The methods that are described were: (1) Liouville's equation; (2) perturbation methods; (3) mean square approximate systems; and (4) nonlinear systems with approximation by linear systems.

Multivariate η-μ fading distribution with arbitrary correlation model

NASA Astrophysics Data System (ADS)

Ghareeb, Ibrahim; Atiani, Amani

2018-03-01

An extensive analysis for the multivariate ? distribution with arbitrary correlation is presented, where novel analytical expressions for the multivariate probability density function, cumulative distribution function and moment generating function (MGF) of arbitrarily correlated and not necessarily identically distributed ? power random variables are derived. Also, this paper provides exact-form expression for the MGF of the instantaneous signal-to-noise ratio at the combiner output in a diversity reception system with maximal-ratio combining and post-detection equal-gain combining operating in slow frequency nonselective arbitrarily correlated not necessarily identically distributed ?-fading channels. The average bit error probability of differentially detected quadrature phase shift keying signals with post-detection diversity reception system over arbitrarily correlated and not necessarily identical fading parameters ?-fading channels is determined by using the MGF-based approach. The effect of fading correlation between diversity branches, fading severity parameters and diversity level is studied.

Kappa and other nonequilibrium distributions from the Fokker-Planck equation and the relationship to Tsallis entropy.

PubMed

Shizgal, Bernie D

2018-05-01

This paper considers two nonequilibrium model systems described by linear Fokker-Planck equations for the time-dependent velocity distribution functions that yield steady state Kappa distributions for specific system parameters. The first system describes the time evolution of a charged test particle in a constant temperature heat bath of a second charged particle. The time dependence of the distribution function of the test particle is given by a Fokker-Planck equation with drift and diffusion coefficients for Coulomb collisions as well as a diffusion coefficient for wave-particle interactions. A second system involves the Fokker-Planck equation for electrons dilutely dispersed in a constant temperature heat bath of atoms or ions and subject to an external time-independent uniform electric field. The momentum transfer cross section for collisions between the two components is assumed to be a power law in reduced speed. The time-dependent Fokker-Planck equations for both model systems are solved with a numerical finite difference method and the approach to equilibrium is rationalized with the Kullback-Leibler relative entropy. For particular choices of the system parameters for both models, the steady distribution is found to be a Kappa distribution. Kappa distributions were introduced as an empirical fitting function that well describe the nonequilibrium features of the distribution functions of electrons and ions in space science as measured by satellite instruments. The calculation of the Kappa distribution from the Fokker-Planck equations provides a direct physically based dynamical approach in contrast to the nonextensive entropy formalism by Tsallis [J. Stat. Phys. 53, 479 (1988)JSTPBS0022-471510.1007/BF01016429].

Kappa and other nonequilibrium distributions from the Fokker-Planck equation and the relationship to Tsallis entropy

NASA Astrophysics Data System (ADS)

Shizgal, Bernie D.

2018-05-01

This paper considers two nonequilibrium model systems described by linear Fokker-Planck equations for the time-dependent velocity distribution functions that yield steady state Kappa distributions for specific system parameters. The first system describes the time evolution of a charged test particle in a constant temperature heat bath of a second charged particle. The time dependence of the distribution function of the test particle is given by a Fokker-Planck equation with drift and diffusion coefficients for Coulomb collisions as well as a diffusion coefficient for wave-particle interactions. A second system involves the Fokker-Planck equation for electrons dilutely dispersed in a constant temperature heat bath of atoms or ions and subject to an external time-independent uniform electric field. The momentum transfer cross section for collisions between the two components is assumed to be a power law in reduced speed. The time-dependent Fokker-Planck equations for both model systems are solved with a numerical finite difference method and the approach to equilibrium is rationalized with the Kullback-Leibler relative entropy. For particular choices of the system parameters for both models, the steady distribution is found to be a Kappa distribution. Kappa distributions were introduced as an empirical fitting function that well describe the nonequilibrium features of the distribution functions of electrons and ions in space science as measured by satellite instruments. The calculation of the Kappa distribution from the Fokker-Planck equations provides a direct physically based dynamical approach in contrast to the nonextensive entropy formalism by Tsallis [J. Stat. Phys. 53, 479 (1988), 10.1007/BF01016429].

Towards a General Theory of Extremes for Observables of Chaotic Dynamical Systems.

PubMed

Lucarini, Valerio; Faranda, Davide; Wouters, Jeroen; Kuna, Tobias

2014-01-01

In this paper we provide a connection between the geometrical properties of the attractor of a chaotic dynamical system and the distribution of extreme values. We show that the extremes of so-called physical observables are distributed according to the classical generalised Pareto distribution and derive explicit expressions for the scaling and the shape parameter. In particular, we derive that the shape parameter does not depend on the chosen observables, but only on the partial dimensions of the invariant measure on the stable, unstable, and neutral manifolds. The shape parameter is negative and is close to zero when high-dimensional systems are considered. This result agrees with what was derived recently using the generalized extreme value approach. Combining the results obtained using such physical observables and the properties of the extremes of distance observables, it is possible to derive estimates of the partial dimensions of the attractor along the stable and the unstable directions of the flow. Moreover, by writing the shape parameter in terms of moments of the extremes of the considered observable and by using linear response theory, we relate the sensitivity to perturbations of the shape parameter to the sensitivity of the moments, of the partial dimensions, and of the Kaplan-Yorke dimension of the attractor. Preliminary numerical investigations provide encouraging results on the applicability of the theory presented here. The results presented here do not apply for all combinations of Axiom A systems and observables, but the breakdown seems to be related to very special geometrical configurations.

Towards a General Theory of Extremes for Observables of Chaotic Dynamical Systems

NASA Astrophysics Data System (ADS)

Lucarini, Valerio; Faranda, Davide; Wouters, Jeroen; Kuna, Tobias

2014-02-01

In this paper we provide a connection between the geometrical properties of the attractor of a chaotic dynamical system and the distribution of extreme values. We show that the extremes of so-called physical observables are distributed according to the classical generalised Pareto distribution and derive explicit expressions for the scaling and the shape parameter. In particular, we derive that the shape parameter does not depend on the chosen observables, but only on the partial dimensions of the invariant measure on the stable, unstable, and neutral manifolds. The shape parameter is negative and is close to zero when high-dimensional systems are considered. This result agrees with what was derived recently using the generalized extreme value approach. Combining the results obtained using such physical observables and the properties of the extremes of distance observables, it is possible to derive estimates of the partial dimensions of the attractor along the stable and the unstable directions of the flow. Moreover, by writing the shape parameter in terms of moments of the extremes of the considered observable and by using linear response theory, we relate the sensitivity to perturbations of the shape parameter to the sensitivity of the moments, of the partial dimensions, and of the Kaplan-Yorke dimension of the attractor. Preliminary numerical investigations provide encouraging results on the applicability of the theory presented here. The results presented here do not apply for all combinations of Axiom A systems and observables, but the breakdown seems to be related to very special geometrical configurations.

Distribution of Quantum Coherence in Multipartite Systems

NASA Astrophysics Data System (ADS)

Radhakrishnan, Chandrashekar; Parthasarathy, Manikandan; Jambulingam, Segar; Byrnes, Tim

2016-04-01

The distribution of coherence in multipartite systems is examined. We use a new coherence measure with entropic nature and metric properties, based on the quantum Jensen-Shannon divergence. The metric property allows for the coherence to be decomposed into various contributions, which arise from local and intrinsic coherences. We find that there are trade-off relations between the various contributions of coherence, as a function of parameters of the quantum state. In bipartite systems the coherence resides on individual sites or is distributed among the sites, which contribute in a complementary way. In more complex systems, the characteristics of the coherence can display more subtle changes with respect to the parameters of the quantum state. In the case of the X X Z Heisenberg model, the coherence changes from a monogamous to a polygamous nature. This allows us to define the shareability of coherence, leading to monogamy relations for coherence.

Numerical weather prediction model tuning via ensemble prediction system

NASA Astrophysics Data System (ADS)

Jarvinen, H.; Laine, M.; Ollinaho, P.; Solonen, A.; Haario, H.

2011-12-01

This paper discusses a novel approach to tune predictive skill of numerical weather prediction (NWP) models. NWP models contain tunable parameters which appear in parameterizations schemes of sub-grid scale physical processes. Currently, numerical values of these parameters are specified manually. In a recent dual manuscript (QJRMS, revised) we developed a new concept and method for on-line estimation of the NWP model parameters. The EPPES ("Ensemble prediction and parameter estimation system") method requires only minimal changes to the existing operational ensemble prediction infra-structure and it seems very cost-effective because practically no new computations are introduced. The approach provides an algorithmic decision making tool for model parameter optimization in operational NWP. In EPPES, statistical inference about the NWP model tunable parameters is made by (i) generating each member of the ensemble of predictions using different model parameter values, drawn from a proposal distribution, and (ii) feeding-back the relative merits of the parameter values to the proposal distribution, based on evaluation of a suitable likelihood function against verifying observations. In the presentation, the method is first illustrated in low-order numerical tests using a stochastic version of the Lorenz-95 model which effectively emulates the principal features of ensemble prediction systems. The EPPES method correctly detects the unknown and wrongly specified parameters values, and leads to an improved forecast skill. Second, results with an atmospheric general circulation model based ensemble prediction system show that the NWP model tuning capacity of EPPES scales up to realistic models and ensemble prediction systems. Finally, a global top-end NWP model tuning exercise with preliminary results is published.

PREDICTING LEAD DISSOLUTION IN DRINKING WATER DISTRIBUTION SYSTEMS: EFFECT OF FLUORIDE ADDITIVES ON LEAD SOLUBILITY AND CORROSION

EPA Science Inventory

Many water systems have encountered difficulties in meeting the action levels established by the Lead and Copper Rule. Several chemical parameters contribute to the corrosion of lead plumbing and may influence the nature of the passivating films formed on distribution materials....

Leveraging AMI data for distribution system model calibration and situational awareness

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

Peppanen, Jouni; Reno, Matthew J.; Thakkar, Mohini

The many new distributed energy resources being installed at the distribution system level require increased visibility into system operations that will be enabled by distribution system state estimation (DSSE) and situational awareness applications. Reliable and accurate DSSE requires both robust methods for managing the big data provided by smart meters and quality distribution system models. This paper presents intelligent methods for detecting and dealing with missing or inaccurate smart meter data, as well as the ways to process the data for different applications. It also presents an efficient and flexible parameter estimation method based on the voltage drop equation andmore » regression analysis to enhance distribution system model accuracy. Finally, it presents a 3-D graphical user interface for advanced visualization of the system state and events. Moreover, we demonstrate this paper for a university distribution network with the state-of-the-art real-time and historical smart meter data infrastructure.« less

Leveraging AMI data for distribution system model calibration and situational awareness

DOE PAGES

Peppanen, Jouni; Reno, Matthew J.; Thakkar, Mohini; ...

2015-01-15

The many new distributed energy resources being installed at the distribution system level require increased visibility into system operations that will be enabled by distribution system state estimation (DSSE) and situational awareness applications. Reliable and accurate DSSE requires both robust methods for managing the big data provided by smart meters and quality distribution system models. This paper presents intelligent methods for detecting and dealing with missing or inaccurate smart meter data, as well as the ways to process the data for different applications. It also presents an efficient and flexible parameter estimation method based on the voltage drop equation andmore » regression analysis to enhance distribution system model accuracy. Finally, it presents a 3-D graphical user interface for advanced visualization of the system state and events. Moreover, we demonstrate this paper for a university distribution network with the state-of-the-art real-time and historical smart meter data infrastructure.« less

Distributed Optimization Design of Continuous-Time Multiagent Systems With Unknown-Frequency Disturbances.

PubMed

Wang, Xinghu; Hong, Yiguang; Yi, Peng; Ji, Haibo; Kang, Yu

2017-05-24

In this paper, a distributed optimization problem is studied for continuous-time multiagent systems with unknown-frequency disturbances. A distributed gradient-based control is proposed for the agents to achieve the optimal consensus with estimating unknown frequencies and rejecting the bounded disturbance in the semi-global sense. Based on convex optimization analysis and adaptive internal model approach, the exact optimization solution can be obtained for the multiagent system disturbed by exogenous disturbances with uncertain parameters.

External calibration of polarimetric radars using point and distributed targets

NASA Technical Reports Server (NTRS)

Yueh, S. H.; Kong, J. A.; Shin, R. T.

1991-01-01

Polarimetric calibration algorithms using combinations of point targets and reciprocal distributed targets are developed. From the reciprocity relations of distributed targets, and equivalent point target response is derived. Then the problem of polarimetric calibration using two point targets and one distributed target reduces to that using three point targets, which has been previously solved. For calibration using one point target and one reciprocal distributed target, two cases are analyzed with the point target being a trihedral reflector or a polarimetric active radar calibrator (PARC). For both cases, the general solutions of the system distortion matrices are written as a product of a particular solution and a matrix with one free parameter. For the trihedral-reflector case, this free parameter is determined by assuming azimuthal symmetry for the distributed target. For the PARC case, knowledge of one ratio of two covariance matrix elements of the distributed target is required to solve for the free parameter. Numerical results are simulated to demonstrate the usefulness of the developed algorithms.

External calibration of polarimetric radars using point and distributed targets

NASA Astrophysics Data System (ADS)

Yueh, S. H.; Kong, J. A.; Shin, R. T.

1991-08-01

Polarimetric calibration algorithms using combinations of point targets and reciprocal distributed targets are developed. From the reciprocity relations of distributed targets, and equivalent point target response is derived. Then the problem of polarimetric calibration using two point targets and one distributed target reduces to that using three point targets, which has been previously solved. For calibration using one point target and one reciprocal distributed target, two cases are analyzed with the point target being a trihedral reflector or a polarimetric active radar calibrator (PARC). For both cases, the general solutions of the system distortion matrices are written as a product of a particular solution and a matrix with one free parameter. For the trihedral-reflector case, this free parameter is determined by assuming azimuthal symmetry for the distributed target. For the PARC case, knowledge of one ratio of two covariance matrix elements of the distributed target is required to solve for the free parameter. Numerical results are simulated to demonstrate the usefulness of the developed algorithms.

Integrated hydraulic and organophosphate pesticide injection simulations for enhancing event detection in water distribution systems.

PubMed

Schwartz, Rafi; Lahav, Ori; Ostfeld, Avi

2014-10-15

As a complementary step towards solving the general event detection problem of water distribution systems, injection of the organophosphate pesticides, chlorpyrifos (CP) and parathion (PA), were simulated at various locations within example networks and hydraulic parameters were calculated over 24-h duration. The uniqueness of this study is that the chemical reactions and byproducts of the contaminants' oxidation were also simulated, as well as other indicative water quality parameters such as alkalinity, acidity, pH and the total concentration of free chlorine species. The information on the change in water quality parameters induced by the contaminant injection may facilitate on-line detection of an actual event involving this specific substance and pave the way to development of a generic methodology for detecting events involving introduction of pesticides into water distribution systems. Simulation of the contaminant injection was performed at several nodes within two different networks. For each injection, concentrations of the relevant contaminants' mother and daughter species, free chlorine species and water quality parameters, were simulated at nodes downstream of the injection location. The results indicate that injection of these substances can be detected at certain conditions by a very rapid drop in Cl2, functioning as the indicative parameter, as well as a drop in alkalinity concentration and a small decrease in pH, both functioning as supporting parameters, whose usage may reduce false positive alarms. Copyright © 2014 Elsevier Ltd. All rights reserved.

MBSSAS: A code for the computation of margules parameters and equilibrium relations in binary solid-solution aqueous-solution systems

USGS Publications Warehouse

Glynn, P.D.

1991-01-01

The computer code MBSSAS uses two-parameter Margules-type excess-free-energy of mixing equations to calculate thermodynamic equilibrium, pure-phase saturation, and stoichiometric saturation states in binary solid-solution aqueous-solution (SSAS) systems. Lippmann phase diagrams, Roozeboom diagrams, and distribution-coefficient diagrams can be constructed from the output data files, and also can be displayed by MBSSAS (on IBM-PC compatible computers). MBSSAS also will calculate accessory information, such as the location of miscibility gaps, spinodal gaps, critical-mixing points, alyotropic extrema, Henry's law solid-phase activity coefficients, and limiting distribution coefficients. Alternatively, MBSSAS can use such information (instead of the Margules, Guggenheim, or Thompson and Waldbaum excess-free-energy parameters) to calculate the appropriate excess-free-energy of mixing equation for any given SSAS system. ?? 1991.

Description of the National Hydrologic Model for use with the Precipitation-Runoff Modeling System (PRMS)

USGS Publications Warehouse

Regan, R. Steven; Markstrom, Steven L.; Hay, Lauren E.; Viger, Roland J.; Norton, Parker A.; Driscoll, Jessica M.; LaFontaine, Jacob H.

2018-01-08

This report documents several components of the U.S. Geological Survey National Hydrologic Model of the conterminous United States for use with the Precipitation-Runoff Modeling System (PRMS). It provides descriptions of the (1) National Hydrologic Model, (2) Geospatial Fabric for National Hydrologic Modeling, (3) PRMS hydrologic simulation code, (4) parameters and estimation methods used to compute spatially and temporally distributed default values as required by PRMS, (5) National Hydrologic Model Parameter Database, and (6) model extraction tool named Bandit. The National Hydrologic Model Parameter Database contains values for all PRMS parameters used in the National Hydrologic Model. The methods and national datasets used to estimate all the PRMS parameters are described. Some parameter values are derived from characteristics of topography, land cover, soils, geology, and hydrography using traditional Geographic Information System methods. Other parameters are set to long-established default values and computation of initial values. Additionally, methods (statistical, sensitivity, calibration, and algebraic) were developed to compute parameter values on the basis of a variety of nationally-consistent datasets. Values in the National Hydrologic Model Parameter Database can periodically be updated on the basis of new parameter estimation methods and as additional national datasets become available. A companion ScienceBase resource provides a set of static parameter values as well as images of spatially-distributed parameters associated with PRMS states and fluxes for each Hydrologic Response Unit across the conterminuous United States.

Advanced electrical power, distribution and control for the Space Transportation System

NASA Astrophysics Data System (ADS)

Hansen, Irving G.; Brandhorst, Henry W., Jr.

1990-08-01

High frequency power distribution and management is a technology ready state of development. As such, a system employs the fewest power conversion steps, and employs zero current switching for those steps. It results in the most efficiency, and lowest total parts system count when equivalent systems are compared. The operating voltage and frequency are application specific trade off parameters. However, a 20 kHz Hertz system is suitable for wide range systems.

Advanced electrical power, distribution and control for the Space Transportation System

NASA Technical Reports Server (NTRS)

Hansen, Irving G.; Brandhorst, Henry W., Jr.

1990-01-01

High frequency power distribution and management is a technology ready state of development. As such, a system employs the fewest power conversion steps, and employs zero current switching for those steps. It results in the most efficiency, and lowest total parts system count when equivalent systems are compared. The operating voltage and frequency are application specific trade off parameters. However, a 20 kHz Hertz system is suitable for wide range systems.

Inverse Gaussian gamma distribution model for turbulence-induced fading in free-space optical communication.

PubMed

Cheng, Mingjian; Guo, Ya; Li, Jiangting; Zheng, Xiaotong; Guo, Lixin

2018-04-20

We introduce an alternative distribution to the gamma-gamma (GG) distribution, called inverse Gaussian gamma (IGG) distribution, which can efficiently describe moderate-to-strong irradiance fluctuations. The proposed stochastic model is based on a modulation process between small- and large-scale irradiance fluctuations, which are modeled by gamma and inverse Gaussian distributions, respectively. The model parameters of the IGG distribution are directly related to atmospheric parameters. The accuracy of the fit among the IGG, log-normal, and GG distributions with the experimental probability density functions in moderate-to-strong turbulence are compared, and results indicate that the newly proposed IGG model provides an excellent fit to the experimental data. As the receiving diameter is comparable with the atmospheric coherence radius, the proposed IGG model can reproduce the shape of the experimental data, whereas the GG and LN models fail to match the experimental data. The fundamental channel statistics of a free-space optical communication system are also investigated in an IGG-distributed turbulent atmosphere, and a closed-form expression for the outage probability of the system is derived with Meijer's G-function.

Characterizing and reducing equifinality by constraining a distributed catchment model with regional signatures, local observations, and process understanding

NASA Astrophysics Data System (ADS)

Kelleher, Christa; McGlynn, Brian; Wagener, Thorsten

2017-07-01

Distributed catchment models are widely used tools for predicting hydrologic behavior. While distributed models require many parameters to describe a system, they are expected to simulate behavior that is more consistent with observed processes. However, obtaining a single set of acceptable parameters can be problematic, as parameter equifinality often results in several behavioral sets that fit observations (typically streamflow). In this study, we investigate the extent to which equifinality impacts a typical distributed modeling application. We outline a hierarchical approach to reduce the number of behavioral sets based on regional, observation-driven, and expert-knowledge-based constraints. For our application, we explore how each of these constraint classes reduced the number of behavioral parameter sets and altered distributions of spatiotemporal simulations, simulating a well-studied headwater catchment, Stringer Creek, Montana, using the distributed hydrology-soil-vegetation model (DHSVM). As a demonstrative exercise, we investigated model performance across 10 000 parameter sets. Constraints on regional signatures, the hydrograph, and two internal measurements of snow water equivalent time series reduced the number of behavioral parameter sets but still left a small number with similar goodness of fit. This subset was ultimately further reduced by incorporating pattern expectations of groundwater table depth across the catchment. Our results suggest that utilizing a hierarchical approach based on regional datasets, observations, and expert knowledge to identify behavioral parameter sets can reduce equifinality and bolster more careful application and simulation of spatiotemporal processes via distributed modeling at the catchment scale.

Computational Control of Flexible Aerospace Systems

NASA Technical Reports Server (NTRS)

Sharpe, Lonnie, Jr.; Shen, Ji Yao

1994-01-01

The main objective of this project is to establish a distributed parameter modeling technique for structural analysis, parameter estimation, vibration suppression and control synthesis of large flexible aerospace structures. This report concentrates on the research outputs produced in the last two years of the project. The main accomplishments can be summarized as follows. A new version of the PDEMOD Code had been completed. A theoretical investigation of the NASA MSFC two-dimensional ground-based manipulator facility by using distributed parameter modelling technique has been conducted. A new mathematical treatment for dynamic analysis and control of large flexible manipulator systems has been conceived, which may provide a embryonic form of a more sophisticated mathematical model for future modified versions of the PDEMOD Codes.

Intelligent decision support algorithm for distribution system restoration.

PubMed

Singh, Reetu; Mehfuz, Shabana; Kumar, Parmod

2016-01-01

Distribution system is the means of revenue for electric utility. It needs to be restored at the earliest if any feeder or complete system is tripped out due to fault or any other cause. Further, uncertainty of the loads, result in variations in the distribution network's parameters. Thus, an intelligent algorithm incorporating hybrid fuzzy-grey relation, which can take into account the uncertainties and compare the sequences is discussed to analyse and restore the distribution system. The simulation studies are carried out to show the utility of the method by ranking the restoration plans for a typical distribution system. This algorithm also meets the smart grid requirements in terms of an automated restoration plan for the partial/full blackout of network.

[Effect on iron release in drinking water distribution systems].

PubMed

Niu, Zhang-bin; Wang, Yang; Zhang, Xiao-jian; Chen, Chao; Wang, Sheng-hui

2007-10-01

Batch-scale experiments were done to quantitatively study the effect of inorganic chemical parameters on iron release in drinking water distribution systems. The parameters include acid-base condition, oxidation-reduction condition, and neutral ion condition. It was found that the iron release rate decreased with pH, alkalinity, the concentration of dissolved oxygen increasing, and the iron release rate increased with the concentration of chloride increasing. The theoretical critical formula of iron release rate was elucidated. According to the formula, the necessary condition for controlling iron release is that pH is above 7.6, the concentration of alkalinity and dissolved oxygen is more than 150 mg/L and 2 mg/L, and the concentration of chloride is less than 150 mg/L of distributed water.

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

Chen, Hang, E-mail: hangchen@mit.edu; Thill, Peter; Cao, Jianshu

In biochemical systems, intrinsic noise may drive the system switch from one stable state to another. We investigate how kinetic switching between stable states in a bistable network is influenced by dynamic disorder, i.e., fluctuations in the rate coefficients. Using the geometric minimum action method, we first investigate the optimal transition paths and the corresponding minimum actions based on a genetic toggle switch model in which reaction coefficients draw from a discrete probability distribution. For the continuous probability distribution of the rate coefficient, we then consider two models of dynamic disorder in which reaction coefficients undergo different stochastic processes withmore » the same stationary distribution. In one, the kinetic parameters follow a discrete Markov process and in the other they follow continuous Langevin dynamics. We find that regulation of the parameters modulating the dynamic disorder, as has been demonstrated to occur through allosteric control in bistable networks in the immune system, can be crucial in shaping the statistics of optimal transition paths, transition probabilities, and the stationary probability distribution of the network.« less

Reflexive reasoning for distributed real-time systems

NASA Technical Reports Server (NTRS)

Goldstein, David

1994-01-01

This paper discusses the implementation and use of reflexive reasoning in real-time, distributed knowledge-based applications. Recently there has been a great deal of interest in agent-oriented systems. Implementing such systems implies a mechanism for sharing knowledge, goals and other state information among the agents. Our techniques facilitate an agent examining both state information about other agents and the parameters of the knowledge-based system shell implementing its reasoning algorithms. The shell implementing the reasoning is the Distributed Artificial Intelligence Toolkit, which is a derivative of CLIPS.

Distributed Parameter Analysis of Pressure and Flow Disturbances in Rocket Propellant Feed Systems

NASA Technical Reports Server (NTRS)

Dorsch, Robert G.; Wood, Don J.; Lightner, Charlene

1966-01-01

A digital distributed parameter model for computing the dynamic response of propellant feed systems is formulated. The analytical approach used is an application of the wave-plan method of analyzing unsteady flow. Nonlinear effects are included. The model takes into account locally high compliances at the pump inlet and at the injector dome region. Examples of the calculated transient and steady-state periodic responses of a simple hypothetical propellant feed system to several types of disturbances are presented. Included are flow disturbances originating from longitudinal structural motion, gimbaling, throttling, and combustion-chamber coupling. The analytical method can be employed for analyzing developmental hardware and offers a flexible tool for the calculation of unsteady flow in these systems.

A novel dispersion compensating fiber grating with a large chirp parameter and period sampled distribution

NASA Astrophysics Data System (ADS)

Xia, Li; Li, Xuhui; Chen, Xiangfei; Xie, Shizhong

2003-11-01

A novel fiber grating structure is proposed for the purpose of dispersion compensation. This kind of grating can be produced with a large chirp parameter and period sampled distribution along the grating length. There are multiple channels in the wide bandwidth and each channel has totally different dispersion and bandwidth. The dispersion compensation effect of this special designed grating is verified through system simulation.

RELATIONSHIPS BETWEEN LEVELS OF HETEROTROPHIC BACTERIA AND WATER QUALITY PARAMETERS IN A DRINKING WATER DISTRIBUTION SYSTEM

EPA Science Inventory

Conventional plating methods were used to quantify heterotrophic bacteria from a drinking water distribution system. Three media, plate count agar (PCA), R2A agar and sheep blood agar (TSA-SB) were used to determine heterotrophic plate count (HPC) levels. Grab samples were collec...

Chloraminated Drinking Water Distribution System Nitrification: Batch and Biofilm Inactivation Studies, Model Nitrifying Biofilm Investigations, and Evaluation of Operational Responses to Nitrification Episodes

EPA Science Inventory

Studies are currently underway to help fill knowledge gaps that exist in the general understanding of nitrification episodes. One of these gaps includes the need for growth and inactivation kinetic parameters for nitrifiers representative of those inhabiting distribution systems ...

Monochloramine Cometabolism by Mixed-Culture Nitrifiers ...

EPA Pesticide Factsheets

The current research investigated monochloramine cometabolism by nitrifying mixed cultures grown under drinking water relevant conditions and harvested from sand-packed reactors before conducting suspended growth batch kinetic experiments. Three batch reactors were used in each experiment: (1) a positive control to estimate ammonia kinetic parameters, (2) a negative control to account for abiotic reactions, and (3) a cometabolism reactor to estimate cometabolism kinetic constants. Kinetic parameters were estimated in AQUASIM with a simultaneous fit to all experimental data. Cometabolism kinetics were best described by a first order model. Monochloramine cometabolism kinetics were similar to those of ammonia metabolism, and monochloramine cometabolism was a significant loss mechanism (30% of the observed monochloramine loss). These results demonstrated that monochloramine cometabolism occurred in mixed cultures similar to those found in drinking water distribution systems; thus, cometabolism may be a significant contribution to monochloramine loss during nitrification episodes in drinking water distribution systems. The results demonstrated that monochloramine cometabolism occurred in mixed cultures similar to those found in drinking water distribution systems; thus, cometabolism may be a significant contribution to monochloramine loss during nitrification episodes in drinking water distribution systems.

Autonomic Management in a Distributed Storage System

NASA Astrophysics Data System (ADS)

Tauber, Markus

2010-07-01

This thesis investigates the application of autonomic management to a distributed storage system. Effects on performance and resource consumption were measured in experiments, which were carried out in a local area test-bed. The experiments were conducted with components of one specific distributed storage system, but seek to be applicable to a wide range of such systems, in particular those exposed to varying conditions. The perceived characteristics of distributed storage systems depend on their configuration parameters and on various dynamic conditions. For a given set of conditions, one specific configuration may be better than another with respect to measures such as resource consumption and performance. Here, configuration parameter values were set dynamically and the results compared with a static configuration. It was hypothesised that under non-changing conditions this would allow the system to converge on a configuration that was more suitable than any that could be set a priori. Furthermore, the system could react to a change in conditions by adopting a more appropriate configuration. Autonomic management was applied to the peer-to-peer (P2P) and data retrieval components of ASA, a distributed storage system. The effects were measured experimentally for various workload and churn patterns. The management policies and mechanisms were implemented using a generic autonomic management framework developed during this work. The experimental evaluations of autonomic management show promising results, and suggest several future research topics. The findings of this thesis could be exploited in building other distributed storage systems that focus on harnessing storage on user workstations, since these are particularly likely to be exposed to varying, unpredictable conditions.

Statistics of the work done on a quantum critical system by quenching a control parameter.

PubMed

Silva, Alessandro

2008-09-19

We study the statistics of the work done on a quantum critical system by quenching a control parameter in the Hamiltonian. We elucidate the relation between the probability distribution of the work and the Loschmidt echo, a quantity emerging usually in the context of dephasing. Using this connection we characterize the statistics of the work done on a quantum Ising chain by quenching locally or globally the transverse field. We show that for local quenches starting at criticality the probability distribution of the work displays an interesting edge singularity.

Adjustable Parameter-Based Distributed Fault Estimation Observer Design for Multiagent Systems With Directed Graphs.

PubMed

Zhang, Ke; Jiang, Bin; Shi, Peng

2017-02-01

In this paper, a novel adjustable parameter (AP)-based distributed fault estimation observer (DFEO) is proposed for multiagent systems (MASs) with the directed communication topology. First, a relative output estimation error is defined based on the communication topology of MASs. Then a DFEO with AP is constructed with the purpose of improving the accuracy of fault estimation. Based on H ∞ and H 2 with pole placement, multiconstrained design is given to calculate the gain of DFEO. Finally, simulation results are presented to illustrate the feasibility and effectiveness of the proposed DFEO design with AP.

The role of extreme orbits in the global organization of periodic regions in parameter space for one dimensional maps

NASA Astrophysics Data System (ADS)

da Costa, Diogo Ricardo; Hansen, Matheus; Guarise, Gustavo; Medrano-T, Rene O.; Leonel, Edson D.

2016-04-01

We show that extreme orbits, trajectories that connect local maximum and minimum values of one dimensional maps, play a major role in the parameter space of dissipative systems dictating the organization for the windows of periodicity, hence producing sets of shrimp-like structures. Here we solve three fundamental problems regarding the distribution of these sets and give: (i) their precise localization in the parameter space, even for sets of very high periods; (ii) their local and global distributions along cascades; and (iii) the association of these cascades to complicate sets of periodicity. The extreme orbits are proved to be a powerful indicator to investigate the organization of windows of periodicity in parameter planes. As applications of the theory, we obtain some results for the circle map and perturbed logistic map. The formalism presented here can be extended to many other different nonlinear and dissipative systems.

Optimal control of first order distributed systems. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Johnson, T. L.

1972-01-01

The problem of characterizing optimal controls for a class of distributed-parameter systems is considered. The system dynamics are characterized mathematically by a finite number of coupled partial differential equations involving first-order time and space derivatives of the state variables, which are constrained at the boundary by a finite number of algebraic relations. Multiple control inputs, extending over the entire spatial region occupied by the system ("distributed controls') are to be designed so that the response of the system is optimal. A major example involving boundary control of an unstable low-density plasma is developed from physical laws.

Model Calibration in Watershed Hydrology

NASA Technical Reports Server (NTRS)

Yilmaz, Koray K.; Vrugt, Jasper A.; Gupta, Hoshin V.; Sorooshian, Soroosh

2009-01-01

Hydrologic models use relatively simple mathematical equations to conceptualize and aggregate the complex, spatially distributed, and highly interrelated water, energy, and vegetation processes in a watershed. A consequence of process aggregation is that the model parameters often do not represent directly measurable entities and must, therefore, be estimated using measurements of the system inputs and outputs. During this process, known as model calibration, the parameters are adjusted so that the behavior of the model approximates, as closely and consistently as possible, the observed response of the hydrologic system over some historical period of time. This Chapter reviews the current state-of-the-art of model calibration in watershed hydrology with special emphasis on our own contributions in the last few decades. We discuss the historical background that has led to current perspectives, and review different approaches for manual and automatic single- and multi-objective parameter estimation. In particular, we highlight the recent developments in the calibration of distributed hydrologic models using parameter dimensionality reduction sampling, parameter regularization and parallel computing.

Decoupled ARX and RBF Neural Network Modeling Using PCA and GA Optimization for Nonlinear Distributed Parameter Systems.

PubMed

Zhang, Ridong; Tao, Jili; Lu, Renquan; Jin, Qibing

2018-02-01

Modeling of distributed parameter systems is difficult because of their nonlinearity and infinite-dimensional characteristics. Based on principal component analysis (PCA), a hybrid modeling strategy that consists of a decoupled linear autoregressive exogenous (ARX) model and a nonlinear radial basis function (RBF) neural network model are proposed. The spatial-temporal output is first divided into a few dominant spatial basis functions and finite-dimensional temporal series by PCA. Then, a decoupled ARX model is designed to model the linear dynamics of the dominant modes of the time series. The nonlinear residual part is subsequently parameterized by RBFs, where genetic algorithm is utilized to optimize their hidden layer structure and the parameters. Finally, the nonlinear spatial-temporal dynamic system is obtained after the time/space reconstruction. Simulation results of a catalytic rod and a heat conduction equation demonstrate the effectiveness of the proposed strategy compared to several other methods.

Modular sensor network node

DOEpatents

Davis, Jesse Harper Zehring [Berkeley, CA; Stark, Jr., Douglas Paul; Kershaw, Christopher Patrick [Hayward, CA; Kyker, Ronald Dean [Livermore, CA

2008-06-10

A distributed wireless sensor network node is disclosed. The wireless sensor network node includes a plurality of sensor modules coupled to a system bus and configured to sense a parameter. The parameter may be an object, an event or any other parameter. The node collects data representative of the parameter. The node also includes a communication module coupled to the system bus and configured to allow the node to communicate with other nodes. The node also includes a processing module coupled to the system bus and adapted to receive the data from the sensor module and operable to analyze the data. The node also includes a power module connected to the system bus and operable to generate a regulated voltage.

Using Approximate Bayesian Computation to Probe Multiple Transiting Planet Systems

NASA Astrophysics Data System (ADS)

Morehead, Robert C.

2015-08-01

The large number of multiple transiting planet systems (MTPS) uncovered with Kepler suggest a population of well-aligned planetary systems. Previously, the distribution of transit duration ratios in MTPSs has been used to place constraints on the distributions of mutual orbital inclinations and orbital eccentricities in these systems. However, degeneracies with the underlying number of planets in these systems pose added challenges and make explicit likelihood functions intractable. Approximate Bayesian computation (ABC) offers an intriguing path forward. In its simplest form, ABC proposes from a prior on the population parameters to produce synthetic datasets via a physically-motivated model. Samples are accepted or rejected based on how close they come to reproducing the actual observed dataset to some tolerance. The accepted samples then form a robust and useful approximation of the true posterior distribution of the underlying population parameters. We will demonstrate the utility of ABC in exoplanet populations by presenting new constraints on the mutual inclination and eccentricity distributions in the Kepler MTPSs. We will also introduce Simple-ABC, a new open-source Python package designed for ease of use and rapid specification of general models, suitable for use in a wide variety of applications in both exoplanet science and astrophysics as a whole.

Feature Selection and Parameters Optimization of SVM Using Particle Swarm Optimization for Fault Classification in Power Distribution Systems.

PubMed

Cho, Ming-Yuan; Hoang, Thi Thom

2017-01-01

Fast and accurate fault classification is essential to power system operations. In this paper, in order to classify electrical faults in radial distribution systems, a particle swarm optimization (PSO) based support vector machine (SVM) classifier has been proposed. The proposed PSO based SVM classifier is able to select appropriate input features and optimize SVM parameters to increase classification accuracy. Further, a time-domain reflectometry (TDR) method with a pseudorandom binary sequence (PRBS) stimulus has been used to generate a dataset for purposes of classification. The proposed technique has been tested on a typical radial distribution network to identify ten different types of faults considering 12 given input features generated by using Simulink software and MATLAB Toolbox. The success rate of the SVM classifier is over 97%, which demonstrates the effectiveness and high efficiency of the developed method.

High spatial resolution distributed fiber system for multi-parameter sensing based on modulated pulses.

PubMed

Zhang, Jingdong; Zhu, Tao; Zhou, Huan; Huang, Shihong; Liu, Min; Huang, Wei

2016-11-28

We demonstrate a cost-effective distributed fiber sensing system for the multi-parameter detection of the vibration, the temperature, and the strain by integrating phase-sensitive optical time domain reflectometry (φ-OTDR) and Brillouin optical time domain reflectometry (B-OTDR). Taking advantage of the fast changing property of the vibration and the static properties of the temperature and the strain, both the width and intensity of the laser pulses are modulated and injected into the single-mode sensing fiber proportionally, so that three concerned parameters can be extracted simultaneously by only one photo-detector and one data acquisition channel. A data processing method based on Gaussian window short time Fourier transform (G-STFT) is capable of achieving high spatial resolution in B-OTDR. The experimental results show that up to 4.8kHz vibration sensing with 3m spatial resolution at 10km standard single-mode fiber can be realized, as well as the distributed temperature and stress profiles along the same fiber with 80cm spatial resolution.

Using a GIS to link digital spatial data and the precipitation-runoff modeling system, Gunnison River Basin, Colorado

USGS Publications Warehouse

Battaglin, William A.; Kuhn, Gerhard; Parker, Randolph S.

1993-01-01

The U.S. Geological Survey Precipitation-Runoff Modeling System, a modular, distributed-parameter, watershed-modeling system, is being applied to 20 smaller watersheds within the Gunnison River basin. The model is used to derive a daily water balance for subareas in a watershed, ultimately producing simulated streamflows that can be input into routing and accounting models used to assess downstream water availability under current conditions, and to assess the sensitivity of water resources in the basin to alterations in climate. A geographic information system (GIS) is used to automate a method for extracting physically based hydrologic response unit (HRU) distributed parameter values from digital data sources, and for the placement of those estimates into GIS spatial datalayers. The HRU parameters extracted are: area, mean elevation, average land-surface slope, predominant aspect, predominant land-cover type, predominant soil type, average total soil water-holding capacity, and average water-holding capacity of the root zone.

The Shock and Vibration Digest, Volume 18, Number 3

DTIC Science & Technology

1986-03-01

Linear Distributed Parameter Des., Proc. Intl. Symp., 11th ONR Naval Struc. Systems by Shifted Legendre Polynomial Func- Mech. Symp., Tucson, AZ, pp...University, Atlanta, Georgia nonlinear problems with elementary algebra . It J. Sound Vib., 102 (2), pp 247-257 (Sept 22, uses i = -1, the Pascal’s...eigenvalues specified. The optimal avoid failure due to resonance under the action control problem of a linear distributed parameter 0School of Mechanical

Distributed adaptive asymptotically consensus tracking control of uncertain Euler-Lagrange systems under directed graph condition.

PubMed

Wang, Wei; Wen, Changyun; Huang, Jiangshuai; Fan, Huijin

2017-11-01

In this paper, a backstepping based distributed adaptive control scheme is proposed for multiple uncertain Euler-Lagrange systems under directed graph condition. The common desired trajectory is allowed totally unknown by part of the subsystems and the linearly parameterized trajectory model assumed in currently available results is no longer needed. To compensate the effects due to unknown trajectory information, a smooth function of consensus errors and certain positive integrable functions are introduced in designing virtual control inputs. Besides, to overcome the difficulty of completely counteracting the coupling terms of distributed consensus errors and parameter estimation errors in the presence of asymmetric Laplacian matrix, extra information transmission of local parameter estimates are introduced among linked subsystem and adaptive gain technique is adopted to generate distributed torque inputs. It is shown that with the proposed distributed adaptive control scheme, global uniform boundedness of all the closed-loop signals and asymptotically output consensus tracking can be achieved. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

A trans-dimensional Bayesian Markov chain Monte Carlo algorithm for model assessment using frequency-domain electromagnetic data

USGS Publications Warehouse

Minsley, Burke J.

2011-01-01

A meaningful interpretation of geophysical measurements requires an assessment of the space of models that are consistent with the data, rather than just a single, ‘best’ model which does not convey information about parameter uncertainty. For this purpose, a trans-dimensional Bayesian Markov chain Monte Carlo (MCMC) algorithm is developed for assessing frequencydomain electromagnetic (FDEM) data acquired from airborne or ground-based systems. By sampling the distribution of models that are consistent with measured data and any prior knowledge, valuable inferences can be made about parameter values such as the likely depth to an interface, the distribution of possible resistivity values as a function of depth and non-unique relationships between parameters. The trans-dimensional aspect of the algorithm allows the number of layers to be a free parameter that is controlled by the data, where models with fewer layers are inherently favoured, which provides a natural measure of parsimony and a significant degree of flexibility in parametrization. The MCMC algorithm is used with synthetic examples to illustrate how the distribution of acceptable models is affected by the choice of prior information, the system geometry and configuration and the uncertainty in the measured system elevation. An airborne FDEM data set that was acquired for the purpose of hydrogeological characterization is also studied. The results compare favorably with traditional least-squares analysis, borehole resistivity and lithology logs from the site, and also provide new information about parameter uncertainty necessary for model assessment.

Bayesian calibration of mechanistic aquatic biogeochemical models and benefits for environmental management

NASA Astrophysics Data System (ADS)

Arhonditsis, George B.; Papantou, Dimitra; Zhang, Weitao; Perhar, Gurbir; Massos, Evangelia; Shi, Molu

2008-09-01

Aquatic biogeochemical models have been an indispensable tool for addressing pressing environmental issues, e.g., understanding oceanic response to climate change, elucidation of the interplay between plankton dynamics and atmospheric CO 2 levels, and examination of alternative management schemes for eutrophication control. Their ability to form the scientific basis for environmental management decisions can be undermined by the underlying structural and parametric uncertainty. In this study, we outline how we can attain realistic predictive links between management actions and ecosystem response through a probabilistic framework that accommodates rigorous uncertainty analysis of a variety of error sources, i.e., measurement error, parameter uncertainty, discrepancy between model and natural system. Because model uncertainty analysis essentially aims to quantify the joint probability distribution of model parameters and to make inference about this distribution, we believe that the iterative nature of Bayes' Theorem is a logical means to incorporate existing knowledge and update the joint distribution as new information becomes available. The statistical methodology begins with the characterization of parameter uncertainty in the form of probability distributions, then water quality data are used to update the distributions, and yield posterior parameter estimates along with predictive uncertainty bounds. Our illustration is based on a six state variable (nitrate, ammonium, dissolved organic nitrogen, phytoplankton, zooplankton, and bacteria) ecological model developed for gaining insight into the mechanisms that drive plankton dynamics in a coastal embayment; the Gulf of Gera, Island of Lesvos, Greece. The lack of analytical expressions for the posterior parameter distributions was overcome using Markov chain Monte Carlo simulations; a convenient way to obtain representative samples of parameter values. The Bayesian calibration resulted in realistic reproduction of the key temporal patterns of the system, offered insights into the degree of information the data contain about model inputs, and also allowed the quantification of the dependence structure among the parameter estimates. Finally, our study uses two synthetic datasets to examine the ability of the updated model to provide estimates of predictive uncertainty for water quality variables of environmental management interest.

Numerical studies of identification in nonlinear distributed parameter systems

NASA Technical Reports Server (NTRS)

Banks, H. T.; Lo, C. K.; Reich, Simeon; Rosen, I. G.

1989-01-01

An abstract approximation framework and convergence theory for the identification of first and second order nonlinear distributed parameter systems developed previously by the authors and reported on in detail elsewhere are summarized and discussed. The theory is based upon results for systems whose dynamics can be described by monotone operators in Hilbert space and an abstract approximation theorem for the resulting nonlinear evolution system. The application of the theory together with numerical evidence demonstrating the feasibility of the general approach are discussed in the context of the identification of a first order quasi-linear parabolic model for one dimensional heat conduction/mass transport and the identification of a nonlinear dissipation mechanism (i.e., damping) in a second order one dimensional wave equation. Computational and implementational considerations, in particular, with regard to supercomputing, are addressed.

Characterization and Remediation of Contaminated Sites:Modeling, Measurement and Assessment

NASA Astrophysics Data System (ADS)

Basu, N. B.; Rao, P. C.; Poyer, I. C.; Christ, J. A.; Zhang, C. Y.; Jawitz, J. W.; Werth, C. J.; Annable, M. D.; Hatfield, K.

2008-05-01

The complexity of natural systems makes it impossible to estimate parameters at the required level of spatial and temporal detail. Thus, it becomes necessary to transition from spatially distributed parameters to spatially integrated parameters that are capable of adequately capturing the system dynamics, without always accounting for local process behavior. Contaminant flux across the source control plane is proposed as an integrated metric that captures source behavior and links it to plume dynamics. Contaminant fluxes were measured using an innovative technology, the passive flux meter at field sites contaminated with dense non-aqueous phase liquids or DNAPLs in the US and Australia. Flux distributions were observed to be positively or negatively correlated with the conductivity distribution, depending on the source characteristics of the site. The impact of partial source depletion on the mean contaminant flux and flux architecture was investigated in three-dimensional complex heterogeneous settings using the multiphase transport code UTCHEM and the reactive transport code ISCO3D. Source mass depletion reduced the mean contaminant flux approximately linearly, while the contaminant flux standard deviation reduced proportionally with the mean (i.e., coefficient of variation of flux distribution is constant with time). Similar analysis was performed using data from field sites, and the results confirmed the numerical simulations. The linearity of the mass depletion-flux reduction relationship indicates the ability to design remediation systems that deplete mass to achieve target reduction in source strength. Stability of the flux distribution indicates the ability to characterize the distributions in time once the initial distribution is known. Lagrangian techniques were used to predict contaminant flux behavior during source depletion in terms of the statistics of the hydrodynamic and DNAPL distribution. The advantage of the Lagrangian techniques lies in their small computation time and their inclusion of spatially integrated parameters that can be measured in the field using tracer tests. Analytical models that couple source depletion to plume transport were used for optimization of source and plume treatment. These models are being used for the development of decision and management tools (for DNAPL sites) that consider uncertainty assessments as an integral part of the decision-making process for contaminated site remediation.

Contents of the NASA ocean data system archive, version 11-90

NASA Technical Reports Server (NTRS)

Smith, Elizabeth A. (Editor); Lassanyi, Ruby A. (Editor)

1990-01-01

The National Aeronautics and Space Administration (NASA) Ocean Data System (NODS) archive at the Jet Propulsion Laboratory (JPL) includes satellite data sets for the ocean sciences and global-change research to facilitate multidisciplinary use of satellite ocean data. Parameters include sea-surface height, surface-wind vector, sea-surface temperature, atmospheric liquid water, and surface pigment concentration. NODS will become the Data Archive and Distribution Service of the JPL Distributed Active Archive Center for the Earth Observing System Data and Information System (EOSDIS) and will be the United States distribution site for Ocean Topography Experiment (TOPEX)/POSEIDON data and metadata.

More Effective Distributed ML via a Stale Synchronous Parallel Parameter Server

PubMed Central

Ho, Qirong; Cipar, James; Cui, Henggang; Kim, Jin Kyu; Lee, Seunghak; Gibbons, Phillip B.; Gibson, Garth A.; Ganger, Gregory R.; Xing, Eric P.

2014-01-01

We propose a parameter server system for distributed ML, which follows a Stale Synchronous Parallel (SSP) model of computation that maximizes the time computational workers spend doing useful work on ML algorithms, while still providing correctness guarantees. The parameter server provides an easy-to-use shared interface for read/write access to an ML model’s values (parameters and variables), and the SSP model allows distributed workers to read older, stale versions of these values from a local cache, instead of waiting to get them from a central storage. This significantly increases the proportion of time workers spend computing, as opposed to waiting. Furthermore, the SSP model ensures ML algorithm correctness by limiting the maximum age of the stale values. We provide a proof of correctness under SSP, as well as empirical results demonstrating that the SSP model achieves faster algorithm convergence on several different ML problems, compared to fully-synchronous and asynchronous schemes. PMID:25400488

Quality of the log-geometric distribution extrapolation for smaller undiscovered oil and gas pool size

USGS Publications Warehouse

Chenglin, L.; Charpentier, R.R.

2010-01-01

The U.S. Geological Survey procedure for the estimation of the general form of the parent distribution requires that the parameters of the log-geometric distribution be calculated and analyzed for the sensitivity of these parameters to different conditions. In this study, we derive the shape factor of a log-geometric distribution from the ratio of frequencies between adjacent bins. The shape factor has a log straight-line relationship with the ratio of frequencies. Additionally, the calculation equations of a ratio of the mean size to the lower size-class boundary are deduced. For a specific log-geometric distribution, we find that the ratio of the mean size to the lower size-class boundary is the same. We apply our analysis to simulations based on oil and gas pool distributions from four petroleum systems of Alberta, Canada and four generated distributions. Each petroleum system in Alberta has a different shape factor. Generally, the shape factors in the four petroleum systems stabilize with the increase of discovered pool numbers. For a log-geometric distribution, the shape factor becomes stable when discovered pool numbers exceed 50 and the shape factor is influenced by the exploration efficiency when the exploration efficiency is less than 1. The simulation results show that calculated shape factors increase with those of the parent distributions, and undiscovered oil and gas resources estimated through the log-geometric distribution extrapolation are smaller than the actual values. ?? 2010 International Association for Mathematical Geology.

Efficient Round-Trip Time Optimization for Replica-Exchange Enveloping Distribution Sampling (RE-EDS).

PubMed

Sidler, Dominik; Cristòfol-Clough, Michael; Riniker, Sereina

2017-06-13

Replica-exchange enveloping distribution sampling (RE-EDS) allows the efficient estimation of free-energy differences between multiple end-states from a single molecular dynamics (MD) simulation. In EDS, a reference state is sampled, which can be tuned by two types of parameters, i.e., smoothness parameters(s) and energy offsets, such that all end-states are sufficiently sampled. However, the choice of these parameters is not trivial. Replica exchange (RE) or parallel tempering is a widely applied technique to enhance sampling. By combining EDS with the RE technique, the parameter choice problem could be simplified and the challenge shifted toward an optimal distribution of the replicas in the smoothness-parameter space. The choice of a certain replica distribution can alter the sampling efficiency significantly. In this work, global round-trip time optimization (GRTO) algorithms are tested for the use in RE-EDS simulations. In addition, a local round-trip time optimization (LRTO) algorithm is proposed for systems with slowly adapting environments, where a reliable estimate for the round-trip time is challenging to obtain. The optimization algorithms were applied to RE-EDS simulations of a system of nine small-molecule inhibitors of phenylethanolamine N-methyltransferase (PNMT). The energy offsets were determined using our recently proposed parallel energy-offset (PEOE) estimation scheme. While the multistate GRTO algorithm yielded the best replica distribution for the ligands in water, the multistate LRTO algorithm was found to be the method of choice for the ligands in complex with PNMT. With this, the 36 alchemical free-energy differences between the nine ligands were calculated successfully from a single RE-EDS simulation 10 ns in length. Thus, RE-EDS presents an efficient method for the estimation of relative binding free energies.

Accuracy of time-domain and frequency-domain methods used to characterize catchment transit time distributions

NASA Astrophysics Data System (ADS)

Godsey, S. E.; Kirchner, J. W.

2008-12-01

The mean residence time - the average time that it takes rainfall to reach the stream - is a basic parameter used to characterize catchment processes. Heterogeneities in these processes lead to a distribution of travel times around the mean residence time. By examining this travel time distribution, we can better predict catchment response to contamination events. A catchment system with shorter residence times or narrower distributions will respond quickly to contamination events, whereas systems with longer residence times or longer-tailed distributions will respond more slowly to those same contamination events. The travel time distribution of a catchment is typically inferred from time series of passive tracers (e.g., water isotopes or chloride) in precipitation and streamflow. Variations in the tracer concentration in streamflow are usually damped compared to those in precipitation, because precipitation inputs from different storms (with different tracer signatures) are mixed within the catchment. Mathematically, this mixing process is represented by the convolution of the travel time distribution and the precipitation tracer inputs to generate the stream tracer outputs. Because convolution in the time domain is equivalent to multiplication in the frequency domain, it is relatively straightforward to estimate the parameters of the travel time distribution in either domain. In the time domain, the parameters describing the travel time distribution are typically estimated by maximizing the goodness of fit between the modeled and measured tracer outputs. In the frequency domain, the travel time distribution parameters can be estimated by fitting a power-law curve to the ratio of precipitation spectral power to stream spectral power. Differences between the methods of parameter estimation in the time and frequency domain mean that these two methods may respond differently to variations in data quality, record length and sampling frequency. Here we evaluate how well these two methods of travel time parameter estimation respond to different sources of uncertainty and compare the methods to one another. We do this by generating synthetic tracer input time series of different lengths, and convolve these with specified travel-time distributions to generate synthetic output time series. We then sample both the input and output time series at various sampling intervals and corrupt the time series with realistic error structures. Using these 'corrupted' time series, we infer the apparent travel time distribution, and compare it to the known distribution that was used to generate the synthetic data in the first place. This analysis allows us to quantify how different record lengths, sampling intervals, and error structures in the tracer measurements affect the apparent mean residence time and the apparent shape of the travel time distribution.

Estimation of discontinuous coefficients in parabolic systems: Applications to reservoir simulation

NASA Technical Reports Server (NTRS)

Lamm, P. D.

1984-01-01

Spline based techniques for estimating spatially varying parameters that appear in parabolic distributed systems (typical of those found in reservoir simulation problems) are presented. The problem of determining discontinuous coefficients, estimating both the functional shape and points of discontinuity for such parameters is discussed. Convergence results and a summary of numerical performance of the resulting algorithms are given.

Dynamical phase transitions in generalized Kuramoto model with distributed Sakaguchi phase

NASA Astrophysics Data System (ADS)

Banerjee, Amitava

2017-11-01

In this numerical work, we have systematically studied the dynamical phase transitions in the Kuramoto-Sakaguchi model of synchronizing phase oscillators controlled by disorder in the Sakaguchi phases. We derive the numerical steady state phase diagrams for quenched and annealed kinds of disorder in the Sakaguchi parameters, using the conventional order parameter and other such statistical quantities as strength of incoherence and discontinuity measures. We have also considered the correlation profile of the local order parameter fluctuations in the various phases identified. The phase diagrams for quenched disorder are qualitatively much different from those in the global coupling regime. The order of various transitions is confirmed by a study of the distribution of the order parameter and its fourth order Binder’s cumulant across the transition for an ensemble of initial distribution of phases. For the annealed type of disorder, in contrast to the case with quenched disorder, the system is almost insensitive to the amount of disorder. We also elucidate the role of chimeralike states in the synchronizing transition of the system, and study the effect of disorder on these states. Finally, we seek justification of our results from simulations guided by the Ott-Antonsen ansatz.

The Approximate Bayesian Computation methods in the localization of the atmospheric contamination source

NASA Astrophysics Data System (ADS)

Kopka, P.; Wawrzynczak, A.; Borysiewicz, M.

2015-09-01

In many areas of application, a central problem is a solution to the inverse problem, especially estimation of the unknown model parameters to model the underlying dynamics of a physical system precisely. In this situation, the Bayesian inference is a powerful tool to combine observed data with prior knowledge to gain the probability distribution of searched parameters. We have applied the modern methodology named Sequential Approximate Bayesian Computation (S-ABC) to the problem of tracing the atmospheric contaminant source. The ABC is technique commonly used in the Bayesian analysis of complex models and dynamic system. Sequential methods can significantly increase the efficiency of the ABC. In the presented algorithm, the input data are the on-line arriving concentrations of released substance registered by distributed sensor network from OVER-LAND ATMOSPHERIC DISPERSION (OLAD) experiment. The algorithm output are the probability distributions of a contamination source parameters i.e. its particular location, release rate, speed and direction of the movement, start time and duration. The stochastic approach presented in this paper is completely general and can be used in other fields where the parameters of the model bet fitted to the observable data should be found.

Determination of the Nucleon-Nucleon Interaction in the ImQMD Model by Nuclear Reactions at Fermi Energy

NASA Astrophysics Data System (ADS)

Li, Cheng; Tian, Jun-Long; Wang, Ning

2013-11-01

The nucleon-nucleon interaction is investigated by using the ImQMD model with the three sets of parameters IQ1, IQ2 and IQ3 in which the corresponding incompressibility coefficients of nuclear matter are different. Fusion excitation function and the charge distribution of fragments are calculated for reaction systems 40Ca+40Ca at different incident energies. It is found that obvious differences in the charge distribution were observed at the energy region 10-25A MeV by adopting the three sets of parameters, while the results were close to each other at energy region of 30-45A MeV for the reaction system. It indicates that the Fermi energy region is a sensitive energy region to explore the N-N interaction. The fragment multiplicity spectrum for 238U+197Au at 15A MeV are reproduced by the ImQMD model with the set of parameter IQ3. It is concluded that charge distribution of the fragments and the fragment multiplicity spectrum are good observables for studying N-N interaction, and IQ3 is a suitable set of parameters for the ImQMD model.

Universal inverse power-law distribution for temperature and rainfall in the UK region

NASA Astrophysics Data System (ADS)

Selvam, A. M.

2014-06-01

Meteorological parameters, such as temperature, rainfall, pressure, etc., exhibit selfsimilar space-time fractal fluctuations generic to dynamical systems in nature such as fluid flows, spread of forest fires, earthquakes, etc. The power spectra of fractal fluctuations display inverse power-law form signifying long-range correlations. A general systems theory model predicts universal inverse power-law form incorporating the golden mean for the fractal fluctuations. The model predicted distribution was compared with observed distribution of fractal fluctuations of all size scales (small, large and extreme values) in the historic month-wise temperature (maximum and minimum) and total rainfall for the four stations Oxford, Armagh, Durham and Stornoway in the UK region, for data periods ranging from 92 years to 160 years. For each parameter, the two cumulative probability distributions, namely cmax and cmin starting from respectively maximum and minimum data value were used. The results of the study show that (i) temperature distributions (maximum and minimum) follow model predicted distribution except for Stornowy, minimum temperature cmin. (ii) Rainfall distribution for cmin follow model predicted distribution for all the four stations. (iii) Rainfall distribution for cmax follows model predicted distribution for the two stations Armagh and Stornoway. The present study suggests that fractal fluctuations result from the superimposition of eddy continuum fluctuations.

Model Predictive Optimal Control of a Time-Delay Distributed-Parameter Systems

NASA Technical Reports Server (NTRS)

Nguyen, Nhan

2006-01-01

This paper presents an optimal control method for a class of distributed-parameter systems governed by first order, quasilinear hyperbolic partial differential equations that arise in many physical systems. Such systems are characterized by time delays since information is transported from one state to another by wave propagation. A general closed-loop hyperbolic transport model is controlled by a boundary control embedded in a periodic boundary condition. The boundary control is subject to a nonlinear differential equation constraint that models actuator dynamics of the system. The hyperbolic equation is thus coupled with the ordinary differential equation via the boundary condition. Optimality of this coupled system is investigated using variational principles to seek an adjoint formulation of the optimal control problem. The results are then applied to implement a model predictive control design for a wind tunnel to eliminate a transport delay effect that causes a poor Mach number regulation.

pT spectra in pp and AA collisions at RHIC and LHC energies using the Tsallis-Weibull approach

NASA Astrophysics Data System (ADS)

Dash, Sadhana; Mahapatra, D. P.

2018-04-01

The Tsallis q -statistics have been incorporated in the Weibull model of particle production, in the form of q-Weibull distribution, to describe the transverse momentum (pT) distribution of charged hadrons at mid-rapidity, measured at RHIC and LHC energies. The q-Weibull distribution is found to describe the observed pT distributions over all ranges of measured pT. Below 2.2 GeV/c, while going from peripheral to central collisions, the parameter q is found to decrease systematically towards unity, indicating an evolution from a non-equilibrated system in peripheral collisions, towards a more thermalized system in central collisions. However, the trend is reversed in the all inclusive pT regime. This can be attributed to an increase in relative contribution of hard pQCD processes in central collisions. The λ-parameter is found to be associated with the mean pT or the collective expansion velocity of the produced hadrons, which shows an expected increase with centrality of collisions. The k parameter is observed to increase with the onset of hard QCD scatterings, initial fluctuations, and other processes leading to non-equilibrium conditions.

Generalized correlation integral vectors: A distance concept for chaotic dynamical systems

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

Haario, Heikki, E-mail: heikki.haario@lut.fi; Kalachev, Leonid, E-mail: KalachevL@mso.umt.edu; Hakkarainen, Janne

2015-06-15

Several concepts of fractal dimension have been developed to characterise properties of attractors of chaotic dynamical systems. Numerical approximations of them must be calculated by finite samples of simulated trajectories. In principle, the quantities should not depend on the choice of the trajectory, as long as it provides properly distributed samples of the underlying attractor. In practice, however, the trajectories are sensitive with respect to varying initial values, small changes of the model parameters, to the choice of a solver, numeric tolerances, etc. The purpose of this paper is to present a statistically sound approach to quantify this variability. Wemore » modify the concept of correlation integral to produce a vector that summarises the variability at all selected scales. The distribution of this stochastic vector can be estimated, and it provides a statistical distance concept between trajectories. Here, we demonstrate the use of the distance for the purpose of estimating model parameters of a chaotic dynamic model. The methodology is illustrated using computational examples for the Lorenz 63 and Lorenz 95 systems, together with a framework for Markov chain Monte Carlo sampling to produce posterior distributions of model parameters.« less

Possible ergodic-nonergodic regions in the quantum Sherrington-Kirkpatrick spin glass model and quantum annealing

NASA Astrophysics Data System (ADS)

Mukherjee, Sudip; Rajak, Atanu; Chakrabarti, Bikas K.

2018-02-01

We explore the behavior of the order parameter distribution of the quantum Sherrington-Kirkpatrick model in the spin glass phase using Monte Carlo technique for the effective Suzuki-Trotter Hamiltonian at finite temperatures and that at zero temperature obtained using the exact diagonalization method. Our numerical results indicate the existence of a low- but finite-temperature quantum-fluctuation-dominated ergodic region along with the classical fluctuation-dominated high-temperature nonergodic region in the spin glass phase of the model. In the ergodic region, the order parameter distribution gets narrower around the most probable value of the order parameter as the system size increases. In the other region, the Parisi order distribution function has nonvanishing value everywhere in the thermodynamic limit, indicating nonergodicity. We also show that the average annealing time for convergence (to a low-energy level of the model, within a small error range) becomes system size independent for annealing down through the (quantum-fluctuation-dominated) ergodic region. It becomes strongly system size dependent for annealing through the nonergodic region. Possible finite-size scaling-type behavior for the extent of the ergodic region is also addressed.

Iterative Importance Sampling Algorithms for Parameter Estimation

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

Grout, Ray W; Morzfeld, Matthias; Day, Marcus S.

In parameter estimation problems one computes a posterior distribution over uncertain parameters defined jointly by a prior distribution, a model, and noisy data. Markov chain Monte Carlo (MCMC) is often used for the numerical solution of such problems. An alternative to MCMC is importance sampling, which can exhibit near perfect scaling with the number of cores on high performance computing systems because samples are drawn independently. However, finding a suitable proposal distribution is a challenging task. Several sampling algorithms have been proposed over the past years that take an iterative approach to constructing a proposal distribution. We investigate the applicabilitymore » of such algorithms by applying them to two realistic and challenging test problems, one in subsurface flow, and one in combustion modeling. More specifically, we implement importance sampling algorithms that iterate over the mean and covariance matrix of Gaussian or multivariate t-proposal distributions. Our implementation leverages massively parallel computers, and we present strategies to initialize the iterations using 'coarse' MCMC runs or Gaussian mixture models.« less

WATGIS: A GIS-Based Lumped Parameter Water Quality Model

Treesearch

Glenn P. Fernandez; George M. Chescheir; R. Wayne Skaggs; Devendra M. Amatya

2002-01-01

A Geographic Information System (GIS)­based, lumped parameter water quality model was developed to estimate the spatial and temporal nitrogen­loading patterns for lower coastal plain watersheds in eastern North Carolina. The model uses a spatially distributed delivery ratio (DR) parameter to account for nitrogen retention or loss along a drainage network. Delivery...

Computational Algorithms or Identification of Distributed Parameter Systems

DTIC Science & Technology

1993-04-24

delay-differential equations, Volterra integral equations, and partial differential equations with memory terms . In particular we investigated a...tested for estimating parameters in a Volterra integral equation arising from a viscoelastic model of a flexible structure with Boltzmann damping. In...particular, one of the parameters identified was the order of the derivative in Volterra integro-differential equations containing fractional

Inferring the distribution of mutational effects on fitness in Drosophila.

PubMed

Loewe, Laurence; Charlesworth, Brian

2006-09-22

The properties of the distribution of deleterious mutational effects on fitness (DDME) are of fundamental importance for evolutionary genetics. Since it is extremely difficult to determine the nature of this distribution, several methods using various assumptions about the DDME have been developed, for the purpose of parameter estimation. We apply a newly developed method to DNA sequence polymorphism data from two Drosophila species and compare estimates of the parameters of the distribution of the heterozygous fitness effects of amino acid mutations for several different distribution functions. The results exclude normal and gamma distributions, since these predict too few effectively lethal mutations and power-law distributions as a result of predicting too many lethals. Only the lognormal distribution appears to fit both the diversity data and the frequency of lethals. This DDME arises naturally in complex systems when independent factors contribute multiplicatively to an increase in fitness-reducing damage. Several important parameters, such as the fraction of effectively neutral non-synonymous mutations and the harmonic mean of non-neutral selection coefficients, are robust to the form of the DDME. Our results suggest that the majority of non-synonymous mutations in Drosophila are under effective purifying selection.

An optimized computational method for determining the beta dose distribution using a multiple-element thermoluminescent dosimeter system.

PubMed

Shen, L; Levine, S H; Catchen, G L

1987-07-01

This paper describes an optimization method for determining the beta dose distribution in tissue, and it describes the associated testing and verification. The method uses electron transport theory and optimization techniques to analyze the responses of a three-element thermoluminescent dosimeter (TLD) system. Specifically, the method determines the effective beta energy distribution incident on the dosimeter system, and thus the system performs as a beta spectrometer. Electron transport theory provides the mathematical model for performing the optimization calculation. In this calculation, parameters are determined that produce calculated doses for each of the chip/absorber components in the three-element TLD system. The resulting optimized parameters describe an effective incident beta distribution. This method can be used to determine the beta dose specifically at 7 mg X cm-2 or at any depth of interest. The doses at 7 mg X cm-2 in tissue determined by this method are compared to those experimentally determined using an extrapolation chamber. For a great variety of pure beta sources having different incident beta energy distributions, good agreement is found. The results are also compared to those produced by a commonly used empirical algorithm. Although the optimization method produces somewhat better results, the advantage of the optimization method is that its performance is not sensitive to the specific method of calibration.

Periodic Peakons, Pseudo-Peakons and Compactons of Ion-Acoustic Wave Model in Electronegative Plasmas with Electrons Featuring Tsallis Distribution

NASA Astrophysics Data System (ADS)

Li, Jibin

The dynamical model of the nonlinear ion-acoustic oscillations is governed by a partial differential equation system. Its traveling system is just a singular traveling wave system of first class depending on four parameters. By using the method of dynamical systems and the theory of singular traveling wave systems, in this paper, we show that there exist parameter groups such that this singular system has pseudo-peakons, periodic peakons and compactons as well as kink and anti-kink wave solutions.

Distribution uniformity of laser-accelerated proton beams

NASA Astrophysics Data System (ADS)

Zhu, Jun-Gao; Zhu, Kun; Tao, Li; Xu, Xiao-Han; Lin, Chen; Ma, Wen-Jun; Lu, Hai-Yang; Zhao, Yan-Ying; Lu, Yuan-Rong; Chen, Jia-Er; Yan, Xue-Qing

2017-09-01

Compared with conventional accelerators, laser plasma accelerators can generate high energy ions at a greatly reduced scale, due to their TV/m acceleration gradient. A compact laser plasma accelerator (CLAPA) has been built at the Institute of Heavy Ion Physics at Peking University. It will be used for applied research like biological irradiation, astrophysics simulations, etc. A beamline system with multiple quadrupoles and an analyzing magnet for laser-accelerated ions is proposed here. Since laser-accelerated ion beams have broad energy spectra and large angular divergence, the parameters (beam waist position in the Y direction, beam line layout, drift distance, magnet angles etc.) of the beamline system are carefully designed and optimised to obtain a radially symmetric proton distribution at the irradiation platform. Requirements of energy selection and differences in focusing or defocusing in application systems greatly influence the evolution of proton distributions. With optimal parameters, radially symmetric proton distributions can be achieved and protons with different energy spread within ±5% have similar transverse areas at the experiment target. Supported by National Natural Science Foundation of China (11575011, 61631001) and National Grand Instrument Project (2012YQ030142)

A Review of Hybrid Fiber-Optic Distributed Simultaneous Vibration and Temperature Sensing Technology and Its Geophysical Applications

PubMed Central

2017-01-01

Distributed sensing systems can transform an optical fiber cable into an array of sensors, allowing users to detect and monitor multiple physical parameters such as temperature, vibration and strain with fine spatial and temporal resolution over a long distance. Fiber-optic distributed acoustic sensing (DAS) and distributed temperature sensing (DTS) systems have been developed for various applications with varied spatial resolution, and spectral and sensing range. Rayleigh scattering-based phase optical time domain reflectometry (OTDR) for vibration and Raman/Brillouin scattering-based OTDR for temperature and strain measurements have been developed over the past two decades. The key challenge has been to find a methodology that would enable the physical parameters to be determined at any point along the sensing fiber with high sensitivity and spatial resolution, yet within acceptable frequency range for dynamic vibration, and temperature detection. There are many applications, especially in geophysical and mining engineering where simultaneous measurements of vibration and temperature are essential. In this article, recent developments of different hybrid systems for simultaneous vibration, temperature and strain measurements are analyzed based on their operation principles and performance. Then, challenges and limitations of the systems are highlighted for geophysical applications. PMID:29104259

A Review of Hybrid Fiber-Optic Distributed Simultaneous Vibration and Temperature Sensing Technology and Its Geophysical Applications.

PubMed

Miah, Khalid; Potter, David K

2017-11-01

Distributed sensing systems can transform an optical fiber cable into an array of sensors, allowing users to detect and monitor multiple physical parameters such as temperature, vibration and strain with fine spatial and temporal resolution over a long distance. Fiber-optic distributed acoustic sensing (DAS) and distributed temperature sensing (DTS) systems have been developed for various applications with varied spatial resolution, and spectral and sensing range. Rayleigh scattering-based phase optical time domain reflectometry (OTDR) for vibration and Raman/Brillouin scattering-based OTDR for temperature and strain measurements have been developed over the past two decades. The key challenge has been to find a methodology that would enable the physical parameters to be determined at any point along the sensing fiber with high sensitivity and spatial resolution, yet within acceptable frequency range for dynamic vibration, and temperature detection. There are many applications, especially in geophysical and mining engineering where simultaneous measurements of vibration and temperature are essential. In this article, recent developments of different hybrid systems for simultaneous vibration, temperature and strain measurements are analyzed based on their operation principles and performance. Then, challenges and limitations of the systems are highlighted for geophysical applications.

Inferring epidemiological parameters from phylogenetic information for the HIV-1 epidemic among MSM

NASA Astrophysics Data System (ADS)

Quax, Rick; van de Vijver, David A. M. C.; Frentz, Dineke; Sloot, Peter M. A.

2013-09-01

The HIV-1 epidemic in Europe is primarily sustained by a dynamic topology of sexual interactions among MSM who have individual immune systems and behavior. This epidemiological process shapes the phylogeny of the virus population. Both fields of epidemic modeling and phylogenetics have a long history, however it remains difficult to use phylogenetic data to infer epidemiological parameters such as the structure of the sexual network and the per-act infectiousness. This is because phylogenetic data is necessarily incomplete and ambiguous. Here we show that the cluster-size distribution indeed contains information about epidemiological parameters using detailed numberical experiments. We simulate the HIV epidemic among MSM many times using the Monte Carlo method with all parameter values and their ranges taken from literature. For each simulation and the corresponding set of parameter values we calculate the likelihood of reproducing an observed cluster-size distribution. The result is an estimated likelihood distribution of all parameters from the phylogenetic data, in particular the structure of the sexual network, the per-act infectiousness, and the risk behavior reduction upon diagnosis. These likelihood distributions encode the knowledge provided by the observed cluster-size distrbution, which we quantify using information theory. Our work suggests that the growing body of genetic data of patients can be exploited to understand the underlying epidemiological process.

Atomic hydrogen distribution. [in Titan atmospheric model

NASA Technical Reports Server (NTRS)

Tabarie, N.

1974-01-01

Several possible H2 vertical distributions in Titan's atmosphere are considered with the constraint of 5 km-A a total quantity. Approximative calculations show that hydrogen distribution is quite sensitive to two other parameters of Titan's atmosphere: the temperature and the presence of other constituents. The escape fluxes of H and H2 are also estimated as well as the consequent distributions trapped in the Saturnian system.

FALCON: A distributed scheduler for MIMD architectures

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

Grimshaw, A.S.; Vivas, V.E. Jr.

1991-01-01

This paper describes FALCON (Fully Automatic Load COordinator for Networks), the scheduler for the Mentat parallel processing system. FALCON has a modular structure and is designed for systems that use a task scheduling mechanism. FALCON is distributed, stable, supports system heterogeneities, and employs a sender-initiated adaptive load sharing policy with static task assignment. FALCON is parameterizable and is implemented in Mentat, a working distributed system. We present the design and implementation of FALCON as well as a brief introduction to those features of the Mentat run-time system that influence FALCON. Performance measures under different scheduler configurations are also presented andmore » analyzed with respect to the system parameters. 36 refs., 8 figs.« less

Peristaltic blood flow with gold nanoparticles as a third grade nanofluid in catheter: Application of cancer therapy

NASA Astrophysics Data System (ADS)

Mekheimer, Kh. S.; Hasona, W. M.; Abo-Elkhair, R. E.; Zaher, A. Z.

2018-01-01

Cancer is dangerous and deadly to most of its patients. Recent studies have shown that gold nanoparticles can cure and overcome it, because these particles have a high atomic number which produce the heat and leads to treatment of malignancy tumors. A motivation of this article is to study the effect of heat transfer with the blood flow (non-Newtonian model) containing gold nanoparticles in a gap between two coaxial tubes, the outer tube has a sinusoidal wave traveling down its wall and the inner tube is rigid. The governing equations of third-grade fluid along with total mass, thermal energy and nanoparticles are simplified by using the assumption of long wavelength. Exact solutions have been evaluated for temperature distribution and nanoparticles concentration, while approximate analytical solutions are found for the velocity distribution using the regular perturbation method with a small third grade parameter. Influence of the physical parameters such as third grade parameter, Brownian motion parameter and thermophoresis parameter on the velocity profile, temperature distribution and nanoparticles concentration are considered. The results pointed to that the gold nanoparticles are effective for drug carrying and drug delivery systems because they control the velocity through the Brownian motion parameter Nb and thermophoresis parameter Nt. Gold nanoparticles also increases the temperature distribution, making it able to destroy cancer cells.

The Monitoring, Detection, Isolation and Assessment of Information Warfare Attacks Through Multi-Level, Multi-Scale System Modeling and Model Based Technology

DTIC Science & Technology

2004-01-01

login identity to the one under which the system call is executed, the parameters of the system call execution - file names including full path...Anomaly detection COAST-EIMDT Distributed on target hosts EMERALD Distributed on target hosts and security servers Signature recognition Anomaly...uses a centralized architecture, and employs an anomaly detection technique for intrusion detection. The EMERALD project [80] proposes a

Competing risk models in reliability systems, a weibull distribution model with bayesian analysis approach

NASA Astrophysics Data System (ADS)

Iskandar, Ismed; Satria Gondokaryono, Yudi

2016-02-01

In reliability theory, the most important problem is to determine the reliability of a complex system from the reliability of its components. The weakness of most reliability theories is that the systems are described and explained as simply functioning or failed. In many real situations, the failures may be from many causes depending upon the age and the environment of the system and its components. Another problem in reliability theory is one of estimating the parameters of the assumed failure models. The estimation may be based on data collected over censored or uncensored life tests. In many reliability problems, the failure data are simply quantitatively inadequate, especially in engineering design and maintenance system. The Bayesian analyses are more beneficial than the classical one in such cases. The Bayesian estimation analyses allow us to combine past knowledge or experience in the form of an apriori distribution with life test data to make inferences of the parameter of interest. In this paper, we have investigated the application of the Bayesian estimation analyses to competing risk systems. The cases are limited to the models with independent causes of failure by using the Weibull distribution as our model. A simulation is conducted for this distribution with the objectives of verifying the models and the estimators and investigating the performance of the estimators for varying sample size. The simulation data are analyzed by using Bayesian and the maximum likelihood analyses. The simulation results show that the change of the true of parameter relatively to another will change the value of standard deviation in an opposite direction. For a perfect information on the prior distribution, the estimation methods of the Bayesian analyses are better than those of the maximum likelihood. The sensitivity analyses show some amount of sensitivity over the shifts of the prior locations. They also show the robustness of the Bayesian analysis within the range between the true value and the maximum likelihood estimated value lines.

Coordinate transformation by minimizing correlations between parameters

NASA Technical Reports Server (NTRS)

Kumar, M.

1972-01-01

This investigation was to determine the transformation parameters (three rotations, three translations and a scale factor) between two Cartesian coordinate systems from sets of coordinates given in both systems. The objective was the determination of well separated transformation parameters with reduced correlations between each other, a problem especially relevant when the sets of coordinates are not well distributed. The above objective is achieved by preliminarily determining the three rotational parameters and the scale factor from the respective direction cosines and chord distances (these being independent of the translation parameters) between the common points, and then computing all the seven parameters from a solution in which the rotations and the scale factor are entered as weighted constraints according to their variances and covariances obtained in the preliminary solutions. Numerical tests involving two geodetic reference systems were performed to evaluate the effectiveness of this approach.

Physical and geometrical parameters of VCBS XIII: HIP 105947

NASA Astrophysics Data System (ADS)

Gumaan Masda, Suhail; Al-Wardat, Mashhoor Ahmed; Pathan, Jiyaulla Khan Moula Khan

2018-06-01

The best physical and geometrical parameters of the main sequence close visual binary system (CVBS), HIP 105947, are presented. These parameters have been constructed conclusively using Al-Wardat’s complex method for analyzing CVBSs, which is a method for constructing a synthetic spectral energy distribution (SED) for the entire binary system using individual SEDs for each component star. The model atmospheres are in its turn built using the Kurucz (ATLAS9) line-blanketed plane-parallel models. At the same time, the orbital parameters for the system are calculated using Tokovinin’s dynamical method for constructing the best orbits of an interferometric binary system. Moreover, the mass-sum of the components, as well as the Δθ and Δρ residuals for the system, is introduced. The combination of Al-Wardat’s and Tokovinin’s methods yields the best estimations of the physical and geometrical parameters. The positions of the components in the system on the evolutionary tracks and isochrones are plotted and the formation and evolution of the system are discussed.

Comparison of Two Methods Used to Model Shape Parameters of Pareto Distributions

USGS Publications Warehouse

Liu, C.; Charpentier, R.R.; Su, J.

2011-01-01

Two methods are compared for estimating the shape parameters of Pareto field-size (or pool-size) distributions for petroleum resource assessment. Both methods assume mature exploration in which most of the larger fields have been discovered. Both methods use the sizes of larger discovered fields to estimate the numbers and sizes of smaller fields: (1) the tail-truncated method uses a plot of field size versus size rank, and (2) the log-geometric method uses data binned in field-size classes and the ratios of adjacent bin counts. Simulation experiments were conducted using discovered oil and gas pool-size distributions from four petroleum systems in Alberta, Canada and using Pareto distributions generated by Monte Carlo simulation. The estimates of the shape parameters of the Pareto distributions, calculated by both the tail-truncated and log-geometric methods, generally stabilize where discovered pool numbers are greater than 100. However, with fewer than 100 discoveries, these estimates can vary greatly with each new discovery. The estimated shape parameters of the tail-truncated method are more stable and larger than those of the log-geometric method where the number of discovered pools is more than 100. Both methods, however, tend to underestimate the shape parameter. Monte Carlo simulation was also used to create sequences of discovered pool sizes by sampling from a Pareto distribution with a discovery process model using a defined exploration efficiency (in order to show how biased the sampling was in favor of larger fields being discovered first). A higher (more biased) exploration efficiency gives better estimates of the Pareto shape parameters. ?? 2011 International Association for Mathematical Geosciences.

VizieR Online Data Catalog: Statistical test on binary stars non-coevality (Valle+, 2016)

NASA Astrophysics Data System (ADS)

Valle, G.; Dell'Omodarme, M.; Valle, G.; Prada Moroni, P. G.; Degl'Innocenti, S.

2016-01-01

The table contains the W0.95 critical values, for the 1087 binary systems considered in the paper. Tha table also lists the parameters of the beta distributions approximating the empirical W distributions. (1 data file).

Progress in Application of Generalized Wigner Distribution to Growth and Other Problems

NASA Astrophysics Data System (ADS)

Einstein, T. L.; Morales-Cifuentes, Josue; Pimpinelli, Alberto; Gonzalez, Diego Luis

We recap the use of the (single-parameter) Generalized Wigner Distribution (GWD) to analyze capture-zone distributions associated with submonolayer epitaxial growth. We discuss recent applications to physical systems, as well as key simulations. We pay particular attention to how this method compares with other methods to assess the critical nucleus size characterizing growth. The following talk discusses a particular case when special insight is needed to reconcile the various methods. We discuss improvements that can be achieved by going to a 2-parameter fragmentation approach. At a much larger scale we have applied this approach to various distributions in socio-political phenomena (areas of secondary administrative units [e.g., counties] and distributions of subway stations). Work at UMD supported by NSF CHE 13-05892.

Interdisciplinary Applications of Autonomous Observation Systems

DTIC Science & Technology

2008-01-01

analytical capabilities for describing the distributions and activities of marine microbes in relation to their physical, chemical and optical environment in...SPONSOR/MONITOR’S REPORT NUMBER(S) 12. DISTRIBUTION /AVAILABILITY STATEMENT Approved for public release; distribution unlimited 13. SUPPLEMENTARY...a sensitive indicator of physiology (light acclimation status) and also a key parameter in models of primary productivity. We are now continuing

Population-based learning of load balancing policies for a distributed computer system

NASA Technical Reports Server (NTRS)

Mehra, Pankaj; Wah, Benjamin W.

1993-01-01

Effective load-balancing policies use dynamic resource information to schedule tasks in a distributed computer system. We present a novel method for automatically learning such policies. At each site in our system, we use a comparator neural network to predict the relative speedup of an incoming task using only the resource-utilization patterns obtained prior to the task's arrival. Outputs of these comparator networks are broadcast periodically over the distributed system, and the resource schedulers at each site use these values to determine the best site for executing an incoming task. The delays incurred in propagating workload information and tasks from one site to another, as well as the dynamic and unpredictable nature of workloads in multiprogrammed multiprocessors, may cause the workload pattern at the time of execution to differ from patterns prevailing at the times of load-index computation and decision making. Our load-balancing policy accommodates this uncertainty by using certain tunable parameters. We present a population-based machine-learning algorithm that adjusts these parameters in order to achieve high average speedups with respect to local execution. Our results show that our load-balancing policy, when combined with the comparator neural network for workload characterization, is effective in exploiting idle resources in a distributed computer system.

Optimization of light quality from color mixing light-emitting diode systems for general lighting

NASA Astrophysics Data System (ADS)

Thorseth, Anders

2012-03-01

Given the problem of metamerisms inherent in color mixing in light-emitting diode (LED) systems with more than three distinct colors, a method for optimizing the spectral output of multicolor LED system with regards to standardized light quality parameters has been developed. The composite spectral power distribution from the LEDs are simulated using spectral radiometric measurements of single commercially available LEDs for varying input power, to account for the efficiency droop and other non-linear effects in electrical power vs. light output. The method uses electrical input powers as input parameters in a randomized steepest decent optimization. The resulting spectral power distributions are evaluated with regard to the light quality using the standard characteristics: CIE color rendering index, correlated color temperature and chromaticity distance. The results indicate Pareto optimal boundaries for each system, mapping the capabilities of the simulated lighting systems with regard to the light quality characteristics.

Nuclear power propulsion system for spacecraft

NASA Astrophysics Data System (ADS)

Koroteev, A. S.; Oshev, Yu. A.; Popov, S. A.; Karevsky, A. V.; Solodukhin, A. Ye.; Zakharenkov, L. E.; Semenkin, A. V.

2015-12-01

The proposed designs of high-power space tugs that utilize solar or nuclear energy to power an electric jet engine are reviewed. The conceptual design of a nuclear power propulsion system (NPPS) is described; its structural diagram, gas circuit, and electric diagram are discussed. The NPPS incorporates a nuclear reactor, a thermal-to-electric energy conversion system, a system for the conversion and distribution of electric energy, and an electric propulsion system. Two criterion parameters were chosen in the considered NPPS design: the temperature of gaseous working medium at the nuclear reactor outlet and the rotor speed of turboalternators. The maintenance of these parameters at a given level guarantees that the needed electric voltage is generated and allows for power mode control. The processes of startup/shutdown and increasing/reducing the power, the principles of distribution of electric energy over loads, and the probable emergencies for the proposed NPPS design are discussed.

Finite-dimensional approximation for optimal fixed-order compensation of distributed parameter systems

NASA Technical Reports Server (NTRS)

Bernstein, Dennis S.; Rosen, I. G.

1988-01-01

In controlling distributed parameter systems it is often desirable to obtain low-order, finite-dimensional controllers in order to minimize real-time computational requirements. Standard approaches to this problem employ model/controller reduction techniques in conjunction with LQG theory. In this paper we consider the finite-dimensional approximation of the infinite-dimensional Bernstein/Hyland optimal projection theory. This approach yields fixed-finite-order controllers which are optimal with respect to high-order, approximating, finite-dimensional plant models. The technique is illustrated by computing a sequence of first-order controllers for one-dimensional, single-input/single-output, parabolic (heat/diffusion) and hereditary systems using spline-based, Ritz-Galerkin, finite element approximation. Numerical studies indicate convergence of the feedback gains with less than 2 percent performance degradation over full-order LQG controllers for the parabolic system and 10 percent degradation for the hereditary system.

Bonus-Malus System with the Claim Frequency Distribution is Geometric and the Severity Distribution is Truncated Weibull

NASA Astrophysics Data System (ADS)

Santi, D. N.; Purnaba, I. G. P.; Mangku, I. W.

2016-01-01

Bonus-Malus system is said to be optimal if it is financially balanced for insurance companies and fair for policyholders. Previous research about Bonus-Malus system concern with the determination of the risk premium which applied to all of the severity that guaranteed by the insurance company. In fact, not all of the severity that proposed by policyholder may be covered by insurance company. When the insurance company sets a maximum bound of the severity incurred, so it is necessary to modify the model of the severity distribution into the severity bound distribution. In this paper, optimal Bonus-Malus system is compound of claim frequency component has geometric distribution and severity component has truncated Weibull distribution is discussed. The number of claims considered to follow a Poisson distribution, and the expected number λ is exponentially distributed, so the number of claims has a geometric distribution. The severity with a given parameter θ is considered to have a truncated exponential distribution is modelled using the Levy distribution, so the severity have a truncated Weibull distribution.

A trans-dimensional Bayesian Markov chain Monte Carlo algorithm for model assessment using frequency-domain electromagnetic data

USGS Publications Warehouse

Minsley, B.J.

2011-01-01

A meaningful interpretation of geophysical measurements requires an assessment of the space of models that are consistent with the data, rather than just a single, 'best' model which does not convey information about parameter uncertainty. For this purpose, a trans-dimensional Bayesian Markov chain Monte Carlo (MCMC) algorithm is developed for assessing frequency-domain electromagnetic (FDEM) data acquired from airborne or ground-based systems. By sampling the distribution of models that are consistent with measured data and any prior knowledge, valuable inferences can be made about parameter values such as the likely depth to an interface, the distribution of possible resistivity values as a function of depth and non-unique relationships between parameters. The trans-dimensional aspect of the algorithm allows the number of layers to be a free parameter that is controlled by the data, where models with fewer layers are inherently favoured, which provides a natural measure of parsimony and a significant degree of flexibility in parametrization. The MCMC algorithm is used with synthetic examples to illustrate how the distribution of acceptable models is affected by the choice of prior information, the system geometry and configuration and the uncertainty in the measured system elevation. An airborne FDEM data set that was acquired for the purpose of hydrogeological characterization is also studied. The results compare favourably with traditional least-squares analysis, borehole resistivity and lithology logs from the site, and also provide new information about parameter uncertainty necessary for model assessment. ?? 2011. Geophysical Journal International ?? 2011 RAS.

On magnetohydrodynamic flow of second grade nanofluid over a nonlinear stretching sheet

NASA Astrophysics Data System (ADS)

Hayat, Tasawar; Aziz, Arsalan; Muhammad, Taseer; Ahmad, Bashir

2016-06-01

This research article addresses the magnetohydrodynamic (MHD) flow of second grade nanofluid over a nonlinear stretching sheet. Heat and mass transfer aspects are investigated through the thermophoresis and Brownian motion effects. Second grade fluid is assumed electrically conducting through a non-uniform applied magnetic field. Mathematical formulation is developed subject to small magnetic Reynolds number and boundary layer assumptions. Newly constructed condition having zero mass flux of nanoparticles at the boundary is incorporated. Transformations have been invoked for the reduction of partial differential systems into the set of nonlinear ordinary differential systems. The governing nonlinear systems have been solved for local behavior. Graphical results of different influential parameters are studied and discussed in detail. Computations for skin friction coefficient and local Nusselt number have been carried out. It is observed that the effects of thermophoresis parameter on the temperature and nanoparticles concentration distributions are qualitatively similar. The temperature and nanoparticles concentration distributions are enhanced for the larger magnetic parameter.

Modification of a rainfall-runoff model for distributed modeling in a GIS and its validation

NASA Astrophysics Data System (ADS)

Nyabeze, W. R.

A rainfall-runoff model, which can be inter-faced with a Geographical Information System (GIS) to integrate definition, measurement, calculating parameter values for spatial features, presents considerable advantages. The modification of the GWBasic Wits Rainfall-Runoff Erosion Model (GWBRafler) to enable parameter value estimation in a GIS (GISRafler) is presented in this paper. Algorithms are applied to estimate parameter values reducing the number of input parameters and the effort to populate them. The use of a GIS makes the relationship between parameter estimates and cover characteristics more evident. This paper has been produced as part of research to generalize the GWBRafler on a spatially distributed basis. Modular data structures are assumed and parameter values are weighted relative to the module area and centroid properties. Modifications to the GWBRafler enable better estimation of low flows, which are typical in drought conditions.

Hiereachical Bayesian Model for Combining Geochemical and Geophysical Data for Environmental Applications Software

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

Chen, Jinsong

2013-05-01

Development of a hierarchical Bayesian model to estimate the spatiotemporal distribution of aqueous geochemical parameters associated with in-situ bioremediation using surface spectral induced polarization (SIP) data and borehole geochemical measurements collected during a bioremediation experiment at a uranium-contaminated site near Rifle, Colorado. The SIP data are first inverted for Cole-Cole parameters including chargeability, time constant, resistivity at the DC frequency and dependence factor, at each pixel of two-dimensional grids using a previously developed stochastic method. Correlations between the inverted Cole-Cole parameters and the wellbore-based groundwater chemistry measurements indicative of key metabolic processes within the aquifer (e.g. ferrous iron, sulfate, uranium)more » were established and used as a basis for petrophysical model development. The developed Bayesian model consists of three levels of statistical sub-models: 1) data model, providing links between geochemical and geophysical attributes, 2) process model, describing the spatial and temporal variability of geochemical properties in the subsurface system, and 3) parameter model, describing prior distributions of various parameters and initial conditions. The unknown parameters are estimated using Markov chain Monte Carlo methods. By combining the temporally distributed geochemical data with the spatially distributed geophysical data, we obtain the spatio-temporal distribution of ferrous iron, sulfate and sulfide, and their associated uncertainity information. The obtained results can be used to assess the efficacy of the bioremediation treatment over space and time and to constrain reactive transport models.« less

Inferring the parameters of a Markov process from snapshots of the steady state

NASA Astrophysics Data System (ADS)

Dettmer, Simon L.; Berg, Johannes

2018-02-01

We seek to infer the parameters of an ergodic Markov process from samples taken independently from the steady state. Our focus is on non-equilibrium processes, where the steady state is not described by the Boltzmann measure, but is generally unknown and hard to compute, which prevents the application of established equilibrium inference methods. We propose a quantity we call propagator likelihood, which takes on the role of the likelihood in equilibrium processes. This propagator likelihood is based on fictitious transitions between those configurations of the system which occur in the samples. The propagator likelihood can be derived by minimising the relative entropy between the empirical distribution and a distribution generated by propagating the empirical distribution forward in time. Maximising the propagator likelihood leads to an efficient reconstruction of the parameters of the underlying model in different systems, both with discrete configurations and with continuous configurations. We apply the method to non-equilibrium models from statistical physics and theoretical biology, including the asymmetric simple exclusion process (ASEP), the kinetic Ising model, and replicator dynamics.

[The limnology of Tunisia: physicochemical study].

PubMed

Boumaiza, M

1984-01-01

Several chemical and physical parameters are measured in forty seven stations, distributed on the most part of the hydrographic systems of Tunisia. Some parameters: temperature of the water (T), salinity (S, electric conductivity (CE), chloride (Cl-), total hardness (DT) and turbidity (TUR) show great variations in the Northern hydrographic systems. In these systems, the parameters (S, CE, Cl-, DT) are generally elevated in the tributaries of the south bank of the Medjerda, the North-East streams, Melah and Tine Streams which flow in the Ichkeul lake. The waters in these septentrional systems are sometimes very turbid. The waters of the meridional hydrological system are very clear. The resurgence thermal waters are characterized by the small amplitude of variations of the studied parameters. The waters are alkaline, generally very mineralized they are well oxygenized in the no-polluted stations.

Life cycle assessment of overhead and underground primary power distribution.

PubMed

Bumby, Sarah; Druzhinina, Ekaterina; Feraldi, Rebe; Werthmann, Danae; Geyer, Roland; Sahl, Jack

2010-07-15

Electrical power can be distributed in overhead or underground systems, both of which generate a variety of environmental impacts at all stages of their life cycles. While there is considerable literature discussing the trade-offs between both systems in terms of aesthetics, safety, cost, and reliability, environmental assessments are relatively rare and limited to power cable production and end-of-life management. This paper assesses environmental impacts from overhead and underground medium voltage power distribution systems as they are currently built and managed by Southern California Edison (SCE). It uses process-based life cycle assessment (LCA) according to ISO 14044 (2006) and SCE-specific primary data to the extent possible. Potential environmental impacts have been calculated using a wide range of midpoint indicators, and robustness of the results has been investigated through sensitivity analysis of the most uncertain and potentially significant parameters. The studied underground system has higher environmental impacts in all indicators and for all parameter values, mostly due to its higher material intensity. For both systems and all indicators the majority of impact occurs during cable production. Promising strategies for impact reduction are thus cable failure rate reduction for overhead and cable lifetime extension for underground systems.

Cryptographic robustness of practical quantum cryptography: BB84 key distribution protocol

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

Molotkov, S. N.

2008-07-15

In real fiber-optic quantum cryptography systems, the avalanche photodiodes are not perfect, the source of quantum states is not a single-photon one, and the communication channel is lossy. For these reasons, key distribution is impossible under certain conditions for the system parameters. A simple analysis is performed to find relations between the parameters of real cryptography systems and the length of the quantum channel that guarantee secure quantum key distribution when the eavesdropper's capabilities are limited only by fundamental laws of quantum mechanics while the devices employed by the legitimate users are based on current technologies. Critical values are determinedmore » for the rate of secure real-time key generation that can be reached under the current technology level. Calculations show that the upper bound on channel length can be as high as 300 km for imperfect photodetectors (avalanche photodiodes) with present-day quantum efficiency ({eta} {approx} 20%) and dark count probability (p{sub dark} {approx} 10{sup -7})« less

Mathematical modelling of flow distribution in the human cardiovascular system

NASA Technical Reports Server (NTRS)

Sud, V. K.; Srinivasan, R. S.; Charles, J. B.; Bungo, M. W.

1992-01-01

The paper presents a detailed model of the entire human cardiovascular system which aims to study the changes in flow distribution caused by external stimuli, changes in internal parameters, or other factors. The arterial-venous network is represented by 325 interconnected elastic segments. The mathematical description of each segment is based on equations of hydrodynamics and those of stress/strain relationships in elastic materials. Appropriate input functions provide for the pumping of blood by the heart through the system. The analysis employs the finite-element technique which can accommodate any prescribed boundary conditions. Values of model parameters are from available data on physical and rheological properties of blood and blood vessels. As a representative example, simulation results on changes in flow distribution with changes in the elastic properties of blood vessels are discussed. They indicate that the errors in the calculated overall flow rates are not significant even in the extreme case of arteries and veins behaving as rigid tubes.

Cryptographic robustness of practical quantum cryptography: BB84 key distribution protocol

NASA Astrophysics Data System (ADS)

Molotkov, S. N.

2008-07-01

In real fiber-optic quantum cryptography systems, the avalanche photodiodes are not perfect, the source of quantum states is not a single-photon one, and the communication channel is lossy. For these reasons, key distribution is impossible under certain conditions for the system parameters. A simple analysis is performed to find relations between the parameters of real cryptography systems and the length of the quantum channel that guarantee secure quantum key distribution when the eavesdropper’s capabilities are limited only by fundamental laws of quantum mechanics while the devices employed by the legitimate users are based on current technologies. Critical values are determined for the rate of secure real-time key generation that can be reached under the current technology level. Calculations show that the upper bound on channel length can be as high as 300 km for imperfect photodetectors (avalanche photodiodes) with present-day quantum efficiency (η ≈ 20%) and dark count probability ( p dark ˜ 10-7).

Energy loss analysis of an integrated space power distribution system

NASA Technical Reports Server (NTRS)

Kankam, M. D.; Ribeiro, P. F.

1992-01-01

The results of studies related to conceptual topologies of an integrated utility-like space power system are described. The system topologies are comparatively analyzed by considering their transmission energy losses as functions of mainly distribution voltage level and load composition. The analysis is expedited by use of a Distribution System Analysis and Simulation (DSAS) software. This recently developed computer program by the Electric Power Research Institute (EPRI) uses improved load models to solve the power flow within the system. However, present shortcomings of the software with regard to space applications, and incompletely defined characteristics of a space power system make the results applicable to only the fundamental trends of energy losses of the topologies studied. Accountability, such as included, for the effects of the various parameters on the system performance can constitute part of a planning tool for a space power distribution system.

Classification framework for partially observed dynamical systems

NASA Astrophysics Data System (ADS)

Shen, Yuan; Tino, Peter; Tsaneva-Atanasova, Krasimira

2017-04-01

We present a general framework for classifying partially observed dynamical systems based on the idea of learning in the model space. In contrast to the existing approaches using point estimates of model parameters to represent individual data items, we employ posterior distributions over model parameters, thus taking into account in a principled manner the uncertainty due to both the generative (observational and/or dynamic noise) and observation (sampling in time) processes. We evaluate the framework on two test beds: a biological pathway model and a stochastic double-well system. Crucially, we show that the classification performance is not impaired when the model structure used for inferring posterior distributions is much more simple than the observation-generating model structure, provided the reduced-complexity inferential model structure captures the essential characteristics needed for the given classification task.

Temperature dependence of positron annihilation parameters in Tl-Ba-Ca-Cu-O superconductors

NASA Astrophysics Data System (ADS)

Sundar, C. S.; Bharathi, A.; Ching, W. Y.; Jean, Y. C.; Hor, P. H.; Meng, R. L.; Huang, Z. J.; Chu, C. W.

1990-08-01

The results of positron lifetime and Doppler broadened line-shape parameter measurements as a function of temperature, across Tc, in the Tl-Ba-Ca-Cu-O superconductors are presented. The bulk lifetime in the normal state is found to decrease with the increase in the number of CuO2 layers. Different temperature dependencies of the annihilation parameters are observed in the various Tl systems containing different numbers of CuO2 layers. In the Tl2Ba2Ca2Cu3O10 system, an increase in lifetime is observed below Tc, whereas in Tl2Ba2CaCu2O8, a decrease in lifetime is seen below Tc. In the Tl2Ba2CuO6 system, the lifetime is observed to be temperature independent. The different temperature variations of positron annihilation parameters are discussed in the light of the positron density distribution, obtained with use of the results of the self-consistent orthogonalized linear combination of atomic orbitals band-structure calculations. It is argued that the different temperature dependencies of the annihilation parameters is related to the positron density distribution within the unit cell and arise due to local charge transfer in the vicinity of the CuO2 layer in the superconducting state.

Space shuttle solid rocket booster recovery system definition. Volume 2: SRB water impact Monte Carlo computer program, user's manual

NASA Technical Reports Server (NTRS)

1973-01-01

The HD 220 program was created as part of the space shuttle solid rocket booster recovery system definition. The model was generated to investigate the damage to SRB components under water impact loads. The random nature of environmental parameters, such as ocean waves and wind conditions, necessitates estimation of the relative frequency of occurrence for these parameters. The nondeterministic nature of component strengths also lends itself to probabilistic simulation. The Monte Carlo technique allows the simultaneous perturbation of multiple independent parameters and provides outputs describing the probability distribution functions of the dependent parameters. This allows the user to determine the required statistics for each output parameter.

Deuteron spin-lattice relaxation in the presence of an activation energy distribution: application to methanols in zeolite NaX.

PubMed

Stoch, G; Ylinen, E E; Birczynski, A; Lalowicz, Z T; Góra-Marek, K; Punkkinen, M

2013-02-01

A new method is introduced for analyzing deuteron spin-lattice relaxation in molecular systems with a broad distribution of activation energies and correlation times. In such samples the magnetization recovery is strongly non-exponential but can be fitted quite accurately by three exponentials. The considered system may consist of molecular groups with different mobility. For each group a Gaussian distribution of the activation energy is introduced. By assuming for every subsystem three parameters: the mean activation energy E(0), the distribution width σ and the pre-exponential factor τ(0) for the Arrhenius equation defining the correlation time, the relaxation rate is calculated for every part of the distribution. Experiment-based limiting values allow the grouping of the rates into three classes. For each class the relaxation rate and weight is calculated and compared with experiment. The parameters E(0), σ and τ(0) are determined iteratively by repeating the whole cycle many times. The temperature dependence of the deuteron relaxation was observed in three samples containing CD(3)OH (200% and 100% loading) and CD(3)OD (200%) in NaX zeolite and analyzed by the described method between 20K and 170K. The obtained parameters, equal for all the three samples, characterize the methyl and hydroxyl mobilities of the methanol molecules at two different locations. Copyright © 2012 Elsevier Inc. All rights reserved.

Distributed Optimal Consensus Over Resource Allocation Network and Its Application to Dynamical Economic Dispatch.

PubMed

Li, Chaojie; Yu, Xinghuo; Huang, Tingwen; He, Xing; Chaojie Li; Xinghuo Yu; Tingwen Huang; Xing He; Li, Chaojie; Huang, Tingwen; He, Xing; Yu, Xinghuo

2018-06-01

The resource allocation problem is studied and reformulated by a distributed interior point method via a -logarithmic barrier. By the facilitation of the graph Laplacian, a fully distributed continuous-time multiagent system is developed for solving the problem. Specifically, to avoid high singularity of the -logarithmic barrier at boundary, an adaptive parameter switching strategy is introduced into this dynamical multiagent system. The convergence rate of the distributed algorithm is obtained. Moreover, a novel distributed primal-dual dynamical multiagent system is designed in a smart grid scenario to seek the saddle point of dynamical economic dispatch, which coincides with the optimal solution. The dual decomposition technique is applied to transform the optimization problem into easily solvable resource allocation subproblems with local inequality constraints. The good performance of the new dynamical systems is, respectively, verified by a numerical example and the IEEE six-bus test system-based simulations.

Stochastic inversion of cross-borehole radar data from metalliferous vein detection

NASA Astrophysics Data System (ADS)

Zeng, Zhaofa; Huai, Nan; Li, Jing; Zhao, Xueyu; Liu, Cai; Hu, Yingsa; Zhang, Ling; Hu, Zuzhi; Yang, Hui

2017-12-01

In the exploration and evaluation of the metalliferous veins with a cross-borehole radar system, traditional linear inversion methods (least squares inversion, LSQR) only get indirect parameters (permittivity, resistivity, or velocity) to estimate the target structure. They cannot accurately reflect the geological parameters of the metalliferous veins’ media properties. In order to get the intrinsic geological parameters and internal distribution, in this paper, we build a metalliferous veins model based on the stochastic effective medium theory, and carry out stochastic inversion and parameter estimation based on the Monte Carlo sampling algorithm. Compared with conventional LSQR, the stochastic inversion can get higher resolution inversion permittivity and velocity of the target body. We can estimate more accurately the distribution characteristics of abnormality and target internal parameters. It provides a new research idea to evaluate the properties of complex target media.

Estimating parameters with pre-specified accuracies in distributed parameter systems using optimal experiment design

NASA Astrophysics Data System (ADS)

Potters, M. G.; Bombois, X.; Mansoori, M.; Hof, Paul M. J. Van den

2016-08-01

Estimation of physical parameters in dynamical systems driven by linear partial differential equations is an important problem. In this paper, we introduce the least costly experiment design framework for these systems. It enables parameter estimation with an accuracy that is specified by the experimenter prior to the identification experiment, while at the same time minimising the cost of the experiment. We show how to adapt the classical framework for these systems and take into account scaling and stability issues. We also introduce a progressive subdivision algorithm that further generalises the experiment design framework in the sense that it returns the lowest cost by finding the optimal input signal, and optimal sensor and actuator locations. Our methodology is then applied to a relevant problem in heat transfer studies: estimation of conductivity and diffusivity parameters in front-face experiments. We find good correspondence between numerical and theoretical results.

Towards a cyber-physical era: soft computing framework based multi-sensor array for water quality monitoring

NASA Astrophysics Data System (ADS)

Bhardwaj, Jyotirmoy; Gupta, Karunesh K.; Gupta, Rajiv

2018-02-01

New concepts and techniques are replacing traditional methods of water quality parameter measurement systems. This paper introduces a cyber-physical system (CPS) approach for water quality assessment in a distribution network. Cyber-physical systems with embedded sensors, processors and actuators can be designed to sense and interact with the water environment. The proposed CPS is comprised of sensing framework integrated with five different water quality parameter sensor nodes and soft computing framework for computational modelling. Soft computing framework utilizes the applications of Python for user interface and fuzzy sciences for decision making. Introduction of multiple sensors in a water distribution network generates a huge number of data matrices, which are sometimes highly complex, difficult to understand and convoluted for effective decision making. Therefore, the proposed system framework also intends to simplify the complexity of obtained sensor data matrices and to support decision making for water engineers through a soft computing framework. The target of this proposed research is to provide a simple and efficient method to identify and detect presence of contamination in a water distribution network using applications of CPS.

A distributed fault-detection and diagnosis system using on-line parameter estimation

NASA Technical Reports Server (NTRS)

Guo, T.-H.; Merrill, W.; Duyar, A.

1991-01-01

The development of a model-based fault-detection and diagnosis system (FDD) is reviewed. The system can be used as an integral part of an intelligent control system. It determines the faults of a system from comparison of the measurements of the system with a priori information represented by the model of the system. The method of modeling a complex system is described and a description of diagnosis models which include process faults is presented. There are three distinct classes of fault modes covered by the system performance model equation: actuator faults, sensor faults, and performance degradation. A system equation for a complete model that describes all three classes of faults is given. The strategy for detecting the fault and estimating the fault parameters using a distributed on-line parameter identification scheme is presented. A two-step approach is proposed. The first step is composed of a group of hypothesis testing modules, (HTM) in parallel processing to test each class of faults. The second step is the fault diagnosis module which checks all the information obtained from the HTM level, isolates the fault, and determines its magnitude. The proposed FDD system was demonstrated by applying it to detect actuator and sensor faults added to a simulation of the Space Shuttle Main Engine. The simulation results show that the proposed FDD system can adequately detect the faults and estimate their magnitudes.

WATER QUALITY EARLY WARNING SYSTEMS FOR SOURCE WATER AND DISTRIBUTION SYSTEM MONITORING

EPA Science Inventory

A variety of probes for use in continuous monitoring of water quality exist. They range from single parameter chemical/physical probes to comprehensive screening systems based on whole organism responses. Originally developed for monitoring specific characteristics of water qua...

Spatial Distribution of Fate and Transport Parameters Using Cxtfit in a Karstified Limestone Model

NASA Astrophysics Data System (ADS)

Toro, J.; Padilla, I. Y.

2017-12-01

Karst environments have a high capacity to transport and store large amounts of water. This makes karst aquifers a productive resource for human consumption and ecological integrity, but also makes them vulnerable to potential contamination of hazardous chemical substances. High heterogeneity and anisotropy of karst aquifer properties make them very difficult to characterize for accurate prediction of contaminant mobility and persistence in groundwater. Current technologies to characterize and quantify flow and transport processes at field-scale is limited by low resolution of spatiotemporal data. To enhance this resolution and provide the essential knowledge of karst groundwater systems, studies at laboratory scale can be conducted. This work uses an intermediate karstified lab-scale physical model (IKLPM) to study fate and transport processes and assess viable tools to characterize heterogeneities in karst systems. Transport experiments are conducted in the IKLPM using step injections of calcium chloride, uranine, and rhodamine wt tracers. Temporal concentration distributions (TCDs) obtained from the experiments are analyzed using the method of moments and CXTFIT to quantify fate and transport parameters in the system at various flow rates. The spatial distribution of the estimated fate and transport parameters for the tracers revealed high variability related to preferential flow heterogeneities and scale dependence. Results are integrated to define spatially-variable transport regions within the system and assess their fate and transport characteristics.

Determination of morphological parameters of biological cells by analysis of scattered-light distributions

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

Burger, D.E.

1979-11-01

The extraction of morphological parameters from biological cells by analysis of light-scatter patterns is described. A light-scattering measurement system has been designed and constructed that allows one to visually examine and photographically record biological cells or cell models and measure the light-scatter pattern of an individual cell or cell model. Using a laser or conventional illumination, the imaging system consists of a modified microscope with a 35 mm camera attached to record the cell image or light-scatter pattern. Models of biological cells were fabricated. The dynamic range and angular distributions of light scattered from these models was compared to calculatedmore » distributions. Spectrum analysis techniques applied on the light-scatter data give the sought after morphological cell parameters. These results compared favorably to shape parameters of the fabricated cell models confirming the mathematical model procedure. For nucleated biological material, correct nuclear and cell eccentricity as well as the nuclear and cytoplasmic diameters were determined. A method for comparing the flow equivalent of nuclear and cytoplasmic size to the actual dimensions is shown. This light-scattering experiment provides baseline information for automated cytology. In its present application, it involves correlating average size as measured in flow cytology to the actual dimensions determined from this technique. (ERB)« less

Mixed Poisson distributions in exact solutions of stochastic autoregulation models.

PubMed

Iyer-Biswas, Srividya; Jayaprakash, C

2014-11-01

In this paper we study the interplay between stochastic gene expression and system design using simple stochastic models of autoactivation and autoinhibition. Using the Poisson representation, a technique whose particular usefulness in the context of nonlinear gene regulation models we elucidate, we find exact results for these feedback models in the steady state. Further, we exploit this representation to analyze the parameter spaces of each model, determine which dimensionless combinations of rates are the shape determinants for each distribution, and thus demarcate where in the parameter space qualitatively different behaviors arise. These behaviors include power-law-tailed distributions, bimodal distributions, and sub-Poisson distributions. We also show how these distribution shapes change when the strength of the feedback is tuned. Using our results, we reexamine how well the autoinhibition and autoactivation models serve their conventionally assumed roles as paradigms for noise suppression and noise exploitation, respectively.

On the issues of probability distribution of GPS carrier phase observations

NASA Astrophysics Data System (ADS)

Luo, X.; Mayer, M.; Heck, B.

2009-04-01

In common practice the observables related to Global Positioning System (GPS) are assumed to follow a Gauss-Laplace normal distribution. Actually, full knowledge of the observables' distribution is not required for parameter estimation by means of the least-squares algorithm based on the functional relation between observations and unknown parameters as well as the associated variance-covariance matrix. However, the probability distribution of GPS observations plays a key role in procedures for quality control (e.g. outlier and cycle slips detection, ambiguity resolution) and in reliability-related assessments of the estimation results. Under non-ideal observation conditions with respect to the factors impacting GPS data quality, for example multipath effects and atmospheric delays, the validity of the normal distribution postulate of GPS observations is in doubt. This paper presents a detailed analysis of the distribution properties of GPS carrier phase observations using double difference residuals. For this purpose 1-Hz observation data from the permanent SAPOS

Engineering Inertial and Primary-Frequency Response for Distributed Energy Resources: Preprint

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

Dall-Anese, Emiliano; Zhao, Changhong; Guggilam, Swaroop

We propose a framework to engineer synthetic-inertia and droop-control parameters for distributed energy resources (DERs) so that the system frequency in a network composed of DERs and synchronous generators conforms to prescribed transient and steady-state performance specifications. Our approach is grounded in a second-order lumped-parameter model that captures the dynamics of synchronous generators and frequency-responsive DERs endowed with inertial and droop control. A key feature of this reduced-order model is that its parameters can be related to those of the originating higher-order dynamical model. This allows one to systematically design the DER inertial and droop-control coefficients leveraging classical frequency-domain responsemore » characteristics of second-order systems. Time-domain simulations validate the accuracy of the model-reduction method and demonstrate how DER controllers can be designed to meet steady-state-regulation and transient-performance specifications.« less

Engineering Inertial and Primary-Frequency Response for Distributed Energy Resources

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

Dall-Anese, Emiliano; Zhao, Changhong; Guggilam, Swaroop

We propose a framework to engineer synthetic-inertia and droop-control parameters for distributed energy resources (DERs) so that the system frequency in a network composed of DERs and synchronous generators conforms to prescribed transient and steady-state performance specifications. Our approach is grounded in a second-order lumped-parameter model that captures the dynamics of synchronous generators and frequency-responsive DERs endowed with inertial and droop control. A key feature of this reduced-order model is that its parameters can be related to those of the originating higherorder dynamical model. This allows one to systematically design the DER inertial and droop-control coefficients leveraging classical frequency-domain responsemore » characteristics of second-order systems. Time-domain simulations validate the accuracy of the model-reduction method and demonstrate how DER controllers can be designed to meet steady-state-regulation and transient-performance specifications.« less

Persistent fluctuations in synchronization rate in globally coupled oscillators with periodic external forcing

NASA Astrophysics Data System (ADS)

Atsumi, Yu; Nakao, Hiroya

2012-05-01

A system of phase oscillators with repulsive global coupling and periodic external forcing undergoing asynchronous rotation is considered. The synchronization rate of the system can exhibit persistent fluctuations depending on parameters and initial phase distributions, and the amplitude of the fluctuations scales with the system size for uniformly random initial phase distributions. Using the Watanabe-Strogatz transformation that reduces the original system to low-dimensional macroscopic equations, we show that the fluctuations are collective dynamics of the system corresponding to low-dimensional trajectories of the reduced equations. It is argued that the amplitude of the fluctuations is determined by the inhomogeneity of the initial phase distribution, resulting in system-size scaling for the random case.

Reliability and sensitivity analysis of a system with multiple unreliable service stations and standby switching failures

NASA Astrophysics Data System (ADS)

Ke, Jyh-Bin; Lee, Wen-Chiung; Wang, Kuo-Hsiung

2007-07-01

This paper presents the reliability and sensitivity analysis of a system with M primary units, W warm standby units, and R unreliable service stations where warm standby units switching to the primary state might fail. Failure times of primary and warm standby units are assumed to have exponential distributions, and service times of the failed units are exponentially distributed. In addition, breakdown times and repair times of the service stations also follow exponential distributions. Expressions for system reliability, RY(t), and mean time to system failure, MTTF are derived. Sensitivity analysis, relative sensitivity analysis of the system reliability and the mean time to failure, with respect to system parameters are also investigated.

Cable Overheating Risk Warning Method Based on Impedance Parameter Estimation in Distribution Network

NASA Astrophysics Data System (ADS)

Yu, Zhang; Xiaohui, Song; Jianfang, Li; Fei, Gao

2017-05-01

Cable overheating will lead to the cable insulation level reducing, speed up the cable insulation aging, even easy to cause short circuit faults. Cable overheating risk identification and warning is nessesary for distribution network operators. Cable overheating risk warning method based on impedance parameter estimation is proposed in the paper to improve the safty and reliability operation of distribution network. Firstly, cable impedance estimation model is established by using least square method based on the data from distribiton SCADA system to improve the impedance parameter estimation accuracy. Secondly, calculate the threshold value of cable impedance based on the historical data and the forecast value of cable impedance based on the forecasting data in future from distribiton SCADA system. Thirdly, establish risks warning rules library of cable overheating, calculate the cable impedance forecast value and analysis the change rate of impedance, and then warn the overheating risk of cable line based on the overheating risk warning rules library according to the variation relationship between impedance and line temperature rise. Overheating risk warning method is simulated in the paper. The simulation results shows that the method can identify the imedance and forecast the temperature rise of cable line in distribution network accurately. The result of overheating risk warning can provide decision basis for operation maintenance and repair.

Modelling topographic potential for erosion and deposition using GIS

Treesearch

Helena Mitasova; Louis R. Iverson

1996-01-01

Modelling of erosion and deposition in complex terrain within a geographical information system (GIS) requires a high resolution digital elevation model (DEM), reliable estimation of topographic parameters, and formulation of erosion models adequate for digital representation of spatially distributed parameters. Regularized spline with tension was integrated within a...

Derivation of the spin-glass order parameter from stochastic thermodynamics

NASA Astrophysics Data System (ADS)

Crisanti, A.; Picco, M.; Ritort, F.

2018-05-01

A fluctuation relation is derived to extract the order parameter function q (x ) in weakly ergodic systems. The relation is based on measuring and classifying entropy production fluctuations according to the value of the overlap q between configurations. For a fixed value of q , entropy production fluctuations are Gaussian distributed allowing us to derive the quasi-FDT so characteristic of aging systems. The theory is validated by extracting the q (x ) in various types of glassy models. It might be generally applicable to other nonequilibrium systems and experimental small systems.

Quasi-Newton methods for parameter estimation in functional differential equations

NASA Technical Reports Server (NTRS)

Brewer, Dennis W.

1988-01-01

A state-space approach to parameter estimation in linear functional differential equations is developed using the theory of linear evolution equations. A locally convergent quasi-Newton type algorithm is applied to distributed systems with particular emphasis on parameters that induce unbounded perturbations of the state. The algorithm is computationally implemented on several functional differential equations, including coefficient and delay estimation in linear delay-differential equations.

Voronoi Cell Patterns: theoretical model and application to submonolayer growth

NASA Astrophysics Data System (ADS)

González, Diego Luis; Einstein, T. L.

2012-02-01

We use a simple fragmentation model to describe the statistical behavior of the Voronoi cell patterns generated by a homogeneous and isotropic set of points in 1D and in 2D. In particular, we are interested in the distribution of sizes of these Voronoi cells. Our model is completely defined by two probability distributions in 1D and again in 2D, the probability to add a new point inside an existing cell and the probability that this new point is at a particular position relative to the preexisting point inside this cell. In 1D the first distribution depends on a single parameter while the second distribution is defined through a fragmentation kernel; in 2D both distributions depend on a single parameter. The fragmentation kernel and the control parameters are closely related to the physical properties of the specific system under study. We apply our model to describe the Voronoi cell patterns of island nucleation for critical island sizes i=0,1,2,3. Experimental results for the Voronoi cells of InAs/GaAs quantum dots are also described by our model.

"TNOs are Cool": A survey of the trans-Neptunian region. XIII. Statistical analysis of multiple trans-Neptunian objects observed with Herschel Space Observatory

NASA Astrophysics Data System (ADS)

Kovalenko, I. D.; Doressoundiram, A.; Lellouch, E.; Vilenius, E.; Müller, T.; Stansberry, J.

2017-11-01

Context. Gravitationally bound multiple systems provide an opportunity to estimate the mean bulk density of the objects, whereas this characteristic is not available for single objects. Being a primitive population of the outer solar system, binary and multiple trans-Neptunian objects (TNOs) provide unique information about bulk density and internal structure, improving our understanding of their formation and evolution. Aims: The goal of this work is to analyse parameters of multiple trans-Neptunian systems, observed with Herschel and Spitzer space telescopes. Particularly, statistical analysis is done for radiometric size and geometric albedo, obtained from photometric observations, and for estimated bulk density. Methods: We use Monte Carlo simulation to estimate the real size distribution of TNOs. For this purpose, we expand the dataset of diameters by adopting the Minor Planet Center database list with available values of the absolute magnitude therein, and the albedo distribution derived from Herschel radiometric measurements. We use the 2-sample Anderson-Darling non-parametric statistical method for testing whether two samples of diameters, for binary and single TNOs, come from the same distribution. Additionally, we use the Spearman's coefficient as a measure of rank correlations between parameters. Uncertainties of estimated parameters together with lack of data are taken into account. Conclusions about correlations between parameters are based on statistical hypothesis testing. Results: We have found that the difference in size distributions of multiple and single TNOs is biased by small objects. The test on correlations between parameters shows that the effective diameter of binary TNOs strongly correlates with heliocentric orbital inclination and with magnitude difference between components of binary system. The correlation between diameter and magnitude difference implies that small and large binaries are formed by different mechanisms. Furthermore, the statistical test indicates, although not significant with the sample size, that a moderately strong correlation exists between diameter and bulk density. Herschel is an ESA space observatory with science instruments provided by European-led Principal Investigator consortia and with important participation from NASA.

Derivation of a Multiparameter Gamma Model for Analyzing the Residence-Time Distribution Function for Nonideal Flow Systems as an Alternative to the Advection-Dispersion Equation

DOE PAGES

Embry, Irucka; Roland, Victor; Agbaje, Oluropo; ...

2013-01-01

A new residence-time distribution (RTD) function has been developed and applied to quantitative dye studies as an alternative to the traditional advection-dispersion equation (AdDE). The new method is based on a jointly combined four-parameter gamma probability density function (PDF). The gamma residence-time distribution (RTD) function and its first and second moments are derived from the individual two-parameter gamma distributions of randomly distributed variables, tracer travel distance, and linear velocity, which are based on their relationship with time. The gamma RTD function was used on a steady-state, nonideal system modeled as a plug-flow reactor (PFR) in the laboratory to validate themore » effectiveness of the model. The normalized forms of the gamma RTD and the advection-dispersion equation RTD were compared with the normalized tracer RTD. The normalized gamma RTD had a lower mean-absolute deviation (MAD) (0.16) than the normalized form of the advection-dispersion equation (0.26) when compared to the normalized tracer RTD. The gamma RTD function is tied back to the actual physical site due to its randomly distributed variables. The results validate using the gamma RTD as a suitable alternative to the advection-dispersion equation for quantitative tracer studies of non-ideal flow systems.« less

Numerical investigation on properties of attack angle for an opposing jet thermal protection system

NASA Astrophysics Data System (ADS)

Lu, Hai-Bo; Liu, Wei-Qiang

2012-08-01

The three-dimensional Navier—Stokes equation and the k-in viscous model are used to simulate the attack angle characteristics of a hemisphere nose-tip with an opposing jet thermal protection system in supersonic flow conditions. The numerical method is validated by the relevant experiment. The flow field parameters, aerodynamic forces, and surface heat flux distributions for attack angles of 0°, 2°, 5°, 7°, and 10° are obtained. The detailed numerical results show that the cruise attack angle has a great influence on the flow field parameters, aerodynamic force, and surface heat flux distribution of the supersonic vehicle nose-tip with an opposing jet thermal protection system. When the attack angle reaches 10°, the heat flux on the windward generatrix is close to the maximal heat flux on the wall surface of the nose-tip without thermal protection system, thus the thermal protection has failed.

Atlas of Relations Between Climatic Parameters and Distributions of Important Trees and Shrubs in North America - Ecoregions of North America

USGS Publications Warehouse

Thompson, Robert S.; Anderson, Katherine H.; Pelltier, Richard T.; Shafer, Sarah L.; Bartlein, Patrick J.

2007-01-01

Climate is the primary factor controlling the continental-scale distribution of plant species, although the relations between climatic parameters and species' ranges are only now beginning to be quantified. This volume examines the relations between climate and the distributions of (1) Kuchler's 'potential natural vegetation' categories for the 48 contiguous States of the United States of America, (2) Bailey's ecoregions of North America, and (3) World Wildlife Fund's ecoregions of North America. For these analyses, we employed a 25-kilometer equal-area grid of modern climatic and bioclimatic parameters for North America, coupled with presence-absence data for the occurrence of each ecoregion under the three classification systems under consideration. The resulting relations between climate and ecoregion distributions are presented in graphical and tabular form. Presentation of ecoregion-climate relations here is intended to be useful for a greater understanding of ecosystem evolution, ecosystem dynamics, and potential effects of future climate change on ecoregions.

Present and future free-space quantum key distribution

NASA Astrophysics Data System (ADS)

Nordholt, Jane E.; Hughes, Richard J.; Morgan, George L.; Peterson, C. Glen; Wipf, Christopher C.

2002-04-01

Free-space quantum key distribution (QKD), more popularly know as quantum cryptography, uses single-photon free-space optical communications to distribute the secret keys required for secure communications. At Los Alamos National Laboratory we have demonstrated a fully automated system that is capable of operations at any time of day over a horizontal range of several kilometers. This has proven the technology is capable of operation from a spacecraft to the ground, opening up the possibility of QKD between any group of users anywhere on Earth. This system, the prototyping of a new system for use on a spacecraft, and the techniques required for world-wide quantum key distribution will be described. The operational parameters and performance of a system designed to operate between low earth orbit (LEO) and the ground will also be discussed.

Multi-Agent Architecture with Support to Quality of Service and Quality of Control

NASA Astrophysics Data System (ADS)

Poza-Luján, Jose-Luis; Posadas-Yagüe, Juan-Luis; Simó-Ten, Jose-Enrique

Multi Agent Systems (MAS) are one of the most suitable frameworks for the implementation of intelligent distributed control system. Agents provide suitable flexibility to give support to implied heterogeneity in cyber-physical systems. Quality of Service (QoS) and Quality of Control (QoC) parameters are commonly utilized to evaluate the efficiency of the communications and the control loop. Agents can use the quality measures to take a wide range of decisions, like suitable placement on the control node or to change the workload to save energy. This article describes the architecture of a multi agent system that provides support to QoS and QoC parameters to optimize de system. The architecture uses a Publish-Subscriber model, based on Data Distribution Service (DDS) to send the control messages. Due to the nature of the Publish-Subscribe model, the architecture is suitable to implement event-based control (EBC) systems. The architecture has been called FSACtrl.

Efficient Calibration of Distributed Catchment Models Using Perceptual Understanding and Hydrologic Signatures

NASA Astrophysics Data System (ADS)

Hutton, C.; Wagener, T.; Freer, J. E.; Duffy, C.; Han, D.

2015-12-01

Distributed models offer the potential to resolve catchment systems in more detail, and therefore simulate the hydrological impacts of spatial changes in catchment forcing (e.g. landscape change). Such models may contain a large number of model parameters which are computationally expensive to calibrate. Even when calibration is possible, insufficient data can result in model parameter and structural equifinality. In order to help reduce the space of feasible models and supplement traditional outlet discharge calibration data, semi-quantitative information (e.g. knowledge of relative groundwater levels), may also be used to identify behavioural models when applied to constrain spatially distributed predictions of states and fluxes. The challenge is to combine these different sources of information together to identify a behavioural region of state-space, and efficiently search a large, complex parameter space to identify behavioural parameter sets that produce predictions that fall within this behavioural region. Here we present a methodology to incorporate different sources of data to efficiently calibrate distributed catchment models. Metrics of model performance may be derived from multiple sources of data (e.g. perceptual understanding and measured or regionalised hydrologic signatures). For each metric, an interval or inequality is used to define the behaviour of the catchment system, accounting for data uncertainties. These intervals are then combined to produce a hyper-volume in state space. The state space is then recast as a multi-objective optimisation problem, and the Borg MOEA is applied to first find, and then populate the hyper-volume, thereby identifying acceptable model parameter sets. We apply the methodology to calibrate the PIHM model at Plynlimon, UK by incorporating perceptual and hydrologic data into the calibration problem. Furthermore, we explore how to improve calibration efficiency through search initialisation from shorter model runs.

Stability, performance and sensitivity analysis of I.I.D. jump linear systems

NASA Astrophysics Data System (ADS)

Chávez Fuentes, Jorge R.; González, Oscar R.; Gray, W. Steven

2018-06-01

This paper presents a symmetric Kronecker product analysis of independent and identically distributed jump linear systems to develop new, lower dimensional equations for the stability and performance analysis of this type of systems than what is currently available. In addition, new closed form expressions characterising multi-parameter relative sensitivity functions for performance metrics are introduced. The analysis technique is illustrated with a distributed fault-tolerant flight control example where the communication links are allowed to fail randomly.

Contents of the JPL Distributed Active Archive Center (DAAC) archive, version 2-91

NASA Technical Reports Server (NTRS)

Smith, Elizabeth A. (Editor); Lassanyi, Ruby A. (Editor)

1991-01-01

The Distributed Active Archive Center (DAAC) archive at the Jet Propulsion Laboratory (JPL) includes satellite data sets for the ocean sciences and global change research to facilitate multidisciplinary use of satellite ocean data. Parameters include sea surface height, surface wind vector, sea surface temperature, atmospheric liquid water, and surface pigment concentration. The Jet Propulsion Laboratory DAAC is an element of the Earth Observing System Data and Information System (EOSDIS) and will be the United States distribution site for the Ocean Topography Experiment (TOPEX)/POSEIDON data and metadata.

JPL Physical Oceanography Distributed Active Archive Center (PO.DAAC) data availability, version 1-94

NASA Technical Reports Server (NTRS)

1994-01-01

The Physical Oceanography Distributed Active Archive Center (PO.DAAC) archive at the Jet Propulsion Laboratory (JPL) includes satellite data sets for the ocean sciences and global-change research to facilitate multidisciplinary use of satellite ocean data. Parameters include sea-surface height, surface-wind vector, sea-surface temperature, atmospheric liquid water, and integrated water vapor. The JPL PO.DAAC is an element of the Earth Observing System Data and Information System (EOSDIS) and is the United States distribution site for Ocean Topography Experiment (TOPEX)/POSEIDON data and metadata.

RF model of the distribution system as a communication channel, phase 2. Volume 2: Task reports

NASA Technical Reports Server (NTRS)

Rustay, R. C.; Gajjar, J. T.; Rankin, R. W.; Wentz, R. C.; Wooding, R.

1982-01-01

Based on the established feasibility of predicting, via a model, the propagation of Power Line Frequency on radial type distribution feeders, verification studies comparing model predictions against measurements were undertaken using more complicated feeder circuits and situations. Detailed accounts of the major tasks are presented. These include: (1) verification of model; (2) extension, implementation, and verification of perturbation theory; (3) parameter sensitivity; (4) transformer modeling; and (5) compensation of power distribution systems for enhancement of power line carrier communication reliability.

Fully Burdened Cost of Energy Analysis: A Model for Marine Corps Systems

DTIC Science & Technology

2013-03-01

and the lognormal parameters are not used in the creation of the output distribution since they are not required values for a triangular distribution...Army energy security implementation strategy. Washington, DC: Government Printing Office. Bell Helicopter. (n.d.). The Bell AH-1Z Zulu [Image

An Analysis of Transient Overvoltages during the Energization of Electric Ship Propulsion Systems

PubMed Central

Brenna, Morris; Foiadelli, Federica; Zaninelli, Dario

2015-01-01

This paper addresses the resonance phenomena that can occur in an isolated distribution system during transient events such as repeated energizations or power converter switching. In particular, the aim of this study is to analyze the energization of an onboard radial distribution system installed on an electric ship and to determine how the various leakage parameters that can cause resonance problems such as high peak overvoltages when the circuit breaker is closed are relevant. The paper presents a detailed model of whole distribution system, which is validated using infield measurements that refer to a real case in which these events damaged the ships transformers, causing it to be removed from duty. PMID:26240835

Mixed-mode oscillations and interspike interval statistics in the stochastic FitzHugh-Nagumo model

NASA Astrophysics Data System (ADS)

Berglund, Nils; Landon, Damien

2012-08-01

We study the stochastic FitzHugh-Nagumo equations, modelling the dynamics of neuronal action potentials in parameter regimes characterized by mixed-mode oscillations. The interspike time interval is related to the random number of small-amplitude oscillations separating consecutive spikes. We prove that this number has an asymptotically geometric distribution, whose parameter is related to the principal eigenvalue of a substochastic Markov chain. We provide rigorous bounds on this eigenvalue in the small-noise regime and derive an approximation of its dependence on the system's parameters for a large range of noise intensities. This yields a precise description of the probability distribution of observed mixed-mode patterns and interspike intervals.

Economic optimization of the energy transport component of a large distributed solar power plant

NASA Technical Reports Server (NTRS)

Turner, R. H.

1976-01-01

A solar thermal power plant with a field of collectors, each locally heating some transport fluid, requires a pipe network system for eventual delivery of energy power generation equipment. For a given collector distribution and pipe network geometry, a technique is herein developed which manipulates basic cost information and physical data in order to design an energy transport system consistent with minimized cost constrained by a calculated technical performance. For a given transport fluid and collector conditions, the method determines the network pipe diameter and pipe thickness distribution and also insulation thickness distribution associated with minimum system cost; these relative distributions are unique. Transport losses, including pump work and heat leak, are calculated operating expenses and impact the total system cost. The minimum cost system is readily selected. The technique is demonstrated on six candidate transport fluids to emphasize which parameters dominate the system cost and to provide basic decision data. Three different power plant output sizes are evaluated in each case to determine severity of diseconomy of scale.

System identification for modeling for control of flexible structures

NASA Technical Reports Server (NTRS)

Mettler, Edward; Milman, Mark

1986-01-01

The major components of a design and operational flight strategy for flexible structure control systems are presented. In this strategy an initial distributed parameter control design is developed and implemented from available ground test data and on-orbit identification using sophisticated modeling and synthesis techniques. The reliability of this high performance controller is directly linked to the accuracy of the parameters on which the design is based. Because uncertainties inevitably grow without system monitoring, maintaining the control system requires an active on-line system identification function to supply parameter updates and covariance information. Control laws can then be modified to improve performance when the error envelopes are decreased. In terms of system safety and stability the covariance information is of equal importance as the parameter values themselves. If the on-line system ID function detects an increase in parameter error covariances, then corresponding adjustments must be made in the control laws to increase robustness. If the error covariances exceed some threshold, an autonomous calibration sequence could be initiated to restore the error enveloped to an acceptable level.

Local instability driving extreme events in a pair of coupled chaotic electronic circuits

NASA Astrophysics Data System (ADS)

de Oliveira, Gilson F.; Di Lorenzo, Orlando; de Silans, Thierry Passerat; Chevrollier, Martine; Oriá, Marcos; Cavalcante, Hugo L. D. de Souza

2016-06-01

For a long time, extreme events happening in complex systems, such as financial markets, earthquakes, and neurological networks, were thought to follow power-law size distributions. More recently, evidence suggests that in many systems the largest and rarest events differ from the other ones. They are dragon kings, outliers that make the distribution deviate from a power law in the tail. Understanding the processes of formation of extreme events and what circumstances lead to dragon kings or to a power-law distribution is an open question and it is a very important one to assess whether extreme events will occur too often in a specific system. In the particular system studied in this paper, we show that the rate of occurrence of dragon kings is controlled by the value of a parameter. The system under study here is composed of two nearly identical chaotic oscillators which fail to remain in a permanently synchronized state when coupled. We analyze the statistics of the desynchronization events in this specific example of two coupled chaotic electronic circuits and find that modifying a parameter associated to the local instability responsible for the loss of synchronization reduces the occurrence of dragon kings, while preserving the power-law distribution of small- to intermediate-size events with the same scaling exponent. Our results support the hypothesis that the dragon kings are caused by local instabilities in the phase space.

Spectroradiometric calibration of the Thematic Mapper and Multispectral Scanner system

NASA Technical Reports Server (NTRS)

Palmer, J. M.; Slater, P. N. (Principal Investigator)

1985-01-01

The effects of the atmosphere on propagating radiation must be known in order to calibrate an in orbit sensor using ground based measurements. A set of model atmosphere parameters, applicable to the White Sands (New Mexico) area is defined with particular attention given to those parameters which are required as input to the Herman Code. The radial size distribution, refractive index, vertical distribution, and visibility of aerosols are discussed as well as the molecular absorbers in the visible and near IR wavelength which produce strong absorption lines. Solar irradiance is also considered.

Effect of Cattaneo-Christov heat flux on Jeffrey fluid flow with variable thermal conductivity

NASA Astrophysics Data System (ADS)

Hayat, Tasawar; Javed, Mehwish; Imtiaz, Maria; Alsaedi, Ahmed

2018-03-01

This paper presents the study of Jeffrey fluid flow by a rotating disk with variable thickness. Energy equation is constructed by using Cattaneo-Christov heat flux model with variable thermal conductivity. A system of equations governing the model is obtained by applying boundary layer approximation. Resulting nonlinear partial differential system is transformed to ordinary differential system. Homotopy concept leads to the convergent solutions development. Graphical analysis for velocities and temperature is made to examine the influence of different involved parameters. Thermal relaxation time parameter signifies that temperature for Fourier's heat law is more than Cattaneo-Christov heat flux. A constitutional analysis is made for skin friction coefficient and heat transfer rate. Effects of Prandtl number on temperature distribution and heat transfer rate are scrutinized. It is observed that larger Reynolds number gives illustrious temperature distribution.

Application of the FADS system on the Re-entry Module

NASA Astrophysics Data System (ADS)

Zhen, Huang

2016-07-01

The aerodynamic model for Flush Air Data Sensing System (FADS) is built based on the surface pressure distribution obtained through the pressure orifices laid on specific positions of the surface,and the flight parameters,such as angle of attack,angle of side-slip,Mach number,free-stream static pressure and dynamic pressure are inferred from the aerodynamic model.The flush air data sensing system (FADS) has been used on several flight tests of aircraft and re-entry vehicle,such as,X-15,space shuttle,F-14,X-33,X-43A and so on. This paper discusses the application of the FADS on the re-entry module with blunt body to obtain high-precision aerodynamic parameters.First of all,a basic theory and operating principle of the FADS is shown.Then,the applications of the FADS on typical aircrafts and re-entry vehicles are described.Thirdly,the application mode on the re-entry module with blunt body is discussed in detail,including aerodynamic simulation,pressure distribution,trajectory reconstruction and the hardware shoule be used,such as flush air data sensing system(FADS),inertial navigation system (INS),data acquisition system,data storage system.Finally,ablunt module re-entry flight test from low earth orbit (LEO) is planned to obtain aerodynamic parameters and amend the aerodynamic model with this FADS system data.The results show that FADS system can be applied widely in re-entry module with blunt bodies.

Thermodynamic behavior of a phase transition in a model for sympatric speciation

NASA Astrophysics Data System (ADS)

Luz-Burgoa, K.; Moss de Oliveira, S.; Schwämmle, Veit; Sá Martins, J. S.

2006-08-01

We investigate the macroscopic effects of the ingredients that drive the origin of species through sympatric speciation. In our model, sympatric speciation is obtained as we tune up the strength of competition between individuals with different phenotypes. As a function of this control parameter, we can characterize, through the behavior of a macroscopic order parameter, a phase transition from a nonspeciation to a speciation state of the system. The behavior of the first derivative of the order parameter with respect to the control parameter is consistent with a phase transition and exhibits a sharp peak at the transition point. For different resources distribution, the transition point is shifted, an effect similar to pressure in a PVT system. The inverse of the parameter related to a sexual selection strength behaves like an external field in the system and, as thus, is also a control parameter. The macroscopic effects of the biological parameters used in our model are a reminiscent of the behavior of thermodynamic quantities in a phase transition of an equilibrium physical system.

Distributed sensor for water and pH measurements using fiber optics and swellable polymeric systems

NASA Astrophysics Data System (ADS)

Michie, W. C.; Culshaw, B.; McKenzie, I.; Konstantakis, M.; Graham, N. B.; Moran, C.; Santos, F.; Bergqvist, E.; Carlstrom, B.

1995-01-01

We report on the design, construction and test of a generic form of sensor for making distributed measurements of a range of chemical parameters. The technique combines optical time-domain reflectometry with chemically sensitive water-swellable polymers (hydrogels). Initial experiments have concentrated on demonstrating a distributed water detector; however, gels have been developed that enable this sensor to be

Logistics Distribution Center Location Evaluation Based on Genetic Algorithm and Fuzzy Neural Network

NASA Astrophysics Data System (ADS)

Shao, Yuxiang; Chen, Qing; Wei, Zhenhua

Logistics distribution center location evaluation is a dynamic, fuzzy, open and complicated nonlinear system, which makes it difficult to evaluate the distribution center location by the traditional analysis method. The paper proposes a distribution center location evaluation system which uses the fuzzy neural network combined with the genetic algorithm. In this model, the neural network is adopted to construct the fuzzy system. By using the genetic algorithm, the parameters of the neural network are optimized and trained so as to improve the fuzzy system’s abilities of self-study and self-adaptation. At last, the sampled data are trained and tested by Matlab software. The simulation results indicate that the proposed identification model has very small errors.

Evaluation of physico-chemical characteristics of groundwater of Company Bagh pumping station and its six distribution points in old Jammu City, India.

PubMed

Khajuria, Meenakshi; Dutta, S P S

2011-10-01

To assess water quality of Company Bagh pumping station and its six distribution points, viz. Parade Ground, Mohalla Paharian, Purani Mandi, Malhotrian Street, Raghunathpura and Hari Market in old Jammu city of India, water parameters viz. temperature, turbidity, pH, electrical conductivity, free carbon dioxide, dissolved oxygen, biochemical oxygen demand, chemical oxygen demand, bicarbonate, chloride, calcium, magnesium, total hardness, sodium, potassium, sulphate, silicate, nitrate, phosphate, iron, copper, zinc, lead and chromium were analyzed during the years 2000-2001/2001-2002. There was alteration in water quality parameters in the distribution system caused by entry of sewage, soil, etc. through dislocation, cracks, valve regulators/turncock, defective joints, breakage, etc. in the pipes through crossing and deposits of biofilms inside the pipes, dead ends and their degradation through microbes. Comparison of water quality with National and International Standards revealed that all the parameters were within permissible limits of drinking water standards. Water Quality Index (WQI) of various physico-chemical parameters revealed that the water of Company Bagh pumping station and its six distribution points was fit for human consumption as it was found under the category of good (WQI < 50).

Nonlinear Control Systems

DTIC Science & Technology

2007-03-01

Finite -dimensional regulators for a class of infinite dimensional systems ,” Systems and Control Letters, 3 (1983), 7-12. [11] B...semiglobal stabilizability by encoded state feedback,” to appear in Systems and Control Letters. 22 29. C. De Persis, A. Isidori, “Global stabilization of...nonequilibrium setting, for both finite and infinite dimensional control systems . Our objectives for distributed parameter systems included

Microbubble Sizing and Shell Characterization Using Flow Cytometry

PubMed Central

Tu, Juan; Swalwell, Jarred E.; Giraud, David; Cui, Weicheng; Chen, Weizhong; Matula, Thomas J.

2015-01-01

Experiments were performed to size, count, and obtain shell parameters for individual ultrasound contrast microbubbles using a modified flow cytometer. Light scattering was modeled using Mie theory, and applied to calibration beads to calibrate the system. The size distribution and population were measured directly from the flow cytometer. The shell parameters (shear modulus and shear viscosity) were quantified at different acoustic pressures (from 95 to 333 kPa) by fitting microbubble response data to a bubble dynamics model. The size distribution of the contrast agent microbubbles is consistent with manufacturer specifications. The shell shear viscosity increases with increasing equilibrium microbubble size, and decreases with increasing shear rate. The observed trends are independent of driving pressure amplitude. The shell elasticity does not vary with microbubble size. The results suggest that a modified flow cytometer can be an effective tool to characterize the physical properties of microbubbles, including size distribution, population, and shell parameters. PMID:21622051

Approximation techniques for parameter estimation and feedback control for distributed models of large flexible structures

NASA Technical Reports Server (NTRS)

Banks, H. T.; Rosen, I. G.

1984-01-01

Approximation ideas are discussed that can be used in parameter estimation and feedback control for Euler-Bernoulli models of elastic systems. Focusing on parameter estimation problems, ways by which one can obtain convergence results for cubic spline based schemes for hybrid models involving an elastic cantilevered beam with tip mass and base acceleration are outlined. Sample numerical findings are also presented.

Classical spin glass system in external field with taking into account relaxation effects

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

Gevorkyan, A. S., E-mail: g_ashot@sci.am; Abajyan, H. G.

2013-08-15

We study statistical properties of disordered spin systems under the influence of an external field with taking into account relaxation effects. For description of system the spatial 1D Heisenberg spin-glass Hamiltonian is used. In addition, we suppose that interactions occur between nearest-neighboring spins and they are random. Exact solutions which define angular configuration of the spin in nodes were obtained from the equations of stationary points of Hamiltonian and the corresponding conditions for the energy local minimum. On the basis of these recurrent solutions an effective parallel algorithm is developed for simulation of stabile spin-chains of an arbitrary length. Itmore » is shown that by way of an independent order of N{sup 2} numerical simulations (where N is number of spin in each chain) it is possible to generate ensemble of spin-chains, which is completely ergodic which is equivalent to full self-averaging of spin-chains' vector polarization. Distributions of different parameters (energy, average polarization by coordinates, and spin-spin interaction constant) of unperturbed system are calculated. In particular, analytically is proved and numerically is shown, that for the Heisenberg nearest-neighboring Hamiltonian model, the distribution of spin-spin interaction constants as opposed to widely used Gauss-Edwards-Anderson distribution satisfies Levy alpha-stable distribution law. This distribution is nonanalytic function and does not have variance. In the work we have in detail studied critical properties of an ensemble depending on value of external field parameters (from amplitude and frequency) and have shown that even at weak external fields the spin-glass systemis strongly frustrated. It is shown that frustrations have fractal behavior, they are selfsimilar and do not disappear at scale decreasing of area. By the numerical computation is shown that the average polarization of spin-glass on a different coordinates can have values which can lead to catastrophes in the equation ofClausius-Mossotti for dielectric constant. In other words, for some values of external field parameter, a critical phenomenon occurs in the system which is impossible to describe by the real-valued Heisenberg spin-glass Hamiltonian. For the solution of this problem at first the complex-valued disordered Hamiltonian is used. Physically this type of extension of Hamiltonian allows to consider relaxation effects which occur in the system under the influence of an external field. On the basis of developed approach an effective parallel algorithm is developed for simulation of statistic parameters of spin-glass system under the influence of an external field.« less

On-Line Water Quality Parameters as Indicators of Distribution System Contamination

EPA Science Inventory

At a time when the safety and security of services we have typically taken for granted are under question, a real-time or near real-time method of monitoring changes in water quality parameters could provide a critical line of defense in protecting public health. This study was u...

Investigating the relationship between a soils classification and the spatial parameters of a conceptual catchment-scale hydrological model

NASA Astrophysics Data System (ADS)

Dunn, S. M.; Lilly, A.

2001-10-01

There are now many examples of hydrological models that utilise the capabilities of Geographic Information Systems to generate spatially distributed predictions of behaviour. However, the spatial variability of hydrological parameters relating to distributions of soils and vegetation can be hard to establish. In this paper, the relationship between a soil hydrological classification Hydrology of Soil Types (HOST) and the spatial parameters of a conceptual catchment-scale model is investigated. A procedure involving inverse modelling using Monte-Carlo simulations on two catchments is developed to identify relative values for soil related parameters of the DIY model. The relative values determine the internal variability of hydrological processes as a function of the soil type. For three out of the four soil parameters studied, the variability between HOST classes was found to be consistent across two catchments when tested independently. Problems in identifying values for the fourth 'fast response distance' parameter have highlighted a potential limitation with the present structure of the model. The present assumption that this parameter can be related simply to soil type rather than topography appears to be inadequate. With the exclusion of this parameter, calibrated parameter sets from one catchment can be converted into equivalent parameter sets for the alternate catchment on the basis of their HOST distributions, to give a reasonable simulation of flow. Following further testing on different catchments, and modifications to the definition of the fast response distance parameter, the technique provides a methodology whereby it is possible to directly derive spatial soil parameters for new catchments.

A digital protection system incorporating knowledge based learning

NASA Astrophysics Data System (ADS)

Watson, Karan; Russell, B. Don; McCall, Kurt

A digital system architecture used to diagnoses the operating state and health of electric distribution lines and to generate actions for line protection is presented. The architecture is described functionally and to a limited extent at the hardware level. This architecture incorporates multiple analysis and fault-detection techniques utilizing a variety of parameters. In addition, a knowledge-based decision maker, a long-term memory retention and recall scheme, and a learning environment are described. Preliminary laboratory implementations of the system elements have been completed. Enhanced protection for electric distribution feeders is provided by this system. Advantages of the system are enumerated.

Distributed Time-Varying Formation Robust Tracking for General Linear Multiagent Systems With Parameter Uncertainties and External Disturbances.

PubMed

Hua, Yongzhao; Dong, Xiwang; Li, Qingdong; Ren, Zhang

2017-05-18

This paper investigates the time-varying formation robust tracking problems for high-order linear multiagent systems with a leader of unknown control input in the presence of heterogeneous parameter uncertainties and external disturbances. The followers need to accomplish an expected time-varying formation in the state space and track the state trajectory produced by the leader simultaneously. First, a time-varying formation robust tracking protocol with a totally distributed form is proposed utilizing the neighborhood state information. With the adaptive updating mechanism, neither any global knowledge about the communication topology nor the upper bounds of the parameter uncertainties, external disturbances and leader's unknown input are required in the proposed protocol. Then, in order to determine the control parameters, an algorithm with four steps is presented, where feasible conditions for the followers to accomplish the expected time-varying formation tracking are provided. Furthermore, based on the Lyapunov-like analysis theory, it is proved that the formation tracking error can converge to zero asymptotically. Finally, the effectiveness of the theoretical results is verified by simulation examples.

A partial exponential lumped parameter model to evaluate groundwater age distributions and nitrate trends in long-screened wells

USGS Publications Warehouse

Jurgens, Bryant; Böhlke, John Karl; Kauffman, Leon J.; Belitz, Kenneth; Esser, Bradley K.

2016-01-01

A partial exponential lumped parameter model (PEM) was derived to determine age distributions and nitrate trends in long-screened production wells. The PEM can simulate age distributions for wells screened over any finite interval of an aquifer that has an exponential distribution of age with depth. The PEM has 3 parameters – the ratio of saturated thickness to the top and bottom of the screen and mean age, but these can be reduced to 1 parameter (mean age) by using well construction information and estimates of the saturated thickness. The PEM was tested with data from 30 production wells in a heterogeneous alluvial fan aquifer in California, USA. Well construction data were used to guide parameterization of a PEM for each well and mean age was calibrated to measured environmental tracer data (3H, 3He, CFC-113, and 14C). Results were compared to age distributions generated for individual wells using advective particle tracking models (PTMs). Age distributions from PTMs were more complex than PEM distributions, but PEMs provided better fits to tracer data, partly because the PTMs did not simulate 14C accurately in wells that captured varying amounts of old groundwater recharged at lower rates prior to groundwater development and irrigation. Nitrate trends were simulated independently of the calibration process and the PEM provided good fits for at least 11 of 24 wells. This work shows that the PEM, and lumped parameter models (LPMs) in general, can often identify critical features of the age distributions in wells that are needed to explain observed tracer data and nonpoint source contaminant trends, even in systems where aquifer heterogeneity and water-use complicate distributions of age. While accurate PTMs are preferable for understanding and predicting aquifer-scale responses to water use and contaminant transport, LPMs can be sensitive to local conditions near individual wells that may be inaccurately represented or missing in an aquifer-scale flow model.

Precipitation-runoff modeling system; user's manual

USGS Publications Warehouse

Leavesley, G.H.; Lichty, R.W.; Troutman, B.M.; Saindon, L.G.

1983-01-01

The concepts, structure, theoretical development, and data requirements of the precipitation-runoff modeling system (PRMS) are described. The precipitation-runoff modeling system is a modular-design, deterministic, distributed-parameter modeling system developed to evaluate the impacts of various combinations of precipitation, climate, and land use on streamflow, sediment yields, and general basin hydrology. Basin response to normal and extreme rainfall and snowmelt can be simulated to evaluate changes in water balance relationships, flow regimes, flood peaks and volumes, soil-water relationships, sediment yields, and groundwater recharge. Parameter-optimization and sensitivity analysis capabilites are provided to fit selected model parameters and evaluate their individual and joint effects on model output. The modular design provides a flexible framework for continued model system enhancement and hydrologic modeling research and development. (Author 's abstract)

Information system of forest growth and productivity by site quality type and elements of forest

NASA Astrophysics Data System (ADS)

Khlyustov, V.

2012-04-01

Information system of forest growth and productivity by site quality type and elements of forest V.K. Khlustov Head of the Forestry Department of Russian State Agrarian University named after K.A.Timiryazev doctor of agricultural sciences, professor The efficiency of forest management can be improved substantially by development and introduction of principally new models of forest growth and productivity dynamics based on regionalized site specific parameters. Therefore an innovative information system was developed. It describes the current state and gives a forecast for forest stand parameters: growth, structure, commercial and biological productivity depend on type of site quality. In contrast to existing yield tables, the new system has environmental basis: site quality type. The information system contains set of multivariate statistical models and can work at the level of individual trees or at the stand level. The system provides a graphical visualization, as well as export of the emulation results. The System is able to calculate detailed description of any forest stand based on five initial indicators: site quality type, site index, stocking, composition, and tree age by elements of the forest. The results of the model run are following parameters: average diameter and height, top height, number of trees, basal area, growing stock (total, commercial with distribution by size, firewood and residuals), live biomass (stem, bark, branches, foliage). The system also provides the distribution of mentioned above forest stand parameters by tree diameter classes. To predict the future forest stand dynamics the system require in addition the time slot only. Full set of forest parameters mention above will be provided by the System. The most conservative initial parameters (site quality type and site index) can be kept in the form of geo referenced polygons. In this case the system would need only 3 dynamic initial parameters (stocking, composition and age) to simulate forest parameters and their dynamics. The system can substitute traditional processing of forest inventory field data and provide users with detailed information on the current state of forest and give a prediction. Implementation of the proposed system in combination with high resolution remote sensing is able to increase significantly the quality of forest inventory and at the same time reduce the costs. The system is a contribution to site oriented forest management. The System is registered in the Russian State Register of Computer Programs 12.07.2011, No 2011615418.

Maximum Renyi entropy principle for systems with power-law Hamiltonians.

PubMed

Bashkirov, A G

2004-09-24

The Renyi distribution ensuring the maximum of Renyi entropy is investigated for a particular case of a power-law Hamiltonian. Both Lagrange parameters alpha and beta can be eliminated. It is found that beta does not depend on a Renyi parameter q and can be expressed in terms of an exponent kappa of the power-law Hamiltonian and an average energy U. The Renyi entropy for the resulting Renyi distribution reaches its maximal value at q=1/(1+kappa) that can be considered as the most probable value of q when we have no additional information on the behavior of the stochastic process. The Renyi distribution for such q becomes a power-law distribution with the exponent -(kappa+1). When q=1/(1+kappa)+epsilon (0

Regression modeling of particle size distributions in urban storm water: advancements through improved sample collection methods

USGS Publications Warehouse

Fienen, Michael N.; Selbig, William R.

2012-01-01

A new sample collection system was developed to improve the representation of sediment entrained in urban storm water by integrating water quality samples from the entire water column. The depth-integrated sampler arm (DISA) was able to mitigate sediment stratification bias in storm water, thereby improving the characterization of suspended-sediment concentration and particle size distribution at three independent study locations. Use of the DISA decreased variability, which improved statistical regression to predict particle size distribution using surrogate environmental parameters, such as precipitation depth and intensity. The performance of this statistical modeling technique was compared to results using traditional fixed-point sampling methods and was found to perform better. When environmental parameters can be used to predict particle size distributions, environmental managers have more options when characterizing concentrations, loads, and particle size distributions in urban runoff.

A high resolution hand-held focused beam profiler

NASA Astrophysics Data System (ADS)

Zapata-Farfan, J.; Garduño-Mejía, J.; Rosete-Aguilar, M.; Ascanio, G.; Román-Moreno, C. J.

2017-05-01

The shape of a beam is important in any laser application and depending on the final implementation, there exists a preferred one which is defined by the irradiance distribution.1 The energy distribution (or laser beam profile) is an important parameter in a focused beam, for instance, in laser cut industry, where the beam shape determines the quality of the cut. In terms of alignment and focusing, the energy distribution also plays an important role since the system must be configured in order to reduce the aberration effects and achieve the highest intensity. Nowadays a beam profiler is used in both industry and research laboratories with the aim to characterize laser beams used in free-space communications, focusing and welding, among other systems. The purpose of the profile analyzers is to know the main parameters of the beam, to control its characteristics as uniformity, shape and beam size as a guide to align the focusing system. In this work is presented a high resolution hand-held and compact design of a beam profiler capable to measure at the focal plane, with covered range from 400 nm to 1000 nm. The detection is reached with a CMOS sensor sized in 3673.6 μm x 2738.4 μm which acquire a snap shot of the previously attenuated focused beam to avoid the sensor damage, the result is an image of beam intensity distribution, which is digitally processed with a RaspberryTMmodule gathering significant parameters such as beam waist, centroid, uniformity and also some aberrations. The profiler resolution is 1.4 μm and was probed and validated in three different focusing systems. The spot sizes measurements were compared with the Foucault knife-edge test.

DAISY-DAMP: A distributed AI system for the dynamic allocation and management of power

NASA Technical Reports Server (NTRS)

Hall, Steven B.; Ohler, Peter C.

1988-01-01

One of the critical parameters that must be addressed when designing a loosely coupled Distributed AI SYstem (DAISY) has to do with the degree to which authority is centralized or decentralized. The decision to implement the Dynamic Allocation and Management of Power (DAMP) system as a network of cooperating agents mandated this study. The DAISY-DAMP problem is described; the component agents of the system are characterized; and the communication protocols system elucidated. The motivations and advantages in designing the system with authority decentralized is discussed. Progress in the area of Speech Act theory is proposed as playing a role in constructing decentralized systems.

Self-similar solutions to isothermal shock problems

NASA Astrophysics Data System (ADS)

Deschner, Stephan C.; Illenseer, Tobias F.; Duschl, Wolfgang J.

We investigate exact solutions for isothermal shock problems in different one-dimensional geometries. These solutions are given as analytical expressions if possible, or are computed using standard numerical methods for solving ordinary differential equations. We test the numerical solutions against the analytical expressions to verify the correctness of all numerical algorithms. We use similarity methods to derive a system of ordinary differential equations (ODE) yielding exact solutions for power law density distributions as initial conditions. Further, the system of ODEs accounts for implosion problems (IP) as well as explosion problems (EP) by changing the initial or boundary conditions, respectively. Taking genuinely isothermal approximations into account leads to additional insights of EPs in contrast to earlier models. We neglect a constant initial energy contribution but introduce a parameter to adjust the initial mass distribution of the system. Moreover, we show that due to this parameter a constant initial density is not allowed for isothermal EPs. Reasonable restrictions for this parameter are given. Both, the (genuinely) isothermal implosion as well as the explosion problem are solved for the first time.

Large-area photogrammetry based testing of wind turbine blades

NASA Astrophysics Data System (ADS)

Poozesh, Peyman; Baqersad, Javad; Niezrecki, Christopher; Avitabile, Peter; Harvey, Eric; Yarala, Rahul

2017-03-01

An optically based sensing system that can measure the displacement and strain over essentially the entire area of a utility-scale blade leads to a measurement system that can significantly reduce the time and cost associated with traditional instrumentation. This paper evaluates the performance of conventional three dimensional digital image correlation (3D DIC) and three dimensional point tracking (3DPT) approaches over the surface of wind turbine blades and proposes a multi-camera measurement system using dynamic spatial data stitching. The potential advantages for the proposed approach include: (1) full-field measurement distributed over a very large area, (2) the elimination of time-consuming wiring and expensive sensors, and (3) the need for large-channel data acquisition systems. There are several challenges associated with extending the capability of a standard 3D DIC system to measure entire surface of utility scale blades to extract distributed strain, deflection, and modal parameters. This paper only tries to address some of the difficulties including: (1) assessing the accuracy of the 3D DIC system to measure full-field distributed strain and displacement over the large area, (2) understanding the geometrical constraints associated with a wind turbine testing facility (e.g. lighting, working distance, and speckle pattern size), (3) evaluating the performance of the dynamic stitching method to combine two different fields of view by extracting modal parameters from aligned point clouds, and (4) determining the feasibility of employing an output-only system identification to estimate modal parameters of a utility scale wind turbine blade from optically measured data. Within the current work, the results of an optical measurement (one stereo-vision system) performed on a large area over a 50-m utility-scale blade subjected to quasi-static and cyclic loading are presented. The blade certification and testing is typically performed using International Electro-Technical Commission standard (IEC 61400-23). For static tests, the blade is pulled in either flap-wise or edge-wise directions to measure deflection or distributed strain at a few limited locations of a large-sized blade. Additionally, the paper explores the error associated with using a multi-camera system (two stereo-vision systems) in measuring 3D displacement and extracting structural dynamic parameters on a mock set up emulating a utility-scale wind turbine blade. The results obtained in this paper reveal that the multi-camera measurement system has the potential to identify the dynamic characteristics of a very large structure.

Some properties of a 5-parameter bivariate probability distribution

NASA Technical Reports Server (NTRS)

Tubbs, J. D.; Brewer, D. W.; Smith, O. E.

1983-01-01

A five-parameter bivariate gamma distribution having two shape parameters, two location parameters and a correlation parameter was developed. This more general bivariate gamma distribution reduces to the known four-parameter distribution. The five-parameter distribution gives a better fit to the gust data. The statistical properties of this general bivariate gamma distribution and a hypothesis test were investigated. Although these developments have come too late in the Shuttle program to be used directly as design criteria for ascent wind gust loads, the new wind gust model has helped to explain the wind profile conditions which cause large dynamic loads. Other potential applications of the newly developed five-parameter bivariate gamma distribution are in the areas of reliability theory, signal noise, and vibration mechanics.

Transuranic biokinetic parameters for marine invertebrates--a review.

PubMed

Ryan, T P

2002-04-01

A catalogue of biokinetic parameters for the transuranic elements plutonium, americium, curium, neptunium, and californium in marine invertebrates is presented. The parameters considered are: the seawater-animal concentration factor (CF); the sediment-animal concentration ratio (CR); transuranic assimilation efficiency; transuranic tissue distribution and transuranic elimination rates. With respect to the seawater-animal CF, authors differ considerably on how they define this parameter and a seven-point reporting system is suggested. Transuranic uptake from sediment by animals is characterised by low CRs. The assimilation efficiencies of transuranic elements in marine invertebrates are high compared to vertebrates and mammals in general and the distribution of transuranics within the body tissue of an animal is dependent on the uptake path. The elimination of transuranics from most species examined conformed to a standard biphasic exponential model though some examples with three elimination phases were identified.

A coupled classification - evolutionary optimization model for contamination event detection in water distribution systems.

PubMed

Oliker, Nurit; Ostfeld, Avi

2014-03-15

This study describes a decision support system, alerts for contamination events in water distribution systems. The developed model comprises a weighted support vector machine (SVM) for the detection of outliers, and a following sequence analysis for the classification of contamination events. The contribution of this study is an improvement of contamination events detection ability and a multi-dimensional analysis of the data, differing from the parallel one-dimensional analysis conducted so far. The multivariate analysis examines the relationships between water quality parameters and detects changes in their mutual patterns. The weights of the SVM model accomplish two goals: blurring the difference between sizes of the two classes' data sets (as there are much more normal/regular than event time measurements), and adhering the time factor attribute by a time decay coefficient, ascribing higher importance to recent observations when classifying a time step measurement. All model parameters were determined by data driven optimization so the calibration of the model was completely autonomic. The model was trained and tested on a real water distribution system (WDS) data set with randomly simulated events superimposed on the original measurements. The model is prominent in its ability to detect events that were only partly expressed in the data (i.e., affecting only some of the measured parameters). The model showed high accuracy and better detection ability as compared to previous modeling attempts of contamination event detection. Copyright © 2013 Elsevier Ltd. All rights reserved.

A Neural Network Aero Design System for Advanced Turbo-Engines

NASA Technical Reports Server (NTRS)

Sanz, Jose M.

1999-01-01

An inverse design method calculates the blade shape that produces a prescribed input pressure distribution. By controlling this input pressure distribution the aerodynamic design objectives can easily be met. Because of the intrinsic relationship between pressure distribution and airfoil physical properties, a Neural Network can be trained to choose the optimal pressure distribution that would meet a set of physical requirements. Neural network systems have been attempted in the context of direct design methods. From properties ascribed to a set of blades the neural network is trained to infer the properties of an 'interpolated' blade shape. The problem is that, especially in transonic regimes where we deal with intrinsically non linear and ill posed problems, small perturbations of the blade shape can produce very large variations of the flow parameters. It is very unlikely that, under these circumstances, a neural network will be able to find the proper solution. The unique situation in the present method is that the neural network can be trained to extract the required input pressure distribution from a database of pressure distributions while the inverse method will still compute the exact blade shape that corresponds to this 'interpolated' input pressure distribution. In other words, the interpolation process is transferred to a smoother problem, namely, finding what pressure distribution would produce the required flow conditions and, once this is done, the inverse method will compute the exact solution for this problem. The use of neural network is, in this context, highly related to the use of proper optimization techniques. The optimization is used essentially as an automation procedure to force the input pressure distributions to achieve the required aero and structural design parameters. A multilayered feed forward network with back-propagation is used to train the system for pattern association and classification.

Information sensitivity functions to assess parameter information gain and identifiability of dynamical systems.

PubMed

Pant, Sanjay

2018-05-01

A new class of functions, called the 'information sensitivity functions' (ISFs), which quantify the information gain about the parameters through the measurements/observables of a dynamical system are presented. These functions can be easily computed through classical sensitivity functions alone and are based on Bayesian and information-theoretic approaches. While marginal information gain is quantified by decrease in differential entropy, correlations between arbitrary sets of parameters are assessed through mutual information. For individual parameters, these information gains are also presented as marginal posterior variances, and, to assess the effect of correlations, as conditional variances when other parameters are given. The easy to interpret ISFs can be used to (a) identify time intervals or regions in dynamical system behaviour where information about the parameters is concentrated; (b) assess the effect of measurement noise on the information gain for the parameters; (c) assess whether sufficient information in an experimental protocol (input, measurements and their frequency) is available to identify the parameters; (d) assess correlation in the posterior distribution of the parameters to identify the sets of parameters that are likely to be indistinguishable; and (e) assess identifiability problems for particular sets of parameters. © 2018 The Authors.

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.

Dome diagnostics system of optical parameters and characteristics of LEDs

NASA Astrophysics Data System (ADS)

Peretyagin, Vladimir S.; Pavlenko, Nikita A.

2017-09-01

Scientific and technological progress of recent years in the production of the light emitting diodes (LEDs) has led to the expansion of areas of their application from the simplest systems to high precision lighting devices used in various fields of human activity. However, development and production (especially mass production) of LED lighting devices are impossible without a thorough analysis of its parameters and characteristics. There are many ways and devices for analysis the spatial, energy and colorimetric parameters of LEDs. The most methods are intended for definition only one parameter (for example, luminous flux) or one characteristic (for example, the angular distribution of energy or the spectral characteristics). Besides, devices used these methods are intended for measuring parameters in only one point or plane. This problem can be solved by using a dome diagnostics system of optical parameters and characteristics of LEDs, developed by specialists of the department OEDS chair of ITMO University in Russia. The paper presents the theoretical aspects of the analysis of LED's spatial (angular), energy and color parameters by using mentioned of diagnostics system. The article also presents the results of spatial), energy and color parameters measurements of some LEDs brands.

The roles of non-extensivity and dust concentration as bifurcation parameters in dust-ion acoustic traveling waves in magnetized dusty plasma

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

Narayan Ghosh, Uday; Kumar Mandal, Pankaj, E-mail: pankajwbmsd@gmail.com; Chatterjee, Prasanta

Dust ion-acoustic traveling waves are studied in a magnetized dusty plasma in presence of static dust and non-extensive distributed electrons in the framework of Zakharov-Kuznesstov-Burgers (ZKB) equation. System of coupled nonlinear ordinary differential equations is derived from ZKB equation, and equilibrium points are obtained. Nonlinear wave phenomena are studied numerically using fourth order Runge-Kutta method. The change from unstable to stable solution and consequently to asymptotic stable of dust ion acoustic traveling waves is studied through dynamical system approach. It is found that some dramatical features emerge when the non-extensive parameter and the dust concentration parameters are varied. Behavior ofmore » the solution of the system changes from unstable to stable and stable to asymptotic stable depending on the value of the non-extensive parameter. It is also observed that when the dust concentration is increased the solution pattern is changed from oscillatory shocks to periodic solution. Thus, non-extensive and dust concentration parameters play crucial roles in determining the nature of the stability behavior of the system. Thus, the non-extensive parameter and the dust concentration parameters can be treated as bifurcation parameters.« less

The Influence of Atmosphere Parameters on the Signal for Remote Sensing Polarimetric Electro-Optical Systems

NASA Astrophysics Data System (ADS)

Budak, Vladimir P.; Korkin, Sergey V.

2009-03-01

The singularity subtraction on the vectorial modification of spherical harmonics method (VMSH) of the solution of the vectorial radiative transfer equation boundary problem is applied to the problem of influence of atmosphere parameters on the polarimetric system signal. We assume in this model different phase matrices (Mie, Rayleigh, and Henyey-Greenstein), reflecting bottom and particle size distribution. The authors describe the main features of the model and some results of its implementation.

Surveillance of industrial processes with correlated parameters

DOEpatents

White, Andrew M.; Gross, Kenny C.; Kubic, William L.; Wigeland, Roald A.

1996-01-01

A system and method for surveillance of an industrial process. The system and method includes a plurality of sensors monitoring industrial process parameters, devices to convert the sensed data to computer compatible information and a computer which executes computer software directed to analyzing the sensor data to discern statistically reliable alarm conditions. The computer software is executed to remove serial correlation information and then calculate Mahalanobis distribution data to carry out a probability ratio test to determine alarm conditions.

Rigorous Results for the Distribution of Money on Connected Graphs

NASA Astrophysics Data System (ADS)

Lanchier, Nicolas; Reed, Stephanie

2018-05-01

This paper is concerned with general spatially explicit versions of three stochastic models for the dynamics of money that have been introduced and studied numerically by statistical physicists: the uniform reshuffling model, the immediate exchange model and the model with saving propensity. All three models consist of systems of economical agents that consecutively engage in pairwise monetary transactions. Computer simulations performed in the physics literature suggest that, when the number of agents and the average amount of money per agent are large, the limiting distribution of money as time goes to infinity approaches the exponential distribution for the first model, the gamma distribution with shape parameter two for the second model and a distribution similar but not exactly equal to a gamma distribution whose shape parameter depends on the saving propensity for the third model. The main objective of this paper is to give rigorous proofs of these conjectures and also extend these conjectures to generalizations of the first two models and a variant of the third model that include local rather than global interactions, i.e., instead of choosing the two interacting agents uniformly at random from the system, the agents are located on the vertex set of a general connected graph and can only interact with their neighbors.

Galerkin approximation for inverse problems for nonautonomous nonlinear distributed systems

NASA Technical Reports Server (NTRS)

Banks, H. T.; Reich, Simeon; Rosen, I. G.

1988-01-01

An abstract framework and convergence theory is developed for Galerkin approximation for inverse problems involving the identification of nonautonomous nonlinear distributed parameter systems. A set of relatively easily verified conditions is provided which are sufficient to guarantee the existence of optimal solutions and their approximation by a sequence of solutions to a sequence of approximating finite dimensional identification problems. The approach is based on the theory of monotone operators in Banach spaces and is applicable to a reasonably broad class of nonlinear distributed systems. Operator theoretic and variational techniques are used to establish a fundamental convergence result. An example involving evolution systems with dynamics described by nonstationary quasilinear elliptic operators along with some applications are presented and discussed.

a R-Shiny Based Phenology Analysis System and Case Study Using Digital Camera Dataset

NASA Astrophysics Data System (ADS)

Zhou, Y. K.

2018-05-01

Accurate extracting of the vegetation phenology information play an important role in exploring the effects of climate changes on vegetation. Repeated photos from digital camera is a useful and huge data source in phonological analysis. Data processing and mining on phenological data is still a big challenge. There is no single tool or a universal solution for big data processing and visualization in the field of phenology extraction. In this paper, we proposed a R-shiny based web application for vegetation phenological parameters extraction and analysis. Its main functions include phenological site distribution visualization, ROI (Region of Interest) selection, vegetation index calculation and visualization, data filtering, growth trajectory fitting, phenology parameters extraction, etc. the long-term observation photography data from Freemanwood site in 2013 is processed by this system as an example. The results show that: (1) this system is capable of analyzing large data using a distributed framework; (2) The combination of multiple parameter extraction and growth curve fitting methods could effectively extract the key phenology parameters. Moreover, there are discrepancies between different combination methods in unique study areas. Vegetation with single-growth peak is suitable for using the double logistic module to fit the growth trajectory, while vegetation with multi-growth peaks should better use spline method.

Temperature evolution of the local order parameter in relaxor ferroelectrics (1 - x)PMN-xPZT

NASA Astrophysics Data System (ADS)

Gridnev, S. A.; Glazunov, A. A.; Tsotsorin, A. N.

2005-09-01

The temperature dependence of the local order parameter and relaxation time distribution function have been determined in (1 - x)PMN-xPZT ceramic samples via dielectric permittivity. Above the Burns temperature, the permittivity was found to follow the Currie-Weiss law, and with temperature decreasing the deviation was observed to increase. A local order parameter was calculated from the dielectric data using a modified Landau-Devonshire approach. These results are compared to the distribution function of relaxation times. It was found that a glasslike freezing of reorientable polar clusters occurs in the temperature range of diffuse relaxor transition. The evolution of the studied system to more ordered state arises from the increased PZT content.

POTENTIAL OF BIOLOGICAL MONITORING SYSTEMS TO DETECT TOXICITY IN A FINISHED MATRIX

EPA Science Inventory

Distribution systems of the U.S. are vulnerable to natural and anthropogenic factors affecting quality for use as drinking water. Important factors include physical parameters such as increased turbidity, ecological cycles such as algal blooms, and episodic contamination events ...

Systematics of capture and fusion dynamics in heavy-ion collisions

NASA Astrophysics Data System (ADS)

Wang, Bing; Wen, Kai; Zhao, Wei-Juan; Zhao, En-Guang; Zhou, Shan-Gui

2017-03-01

We perform a systematic study of capture excitation functions by using an empirical coupled-channel (ECC) model. In this model, a barrier distribution is used to take effectively into account the effects of couplings between the relative motion and intrinsic degrees of freedom. The shape of the barrier distribution is of an asymmetric Gaussian form. The effect of neutron transfer channels is also included in the barrier distribution. Based on the interaction potential between the projectile and the target, empirical formulas are proposed to determine the parameters of the barrier distribution. Theoretical estimates for barrier distributions and calculated capture cross sections together with experimental cross sections of 220 reaction systems with 182 ⩽ZPZT ⩽ 1640 are tabulated. The results show that the ECC model together with the empirical formulas for parameters of the barrier distribution work quite well in the energy region around the Coulomb barrier. This ECC model can provide prediction of capture cross sections for the synthesis of superheavy nuclei as well as valuable information on capture and fusion dynamics.

Wigner distributions for an electron

NASA Astrophysics Data System (ADS)

Kumar, Narinder; Mondal, Chandan

2018-06-01

We study the Wigner distributions for a physical electron, which reveal the multidimensional images of the electron. The physical electron is considered as a composite system of a bare electron and photon. The Wigner distributions for unpolarized, longitudinally polarized and transversely polarized electron are presented in transverse momentum plane as well as in impact-parameter plane. The spin-spin correlations between the bare electron and the physical electron are discussed. We also evaluate all the leading twist generalized transverse momentum distributions (GTMDs) for electron.

Synchronization of distributed power grids with the external loading system

NASA Astrophysics Data System (ADS)

Wei, Duqu; Mei, Chuncao

2018-06-01

In this paper, the synchronization between spatially distributed power plants and their supported consumers is studied, where the case of Kuramoto-like model power grids connected to an external permanent magnet synchronous motor (PMSM) is taken as an example. We focus on the dependence of the synchronization on the coupling coefficient. To quantitatively study the synchronization degree, we introduce the order parameter and the frequency deviation to measure the synchronization of the coupled system. It is found that as the external coupling coefficient is increased, the distributed power grids and the loading system become more and more synchronized in space, and the complete synchronization appears at a particular value of external coupling coefficient. Our results may provide a useful tip for analyzing the synchronous ability of distributed power grids.

Frequency distributions from birth, death, and creation processes.

PubMed

Bartley, David L; Ogden, Trevor; Song, Ruiguang

2002-01-01

The time-dependent frequency distribution of groups of individuals versus group size was investigated within a continuum approximation, assuming a simplified individual growth, death and creation model. The analogy of the system to a physical fluid exhibiting both convection and diffusion was exploited in obtaining various solutions to the distribution equation. A general solution was approximated through the application of a Green's function. More specific exact solutions were also found to be useful. The solutions were continually checked against the continuum approximation through extensive simulation of the discrete system. Over limited ranges of group size, the frequency distributions were shown to closely exhibit a power-law dependence on group size, as found in many realizations of this type of system, ranging from colonies of mutated bacteria to the distribution of surnames in a given population. As an example, the modeled distributions were successfully fit to the distribution of surnames in several countries by adjusting the parameters specifying growth, death and creation rates.

Corrosion and scaling potential in drinking water distribution system of tabriz, northwestern iran.

PubMed

Taghipour, Hassan; Shakerkhatibi, Mohammad; Pourakbar, Mojtaba; Belvasi, Mehdi

2012-01-01

This paper discusses the corrosion and scaling potential of Tabriz drinking water distribution system in Northwest of Iran. Internal corrosion of piping is a serious problem in drinking water industry. Corrosive water can cause intrusion of heavy metals especially lead in to water, therefore effecting public health. The aim of this study was to determine corrosion and scaling potential in potable water distribution system of Tabriz during the spring and summer in 2011. This study was carried out using Langlier Saturation Index, Ryznar Stability Index, Puckorius Scaling Index, and Aggressiveness indices. Eighty samples were taken from all over the city within two seasons, spring, and summer. Related parameters including temperature, pH, total dissolved solids, calcium hardness, and total alkalinity in all samples were measured in laboratory according to standard method manual. For the statistical analysis of the results, SPSS software (version 11.5) was used The mean and standard deviation values of Langlier, Ryznar, Puckorius and Aggressiveness Indices were equal to -0.68 (±0.43), 8.43 (±0.55), 7.86 (±0.36) and 11.23 (±0.43), respectively. By survey of corrosion indices, it was found that Tabriz drinking water is corrosive. In order to corrosion control, it is suggested that laboratorial study with regard to the distribution system condition be carried out to adjust effective parameters such as pH.

Time evolution of pore system in lime - Pozzolana composites

NASA Astrophysics Data System (ADS)

Doleželová, Magdaléna; Čáchová, Monika; Scheinherrová, Lenka; Keppert, Martin

2017-11-01

The lime - pozzolana mortars and plasters are used in restoration works on building cultural heritage but these materials are also following the trend of energy - efficient solutions in civil engineering. Porosity and pore size distribution is one of crucial parameters influencing engineering properties of porous materials. The pore size distribution of lime based system is changing in time due to chemical processes occurring in the material. The present paper describes time evolution of pore system in lime - pozzolana composites; the obtained results are useful in prediction of performance of lime - pozzolana systems in building structures.

Scaling properties of a rice-pile model: inertia and friction effects.

PubMed

Khfifi, M; Loulidi, M

2008-11-01

We present a rice-pile cellular automaton model that includes inertial and friction effects. This model is studied in one dimension, where the updating of metastable sites is done according to a stochastic dynamics governed by a probabilistic toppling parameter p that depends on the accumulated energy of moving grains. We investigate the scaling properties of the model using finite-size scaling analysis. The avalanche size, the lifetime, and the residence time distributions exhibit a power-law behavior. Their corresponding critical exponents, respectively, tau, y, and yr, are not universal. They present continuous variation versus the parameters of the system. The maximal value of the critical exponent tau that our model gives is very close to the experimental one, tau=2.02 [Frette, Nature (London) 379, 49 (1996)], and the probability distribution of the residence time is in good agreement with the experimental results. We note that the critical behavior is observed only in a certain range of parameter values of the system which correspond to low inertia and high friction.

Impact of generalized Fourier's and Fick's laws on MHD 3D second grade nanofluid flow with variable thermal conductivity and convective heat and mass conditions

NASA Astrophysics Data System (ADS)

Ramzan, M.; Bilal, M.; Chung, Jae Dong; Lu, Dian Chen; Farooq, Umer

2017-09-01

A mathematical model has been established to study the magnetohydrodynamic second grade nanofluid flow past a bidirectional stretched surface. The flow is induced by Cattaneo-Christov thermal and concentration diffusion fluxes. Novel characteristics of Brownian motion and thermophoresis are accompanied by temperature dependent thermal conductivity and convective heat and mass boundary conditions. Apposite transformations are betrothed to transform a system of nonlinear partial differential equations to nonlinear ordinary differential equations. Analytic solutions of the obtained nonlinear system are obtained via a convergent method. Graphs are plotted to examine how velocity, temperature, and concentration distributions are affected by varied physical involved parameters. Effects of skin friction coefficients along the x- and y-direction versus various parameters are also shown through graphs and are well debated. Our findings show that velocities along both the x and y axes exhibit a decreasing trend for the Hartmann number. Moreover, temperature and concentration distributions are decreasing functions of thermal and concentration relaxation parameters.

A family of models for spherical stellar systems

NASA Technical Reports Server (NTRS)

Tremaine, Scott; Richstone, Douglas O.; Byun, Yong-Ik; Dressler, Alan; Faber, S. M.; Grillmair, Carl; Kormendy, John; Lauer, Tod R.

1994-01-01

We describe a one-parameter family of models of stable sperical stellar systems in which the phase-space distribution function depends only on energy. The models have similar density profiles in their outer parts (rho propotional to r(exp -4)) and central power-law density cusps, rho proportional to r(exp 3-eta), 0 less than eta less than or = 3. The family contains the Jaffe (1983) and Hernquist (1990) models as special cases. We evaluate the surface brightness profile, the line-of-sight velocity dispersion profile, and the distribution function, and discuss analogs of King's core-fitting formula for determining mass-to-light ratio. We also generalize the models to a two-parameter family, in which the galaxy contains a central black hole; the second parameter is the mass of the black hole. Our models can be used to estimate the detectability of central black holes and the velocity-dispersion profiles of galaxies that contain central cusps, with or without a central black hole.

Propagation of cylindrical ion acoustic waves in a plasma with q-nonextensive electrons with nonthermal distribution

NASA Astrophysics Data System (ADS)

El-Depsy, A.; Selim, M. M.

2016-12-01

The propagation of ion acoustic waves (IAWs) in a cylindrical collisionless unmagnetized plasma, containing ions and electrons is investigated. The electrons are considered to be nonextensive and follow nonthermal distribution. The reductive perturbation technique (RPT) is used to obtain a nonlinear cylindrical Kadomtsev-Petviashvili (CKP) evolution equation. This equation is solved analytically. The effects of plasma parameters on the IAWs characteristics are discussed in details. Both compressive and rarefactive solitons are found to be created in the proposed plasma system. The profile of IAWs is found to depend on the nonextensive and nonthermal parameters. The present study is useful for understanding IAWs in the regions where mixed electron distribution in space, or laboratory plasmas, exist.

A new approach to interpretation of heterogeneity of fluorescence decay in complex biological systems

NASA Astrophysics Data System (ADS)

Wlodarczyk, Jakub; Kierdaszuk, Borys

2005-08-01

Decays of tyrosine fluorescence in protein-ligand complexes are described by a model of continuous distribution of fluorescence lifetimes. Resulted analytical power-like decay function provides good fits to highly complex fluorescence kinetics. Moreover, this is a manifestation of so-called Tsallis q-exponential function, which is suitable for description of the systems with long-range interactions, memory effect, as well as with fluctuations of the characteristic lifetime of fluorescence. The proposed decay functions were applied to analysis of fluorescence decays of tyrosine in a protein, i.e. the enzyme purine nucleoside phosphorylase from E. coli (the product of the deoD gene), free in aqueous solution and in a complex with formycin A (an inhibitor) and orthophosphate (a co-substrate). The power-like function provides new information about enzyme-ligand complex formation based on the physically justified heterogeneity parameter directly related to the lifetime distribution. A measure of the heterogeneity parameter in the enzyme systems is provided by a variance of fluorescence lifetime distribution. The possible number of deactivation channels and excited state mean lifetime can be easily derived without a priori knowledge of the complexity of studied system. Moreover, proposed model is simpler then traditional multi-exponential one, and better describes heterogeneous nature of studied systems.

SU-E-T-459: Dosimetric Consequences of Rotated Elliptical Proton Spots in Modeling In-Air Proton Fluence for Calculating Doses in Water of Proton Pencil Beams

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

Matysiak, W; Yeung, D; Hsi, W

2014-06-01

Purpose: We present a study of dosimetric consequences on doses in water in modeling in-air proton fluence independently along principle axes for rotated elliptical spots. Methods: Phase-space parameters for modeling in-air fluence are the position sigma for the spatial distribution, the angle sigma for the angular distribution, and the correlation between position and angle distributions. Proton spots of the McLaren proton therapy system were measured at five locations near the isocenter for the energies of 180 MeV and 250 MeV. An elongated elliptical spot rotated with respect to the principle axes was observed for the 180 MeV, while a circular-likemore » spot was observed for the 250 MeV. In the first approach, the phase-space parameters were derived in the principle axes without rotation. In the second approach, the phase space parameters were derived in the reference frame with axes rotated to coincide with the major axes of the elliptical spot. Monte-Carlo simulations with derived phase-space parameters using both approaches to tally doses in water were performed and analyzed. Results: For the rotated elliptical 180 MeV spots, the position sigmas were 3.6 mm and 3.2 mm in principle axes, but were 4.3 mm and 2.0 mm when the reference frame was rotated. Measured spots fitted poorly the uncorrelated 2D Gaussian, but the quality of fit was significantly improved after the reference frame was rotated. As a Result, phase space parameters in the rotated frame were more appropriate for modeling in-air proton fluence of 180 MeV protons. Considerable differences were observed in Monte Carlo simulated dose distributions in water with phase-space parameters obtained with the two approaches. Conclusion: For rotated elliptical proton spots, phase-space parameters obtained in the rotated reference frame are better for modeling in-air proton fluence, and can be introduced into treatment planning systems.« less

Extended q -Gaussian and q -exponential distributions from gamma random variables

NASA Astrophysics Data System (ADS)

Budini, Adrián A.

2015-05-01

The family of q -Gaussian and q -exponential probability densities fit the statistical behavior of diverse complex self-similar nonequilibrium systems. These distributions, independently of the underlying dynamics, can rigorously be obtained by maximizing Tsallis "nonextensive" entropy under appropriate constraints, as well as from superstatistical models. In this paper we provide an alternative and complementary scheme for deriving these objects. We show that q -Gaussian and q -exponential random variables can always be expressed as a function of two statistically independent gamma random variables with the same scale parameter. Their shape index determines the complexity q parameter. This result also allows us to define an extended family of asymmetric q -Gaussian and modified q -exponential densities, which reduce to the standard ones when the shape parameters are the same. Furthermore, we demonstrate that a simple change of variables always allows relating any of these distributions with a beta stochastic variable. The extended distributions are applied in the statistical description of different complex dynamics such as log-return signals in financial markets and motion of point defects in a fluid flow.

A wideband channel model for land mobile satellite systems

NASA Technical Reports Server (NTRS)

Jahn, Axel; Buonomo, Sergio; Sforza, Mario; Lutz, Erich

1995-01-01

A wideband channel model for Land Mobile Satellite (LMS) services is presented which characterizes the time-varying transmission channel between a satellite and a mobile user terminal. The channel model statistic parameters are the results of fitting procedures to measured data. The data used for fitting have a time resolution of 33 ns corresponding to a bandwidth of 30 MHz. Thus, the model is capable to characterize the channel behaviour for a wide range of services e.g., voice transmission, digital audio broadcasting (DAB), and spread spectrum modulation schemes. The model is presented for different environments and scenarios. The model is derived for a quasi-mobile user with hand-held terminal being in two different environments: rural and urban. The parameters needed for the description are (a) the number of echoes, (b) the distribution of the echo power, and (c) the distribution of the echo delay. It is shown that the direct path follows a Rician distribution whereas the reflected paths are Rayleigh/lognormal distributed. The parameters are given for an elevation angle of 25 deg.

Orbit/attitude estimation with LANDSAT Landmark data

NASA Technical Reports Server (NTRS)

Hall, D. L.; Waligora, S.

1979-01-01

The use of LANDSAT landmark data for orbit/attitude and camera bias estimation was studied. The preliminary results of these investigations are presented. The Goddard Trajectory Determination System (GTDS) error analysis capability was used to perform error analysis studies. A number of questions were addressed including parameter observability and sensitivity, effects on the solve-for parameter errors of data span, density, and distribution an a priori covariance weighting. The use of the GTDS differential correction capability with acutal landmark data was examined. The rms line and element observation residuals were studied as a function of the solve-for parameter set, a priori covariance weighting, force model, attitude model and data characteristics. Sample results are presented. Finally, verfication and preliminary system evaluation of the LANDSAT NAVPAK system for sequential (extended Kalman Filter) estimation of orbit, and camera bias parameters is given.

Calculation of the Thermal Resistance of a Heat Distributer in the Cooling System of a Heat-Loaded Element

NASA Astrophysics Data System (ADS)

Vasil'ev, E. N.

2018-04-01

Numerical simulation is performed for heat transfer in a heat distributer of a thermoelectric cooling system, which is located between the heat-loaded element and the thermoelectric module, for matching their sizes and for heat flux equalization. The dependences of the characteristic values of temperature and thermal resistance of the copper and aluminum heat distributer on its thickness and on the size of the heatloaded element. Comparative analysis is carried out for determining the effect of the thermal conductivity of the material and geometrical parameters on the heat resistance. The optimal thickness of the heat distributer depending on the size of the heat-loaded element is determined.

Quadratic RK shooting solution for a environmental parameter prediction boundary value problem

NASA Astrophysics Data System (ADS)

Famelis, Ioannis Th.; Tsitouras, Ch.

2014-10-01

Using tools of Information Geometry, the minimum distance between two elements of a statistical manifold is defined by the corresponding geodesic, e.g. the minimum length curve that connects them. Such a curve, where the probability distribution functions in the case of our meteorological data are two parameter Weibull distributions, satisfies a 2nd order Boundary Value (BV) system. We study the numerical treatment of the resulting special quadratic form system using Shooting method. We compare the solutions of the problem when we employ a classical Singly Diagonally Implicit Runge Kutta (SDIRK) 4(3) pair of methods and a quadratic SDIRK 5(3) pair . Both pairs have the same computational costs whereas the second one attains higher order as it is specially constructed for quadratic problems.

A spatial domain decomposition approach to distributed H ∞ observer design of a linear unstable parabolic distributed parameter system with spatially discrete sensors

NASA Astrophysics Data System (ADS)

Wang, Jun-Wei; Liu, Ya-Qiang; Hu, Yan-Yan; Sun, Chang-Yin

2017-12-01

This paper discusses the design problem of distributed H∞ Luenberger-type partial differential equation (PDE) observer for state estimation of a linear unstable parabolic distributed parameter system (DPS) with external disturbance and measurement disturbance. Both pointwise measurement in space and local piecewise uniform measurement in space are considered; that is, sensors are only active at some specified points or applied at part thereof of the spatial domain. The spatial domain is decomposed into multiple subdomains according to the location of the sensors such that only one sensor is located at each subdomain. By using Lyapunov technique, Wirtinger's inequality at each subdomain, and integration by parts, a Lyapunov-based design of Luenberger-type PDE observer is developed such that the resulting estimation error system is exponentially stable with an H∞ performance constraint, and presented in terms of standard linear matrix inequalities (LMIs). For the case of local piecewise uniform measurement in space, the first mean value theorem for integrals is utilised in the observer design development. Moreover, the problem of optimal H∞ observer design is also addressed in the sense of minimising the attenuation level. Numerical simulation results are presented to show the satisfactory performance of the proposed design method.

CONSTRAINTS FROM ASYMMETRIC HEATING: INVESTIGATING THE EPSILON AURIGAE DISK

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

Pearson, Richard L. III; Stencel, Robert E., E-mail: richard.pearson@du.edu, E-mail: robert.stencel@du.edu

2015-01-01

Epsilon Aurigae is a long-period eclipsing binary that likely contains an F0Ia star and a circumstellar disk enshrouding a hidden companion, assumed to be a main-sequence B star. High uncertainty in its parallax has kept the evolutionary status of the system in question and, hence, the true nature of each component. This unknown, as well as the absence of solid state spectral features in the infrared, requires an investigation of a wide parameter space by means of both analytic and Monte Carlo radiative transfer (MCRT) methods. The first MCRT models of epsilon Aurigae that include all three system components aremore » presented here. We seek additional system parameter constraints by melding analytic approximations with MCRT outputs (e.g., dust temperatures) on a first-order level. The MCRT models investigate the effects of various parameters on the disk-edge temperatures; these include two distances, three particle size distributions, three compositions, and two disk masses, resulting in 36 independent models. Specifically, the MCRT temperatures permit analytic calculations of effective heating and cooling curves along the disk edge. These are used to calculate representative observed fluxes and corresponding temperatures. This novel application of thermal properties provides the basis for utilization of other binary systems containing disks. We find degeneracies in the model fits for the various parameter sets. However, the results show a preference for a carbon disk with particle size distributions ≥10 μm. Additionally, a linear correlation between the MCRT noon and basal temperatures serves as a tool for effectively eliminating portions of the parameter space.« less

Uncertainty Quantification and Global Sensitivity Analysis of Subsurface Flow Parameters to Gravimetric Variations During Pumping Tests in Unconfined Aquifers

NASA Astrophysics Data System (ADS)

Maina, Fadji Zaouna; Guadagnini, Alberto

2018-01-01

We study the contribution of typically uncertain subsurface flow parameters to gravity changes that can be recorded during pumping tests in unconfined aquifers. We do so in the framework of a Global Sensitivity Analysis and quantify the effects of uncertainty of such parameters on the first four statistical moments of the probability distribution of gravimetric variations induced by the operation of the well. System parameters are grouped into two main categories, respectively, governing groundwater flow in the unsaturated and saturated portions of the domain. We ground our work on the three-dimensional analytical model proposed by Mishra and Neuman (2011), which fully takes into account the richness of the physical process taking place across the unsaturated and saturated zones and storage effects in a finite radius pumping well. The relative influence of model parameter uncertainties on drawdown, moisture content, and gravity changes are quantified through (a) the Sobol' indices, derived from a classical decomposition of variance and (b) recently developed indices quantifying the relative contribution of each uncertain model parameter to the (ensemble) mean, skewness, and kurtosis of the model output. Our results document (i) the importance of the effects of the parameters governing the unsaturated flow dynamics on the mean and variance of local drawdown and gravity changes; (ii) the marked sensitivity (as expressed in terms of the statistical moments analyzed) of gravity changes to the employed water retention curve model parameter, specific yield, and storage, and (iii) the influential role of hydraulic conductivity of the unsaturated and saturated zones to the skewness and kurtosis of gravimetric variation distributions. The observed temporal dynamics of the strength of the relative contribution of system parameters to gravimetric variations suggest that gravity data have a clear potential to provide useful information for estimating the key hydraulic parameters of the system.

Cost-constrained optimal sampling for system identification in pharmacokinetics applications with population priors and nuisance parameters.

PubMed

Sorzano, Carlos Oscars S; Pérez-De-La-Cruz Moreno, Maria Angeles; Burguet-Castell, Jordi; Montejo, Consuelo; Ros, Antonio Aguilar

2015-06-01

Pharmacokinetics (PK) applications can be seen as a special case of nonlinear, causal systems with memory. There are cases in which prior knowledge exists about the distribution of the system parameters in a population. However, for a specific patient in a clinical setting, we need to determine her system parameters so that the therapy can be personalized. This system identification is performed many times by measuring drug concentrations in plasma. The objective of this work is to provide an irregular sampling strategy that minimizes the uncertainty about the system parameters with a fixed amount of samples (cost constrained). We use Monte Carlo simulations to estimate the average Fisher's information matrix associated to the PK problem, and then estimate the sampling points that minimize the maximum uncertainty associated to system parameters (a minimax criterion). The minimization is performed employing a genetic algorithm. We show that such a sampling scheme can be designed in a way that is adapted to a particular patient and that it can accommodate any dosing regimen as well as it allows flexible therapeutic strategies. © 2015 Wiley Periodicals, Inc. and the American Pharmacists Association.

Geophysical Parameter Estimation of Near Surface Materials Using Nuclear Magnetic Resonance

NASA Astrophysics Data System (ADS)

Keating, K.

2017-12-01

Proton nuclear magnetic resonance (NMR), a mature geophysical technology used in petroleum applications, has recently emerged as a promising tool for hydrogeophysicists. The NMR measurement, which can be made in the laboratory, in boreholes, and using a surface based instrument, are unique in that it is directly sensitive to water, via the initial signal magnitude, and thus provides a robust estimate of water content. In the petroleum industry rock physics models have been established that relate NMR relaxation times to pore size distributions and permeability. These models are often applied directly for hydrogeophysical applications, despite differences in the material in these two environments (e.g., unconsolidated versus consolidated, and mineral content). Furthermore, the rock physics models linking NMR relaxation times to pore size distributions do not account for partially saturated systems that are important for understanding flow in the vadose zone. In our research, we are developing and refining quantitative rock physics models that relate NMR parameters to hydrogeological parameters. Here we highlight the limitations of directly applying established rock physics models to estimate hydrogeological parameters from NMR measurements, and show some of the successes we have had in model improvement. Using examples drawn from both laboratory and field measurements, we focus on the use of NMR in partial saturated systems to estimate water content, pore-size distributions, and the water retention curve. Despite the challenges in interpreting the measurements, valuable information about hydrogeological parameters can be obtained from NMR relaxation data, and we conclude by outlining pathways for improving the interpretation of NMR data for hydrogeophysical investigations.

Surveillance of industrial processes with correlated parameters

DOEpatents

White, A.M.; Gross, K.C.; Kubic, W.L.; Wigeland, R.A.

1996-12-17

A system and method for surveillance of an industrial process are disclosed. The system and method includes a plurality of sensors monitoring industrial process parameters, devices to convert the sensed data to computer compatible information and a computer which executes computer software directed to analyzing the sensor data to discern statistically reliable alarm conditions. The computer software is executed to remove serial correlation information and then calculate Mahalanobis distribution data to carry out a probability ratio test to determine alarm conditions. 10 figs.

Estimation of kinematic parameters in CALIFA galaxies: no-assumption on internal dynamics

NASA Astrophysics Data System (ADS)

García-Lorenzo, B.; Barrera-Ballesteros, J.; CALIFA Team

2016-06-01

We propose a simple approach to homogeneously estimate kinematic parameters of a broad variety of galaxies (elliptical, spirals, irregulars or interacting systems). This methodology avoids the use of any kinematical model or any assumption on internal dynamics. This simple but novel approach allows us to determine: the frequency of kinematic distortions, systemic velocity, kinematic center, and kinematic position angles which are directly measured from the two dimensional-distributions of radial velocities. We test our analysis tools using the CALIFA Survey

Parameter estimation of multivariate multiple regression model using bayesian with non-informative Jeffreys’ prior distribution

NASA Astrophysics Data System (ADS)

Saputro, D. R. S.; Amalia, F.; Widyaningsih, P.; Affan, R. C.

2018-05-01

Bayesian method is a method that can be used to estimate the parameters of multivariate multiple regression model. Bayesian method has two distributions, there are prior and posterior distributions. Posterior distribution is influenced by the selection of prior distribution. Jeffreys’ prior distribution is a kind of Non-informative prior distribution. This prior is used when the information about parameter not available. Non-informative Jeffreys’ prior distribution is combined with the sample information resulting the posterior distribution. Posterior distribution is used to estimate the parameter. The purposes of this research is to estimate the parameters of multivariate regression model using Bayesian method with Non-informative Jeffreys’ prior distribution. Based on the results and discussion, parameter estimation of β and Σ which were obtained from expected value of random variable of marginal posterior distribution function. The marginal posterior distributions for β and Σ are multivariate normal and inverse Wishart. However, in calculation of the expected value involving integral of a function which difficult to determine the value. Therefore, approach is needed by generating of random samples according to the posterior distribution characteristics of each parameter using Markov chain Monte Carlo (MCMC) Gibbs sampling algorithm.

Compression and release dynamics of an active matter system of Euglena gracilis

NASA Astrophysics Data System (ADS)

Lam, Amy; Tsang, Alan C. H.; Ouellette, Nicholas; Riedel-Kruse, Ingmar

Active matter, defined as ensembles of self-propelled particles, encompasses a large variety of systems at all scales, from nanoparticles to bird flocks. Though various models and simulations have been created to describe the dynamics of these systems, experimental verification has been difficult to obtain. This is frequently due to the complex interaction rules which govern the particle behavior, in turn making systematic varying of parameters impossible. Here, we propose a model for predicting the system evolution of compression and release of an active system based on experiments and simulations. In particular, we consider ensembles of the unicellular, photo-responsive algae, Euglena gracilis, under light stimulation. By varying the spatiotemporal light patterns, we are able to finely adjust cell densities and achieve arbitrary non-homogeneous distributions, including compression into high-density aggregates of varying geometries. We observe the formation of depletion zones after the release of the confining stimulus and investigate the effects of the density distribution and particle rotational noise on the depletion. These results provide implications for defining state parameters which determine system evolution.

Anticipating the Chaotic Behaviour of Industrial Systems Based on Stochastic, Event-Driven Simulations

NASA Astrophysics Data System (ADS)

Bruzzone, Agostino G.; Revetria, Roberto; Simeoni, Simone; Viazzo, Simone; Orsoni, Alessandra

2004-08-01

In logistics and industrial production managers must deal with the impact of stochastic events to improve performances and reduce costs. In fact, production and logistics systems are generally designed considering some parameters as deterministically distributed. While this assumption is mostly used for preliminary prototyping, it is sometimes also retained during the final design stage, and especially for estimated parameters (i.e. Market Request). The proposed methodology can determine the impact of stochastic events in the system by evaluating the chaotic threshold level. Such an approach, based on the application of a new and innovative methodology, can be implemented to find the condition under which chaos makes the system become uncontrollable. Starting from problem identification and risk assessment, several classification techniques are used to carry out an effect analysis and contingency plan estimation. In this paper the authors illustrate the methodology with respect to a real industrial case: a production problem related to the logistics of distributed chemical processing.

Macroscopically constrained Wang-Landau method for systems with multiple order parameters and its application to drawing complex phase diagrams

NASA Astrophysics Data System (ADS)

Chan, C. H.; Brown, G.; Rikvold, P. A.

2017-05-01

A generalized approach to Wang-Landau simulations, macroscopically constrained Wang-Landau, is proposed to simulate the density of states of a system with multiple macroscopic order parameters. The method breaks a multidimensional random-walk process in phase space into many separate, one-dimensional random-walk processes in well-defined subspaces. Each of these random walks is constrained to a different set of values of the macroscopic order parameters. When the multivariable density of states is obtained for one set of values of fieldlike model parameters, the density of states for any other values of these parameters can be obtained by a simple transformation of the total system energy. All thermodynamic quantities of the system can then be rapidly calculated at any point in the phase diagram. We demonstrate how to use the multivariable density of states to draw the phase diagram, as well as order-parameter probability distributions at specific phase points, for a model spin-crossover material: an antiferromagnetic Ising model with ferromagnetic long-range interactions. The fieldlike parameters in this model are an effective magnetic field and the strength of the long-range interaction.

Computer-Controlled System for Plasma Ion Energy Auto-Analyzer

NASA Astrophysics Data System (ADS)

Wu, Xian-qiu; Chen, Jun-fang; Jiang, Zhen-mei; Zhong, Qing-hua; Xiong, Yu-ying; Wu, Kai-hua

2003-02-01

A computer-controlled system for plasma ion energy auto-analyzer was technically studied for rapid and online measurement of plasma ion energy distribution. The system intelligently controls all the equipments via a RS-232 port, a printer port and a home-built circuit. The software designed by Lab VIEW G language automatically fulfils all of the tasks such as system initializing, adjustment of scanning-voltage, measurement of weak-current, data processing, graphic export, etc. By using the system, a few minutes are taken to acquire the whole ion energy distribution, which rapidly provides important parameters of plasma process techniques based on semiconductor devices and microelectronics.

Reliability Implications in Wood Systems of a Bivariate Gaussian-Weibull Distribution and the Associated Univariate Pseudo-truncated Weibull

Treesearch

Steve P. Verrill; James W. Evans; David E. Kretschmann; Cherilyn A. Hatfield

2014-01-01

Two important wood properties are the modulus of elasticity (MOE) and the modulus of rupture (MOR). In the past, the statistical distribution of the MOE has often been modeled as Gaussian, and that of the MOR as lognormal or as a two- or three-parameter Weibull distribution. It is well known that MOE and MOR are positively correlated. To model the simultaneous behavior...

Nested Sampling for Bayesian Model Comparison in the Context of Salmonella Disease Dynamics

PubMed Central

Dybowski, Richard; McKinley, Trevelyan J.; Mastroeni, Pietro; Restif, Olivier

2013-01-01

Understanding the mechanisms underlying the observed dynamics of complex biological systems requires the statistical assessment and comparison of multiple alternative models. Although this has traditionally been done using maximum likelihood-based methods such as Akaike's Information Criterion (AIC), Bayesian methods have gained in popularity because they provide more informative output in the form of posterior probability distributions. However, comparison between multiple models in a Bayesian framework is made difficult by the computational cost of numerical integration over large parameter spaces. A new, efficient method for the computation of posterior probabilities has recently been proposed and applied to complex problems from the physical sciences. Here we demonstrate how nested sampling can be used for inference and model comparison in biological sciences. We present a reanalysis of data from experimental infection of mice with Salmonella enterica showing the distribution of bacteria in liver cells. In addition to confirming the main finding of the original analysis, which relied on AIC, our approach provides: (a) integration across the parameter space, (b) estimation of the posterior parameter distributions (with visualisations of parameter correlations), and (c) estimation of the posterior predictive distributions for goodness-of-fit assessments of the models. The goodness-of-fit results suggest that alternative mechanistic models and a relaxation of the quasi-stationary assumption should be considered. PMID:24376528

Measuring Dark Matter With MilkyWay@home

NASA Astrophysics Data System (ADS)

Shelton, Siddhartha; Newberg, Heidi Jo; Arsenault, Matthew; Bauer, Jacob; Desell, Travis; Judd, Roland; Magdon-Ismail, Malik; Newby, Matthew; Rice, Colin; Thompson, Jeffrey; Ulin, Steve; Weiss, Jake; Widrow, Larry

2016-01-01

We perform N-body simulations of two component dwarf galaxies (dark matter and stars follow separate distributions) falling into the Milky Way and the forming of tidal streams. Using MilkyWay@home we optimize the parameters of the progenitor dwarf galaxy and the orbital time to fit the simulated distribution of stars along the tidal stream to the observed distribution of stars. Our initial dwarf galaxy models are constructed with two separate Plummer profiles (one for the dark matter and one for the baryonic matter), sampled using a generalized distribution function for spherically symmetric systems. We perform rigorous testing to ensure that our simulated galaxies are in virial equilibrium, and stable over a simulation time. The N-body simulations are performed using a Barnes-Hut Tree algorithm. Optimization traverses the likelihood surface from our six model parameters using particle swarm and differential evolution methods. We have generated simulated data with known model parameters that are similar to those of the Orphan Stream. We show that we are able to recover a majority of our model parameters, and most importantly the mass-to-light ratio of the now disrupted progenitor galaxy, using MilkyWay@home. This research is supported by generous gifts from the Marvin Clan, Babette Josephs, Manit Limlamai, and the MilkyWay@home volunteers.

Structural stocking guides: a new look at an old friend

Treesearch

Jeffrey H. Gove

2004-01-01

A parameter recovery-based model is developed that allows the incorporation of diameter distribution information directly into stocking guides. The method is completely general in applicability across different guides and forest types and could be adapted to other systems such as density management diagrams. It relies on a simple measure of diameter distribution shape...

Substantiation of the Parameters of the Central Distributor for Mineral Fertilizers

ERIC Educational Resources Information Center

Nukeshev, Sayakhat O.; Eskhozhin, Kairat D.; Tokushev, Masgut H.; Zhazykbayeva, Zhazira M.

2016-01-01

The main problem of distribution systems with a centralized metering seed actions of pneumatic planters is deficient feed-rate consistency of seeds in supply coulters. Thus, the purpose of the study is to develop the optimal ways of decreasing the irregular distribution of the seeds and mineral fertilizers in the coulters. In order to achieve this…

A superstatistical model of metastasis and cancer survival

NASA Astrophysics Data System (ADS)

Leon Chen, L.; Beck, Christian

2008-05-01

We introduce a superstatistical model for the progression statistics of malignant cancer cells. The metastatic cascade is modeled as a complex nonequilibrium system with several macroscopic pathways and inverse-chi-square distributed parameters of the underlying Poisson processes. The predictions of the model are in excellent agreement with observed survival-time probability distributions of breast cancer patients.

Modelling Parameters Characterizing Selected Water Supply Systems in Lower Silesia Province

NASA Astrophysics Data System (ADS)

Nowogoński, Ireneusz; Ogiołda, Ewa

2017-12-01

The work presents issues of modelling water supply systems in the context of basic parameters characterizing their operation. In addition to typical parameters, such as water pressure and flow rate, assessing the age of the water is important, as a parameter of assessing the quality of the distributed medium. The analysis was based on two facilities, including one with a diverse spectrum of consumers, including residential housing and industry. The carried out simulations indicate the possibility of the occurrence of water quality degradation as a result of excessively long periods of storage in the water supply network. Also important is the influence of the irregularity of water use, especially in the case of supplying various kinds of consumers (in the analysed case - mining companies).

Algorithms and Results of Eye Tissues Differentiation Based on RF Ultrasound

PubMed Central

Jurkonis, R.; Janušauskas, A.; Marozas, V.; Jegelevičius, D.; Daukantas, S.; Patašius, M.; Paunksnis, A.; Lukoševičius, A.

2012-01-01

Algorithms and software were developed for analysis of B-scan ultrasonic signals acquired from commercial diagnostic ultrasound system. The algorithms process raw ultrasonic signals in backscattered spectrum domain, which is obtained using two time-frequency methods: short-time Fourier and Hilbert-Huang transformations. The signals from selected regions of eye tissues are characterized by parameters: B-scan envelope amplitude, approximated spectral slope, approximated spectral intercept, mean instantaneous frequency, mean instantaneous bandwidth, and parameters of Nakagami distribution characterizing Hilbert-Huang transformation output. The backscattered ultrasound signal parameters characterizing intraocular and orbit tissues were processed by decision tree data mining algorithm. The pilot trial proved that applied methods are able to correctly classify signals from corpus vitreum blood, extraocular muscle, and orbit tissues. In 26 cases of ocular tissues classification, one error occurred, when tissues were classified into classes of corpus vitreum blood, extraocular muscle, and orbit tissue. In this pilot classification parameters of spectral intercept and Nakagami parameter for instantaneous frequencies distribution of the 1st intrinsic mode function were found specific for corpus vitreum blood, orbit and extraocular muscle tissues. We conclude that ultrasound data should be further collected in clinical database to establish background for decision support system for ocular tissue noninvasive differentiation. PMID:22654643

Life and Death Near Zero: The distribution and evolution of NEA orbits of near-zero MOID, (e, i), and q

NASA Astrophysics Data System (ADS)

Harris, Alan W.; Morbidelli, Alessandro; Granvik, Mikael

2016-10-01

Modeling the distribution of orbits with near-zero orbital parameters requires special attention to the dimensionality of the parameters in question. This is even more true since orbits of near-zero MOID, (e, i), or q are especially interesting as sources or sinks of NEAs. An essentially zero value of MOID (Minimum Orbital Intersection Distance) with respect to the Earth's orbit is a requirement for an impact trajectory, and initially also for ejecta from lunar impacts into heliocentric orbits. The collision cross section of the Earth goes up greatly with decreasing relative encounter velocity, venc, thus the impact flux onto the Earth is enhanced in such low-venc objects, which correspond to near-zero (e,i) orbits. And lunar ejecta that escapes from the Earth-moon system mostly does so at only barely greater than minimum velocity for escape (Gladman, et al., 1995, Icarus 118, 302-321), so the Earth-moon system is both a source and a sink of such low-venc orbits, and understanding the evolution of these populations requires accurately modeling the orbit distributions. Lastly, orbits of very low heliocentric perihelion distance, q, are particularly interesting as a "sink" in the NEA population as asteroids "fall into the sun" (Farinella, et al., 1994, Nature 371, 314-317). Understanding this process, and especially the role of disintegration of small asteroids as they evolve into low-q orbits (Granvik et al., 2016, Nature 530, 303-306), requires accurate modeling of the q distribution that would exist in the absence of a "sink" in the distribution. In this paper, we derive analytical expressions for the expected steady-state distributions near zero of MOID, (e,i), and q in the absence of sources or sinks, compare those to numerical simulations of orbit distributions, and lastly evaluate the distributions of discovered NEAs to try to understand the sources and sinks of NEAs "near zero" of these orbital parameters.

Multi-Parameter Scattering Sensor and Methods

NASA Technical Reports Server (NTRS)

Greenberg, Paul S. (Inventor); Fischer, David G. (Inventor)

2016-01-01

Methods, detectors and systems detect particles and/or measure particle properties. According to one embodiment, a detector for detecting particles comprises: a sensor for receiving radiation scattered by an ensemble of particles; and a processor for determining a physical parameter for the detector, or an optimal detection angle or a bound for an optimal detection angle, for measuring at least one moment or integrated moment of the ensemble of particles, the physical parameter, or detection angle, or detection angle bound being determined based on one or more of properties (a) and/or (b) and/or (c) and/or (d) or ranges for one or more of properties (a) and/or (b) and/or (c) and/or (d), wherein (a)-(d) are the following: (a) is a wavelength of light incident on the particles, (b) is a count median diameter or other characteristic size parameter of the particle size distribution, (c) is a standard deviation or other characteristic width parameter of the particle size distribution, and (d) is a refractive index of particles.

The Effect of Stiffness Parameter on Mass Distribution in Heavy-Ion Induced Fission

NASA Astrophysics Data System (ADS)

Soheyli, Saeed; Khalil Khalili, Morteza; Ashrafi, Ghazaaleh

2018-06-01

The stiffness parameter of the composite system has been studied for several heavy-ion induced fission reactions without the contribution of non-compound nucleus fission events. In this research, determination of the stiffness parameter is based on the comparison between the experimental data on the mass widths of fission fragments and those predicted by the statistical model treatments at the saddle and scission points. Analysis of the results shows that for the induced fission reactions of different targets by the same projectile, the stiffness parameter of the composite system decreases with increasing the fissility parameter, as well as with increasing the mass number of the compound nucleus. This parameter also exhibits a similar behavior for the reactions of a given target induced by different projectiles. As expected, nearly same stiffness values are obtained for different reactions leading to the same compound nucleus.

Boiling histotripsy lesion characterization on a clinical magnetic resonance imaging-guided high intensity focused ultrasound system

PubMed Central

Eranki, Avinash; Farr, Navid; Partanen, Ari; V. Sharma, Karun; Chen, Hong; Rossi, Christopher T.; Kothapalli, Satya V. V. N.; Oetgen, Matthew; Kim, AeRang; H. Negussie, Ayele; Woods, David; J. Wood, Bradford; C. W. Kim, Peter; S. Yarmolenko, Pavel

2017-01-01

Purpose High intensity focused ultrasound (HIFU) is a non-invasive therapeutic technique that can thermally ablate tumors. Boiling histotripsy (BH) is a HIFU approach that can emulsify tissue in a few milliseconds. Lesion volume and temperature effects for different BH sonication parameters are currently not well characterized. In this work, lesion volume, temperature distribution, and area of lethal thermal dose were characterized for varying BH sonication parameters in tissue-mimicking phantoms (TMP) and demonstrated in ex vivo tissues. Methods The following BH sonication parameters were varied using a clinical MR-HIFU system (Sonalleve V2, Philips, Vantaa, Finland): acoustic power, number of cycles/pulse, total sonication time, and pulse repetition frequency (PRF). A 3×3×3 pattern was sonicated inside TMP’s and ex vivo tissues. Post sonication, lesion volumes were quantified using 3D ultrasonography and temperature and thermal dose distributions were analyzed offline. Ex vivo tissues were sectioned and stained with H&E post sonication to assess tissue damage. Results Significant increase in lesion volume was observed while increasing the number of cycles/pulse and PRF. Other sonication parameters had no significant effect on lesion volume. Temperature full width at half maximum at the end of sonication increased significantly with all parameters except total sonication time. Positive correlation was also found between lethal thermal dose and lesion volume for all parameters except number of cycles/pulse. Gross pathology of ex vivo tissues post sonication displayed either completely or partially damaged tissue at the focal region. Surrounding tissues presented sharp boundaries, with little or no structural damage to adjacent critical structures such as bile duct and nerves. Conclusion Our characterization of effects of HIFU sonication parameters on the resulting lesion demonstrates the ability to control lesion morphologic and thermal characteristics with a clinical MR-HIFU system in TMP’s and ex vivo tissues. We demonstrate that this system can produce spatially precise lesions in both phantoms and ex vivo tissues. The results provide guidance on a preliminary set of BH sonication parameters for this system, with a potential to facilitate BH translation to the clinic. PMID:28301597

Parameter estimation problems for distributed systems using a multigrid method

NASA Technical Reports Server (NTRS)

Ta'asan, Shlomo; Dutt, Pravir

1990-01-01

The problem of estimating spatially varying coefficients of partial differential equations is considered from observation of the solution and of the right hand side of the equation. It is assumed that the observations are distributed in the domain and that enough observations are given. A method of discretization and an efficient multigrid method for solving the resulting discrete systems are described. Numerical results are presented for estimation of coefficients in an elliptic and a parabolic partial differential equation.

Coherent attacking continuous-variable quantum key distribution with entanglement in the middle

NASA Astrophysics Data System (ADS)

Zhang, Zhaoyuan; Shi, Ronghua; Zeng, Guihua; Guo, Ying

2018-06-01

We suggest an approach on the coherent attack of continuous-variable quantum key distribution (CVQKD) with an untrusted entangled source in the middle. The coherent attack strategy can be performed on the double links of quantum system, enabling the eavesdropper to steal more information from the proposed scheme using the entanglement correlation. Numeric simulation results show the improved performance of the attacked CVQKD system in terms of the derived secret key rate with the controllable parameters maximizing the stolen information.

Distribution of thermal neutrons in a temperature gradient

NASA Astrophysics Data System (ADS)

Molinari, V. G.; Pollachini, L.

A method to determine the spatial distribution of the thermal spectrum of neutrons in heterogeneous systems is presented. The method is based on diffusion concepts and has a simple mathematical structure which increases computing efficiency. The application of this theory to the neutron thermal diffusion induced by a temperature gradient, as found in nuclear reactors, is described. After introducing approximations, a nonlinear equation system representing the neutron temperature is given. Values of the equation parameters and its dependence on geometrical factors and media characteristics are discussed.

Parameter optimization of a hydrologic model in a snow-dominated basin using a modular Python framework

NASA Astrophysics Data System (ADS)

Volk, J. M.; Turner, M. A.; Huntington, J. L.; Gardner, M.; Tyler, S.; Sheneman, L.

2016-12-01

Many distributed models that simulate watershed hydrologic processes require a collection of multi-dimensional parameters as input, some of which need to be calibrated before the model can be applied. The Precipitation Runoff Modeling System (PRMS) is a physically-based and spatially distributed hydrologic model that contains a considerable number of parameters that often need to be calibrated. Modelers can also benefit from uncertainty analysis of these parameters. To meet these needs, we developed a modular framework in Python to conduct PRMS parameter optimization, uncertainty analysis, interactive visual inspection of parameters and outputs, and other common modeling tasks. Here we present results for multi-step calibration of sensitive parameters controlling solar radiation, potential evapo-transpiration, and streamflow in a PRMS model that we applied to the snow-dominated Dry Creek watershed in Idaho. We also demonstrate how our modular approach enables the user to use a variety of parameter optimization and uncertainty methods or easily define their own, such as Monte Carlo random sampling, uniform sampling, or even optimization methods such as the downhill simplex method or its commonly used, more robust counterpart, shuffled complex evolution.

Transponder-aided joint calibration and synchronization compensation for distributed radar systems.

PubMed

Wang, Wen-Qin

2015-01-01

High-precision radiometric calibration and synchronization compensation must be provided for distributed radar system due to separate transmitters and receivers. This paper proposes a transponder-aided joint radiometric calibration, motion compensation and synchronization for distributed radar remote sensing. As the transponder signal can be separated from the normal radar returns, it is used to calibrate the distributed radar for radiometry. Meanwhile, the distributed radar motion compensation and synchronization compensation algorithms are presented by utilizing the transponder signals. This method requires no hardware modifications to both the normal radar transmitter and receiver and no change to the operating pulse repetition frequency (PRF). The distributed radar radiometric calibration and synchronization compensation require only one transponder, but the motion compensation requires six transponders because there are six independent variables in the distributed radar geometry. Furthermore, a maximum likelihood method is used to estimate the transponder signal parameters. The proposed methods are verified by simulation results.

Multi-parameter monitoring of electrical machines using integrated fibre Bragg gratings

NASA Astrophysics Data System (ADS)

Fabian, Matthias; Hind, David; Gerada, Chris; Sun, Tong; Grattan, Kenneth T. V.

2017-04-01

In this paper a sensor system for multi-parameter electrical machine condition monitoring is reported. The proposed FBG-based system allows for the simultaneous monitoring of machine vibration, rotor speed and position, torque, spinning direction, temperature distribution along the stator windings and on the rotor surface as well as the stator wave frequency. This all-optical sensing solution reduces the component count of conventional sensor systems, i.e., all 48 sensing elements are contained within the machine operated by a single sensing interrogation unit. In this work, the sensing system has been successfully integrated into and tested on a permanent magnet motor prototype.

Origins and properties of kappa distributions in space plasmas

NASA Astrophysics Data System (ADS)

Livadiotis, George

2016-07-01

Classical particle systems reside at thermal equilibrium with their velocity distribution function stabilized into a Maxwell distribution. On the contrary, collisionless and correlated particle systems, such as the space and astrophysical plasmas, are characterized by a non-Maxwellian behavior, typically described by the so-called kappa distributions. Empirical kappa distributions have become increasingly widespread across space and plasma physics. However, a breakthrough in the field came with the connection of kappa distributions to the solid statistical framework of Tsallis non-extensive statistical mechanics. Understanding the statistical origin of kappa distributions was the cornerstone of further theoretical developments and applications, some of which will be presented in this talk: (i) The physical meaning of thermal parameters, e.g., temperature and kappa index; (ii) the multi-particle description of kappa distributions; (iii) the phase-space kappa distribution of a Hamiltonian with non-zero potential; (iv) the Sackur-Tetrode entropy for kappa distributions, and (v) the new quantization constant, h _{*}˜10 ^{-22} Js.

Performance of device-independent quantum key distribution

NASA Astrophysics Data System (ADS)

Cao, Zhu; Zhao, Qi; Ma, Xiongfeng

2016-07-01

Quantum key distribution provides information-theoretically-secure communication. In practice, device imperfections may jeopardise the system security. Device-independent quantum key distribution solves this problem by providing secure keys even when the quantum devices are untrusted and uncharacterized. Following a recent security proof of the device-independent quantum key distribution, we improve the key rate by tightening the parameter choice in the security proof. In practice where the system is lossy, we further improve the key rate by taking into account the loss position information. From our numerical simulation, our method can outperform existing results. Meanwhile, we outline clear experimental requirements for implementing device-independent quantum key distribution. The maximal tolerable error rate is 1.6%, the minimal required transmittance is 97.3%, and the minimal required visibility is 96.8 % .

Temporal rainfall estimation using input data reduction and model inversion

NASA Astrophysics Data System (ADS)

Wright, A. J.; Vrugt, J. A.; Walker, J. P.; Pauwels, V. R. N.

2016-12-01

Floods are devastating natural hazards. To provide accurate, precise and timely flood forecasts there is a need to understand the uncertainties associated with temporal rainfall and model parameters. The estimation of temporal rainfall and model parameter distributions from streamflow observations in complex dynamic catchments adds skill to current areal rainfall estimation methods, allows for the uncertainty of rainfall input to be considered when estimating model parameters and provides the ability to estimate rainfall from poorly gauged catchments. Current methods to estimate temporal rainfall distributions from streamflow are unable to adequately explain and invert complex non-linear hydrologic systems. This study uses the Discrete Wavelet Transform (DWT) to reduce rainfall dimensionality for the catchment of Warwick, Queensland, Australia. The reduction of rainfall to DWT coefficients allows the input rainfall time series to be simultaneously estimated along with model parameters. The estimation process is conducted using multi-chain Markov chain Monte Carlo simulation with the DREAMZS algorithm. The use of a likelihood function that considers both rainfall and streamflow error allows for model parameter and temporal rainfall distributions to be estimated. Estimation of the wavelet approximation coefficients of lower order decomposition structures was able to estimate the most realistic temporal rainfall distributions. These rainfall estimates were all able to simulate streamflow that was superior to the results of a traditional calibration approach. It is shown that the choice of wavelet has a considerable impact on the robustness of the inversion. The results demonstrate that streamflow data contains sufficient information to estimate temporal rainfall and model parameter distributions. The extent and variance of rainfall time series that are able to simulate streamflow that is superior to that simulated by a traditional calibration approach is a demonstration of equifinality. The use of a likelihood function that considers both rainfall and streamflow error combined with the use of the DWT as a model data reduction technique allows the joint inference of hydrologic model parameters along with rainfall.

Evaluation of the Performance of the Distributed Phased-MIMO Sonar.

PubMed

Pan, Xiang; Jiang, Jingning; Wang, Nan

2017-01-11

A broadband signal model is proposed for a distributed multiple-input multiple-output (MIMO) sonar system consisting of two transmitters and a receiving linear array. Transmitters are widely separated to illuminate the different aspects of an extended target of interest. The beamforming technique is utilized at the reception ends for enhancement of weak target echoes. A MIMO detector is designed with the estimated target position parameters within the general likelihood rate test (GLRT) framework. For the high signal-to-noise ratio case, the detection performance of the MIMO system is better than that of the phased-array system in the numerical simulations and the tank experiments. The robustness of the distributed phased-MIMO sonar system is further demonstrated in localization of a target in at-lake experiments.

Evaluation of the Performance of the Distributed Phased-MIMO Sonar

PubMed Central

Pan, Xiang; Jiang, Jingning; Wang, Nan

2017-01-01

A broadband signal model is proposed for a distributed multiple-input multiple-output (MIMO) sonar system consisting of two transmitters and a receiving linear array. Transmitters are widely separated to illuminate the different aspects of an extended target of interest. The beamforming technique is utilized at the reception ends for enhancement of weak target echoes. A MIMO detector is designed with the estimated target position parameters within the general likelihood rate test (GLRT) framework. For the high signal-to-noise ratio case, the detection performance of the MIMO system is better than that of the phased-array system in the numerical simulations and the tank experiments. The robustness of the distributed phased-MIMO sonar system is further demonstrated in localization of a target in at-lake experiments. PMID:28085071

The H,G_1,G_2 photometric system with scarce observational data

NASA Astrophysics Data System (ADS)

Penttilä, A.; Granvik, M.; Muinonen, K.; Wilkman, O.

2014-07-01

The H,G_1,G_2 photometric system was officially adopted at the IAU General Assembly in Beijing, 2012. The system replaced the H,G system from 1985. The 'photometric system' is a parametrized model V(α; params) for the magnitude-phase relation of small Solar System bodies, and the main purpose is to predict the magnitude at backscattering, H := V(0°), i.e., the (absolute) magnitude of the object. The original H,G system was designed using the best available data in 1985, but since then new observations have been made showing certain features, especially near backscattering, to which the H,G function has troubles adjusting to. The H,G_1,G_2 system was developed especially to address these issues [1]. With a sufficient number of high-accuracy observations and with a wide phase-angle coverage, the H,G_1,G_2 system performs well. However, with scarce low-accuracy data the system has troubles producing a reliable fit, as would any other three-parameter nonlinear function. Therefore, simultaneously with the H,G_1,G_2 system, a two-parameter version of the model, the H,G_{12} system, was introduced [1]. The two-parameter version ties the parameters G_1,G_2 into a single parameter G_{12} by a linear relation, and still uses the H,G_1,G_2 system in the background. This version dramatically improves the possibility to receive a reliable phase-curve fit to scarce data. The amount of observed small bodies is increasing all the time, and so is the need to produce estimates for the absolute magnitude/diameter/albedo and other size/composition related parameters. The lack of small-phase-angle observations is especially topical for near-Earth objects (NEOs). With these, even the two- parameter version faces problems. The previous procedure with the H,G system in such circumstances has been that the G-parameter has been fixed to some constant value, thus only fitting a single-parameter function. In conclusion, there is a definitive need for a reliable procedure to produce photometric fits to very scarce and low-accuracy data. There are a few details that should be considered with the H,G_1,G_2 or H,G_{12} systems with scarce data. The first point is the distribution of errors in the fit. The original H,G system allowed linear regression in the flux space, thus making the estimation computationally easier. The same principle was repeated with the H,G_1,G_2 system. There is, however, a major hidden assumption in the transformation. With regression modeling, the residuals should be distributed symmetrically around zero. If they are normally distributed, even better. We have noticed that, at least with some NEO observations, the residuals in the flux space are far from symmetric, and seem to be much more symmetric in the magnitude space. The result is that the nonlinear fit in magnitude space is far more reliable than the linear fit in the flux space. Since the computers and nonlinear regression algorithms are efficient enough, we conclude that, in many cases, with low-accuracy data the nonlinear fit should be favored. In fact, there are statistical procedures that should be employed with the photometric fit. At the moment, the choice between the three-parameter and two-parameter versions is simply based on subjective decision-making. By checking parameter error and model comparison statistics, the choice could be done objectively. Similarly, the choice between the linear fit in flux space and the nonlinear fit in magnitude space should be based on a statistical test of unbiased residuals. Furthermore, the so-called Box-Cox transform could be employed to find an optimal transformation somewhere between the magnitude and flux spaces. The H,G_1,G_2 system is based on cubic splines, and is therefore a bit more complicated to implement than a system with simpler basis functions. The same applies to a complete program that would automatically choose the best transforms to data, test if two- or three-parameter version of the model should be fitted, and produce the fitted parameters with their error estimates. Our group has already made implementations of the H,G_1,G_2 system publicly available [2]. We plan to implement the abovementioned improvements to the system and make also these tools public.

A Robust Distributed Multipoint Fiber Optic Gas Sensor System Based on AGC Amplifier Structure.

PubMed

Zhu, Cunguang; Wang, Rende; Tao, Xuechen; Wang, Guangwei; Wang, Pengpeng

2016-07-28

A harsh environment-oriented distributed multipoint fiber optic gas sensor system realized by automatic gain control (AGC) technology is proposed. To improve the photoelectric signal reliability, the electronic variable gain can be modified in real time by an AGC closed-loop feedback structure to compensate for optical transmission loss which is caused by the fiber bend loss or other reasons. The deviation of the system based on AGC structure is below 4.02% when photoelectric signal decays due to fiber bending loss for bending radius of 5 mm, which is 20 times lower than the ordinary differential system. In addition, the AGC circuit with the same electric parameters can keep the baseline intensity of signals in different channels of the distributed multipoint sensor system at the same level. This avoids repetitive calibrations and streamlines the installation process.

Parameter optimization in biased decoy-state quantum key distribution with both source errors and statistical fluctuations

NASA Astrophysics Data System (ADS)

Zhu, Jian-Rong; Li, Jian; Zhang, Chun-Mei; Wang, Qin

2017-10-01

The decoy-state method has been widely used in commercial quantum key distribution (QKD) systems. In view of the practical decoy-state QKD with both source errors and statistical fluctuations, we propose a universal model of full parameter optimization in biased decoy-state QKD with phase-randomized sources. Besides, we adopt this model to carry out simulations of two widely used sources: weak coherent source (WCS) and heralded single-photon source (HSPS). Results show that full parameter optimization can significantly improve not only the secure transmission distance but also the final key generation rate. And when taking source errors and statistical fluctuations into account, the performance of decoy-state QKD using HSPS suffered less than that of decoy-state QKD using WCS.

The role of community structure on the nature of explosive synchronization.

PubMed

Lotfi, Nastaran; Rodrigues, Francisco A; Darooneh, Amir Hossein

2018-03-01

In this paper, we analyze explosive synchronization in networks with a community structure. The results of our study indicate that the mesoscopic structure of the networks could affect the synchronization of coupled oscillators. With the variation of three parameters, the degree probability distribution exponent, the community size probability distribution exponent, and the mixing parameter, we could have a fast or slow phase transition. Besides, in some cases, we could have communities which are synchronized inside but not with other communities and vice versa. We also show that there is a limit in these mesoscopic structures which suppresses the transition from the second-order phase transition and results in explosive synchronization. This could be considered as a tuning parameter changing the transition of the system from the second order to the first order.

Dust-concentration measurement based on Mie scattering of a laser beam

PubMed Central

Yu, Xiaoyu; Shi, Yunbo; Wang, Tian; Sun, Xu

2017-01-01

To realize automatic measurement of the concentration of dust particles in the air, a theory for dust concentration measurement was developed, and a system was designed to implement the dust concentration measurement method based on laser scattering. In the study, the principle of dust concentration detection using laser scattering is studied, and the detection basis of Mie scattering theory is determined. Through simulation, the influence of the incident laser wavelength, dust particle diameter, and refractive index of dust particles on the scattered light intensity distribution are obtained for determining the scattered light intensity curves of single suspended dust particles under different characteristic parameters. A genetic algorithm was used to study the inverse particle size distribution, and the reliability of the measurement system design is proven theoretically. The dust concentration detection system, which includes a laser system, computer circuitry, air flow system, and control system, was then implemented according to the parameters obtained from the theoretical analysis. The performance of the designed system was evaluated. Experimental results show that the system performance was stable and reliable, resulting in high-precision automatic dust concentration measurement with strong anti-interference ability. PMID:28767662

Collisional evolution - an analytical study for the nonsteady-state mass distribution

NASA Astrophysics Data System (ADS)

Martins, R. Vieira

1999-05-01

To study the collisional evolution of asteroidal groups we can use an analytical solutionfor the self-similar collision cascades. This solution is suitable to study the steady-state massdistribution of the collisional fragmentation. However, out of the steady-state conditions, thissolution is not satisfactory for some values of the collisional parameters. In fact, for some valuesfor the exponent of the mass distribution power law of an asteroidal group and its relation to theexponent of the function which describes how rocks break we arrive at singular points for theequation which describes the collisional evolution. These singularities appear since someapproximations are usually made in the laborious evaluation of many integrals that appear in theanalytical calculations. They concern the cutoff for the smallest and the largest bodies. Thesesingularities set some restrictions to the study of the analytical solution for the collisionalequation. To overcome these singularities we performed an algebraic computationconsidering the smallest and the largest bodies and we obtained the analytical expressions for theintegrals that describe the collisional evolution without restriction on the parameters. However,the new distribution is more sensitive to the values of the collisional parameters. In particular thesteady-state solution for the differential mass distribution has exponents slightly different from11⧸6 for the usual parameters in the Asteroid Belt. The sensitivity of this distribution with respectto the parameters is analyzed for the usual values in the asteroidal groups. With anexpression for the mass distribution without singularities, we can evaluate also its time evolution.We arrive at an analytical expression given by a power series of terms constituted by a smallparameter multiplied by the mass to an exponent, which depends on the initial power lawdistribution. This expression is a formal solution for the equation which describes the collisionalevolution. Furthermore, the first-order term for this solution is the time rate of the distribution atthe initial time. In particular the solution shows the fundamental importance played by theexponent of the power law initial condition in the evolution of the system.

Study of Parameters And Methods of LL-Ⅳ Distributed Hydrological Model in DMIP2

NASA Astrophysics Data System (ADS)

Li, L.; Wu, J.; Wang, X.; Yang, C.; Zhao, Y.; Zhou, H.

2008-05-01

: The Physics-based distributed hydrological model is considered as an important developing period from the traditional experience-hydrology to the physical hydrology. The Hydrology Laboratory of the NOAA National Weather Service proposes the first and second phase of the Distributed Model Intercomparison Project (DMIP)，that it is a great epoch-making work. LL distributed hydrological model has been developed to the fourth generation since it was established in 1997 on the Fengman-I district reservoir area (11000 km2).The LL-I distributed hydrological model was born with the applications of flood control system in the Fengman-I in China. LL-II was developed under the DMIP-I support, it is combined with GIS, RS, GPS, radar rainfall measurement.LL-III was established along with Applications of LL Distributed Model on Water Resources which was supported by the 973-projects of The Ministry of Science and Technology of the People's Republic of China. LL-Ⅳ was developed to face China's water problem. Combined with Blue River and the Baron Fork River basin of DMIP-II, the convection-diffusion equation of non-saturated and saturated seepage was derived from the soil water dynamics and continuous equation. In view of the technical characteristics of the model, the advantage of using convection-diffusion equation to compute confluence overall is longer period of predictable, saving memory space, fast budgeting, clear physical concepts, etc. The determination of parameters of hydrological model is the key, including experience coefficients and parameters of physical parameters. There are methods of experience, inversion, and the optimization to determine the model parameters, and each has advantages and disadvantages. This paper briefly introduces the LL-Ⅳ distribution hydrological model equations, and particularly introduces methods of parameters determination and simulation results on Blue River and Baron Fork River basin for DMIP-II. The soil moisture diffusion coefficient and coefficient of hydraulic conductivity are involved all through the LL-Ⅳ distribution of runoff and slope convergence model, used mainly empirical formula to determine. It's used optimization methods to calculate the two parameters of evaporation capacity (coefficient of bare land and vegetation land), two parameters of interception and wave velocity of Overland Flow, interflow and groundwater. The approach of determining wave velocity of River Network confluence and diffusion coefficient is: 1. Estimate roughness based mainly on digital information such as land use, soil texture, etc. 2.Establish the empirical formula. Another method is called convection-diffusion numerical inversion.

Temperature control in continuous furnace by structural diagram method

NASA Technical Reports Server (NTRS)

Lei, Xia; Hartley, Tom T.

1991-01-01

The fundamentals of the structural diagram method for distributed parameter systems (DPSs) are presented and reviewed. An example is given to illustrate the application of this method for control design.

Surfactant enhanced recovery of tetrachloroethylene from a porous medium containing low permeability lenses. 2. Numerical simulation.

PubMed

Rathfelder, K M; Abriola, L M; Taylor, T P; Pennell, K D

2001-04-01

A numerical model of surfactant enhanced solubilization was developed and applied to the simulation of nonaqueous phase liquid recovery in two-dimensional heterogeneous laboratory sand tank systems. Model parameters were derived from independent, small-scale, batch and column experiments. These parameters included viscosity, density, solubilization capacity, surfactant sorption, interfacial tension, permeability, capillary retention functions, and interphase mass transfer correlations. Model predictive capability was assessed for the evaluation of the micellar solubilization of tetrachloroethylene (PCE) in the two-dimensional systems. Predicted effluent concentrations and mass recovery agreed reasonably well with measured values. Accurate prediction of enhanced solubilization behavior in the sand tanks was found to require the incorporation of pore-scale, system-dependent, interphase mass transfer limitations, including an explicit representation of specific interfacial contact area. Predicted effluent concentrations and mass recovery were also found to depend strongly upon the initial NAPL entrapment configuration. Numerical results collectively indicate that enhanced solubilization processes in heterogeneous, laboratory sand tank systems can be successfully simulated using independently measured soil parameters and column-measured mass transfer coefficients, provided that permeability and NAPL distributions are accurately known. This implies that the accuracy of model predictions at the field scale will be constrained by our ability to quantify soil heterogeneity and NAPL distribution.

Bayesian calibration of the Community Land Model using surrogates

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

Ray, Jaideep; Hou, Zhangshuan; Huang, Maoyi

2014-02-01

We present results from the Bayesian calibration of hydrological parameters of the Community Land Model (CLM), which is often used in climate simulations and Earth system models. A statistical inverse problem is formulated for three hydrological parameters, conditional on observations of latent heat surface fluxes over 48 months. Our calibration method uses polynomial and Gaussian process surrogates of the CLM, and solves the parameter estimation problem using a Markov chain Monte Carlo sampler. Posterior probability densities for the parameters are developed for two sites with different soil and vegetation covers. Our method also allows us to examine the structural errormore » in CLM under two error models. We find that surrogate models can be created for CLM in most cases. The posterior distributions are more predictive than the default parameter values in CLM. Climatologically averaging the observations does not modify the parameters' distributions significantly. The structural error model reveals a correlation time-scale which can be used to identify the physical process that could be contributing to it. While the calibrated CLM has a higher predictive skill, the calibration is under-dispersive.« less

Event-Based Variance-Constrained ${\\mathcal {H}}_{\\infty }$ Filtering for Stochastic Parameter Systems Over Sensor Networks With Successive Missing Measurements.

PubMed

Wang, Licheng; Wang, Zidong; Han, Qing-Long; Wei, Guoliang

2018-03-01

This paper is concerned with the distributed filtering problem for a class of discrete time-varying stochastic parameter systems with error variance constraints over a sensor network where the sensor outputs are subject to successive missing measurements. The phenomenon of the successive missing measurements for each sensor is modeled via a sequence of mutually independent random variables obeying the Bernoulli binary distribution law. To reduce the frequency of unnecessary data transmission and alleviate the communication burden, an event-triggered mechanism is introduced for the sensor node such that only some vitally important data is transmitted to its neighboring sensors when specific events occur. The objective of the problem addressed is to design a time-varying filter such that both the requirements and the variance constraints are guaranteed over a given finite-horizon against the random parameter matrices, successive missing measurements, and stochastic noises. By recurring to stochastic analysis techniques, sufficient conditions are established to ensure the existence of the time-varying filters whose gain matrices are then explicitly characterized in term of the solutions to a series of recursive matrix inequalities. A numerical simulation example is provided to illustrate the effectiveness of the developed event-triggered distributed filter design strategy.

Distribution of trace metals in the vicinity of a wastewater treatment plant on the Potomac River, Washington, DC, USA

NASA Astrophysics Data System (ADS)

Smith, J. P.; Muller, A. C.

2013-05-01

Predicting the fate and distribution of anthropogenic-sourced trace metals in riverine and estuarine systems is challenging due to multiple and varying source functions and dynamic physiochemical conditions. Between July 2011 and November 2012, sediment and water column samples were collected from over 20 sites in the tidal-fresh Potomac River estuary, Washington, DC near the outfall of the Blue Plains Advanced Wastewater Treatment Plant (BPWTP) for measurement of select trace metals. Field observations of water column parameters (conductivity, temperature, pH, turbidity) were also made at each sampling site. Trace metal concentrations were normalized to the "background" composition of the river determined from control sites in order to investigate the distribution BPWTP-sourced in local Potomac River receiving waters. Temporal differences in the observed distribution of trace metals were attributed to changes in the relative contribution of metals from different sources (wastewater, riverine, other) coupled with differences in the physiochemical conditions of the water column. Results show that normalizing near-source concentrations to the background composition of the water body and also to key environmental parameters can aid in predicting the fate and distribution of anthropogenic-sourced trace metals in dynamic riverine and estuarine systems like the tidal-fresh Potomac River.

Dynamic stability analysis of torsional vibrations of a shaft system connected by a Hooke's joint through a continuous system model

NASA Astrophysics Data System (ADS)

Bulut, Gökhan

2014-08-01

Stability of parametrically excited torsional vibrations of a shaft system composed of two torsionally elastic shafts interconnected through a Hooke's joint is studied. The shafts are considered to be continuous (distributed-parameter) systems and an approximate discrete model for the torsional vibrations of the shaft system is derived via a finite element scheme. The stability of the solutions of the linearized equations of motion, consisting of a set of Mathieu-Hill type equations, is examined by means of a monodromy matrix method and the results are presented in the form of a Strutt-Ince diagram visualizing the effects of the system parameters on the stability of the shaft system.

A physically based catchment partitioning method for hydrological analysis

NASA Astrophysics Data System (ADS)

Menduni, Giovanni; Riboni, Vittoria

2000-07-01

We propose a partitioning method for the topographic surface, which is particularly suitable for hydrological distributed modelling and shallow-landslide distributed modelling. The model provides variable mesh size and appears to be a natural evolution of contour-based digital terrain models. The proposed method allows the drainage network to be derived from the contour lines. The single channels are calculated via a search for the steepest downslope lines. Then, for each network node, the contributing area is determined by means of a search for both steepest upslope and downslope lines. This leads to the basin being partitioned into physically based finite elements delimited by irregular polygons. In particular, the distributed computation of local geomorphological parameters (i.e. aspect, average slope and elevation, main stream length, concentration time, etc.) can be performed easily for each single element. The contributing area system, together with the information on the distribution of geomorphological parameters provide a useful tool for distributed hydrological modelling and simulation of environmental processes such as erosion, sediment transport and shallow landslides.

Optimal startup control of a jacketed tubular reactor.

NASA Technical Reports Server (NTRS)

Hahn, D. R.; Fan, L. T.; Hwang, C. L.

1971-01-01

The optimal startup policy of a jacketed tubular reactor, in which a first-order, reversible, exothermic reaction takes place, is presented. A distributed maximum principle is presented for determining weak necessary conditions for optimality of a diffusional distributed parameter system. A numerical technique is developed for practical implementation of the distributed maximum principle. This involves the sequential solution of the state and adjoint equations, in conjunction with a functional gradient technique for iteratively improving the control function.

Transient queue-size distribution in a finite-capacity queueing system with server breakdowns and Bernoulli feedback

NASA Astrophysics Data System (ADS)

Kempa, Wojciech M.

2017-12-01

A finite-capacity queueing system with server breakdowns is investigated, in which successive exponentially distributed failure-free times are followed by repair periods. After the processing a customer may either rejoin the queue (feedback) with probability q, or definitely leave the system with probability 1 - q. The system of integral equations for transient queue-size distribution, conditioned by the initial level of buffer saturation, is build. The solution of the corresponding system written for Laplace transforms is found using the linear algebraic approach. The considered queueing system can be successfully used in modelling production lines with machine failures, in which the parameter q may be considered as a typical fraction of items demanding corrections. Morever, this queueing model can be applied in the analysis of real TCP/IP performance, where q stands for the fraction of packets requiring retransmission.

Modelling study on the three-dimensional neutron depolarisation response of the evolving ferrite particle size distribution during the austenite-ferrite phase transformation in steels

NASA Astrophysics Data System (ADS)

Fang, H.; van der Zwaag, S.; van Dijk, N. H.

2018-07-01

The magnetic configuration of a ferromagnetic system with mono-disperse and poly-disperse distribution of magnetic particles with inter-particle interactions has been computed. The analysis is general in nature and applies to all systems containing magnetically interacting particles in a non-magnetic matrix, but has been applied to steel microstructures, consisting of a paramagnetic austenite phase and a ferromagnetic ferrite phase, as formed during the austenite-to-ferrite phase transformation in low-alloyed steels. The characteristics of the computational microstructures are linked to the correlation function and determinant of depolarisation matrix, which can be experimentally obtained in three-dimensional neutron depolarisation (3DND). By tuning the parameters in the model used to generate the microstructure, we studied the effect of the (magnetic) particle size distribution on the 3DND parameters. It is found that the magnetic particle size derived from 3DND data matches the microstructural grain size over a wide range of volume fractions and grain size distributions. A relationship between the correlation function and the relative width of the particle size distribution was proposed to accurately account for the width of the size distribution. This evaluation shows that 3DND experiments can provide unique in situ information on the austenite-to-ferrite phase transformation in steels.

Data catalog for JPL Physical Oceanography Distributed Active Archive Center (PO.DAAC)

NASA Technical Reports Server (NTRS)

Digby, Susan

1995-01-01

The Physical Oceanography Distributed Active Archive Center (PO.DAAC) archive at the Jet Propulsion Laboratory contains satellite data sets and ancillary in-situ data for the ocean sciences and global-change research to facilitate multidisciplinary use of satellite ocean data. Geophysical parameters available from the archive include sea-surface height, surface-wind vector, surface-wind speed, surface-wind stress vector, sea-surface temperature, atmospheric liquid water, integrated water vapor, phytoplankton pigment concentration, heat flux, and in-situ data. PO.DAAC is an element of the Earth Observing System Data and Information System and is the United States distribution site for TOPEX/POSEIDON data and metadata.

Distributed acoustic fibre optic sensors for condition monitoring of pipelines

NASA Astrophysics Data System (ADS)

Hussels, Maria-Teresa; Chruscicki, Sebastian; Habib, Abdelkarim; Krebber, Katerina

2016-05-01

Industrial piping systems are particularly relevant to public safety and the continuous availability of infrastructure. However, condition monitoring systems based on many discrete sensors are generally not well-suited for widespread piping systems due to considerable installation effort, while use of distributed fibre-optic sensors would reduce this effort to a minimum. Specifically distributed acoustic sensing (DAS) is employed for detection of third-party threats and leaks in oil and gas pipelines in recent years and can in principle also be applied to industrial plants. Further possible detection routes amenable by DAS that could identify damage prior to emission of medium are subject of a current project at BAM, which aims at qualifying distributed fibre optic methods such as DAS as a means for spatially continuous monitoring of industrial piping systems. Here, first tests on a short pipe are presented, where optical fibres were applied directly to the surface. An artificial signal was used to define suitable parameters of the measurement system and compare different ways of applying the sensor.

Time Correlations in Mode Hopping of Coupled Oscillators

NASA Astrophysics Data System (ADS)

Heltberg, Mathias L.; Krishna, Sandeep; Jensen, Mogens H.

2017-05-01

We study the dynamics in a system of coupled oscillators when Arnold Tongues overlap. By varying the initial conditions, the deterministic system can be attracted to different limit cycles. Adding noise, the mode hopping between different states become a dominating part of the dynamics. We simplify the system through a Poincare section, and derive a 1D model to describe the dynamics. We explain that for some parameter values of the external oscillator, the time distribution of occupancy in a state is exponential and thus memoryless. In the general case, on the other hand, it is a sum of exponential distributions characteristic of a system with time correlations.

Analytical performance evaluation of SAR ATR with inaccurate or estimated models

NASA Astrophysics Data System (ADS)

DeVore, Michael D.

2004-09-01

Hypothesis testing algorithms for automatic target recognition (ATR) are often formulated in terms of some assumed distribution family. The parameter values corresponding to a particular target class together with the distribution family constitute a model for the target's signature. In practice such models exhibit inaccuracy because of incorrect assumptions about the distribution family and/or because of errors in the assumed parameter values, which are often determined experimentally. Model inaccuracy can have a significant impact on performance predictions for target recognition systems. Such inaccuracy often causes model-based predictions that ignore the difference between assumed and actual distributions to be overly optimistic. This paper reports on research to quantify the effect of inaccurate models on performance prediction and to estimate the effect using only trained parameters. We demonstrate that for large observation vectors the class-conditional probabilities of error can be expressed as a simple function of the difference between two relative entropies. These relative entropies quantify the discrepancies between the actual and assumed distributions and can be used to express the difference between actual and predicted error rates. Focusing on the problem of ATR from synthetic aperture radar (SAR) imagery, we present estimators of the probabilities of error in both ideal and plug-in tests expressed in terms of the trained model parameters. These estimators are defined in terms of unbiased estimates for the first two moments of the sample statistic. We present an analytical treatment of these results and include demonstrations from simulated radar data.

Statistics of the Work done in a Quantum Quench

NASA Astrophysics Data System (ADS)

Silva, Alessandro

2009-03-01

The quantum quench, i.e. a rapid change in time of a control parameter of a quantum system, is the simplest paradigm of non-equilibrium process, completely analogous to a standard thermodynamic transformation. The dynamics following a quantum quench is particularly interesting in strongly correlated quantum systems, most prominently when the quench in performed across a quantum critical point. In this talk I will present a way to characterize the physics of quantum quenches by looking at the statistics of a basic thermodynamic variable: the work done on the system by changing its parameters [1]. I will first elucidate the relation between the probability distribution of the work, quantum Jarzynski equalities, and the Loschmidt echo, a quantity that emerges usually in the context of dephasing. Using this connection, I will then characterize the statistics of the work done on a Quantum Ising chain by quenching locally or globally the transverse field. I will then show that for global quenches the presence of a quantum critical point results in singularities of the moments of the distribution, while, for local quenches starting at criticality, the probability distribution itself displays an interesting edge singularity. The results of a similar analysis for other systems will be discussed. [4pt] [1] A. Silva, Phys. Rev. Lett. 101, 120603 (2008).

Modeling of biodynamic responses distributed at the fingers and the palm of the human hand-arm system.

PubMed

Dong, Ren G; Dong, Jennie H; Wu, John Z; Rakheja, Subhash

2007-01-01

The objective of this study is to develop analytical models for simulating driving-point biodynamic responses distributed at the fingers and palm of the hand under vibration along the forearm direction (z(h)-axis). Two different clamp-like model structures are formulated to analyze the distributed responses at the fingers-handle and palm-handle interfaces, as opposed to the single driving point invariably considered in the reported models. The parameters of the proposed four- and five degrees-of-freedom models are identified through minimization of an rms error function of the model and measured responses under different hand actions, namely, fingers pull, push only, grip only, and combined push and grip. The results show that the responses predicted from both models agree reasonably well with the measured data in terms of distributed as well total impedance magnitude and phase. The variations in the identified model parameters under different hand actions are further discussed in view of the biological system behavior. The proposed models are considered to serve as useful tools for design and assessment of vibration isolation methods, and for developing a hand-arm simulator for vibration analysis of power tools.

In silico study on the effects of matrix structure in controlled drug release

NASA Astrophysics Data System (ADS)

Villalobos, Rafael; Cordero, Salomón; Maria Vidales, Ana; Domínguez, Armando

2006-07-01

Purpose: To study the effects of drug concentration and spatial distribution of the medicament, in porous solid dosage forms, on the kinetics and total yield of drug release. Methods: Cubic networks are used as models of drug release systems. They were constructed by means of the dual site-bond model framework, which allows a substrate to have adequate geometrical and topological distribution of its pore elements. Drug particles can move inside the networks by following a random walk model with excluded volume interactions between the particles. The drug release time evolution for different drug concentration and different initial drug spatial distribution has been monitored. Results: The numerical results show that in all the studied cases, drug release presents an anomalous behavior, and the consequences of the matrix structural properties, i.e., drug spatial distribution and drug concentration, on the drug release profile have been quantified. Conclusions: The Weibull function provides a simple connection between the model parameters and the microstructure of the drug release device. A critical modeling of drug release from matrix-type delivery systems is important in order to understand the transport mechanisms that are implicated, and to predict the effect of the device design parameters on the release rate.

Statistical characterization of discrete conservative systems: The web map

NASA Astrophysics Data System (ADS)

Ruiz, Guiomar; Tirnakli, Ugur; Borges, Ernesto P.; Tsallis, Constantino

2017-10-01

We numerically study the two-dimensional, area preserving, web map. When the map is governed by ergodic behavior, it is, as expected, correctly described by Boltzmann-Gibbs statistics, based on the additive entropic functional SB G[p (x ) ] =-k ∫d x p (x ) lnp (x ) . In contrast, possible ergodicity breakdown and transitory sticky dynamical behavior drag the map into the realm of generalized q statistics, based on the nonadditive entropic functional Sq[p (x ) ] =k 1/-∫d x [p(x ) ] q q -1 (q ∈R ;S1=SB G ). We statistically describe the system (probability distribution of the sum of successive iterates, sensitivity to the initial condition, and entropy production per unit time) for typical values of the parameter that controls the ergodicity of the map. For small (large) values of the external parameter K , we observe q -Gaussian distributions with q =1.935 ⋯ (Gaussian distributions), like for the standard map. In contrast, for intermediate values of K , we observe a different scenario, due to the fractal structure of the trajectories embedded in the chaotic sea. Long-standing non-Gaussian distributions are characterized in terms of the kurtosis and the box-counting dimension of chaotic sea.

An optimal beam alignment method for large-scale distributed space surveillance radar system

NASA Astrophysics Data System (ADS)

Huang, Jian; Wang, Dongya; Xia, Shuangzhi

2018-06-01

Large-scale distributed space surveillance radar is a very important ground-based equipment to maintain a complete catalogue for Low Earth Orbit (LEO) space debris. However, due to the thousands of kilometers distance between each sites of the distributed radar system, how to optimally implement the Transmitting/Receiving (T/R) beams alignment in a great space using the narrow beam, which proposed a special and considerable technical challenge in the space surveillance area. According to the common coordinate transformation model and the radar beam space model, we presented a two dimensional projection algorithm for T/R beam using the direction angles, which could visually describe and assess the beam alignment performance. Subsequently, the optimal mathematical models for the orientation angle of the antenna array, the site location and the T/R beam coverage are constructed, and also the beam alignment parameters are precisely solved. At last, we conducted the optimal beam alignment experiments base on the site parameters of Air Force Space Surveillance System (AFSSS). The simulation results demonstrate the correctness and effectiveness of our novel method, which can significantly stimulate the construction for the LEO space debris surveillance equipment.

Air data system optimization using a genetic algorithm

NASA Technical Reports Server (NTRS)

Deshpande, Samir M.; Kumar, Renjith R.; Seywald, Hans; Siemers, Paul M., III

1992-01-01

An optimization method for flush-orifice air data system design has been developed using the Genetic Algorithm approach. The optimization of the orifice array minimizes the effect of normally distributed random noise in the pressure readings on the calculation of air data parameters, namely, angle of attack, sideslip angle and freestream dynamic pressure. The optimization method is applied to the design of Pressure Distribution/Air Data System experiment (PD/ADS) proposed for inclusion in the Aeroassist Flight Experiment (AFE). Results obtained by the Genetic Algorithm method are compared to the results obtained by conventional gradient search method.

Distributed Generators Allocation in Radial Distribution Systems with Load Growth using Loss Sensitivity Approach

NASA Astrophysics Data System (ADS)

Kumar, Ashwani; Vijay Babu, P.; Murty, V. V. S. N.

2017-06-01

Rapidly increasing electricity demands and capacity shortage of transmission and distribution facilities are the main driving forces for the growth of distributed generation (DG) integration in power grids. One of the reasons for choosing a DG is its ability to support voltage in a distribution system. Selection of effective DG characteristics and DG parameters is a significant concern of distribution system planners to obtain maximum potential benefits from the DG unit. The objective of the paper is to reduce the power losses and improve the voltage profile of the radial distribution system with optimal allocation of the multiple DG in the system. The main contribution in this paper is (i) combined power loss sensitivity (CPLS) based method for multiple DG locations, (ii) determination of optimal sizes for multiple DG units at unity and lagging power factor, (iii) impact of DG installed at optimal, that is, combined load power factor on the system performance, (iv) impact of load growth on optimal DG planning, (v) Impact of DG integration in distribution systems on voltage stability index, (vi) Economic and technical Impact of DG integration in the distribution systems. The load growth factor has been considered in the study which is essential for planning and expansion of the existing systems. The technical and economic aspects are investigated in terms of improvement in voltage profile, reduction in total power losses, cost of energy loss, cost of power obtained from DG, cost of power intake from the substation, and savings in cost of energy loss. The results are obtained on IEEE 69-bus radial distribution systems and also compared with other existing methods.

Inverse modeling for seawater intrusion in coastal aquifers: Insights about parameter sensitivities, variances, correlations and estimation procedures derived from the Henry problem

USGS Publications Warehouse

Sanz, E.; Voss, C.I.

2006-01-01

Inverse modeling studies employing data collected from the classic Henry seawater intrusion problem give insight into several important aspects of inverse modeling of seawater intrusion problems and effective measurement strategies for estimation of parameters for seawater intrusion. Despite the simplicity of the Henry problem, it embodies the behavior of a typical seawater intrusion situation in a single aquifer. Data collected from the numerical problem solution are employed without added noise in order to focus on the aspects of inverse modeling strategies dictated by the physics of variable-density flow and solute transport during seawater intrusion. Covariances of model parameters that can be estimated are strongly dependent on the physics. The insights gained from this type of analysis may be directly applied to field problems in the presence of data errors, using standard inverse modeling approaches to deal with uncertainty in data. Covariance analysis of the Henry problem indicates that in order to generally reduce variance of parameter estimates, the ideal places to measure pressure are as far away from the coast as possible, at any depth, and the ideal places to measure concentration are near the bottom of the aquifer between the center of the transition zone and its inland fringe. These observations are located in and near high-sensitivity regions of system parameters, which may be identified in a sensitivity analysis with respect to several parameters. However, both the form of error distribution in the observations and the observation weights impact the spatial sensitivity distributions, and different choices for error distributions or weights can result in significantly different regions of high sensitivity. Thus, in order to design effective sampling networks, the error form and weights must be carefully considered. For the Henry problem, permeability and freshwater inflow can be estimated with low estimation variance from only pressure or only concentration observations. Permeability, freshwater inflow, solute molecular diffusivity, and porosity can be estimated with roughly equivalent confidence using observations of only the logarithm of concentration. Furthermore, covariance analysis allows a logical reduction of the number of estimated parameters for ill-posed inverse seawater intrusion problems. Ill-posed problems may exhibit poor estimation convergence, have a non-unique solution, have multiple minima, or require excessive computational effort, and the condition often occurs when estimating too many or co-dependent parameters. For the Henry problem, such analysis allows selection of the two parameters that control system physics from among all possible system parameters. ?? 2005 Elsevier Ltd. All rights reserved.

Properties of Air Traffic Conflicts for Free and Structured Routing

NASA Technical Reports Server (NTRS)

Bilimoria, Karl D.; Lee, Hilda Q.

2001-01-01

This paper analyzes the properties of air traffic conflicts in a future free routing system against those in the current structured routing system. Simulation of en route air traffic operations (above 18,000 ft) over the contiguous United States for a 24-hour period, constructed with initial conditions from actual air traffic data, were conducted using the Future ATM Concepts Evaluation Tool (FACET). Free routes were modeled as great circle (direct) routes from origin to destination, and structured routes were derived from actual flight plans along the current system of air routes. The conflict properties analyzed in this study include: (1) Total number of conflicts; (2) Distributions of key conflict parameters; and, (3) Categorization of conflicts into independent conflicts and two types of interacting conflicts. Preliminary results (for Denver Center traffic) indicate that conflict properties in a free routing system are different from those in the current structured routing system. In particular, a free routing system has significantly fewer conflicts, involving a correspondingly smaller number of aircraft, compared to the current structured routing system. Additionally, the conflict parameter distributions indicate that free routing conflicts are less intrusive than structured routing conflicts, and would therefore require small trajectory deviations for resolution.

An analysis of the first two years of GASP data

NASA Technical Reports Server (NTRS)

Holdeman, J. D.; Nastrom, G. D.; Falconer, P. D.

1977-01-01

Distributions of mean ozone levels from the first two years of data from the NASA Global Atmospheric Sampling Program (GASP) show spatial and temporal variations in agreement with previous measurements. The standard deviations of these distributions reflect the large natural variability of ozone levels in the altitude range of the GASP measurements. Monthly mean levels of ozone below the tropopause show an annual cycle with a spring maximum which is believed to result from transport from the stratosphere. Correlations of ozone with independent meteorological parameters, and meteorological parameters obtained by the GASP systems show that this transport occurs primarily through cyclogenesis at mid-latitudes.

Sulfate passivation in the lead-acid system as a capacity limiting process

NASA Astrophysics Data System (ADS)

Kappus, W.; Winsel, A.

1982-10-01

Calculations of the discharge capacity of Pb and PbO 2 electrodes as a function of various parameters are presented. They are based on the solution-precipitation mechanism for the discharge reaction and its formulation by Winsel et al. A logarithmic pore size distribution is used to fit experimental porosigrams of Pb and PbO 2 electrodes. Based on this pore size distribution the capacity is calculated as a function of current, BET surface, and porosity of the PbSO 4 diaphragm. The PbSO 4 supersaturation as the driving force of the diffusive transport is chosen as a free parameter.

An offline approach for output-only Bayesian identification of stochastic nonlinear systems using unscented Kalman filtering

NASA Astrophysics Data System (ADS)

Erazo, Kalil; Nagarajaiah, Satish

2017-06-01

In this paper an offline approach for output-only Bayesian identification of stochastic nonlinear systems is presented. The approach is based on a re-parameterization of the joint posterior distribution of the parameters that define a postulated state-space stochastic model class. In the re-parameterization the state predictive distribution is included, marginalized, and estimated recursively in a state estimation step using an unscented Kalman filter, bypassing state augmentation as required by existing online methods. In applications expectations of functions of the parameters are of interest, which requires the evaluation of potentially high-dimensional integrals; Markov chain Monte Carlo is adopted to sample the posterior distribution and estimate the expectations. The proposed approach is suitable for nonlinear systems subjected to non-stationary inputs whose realization is unknown, and that are modeled as stochastic processes. Numerical verification and experimental validation examples illustrate the effectiveness and advantages of the approach, including: (i) an increased numerical stability with respect to augmented-state unscented Kalman filtering, avoiding divergence of the estimates when the forcing input is unmeasured; (ii) the ability to handle arbitrary prior and posterior distributions. The experimental validation of the approach is conducted using data from a large-scale structure tested on a shake table. It is shown that the approach is robust to inherent modeling errors in the description of the system and forcing input, providing accurate prediction of the dynamic response when the excitation history is unknown.

Towards an information geometric characterization/classification of complex systems. I. Use of generalized entropies

NASA Astrophysics Data System (ADS)

Ghikas, Demetris P. K.; Oikonomou, Fotios D.

2018-04-01

Using the generalized entropies which depend on two parameters we propose a set of quantitative characteristics derived from the Information Geometry based on these entropies. Our aim, at this stage, is to construct first some fundamental geometric objects which will be used in the development of our geometrical framework. We first establish the existence of a two-parameter family of probability distributions. Then using this family we derive the associated metric and we state a generalized Cramer-Rao Inequality. This gives a first two-parameter classification of complex systems. Finally computing the scalar curvature of the information manifold we obtain a further discrimination of the corresponding classes. Our analysis is based on the two-parameter family of generalized entropies of Hanel and Thurner (2011).

Operation of remote mobile sensors for security of drinking water distribution systems.

PubMed

Perelman, By Lina; Ostfeld, Avi

2013-09-01

The deployment of fixed online water quality sensors in water distribution systems has been recognized as one of the key components of contamination warning systems for securing public health. This study proposes to explore how the inclusion of mobile sensors for inline monitoring of various water quality parameters (e.g., residual chlorine, pH) can enhance water distribution system security. Mobile sensors equipped with sampling, sensing, data acquisition, wireless transmission and power generation systems are being designed, fabricated, and tested, and prototypes are expected to be released in the very near future. This study initiates the development of a theoretical framework for modeling mobile sensor movement in water distribution systems and integrating the sensory data collected from stationary and non-stationary sensor nodes to increase system security. The methodology is applied and demonstrated on two benchmark networks. Performance of different sensor network designs are compared for fixed and combined fixed and mobile sensor networks. Results indicate that complementing online sensor networks with inline monitoring can increase detection likelihood and decrease mean time to detection. Copyright © 2013 Elsevier Ltd. All rights reserved.

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

Costa, Mafalda T., E-mail: mafaldatcosta@gmail.com; Carolino, Elisabete, E-mail: lizcarolino@gmail.com; Oliveira, Teresa A., E-mail: teresa.oliveira@uab.pt

In water supply systems with distribution networkthe most critical aspects of control and Monitoring of water quality, which generates crises system, are the effects of cross-contamination originated by the network typology. The classics of control of quality systems through the application of Shewhart charts are generally difficult to manage in real time due to the high number of charts that must be completed and evaluated. As an alternative to the traditional control systems with Shewhart charts, this study aimed to apply a simplified methodology of a monitoring plan quality parameters in a drinking water distribution, by applying Hotelling’s T{sup 2}more » charts and supplemented with Shewhart charts with Bonferroni limits system, whenever instabilities with processes were detected.« less

Optimization of the structural and control system for LSS with reduced-order model

NASA Technical Reports Server (NTRS)

Khot, N. S.

1989-01-01

The objective is the simultaneous design of the structural and control system for space structures. The minimum weight of the structure is the objective function, and the constraints are placed on the closed loop distribution of the frequencies and the damping parameters. The controls approach used is linear quadratic regulator with constant feedback. A reduced-order control system is used. The effect of uncontrolled modes is taken into consideration by the model error sensitivity suppression (MESS) technique which modified the weighting parameters for the control forces. For illustration, an ACOSS-FOUR structure is designed for a different number of controlled modes with specified values for the closed loop damping parameters and frequencies. The dynamic response of the optimum designs for an initial disturbance is compared.

Estimation of Power Consumption in the Circular Sawing of Stone Based on Tangential Force Distribution

NASA Astrophysics Data System (ADS)

Huang, Guoqin; Zhang, Meiqin; Huang, Hui; Guo, Hua; Xu, Xipeng

2018-04-01

Circular sawing is an important method for the processing of natural stone. The ability to predict sawing power is important in the optimisation, monitoring and control of the sawing process. In this paper, a predictive model (PFD) of sawing power, which is based on the tangential force distribution at the sawing contact zone, was proposed, experimentally validated and modified. With regard to the influence of sawing speed on tangential force distribution, the modified PFD (MPFD) performed with high predictive accuracy across a wide range of sawing parameters, including sawing speed. The mean maximum absolute error rate was within 6.78%, and the maximum absolute error rate was within 11.7%. The practicability of predicting sawing power by the MPFD with few initial experimental samples was proved in case studies. On the premise of high sample measurement accuracy, only two samples are required for a fixed sawing speed. The feasibility of applying the MPFD to optimise sawing parameters while lowering the energy consumption of the sawing system was validated. The case study shows that energy use was reduced 28% by optimising the sawing parameters. The MPFD model can be used to predict sawing power, optimise sawing parameters and control energy.

Bayesian analysis of physiologically based toxicokinetic and toxicodynamic models.

PubMed

Hack, C Eric

2006-04-17

Physiologically based toxicokinetic (PBTK) and toxicodynamic (TD) models of bromate in animals and humans would improve our ability to accurately estimate the toxic doses in humans based on available animal studies. These mathematical models are often highly parameterized and must be calibrated in order for the model predictions of internal dose to adequately fit the experimentally measured doses. Highly parameterized models are difficult to calibrate and it is difficult to obtain accurate estimates of uncertainty or variability in model parameters with commonly used frequentist calibration methods, such as maximum likelihood estimation (MLE) or least squared error approaches. The Bayesian approach called Markov chain Monte Carlo (MCMC) analysis can be used to successfully calibrate these complex models. Prior knowledge about the biological system and associated model parameters is easily incorporated in this approach in the form of prior parameter distributions, and the distributions are refined or updated using experimental data to generate posterior distributions of parameter estimates. The goal of this paper is to give the non-mathematician a brief description of the Bayesian approach and Markov chain Monte Carlo analysis, how this technique is used in risk assessment, and the issues associated with this approach.

Static shape control for flexible structures

NASA Technical Reports Server (NTRS)

Rodriguez, G.; Scheid, R. E., Jr.

1986-01-01

An integrated methodology is described for defining static shape control laws for large flexible structures. The techniques include modeling, identifying and estimating the control laws of distributed systems characterized in terms of infinite dimensional state and parameter spaces. The models are expressed as interconnected elliptic partial differential equations governing a range of static loads, with the capability of analyzing electromagnetic fields around antenna systems. A second-order analysis is carried out for statistical errors, and model parameters are determined by maximizing an appropriate defined likelihood functional which adjusts the model to observational data. The parameter estimates are derived from the conditional mean of the observational data, resulting in a least squares superposition of shape functions obtained from the structural model.

Polarization effects on hard target calibration of lidar systems

NASA Technical Reports Server (NTRS)

Kavaya, Michael J.

1987-01-01

The theory of hard target calibration of lidar backscatter data, including laboratory measurements of the pertinent target reflectance parameters, is extended to include the effects of polarization of the transmitted and received laser radiation. The bidirectional reflectance-distribution function model of reflectance is expanded to a 4 x 4 matrix allowing Mueller matrix and Stokes vector calculus to be employed. Target reflectance parameters for calibration of lidar backscatter data are derived for various lidar system polarization configurations from integrating sphere and monostatic reflectometer measurements. It is found that correct modeling of polarization effects is mandatory for accurate calibration of hard target reflectance parameters and, therefore, for accurate calibration of lidar backscatter data.

Review of current status of smart structures and integrated systems

NASA Astrophysics Data System (ADS)

Chopra, Inderjit

1996-05-01

A smart structure involves distributed actuators and sensors, and one or more microprocessors that analyze the responses from the sensors and use distributed-parameter control theory to command the actuators to apply localized strains to minimize system response. A smart structure has the capability to respond to a changing external environment (such as loads or shape change) as well as to a changing internal environment (such as damage or failure). It incorporates smart actuators that allow the alteration of system characteristics (such as stiffness or damping) as well as of system response (such as strain or shape) in a controlled manner. Many types of actuators and sensors are being considered, such as piezoelectric materials, shape memory alloys, electrostrictive materials, magnetostrictive materials, electro- rheological fluids and fiber optics. These can be integrated with main load-carrying structures by surface bonding or embedding without causing any significant changes in the mass or structural stiffness of the system. Numerous applications of smart structures technology to various physical systems are evolving to actively control vibration, noise, aeroelastic stability, damping, shape and stress distribution. Applications range from space systems, fixed-wing and rotary-wing aircraft, automotive, civil structures and machine tools. Much of the early development of smart structures methodology was driven by space applications such as vibration and shape control of large flexible space structures, but now wider applications are envisaged for aeronautical and other systems. Embedded or surface-bonded smart actuators on an airplane wing or helicopter blade will induce alteration of twist/camber of airfoil (shape change), that in turn will cause variation of lift distribution and may help to control static and dynamic aeroelastic problems. Applications of smart structures technology to aerospace and other systems are expanding rapidly. Major barriers are: actuator stroke, reliable data base of smart material characteristics, non-availability of robust distributed parameter control strategies, and non-existent mathematical modeling of smart systems. The objective of this paper is to review the state-of-the-art of smart actuators and sensors and integrated systems and point out the needs for future research.

Optimal feedback control infinite dimensional parabolic evolution systems: Approximation techniques

NASA Technical Reports Server (NTRS)

Banks, H. T.; Wang, C.

1989-01-01

A general approximation framework is discussed for computation of optimal feedback controls in linear quadratic regular problems for nonautonomous parabolic distributed parameter systems. This is done in the context of a theoretical framework using general evolution systems in infinite dimensional Hilbert spaces. Conditions are discussed for preservation under approximation of stabilizability and detectability hypotheses on the infinite dimensional system. The special case of periodic systems is also treated.

Theory of a general class of dissipative processes.

NASA Technical Reports Server (NTRS)

Hale, J. K.; Lasalle, J. P.; Slemrod, M.

1972-01-01

Development of a theory of periodic processes that is of sufficient generality for being applied to systems defined by partial differential equations (distributed parameter systems) and functional differential equations of the retarded and neutral type (hereditary systems), as well as to systems arising in the theory of elasticity. In particular, the attempt is made to develop a meaningful general theory of dissipative periodic systems with a wide range of applications.

Pedestrian simulation and distribution in urban space based on visibility analysis and agent simulation

NASA Astrophysics Data System (ADS)

Ying, Shen; Li, Lin; Gao, Yurong

2009-10-01

Spatial visibility analysis is the important direction of pedestrian behaviors because our visual conception in space is the straight method to get environment information and navigate your actions. Based on the agent modeling and up-tobottom method, the paper develop the framework about the analysis of the pedestrian flow depended on visibility. We use viewshed in visibility analysis and impose the parameters on agent simulation to direct their motion in urban space. We analyze the pedestrian behaviors in micro-scale and macro-scale of urban open space. The individual agent use visual affordance to determine his direction of motion in micro-scale urban street on district. And we compare the distribution of pedestrian flow with configuration in macro-scale urban environment, and mine the relationship between the pedestrian flow and distribution of urban facilities and urban function. The paper first computes the visibility situations at the vantage point in urban open space, such as street network, quantify the visibility parameters. The multiple agents use visibility parameters to decide their direction of motion, and finally pedestrian flow reach to a stable state in urban environment through the simulation of multiple agent system. The paper compare the morphology of visibility parameters and pedestrian distribution with urban function and facilities layout to confirm the consistence between them, which can be used to make decision support in urban design.

Deceit: A flexible distributed file system

NASA Technical Reports Server (NTRS)

Siegel, Alex; Birman, Kenneth; Marzullo, Keith

1989-01-01

Deceit, a distributed file system (DFS) being developed at Cornell, focuses on flexible file semantics in relation to efficiency, scalability, and reliability. Deceit servers are interchangeable and collectively provide the illusion of a single, large server machine to any clients of the Deceit service. Non-volatile replicas of each file are stored on a subset of the file servers. The user is able to set parameters on a file to achieve different levels of availability, performance, and one-copy serializability. Deceit also supports a file version control mechanism. In contrast with many recent DFS efforts, Deceit can behave like a plain Sun Network File System (NFS) server and can be used by any NFS client without modifying any client software. The current Deceit prototype uses the ISIS Distributed Programming Environment for all communication and process group management, an approach that reduces system complexity and increases system robustness.

Fast-Response electric drives of Mechanical Engineering objects

NASA Astrophysics Data System (ADS)

Doykina, L. A.; Bukhanov, S. S.; Gryzlov, A. A.

2018-03-01

The article gives a solution to the problem of increasing the speed in the electrical drives of machine-building enterprises due to the application of a structure with ISC control. In this case, it is possible to get rid of the speed sensors. It is noted that in this case no circulating pulsations are applied to the input of the control system, caused by a non-identical interface between the sensor and the shaft of the operating mechanism. For detailed modeling, a mathematical model of an electric drive with distributed parameters was proposed. The calculation of such system was carried out by the finite element method. Taking into account the distributed characteristic of the system parameters allowed one to take into account the discrete nature of the electric machine’s work. The simulation results showed that the response time in the control circuit is estimated at a time constant of 0.0015, which is about twice as fast as in traditional vector control schemes.

Generic emergence of power law distributions and Lévy-Stable intermittent fluctuations in discrete logistic systems

NASA Astrophysics Data System (ADS)

Biham, Ofer; Malcai, Ofer; Levy, Moshe; Solomon, Sorin

1998-08-01

The dynamics of generic stochastic Lotka-Volterra (discrete logistic) systems of the form wi(t+1)=λ(t)wi(t)+aw¯(t)-bwi(t)w¯(t) is studied by computer simulations. The variables wi, i=1,...,N, are the individual system components and w¯(t)=(1/N)∑iwi(t) is their average. The parameters a and b are constants, while λ(t) is randomly chosen at each time step from a given distribution. Models of this type describe the temporal evolution of a large variety of systems such as stock markets and city populations. These systems are characterized by a large number of interacting objects and the dynamics is dominated by multiplicative processes. The instantaneous probability distribution P(w,t) of the system components wi turns out to fulfill a Pareto power law P(w,t)~w-1-α. The time evolution of w¯(t) presents intermittent fluctuations parametrized by a Lévy-stable distribution with the same index α, showing an intricate relation between the distribution of the wi's at a given time and the temporal fluctuations of their average.

Centralized versus distributed propulsion

NASA Technical Reports Server (NTRS)

Clark, J. P.

1982-01-01

The functions and requirements of auxiliary propulsion systems are reviewed. None of the three major tasks (attitude control, stationkeeping, and shape control) can be performed by a collection of thrusters at a single central location. If a centralized system is defined as a collection of separated clusters, made up of the minimum number of propulsion units, then such a system can provide attitude control and stationkeeping for most vehicles. A distributed propulsion system is characterized by more numerous propulsion units in a regularly distributed arrangement. Various proposed large space systems are reviewed and it is concluded that centralized auxiliary propulsion is best suited to vehicles with a relatively rigid core. These vehicles may carry a number of flexible or movable appendages. A second group, consisting of one or more large flexible flat plates, may need distributed propulsion for shape control. There is a third group, consisting of vehicles built up from multiple shuttle launches, which may be forced into a distributed system because of the need to add additional propulsion units as the vehicles grow. The effects of distributed propulsion on a beam-like structure were examined. The deflection of the structure under both translational and rotational thrusts is shown as a function of the number of equally spaced thrusters. When two thrusters only are used it is shown that location is an important parameter. The possibility of using distributed propulsion to achieve minimum overall system weight is also examined. Finally, an examination of the active damping by distributed propulsion is described.

Nonlinear dynamic analysis of cantilevered piezoelectric energy harvesters under simultaneous parametric and external excitations

NASA Astrophysics Data System (ADS)

Fang, Fei; Xia, Guanghui; Wang, Jianguo

2018-02-01

The nonlinear dynamics of cantilevered piezoelectric beams is investigated under simultaneous parametric and external excitations. The beam is composed of a substrate and two piezoelectric layers and assumed as an Euler-Bernoulli model with inextensible deformation. A nonlinear distributed parameter model of cantilevered piezoelectric energy harvesters is proposed using the generalized Hamilton's principle. The proposed model includes geometric and inertia nonlinearity, but neglects the material nonlinearity. Using the Galerkin decomposition method and harmonic balance method, analytical expressions of the frequency-response curves are presented when the first bending mode of the beam plays a dominant role. Using these expressions, we investigate the effects of the damping, load resistance, electromechanical coupling, and excitation amplitude on the frequency-response curves. We also study the difference between the nonlinear lumped-parameter and distributed-parameter model for predicting the performance of the energy harvesting system. Only in the case of parametric excitation, we demonstrate that the energy harvesting system has an initiation excitation threshold below which no energy can be harvested. We also illustrate that the damping and load resistance affect the initiation excitation threshold.

Nonlinear dynamic analysis of cantilevered piezoelectric energy harvesters under simultaneous parametric and external excitations

NASA Astrophysics Data System (ADS)

Fang, Fei; Xia, Guanghui; Wang, Jianguo

2018-06-01

The nonlinear dynamics of cantilevered piezoelectric beams is investigated under simultaneous parametric and external excitations. The beam is composed of a substrate and two piezoelectric layers and assumed as an Euler-Bernoulli model with inextensible deformation. A nonlinear distributed parameter model of cantilevered piezoelectric energy harvesters is proposed using the generalized Hamilton's principle. The proposed model includes geometric and inertia nonlinearity, but neglects the material nonlinearity. Using the Galerkin decomposition method and harmonic balance method, analytical expressions of the frequency-response curves are presented when the first bending mode of the beam plays a dominant role. Using these expressions, we investigate the effects of the damping, load resistance, electromechanical coupling, and excitation amplitude on the frequency-response curves. We also study the difference between the nonlinear lumped-parameter and distributed-parameter model for predicting the performance of the energy harvesting system. Only in the case of parametric excitation, we demonstrate that the energy harvesting system has an initiation excitation threshold below which no energy can be harvested. We also illustrate that the damping and load resistance affect the initiation excitation threshold.

Adaption of the LHC cold mass cooling system to the requirements of the Future Circular Collider (FCC)

NASA Astrophysics Data System (ADS)

Kotnig, C.; Tavian, L.; Brenn, G.

2017-12-01

The cooling of the superconducting magnet cold masses with superfluid helium (He II) is a well-established concept successfully in operation for years in the LHC. Consequently, its application for the cooling of FCC magnets is an obvious option. The 12-kW heat loads distributed over 10-km long sectors not only require an adaption of the magnet bayonet heat exchangers but also present new challenges to the cryogenic plants, the distribution system and the control strategy. This paper recalls the basic LHC cooling concept with superfluid helium and defines the main parameters for the adaption to the FCC requirements. Pressure drop and hydrostatic head are developed in the distribution and pumping systems; their impact on the magnet temperature profile and the corresponding cooling efficiency is presented and compared for different distribution and pumping schemes.

Simultaneous classical communication and quantum key distribution using continuous variables*

NASA Astrophysics Data System (ADS)

Qi, Bing

2016-10-01

Presently, classical optical communication systems employing strong laser pulses and quantum key distribution (QKD) systems working at single-photon levels are very different communication modalities. Dedicated devices are commonly required to implement QKD. In this paper, we propose a scheme which allows classical communication and QKD to be implemented simultaneously using the same communication infrastructure. More specially, we propose a coherent communication scheme where both the bits for classical communication and the Gaussian distributed random numbers for QKD are encoded on the same weak coherent pulse and decoded by the same coherent receiver. Simulation results based on practical system parameters show that both deterministic classical communication with a bit error rate of 10-9 and secure key distribution could be achieved over tens of kilometers of single-mode fibers. It is conceivable that in the future coherent optical communication network, QKD will be operated in the background of classical communication at a minimal cost.

Model‐based analysis of the influence of catchment properties on hydrologic partitioning across five mountain headwater subcatchments

PubMed Central

Wagener, Thorsten; McGlynn, Brian

2015-01-01

Abstract Ungauged headwater basins are an abundant part of the river network, but dominant influences on headwater hydrologic response remain difficult to predict. To address this gap, we investigated the ability of a physically based watershed model (the Distributed Hydrology‐Soil‐Vegetation Model) to represent controls on metrics of hydrologic partitioning across five adjacent headwater subcatchments. The five study subcatchments, located in Tenderfoot Creek Experimental Forest in central Montana, have similar climate but variable topography and vegetation distribution. This facilitated a comparative hydrology approach to interpret how parameters that influence partitioning, detected via global sensitivity analysis, differ across catchments. Model parameters were constrained a priori using existing regional information and expert knowledge. Influential parameters were compared to perceptions of catchment functioning and its variability across subcatchments. Despite between‐catchment differences in topography and vegetation, hydrologic partitioning across all metrics and all subcatchments was sensitive to a similar subset of snow, vegetation, and soil parameters. Results also highlighted one subcatchment with low certainty in parameter sensitivity, indicating that the model poorly represented some complexities in this subcatchment likely because an important process is missing or poorly characterized in the mechanistic model. For use in other basins, this method can assess parameter sensitivities as a function of the specific ungauged system to which it is applied. Overall, this approach can be employed to identify dominant modeled controls on catchment response and their agreement with system understanding. PMID:27642197

Numerical and machine learning simulation of parametric distributions of groundwater residence time in streams and wells

NASA Astrophysics Data System (ADS)

Starn, J. J.; Belitz, K.; Carlson, C.

2017-12-01

Groundwater residence-time distributions (RTDs) are critical for assessing susceptibility of water resources to contamination. This novel approach for estimating regional RTDs was to first simulate groundwater flow using existing regional digital data sets in 13 intermediate size watersheds (each an average of 7,000 square kilometers) that are representative of a wide range of glacial systems. RTDs were simulated with particle tracking. We refer to these models as "general models" because they are based on regional, as opposed to site-specific, digital data. Parametric RTDs were created from particle RTDs by fitting 1- and 2-component Weibull, gamma, and inverse Gaussian distributions, thus reducing a large number of particle travel times to 3 to 7 parameters (shape, location, and scale for each component plus a mixing fraction) for each modeled area. The scale parameter of these distributions is related to the mean exponential age; the shape parameter controls departure from the ideal exponential distribution and is partly a function of interaction with bedrock and with drainage density. Given the flexible shape and mathematical similarity of these distributions, any of them are potentially a good fit to particle RTDs. The 1-component gamma distribution provided a good fit to basin-wide particle RTDs. RTDs at monitoring wells and streams often have more complicated shapes than basin-wide RTDs, caused in part by heterogeneity in the model, and generally require 2-component distributions. A machine learning model was trained on the RTD parameters using features derived from regionally available watershed characteristics such as recharge rate, material thickness, and stream density. RTDs appeared to vary systematically across the landscape in relation to watershed features. This relation was used to produce maps of useful metrics with respect to risk-based thresholds, such as the time to first exceedance, time to maximum concentration, time above the threshold (exposure time), and the time until last exceedance; thus, the parameters of groundwater residence time are measures of the intrinsic susceptibility of groundwater to contamination.

A physical parameter method for the design of broad-band X-ray imaging systems to do coronal plasma diagnostics

NASA Technical Reports Server (NTRS)

Kahler, S.; Krieger, A. S.

1978-01-01

The technique commonly used for the analysis of data from broad-band X-ray imaging systems for plasma diagnostics is the filter ratio method. This requires the use of two or more broad-band filters to derive temperatures and line-of-sight emission integrals or emission measure distributions as a function of temperature. Here an alternative analytical approach is proposed in which the temperature response of the imaging system is matched to the physical parameter being investigated. The temperature response of a system designed to measure the total radiated power along the line of sight of any coronal structure is calculated. Other examples are discussed.

Numerical Simulation of Measurements during the Reactor Physical Startup at Unit 3 of Rostov NPP

NASA Astrophysics Data System (ADS)

Tereshonok, V. A.; Kryakvin, L. V.; Pitilimov, V. A.; Karpov, S. A.; Kulikov, V. I.; Zhylmaganbetov, N. M.; Kavun, O. Yu.; Popykin, A. I.; Shevchenko, R. A.; Shevchenko, S. A.; Semenova, T. V.

2017-12-01

The results of numerical calculations and measurements of some reactor parameters during the physical startup tests at unit 3 of Rostov NPP are presented. The following parameters are considered: the critical boron acid concentration and the currents from ionization chambers (IC) during the scram system efficiency evaluation. The scram system efficiency was determined using the inverse point kinetics equation with the measured and simulated IC currents. The results of steady-state calculations of relative power distribution and efficiency of the scram system and separate groups of control rods of the control and protection system are also presented. The calculations are performed using several codes, including precision ones.

Channel-parameter estimation for satellite-to-submarine continuous-variable quantum key distribution

NASA Astrophysics Data System (ADS)

Guo, Ying; Xie, Cailang; Huang, Peng; Li, Jiawei; Zhang, Ling; Huang, Duan; Zeng, Guihua

2018-05-01

This paper deals with a channel-parameter estimation for continuous-variable quantum key distribution (CV-QKD) over a satellite-to-submarine link. In particular, we focus on the channel transmittances and the excess noise which are affected by atmospheric turbulence, surface roughness, zenith angle of the satellite, wind speed, submarine depth, etc. The estimation method is based on proposed algorithms and is applied to low-Earth orbits using the Monte Carlo approach. For light at 550 nm with a repetition frequency of 1 MHz, the effects of the estimated parameters on the performance of the CV-QKD system are assessed by a simulation by comparing the secret key bit rate in the daytime and at night. Our results show the feasibility of satellite-to-submarine CV-QKD, providing an unconditionally secure approach to achieve global networks for underwater communications.

Performance prediction evaluation of ceramic materials in point-focusing solar receivers

NASA Technical Reports Server (NTRS)

Ewing, J.; Zwissler, J.

1979-01-01

A performance prediction was adapted to evaluate the use of ceramic materials in solar receivers for point focusing distributed applications. System requirements were determined including the receiver operating environment and system operating parameters for various engine types. Preliminary receiver designs were evolved from these system requirements. Specific receiver designs were then evaluated to determine material functional requirements.

Comparative evaluation of distributed-collector solar thermal electric power plants

NASA Technical Reports Server (NTRS)

Fujita, T.; El Gabalawi, N.; Herrera, G. G.; Caputo, R. S.

1978-01-01

Distributed-collector solar thermal-electric power plants are compared by projecting power plant economics of selected systems to the 1990-2000 timeframe. The approach taken is to evaluate the performance of the selected systems under the same weather conditions. Capital and operational costs are estimated for each system. Energy costs are calculated for different plant sizes based on the plant performance and the corresponding capital and maintenance costs. Optimum systems are then determined as the systems with the minimum energy costs for a given load factor. The optimum system is comprised of the best combination of subsystems which give the minimum energy cost for every plant size. Sensitivity analysis is done around the optimum point for various plant parameters.

Characteristics of liver fibrosis with different etiologies using a fully quantitative fibrosis assessment tool.

PubMed

Wu, Q; Zhao, X; You, H

2017-05-18

This study aimed to test the diagnostic performance of a fully quantitative fibrosis assessment tool for liver fibrosis in patients with chronic hepatitis B (CHB), primary biliary cirrhosis (PBC) and non-alcoholic steatohepatitis (NASH). A total of 117 patients with liver fibrosis were included in this study, including 50 patients with CHB, 49 patients with PBC and 18 patients with NASH. All patients underwent liver biopsy (LB). Fibrosis stages were assessed by two experienced pathologists. Histopathological images of LB slices were processed by second harmonic generation (SHG)/two-photon excited fluorescence (TPEF) microscopy without staining, a system called qFibrosis (quantitative fibrosis) system. Altogether 101 quantitative features of the SHG/TPEF images were acquired. The parameters of aggregated collagen in portal, septal and fibrillar areas increased significantly with stages of liver fibrosis in PBC and CHB (P<0.05), but the same was not found for parameters of distributed collagen (P>0.05). There was a significant correlation between parameters of aggregated collagen in portal, septal and fibrillar areas and stages of liver fibrosis from CHB and PBC (P<0.05), but no correlation was found between the distributed collagen parameters and the stages of liver fibrosis from those patients (P>0.05). There was no significant correlation between NASH parameters and stages of fibrosis (P>0.05). For CHB and PBC patients, the highest correlation was between septal parameters and fibrosis stages, the second highest was between portal parameters and fibrosis stages and the lowest correlation was between fibrillar parameters and fibrosis stages. The correlation between the septal parameters of the PBC and stages is significantly higher than the parameters of the other two areas (P<0.05). The qFibrosis candidate parameters based on CHB were also applicable for quantitative analysis of liver fibrosis in PBC patients. Different parameters should be selected for liver fibrosis assessment in different stages of PBC compared with CHB.

Characteristics of liver fibrosis with different etiologies using a fully quantitative fibrosis assessment tool

PubMed Central

Wu, Q.; Zhao, X.; You, H.

2017-01-01

This study aimed to test the diagnostic performance of a fully quantitative fibrosis assessment tool for liver fibrosis in patients with chronic hepatitis B (CHB), primary biliary cirrhosis (PBC) and non-alcoholic steatohepatitis (NASH). A total of 117 patients with liver fibrosis were included in this study, including 50 patients with CHB, 49 patients with PBC and 18 patients with NASH. All patients underwent liver biopsy (LB). Fibrosis stages were assessed by two experienced pathologists. Histopathological images of LB slices were processed by second harmonic generation (SHG)/two-photon excited fluorescence (TPEF) microscopy without staining, a system called qFibrosis (quantitative fibrosis) system. Altogether 101 quantitative features of the SHG/TPEF images were acquired. The parameters of aggregated collagen in portal, septal and fibrillar areas increased significantly with stages of liver fibrosis in PBC and CHB (P<0.05), but the same was not found for parameters of distributed collagen (P>0.05). There was a significant correlation between parameters of aggregated collagen in portal, septal and fibrillar areas and stages of liver fibrosis from CHB and PBC (P<0.05), but no correlation was found between the distributed collagen parameters and the stages of liver fibrosis from those patients (P>0.05). There was no significant correlation between NASH parameters and stages of fibrosis (P>0.05). For CHB and PBC patients, the highest correlation was between septal parameters and fibrosis stages, the second highest was between portal parameters and fibrosis stages and the lowest correlation was between fibrillar parameters and fibrosis stages. The correlation between the septal parameters of the PBC and stages is significantly higher than the parameters of the other two areas (P<0.05). The qFibrosis candidate parameters based on CHB were also applicable for quantitative analysis of liver fibrosis in PBC patients. Different parameters should be selected for liver fibrosis assessment in different stages of PBC compared with CHB. PMID:28538834

Army Selective Reenlistment Bonus Management System: Functional and User Documentation

DTIC Science & Technology

2005-06-01

Study Note 2005-04 Arlington, VA 22202-3926 12. DISTRIBUTION/AVAILABILITY STATEMENT Approved for public release; distribution is unlimited. 13...of the study, retention parameters that capture the financial incentive effects of the SRB reenlistment program were estimated for Army occupations...all possible outcomes in the Army SRB Data Utility. The Army SRB Program provides financial incentives for reenlistment that vary by occupational

Analysis of ground-motion simulation big data

NASA Astrophysics Data System (ADS)

Maeda, T.; Fujiwara, H.

2016-12-01

We developed a parallel distributed processing system which applies a big data analysis to the large-scale ground motion simulation data. The system uses ground-motion index values and earthquake scenario parameters as input. We used peak ground velocity value and velocity response spectra as the ground-motion index. The ground-motion index values are calculated from our simulation data. We used simulated long-period ground motion waveforms at about 80,000 meshes calculated by a three dimensional finite difference method based on 369 earthquake scenarios of a great earthquake in the Nankai Trough. These scenarios were constructed by considering the uncertainty of source model parameters such as source area, rupture starting point, asperity location, rupture velocity, fmax and slip function. We used these parameters as the earthquake scenario parameter. The system firstly carries out the clustering of the earthquake scenario in each mesh by the k-means method. The number of clusters is determined in advance using a hierarchical clustering by the Ward's method. The scenario clustering results are converted to the 1-D feature vector. The dimension of the feature vector is the number of scenario combination. If two scenarios belong to the same cluster the component of the feature vector is 1, and otherwise the component is 0. The feature vector shows a `response' of mesh to the assumed earthquake scenario group. Next, the system performs the clustering of the mesh by k-means method using the feature vector of each mesh previously obtained. Here the number of clusters is arbitrarily given. The clustering of scenarios and meshes are performed by parallel distributed processing with Hadoop and Spark, respectively. In this study, we divided the meshes into 20 clusters. The meshes in each cluster are geometrically concentrated. Thus this system can extract regions, in which the meshes have similar `response', as clusters. For each cluster, it is possible to determine particular scenario parameters which characterize the cluster. In other word, by utilizing this system, we can obtain critical scenario parameters of the ground-motion simulation for each evaluation point objectively. This research was supported by CREST, JST.

Conserved directed percolation: exact quasistationary distribution of small systems and Monte Carlo simulations

NASA Astrophysics Data System (ADS)

César Mansur Filho, Júlio; Dickman, Ronald

2011-05-01

We study symmetric sleepy random walkers, a model exhibiting an absorbing-state phase transition in the conserved directed percolation (CDP) universality class. Unlike most examples of this class studied previously, this model possesses a continuously variable control parameter, facilitating analysis of critical properties. We study the model using two complementary approaches: analysis of the numerically exact quasistationary (QS) probability distribution on rings of up to 22 sites, and Monte Carlo simulation of systems of up to 32 000 sites. The resulting estimates for critical exponents β, \\beta /\

Whirling and stability of flywheel systems, part I: Derivation of combined and lumped parameter models

NASA Astrophysics Data System (ADS)

Ramanujam, G.; Bert, C. W.

1983-06-01

The objective of this paper is to provide a theoretical foundation to predict many aspects of dynamic behavior of flywheel systems when spin-tested with a quill shaft support and driven by an air turbine. Theoretical analyses for the following are presented: (1) determination of natural frequencies (or for brevity critical speeds of various orders), (2) Routh-type stability analysis to determine the stability limits (i.e., the speed range within which small perturbations attenuate rather than cause catastrophic failure), and (3) forced whirling analysis to estimate the response of major components of the system to flywheel mass eccentricity and initial tilt. For the first and third kinds of analyses, two different mathematical models of the generic system are investigated. One is a seven-degree-of-freedom lumped parameter analysis, while the other is a combined distributed and lumped parameter analysis.

A phenomenological approach to study the effect of uniaxial anisotropy on the magnetization of ferromagnetic nanoparticles

NASA Astrophysics Data System (ADS)

Sánchez-Marín, N.; Cuchillo, A.; Knobel, M.; Vargas, P.

2018-04-01

We study the effect of the uniaxial anisotropy in a system of ideal, noninteracting ferromagnetic nanoparticles by means of a thermodynamical model. We show that the effect of the anisotropy can be easily assimilated in a temperature shift Ta∗, in analogy to what was proposed by Allia et al. (2001) in the case of interacting nanomagnets. The phenomenological anisotropic Ta∗ parameter can be negative, indicating an antiferromagnetic-like behavior, or positive, indicating a ferromagnetic-like character as seen in the inverse susceptibility behavior as a function of temperature. The study is done considering an easy axis distribution to take into account the anisotropy axis dispersion in real samples (texture). In the case of a volumetric uniform distribution of anisotropy axes, the net effect makes Ta∗ to vanish, and the magnetic susceptibility behaves like a conventional superparamagnetic system, whereas in the others a finite value is obtained for Ta∗ . When magnetic moment distribution is considered, the effect is to enhance the Ta∗ parameter, when the dispersion of the magnetic moments becomes wider.

Modeling and forecasting the distribution of Vibrio vulnificus in Chesapeake Bay

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

Jacobs, John M.; Rhodes, M.; Brown, C. W.

The aim is to construct statistical models to predict the presence, abundance and potential virulence of Vibrio vulnificus in surface waters. A variety of statistical techniques were used in concert to identify water quality parameters associated with V. vulnificus presence, abundance and virulence markers in the interest of developing strong predictive models for use in regional oceanographic modeling systems. A suite of models are provided to represent the best model fit and alternatives using environmental variables that allow them to be put to immediate use in current ecological forecasting efforts. Conclusions: Environmental parameters such as temperature, salinity and turbidity aremore » capable of accurately predicting abundance and distribution of V. vulnificus in Chesapeake Bay. Forcing these empirical models with output from ocean modeling systems allows for spatially explicit forecasts for up to 48 h in the future. This study uses one of the largest data sets compiled to model Vibrio in an estuary, enhances our understanding of environmental correlates with abundance, distribution and presence of potentially virulent strains and offers a method to forecast these pathogens that may be replicated in other regions.« less

A glacier runoff extension to the Precipitation Runoff Modeling System

Treesearch

A. E. Van Beusekom; R. J. Viger

2016-01-01

A module to simulate glacier runoff, PRMSglacier, was added to PRMS (Precipitation Runoff Modeling System), a distributed-parameter, physical-process hydrological simulation code. The extension does not require extensive on-glacier measurements or computational expense but still relies on physical principles over empirical relations as much as is feasible while...

Relationships between digital signal processing and control and estimation theory

NASA Technical Reports Server (NTRS)

Willsky, A. S.

1978-01-01

Research areas associated with digital signal processing and control and estimation theory are identified. Particular attention is given to image processing, system identification problems (parameter identification, linear prediction, least squares, Kalman filtering), stability analyses (the use of the Liapunov theory, frequency domain criteria, passivity), and multiparameter systems, distributed processes, and random fields.

The WS transform for the Kuramoto model with distributed amplitudes, phase lag and time delay

NASA Astrophysics Data System (ADS)

Lohe, M. A.

2017-12-01

We apply the Watanabe-Strogatz (WS) transform to a generalized Kuramoto model with distributed parameters describing the amplitude of oscillation, phase lag, and time delay at each node of the system. The model has global coupling and identical frequencies, but allows for repulsive interactions at arbitrary nodes leading to conformist-contrarian phenomena together with variable amplitude and time-delay effects. We show how to determine the initial values of the WS system for any initial conditions for the Kuramoto system, and investigate the asymptotic behaviour of the WS variables. For the case of zero time delay the possible asymptotic configurations are determined by the sign of a single parameter μ which measures whether or not the attractive nodes dominate the repulsive nodes. If μ>0 the system completely synchronizes from general initial conditions, whereas if μ<0 one of two types of phase-locked synchronization occurs, depending on the initial values, while for μ=0 periodic solutions can occur. For the case of arbitrary non-uniform time delays we derive a stability condition for completely synchronized solutions.

Active vibration mitigation of distributed parameter, smart-type structures using Pseudo-Feedback Optimal Control (PFOC)

NASA Technical Reports Server (NTRS)

Patten, W. N.; Robertshaw, H. H.; Pierpont, D.; Wynn, R. H.

1989-01-01

A new, near-optimal feedback control technique is introduced that is shown to provide excellent vibration attenuation for those distributed parameter systems that are often encountered in the areas of aeroservoelasticity and large space systems. The technique relies on a novel solution methodology for the classical optimal control problem. Specifically, the quadratic regulator control problem for a flexible vibrating structure is first cast in a weak functional form that admits an approximate solution. The necessary conditions (first-order) are then solved via a time finite-element method. The procedure produces a low dimensional, algebraic parameterization of the optimal control problem that provides a rigorous basis for a discrete controller with a first-order like hold output. Simulation has shown that the algorithm can successfully control a wide variety of plant forms including multi-input/multi-output systems and systems exhibiting significant nonlinearities. In order to firmly establish the efficacy of the algorithm, a laboratory control experiment was implemented to provide planar (bending) vibration attenuation of a highly flexible beam (with a first clamped-free mode of approximately 0.5 Hz).

Automated crystallographic system for high-throughput protein structure determination.

PubMed

Brunzelle, Joseph S; Shafaee, Padram; Yang, Xiaojing; Weigand, Steve; Ren, Zhong; Anderson, Wayne F

2003-07-01

High-throughput structural genomic efforts require software that is highly automated, distributive and requires minimal user intervention to determine protein structures. Preliminary experiments were set up to test whether automated scripts could utilize a minimum set of input parameters and produce a set of initial protein coordinates. From this starting point, a highly distributive system was developed that could determine macromolecular structures at a high throughput rate, warehouse and harvest the associated data. The system uses a web interface to obtain input data and display results. It utilizes a relational database to store the initial data needed to start the structure-determination process as well as generated data. A distributive program interface administers the crystallographic programs which determine protein structures. Using a test set of 19 protein targets, 79% were determined automatically.

Fusion cross sections for reactions involving medium and heavy nucleus-nucleus systems

NASA Astrophysics Data System (ADS)

Atta, Debasis; Basu, D. N.

2014-12-01

Existing data on near-barrier fusion excitation functions of medium and heavy nucleus-nucleus systems have been analyzed by using a simple diffused-barrier formula derived assuming the Gaussian shape of the barrier-height distributions. The fusion cross section is obtained by folding the Gaussian barrier distribution with the classical expression for the fusion cross section for a fixed barrier. The energy dependence of the fusion cross section, thus obtained, provides good description to the existing data on near-barrier fusion and capture excitation functions for medium and heavy nucleus-nucleus systems. The theoretical values for the parameters of the barrier distribution are estimated which can be used for fusion or capture cross-section predictions that are especially important for planning experiments for synthesizing new superheavy elements.

Applications of computer algebra to distributed parameter systems

NASA Technical Reports Server (NTRS)

Storch, Joel A.

1993-01-01

In the analysis of vibrations of continuous elastic systems, one often encounters complicated transcendental equations with roots directly related to the system's natural frequencies. Typically, these equations contain system parameters whose values must be specified before a numerical solution can be obtained. The present paper presents a method whereby the fundamental frequency can be obtained in analytical form to any desired degree of accuracy. The method is based upon truncation of rapidly converging series involving inverse powers of the system natural frequencies. A straightforward method to developing these series and summing them in closed form is presented. It is demonstrated how Computer Algebra can be exploited to perform the intricate analytical procedures which otherwise would render the technique difficult to apply in practice. We illustrate the method by developing two analytical approximations to the fundamental frequency of a vibrating cantilever carrying a rigid tip body. The results are compared to the numerical solution of the exact (transcendental) frequency equation over a range of system parameters.

Extrusion and rheology of fine particulate ceramic pastes

NASA Astrophysics Data System (ADS)

Mazzeo, Fred Anthony

A rheological study was conducted on an extruded blend of two alumina powders, Alcoa A-3500-SG and Reynolds ERC. These extruded blends were mixed in four compositions, varying in distribution modulus. This work focuses on the interaction of the composition components, mainly particle size distribution and amount of water at a constant binder amount. The rheological parameters of extruded pastes, Sigma, Tau, alpha and beta, were determined by using capillary rheometry modeling by the methodology set forth by Benbow and Bridgwater. This methodology makes use of capillary rheometer to determine extrusion parameters, which describe the flow behavior of a paste. The parameter values are indirectly determined by extrapolating high shear rate information obtained by the extrusion process. A goal of this research was to determine fundamental rheological properties directly from fundamental rheological equations of state. This was accomplished by assessing the material properties by using a dynamic stress rheometer. The rheological parameters used in this study to characterize the paste are elastic modulus, viscosity, tan delta, and relaxation time. This technique approaches a step closer in understanding the microstructural influence on flow behavior of a paste. This method directly determines rheological properties by using linear viscoelastic theory, giving a quantitative analysis of material properties. A strong correlation between the elastic modulus and sigma, and viscosity and alpha is shown to exist, indicating a relationship between these two techniques. Predictive process control methodology, based on particle packing modeling, quantitatively determined structural parameters useful in evaluating a composition. The determined parameters are: distribution modulus, interparticle separation distance, porosity, and particle crowding index, which are important to understand the extrudates packed state. A connection between the physical structure of the extrudate and its rheological behavior, can lead to a better understanding of what conditions and parameters are necessary to characterize the extrusion process. This study shows how particle packing and particle size influences the rheological behavior of the paste. Results showed that an optimally packed system was found to occur at a distribution modulus of 0.51. This system was determined both experimentally and quantitatively to exhibit the lowest porosity at any water content. The 0.51 system required a lower amount of water to extrude and the parameters of both rheological techniques agreed well, in which all parameters are influenced by the packing state of the paste, and a consistent trend was generally found. The capillary rheometry results can be explained by the strong interaction of particles that occurs at high shear rates. The dynamic stress rheometer results can be explained by the particle packing characteristics, interparticle separation distance and particle-crowding index, and the capillary forces between particles. The excess amount of liquid that is present in the structure decreases the role of the capillary attraction between particles and an increase in the particle size role on the rheological behavior of the pastes occurs.

Estimation of beam material random field properties via sensitivity-based model updating using experimental frequency response functions

NASA Astrophysics Data System (ADS)

Machado, M. R.; Adhikari, S.; Dos Santos, J. M. C.; Arruda, J. R. F.

2018-03-01

Structural parameter estimation is affected not only by measurement noise but also by unknown uncertainties which are present in the system. Deterministic structural model updating methods minimise the difference between experimentally measured data and computational prediction. Sensitivity-based methods are very efficient in solving structural model updating problems. Material and geometrical parameters of the structure such as Poisson's ratio, Young's modulus, mass density, modal damping, etc. are usually considered deterministic and homogeneous. In this paper, the distributed and non-homogeneous characteristics of these parameters are considered in the model updating. The parameters are taken as spatially correlated random fields and are expanded in a spectral Karhunen-Loève (KL) decomposition. Using the KL expansion, the spectral dynamic stiffness matrix of the beam is expanded as a series in terms of discretized parameters, which can be estimated using sensitivity-based model updating techniques. Numerical and experimental tests involving a beam with distributed bending rigidity and mass density are used to verify the proposed method. This extension of standard model updating procedures can enhance the dynamic description of structural dynamic models.

Kinetic analysis of single molecule FRET transitions without trajectories

NASA Astrophysics Data System (ADS)

Schrangl, Lukas; Göhring, Janett; Schütz, Gerhard J.

2018-03-01

Single molecule Förster resonance energy transfer (smFRET) is a popular tool to study biological systems that undergo topological transitions on the nanometer scale. smFRET experiments typically require recording of long smFRET trajectories and subsequent statistical analysis to extract parameters such as the states' lifetimes. Alternatively, analysis of probability distributions exploits the shapes of smFRET distributions at well chosen exposure times and hence works without the acquisition of time traces. Here, we describe a variant that utilizes statistical tests to compare experimental datasets with Monte Carlo simulations. For a given model, parameters are varied to cover the full realistic parameter space. As output, the method yields p-values which quantify the likelihood for each parameter setting to be consistent with the experimental data. The method provides suitable results even if the actual lifetimes differ by an order of magnitude. We also demonstrated the robustness of the method to inaccurately determine input parameters. As proof of concept, the new method was applied to the determination of transition rate constants for Holliday junctions.

[Subjective Gait Stability in the Elderly].

PubMed

Hirsch, Theresa; Lampe, Jasmin; Michalk, Katrin; Röder, Lotte; Munsch, Karoline; Marquardt, Jonas

2017-07-10

It can be assumed that the feeling of gait stability or gait instability in the elderly may be independent of a possible fear of falling or a history of falling when walking. Up to now, there has been a lack of spatiotemporal gait parameters for older people who subjectively feel secure when walking. The aim of the study is to analyse the distribution of various gait parameters for older people who subjectively feel secure when walking. In a cross-sectional study, the gait parameters stride time, step time, stride length, step length, double support, single support, and walking speed were measured using a Vicon three-dimensional motion capture system (Plug-In Gait Lower-Body Marker Set) in 31 healthy people aged 65 years and older (mean age 72 ± 3.54 years) who subjectively feel secure when walking. There was a homogeneous distribution in the gait parameters examined, with no abnormalities. The mean values have a low variance with narrow confidence intervals. This study provides evidence that people who subjectively feel secure when walking demonstrate similarly objective gait parameters..

Effects of Distributed Generation on Overcurrent Relay Coordination and an Adaptive Protection Scheme

NASA Astrophysics Data System (ADS)

Ilik, Semih C.; Arsoy, Aysen B.

2017-07-01

Integration of distributed generation (DG) such as renewable energy sources to electrical network becomes more prevalent in recent years. Grid connection of DG has effects on load flow directions, voltage profile, short circuit power and especially protection selectivity. Applying traditional overcurrent protection scheme is inconvenient when system reliability and sustainability are considered. If a fault happens in DG connected network, short circuit contribution of DG, creates additional branch element feeding the fault current; compels to consider directional overcurrent (OC) protection scheme. Protection coordination might get lost for changing working conditions when DG sources are connected. Directional overcurrent relay parameters are determined for downstream and upstream relays when different combinations of DG connected singular or plural, on radial test system. With the help of proposed flow chart, relay parameters are updated and coordination between relays kept sustained for different working conditions in DigSILENT PowerFactory program.

CATS - A process-based model for turbulent turbidite systems at the reservoir scale

NASA Astrophysics Data System (ADS)

Teles, Vanessa; Chauveau, Benoît; Joseph, Philippe; Weill, Pierre; Maktouf, Fakher

2016-09-01

The Cellular Automata for Turbidite systems (CATS) model is intended to simulate the fine architecture and facies distribution of turbidite reservoirs with a multi-event and process-based approach. The main processes of low-density turbulent turbidity flow are modeled: downslope sediment-laden flow, entrainment of ambient water, erosion and deposition of several distinct lithologies. This numerical model, derived from (Salles, 2006; Salles et al., 2007), proposes a new approach based on the Rouse concentration profile to consider the flow capacity to carry the sediment load in suspension. In CATS, the flow distribution on a given topography is modeled with local rules between neighboring cells (cellular automata) based on potential and kinetic energy balance and diffusion concepts. Input parameters are the initial flow parameters and a 3D topography at depositional time. An overview of CATS capabilities in different contexts is presented and discussed.

Distributed Optimization

NASA Technical Reports Server (NTRS)

Macready, William; Wolpert, David

2005-01-01

We demonstrate a new framework for analyzing and controlling distributed systems, by solving constrained optimization problems with an algorithm based on that framework. The framework is ar. information-theoretic extension of conventional full-rationality game theory to allow bounded rational agents. The associated optimization algorithm is a game in which agents control the variables of the optimization problem. They do this by jointly minimizing a Lagrangian of (the probability distribution of) their joint state. The updating of the Lagrange parameters in that Lagrangian is a form of automated annealing, one that focuses the multi-agent system on the optimal pure strategy. We present computer experiments for the k-sat constraint satisfaction problem and for unconstrained minimization of NK functions.

Regional probability distribution of the annual reference evapotranspiration and its effective parameters in Iran

NASA Astrophysics Data System (ADS)

Khanmohammadi, Neda; Rezaie, Hossein; Montaseri, Majid; Behmanesh, Javad

2017-10-01

The reference evapotranspiration (ET0) plays an important role in water management plans in arid or semi-arid countries such as Iran. For this reason, the regional analysis of this parameter is important. But, ET0 process is affected by several meteorological parameters such as wind speed, solar radiation, temperature and relative humidity. Therefore, the effect of distribution type of effective meteorological variables on ET0 distribution was analyzed. For this purpose, the regional probability distribution of the annual ET0 and its effective parameters were selected. Used data in this research was recorded data at 30 synoptic stations of Iran during 1960-2014. Using the probability plot correlation coefficient (PPCC) test and the L-moment method, five common distributions were compared and the best distribution was selected. The results of PPCC test and L-moment diagram indicated that the Pearson type III distribution was the best probability distribution for fitting annual ET0 and its four effective parameters. The results of RMSE showed that the ability of the PPCC test and L-moment method for regional analysis of reference evapotranspiration and its effective parameters was similar. The results also showed that the distribution type of the parameters which affected ET0 values can affect the distribution of reference evapotranspiration.

Probabilistic Harmonic Analysis on Distributed Photovoltaic Integration Considering Typical Weather Scenarios

NASA Astrophysics Data System (ADS)

Bin, Che; Ruoying, Yu; Dongsheng, Dang; Xiangyan, Wang

2017-05-01

Distributed Generation (DG) integrating to the network would cause the harmonic pollution which would cause damages on electrical devices and affect the normal operation of power system. On the other hand, due to the randomness of the wind and solar irradiation, the output of DG is random, too, which leads to an uncertainty of the harmonic generated by the DG. Thus, probabilistic methods are needed to analyse the impacts of the DG integration. In this work we studied the harmonic voltage probabilistic distribution and the harmonic distortion in distributed network after the distributed photovoltaic (DPV) system integrating in different weather conditions, mainly the sunny day, cloudy day, rainy day and the snowy day. The probabilistic distribution function of the DPV output power in different typical weather conditions could be acquired via the parameter identification method of maximum likelihood estimation. The Monte-Carlo simulation method was adopted to calculate the probabilistic distribution of harmonic voltage content at different frequency orders as well as the harmonic distortion (THD) in typical weather conditions. The case study was based on the IEEE33 system and the results of harmonic voltage content probabilistic distribution as well as THD in typical weather conditions were compared.

Polarizable atomic multipole-based force field for DOPC and POPE membrane lipids

NASA Astrophysics Data System (ADS)

Chu, Huiying; Peng, Xiangda; Li, Yan; Zhang, Yuebin; Min, Hanyi; Li, Guohui

2018-04-01

A polarizable atomic multipole-based force field for the membrane bilayer models 1,2-dioleoyl-phosphocholine (DOPC) and 1-palmitoyl-2-oleoyl-phosphatidylethanolamine (POPE) has been developed. The force field adopts the same framework as the Atomic Multipole Optimized Energetics for Biomolecular Applications (AMOEBA) model, in which the charge distribution of each atom is represented by the permanent atomic monopole, dipole and quadrupole moments. Many-body polarization including the inter- and intra-molecular polarization is modelled in a consistent manner with distributed atomic polarizabilities. The van der Waals parameters were first transferred from existing AMOEBA parameters for small organic molecules and then optimised by fitting to ab initio intermolecular interaction energies between models and a water molecule. Molecular dynamics simulations of the two aqueous DOPC and POPE membrane bilayer systems, consisting of 72 model molecules, were then carried out to validate the force field parameters. Membrane width, area per lipid, volume per lipid, deuterium order parameters, electron density profile, etc. were consistent with experimental values.

Robust distributed control of spacecraft formation flying with adaptive network topology

NASA Astrophysics Data System (ADS)

Shasti, Behrouz; Alasty, Aria; Assadian, Nima

2017-07-01

In this study, the distributed six degree-of-freedom (6-DOF) coordinated control of spacecraft formation flying in low earth orbit (LEO) has been investigated. For this purpose, an accurate coupled translational and attitude relative dynamics model of the spacecraft with respect to the reference orbit (virtual leader) is presented by considering the most effective perturbation acceleration forces on LEO satellites, i.e. the second zonal harmonic and the atmospheric drag. Subsequently, the 6-DOF coordinated control of spacecraft in formation is studied. During the mission, the spacecraft communicate with each other through a switching network topology in which the weights of its graph Laplacian matrix change adaptively based on a distance-based connectivity function between neighboring agents. Because some of the dynamical system parameters such as spacecraft masses and moments of inertia may vary with time, an adaptive law is developed to estimate the parameter values during the mission. Furthermore, for the case that there is no knowledge of the unknown and time-varying parameters of the system, a robust controller has been developed. It is proved that the stability of the closed-loop system coupled with adaptation in network topology structure and optimality and robustness in control is guaranteed by the robust contraction analysis as an incremental stability method for multiple synchronized systems. The simulation results show the effectiveness of each control method in the presence of uncertainties and parameter variations. The adaptive and robust controllers show their superiority in reducing the state error integral as well as decreasing the control effort and settling time.

Failure probability under parameter uncertainty.

PubMed

Gerrard, R; Tsanakas, A

2011-05-01

In many problems of risk analysis, failure is equivalent to the event of a random risk factor exceeding a given threshold. Failure probabilities can be controlled if a decisionmaker is able to set the threshold at an appropriate level. This abstract situation applies, for example, to environmental risks with infrastructure controls; to supply chain risks with inventory controls; and to insurance solvency risks with capital controls. However, uncertainty around the distribution of the risk factor implies that parameter error will be present and the measures taken to control failure probabilities may not be effective. We show that parameter uncertainty increases the probability (understood as expected frequency) of failures. For a large class of loss distributions, arising from increasing transformations of location-scale families (including the log-normal, Weibull, and Pareto distributions), the article shows that failure probabilities can be exactly calculated, as they are independent of the true (but unknown) parameters. Hence it is possible to obtain an explicit measure of the effect of parameter uncertainty on failure probability. Failure probability can be controlled in two different ways: (1) by reducing the nominal required failure probability, depending on the size of the available data set, and (2) by modifying of the distribution itself that is used to calculate the risk control. Approach (1) corresponds to a frequentist/regulatory view of probability, while approach (2) is consistent with a Bayesian/personalistic view. We furthermore show that the two approaches are consistent in achieving the required failure probability. Finally, we briefly discuss the effects of data pooling and its systemic risk implications. © 2010 Society for Risk Analysis.

Recovering Parameters of Johnson's SB Distribution

Treesearch

Bernard R. Parresol

2003-01-01

A new parameter recovery model for Johnson's SB distribution is developed. This latest alternative approach permits recovery of the range and both shape parameters. Previous models recovered only the two shape parameters. Also, a simple procedure for estimating the distribution minimum from sample values is presented. The new methodology...

MTL distributed magnet measurement system

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

Nogiec, J.M.; Craker, P.A.; Garbarini, J.P.

1993-04-01

The Magnet Test Laboratory (MTL) at the Superconducting Super collider Laboratory will be required to precisely and reliably measure properties of magnets in a production environment. The extensive testing of the superconducting magnets comprises several types of measurements whose main purpose is to evaluate some basic parameters characterizing magnetic, mechanic and cryogenic properties of magnets. The measurement process will produce a significant amount of data which will be subjected to complex analysis. Such massive measurements require a careful design of both the hardware and software of computer systems, having in mind a reliable, maximally automated system. In order to fulfillmore » this requirement a dedicated Distributed Magnet Measurement System (DMMS) is being developed.« less

Transmuted of Rayleigh Distribution with Estimation and Application on Noise Signal

NASA Astrophysics Data System (ADS)

Ahmed, Suhad; Qasim, Zainab

2018-05-01

This paper deals with transforming one parameter Rayleigh distribution, into transmuted probability distribution through introducing a new parameter (λ), since this studied distribution is necessary in representing signal data distribution and failure data model the value of this transmuted parameter |λ| ≤ 1, is also estimated as well as the original parameter (⊖) by methods of moments and maximum likelihood using different sample size (n=25, 50, 75, 100) and comparing the results of estimation by statistical measure (mean square error, MSE).

PC Software graphics tool for conceptual design of space/planetary electrical power systems

NASA Technical Reports Server (NTRS)

Truong, Long V.

1995-01-01

This paper describes the Decision Support System (DSS), a personal computer software graphics tool for designing conceptual space and/or planetary electrical power systems. By using the DSS, users can obtain desirable system design and operating parameters, such as system weight, electrical distribution efficiency, and bus power. With this tool, a large-scale specific power system was designed in a matter of days. It is an excellent tool to help designers make tradeoffs between system components, hardware architectures, and operation parameters in the early stages of the design cycle. The DSS is a user-friendly, menu-driven tool with online help and a custom graphical user interface. An example design and results are illustrated for a typical space power system with multiple types of power sources, frequencies, energy storage systems, and loads.

Aging transition in systems of oscillators with global distributed-delay coupling.

PubMed

Rahman, B; Blyuss, K B; Kyrychko, Y N

2017-09-01

We consider a globally coupled network of active (oscillatory) and inactive (nonoscillatory) oscillators with distributed-delay coupling. Conditions for aging transition, associated with suppression of oscillations, are derived for uniform and gamma delay distributions in terms of coupling parameters and the proportion of inactive oscillators. The results suggest that for the uniform distribution increasing the width of distribution for the same mean delay allows aging transition to happen for a smaller coupling strength and a smaller proportion of inactive elements. For gamma distribution with sufficiently large mean time delay, it may be possible to achieve aging transition for an arbitrary proportion of inactive oscillators, as long as the coupling strength lies in a certain range.

An application of the Krylov-FSP-SSA method to parameter fitting with maximum likelihood

NASA Astrophysics Data System (ADS)

Dinh, Khanh N.; Sidje, Roger B.

2017-12-01

Monte Carlo methods such as the stochastic simulation algorithm (SSA) have traditionally been employed in gene regulation problems. However, there has been increasing interest to directly obtain the probability distribution of the molecules involved by solving the chemical master equation (CME). This requires addressing the curse of dimensionality that is inherent in most gene regulation problems. The finite state projection (FSP) seeks to address the challenge and there have been variants that further reduce the size of the projection or that accelerate the resulting matrix exponential. The Krylov-FSP-SSA variant has proved numerically efficient by combining, on one hand, the SSA to adaptively drive the FSP, and on the other hand, adaptive Krylov techniques to evaluate the matrix exponential. Here we apply this Krylov-FSP-SSA to a mutual inhibitory gene network synthetically engineered in Saccharomyces cerevisiae, in which bimodality arises. We show numerically that the approach can efficiently approximate the transient probability distribution, and this has important implications for parameter fitting, where the CME has to be solved for many different parameter sets. The fitting scheme amounts to an optimization problem of finding the parameter set so that the transient probability distributions fit the observations with maximum likelihood. We compare five optimization schemes for this difficult problem, thereby providing further insights into this approach of parameter estimation that is often applied to models in systems biology where there is a need to calibrate free parameters. Work supported by NSF grant DMS-1320849.

Automatic Calibration of a Semi-Distributed Hydrologic Model Using Particle Swarm Optimization

NASA Astrophysics Data System (ADS)

Bekele, E. G.; Nicklow, J. W.

2005-12-01

Hydrologic simulation models need to be calibrated and validated before using them for operational predictions. Spatially-distributed hydrologic models generally have a large number of parameters to capture the various physical characteristics of a hydrologic system. Manual calibration of such models is a very tedious and daunting task, and its success depends on the subjective assessment of a particular modeler, which includes knowledge of the basic approaches and interactions in the model. In order to alleviate these shortcomings, an automatic calibration model, which employs an evolutionary optimization technique known as Particle Swarm Optimizer (PSO) for parameter estimation, is developed. PSO is a heuristic search algorithm that is inspired by social behavior of bird flocking or fish schooling. The newly-developed calibration model is integrated to the U.S. Department of Agriculture's Soil and Water Assessment Tool (SWAT). SWAT is a physically-based, semi-distributed hydrologic model that was developed to predict the long term impacts of land management practices on water, sediment and agricultural chemical yields in large complex watersheds with varying soils, land use, and management conditions. SWAT was calibrated for streamflow and sediment concentration. The calibration process involves parameter specification, whereby sensitive model parameters are identified, and parameter estimation. In order to reduce the number of parameters to be calibrated, parameterization was performed. The methodology is applied to a demonstration watershed known as Big Creek, which is located in southern Illinois. Application results show the effectiveness of the approach and model predictions are significantly improved.

Dynamic modeling, property investigation, and adaptive controller design of serial robotic manipulators modeled with structural compliance

NASA Technical Reports Server (NTRS)

Tesar, Delbert; Tosunoglu, Sabri; Lin, Shyng-Her

1990-01-01

Research results on general serial robotic manipulators modeled with structural compliances are presented. Two compliant manipulator modeling approaches, distributed and lumped parameter models, are used in this study. System dynamic equations for both compliant models are derived by using the first and second order influence coefficients. Also, the properties of compliant manipulator system dynamics are investigated. One of the properties, which is defined as inaccessibility of vibratory modes, is shown to display a distinct character associated with compliant manipulators. This property indicates the impact of robot geometry on the control of structural oscillations. Example studies are provided to illustrate the physical interpretation of inaccessibility of vibratory modes. Two types of controllers are designed for compliant manipulators modeled by either lumped or distributed parameter techniques. In order to maintain the generality of the results, neither linearization is introduced. Example simulations are given to demonstrate the controller performance. The second type controller is also built for general serial robot arms and is adaptive in nature which can estimate uncertain payload parameters on-line and simultaneously maintain trajectory tracking properties. The relation between manipulator motion tracking capability and convergence of parameter estimation properties is discussed through example case studies. The effect of control input update delays on adaptive controller performance is also studied.

Effect of Propellant Feed System Coupling and Hydraulic Parameters on Analysis of Chugging

NASA Technical Reports Server (NTRS)

Wood, Don J.; Dorsch, Robert G.

1967-01-01

A digital distributed parameter model was used to study the effects of propellant-feed- system coupling and various hydraulic parameters on the analytical prediction of chugging instabilities. Coupling between the combustion chamber and feed system was controlled by varying the compliance of the injector-dome region. The coupling with the feed system above the pump was varied by changing the amount of cavitation compliance at the pump inlet. The stability limits and chugging frequencies proved to be strongly dependent on the degree of feed-system coupling. The maximum stability condition occurred with intermediate coupling. Under conditions of a high degree of feed-system-combustor coupling, the stability limits and chugging frequencies were primarily dependent on the feed-system characteristics; the responses were characterized by beating patterns. For the system analyzed, the pump suction line had little effect on the stability limits or chugging frequencies. Beating, present under the condition of near zero injector -dome compliance, was eliminated when the suction line was decoupled by employing a sufficiently high value of pump-inlet compliance. Under conditions of maximum feed-system coupling, the magnitude and distribution of line losses in the discharge line had a significant effect on the stability limits but had negligible effect on the chugging frequency and beating characteristics. Also, the length of the discharge line greatly affected the stability limits, chugging frequency, and beating characteristics. The length of the suction line, however, had little effect on the stability limits and chugging frequency but did influence the beating pattern. A resistive-shunt device attached to the pump discharge line to suppress chugging was investigated. The analysis showed that the device was effective under conditions of high feed-system coupling.

Generalized Distributed Consensus-based Algorithms for Uncertain Systems and Networks

DTIC Science & Technology

2010-01-01

time linear systems with markovian jumping parameters and additive disturbances. SIAM Journal on Control and Optimization, 44(4):1165– 1191, 2005... time marko- vian jump linear systems , in the presence of delayed mode observations. Proceed- ings of the 2008 IEEE American Control Conference, pages...Markovian Jump Linear System state estimation . . . . 147 6 Conclusions 152 A Discrete- Time Coupled Matrix Equations 156 A.1 Properties of a special

Robust/optimal temperature profile control of a high-speed aerospace vehicle using neural networks.

PubMed

Yadav, Vivek; Padhi, Radhakant; Balakrishnan, S N

2007-07-01

An approximate dynamic programming (ADP)-based suboptimal neurocontroller to obtain desired temperature for a high-speed aerospace vehicle is synthesized in this paper. A 1-D distributed parameter model of a fin is developed from basic thermal physics principles. "Snapshot" solutions of the dynamics are generated with a simple dynamic inversion-based feedback controller. Empirical basis functions are designed using the "proper orthogonal decomposition" (POD) technique and the snapshot solutions. A low-order nonlinear lumped parameter system to characterize the infinite dimensional system is obtained by carrying out a Galerkin projection. An ADP-based neurocontroller with a dual heuristic programming (DHP) formulation is obtained with a single-network-adaptive-critic (SNAC) controller for this approximate nonlinear model. Actual control in the original domain is calculated with the same POD basis functions through a reverse mapping. Further contribution of this paper includes development of an online robust neurocontroller to account for unmodeled dynamics and parametric uncertainties inherent in such a complex dynamic system. A neural network (NN) weight update rule that guarantees boundedness of the weights and relaxes the need for persistence of excitation (PE) condition is presented. Simulation studies show that in a fairly extensive but compact domain, any desired temperature profile can be achieved starting from any initial temperature profile. Therefore, the ADP and NN-based controllers appear to have the potential to become controller synthesis tools for nonlinear distributed parameter systems.

Model error estimation for distributed systems described by elliptic equations

NASA Technical Reports Server (NTRS)

Rodriguez, G.

1983-01-01

A function space approach is used to develop a theory for estimation of the errors inherent in an elliptic partial differential equation model for a distributed parameter system. By establishing knowledge of the inevitable deficiencies in the model, the error estimates provide a foundation for updating the model. The function space solution leads to a specification of a method for computation of the model error estimates and development of model error analysis techniques for comparison between actual and estimated errors. The paper summarizes the model error estimation approach as well as an application arising in the area of modeling for static shape determination of large flexible systems.

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

Bank, J.; Mather, B.

This paper, presented at the IEEE Green Technologies Conference 2013, utilizes information from high resolution data acquisition systems developed at the National Renewable Energy Laboratory and deployed on a high-penetration PV distribution system to analyze the variability of different electrical parameters. High-resolution solar irradiance data is also available in the same area which is used to characterize the available resource and how it affects the electrical characteristics of the study circuit. This paper takes a data-driven look at the variability caused by load and compares those results against times when significant PV production is present. Comparisons between the variability inmore » system load and the variability of distributed PV generation are made.« less

Influences of geological parameters to probabilistic assessment of slope stability of embankment

NASA Astrophysics Data System (ADS)

Nguyen, Qui T.; Le, Tuan D.; Konečný, Petr

2018-04-01

This article considers influences of geological parameters to slope stability of the embankment in probabilistic analysis using SLOPE/W computational system. Stability of a simple slope is evaluated with and without pore–water pressure on the basis of variation of soil properties. Normal distributions of unit weight, cohesion and internal friction angle are assumed. Monte Carlo simulation technique is employed to perform analysis of critical slip surface. Sensitivity analysis is performed to observe the variation of the geological parameters and their effects on safety factors of the slope stability.

Evaluation of the pre-posterior distribution of optimized sampling times for the design of pharmacokinetic studies.

PubMed

Duffull, Stephen B; Graham, Gordon; Mengersen, Kerrie; Eccleston, John

2012-01-01

Information theoretic methods are often used to design studies that aim to learn about pharmacokinetic and linked pharmacokinetic-pharmacodynamic systems. These design techniques, such as D-optimality, provide the optimum experimental conditions. The performance of the optimum design will depend on the ability of the investigator to comply with the proposed study conditions. However, in clinical settings it is not possible to comply exactly with the optimum design and hence some degree of unplanned suboptimality occurs due to error in the execution of the study. In addition, due to the nonlinear relationship of the parameters of these models to the data, the designs are also locally dependent on an arbitrary choice of a nominal set of parameter values. A design that is robust to both study conditions and uncertainty in the nominal set of parameter values is likely to be of use clinically. We propose an adaptive design strategy to account for both execution error and uncertainty in the parameter values. In this study we investigate designs for a one-compartment first-order pharmacokinetic model. We do this in a Bayesian framework using Markov-chain Monte Carlo (MCMC) methods. We consider log-normal prior distributions on the parameters and investigate several prior distributions on the sampling times. An adaptive design was used to find the sampling window for the current sampling time conditional on the actual times of all previous samples.

Small traveling clusters in attractive and repulsive Hamiltonian mean-field models.

PubMed

Barré, Julien; Yamaguchi, Yoshiyuki Y

2009-03-01

Long-lasting small traveling clusters are studied in the Hamiltonian mean-field model by comparing between attractive and repulsive interactions. Nonlinear Landau damping theory predicts that a Gaussian momentum distribution on a spatially homogeneous background permits the existence of traveling clusters in the repulsive case, as in plasma systems, but not in the attractive case. Nevertheless, extending the analysis to a two-parameter family of momentum distributions of Fermi-Dirac type, we theoretically predict the existence of traveling clusters in the attractive case; these findings are confirmed by direct N -body numerical simulations. The parameter region with the traveling clusters is much reduced in the attractive case with respect to the repulsive case.

A study on post impingement effects of urea-water solution spray on the heated wall of automotive SCR systems

NASA Astrophysics Data System (ADS)

Shahariar, G. M. H.; Wardana, M. K. A.; Lim, O. T.

2018-04-01

The post impingement effects of urea-water solution spray on the heated wall of automotive SCR systems was numerically investigated in a constant volume chamber using STAR CCM+ CFD code. The turbulence flow was modelled by realizable k-ε two-layer model together with standard wall function and all y+ treatment was applied along with two-layer approach. The Eulerian-Lagrangian approach was used for the modelling of multi phase flow. Urea water solution (UWS) was injected onto the heated wall for the wall temperature of 338, 413, 473, 503 & 573 K. Spray development after impinging on the heated wall was visualized and measured. Droplet size distribution and droplet evaporation rates were also measured, which are vital parameters for the system performance but still not well researched. Specially developed user defined functions (UDF) are implemented to simulate the desired conditions and parameters. The investigation reveals that wall temperature has a great impact on spray development after impingement, droplet size distribution and evaporation. Increasing the wall temperature leads to longer spray front projection length, smaller droplet size and faster droplet evaporation which are preconditions for urea crystallization reduction. The numerical model and parameters are validated comparing with experimental data.

Multiobjective design of aquifer monitoring networks for optimal spatial prediction and geostatistical parameter estimation

NASA Astrophysics Data System (ADS)

Alzraiee, Ayman H.; Bau, Domenico A.; Garcia, Luis A.

2013-06-01

Effective sampling of hydrogeological systems is essential in guiding groundwater management practices. Optimal sampling of groundwater systems has previously been formulated based on the assumption that heterogeneous subsurface properties can be modeled using a geostatistical approach. Therefore, the monitoring schemes have been developed to concurrently minimize the uncertainty in the spatial distribution of systems' states and parameters, such as the hydraulic conductivity K and the hydraulic head H, and the uncertainty in the geostatistical model of system parameters using a single objective function that aggregates all objectives. However, it has been shown that the aggregation of possibly conflicting objective functions is sensitive to the adopted aggregation scheme and may lead to distorted results. In addition, the uncertainties in geostatistical parameters affect the uncertainty in the spatial prediction of K and H according to a complex nonlinear relationship, which has often been ineffectively evaluated using a first-order approximation. In this study, we propose a multiobjective optimization framework to assist the design of monitoring networks of K and H with the goal of optimizing their spatial predictions and estimating the geostatistical parameters of the K field. The framework stems from the combination of a data assimilation (DA) algorithm and a multiobjective evolutionary algorithm (MOEA). The DA algorithm is based on the ensemble Kalman filter, a Monte-Carlo-based Bayesian update scheme for nonlinear systems, which is employed to approximate the posterior uncertainty in K, H, and the geostatistical parameters of K obtained by collecting new measurements. Multiple MOEA experiments are used to investigate the trade-off among design objectives and identify the corresponding monitoring schemes. The methodology is applied to design a sampling network for a shallow unconfined groundwater system located in Rocky Ford, Colorado. Results indicate that the effect of uncertainties associated with the geostatistical parameters on the spatial prediction might be significantly alleviated (by up to 80% of the prior uncertainty in K and by 90% of the prior uncertainty in H) by sampling evenly distributed measurements with a spatial measurement density of more than 1 observation per 60 m × 60 m grid block. In addition, exploration of the interaction of objective functions indicates that the ability of head measurements to reduce the uncertainty associated with the correlation scale is comparable to the effect of hydraulic conductivity measurements.

Examining System-Wide Impacts of Solar PV Control Systems with a Power Hardware-in-the-Loop Platform

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

Williams, Tess L.; Fuller, Jason C.; Schneider, Kevin P.

2014-06-08

High penetration levels of distributed solar PV power generation can lead to adverse power quality impacts, such as excessive voltage rise, voltage flicker, and reactive power values that result in unacceptable voltage levels. Advanced inverter control schemes have been developed that have the potential to mitigate many power quality concerns. However, local closed-loop control may lead to unintended behavior in deployed systems as complex interactions can occur between numerous operating devices. To enable the study of the performance of advanced control schemes in a detailed distribution system environment, a test platform has been developed that integrates Power Hardware-in-the-Loop (PHIL) withmore » concurrent time-series electric distribution system simulation. In the test platform, GridLAB-D, a distribution system simulation tool, runs a detailed simulation of a distribution feeder in real-time mode at the Pacific Northwest National Laboratory (PNNL) and supplies power system parameters at a point of common coupling. At the National Renewable Energy Laboratory (NREL), a hardware inverter interacts with grid and PV simulators emulating an operational distribution system. Power output from the inverters is measured and sent to PNNL to update the real-time distribution system simulation. The platform is described and initial test cases are presented. The platform is used to study the system-wide impacts and the interactions of inverter control modes—constant power factor and active Volt/VAr control—when integrated into a simulated IEEE 8500-node test feeder. We demonstrate that this platform is well-suited to the study of advanced inverter controls and their impacts on the power quality of a distribution feeder. Additionally, results are used to validate GridLAB-D simulations of advanced inverter controls.« less

System theory as applied differential geometry. [linear system

NASA Technical Reports Server (NTRS)

Hermann, R.

1979-01-01

The invariants of input-output systems under the action of the feedback group was examined. The approach used the theory of Lie groups and concepts of modern differential geometry, and illustrated how the latter provides a basis for the discussion of the analytic structure of systems. Finite dimensional linear systems in a single independent variable are considered. Lessons of more general situations (e.g., distributed parameter and multidimensional systems) which are increasingly encountered as technology advances are presented.

Bivariate extreme value distributions

NASA Technical Reports Server (NTRS)

Elshamy, M.

1992-01-01

In certain engineering applications, such as those occurring in the analyses of ascent structural loads for the Space Transportation System (STS), some of the load variables have a lower bound of zero. Thus, the need for practical models of bivariate extreme value probability distribution functions with lower limits was identified. We discuss the Gumbel models and present practical forms of bivariate extreme probability distributions of Weibull and Frechet types with two parameters. Bivariate extreme value probability distribution functions can be expressed in terms of the marginal extremel distributions and a 'dependence' function subject to certain analytical conditions. Properties of such bivariate extreme distributions, sums and differences of paired extremals, as well as the corresponding forms of conditional distributions, are discussed. Practical estimation techniques are also given.

Exact extreme-value statistics at mixed-order transitions.

PubMed

Bar, Amir; Majumdar, Satya N; Schehr, Grégory; Mukamel, David

2016-05-01

We study extreme-value statistics for spatially extended models exhibiting mixed-order phase transitions (MOT). These are phase transitions that exhibit features common to both first-order (discontinuity of the order parameter) and second-order (diverging correlation length) transitions. We consider here the truncated inverse distance squared Ising model, which is a prototypical model exhibiting MOT, and study analytically the extreme-value statistics of the domain lengths The lengths of the domains are identically distributed random variables except for the global constraint that their sum equals the total system size L. In addition, the number of such domains is also a fluctuating variable, and not fixed. In the paramagnetic phase, we show that the distribution of the largest domain length l_{max} converges, in the large L limit, to a Gumbel distribution. However, at the critical point (for a certain range of parameters) and in the ferromagnetic phase, we show that the fluctuations of l_{max} are governed by novel distributions, which we compute exactly. Our main analytical results are verified by numerical simulations.

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

Dana L. Kelly

Typical engineering systems in applications with high failure consequences such as nuclear reactor plants often employ redundancy and diversity of equipment in an effort to lower the probability of failure and therefore risk. However, it has long been recognized that dependencies exist in these redundant and diverse systems. Some dependencies, such as common sources of electrical power, are typically captured in the logic structure of the risk model. Others, usually referred to as intercomponent dependencies, are treated implicitly by introducing one or more statistical parameters into the model. Such common-cause failure models have limitations in a simulation environment. In addition,more » substantial subjectivity is associated with parameter estimation for these models. This paper describes an approach in which system performance is simulated by drawing samples from the joint distributions of dependent variables. The approach relies on the notion of a copula distribution, a notion which has been employed by the actuarial community for ten years or more, but which has seen only limited application in technological risk assessment. The paper also illustrates how equipment failure data can be used in a Bayesian framework to estimate the parameter values in the copula model. This approach avoids much of the subjectivity required to estimate parameters in traditional common-cause failure models. Simulation examples are presented for failures in time. The open-source software package R is used to perform the simulations. The open-source software package WinBUGS is used to perform the Bayesian inference via Markov chain Monte Carlo sampling.« less

Modeling the human body/seat system in a vibration environment.

PubMed

Rosen, Jacob; Arcan, Mircea

2003-04-01

The vibration environment is a common man-made artificial surrounding with which humans have a limited tolerance to cope due to their body dynamics. This research studied the dynamic characteristics of a seated human body/seat system in a vibration environment. The main result is a multi degrees of freedom lumped parameter model that synthesizes two basic dynamics: (i) global human dynamics, the apparent mass phenomenon, including a systematic set of the model parameters for simulating various conditions like body posture, backrest, footrest, muscle tension, and vibration directions, and (ii) the local human dynamics, represented by the human pelvis/vibrating seat contact, using a cushioning interface. The model and its selected parameters successfully described the main effects of the apparent mass phenomenon compared to experimental data documented in the literature. The model provided an analytical tool for human body dynamics research. It also enabled a primary tool for seat and cushioning design. The model was further used to develop design guidelines for a composite cushion using the principle of quasi-uniform body/seat contact force distribution. In terms of evenly distributing the contact forces, the best result for the different materials and cushion geometries simulated in the current study was achieved using a two layer shaped geometry cushion built from three materials. Combining the geometry and the mechanical characteristics of a structure under large deformation into a lumped parameter model enables successful analysis of the human/seat interface system and provides practical results for body protection in dynamic environment.

Development of uncertainty-based work injury model using Bayesian structural equation modelling.

PubMed

Chatterjee, Snehamoy

2014-01-01

This paper proposed a Bayesian method-based structural equation model (SEM) of miners' work injury for an underground coal mine in India. The environmental and behavioural variables for work injury were identified and causal relationships were developed. For Bayesian modelling, prior distributions of SEM parameters are necessary to develop the model. In this paper, two approaches were adopted to obtain prior distribution for factor loading parameters and structural parameters of SEM. In the first approach, the prior distributions were considered as a fixed distribution function with specific parameter values, whereas, in the second approach, prior distributions of the parameters were generated from experts' opinions. The posterior distributions of these parameters were obtained by applying Bayesian rule. The Markov Chain Monte Carlo sampling in the form Gibbs sampling was applied for sampling from the posterior distribution. The results revealed that all coefficients of structural and measurement model parameters are statistically significant in experts' opinion-based priors, whereas, two coefficients are not statistically significant when fixed prior-based distributions are applied. The error statistics reveals that Bayesian structural model provides reasonably good fit of work injury with high coefficient of determination (0.91) and less mean squared error as compared to traditional SEM.

Event-by-event gluon multiplicity, energy density, and eccentricities in ultrarelativistic heavy-ion collisions

NASA Astrophysics Data System (ADS)

Schenke, Björn; Tribedy, Prithwish; Venugopalan, Raju

2012-09-01

The event-by-event multiplicity distribution, the energy densities and energy density weighted eccentricity moments ɛn (up to n=6) at early times in heavy-ion collisions at both the BNL Relativistic Heavy Ion Collider (RHIC) (s=200GeV) and the CERN Large Hardron Collider (LHC) (s=2.76TeV) are computed in the IP-Glasma model. This framework combines the impact parameter dependent saturation model (IP-Sat) for nucleon parton distributions (constrained by HERA deeply inelastic scattering data) with an event-by-event classical Yang-Mills description of early-time gluon fields in heavy-ion collisions. The model produces multiplicity distributions that are convolutions of negative binomial distributions without further assumptions or parameters. In the limit of large dense systems, the n-particle gluon distribution predicted by the Glasma-flux tube model is demonstrated to be nonperturbatively robust. In the general case, the effect of additional geometrical fluctuations is quantified. The eccentricity moments are compared to the MC-KLN model; a noteworthy feature is that fluctuation dominated odd moments are consistently larger than in the MC-KLN model.

Building an experimental model of the human body with non-physiological parameters.

PubMed

Labuz, Joseph M; Moraes, Christopher; Mertz, David R; Leung, Brendan M; Takayama, Shuichi

2017-03-01

New advances in engineering and biomedical technology have enabled recent efforts to capture essential aspects of human physiology in microscale, in-vitro systems. The application of these advances to experimentally model complex processes in an integrated platform - commonly called a 'human-on-a-chip (HOC)' - requires that relevant compartments and parameters be sized correctly relative to each other and to the system as a whole. Empirical observation, theoretical treatments of resource distribution systems and natural experiments can all be used to inform rational design of such a system, but technical and fundamental challenges (e.g. small system blood volumes and context-dependent cell metabolism, respectively) pose substantial, unaddressed obstacles. Here, we put forth two fundamental principles for HOC design: inducing in-vivo -like cellular metabolic rates is necessary and may be accomplished in-vitro by limiting O 2 availability and that the effects of increased blood volumes on drug concentration can be mitigated through pharmacokinetics-based treatments of solute distribution. Combining these principles with natural observation and engineering workarounds, we derive a complete set of design criteria for a practically realizable, physiologically faithful, five-organ millionth-scale (× 10 -6 ) microfluidic model of the human body.

Modular modeling system for building distributed hydrologic models with a user-friendly software package

NASA Astrophysics Data System (ADS)

Wi, S.; Ray, P. A.; Brown, C.

2015-12-01

A software package developed to facilitate building distributed hydrologic models in a modular modeling system is presented. The software package provides a user-friendly graphical user interface that eases its practical use in water resources-related research and practice. The modular modeling system organizes the options available to users when assembling models according to the stages of hydrological cycle, such as potential evapotranspiration, soil moisture accounting, and snow/glacier melting processes. The software is intended to be a comprehensive tool that simplifies the task of developing, calibrating, validating, and using hydrologic models through the inclusion of intelligent automation to minimize user effort, and reduce opportunities for error. Processes so far automated include the definition of system boundaries (i.e., watershed delineation), climate and geographical input generation, and parameter calibration. Built-in post-processing toolkits greatly improve the functionality of the software as a decision support tool for water resources system management and planning. Example post-processing toolkits enable streamflow simulation at ungauged sites with predefined model parameters, and perform climate change risk assessment by means of the decision scaling approach. The software is validated through application to watersheds representing a variety of hydrologic regimes.

Building an experimental model of the human body with non-physiological parameters

PubMed Central

Labuz, Joseph M.; Moraes, Christopher; Mertz, David R.; Leung, Brendan M.; Takayama, Shuichi

2017-01-01

New advances in engineering and biomedical technology have enabled recent efforts to capture essential aspects of human physiology in microscale, in-vitro systems. The application of these advances to experimentally model complex processes in an integrated platform — commonly called a ‘human-on-a-chip (HOC)’ — requires that relevant compartments and parameters be sized correctly relative to each other and to the system as a whole. Empirical observation, theoretical treatments of resource distribution systems and natural experiments can all be used to inform rational design of such a system, but technical and fundamental challenges (e.g. small system blood volumes and context-dependent cell metabolism, respectively) pose substantial, unaddressed obstacles. Here, we put forth two fundamental principles for HOC design: inducing in-vivo-like cellular metabolic rates is necessary and may be accomplished in-vitro by limiting O2 availability and that the effects of increased blood volumes on drug concentration can be mitigated through pharmacokinetics-based treatments of solute distribution. Combining these principles with natural observation and engineering workarounds, we derive a complete set of design criteria for a practically realizable, physiologically faithful, five-organ millionth-scale (× 10−6) microfluidic model of the human body. PMID:28713851

Security of subcarrier wave quantum key distribution against the collective beam-splitting attack.

PubMed

Miroshnichenko, G P; Kozubov, A V; Gaidash, A A; Gleim, A V; Horoshko, D B

2018-04-30

We consider a subcarrier wave quantum key distribution (QKD) system, where quantum encoding is carried out at weak sidebands generated around a coherent optical beam as a result of electro-optical phase modulation. We study security of two protocols, B92 and BB84, against one of the most powerful attacks for this class of systems, the collective beam-splitting attack. Our analysis includes the case of high modulation index, where the sidebands are essentially multimode. We demonstrate numerically and experimentally that a subcarrier wave QKD system with realistic parameters is capable of distributing cryptographic keys over large distances in presence of collective attacks. We also show that BB84 protocol modification with discrimination of only one state in each basis performs not worse than the original BB84 protocol in this class of QKD systems, thus significantly simplifying the development of cryptographic networks using the considered QKD technique.

Estimation of sum-to-one constrained parameters with non-Gaussian extensions of ensemble-based Kalman filters: application to a 1D ocean biogeochemical model

NASA Astrophysics Data System (ADS)

Simon, E.; Bertino, L.; Samuelsen, A.

2011-12-01

Combined state-parameter estimation in ocean biogeochemical models with ensemble-based Kalman filters is a challenging task due to the non-linearity of the models, the constraints of positiveness that apply to the variables and parameters, and the non-Gaussian distribution of the variables in which they result. Furthermore, these models are sensitive to numerous parameters that are poorly known. Previous works [1] demonstrated that the Gaussian anamorphosis extensions of ensemble-based Kalman filters were relevant tools to perform combined state-parameter estimation in such non-Gaussian framework. In this study, we focus on the estimation of the grazing preferences parameters of zooplankton species. These parameters are introduced to model the diet of zooplankton species among phytoplankton species and detritus. They are positive values and their sum is equal to one. Because the sum-to-one constraint cannot be handled by ensemble-based Kalman filters, a reformulation of the parameterization is proposed. We investigate two types of changes of variables for the estimation of sum-to-one constrained parameters. The first one is based on Gelman [2] and leads to the estimation of normal distributed parameters. The second one is based on the representation of the unit sphere in spherical coordinates and leads to the estimation of parameters with bounded distributions (triangular or uniform). These formulations are illustrated and discussed in the framework of twin experiments realized in the 1D coupled model GOTM-NORWECOM with Gaussian anamorphosis extensions of the deterministic ensemble Kalman filter (DEnKF). [1] Simon E., Bertino L. : Gaussian anamorphosis extension of the DEnKF for combined state and parameter estimation : application to a 1D ocean ecosystem model. Journal of Marine Systems, 2011. doi :10.1016/j.jmarsys.2011.07.007 [2] Gelman A. : Method of Moments Using Monte Carlo Simulation. Journal of Computational and Graphical Statistics, 4, 1, 36-54, 1995.

Mathematical Modelling of Continuous Biotechnological Processes

ERIC Educational Resources Information Center

Pencheva, T.; Hristozov, I.; Shannon, A. G.

2003-01-01

Biotechnological processes (BTP) are characterized by a complicated structure of organization and interdependent characteristics. Partial differential equations or systems of partial differential equations are used for their behavioural description as objects with distributed parameters. Modelling of substrate without regard to dispersion…

Proceedings of the 3rd Annual SCOLE Workshop

NASA Technical Reports Server (NTRS)

Taylor, Lawrence W., Jr. (Compiler)

1987-01-01

Topics addressed include: modeling and controlling the Spacecraft Control Laboratory Experiment (SCOLE) configurations; slewing maneuvers; mathematical models; vibration damping; gravitational effects; structural dynamics; finite element method; distributed parameter system; on-line pulse control; stability augmentation; and stochastic processes.

Optoelectronics in TESLA, LHC, and pi-of-the-sky experiments

NASA Astrophysics Data System (ADS)

Romaniuk, Ryszard S.; Pozniak, Krzysztof T.; Wrochna, Grzegorz; Simrock, Stefan

2004-09-01

Optical and optoelectronics technologies are more and more widely used in the biggest world experiments of high energy and nuclear physics, as well as in the astronomy. The paper is a kind of a broad digest describing the usage of optoelectronics is such experiments and information about some of the involved teams. The described experiments include: TESLA linear accelerator and FEL, Compact Muon Solenoid at LHC and recently started π-of-the-sky global gamma ray bursts (with asociated optical flashes) observation experiment. Optoelectornics and photonics offer several key features which are either extending the technical parameters of existing solutions or adding quite new practical application possibilities. Some of these favorable features of photonic systems are: high selectivity of optical sensors, immunity to some kinds of noise processes, extremely broad bandwidth exchangeable for either terabit rate transmission or ultrashort pulse generation, parallel image processing capability, etc. The following groups of photonic components and systems were described: (1) discrete components applications like: LED, PD, LD, CCD and CMOS cameras, active optical crystals and optical fibers in radiation dosimetry, astronomical image processing and for building of more complex photonic systems; (2) optical fiber networks serving as very stable phase distribution, clock signal distribution, distributed dosimeters, distributed gigabit transmission for control, diagnostics and data acquisition/processing; (3) fast and stable coherent femtosecond laser systems with active optical components for electro-optical sampling and photocathode excitation in the RF electron gun for linac; The parameters of some of these systems were quoted and discussed. A number of the debated solutions seems to be competitive against the classical ones. Several future fields seem to emerge involving direct coupling between the ultrafast photonic and the VLSI FPGA based technologies.

European distributed seismological data archives infrastructure: EIDA

NASA Astrophysics Data System (ADS)

Clinton, John; Hanka, Winfried; Mazza, Salvatore; Pederson, Helle; Sleeman, Reinoud; Stammler, Klaus; Strollo, Angelo

2014-05-01

The European Integrated waveform Data Archive (EIDA) is a distributed Data Center system within ORFEUS that (a) securely archives seismic waveform data and related metadata gathered by European research infrastructures, and (b) provides transparent access to the archives for the geosciences research communities. EIDA was founded in 2013 by ORFEUS Data Center, GFZ, RESIF, ETH, INGV and BGR to ensure sustainability of a distributed archive system and the implementation of standards (e.g. FDSN StationXML, FDSN webservices) and coordinate new developments. Under the mandate of the ORFEUS Board of Directors and Executive Committee the founding group is responsible for steering and maintaining the technical developments and organization of the European distributed seismic waveform data archive and the integration within broader multidisciplanry frameworks like EPOS. EIDA currently offers uniform data access to unrestricted data from 8 European archives (www.orfeus-eu.org/eida), linked by the Arclink protocol, hosting data from 75 permanent networks (1800+ stations) and 33 temporary networks (1200+) stations). Moreover, each archive may also provide unique, restricted datasets. A webinterface, developed at GFZ, offers interactive access to different catalogues (EMSC, GFZ, USGS) and EIDA waveform data. Clients and toolboxes like arclink_fetch and ObsPy can connect directly to any EIDA node to collect data. Current developments are directed to the implementation of quality parameters and strong motion parameters.

Effects of cooling system parameters on heat transfer in PAFC stack. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Abdul-Aziz, Ali A.

1985-01-01

Analytical and experimental study for the effects of cooling system parameters on the heat transfer and temperature distribution in the electrode plates of a phosphoric acid fuel-cell has been conducted. An experimental set-up that simulates the operating conditions prevailing in a phosphoric-acid fuel-cell stack was designed and constructed. The set-up was then used to measure the overall heat transfer coefficient, the thermal contact resistance, and the electrode temperature distribution for two different cooling plate configurations. Two types of cooling plate configurations, serpentine and straight, were tested. Air, water, and oil were used as coolants. Measurements for the heat transfer coefficient and the thermal contact resistance were made for various flow rates ranging from 16 to 88 Kg/hr, and stack clamping pressure ranging from O to 3448 Kpa. The experimental results for the overall heat transfer coefficient were utilized to derive mathematical relations for the overall heat transfer coefficient as a function of stack clamping pressure and Reynolds number for the three coolants. The empirically derived formulas were incorporated in a previously developed computer program to predict electrodes temperature distribution and the performance of the stack cooling system. The results obtained were then compared with those available in the literature. The comparison showed maximum deviation of +/- 11%.

Parameter inference in small world network disease models with approximate Bayesian Computational methods

NASA Astrophysics Data System (ADS)

Walker, David M.; Allingham, David; Lee, Heung Wing Joseph; Small, Michael

2010-02-01

Small world network models have been effective in capturing the variable behaviour of reported case data of the SARS coronavirus outbreak in Hong Kong during 2003. Simulations of these models have previously been realized using informed “guesses” of the proposed model parameters and tested for consistency with the reported data by surrogate analysis. In this paper we attempt to provide statistically rigorous parameter distributions using Approximate Bayesian Computation sampling methods. We find that such sampling schemes are a useful framework for fitting parameters of stochastic small world network models where simulation of the system is straightforward but expressing a likelihood is cumbersome.

Modelling Root Systems Using Oriented Density Distributions

NASA Astrophysics Data System (ADS)

Dupuy, Lionel X.

2011-09-01

Root architectural models are essential tools to understand how plants access and utilize soil resources during their development. However, root architectural models use complex geometrical descriptions of the root system and this has limitations to model interactions with the soil. This paper presents the development of continuous models based on the concept of oriented density distribution function. The growth of the root system is built as a hierarchical system of partial differential equations (PDEs) that incorporate single root growth parameters such as elongation rate, gravitropism and branching rate which appear explicitly as coefficients of the PDE. Acquisition and transport of nutrients are then modelled by extending Darcy's law to oriented density distribution functions. This framework was applied to build a model of the growth and water uptake of barley root system. This study shows that simplified and computer effective continuous models of the root system development can be constructed. Such models will allow application of root growth models at field scale.

Characteristics of buoyancy force on stagnation point flow with magneto-nanoparticles and zero mass flux condition

NASA Astrophysics Data System (ADS)

Uddin, Iftikhar; Khan, Muhammad Altaf; Ullah, Saif; Islam, Saeed; Israr, Muhammad; Hussain, Fawad

2018-03-01

This attempt dedicated to the solution of buoyancy effect over a stretching sheet in existence of MHD stagnation point flow with convective boundary conditions. Thermophoresis and Brownian motion aspects are included. Incompressible fluid is electrically conducted in the presence of varying magnetic field. Boundary layer analysis is used to develop the mathematical formulation. Zero mass flux condition is considered at the boundary. Non-linear ordinary differential system of equations is constructed by means of proper transformations. Interval of convergence via numerical data and plots are developed. Characteristics of involved variables on the velocity, temperature and concentration distributions are sketched and discussed. Features of correlated parameters on Cf and Nu are examined by means of tables. It is found that buoyancy ratio and magnetic parameters increase and reduce the velocity field. Further opposite feature is noticed for higher values of thermophoresis and Brownian motion parameters on concentration distribution.

Temperature based Restricted Boltzmann Machines

NASA Astrophysics Data System (ADS)

Li, Guoqi; Deng, Lei; Xu, Yi; Wen, Changyun; Wang, Wei; Pei, Jing; Shi, Luping

2016-01-01

Restricted Boltzmann machines (RBMs), which apply graphical models to learning probability distribution over a set of inputs, have attracted much attention recently since being proposed as building blocks of multi-layer learning systems called deep belief networks (DBNs). Note that temperature is a key factor of the Boltzmann distribution that RBMs originate from. However, none of existing schemes have considered the impact of temperature in the graphical model of DBNs. In this work, we propose temperature based restricted Boltzmann machines (TRBMs) which reveals that temperature is an essential parameter controlling the selectivity of the firing neurons in the hidden layers. We theoretically prove that the effect of temperature can be adjusted by setting the parameter of the sharpness of the logistic function in the proposed TRBMs. The performance of RBMs can be improved by adjusting the temperature parameter of TRBMs. This work provides a comprehensive insights into the deep belief networks and deep learning architectures from a physical point of view.

Physical parameters in long-decay coronal enhancements. [from Skylab X ray observations

NASA Technical Reports Server (NTRS)

Maccombie, W. J.; Rust, D. M.

1979-01-01

Four well-observed long-decay X-ray enhancements (LDEs) are examined which were associated with filament eruptions, white-light transients, and loop prominence systems. In each case the physical parameters of the X-ray-emitting plasma are determined, including the spatial distribution and temporal evolution of temperature and density. The results and recent analyses of other aspects of the four LDEs are compared with current models of loop prominence systems. It is concluded that only a magnetic-reconnection model, such as that proposed by Kopp and Pneuman (1976) is consistent with the observations.

Stability of a three-species stochastic delay predator-prey system with Lévy noise

NASA Astrophysics Data System (ADS)

Wu, Jian

2018-07-01

This work is concerned with a three-species stochastic delay prey-mesopredator-superpredator system with Lévy noise. We will characterize the complete dynamic scenarios of stability in distribution of solution (SDS) by three parameters κ1 ,κ2 ,κ3 which depend on the interaction and Lévy noise.

Evaluating effective swath width and droplet distribution of aerial spraying systems on M-18B and Thrush 510G airplanes

USDA-ARS?s Scientific Manuscript database

Aerial spraying plays an important role in promoting agricultural production and protecting the biological environment due to its flexibility, high effectiveness, and large operational area per unit of time. In order to evaluate the performance parameters of the spraying systems on two fixed wing ai...

Architecture, Voltage, and Components for a Turboelectric Distributed Propulsion Electric Grid (AVC-TeDP)

NASA Technical Reports Server (NTRS)

Gemin, Paul; Kupiszewski, Tom; Radun, Arthur; Pan, Yan; Lai, Rixin; Zhang, Di; Wang, Ruxi; Wu, Xinhui; Jiang, Yan; Galioto, Steve;

Mathematical Model to estimate the wind power using four-parameter Burr distribution

NASA Astrophysics Data System (ADS)

Liu, Sanming; Wang, Zhijie; Pan, Zhaoxu

2018-03-01

When the real probability of wind speed in the same position needs to be described, the four-parameter Burr distribution is more suitable than other distributions. This paper introduces its important properties and characteristics. Also, the application of the four-parameter Burr distribution in wind speed prediction is discussed, and the expression of probability distribution of output power of wind turbine is deduced.

Leader-follower formation control of underactuated surface vehicles based on sliding mode control and parameter estimation.

PubMed

Sun, Zhijian; Zhang, Guoqing; Lu, Yu; Zhang, Weidong

2018-01-01

This paper studies the leader-follower formation control of underactuated surface vehicles with model uncertainties and environmental disturbances. A parameter estimation and upper bound estimation based sliding mode control scheme is proposed to solve the problem of the unknown plant parameters and environmental disturbances. For each of these leader-follower formation systems, the dynamic equations of position and attitude are analyzed using coordinate transformation with the aid of the backstepping technique. All the variables are guaranteed to be uniformly ultimately bounded stable in the closed-loop system, which is proven by the distribution design Lyapunov function synthesis. The main advantages of this approach are that: first, parameter estimation based sliding mode control can enhance the robustness of the closed-loop system in presence of model uncertainties and environmental disturbances; second, a continuous function is developed to replace the signum function in the design of sliding mode scheme, which devotes to reduce the chattering of the control system. Finally, numerical simulations are given to demonstrate the effectiveness of the proposed method. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Effects of microgravity on the immune system

NASA Technical Reports Server (NTRS)

Sonnenfeld, Gerald; Taylor, Gerald R.

1991-01-01

Changes in resistance to bacterial and viral infections in Apollo crew members has stimulated interest in the study of immunity and space flight. Results of studies from several laboratories in both humans and rodents have indicated alterations after space flight that include the following immunological parameters: thymus size, lymphocyte blastogenesis, interferon and interleukin production, natural killer cell activity, cytotoxic T-cell activity, leukocyte subset population distribution, response of bone marrow cells to colony stimulating factors, and delayed hypersensitivity skin test reactivity. The interactions of the immune system with other physiological systems, including muscle, bone, and the nervous system, may play a major role in the development of these immunological parameters during and after flight. There may also be direct effects of space flight on immune responses.

Tool Support for Parametric Analysis of Large Software Simulation Systems

NASA Technical Reports Server (NTRS)

Schumann, Johann; Gundy-Burlet, Karen; Pasareanu, Corina; Menzies, Tim; Barrett, Tony

2008-01-01

The analysis of large and complex parameterized software systems, e.g., systems simulation in aerospace, is very complicated and time-consuming due to the large parameter space, and the complex, highly coupled nonlinear nature of the different system components. Thus, such systems are generally validated only in regions local to anticipated operating points rather than through characterization of the entire feasible operational envelope of the system. We have addressed the factors deterring such an analysis with a tool to support envelope assessment: we utilize a combination of advanced Monte Carlo generation with n-factor combinatorial parameter variations to limit the number of cases, but still explore important interactions in the parameter space in a systematic fashion. Additional test-cases, automatically generated from models (e.g., UML, Simulink, Stateflow) improve the coverage. The distributed test runs of the software system produce vast amounts of data, making manual analysis impossible. Our tool automatically analyzes the generated data through a combination of unsupervised Bayesian clustering techniques (AutoBayes) and supervised learning of critical parameter ranges using the treatment learner TAR3. The tool has been developed around the Trick simulation environment, which is widely used within NASA. We will present this tool with a GN&C (Guidance, Navigation and Control) simulation of a small satellite system.

Geometric multiaxial representation of N -qubit mixed symmetric separable states

NASA Astrophysics Data System (ADS)

SP, Suma; Sirsi, Swarnamala; Hegde, Subramanya; Bharath, Karthik

2017-08-01

The study of N -qubit mixed symmetric separable states is a longstanding challenging problem as no unique separability criterion exists. In this regard, we take up the N -qubit mixed symmetric separable states for a detailed study as these states are of experimental importance and offer an elegant mathematical analysis since the dimension of the Hilbert space is reduced from 2N to N +1 . Since there exists a one-to-one correspondence between the spin-j system and an N -qubit symmetric state, we employ Fano statistical tensor parameters for the parametrization of the spin-density matrix. Further, we use a geometric multiaxial representation (MAR) of the density matrix to characterize the mixed symmetric separable states. Since the separability problem is NP-hard, we choose to study it in the continuum limit where mixed symmetric separable states are characterized by the P -distribution function λ (θ ,ϕ ) . We show that the N -qubit mixed symmetric separable states can be visualized as a uniaxial system if the distribution function is independent of θ and ϕ . We further choose a distribution function to be the most general positive function on a sphere and observe that the statistical tensor parameters characterizing the N -qubit symmetric system are the expansion coefficients of the distribution function. As an example for the discrete case, we investigate the MAR of a uniformly weighted two-qubit mixed symmetric separable state. We also observe that there exists a correspondence between the separability and classicality of states.

Elliptic flow in small systems due to elliptic gluon distributions?

DOE PAGES

Hagiwara, Yoshikazu; Hatta, Yoshitaka; Xiao, Bo-Wen; ...

2017-05-31

We investigate the contributions from the so-called elliptic gluon Wigner distributions to the rapidity and azimuthal correlations of particles produced in high energy pp and pA collisions by applying the double parton scattering mechanism. We compute the ‘elliptic flow’ parameter v 2 as a function of the transverse momentum and rapidity, and find qualitative agreement with experimental observations. This shall encourage further developments with more rigorous studies of the elliptic gluon distributions and their applications in hard scattering processes in pp and pA collisions.

Temporal Evolution of Non-equilibrium Gamma’ Precipitates in a Rapidly Quenched Nickel Base Superalloy (Preprint)

DTIC Science & Technology

2014-04-01

with the binomial distribution for a particular dataset. This technique is more commonly known as the Langer, Bar-on and Miller ( LBM ) method [22,23...distribution unlimited. Using the LBM method, the frequency distribution plot for a dataset corresponding to a phase separated system, exhibiting a split peak...estimated parameters (namely μ1, μ2, σ, fγ’ and fγ) obtained from the LBM plots in Fig. 5 are summarized in Table 3. The EWQ sample does not exhibit any

Elliptic flow in small systems due to elliptic gluon distributions?

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

Hagiwara, Yoshikazu; Hatta, Yoshitaka; Xiao, Bo-Wen

We investigate the contributions from the so-called elliptic gluon Wigner distributions to the rapidity and azimuthal correlations of particles produced in high energy pp and pA collisions by applying the double parton scattering mechanism. We compute the ‘elliptic flow’ parameter v 2 as a function of the transverse momentum and rapidity, and find qualitative agreement with experimental observations. This shall encourage further developments with more rigorous studies of the elliptic gluon distributions and their applications in hard scattering processes in pp and pA collisions.

Logic Gates Made of N-Channel JFETs and Epitaxial Resistors

NASA Technical Reports Server (NTRS)

Krasowski, Michael J.

2008-01-01

Prototype logic gates made of n-channel junction field-effect transistors (JFETs) and epitaxial resistors have been demonstrated, with a view toward eventual implementation of digital logic devices and systems in silicon carbide (SiC) integrated circuits (ICs). This development is intended to exploit the inherent ability of SiC electronic devices to function at temperatures from 300 to somewhat above 500 C and withstand large doses of ionizing radiation. SiC-based digital logic devices and systems could enable operation of sensors and robots in nuclear reactors, in jet engines, near hydrothermal vents, and in other environments that are so hot or radioactive as to cause conventional silicon electronic devices to fail. At present, current needs for digital processing at high temperatures exceed SiC integrated circuit production capabilities, which do not allow for highly integrated circuits. Only single to small number component production of depletion mode n-channel JFETs and epitaxial resistors on a single substrate is possible. As a consequence, the fine matching of components is impossible, resulting in rather large direct-current parameter distributions within a group of transistors typically spanning multiples of 5 to 10. Add to this the lack of p-channel devices to complement the n-channel FETs, the lack of precise dropping diodes, and the lack of enhancement mode devices at these elevated temperatures and the use of conventional direct coupled and buffered direct coupled logic gate design techniques is impossible. The presented logic gate design is tolerant of device parameter distributions and is not hampered by the lack of complementary devices or dropping diodes. In addition to n-channel JFETs, these gates include level-shifting and load resistors (see figure). Instead of relying on precise matching of parameters among individual JFETS, these designs rely on choosing the values of these resistors and of supply potentials so as to make the circuits perform the desired functions throughout the ranges over which the parameters of the JFETs are distributed. The supply rails V(sub dd) and V(sub ss) and the resistors R are chosen as functions of the distribution of direct-current operating parameters of the group of transistors used.

Uncertainty and the Social Cost of Methane Using Bayesian Constrained Climate Models

NASA Astrophysics Data System (ADS)

Errickson, F. C.; Anthoff, D.; Keller, K.

2016-12-01

Social cost estimates of greenhouse gases are important for the design of sound climate policies and are also plagued by uncertainty. One major source of uncertainty stems from the simplified representation of the climate system used in the integrated assessment models that provide these social cost estimates. We explore how uncertainty over the social cost of methane varies with the way physical processes and feedbacks in the methane cycle are modeled by (i) coupling three different methane models to a simple climate model, (ii) using MCMC to perform a Bayesian calibration of the three coupled climate models that simulates direct sampling from the joint posterior probability density function (pdf) of model parameters, and (iii) producing probabilistic climate projections that are then used to calculate the Social Cost of Methane (SCM) with the DICE and FUND integrated assessment models. We find that including a temperature feedback in the methane cycle acts as an additional constraint during the calibration process and results in a correlation between the tropospheric lifetime of methane and several climate model parameters. This correlation is not seen in the models lacking this feedback. Several of the estimated marginal pdfs of the model parameters also exhibit different distributional shapes and expected values depending on the methane model used. As a result, probabilistic projections of the climate system out to the year 2300 exhibit different levels of uncertainty and magnitudes of warming for each of the three models under an RCP8.5 scenario. We find these differences in climate projections result in differences in the distributions and expected values for our estimates of the SCM. We also examine uncertainty about the SCM by performing a Monte Carlo analysis using a distribution for the climate sensitivity while holding all other climate model parameters constant. Our SCM estimates using the Bayesian calibration are lower and exhibit less uncertainty about extremely high values in the right tail of the distribution compared to the Monte Carlo approach. This finding has important climate policy implications and suggests previous work that accounts for climate model uncertainty by only varying the climate sensitivity parameter may overestimate the SCM.

Development of preliminary design concept for multifunction display and control system for Orbiter crew station. Task 3: Concept analysis

NASA Technical Reports Server (NTRS)

Spiger, R. J.; Farrell, R. J.; Holcomb, G. A.

1982-01-01

The access schema developed to access both individual switch functions as well as automated or semiautomated procedures for the orbital maneuvering system and electrical power and distribution and control system discussed and the operation of the system is described. Feasibility tests and analyses used to define display parameters and to select applicable hardware choices for use in such a system are presented and the results are discussed.

Study of metal transfer in CO2 laser+GMAW-P hybrid welding using argon-helium mixtures

NASA Astrophysics Data System (ADS)

Zhang, Wang; Hua, Xueming; Liao, Wei; Li, Fang; Wang, Min

2014-03-01

The metal transfer in CO2 Laser+GMAW-P hybrid welding by using argon-helium mixtures was investigated and the effect of the laser on the mental transfer is discussed. A 650 nm laser, in conjunction with the shadow graph technique, is used to observe the metal transfer process. In order to analyze the heat input to the droplet and the droplet internal current line distribution. An optical emission spectroscopy system was employed to estimate default parameter and optimized plasma temperature, electron number densities distribution. The results indicate that the CO2 plasma plume have a significant impact to the electrode melting, droplet formation, detachment, impingement onto the workpiece and weld morphology. Since the current distribution direction flow changes to the keyhole, to obtain a metal transfer mode of one droplet per pulse, the welding parameters should be adjusted to a higher pulse time (TP) and a lower voltage.

Bidirectional reflectance distribution function based surface modeling of non-Lambertian using intensity data of light detection and ranging.

PubMed

Li, Xiaolu; Liang, Yu; Xu, Lijun

2014-09-01

To provide a credible model for light detection and ranging (LiDAR) target classification, the focus of this study is on the relationship between intensity data of LiDAR and the bidirectional reflectance distribution function (BRDF). An integration method based on the built-in-lab coaxial laser detection system was advanced. A kind of intermediary BRDF model advanced by Schlick was introduced into the integration method, considering diffuse and specular backscattering characteristics of the surface. A group of measurement campaigns were carried out to investigate the influence of the incident angle and detection range on the measured intensity data. Two extracted parameters r and S(λ) are influenced by different surface features, which illustrate the surface features of the distribution and magnitude of reflected energy, respectively. The combination of two parameters can be used to describe the surface characteristics for target classification in a more plausible way.

A preliminary assessment of two hospital food service systems using parameters of food safety and consumer opinion.

PubMed

Hartwell, H; Edwards, J S

2001-12-01

The goal of any hospital caterer should be to provide food that meets nutritional requirements, satisfies the patient, improves morale and is microbiologically safe. Food distribution to hospital wards plays a critical role. The aim of this study was to compare two hospital food service systems using parameters of food safety and consumer opinion. An NHS hospital was selected where food delivery was due to change from a plated system to a cafeteria trolley system. Samples (50 g) of dishes (n = 27) considered to be high-risk were collected for three consecutive days from breakfast, lunch and supper meals. The samples were taken from a pre-ordered tray (similar to that of a patient) in the plated system and from the trolley on the ward in the cafeteria system of meal delivery (approximately six months after its introduction). Consumer opinions cards (n = 180) were distributed and interviews also conducted. Microbiologically, the quality of food items delivered by both systems was satisfactory. However, concern was raised with the plated system, not for hot foods cooling down but for chilled foods warming up and being sustained in ambient conditions. Overall consumer satisfaction and experience was enhanced with the trolley system. Food was hotter and generally perceived to be of a better quality. Satisfaction with cold desserts was not dependent on the delivery system.

Estimation of Parameters from Discrete Random Nonstationary Time Series

NASA Astrophysics Data System (ADS)

Takayasu, H.; Nakamura, T.

For the analysis of nonstationary stochastic time series we introduce a formulation to estimate the underlying time-dependent parameters. This method is designed for random events with small numbers that are out of the applicability range of the normal distribution. The method is demonstrated for numerical data generated by a known system, and applied to time series of traffic accidents, batting average of a baseball player and sales volume of home electronics.

Approximate Bayesian Computation by Subset Simulation using hierarchical state-space models

NASA Astrophysics Data System (ADS)

Vakilzadeh, Majid K.; Huang, Yong; Beck, James L.; Abrahamsson, Thomas

2017-02-01

A new multi-level Markov Chain Monte Carlo algorithm for Approximate Bayesian Computation, ABC-SubSim, has recently appeared that exploits the Subset Simulation method for efficient rare-event simulation. ABC-SubSim adaptively creates a nested decreasing sequence of data-approximating regions in the output space that correspond to increasingly closer approximations of the observed output vector in this output space. At each level, multiple samples of the model parameter vector are generated by a component-wise Metropolis algorithm so that the predicted output corresponding to each parameter value falls in the current data-approximating region. Theoretically, if continued to the limit, the sequence of data-approximating regions would converge on to the observed output vector and the approximate posterior distributions, which are conditional on the data-approximation region, would become exact, but this is not practically feasible. In this paper we study the performance of the ABC-SubSim algorithm for Bayesian updating of the parameters of dynamical systems using a general hierarchical state-space model. We note that the ABC methodology gives an approximate posterior distribution that actually corresponds to an exact posterior where a uniformly distributed combined measurement and modeling error is added. We also note that ABC algorithms have a problem with learning the uncertain error variances in a stochastic state-space model and so we treat them as nuisance parameters and analytically integrate them out of the posterior distribution. In addition, the statistical efficiency of the original ABC-SubSim algorithm is improved by developing a novel strategy to regulate the proposal variance for the component-wise Metropolis algorithm at each level. We demonstrate that Self-regulated ABC-SubSim is well suited for Bayesian system identification by first applying it successfully to model updating of a two degree-of-freedom linear structure for three cases: globally, locally and un-identifiable model classes, and then to model updating of a two degree-of-freedom nonlinear structure with Duffing nonlinearities in its interstory force-deflection relationship.

Mathematical modelling of the human cardiovascular system in the presence of stenosis

NASA Technical Reports Server (NTRS)

Sud, V. K.; Srinivasan, R. S.; Charles, J. B.; Bungo, M. W.

1993-01-01

This paper reports a theoretical study on the distribution of blood flow in the human cardiovascular system when one or more blood vessels are affected by stenosis. The analysis employs a mathematical model of the entire system based on the finite element method. The arterial-venous network is represented by a large number of interconnected segments in the model. Values for the model parameters are based upon the published data on the physiological and rheological properties of blood. Computational results show how blood flow through various parts of the cardiovascular system is affected by stenosis in different blood vessels. No significant changes in the flow parameters of the cardiovascular system were found to occur when the reduction in the lumen diameter of the stenosed vessels was less than 65%.

Statistical simplex approach to primary and secondary color correction in thick lens assemblies

NASA Astrophysics Data System (ADS)

Ament, Shelby D. V.; Pfisterer, Richard

2017-11-01

A glass selection optimization algorithm is developed for primary and secondary color correction in thick lens systems. The approach is based on the downhill simplex method, and requires manipulation of the surface color equations to obtain a single glass-dependent parameter for each lens element. Linear correlation is used to relate this parameter to all other glass-dependent variables. The algorithm provides a statistical distribution of Abbe numbers for each element in the system. Examples of several lenses, from 2-element to 6-element systems, are performed to verify this approach. The optimization algorithm proposed is capable of finding glass solutions with high color correction without requiring an exhaustive search of the glass catalog.

NASA Exhibits

NASA Technical Reports Server (NTRS)

Deardorff, Glenn; Djomehri, M. Jahed; Freeman, Ken; Gambrel, Dave; Green, Bryan; Henze, Chris; Hinke, Thomas; Hood, Robert; Kiris, Cetin; Moran, Patrick;

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.

Statistical analysis of modal parameters of a suspension bridge based on Bayesian spectral density approach and SHM data

NASA Astrophysics Data System (ADS)

Li, Zhijun; Feng, Maria Q.; Luo, Longxi; Feng, Dongming; Xu, Xiuli

2018-01-01

Uncertainty of modal parameters estimation appear in structural health monitoring (SHM) practice of civil engineering to quite some significant extent due to environmental influences and modeling errors. Reasonable methodologies are needed for processing the uncertainty. Bayesian inference can provide a promising and feasible identification solution for the purpose of SHM. However, there are relatively few researches on the application of Bayesian spectral method in the modal identification using SHM data sets. To extract modal parameters from large data sets collected by SHM system, the Bayesian spectral density algorithm was applied to address the uncertainty of mode extraction from output-only response of a long-span suspension bridge. The posterior most possible values of modal parameters and their uncertainties were estimated through Bayesian inference. A long-term variation and statistical analysis was performed using the sensor data sets collected from the SHM system of the suspension bridge over a one-year period. The t location-scale distribution was shown to be a better candidate function for frequencies of lower modes. On the other hand, the burr distribution provided the best fitting to the higher modes which are sensitive to the temperature. In addition, wind-induced variation of modal parameters was also investigated. It was observed that both the damping ratios and modal forces increased during the period of typhoon excitations. Meanwhile, the modal damping ratios exhibit significant correlation with the spectral intensities of the corresponding modal forces.

Capability of Hyperspectral data in Spatial Variability Distribution of Chlorophyll and Water Stress in Rice Agriculture System

NASA Astrophysics Data System (ADS)

Moharana, S.; Dutta, S.

2016-12-01

Abstract : The mapping and analysis of spatial variability within the field is a challenging task. However, field variability of a single vegetation cover does not give satisfactory results mainly due to low spectral resolution and non-availability of remote sensing data. From the NASA Earth Observing-1 (EO-1) satellite data, spatial distribution of biophysical parameters like chlorophyll and relative water content in a rice agriculture system is carried out in the present study. Hyperion L1R product composed of 242 spectral bands with 30m spatial resolution was acquired for Assam, India. This high dimensional data is allowed for pre-processing to get an atmospherically corrected imagery. Moreover, ground based hyperspectral measurements are collected from experimental rice fields from the study site using hand held ASD spectroradiometer (350-1050 nm). Published indices specifically designed for chlorophyll (OASVI, mSR, and MTCI indices) and water content (WI and WBI indices) are selected based on stastical performance of the in-situ hyperspectral data. Index models are established for the respective biophysical parameters and observed that the aforementioned indices followed different linear and nonlinear relationships which are completely different from the published indices. By employing the presently developed relationships, spatial variation of total chlorophyll and water stress are mapped for a rice agriculture system from Hyperion imagery. The findings showed that, the variation of chlorophyll and water content ranged from 1.77-10.61mg/g and 40-90% respectively for the studied rice agriculture system. The spatial distribution of these parameters resulted from presently developed index models are well captured from Hyperion imagery and they have good agreement with observed field based chlorophyll (1.14-7.26 mg/g) and water content (60-95%) of paddy crop. This study can be useful in providing essential information to assess the paddy field heterogeneity in an agriculture system. Keywords: Paddy crop, vegetation index, hyperspectral data, chlorophyll, water content

A Family of Poisson Processes for Use in Stochastic Models of Precipitation

NASA Astrophysics Data System (ADS)

Penland, C.

2013-12-01

Both modified Poisson processes and compound Poisson processes can be relevant to stochastic parameterization of precipitation. This presentation compares the dynamical properties of these systems and discusses the physical situations in which each might be appropriate. If the parameters describing either class of systems originate in hydrodynamics, then proper consideration of stochastic calculus is required during numerical implementation of the parameterization. It is shown here that an improper numerical treatment can have severe implications for estimating rainfall distributions, particularly in the tails of the distributions and, thus, on the frequency of extreme events.

Form factors and generalized parton distributions in basis light-front quantization

NASA Astrophysics Data System (ADS)

Adhikari, Lekha; Li, Yang; Zhao, Xingbo; Maris, Pieter; Vary, James P.; El-Hady, Alaa Abd

2016-05-01

We calculate the elastic form factors and the generalized parton distributions (GPDs) for four low-lying bound states of a demonstration fermion-antifermion system, strong-coupling positronium (e e ¯ ), using basis light-front quantization (BLFQ). By using this approach, we also calculate the impact-parameter-dependent GPDs q (x ,b⃗⊥) to visualize the fermion density in the transverse plane (b⃗⊥). We compare selected results with corresponding quantities in the nonrelativistic limit to reveal relativistic effects. Our results establish the foundation within BLFQ for investigating the form factors and the GPDs for hadronic systems.

High-resolution distributed temperature sensing with the multiphoton-timing technique

NASA Astrophysics Data System (ADS)

Höbel, M.; Ricka, J.; Wüthrich, M.; Binkert, Th.

1995-06-01

We report on a multiphoton-timing distributed temperature sensor (DTS) based on the concept of distributed anti-Stokes Raman thermometry. The sensor combines the advantage of very high spatial resolution (40 cm) with moderate measurement times. In 5 min it is possible to determine the temperature of as many as 4000 points along an optical fiber with an accuracy Delta T less than 2 deg C. The new feature of the DTS system is the combination of a fast single-photon avalanche diode with specially designed real-time signal-processing electronics. We discuss various parameters that affect the operation of analog and photon-timing DTS systems. Particular emphasis is put on the consequences of the nonideal behavior of sensor components and the corresponding correction procedures.

Density-based penalty parameter optimization on C-SVM.

PubMed

Liu, Yun; Lian, Jie; Bartolacci, Michael R; Zeng, Qing-An

2014-01-01

The support vector machine (SVM) is one of the most widely used approaches for data classification and regression. SVM achieves the largest distance between the positive and negative support vectors, which neglects the remote instances away from the SVM interface. In order to avoid a position change of the SVM interface as the result of an error system outlier, C-SVM was implemented to decrease the influences of the system's outliers. Traditional C-SVM holds a uniform parameter C for both positive and negative instances; however, according to the different number proportions and the data distribution, positive and negative instances should be set with different weights for the penalty parameter of the error terms. Therefore, in this paper, we propose density-based penalty parameter optimization of C-SVM. The experiential results indicated that our proposed algorithm has outstanding performance with respect to both precision and recall.

Polarization variations in installed fibers and their influence on quantum key distribution systems.

PubMed

Ding, Yu-Yang; Chen, Hua; Wang, Shuang; He, De-Yong; Yin, Zhen-Qiang; Chen, Wei; Zhou, Zheng; Guo, Guang-Can; Han, Zheng-Fu

2017-10-30

Polarization variations in the installed fibers are complex and volatile, and would severely affect the performances of polarization-sensitive quantum key distribution (QKD) systems. Based on the recorded data about polarization variations of different installed fibers, we establish an analytical methodology to quantitatively evaluate the influence of polarization variations on polarization-sensitive QKD systems. Using the increased quantum bit error rate induced by polarization variations as a key criteria, we propose two parameters - polarization drift time and required tracking speed - to characterize polarization variations. For field buried and aerial fibers with different length, we quantitatively evaluate the influence of polarization variations, and also provide requirements and suggestions for polarization basis alignment modules of QKD systems deployed in different kind of fibers.

Parameter estimation for the 4-parameter Asymmetric Exponential Power distribution by the method of L-moments using R

USGS Publications Warehouse

Asquith, William H.

2014-01-01

The implementation characteristics of two method of L-moments (MLM) algorithms for parameter estimation of the 4-parameter Asymmetric Exponential Power (AEP4) distribution are studied using the R environment for statistical computing. The objective is to validate the algorithms for general application of the AEP4 using R. An algorithm was introduced in the original study of the L-moments for the AEP4. A second or alternative algorithm is shown to have a larger L-moment-parameter domain than the original. The alternative algorithm is shown to provide reliable parameter production and recovery of L-moments from fitted parameters. A proposal is made for AEP4 implementation in conjunction with the 4-parameter Kappa distribution to create a mixed-distribution framework encompassing the joint L-skew and L-kurtosis domains. The example application provides a demonstration of pertinent algorithms with L-moment statistics and two 4-parameter distributions (AEP4 and the Generalized Lambda) for MLM fitting to a modestly asymmetric and heavy-tailed dataset using R.

Statistical Analysis of Adaptive Beam-Forming Methods

DTIC Science & Technology

1988-05-01

minimum amount of computing resources? * What are the tradeoffs being made when a system design selects block averaging over exponential averaging? Will...understood by many signal processing practitioners, however, is how system parameters and the number of sensors effect the distribution of the... system performance improve and if so by how much? b " It is well known that the noise sampled at adjacent sensors is not statistically independent

A distributed approach for optimizing cascaded classifier topologies in real-time stream mining systems.

PubMed

Foo, Brian; van der Schaar, Mihaela

2010-11-01

In this paper, we discuss distributed optimization techniques for configuring classifiers in a real-time, informationally-distributed stream mining system. Due to the large volume of streaming data, stream mining systems must often cope with overload, which can lead to poor performance and intolerable processing delay for real-time applications. Furthermore, optimizing over an entire system of classifiers is a difficult task since changing the filtering process at one classifier can impact both the feature values of data arriving at classifiers further downstream and thus, the classification performance achieved by an ensemble of classifiers, as well as the end-to-end processing delay. To address this problem, this paper makes three main contributions: 1) Based on classification and queuing theoretic models, we propose a utility metric that captures both the performance and the delay of a binary filtering classifier system. 2) We introduce a low-complexity framework for estimating the system utility by observing, estimating, and/or exchanging parameters between the inter-related classifiers deployed across the system. 3) We provide distributed algorithms to reconfigure the system, and analyze the algorithms based on their convergence properties, optimality, information exchange overhead, and rate of adaptation to non-stationary data sources. We provide results using different video classifier systems.

Uniwavelength lidar sensitivity to spherical aerosol microphysical properties for the interpretation of Lagrangian stratospheric observations

NASA Astrophysics Data System (ADS)

Jumelet, Julien; David, Christine; Bekki, Slimane; Keckhut, Philippe

2009-01-01

The determination of stratospheric particle microphysical properties from multiwavelength lidar, including Rayleigh and/or Raman detection, has been widely investigated. However, most lidar systems are uniwavelength operating at 532 nm. Although the information content of such lidar data is too limited to allow the retrieval of the full size distribution, the coupling of two or more uniwavelength lidar measurements probing the same moving air parcel may provide some meaningful size information. Within the ORACLE-O3 IPY project, the coordination of several ground-based lidars and the CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) space-borne lidar is planned during measurement campaigns called MATCH-PSC (Polar Stratospheric Clouds). While probing the same moving air masses, the evolution of the measured backscatter coefficient (BC) should reflect the variation of particles microphysical properties. A sensitivity study of 532 nm lidar particle backscatter to variations of particles size distribution parameters is carried out. For simplicity, the particles are assumed to be spherical (liquid) particles and the size distribution is represented with a unimodal log-normal distribution. Each of the four microphysical parameters (i.e. log-normal size distribution parameters, refractive index) are analysed separately, while the three others are remained set to constant reference values. Overall, the BC behaviour is not affected by the initial values taken as references. The total concentration (N0) is the parameter to which BC is least sensitive, whereas it is most sensitive to the refractive index (m). A 2% variation of m induces a 15% variation of the lidar BC, while the uncertainty on the BC retrieval can also reach 15%. This result underlines the importance of having both an accurate lidar inversion method and a good knowledge of the temperature for size distribution retrieval techniques. The standard deviation ([sigma]) is the second parameter to which BC is most sensitive to. Yet, the impact of m and [sigma] on BC variations is limited by the realistic range of their variations. The mean radius (rm) of the size distribution is thus the key parameter for BC, as it can vary several-fold. BC is most sensitive to the presence of large particles. The sensitivity of BC to rm and [sigma] variations increases when the initial size distributions are characterized by low rm and large [sigma]. This makes lidar more suitable to detect particles growing on background aerosols than on volcanic aerosols.

Computational control of flexible aerospace systems

NASA Technical Reports Server (NTRS)

Sharpe, Lonnie, Jr.; Shen, Ji Yao

1994-01-01

The main objective of this project is to establish a distributed parameter modeling technique for structural analysis, parameter estimation, vibration suppression and control synthesis of large flexible aerospace structures. This report concentrates on the research outputs produced in the last two years. The main accomplishments can be summarized as follows. A new version of the PDEMOD Code had been completed based on several incomplete versions. The verification of the code had been conducted by comparing the results with those examples for which the exact theoretical solutions can be obtained. The theoretical background of the package and the verification examples has been reported in a technical paper submitted to the Joint Applied Mechanics & Material Conference, ASME. A brief USER'S MANUAL had been compiled, which includes three parts: (1) Input data preparation; (2) Explanation of the Subroutines; and (3) Specification of control variables. Meanwhile, a theoretical investigation of the NASA MSFC two-dimensional ground-based manipulator facility by using distributed parameter modeling technique has been conducted. A new mathematical treatment for dynamic analysis and control of large flexible manipulator systems has been conceived, which may provide an embryonic form of a more sophisticated mathematical model for future modified versions of the PDEMOD Codes.

Perceiving while producing: Modeling the dynamics of phonological planning

PubMed Central

Roon, Kevin D.; Gafos, Adamantios I.

2016-01-01

We offer a dynamical model of phonological planning that provides a formal instantiation of how the speech production and perception systems interact during online processing. The model is developed on the basis of evidence from an experimental task that requires concurrent use of both systems, the so-called response-distractor task in which speakers hear distractor syllables while they are preparing to produce required responses. The model formalizes how ongoing response planning is affected by perception and accounts for a range of results reported across previous studies. It does so by explicitly addressing the setting of parameter values in representations. The key unit of the model is that of the dynamic field, a distribution of activation over the range of values associated with each representational parameter. The setting of parameter values takes place by the attainment of a stable distribution of activation over the entire field, stable in the sense that it persists even after the response cue in the above experiments has been removed. This and other properties of representations that have been taken as axiomatic in previous work are derived by the dynamics of the proposed model. PMID:27440947