Model Predictive Control-Based Fast Charging for Vehicular Batteries
Directory of Open Access Journals (Sweden)
Zhibin Song
2011-08-01
Full Text Available Battery fast charging is one of the most significant and difficult techniques affecting the commercialization of electric vehicles (EVs. In this paper, we propose a fast charge framework based on model predictive control, with the aim of simultaneously reducing the charge duration, which represents the out-of-service time of vehicles, and the increase in temperature, which represents safety and energy efficiency during the charge process. The RC model is employed to predict the future State of Charge (SOC. A single mode lumped-parameter thermal model and a neural network trained by real experimental data are also applied to predict the future temperature in simulations and experiments respectively. A genetic algorithm is then applied to find the best charge sequence under a specified fitness function, which consists of two objectives: minimizing the charging duration and minimizing the increase in temperature. Both simulation and experiment demonstrate that the Pareto front of the proposed method dominates that of the most popular constant current constant voltage (CCCV charge method.
Charge transport model to predict intrinsic reliability for dielectric materials
Energy Technology Data Exchange (ETDEWEB)
Ogden, Sean P. [Howard P. Isermann Department of Chemical and Biological Engineering, Rensselaer Polytechnic Institute, Troy, New York 12180 (United States); GLOBALFOUNDRIES, 400 Stonebreak Rd. Ext., Malta, New York 12020 (United States); Borja, Juan; Plawsky, Joel L., E-mail: plawsky@rpi.edu; Gill, William N. [Howard P. Isermann Department of Chemical and Biological Engineering, Rensselaer Polytechnic Institute, Troy, New York 12180 (United States); Lu, T.-M. [Department of Physics, Rensselaer Polytechnic Institute, Troy, New York 12180 (United States); Yeap, Kong Boon [GLOBALFOUNDRIES, 400 Stonebreak Rd. Ext., Malta, New York 12020 (United States)
2015-09-28
Several lifetime models, mostly empirical in nature, are used to predict reliability for low-k dielectrics used in integrated circuits. There is a dispute over which model provides the most accurate prediction for device lifetime at operating conditions. As a result, there is a need to transition from the use of these largely empirical models to one built entirely on theory. Therefore, a charge transport model was developed to predict the device lifetime of low-k interconnect systems. The model is based on electron transport and donor-type defect formation. Breakdown occurs when a critical defect concentration accumulates, resulting in electron tunneling and the emptying of positively charged traps. The enhanced local electric field lowers the barrier for electron injection into the dielectric, causing a positive feedforward failure. The charge transport model is able to replicate experimental I-V and I-t curves, capturing the current decay at early stress times and the rapid current increase at failure. The model is based on field-driven and current-driven failure mechanisms and uses a minimal number of parameters. All the parameters have some theoretical basis or have been measured experimentally and are not directly used to fit the slope of the time-to-failure versus applied field curve. Despite this simplicity, the model is able to accurately predict device lifetime for three different sources of experimental data. The simulation's predictions at low fields and very long lifetimes show that the use of a single empirical model can lead to inaccuracies in device reliability.
Electric vehicle charge planning using Economic Model Predictive Control
DEFF Research Database (Denmark)
Halvgaard, Rasmus; Poulsen, Niels K.; Madsen, Henrik;
2012-01-01
Economic Model Predictive Control (MPC) is very well suited for controlling smart energy systems since electricity price and demand forecasts are easily integrated in the controller. Electric vehicles (EVs) are expected to play a large role in the future Smart Grid. They are expected to provide...... grid services, both for peak reduction and for ancillary services, by absorbing short term variations in the electricity production. In this paper the Economic MPC minimizes the cost of electricity consumption for a single EV. Simulations show savings of 50–60% of the electricity costs compared...... should be consumed as soon as it is produced to avoid the need for energy storage as this is expensive, limited and introduces efficiency losses. The Economic MPC for EVs described in this paper may contribute to facilitating transition to a fossil free energy system....
Lint, de W.B. Samuel; Benes, Nieck E.
2004-01-01
The charge-regulation concept is combined with the theory of irreversible processes to predict multi-component electrolyte transport in nanofiltration membranes. Charging of the membrane surface is described using a 1-pK site-binding model with a triple-layer electrostatic description. Mass transpor
Prediction Model of Battery State of Charge and Control Parameter Optimization for Electric Vehicle
Directory of Open Access Journals (Sweden)
Bambang Wahono
2015-07-01
Full Text Available This paper presents the construction of a battery state of charge (SOC prediction model and the optimization method of the said model to appropriately control the number of parameters in compliance with the SOC as the battery output objectives. Research Centre for Electrical Power and Mechatronics, Indonesian Institute of Sciences has tested its electric vehicle research prototype on the road, monitoring its voltage, current, temperature, time, vehicle velocity, motor speed, and SOC during the operation. Using this experimental data, the prediction model of battery SOC was built. Stepwise method considering multicollinearity was able to efficiently develops the battery prediction model that describes the multiple control parameters in relation to the characteristic values such as SOC. It was demonstrated that particle swarm optimization (PSO succesfully and efficiently calculated optimal control parameters to optimize evaluation item such as SOC based on the model.
A PREDICTING MODEL OF THE LIMITING FLUX FOR THE CHARGED SOLUTE IN ULTRAFILTRATION PROCESS
Institute of Scientific and Technical Information of China (English)
LUO Ming-liang; GUO Yan; PU Chun-sheng; LU Feng-ji
2004-01-01
In the process of ultrafiltration , the occur-rence of the limiting flux is elucidated with the formation of a cake(gel) layer on the membrane surface. Before cake formation, the pressure drop on the concentration polarization layer, as well as the permeate flux, increases with the applied pressure. The pressure drop on the concentration polarization layer, however, will no longer change with the applied pressure after the formation of the cake layer. The limiting flux will be obtained if the hydrodynamic conditions in the filtration channel are not affected by the cake layer. A mathematics model for predicting the limiting flux for the charged solute in ultrafiltration is developed. In this model, a repulsive electric force is taken into account in addition to convection and diffusion when the solute is carrying the same charge as the membrane material. A procedure to correlate the model with experimental ultrafiltration data is also present. The results show that a model in this paper is developed on a more realistic perception of the ultrafiltration system and the predicting data agrees well with experimental data.
Kim, Myung-Hee Y.; Cucinotta, Francis A.; Zeitlin, Cary; Hassler, Donald M.; Ehresmann, Bent; Rafkin, Scot C. R.; Wimmer-Schweingruber, Robert F.; Boettcher, Stephan; Boehm, Eckart; Guo, Jingnan; Koehler, Jan; Martin, Cesar; Reitz, Guenther; Posner, Arik
2014-01-01
Detailed measurements of the energetic particle radiation environment on the surface of Mars have been made by the Radiation Assessment Detector (RAD) on the Curiosity rover since August 2012. RAD is a particle detector that measures the energy spectrum of charged particles (10 to approx. 200 MeV/u) and high energy neutrons (approx 8 to 200 MeV). The data obtained on the surface of Mars for 300 sols are compared to the simulation results using the Badhwar-O'Neill galactic cosmic ray (GCR) environment model and the high-charge and energy transport (HZETRN) code. For the nuclear interactions of primary GCR through Mars atmosphere and Curiosity rover, the quantum multiple scattering theory of nuclear fragmentation (QMSFRG) is used. For describing the daily column depth of atmosphere, daily atmospheric pressure measurements at Gale Crater by the MSL Rover Environmental Monitoring Station (REMS) are implemented into transport calculations. Particle flux at RAD after traversing varying depths of atmosphere depends on the slant angles, and the model accounts for shielding of the RAD "E" dosimetry detector by the rest of the instrument. Detailed comparisons between model predictions and spectral data of various particle types provide the validation of radiation transport models, and suggest that future radiation environments on Mars can be predicted accurately. These contributions lend support to the understanding of radiation health risks to astronauts for the planning of various mission scenarios
Surface Complexation Modeling in Variable Charge Soils: Prediction of Cadmium Adsorption
Directory of Open Access Journals (Sweden)
Giuliano Marchi
2015-10-01
Full Text Available ABSTRACT Intrinsic equilibrium constants for 22 representative Brazilian Oxisols were estimated from a cadmium adsorption experiment. Equilibrium constants were fitted to two surface complexation models: diffuse layer and constant capacitance. Intrinsic equilibrium constants were optimized by FITEQL and by hand calculation using Visual MINTEQ in sweep mode, and Excel spreadsheets. Data from both models were incorporated into Visual MINTEQ. Constants estimated by FITEQL and incorporated in Visual MINTEQ software failed to predict observed data accurately. However, FITEQL raw output data rendered good results when predicted values were directly compared with observed values, instead of incorporating the estimated constants into Visual MINTEQ. Intrinsic equilibrium constants optimized by hand calculation and incorporated in Visual MINTEQ reliably predicted Cd adsorption reactions on soil surfaces under changing environmental conditions.
International Nuclear Information System (INIS)
Highlights: ► Max torque and power values were obtained at 3.5 bar Pch, 1273 K Hst and 1.4:1 r. ► According to ANOVA, the most influential parameter on power was Hst with 48.75%. ► According to ANOVA, the most influential parameter on torque was Hst with 41.78%. ► ANN (R2 = 99.8% for T, P) was superior to regression method (R2 = 92% for T, 81% for P). ► LM was the best learning algorithm in predicting both power and torque. - Abstract: In this study, an artificial neural network (ANN) model was developed to predict the torque and power of a beta-type Stirling engine using helium as the working fluid. The best results were obtained by 5-11-7-1 and 5-13-7-1 network architectures, with double hidden layers for the torque and power respectively. For these network architectures, the Levenberg–Marquardt (LM) learning algorithm was used. Engine performance values predicted with the developed ANN model were compared with the actual performance values measured experimentally, and substantially coinciding results were observed. After ANN training, correlation coefficients (R2) of both engine performance values for testing and training data were very close to 1. Similarly, root-mean-square error (RMSE) and mean error percentage (MEP) values for the testing and training data were less than 0.02% and 3.5% respectively. These results showed that the ANN is an acceptable model for prediction of the torque and power of the beta-type Stirling engine
Energy Technology Data Exchange (ETDEWEB)
Pierce, Flint; Grillet, Anne Mary; Grest, Gary Stephen; Lechman, Jeremy B.; Plimpton, Steven James; in' t Veld, Pieter J. (BASF Corporation Ludwigshafen, Germany); Schunk, Peter Randall; Heine, D. R. (Corning, Inc. Corning, NY); Stoltz, C. (Procter and Gamble Co. West Chester, OH); Weiss, Horst (BASF Corporation Ludwigshafen, Germany); Jendrejack, R. (3M Corporation St. Paul, MN); Petersen, Matthew K.
2010-06-01
In this presentation we examine the accuracy and performance of a suite of discrete-element-modeling approaches to predicting equilibrium and dynamic rheological properties of polystyrene suspensions. What distinguishes each approach presented is the methodology of handling the solvent hydrodynamics. Specifically, we compare stochastic rotation dynamics (SRD), fast lubrication dynamics (FLD) and dissipative particle dynamics (DPD). Method-to-method comparisons are made as well as comparisons with experimental data. Quantities examined are equilibrium structure properties (e.g. pair-distribution function), equilibrium dynamic properties (e.g. short- and long-time diffusivities), and dynamic response (e.g. steady shear viscosity). In all approaches we deploy the DLVO potential for colloid-colloid interactions. Comparisons are made over a range of volume fractions and salt concentrations. Our results reveal the utility of such methods for long-time diffusivity prediction can be dubious in certain ranges of volume fraction, and other discoveries regarding the best formulation to use in predicting rheological response.
Carmona Benitez, R.B.; Lodewijiks, G.
2010-01-01
A mathematical model to estimate the average airlines operational costs and airports charges per route is important for airlines companies trying to open new routes and for data generation for other purpose such as transport modeling, simulation modeling, investment analyses for airlines and airport
Electrostatic charge bounds for ball lightning models
Energy Technology Data Exchange (ETDEWEB)
Stephan, Karl D [Department of Technology, Texas State University, San Marcos, TX 78666 (United States)], E-mail: kdstephan@txstate.edu
2008-03-15
Several current theories concerning the nature of ball lightning predict a substantial electrostatic charge in order to account for its observed motion and shape (Turner 1998 Phys. Rep. 293 1; Abrahamson and Dinniss 2000 Nature 403 519). Using charged soap bubbles as a physical model for ball lightning, we show that the magnitude of charge predicted by some of these theories is too high to allow for the types of motion commonly observed in natural ball lightning, which includes horizontal motion above the ground and movement near grounded conductors. Experiments show that at charge levels of only 10-15 nC, 3-cm-diameter soap bubbles tend to be attracted by induced charges to the nearest grounded conductor and rupture. We conclude with a scaling rule that can be used to extrapolate these results to larger objects and surroundings.
Borstnik, Norma Susana Mankoc
2013-01-01
This contribution is to show how does the spin-charge-family theory interpret the assumptions of the standard model, and those extensions of this model, which are trying to see the Yukawa couplings as scalar fields with the family (flavour) charges in the fundamental representations of the group. The purpose of these contribution is i.) to try to understand why the standard model works so well, although its assumptions look quite artificial, and ii.) how do predictions of the spin-charge-family theory about the measurements of the scalar fields differ from predictions of the {\\em standard model}, which has only one scalar field - the Higgs - and also from its more or less direct extensions with Yukawas as the scalar dynamical fields with the family charge in the fundamental or anti-fundamental representation of group.
Directory of Open Access Journals (Sweden)
Arteaga-Velázquez J.C.
2015-01-01
Full Text Available KASCADE-Grande was an air-shower experiment designed to study cosmic rays between 1016 and 1018 eV. The instrument was located at the site of the Karlsruhe Institute of Technology, Germany at an altitude of 110 m a.s.l. and covered an area of 0.5 km2. KASCADE-Grande consisted of several detector systems dedicated to measure different components of the EAS generated by the primary cosmic rays, i.e., the muon and the electron contents of the air-shower. With such a number of EAS observables and the precision of the measurements, the KASCADE-Grande data can be used to not only study in detail the properties of cosmic rays but also to test the predictions of hadronic-interaction models. In this work, in particular, the attenuation lengths of the muon number and the charged number of particles of EAS in the atmosphere were extracted from the KASCADE-Grande data and the results were compared with the predictions of the new EPOS-LHC hadronic-interaction model.
New charged anisotropic compact models
Kileba Matondo, D.; Maharaj, S. D.
2016-07-01
We find new exact solutions to the Einstein-Maxwell field equations which are relevant in the description of highly compact stellar objects. The relativistic star is charged and anisotropic with a quark equation of state. Exact solutions of the field equations are found in terms of elementary functions. It is interesting to note that we regain earlier quark models with uncharged and charged matter distributions. A physical analysis indicates that the matter distributions are well behaved and regular throughout the stellar structure. A range of stellar masses are generated for particular parameter values in the electric field. In particular the observed mass for a binary pulsar is regained.
Theory and applications of fluctuating-charge models
Chen, Jiahao
2010-01-01
Fluctuating-charge models are computationally efficient methods of treating polarization and charge-transfer phenomena in molecular mechanics and classical molecular dynamics simulations. They are also theoretically appealing as they are minimally parameterized, with parameters corresponding to the chemically important concepts of electronegativities and chemical hardness. However, they are known to overestimate charge transfer for widely separated atoms, leading to qualitative errors in the predicted charge distribution and exaggerated electrostatic properties. We present the charge transfer with polarization current equilibration (QTPIE) model, which solves this problem by introducing distance-dependent electronegativities. A graph-theoretic analysis of the topology of charge transfer allows us to relate the fundamental quantities of charge transfer back to the more familiar variables that represent atomic partial charges. This allows us to formulate a unified theoretical framework for fluctuating-charge mo...
Borštnik, Norma Susana Mankoč
2016-01-01
The spin-charge-family theory, which is a kind of the Kaluza-Klein theories but with fermions carrying two kinds of spins (no charges), offers the explanation for all the assumptions of the standard model, with the origin of families, the higgs and the Yukawa couplings included. It offers the explanation also for other phenomena, like the origin of the dark matter and of the matter/antimatter asymmetry in the universe. It predicts the existence of the fourth family to the observed three, as w...
Visualizing Risk Prediction Models
Vanya Van Belle; Ben Van Calster
2015-01-01
Objective Risk prediction models can assist clinicians in making decisions. To boost the uptake of these models in clinical practice, it is important that end-users understand how the model works and can efficiently communicate its results. We introduce novel methods for interpretable model visualization. Methods The proposed visualization techniques are applied to two prediction models from the Framingham Heart Study for the prediction of intermittent claudication and stroke after atrial fib...
Modeling charge transport in organic photovoltaic materials.
Nelson, Jenny; Kwiatkowski, Joe J; Kirkpatrick, James; Frost, Jarvist M
2009-11-17
The performance of an organic photovoltaic cell depends critically on the mobility of charge carriers within the constituent molecular semiconductor materials. However, a complex combination of phenomena that span a range of length and time scales control charge transport in disordered organic semiconductors. As a result, it is difficult to rationalize charge transport properties in terms of material parameters. Until now, efforts to improve charge mobilities in molecular semiconductors have proceeded largely by trial and error rather than through systematic design. However, recent developments have enabled the first predictive simulation studies of charge transport in disordered organic semiconductors. This Account describes a set of computational methods, specifically molecular modeling methods, to simulate molecular packing, quantum chemical calculations of charge transfer rates, and Monte Carlo simulations of charge transport. Using case studies, we show how this combination of methods can reproduce experimental mobilities with few or no fitting parameters. Although currently applied to material systems of high symmetry or well-defined structure, further developments of this approach could address more complex systems such anisotropic or multicomponent solids and conjugated polymers. Even with an approximate treatment of packing disorder, these computational methods simulate experimental mobilities within an order of magnitude at high electric fields. We can both reproduce the relative values of electron and hole mobility in a conjugated small molecule and rationalize those values based on the symmetry of frontier orbitals. Using fully atomistic molecular dynamics simulations of molecular packing, we can quantitatively replicate vertical charge transport along stacks of discotic liquid crystals which vary only in the structure of their side chains. We can reproduce the trends in mobility with molecular weight for self-organizing polymers using a cheap, coarse
Predictive models of radiative neutrino masses
Julio, J.
2016-06-01
We discuss two models of radiative neutrino mass generation. The first model features one-loop Zee model with Z4 symmetry. The second model is the two-loop neutrino mass model with singly- and doubly-charged scalars. These two models fit neutrino oscillation data well and predict some interesting rates for lepton flavor violation processes.
Predictive modeling of complications.
Osorio, Joseph A; Scheer, Justin K; Ames, Christopher P
2016-09-01
Predictive analytic algorithms are designed to identify patterns in the data that allow for accurate predictions without the need for a hypothesis. Therefore, predictive modeling can provide detailed and patient-specific information that can be readily applied when discussing the risks of surgery with a patient. There are few studies using predictive modeling techniques in the adult spine surgery literature. These types of studies represent the beginning of the use of predictive analytics in spine surgery outcomes. We will discuss the advancements in the field of spine surgery with respect to predictive analytics, the controversies surrounding the technique, and the future directions. PMID:27286683
Zephyr - The prediction models
Energy Technology Data Exchange (ETDEWEB)
Nielsen, T.S.; Madsen, H.; Nielsen, H.Aa. [Informatics and Mathematical Modelling - DTU, Kgs. Lyngby (Denmark); Landberg, L.; Giebel, G. [Risoe National Lab., Roskilde (Denmark)
2006-07-01
This paper briefly describes new models and methods for predicting the wind power output from wind farms. The system is being developed in a project which has the research organization Risoe and the department of Informatics and Mathematical Modelling (IMM) as the modelling team and all the Danish utilities as partners and users. The new models are evaluated for five wind farms in Denmark as well as one wind farm in Spain. It is shown that the predictions based on conditional parametric models are superior to the predictions obtained by state-of-the-art parametric models. (au)
Fuel Burning Rate Model for Stratified Charge Engine
Institute of Scientific and Technical Information of China (English)
SONG Jin'ou; JIANG Zejun; YAO Chunde; WANG Hongfu
2006-01-01
A zero-dimensional single-zone double-curve model is presented to predict fuel burning rate in stratified charge engines, and it is integrated with GT-Power to predict the overall performance of the stratified charge engines.The model consists of two exponential functions for calculating the fuel burning rate in different charge zones.The model factors are determined by a non-linear curve fitting technique, based on the experimental data obtained from 30 cases in middle and low loads.The results show good agreement between the measured and calculated cylinder pressures,and the deviation between calculated and measured cylinder pressures is less than 5%.The zerodimensional single-zone double-curve model is successful in the combustion modeling for stratified charge engines.
Levy, R.; Mcginness, H.
1976-01-01
Investigations were performed to predict the power available from the wind at the Goldstone, California, antenna site complex. The background for power prediction was derived from a statistical evaluation of available wind speed data records at this location and at nearby locations similarly situated within the Mojave desert. In addition to a model for power prediction over relatively long periods of time, an interim simulation model that produces sample wind speeds is described. The interim model furnishes uncorrelated sample speeds at hourly intervals that reproduce the statistical wind distribution at Goldstone. A stochastic simulation model to provide speed samples representative of both the statistical speed distributions and correlations is also discussed.
Zephyr - the prediction models
DEFF Research Database (Denmark)
Nielsen, Torben Skov; Madsen, Henrik; Nielsen, Henrik Aalborg;
2001-01-01
This paper briefly describes new models and methods for predicationg the wind power output from wind farms. The system is being developed in a project which has the research organization Risø and the department of Informatics and Mathematical Modelling (IMM) as the modelling team and all the Danish...... utilities as partners and users. The new models are evaluated for five wind farms in Denmark as well as one wind farm in Spain. It is shown that the predictions based on conditional parametric models are superior to the predictions obatined by state-of-the-art parametric models....
Borštnik, Norma Susana Mankoč
2016-01-01
The spin-charge-family theory, which is a kind of the Kaluza-Klein theories but with fermions carrying two kinds of spins (no charges), offers the explanation for all the assumptions of the standard model, with the origin of families, the higgs and the Yukawa couplings included. It offers the explanation also for other phenomena, like the origin of the dark matter and of the matter/antimatter asymmetry in the universe. It predicts the existence of the fourth family to the observed three, as well as several scalar fields with the weak and the hyper charge of the standard model higgs ($\\pm \\frac{1}{2}, \\mp \\frac{1}{2}$, respectively), which determine the mass matrices of family members, offering an explanation, why the fourth family with the masses above $1$ TeV contributes weakly to the gluon-fusion production of the observed higgs and to its decay into two photons, and predicting that the two photons events, observed at the LHC at $\\approx 750$ GeV, might be an indication for the existence of one of several s...
Discrete Element Modeling of Triboelectrically Charged Particles
Hogue, Michael D.; Calle, Carlos I.; Weitzman, Peter S.; Curry, David R.
2008-01-01
Tribocharging of particles is common in many processes including fine powder handling and mixing, printer toner transport and dust extraction. In a lunar environment with its high vacuum and lack of water, electrostatic forces are an important factor to consider when designing and operating equipment. Dust mitigation and management is critical to safe and predictable performance of people and equipment. The extreme nature of lunar conditions makes it difficult and costly to carry out experiments on earth which are necessary to better understand how particles gather and transfer charge between each other and with equipment surfaces. DEM (Discrete Element Modeling) provides an excellent virtual laboratory for studying tribocharging of particles as well as for design of devices for dust mitigation and for other purposes related to handling and processing of lunar regolith. Theoretical and experimental work has been performed pursuant to incorporating screened Coulombic electrostatic forces into EDEM, a commercial DEM software package. The DEM software is used to model the trajectories of large numbers of particles for industrial particulate handling and processing applications and can be coupled with other solvers and numerical models to calculate particle interaction with surrounding media and force fields. While simple Coulombic force between two particles is well understood, its operation in an ensemble of particles is more complex. When the tribocharging of particles and surfaces due to frictional contact is also considered, it is necessary to consider longer range of interaction of particles in response to electrostatic charging. The standard DEM algorithm accounts for particle mechanical properties and inertia as a function of particle shape and mass. If fluid drag is neglected, then particle dynamics are governed by contact between particles, between particles and equipment surfaces and gravity forces. Consideration of particle charge and any tribocharging and
STRATEGY PATTERNS PREDICTION MODEL
Aram Baruch Gonzalez Perez; Jorge Adolfo Ramirez Uresti
2014-01-01
Multi-agent systems are broadly known for being able to simulate real-life situations which require the interaction and cooperation of individuals. Opponent modeling can be used along with multi-agent systems to model complex situations such as competitions like soccer games. In this study, a model for predicting opponent moves based on their target is presented. The model is composed by an offline step (learning phase) and an online one (execution phase). The offline step gets and analyses p...
STRATEGY PATTERNS PREDICTION MODEL
Directory of Open Access Journals (Sweden)
Aram Baruch Gonzalez Perez
2014-01-01
Full Text Available Multi-agent systems are broadly known for being able to simulate real-life situations which require the interaction and cooperation of individuals. Opponent modeling can be used along with multi-agent systems to model complex situations such as competitions like soccer games. In this study, a model for predicting opponent moves based on their target is presented. The model is composed by an offline step (learning phase and an online one (execution phase. The offline step gets and analyses previous experiences while the online step uses the data generated by offline analysis to predict opponent moves. This model is illustrated by an experiment with the RoboCup 2D Soccer Simulator. The proposed model was tested using 22 games to create the knowledge base and getting an accuracy rate over 80%.
Modeling Charge Collection in Detector Arrays
Hardage, Donna (Technical Monitor); Pickel, J. C.
2003-01-01
A detector array charge collection model has been developed for use as an engineering tool to aid in the design of optical sensor missions for operation in the space radiation environment. This model is an enhancement of the prototype array charge collection model that was developed for the Next Generation Space Telescope (NGST) program. The primary enhancements were accounting for drift-assisted diffusion by Monte Carlo modeling techniques and implementing the modeling approaches in a windows-based code. The modeling is concerned with integrated charge collection within discrete pixels in the focal plane array (FPA), with high fidelity spatial resolution. It is applicable to all detector geometries including monolithc charge coupled devices (CCDs), Active Pixel Sensors (APS) and hybrid FPA geometries based on a detector array bump-bonded to a readout integrated circuit (ROIC).
International Nuclear Information System (INIS)
Prediction model Perla presents one of a tool for an evaluation of a stream ecological status. It enables a comparing with a standard. The standard is formed by a dataset of sites from all area of the Czech Republic. The sites were influenced by a human activity as few as possible. 8 variables were used for prediction (distance from source, elevation, stream width and depth, slope, substrate roughness, longitude and latitude. All of them were statistically important for benthic communities. Results do not response ecoregions, but rather stream size (type). B (EQItaxonu), EQISi, EQIASPT a EQIH appears applicable for assessment using the prediction model and for natural and human stress differentiating. Limiting values of the indices for good ecological status are suggested. On the contrary, using of EQIEPT a EQIekoprof indices would be possible only with difficulties. (authors)
Some phenomenological predictions of charged Higgs bosons in electroweak interactions
Energy Technology Data Exchange (ETDEWEB)
Garcia Canal, C.A.; Santangelo, E.M.
1984-05-01
Some phenomenological consequences of an extended Salam-Weinberg model are studied. In particular, the existence, or absence, of e-..mu.. asymmetry in beam-dump experiments is analyzed and an increase in same sign dilepton cross sections is shown to exist due to the contribution of charged Higgs-mediated diagrams. The model is shown to be compatible with experimental results for other processes.
Prediction and optimization methods for electric vehicle charging schedules in the EDISON project
DEFF Research Database (Denmark)
Aabrandt, Andreas; Andersen, Peter Bach; Pedersen, Anders Bro;
2012-01-01
Smart charging, where the charging of an electric vehicle battery is delayed or advanced in time based on energy costs, grid capacity or renewable contents, has a great potential for increasing the value of the electric vehicle to the owner, the grid and society as a whole. The Danish EDISON...... project has been launched to investigate various areas relevant to electric vehicle integration. As part of EDISON an electric vehicle aggregator has been developed to demonstrate smart charging of electric vehicles. The emphasis of this paper is the mathematical methods on which the EDISON aggregator...... is based. This includes an analysis of the problem of EV driving prediction and charging optimization, a description of the mathematical models implemented and an evaluation of the accuracy of such models. Finally, additional optimization considerations as well as possible future extensions...
Nominal model predictive control
Grüne, Lars
2013-01-01
5 p., to appear in Encyclopedia of Systems and Control, Tariq Samad, John Baillieul (eds.); International audience; Model Predictive Control is a controller design method which synthesizes a sampled data feedback controller from the iterative solution of open loop optimal control problems.We describe the basic functionality of MPC controllers, their properties regarding feasibility, stability and performance and the assumptions needed in order to rigorously ensure these properties in a nomina...
Modeling and Prediction Overview
Energy Technology Data Exchange (ETDEWEB)
Ermak, D L
2002-10-18
Effective preparation for and response to the release of toxic materials into the atmosphere hinges on accurate predictions of the dispersion pathway, concentration, and ultimate fate of the chemical or biological agent. Of particular interest is the threat to civilian populations within major urban areas, which are likely targets for potential attacks. The goals of the CBNP Modeling and Prediction area are: (1) Development of a suite of validated, multi-scale, atmospheric transport and fate modeling capabilities for chemical and biological agent releases within the complex urban environment; (2) Integration of these models and related user tools into operational emergency response systems. Existing transport and fate models are being adapted to treat the complex atmospheric flows within and around structures (e.g., buildings, subway systems, urban areas) and over terrain. Relevant source terms and the chemical and physical behavior of gas- and particle-phase species (e.g., losses due to deposition, bio-agent viability, degradation) are also being developed and incorporated into the models. Model validation is performed using both laboratory and field data. CBNP is producing and testing a suite of models with differing levels of complexity and fidelity to address the full range of user needs and applications. Lumped-parameter transport models are being developed for subway systems and building interiors, supplemented by the use of computational fluid dynamics (CFD) models to describe the circulation within large, open spaces such as auditoriums. Both sophisticated CFD transport models and simpler fast-response models are under development to treat the complex flow around individual structures and arrays of buildings. Urban parameterizations are being incorporated into regional-scale weather forecast, meteorological data assimilation, and dispersion models for problems involving larger-scale urban and suburban areas. Source term and dose response models are being
Multiscale modelling of charge transport in organic electronic materials
Nelson, Jenny
2010-03-01
Charge transport in disordered organic semiconductors is controlled by a complex combination of phenomena that span a range of length and time scales. As a result, it is difficult to rationalize charge transport properties in terms of material parameters. Until now, efforts to improve charge mobilities in molecular semiconductors have proceeded largely by trial and error rather than through systematic design. However, recent developments have enabled the first predictive simulation studies of charge transport in disordered organic semiconductors. In this presentation we will show how a set of computational methods, namely molecular modelling methods to simulate molecular packing, quantum chemical calculations of charge transfer rates, and Monte Carlo simulations of charge transport can be used to reproduce experimental charge mobilities with few or no fitting parameters. Using case studies, we will show how such simulations can explain the relative values of electron and hole mobility and the effects of grain size, side chains and polymer molecular weight on charge mobility. Although currently applied to material systems of relatively high symmetry or well defined structure, this approach can be developed to address more complex systems such as multicomponent solids and conjugated polymers.
Hydrodynamic Model for Charge Carriers
Choquet, Isabelle; Degond, Pierre; Schmeiser, Christian
2003-01-01
A set of hydrodynamic equations modeling strong ionization in semiconductors is formally derived from a kinetic framework. To that purpose, a system of Boltzmann transport equations governing the distribution functions of conduction electrons and holes is considered. Apart from impact ionization, the model accounts for phonon, lattice defects, and particle-particle scattering. Also degeneracy effects are included. The band diagram models are approximations close to the extre...
Electrostatic Model Applied to ISS Charged Water Droplet Experiment
Stevenson, Daan; Schaub, Hanspeter; Pettit, Donald R.
2015-01-01
The electrostatic force can be used to create novel relative motion between charged bodies if it can be isolated from the stronger gravitational and dissipative forces. Recently, Coulomb orbital motion was demonstrated on the International Space Station by releasing charged water droplets in the vicinity of a charged knitting needle. In this investigation, the Multi-Sphere Method, an electrostatic model developed to study active spacecraft position control by Coulomb charging, is used to simulate the complex orbital motion of the droplets. When atmospheric drag is introduced, the simulated motion closely mimics that seen in the video footage of the experiment. The electrostatic force's inverse dependency on separation distance near the center of the needle lends itself to analytic predictions of the radial motion.
Candidate Prediction Models and Methods
DEFF Research Database (Denmark)
Nielsen, Henrik Aalborg; Nielsen, Torben Skov; Madsen, Henrik;
2005-01-01
This document lists candidate prediction models for Work Package 3 (WP3) of the PSO-project called ``Intelligent wind power prediction systems'' (FU4101). The main focus is on the models transforming numerical weather predictions into predictions of power production. The document also outlines the...
Melanoma risk prediction models
Directory of Open Access Journals (Sweden)
Nikolić Jelena
2014-01-01
Full Text Available Background/Aim. The lack of effective therapy for advanced stages of melanoma emphasizes the importance of preventive measures and screenings of population at risk. Identifying individuals at high risk should allow targeted screenings and follow-up involving those who would benefit most. The aim of this study was to identify most significant factors for melanoma prediction in our population and to create prognostic models for identification and differentiation of individuals at risk. Methods. This case-control study included 697 participants (341 patients and 356 controls that underwent extensive interview and skin examination in order to check risk factors for melanoma. Pairwise univariate statistical comparison was used for the coarse selection of the most significant risk factors. These factors were fed into logistic regression (LR and alternating decision trees (ADT prognostic models that were assessed for their usefulness in identification of patients at risk to develop melanoma. Validation of the LR model was done by Hosmer and Lemeshow test, whereas the ADT was validated by 10-fold cross-validation. The achieved sensitivity, specificity, accuracy and AUC for both models were calculated. The melanoma risk score (MRS based on the outcome of the LR model was presented. Results. The LR model showed that the following risk factors were associated with melanoma: sunbeds (OR = 4.018; 95% CI 1.724- 9.366 for those that sometimes used sunbeds, solar damage of the skin (OR = 8.274; 95% CI 2.661-25.730 for those with severe solar damage, hair color (OR = 3.222; 95% CI 1.984-5.231 for light brown/blond hair, the number of common naevi (over 100 naevi had OR = 3.57; 95% CI 1.427-8.931, the number of dysplastic naevi (from 1 to 10 dysplastic naevi OR was 2.672; 95% CI 1.572-4.540; for more than 10 naevi OR was 6.487; 95%; CI 1.993-21.119, Fitzpatricks phototype and the presence of congenital naevi. Red hair, phototype I and large congenital naevi were
Modeling the work piece charging during e-beam lithography
Alles, Benjamin; Cotte, Eric; Simeon, Bernd; Wandel, Timo
2008-03-01
Nowadays, high end photomasks are usually patterned with electron beam writers since they provide a superior resolution. However, placement accuracy is severely limited by the so-called charging effect: Each shot with the electron beam deposits charges inside the mask blank which deflect the electrons in the subsequent shots and therefore cause placement errors. In this paper, a model is proposed which allows to establish a prediction of the deflection of the beam and thus provide a method for improving pattern placement for photomasks.
Ostwald ripening of charged supported metal nanoparticles: Schottky model
Zhdanov, Vladimir P.
2015-07-01
Due to high surface area, supported metal nanoparticles are thermodynamically prone to sintering. The experimental studies of this process exhibit sometimes transient bimodal particle size distributions. Such observations may result from the support heterogeneity. Looking retrospectively, one can also find the prediction that in the case of Ostwald ripening this feature can be related to charge of metal nanoparticles. In real systems, this charge is often associated with the metal-support interaction and can be interpreted in the framework of the Schottky model. Using this model, the author shows that the charge redistribution cannot be behind bimodal particle size distributions. Moreover, the corresponding contribution to the driving force for Ostwald ripening is typically much smaller than the conventional one.
Models of charge pair generation in organic solar cells.
Few, Sheridan; Frost, Jarvist M; Nelson, Jenny
2015-01-28
Efficient charge pair generation is observed in many organic photovoltaic (OPV) heterojunctions, despite nominal electron-hole binding energies which greatly exceed the average thermal energy. Empirically, the efficiency of this process appears to be related to the choice of donor and acceptor materials, the resulting sequence of excited state energy levels and the structure of the interface. In order to establish a suitable physical model for the process, a range of different theoretical studies have addressed the nature and energies of the interfacial states, the energetic profile close to the heterojunction and the dynamics of excited state transitions. In this paper, we review recent developments underpinning the theory of charge pair generation and phenomena, focussing on electronic structure calculations, electrostatic models and approaches to excited state dynamics. We discuss the remaining challenges in achieving a predictive approach to charge generation efficiency. PMID:25462189
Geriatric Hip Fractures and Inpatient Services: Predicting Hospital Charges Using the ASA Score
Directory of Open Access Journals (Sweden)
Rachel V. Thakore
2014-01-01
Full Text Available Purpose. To determine if the American Society of Anesthesiologist (ASA score can be used to predict hospital charges for inpatient services. Materials and Methods. A retrospective chart review was conducted at a level I trauma center on 547 patients over the age of 60 who presented with a hip fracture and required operative fixation. Hospital charges associated with inpatient and postoperative services were organized within six categories of care. Analysis of variance and a linear regression model were performed to compare preoperative ASA scores with charges and inpatient services. Results. Inpatient and postoperative charges and services were significantly associated with patients’ ASA scores. Patients with an ASA score of 4 had the highest average inpatient charges of services of $15,555, compared to $10,923 for patients with an ASA score of 2. Patients with an ASA score of 4 had an average of 45.3 hospital services compared to 24.1 for patients with a score of 2. Conclusions. A patient’s ASA score is associated with total and specific hospital charges related to inpatient services. The findings of this study will allow payers to identify the major cost drivers for inpatient services based on a hip fracture patient’s preoperative physical status.
Continuum modeling of charging process and piezoelectricity of ferroelectrets
Xu, Bai-Xiang; von Seggern, Heinz; Zhukov, Sergey; Gross, Dietmar
2013-09-01
Ferroelectrets in the form of electrically charged micro-porous foams exhibit a very large longitudinal piezoelectric coefficient d33. The structure has hence received wide application interests as sensors particularly in acoustic devices. During charging process, electrical breakdown (Paschen breakdown) takes place in the air pores of the foam and introduces free charge pairs. These charges are separated by electrostatic forces and relocated at the interfaces between the polymer and the electrically broken-down medium, where they are trapped quasistatically. The development of this trapped charge density along the interfaces is key for enabling the piezoelectricity of ferroelectrets. In this article, an internal variable based continuum model is proposed to calculate the charge density development at the interfaces, whereas a Maxwell stress based electromechanical model is used for the bulk behavior, i.e., of the polymer and of the medium where the Paschen breakdown takes place. In the modeling, the electrostatic forces between the separated charge pairs are included, as well as the influence of deformation of the solid layers. The material models are implemented in a nonlinear finite element scheme, which allows a detailed analysis of different geometries. A ferroelectret unit with porous expanded polytetrafluoroethylene (ePTFE) surrounded by fluorinated ethylene propylene is studied first. The simulated hysteresis curves of charge density at the surfaces and the calculated longitudinal piezoelectric constant are in good agreement with experimental results. Simulations show a strong dependency of the interface charge development and thus the remnant charges on the thicknesses of the layers and the permittivity of the materials. According to the calculated relation between d33 and the Young's modulus of ePTFE, the value of the Young's modulus of ePTFE is identified to be around 0.75 MPa, which lies well in the predicted range of 0.45 to 0.80 MPa, determined from
Regge-plus-resonance predictions for charged-kaon photoproduction from the deuteron
Directory of Open Access Journals (Sweden)
Van Cauteren T.
2010-04-01
Full Text Available We present a Regge-inspired eﬀective-Lagrangian framework for charged-kaon photoproduction from the deuteron. Quasi-free kaon production is investigated using the Regge-plus-resonance elementary operator within the non-relativistic plane-wave impulse approximation. The Regge-plus-resonance model was developed to describe photoinduced and electroinduced kaon production oﬀ protons and can be extended to strangeness production oﬀ neutrons. The non-resonant contributions to the amplitude are modelled in terms of K+ (494 and K*+ (892 Regge-trajectory exchange in the t-channel. This amplitude is supplemented with a selection of s-channel resonance-exchange diagrams. We investigate several sources of theoretical uncertainties on the semi-inclusive charged-kaon production cross section. The experimental error bars on the photocoupling helicity amplitudes turn out to put severe limits on the predictive power when considering quasi-free kaon production on a bound neutron.
Prediction of coking dynamics for wet coal charge
Directory of Open Access Journals (Sweden)
Kardaś Dariusz
2015-09-01
Full Text Available A one-dimensional transient mathematical model describing thermal and flow phenomena during coal coking in an oven chamber was studied in the paper. It also accounts for heat conduction in the ceramic oven wall when assuming a constant temperature at the heating channel side. The model was solved numerically using partly implicit methods for gas flow and heat transfer problems. The histories of temperature, gas evolution and internal pressure were presented and analysed. The theoretical predictions of temperature change in the centre plane of the coke oven were compared with industrialscale measurements. Both, the experimental data and obtained numerical results show that moisture content determines the coking process dynamics, lagging the temperature increase above the water steam evaporation temperature and in consequence the total coking time. The phenomenon of internal pressure generation in the context of overlapping effects of simultaneously occurring coal transitions - devolatilisation and coal permeability decrease under plastic stage - was also discussed.
Institute of Scientific and Technical Information of China (English)
胡继敏; 金家善; 严志腾
2013-01-01
The thermodynamic charge performance of a variable-mass thermodynamic system was investigated by the simulation modeling and experimental analysis. Three sets of experiments were conducted for various charge time and charge steam flow under three different control strategies of charge valve. Characteristic performance parameters from the average sub-cooled degree and the charging energy coefficient point of views were also defined to evaluate and predict the charge performance of system combined with the simulation model and experimental data. The results show that the average steam flow reflects the average sub-cooled degree qualitatively, while the charging energy coefficients of 74.6%, 69.9% and 100% relate to the end value of the average sub-cooled degree at 2.1, 2.9 and 0 respectively for the three sets of experiments. The mean and maximum deviations of the results predicted from those by experimental data are smaller than 6.8% and 10.8%, respectively. In conclusion, the decrease of average steam flow can effectively increase the charging energy coefficient in the same charge time condition and therefore improve the thermodynamic charge performance of system. While the increase of the charging energy coefficient by extending the charge time needs the consideration of the operating frequency for steam users.
Modelling, controlling, predicting blackouts
Wang, Chengwei; Baptista, Murilo S
2016-01-01
The electric power system is one of the cornerstones of modern society. One of its most serious malfunctions is the blackout, a catastrophic event that may disrupt a substantial portion of the system, playing havoc to human life and causing great economic losses. Thus, understanding the mechanisms leading to blackouts and creating a reliable and resilient power grid has been a major issue, attracting the attention of scientists, engineers and stakeholders. In this paper, we study the blackout problem in power grids by considering a practical phase-oscillator model. This model allows one to simultaneously consider different types of power sources (e.g., traditional AC power plants and renewable power sources connected by DC/AC inverters) and different types of loads (e.g., consumers connected to distribution networks and consumers directly connected to power plants). We propose two new control strategies based on our model, one for traditional power grids, and another one for smart grids. The control strategie...
Confidence scores for prediction models
DEFF Research Database (Denmark)
Gerds, Thomas Alexander; van de Wiel, MA
2011-01-01
modelling strategy is applied to different training sets. For each modelling strategy we estimate a confidence score based on the same repeated bootstraps. A new decomposition of the expected Brier score is obtained, as well as the estimates of population average confidence scores. The latter can be used...... to distinguish rival prediction models with similar prediction performances. Furthermore, on the subject level a confidence score may provide useful supplementary information for new patients who want to base a medical decision on predicted risk. The ideas are illustrated and discussed using data from cancer...
Model Predictive Control for Smart Energy Systems
DEFF Research Database (Denmark)
Halvgaard, Rasmus
pumps, heat tanks, electrical vehicle battery charging/discharging, wind farms, power plants). 2.Embed forecasting methodologies for the weather (e.g. temperature, solar radiation), the electricity consumption, and the electricity price in a predictive control system. 3.Develop optimization algorithms...... 2 provides linear dynamical models of Smart Grid units: Electric Vehicles, buildings with heat pumps, refrigeration systems, solar collectors, heat storage tanks, power plants, and wind farms. The models can be realized as discrete time state space models that fit into a predictive control system...... supply electricity reliably to both residential and industrial consumers around the clock. More and more fluctuating renewable energy sources, like wind and solar, are integrated in the power system. Consequently, uncertainty in production starts to affect an otherwise controllable power production...
Atomic charges for modeling metal–organic frameworks: Why and how
Energy Technology Data Exchange (ETDEWEB)
Hamad, Said, E-mail: said@upo.es; Balestra, Salvador R.G.; Bueno-Perez, Rocio; Calero, Sofia; Ruiz-Salvador, A. Rabdel
2015-03-15
Atomic partial charges are parameters of key importance in the simulation of Metal–Organic Frameworks (MOFs), since Coulombic interactions decrease with the distance more slowly than van der Waals interactions. But despite its relevance, there is no method to unambiguously assign charges to each atom, since atomic charges are not quantum observables. There are several methods that allow the calculation of atomic charges, most of them starting from the electronic wavefunction or the electronic density or the system, as obtained with quantum mechanics calculations. In this work, we describe the most common methods employed to calculate atomic charges in MOFs. In order to show the influence that even small variations of structure have on atomic charges, we present the results that we obtained for DMOF-1. We also discuss the effect that small variations of atomic charges have on the predicted structural properties of IRMOF-1. - Graphical abstract: We review the different method with which to calculate atomic partial charges that can be used in force field-based calculations. We also present two examples that illustrate the influence of the geometry on the calculated charges and the influence of the charges on structural properties. - Highlights: • The choice of atomic charges is crucial in modeling adsorption and diffusion in MOFs. • Methods for calculating atomic charges in MOFs are reviewed. • We discuss the influence of the framework geometry on the calculated charges. • We discuss the influence of the framework charges on structural the properties.
Melanoma Risk Prediction Models
Developing statistical models that estimate the probability of developing melanoma cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.
Li, Hua; Wang, Bowen; Li, Zhiwei; Liu, De; Lin, Fuchang; Dai, Ling; Zhang, Qin; Chen, Yaohong
2013-10-01
Metallized biaxially oriented polypropylene film (BOPP) capacitors are widely used in pulsed power systems. When the capacitor is used as the energy storage equipment under high electric field, more charges should be provided to maintain the voltage of the capacitor. This should be ascribed to the completion of the slow polarization which may take several hours or even longer. This paper focuses on the stored charge in metallized BOPP film capacitors. The modeling of the stored charge by the equivalent conversion of circuits is conducted to analyse the slow polarization in the BOPP film. The 3-RC network is proposed to represent the time-dependent charge stored in the capacitor. A charging current measurement system is established to investigate the charge storage property of the capacitor. The measurement system can measure the long time charging current with a sampling rate of 300 Hz. The total charge calculated by the charging current indicates that the stored charge in the capacitor under the electric field of 400 V/μm is 13.5% larger than the product of the voltage and the capacitance measured by the AC bridge. The nonlinear effect of the electric field on the slow polarization charge is also demonstrated. And the simulation of charge storage based on the 3-RC network can match well with the trend of the stored charge increasing with the time. PMID:24182144
Li, Hua; Wang, Bowen; Li, Zhiwei; Liu, De; Lin, Fuchang; Dai, Ling; Zhang, Qin; Chen, Yaohong
2013-10-01
Metallized biaxially oriented polypropylene film (BOPP) capacitors are widely used in pulsed power systems. When the capacitor is used as the energy storage equipment under high electric field, more charges should be provided to maintain the voltage of the capacitor. This should be ascribed to the completion of the slow polarization which may take several hours or even longer. This paper focuses on the stored charge in metallized BOPP film capacitors. The modeling of the stored charge by the equivalent conversion of circuits is conducted to analyse the slow polarization in the BOPP film. The 3-RC network is proposed to represent the time-dependent charge stored in the capacitor. A charging current measurement system is established to investigate the charge storage property of the capacitor. The measurement system can measure the long time charging current with a sampling rate of 300Hz. The total charge calculated by the charging current indicates that the stored charge in the capacitor under the electric field of 400 V/μm is 13.5% larger than the product of the voltage and the capacitance measured by the AC bridge. The nonlinear effect of the electric field on the slow polarization charge is also demonstrated. And the simulation of charge storage based on the 3-RC network can match well with the trend of the stored charge increasing with the time.
Charged Ising Model of Neutron Star Matter
Hasnaoui, K H O
2012-01-01
Background: The inner crust of a neutron star is believed to consist of Coulomb-frustrated complex structures known as "nuclear pasta" that display interesting and unique low-energy dynamics. Purpose: To elucidate the structure and composition of the neutron-star crust as a function of temperature, density, and proton fraction. Methods: A new lattice-gas model, the "Charged-Ising Model" (CIM), is introduced to simulate the behavior of neutron-star matter. Preliminary Monte Carlo simulations on 30^3 lattices are performed for a variety of temperatures, densities, and proton fractions. Results: Results are obtained for the heat capacity, pair-correlation function, and static structure factor for a variety of conditions appropriate to the inner stellar crust. Conclusions: Although relatively simple, the CIM captures the essence of Coulomb frustration that is required to simulate the subtle dynamics of the inner stellar crust. Moreover, the computationally demanding long-range Coulomb interactions have been pre-c...
Predictive Models and Computational Embryology
EPA’s ‘virtual embryo’ project is building an integrative systems biology framework for predictive models of developmental toxicity. One schema involves a knowledge-driven adverse outcome pathway (AOP) framework utilizing information from public databases, standardized ontologies...
Modeling taper charge with a non-linear equation
Mcdermott, P. P.
1985-01-01
Work aimed at modeling the charge voltage and current characteristics of nickel-cadmium cells subject to taper charge is presented. Work reported at previous NASA Battery Workshops has shown that the voltage of cells subject to constant current charge and discharge can be modeled very accurately with the equation: voltage = A + (B/(C-X)) + De to the -Ex where A, B, D, and E are fit parameters and x is amp-hr of charge removed during discharge or returned during charge. In a constant current regime, x is also equivalent to time on charge or discharge.
On the Preon Model with Preonic Charge
Senju, H.
1987-05-01
It is proposed to identify ghe recently introduced preonic charge as the source of the binding force with the magnetic charge. This identification leads to the necessary relation of composite quarks and leptons among preonic charges. The reason why the charge of quark is a third of e is under stood. The color number 3 and the preon number 3 in lepton and quark are correlated.
Schizophrenia and Crime: How Predictable Are Charges, Convictions and Violence?
Heinrichs, R. Walter; Sam, Eleanor P.
2012-01-01
The schizophrenia-crime relationship was studied in 151 research participants meeting DSM-IV criteria for schizophrenia or schizoaffective disorder and with histories positive or negative for criminal charges, convictions and offences involving violence. These crime-related variables were regressed on a block of nine predictors reflecting…
Directory of Open Access Journals (Sweden)
Ricardo Infante-Castillo
2012-01-01
Full Text Available This work presents a new quantitative model to predict the heat of explosion of nitroaromatic compounds using the natural bond orbital (NBO charge and 15N NMR chemical shifts of the nitro groups (15NNitro as structural parameters. The values of the heat of explosion predicted for 21 nitroaromatic compounds using the model described here were compared with experimental data. The prediction ability of the model was assessed by the leave-one-out cross-validation method. The cross-validation results show that the model is significant and stable and that the predicted accuracy is within 0.146 MJ kg−1, with an overall root mean squared error of prediction (RMSEP below 0.183 MJ kg−1. Strong correlations were observed between the heat of explosion and the charges (R2 = 0.9533 and 15N NMR chemical shifts (R2 = 0.9531 of the studied compounds. In addition, the dependence of the heat of explosion on the presence of activating or deactivating groups of nitroaromatic explosives was analyzed. All calculations, including optimizations, NBO charges, and 15NNitro NMR chemical shifts analyses, were performed using density functional theory (DFT and a 6-311+G(2d,p basis set. Based on these results, this practical quantitative model can be used as a tool in the design and development of highly energetic materials (HEM based on nitroaromatic compounds.
Prediction models in complex terrain
DEFF Research Database (Denmark)
Marti, I.; Nielsen, Torben Skov; Madsen, Henrik;
2001-01-01
The objective of the work is to investigatethe performance of HIRLAM in complex terrain when used as input to energy production forecasting models, and to develop a statistical model to adapt HIRLAM prediction to the wind farm. The features of the terrain, specially the topography, influence...
A contrail cirrus prediction model
Directory of Open Access Journals (Sweden)
U. Schumann
2012-05-01
Full Text Available A new model to simulate and predict the properties of a large ensemble of contrails as a function of given air traffic and meteorology is described. The model is designed for approximate prediction of contrail cirrus cover and analysis of contrail climate impact, e.g. within aviation system optimization processes. The model simulates the full contrail life-cycle. Contrail segments form between waypoints of individual aircraft tracks in sufficiently cold and humid air masses. The initial contrail properties depend on the aircraft. The advection and evolution of the contrails is followed with a Lagrangian Gaussian plume model. Mixing and bulk cloud processes are treated quasi analytically or with an effective numerical scheme. Contrails disappear when the bulk ice content is sublimating or precipitating. The model has been implemented in a "Contrail Cirrus Prediction Tool" (CoCiP. This paper describes the model assumptions, the equations for individual contrails, and the analysis-method for contrail-cirrus cover derived from the optical depth of the ensemble of contrails and background cirrus. The model has been applied for a case study and compared to the results of other models and in-situ contrail measurements. The simple model reproduces a considerable part of observed contrail properties. Mid-aged contrails provide the largest contributions to the product of optical depth and contrail width, important for climate impact.
A contrail cirrus prediction model
Directory of Open Access Journals (Sweden)
U. Schumann
2011-11-01
Full Text Available A new model to simulate and predict the properties of a large ensemble of contrails as a function of given air traffic and meteorology is described. The model is designed for approximate prediction of contrail cirrus cover and analysis of contrail climate impact, e.g. within aviation system optimization processes. The model simulates the full contrail life-cycle. Contrail segments form between waypoints of individual aircraft tracks in sufficiently cold and humid air masses. The initial contrail properties depend on the aircraft. The advection and evolution of the contrails is followed with a Lagrangian Gaussian plume model. Mixing and bulk cloud processes are treated quasi analytically or with an effective numerical scheme. Contrails disappear when the bulk ice content is sublimating or precipitating. The model has been implemented in a "Contrail Cirrus Prediction Tool" (CoCiP. This paper describes the model assumptions, the equations for individual contrails, and the analysis-method for contrail-cirrus cover derived from the optical depth of the ensemble of contrails and background cirrus. The model has been applied for a case study and compared to the results of other models and in-situ contrail measurements. The simple model reproduces a considerable part of observed contrail properties. Mid-aged contrails provide the largest contributions to the product of optical depth and contrail width, important for climate impact.
Analytical Charge Voltage Model in MOS Inversion Layer Based on Space Charge Capacitance
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
The concept of Space Charge Capacitance (SCC) is proposed and used to make a novel analytical charge model of quantized inversion layer in MOS structures. Based on SCC,continuous expressions of surface potential and inversion layer carrier density are derived.Quantum mechanical effects on both inversion layer carrier density and surface potential are extensively included. The accuracy of the model is verified by the numerical solution to Schrodinger and Poisson equation and the model is demonstrated,too.
Preconditioned Continuation Model Predictive Control
Knyazev, Andrew; Fujii, Yuta; Malyshev, Alexander,
2015-01-01
Model predictive control (MPC) anticipates future events to take appropriate control actions. Nonlinear MPC (NMPC) describes systems with nonlinear models and/or constraints. A Continuation/GMRES Method for NMPC, suggested by T. Ohtsuka in 2004, uses the GMRES iterative algorithm to solve a forward difference approximation $Ax=b$ of the Continuation NMPC (CNMPC) equations on every time step. The coefficient matrix $A$ of the linear system is often ill-conditioned, resulting in poor GMRES conv...
Boulmene, Reda; Boussouf, Karim; Prakash, Muthuramalingam; Komiha, Najia; Al-Mogren, Muneerah M; Hochlaf, Majdi
2016-04-01
Using first-principles methodologies, the equilibrium structures and the relative stability of CO2 @[Zn(q+) Im] (where q=0, 1, 2; Im=imidazole) complexes are studied to understand the nature of the interactions between the CO2 and Zn(q+) -imidazole entities. These complexes are considered as prototype models mimicking the interactions of CO2 with these subunits of zeolitic imidazolate frameworks or Zn enzymes. These computations are performed using both ab initio calculations and density functional theory. Dispersion effects accounting for long-range interactions are considered. Solvent (water) effects were also considered using a polarizable continuum model approach. Natural bond orbital, charge, frontier orbital and vibrational analyses clearly reveal the occurrence of charge transfer through covalent and noncovalent interactions. Moreover, it is found that CO2 can adsorb through more favorable π-type stacking as well as σ-type hydrogen-bonding interactions. The inter-monomer interaction potentials show a significant anisotropy that might induce CO2 orientation and site-selectivity effects in porous materials and in active sites of Zn enzymes. Hence, this study provides valuable information about how CO2 adsorption takes place at the microscopic level within zeolitic imidazolate frameworks and biomolecules. These findings might help in understanding the role of such complexes in chemistry, biology and material science for further development of new materials and industrial applications. PMID:26790137
Failure prediction model: Model napovedovanja odpovedi:
Čelan, Štefan; Težak, Oto; Žižek, Adolf
2002-01-01
Preventative maintenance is vital for delicate technical products. Electronic components or the whole system must be changed, and thus need a good model that will indicate failure accurately. In this paper a stochastic stress-strength quantitative model is presented, folowing the five original hypothesis. Proposed new model of failure prediction could be used by the system maintenance. Failure risk could be instantaneosly calculated. The given theory considers the influences of stress on the ...
Prediction of coking dynamics for wet coal charge
Kardaś Dariusz; Polesek-Karczewska Sylwia; Ciżmiński Przemysław; Stelmach Sławomir
2015-01-01
A one-dimensional transient mathematical model describing thermal and flow phenomena during coal coking in an oven chamber was studied in the paper. It also accounts for heat conduction in the ceramic oven wall when assuming a constant temperature at the heating channel side. The model was solved numerically using partly implicit methods for gas flow and heat transfer problems. The histories of temperature, gas evolution and internal pressure were presented and analysed. The theoretical predi...
Modulated charge patterns and noise effect in a twisted DNA model with solvent interaction
Tabi, C. B.; Dang Koko, A.; Oumarou Doko, R.; Ekobena Fouda, H. P.; Kofané, T. C.
2016-01-01
We modify the Peyrard-Bishop-Holstein model and bring out the influence of the torsion and solvent interactions on charge transport in DNA. Through the linear stability analysis, we detect regions of instability and we compare the results with those of the standard Peyrard-Bishop-Holstein model. There are two regimes where modulated charge patterns can occur: the undertwisted and the overtwisted conformations. Numerical simulations are used to confirm our analytical predictions. Charge patterns are obtained and propagate more easily in an overwinded helix than in an underwinded one. The effects of dissipation and thermal fluctuations are also studied, which confirm the robustness of the obtained modulated patterns. On the one hand, we argue that in the absence of twisting, temperature can lead to the breaking of the hydrogen bonds between bases and prevent charges from propagating. On the other hand, when the molecule is overtwisted, the solvent and the temperature will rather enhance charge spreading patterns with random features.
Leherte, Laurence; Vercauteren, Daniel P
2011-10-01
To generate reduced point charge models of proteins, we developed an original approach to hierarchically locate extrema in charge density distribution functions built from the Poisson equation applied to smoothed molecular electrostatic potential (MEP) functions. A charge fitting program was used to assign charge values to the so-obtained reduced representations. In continuation to a previous work, the Amber99 force field was selected. To easily generate reduced point charge models for protein structures, a library of amino acid templates was designed. Applications to four small peptides, a set of 53 protein structures, and four KcsA ion channel models, are presented. Electrostatic potential and solvation free energy values generated by the reduced models are compared with the corresponding values obtained using the original set of atomic charges. Results are in closer agreement with the original all-atom electrostatic properties than those obtained with a previous reduced model that was directly built from the smoothed MEP functions [Leherte and Vercauteren in J Chem Theory Comput 5:3279-3298, 2009]. PMID:21915750
Symmetrization of mathematical model of charge transport in semiconductors
Directory of Open Access Journals (Sweden)
Alexander M. Blokhin
2002-11-01
Full Text Available A mathematical model of charge transport in semiconductors is considered. The model is a quasilinear system of differential equations. A problem of finding an additional entropy conservation law and system symmetrization are solved.
Geriatric Hip Fractures and Inpatient Services: Predicting Hospital Charges Using the ASA Score
Thakore, Rachel V.; Young M. Lee; Vasanth Sathiyakumar; Obremskey, William T.; Sethi, Manish K.
2014-01-01
Purpose. To determine if the American Society of Anesthesiologist (ASA) score can be used to predict hospital charges for inpatient services. Materials and Methods. A retrospective chart review was conducted at a level I trauma center on 547 patients over the age of 60 who presented with a hip fracture and required operative fixation. Hospital charges associated with inpatient and postoperative services were organized within six categories of care. Analysis of variance and a linear regression...
Electron transport model of dielectric charging
Beers, B. L.; Hwang, H. C.; Lin, D. L.; Pine, V. W.
1979-01-01
A computer code (SCCPOEM) was assembled to describe the charging of dielectrics due to irradiation by electrons. The primary purpose for developing the code was to make available a convenient tool for studying the internal fields and charge densities in electron-irradiated dielectrics. The code, which is based on the primary electron transport code POEM, is applicable to arbitrary dielectrics, source spectra, and current time histories. The code calculations are illustrated by a series of semianalytical solutions. Calculations to date suggest that the front face electric field is insufficient to cause breakdown, but that bulk breakdown fields can easily be exceeded.
Neutrino nucleosynthesis in supernovae: Shell model predictions
International Nuclear Information System (INIS)
Almost all of the 3 · 1053 ergs liberated in a core collapse supernova is radiated as neutrinos by the cooling neutron star. I will argue that these neutrinos interact with nuclei in the ejected shells of the supernovae to produce new elements. It appears that this nucleosynthesis mechanism is responsible for the galactic abundances of 7Li, 11B, 19F, 138La, and 180Ta, and contributes significantly to the abundances of about 15 other light nuclei. I discuss shell model predictions for the charged and neutral current allowed and first-forbidden responses of the parent nuclei, as well as the spallation processes that produce the new elements. 18 refs., 1 fig., 1 tab
Leptonic Charged Higgs Decays in the Zee Model
Sierra, D A; Restrepo, Diego
2006-01-01
We consider the version of the Zee model where both Higgs doublets couple to leptons. Within this framework we study charged Higgs decays. We focus on a model with minimal number of parameters consistent with experimental neutrino data. Using constraints from neutrino physics we (i) discuss the reconstruction of the parameter space of the model using the leptonic decay patterns of both of the two charged Higgses, $h_{1,2}^{+}\\to \\ell_{j}^{+}\
Charge transport models for reliability engineering of semiconductor devices
International Nuclear Information System (INIS)
correlation. This shows that an NMP-based theory of the bias temperature instability can both explain characteristic time constants experimentally found in the drain and the gate current after bias temperature stress as well as the overall threshold voltage shift. These findings imply that for an accurate lifetime prediction an NMP-based theory is a good choice. However, in order to obtain an accurate lifetime prediction information on the threshold voltage shift caused by a single discrete trap created during bias temperature stress needs to be investigated. To this end small area MOSFETs have been investigated on a statistical basis using random discrete doping in order to determine the cumulative distribution function (CFD) of threshold voltage shifts caused by random discrete charged traps as well as their characteristic capture and emission times. It is found that the experimentally observed CFDs of the threshold voltage shifts caused by single charged traps cannot be reproduced using Minimos-NT by considering potential fluctuations alone. Thus further investigations into this subject are needed. Since the study of hot-carrier degradation requires exact information on the energy distribution of charge carriers, a solution of the Boltzmann transport equation is necessary. For detailed investigations into hot-carrier degradation, ViennaSHE, a device simulator based on a spherical harmonics expansion (SHE) of the Boltzmann transport equation, has been extended in the course of this thesis. To compare SHE to moment-based transport models, quantum correction models, variability caused by random discrete dopants, the classical SRH trapping theory as well as a four state degradation model based on non-radiative multi-phonon theory are incorporated into the simulator. These additions to ViennaSHE allow to evaluate the device characteristics of virgin as well as degraded devices under hot-carrier or bias temperature stress or both. Additionally, ViennaSHE is extended by the
Production of Charged Scalars from the Littlest Higgs Model Associated with Top Quark at LHC
Institute of Scientific and Technical Information of China (English)
LIU Wei-Na; LIU Yao-Bei; LI Ping; SHEN Jie-Fen; GOU Qing-Quan; CUI Xiao-Min; ZHAO Yan-Ping; REN Xiao-Yan
2008-01-01
The littlest Higgs (LH) model is the most economical one among various little Higgs models, which predicts the existence of the charged scalars φ±. In this paper, we study the production of the charged Higgs boson φ- with single top quark via the process gb → tφ- at the CERN Large Hadron Collider (LHC). The numerical results show that the production cross section is smaller than 0.2 pb in most of the parameters space, it is very difficult to observe the signatures of the charged scalars via the process pp → gb + X → tφ- + X at the LHC experiments. However, it can open a window to distinguish the top-pions in the TC2 model or charged Higgs in the MSSM from φ±.
Predictive Model of Radiative Neutrino Masses
Babu, K S
2013-01-01
We present a simple and predictive model of radiative neutrino masses. It is a special case of the Zee model which introduces two Higgs doublets and a charged singlet. We impose a family-dependent Z_4 symmetry acting on the leptons, which reduces the number of parameters describing neutrino oscillations to four. A variety of predictions follow: The hierarchy of neutrino masses must be inverted; the lightest neutrino mass is extremely small and calculable; one of the neutrino mixing angles is determined in terms of the other two; the phase parameters take CP-conserving values with \\delta_{CP} = \\pi; and the effective mass in neutrinoless double beta decay lies in a narrow range, m_{\\beta \\beta} = (17.6 - 18.5) meV. The ratio of vacuum expectation values of the two Higgs doublets, tan\\beta, is determined to be either 1.9 or 0.19 from neutrino oscillation data. Flavor-conserving and flavor-changing couplings of the Higgs doublets are also determined from neutrino data. The non-standard neutral Higgs bosons, if t...
Electrochemical model based charge optimization for lithium-ion batteries
Pramanik, Sourav; Anwar, Sohel
2016-05-01
In this paper, we propose the design of a novel optimal strategy for charging the lithium-ion battery based on electrochemical battery model that is aimed at improved performance. A performance index that aims at minimizing the charging effort along with a minimum deviation from the rated maximum thresholds for cell temperature and charging current has been defined. The method proposed in this paper aims at achieving a faster charging rate while maintaining safe limits for various battery parameters. Safe operation of the battery is achieved by including the battery bulk temperature as a control component in the performance index which is of critical importance for electric vehicles. Another important aspect of the performance objective proposed here is the efficiency of the algorithm that would allow higher charging rates without compromising the internal electrochemical kinetics of the battery which would prevent abusive conditions, thereby improving the long term durability. A more realistic model, based on battery electro-chemistry has been used for the design of the optimal algorithm as opposed to the conventional equivalent circuit models. To solve the optimization problem, Pontryagins principle has been used which is very effective for constrained optimization problems with both state and input constraints. Simulation results show that the proposed optimal charging algorithm is capable of shortening the charging time of a lithium ion cell while maintaining the temperature constraint when compared with the standard constant current charging. The designed method also maintains the internal states within limits that can avoid abusive operating conditions.
Capozza, R.; Vanossi, A.; Benassi, A.; Tosatti, E.
2015-02-01
Electrical charging of parallel plates confining a model ionic liquid down to nanoscale distances yields a variety of charge-induced changes in the structural features of the confined film. That includes even-odd switching of the structural layering and charging-induced solidification and melting, with important changes of local ordering between and within layers, and of squeezout behavior. By means of molecular dynamics simulations, we explore this variety of phenomena in the simplest charged Lennard-Jones coarse-grained model including or excluding the effect a neutral tail giving an anisotropic shape to one of the model ions. Using these models and open conditions permitting the flow of ions in and out of the interplate gap, we simulate the liquid squeezout to obtain the distance dependent structure and forces between the plates during their adiabatic approach under load. Simulations at fixed applied force illustrate an effective electrical pumping of the ionic liquid, from a thick nearly solid film that withstands the interplate pressure for high plate charge to complete squeezout following melting near zero charge. Effective enthalpy curves obtained by integration of interplate forces versus distance show the local minima that correspond to layering and predict the switching between one minimum and another under squeezing and charging.
Modeling charge relaxation in graphene quantum dots induced by electron-phonon interaction
Reichardt, Sven; Stampfer, Christoph
2016-06-01
We study and compare two analytic models of graphene quantum dots for calculating charge relaxation times due to electron-phonon interaction. Recently, charge relaxation processes in graphene quantum dots have been probed experimentally and here we provide a theoretical estimate of relaxation times. By comparing a model with pure edge confinement to a model with electrostatic confinement, we find that the latter features much larger relaxation times. Interestingly, relaxation times in electrostatically defined quantum dots are predicted to exceed the experimentally observed lower bound of ˜100 ns.
Black Hole Evaporation in a Noncommutative Charged Vaidya Model
Sharif, M.; Javed, Wajiha
2012-01-01
The aim of this paper is to study the black hole evaporation and Hawking radiation for a noncommutative charged Vaidya black hole. For this purpose, we determine spherically symmetric charged Vaidya model and then formulate a noncommutative Reissner-Nordstr$\\ddot{o}$m-like solution of this model which leads to an exact $(t-r)$ dependent metric. The behavior of temporal component of this metric and the corresponding Hawking temperature is investigated. The results are shown in the form of grap...
Tight-binding modeling of charge migration in DNA devices
Cuniberti, G.; Macia, E.; Rodriguez, A.; R.A. Römer
2007-01-01
Long range charge transfer experiments in DNA oligomers and the subsequently measured -- and very diverse -- transport response of DNA wires in solid state experiments exemplifies the need for a thorough theoretical understanding of charge migration in DNA-based natural and artificial materials. Here we present a review of tight-binding models for DNA conduction which have the intrinsic merit of containing more structural information than plain rate-equation models while still retaining suffi...
Computer simulation study of water using a fluctuating charge model
Indian Academy of Sciences (India)
M Krishnan; A Verma; S Balasubramanian
2001-10-01
Hydrogen bonding in small water clusters is studied through computer simulation methods using a sophisticated, empirical model of interaction developed by Rick et al (S W Rick, S J Stuart and B J Berne 1994 J. Chem. Phys. 101 6141) and others. The model allows for the charges on the interacting sites to fluctuate as a function of time, depending on their local environment. The charge flow is driven by the difference in the electronegativity of the atoms within the water molecule, thus effectively mimicking the effects of polarization of the charge density. The potential model is thus transferable across all phases of water. Using this model, we have obtained the minimum energy structures of water clusters up to a size of ten. The cluster structures agree well with experimental data. In addition, we are able to distinctly identify the hydrogens that form hydrogen bonds based on their charges alone, a feature that is not possible in simulations using fixed charge models. We have also studied the structure of liquid water at ambient conditions using this fluctuating charge model.
DETAILED MODELLING OF CHARGING BEHAVIOUR OF SMART SOLAR TANKS
DEFF Research Database (Denmark)
Fan, Jianhua; Andersen, Elsa; Furbo, Simon;
The charging behaviour of smart solar tanks for solar combisystems for one-family houses is investigated with detailed Computational Fluid Dynamics (CFD) modelling and Particle Image Velocimetry (PIV) measurements. The smart solar tank can be charged with a variable auxiliary volume fitted...... to the expected future energy demand. Therefore the heat loss from the tank is decreased and the thermal performance of the solar heating system is increased compared to a traditional system with a fixed auxiliary volume. The solar tank can be charged either by an electric heating element situated in the tank...... or by an electric heating element in a side-arm mounted on the side of the tank. Detailed CFD models of the smart tanks are built with different mesh densities in the tank and in the side-arm. The thermal conditions of the tank during charging are calculated with the CFD models. The fluid flow and temperature...
DETAILED MODELLING OF CHARGING BEHAVIOUR OF SMART SOLAR TANKS
DEFF Research Database (Denmark)
Fan, Jianhua; Andersen, Elsa; Furbo, Simon;
2010-01-01
The charging behaviour of smart solar tanks for solar combisystems for one-family houses is investigated with detailed Computational Fluid Dynamics (CFD) modelling and Particle Image Velocimetry (PIV) measurements. The smart solar tank can be charged with a variable auxiliary volume fitted...... to the expected future energy demand. Therefore the heat loss from the tank is decreased and the thermal performance of the solar heating system is increased compared to a traditional system with a fixed auxiliary volume. The solar tank can be charged either by an electric heating element situated in the tank...... or by an electric heating element in a side-arm mounted on the side of the tank. Detailed CFD models of the smart tanks are built with different mesh densities in the tank and in the side-arm. The thermal conditions of the tank during charging are calculated with the CFD models. The fluid flow and temperature...
Energy Technology Data Exchange (ETDEWEB)
Fernández, Ariel, E-mail: ariel@afinnovation.com [Argentine Institute of Mathematics (I. A. M.), National Research Council (CONICET), Buenos Aires 1083 (Argentina); Collegium Basilea – Institute for Advanced Study, Basel CH4053 (Switzerland)
2015-10-16
The spontaneous negative charging of aqueous nonpolar interfaces has eluded quantitative first-principle prediction, possibly because it steadfastly challenges the classical Debye dielectric picture. In this work we show that quantitative prediction requires a substantive revision of Debye's linear dielectric ansatz to incorporate an anomalous polarization component yielding electrostatic energy stored as interfacial tension and detailed enough to account for the differences in electronic structure between water and its ionized states. The minimization of this interfacial tension is due to a quantum effect resulting in the reduction in hydrogen-bond frustration that takes place upon hydroxide ion adsorption. The quantitative predictions are validated vis-à-vis measurements of the free energy change associated with hydroxide adsorption obtained using sum-frequency vibrational spectroscopy. - Highlights: • Spontaneous charging of aqueous nonpolar interfaces challenges Debye dielectrics. • A quantum non-Debye theory of interfacial tension is developed. • The minimization of the interfacial tension promotes hydroxide ion adsorption.
Numerical weather prediction model tuning via ensemble prediction system
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.
Discrete Element Modeling (DEM) of Triboelectrically Charged Particles: Revised Experiments
Hogue, Michael D.; Calle, Carlos I.; Curry, D. R.; Weitzman, P. S.
2008-01-01
In a previous work, the addition of basic screened Coulombic electrostatic forces to an existing commercial discrete element modeling (DEM) software was reported. Triboelectric experiments were performed to charge glass spheres rolling on inclined planes of various materials. Charge generation constants and the Q/m ratios for the test materials were calculated from the experimental data and compared to the simulation output of the DEM software. In this paper, we will discuss new values of the charge generation constants calculated from improved experimental procedures and data. Also, planned work to include dielectrophoretic, Van der Waals forces, and advanced mechanical forces into the software will be discussed.
Black hole evaporation in a noncommutative charged Vaidya model
Energy Technology Data Exchange (ETDEWEB)
Sharif, M., E-mail: msharif.math@pu.edu.pk; Javed, W. [University of the Punjab, Department of Mathematics (Pakistan)
2012-06-15
We study the black hole evaporation and Hawking radiation for a noncommutative charged Vaidya black hole. For this purpose, we determine a spherically symmetric charged Vaidya model and then formulate a noncommutative Reissner-Nordstroem-like solution of this model, which leads to an exact (t - r)-dependent metric. The behavior of the temporal component of this metric and the corresponding Hawking temperature are investigated. The results are shown in the form of graphs. Further, we examine the tunneling process of charged massive particles through the quantum horizon. We find that the tunneling amplitude is modified due to noncommutativity. Also, it turns out that the black hole evaporates completely in the limits of large time and horizon radius. The effect of charge is to reduce the temperature from a maximum value to zero. We note that the final stage of black hole evaporation is a naked singularity.
Black Hole Evaporation in a Noncommutative Charged Vaidya Model
Sharif, M
2012-01-01
The aim of this paper is to study the black hole evaporation and Hawking radiation for a noncommutative charged Vaidya black hole. For this purpose, we determine spherically symmetric charged Vaidya model and then formulate a noncommutative Reissner-Nordstr$\\ddot{o}$m-like solution of this model which leads to an exact $(t-r)$ dependent metric. The behavior of temporal component of this metric and the corresponding Hawking temperature is investigated. The results are shown in the form of graphs. Further, we examine the tunneling process of the charged massive particles through the quantum horizon. It is found that the tunneling amplitude is modified due to noncommutativity. Also, it turns out that black hole evaporates completely in the limits of large time and horizon radius. The effect of charge is to reduce the temperature from maximum value to zero. It is mentioned here that the final stage of black hole evaporation turns out to be a naked singularity.
Black hole evaporation in a noncommutative charged Vaidya model
Sharif, M.; Javed, W.
2012-06-01
We study the black hole evaporation and Hawking radiation for a noncommutative charged Vaidya black hole. For this purpose, we determine a spherically symmetric charged Vaidya model and then formulate a noncommutative Reissner-Nordström-like solution of this model, which leads to an exact ( t - r)-dependent metric. The behavior of the temporal component of this metric and the corresponding Hawking temperature are investigated. The results are shown in the form of graphs. Further, we examine the tunneling process of charged massive particles through the quantum horizon. We find that the tunneling amplitude is modified due to noncommutativity. Also, it turns out that the black hole evaporates completely in the limits of large time and horizon radius. The effect of charge is to reduce the temperature from a maximum value to zero. We note that the final stage of black hole evaporation is a naked singularity.
Black hole evaporation in a noncommutative charged Vaidya model
International Nuclear Information System (INIS)
We study the black hole evaporation and Hawking radiation for a noncommutative charged Vaidya black hole. For this purpose, we determine a spherically symmetric charged Vaidya model and then formulate a noncommutative Reissner-Nordström-like solution of this model, which leads to an exact (t − r)-dependent metric. The behavior of the temporal component of this metric and the corresponding Hawking temperature are investigated. The results are shown in the form of graphs. Further, we examine the tunneling process of charged massive particles through the quantum horizon. We find that the tunneling amplitude is modified due to noncommutativity. Also, it turns out that the black hole evaporates completely in the limits of large time and horizon radius. The effect of charge is to reduce the temperature from a maximum value to zero. We note that the final stage of black hole evaporation is a naked singularity.
A PEV Charging Service Model for Smart Grids
Directory of Open Access Journals (Sweden)
Mohammed Abdel-Hafez
2012-11-01
Full Text Available Plug-in Electric Vehicles (PEVs are envisioned to be more popular during the next decade as part of Smart Grid implementations. Charging multiple PEVs at the same time within a power distribution area constitutes a major challenge for energy service providers. This paper discusses a priority-based approach for charging PEVs in a Smart Grid environment. In this work, ideas from the communication network paradigm are being utilized and tailored toward achieving the desired objective of monitoring and controlling PEVs electric load in Smart Grid. A detailed example is given to show how uncontrolled penetration of PEVs can impact distribution transformer reliability. The paper introduces the concept of Charging Quality of Service (CQoS as a smart electric vehicle charging scheme and models it using a priority-controlled leaky bucket approach. The performance of such a model is investigated under the umbrella of a Smart Grid environment.
Lattice charge models and core level shifts in disordered alloys
Underwood, T. L.; Cole, R. J.
2013-10-01
Differences in core level binding energies between atoms belonging to the same chemical species can be related to differences in their intra- and extra-atomic charge distributions, and differences in how their core holes are screened. With this in mind, we consider the charge-excess functional model (CEFM) for net atomic charges in alloys (Bruno et al 2003 Phys. Rev. Lett. 91 166401). We begin by deriving the CEFM energy function in order to elucidate the approximations which underpin this model. We thereafter consider the particular case of the CEFM in which the strengths of the ‘local interactions’ within all atoms are the same. We show that for binary alloys the ground state charges of this model can be expressed in terms of charge transfer between all pairs of unlike atoms analogously to the linear charge model (Magri et al 1990 Phys. Rev. B 42 11388). Hence, the model considered is a generalization of the linear charge model for alloys containing more than two chemical species. We then determine the model’s unknown ‘geometric factors’ over a wide range of parameter space. These quantities are linked to the nature of charge screening in the model, and we illustrate that the screening becomes increasingly universal as the strength of the local interactions is increased. We then use the model to derive analytical expressions for various physical quantities, including the Madelung energy and the disorder broadening in the core level binding energies. These expressions are applied to ternary random alloys, for which it is shown that the Madelung energy and magnitude of disorder broadening are maximized at the composition at which the two species with the largest ‘electronegativity difference’ are equal, while the remaining species have a vanishing concentration. This result is somewhat counterintuitive with regards to the disorder broadening since it does not correspond to the composition with the highest entropy. Finally, the model is applied to Cu
DETAILED MODELLING OF CHARGING BEHAVIOUR OF SMART SOLAR TANKS
Fan, Jianhua; Andersen, Elsa; Furbo, Simon; Perers, Bengt
2010-01-01
The charging behaviour of smart solar tanks for solar combisystems for one-family houses is investigated with detailed Computational Fluid Dynamics (CFD) modelling and Particle Image Velocimetry (PIV) measurements. The smart solar tank can be charged with a variable auxiliary volume fitted to the expected future energy demand. Therefore the heat loss from the tank is decreased and the thermal performance of the solar heating system is increased compared to a traditional system with a fixed au...
Image Charge Undulator: Theoretical Model and Technical Issues
International Nuclear Information System (INIS)
A new device, an image charge undulator, has been proposed recently [1] to utilize this mechanism for generating coherent hard radiation. We demonstrate physics principle of this device by a 2D model of a uniform sheet beam. The transverse image charge wakefields, synchrotron radiation FR-equency and coherent radiation gain length are presented. We discuss a proof-of-principle experiment that takes into consideration such technical issues as grating fabrication, flat beams and beam alignment
Charge State Evolution in the Solar Wind. III. Model Comparison with Observations
Landi, E.; Oran, R.; Lepri, S. T.; Zurbuchen, T. H.; Fisk, L. A.; van der Holst, B.
2014-08-01
We test three theoretical models of the fast solar wind with a set of remote sensing observations and in-situ measurements taken during the minimum of solar cycle 23. First, the model electron density and temperature are compared to SOHO/SUMER spectroscopic measurements. Second, the model electron density, temperature, and wind speed are used to predict the charge state evolution of the wind plasma from the source regions to the freeze-in point. Frozen-in charge states are compared with Ulysses/SWICS measurements at 1 AU, while charge states close to the Sun are combined with the CHIANTI spectral code to calculate the intensities of selected spectral lines, to be compared with SOHO/SUMER observations in the north polar coronal hole. We find that none of the theoretical models are able to completely reproduce all observations; namely, all of them underestimate the charge state distribution of the solar wind everywhere, although the levels of disagreement vary from model to model. We discuss possible causes of the disagreement, namely, uncertainties in the calculation of the charge state evolution and of line intensities, in the atomic data, and in the assumptions on the wind plasma conditions. Last, we discuss the scenario where the wind is accelerated from a region located in the solar corona rather than in the chromosphere as assumed in the three theoretical models, and find that a wind originating from the corona is in much closer agreement with observations.
Charge state evolution in the solar wind. III. Model comparison with observations
Energy Technology Data Exchange (ETDEWEB)
Landi, E.; Oran, R.; Lepri, S. T.; Zurbuchen, T. H.; Fisk, L. A.; Van der Holst, B. [Department of Atmospheric, Oceanic and Space Sciences, University of Michigan, Ann Arbor, MI 48109 (United States)
2014-08-01
We test three theoretical models of the fast solar wind with a set of remote sensing observations and in-situ measurements taken during the minimum of solar cycle 23. First, the model electron density and temperature are compared to SOHO/SUMER spectroscopic measurements. Second, the model electron density, temperature, and wind speed are used to predict the charge state evolution of the wind plasma from the source regions to the freeze-in point. Frozen-in charge states are compared with Ulysses/SWICS measurements at 1 AU, while charge states close to the Sun are combined with the CHIANTI spectral code to calculate the intensities of selected spectral lines, to be compared with SOHO/SUMER observations in the north polar coronal hole. We find that none of the theoretical models are able to completely reproduce all observations; namely, all of them underestimate the charge state distribution of the solar wind everywhere, although the levels of disagreement vary from model to model. We discuss possible causes of the disagreement, namely, uncertainties in the calculation of the charge state evolution and of line intensities, in the atomic data, and in the assumptions on the wind plasma conditions. Last, we discuss the scenario where the wind is accelerated from a region located in the solar corona rather than in the chromosphere as assumed in the three theoretical models, and find that a wind originating from the corona is in much closer agreement with observations.
Return Predictability, Model Uncertainty, and Robust Investment
DEFF Research Database (Denmark)
Lukas, Manuel
Stock return predictability is subject to great uncertainty. In this paper we use the model confidence set approach to quantify uncertainty about expected utility from investment, accounting for potential return predictability. For monthly US data and six representative return prediction models, we...
Kiiskinen, A P
2004-01-01
This thesis describes direct searches for pair production of charged Higgs bosons performed in the data collected by the DELPHI detector at the LEP collider at CERN. In addition, the possibilities to discover and study heavy charged Higgs bosons at possible future high-energy linear colliders are presented. The existence of charged Higgs bosons is predicted by many extensions of the Standard Model. A possible discovery of these particles would be a solid proof for physics beyond the Standard Model. Discovery of charged Higgs bosons, and measurement of their properties, would also provide useful information about the structure of the more general theory. New analysis methods were developed for the searches performed at LEP. A large, previously unexplored, mass range for cover but no evidence for the existence of the charged Higgs bosons was found. This allowed setting new lower mass limits for the charged Higgs boson within the framework of general two Higgs doublet models. Results have been interpreted and pr...
Accurate predictions for charged Higgs production: closing the $m_{H^{\\pm}}\\sim m_t$ window
Degrande, Celine; Hirschi, Valentin; Ubiali, Maria; Wiesemann, Marius; Zaro, Marco
2016-01-01
We present predictions for the total cross section for the production of a charged Higgs boson in a generic type-II two-Higgs-doublet model in the intermediate-mass range ($m_{H^{\\pm}}\\sim m_t$) at the LHC. Results are obtained at next-to-leading order (NLO) accuracy in QCD perturbation theory, by studying the full process $pp\\to H^\\pm W^\\mp b \\bar b$ in the complex-(top)-mass scheme with massive bottom quarks. Compared to lowest-order predictions, NLO corrections have a sizable impact: they increase the cross section by roughly 50% and reduce uncertainties due to scale variations by more than a factor of two. Our computation reliably interpolates between the low- and high-mass regime. Our results provide the first NLO prediction for charged Higgs production in the intermediate-mass range and therefore allow to have NLO accurate predictions in the full $m_{H^{\\pm}}$ range.
Stassinopoulos, E. G.; Brucker, G. J.; Calvel, P.; Baiget, A.; Peyrotte, C.; Gaillard, R.
1992-01-01
The transport, energy loss, and charge production of heavy ions in the sensitive regions of IRF 150 power MOSFETs are described. The dependence and variation of transport parameters with ion type and energy relative to the requirements for single event burnout in this part type are discussed. Test data taken with this power MOSFET are used together with analyses by means of a computer code of the ion energy loss and charge production in the device to establish criteria for burnout and parameters for space predictions. These parameters are then used in an application to predict burnout rates in a geostationary orbit for power converters operating in a dynamic mode. Comparisons of rates for different geometries in simulating SEU (single event upset) sensitive volumes are presented.
Business Models for Solar Powered Charging Stations to Develop Infrastructure for Electric Vehicles
Directory of Open Access Journals (Sweden)
Jessica Robinson
2014-10-01
Full Text Available Electric power must become less dependent on fossil fuels and transportation must become more electric to decrease carbon emissions and mitigate climate change. Increasing availability and accessibility of charging stations is predicted to increase purchases of electric vehicles. In order to address the current inadequate charging infrastructure for electric vehicles, major entities must adopt business models for solar powered charging stations (SPCS. These SPCS should be located in parking lots to produce electricity for the grid and provide an integrated infrastructure for charging electric vehicles. Due to the lack of information related to SPCS business models, this manuscript designs several models for major entities including industry, the federal and state government, utilities, universities, and public parking. A literature review of the available relevant business models and case studies of constructed charging stations was completed to support the proposals. In addition, a survey of a university’s students, staff, and faculty was conducted to provide consumer research on people’s opinion of SPCS construction and preference of business model aspects. Results showed that 69% of respondents would be more willing to invest in an electric vehicle if there was sufficient charging station infrastructure at the university. Among many recommendations, the business models suggest installing level 1 charging for the majority of entities, and to match entities’ current pricing structures for station use. The manuscript discusses the impacts of fossil fuel use, and the benefits of electric car and SPCS use, accommodates for the present gap in available literature on SPCS business models, and provides current consumer data for SPCS and the models proposed.
Impact of modellers' decisions on hydrological a priori predictions
Holländer, H. M.; Bormann, H.; Blume, T.; Buytaert, W.; Chirico, G. B.; Exbrayat, J.-F.; Gustafsson, D.; Hölzel, H.; Krauße, T.; Kraft, P.; Stoll, S.; Blöschl, G.; Flühler, H.
2014-06-01
In practice, the catchment hydrologist is often confronted with the task of predicting discharge without having the needed records for calibration. Here, we report the discharge predictions of 10 modellers - using the model of their choice - for the man-made Chicken Creek catchment (6 ha, northeast Germany, Gerwin et al., 2009b) and we analyse how well they improved their prediction in three steps based on adding information prior to each following step. The modellers predicted the catchment's hydrological response in its initial phase without having access to the observed records. They used conceptually different physically based models and their modelling experience differed largely. Hence, they encountered two problems: (i) to simulate discharge for an ungauged catchment and (ii) using models that were developed for catchments, which are not in a state of landscape transformation. The prediction exercise was organized in three steps: (1) for the first prediction the modellers received a basic data set describing the catchment to a degree somewhat more complete than usually available for a priori predictions of ungauged catchments; they did not obtain information on stream flow, soil moisture, nor groundwater response and had therefore to guess the initial conditions; (2) before the second prediction they inspected the catchment on-site and discussed their first prediction attempt; (3) for their third prediction they were offered additional data by charging them pro forma with the costs for obtaining this additional information. Holländer et al. (2009) discussed the range of predictions obtained in step (1). Here, we detail the modeller's assumptions and decisions in accounting for the various processes. We document the prediction progress as well as the learning process resulting from the availability of added information. For the second and third steps, the progress in prediction quality is evaluated in relation to individual modelling experience and costs of
Charging stations location model based on spatiotemporal electromobility use patterns
Pagany, Raphaela; Marquardt, Anna; Zink, Roland
2016-04-01
One of the major challenges for mainstream adoption of electric vehicles is the provision of infrastructure for charging the batteries of the vehicles. The charging stations must not only be located dense enough to allow users to complete their journeys, but the electric energy must also be provided from renewable sources in order to truly offer a transportation with less CO2 emissions. The examination of potential locations for the charging of electric vehicles can facilitate the adaption of electromobility and the integration of electronic vehicles in everyday life. A geographic information system (GIS) based model for optimal location of charging stations in a small and regional scale is presented. This considers parameters such as the forecast of electric vehicle use penetration, the relevant weight of diverse point of interests and the distance between parking area and destination for different vehicle users. In addition to the spatial scale the temporal modelling of the energy demand at the different charging locations has to be considerate. Depending on different user profiles (commuters, short haul drivers etc.) the frequency of charging vary during the day, the week and the year. In consequence, the spatiotemporal variability is a challenge for a reliable energy supply inside a decentralized renewable energy system. The presented model delivers on the one side the most adequate identified locations for charging stations and on the other side the interaction between energy supply and demand for electromobility under the consideration of temporal aspects. Using ESRI ArcGIS Desktop, first results for the case study region of Lower Bavaria are generated. The aim of the concept is to keep the model transferable to other regions and also open to integrate further and more detailed user profiles, derived from social studies about i.e. the daily behavior and the perception of electromobility in a next step.
Solid charged-core model of ball lightning
Directory of Open Access Journals (Sweden)
D. B. Muldrew
2010-01-01
Full Text Available In this study, ball lightning (BL is assumed to have a solid, positively-charged core. According to this underlying assumption, the core is surrounded by a thin electron layer with a charge nearly equal in magnitude to that of the core. A vacuum exists between the core and the electron layer containing an intense electromagnetic (EM field which is reflected and guided by the electron layer. The microwave EM field applies a ponderomotive force (radiation pressure to the electrons preventing them from falling into the core. The energetic electrons ionize the air next to the electron layer forming a neutral plasma layer. The electric-field distributions and their associated frequencies in the ball are determined by applying boundary conditions to a differential equation given by Stratton (1941. It is then shown that the electron and plasma layers are sufficiently thick and dense to completely trap and guide the EM field. This model of BL is exceptional in that it can explain all or nearly all of the peculiar characteristics of BL. The ES energy associated with the core charge can be extremely large which can explain the observations that occasionally BL contains enormous energy. The mass of the core prevents the BL from rising like a helium-filled balloon – a problem with most plasma and burning-gas models. The positively charged core keeps the negatively charged electron layer from diffusing away, i.e. it holds the ball together; other models do not have a mechanism to do this. The high electrical charges on the core and in the electron layer explains why some people have been electrocuted by BL. Experiments indicate that BL radiates microwaves upon exploding and this is consistent with the model. The fact that this novel model of BL can explain these and other observations is strong evidence that the model should be taken seriously.
Modeling of the charge acceptance of lead-acid batteries
Energy Technology Data Exchange (ETDEWEB)
Thele, M.; Schiffer, J.; Sauer, D.U. [Electrochemical Energy Conversion and Storage Systems Group, Institute for Power Electronics and Electrical Drives (ISEA), RWTH Aachen University, Jaegerstrasse 17-19, D-52066 Aachen (Germany); Karden, E.; Surewaard, E. [Ford Research Center Aachen, Aachen (Germany)
2007-05-25
This paper presents a model for flooded and VRLA batteries that is parameterized by impedance spectroscopy and includes the overcharging effects to allow charge-acceptance simulations (e.g. for regenerative-braking drive-cycle profiles). The full dynamic behavior and the short-term charge/discharge history is taken into account. This is achieved by a detailed modeling of the sulfate crystal growth and modeling of the internal gas recombination cycle. The model is applicable in the full realistic temperature and current range of automotive applications. For model validation, several load profiles (covering the dynamics and the current range appearing in electrically assisted or hybrid cars) are examined and the charge-acceptance limiting effects are elaborately discussed. The validation measurements have been performed for different types of lead-acid batteries (flooded and VRLA). The model is therefore an important tool for the development of automotive power nets, but it also allows to analyze different charging strategies and energy gains which can be achieved during regenerative-braking. (author)
Staying Power of Churn Prediction Models
Risselada, Hans; Verhoef, Peter C.; Bijmolt, Tammo H. A.
2010-01-01
In this paper, we study the staying power of various churn prediction models. Staying power is defined as the predictive performance of a model in a number of periods after the estimation period. We examine two methods, logit models and classification trees, both with and without applying a bagging
A zero dimensional model of lithium-sulfur batteries during charge and discharge.
Marinescu, Monica; Zhang, Teng; Offer, Gregory J
2016-01-01
Lithium-sulfur cells present an attractive alternative to Li-ion batteries due to their large energy density, safety, and possible low cost. Their successful commercialisation is dependent on improving their performance, but also on acquiring sufficient understanding of the underlying mechanisms to allow for the development of predictive models for operational cells. To address the latter, we present a zero dimensional model that predicts many of the features observed in the behaviour of a lithium-sulfur cell during charge and discharge. The model accounts for two electrochemical reactions via the Nernst formulation, power limitations through Butler-Volmer kinetics, and precipitation/dissolution of one species, including nucleation. It is shown that the flat shape of the low voltage plateau typical of the lithium-sulfur cell discharge is caused by precipitation. During charge, it is predicted that the dissolution can act as a bottleneck, because for large enough currents the amount that dissolves becomes limited. This results in reduced charge capacity and an earlier onset of the high plateau reaction, such that the two voltage plateaus merge. By including these effects, the model improves on the existing zero dimensional models, while requiring considerably fewer input parameters and computational resources than one dimensional models. The model also predicts that, due to precipitation, the customary way of experimentally obtaining the open circuit voltage from a low rate discharge might not be suitable for lithium-sulfur. This model can provide the basis for mechanistic studies, identification of dominant effects in a real cell, predictions of operational behaviour under realistic loads, and control algorithms for applications. PMID:26618508
A zero dimensional model of lithium-sulfur batteries during charge and discharge.
Marinescu, Monica; Zhang, Teng; Offer, Gregory J
2016-01-01
Lithium-sulfur cells present an attractive alternative to Li-ion batteries due to their large energy density, safety, and possible low cost. Their successful commercialisation is dependent on improving their performance, but also on acquiring sufficient understanding of the underlying mechanisms to allow for the development of predictive models for operational cells. To address the latter, we present a zero dimensional model that predicts many of the features observed in the behaviour of a lithium-sulfur cell during charge and discharge. The model accounts for two electrochemical reactions via the Nernst formulation, power limitations through Butler-Volmer kinetics, and precipitation/dissolution of one species, including nucleation. It is shown that the flat shape of the low voltage plateau typical of the lithium-sulfur cell discharge is caused by precipitation. During charge, it is predicted that the dissolution can act as a bottleneck, because for large enough currents the amount that dissolves becomes limited. This results in reduced charge capacity and an earlier onset of the high plateau reaction, such that the two voltage plateaus merge. By including these effects, the model improves on the existing zero dimensional models, while requiring considerably fewer input parameters and computational resources than one dimensional models. The model also predicts that, due to precipitation, the customary way of experimentally obtaining the open circuit voltage from a low rate discharge might not be suitable for lithium-sulfur. This model can provide the basis for mechanistic studies, identification of dominant effects in a real cell, predictions of operational behaviour under realistic loads, and control algorithms for applications.
Predictive Modelling and Time: An Experiment in Temporal Archaeological Predictive Models
Directory of Open Access Journals (Sweden)
David Ebert
2006-08-01
Full Text Available One of the most common criticisms of archaeological predictive modelling is that it fails to account for temporal or functional differences in sites. However, a practical solution to temporal or functional predictive modelling has proven to be elusive. This article discusses temporal predictive modelling, focusing on the difficulties of employing temporal variables, then introduces and tests a simple methodology for the implementation of temporal modelling. The temporal models thus created are then compared to a traditional predictive model.
Prediction of Physical Properties of Nanofiltration Membranes for Neutral and Charged Solutes
Two commercial nanofiltration (NF) membranes viz., NF 300 MWCO and NF 250 MWCO were used for neutral and charged solute species viz., glucose, sodium chloride and magnesium chloride to investigate their rejection rates using Donnan steric pore model (DSPM) and DSPM-dielectric exc...
Guo, Xuhong; Kirton, Gavin F; Dubin, Paul L
2006-10-26
Carboxylated ficolls were prepared as model spherical colloids of variable charge and size, with radii ranging from 3.0 to 19.3 nm. Capillary electrophoresis (CE), electrophoretic light scattering (ELS), and potentiometric titration were used to determine mobilities as a function of pH, degree of ionization alpha, and surface potential psi(0). Measured mobilities typically display a plateau at high pH, corresponding to high alpha and psi(0), confirming the general nature of this effect for charged spheres, seen also for charged dendrimers and charged latex particles. This result is examined in the context of a discontinuity in mobility predicted by the Wiersema, O'Brien, and White (WOW) theory and a more recent primitive model electrophoresis (PME) theory, in which bound counterions are considered either as point charges or as hard spheres. While no mobility maximum can be determined as expected by these two theories, our data seem more to support Belloni's theoretical expectations on charged polymers and spheres. Here we explain the mobility plateaus in terms of counterions accumulated close to the surface (surface potential-determining ions) or within the shear plane (mobility-determining ions).
CERN PS Booster space charge simulations with a realistic model for alignement and field errors
Forte, V; McAteer, M
2014-01-01
The CERN PS Booster is one of the machines of the LHC injector chain which will be upgraded within the LIU (LHC Injectors upgrade) project. The injection energy of the PSB will be increased to 160MeV in order to mitigate direct space charge effects, considered to be the main performance limitation, thus allowing to double the brightness for the LHC beams. In order to better predict the gain to be expected, space charge simulations are being carried out. Efforts to establish a realistic modeling of field and alignment errors aim at extending the basic model of the machine towards a more realistic one. Simulations of beam dynamics with strong direct space charge and realistic errors are presented and analysed in this paper.
Comparison of Prediction-Error-Modelling Criteria
DEFF Research Database (Denmark)
Jørgensen, John Bagterp; Jørgensen, Sten Bay
2007-01-01
Single and multi-step prediction-error-methods based on the maximum likelihood and least squares criteria are compared. The prediction-error methods studied are based on predictions using the Kalman filter and Kalman predictors for a linear discrete-time stochastic state space model, which...
DEFF Research Database (Denmark)
De Vico, L.; Iversen, L.; Sørensen, Martin Hedegård;
2011-01-01
A single charge screening model of surface charge sensors in liquids (De Vico et al., Nanoscale, 2011, 3, 706-717) is extended to multiple charges to model the effect of the charge distributions of analyte proteins on FET sensor response. With this model we show that counter-intuitive signal...... changes (e.g. a positive signal change due to a net positive protein binding to a p-type conductor) can occur for certain combinations of charge distributions and Debye lengths. The new method is applied to interpret published experimental data on Streptavidin (Ishikawa et al., ACS Nano, 2009, 3, 3969...
Thermodynamic model for bouncing charged particles inside a capacitor
Rezaeizadeh, Amin; Mameghani, Pooya
2013-08-01
We introduce an equation of state for a conducting particle inside a charged parallel-plate capacitor and show that it is similar to the equation of state for an ideal gas undergoing an adiabatic process. We describe a simple experiment that shows reasonable agreement with the theoretical model.
Quantitative prediction of charge mobilities of π-stacked systems by first-principles simulation.
Deng, Wei-Qiao; Sun, Lei; Huang, Jin-Dou; Chai, Shuo; Wen, Shu-Hao; Han, Ke-Li
2015-04-01
This protocol is intended to provide chemists and physicists with a tool for predicting the charge carrier mobilities of π-stacked systems such as organic semiconductors and the DNA double helix. An experimentally determined crystal structure is required as a starting point. The simulation involves the following operations: (i) searching the crystal structure; (ii) selecting molecular monomers and dimers from the crystal structure; (iii) using density function theory (DFT) calculations to determine electronic coupling for dimers; (iv) using DFT calculations to determine self-reorganization energy of monomers; and (v) using a numerical calculation to determine the charge carrier mobility. For a single crystal structure consisting of medium-sized molecules, this protocol can be completed in ∼4 h. We have selected two case studies (a rubrene crystal and a DNA segment) as examples of how this procedure can be used. PMID:25811897
Sparse preconditioning for model predictive control
Knyazev, Andrew; Malyshev, Alexander,
2015-01-01
We propose fast O(N) preconditioning, where N is the number of gridpoints on the prediction horizon, for iterative solution of (non)-linear systems appearing in model predictive control methods such as forward-difference Newton-Krylov methods. The Continuation/GMRES method for nonlinear model predictive control, suggested by T. Ohtsuka in 2004, is a specific application of the Newton-Krylov method, which uses the GMRES iterative algorithm to solve a forward difference approximation of the opt...
Meta-analysis of clinical prediction models
Debray, T.P.A.
2013-01-01
The past decades there has been a clear shift from implicit to explicit diagnosis and prognosis. This includes appreciation of clinical -diagnostic and prognostic- prediction models, which is likely to increase with the introduction of fully computerized patient records. Prediction models aim to pro
Unreachable Setpoints in Model Predictive Control
DEFF Research Database (Denmark)
Rawlings, James B.; Bonné, Dennis; Jørgensen, John Bagterp;
2008-01-01
In this work, a new model predictive controller is developed that handles unreachable setpoints better than traditional model predictive control methods. The new controller induces an interesting fast/slow asymmetry in the tracking response of the system. Nominal asymptotic stability of the optimal...
Childhood asthma prediction models: a systematic review.
Smit, Henriette A; Pinart, Mariona; Antó, Josep M; Keil, Thomas; Bousquet, Jean; Carlsen, Kai H; Moons, Karel G M; Hooft, Lotty; Carlsen, Karin C Lødrup
2015-12-01
Early identification of children at risk of developing asthma at school age is crucial, but the usefulness of childhood asthma prediction models in clinical practice is still unclear. We systematically reviewed all existing prediction models to identify preschool children with asthma-like symptoms at risk of developing asthma at school age. Studies were included if they developed a new prediction model or updated an existing model in children aged 4 years or younger with asthma-like symptoms, with assessment of asthma done between 6 and 12 years of age. 12 prediction models were identified in four types of cohorts of preschool children: those with health-care visits, those with parent-reported symptoms, those at high risk of asthma, or children in the general population. Four basic models included non-invasive, easy-to-obtain predictors only, notably family history, allergic disease comorbidities or precursors of asthma, and severity of early symptoms. Eight extended models included additional clinical tests, mostly specific IgE determination. Some models could better predict asthma development and other models could better rule out asthma development, but the predictive performance of no single model stood out in both aspects simultaneously. This finding suggests that there is a large proportion of preschool children with wheeze for which prediction of asthma development is difficult.
Charge quantization in the CP(1) nonlinear σ-model
Energy Technology Data Exchange (ETDEWEB)
Hellerman, Simeon, E-mail: simeon.hellerman.1@gmail.com; Kehayias, John, E-mail: john.kehayias@ipmu.jp; Yanagida, Tsutomu T., E-mail: tsutomu.tyanagida@ipmu.jp
2014-01-20
We investigate the consistency conditions for matter fields coupled to the four-dimensional (N=1 supersymmetric) CP(1) nonlinear sigma model (the coset space SU(2){sub G}/U(1){sub H}). We find that consistency requires that the U(1){sub H} charge of the matter be quantized, in units of half of the U(1){sub H} charge of the Nambu–Goldstone (NG) boson, if the matter has a nonsingular kinetic term and the dynamics respect the full group SU(2){sub G}. We can then take the linearly realized group U(1){sub H} to comprise the weak hypercharge group U(1){sub Y} of the Standard Model. Thus we have charge quantization without a Grand Unified Theory (GUT), completely avoiding problems like proton decay, doublet–triplet splitting, and magnetic monopoles. We briefly investigate the phenomenological implications of this model-building framework. The NG boson is fractionally charged and completely stable. It can be naturally light, avoiding constraints while being a component of dark matter or having applications in nuclear physics. We also comment on the extension to other NLSMs on coset spaces, which will be explored more fully in a followup paper.
Charge Quantization in the CP(1) Nonlinear Sigma-Model
Hellerman, Simeon; Yanagida, Tsutomu T
2013-01-01
We investigate the consistency conditions for matter fields coupled to the four-dimensional (N = 1 supersymmetric) CP(1) nonlinear sigma model (the coset space SU(2)_G/U(1)_H). We find that consistency requires that the U(1)_H charge of the matter be quantized, in units of half of the U(1)_H charge of the Nambu-Goldstone (NG) boson, if the matter has a nonsingular kinetic term and the dynamics respect the full group SU(2)_G. We can then take the linearly realized group U(1)_H to comprise the weak hypercharge group U(1)_Y of the Standard Model. Thus we have charge quantization without a Grand Unified Theory (GUT), completely avoiding problems like proton decay, doublet-triplet splitting, and magnetic monopoles. We briefly investigate the phenomenological implications of this model-building framework. The NG boson is fractionally charged and completely stable. It can be naturally light, avoiding constraints while being a component of dark matter or having applications in nuclear physics. We also comment on the ...
A Unified Channel Charges Expression for Analytic MOSFET Modeling
Hugues Murray; Patrick Martin
2012-01-01
Based on a 1D Poissons equation resolution, we present an analytic model of inversion charges allowing calculation of the drain current and transconductance in the Metal Oxide Semiconductor Field Effect Transistor. The drain current and transconductance are described by analytical functions including mobility corrections and short channel effects (CLM, DIBL). The comparison with the Pao-Sah integral shows excellent accuracy of the model in all inversion modes from strong to weak inversion in ...
Models for Energy and Charge Transport and Storage in Biomolecules
Mingaleev, S. F.; Christiansen, P. L.; Gaididei, Yu. B.; M. Johansson; Rasmussen, K.Ø.
1999-01-01
Two models for energy and charge transport and storage in biomolecules are considered. A model based on the discrete nonlinear Schrodinger equation with long-range dispersive interactions (LRI's) between base pairs of DNA is offered for the description of nonlinear dynamics of the DNA molecule. We show that LRI's are responsible for the existence of an interval of bistability where two stable stationary states, a narrow, pinned state and a broad, mobile state, coexist at each value of the tot...
Universal Finite Size Corrections and the Central Charge in Non-solvable Ising Models
Giuliani, Alessandro; Mastropietro, Vieri
2013-01-01
We investigate a non solvable two-dimensional ferromagnetic Ising model with nearest neighbor plus weak finite range interactions of strength \\lambda. We rigorously establish one of the predictions of Conformal Field Theory (CFT), namely the fact that at the critical temperature the finite size corrections to the free energy are universal, in the sense that they are exactly independent of the interaction. The corresponding central charge, defined in terms of the coefficient of the first suble...
Combinatorial Modelling and Learning with Prediction Markets
Hu, Jinli
2012-01-01
Combining models in appropriate ways to achieve high performance is commonly seen in machine learning fields today. Although a large amount of combinatorial models have been created, little attention is drawn to the commons in different models and their connections. A general modelling technique is thus worth studying to understand model combination deeply and shed light on creating new models. Prediction markets show a promise of becoming such a generic, flexible combinatorial model. By reviewing on several popular combinatorial models and prediction market models, this paper aims to show how the market models can generalise different combinatorial stuctures and how they implement these popular combinatorial models in specific conditions. Besides, we will see among different market models, Storkey's \\emph{Machine Learning Markets} provide more fundamental, generic modelling mechanisms than the others, and it has a significant appeal for both theoretical study and application.
Institute of Scientific and Technical Information of China (English)
Hu Bo; Huang Shi-Hua; Wu Feng-Min
2013-01-01
A model based on analysis of the self-consistent Poisson-Schrodinger equation is proposed to investigate the tunneling current of electrons in the inversion layer of a p-type metal-oxide-semiconductor (MOS) structure.In this model,the influences of interface trap charge (ITC) at the Si-SiO2 interface and fixed oxide charge (FOC) in the oxide region are taken into account,and one-band effective mass approximation is used.The tunneling probability is obtained by employing the transfer matrix method.Further,the effects of in-plane momentum on the quantization in the electron motion perpendicular to the Si-SiO2 interface of a MOS device are investigated.Theoretical simulation results indicate that both ITC and FOC have great influence on the tunneling current through a MOS structure when their densities are larger than 1012 cm-2,which results from the great change of bound electrons near the Si-SiO2 interface and the oxide region.Therefore,for real ultrathin MOS structures with ITC and FOC,this model can give a more accurate description for the tunneling current in the inversion layer.
Model predictive control classical, robust and stochastic
Kouvaritakis, Basil
2016-01-01
For the first time, a textbook that brings together classical predictive control with treatment of up-to-date robust and stochastic techniques. Model Predictive Control describes the development of tractable algorithms for uncertain, stochastic, constrained systems. The starting point is classical predictive control and the appropriate formulation of performance objectives and constraints to provide guarantees of closed-loop stability and performance. Moving on to robust predictive control, the text explains how similar guarantees may be obtained for cases in which the model describing the system dynamics is subject to additive disturbances and parametric uncertainties. Open- and closed-loop optimization are considered and the state of the art in computationally tractable methods based on uncertainty tubes presented for systems with additive model uncertainty. Finally, the tube framework is also applied to model predictive control problems involving hard or probabilistic constraints for the cases of multiplic...
Disease Models for Event Prediction
Corley, Courtney D.; Pullum, Laura
2013-01-01
Objective The objective of this manuscript is to present a systematic review of biosurveillance models that operate on select agents and can forecast the occurrence of a disease event. Introduction One of the primary goals of this research was to characterize the viability of biosurveillance models to provide operationally relevant information to decision makers, in order to identify areas for future research. Two critical characteristics differentiate this work from other infectious disease ...
Unique Phenomena in Preon Model with Preonic Charge
Senju, H.
1988-01-01
Properties of new particles predicted by the recently proposed preon model are discussed based on SU(6)_{wc}. q' and q_{3}'' are expected to be observed in a relatively low energy region. Their experimental signatures are discussed.
Directory of Open Access Journals (Sweden)
Yin Hua
2015-04-01
Full Text Available Estimation of state of charge (SOC is of great importance for lithium-ion (Li-ion batteries used in electric vehicles. This paper presents a state of charge estimation method using nonlinear predictive filter (NPF and evaluates the proposed method on the lithium-ion batteries with different chemistries. Contrary to most conventional filters which usually assume a zero mean white Gaussian process noise, the advantage of NPF is that the process noise in NPF is treated as an unknown model error and determined as a part of the solution without any prior assumption, and it can take any statistical distribution form, which improves the estimation accuracy. In consideration of the model accuracy and computational complexity, a first-order equivalent circuit model is applied to characterize the battery behavior. The experimental test is conducted on the LiCoO2 and LiFePO4 battery cells to validate the proposed method. The results show that the NPF method is able to accurately estimate the battery SOC and has good robust performance to the different initial states for both cells. Furthermore, the comparison study between NPF and well-established extended Kalman filter for battery SOC estimation indicates that the proposed NPF method has better estimation accuracy and converges faster.
A minimal and predictive $T_7$ lepton flavor 331 model
Hernández, A E Cárcamo
2015-01-01
We present a model based on the $SU(3)_{C}\\otimes SU(3)_{L}\\otimes U(1)_{X}$ gauge group having an extra $T_{7}\\otimes Z_{3}\\otimes Z_{14}$ flavor group, where the light active neutrino masses arise via double seesaw mechanism and the observed charged lepton mass hierarchy is a consequence of the $Z_{14}$ symmetry breaking at very high energy. In our minimal and predictive $T_7$ lepton flavor 331 model, the spectrum of neutrinos includes very light active neutrinos and heavy and very heavy sterile neutrinos. The obtained neutrino mixing parameters and neutrino mass squared splittings are compatible with the neutrino oscillation experimental data, for both normal and inverted hierarchies. The model predicts CP conservation in neutrino oscillations.
Single Production of Doubly Charged Higgs Boson via e7 Collision in Higgs Triplet Model
Institute of Scientific and Technical Information of China (English)
苏雪松; 岳崇兴; 张娇; 王珏
2011-01-01
The Higgs triplet model （HTM） predicts the existence of a pair of doubly charged Higgs bosons H±±. Single production of H±± via e7 collision at the next generation e＋ e- International Linear Collider （ILC） and the Large Hadron electron Collider （LHeC） is considered. The numerical results show that the production cross sections are very sensitive to the neutrino oscillation parameters. Their values for the inverted hierarchy mass spectrum are larger than those for the normal hierarchy mass spectrum at these two kinds of collider experiments. With reasonable values of the relevant free parameters, the possible signals of the doubly charged Higgs bosons predicted by the HTM might be detected in future ILC experiments.
Massive Predictive Modeling using Oracle R Enterprise
CERN. Geneva
2014-01-01
R is fast becoming the lingua franca for analyzing data via statistics, visualization, and predictive analytics. For enterprise-scale data, R users have three main concerns: scalability, performance, and production deployment. Oracle's R-based technologies - Oracle R Distribution, Oracle R Enterprise, Oracle R Connector for Hadoop, and the R package ROracle - address these concerns. In this talk, we introduce Oracle's R technologies, highlighting how each enables R users to achieve scalability and performance while making production deployment of R results a natural outcome of the data analyst/scientist efforts. The focus then turns to Oracle R Enterprise with code examples using the transparency layer and embedded R execution, targeting massive predictive modeling. One goal behind massive predictive modeling is to build models per entity, such as customers, zip codes, simulations, in an effort to understand behavior and tailor predictions at the entity level. Predictions...
Optimal Prediction in Loglinear Models
K.J. van Garderen
2001-01-01
This paper introduces a Laplace inversion technique for deriving unbiased predictors in exponential families. This general technique is applied to derive the exact optimal unbiased predictor in loglinear models with Gaussian disturbances under quadratic loss. An exact unbiased estimator for its vari
Liver Cancer Risk Prediction Models
Developing statistical models that estimate the probability of developing liver cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.
Breast Cancer Risk Prediction Models
Developing statistical models that estimate the probability of developing breast cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.
Prostate Cancer Risk Prediction Models
Developing statistical models that estimate the probability of developing prostate cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.
Pancreatic Cancer Risk Prediction Models
Developing statistical models that estimate the probability of developing pancreatic cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.
Colorectal Cancer Risk Prediction Models
Developing statistical models that estimate the probability of developing colorectal cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.
Bladder Cancer Risk Prediction Models
Developing statistical models that estimate the probability of developing bladder cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.
Esophageal Cancer Risk Prediction Models
Developing statistical models that estimate the probability of developing esophageal cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.
Cervical Cancer Risk Prediction Models
Developing statistical models that estimate the probability of developing cervical cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.
Testicular Cancer Risk Prediction Models
Developing statistical models that estimate the probability of testicular cervical cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.
Ovarian Cancer Risk Prediction Models
Developing statistical models that estimate the probability of developing ovarian cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.
Lung Cancer Risk Prediction Models
Developing statistical models that estimate the probability of developing lung cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.
Impact of modellers' decisions on hydrological a priori predictions
Directory of Open Access Journals (Sweden)
H. M. Holländer
2013-07-01
Full Text Available The purpose of this paper is to stimulate a re-thinking of how we, the catchment hydrologists, could become reliable forecasters. A group of catchment modellers predicted the hydrological response of a man-made 6 ha catchment in its initial phase (Chicken Creek without having access to the observed records. They used conceptually different model families. Their modelling experience differed largely. The prediction exercise was organized in three steps: (1 for the 1st prediction modellers received a basic data set describing the internal structure of the catchment (somewhat more complete than usually available to a priori predictions in ungauged catchments. They did not obtain time series of stream flow, soil moisture or groundwater response. (2 Before the 2nd improved prediction they inspected the catchment on-site and attended a workshop where the modellers presented and discussed their first attempts. (3 For their improved 3rd prediction they were offered additional data by charging them pro forma with the costs for obtaining this additional information. Holländer et al. (2009 discussed the range of predictions obtained in step 1. Here, we detail the modeller's decisions in accounting for the various processes based on what they learned during the field visit (step 2 and add the final outcome of step 3 when the modellers made use of additional data. We document the prediction progress as well as the learning process resulting from the availability of added information. For the 2nd and 3rd step, the progress in prediction quality could be evaluated in relation to individual modelling experience and costs of added information. We learned (i that soft information such as the modeller's system understanding is as important as the model itself (hard information, (ii that the sequence of modelling steps matters (field visit, interactions between differently experienced experts, choice of model, selection of available data, and methods for parameter
Simple models for charge and salt effects in protein crystallisation
Warren, Patrick B
2002-01-01
A simple extension of existing models for protein crystallisation is described, in which salt ions and charge neutrality are explicitly incorporated. This provides a straightforward explanation for the shape of protein crystallisation boundaries, the associated scaling properties seen for lysozyme, and can also explain much of the salt dependence of the second virial coefficient. The analysis has wider implications for the use of pair potentials to understand protein crystallisation.
A Model of Charge Transfer Excitons: Diffusion, Spin Dynamics, and Magnetic Field Effects
Lee, Chee Kong; Willard, Adam P
2016-01-01
In this letter we explore how the microscopic dynamics of charge transfer (CT) excitons are influenced by the presence of an external magnetic field in disordered molecular semiconductors. This influence is driven by the dynamic interplay between the spin and spatial degrees of freedom of the electron-hole pair. To account for this interplay we have developed a numerical framework that combines a traditional model of quantum spin dynamics with a coarse-grained model of stochastic charge transport. This combination provides a general and efficient methodology for simulating the effects of magnetic field on CT state dynamics, therefore providing a basis for revealing the microscopic origin of experimentally observed magnetic field effects. We demonstrate that simulations carried out on our model are capable of reproducing experimental results as well as generating theoretical predictions related to the efficiency of organic electronic materials.
Modeling and Prediction Using Stochastic Differential Equations
DEFF Research Database (Denmark)
Juhl, Rune; Møller, Jan Kloppenborg; Jørgensen, John Bagterp;
2016-01-01
Pharmacokinetic/pharmakodynamic (PK/PD) modeling for a single subject is most often performed using nonlinear models based on deterministic ordinary differential equations (ODEs), and the variation between subjects in a population of subjects is described using a population (mixed effects) setup...... deterministic and can predict the future perfectly. A more realistic approach would be to allow for randomness in the model due to e.g., the model be too simple or errors in input. We describe a modeling and prediction setup which better reflects reality and suggests stochastic differential equations (SDEs...
Charged Higgs pair production at the LHC as a probe of the top-seesaw assisted technicolor model
Liu, Guo-Li; Zhou, Ping; Guo, Xiao-Fei; Wu, Kun; Jiang, Ji
2016-07-01
The top-seesaw assisted technicolor (TC) model, which was proposed recently to accommodate the 126 GeV Higgs mass discovered by the Large Hadron Colliders (LHC), predicts light and heavy charged Higgs bosons in addition to the neutral Higgses. In this paper, we will study the pair productions of the charged Higgs, proceeding through gluon-gluon fusion and quark-antiquark annihilation, at the LHC in the frame of the top-seesaw assisted TC model. We find that in a large part of parameter space the production cross-sections of the light charged Higgs pair at the LHC can be quite large compared with the low standard model backgrounds, while it is impossible for the pair production of the heavy ones to be detected with the strong final mass suppression. Therefore, the light charged Higgs pair production may be served as a probe of this new TC model at the LHC.
A Physics-Based Charge-Control Model for InP DHBT Including Current-Blocking Effect
Institute of Scientific and Technical Information of China (English)
GE Ji; JIN Zhi; SU Yong-Bo; CHENG Wei; WANG Xian-Wai; CHEN Gao-Peng; LIU Xin-Yu
2009-01-01
We develop a physics-based charge-control InP double heterojunction bipolar transistor model including three important effects: current blocking, mobile-charge modulation of the base-collector capacitance and velocity-field modulation in the transit time. The bias-dependent base-collector depletion charge is obtained analytically, which takes into account the mobile-charge modulation. Then, a measurement based voltage-dependent transit time formulation is implemented. As a result, over a wide range of biases, the developed model shows good agreement between the modeled and measured S-parameters and cutoff frequency. Also, the model considering current blocking effect demonstrates more accurate prediction of the output characteristics than conventional vertical bipolar inter company results.
Lepton Flavor Violation in Predictive SUSY-GUT Models
Energy Technology Data Exchange (ETDEWEB)
Albright, Carl H.; /Northern Illinois U. /Fermilab; Chen, Mu-Chun; /UC, Irvine
2008-02-01
There have been many theoretical models constructed which aim to explain the neutrino masses and mixing patterns. While many of the models will be eliminated once more accurate determinations of the mixing parameters, especially sin{sup 2} 2{theta}{sub 13}, are obtained, charged lepton flavor violation (LFV) experiments are able to differentiate even further among the models. In this paper, they investigate various rare LFV processes, such as {ell}{sub i} {yields} {ell}{sub j} + {gamma} and {mu} - e conversion, in five predictive SUSY SO(10) models and their allowed soft SUSY breaking parameter space in the constrained minimal SUSY standard model (CMSSM). Utilizing the WMAP dark matter constraints, they obtain lower bounds on the branching ratios of these rare processes and find that at least three of the five models they consider give rise to predictions for {mu} {yields} e + {gamma} that will be tested by the MEG collaboration at PSI. in addition, the next generation {mu} - e conversion experiment has sensitivity to the predictions of all five models, making it an even more robust way to test these models. While generic studies have emphasized the dependence of the branching ratios of these rare processes on the reactor neutrino angle, {theta}{sub 13}, and the mass of the heaviest right-handed neutrino, M{sub 3}, they find very massive M{sub 3} is more significant than large {theta}{sub 13} in leading to branching ratios near to the present upper limits.
Mathematical modeling to predict residential solid waste generation
International Nuclear Information System (INIS)
One of the challenges faced by waste management authorities is determining the amount of waste generated by households in order to establish waste management systems, as well as trying to charge rates compatible with the principle applied worldwide, and design a fair payment system for households according to the amount of residential solid waste (RSW) they generate. The goal of this research work was to establish mathematical models that correlate the generation of RSW per capita to the following variables: education, income per household, and number of residents. This work was based on data from a study on generation, quantification and composition of residential waste in a Mexican city in three stages. In order to define prediction models, five variables were identified and included in the model. For each waste sampling stage a different mathematical model was developed, in order to find the model that showed the best linear relation to predict residential solid waste generation. Later on, models to explore the combination of included variables and select those which showed a higher R2 were established. The tests applied were normality, multicolinearity and heteroskedasticity. Another model, formulated with four variables, was generated and the Durban-Watson test was applied to it. Finally, a general mathematical model is proposed to predict residential waste generation, which accounts for 51% of the total
Charge-Spot Model for Electrostatic Forces in Simulation of Fine Particulates
Walton, Otis R.; Johnson, Scott M.
2010-01-01
The charge-spot technique for modeling the static electric forces acting between charged fine particles entails treating electric charges on individual particles as small sets of discrete point charges, located near their surfaces. This is in contrast to existing models, which assume a single charge per particle. The charge-spot technique more accurately describes the forces, torques, and moments that act on triboelectrically charged particles, especially image-charge forces acting near conducting surfaces. The discrete element method (DEM) simulation uses a truncation range to limit the number of near-neighbor charge spots via a shifted and truncated potential Coulomb interaction. The model can be readily adapted to account for induced dipoles in uncharged particles (and thus dielectrophoretic forces) by allowing two charge spots of opposite signs to be created in response to an external electric field. To account for virtual overlap during contacts, the model can be set to automatically scale down the effective charge in proportion to the amount of virtual overlap of the charge spots. This can be accomplished by mimicking the behavior of two real overlapping spherical charge clouds, or with other approximate forms. The charge-spot method much more closely resembles real non-uniform surface charge distributions that result from tribocharging than simpler approaches, which just assign a single total charge to a particle. With the charge-spot model, a single particle may have a zero net charge, but still have both positive and negative charge spots, which could produce substantial forces on the particle when it is close to other charges, when it is in an external electric field, or when near a conducting surface. Since the charge-spot model can contain any number of charges per particle, can be used with only one or two charge spots per particle for simulating charging from solar wind bombardment, or with several charge spots for simulating triboelectric charging
A Course in... Model Predictive Control.
Arkun, Yaman; And Others
1988-01-01
Describes a graduate engineering course which specializes in model predictive control. Lists course outline and scope. Discusses some specific topics and teaching methods. Suggests final projects for the students. (MVL)
Equivalency and unbiasedness of grey prediction models
Institute of Scientific and Technical Information of China (English)
Bo Zeng; Chuan Li; Guo Chen; Xianjun Long
2015-01-01
In order to deeply research the structure discrepancy and modeling mechanism among different grey prediction mo-dels, the equivalence and unbiasedness of grey prediction mo-dels are analyzed and verified. The results show that al the grey prediction models that are strictly derived from x(0)(k) +az(1)(k) = b have the identical model structure and simulation precision. Moreover, the unbiased simulation for the homoge-neous exponential sequence can be accomplished. However, the models derived from dx(1)/dt+ax(1) =b are only close to those derived from x(0)(k)+az(1)(k)=b provided that|a|has to satisfy|a| < 0.1; neither could the unbiased simulation for the homoge-neous exponential sequence be achieved. The above conclusions are proved and verified through some theorems and examples.
Property predictions using microstructural modeling
Energy Technology Data Exchange (ETDEWEB)
Wang, K.G. [Department of Materials Science and Engineering, Rensselaer Polytechnic Institute, CII 9219, 110 8th Street, Troy, NY 12180-3590 (United States)]. E-mail: wangk2@rpi.edu; Guo, Z. [Sente Software Ltd., Surrey Technology Centre, 40 Occam Road, Guildford GU2 7YG (United Kingdom); Sha, W. [Metals Research Group, School of Civil Engineering, Architecture and Planning, The Queen' s University of Belfast, Belfast BT7 1NN (United Kingdom); Glicksman, M.E. [Department of Materials Science and Engineering, Rensselaer Polytechnic Institute, CII 9219, 110 8th Street, Troy, NY 12180-3590 (United States); Rajan, K. [Department of Materials Science and Engineering, Rensselaer Polytechnic Institute, CII 9219, 110 8th Street, Troy, NY 12180-3590 (United States)
2005-07-15
Precipitation hardening in an Fe-12Ni-6Mn maraging steel during overaging is quantified. First, applying our recent kinetic model of coarsening [Phys. Rev. E, 69 (2004) 061507], and incorporating the Ashby-Orowan relationship, we link quantifiable aspects of the microstructures of these steels to their mechanical properties, including especially the hardness. Specifically, hardness measurements allow calculation of the precipitate size as a function of time and temperature through the Ashby-Orowan relationship. Second, calculated precipitate sizes and thermodynamic data determined with Thermo-Calc[copyright] are used with our recent kinetic coarsening model to extract diffusion coefficients during overaging from hardness measurements. Finally, employing more accurate diffusion parameters, we determined the hardness of these alloys independently from theory, and found agreement with experimental hardness data. Diffusion coefficients determined during overaging of these steels are notably higher than those found during the aging - an observation suggesting that precipitate growth during aging and precipitate coarsening during overaging are not controlled by the same diffusion mechanism.
Predictive technology model for robust nanoelectronic design
Cao, Yu
2011-01-01
Predictive Technology Model for Robust Nanoelectronic Design explains many of the technical mysteries behind the Predictive Technology Model (PTM) that has been adopted worldwide in explorative design research. Through physical derivation and technology extrapolation, PTM is the de-factor device model used in electronic design. This work explains the systematic model development and provides a guide to robust design practice in the presence of variability and reliability issues. Having interacted with multiple leading semiconductor companies and university research teams, the author brings a s
A Unified Channel Charges Expression for Analytic MOSFET Modeling
Directory of Open Access Journals (Sweden)
Hugues Murray
2012-01-01
Full Text Available Based on a 1D Poissons equation resolution, we present an analytic model of inversion charges allowing calculation of the drain current and transconductance in the Metal Oxide Semiconductor Field Effect Transistor. The drain current and transconductance are described by analytical functions including mobility corrections and short channel effects (CLM, DIBL. The comparison with the Pao-Sah integral shows excellent accuracy of the model in all inversion modes from strong to weak inversion in submicronics MOSFET. All calculations are encoded with a simple C program and give instantaneous results that provide an efficient tool for microelectronics users.
Modeling Dendrimers Charge Interaction in Solution: Relevance in Biosystems
Directory of Open Access Journals (Sweden)
Domenico Lombardo
2014-01-01
Full Text Available Dendrimers are highly branched macromolecules obtained by stepwise controlled, reaction sequences. The ability to be designed for specific applications makes dendrimers unprecedented components to control the structural organization of matter during the bottom-up synthesis of functional nanostructures. For their applications in the field of biotechnology the determination of dendrimer structural properties as well as the investigation of the specific interaction with guest components are needed. We show how the analysis of the scattering structure factor S(q, in the framework of current models for charged systems in solution, allows for obtaining important information of the interdendrimers electrostatic interaction potential. The finding of the presented results outlines the important role of the dendrimer charge and the solvent conditions in regulating, through the modulation of the electrostatic interaction potential, great part of the main structural properties. This charge interaction has been indicated by many studies as a crucial factor for a wide range of structural processes involving their biomedical application. Due to their easily controllable properties dendrimers can be considered at the crossroad between traditional colloids, associating polymers, and biological systems and represent then an interesting new technological approach and a suitable model system of molecular organization in biochemistry and related fields.
Prediction of blast-induced air overpressure: a hybrid AI-based predictive model.
Jahed Armaghani, Danial; Hajihassani, Mohsen; Marto, Aminaton; Shirani Faradonbeh, Roohollah; Mohamad, Edy Tonnizam
2015-11-01
Blast operations in the vicinity of residential areas usually produce significant environmental problems which may cause severe damage to the nearby areas. Blast-induced air overpressure (AOp) is one of the most important environmental impacts of blast operations which needs to be predicted to minimize the potential risk of damage. This paper presents an artificial neural network (ANN) optimized by the imperialist competitive algorithm (ICA) for the prediction of AOp induced by quarry blasting. For this purpose, 95 blasting operations were precisely monitored in a granite quarry site in Malaysia and AOp values were recorded in each operation. Furthermore, the most influential parameters on AOp, including the maximum charge per delay and the distance between the blast-face and monitoring point, were measured and used to train the ICA-ANN model. Based on the generalized predictor equation and considering the measured data from the granite quarry site, a new empirical equation was developed to predict AOp. For comparison purposes, conventional ANN models were developed and compared with the ICA-ANN results. The results demonstrated that the proposed ICA-ANN model is able to predict blast-induced AOp more accurately than other presented techniques. PMID:26433903
Predictions of charged charmonium-like structures with hidden-charm and open-strange channel
Chen, Dian-Yong; Matsuki, Takayuki
2013-01-01
We propose the initial single chiral particle emission (ISChE) mechanism, with which the hidden-charm di-kaon decays of higher charmonia and charmonium-like states are studied. Calculating the distributions of differential decay width, we obtain the line shape of the $J/\\psi K^+$ invariant mass spectrum of $\\psi_i\\to J/\\psi K^+K^-$, where $\\psi_i=\\psi(4415), Y(4660)$, and $\\psi(4790)$. Our numerical results show that there exist enhancement structures with both hidden-charm and open-strange, which are near the $D\\bar{D}_s^*/D^*\\bar{D}_s$ and $D^*\\bar{D}_s^*/\\bar{D}^*{D}_s^*$ thresholds. These charged charmonium-like structures predicted in this paper can be accessible at future experiment, especially BESIII, BelleII and SuperB.
Current mixing and properties of vector bosons in preon model with preonic charge
Energy Technology Data Exchange (ETDEWEB)
Senju, Hirofumi (Nagoya Municipal Women' s Coll. (Japan))
1994-09-01
In the preon model with preonic charge, new vector boson which can mix with the photon exists. On the basis of the current mixing model, its properties are studied. Cross sections of e[sup +]e[sup -] [yields] U boson pair and of [iota][sub s]-nucleus scattering are given. It will be also shown that, if the new vector boson is sufficiently heavy (say [approx] 500 GeV), the success of the standard model at the LEP level is naturally reproduced. Small deviations from the standard model are predicted in a definite way, which seems to be rather supported by the data. Our model leads to lighter W boson than the standard model does and to positive [epsilon][sub b] parameter in contrast to the standard model. (author).
Current Mixing and Properties of Vector Bosons in Preon Model with Preonic Charge
Senju, H.
1994-09-01
In the preon model with preonic charge, new vector boson which can mix with the photon exists. On the basis of the current mixing model, its properties are studied. Cross sections of e+e- --> U boson pair and of ls-nucleus scattering are given. It will be also shown that, if the new vector boson is sufficiently heavy (say ~500 GeV), the success of the standard model at the LEP level is naturally reproduced. Small deviations from the standard model are predicted in a definite way, which seems to be rather supported by the data. Our model leads to lighter W boson than the standard model does and to positive ɛb parameter in contrast to the standard model.
Prediction of PARP Inhibition with Proteochemometric Modelling and Conformal Prediction.
Cortés-Ciriano, Isidro; Bender, Andreas; Malliavin, Thérèse
2015-06-01
Poly(ADP-ribose) polymerases (PARPs) play a key role in DNA damage repair. PARP inhibitors act as chemo- and radio- sensitizers and thus potentiate the cytotoxicity of DNA damaging agents. Although PARP inhibitors are currently investigated as chemotherapeutic agents, their cross-reactivity with other members of the PARP family remains unclear. Here, we apply Proteochemometric Modelling (PCM) to model the activity of 181 compounds on 12 human PARPs. We demonstrate that PCM (R0 (2) test =0.65-0.69; RMSEtest =0.95-1.01 °C) displays higher performance on the test set (interpolation) than Family QSAR and Family QSAM (Tukey's HSD, α 0.05), and outperforms Inductive Transfer knowledge among targets (Tukey's HSD, α 0.05). We benchmark the predictive signal of 8 amino acid and 11 full-protein sequence descriptors, obtaining that all of them (except for SOCN) perform at the same level of statistical significance (Tukey's HSD, α 0.05). The extrapolation power of PCM to new compounds (RMSE=1.02±0.80 °C) and targets (RMSE=1.03±0.50 °C) is comparable to interpolation, although the extrapolation ability is not uniform across the chemical and the target space. For this reason, we also provide confidence intervals calculated with conformal prediction. In addition, we present the R package conformal, which permits the calculation of confidence intervals for regression and classification caret models. PMID:27490382
Mao, Runfang; Lee, Ming-Tsung; Vishnyakov, Aleksey; Neimark, Alexander V
2015-09-01
Using dissipative particle dynamics (DPD) simulations, we explore the specifics of micellization in the solutions of anionic and cationic surfactants and their mixtures. Anionic surfactant sodium dodecyl sulfate (SDS) and cationic surfactant cetyltrimethylammonium bromide (CTAB) are chosen as characteristic examples. Coarse-grained models of the surfactants are constructed and parameterized using a combination of atomistic molecular simulation and infinite dilution activity coefficient calibration. Electrostatic interactions of charged beads are treated using a smeared charge approximation: the surfactant heads and dissociated counterions are modeled as beads with charges distributed around the bead center in an implicit dielectric medium. The proposed models semiquantitatively describe self-assembly in solutions of SDS and CTAB at various surfactant concentrations and molarities of added electrolyte. In particular, the model predicts a decline in the free surfactant concentration with the increase of the total surfactant loading, as well as characteristic aggregation transitions in single-component surfactant solutions caused by the addition of salt. The calculated values of the critical micelle concentration reasonably agree with experimental observations. Modeling of catanionic SDS-CTAB mixtures show consecutive transitions to worm-like micelles and then to vesicles caused by the addition of CTAB to micellar solution of SDS. PMID:26241704
Modelling Chemical Reasoning to Predict Reactions
Segler, Marwin H S
2016-01-01
The ability to reason beyond established knowledge allows Organic Chemists to solve synthetic problems and to invent novel transformations. Here, we propose a model which mimics chemical reasoning and formalises reaction prediction as finding missing links in a knowledge graph. We have constructed a knowledge graph containing 14.4 million molecules and 8.2 million binary reactions, which represents the bulk of all chemical reactions ever published in the scientific literature. Our model outperforms a rule-based expert system in the reaction prediction task for 180,000 randomly selected binary reactions. We show that our data-driven model generalises even beyond known reaction types, and is thus capable of effectively (re-) discovering novel transformations (even including transition-metal catalysed reactions). Our model enables computers to infer hypotheses about reactivity and reactions by only considering the intrinsic local structure of the graph, and because each single reaction prediction is typically ac...
Energy based prediction models for building acoustics
DEFF Research Database (Denmark)
Brunskog, Jonas
2012-01-01
In order to reach robust and simplified yet accurate prediction models, energy based principle are commonly used in many fields of acoustics, especially in building acoustics. This includes simple energy flow models, the framework of statistical energy analysis (SEA) as well as more elaborated...... principles as, e.g., wave intensity analysis (WIA). The European standards for building acoustic predictions, the EN 12354 series, are based on energy flow and SEA principles. In the present paper, different energy based prediction models are discussed and critically reviewed. Special attention is placed...... on underlying basic assumptions, such as diffuse fields, high modal overlap, resonant field being dominant, etc., and the consequences of these in terms of limitations in the theory and in the practical use of the models....
Light charged Higgs boson scenario in 3-Higgs doublet models
Akeroyd, A G; Yagyu, Kei; Yildirim, Emine
2016-01-01
The constraints from the measurements of the $B\\to X_s\\gamma$ decay rate on the parameter space of 3-Higgs Doublet Models (3HDMs), where all the doublets have non-zero vacuum expectation values, are studied at the next-to-leading order in QCD. In order to naturally avoid the presence of flavour changing neutral currents at the tree level, we impose two softly-broken discrete $Z_2$ symmetries. This gives rise to five independent types of 3HDMs that differ in their Yukawa couplings. We show that in all these 3HDMs (including the case of type-II-like Yukawa interactions) both masses of the two charged Higgs bosons $m_{H_1^\\pm}$ and $m_{H_2^\\pm}$ can be smaller than the top mass $m_t$ while complying with the constraints from $B\\to X_s\\gamma$. As an interesting phenomenological consequence, the branching ratios of the charged Higgs bosons decay into the $cb$ final states can be as large as $80\\%$ when their masses are taken to be below $m_t$ in two of the five 3HDMs (named as Type-Y and Type-Z). This light charge...
Evaluation of CASP8 model quality predictions
Cozzetto, Domenico
2009-01-01
The model quality assessment problem consists in the a priori estimation of the overall and per-residue accuracy of protein structure predictions. Over the past years, a number of methods have been developed to address this issue and CASP established a prediction category to evaluate their performance in 2006. In 2008 the experiment was repeated and its results are reported here. Participants were invited to infer the correctness of the protein models submitted by the registered automatic servers. Estimates could apply to both whole models and individual amino acids. Groups involved in the tertiary structure prediction categories were also asked to assign local error estimates to each predicted residue in their own models and their results are also discussed here. The correlation between the predicted and observed correctness measures was the basis of the assessment of the results. We observe that consensus-based methods still perform significantly better than those accepting single models, similarly to what was concluded in the previous edition of the experiment. © 2009 WILEY-LISS, INC.
Genetic models of homosexuality: generating testable predictions
Gavrilets, Sergey; Rice, William R.
2006-01-01
Homosexuality is a common occurrence in humans and other species, yet its genetic and evolutionary basis is poorly understood. Here, we formulate and study a series of simple mathematical models for the purpose of predicting empirical patterns that can be used to determine the form of selection that leads to polymorphism of genes influencing homosexuality. Specifically, we develop theory to make contrasting predictions about the genetic characteristics of genes influencing homosexuality inclu...
Efficient particle continuation model predictive control
Knyazev, Andrew; Malyshev, Alexander,
2015-01-01
Continuation model predictive control (MPC), introduced by T. Ohtsuka in 2004, uses Krylov-Newton approaches to solve MPC optimization and is suitable for nonlinear and minimum time problems. We suggest particle continuation MPC in the case, where the system dynamics or constraints can discretely change on-line. We propose an algorithm for on-line controller implementation of continuation MPC for ensembles of predictions corresponding to various anticipated changes and demonstrate its numeric...
Models for Predictive Railway Traffic Management
Kecman, P.
2014-01-01
The potential growth in transport demand in the next decade and beyond requires a change from reactive to proactive traffic control to maintain and improve the reliability of railway traffic. In order to enable an anticipative approach to traffic management, it is necessary to develop the tools for monitoring, prediction and optimisation of the traffic operations. This thesis presents the models that can be used as components for a decision support system for predictive traffic management.
A High Precision Prediction Model Using Hybrid Grey Dynamic Model
Li, Guo-Dong; Yamaguchi, Daisuke; Nagai, Masatake; Masuda, Shiro
2008-01-01
In this paper, we propose a new prediction analysis model which combines the first order one variable Grey differential equation Model (abbreviated as GM(1,1) model) from grey system theory and time series Autoregressive Integrated Moving Average (ARIMA) model from statistics theory. We abbreviate the combined GM(1,1) ARIMA model as ARGM(1,1)…
Modeling of mesoscopic electrokinetic phenomena using charged dissipative particle dynamics
Deng, Mingge; Li, Zhen; Karniadakis, George
2015-11-01
In this work, we propose a charged dissipative particle dynamics (cDPD) model for investigation of mesoscopic electrokinetic phenomena. In particular, this particle-based method was designed to simulate micro- or nano- flows which governing by Poisson-Nernst-Planck (PNP) equation coupled with Navier-Stokes (NS) equation. For cDPD simulations of wall-bounded fluid systems, a methodology for imposing correct Dirichlet and Neumann boundary conditions for both PNP and NS equations is developed. To validate the present cDPD model and the corresponding boundary method, we perform cDPD simulations of electrostatic double layer (EDL) in the vicinity of a charged wall, and the results show good agreement with the mean-field theoretical solutions. The capacity density of a parallel plate capacitor in salt solution is also investigated with different salt concentration. Moreover, we utilize the proposed methodology to study the electroosmotic and electroosmotic/pressure-driven flow in a micro-channel. In the last, we simulate the dilute polyelectrolyte solution both in bulk and micro-channel, which show the flexibility and capability of this method in studying complex fluids. This work was sponsored by the Collaboratory on Mathematics for Mesoscopic Modeling of Materials (CM4) supported by DOE.
Models for Energy and Charge Transport, and Storage in Biomolecules
Mingaleev, S F; Gaididei, Yu B; Johansson, M; Rasmussen, K O; Mingaleev, Serge F.; Christiansen, Peter L.; Gaididei, Yuri B.; Johansson, Magnus; Rasmussen, Kim O.
1999-01-01
Two models for energy and charge transport and storage in biomolecules are considered. A model based on the discrete nonlinear Schrodinger equation with long-range dispersive interactions (LRI's) between base pairs of DNA is offered for the description of nonlinear dynamics of the DNA molecule. We show that LRI's are responsible for the existence of an interval of bistability where two stable stationary states, a narrow, pinned state and a broad, mobile state, coexist at each value of the total energy. The possibility of controlled switching between pinned and mobile states is demonstrated. The mechanism could be important for controlling energy storage and transport in DNA molecules. Another model is offered for the description of nonlinear excitations in proteins and other anharmonic biomolecules. We show that in the highly anharmonic systems a bound state of Davydov and Boussinesq solitons can exist.
Modelling of Charged anisotropic compact stars with EOS $\\rho=f(p)$
Maurya, S K
2016-01-01
Charged compact star models have been determined for anisotropic fluid distribution. We have solved the Einstein's- Maxwell field equations to construct the charged compact star models by using radial pressure, metric function $e^{\\lambda}$ and electric charge function. The generic charged anisotropic solution is verified by exploring different physical conditions like, causality condition, mass-radius relation and stability of the solution (via. adiabatic index, TOV equations and Herrera cracking concept). It is observed that the present charged anisotropic compact star is compatible with the star PSR 1937+21. However we also presented the EOS $\\rho=f(p)$ for present charged compact star model.
Xie, Dexuan; Volkmer, Hans W.; Ying, Jinyong
2016-04-01
The nonlocal dielectric approach has led to new models and solvers for predicting electrostatics of proteins (or other biomolecules), but how to validate and compare them remains a challenge. To promote such a study, in this paper, two typical nonlocal dielectric models are revisited. Their analytical solutions are then found in the expressions of simple series for a dielectric sphere containing any number of point charges. As a special case, the analytical solution of the corresponding Poisson dielectric model is also derived in simple series, which significantly improves the well known Kirkwood's double series expansion. Furthermore, a convolution of one nonlocal dielectric solution with a commonly used nonlocal kernel function is obtained, along with the reaction parts of these local and nonlocal solutions. To turn these new series solutions into a valuable research tool, they are programed as a free fortran software package, which can input point charge data directly from a protein data bank file. Consequently, different validation tests can be quickly done on different proteins. Finally, a test example for a protein with 488 atomic charges is reported to demonstrate the differences between the local and nonlocal models as well as the importance of using the reaction parts to develop local and nonlocal dielectric solvers.
PREDICTIVE CAPACITY OF ARCH FAMILY MODELS
Directory of Open Access Journals (Sweden)
Raphael Silveira Amaro
2016-03-01
Full Text Available In the last decades, a remarkable number of models, variants from the Autoregressive Conditional Heteroscedastic family, have been developed and empirically tested, making extremely complex the process of choosing a particular model. This research aim to compare the predictive capacity, using the Model Confidence Set procedure, than five conditional heteroskedasticity models, considering eight different statistical probability distributions. The financial series which were used refers to the log-return series of the Bovespa index and the Dow Jones Industrial Index in the period between 27 October 2008 and 30 December 2014. The empirical evidences showed that, in general, competing models have a great homogeneity to make predictions, either for a stock market of a developed country or for a stock market of a developing country. An equivalent result can be inferred for the statistical probability distributions that were used.
A Predictive Model for Root Caries Incidence.
Ritter, André V; Preisser, John S; Puranik, Chaitanya P; Chung, Yunro; Bader, James D; Shugars, Daniel A; Makhija, Sonia; Vollmer, William M
2016-01-01
This study aimed to find the set of risk indicators best able to predict root caries (RC) incidence in caries-active adults utilizing data from the Xylitol for Adult Caries Trial (X-ACT). Five logistic regression models were compared with respect to their predictive performance for incident RC using data from placebo-control participants with exposed root surfaces at baseline and from two study centers with ancillary data collection (n = 155). Prediction performance was assessed from baseline variables and after including ancillary variables [smoking, diet, use of removable partial dentures (RPD), toothbrush use, income, education, and dental insurance]. A sensitivity analysis added treatment to the models for both the control and treatment participants (n = 301) to predict RC for the control participants. Forty-nine percent of the control participants had incident RC. The model including the number of follow-up years at risk, the number of root surfaces at risk, RC index, gender, race, age, and smoking resulted in the best prediction performance, having the highest AUC and lowest Brier score. The sensitivity analysis supported the primary analysis and gave slightly better performance summary measures. The set of risk indicators best able to predict RC incidence included an increased number of root surfaces at risk and increased RC index at baseline, followed by white race and nonsmoking, which were strong nonsignificant predictors. Gender, age, and increased number of follow-up years at risk, while included in the model, were also not statistically significant. The inclusion of health, diet, RPD use, toothbrush use, income, education, and dental insurance variables did not improve the prediction performance. PMID:27160516
Predictive Models of Li-ion Battery Lifetime (Presentation)
Energy Technology Data Exchange (ETDEWEB)
Smith, K.; Wood, E.; Santhanagopalan, S.; Kim, G.; Shi, Y.; Pesaran, A.
2014-09-01
Predictive models of Li-ion battery reliability must consider a multiplicity of electrochemical, thermal and mechanical degradation modes experienced by batteries in application environments. Complicating matters, Li-ion batteries can experience several path dependent degradation trajectories dependent on storage and cycling history of the application environment. Rates of degradation are controlled by factors such as temperature history, electrochemical operating window, and charge/discharge rate. Lacking accurate models and tests, lifetime uncertainty must be absorbed by overdesign and warranty costs. Degradation models are needed that predict lifetime more accurately and with less test data. Models should also provide engineering feedback for next generation battery designs. This presentation reviews both multi-dimensional physical models and simpler, lumped surrogate models of battery electrochemical and mechanical degradation. Models are compared with cell- and pack-level aging data from commercial Li-ion chemistries. The analysis elucidates the relative importance of electrochemical and mechanical stress-induced degradation mechanisms in real-world operating environments. Opportunities for extending the lifetime of commercial battery systems are explored.
Nonlinear potential model of space-charge-limited electron beams
Energy Technology Data Exchange (ETDEWEB)
Litz, M.S. [Army Research Lab., Adelphi, MD (United States); Golden, J. [Berkeley Research Associates, Springfield, VA (United States)
1995-11-01
A one-dimensional (1D) time-varying nonlinear theory based on the Duffing equation is applied to space-charge limited beams and specifically vircators. This theory classifies test particle trajectories in a modulated nonlinear potential. Two predictions of the theory that can be directly compared to experiment are the final state of electron trajectories and the oscillation frequency of the electrons m the potential well. Experimental measurements of electron flux recorded along the vircator chamber wall correlates well with the numerically integrated final state of electron trajectory in the 1D theory. The oscillation frequency measured in the experiment is shown to be a better match to the oscillation frequency calculated from the nonlinear potential as compared to a parabolic potential (that results from a linear restoring force). In the experiment, random initial conditions arise from beam thermalization and nonuniform electron emission at the surface of the cathode. However, these characteristics alone do not explain the experimentally observed fluctuations in rf power and frequency. The predictions of the time-varying nonlinear potential theory clearly exhibits trends that were observed in the experimental results, in the form of classes of particle trajectories, fluctuations in particle asymptotic states, and particle motion sensitive to the shape of the virtual cathode.
A Massless-Point-Charge Model for the Electron
Directory of Open Access Journals (Sweden)
Daywitt W. C.
2010-04-01
Full Text Available "It is rather remarkable that the modern concept of electrodynamics is not quite 100 years old and yet still does not rest firmly upon uniformly accepted theoretical foundations. Maxwell's theory of the electromagnetic field is firmly ensconced in modern physics, to be sure, but the details of how charged particles are to be coupled to this field remain somewhat uncertain, despite the enormous advances in quantum electrodynamics over the past 45 years. Our theories remain mathematically ill-posed and mired in conceptual ambiguities which quantum mechanics has only moved to another arena rather than resolve. Fundamentally, we still do not understand just what is a charged particle" (Grandy W.T. Jr. Relativistic quantum mechanics of leptons and fields. Kluwer Academic Publishers, Dordrecht-London, 1991, p.367. As a partial answer to the preceeding quote, this paper presents a new model for the electron that combines the seminal work of Puthoff with the theory of the Planck vacuum (PV, the basic idea for the model following from Puthoff with the PV theory adding some important details.
Predictive coding as a model of cognition.
Spratling, M W
2016-08-01
Previous work has shown that predictive coding can provide a detailed explanation of a very wide range of low-level perceptual processes. It is also widely believed that predictive coding can account for high-level, cognitive, abilities. This article provides support for this view by showing that predictive coding can simulate phenomena such as categorisation, the influence of abstract knowledge on perception, recall and reasoning about conceptual knowledge, context-dependent behavioural control, and naive physics. The particular implementation of predictive coding used here (PC/BC-DIM) has previously been used to simulate low-level perceptual behaviour and the neural mechanisms that underlie them. This algorithm thus provides a single framework for modelling both perceptual and cognitive brain function. PMID:27118562
Modelling the predictive performance of credit scoring
Directory of Open Access Journals (Sweden)
Shi-Wei Shen
2013-02-01
Full Text Available Orientation: The article discussed the importance of rigour in credit risk assessment.Research purpose: The purpose of this empirical paper was to examine the predictive performance of credit scoring systems in Taiwan.Motivation for the study: Corporate lending remains a major business line for financial institutions. However, in light of the recent global financial crises, it has become extremely important for financial institutions to implement rigorous means of assessing clients seeking access to credit facilities.Research design, approach and method: Using a data sample of 10 349 observations drawn between 1992 and 2010, logistic regression models were utilised to examine the predictive performance of credit scoring systems.Main findings: A test of Goodness of fit demonstrated that credit scoring models that incorporated the Taiwan Corporate Credit Risk Index (TCRI, micro- and also macroeconomic variables possessed greater predictive power. This suggests that macroeconomic variables do have explanatory power for default credit risk.Practical/managerial implications: The originality in the study was that three models were developed to predict corporate firms’ defaults based on different microeconomic and macroeconomic factors such as the TCRI, asset growth rates, stock index and gross domestic product.Contribution/value-add: The study utilises different goodness of fits and receiver operator characteristics during the examination of the robustness of the predictive power of these factors.
Modeling the Hydrogen-Proton Charge-Exchange Process in Global Heliospheric Simulations
DeStefano, A.; Heerikhuisen, J.
2015-12-01
The environment surrounding our Solar System has a vast and dynamic structure. As the Sun rounds the Milky Way galaxy, interstellar dust and gas interact with the Sun's outflow of solar wind. A bubble of hot plasma forms around the Sun due to this interaction, called the heliosphere. In order to understand the structure of the heliosphere, observations and simulations must work in tandem. Within the past decade or so, 3D models of the heliosphere have been developed exhibiting non- symmmetric as well as predicting structures such as the hydrogen wall and the IBEX ribbon. In this poster we explore new ways to compute charge-exchange source terms. The charge-exchange process is the coupling mechanism between the MHD and kinetic theories. The understanding of this process is crucial in order to make valuable predictions. Energy dependant cross section terms will aid in settling non-linear affects coupling the intestellar and solar particles. Through these new ways of computing source terms, resolving fine structures in the plasma in the heliopause may be possible. In addition, other non-trivial situations, such as charge-exchange mediated shocks, may be addressed.
Global Solar Dynamo Models: Simulations and Predictions
Indian Academy of Sciences (India)
Mausumi Dikpati; Peter A. Gilman
2008-03-01
Flux-transport type solar dynamos have achieved considerable success in correctly simulating many solar cycle features, and are now being used for prediction of solar cycle timing and amplitude.We first define flux-transport dynamos and demonstrate how they work. The essential added ingredient in this class of models is meridional circulation, which governs the dynamo period and also plays a crucial role in determining the Sun’s memory about its past magnetic fields.We show that flux-transport dynamo models can explain many key features of solar cycles. Then we show that a predictive tool can be built from this class of dynamo that can be used to predict mean solar cycle features by assimilating magnetic field data from previous cycles.
Grey Model for Stream Flow Prediction
Directory of Open Access Journals (Sweden)
P. Syamala
2012-04-01
Full Text Available Design, operation and planning of water resources, irrigation and water supply systems require estimation of stream flow. A grey system or stochastic approach is required for dealing with the hydrological complexities of mid and long-term stream flow prediction. Generally relatively long period data series of stream flow records is required for the prediction using stochastic methods. In developing countries like India, availability of long period hydrological records is a problem. Grey system theory is applicable in the case of unclear innerrelationship, uncertain mechanisms and insufficient information and requires only small samples for parameter estimation. Stream flow records of Bharathapuzha river basin, Kerala, India is subjected to grey analysis. Model parameters were estimated using least-squares method. Statistical indices for the developed models indicate their ability to predict stream flow in the river under study with reasonable accuracy
An exponential filter model predicts lightness illusions
Directory of Open Access Journals (Sweden)
Astrid eZeman
2015-06-01
Full Text Available Lightness, or perceived reflectance of a surface, is influenced by surrounding context. This is demonstrated by the Simultaneous Contrast Illusion (SCI, where a grey patch is perceived lighter against a black background and vice versa. Conversely, assimilation is where the lightness of the target patch moves towards that of the bounding areas and can be demonstrated in White's effect. Blakeslee and McCourt (2007 introduced an oriented difference-of-Gaussian (ODOG model that is able to account for both contrast and assimilation in a number of lightness illusions and that has been subsequently improved using localized normalization techniques. We introduce a model inspired by image statistics that is based on a family of exponential filters, with kernels spanning across multiple sizes and shapes. We include an optional second stage of normalization based on contrast gain control. Our model was tested on a well-known set of lightness illusions that have previously been used to evaluate ODOG and its variants, and model lightness values were compared with typical human data. We investigate whether predictive success depends on filters of a particular size or shape and whether pooling information across filters can improve performance. The best single filter correctly predicted the direction of lightness effects for 21 out of 27 illusions. Combining two filters together increased the best performance to 23, with asymptotic performance at 24 for an arbitrarily large combination of filter outputs. While normalization improved prediction magnitudes, it only slightly improved overall scores in direction predictions. The prediction performance of 24 out of 27 illusions equals that of the best performing ODOG variant, with greater parsimony. Our model shows that V1-style orientation-selectivity is not necessary to account for lightness illusions and that a low-level model based on image statistics is able to account for a wide range of both contrast and
DKIST Polarization Modeling and Performance Predictions
Harrington, David
2016-05-01
Calibrating the Mueller matrices of large aperture telescopes and associated coude instrumentation requires astronomical sources and several modeling assumptions to predict the behavior of the system polarization with field of view, altitude, azimuth and wavelength. The Daniel K Inouye Solar Telescope (DKIST) polarimetric instrumentation requires very high accuracy calibration of a complex coude path with an off-axis f/2 primary mirror, time dependent optical configurations and substantial field of view. Polarization predictions across a diversity of optical configurations, tracking scenarios, slit geometries and vendor coating formulations are critical to both construction and contined operations efforts. Recent daytime sky based polarization calibrations of the 4m AEOS telescope and HiVIS spectropolarimeter on Haleakala have provided system Mueller matrices over full telescope articulation for a 15-reflection coude system. AEOS and HiVIS are a DKIST analog with a many-fold coude optical feed and similar mirror coatings creating 100% polarization cross-talk with altitude, azimuth and wavelength. Polarization modeling predictions using Zemax have successfully matched the altitude-azimuth-wavelength dependence on HiVIS with the few percent amplitude limitations of several instrument artifacts. Polarization predictions for coude beam paths depend greatly on modeling the angle-of-incidence dependences in powered optics and the mirror coating formulations. A 6 month HiVIS daytime sky calibration plan has been analyzed for accuracy under a wide range of sky conditions and data analysis algorithms. Predictions of polarimetric performance for the DKIST first-light instrumentation suite have been created under a range of configurations. These new modeling tools and polarization predictions have substantial impact for the design, fabrication and calibration process in the presence of manufacturing issues, science use-case requirements and ultimate system calibration
Model Predictive Control of Autonomous Vehicles
Zanon, Mario; Frasch, Janick V.; Vukov, Milan; Sager, Sebastian; Diehl, Moritz
2014-01-01
International audience The control of autonomous vehicles is a challenging task that requires advanced control schemes. Nonlinear Model Predictive Control (NMPC) and Moving Horizon Estimation (MHE) are optimization-based control and estimation techniques that are able to deal with highly nonlinear, constrained, unstable and fast dynamic systems. In this chapter, these techniques are detailed, a descriptive nonlinear model is derived and the performance of the proposed control scheme is dem...
Continuation model predictive control on smooth manifolds
Knyazev, Andrew; Malyshev, Alexander,
2015-01-01
Model predictive control (MPC) anticipates future events to take appropriate control actions. Nonlinear MPC (NMPC) describes systems with nonlinear models and/or constraints. Continuation MPC, suggested by T.~Ohtsuka in 2004, uses Krylov-Newton iterations. Continuation MPC is suitable for nonlinear problems and has been recently adopted for minimum time problems. We extend the continuation MPC approach to a case where the state is implicitly constrained to a smooth manifold. We propose an alg...
Preconditioning for continuation model predictive control
Knyazev, Andrew; Malyshev, Alexander,
2015-01-01
Model predictive control (MPC) anticipates future events to take appropriate control actions. Nonlinear MPC (NMPC) deals with nonlinear models and/or constraints. A Continuation/GMRES Method for NMPC, suggested by T. Ohtsuka in 2004, uses the GMRES iterative algorithm to solve a forward difference approximation $Ax=b$ of the original NMPC equations on every time step. We have previously proposed accelerating the GMRES and MINRES convergence by preconditioning the coefficient matrix $A$. We no...
Predictive Modeling of the CDRA 4BMS
Coker, Robert; Knox, James
2016-01-01
Fully predictive models of the Four Bed Molecular Sieve of the Carbon Dioxide Removal Assembly on the International Space Station are being developed. This virtual laboratory will be used to help reduce mass, power, and volume requirements for future missions. In this paper we describe current and planned modeling developments in the area of carbon dioxide removal to support future crewed Mars missions as well as the resolution of anomalies observed in the ISS CDRA.
Hierarchical Model Predictive Control for Resource Distribution
DEFF Research Database (Denmark)
Bendtsen, Jan Dimon; Trangbæk, K; Stoustrup, Jakob
2010-01-01
This paper deals with hierarchichal model predictive control (MPC) of distributed systems. A three level hierachical approach is proposed, consisting of a high level MPC controller, a second level of so-called aggregators, controlled by an online MPC-like algorithm, and a lower level of autonomous...
Predictability of extreme values in geophysical models
Sterk, A.E.; Holland, M.P.; Rabassa, P.; Broer, H.W.; Vitolo, R.
2012-01-01
Extreme value theory in deterministic systems is concerned with unlikely large (or small) values of an observable evaluated along evolutions of the system. In this paper we study the finite-time predictability of extreme values, such as convection, energy, and wind speeds, in three geophysical model
Predictive Modelling of Mycotoxins in Cereals
Fels, van der H.J.; Liu, C.
2015-01-01
In dit artikel worden de samenvattingen van de presentaties tijdens de 30e bijeenkomst van de Werkgroep Fusarium weergegeven. De onderwerpen zijn: Predictive Modelling of Mycotoxins in Cereals.; Microbial degradation of DON.; Exposure to green leaf volatiles primes wheat against FHB but boosts produ
MODELING CHARGE RELAXATION ON SURFACES OF PARTICLES SUSPENDED IN LIQUID
Institute of Scientific and Technical Information of China (English)
Guoqing Gu; Kin Wah Yu
2005-01-01
A general theory on charges relaxation process in particle-fluid systems is introduced in this article. The method to derive analytical solutions for the charge relaxation equation is illustrated, and some respects for this theory are discussed in detail.
Specialized Language Models using Dialogue Predictions
Popovici, C; Popovici, Cosmin; Baggia, Paolo
1996-01-01
This paper analyses language modeling in spoken dialogue systems for accessing a database. The use of several language models obtained by exploiting dialogue predictions gives better results than the use of a single model for the whole dialogue interaction. For this reason several models have been created, each one for a specific system question, such as the request or the confirmation of a parameter. The use of dialogue-dependent language models increases the performance both at the recognition and at the understanding level, especially on answers to system requests. Moreover other methods to increase performance, like automatic clustering of vocabulary words or the use of better acoustic models during recognition, does not affect the improvements given by dialogue-dependent language models. The system used in our experiments is Dialogos, the Italian spoken dialogue system used for accessing railway timetable information over the telephone. The experiments were carried out on a large corpus of dialogues coll...
Kumar, Vijesh; Leweke, Samuel; von Lieres, Eric; Rathore, Anurag S
2015-12-24
Ion-exchange chromatography (IEX) is universally accepted as the optimal method for achieving process scale separation of charge variants of a monoclonal antibody (mAb) therapeutic. These variants are closely related to the product and a baseline separation is rarely achieved. The general practice is to fractionate the eluate from the IEX column, analyze the fractions and then pool the desired fractions to obtain the targeted composition of variants. This is, however, a very cumbersome and time consuming exercise. A mechanistic model that is capable of simulating the peak profile will be a much more elegant and effective way to make a decision on the pooling strategy. This paper proposes a mechanistic model, based on the general rate model, to predict elution peak profile for separation of the main product from its variants. The proposed approach uses inverse fit of process scale chromatogram for estimation of model parameters using the initial values that are obtained from theoretical correlations. The packed bed column has been modeled along with the chromatographic system consisting of the mixer, tubing and detectors as a series of dispersed plug flow and continuous stirred tank reactors. The model uses loading ranges starting at 25% to a maximum of 70% of the loading capacity and hence is applicable to process scale separations. Langmuir model has been extended to include the effects of salt concentration and temperature on the model parameters. The extended Langmuir model that has been proposed uses one less parameter than the SMA model and this results in a significant ease of estimating the model parameters from inverse fitting. The proposed model has been validated with experimental data and has been shown to successfully predict peak profile for a range of load capacities (15-28mg/mL), gradient lengths (10-30CV), bed heights (6-20cm), and for three different resins with good accuracy (as measured by estimation of residuals). The model has been also
Disease prediction models and operational readiness.
Directory of Open Access Journals (Sweden)
Courtney D Corley
Full Text Available The objective of this manuscript is to present a systematic review of biosurveillance models that operate on select agents and can forecast the occurrence of a disease event. We define a disease event to be a biological event with focus on the One Health paradigm. These events are characterized by evidence of infection and or disease condition. We reviewed models that attempted to predict a disease event, not merely its transmission dynamics and we considered models involving pathogens of concern as determined by the US National Select Agent Registry (as of June 2011. We searched commercial and government databases and harvested Google search results for eligible models, using terms and phrases provided by public health analysts relating to biosurveillance, remote sensing, risk assessments, spatial epidemiology, and ecological niche modeling. After removal of duplications and extraneous material, a core collection of 6,524 items was established, and these publications along with their abstracts are presented in a semantic wiki at http://BioCat.pnnl.gov. As a result, we systematically reviewed 44 papers, and the results are presented in this analysis. We identified 44 models, classified as one or more of the following: event prediction (4, spatial (26, ecological niche (28, diagnostic or clinical (6, spread or response (9, and reviews (3. The model parameters (e.g., etiology, climatic, spatial, cultural and data sources (e.g., remote sensing, non-governmental organizations, expert opinion, epidemiological were recorded and reviewed. A component of this review is the identification of verification and validation (V&V methods applied to each model, if any V&V method was reported. All models were classified as either having undergone Some Verification or Validation method, or No Verification or Validation. We close by outlining an initial set of operational readiness level guidelines for disease prediction models based upon established Technology
Theoretical Prediction of Isotope Effects on Charge Transport in Organic Semiconductors.
Jiang, Yuqian; Geng, Hua; Shi, Wen; Peng, Qian; Zheng, Xiaoyan; Shuai, Zhigang
2014-07-01
We suggest that the nuclear tunneling effect is important in organic semiconductors, which we showed is absent in both the widely employed Marcus theory and the band-like transport as described by the deformation potential theory. Because the quantum nuclear tunneling tends to favor electron transfer while heavier nuclei decrease the quantum effect, there should occur an isotope effect for carrier mobility. For N,N'-n-bis(n-hexyl)-naphthalene diimide, electron mobility of all-deuteration on alkyls and all (13)C-substitution on the backbone decrease ∼18 and 7%, respectively. Similar isotope effects are found in the N,N'-n-bis(n-octyl)-perylene diimide. However, there is nearly no isotope effect for all-deuterated rubrene or tetracene. We have found that the isotopic effect only occurs when the substituted nuclei contribute actively to vibrations with appreciable charge reorganization energy and coupling with carrier motion. Thus, this prediction can shed light on the current dispute over the hopping versus band-like mechanisms in organic semiconductors. PMID:26279545
Electrostatic ion thrusters - towards predictive modeling
Energy Technology Data Exchange (ETDEWEB)
Kalentev, O.; Matyash, K.; Duras, J.; Lueskow, K.F.; Schneider, R. [Ernst-Moritz-Arndt Universitaet Greifswald, D-17489 (Germany); Koch, N. [Technische Hochschule Nuernberg Georg Simon Ohm, Kesslerplatz 12, D-90489 Nuernberg (Germany); Schirra, M. [Thales Electronic Systems GmbH, Soeflinger Strasse 100, D-89077 Ulm (Germany)
2014-02-15
The development of electrostatic ion thrusters so far has mainly been based on empirical and qualitative know-how, and on evolutionary iteration steps. This resulted in considerable effort regarding prototype design, construction and testing and therefore in significant development and qualification costs and high time demands. For future developments it is anticipated to implement simulation tools which allow for quantitative prediction of ion thruster performance, long-term behavior and space craft interaction prior to hardware design and construction. Based on integrated numerical models combining self-consistent kinetic plasma models with plasma-wall interaction modules a new quality in the description of electrostatic thrusters can be reached. These open the perspective for predictive modeling in this field. This paper reviews the application of a set of predictive numerical modeling tools on an ion thruster model of the HEMP-T (High Efficiency Multi-stage Plasma Thruster) type patented by Thales Electron Devices GmbH. (copyright 2014 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim) (orig.)
Genetic models of homosexuality: generating testable predictions.
Gavrilets, Sergey; Rice, William R
2006-12-22
Homosexuality is a common occurrence in humans and other species, yet its genetic and evolutionary basis is poorly understood. Here, we formulate and study a series of simple mathematical models for the purpose of predicting empirical patterns that can be used to determine the form of selection that leads to polymorphism of genes influencing homosexuality. Specifically, we develop theory to make contrasting predictions about the genetic characteristics of genes influencing homosexuality including: (i) chromosomal location, (ii) dominance among segregating alleles and (iii) effect sizes that distinguish between the two major models for their polymorphism: the overdominance and sexual antagonism models. We conclude that the measurement of the genetic characteristics of quantitative trait loci (QTLs) found in genomic screens for genes influencing homosexuality can be highly informative in resolving the form of natural selection maintaining their polymorphism.
ENSO Prediction using Vector Autoregressive Models
Chapman, D. R.; Cane, M. A.; Henderson, N.; Lee, D.; Chen, C.
2013-12-01
A recent comparison (Barnston et al, 2012 BAMS) shows the ENSO forecasting skill of dynamical models now exceeds that of statistical models, but the best statistical models are comparable to all but the very best dynamical models. In this comparison the leading statistical model is the one based on the Empirical Model Reduction (EMR) method. Here we report on experiments with multilevel Vector Autoregressive models using only sea surface temperatures (SSTs) as predictors. VAR(L) models generalizes Linear Inverse Models (LIM), which are a VAR(1) method, as well as multilevel univariate autoregressive models. Optimal forecast skill is achieved using 12 to 14 months of prior state information (i.e 12-14 levels), which allows SSTs alone to capture the effects of other variables such as heat content as well as seasonality. The use of multiple levels allows the model advancing one month at a time to perform at least as well for a 6 month forecast as a model constructed to explicitly forecast 6 months ahead. We infer that the multilevel model has fully captured the linear dynamics (cf. Penland and Magorian, 1993 J. Climate). Finally, while VAR(L) is equivalent to L-level EMR, we show in a 150 year cross validated assessment that we can increase forecast skill by improving on the EMR initialization procedure. The greatest benefit of this change is in allowing the prediction to make effective use of information over many more months.
Model Predictive Control based on Finite Impulse Response Models
DEFF Research Database (Denmark)
Prasath, Guru; Jørgensen, John Bagterp
2008-01-01
We develop a regularized l2 finite impulse response (FIR) predictive controller with input and input-rate constraints. Feedback is based on a simple constant output disturbance filter. The performance of the predictive controller in the face of plant-model mismatch is investigated by simulations ...
Phenomenological models of elastic nucleon scattering and predictions for LHC
Kundrat, V; Lokajicek, M; Prochazka, J
2011-01-01
The hitherto analyses of elastic collisions of charged nucleons involving common influence of Coulomb and hadronic scattering have been based practically on West and Yennie formula. However, this approach has been shown recently to be inadequate from experimental as well as theoretical points of view. The eikonal model enabling to determine physical characteristics in impact parameter space seems to be more pertinent. The contemporary phenomenological models admit, of course, different distributions of collision processes in the impact parameter space and cannot give any definite answer. Nevertheless, some predictions for the planned LHC energy that have been given on their basis may be useful, as well as the possibility of determining the luminosity from elastic scattering. (C) 2010 Elsevier B.V. All rights reserved.
NONLINEAR MODEL PREDICTIVE CONTROL OF CHEMICAL PROCESSES
Directory of Open Access Journals (Sweden)
SILVA R. G.
1999-01-01
Full Text Available A new algorithm for model predictive control is presented. The algorithm utilizes a simultaneous solution and optimization strategy to solve the model's differential equations. The equations are discretized by equidistant collocation, and along with the algebraic model equations are included as constraints in a nonlinear programming (NLP problem. This algorithm is compared with the algorithm that uses orthogonal collocation on finite elements. The equidistant collocation algorithm results in simpler equations, providing a decrease in computation time for the control moves. Simulation results are presented and show a satisfactory performance of this algorithm.
Charged Lepton Flavor-violating Transitions in Color Octet Model
Li, Bin; Ma, Xiao-Dong
2016-01-01
We study charged lepton flavor-violating (LFV) transitions in the color octet model that generates neutrino mass and lepton mixing at one loop. By taking into account neutrino oscillation data and assuming octet particles of TeV scale mass, we examine the feasibility to detect these transitions in current and future experiments. We find that for general values of parameters the branching ratios for LFV decays of the Higgs and $Z$ bosons are far below current and even future experimental bounds. For LFV transitions of the muon, the present bounds can be satisfied generally, while future sensitivities could distinguish between the singlet and triplet color-octet fermions. The triplet case could be ruled out by future $\\mu-e$ conversion in nuclei, and for the singlet case the conversion and the decays $\\mu\\to 3e,~e\\gamma$ play complementary roles in excluding relatively low mass regions of the octet particles.
Predictive modeling of nanomaterial exposure effects in biological systems
Directory of Open Access Journals (Sweden)
Liu X
2013-09-01
Full Text Available Xiong Liu,1 Kaizhi Tang,1 Stacey Harper,2 Bryan Harper,2 Jeffery A Steevens,3 Roger Xu1 1Intelligent Automation, Inc., Rockville, MD, USA; 2Department of Environmental and Molecular Toxicology, School of Chemical, Biological, and Environmental Engineering, Oregon State University, Corvallis, OR, USA; 3ERDC Environmental Laboratory, Vicksburg, MS, USA Background: Predictive modeling of the biological effects of nanomaterials is critical for industry and policymakers to assess the potential hazards resulting from the application of engineered nanomaterials. Methods: We generated an experimental dataset on the toxic effects experienced by embryonic zebrafish due to exposure to nanomaterials. Several nanomaterials were studied, such as metal nanoparticles, dendrimer, metal oxide, and polymeric materials. The embryonic zebrafish metric (EZ Metric was used as a screening-level measurement representative of adverse effects. Using the dataset, we developed a data mining approach to model the toxic endpoints and the overall biological impact of nanomaterials. Data mining techniques, such as numerical prediction, can assist analysts in developing risk assessment models for nanomaterials. Results: We found several important attributes that contribute to the 24 hours post-fertilization (hpf mortality, such as dosage concentration, shell composition, and surface charge. These findings concur with previous studies on nanomaterial toxicity using embryonic zebrafish. We conducted case studies on modeling the overall effect/impact of nanomaterials and the specific toxic endpoints such as mortality, delayed development, and morphological malformations. The results show that we can achieve high prediction accuracy for certain biological effects, such as 24 hpf mortality, 120 hpf mortality, and 120 hpf heart malformation. The results also show that the weighting scheme for individual biological effects has a significant influence on modeling the overall impact of
Performance model to predict overall defect density
Directory of Open Access Journals (Sweden)
J Venkatesh
2012-08-01
Full Text Available Management by metrics is the expectation from the IT service providers to stay as a differentiator. Given a project, the associated parameters and dynamics, the behaviour and outcome need to be predicted. There is lot of focus on the end state and in minimizing defect leakage as much as possible. In most of the cases, the actions taken are re-active. It is too late in the life cycle. Root cause analysis and corrective actions can be implemented only to the benefit of the next project. The focus has to shift left, towards the execution phase than waiting for lessons to be learnt post the implementation. How do we pro-actively predict defect metrics and have a preventive action plan in place. This paper illustrates the process performance model to predict overall defect density based on data from projects in an organization.
Critical parameters of unrestricted primitive model electrolytes with charge asymmetries up to 10:1
Cheong, Daniel W.; Panagiotopoulos, Athanassios Z.
2003-10-01
The phase behavior of charge- and size-asymmetric primitive model electrolytes has been investigated using reservoir grand canonical Monte Carlo simulations. The simulations rely on the insertion and removal of neutral ion clusters from a reservoir of possible configurations. We first validated our approach by investigating the effect of Rc, the maximum allowable distance between the central cation and its associated anions, on the critical parameters of 2:1 and 3:1 electrolytes. We have shown that the effect of Rc is weak and does not change the qualitative dependence of the critical parameters on size and charge asymmetry. The critical temperature for 2:1 and 3:1 electrolytes shows a maximum at Rc≈3, while the critical volume fraction decreases more or less monotonically, consistent with previous results for 1:1 electrolytes by Romero-Enrique et al. [Phys. Rev. E 66, 041204 (2002)]. We have used the reservoir method to obtain the critical parameters for 5:1 and 10:1 electrolytes. The critical temperature decreases with increasing charge asymmetry and shows a maximum as a function of δ, the size asymmetry parameter. The critical volume fraction however, defined as the volume occupied by ions divided by the total volume of the simulation box, increases with increasing charge asymmetry and exhibits a minimum as a function of δ. This trend is contrary to what is generally predicted by theories, although more recent approaches based on the Debye-Hückel theory reproduce this observed trend. Our results deviate somewhat from the predictions of Linse [Philos. Trans. R. Soc. London, Ser. A 359, 853 (2001)] for the scaling of the critical temperature for a system of macroions with point counterions.
Neuro-fuzzy modeling in bankruptcy prediction
Directory of Open Access Journals (Sweden)
Vlachos D.
2003-01-01
Full Text Available For the past 30 years the problem of bankruptcy prediction had been thoroughly studied. From the paper of Altman in 1968 to the recent papers in the '90s, the progress of prediction accuracy was not satisfactory. This paper investigates an alternative modeling of the system (firm, combining neural networks and fuzzy controllers, i.e. using neuro-fuzzy models. Classical modeling is based on mathematical models that describe the behavior of the firm under consideration. The main idea of fuzzy control, on the other hand, is to build a model of a human control expert who is capable of controlling the process without thinking in a mathematical model. This control expert specifies his control action in the form of linguistic rules. These control rules are translated into the framework of fuzzy set theory providing a calculus, which can stimulate the behavior of the control expert and enhance its performance. The accuracy of the model is studied using datasets from previous research papers.
Modeling the Flux-Charge Relation of Memristor with Neural Network of Smooth Hinge Functions
Directory of Open Access Journals (Sweden)
X. Mu
2014-09-01
Full Text Available The memristor was proposed to characterize the flux-charge relation. We propose the generalized flux-charge relation model of memristor with neural network of smooth hinge functions. There is effective identification algorithm for the neural network of smooth hinge functions. The representation capability of this model is theoretically guaranteed. Any functional flux-charge relation of a memristor can be approximated by the model. We also give application examples to show that the given model can approximate the flux-charge relation of existing piecewise linear memristor model, window function memristor model, and a physical memristor device.
Modeling the Flux-Charge Relation of Memristor with Neural Network of Smooth Hinge Functions
X. Mu; Yu, J.; Wang, S.
2014-01-01
The memristor was proposed to characterize the flux-charge relation. We propose the generalized flux-charge relation model of memristor with neural network of smooth hinge functions. There is effective identification algorithm for the neural network of smooth hinge functions. The representation capability of this model is theoretically guaranteed. Any functional flux-charge relation of a memristor can be approximated by the model. We also give application examples to show that the given model...
Seasonal Predictability in a Model Atmosphere.
Lin, Hai
2001-07-01
The predictability of atmospheric mean-seasonal conditions in the absence of externally varying forcing is examined. A perfect-model approach is adopted, in which a global T21 three-level quasigeostrophic atmospheric model is integrated over 21 000 days to obtain a reference atmospheric orbit. The model is driven by a time-independent forcing, so that the only source of time variability is the internal dynamics. The forcing is set to perpetual winter conditions in the Northern Hemisphere (NH) and perpetual summer in the Southern Hemisphere.A significant temporal variability in the NH 90-day mean states is observed. The component of that variability associated with the higher-frequency motions, or climate noise, is estimated using a method developed by Madden. In the polar region, and to a lesser extent in the midlatitudes, the temporal variance of the winter means is significantly greater than the climate noise, suggesting some potential predictability in those regions.Forecast experiments are performed to see whether the presence of variance in the 90-day mean states that is in excess of the climate noise leads to some skill in the prediction of these states. Ensemble forecast experiments with nine members starting from slightly different initial conditions are performed for 200 different 90-day means along the reference atmospheric orbit. The serial correlation between the ensemble means and the reference orbit shows that there is skill in the 90-day mean predictions. The skill is concentrated in those regions of the NH that have the largest variance in excess of the climate noise. An EOF analysis shows that nearly all the predictive skill in the seasonal means is associated with one mode of variability with a strong axisymmetric component.
Optical resonances in electrically charged particles and their relation to the Drude model
Kocifaj, Miroslav; Kundracik, František; Videen, Gorden; Yuffa, Alex J.; Klačka, Jozef
2016-07-01
The Drude model is conventionally used to explain the average motion of electrons in typical material. In this paper, we analyze the individual terms of the Drude model in order to uncover their influence on the scattering properties of small particles. Namely, a query on whether resonance enhancement is due to optical effects or the conductivity model. This query arose from our earlier theoretical and numerical experiments and still remains unresolved today. We show that certain resonance features are caused primarily by the interaction of the electromagnetic wave with the excess electric charge on the particles. Furthermore, we show that the role of a conductivity model is limited to only establishing the relative importance of the inertial moment of the carriers and the viscous drag forces. For frequencies ω ≤kB T / ℏ , the viscous forces only cause minor damping effects and the change in the peak resonance (along with its amplitude) are caused by the electric and inertial forces. These forces dominate because the viscous forces quickly decay with decreasing temperature. In order to demonstrate the optical behavior of charged water droplets, we construct a Mie-series solution with modified boundary conditions that properly account for the excess electric charge on the droplets. Our solution explains the weak scattering enhancement for frequencies far beyond the resonance, and it also predicts an absorption resonance edge in the long-wavelength limit. Our findings are not only useful to theoreticians who focus on the individual parameters such as the viscous term in the Drude model and/or search for better surface conductivity models, but also to experimentalists who gather as much data as possible in order to ascertain how the numerically determined optical properties compare with the experimental measurements.
Committee neural network model for rock permeability prediction
Bagheripour, Parisa
2014-05-01
Quantitative formulation between conventional well log data and rock permeability, undoubtedly the most critical parameter of hydrocarbon reservoir, could be a potent tool for solving problems associated with almost all tasks involved in petroleum engineering. The present study proposes a novel approach in charge of the quest for high-accuracy method of permeability prediction. At the first stage, overlapping of conventional well log data (inputs) was eliminated by means of principal component analysis (PCA). Subsequently, rock permeability was predicted from extracted PCs using multi-layer perceptron (MLP), radial basis function (RBF), and generalized regression neural network (GRNN). Eventually, a committee neural network (CNN) was constructed by virtue of genetic algorithm (GA) to enhance the precision of ultimate permeability prediction. The values of rock permeability, derived from the MPL, RBF, and GRNN models, were used as inputs of CNN. The proposed CNN combines results of different ANNs to reap beneficial advantages of all models and consequently producing more accurate estimations. The GA, embedded in the structure of the CNN assigns a weight factor to each ANN which shows relative involvement of each ANN in overall prediction of rock permeability from PCs of conventional well logs. The proposed methodology was applied in Kangan and Dalan Formations, which are the major carbonate reservoir rocks of South Pars Gas Field-Iran. A group of 350 data points was used to establish the CNN model, and a group of 245 data points was employed to assess the reliability of constructed CNN model. Results showed that the CNN method performed better than individual intelligent systems performing alone.
A kinetic model for predicting biodegradation.
Dimitrov, S; Pavlov, T; Nedelcheva, D; Reuschenbach, P; Silvani, M; Bias, R; Comber, M; Low, L; Lee, C; Parkerton, T; Mekenyan, O
2007-01-01
Biodegradation plays a key role in the environmental risk assessment of organic chemicals. The need to assess biodegradability of a chemical for regulatory purposes supports the development of a model for predicting the extent of biodegradation at different time frames, in particular the extent of ultimate biodegradation within a '10 day window' criterion as well as estimating biodegradation half-lives. Conceptually this implies expressing the rate of catabolic transformations as a function of time. An attempt to correlate the kinetics of biodegradation with molecular structure of chemicals is presented. A simplified biodegradation kinetic model was formulated by combining the probabilistic approach of the original formulation of the CATABOL model with the assumption of first order kinetics of catabolic transformations. Nonlinear regression analysis was used to fit the model parameters to OECD 301F biodegradation kinetic data for a set of 208 chemicals. The new model allows the prediction of biodegradation multi-pathways, primary and ultimate half-lives and simulation of related kinetic biodegradation parameters such as biological oxygen demand (BOD), carbon dioxide production, and the nature and amount of metabolites as a function of time. The model may also be used for evaluating the OECD ready biodegradability potential of a chemical within the '10-day window' criterion.
The Weak Charge of the Proton. A Search For Physics Beyond the Standard Model
International Nuclear Information System (INIS)
The Qweak experiment, which completed running in May of 2012 at Jefferson Laboratory, has measured the parity-violating asymmetry in elastic electron-proton scattering at four-momentum transfer Q2 =0.025 (GeV/c)2 in order to provide the first direct measurement of the proton's weak charge, QW^{p}. The Standard Model makes firm predictions for the weak charge; deviations from the predicted value would provide strong evidence of new physics beyond the Standard Model. Using an 89% polarized electron beam at 145 microA scattering from a 34.4 cm long liquid hydrogen target, scattered electrons were detected using an array of eight fused-silica detectors placed symmetric about the beam axis. The parity-violating asymmetry was then measured by reversing the helicity of the incoming electrons and measuring the normalized difference in rate seen in the detectors. The low Q2 enables a theoretically clean measurement; the higher-order hadronic corrections are constrained using previous parity-violating electron scattering world data. The experimental method will be discussed, with recent results constituting 4% of our total data and projections of our proposed uncertainties on the full data set.
The Weak Charge of the Proton. A Search For Physics Beyond the Standard Model
Energy Technology Data Exchange (ETDEWEB)
MacEwan, Scott J. [Univ. of Manitoba, Winnipeg, MB (Canada)
2015-05-01
The Q_{weak} experiment, which completed running in May of 2012 at Jefferson Laboratory, has measured the parity-violating asymmetry in elastic electron-proton scattering at four-momentum transfer Q^{2} =0.025 (GeV/c)^{2} in order to provide the first direct measurement of the proton's weak charge, Q_{W}^{p}. The Standard Model makes firm predictions for the weak charge; deviations from the predicted value would provide strong evidence of new physics beyond the Standard Model. Using an 89% polarized electron beam at 145 microA scattering from a 34.4 cm long liquid hydrogen target, scattered electrons were detected using an array of eight fused-silica detectors placed symmetric about the beam axis. The parity-violating asymmetry was then measured by reversing the helicity of the incoming electrons and measuring the normalized difference in rate seen in the detectors. The low Q^{2} enables a theoretically clean measurement; the higher-order hadronic corrections are constrained using previous parity-violating electron scattering world data. The experimental method will be discussed, with recent results constituting 4% of our total data and projections of our proposed uncertainties on the full data set.
Disease Prediction Models and Operational Readiness
Energy Technology Data Exchange (ETDEWEB)
Corley, Courtney D.; Pullum, Laura L.; Hartley, David M.; Benedum, Corey M.; Noonan, Christine F.; Rabinowitz, Peter M.; Lancaster, Mary J.
2014-03-19
INTRODUCTION: The objective of this manuscript is to present a systematic review of biosurveillance models that operate on select agents and can forecast the occurrence of a disease event. One of the primary goals of this research was to characterize the viability of biosurveillance models to provide operationally relevant information for decision makers to identify areas for future research. Two critical characteristics differentiate this work from other infectious disease modeling reviews. First, we reviewed models that attempted to predict the disease event, not merely its transmission dynamics. Second, we considered models involving pathogens of concern as determined by the US National Select Agent Registry (as of June 2011). Methods: We searched dozens of commercial and government databases and harvested Google search results for eligible models utilizing terms and phrases provided by public health analysts relating to biosurveillance, remote sensing, risk assessments, spatial epidemiology, and ecological niche-modeling, The publication date of search results returned are bound by the dates of coverage of each database and the date in which the search was performed, however all searching was completed by December 31, 2010. This returned 13,767 webpages and 12,152 citations. After de-duplication and removal of extraneous material, a core collection of 6,503 items was established and these publications along with their abstracts are presented in a semantic wiki at http://BioCat.pnnl.gov. Next, PNNL’s IN-SPIRE visual analytics software was used to cross-correlate these publications with the definition for a biosurveillance model resulting in the selection of 54 documents that matched the criteria resulting Ten of these documents, However, dealt purely with disease spread models, inactivation of bacteria, or the modeling of human immune system responses to pathogens rather than predicting disease events. As a result, we systematically reviewed 44 papers and the
Nonlinear model predictive control using automatic differentiation
Al Seyab, Rihab Khalid Shakir
2006-01-01
Although nonlinear model predictive control (NMPC) might be the best choice for a nonlinear plant, it is still not widely used. This is mainly due to the computational burden associated with solving online a set of nonlinear differential equations and a nonlinear dynamic optimization problem in real time. This thesis is concerned with strategies aimed at reducing the computational burden involved in different stages of the NMPC such as optimization problem, state estimation, an...
Microscopic modeling of charge transport in sensing proteins
Reggiani, Lino; Millithaler, Jean-Francois; Pennetta, Cecilia
2012-06-01
electrical change of the receptor when passing from the native to the active state is used to interpret the macroscopic measurement obtained within different methods. The developed INPA model is found to be very promising for a better understanding of the role of receptor topology in the mechanism responsible of charge transfer. Present results point favorably to the development of a new generation of nano-biosensors within the lab-on-chip strategy.
Model Predictive Control of Hybrid Thermal Energy Systems in Transport Refrigeration
DEFF Research Database (Denmark)
Shafiei, Seyed Ehsan; Alleyne, Andrew
2015-01-01
and future estimate of the vehicle driving state and load prediction. This assumes vehicle communications are aware of the traffic state along the prescribed delivery route. For the test case under consideration, this paper first shows that a 17% savings in energy use is achieved for charging the TES......A predictive control scheme is designed to control a transport refrigeration system, such as a delivery truck, that includes a vapor compression cycle configured in parallel with a thermal energy storage (TES) unit. A novel approach to TES utilization is introduced and is based on the current...... by simply shifting the charging to the time when vehicle is moving above a threshold speed. Subsequently, a cascade control structure is proposed consisting of (i) an outer loop controller that schedules the TES charging profile using a receding horizon optimization, and (ii) an inner loop model predictive...
Probabilistic prediction models for aggregate quarry siting
Robinson, G.R.; Larkins, P.M.
2007-01-01
Weights-of-evidence (WofE) and logistic regression techniques were used in a GIS framework to predict the spatial likelihood (prospectivity) of crushed-stone aggregate quarry development. The joint conditional probability models, based on geology, transportation network, and population density variables, were defined using quarry location and time of development data for the New England States, North Carolina, and South Carolina, USA. The Quarry Operation models describe the distribution of active aggregate quarries, independent of the date of opening. The New Quarry models describe the distribution of aggregate quarries when they open. Because of the small number of new quarries developed in the study areas during the last decade, independent New Quarry models have low parameter estimate reliability. The performance of parameter estimates derived for Quarry Operation models, defined by a larger number of active quarries in the study areas, were tested and evaluated to predict the spatial likelihood of new quarry development. Population density conditions at the time of new quarry development were used to modify the population density variable in the Quarry Operation models to apply to new quarry development sites. The Quarry Operation parameters derived for the New England study area, Carolina study area, and the combined New England and Carolina study areas were all similar in magnitude and relative strength. The Quarry Operation model parameters, using the modified population density variables, were found to be a good predictor of new quarry locations. Both the aggregate industry and the land management community can use the model approach to target areas for more detailed site evaluation for quarry location. The models can be revised easily to reflect actual or anticipated changes in transportation and population features. ?? International Association for Mathematical Geology 2007.
Nonconvex Model Predictive Control for Commercial Refrigeration
DEFF Research Database (Denmark)
Hovgaard, Tobias Gybel; Larsen, Lars F.S.; Jørgensen, John Bagterp;
2013-01-01
the iterations, which is more than fast enough to run in real-time. We demonstrate our method on a realistic model, with a full year simulation and 15 minute time periods, using historical electricity prices and weather data, as well as random variations in thermal load. These simulations show substantial cost...... is to minimize the total energy cost, using real-time electricity prices, while obeying temperature constraints on the zones. We propose a variation on model predictive control to achieve this goal. When the right variables are used, the dynamics of the system are linear, and the constraints are convex. The cost...
Predictive Modeling of the CDRA 4BMS
Coker, Robert F.; Knox, James C.
2016-01-01
As part of NASA's Advanced Exploration Systems (AES) program and the Life Support Systems Project (LSSP), fully predictive models of the Four Bed Molecular Sieve (4BMS) of the Carbon Dioxide Removal Assembly (CDRA) on the International Space Station (ISS) are being developed. This virtual laboratory will be used to help reduce mass, power, and volume requirements for future missions. In this paper we describe current and planned modeling developments in the area of carbon dioxide removal to support future crewed Mars missions as well as the resolution of anomalies observed in the ISS CDRA.
Predictive In Vivo Models for Oncology.
Behrens, Diana; Rolff, Jana; Hoffmann, Jens
2016-01-01
Experimental oncology research and preclinical drug development both substantially require specific, clinically relevant in vitro and in vivo tumor models. The increasing knowledge about the heterogeneity of cancer requested a substantial restructuring of the test systems for the different stages of development. To be able to cope with the complexity of the disease, larger panels of patient-derived tumor models have to be implemented and extensively characterized. Together with individual genetically engineered tumor models and supported by core functions for expression profiling and data analysis, an integrated discovery process has been generated for predictive and personalized drug development.Improved “humanized” mouse models should help to overcome current limitations given by xenogeneic barrier between humans and mice. Establishment of a functional human immune system and a corresponding human microenvironment in laboratory animals will strongly support further research.Drug discovery, systems biology, and translational research are moving closer together to address all the new hallmarks of cancer, increase the success rate of drug development, and increase the predictive value of preclinical models.
Charged Scalar Phenomenology in the Bilinear R-Parity Breaking Model
Ferrandis, J
1998-01-01
We consider the charged scalar boson phenomenology in the bilinear R-parity breaking model which induces a mixing between staus and the charged Higgs boson. The charged Higgs boson mass can be lower than expected in the MSSM, even before including radiative corrections. The R-parity violating decay rates can be comparable or even bigger than the R-parity conserving ones. These features could have implications for charged supersymmetric scalar boson searches at future accelerators.
A predictive model for dimensional errors in fused deposition modeling
DEFF Research Database (Denmark)
Stolfi, A.
2015-01-01
values of L (0.254 mm, 0.330 mm) was produced by comparing predicted values with external face-to-face measurements. After removing outliers, the results show that the developed two-parameter model can serve as tool for modeling the FDM dimensional behavior in a wide range of deposition angles.......This work concerns the effect of deposition angle (a) and layer thickness (L) on the dimensional performance of FDM parts using a predictive model based on the geometrical description of the FDM filament profile. An experimental validation over the whole a range from 0° to 177° at 3° steps and two...
Ground Motion Prediction Models for Caucasus Region
Jorjiashvili, Nato; Godoladze, Tea; Tvaradze, Nino; Tumanova, Nino
2016-04-01
Ground motion prediction models (GMPMs) relate ground motion intensity measures to variables describing earthquake source, path, and site effects. Estimation of expected ground motion is a fundamental earthquake hazard assessment. The most commonly used parameter for attenuation relation is peak ground acceleration or spectral acceleration because this parameter gives useful information for Seismic Hazard Assessment. Since 2003 development of Georgian Digital Seismic Network has started. In this study new GMP models are obtained based on new data from Georgian seismic network and also from neighboring countries. Estimation of models is obtained by classical, statistical way, regression analysis. In this study site ground conditions are additionally considered because the same earthquake recorded at the same distance may cause different damage according to ground conditions. Empirical ground-motion prediction models (GMPMs) require adjustment to make them appropriate for site-specific scenarios. However, the process of making such adjustments remains a challenge. This work presents a holistic framework for the development of a peak ground acceleration (PGA) or spectral acceleration (SA) GMPE that is easily adjustable to different seismological conditions and does not suffer from the practical problems associated with adjustments in the response spectral domain.
Modeling and Prediction of Krueger Device Noise
Guo, Yueping; Burley, Casey L.; Thomas, Russell H.
2016-01-01
This paper presents the development of a noise prediction model for aircraft Krueger flap devices that are considered as alternatives to leading edge slotted slats. The prediction model decomposes the total Krueger noise into four components, generated by the unsteady flows, respectively, in the cove under the pressure side surface of the Krueger, in the gap between the Krueger trailing edge and the main wing, around the brackets supporting the Krueger device, and around the cavity on the lower side of the main wing. For each noise component, the modeling follows a physics-based approach that aims at capturing the dominant noise-generating features in the flow and developing correlations between the noise and the flow parameters that control the noise generation processes. The far field noise is modeled using each of the four noise component's respective spectral functions, far field directivities, Mach number dependencies, component amplitudes, and other parametric trends. Preliminary validations are carried out by using small scale experimental data, and two applications are discussed; one for conventional aircraft and the other for advanced configurations. The former focuses on the parametric trends of Krueger noise on design parameters, while the latter reveals its importance in relation to other airframe noise components.
Artificial Neural Network Model for Predicting Compressive
Directory of Open Access Journals (Sweden)
Salim T. Yousif
2013-05-01
Full Text Available Compressive strength of concrete is a commonly used criterion in evaluating concrete. Although testing of the compressive strength of concrete specimens is done routinely, it is performed on the 28th day after concrete placement. Therefore, strength estimation of concrete at early time is highly desirable. This study presents the effort in applying neural network-based system identification techniques to predict the compressive strength of concrete based on concrete mix proportions, maximum aggregate size (MAS, and slump of fresh concrete. Back-propagation neural networks model is successively developed, trained, and tested using actual data sets of concrete mix proportions gathered from literature. The test of the model by un-used data within the range of input parameters shows that the maximum absolute error for model is about 20% and 88% of the output results has absolute errors less than 10%. The parametric study shows that water/cement ratio (w/c is the most significant factor affecting the output of the model. The results showed that neural networks has strong potential as a feasible tool for predicting compressive strength of concrete.
A prediction model for Clostridium difficile recurrence
Directory of Open Access Journals (Sweden)
Francis D. LaBarbera
2015-02-01
Full Text Available Background: Clostridium difficile infection (CDI is a growing problem in the community and hospital setting. Its incidence has been on the rise over the past two decades, and it is quickly becoming a major concern for the health care system. High rate of recurrence is one of the major hurdles in the successful treatment of C. difficile infection. There have been few studies that have looked at patterns of recurrence. The studies currently available have shown a number of risk factors associated with C. difficile recurrence (CDR; however, there is little consensus on the impact of most of the identified risk factors. Methods: Our study was a retrospective chart review of 198 patients diagnosed with CDI via Polymerase Chain Reaction (PCR from February 2009 to Jun 2013. In our study, we decided to use a machine learning algorithm called the Random Forest (RF to analyze all of the factors proposed to be associated with CDR. This model is capable of making predictions based on a large number of variables, and has outperformed numerous other models and statistical methods. Results: We came up with a model that was able to accurately predict the CDR with a sensitivity of 83.3%, specificity of 63.1%, and area under curve of 82.6%. Like other similar studies that have used the RF model, we also had very impressive results. Conclusions: We hope that in the future, machine learning algorithms, such as the RF, will see a wider application.
Hollenbeck, Dawn; Martini, K. Michael; Langner, Andreas; Ross, David; Harkin, Anthony; Nelson, Edward; Thurston, George
2010-03-01
We study the pattern-specific work of charging for two spherical model proteins in close proximity in ionic solution, using a grand-canonical partition function together with a coarse-grained, linear Debye-Huckel model to calculate the needed work of charging for each possible proton occupancy configuration. We seek to delineate a parameter-space phase diagram to characterize the circumstances under which patterned charge regulation, attractions due to heterogeneous protein charging patterns, and screened net protein charge could individually dominate the electrostatic portion of the interaction between model particles. Within the model, we place titratable residues in accordance with the tertiary protein structure, as is done in the case of a single protein within the Tanford-Kirkwood protein electrostatics model. We use Monte-Carlo simulation and analytical work to evaluate how the local statistics of the charging patterns on each protein respond to close proximity and relative orientation of neighboring proteins.
Predictions in multifield models of inflation
International Nuclear Information System (INIS)
This paper presents a method for obtaining an analytic expression for the density function of observables in multifield models of inflation with sum-separable potentials. The most striking result is that the density function in general possesses a sharp peak and the location of this peak is only mildly sensitive to the distribution of initial conditions. A simple argument is given for why this result holds for a more general class of models than just those with sum-separable potentials and why for such models, it is possible to obtain robust predictions for observable quantities. As an example, the joint density function of the spectral index and running in double quadratic inflation is computed. For scales leaving the horizon 55 e-folds before the end of inflation, the density function peaks at ns = 0.967 and α = 0.0006 for the spectral index and running respectively
An analytical model for climatic predictions
International Nuclear Information System (INIS)
A climatic model based upon analytical expressions is presented. This model is capable of making long-range predictions of heat energy variations on regional or global scales. These variations can then be transformed into corresponding variations of some other key climatic parameters since weather and climatic changes are basically driven by differential heating and cooling around the earth. On the basis of the mathematical expressions upon which the model is based, it is shown that the global heat energy structure (and hence the associated climatic system) are characterized by zonally as well as latitudinally propagating fluctuations at frequencies downward of 0.5 day-1. We have calculated the propagation speeds for those particular frequencies that are well documented in the literature. The calculated speeds are in excellent agreement with the measured speeds. (author). 13 refs
An Anisotropic Hardening Model for Springback Prediction
Zeng, Danielle; Xia, Z. Cedric
2005-08-01
As more Advanced High-Strength Steels (AHSS) are heavily used for automotive body structures and closures panels, accurate springback prediction for these components becomes more challenging because of their rapid hardening characteristics and ability to sustain even higher stresses. In this paper, a modified Mroz hardening model is proposed to capture realistic Bauschinger effect at reverse loading, such as when material passes through die radii or drawbead during sheet metal forming process. This model accounts for material anisotropic yield surface and nonlinear isotropic/kinematic hardening behavior. Material tension/compression test data are used to accurately represent Bauschinger effect. The effectiveness of the model is demonstrated by comparison of numerical and experimental springback results for a DP600 straight U-channel test.
Predictivity of models with spontaneously broken non-Abelian discrete flavor symmetries
Chen, Mu-Chun; Fallbacher, Maximilian; Omura, Yuji; Ratz, Michael; Staudt, Christian
2013-08-01
In a class of supersymmetric flavor models predictions are based on residual symmetries of some subsectors of the theory such as those of the charged leptons and neutrinos. However, the vacuum expectation values of the so-called flavon fields generally modify the Kähler potential of the setting, thus changing the predictions. We derive simple analytic formulae that allow us to understand the impact of these corrections on the predictions for the masses and mixing parameters. Furthermore, we discuss the effects on the vacuum alignment and on flavor changing neutral currents. Our results can also be applied to non-supersymmetric flavor models.
Predictivity of models with spontaneously broken non-Abelian discrete flavor symmetries
Chen, Mu-Chun; Omura, Yuji; Ratz, Michael; Staudt, Christian
2013-01-01
In a class of supersymmetric flavor models predictions are based on residual symmetries of some subsectors of the theory such as those of the charged leptons and neutrinos. However, the vacuum expectation values of the so-called flavon fields generally modify the K\\"ahler potential of the setting, thus changing the predictions. We derive simple analytic formulae that allow us to understand the impact of these corrections on the predictions for the masses and mixing parameters. Furthermore, we discuss the effects on the vacuum alignment and on flavor changing neutral currents. Our results can also be applied to non--supersymmetric flavor models.
The Binding Energy, Spin-Excitation Gap, and Charged Gap in the Boson-Fermion Model
Institute of Scientific and Technical Information of China (English)
YANG Kai-Hua; TIAN Guang-Shan; HAN Ru-Qi
2003-01-01
In this paper, by applying a simplified version of Lieb 's spin-refleetion-positivity method, which was recentlydeveloped by one of us [G.S. Tian and J.G. Wang, J. Phys. A: Math. Gen. 35 (2002) 941], we investigate some generalproperties of the boson-fermion Hamiltonian, which has been widely used as a phenomenological model to describe thereal-space pairing of electrons. On a mathematically rigorous basis, we prove that for either negative or positive couplingV, which represents the spontaneous decay and recombination process between boson and fermion in the model, thepairing energy of electrons is nonzero. Furthermore, we also show that the spin-excitation gap of the boson-fermionHamiltonian is always larger than its charged gap, as predicted by the pre-paired electron theory.
The Binding Energy, Spin－Excitation Gap, and Charged Gap in the Boson－Fermion Model
Institute of Scientific and Technical Information of China (English)
YANGKai-Hua; Guang-Shan; HANRu-Qi
2003-01-01
In this paper, by applying a simplified version of Lieb's spin-reflection-positivity method, which was recently developed by one of us [G.S. Tian and J.G. Wang, J. Phys. A: Math. Gen. 35 (2002) 941], we investigate some general properties of the boeon-fermion Hamiltonlan, which has been widely used as a phenomenological model to describe the real-space pairing of electrons. On a mathematically rigorous basis, we prove that for either negative or positive couping V, which represents the spontaneous decay and recombination process between boson and fermion in the model, the pairing energy of electrons is nonzero. Furthermore, we also show that the spin-excitation gap of the boson-fermion Hamiltonian is always larger than its charged gap, as predicted by the pre-palred electron theory.
Simple predictions from multifield inflationary models.
Easther, Richard; Frazer, Jonathan; Peiris, Hiranya V; Price, Layne C
2014-04-25
We explore whether multifield inflationary models make unambiguous predictions for fundamental cosmological observables. Focusing on N-quadratic inflation, we numerically evaluate the full perturbation equations for models with 2, 3, and O(100) fields, using several distinct methods for specifying the initial values of the background fields. All scenarios are highly predictive, with the probability distribution functions of the cosmological observables becoming more sharply peaked as N increases. For N=100 fields, 95% of our Monte Carlo samples fall in the ranges ns∈(0.9455,0.9534), α∈(-9.741,-7.047)×10-4, r∈(0.1445,0.1449), and riso∈(0.02137,3.510)×10-3 for the spectral index, running, tensor-to-scalar ratio, and isocurvature-to-adiabatic ratio, respectively. The expected amplitude of isocurvature perturbations grows with N, raising the possibility that many-field models may be sensitive to postinflationary physics and suggesting new avenues for testing these scenarios.
Predictions of models for environmental radiological assessment
Energy Technology Data Exchange (ETDEWEB)
Peres, Sueli da Silva; Lauria, Dejanira da Costa, E-mail: suelip@ird.gov.br, E-mail: dejanira@irg.gov.br [Instituto de Radioprotecao e Dosimetria (IRD/CNEN-RJ), Servico de Avaliacao de Impacto Ambiental, Rio de Janeiro, RJ (Brazil); Mahler, Claudio Fernando [Coppe. Instituto Alberto Luiz Coimbra de Pos-Graduacao e Pesquisa de Engenharia, Universidade Federal do Rio de Janeiro (UFRJ) - Programa de Engenharia Civil, RJ (Brazil)
2011-07-01
In the field of environmental impact assessment, models are used for estimating source term, environmental dispersion and transfer of radionuclides, exposure pathway, radiation dose and the risk for human beings Although it is recognized that the specific information of local data are important to improve the quality of the dose assessment results, in fact obtaining it can be very difficult and expensive. Sources of uncertainties are numerous, among which we can cite: the subjectivity of modelers, exposure scenarios and pathways, used codes and general parameters. The various models available utilize different mathematical approaches with different complexities that can result in different predictions. Thus, for the same inputs different models can produce very different outputs. This paper presents briefly the main advances in the field of environmental radiological assessment that aim to improve the reliability of the models used in the assessment of environmental radiological impact. The intercomparison exercise of model supplied incompatible results for {sup 137}Cs and {sup 60}Co, enhancing the need for developing reference methodologies for environmental radiological assessment that allow to confront dose estimations in a common comparison base. The results of the intercomparison exercise are present briefly. (author)
Distributed Model Predictive Control via Dual Decomposition
DEFF Research Database (Denmark)
Biegel, Benjamin; Stoustrup, Jakob; Andersen, Palle
2014-01-01
This chapter presents dual decomposition as a means to coordinate a number of subsystems coupled by state and input constraints. Each subsystem is equipped with a local model predictive controller while a centralized entity manages the subsystems via prices associated with the coupling constraints....... This allows coordination of all the subsystems without the need of sharing local dynamics, objectives and constraints. To illustrate this, an example is included where dual decomposition is used to resolve power grid congestion in a distributed manner among a number of players coupled by distribution grid...
Explicit model predictive control accuracy analysis
Knyazev, Andrew; Zhu, Peizhen; Di Cairano, Stefano
2015-01-01
Model Predictive Control (MPC) can efficiently control constrained systems in real-time applications. MPC feedback law for a linear system with linear inequality constraints can be explicitly computed off-line, which results in an off-line partition of the state space into non-overlapped convex regions, with affine control laws associated to each region of the partition. An actual implementation of this explicit MPC in low cost micro-controllers requires the data to be "quantized", i.e. repre...
Model predictive control of smart microgrids
DEFF Research Database (Denmark)
Hu, Jiefeng; Zhu, Jianguo; Guerrero, Josep M.
2014-01-01
required to realise high-performance of distributed generations and will realise innovative control techniques utilising model predictive control (MPC) to assist in coordinating the plethora of generation and load combinations, thus enable the effective exploitation of the clean renewable energy sources......The exploitation of renewable energy and the development of intelligent electricity network have become the main concerns worldwide. This paper aims to integrate renewable energy sources, local loads, and energy storage devices into smart microgrids. It proposes a new microgrid configuration...
A Modified Model Predictive Control Scheme
Institute of Scientific and Technical Information of China (English)
Xiao-Bing Hu; Wen-Hua Chen
2005-01-01
In implementations of MPC (Model Predictive Control) schemes, two issues need to be addressed. One is how to enlarge the stability region as much as possible. The other is how to guarantee stability when a computational time limitation exists. In this paper, a modified MPC scheme for constrained linear systems is described. An offline LMI-based iteration process is introduced to expand the stability region. At the same time, a database of feasible control sequences is generated offline so that stability can still be guaranteed in the case of computational time limitations. Simulation results illustrate the effectiveness of this new approach.
Directory of Open Access Journals (Sweden)
D. J. de Ridder
2009-10-01
Full Text Available The occurrence of organic micropollutants in drinking water and its sources has opened up a field of study related to monitoring concentration levels in water sources, evaluating their toxicity and estimating their removal in drinking water treatment processes. Because a large number of organic micropollutants is currently present (although in relatively low concentrations in drinking water sources, a method should be developed to select which micropollutants has to be evaluated with priority. In this paper, a screening model is presented that can predict solute removal by activated carbon, in ultrapure water and in natural water. Solute removal prediction is based on a combination of solute hydrophobicity (expressed as log D, the pH corrected log K_{ow}, solute charge and the carbon dose. Solute molecular weight was also considered as model input parameter, but this solute property appeared to relate insufficiently to solute removal.
Removal of negatively charged solutes by preloaded activated carbon was reduced while the removal of positively charged solutes was increased, compared with freshly regenerated activated carbon. Differences in charged solute removal by freshly regenerated activated carbon were small, indicating that charge interactions are an important mechanism in adsorption onto preloaded carbon. The predicted solute removal was within 20 removal-% deviation of experimentally measured values.
Directory of Open Access Journals (Sweden)
D. J. de Ridder
2009-12-01
Full Text Available The occurrence of organic micropollutants in drinking water and its sources has opened up a field of study related to monitoring concentration levels in water sources, evaluating their toxicity and estimating their removal in drinking water treatment processes. Because a large number of organic micropollutants is currently present (although in relatively low concentrations in drinking water sources, a method should be developed to select which micropollutants has to be evaluated with priority. In this paper, a screening model is presented that can predict solute removal by activated carbon, in ultrapure water and in natural water. Solute removal prediction is based on a combination of solute hydrophobicity (expressed as log D, the pH corrected log K_{ow}, solute charge and the carbon dose. Solute molecular weight was also considered as model input parameter, but this solute property appeared to relate insufficiently to solute removal.
Removal of negatively charged solutes by preloaded activated carbon was reduced while the removal of positively charged solutes was increased, compared with freshly regenerated activated carbon. Differences in charged solute removal by freshly regenerated activated carbon were small, indicating that charge interactions are an important mechanism in adsorption onto preloaded carbon. The predicted solute removal was within 20 removal-% deviation of experimentally measured values for most solutes.
Predictive modelling of boiler fouling. Final report.
Energy Technology Data Exchange (ETDEWEB)
Chatwani, A
1990-12-31
A spectral element method embodying Large Eddy Simulation based on Re- Normalization Group theory for simulating Sub Grid Scale viscosity was chosen for this work. This method is embodied in a computer code called NEKTON. NEKTON solves the unsteady, 2D or 3D,incompressible Navier Stokes equations by a spectral element method. The code was later extended to include the variable density and multiple reactive species effects at low Mach numbers, and to compute transport of large particles governed by inertia. Transport of small particles is computed by treating them as trace species. Code computations were performed for a number of test conditions typical of flow past a deep tube bank in a boiler. Results indicate qualitatively correct behavior. Predictions of deposition rates and deposit shape evolution also show correct qualitative behavior. These simulations are the first attempts to compute flow field results at realistic flow Reynolds numbers of the order of 10{sup 4}. Code validation was not done; comparison with experiment also could not be made as many phenomenological model parameters, e.g., sticking or erosion probabilities and their dependence on experimental conditions were not known. The predictions however demonstrate the capability to predict fouling from first principles. Further work is needed: use of large or massively parallel machine; code validation; parametric studies, etc.
Coarse Point Charge Models For Proteins From Smoothed Molecular Electrostatic Potentials.
Leherte, Laurence; Vercauteren, Daniel P
2009-12-01
To generate coarse electrostatic models of proteins, we developed an original approach to hierarchically locate maxima and minima in smoothed molecular electrostatic potentials. A charge-fitting program was used to assign charges to the so-obtained reduced representations. Templates are defined to easily generate coarse point charge models for protein structures, in the particular cases of the Amber99 and Gromos43A1 force fields. Applications to four small peptides and to the ion channel KcsA are presented. Electrostatic potential values generated by the reduced models are compared with the corresponding values obtained using the original sets of atomic charges. PMID:26602509
Zhang, Yanzhen; Liu, Yonghong; Wang, Xiaolong; Shen, Yang; Ji, Renjie; Cai, Baoping
2013-02-01
The charging characteristics of micrometer sized aqueous droplets have attracted more and more attentions due to the development of the microfluidics technology since the electrophoretic motion of a charged droplet can be used as the droplet actuation method. This work proposed a novel method of investigating the charging characteristics of micrometer sized aqueous droplets based on parallel plate capacitor model. With this method, the effects of the electric field strength, electrolyte concentration, and ion species on the charging characteristics of the aqueous droplets was investigated. Experimental results showed that the charging characteristics of micrometer sized droplets can be investigated by this method.
Borstnik, Norma Susana Mankoc
2013-01-01
The spin-charge-family theory, proposed by the author as a possible new way to explain the assumptions of the standard model, predicts at the low energy regime two decoupled groups of four families of quarks and leptons. In two successive breaks the massless families, first the group of four and at the second break the rest four families, gain nonzero mass matrices. The families are identical with respect to the charges and spin. There are two kinds of fields in this theory, which manifest at low energies as the gauge vector and scalar fields: the fields which couple to the charges and spin, and the fields which couple to the family quantum numbers. In loop corrections to the tree level mass matrices both kinds start to contribute coherently. The fourth family of the lower group of four families is predicted to be possibly observed at the LHC and the stable of the higher four families -- the fifth family -- is the candidate to constitute the dark matter. Properties of the families of quarks and leptons and of...
A Predictive Maintenance Model for Railway Tracks
DEFF Research Database (Denmark)
Li, Rui; Wen, Min; Salling, Kim Bang;
2015-01-01
presents a mathematical model based on Mixed Integer Programming (MIP) which is designed to optimize the predictive railway tamping activities for ballasted track for the time horizon up to four years. The objective function is setup to minimize the actual costs for the tamping machine (measured by time...... recovery on the track quality after tamping operation and (5) Tamping machine operation factors. A Danish railway track between Odense and Fredericia with 57.2 km of length is applied for a time period of two to four years in the proposed maintenance model. The total cost can be reduced with up to 50......For the modern railways, maintenance is critical for ensuring safety, train punctuality and overall capacity utilization. The cost of railway maintenance in Europe is high, on average between 30,000 – 100,000 Euro per km per year [1]. Aiming to reduce such maintenance expenditure, this paper...
Model Predictive Control of Wind Turbines
DEFF Research Database (Denmark)
Henriksen, Lars Christian
are controlled by pitching the blades and by controlling the electro-magnetic torque of the generator, thus slowing the rotation of the blades. Improved control of wind turbines, leading to reduced fatigue loads, can be exploited by using less materials in the construction of the wind turbine or by reducing...... been the foundation on which the control algorithms have been build. Three controllers are presented in the thesis. The first is based on four different linear model predictive controllers where appropriate switching conditions determine which controller is active. Constraint handling of actuator...... the need for maintenance of the wind turbine. Either way, better total-cost-of-ownership for wind turbine operators can be achieved by improved control of the wind turbines. Wind turbine control can be improved in two ways, by improving the model on which the controller bases its design or by improving...
Modeling Reef Hydrodynamics to Predict Coral Bleaching
Bird, James; Steinberg, Craig; Hardy, Tom
2005-11-01
The aim of this study is to use environmental physics to predict water temperatures around and within coral reefs. Anomalously warm water is the leading cause for mass coral bleaching; thus a clearer understanding of the oceanographic mechanisms that control reef water temperatures will enable better reef management. In March 1998 a major coral bleaching event occurred at Scott Reef, a 40 km-wide lagoon 300 km off the northwest coast of Australia. Meteorological and coral cover observations were collected before, during, and after the event. In this study, two hydrodynamic models are applied to Scott Reef and validated against oceanographic data collected between March and June 2003. The models are then used to hindcast the reef hydrodynamics that led up to the 1998 bleaching event. Results show a positive correlation between poorly mixed regions and bleaching severity.
Image charge effects in the nonequilibrium Anderson-Holstein model
Perfetto, E.; Stefanucci, G.
2013-12-01
Image charge effects in nanoscale junctions with strong electron-phonon coupling open the way to unexplored physical scenarios. We propose a simple and still accurate many-body approach to deal with the simultaneous occurrence of the Franck-Condon blockade and the screening-induced enhancement of the polaron mobility. A transparent analytic expression for the polaron decay rate is derived and the dependence on the strength and range of the screening is highlighted. This allows us to interpret and explain several transient and steady-state features of the electrical current. Remarkably, we find that the competition between the charge blocking due to the electron-phonon interaction and the charge deblocking due to the image charges gives rise to a novel mechanism of negative differential conductance. An experimental setup to observe this phenomenon is discussed.
A predictive fitness model for influenza
Łuksza, Marta; Lässig, Michael
2014-03-01
The seasonal human influenza A/H3N2 virus undergoes rapid evolution, which produces significant year-to-year sequence turnover in the population of circulating strains. Adaptive mutations respond to human immune challenge and occur primarily in antigenic epitopes, the antibody-binding domains of the viral surface protein haemagglutinin. Here we develop a fitness model for haemagglutinin that predicts the evolution of the viral population from one year to the next. Two factors are shown to determine the fitness of a strain: adaptive epitope changes and deleterious mutations outside the epitopes. We infer both fitness components for the strains circulating in a given year, using population-genetic data of all previous strains. From fitness and frequency of each strain, we predict the frequency of its descendent strains in the following year. This fitness model maps the adaptive history of influenza A and suggests a principled method for vaccine selection. Our results call for a more comprehensive epidemiology of influenza and other fast-evolving pathogens that integrates antigenic phenotypes with other viral functions coupled by genetic linkage.
A PEV Charging Service Model for Smart Grids
Mohammed Abdel-Hafez; Ahmed Gaouda; Liren Zhang; Khaled Shuaib
2012-01-01
Plug-in Electric Vehicles (PEVs) are envisioned to be more popular during the next decade as part of Smart Grid implementations. Charging multiple PEVs at the same time within a power distribution area constitutes a major challenge for energy service providers. This paper discusses a priority-based approach for charging PEVs in a Smart Grid environment. In this work, ideas from the communication network paradigm are being utilized and tailored toward achieving the desired objective of monitor...
CHARGE AND SPIN GAPS IN THE DIMERIZED HUBBARD MODEL
Institute of Scientific and Technical Information of China (English)
Ding Guo-hui; Ye Fei; Xu bo-wei
2000-01-01
By using the bosonization and renormalization group methods, we have studied the low energy physical properties in the one-dimensional dimerized Hubbardmodel. The formation of charge and spin gaps is investigated both for thehalf-filled electron band and away from the half-filled band. The scaling lawsof the charge and spin gaps with the dimerization parameterand the repulsiveinteraction strength U are obtained.
Predictive Capability Maturity Model for computational modeling and simulation.
Energy Technology Data Exchange (ETDEWEB)
Oberkampf, William Louis; Trucano, Timothy Guy; Pilch, Martin M.
2007-10-01
The Predictive Capability Maturity Model (PCMM) is a new model that can be used to assess the level of maturity of computational modeling and simulation (M&S) efforts. The development of the model is based on both the authors experience and their analysis of similar investigations in the past. The perspective taken in this report is one of judging the usefulness of a predictive capability that relies on the numerical solution to partial differential equations to better inform and improve decision making. The review of past investigations, such as the Software Engineering Institute's Capability Maturity Model Integration and the National Aeronautics and Space Administration and Department of Defense Technology Readiness Levels, indicates that a more restricted, more interpretable method is needed to assess the maturity of an M&S effort. The PCMM addresses six contributing elements to M&S: (1) representation and geometric fidelity, (2) physics and material model fidelity, (3) code verification, (4) solution verification, (5) model validation, and (6) uncertainty quantification and sensitivity analysis. For each of these elements, attributes are identified that characterize four increasing levels of maturity. Importantly, the PCMM is a structured method for assessing the maturity of an M&S effort that is directed toward an engineering application of interest. The PCMM does not assess whether the M&S effort, the accuracy of the predictions, or the performance of the engineering system satisfies or does not satisfy specified application requirements.
Modelling die filling with charged particles using DEM/CFD
Institute of Scientific and Technical Information of China (English)
Emmanuel Nkem Nwose; Chunlei Pei; Chuan-Yu Wu
2012-01-01
The effects of electrostatic charge on powder flow behaviour during die filling in a vacuum and in air were analysed using a coupled discrete element method and computational fluid dynamics (DEM/CFD) code,in which long range electrostatic interactions were implemented.The present 2D simulations revealed that both electrostatic charge and the presence of air can affect the powder flow behaviour during die filling.It was found that the electrostatic charge inhibited the flow of powders into the die and induced a loose packing structure.At the same filling speed,increasing the electrostatic charge led to a decrease in the fill ratio which quantifies the volumetric occupancy of powder in the die.In addition,increasing the shoe speed caused a further decrease in the fill ratio,which was characterised using the concept of critical filling speed.When the electrostatic charge was low,the air/particle interaction was strong so that a lower critical filling speed was obtained for die filling in air than in a vacuum.With high electrostatic charge,the electrostatic interactions became dominant.Consequently,similar fill ratio and critical filling speed were obtained for die filling in air and in a vacuum.
Li, Guochang; Chen, George; Li, Shengtao
2016-08-01
Charge transport properties in nanodielectrics present different tendencies for different loading concentrations. The exact mechanisms that are responsible for charge transport in nanodielectrics are not detailed, especially for high loading concentration. A charge transport model in nanodielectrics has been proposed based on quantum tunneling mechanism and dual-level traps. In the model, the thermally assisted hopping (TAH) process for the shallow traps and the tunnelling process for the deep traps are considered. For different loading concentrations, the dominant charge transport mechanisms are different. The quantum tunneling mechanism plays a major role in determining the charge conduction in nanodielectrics with high loading concentrations. While for low loading concentrations, the thermal hopping mechanism will dominate the charge conduction process. The model can explain the observed conductivity property in nanodielectrics with different loading concentrations.
Casalicchio, Giuseppe; Bischl, Bernd; Boulesteix, Anne-Laure; Schmid, Matthias
2015-01-01
It is agreed among biostatisticians that prediction models for binary outcomes should satisfy two essential criteria: First, a prediction model should have a high discriminatory power, implying that it is able to clearly separate cases from controls. Second, the model should be well calibrated, meaning that the predicted risks should closely agree with the relative frequencies observed in the data. The focus of this work is on the predictiveness curve, which has been proposed by Huang et ...
Charge Exchange Induced X-ray Emission of Fe XXV and Fe XXVI via a Streamlined Model
Mullen, P D; Lyons, D; Stancil, P C
2016-01-01
Charge exchange is an important process for the modeling of X-ray spectra obtained by the Chandra, XMM-Newton, and Suzaku X-ray observatories, as well as the anticipated Astro-H mission. The understanding of the observed X-ray spectra produced by many astrophysical environments is hindered by the current incompleteness of available atomic and molecular data -- especially for charge exchange. Here, we implement a streamlined program set that applies quantum defect methods and the Landau-Zener theory to generate total, n-resolved, and nlS-resolved cross sections for any given projectile ion/ target charge exchange collision. Using this data in a cascade model for X-ray emission, theoretical spectra for such systems can be predicted. With these techniques, Fe25+ and Fe26+ charge exchange collisions with H, He, H2, N2, H2O, and CO are studied for single electron capture. These systems have been selected as they illustrate computational difficulties for high projectile charges. Further, Fe XXV and Fe XXVI emission...
A Symplectic Multi-Particle Tracking Model for Self-Consistent Space-Charge Simulation
Qiang, Ji
2016-01-01
Symplectic tracking is important in accelerator beam dynamics simulation. So far, to the best of our knowledge, there is no self-consistent symplectic space-charge tracking model available in the accelerator community. In this paper, we present a two-dimensional and a three-dimensional symplectic multi-particle spectral model for space-charge tracking simulation. This model includes both the effect from external fields and the effect of self-consistent space-charge fields using a split-operator method. Such a model preserves the phase space structure and shows much less numerical emittance growth than the particle-in-cell model in the illustrative examples.
Braun, M A; Kondratev, V P; Vechernin, V V
1999-01-01
We present results of Monte Carlo simulations of charged particles multiplicity distributions and ALICE background conditions in forward region for PbPb collisions at LHC.HIJING event generator [1] results are compared with predictions of Coloured String Fusion Model [2,3].Requirements to the Forward Multiplicity Detector for ALICE arising from these simulations are discussed (multiplicity range, resolution in multiplicity, granularity, timing resolution).References: [1] N.van Eijndhoven et al., ALICE/CERN 95-32, Internal Note 1996[2] M.Braun and C.Pajares, PHys. Rev. D47 (1993) 114-122[2] M.Braun and C.Pajares, PHys. Rev. C51 (1995) 879-889
Modeling charge polarization voltage for large lithium-ion batteries in electric vehicles
Directory of Open Access Journals (Sweden)
Yan Jiang
2013-06-01
Full Text Available Purpose: Polarization voltage of the lithium-ion battery is an important parameter that has direct influence on battery performance. The paper aims to analyze the impedance characteristics of the lithium-ion battery based on EIS data. Design/methodology/approach: The effects of currents, initial SOC of the battery on charge polarization voltage are investigated, which is approximately linear function of charge current. The change of charge polarization voltage is also analyzed with the gradient analytical method in the SOC domain. The charge polarization model with two RC networks is presented, and parts of model parameters like Ohmic resistance and charge transfer impedance are estimated by both EIS method and battery constant current testing method. Findings: This paper reveals that the Ohmic resistance accounts for much contribution to battery total polarization compared to charge transfer impedance. Practical implications: Experimental results demonstrate the efficacy of the model with the proposed identification method, which provides the foundation for battery charging optimization. Originality/value: The paper analyzed the impedance characteristics of the lithium-ion battery based on EIS data, presented a charge polarization model with two RC networks, and estimated parameters like Ohmic resistance and charge transfer impedance.
DEFF Research Database (Denmark)
Ugur, Ilke; Marion, Antoine; Parant, Stéphane;
2014-01-01
of the experimental pKa's of phenols, alcohols, and thiols. Our protocol is based on the linear relationship between computed atomic charges of the anionic form of the molecules (being either phenolates, alkoxides, or thiolates) and their respective experimental pKa values. It is tested with different environment...... approaches (gas phase or continuum solvent-based approaches), with five distinct atomic charge models (Mulliken, Löwdin, NPA, Merz-Kollman, and CHelpG), and with nine different DFT functionals combined with 16 different basis sets. Moreover, the capability of semiempirical methods (AM1, RM1, PM3, and PM6......) to also predict pKa's of thiols, phenols, and alcohols is analyzed. From our benchmarks, the best combination to reproduce experimental pKa's is to compute NPA atomic charge using the CPCM model at the B3LYP/3-21G and M062X/6-311G levels for alcohols (R(2) = 0.995) and thiols (R(2) = 0.986), respectively...
Heuristic Modeling for TRMM Lifetime Predictions
Jordan, P. S.; Sharer, P. J.; DeFazio, R. L.
1996-01-01
Analysis time for computing the expected mission lifetimes of proposed frequently maneuvering, tightly altitude constrained, Earth orbiting spacecraft have been significantly reduced by means of a heuristic modeling method implemented in a commercial-off-the-shelf spreadsheet product (QuattroPro) running on a personal computer (PC). The method uses a look-up table to estimate the maneuver frequency per month as a function of the spacecraft ballistic coefficient and the solar flux index, then computes the associated fuel use by a simple engine model. Maneuver frequency data points are produced by means of a single 1-month run of traditional mission analysis software for each of the 12 to 25 data points required for the table. As the data point computations are required only a mission design start-up and on the occasion of significant mission redesigns, the dependence on time consuming traditional modeling methods is dramatically reduced. Results to date have agreed with traditional methods to within 1 to 1.5 percent. The spreadsheet approach is applicable to a wide variety of Earth orbiting spacecraft with tight altitude constraints. It will be particularly useful to such missions as the Tropical Rainfall Measurement Mission scheduled for launch in 1997, whose mission lifetime calculations are heavily dependent on frequently revised solar flux predictions.
Prediction of Catastrophes: an experimental model
Peters, Randall D; Pomeau, Yves
2012-01-01
Catastrophes of all kinds can be roughly defined as short duration-large amplitude events following and followed by long periods of "ripening". Major earthquakes surely belong to the class of 'catastrophic' events. Because of the space-time scales involved, an experimental approach is often difficult, not to say impossible, however desirable it could be. Described in this article is a "laboratory" setup that yields data of a type that is amenable to theoretical methods of prediction. Observations are made of a critical slowing down in the noisy signal of a solder wire creeping under constant stress. This effect is shown to be a fair signal of the forthcoming catastrophe in both of two dynamical models. The first is an "abstract" model in which a time dependent quantity drifts slowly but makes quick jumps from time to time. The second is a realistic physical model for the collective motion of dislocations (the Ananthakrishna set of equations for creep). Hope thus exists that similar changes in the response to ...
Distributed model predictive control made easy
Negenborn, Rudy
2014-01-01
The rapid evolution of computer science, communication, and information technology has enabled the application of control techniques to systems beyond the possibilities of control theory just a decade ago. Critical infrastructures such as electricity, water, traffic and intermodal transport networks are now in the scope of control engineers. The sheer size of such large-scale systems requires the adoption of advanced distributed control approaches. Distributed model predictive control (MPC) is one of the promising control methodologies for control of such systems. This book provides a state-of-the-art overview of distributed MPC approaches, while at the same time making clear directions of research that deserve more attention. The core and rationale of 35 approaches are carefully explained. Moreover, detailed step-by-step algorithmic descriptions of each approach are provided. These features make the book a comprehensive guide both for those seeking an introduction to distributed MPC as well as for those ...
Directory of Open Access Journals (Sweden)
Chi-Ho Chan
Full Text Available Optimization of the surface charges is a promising strategy for increasing thermostability of proteins. Electrostatic contribution of ionizable groups to the protein stability can be estimated from the differences between the pKa values in the folded and unfolded states of a protein. Using this pKa-shift approach, we experimentally measured the electrostatic contribution of all aspartate and glutamate residues to the stability of a thermophilic ribosomal protein L30e from Thermococcus celer. The pKa values in the unfolded state were found to be similar to model compound pKas. The pKa values in both the folded and unfolded states obtained at 298 and 333 K were similar, suggesting that electrostatic contribution of ionizable groups to the protein stability were insensitive to temperature changes. The experimental pKa values for the L30e protein in the folded state were used as a benchmark to test the robustness of pKa prediction by various computational methods such as H++, MCCE, MEAD, pKD, PropKa, and UHBD. Although the predicted pKa values were affected by crystal contacts that may alter the side-chain conformation of surface charged residues, most computational methods performed well, with correlation coefficients between experimental and calculated pKa values ranging from 0.49 to 0.91 (p<0.01. The changes in protein stability derived from the experimental pKa-shift approach correlate well (r = 0.81 with those obtained from stability measurements of charge-to-alanine substituted variants of the L30e protein. Our results demonstrate that the knowledge of the pKa values in the folded state provides sufficient rationale for the redesign of protein surface charges leading to improved protein stability.
Improved Space Charge Modeling for Simulation and Design of Photoinjectors
Energy Technology Data Exchange (ETDEWEB)
Robert H. Jackson, Thuc Bui, John Verboncoeur
2010-04-19
Photoinjectors in advanced high-energy accelerators reduce beam energy spreads and enhance undulator photon fluxes. Photoinjector design is difficult because of the substantial differences in time and spatial scales. This Phase I program explored an innovative technique, the local Taylor polynomial (LTP) formulation, for improving finite difference analysis of photoinjectors. This included improved weighting techniques, systematic formula for high order interpolation and electric field computation, and improved handling of space charge. The Phase I program demonstrated that the approach was powerful, accurate, and efficient. It handles space charge gradients better than currently available technology.
Effect of pipeline rupture transient release modelling on predicted consequences
Energy Technology Data Exchange (ETDEWEB)
Johnston, C.R.; Springer, W.A.J.; Rowe, R.D. [Calgary Univ., Dept. of Mechanical Engineering, Calgary, AB (Canada)
1998-09-01
A mathematical model was developed to predict the consequences of a rupture in a natural gas pipeline. The model was a real-fluid, non-isentropic blowdown (RFB) model. A comparison of this model and the widely accepted double exponential model presented some interesting similarities and differences. The mass flow rates predicted by the two models were in close agreement, but the double exponential model was not able to predict the release of fluid as liquid. The RFB model predicted that 25 per cent of the mass released would be liquid.
Modeling Transport in Ultrathin Si Nanowires: Charged versus Neutral Impurities
DEFF Research Database (Denmark)
Rurali, Riccardo; Markussen, Troels; Suné, Jordi;
2008-01-01
Abstract: At room temperature dopants in semiconducting nanowires are ionized. We show that the long-range electrostatic potential due to charged dopants has a dramatic impact on the transport properties in ultrathin wires and can virtually block minority carriers. Our quantitative estimates of t...
Screening model for nanowire surface-charge sensors in liquid
DEFF Research Database (Denmark)
Sørensen, Martin Hedegård; Mortensen, Asger; Brandbyge, Mads
2007-01-01
. The authors discuss this effect within Thomas-Fermi and Debye-Hückel theory and derive analytical results for cylindrical wires which can be used to estimate the sensitivity of nanowire surface-charge sensors. They study the interplay between the nanowire radius, the Thomas-Fermi and Debye screening lengths...
Model predictive control of a wind turbine modelled in Simpack
Jassmann, U.; Berroth, J.; Matzke, D.; Schelenz, R.; Reiter, M.; Jacobs, G.; Abel, D.
2014-06-01
Wind turbines (WT) are steadily growing in size to increase their power production, which also causes increasing loads acting on the turbine's components. At the same time large structures, such as the blades and the tower get more flexible. To minimize this impact, the classical control loops for keeping the power production in an optimum state are more and more extended by load alleviation strategies. These additional control loops can be unified by a multiple-input multiple-output (MIMO) controller to achieve better balancing of tuning parameters. An example for MIMO control, which has been paid more attention to recently by wind industry, is Model Predictive Control (MPC). In a MPC framework a simplified model of the WT is used to predict its controlled outputs. Based on a user-defined cost function an online optimization calculates the optimal control sequence. Thereby MPC can intrinsically incorporate constraints e.g. of actuators. Turbine models used for calculation within the MPC are typically simplified. For testing and verification usually multi body simulations, such as FAST, BLADED or FLEX5 are used to model system dynamics, but they are still limited in the number of degrees of freedom (DOF). Detailed information about load distribution (e.g. inside the gearbox) cannot be provided by such models. In this paper a Model Predictive Controller is presented and tested in a co-simulation with SlMPACK, a multi body system (MBS) simulation framework used for detailed load analysis. The analysis are performed on the basis of the IME6.0 MBS WT model, described in this paper. It is based on the rotor of the NREL 5MW WT and consists of a detailed representation of the drive train. This takes into account a flexible main shaft and its main bearings with a planetary gearbox, where all components are modelled flexible, as well as a supporting flexible main frame. The wind loads are simulated using the NREL AERODYN v13 code which has been implemented as a routine to
Model predictive control of a wind turbine modelled in Simpack
International Nuclear Information System (INIS)
Wind turbines (WT) are steadily growing in size to increase their power production, which also causes increasing loads acting on the turbine's components. At the same time large structures, such as the blades and the tower get more flexible. To minimize this impact, the classical control loops for keeping the power production in an optimum state are more and more extended by load alleviation strategies. These additional control loops can be unified by a multiple-input multiple-output (MIMO) controller to achieve better balancing of tuning parameters. An example for MIMO control, which has been paid more attention to recently by wind industry, is Model Predictive Control (MPC). In a MPC framework a simplified model of the WT is used to predict its controlled outputs. Based on a user-defined cost function an online optimization calculates the optimal control sequence. Thereby MPC can intrinsically incorporate constraints e.g. of actuators. Turbine models used for calculation within the MPC are typically simplified. For testing and verification usually multi body simulations, such as FAST, BLADED or FLEX5 are used to model system dynamics, but they are still limited in the number of degrees of freedom (DOF). Detailed information about load distribution (e.g. inside the gearbox) cannot be provided by such models. In this paper a Model Predictive Controller is presented and tested in a co-simulation with SlMPACK, a multi body system (MBS) simulation framework used for detailed load analysis. The analysis are performed on the basis of the IME6.0 MBS WT model, described in this paper. It is based on the rotor of the NREL 5MW WT and consists of a detailed representation of the drive train. This takes into account a flexible main shaft and its main bearings with a planetary gearbox, where all components are modelled flexible, as well as a supporting flexible main frame. The wind loads are simulated using the NREL AERODYN v13 code which has been implemented as a routine
Hummer, G; Neumann, M; Hummer, Gerhard; Gr{ø}nbech-Jensen, Niels; Neumann, Martin
1998-01-01
Ewald summation and physically equivalent methods such as particle-mesh Ewald, kubic-harmonic expansions, or Lekner sums are commonly used to calculate long-range electrostatic interactions in computer simulations of polar and charged substances. The calculation of pressures in such systems is investigated. We find that the virial and thermodynamic pressures differ because of the explicit volume dependence of the effective, resummed Ewald potential. The thermodynamic pressure, obtained from the volume derivative of the Helmholtz free energy, can be expressed easily for both ionic and rigid molecular systems. For a system of rigid molecules, the electrostatic energy and the forces at the atom positions are required, both of which are readily available in molecular dynamics codes. We then calculate the virial and thermodynamic pressures for the extended simple point charge (SPC/E) water model at standard conditions. We find that the thermodynamic pressure exhibits considerably less system size dependence than t...
Kornbleuth, Marc; Wargelin, Bradford J.; Juda, Michael
2014-06-01
Solar wind charge exchange (SWCX) X-rays are emitted when highly charged solar wind ions such as O7+ collide with neutral gas. The best known examples of this occur around comets, but SWCX emission also arises in the Earth's tenuous outer atmosphere and throughout the heliosphere as neutral H and He from the interstellar medium flows into the solar system. This geocoronal and heliospheric emission comprises much of the soft X-ray background and is seen in every X-ray observation. Geocoronal emission, although usually weaker than heliospheric emission, arises within a few tens of Earth radii and therefore responds much more quickly (on time scales of less than an hour) to changes in solar wind intensity than the widely distributed heliospheric emission.We have studied a dozen Chandra observations when the flux of solar wind protons and O7+ ions was at its highest. These gusts of wind cause correspondingly abrupt changes in geocoronal SWCX X-ray emission,which may or may not be apparent in Chandra data depending on a given observation's line of sight through the magnetosphere. We compare observed changes in the X-ray background with predictions from a fully 3D analysis of SWCX emission based on magnetospheric simulations using the BATS-R-US model.
A Predictive Model of Geosynchronous Magnetopause Crossings
Dmitriev, A; Chao, J -K
2013-01-01
We have developed a model predicting whether or not the magnetopause crosses geosynchronous orbit at given location for given solar wind pressure Psw, Bz component of interplanetary magnetic field (IMF) and geomagnetic conditions characterized by 1-min SYM-H index. The model is based on more than 300 geosynchronous magnetopause crossings (GMCs) and about 6000 minutes when geosynchronous satellites of GOES and LANL series are located in the magnetosheath (so-called MSh intervals) in 1994 to 2001. Minimizing of the Psw required for GMCs and MSh intervals at various locations, Bz and SYM-H allows describing both an effect of magnetopause dawn-dusk asymmetry and saturation of Bz influence for very large southward IMF. The asymmetry is strong for large negative Bz and almost disappears when Bz is positive. We found that the larger amplitude of negative SYM-H the lower solar wind pressure is required for GMCs. We attribute this effect to a depletion of the dayside magnetic field by a storm-time intensification of t...
A THERMODYNAMIC MODEL TO PREDICT WAX FORMATION IN PETROLEUM FLUIDS
Coutinho J.A.P.; Pauly J.; Daridon J.L.
2001-01-01
Some years ago the authors proposed a model for the non-ideality of the solid phase, based on the Predictive Local Composition concept. This was first applied to the Wilson equation and latter extended to NRTL and UNIQUAC models. Predictive UNIQUAC proved to be extraordinarily successful in predicting the behaviour of both model and real hydrocarbon fluids at low temperatures. This work illustrates the ability of Predictive UNIQUAC in the description of the low temperature behaviour of petrol...
Modeling and simulation of charge collection properties for 3D-trench electrode detector
Energy Technology Data Exchange (ETDEWEB)
Ding, Hao; Chen, Jianwei [School of Materials Science and Engineering, Xiangtan University, Xiangtan 411105 (China); Center for Semiconductor Particle and photon Imaging Detector Development and Fabrication, Xiangtan University, Xiangtan 411105 (China); Li, Zheng, E-mail: zhengli58@gmail.com [School of Materials Science and Engineering, Xiangtan University, Xiangtan 411105 (China); Center for Semiconductor Particle and photon Imaging Detector Development and Fabrication, Xiangtan University, Xiangtan 411105 (China); Brookhaven National Laboratory, Upton, NY (United States); Yan, Shaoan [School of Materials Science and Engineering, Xiangtan University, Xiangtan 411105 (China); Center for Semiconductor Particle and photon Imaging Detector Development and Fabrication, Xiangtan University, Xiangtan 411105 (China)
2015-10-01
3D-trench electrode detectors were simulated in this paper. Charge collection of 3D-trench electrode detector was simulated using the full 3D device simulation. The induced current and collected charge caused by drifting carriers, generated by a minimum ionizing particle (MIP) incident through the detector, have been modeled and calculated. The results indicate that the total collected charge in irradiated detector change with particle incident position and radiation fluence. In addition, we have estimated the average total collected charge generated by a MIP incident in 3D-trench electrode detector.
Xiong, Binyu; Zhao, Jiyun; Wei, Zhongbao; Skyllas-Kazacos, Maria
2014-09-01
State of charge (SOC) estimation is a key issue for battery management since an accurate estimation method can ensure safe operation and prevent the over-charge/discharge of a battery. Traditionally, open circuit voltage (OCV) method is utilized to estimate the stack SOC and one open flow cell is needed in each battery stack [1,2]. In this paper, an alternative method, extended Kalman filter (EKF) method, is proposed for SOC estimation for VRBs. By measuring the stack terminal voltages and applied currents, SOC can be predicted with a state estimator instead of an additional open circuit flow cell. To implement EKF estimator, an electrical model is required for battery analysis. A thermal-dependent electrical circuit model is proposed to describe the charge/discharge characteristics of the VRB. Two scenarios are tested for the robustness of the EKF. For the lab testing scenarios, the filtered stack voltage tracks the experimental data despite the model errors. For the online operation, the simulated temperature rise is observed and the maximum SOC error is within 5.5%. It is concluded that EKF method is capable of accurately predicting SOC using stack terminal voltages and applied currents in the absence of an open flow cell for OCV measurement.
Modelling Inductive Charging of Battery Electric Vehicles using an Agent-Based Approach
Directory of Open Access Journals (Sweden)
Zain Ul Abedin
2014-09-01
Full Text Available The introduction of battery electric vehicles (BEVs could help to reduce dependence on fossil fuels and emissions from transportation and as such increase energy security and foster sustainable use of energy resources. However a major barrier to the introduction of BEVs is their limited battery capacity and long charging durations. To address these issues of BEVs several solutions are proposed such as battery swapping and fast charging stations. However apart from these stationary modes of charging, recently a new mode of charging has been introduced which is called inductive charging. This allows charging of BEVs as they drive along roads without the need of plugs, using induction. But it is unclear, if and how such technology could be utilized best. In order to investigate the possible impact of the introduction of such inductive charging infrastructure, its potential and its optimal placement, a framework for simulating BEVs using a multi-agent transport simulation was used. This framework was extended by an inductive charging module and initial test runs were performed. In this paper we present the simulation results of these preliminary tests together with analysis which suggests that battery sizes of BEVs could be reduced even if inductive charging technology is implemented only at a small number of high traffic volume links. The paper also demonstrates that our model can effectively support policy and decision making for deploying inductive charging infrastructure.
Directory of Open Access Journals (Sweden)
Jing Lu
2014-11-01
Full Text Available We propose a weather prediction model in this article based on neural network and fuzzy inference system (NFIS-WPM, and then apply it to predict daily fuzzy precipitation given meteorological premises for testing. The model consists of two parts: the first part is the “fuzzy rule-based neural network”, which simulates sequential relations among fuzzy sets using artificial neural network; and the second part is the “neural fuzzy inference system”, which is based on the first part, but could learn new fuzzy rules from the previous ones according to the algorithm we proposed. NFIS-WPM (High Pro and NFIS-WPM (Ave are improved versions of this model. It is well known that the need for accurate weather prediction is apparent when considering the benefits. However, the excessive pursuit of accuracy in weather prediction makes some of the “accurate” prediction results meaningless and the numerical prediction model is often complex and time-consuming. By adapting this novel model to a precipitation prediction problem, we make the predicted outcomes of precipitation more accurate and the prediction methods simpler than by using the complex numerical forecasting model that would occupy large computation resources, be time-consuming and which has a low predictive accuracy rate. Accordingly, we achieve more accurate predictive precipitation results than by using traditional artificial neural networks that have low predictive accuracy.
Integrated DEM–CFD modeling of the contact charging of pneumatically conveyed powders
Korevaar, M.W.; Padding, J.T.; Hoef, van der M.A.; Kuipers, J.A.M.
2014-01-01
A model is proposed that incorporates contact charging (also known as triboelectric charging) of pneumatically conveyed powders in a DEM–CFD framework, which accounts for the electrostatic interactions, both between particles and between the particles and conducting walls. The simulation results rev
Models of environment and T_1 relaxation in Josephson Charge Qubits
Faoro, Lara; Bergli, Joakim; Altshuler, Boris L.; Galperin, Yuri M.
2004-01-01
A theoretical interpretation of the recent experiments of Astafiev et. al. on the T_1-relaxation rate in Josephson Charge Qubits is proposed. The experimentally observed reproducible nonmonotonic dependence of T_1 on the splitting E_J of the qubit levels suggests further specification of the previously proposed models of the background charge noise. From our point of view the most promising is the ``Andreev fluctuator'' model of the noise. In this model the fluctuator is a Cooper pair that tu...
Charge transfer along DNA molecule within Peyrard-Bishop-Holstein model
Edirisinghe, Neranjan; Apalkov, Vadym
2010-03-01
Charge transport through DNA molecule is important in many areas ranging from DNA damage repair to molecular nanowires. It is now widely accepted that a phonon mediated hopping of a charge carrier plays a major role in charge transport through DNA. In the present study we investigate system dynamics within Peyrard-Bishop-Holstein model for the charge transfer between donor and acceptor sites. We found that an escape time of a charge, trapped at the donor state of the DNA strand, is very sensitive to the initial value of H-bond stretching. This suggests importance of ensemble averaging. Moreover sharp phase transitions were observed for escape time in parameter space of transfer integrals and phonon-charge coupling constant.
Analytical estimation of effective charges at saturation in Poisson-Boltzmann cell models
Trizac, E; Bocquet, L
2003-01-01
We propose a simple approximation scheme for computing the effective charges of highly charged colloids (spherical or cylindrical with infinite length). Within non-linear Poisson-Boltzmann theory, we start from an expression for the effective charge in the infinite-dilution limit which is asymptotically valid for large salt concentrations; this result is then extended to finite colloidal concentration, approximating the salt partitioning effect which relates the salt content in the suspension to that of a dialysing reservoir. This leads to an analytical expression for the effective charge as a function of colloid volume fraction and salt concentration. These results compare favourably with the effective charges at saturation (i.e. in the limit of large bare charge) computed numerically following the standard prescription proposed by Alexander et al within the cell model.
RFI modeling and prediction approach for SATOP applications: RFI prediction models
Nguyen, Tien M.; Tran, Hien T.; Wang, Zhonghai; Coons, Amanda; Nguyen, Charles C.; Lane, Steven A.; Pham, Khanh D.; Chen, Genshe; Wang, Gang
2016-05-01
This paper describes a technical approach for the development of RFI prediction models using carrier synchronization loop when calculating Bit or Carrier SNR degradation due to interferences for (i) detecting narrow-band and wideband RFI signals, and (ii) estimating and predicting the behavior of the RFI signals. The paper presents analytical and simulation models and provides both analytical and simulation results on the performance of USB (Unified S-Band) waveforms in the presence of narrow-band and wideband RFI signals. The models presented in this paper will allow the future USB command systems to detect the RFI presence, estimate the RFI characteristics and predict the RFI behavior in real-time for accurate assessment of the impacts of RFI on the command Bit Error Rate (BER) performance. The command BER degradation model presented in this paper also allows the ground system operator to estimate the optimum transmitted SNR to maintain a required command BER level in the presence of both friendly and un-friendly RFI sources.
Dynamics of Charged Particulate Systems Modeling, Theory and Computation
Zohdi, Tarek I
2012-01-01
The objective of this monograph is to provide a concise introduction to the dynamics of systems comprised of charged small-scale particles. Flowing, small-scale, particles ("particulates'') are ubiquitous in industrial processes and in the natural sciences. Applications include electrostatic copiers, inkjet printers, powder coating machines, etc., and a variety of manufacturing processes. Due to their small-scale size, external electromagnetic fields can be utilized to manipulate and control charged particulates in industrial processes in order to achieve results that are not possible by purely mechanical means alone. A unique feature of small-scale particulate flows is that they exhibit a strong sensitivity to interparticle near-field forces, leading to nonstandard particulate dynamics, agglomeration and cluster formation, which can strongly affect manufactured product quality. This monograph also provides an introduction to the mathematically-related topic of the dynamics of swarms of interacting objects, ...
Strong approximations in a charged-polymer model
Hu, Yueyun
2009-01-01
We study the large-time behavior of the charged-polymer Hamiltonian $H_n$ of Kantor and Kardar [Bernoulli case] and Derrida, Griffiths, and Higgs [Gaussian case], using strong approximations to Brownian motion. Our results imply, among other things, that in one dimension the process $\\{H_{[nt]}\\}_{0\\le t\\le 1}$ behaves like a Brownian motion, time-changed by the intersection local-time process of an independent Brownian motion. Chung-type LILs are also discussed.
Effective models for charge transport in DNA nanowires
Gutierrez, Rafael; Cuniberti, Gianaurelio
2006-01-01
The rapid progress in the field of molecular electronics has led to an increasing interest on DNA oligomers as possible components of electronic circuits at the nanoscale. For this, however, an understanding of charge transfer and transport mechanisms in this molecule is required. Experiments show that a large number of factors may influence the electronic properties of DNA. Though full first principle approaches are the ideal tool for a theoretical characterization of the structural and elec...
Dealing with missing predictor values when applying clinical prediction models.
Janssen, K.J.; Vergouwe, Y.; Donders, A.R.T.; Harrell Jr, F.E.; Chen, Q.; Grobbee, D.E.; Moons, K.G.
2009-01-01
BACKGROUND: Prediction models combine patient characteristics and test results to predict the presence of a disease or the occurrence of an event in the future. In the event that test results (predictor) are unavailable, a strategy is needed to help users applying a prediction model to deal with suc
Filicori, Fabio; Traverso, Pier Andrea; Florian, Corrado; Borgarino, Mattia
2004-05-01
The basic features of the recently proposed Charge-Controlled Non-linear Noise (CCNN) model for the prediction of low-to-high-frequency noise up-conversion in electron devices under large-signal RF operation are synthetically presented. It is shown that the different noise generation phenomena within the device can be described by four equivalent noise sources, which are connected at the ports of a "noiseless" device model and are non-linearly controlled by the time-varying instantaneous values of the intrinsic device voltages. For the empirical identification of the voltage-controlled equivalent noise sources, different possible characterization procedures, based not only on conventional low-frequency noise data, but also on different types of noise measurements carried out under large-signal RF operating conditions are discussed. As an example of application, the measurement-based identification of the CCNN model for a GaInP heterojunction bipolar microwave transistor is presented. Preliminary validation results show that the proposed model can describe with adequate accuracy not only the low-frequency noise of the HBT, but also its phase-noise performance in a prototype VCO implemented by using the same monolithic GaAs technology.
Indian Academy of Sciences (India)
E Coniavitis; A Ferrari
2007-11-01
The minimal supersymmetric extension of the standard model (MSSM) predicts the existence of new charged and neutral Higgs bosons. The pair creation of these new particles at the multi-TeV + − compact linear collider (CLIC), followed by decays into standard model particles, were simulated along with the corresponding background. High-energy beam–beam effects such as ISR, beamstrahlung and hadronic background were included. We have investigated the possibility of using the ratio between the number of events found in various decay channels to determine the MSSM parameter tan and we have derived the corresponding statistical error from the uncertainties on the measured cross-sections and Higgs boson masses.
Energy Technology Data Exchange (ETDEWEB)
Xavier, MA; Trimboli, MS
2015-07-01
This paper introduces a novel application of model predictive control (MPC) to cell-level charging of a lithium-ion battery utilizing an equivalent circuit model of battery dynamics. The approach employs a modified form of the MPC algorithm that caters for direct feed-though signals in order to model near-instantaneous battery ohmic resistance. The implementation utilizes a 2nd-order equivalent circuit discrete-time state-space model based on actual cell parameters; the control methodology is used to compute a fast charging profile that respects input, output, and state constraints. Results show that MPC is well-suited to the dynamics of the battery control problem and further suggest significant performance improvements might be achieved by extending the result to electrochemical models. (C) 2015 Elsevier B.V. All rights reserved.
Foundation Settlement Prediction Based on a Novel NGM Model
Directory of Open Access Journals (Sweden)
Peng-Yu Chen
2014-01-01
Full Text Available Prediction of foundation or subgrade settlement is very important during engineering construction. According to the fact that there are lots of settlement-time sequences with a nonhomogeneous index trend, a novel grey forecasting model called NGM (1,1,k,c model is proposed in this paper. With an optimized whitenization differential equation, the proposed NGM (1,1,k,c model has the property of white exponential law coincidence and can predict a pure nonhomogeneous index sequence precisely. We used two case studies to verify the predictive effect of NGM (1,1,k,c model for settlement prediction. The results show that this model can achieve excellent prediction accuracy; thus, the model is quite suitable for simulation and prediction of approximate nonhomogeneous index sequence and has excellent application value in settlement prediction.
International Nuclear Information System (INIS)
HiggsBounds 2.0.0 is a computer code which tests both neutral and charged Higgs sectors of arbitrary models against the current exclusion bounds from the Higgs searches at LEP and the Tevatron. As input, it requires a selection of model predictions, such as Higgs masses, branching ratios, effective couplings and total decay widths. HiggsBounds 2.0.0 then uses the expected and observed topological cross section limits from the Higgs searches to determine whether a given parameter scenario of a model is excluded at the 95% C.L. by those searches. Version 2.0.0 represents a significant extension of the code since its first release (1.0.0). It includes now 28/53 LEP/Tevatron Higgs search analyses, compared to the 11/22 in the first release, of which many of the ones from the Tevatron are replaced by updates. As a major extension, the code allows now the predictions for (singly) charged Higgs bosons to be confronted with LEP and Tevatron searches. Furthermore, the newly included analyses contain LEP searches for neutral Higgs bosons (H) decaying invisibly or into (non flavour tagged) hadrons as well as decay-mode independent searches for neutral Higgs bosons, LEP searches via the production modes τ+τ-H and b anti bH, and Tevatron searches via t anti tH. Also, all Tevatron results presented at the ICHEP'10 are included in version 2.0.0. As physics applications of HiggsBounds 2.0.0 we study the allowed Higgs mass range for model scenarios with invisible Higgs decays and we obtain exclusion results for the scalar sector of the Randall-Sundrum model using up-to-date LEP and Tevatron direct search results. (orig.)
Energy Technology Data Exchange (ETDEWEB)
Bechtle, P.; Weiglein, G. [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany); Brein, O. [Freiburg Univ. (Germany). Physikalisches Inst.; Heinemeyer, S. [Instituto de Fisica de Cantabria (CSIC-UC), Santander (Spain); Williams, K.E. [Bonn Univ. (Germany). Bethe Center for Theoretical Physics
2011-03-15
HiggsBounds 2.0.0 is a computer code which tests both neutral and charged Higgs sectors of arbitrary models against the current exclusion bounds from the Higgs searches at LEP and the Tevatron. As input, it requires a selection of model predictions, such as Higgs masses, branching ratios, effective couplings and total decay widths. HiggsBounds 2.0.0 then uses the expected and observed topological cross section limits from the Higgs searches to determine whether a given parameter scenario of a model is excluded at the 95% C.L. by those searches. Version 2.0.0 represents a significant extension of the code since its first release (1.0.0). It includes now 28/53 LEP/Tevatron Higgs search analyses, compared to the 11/22 in the first release, of which many of the ones from the Tevatron are replaced by updates. As a major extension, the code allows now the predictions for (singly) charged Higgs bosons to be confronted with LEP and Tevatron searches. Furthermore, the newly included analyses contain LEP searches for neutral Higgs bosons (H) decaying invisibly or into (non flavour tagged) hadrons as well as decay-mode independent searches for neutral Higgs bosons, LEP searches via the production modes {tau}{sup +}{tau}{sup -}H and b anti bH, and Tevatron searches via t anti tH. Also, all Tevatron results presented at the ICHEP'10 are included in version 2.0.0. As physics applications of HiggsBounds 2.0.0 we study the allowed Higgs mass range for model scenarios with invisible Higgs decays and we obtain exclusion results for the scalar sector of the Randall-Sundrum model using up-to-date LEP and Tevatron direct search results. (orig.)
Cell survival in carbon beams - comparison of amorphous track model predictions
DEFF Research Database (Denmark)
Grzanka, L.; Greilich, S.; Korcyl, M.;
Introduction: Predictions of the radiobiological effectiveness (RBE) play an essential role in treatment planning with heavy charged particles. Amorphous track models ( [1] , [2] , also referred to as track structure models) provide currently the most suitable description of cell survival under ion...... distribution models, and gamma response models was developed. This software can be used for direct numerical comparison between the models, submodels and their parameters and experimental data. In the present paper, we look at 10%-survival data from cell lines irradiated in vitro with carbon and proton beams...... irradiation. The aim of this paper is to compare the predictions from different amorphous approaches found in the literature - more specifically the phenomenological, analytical model by Katz and co-workers [1] and a Monte-Carlo based full as implemented for example in the local effect model by Scholz et al...
Borstnik, N S Mankoc
2010-01-01
The Approach unifying spin and charges, assuming that all the internal degrees of freedom---the spin, all the charges and the families---originate in $d > (1+3)$ in only two kinds of spins (the Dirac one and the only one existing beside the Dirac one and anticommuting with the Dirac one), is offering a new way in understanding the appearance of the families and the charges (in the case of charges the similarity with the Kaluza-Klein-like theories must be emphasized). A simple starting action in $d >(1+3)$ for gauge fields (the vielbeins and the two kinds of the spin connections) and a spinor (which carries only two kinds of spins and interacts with the corresponding gauge fields) manifests after particular breaks of the starting symmetry the massless four (rather than three) families with the properties as assumed by the Standard model for the three known families, and the additional four massive families. The lowest of these additional four families is stable. A part of the starting action contributes, toget...
SAAMBE: Webserver to Predict the Charge of Binding Free Energy Caused by Amino Acids Mutations
Directory of Open Access Journals (Sweden)
Marharyta Petukh
2016-04-01
Full Text Available Predicting the effect of amino acid substitutions on protein–protein affinity (typically evaluated via the change of protein binding free energy is important for both understanding the disease-causing mechanism of missense mutations and guiding protein engineering. In addition, researchers are also interested in understanding which energy components are mostly affected by the mutation and how the mutation affects the overall structure of the corresponding protein. Here we report a webserver, the Single Amino Acid Mutation based change in Binding free Energy (SAAMBE webserver, which addresses the demand for tools for predicting the change of protein binding free energy. SAAMBE is an easy to use webserver, which only requires that a coordinate file be inputted and the user is provided with various, but easy to navigate, options. The user specifies the mutation position, wild type residue and type of mutation to be made. The server predicts the binding free energy change, the changes of the corresponding energy components and provides the energy minimized 3D structure of the wild type and mutant proteins for download. The SAAMBE protocol performance was tested by benchmarking the predictions against over 1300 experimentally determined changes of binding free energy and a Pearson correlation coefficient of 0.62 was obtained. How the predictions can be used for discriminating disease-causing from harmless mutations is discussed. The webserver can be accessed via http://compbio.clemson.edu/saambe_webserver/.
Directory of Open Access Journals (Sweden)
Yongjun Ahn
Full Text Available The charging infrastructure location problem is becoming more significant due to the extensive adoption of electric vehicles. Efficient charging station planning can solve deeply rooted problems, such as driving-range anxiety and the stagnation of new electric vehicle consumers. In the initial stage of introducing electric vehicles, the allocation of charging stations is difficult to determine due to the uncertainty of candidate sites and unidentified charging demands, which are determined by diverse variables. This paper introduces the Estimating the Required Density of EV Charging (ERDEC stations model, which is an analytical approach to estimating the optimal density of charging stations for certain urban areas, which are subsequently aggregated to city level planning. The optimal charging station's density is derived to minimize the total cost. A numerical study is conducted to obtain the correlations among the various parameters in the proposed model, such as regional parameters, technological parameters and coefficient factors. To investigate the effect of technological advances, the corresponding changes in the optimal density and total cost are also examined by various combinations of technological parameters. Daejeon city in South Korea is selected for the case study to examine the applicability of the model to real-world problems. With real taxi trajectory data, the optimal density map of charging stations is generated. These results can provide the optimal number of chargers for driving without driving-range anxiety. In the initial planning phase of installing charging infrastructure, the proposed model can be applied to a relatively extensive area to encourage the usage of electric vehicles, especially areas that lack information, such as exact candidate sites for charging stations and other data related with electric vehicles. The methods and results of this paper can serve as a planning guideline to facilitate the extensive
Ahn, Yongjun; Yeo, Hwasoo
2015-01-01
The charging infrastructure location problem is becoming more significant due to the extensive adoption of electric vehicles. Efficient charging station planning can solve deeply rooted problems, such as driving-range anxiety and the stagnation of new electric vehicle consumers. In the initial stage of introducing electric vehicles, the allocation of charging stations is difficult to determine due to the uncertainty of candidate sites and unidentified charging demands, which are determined by diverse variables. This paper introduces the Estimating the Required Density of EV Charging (ERDEC) stations model, which is an analytical approach to estimating the optimal density of charging stations for certain urban areas, which are subsequently aggregated to city level planning. The optimal charging station's density is derived to minimize the total cost. A numerical study is conducted to obtain the correlations among the various parameters in the proposed model, such as regional parameters, technological parameters and coefficient factors. To investigate the effect of technological advances, the corresponding changes in the optimal density and total cost are also examined by various combinations of technological parameters. Daejeon city in South Korea is selected for the case study to examine the applicability of the model to real-world problems. With real taxi trajectory data, the optimal density map of charging stations is generated. These results can provide the optimal number of chargers for driving without driving-range anxiety. In the initial planning phase of installing charging infrastructure, the proposed model can be applied to a relatively extensive area to encourage the usage of electric vehicles, especially areas that lack information, such as exact candidate sites for charging stations and other data related with electric vehicles. The methods and results of this paper can serve as a planning guideline to facilitate the extensive adoption of electric
Predictability in models of the atmospheric circulation.
Houtekamer, P.L.
1992-01-01
It will be clear from the above discussions that skill forecasts are still in their infancy. Operational skill predictions do not exist. One is still struggling to prove that skill predictions, at any range, have any quality at all. It is not clear what the statistics of the analysis error are. The
An online railway traffic prediction model
Kecman, P.; Goverde, R.M.P.
2013-01-01
Prediction of train positions in time and space is required for traffic control and passenger information. However, in practice only the last measured train delays are known and dispatchers must predict the arrival times of trains without adequate computer support. This paper presents a real-time to
Knapen, Luk; Kochan, Bruno; BELLEMANS, Tom; JANSSENS, Davy; Wets, Geert
2012-01-01
Electric power demand for household generated trafﬁc is estimated as a function of time and space for the region of Flanders. An activity-based model is used to predict trafﬁc demand. Electric vehicle (EV) type and charger characteristics are determined on the basis of car ownership and by assuming that EV categories market shares will be similar to the current ones for internal combustion engine vehicles (ICEV) published in government statistics. Charging opportunities at home and work locat...
Jones, Bleddyn
2015-01-01
The aim of this work is to predict relative biological effectiveness (RBE) for protons and clinically relevant heavier ions, by using a simplified semi-empirical process based on rational expectations and published experimental results using different ion species. The model input parameters are: Z (effective nuclear charge) and radiosensitivity parameters αL and βL of the control low linear energy transfer (LET) radiation. Sequential saturation processes are assumed for: (a) the position of t...
Antila, Hanne S; Salonen, Emppu
2015-04-15
The Thole induced point dipole model is combined with three different point charge fitting methods, Merz-Kollman (MK), charges from electrostatic potentials using a grid (CHELPG), and restrained electrostatic potential (RESP), and two multipole algorithms, distributed multipole analysis (DMA) and Gaussian multipole model (GMM), which can be used to describe the electrostatic potential (ESP) around molecules in molecular mechanics force fields. This is done to study how the different methods perform when intramolecular polarizability contributions are self-consistently removed from the fitting done in the force field parametrization. It is demonstrated that the polarizable versions of the partial charge models provide a good compromise between accuracy and computational efficiency in describing the ESP of small organic molecules undergoing conformational changes. For the point charge models, the inclusion of polarizability reduced the the average root mean square error of ESP over the test set by 4-10%.
Modelling surface restructuring by slow highly charged ions
International Nuclear Information System (INIS)
We theoretically investigate surface modifications on alkaline earth halides due to highly charged ion impact, focusing on recent experimental evidence for both etch pit and nano-hillock formation on CaF2 (A.S. El-Said et al., Phys. Rev. Lett. 109, (2012) 117602 [1]). We discuss mechanisms for converting the projectile potential and kinetic energies into thermal energy capable of changing the surface structure. A proof-of-principle classical molecular dynamics simulation suggests the existence of two thresholds which we associate with etch pit and nano-hillock formation in qualitative agreement with experiment
Model for charge/discharge-rate-dependent plastic flow in amorphous battery materials
Khosrownejad, S. M.; Curtin, W. A.
2016-09-01
Plastic flow is an important mechanism for relaxing stresses that develop due to swelling/shrinkage during charging/discharging of battery materials. Amorphous high-storage-capacity Li-Si has lower flow stresses than crystalline materials but there is evidence that the plastic flow stress depends on the conditions of charging and discharging, indicating important non-equilibrium aspects to the flow behavior. Here, a mechanistically-based constitutive model for rate-dependent plastic flow in amorphous materials, such as LixSi alloys, during charging and discharging is developed based on two physical concepts: (i) excess energy is stored in the material during electrochemical charging and discharging due to the inability of the amorphous material to fully relax during the charging/discharging process and (ii) this excess energy reduces the barriers for plastic flow processes and thus reduces the applied stresses necessary to cause plastic flow. The plastic flow stress is thus a competition between the time scales of charging/discharging and the time scales of glassy relaxation. The two concepts, as well as other aspects of the model, are validated using molecular simulations on a model Li-Si system. The model is applied to examine the plastic flow behavior of typical specimen geometries due to combined charging/discharging and stress history, and the results generally rationalize experimental observations.
Directory of Open Access Journals (Sweden)
Zhenpo Wang
2013-01-01
Full Text Available In order to adapt the matching and planning requirements of charging station in the electric vehicle (EV marketization application, with related layout theories of the gas stations, a location model of charging stations is established based on electricity consumption along the roads among cities. And a quantitative model of charging stations is presented based on the conversion of oil sales in a certain area. Both are combining the principle based on energy consuming equivalence substitution in process of replacing traditional vehicles with EVs. Defined data are adopted in the example analysis of two numerical case models and analyze the influence on charging station layout and quantity from the factors like the proportion of vehicle types and the EV energy consumption at the same time. The results show that the quantitative model of charging stations is reasonable and feasible. The number of EVs and the energy consumption of EVs bring more significant impact on the number of charging stations than that of vehicle type proportion, which provides a basis for decision making for charging stations construction layout in reality.
Bilevel linear programming model of charging for effluent based on price control
Institute of Scientific and Technical Information of China (English)
LI Yu-hua; LI Lei; HU Yun-quan; SHAO Hai-hong
2007-01-01
For the optimum price problem of charging for effluent, this paper analyzes the optimal Pigovian Tax and the serious information asymmetry problem existing in the application process of optimal Pigovian Tax,which is predominant in theory. Then the bilevel system optimizing decision-making theory is applied to give bilevel linear programming decision-making model of charging for effluent, in which the government (environmental protection agency) acts as the upper level decision-making unit and the polluting enterprises act as the lower level decision-making unit. To some extent, the model avoids the serious information asymmetry between the government and the polluting enterprises on charging for effluent.
Top quark forward-backward asymmetry and charge asymmetry in left-right twin Higgs model
Wang, Lei; Yang, Jin Min
2012-01-01
In order to explain the Tevatron anomaly of the top quark forward-backward asymmetry $A_{FB}^t$ in the left-right twin Higgs model, we choose to give up the lightest neutral particle of $\\hat{h}$ as a stable dark matter candidate. Then a new Yukawa interaction for $\\hat{h}$ is allowed, which contributes sizably to $A_{FB}^t$. Considering the constraints from the production rates of the top pair ($t\\bar t$) and the same-sign top pair as well as the top FCNC decay rates, we find that this model with such new Yukawa interaction can explain $A_{FB}^t$ measured at the Tevatron while satisfying the charge asymmetry $A_{C}^t$ measured at the LHC. Moreover, this model predicts a strongly correlation between $A_{C}^t$ at the LHC and $A_{FB}^t$ at the Tevatron, i.e., $A_{C}^t$ increases as $A_{FB}^t$ increases.
OPTIMIZATION OF THE HEAT TREATMENT PROCESS OF A STEEL POROUS CHARGE USING AN INTEGRATED MODELLING
Directory of Open Access Journals (Sweden)
Rafał Wyczółkowski
2014-11-01
Full Text Available The paper discusses the structure and principle of operation of programs for integrated modelling of the processes of heat treatment of porous-structure steel charges, such as long product bundles or strip or wire coils. Consideration is given to the specificity of these models in respect to porous charges. This is associated with their untypical thermal properties, which are expressed using the concept of effective thermal conductivity.
OPTIMIZATION OF THE HEAT TREATMENT PROCESS OF A STEEL POROUS CHARGE USING AN INTEGRATED MODELLING
Rafał Wyczółkowski; Agnieszka Benduch
2014-01-01
The paper discusses the structure and principle of operation of programs for integrated modelling of the processes of heat treatment of porous-structure steel charges, such as long product bundles or strip or wire coils. Consideration is given to the specificity of these models in respect to porous charges. This is associated with their untypical thermal properties, which are expressed using the concept of effective thermal conductivity.
Jagannathan, M.; Chandran, K. S. Ravi
2014-02-01
Physically-based analytical models that provide insights into the diffusion and/or interface charge transfer effects in bulk (lithiating/delithiating) electrodes are needed to truly assess the performance/limitations of electrode materials for Li-ion batteries. In this context, an analytical modeling framework is constructed here to predict the electrochemical charge-discharge characteristics during lithiation and delithiation of solid amorphous Si (a-Si) thin film electrodes. The framework includes analytical expressions that satisfy Fick's second law for Li transport and the requisite flux boundary conditions of lithiation and delithiation steps. The expressions are derived here by the method of separation of variables. They enable the determination of transient Li concentration profiles in the thin film electrode as a function of state of charge/discharge. The time-dependent electrode surface concentrations (at the electrode-electrolyte interface) obtained from these profiles were used to determine the activation overpotentials and thus, the non-equilibrium cell potentials, as a function of state of charge/discharge using Butler-Volmer kinetics. The simulated charge/discharge characteristics agreed well with the experimental data of a-Si thin film electrodes obtained at different C-rates. The model offers insights into how the charge-discharge behavior is controlled by diffusion limitation within electrode and/or the activation overpotentials at the interface. The analytical framework is also shown to predict successfully the hysteretic behavior of lithiation/delithiation voltage curves.
Predicting stroke through genetic risk functions the CHARGE risk score project
C.A. Ibrahim-Verbaas (Carla); M. Fornage (Myriam); J.C. Bis (Joshua); S.-H. Choi (Seung-Hoan); B.M. Psaty (Bruce); J.B. Meigs (James); M. Rao (Madhu); M.A. Nalls (Michael); M. Fontes (Michel); C.J. O'Donnell (Christopher); S. Kathiresan (Sekar); G.B. Ehret (Georg); C.S. Fox (Caroline); R. Malik (Rainer); C. Kubisch (Christian); R. Schmidt (Reinhold); J. Lahti (Jari); S.R. Heckbert (Susan); T. Lumley (Thomas); K.M. Rice (Kenneth); J.I. Rotter (Jerome); K.D. Taylor (Kent); A.R. Folsom (Aaron); E.A. Boerwinkle (Eric); W.D. Rosamond (Wayne); E. Shahar (Eyal); R.F. Gottesman (Rebecca); P.J. Koudstaal (Peter Jan); N. Amin (Najaf); R.G. Wieberdink (Renske); A. Dehghan (Abbas); A. Hofman (Albert); A.G. Uitterlinden (André); A.L. DeStefano (Anita); S. Debette (Stéphanie); L. Xue (Luting); A. Beiser (Alexa); P.A. Wolf (Philip); C. DeCarli (Charles); M.A. Ikram (Arfan); S. Seshadri (Sudha); T.H. Mosley (Thomas); W.T. Longstreth Jr; C.M. van Duijn (Cock); L.J. Launer (Lenore)
2014-01-01
textabstractBackground and Purpose - Beyond the Framingham Stroke Risk Score, prediction of future stroke may improve with a genetic risk score (GRS) based on single-nucleotide polymorphisms associated with stroke and its risk factors. Methods - The study includes 4 population-based cohorts with 204
Modelling and measurements of fibrinogen adsorption on positively charged microspheres
Directory of Open Access Journals (Sweden)
P. Zeliszewska
2016-02-01
Full Text Available Adsorption of fibrinogen on positively charged microspheres was theoretically and experimentally studied. The structure of monolayers and the maximum coverage were determined by applying the experimental measurements at pH = 3.5 and 9.7 for NaCl concentration in the range of 10^{-3} - 0.15 M. The maximum coverage of fibrinogen on latex particles was precisely determined by the AFM method. Unexpectedly, at pH = 3.5, where both fibrinogen molecule and the latex particles were positively charged, the maximum coverage varied between 0.9 mg m^{-2} and 1.1 mg m^{-2} for 10^{-2} and 0.15 M NaCl, respectively. On the other hand, at pH = 9.7, the maximum coverage of fibrinogen was larger, varying between 1.8 mg m^{-2} and 3.4 mg m^{-2} for 10^{-2} and 0.15 M NaCl, respectively. The experimental results were quantitatively interpreted by the numerical simulations.
Ion-UHMA: a model for simulating the dynamics of neutral and charged aerosol particles.
Energy Technology Data Exchange (ETDEWEB)
Leppae, J.; Kerminen, V.-M. (Finnish Meteorological Institute, Climate Change Research, Helsinki (Finland)); Gagne, S.; Manninen, H. E.; Nieminen, T.; Kulmala, M. (Dept. of Physics, Univ. of Helsinki (Finland)); Laakso, L. (Dept. of Physics, Univ. of Helsinki (Finland); School of Physical and Chemical Sciences, North-West Univ. Potchefstroom (South Africa)); Korhonen, H. (Univ. of Kuopio, Dept. of Physics (Finland)); Lehtinen, K. E. J. (Univ. of Kuopio, Dept. of Physics (Finland); Finnish Meteorological Institute, Kuopio Unit (Finland))
2009-07-01
A new aerosol dynamical box model, Ion-UHMA (University of Helsinki Multicomponent Aerosol model for neutral and charged particles), is introduced in this paper. The model includes basic dynamical processes (condensation, coagulation and deposition) as well as ion-aerosol attachment and ion-ion recombination. The formation of particles is treated as model input or, alternatively, the model can be coupled with an existing nucleation model. Ion-UHMA was found to be able to reproduce qualitatively the measured time evolution of the particle number size distribution, when the particle formation and growth rates as well as concentrations of particles > 20 nm in diameter were taken from measurements. The simulated charging state of freshly formed particles during a new particle formation event evolved towards charge equilibrium in line with previously-derived analytical formulae. We provided a few illustrative examples to demonstrate possible applications, to which the Ion-UHMA model could be used in the near future. (orig.)
Required Collaborative Work in Online Courses: A Predictive Modeling Approach
Smith, Marlene A.; Kellogg, Deborah L.
2015-01-01
This article describes a predictive model that assesses whether a student will have greater perceived learning in group assignments or in individual work. The model produces correct classifications 87.5% of the time. The research is notable in that it is the first in the education literature to adopt a predictive modeling methodology using data…
Model Predictive Control of a Wave Energy Converter
DEFF Research Database (Denmark)
Andersen, Palle; Pedersen, Tom Søndergård; Nielsen, Kirsten Mølgaard;
2015-01-01
In this paper reactive control and Model Predictive Control (MPC) for a Wave Energy Converter (WEC) are compared. The analysis is based on a WEC from Wave Star A/S designed as a point absorber. The model predictive controller uses wave models based on the dominating sea states combined with a mod...
A new ensemble model for short term wind power prediction
DEFF Research Database (Denmark)
Madsen, Henrik; Albu, Razvan-Daniel; Felea, Ioan;
2012-01-01
As the objective of this study, a non-linear ensemble system is used to develop a new model for predicting wind speed in short-term time scale. Short-term wind power prediction becomes an extremely important field of research for the energy sector. Regardless of the recent advancements in the re......-search of prediction models, it was observed that different models have different capabilities and also no single model is suitable under all situations. The idea behind EPS (ensemble prediction systems) is to take advantage of the unique features of each subsystem to detain diverse patterns that exist in the dataset...
From Predictive Models to Instructional Policies
Rollinson, Joseph; Brunskill, Emma
2015-01-01
At their core, Intelligent Tutoring Systems consist of a student model and a policy. The student model captures the state of the student and the policy uses the student model to individualize instruction. Policies require different properties from the student model. For example, a mastery threshold policy requires the student model to have a way…
Charge Transport in Dendrimer Melt using Multiscale Modeling Simulation
Bag, Saientan; Maiti, Prabal K
2016-01-01
In this paper we present a theoretical calculation of the charge carrier mobility in two different dendrimeric melt system (Dendritic phenyl azomethine with Triphenyl amine core and Dendritic Carbazole with Cyclic Phenylazomethine as core), which have recently been reported1 to increase the efficiency of Dye-Sensitized solar cells (DSSCs) by interface modification. Our mobility calculation, which is a combination of molecular dynamics simulation, first principles calculation and kinetic Monte Carlo simulation, leads to mobilities that are in quantitative agreement with available experimental data. We also show how the mobility depends on the dendrimer generation. Furthermore, we examine the variation of mobility with external electric field and external reorganization energy. Physical mechanisms behind observed electric field and generation dependencies of mobility are also explored.
Rational Design of Lanthanoid Single-Ion Magnets: Predictive Power of the Theoretical Models.
Baldoví, José J; Duan, Yan; Morales, Roser; Gaita-Ariño, Alejandro; Ruiz, Eliseo; Coronado, Eugenio
2016-09-12
We report two new single-ion magnets (SIMs) of a family of oxydiacetate lanthanide complexes with D3 symmetry to test the predictive capabilities of complete active space ab initio methods (CASSCF and CASPT2) and the semiempirical radial effective charge (REC) model. Comparison of the theoretical predictions of the energy levels, wave functions and magnetic properties with detailed spectroscopic and magnetic characterisation is used to critically discuss the limitations of these theoretical approaches. The need for spectroscopic information for a reliable description of the properties of lanthanide SIMs is emphasised.
Refining the committee approach and uncertainty prediction in hydrological modelling
N. Kayastha
2014-01-01
Due to the complexity of hydrological systems a single model may be unable to capture the full range of a catchment response and accurately predict the streamflows. The multi modelling approach opens up possibilities for handling such difficulties and allows improve the predictive capability of models. One of multi modelling approaches called "committee modelling" is one of the topics in part of this study. Special attention is given to the so-called “fuzzy committee” approach to hydrological...
Real-time multi-model decadal climate predictions
Smith, D.M.; Scaife, A.A.; Boer, G.J.; Caian, M.; Doblas-Reyes, F.J.; Guemas, V.; Hawkins, E.; Hazeleger, W.; Hermanson, L.; Ho, C.K.; Ishii, M.; Kharin, V.; Kimoto, M.; Kirtman, B.; Lean, J.; Matei, D.; Merryfield, W.J.; Muller, W.A.; Pohlmann, H.; Rosati, A.; Wouters, B.; Wyser, K.
2013-01-01
We present the first climate prediction of the coming decade made with multiple models, initialized with prior observations. This prediction accrues from an international activity to exchange decadal predictions in near real-time, in order to assess differences and similarities, provide a consensus
Prediction of peptide bonding affinity: kernel methods for nonlinear modeling
Bergeron, Charles; Sundling, C Matthew; Krein, Michael; Katt, Bill; Sukumar, Nagamani; Breneman, Curt M; Bennett, Kristin P
2011-01-01
This paper presents regression models obtained from a process of blind prediction of peptide binding affinity from provided descriptors for several distinct datasets as part of the 2006 Comparative Evaluation of Prediction Algorithms (COEPRA) contest. This paper finds that kernel partial least squares, a nonlinear partial least squares (PLS) algorithm, outperforms PLS, and that the incorporation of transferable atom equivalent features improves predictive capability.
Indian Academy of Sciences (India)
M E ZOMORRODIAN; M HASHEMINIA; S M ZABIHINPOUR; A MIRJALILI
2016-08-01
Inclusive momentum distributions of charged particles are measured in dijet events. Events were produced at the AMY detector with a centre of mass energy of 60 ${\\rm GeV}$. Our results were compared, on the one hand to those obtained from other $e^+ e^-$, $ep$ as well as CDF data, and on the other hand to the perturbative QCD calculations carried out in the framework of the modified leading log approximation (MLLA) and assuming local parton--hadron duality (LPHD). A fit of the shape of the distributions yields $\\scr Q_{eff} = 263 \\pm 13 {\\rm MeV}$ for the AMY data. In addition, a fit to the evolution of the peak position with dijet mass using all data from different experiments gives $\\scr Q_{eff} = 226 \\pm 18 {\\rm MeV}$. Next, αs was extracted using the shape of the distribution at the Z0 scale, with a value of 0.118 \\pm 0.013. This is consistent, within the statistical errors, with many accurate measurements. We conclude that it is the success of LPHD + MLLA that the extracted value of $\\alpha_{s}$ is correct. Possible explanations for all these features will be presented in this paper.
First-Principles Prediction of the Charge Mobility in Black Phosphorus Semiconductor Nanoribbons.
Xiao, Jin; Long, Mengqiu; Zhang, Xiaojiao; Zhang, Dan; Xu, Hui; Chan, Kwok Sum
2015-10-15
We have investigated the electronic structure and carrier mobility of monolayer black phosphorus nanoribbons (BPNRs) using density functional theory combined with Boltzmann transport method with relaxation time approximation. It is shown that the calculated ultrahigh electron mobility can even reach the order of 10(3) to 10(7) cm(2) V(-1) s(-1) at room temperature. Owing to the electron mobility being higher than the hole mobility, armchair and diagonal BPNRs behave like n-type semiconductors. Comparing with the bare BPNRs, the difference between the hole and electronic mobilities can be enhanced in ribbons with the edges terminated by H atoms. Moreover, because the hole mobility is about two orders of magnitude larger than the electron mobility, zigzag BPNRs with H termination behave like p-type semiconductors. Our results indicate that BPNRs can be considered as a new kind of nanomaterial for applications in optoelectronics, nanoelectronic devices owing to the intrinsic band gap and ultrahigh charge mobility. PMID:26722789
Galatà, A.; Mascali, D.; Neri, L.; Torrisi, G.; Celona, L.
2016-02-01
A Charge Breeder (CB) is a crucial device of an ISOL facility, allowing post-acceleration of radioactive ions: it accepts an incoming 1+ beam, then multiplying its charge with a highly charged q+ beam as an output. The overall performances of the facility (intensity and attainable final energy) critically depend on the charge breeder optimization. Experimental results collected along the years confirm that the breeding process is still not fully understood and room for improvements still exists: a new numerical approach has been therefore developed and applied to the description of a 85Rb1+ beam capture by the plasma of the 14.5 GHz PHOENIX ECR-based CB, installed at the Laboratoire de Physique Subatomique et de Cosmologie (LPSC), and adopted for the Selective Production of Exotic Species project under construction at Laboratori Nazionali di Legnaro. The results of the numerical simulations, obtained implementing a plasma-target model of increasing accuracy and different values for the plasma potential, will be described along the paper: results very well agree with the theoretical predictions and with the experimental results obtained on the LPSC test bench.
Energy Technology Data Exchange (ETDEWEB)
Galatà, A., E-mail: alessio.galata@lnl.infn.it [INFN–Laboratori Nazionali di Legnaro, Viale dell’Università 2, 35020 Legnaro, Padova (Italy); Mascali, D.; Neri, L.; Torrisi, G.; Celona, L. [INFN–Laboratori Nazionali del Sud, Via S. Sofia 62, 95123 Catania (Italy)
2016-02-15
A Charge Breeder (CB) is a crucial device of an ISOL facility, allowing post-acceleration of radioactive ions: it accepts an incoming 1+ beam, then multiplying its charge with a highly charged q+ beam as an output. The overall performances of the facility (intensity and attainable final energy) critically depend on the charge breeder optimization. Experimental results collected along the years confirm that the breeding process is still not fully understood and room for improvements still exists: a new numerical approach has been therefore developed and applied to the description of a {sup 85}Rb{sup 1+} beam capture by the plasma of the 14.5 GHz PHOENIX ECR-based CB, installed at the Laboratoire de Physique Subatomique et de Cosmologie (LPSC), and adopted for the Selective Production of Exotic Species project under construction at Laboratori Nazionali di Legnaro. The results of the numerical simulations, obtained implementing a plasma-target model of increasing accuracy and different values for the plasma potential, will be described along the paper: results very well agree with the theoretical predictions and with the experimental results obtained on the LPSC test bench.
Galatà, A; Mascali, D; Neri, L; Torrisi, G; Celona, L
2016-02-01
A Charge Breeder (CB) is a crucial device of an ISOL facility, allowing post-acceleration of radioactive ions: it accepts an incoming 1+ beam, then multiplying its charge with a highly charged q+ beam as an output. The overall performances of the facility (intensity and attainable final energy) critically depend on the charge breeder optimization. Experimental results collected along the years confirm that the breeding process is still not fully understood and room for improvements still exists: a new numerical approach has been therefore developed and applied to the description of a (85)Rb(1+) beam capture by the plasma of the 14.5 GHz PHOENIX ECR-based CB, installed at the Laboratoire de Physique Subatomique et de Cosmologie (LPSC), and adopted for the Selective Production of Exotic Species project under construction at Laboratori Nazionali di Legnaro. The results of the numerical simulations, obtained implementing a plasma-target model of increasing accuracy and different values for the plasma potential, will be described along the paper: results very well agree with the theoretical predictions and with the experimental results obtained on the LPSC test bench. PMID:26932060
Pair production of charged Higgs bosons in the left-right twin Higgs model at the ILC and LHC
Energy Technology Data Exchange (ETDEWEB)
Liu, Yao-Bei; Han, Hong-Mei [Henan Institute of Science and Technology, School of Machinery and Electricity, Xinxiang (China); Wang, Xue-Lei [Henan Normal University, College of Physics and Information Engineering, Xinxiang (China)
2008-02-15
The left-right twin Higgs (LRTH) model predicts the existence of a pair of charged Higgs bosons {phi}{sup {+-}}. In this paper, we study the production of the charged Higgs boson pair {phi}{sup {+-}} at the international linear collider (ILC) and the CERN large hadron collider (LHC). The numerical results show that the production rates are at the level of several tens fb at the ILC, and the process e{sup +}e{sup -}{yields}{phi}{sup +}{phi}{sup -} can produce adequately distinct multi-jet final states. We also discuss the charged Higgs boson pair production via the process qq{yields}{phi}{sup +}{phi}{sup -} at the LHC and estimate in this case the production rates. We find that, as long as the charged Higgs bosons are not too heavy, they can be abundantly produced at the LHC. The possible signatures of these new particles might be detected at the ILC and LHC experiments. (orig.)
Electrical charging effects on the sliding friction of a model nano-confined ionic liquid
Energy Technology Data Exchange (ETDEWEB)
Capozza, R.; Vanossi, A. [International School for Advanced Studies (SISSA), Via Bonomea 265, 34136 Trieste (Italy); CNR-IOM Democritos National Simulation Center, Via Bonomea 265, 34136 Trieste (Italy); Benassi, A. [CNR-IOM Democritos National Simulation Center, Via Bonomea 265, 34136 Trieste (Italy); Institute for Materials Science and Max Bergmann Center of Biomaterials, TU Dresden, 01062 Dresden (Germany); Tosatti, E. [International School for Advanced Studies (SISSA), Via Bonomea 265, 34136 Trieste (Italy); CNR-IOM Democritos National Simulation Center, Via Bonomea 265, 34136 Trieste (Italy); International Centre for Theoretical Physics (ICTP), Strada Costiera 11, 34014 Trieste (Italy)
2015-10-14
Recent measurements suggest the possibility to exploit ionic liquids (ILs) as smart lubricants for nano-contacts, tuning their tribological and rheological properties by charging the sliding interfaces. Following our earlier theoretical study of charging effects on nanoscale confinement and squeezout of a model IL, we present here molecular dynamics simulations of the frictional and lubrication properties of that model under charging conditions. First, we describe the case when two equally charged plates slide while being held together to a confinement distance of a few molecular layers. The shear sliding stress is found to rise strongly and discontinuously as the number of IL layers decreases stepwise. However, the shear stress shows, within each given number of layers, only a weak dependence upon the precise value of the normal load, a result in agreement with data extracted from recent experiments. We subsequently describe the case of opposite charging of the sliding plates and follow the shear stress when the charging is slowly and adiabatically reversed in the course of time, under fixed load. Despite the fixed load, the number and structure of the confined IL layers change with changing charge, and that in turn drives strong friction variations. The latter involves first of all charging-induced freezing of the IL film, followed by a discharging-induced melting, both made possible by the nanoscale confinement. Another mechanism for charging-induced frictional changes is a shift of the plane of maximum shear from mid-film to the plate-film interface, and vice versa. While these occurrences and results invariably depend upon the parameters of the model IL and upon its specific interaction with the plates, the present study helps identifying a variety of possible behavior, obtained under very simple assumptions, while connecting it to an underlying equilibrium thermodynamics picture.
Electrical charging effects on the sliding friction of a model nano-confined ionic liquid
International Nuclear Information System (INIS)
Recent measurements suggest the possibility to exploit ionic liquids (ILs) as smart lubricants for nano-contacts, tuning their tribological and rheological properties by charging the sliding interfaces. Following our earlier theoretical study of charging effects on nanoscale confinement and squeezout of a model IL, we present here molecular dynamics simulations of the frictional and lubrication properties of that model under charging conditions. First, we describe the case when two equally charged plates slide while being held together to a confinement distance of a few molecular layers. The shear sliding stress is found to rise strongly and discontinuously as the number of IL layers decreases stepwise. However, the shear stress shows, within each given number of layers, only a weak dependence upon the precise value of the normal load, a result in agreement with data extracted from recent experiments. We subsequently describe the case of opposite charging of the sliding plates and follow the shear stress when the charging is slowly and adiabatically reversed in the course of time, under fixed load. Despite the fixed load, the number and structure of the confined IL layers change with changing charge, and that in turn drives strong friction variations. The latter involves first of all charging-induced freezing of the IL film, followed by a discharging-induced melting, both made possible by the nanoscale confinement. Another mechanism for charging-induced frictional changes is a shift of the plane of maximum shear from mid-film to the plate-film interface, and vice versa. While these occurrences and results invariably depend upon the parameters of the model IL and upon its specific interaction with the plates, the present study helps identifying a variety of possible behavior, obtained under very simple assumptions, while connecting it to an underlying equilibrium thermodynamics picture
Grey Smoothing Model for Predicting Mine Gas Emission
Institute of Scientific and Technical Information of China (English)
潘结南; 孟召平; 刘亚川
2003-01-01
A grey smoothing model for predicting mine gas emission was presented by combining the grey system theory with the smoothing prediction technique. First of all, according to the variable sequence, GM(1,1) model was set up to predict the general development trend of variable as first fitted values, then the smoothing prediction technique was used to revise the fitted values so as to improve the accuracy of prediction. The results of application in the No.6 Coal Mine in Pingdingshan mining area show that the grey smoothing model has higher accuracy than that of GM(1,1) in predicting the variable sequence with strong fluctuation. The research provides a new scientific method for predicting mine gas emission.
Ab initio charge-carrier mobility model for amorphous molecular semiconductors
Massé, Andrea; Friederich, Pascal; Symalla, Franz; Liu, Feilong; Nitsche, Robert; Coehoorn, Reinder; Wenzel, Wolfgang; Bobbert, Peter A.
2016-05-01
Accurate charge-carrier mobility models of amorphous organic molecular semiconductors are essential to describe the electrical properties of devices based on these materials. The disordered nature of these semiconductors leads to percolative charge transport with a large characteristic length scale, posing a challenge to the development of such models from ab initio simulations. Here, we develop an ab initio mobility model using a four-step procedure. First, the amorphous morphology together with its energy disorder and intermolecular charge-transfer integrals are obtained from ab initio simulations in a small box. Next, the ab initio information is used to set up a stochastic model for the morphology and transfer integrals. This stochastic model is then employed to generate a large simulation box with modeled morphology and transfer integrals, which can fully capture the percolative charge transport. Finally, the charge-carrier mobility in this simulation box is calculated by solving a master equation, yielding a mobility function depending on temperature, carrier concentration, and electric field. We demonstrate the procedure for hole transport in two important molecular semiconductors, α -NPD and TCTA. In contrast to a previous study, we conclude that spatial correlations in the energy disorder are unimportant for α -NPD. We apply our mobility model to two types of hole-only α -NPD devices and find that the experimental temperature-dependent current density-voltage characteristics of all devices can be well described by only slightly decreasing the simulated energy disorder strength.
Predictive modeling and reducing cyclic variability in autoignition engines
Energy Technology Data Exchange (ETDEWEB)
Hellstrom, Erik; Stefanopoulou, Anna; Jiang, Li; Larimore, Jacob
2016-08-30
Methods and systems are provided for controlling a vehicle engine to reduce cycle-to-cycle combustion variation. A predictive model is applied to predict cycle-to-cycle combustion behavior of an engine based on observed engine performance variables. Conditions are identified, based on the predicted cycle-to-cycle combustion behavior, that indicate high cycle-to-cycle combustion variation. Corrective measures are then applied to prevent the predicted high cycle-to-cycle combustion variation.
Predicting Historical Droughts in the US With a Multi-model Seasonal Hydrologic Prediction System
Luo, L.; Wood, E.; Sheffield, J.; Li, H.
2008-12-01
Droughts are as much a part of weather and climate extremes as floods, hurricanes and tornadoes are, but they are the most costly extremes among all natural disasters in the U.S. The estimated annual direct losses to the U.S economy due to droughts are about 6-8 billion, with the drought of 1988 estimated to have damages over $39 billion. Having a seasonal drought prediction system that can accurately predict the onset, development and recovery of drought episodes will significantly help to reduce the loss due to drought. In this study, a seasonal hydrologic ensemble prediction system developed for the eastern United States is used to predict historical droughts in the US retrospectively. The system uses a hydrologic model (i.e., the Variable Infiltration Capacity model) as the central element for producing ensemble predictions of soil moisture, snow, and streamflow with lead times up to six months. One unique feature of this system is in the method for generating ensemble atmospheric forcings for the forecast period. It merges seasonal climate forecasts from multiple climate models with observed climatology in a Bayesian framework, such that the uncertainties related to the atmospheric forcings can be better quantified while the signals from individual models are combined. Simultaneously, climate model forecasts are downscaled to an appropriate spatial scale for hydrologic predictions. When generating daily meteorological forcing, the system uses the rank structures of selected historical forcing records to ensure reasonable weather patterns in space and time. The system is applied to different regions in the US to predict historical drought episodes. These forecasts use seasonal climate forecast from a combination of the NCEP CFS and seven climate models in the European Union's Development of a European Multimodel Ensemble System for Seasonal to-Interannual Prediction (CFS+DEMETER). This study validates the approach of using seasonal climate predictions from
Shell-model calculations for A=18 nuclei with a finite charge-dependent potential
Energy Technology Data Exchange (ETDEWEB)
Deka, A.K.; Mahanta, P.
1976-05-01
Shell-model calculations of T = 1 isospin states of A = 18 nuclei have been performed with a realistic, finite, and charge-dependent potential. The charge dependence is found to influence the reduced integrals calculated by using the separation method and the reference spectrum method. The two-body matrix elements and the energy levels show good agreement with the results of other realistic potentials, particularly with those of the Hamada-Johnston potential. An estimate of the charge dependence of the potential is also made and compared with similar results. (AIP)
Estimating Model Prediction Error: Should You Treat Predictions as Fixed or Random?
Wallach, Daniel; Thorburn, Peter; Asseng, Senthold; Challinor, Andrew J.; Ewert, Frank; Jones, James W.; Rotter, Reimund; Ruane, Alexander
2016-01-01
Crop models are important tools for impact assessment of climate change, as well as for exploring management options under current climate. It is essential to evaluate the uncertainty associated with predictions of these models. We compare two criteria of prediction error; MSEP fixed, which evaluates mean squared error of prediction for a model with fixed structure, parameters and inputs, and MSEP uncertain( X), which evaluates mean squared error averaged over the distributions of model structure, inputs and parameters. Comparison of model outputs with data can be used to estimate the former. The latter has a squared bias term, which can be estimated using hindcasts, and a model variance term, which can be estimated from a simulation experiment. The separate contributions to MSEP uncertain (X) can be estimated using a random effects ANOVA. It is argued that MSEP uncertain (X) is the more informative uncertainty criterion, because it is specific to each prediction situation.
Predicting Career Advancement with Structural Equation Modelling
Heimler, Ronald; Rosenberg, Stuart; Morote, Elsa-Sofia
2012-01-01
Purpose: The purpose of this paper is to use the authors' prior findings concerning basic employability skills in order to determine which skills best predict career advancement potential. Design/methodology/approach: Utilizing survey responses of human resource managers, the employability skills showing the largest relationships to career…
Sugioka, Hideyuki
2015-10-01
Transient space charge phenomena at high step voltages are interesting since they play a central role in many exotic nonequilibrium phenomena of ion dynamics in an electrolyte. However, the fundamental equations [i.e., the nonsteady Poisson-Nernst-Planck (PNP) equations] have not been solved analytically at high applied voltages because of their large nonlinearity. In this study, on the basis of the steady PNP solution, we propose an electrical circuit model that considers transient space charge effects and find that the dc and ac responses of the total charge of the electrical double layer are in fairly good agreement with the numerical results even at large applied voltages. Furthermore, on the basis of this model, we find approximate analytical solutions for the nonsteady PNP equations that are in good agreement with the numerical solutions of the concentration, charge density, and potential distribution at high applied voltages at each time in a surface region.
Gandhi, K. S.
2015-03-01
Electrical resistance of both the electrodes of a lead-acid battery increases during discharge due to formation of lead sulfate, an insulator. Work of Metzendorf [1] shows that resistance increases sharply at about 65% conversion of active materials, and battery stops discharging once this critical conversion is reached. However, these aspects are not incorporated into existing mathematical models. Present work uses the results of Metzendorf [1], and develops a model that includes the effect of variable resistance. Further, it uses a reasonable expression to account for the decrease in active area during discharge instead of the empirical equations of previous work. The model's predictions are compared with observations of Cugnet et al. [2]. The model is as successful as the non-mechanistic models existing in literature. Inclusion of variation in resistance of electrodes in the model is important if one of the electrodes is a limiting reactant. If active materials are stoichiometrically balanced, resistance of electrodes can be very large at the end of discharge but has only a minor effect on charging of batteries. The model points to the significance of electrical conductivity of electrodes in the charging of deep discharged batteries.
Modeling of homogeneous charge compression ignition (HCCI) of methane
Energy Technology Data Exchange (ETDEWEB)
Smith, J.R.; Aceves, S.M.; Westbrook, C.; Pitz, W.
1997-05-01
The operation of piston engines on a compression ignition cycle using a lean, homogeneous charge has many potential attractive features. These include the potential for extremely low NO{sub x} and particulate emissions while maintaining high thermal efficiency and not requiring the expensive high pressure injection system of the typical modem diesel engine. Using the HCT chemical kinetics code to simulate autoignition of methane-air mixtures, we have explored the ignition timing, burn duration, NO{sub x} production, indicated efficiency and power output of an engine with a compression ratio of 15:1 at 1200 and 2400 rpm. HCT was modified to include the effects of heat transfer. This study used a single control volume reaction zone that varies as a function of crank angle. The ignition process is controlled by varying the intake equivalence ratio and varying the residual gas trapping (RGT). RGT is internal exhaust gas recirculation which recycles both heat and combustion product species. It is accomplished by varying the timing of the exhaust valve closure. Inlet manifold temperature was held constant at 330 Kelvins. Results show that there is a narrow range of operational conditions that show promise of achieving the control necessary to vary power output while keeping indicated efficiency above 50% and NO{sub x} levels below 100 ppm.
Investigation on penetration model of shaped charge jet in water
Shi, Jinwei; Luo, Xingbai; Li, Jinming; Jiang, Jianwei
2016-01-01
To analyze the process of jet penetration in water medium quantitatively, the properties of jet penetration spaced target with water interlayer were studied through test and numerical simulation. Two theoretical models of jet penetration in water were proposed. The theoretical model 1 was established considering the impact of the shock wave, combined with the shock equation Rankine-Hugoniot and the virtual origin calculation method. The theoretical model 2 was obtained by fitting theoretical analysis and numerical simulation results. The effectiveness and universality of the two theoretical models were compared through the numerical simulation results. Both the models can reflect the relationship between the penetration velocity and the penetration distance in water well, and both the deviation and stability of theoretical model 1 are better than 2, the lower penetration velocity, and the larger deviation of the theoretical model 2. Therefore, the theoretical model 1 can reflect the properties of jet penetration in water effectively, and provide the reference of model simulation and theoretical research.
A model to predict the power output from wind farms
Energy Technology Data Exchange (ETDEWEB)
Landberg, L. [Riso National Lab., Roskilde (Denmark)
1997-12-31
This paper will describe a model that can predict the power output from wind farms. To give examples of input the model is applied to a wind farm in Texas. The predictions are generated from forecasts from the NGM model of NCEP. These predictions are made valid at individual sites (wind farms) by applying a matrix calculated by the sub-models of WASP (Wind Atlas Application and Analysis Program). The actual wind farm production is calculated using the Riso PARK model. Because of the preliminary nature of the results, they will not be given. However, similar results from Europe will be given.
A Prediction Model of the Capillary Pressure J-Function
Xu, W. S.; Luo, P. Y.; Sun, L.; Lin, N.
2016-01-01
The capillary pressure J-function is a dimensionless measure of the capillary pressure of a fluid in a porous medium. The function was derived based on a capillary bundle model. However, the dependence of the J-function on the saturation Sw is not well understood. A prediction model for it is presented based on capillary pressure model, and the J-function prediction model is a power function instead of an exponential or polynomial function. Relative permeability is calculated with the J-function prediction model, resulting in an easier calculation and results that are more representative. PMID:27603701
Intelligent predictive model of ventilating capacity of imperial smelt furnace
Institute of Scientific and Technical Information of China (English)
唐朝晖; 胡燕瑜; 桂卫华; 吴敏
2003-01-01
In order to know the ventilating capacity of imperial smelt furnace (ISF), and increase the output of plumbum, an intelligent modeling method based on gray theory and artificial neural networks(ANN) is proposed, in which the weight values in the integrated model can be adjusted automatically. An intelligent predictive model of the ventilating capacity of the ISF is established and analyzed by the method. The simulation results and industrial applications demonstrate that the predictive model is close to the real plant, the relative predictive error is 0.72%, which is 50% less than the single model, leading to a notable increase of the output of plumbum.
BEHAVE : Fire Behavior Prediction and Fuel Modeling System -- FUEL Subsystem
Burgan, Robert E; Rothermel, Richard C
1984-01-01
This manual documents the fuel modeling procedures of BEHAVE - a state-of-the-art wildland fire behavior prediction system. Described are procedures for collecting fuel data, using the data with the program, and testing and adjusting the fuel model.
Model-based uncertainty in species range prediction
DEFF Research Database (Denmark)
Pearson, R. G.; Thuiller, Wilfried; Bastos Araujo, Miguel;
2006-01-01
Aim Many attempts to predict the potential range of species rely on environmental niche (or 'bioclimate envelope') modelling, yet the effects of using different niche-based methodologies require further investigation. Here we investigate the impact that the choice of model can have on predictions......, identify key reasons why model output may differ and discuss the implications that model uncertainty has for policy-guiding applications. Location The Western Cape of South Africa. Methods We applied nine of the most widely used modelling techniques to model potential distributions under current...... and predicted future climate for four species (including two subspecies) of Proteaceae. Each model was built using an identical set of five input variables and distribution data for 3996 sampled sites. We compare model predictions by testing agreement between observed and simulated distributions for the present...
Ocean wave prediction using numerical and neural network models
Digital Repository Service at National Institute of Oceanography (India)
Mandal, S.; Prabaharan, N.
This paper presents an overview of the development of the numerical wave prediction models and recently used neural networks for ocean wave hindcasting and forecasting. The numerical wave models express the physical concepts of the phenomena...
Modelling microbial interactions and food structure in predictive microbiology
Malakar, P.K.
2002-01-01
Keywords: modelling, dynamic models, microbial interactions, diffusion, microgradients, colony growth, predictive microbiology. Growth response of microorganisms in foods is a complex process. Innovations in food production and preservation techniques have resulted in adoption of new technologies
Tzul, Franco O.; Schweiker, Katrina L.; Makhatadze, George I.
2015-01-01
Quantitative understanding of how individual interactions contribute to the kinetics and thermodynamics of protein folding is critical for deciphering the underlying molecular mechanisms that define the energy folding landscape. We applied a structure-based model that explicitly accounts for the interactions between charges, to folding–unfolding of four different protein pairs: rationally stabilized, via optimization of surface charge–charge interactions, variants, and respective wild types. ...
Solar wind charge exchange X-ray emission from Mars Model and data comparison
Koutroumpa, Dimitra; Modolo, Ronan; Chanteur, Gerard; Chaufray, Jean-Yves; Kharchenko, Vasili; Lallement, Rosine
2012-01-01
Aims. We study the soft X-ray emission induced by charge exchange (CX) collisions between solar-wind, highly charged ions and neutral atoms of the Martian exosphere. Methods. A 3D multi species hybrid simulation model with improved spatial resolution (130 km) is used to describe the interaction between the solar wind and the Martian neutrals. We calculated velocity and density distributions of the solar wind plasma in the Martian environment with realistic planetary ions description, using sp...
Adler-type sum rule, charge symmetry and neutral current in general multi-triplet model
International Nuclear Information System (INIS)
We derive Adler-type sum rule extended to general multi-triplet model. Paying attention to roles of the colour degree of freedom, we discuss the charge symmetry property of the weak charged current and the structure functions for ν(ν-)+N→l(l-)+X, and also the structure of the neutral current. A comment is given on implications in our theory of Koike and Konuma's result on the neutral hadronic current. (auth.)
A stochastic-hydrodynamic model of halo formation in charged particle beams
Petroni, Nicola Cufaro; De Martino, Salvatore; De Siena, Silvio; Illuminati, Fabrizio
2003-01-01
The formation of the beam halo in charged particle accelerators is studied in the framework of a stochastic-hydrodynamic model for the collective motion of the particle beam. In such a stochastic-hydrodynamic theory the density and the phase of the charged beam obey a set of coupled nonlinear hydrodynamic equations with explicit time-reversal invariance. This leads to a linearized theory that describes the collective dynamics of the beam in terms of a classical Schr\\"odinger equation. Taking ...
Mondal, Anirban; Balasubramanian, Sundaram
2014-03-27
Quantitative prediction of physical properties of room temperature ionic liquids through nonpolarizable force field based molecular dynamics simulations is a challenging task. The challenge lies in the fact that mean ion charges in the condensed phase can be less than unity due to polarization and charge transfer effects whose magnitude cannot be fully captured through quantum chemical calculations conducted in the gas phase. The present work employed the density-derived electrostatic and chemical (DDEC/c3) charge partitioning method to calculate site charges of ions using electronic charge densities obtained from periodic density functional theory (DFT) calculations of their crystalline phases. The total ion charges obtained thus range between -0.6e for chloride and -0.8e for the PF6 ion. The mean value of the ion charges obtained from DFT calculations of an ionic liquid closely matches that obtained from the corresponding crystal thus confirming the suitability of using crystal site charges in simulations of liquids. These partial charges were deployed within the well-established force field developed by Lopes et al., and consequently, parameters of its nonbonded and torsional interactions were refined to ensure that they reproduced quantum potential energy scans for ion pairs in the gas phase. The refined force field was employed in simulations of seven ionic liquids with six different anions. Nearly quantitative agreement with experimental measurements was obtained for the density, surface tension, enthalpy of vaporization, and ion diffusion coefficients. PMID:24605817
Model selection and paradoxes of prediction (in Russian)
Oleg Itskhoki
2006-01-01
In this essay we postulate a number of theoretical hypotheses allowing one to resolve in some degree the following two prediction paradoxes: (1) why simple linear models often have an advantage in predictive power over more complex nonlinear models that lead to a better in-sample fit; (2) why combinations of forecasts often increase the predictive power of individual forecasts. We also give a numerical example illustrating our theoretical statements.
Depletion models can predict shorebird distribution at different spatial scales.
Gill, J. A.; Sutherland, W. J.; Norris, K.
2001-01-01
Predicting the impact of habitat change on populations requires an understanding of the number of animals that a given area can support. Depletion models enable predictions of the numbers of individuals an area can support from prey density and predator searching efficiency and handling time. Depletion models have been successfully employed to predict patterns of abundance over small spatial scales, but most environmental change occurs over large spatial scales. We test the ability of depleti...
Prediction Model of Sewing Technical Condition by Grey Neural Network
Institute of Scientific and Technical Information of China (English)
DONG Ying; FANG Fang; ZHANG Wei-yuan
2007-01-01
The grey system theory and the artificial neural network technology were applied to predict the sewing technical condition. The representative parameters, such as needle, stitch, were selected. Prediction model was established based on the different fabrics' mechanical properties that measured by KES instrument. Grey relevant degree analysis was applied to choose the input parameters of the neural network. The result showed that prediction model has good precision. The average relative error was 4.08% for needle and 4.25% for stitch.
Comparison of Simple Versus Performance-Based Fall Prediction Models
Directory of Open Access Journals (Sweden)
Shekhar K. Gadkaree BS
2015-05-01
Full Text Available Objective: To compare the predictive ability of standard falls prediction models based on physical performance assessments with more parsimonious prediction models based on self-reported data. Design: We developed a series of fall prediction models progressing in complexity and compared area under the receiver operating characteristic curve (AUC across models. Setting: National Health and Aging Trends Study (NHATS, which surveyed a nationally representative sample of Medicare enrollees (age ≥65 at baseline (Round 1: 2011-2012 and 1-year follow-up (Round 2: 2012-2013. Participants: In all, 6,056 community-dwelling individuals participated in Rounds 1 and 2 of NHATS. Measurements: Primary outcomes were 1-year incidence of “any fall” and “recurrent falls.” Prediction models were compared and validated in development and validation sets, respectively. Results: A prediction model that included demographic information, self-reported problems with balance and coordination, and previous fall history was the most parsimonious model that optimized AUC for both any fall (AUC = 0.69, 95% confidence interval [CI] = [0.67, 0.71] and recurrent falls (AUC = 0.77, 95% CI = [0.74, 0.79] in the development set. Physical performance testing provided a marginal additional predictive value. Conclusion: A simple clinical prediction model that does not include physical performance testing could facilitate routine, widespread falls risk screening in the ambulatory care setting.
Refining the Committee Approach and Uncertainty Prediction in Hydrological Modelling
Kayastha, N.
2014-01-01
Due to the complexity of hydrological systems a single model may be unable to capture the full range of a catchment response and accurately predict the streamflows. The multi modelling approach opens up possibilities for handling such difficulties and allows improve the predictive capability of mode
Refining the committee approach and uncertainty prediction in hydrological modelling
Kayastha, N.
2014-01-01
Due to the complexity of hydrological systems a single model may be unable to capture the full range of a catchment response and accurately predict the streamflows. The multi modelling approach opens up possibilities for handling such difficulties and allows improve the predictive capability of mode
Bayesian variable order Markov models: Towards Bayesian predictive state representations
C. Dimitrakakis
2009-01-01
We present a Bayesian variable order Markov model that shares many similarities with predictive state representations. The resulting models are compact and much easier to specify and learn than classical predictive state representations. Moreover, we show that they significantly outperform a more st
Verification of FAC prediction model in pipe wall thinning prediction software 'FALSET'
International Nuclear Information System (INIS)
Flow accelerated corrosion (FAC) and liquid droplet impingement erosion (LDI) are the main pipe wall thinning phenomena in piping system of power plants. At present, the management is based on thinning rate and residual lifetime evaluation using pipe wall thickness measurement results. For future improvement of the management, introduction of domestic prediction code is expected. Yoneda et al. have developed original prediction software for pipe wall thinning 'FALSET', which is one-dimensional prediction for maximum thinning rate in each element in pipelines by simplifying their prediction models for local thinning rate of FAC/LDI. In this study, FAC prediction model in FALSET was verified with FAC data in domestic PWR secondary system, and prediction accuracy at present was discussed. (author)
A Model Coupling Method for Shape Prediction
Institute of Scientific and Technical Information of China (English)
WANG Dong-cheng; LIU Hong-min
2012-01-01
The shape of strip is calculated by iterative method which combines strip plastic deformation model with rolls elastic deformation model through their calculation results, which can be called results coupling method. Be- cause the shape and rolling force distribution are very sensitive to strip thickness transverse distribution% variation, the iterative course is rather unstable and sometimes convergence cannot be achieved. In addition, the calculating speed of results coupling method is low, which restricts its usable range. To solve the problem, a new model cou- pling method is developed, which takes the force distribution between rolls, rolling force distribution and strip＇s exit transverse displacement distribution as basic unknowns, and integrates strip plastic deformation model and rolls elas- tic deformation model as a unified linear equations through their internal relation, so the iterative calculation between the strip plastic deformation model and rolls elastic deformation model can be avoided. To prove the effectiveness of the model coupling method, two examples are calculated by results coupling method and model coupling method re- spectively. The results of front tension stress, back tension stress, strip~s exit gauge, the force between rolls and rolling force distribution calculated by model coupling method coincide very well with results coupling method. How- ever the calculation course of model coupling method is more steady than results coupling method, and its calculating speed is about ten times as much as the maximal speed of results coupling method, which validates its practicability and reliability.
Modelling charge transport lengths in heterojunction solar cells
Musselman, K. P.; Ievskaya, Y.; MacManus-Driscoll, J. L.
2012-12-01
A drift-diffusion model is used to estimate the minority carrier transport length and depletion width in heterojunction solar cells from measured external quantum efficiency (EQE) data. The model is applied to Cu2O-ZnO heterojunctions synthesized by electrodeposition and thermal oxidation, and the electron drift and diffusion lengths are estimated: Ldrift ≈ 110 nm for electrodeposited Cu2O and Ldrift ≈ 2790 nm and Ldiff ≈ 310 nm for thermally oxidized Cu2O. Better fitting of EQE data is obtained than with traditional models that neglect recombination in the depletion region.
Predictive model of cationic surfactant binding to humic substances
Ishiguro, M.; Koopal, L.K.
2011-01-01
The humic substances (HS) have a high reactivity with other components in the natural environment. An important factor for the reactivity of HS is their negative charge. Cationic surfactants bind strongly to HS by electrostatic and specific interaction. Therefore, a surfactant binding model is devel
Three-loop Neutrino Mass Model with Doubly Charged Particles from Iso-Doublets
Okada, Hiroshi
2016-01-01
We propose a new type of a three-loop induced neutrino mass model with dark matter candidates which are required for the neutrino mass generation. The smallness of neutrino masses can be naturally explained without introducing super heavy particles, namely, much heavier than a TeV scale and quite small couplings as compared to the gauge couplings. We find that as a bonus, the anomaly of the muon anomalous magnetic moment can simultaneously be explained by loop effects of new particles. In our model, there are doubly charged scalar bosons and leptons from isospin doublet fields which give characteristic collider signatures. In particular, the doubly charged scalar bosons can decay into the same sign dilepton with its chirality of both right-handed or left- and right-handed. This can be a smoking gun signature to identify our model and be useful to distinguish other models with doubly charged scalar bosons at collider experiments.
Three-loop neutrino mass model with doubly charged particles from isodoublets
Okada, Hiroshi; Yagyu, Kei
2016-01-01
We propose a new type of a three-loop induced neutrino mass model with dark matter candidates which are required for the neutrino mass generation. The smallness of neutrino masses can be naturally explained without introducing super heavy particles, namely, much heavier than a TeV scale and quite small couplings as compared to the gauge couplings. We find that as a bonus, the anomaly of the muon anomalous magnetic moment can simultaneously be explained by loop effects of new particles. In our model, there are doubly charged scalar bosons and leptons from isospin doublet fields which give characteristic collider signatures. In particular, the doubly charged scalar bosons can decay into the same-sign dilepton with its chirality of both right-handed or left- and right-handed. This can be a smoking gun signature to identify our model and be useful to distinguish other models with doubly charged scalar bosons at collider experiments.
Computational models of an inductive power transfer system for electric vehicle battery charge
Anele, A. O.; Hamam, Y.; Chassagne, L.; Linares, J.; Alayli, Y.; Djouani, K.
2015-09-01
One of the issues to be solved for electric vehicles (EVs) to become a success is the technical solution of its charging system. In this paper, computational models of an inductive power transfer (IPT) system for EV battery charge are presented. Based on the fundamental principles behind IPT systems, 3 kW single phase and 22 kW three phase IPT systems for Renault ZOE are designed in MATLAB/Simulink. The results obtained based on the technical specifications of the lithium-ion battery and charger type of Renault ZOE show that the models are able to provide the total voltage required by the battery. Also, considering the charging time for each IPT model, they are capable of delivering the electricity needed to power the ZOE. In conclusion, this study shows that the designed computational IPT models may be employed as a support structure needed to effectively power any viable EV.
A new model for spherically symmetric charged compact stars of embedding class one
Maurya, S K; Ray, Saibal; Deb, Debabrata
2016-01-01
In the present study we search for a new stellar model with spherically symmetric matter and charged distribution under the general relativistic framework. The model represents a compact star of embedding class one. The solutions obtain here are general in their nature having the following two features: firstly, the metric becomes flat and also the expressions for the pressure, energy density and electric charge become zero in all the cases if we consider the constant $A=0$, which shows that our solutions represent the so-called `electromagnetic mass models'~\\cite{Lorentz1904}, and secondly, the metric function $\
Scalar potential without cubic term in 3-3-1 models without exotic electric charges
Energy Technology Data Exchange (ETDEWEB)
Giraldo, Yithsbey [Universidad de Narino, Departamento de Fisica, A.A. 1175, Pasto (Colombia); Universidad de Antioquia, Instituto de Fisica, A.A. 1226, Medellin (Colombia); Ponce, William A. [Universidad de Antioquia, Instituto de Fisica, A.A. 1226, Medellin (Colombia)
2011-07-15
A detailed study of the criteria for stability of the scalar potential, and the proper electroweak symmetry breaking pattern in some 3-3-1 models without exotic electric charges is presented. In this paper we concentrate in a scalar sector with three Higgs scalar triplets, with a potential that does not include the cubic term, due to the presence of a discrete symmetry. For the analysis we use, and improve, a method previously developed to study the scalar potential in the two-Higgs-doublet extension of the standard model. Our main result is to show the consistency of those 3-3-1 models without exotic electric charges. (orig.)
Minow, Joseph I.
2011-01-01
Internal charging is a risk to spacecraft in energetic electron environments. DICTAT, NU MIT computational codes are the most widely used engineering tools for evaluating internal charging of insulator materials exposed to these environments. Engineering tools are designed for rapid evaluation of ESD threats, but there is a need for more physics based models for investigating the science of materials interactions with energetic electron environments. Current tools are limited by the physics included in the models and ease of user implementation .... additional development work is needed to improve models.
MULTI MODEL DATA MINING APPROACH FOR HEART FAILURE PREDICTION
Directory of Open Access Journals (Sweden)
Priyanka H U
2016-09-01
Full Text Available Developing predictive modelling solutions for risk estimation is extremely challenging in health-care informatics. Risk estimation involves integration of heterogeneous clinical sources having different representation from different health-care provider making the task increasingly complex. Such sources are typically voluminous, diverse, and significantly change over the time. Therefore, distributed and parallel computing tools collectively termed big data tools are in need which can synthesize and assist the physician to make right clinical decisions. In this work we propose multi-model predictive architecture, a novel approach for combining the predictive ability of multiple models for better prediction accuracy. We demonstrate the effectiveness and efficiency of the proposed work on data from Framingham Heart study. Results show that the proposed multi-model predictive architecture is able to provide better accuracy than best model approach. By modelling the error of predictive models we are able to choose sub set of models which yields accurate results. More information was modelled into system by multi-level mining which has resulted in enhanced predictive accuracy.
Electrical models of excitation-contraction coupling and charge movement in skeletal muscle.
Mathias, R T; Levis, R A; Eisenberg, R S
1980-07-01
The consequences of ionic current flow from the T system to the sarcoplasmic reticulum (SR) of skeletal muscle are examined. The Appendix analyzes a simple model in which the conductance gx, linking T system and SR, is in series with a parallel resistor and capacitor having fixed values. The conductance gx is supposed to increase rapidly with depolarization and to decrease slowly with repolarization. Nonlinear transient currents computed from this model have some of the properties of gating currents produced by intramembrane charge movement. In particular, the integral of the transient current upon depolarization approximates that upon repolarization. Thus, equality of nonlinear charge movement can occur without intramembrane charge movement. A more complicated model is used in the text to fit the structure of skeletal muscle and other properties of its charge movement. Rectification is introduced into gx and the membrane conductance of the terminal cisternae to give asymmetry in the time-course of the transient currents and saturation in the curve relating charge movement to depolarization, respectively. The more complex model fits experimental data quite well if the longitudinal tubules of the sarcoplasmic reticulum are isolated from the terminal cisternae by a substantial resistance and if calcium release from the terminal cisternae is, for the most part, electrically silent. Specific experimental tests of the model are proposed, and the implications for excitation-contraction coupling are discussed.
Gaussian mixture models as flux prediction method for central receivers
Grobler, Annemarie; Gauché, Paul; Smit, Willie
2016-05-01
Flux prediction methods are crucial to the design and operation of central receiver systems. Current methods such as the circular and elliptical (bivariate) Gaussian prediction methods are often used in field layout design and aiming strategies. For experimental or small central receiver systems, the flux profile of a single heliostat often deviates significantly from the circular and elliptical Gaussian models. Therefore a novel method of flux prediction was developed by incorporating the fitting of Gaussian mixture models onto flux profiles produced by flux measurement or ray tracing. A method was also developed to predict the Gaussian mixture model parameters of a single heliostat for a given time using image processing. Recording the predicted parameters in a database ensures that more accurate predictions are made in a shorter time frame.
Application of Nonlinear Predictive Control Based on RBF Network Predictive Model in MCFC Plant
Institute of Scientific and Technical Information of China (English)
CHEN Yue-hua; CAO Guang-yi; ZHU Xin-jian
2007-01-01
This paper described a nonlinear model predictive controller for regulating a molten carbonate fuel cell (MCFC). A detailed mechanism model of output voltage of a MCFC was presented at first. However, this model was too complicated to be used in a control system. Consequently, an off line radial basis function (RBF) network was introduced to build a nonlinear predictive model. And then, the optimal control sequences were obtained by applying golden mean method. The models and controller have been realized in the MATLAB environment. Simulation results indicate the proposed algorithm exhibits satisfying control effect even when the current densities vary largely.
Kloet, S.K.; Walczak, A.P.; Louisse, J.; Berg, H.H.J. van den; Bouwmeester, H.; Tromp, P.; Fokkink, R.G.; Rietjens, I.M.C.M.
2015-01-01
To obtain insight in translocation of nanoparticles across the placental barrier, translocation was studied for one positively and two negatively charged polystyrene nanoparticles (PS-NPs) of similar size in an in vitro model. The model consisted of BeWo b30 cells, derived from a human choriocarcino
A spectroscopic charge pumping model in spice for the low dimensional MOSFET's
Kahouadji, M.; Djahli, F.
2002-01-01
We have simulated the experimental spectroscopic charge pumping technique by the implementation of a model in the electrical simulator SPICE3F4. This model takes into account the temperature effect on the geometrical and electrical parameters of the studied transistor. The simulated results are in a good agreement with recent and different experimental results.
Lakhno, V D; Sultanov, V B
2007-01-01
In the framework of the earlier developed combined hopping-superexchange mechanism of charge transfer in DNA, a model with all nearest interactions between nucleobases is proposed. It is shown that the transfer rates for various types of nucleotide sequences calculated within this model are in a good agreement with experimental data.
Monte Carlo Shell Model Mass Predictions
International Nuclear Information System (INIS)
The nuclear mass calculation is discussed in terms of large-scale shell model calculations. First, the development and limitations of the conventional shell model calculations are mentioned. In order to overcome the limitations, the Quantum Monte Carlo Diagonalization (QMCD) method has been proposed. The basic formulation and features of the QMCD method are presented as well as its application to the nuclear shell model, referred to as Monte Carlo Shell Model (MCSM). The MCSM provides us with a breakthrough in shell model calculations: the structure of low-lying states can be studied with realistic interactions for a nearly unlimited variety of nuclei. Thus, the MCSM can contribute significantly to the study of nuclear masses. An application to N∼20 unstable nuclei far from the β-stability line is mentioned
A burnout prediction model based around char morphology
Energy Technology Data Exchange (ETDEWEB)
T. Wu; E. Lester; M. Cloke [University of Nottingham, Nottingham (United Kingdom). Nottingham Energy and Fuel Centre
2005-07-01
Poor burnout in a coal-fired power plant has marked penalties in the form of reduced energy efficiency and elevated waste material that can not be utilized. The prediction of coal combustion behaviour in a furnace is of great significance in providing valuable information not only for process optimization but also for coal buyers in the international market. Coal combustion models have been developed that can make predictions about burnout behaviour and burnout potential. Most of these kinetic models require standard parameters such as volatile content, particle size and assumed char porosity in order to make a burnout prediction. This paper presents a new model called the Char Burnout Model (ChB) that also uses detailed information about char morphology in its prediction. The model can use data input from one of two sources. Both sources are derived from image analysis techniques. The first from individual analysis and characterization of real char types using an automated program. The second from predicted char types based on data collected during the automated image analysis of coal particles. Modelling results were compared with a different carbon burnout kinetic model and burnout data from re-firing the chars in a drop tube furnace operating at 1300{sup o}C, 5% oxygen across several residence times. An improved agreement between ChB model and DTF experimental data proved that the inclusion of char morphology in combustion models can improve model predictions. 27 refs., 4 figs., 4 tabs.
Communication: Fragment-based Hamiltonian model of electronic charge-excitation gaps and gap closure
International Nuclear Information System (INIS)
Capturing key electronic properties such as charge excitation gaps within models at or above the atomic scale presents an ongoing challenge to understanding molecular, nanoscale, and condensed phase systems. One strategy is to describe the system in terms of properties of interacting material fragments, but it is unclear how to accomplish this for charge-excitation and charge-transfer phenomena. Hamiltonian models such as the Hubbard model provide formal frameworks for analyzing gap properties but are couched purely in terms of states of electrons, rather than the states of the fragments at the scale of interest. The recently introduced Fragment Hamiltonian (FH) model uses fragments in different charge states as its building blocks, enabling a uniform, quantum-mechanical treatment that captures the charge-excitation gap. These gaps are preserved in terms of inter-fragment charge-transfer hopping integrals T and on-fragment parameters U(FH). The FH model generalizes the standard Hubbard model (a single intra-band hopping integral t and on-site repulsion U) from quantum states for electrons to quantum states for fragments. We demonstrate that even for simple two-fragment and multi-fragment systems, gap closure is enabled once T exceeds the threshold set by U(FH), thus providing new insight into the nature of metal-insulator transitions. This result is in contrast to the standard Hubbard model for 1d rings, for which Lieb and Wu proved that gap closure was impossible, regardless of the choices for t and U
Communication: Fragment-based Hamiltonian model of electronic charge-excitation gaps and gap closure
Energy Technology Data Exchange (ETDEWEB)
Valone, S. M.; Pilania, G.; Liu, X. Y. [Materials Science and Technology Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545 (United States); Allen, J. R.; Wu, T.-C.; Atlas, S. R.; Dunlap, D. H. [Department of Physics and Astronomy, University of New Mexico, Albuquerque, New Mexico 87131 (United States)
2015-11-14
Capturing key electronic properties such as charge excitation gaps within models at or above the atomic scale presents an ongoing challenge to understanding molecular, nanoscale, and condensed phase systems. One strategy is to describe the system in terms of properties of interacting material fragments, but it is unclear how to accomplish this for charge-excitation and charge-transfer phenomena. Hamiltonian models such as the Hubbard model provide formal frameworks for analyzing gap properties but are couched purely in terms of states of electrons, rather than the states of the fragments at the scale of interest. The recently introduced Fragment Hamiltonian (FH) model uses fragments in different charge states as its building blocks, enabling a uniform, quantum-mechanical treatment that captures the charge-excitation gap. These gaps are preserved in terms of inter-fragment charge-transfer hopping integrals T and on-fragment parameters U{sup (FH)}. The FH model generalizes the standard Hubbard model (a single intra-band hopping integral t and on-site repulsion U) from quantum states for electrons to quantum states for fragments. We demonstrate that even for simple two-fragment and multi-fragment systems, gap closure is enabled once T exceeds the threshold set by U{sup (FH)}, thus providing new insight into the nature of metal-insulator transitions. This result is in contrast to the standard Hubbard model for 1d rings, for which Lieb and Wu proved that gap closure was impossible, regardless of the choices for t and U.
Cold Dark Matter and Preon Model with Preonic Charge
Senju, H.
1988-06-01
In our model a weakly-interacting massive stable particle l_{S}(e) exists. It is examined whether l_{S}(e) can be a candidate of the cold dark matter in the universe. Proton decay and the baryon asymmetry in the universe are also discussed.
International Nuclear Information System (INIS)
A new way for the modelling of the charge and discharge processes in electrochemical batteries based on the use of integral equations is presented. The proposed method models the charge curves by the so called fractional or cumulative integrals of a certain objective function f(t) that must be sought. The charge figures can be easily fitted by breaking down this objective function as the addition of two different Lorentz type functions: the first one is associated to the own charge process and the second one to the overcharge process. The method allows calculating the starting voltage for overcharge as the intersection between both functions. The curve fitting of this model to different experimental charge curves, by using the Marquart algorithm, has shown very accurate results. In the case of discharge curves, two possible methods for modelling purposes are suggested, well by using the same kind of integral equations, well by the simple subtraction of an objective function f(t) from a constant value VOD. Many other aspects for the study and analysis of this method in order to improve its results in further developments are also discussed. (Author) 10 refs
Benkert, Pascal
2007-01-01
Knowledge of the three-dimensional structure of proteins is of vital importance for understanding their function and for the rational development of new drugs. Homology modelling is currently the most successful method for the prediction of the structure of a protein from its sequence. A structural model is thereby built by incorporating information from experimentally solved proteins showing an evolutionary relationship to the target protein. The accurate prediction of loop regions which fre...
Predictive Modelling of Contagious Deforestation in the Brazilian Amazon
Rosa, Isabel M. D.; Drew Purves; Carlos Souza; Ewers, Robert M.
2013-01-01
Tropical forests are diminishing in extent due primarily to the rapid expansion of agriculture, but the future magnitude and geographical distribution of future tropical deforestation is uncertain. Here, we introduce a dynamic and spatially-explicit model of deforestation that predicts the potential magnitude and spatial pattern of Amazon deforestation. Our model differs from previous models in three ways: (1) it is probabilistic and quantifies uncertainty around predictions and parameters; (...
Physical model for the prediction of pavement polishing
Do, Minh Tan; Kane, Malal; TANG, Zhen Zhong; De Larrard, François
2009-01-01
Works are presented on the development of a model predicting road skid-resistance variations. Influential phenomena are incorporated (aggregate polishing, binder removal and binder ageing due to climate) and represented by simple mathematical functions. Model parameters are obtained by fitting to data provided by laboratory tests. Experimental roads have been tracked for 4 years and data regurlarly collected from extracted cores are used to validate the model. Predictions are satisfactory and...
Model Based Predictive Control of a Fully Parallel Robot
Vivas, Oscar Andrès; Poignet, Philippe
2003-01-01
This paper deals with an efficient application of a model based predictive control in parallel machines. A receding horizon control strategy based on a simplified dynamic model is implemented. Experimental results are shown for the H4 robot, a fully parallel structure providing 3 degrees of freedom (dof) in translation and 1 dof in rotation. The model based predictive control and the commonly used computed torque control strategies are compared. The tracking performances and the robustness wi...
Chang, We-Fu; Wong, Chi-Fong; Xu, Fanrong
2016-01-01
We considered a neutrino mass generating model which employs a scalar leptoquark, $\\Delta$, and a scalar diquark, $S$. The new scalars $\\Delta$ and $S$ carry the standard model $SU(3)_c\\times SU(2)_L\\times U(1)_Y$ quantum numbers $(3,1,-1/3)$ and $(6,1,-2/3)$ respectively. The neutrino masses are generated at the two-loop level similar to that in the Zee-Babu model\\cite{Zee-Babu}. And $\\Delta/S$ plays the role of the doubly/singly charged scalar in the Zee-Babu model. With a moderate working assumption that the magnitudes of the six Yukawa couplings between $S$ and the down-type quarks are of the same order, strong connections were found between the neutrino masses and the charged lepton flavor violating(cLFV) processes. In particular, $Z\\rightarrow \\overline{l} l'$, and $l\\rightarrow l' \\gamma$ were studied and it was found that some portions of the parameter space of this model are within the reach of the planned cLFV experiments. Interesting lower bounds on the cLFV processes were predicted that $B(Z\\right...
A thermodynamic model to predict wax formation in petroleum fluids
Energy Technology Data Exchange (ETDEWEB)
Coutinho, J.A.P. [Universidade de Aveiro (Portugal). Dept. de Quimica. Centro de Investigacao em Quimica]. E-mail: jcoutinho@dq.ua.pt; Pauly, J.; Daridon, J.L. [Universite de Pau et des Pays de l' Adour, Pau (France). Lab. des Fluides Complexes
2001-12-01
Some years ago the authors proposed a model for the non-ideality of the solid phase, based on the Predictive Local Composition concept. This was first applied to the Wilson equation and latter extended to NRTL and UNIQUAC models. Predictive UNIQUAC proved to be extraordinarily successful in predicting the behaviour of both model and real hydrocarbon fluids at low temperatures. This work illustrates the ability of Predictive UNIQUAC in the description of the low temperature behaviour of petroleum fluids. It will be shown that using Predictive UNIQUAC in the description of the solid phase non-ideality a complete prediction of the low temperature behaviour of synthetic paraffin solutions, fuels and crude oils is achieved. The composition of both liquid and solid phases, the amount of crystals formed and the cloud points are predicted within the accuracy of the experimental data. The extension of Predictive UNIQUAC to high pressures, by coupling it with an EOS/G{sup E} model based on the SRK EOS used with the LCVM mixing rule, is proposed and predictions of phase envelopes for live oils are compared with experimental data. (author)
A THERMODYNAMIC MODEL TO PREDICT WAX FORMATION IN PETROLEUM FLUIDS
Directory of Open Access Journals (Sweden)
J.A.P. Coutinho
2001-12-01
Full Text Available Some years ago the authors proposed a model for the non-ideality of the solid phase, based on the Predictive Local Composition concept. This was first applied to the Wilson equation and latter extended to NRTL and UNIQUAC models. Predictive UNIQUAC proved to be extraordinarily successful in predicting the behaviour of both model and real hydrocarbon fluids at low temperatures. This work illustrates the ability of Predictive UNIQUAC in the description of the low temperature behaviour of petroleum fluids. It will be shown that using Predictive UNIQUAC in the description of the solid phase non-ideality a complete prediction of the low temperature behaviour of synthetic paraffin solutions, fuels and crude oils is achieved. The composition of both liquid and solid phases, the amount of crystals formed and the cloud points are predicted within the accuracy of the experimental data. The extension of Predictive UNIQUAC to high pressures, by coupling it with an EOS/G E model based on the SRK EOS used with the LCVM mixing rule, is proposed and predictions of phase envelopes for live oils are compared with experimental data.
Monotone models for prediction in data mining
Velikova, M.V.
2006-01-01
This dissertation studies the incorporation of monotonicity constraints as a type of domain knowledge into a data mining process. Monotonicity constraints are enforced at two stages¿data preparation and data modeling. The main contributions of the research are a novel procedure to test the degree of monotonicity of a real data set, a greedy algorithm to transform non-monotone into monotone data, and extended and novel approaches for building monotone decision models. The results from simulati...
Thermal barrier coating life prediction model development
Strangman, T. E.; Neumann, J. F.; Liu, A.
1986-01-01
Thermal barrier coatings (TBCs) for turbine airfoils in high-performance engines represent an advanced materials technology with both performance and durability benefits. The foremost TBC benefit is the reduction of heat transferred into air-cooled components, which yields performance and durability benefits. This program focuses on predicting the lives of two types of strain-tolerant and oxidation-resistant TBC systems that are produced by commercial coating suppliers to the gas turbine industry. The plasma-sprayed TBC system, composed of a low-pressure plasma-spray (LPPS) or an argon shrouded plasma-spray (ASPS) applied oxidation resistant NiCrAlY (or CoNiCrAlY) bond coating and an air-plasma-sprayed yttria (8 percent) partially stabilized zirconia insulative layer, is applied by Chromalloy, Klock, and Union Carbide. The second type of TBC is applied by the electron beam-physical vapor deposition (EB-PVD) process by Temescal.
Roy, Palas; Jha, Ajay; Dasgupta, Jyotishman
2016-01-01
The device efficiency of bulk heterojunction (BHJ) solar cells is critically dependent on the nano-morphology of the solution-processed polymer : fullerene blend. Active control on blend morphology can only emanate from a detailed understanding of solution structures during the film casting process. Here we use photoinduced charge transfer (CT) rates to probe the effective length scale of the pre-formed solution structures and their energy disorder arising from a mixture of poly(3-hexylthiophene-2,5-diyl) (P3HT) and [6,6]-phenyl-C61-butyric acid methyl ester (PCBM) in three different organic solvents. The observed solvent-dependent ultrafast biphasic rise of the transient polaron state in solution along with changes detected in the C&z.dbd;C stretching frequency of bound PCBM provides direct evidence for film-like P3HT : PCBM interfaces in solution. Using the diffusive component of the charge transfer rate, we deduce ~3-times larger functional nano-domain size in toluene than in chlorobenzene thereby correctly predicting the relative polymer nanofiber widths observed in annealed films. We thus provide first experimental evidence for the postulated polymer : fullerene : solvent ternary phase that seeds the eventual morphology in spin-cast films. Our work motivates the design of new chemical additives to tune the grain size of the evolving polymer : fullerene domains within the solution phase.The device efficiency of bulk heterojunction (BHJ) solar cells is critically dependent on the nano-morphology of the solution-processed polymer : fullerene blend. Active control on blend morphology can only emanate from a detailed understanding of solution structures during the film casting process. Here we use photoinduced charge transfer (CT) rates to probe the effective length scale of the pre-formed solution structures and their energy disorder arising from a mixture of poly(3-hexylthiophene-2,5-diyl) (P3HT) and [6,6]-phenyl-C61-butyric acid methyl ester (PCBM) in three
Predictive error analysis for a water resource management model
Gallagher, Mark; Doherty, John
2007-02-01
SummaryIn calibrating a model, a set of parameters is assigned to the model which will be employed for the making of all future predictions. If these parameters are estimated through solution of an inverse problem, formulated to be properly posed through either pre-calibration or mathematical regularisation, then solution of this inverse problem will, of necessity, lead to a simplified parameter set that omits the details of reality, while still fitting historical data acceptably well. Furthermore, estimates of parameters so obtained will be contaminated by measurement noise. Both of these phenomena will lead to errors in predictions made by the model, with the potential for error increasing with the hydraulic property detail on which the prediction depends. Integrity of model usage demands that model predictions be accompanied by some estimate of the possible errors associated with them. The present paper applies theory developed in a previous work to the analysis of predictive error associated with a real world, water resource management model. The analysis offers many challenges, including the fact that the model is a complex one that was partly calibrated by hand. Nevertheless, it is typical of models which are commonly employed as the basis for the making of important decisions, and for which such an analysis must be made. The potential errors associated with point-based and averaged water level and creek inflow predictions are examined, together with the dependence of these errors on the amount of averaging involved. Error variances associated with predictions made by the existing model are compared with "optimized error variances" that could have been obtained had calibration been undertaken in such a way as to minimize predictive error variance. The contributions by different parameter types to the overall error variance of selected predictions are also examined.
Aerodynamic Noise Prediction Using stochastic Turbulence Modeling
Directory of Open Access Journals (Sweden)
Arash Ahmadzadegan
2008-01-01
Full Text Available Amongst many approaches to determine the sound propagated from turbulent flows, hybrid methods, in which the turbulent noise source field is computed or modeled separately from the far field calculation, are frequently used. For basic estimation of sound propagation, less computationally intensive methods can be developed using stochastic models of the turbulent fluctuations (turbulent noise source field. A simple and easy to use stochastic model for generating turbulent velocity fluctuations called continuous filter white noise (CFWN model was used. This method based on the use of classical Langevian-equation to model the details of fluctuating field superimposed on averaged computed quantities. The resulting sound field due to the generated unsteady flow field was evaluated using Lighthill's acoustic analogy. Volume integral method used for evaluating the acoustic analogy. This formulation presents an advantage, as it confers the possibility to determine separately the contribution of the different integral terms and also integration regions to the radiated acoustic pressure. Our results validated by comparing the directivity and the overall sound pressure level (OSPL magnitudes with the available experimental results. Numerical results showed reasonable agreement with the experiments, both in maximum directivity and magnitude of the OSPL. This method presents a very suitable tool for the noise calculation of different engineering problems in early stages of the design process where rough estimates using cheaper methods are needed for different geometries.
Wu, Jie; Ren, Hong-Li; Zuo, Jinqing; Zhao, Chongbo; Chen, Lijuan; Li, Qiaoping
2016-09-01
This study evaluates performance of Madden-Julian oscillation (MJO) prediction in the Beijing Climate Center Atmospheric General Circulation Model (BCC_AGCM2.2). By using the real-time multivariate MJO (RMM) indices, it is shown that the MJO prediction skill of BCC_AGCM2.2 extends to about 16-17 days before the bivariate anomaly correlation coefficient drops to 0.5 and the root-mean-square error increases to the level of the climatological prediction. The prediction skill showed a seasonal dependence, with the highest skill occurring in boreal autumn, and a phase dependence with higher skill for predictions initiated from phases 2-4. The results of the MJO predictability analysis showed that the upper bounds of the prediction skill can be extended to 26 days by using a single-member estimate, and to 42 days by using the ensemble-mean estimate, which also exhibited an initial amplitude and phase dependence. The observed relationship between the MJO and the North Atlantic Oscillation was accurately reproduced by BCC_AGCM2.2 for most initial phases of the MJO, accompanied with the Rossby wave trains in the Northern Hemisphere extratropics driven by MJO convection forcing. Overall, BCC_AGCM2.2 displayed a significant ability to predict the MJO and its teleconnections without interacting with the ocean, which provided a useful tool for fully extracting the predictability source of subseasonal prediction.
Modeling and Characterization of Charged Particle Trajectories in an Oscillating Magnetic Field
Irawan, Dani; Khotimah, Siti Nurul; Latief, Fourier Dzar Eljabbar; Novitrian,
2015-01-01
A constant magnetic field has frequently been discussed and has been known that it can cause a charged particle to form interesting trajectories such as cycloid and helix in presence of electric field, but a changing magnetic field is rarely discussed. In this work, modeling and characterization of charged particle trajectories in oscillating magnetic field is reported. The modeling is performed using Euler method with speed corrector. The result shows that there are two types of trajectory patterns that will recur for every $180 n T_0$ ($n = 0, 1, 2, ..$) in increasing of magnetic field oscillation period, where $T_0$ is about $6.25\\times10^{-7}$ s.
Fuzzy chance constrained linear programming model for scrap charge optimization in steel production
DEFF Research Database (Denmark)
Rong, Aiying; Lahdelma, Risto
2008-01-01
the uncertainty based on fuzzy set theory and constrain the failure risk based on a possibility measure. Consequently, the scrap charge optimization problem is modeled as a fuzzy chance constrained linear programming problem. Since the constraints of the model mainly address the specification of the product......Optimizing the charge in secondary steel production is challenging because the chemical composition of the scrap is highly uncertain. The uncertainty can cause a considerable risk of the scrap mix failing to satisfy the composition requirements for the final product. In this paper, we represent......-based production processes....
Noncausal spatial prediction filtering based on an ARMA model
Institute of Scientific and Technical Information of China (English)
Liu Zhipeng; Chen Xiaohong; Li Jingye
2009-01-01
Conventional f-x prediction filtering methods are based on an autoregressive model. The error section is first computed as a source noise but is removed as additive noise to obtain the signal, which results in an assumption inconsistency before and after filtering. In this paper, an autoregressive, moving-average model is employed to avoid the model inconsistency. Based on the ARMA model, a noncasual prediction filter is computed and a self-deconvolved projection filter is used for estimating additive noise in order to suppress random noise. The 1-D ARMA model is also extended to the 2-D spatial domain, which is the basis for noncasual spatial prediction filtering for random noise attenuation on 3-D seismic data. Synthetic and field data processing indicate this method can suppress random noise more effectively and preserve the signal simultaneously and does much better than other conventional prediction filtering methods.
Multikernel linear mixed models for complex phenotype prediction.
Weissbrod, Omer; Geiger, Dan; Rosset, Saharon
2016-07-01
Linear mixed models (LMMs) and their extensions have recently become the method of choice in phenotype prediction for complex traits. However, LMM use to date has typically been limited by assuming simple genetic architectures. Here, we present multikernel linear mixed model (MKLMM), a predictive modeling framework that extends the standard LMM using multiple-kernel machine learning approaches. MKLMM can model genetic interactions and is particularly suitable for modeling complex local interactions between nearby variants. We additionally present MKLMM-Adapt, which automatically infers interaction types across multiple genomic regions. In an analysis of eight case-control data sets from the Wellcome Trust Case Control Consortium and more than a hundred mouse phenotypes, MKLMM-Adapt consistently outperforms competing methods in phenotype prediction. MKLMM is as computationally efficient as standard LMMs and does not require storage of genotypes, thus achieving state-of-the-art predictive power without compromising computational feasibility or genomic privacy. PMID:27302636
Performance Predictable ServiceBSP Model for Grid Computing
Institute of Scientific and Technical Information of China (English)
TONG Weiqin; MIAO Weikai
2007-01-01
This paper proposes a performance prediction model for grid computing model ServiceBSP to support developing high quality applications in grid environment. In ServiceBSP model,the agents carrying computing tasks are dispatched to the local domain of the selected computation services. By using the IP (integer program) approach, the Service Selection Agent selects the computation services with global optimized QoS (quality of service) consideration. The performance of a ServiceBSP application can be predicted according to the performance prediction model based on the QoS of the selected services. The performance prediction model can help users to analyze their applications and improve them by optimized the factors which affects the performance. The experiment shows that the Service Selection Agent can provide ServiceBSP users with satisfied QoS of applications.
Entropy-growth-based model of emotionally charged online dialogues
Sienkiewicz, Julian; Paltoglou, Georgios; Holyst, Janusz A
2012-01-01
We analyze emotionally annotated massive data from IRC (Internet Relay Chat) and model the dialogues between its participants by assuming that the driving force for the discussion is the entropy growth of emotional probability distribution. This process is claimed to be correlated to the emergence of the power-law distribution of the discussion lengths observed in the dialogues. We perform numerical simulations based on the noticed phenomenon obtaining a good agreement with the real data. Finally, we propose a method to artificially prolong the duration of the discussion that relies on the entropy of emotional probability distribution.
Predicting Footbridge Response using Stochastic Load Models
DEFF Research Database (Denmark)
Pedersen, Lars; Frier, Christian
2013-01-01
Walking parameters such as step frequency, pedestrian mass, dynamic load factor, etc. are basically stochastic, although it is quite common to adapt deterministic models for these parameters. The present paper considers a stochastic approach to modeling the action of pedestrians, but when doing so...... decisions need to be made in terms of statistical distributions of walking parameters and in terms of the parameters describing the statistical distributions. The paper explores how sensitive computations of bridge response are to some of the decisions to be made in this respect. This is useful...
Systems models for predicting radioactive waste
International Nuclear Information System (INIS)
This paper illustrates how a model can be constructed to analyze the growth of accumulated spent Light-Water-Reactor fuel using a technique from systems theory which has proved to be capable of describing with a very high degree of accuracy the growth of both human populations and railways, highways, airports, local government revenues, college enrollments and similar technologies and infrastructural elements. The coupled nonlinear equations which describe these phenomena have been treated and numerical examples are displayed. The fundamental nature of the models is found to be logistic, and there is switching at the critical points between growth regimes or phases
Hoang, M.-Q.; Le Roy, S.; Boudou, L.; Teyssedre, G.
2016-06-01
One of the difficulties in unravelling transport processes in electrically insulating materials is the fact that the response, notably charging current transients, can have mixed contributions from orientation polarization and from space charge processes. This work aims at identifying and characterizing the polarization processes in a polar polymer in the time and frequency-domains and to implement the contribution of the polarization into a charge transport model. To do so, Alternate Polarization Current (APC) and Dielectric Spectroscopy measurements have been performed on poly(ethylene naphthalene 2,6-dicarboxylate) (PEN), an aromatic polar polymer, providing information on polarization mechanisms in the time- and frequency-domain, respectively. In the frequency-domain, PEN exhibits 3 relaxation processes termed β, β* (sub-glass transitions), and α relaxations (glass transition) in increasing order of temperature. Conduction was also detected at high temperatures. Dielectric responses were treated using a simplified version of the Havriliak-Negami model (Cole-Cole (CC) model), using 3 parameters per relaxation process, these parameters being temperature dependent. The time dependent polarization obtained from the CC model is then added to a charge transport model. Simulated currents issued from the transport model implemented with the polarization are compared with the measured APCs, showing a good consistency between experiments and simulations in a situation where the response comes essentially from dipolar processes.
Yang, Hyun-Ho; Han, Chang-Hoon; Oen Lee, Jeong; Yoon, Jun-Bo
2014-06-01
As a powerful method to reduce actuation voltage in an electrostatic micro-actuator, we propose and investigate an electrostatic micro-actuator with a pre-charged series capacitor. In contrast to a conventional electrostatic actuator, the injected pre-charges into the series capacitor can freely modulate the pull-in voltage of the proposed actuator even after the completion of fabrication. The static characteristics of the proposed actuator were investigated by first developing analytical models based on a parallel-plate capacitor model. We then successfully designed and demonstrated a micro-switch with a pre-charged series capacitor. The pull-in voltage of the fabricated micro-switch was reduced from 65.4 to 0.6 V when pre-charged with 46.3 V. The on-resistance of the fabricated micro-switch was almost the same as the initial one, even when the device was pre-charged, which was demonstrated for the first time. All results from the analytical models, finite element method simulations, and measurements were in good agreement with deviations of less than 10%. This work can be favorably adapted to electrostatic micro-switches which need a low actuation voltage without noticeable degradation of performance.
Charged Polaritons with Spin 1
Directory of Open Access Journals (Sweden)
Minasyan V.
2011-04-01
Full Text Available We present a new model for metal which is based on the stimulated vibration of in- dependent charged Fermi-ions, representing as independent harmonic oscillators with natural frequencies, under action of longitudinal and transverse elastic waves. Due to application of the elastic wave-particle principle and ion-wave dualities, we predict the existence of two types of charged Polaritons with spin 1 which are induced by longitu- dinal and transverse elastic fields. As result of presented theory, at small wavenumbers, these charged polaritons represent charged phonons.
Charged Polaritons with Spin 1
Directory of Open Access Journals (Sweden)
Samoilov V.
2011-04-01
Full Text Available We present a new model for metal which is based on the stimulated vibration of independent charged Fermi-ions, representing as independent harmonic oscillators with natural frequencies, under action of longitudinal and transverse elastic waves. Due to application of the elastic wave-particle principle and ion-wave dualities, we predict the existence of two types of charged Polaritons with spin 1 which are induced by longitudinal and transverse elastic fields. As result of presented theory, at small wavenumbers, these charged polaritons represent charged phonons.
Predicting Chandra CCD Degradation with the Chandra Radiation Model
Minow, Joseph I.; Blackwell, William C.; DePasquale, Joseph M.; Grant, Catherine E.; O'Dell, Stephen L.; Plucinsky, Paul P.; Schwartz, Daniel A.; Spitzbart, Bradley D.; Wolk, Scott J.
2008-01-01
Not long after launch of the Chandra X-Ray Observatory, it was discovered that the Advanced CCD Imaging Spectrometer (ACIS) detector was rapidly degrading due to radiation. Analysis by Chandra personnel showed that this degradation was due to 10w energy protons (100 - 200 keV) that scattered down the optical path onto the focal plane. In response to this unexpected problem, the Chandra Team developed a radiation-protection program that has been used to manage the radiation damage to the CCDs. This program consists of multiple approaches - scheduled sating of the ACIS detector from the radiation environment during passage through radiation belts, real-time monitoring of space weather conditions, on-board monitoring of radiation environment levels, and the creation of a radiation environment model for use in computing proton flux and fluence at energies that damage the ACIS detector. This radiation mitigation program has been very successful. The initial precipitous increase in the CCDs' charge transfer inefficiency (CTI) resulting from proton damage has been slowed dramatically, with the front-illuminated CCDS having an increase in CTI of only 2.3% per year, allowing the ASIS detector's expected lifetime to exceed requirements. This paper concentrates on one aspect of the Chandra radiation mitigation program, the creation of the Chandra Radiation Model (CRM). Because of Chandra's highly elliptical orbit, the spacecraft spends most of its time outside of the trapped radiation belts that present the severest risks to the ACIS detector. However, there is still a proton flux environment that must be accounted for in all parts of Chandra's orbit. At the time of Chandra's launch there was no engineering model of the radiation environment that could be used in the outer regions of the spacecraft's orbit, so the CRM was developed to provide the flux environment of 100 - 200 keV protons in the outer magnetosphere, magnetosheath, and solar wind regions of geospace. This
The impact of business groups on bankruptcy prediction modeling
Dewaelheyns, Nico; Van Hulle, Cynthia
2004-01-01
The bankruptcy prediction literature generally ignores corporate ownership and assumes companies are independent economic entities. In Continental Europe this latter assumption does not hold, due to the importance of business groups. Using a sample of mostly non-quoted Belgian medium and large sized companies, we show that the predictive power of several accounting ratios that are commonly used in bankruptcy prediction models (e.g. performance, leverage, liquidity and efficiency) is different...
Numerical Modeling and Prediction of Bubbling Fluidized Beds
England, Jonas Andrew
2011-01-01
Numerical modeling and prediction techniques are used to determine pressure drop, minimum fluidization velocity and segregation for bubbling fluidized beds. The computational fluid dynamics (CFD) code Multiphase Flow with Interphase eXchange (MFIX) is used to study a two-stage reactor geometry with a binary mixture. MFIX is demonstrated to accurately predict pressure drop versus inlet gas velocity for binary mixtures. A new method is developed to predict the pressure drop versus inlet gas v...
Predicting and Modelling of Survival Data when Cox's Regression Model does not hold
DEFF Research Database (Denmark)
Scheike, Thomas H.; Zhang, Mei-Jie
2002-01-01
Aalen model; additive risk model; counting processes; competing risk; Cox regression; flexible modeling; goodness of fit; prediction of survival; survival analysis; time-varying effects......Aalen model; additive risk model; counting processes; competing risk; Cox regression; flexible modeling; goodness of fit; prediction of survival; survival analysis; time-varying effects...
A Predictive Model of High Shear Thrombus Growth.
Mehrabadi, Marmar; Casa, Lauren D C; Aidun, Cyrus K; Ku, David N
2016-08-01
The ability to predict the timescale of thrombotic occlusion in stenotic vessels may improve patient risk assessment for thrombotic events. In blood contacting devices, thrombosis predictions can lead to improved designs to minimize thrombotic risks. We have developed and validated a model of high shear thrombosis based on empirical correlations between thrombus growth and shear rate. A mathematical model was developed to predict the growth of thrombus based on the hemodynamic shear rate. The model predicts thrombus deposition based on initial geometric and fluid mechanic conditions, which are updated throughout the simulation to reflect the changing lumen dimensions. The model was validated by comparing predictions against actual thrombus growth in six separate in vitro experiments: stenotic glass capillary tubes (diameter = 345 µm) at three shear rates, the PFA-100(®) system, two microfluidic channel dimensions (heights = 300 and 82 µm), and a stenotic aortic graft (diameter = 5.5 mm). Comparison of the predicted occlusion times to experimental results shows excellent agreement. The model is also applied to a clinical angiography image to illustrate the time course of thrombosis in a stenotic carotid artery after plaque cap rupture. Our model can accurately predict thrombotic occlusion time over a wide range of hemodynamic conditions.
A Predictive Model of High Shear Thrombus Growth.
Mehrabadi, Marmar; Casa, Lauren D C; Aidun, Cyrus K; Ku, David N
2016-08-01
The ability to predict the timescale of thrombotic occlusion in stenotic vessels may improve patient risk assessment for thrombotic events. In blood contacting devices, thrombosis predictions can lead to improved designs to minimize thrombotic risks. We have developed and validated a model of high shear thrombosis based on empirical correlations between thrombus growth and shear rate. A mathematical model was developed to predict the growth of thrombus based on the hemodynamic shear rate. The model predicts thrombus deposition based on initial geometric and fluid mechanic conditions, which are updated throughout the simulation to reflect the changing lumen dimensions. The model was validated by comparing predictions against actual thrombus growth in six separate in vitro experiments: stenotic glass capillary tubes (diameter = 345 µm) at three shear rates, the PFA-100(®) system, two microfluidic channel dimensions (heights = 300 and 82 µm), and a stenotic aortic graft (diameter = 5.5 mm). Comparison of the predicted occlusion times to experimental results shows excellent agreement. The model is also applied to a clinical angiography image to illustrate the time course of thrombosis in a stenotic carotid artery after plaque cap rupture. Our model can accurately predict thrombotic occlusion time over a wide range of hemodynamic conditions. PMID:26795978
The application of modeling and prediction with MRA wavelet network
Institute of Scientific and Technical Information of China (English)
LU Shu-ping; YANG Xue-jing; ZHAO Xi-ren
2004-01-01
As there are lots of non-linear systems in the real engineering, it is very important to do more researches on the modeling and prediction of non-linear systems. Based on the multi-resolution analysis (MRA) of wavelet theory, this paper combined the wavelet theory with neural network and established a MRA wavelet network with the scaling function and wavelet function as its neurons. From the analysis in the frequency domain, the results indicated that MRA wavelet network was better than other wavelet networks in the ability of approaching to the signals. An essential research was carried out on modeling and prediction with MRA wavelet network in the non-linear system. Using the lengthwise sway data received from the experiment of ship model, a model of offline prediction was established and was applied to the short-time prediction of ship motion. The simulation results indicated that the forecasting model improved the prediction precision effectively, lengthened the forecasting time and had a better prediction results than that of AR linear model.The research indicates that it is feasible to use the MRA wavelet network in the short -time prediction of ship motion.
Monotone models for prediction in data mining
Velikova, M.V.
2006-01-01
This dissertation studies the incorporation of monotonicity constraints as a type of domain knowledge into a data mining process. Monotonicity constraints are enforced at two stages¿data preparation and data modeling. The main contributions of the research are a novel procedure to test the degree of
Prediction of mortality in very premature infants: a systematic review of prediction models.
Directory of Open Access Journals (Sweden)
Stephanie Medlock
Full Text Available CONTEXT: Being born very preterm is associated with elevated risk for neonatal mortality. The aim of this review is to give an overview of prediction models for mortality in very premature infants, assess their quality, identify important predictor variables, and provide recommendations for development of future models. METHODS: Studies were included which reported the predictive performance of a model for mortality in a very preterm or very low birth weight population, and classified as development, validation, or impact studies. For each development study, we recorded the population, variables, aim, predictive performance of the model, and the number of times each model had been validated. Reporting quality criteria and minimum methodological criteria were established and assessed for development studies. RESULTS: We identified 41 development studies and 18 validation studies. In addition to gestational age and birth weight, eight variables frequently predicted survival: being of average size for gestational age, female gender, non-white ethnicity, absence of serious congenital malformations, use of antenatal steroids, higher 5-minute Apgar score, normal temperature on admission, and better respiratory status. Twelve studies met our methodological criteria, three of which have been externally validated. Low reporting scores were seen in reporting of performance measures, internal and external validation, and handling of missing data. CONCLUSIONS: Multivariate models can predict mortality better than birth weight or gestational age alone in very preterm infants. There are validated prediction models for classification and case-mix adjustment. Additional research is needed in validation and impact studies of existing models, and in prediction of mortality in the clinically important subgroup of infants where age and weight alone give only an equivocal prognosis.
Prediction model for spring dust weather frequency in North China
Institute of Scientific and Technical Information of China (English)
2008-01-01
It is of great social and scientific importance and also very difficult to make reliable prediction for dust weather frequency (DWF) in North China. In this paper, the correlation between spring DWF in Beijing and Tianjin observation stations, taken as examples in North China, and seasonally averaged surface air temperature, precipitation, Arctic Oscillation, Antarctic Oscillation, South Oscillation, near surface meridional wind and Eurasian westerly index is respectively calculated so as to construct a prediction model for spring DWF in North China by using these climatic factors. Two prediction models, i.e. model-I and model-II, are then set up respectively based on observed climate data and the 32-year (1970 -2001) extra-seasonal hindcast experiment data as reproduced by the nine-level Atmospheric General Circulation Model developed at the Institute of Atmospheric Physics (IAP9L-AGCM). It is indicated that the correlation coefficient between the observed and predicted DWF reaches 0.933 in the model-I, suggesting a high prediction skill one season ahead. The corresponding value is high up to 0.948 for the subsequent model-II, which involves synchronous spring climate data reproduced by the IAP9L-AGCM relative to the model-I. The model-II can not only make more precise prediction but also can bring forward the lead time of real-time prediction from the model-I’s one season to half year. At last, the real-time predictability of the two models is evaluated. It follows that both the models display high prediction skill for both the interannual variation and linear trend of spring DWF in North China, and each is also featured by different advantages. As for the model-II, the prediction skill is much higher than that of original approach by use of the IAP9L-AGCM alone. Therefore, the prediction idea put forward here should be popularized in other regions in China where dust weather occurs frequently.
Prediction model for spring dust weather frequency in North China
Institute of Scientific and Technical Information of China (English)
LANG XianMei
2008-01-01
It is of great social and scientific importance and also very difficult to make reliable prediction for dust weather frequency (DWF) in North China. In this paper, the correlation between spring DWF in Beijing and Tianjin observation stations, taken as examples in North China, and seasonally averaged surface air temperature, precipitation, Arctic Oscillation, Antarctic Oscillation, South Oscillation, near surface meridional wind and Eurasian westerly index is respectively calculated so as to construct a prediction model for spring DWF in North China by using these climatic factors. Two prediction models, I.e. Model-Ⅰ and model-Ⅱ, are then set up respectively based on observed climate data and the 32-year (1970--2001) extra-seasonal hindcast experiment data as reproduced by the nine-level Atmospheric General Circulation Model developed at the Institute of Atmospheric Physics (IAP9L-AGCM). It is indicated that the correlation coefficient between the observed and predicted DWF reaches 0.933 in the model-Ⅰ, suggesting a high prediction skill one season ahead. The corresponding value is high up to 0.948 for the subsequent model-Ⅱ, which involves synchronous spring climate data reproduced by the IAP9L-AGCM relative to the model-Ⅰ. The model-Ⅱ can not only make more precise prediction but also can bring forward the lead time of real-time prediction from the model-Ⅰ's one season to half year. At last, the real-time predictability of the two models is evaluated. It follows that both the models display high prediction skill for both the interannual variation and linear trend of spring DWF in North China, and each is also featured by different advantages. As for the model-Ⅱ, the prediction skill is much higher than that of original approach by use of the IAP9L-AGCM alone. Therefore, the prediction idea put forward here should be popularized in other regions in China where dust weather occurs frequently.
Application of Wavelet Random Coupling Model in Monthly Rainfall Prediction
Institute of Scientific and Technical Information of China (English)
DONG Lili; XU Shuqin; LIU Yang; WANG Yunhe
2011-01-01
A Trous algorithm of wavelet transform was used to decompose wavelet signal, and the cross-correlation analysis was used to analyze the sequence of each wavelet transform, and then the mathematical model correspond with wavelet transform sequence was established, finally wavelet random coupling model was obtained by wavelet reconstruction algorithm. Then, according to the rainfall data in crop growth period of Farm Chahayang from 1956 to 2008, the wavelet random coupling model was established to fit the model prediction test. The results showed that the prediction and fitting accuracy of the model was high, the model could reflect the rainfall variation regulation in the region, and it was a practical prediction model. It was very important for us to determine reasonably irrigation schedule and to use efficiency coefficient of precipitation resource.
Determining Trajectory of Triboelectrically Charged Particles, Using Discrete Element Modeling
2008-01-01
The Kennedy Space Center (KSC) Electrostatics and Surface Physics Laboratory is participating in an Innovative Partnership Program (IPP) project with an industry partner to modify a commercial off-the-shelf simulation software product to treat the electrodynamics of particulate systems. Discrete element modeling (DEM) is a numerical technique that can track the dynamics of particle systems. This technique, which was introduced in 1979 for analysis of rock mechanics, was recently refined to include the contact force interaction of particles with arbitrary surfaces and moving machinery. In our work, we endeavor to incorporate electrostatic forces into the DEM calculations to enhance the fidelity of the software and its applicability to (1) particle processes, such as electrophotography, that are greatly affected by electrostatic forces, (2) grain and dust transport, and (3) the study of lunar and Martian regoliths.
A burnout prediction model based around char morphology
Energy Technology Data Exchange (ETDEWEB)
Tao Wu; Edward Lester; Michael Cloke [University of Nottingham, Nottingham (United Kingdom). School of Chemical, Environmental and Mining Engineering
2006-05-15
Several combustion models have been developed that can make predictions about coal burnout and burnout potential. Most of these kinetic models require standard parameters such as volatile content and particle size to make a burnout prediction. This article presents a new model called the char burnout (ChB) model, which also uses detailed information about char morphology in its prediction. The input data to the model is based on information derived from two different image analysis techniques. One technique generates characterization data from real char samples, and the other predicts char types based on characterization data from image analysis of coal particles. The pyrolyzed chars in this study were created in a drop tube furnace operating at 1300{sup o}C, 200 ms, and 1% oxygen. Modeling results were compared with a different carbon burnout kinetic model as well as the actual burnout data from refiring the same chars in a drop tube furnace operating at 1300{sup o}C, 5% oxygen, and residence times of 200, 400, and 600 ms. A good agreement between ChB model and experimental data indicates that the inclusion of char morphology in combustion models could well improve model predictions. 38 refs., 5 figs., 6 tabs.
A Multi-Criteria Prediction model for project Risk classifications
Laryea, Rueben
2013-01-01
Project distress predictions are essential in project management. Developing appropriate methods to classify projects and building prediction models for multicriteria decisions requires empirical methods to minimise misclassification errors. This paper carries out multicriteria analysis to classify project risks using a preference disaggregation method, UTilit.
Haskell financial data modeling and predictive analytics
Ryzhov, Pavel
2013-01-01
This book is a hands-on guide that teaches readers how to use Haskell's tools and libraries to analyze data from real-world sources in an easy-to-understand manner.This book is great for developers who are new to financial data modeling using Haskell. A basic knowledge of functional programming is not required but will be useful. An interest in high frequency finance is essential.
ANN modeling for flood prediction in the upstream Eure's catchment (France)
Kharroubi, Ouissem; masson, Eric; Blanpain, Olivier; Lallahem, Sami
2013-04-01
Rainfall-Runoff relationship at basin scale is strongly depending on the catchment complexity including multi-scale interactions. In extreme events cases (i.e. floods and droughts) this relationship is even more complex and differs from average hydrological conditions making extreme runoff prediction very difficult to achieve. However, flood warning, flood prevention and flood mitigation rely on the possibility to predict both flood peak runoff and lag time. This point is crucial for decision making and flood warning to prevent populations and economical stakes to be damaged by extreme hydrological events. Since 2003 in France, a dedicated state service is in charge of producing flood warning from national level (i.e. SCHAPI) to regional level (i.e. SPC). This flood warning service is combining national weather forecast agency (i.e. Meteo France) together with a fully automated realtime hydrological network (i.e. Rainfall-Runoff) in order to produce a flood warning national map online and provide a set of hydro-meteorological data to the SPC in charge of flood prediction from regional to local scale. The SPC is in fact the flood service delivering hydrological prediction at operational level for decision making about flood alert for municipalities and first help services. Our research in collaboration with the SPC SACN (i.e. "Seine Aval et fleuves Côtiers Normands") is focused on the implementation of an Artificial Neural Network model (ANN) for flood prediction in deferent key points of the Eure's catchment and main subcatchment. Our contribution will focus on the ANN model developed for Saint-Luperce gauging station in the upstream part of the Eure's catchment. Prediction of extreme runoff at Saint-Luperce station is of high importance for flood warning in the Eure's catchment because it gives a good indicator on the extreme status and the downstream propagation of a potential flood event. Despite a good runoff monitoring since 27 years Saint Luperce flood
Predictive Modeling for Comfortable Death Outcome Using Electronic Health Records
Lodhi, Muhammad Kamran; Ansari, Rashid; Yao, Yingwei; Keenan, Gail M.; Wilkie, Diana J.; Khokhar, Ashfaq A.
2016-01-01
Electronic health record (EHR) systems are used in healthcare industry to observe the progress of patients. With fast growth of the data, EHR data analysis has become a big data problem. Most EHRs are sparse and multi-dimensional datasets and mining them is a challenging task due to a number of reasons. In this paper, we have used a nursing EHR system to build predictive models to determine what factors impact death anxiety, a significant problem for the dying patients. Different existing modeling techniques have been used to develop coarse-grained as well as fine-grained models to predict patient outcomes. The coarse-grained models help in predicting the outcome at the end of each hospitalization, whereas fine-grained models help in predicting the outcome at the end of each shift, therefore providing a trajectory of predicted outcomes. Based on different modeling techniques, our results show significantly accurate predictions, due to relatively noise-free data. These models can help in determining effective treatments, lowering healthcare costs, and improving the quality of end-of-life (EOL) care.
Comparison of two models for bridge-assisted charge transfer
Schreiber, M; Kleinekathöfer, U
1999-01-01
Based on the reduced density matrix method, we compare two different approaches to calculate the dynamics of the electron transfer in systems with donor, bridge, and acceptor. In the first approach a vibrational substructure is taken into account for each electronic state and the corresponding states are displaced along a common reaction coordinate. In the second approach it is assumed that vibrational relaxation is much faster than the electron transfer and therefore the states are modeled by electronic levels only. In both approaches the system is coupled to a bath of harmonic oscillators but the way of relaxation is quite different. The theory is applied to the electron transfer in ${\\rm H_2P}-{\\rm ZnP}-{\\rm Q}$ with free-base porphyrin (${\\rm H_2P}$) being the donor, zinc porphyrin (${\\rm ZnP}$) being the bridge and quinone (${\\rm Q}$) the acceptor. The parameters are chosen as similar as possible for both approaches and the quality of the agreement is discussed.
Better predictions when models are wrong or underspecified
Ommen, Matthijs van
2015-01-01
Many statistical methods rely on models of reality in order to learn from data and to make predictions about future data. By necessity, these models usually do not match reality exactly, but are either wrong (none of the hypotheses in the model provides an accurate description of reality) or undersp
Basant, Nikita; Gupta, Shikha; Singh, Kunwar P
2015-11-01
In this study, we established nonlinear quantitative-structure toxicity relationship (QSTR) models for predicting the toxicities of chemical pesticides in multiple aquatic test species following the OECD (Organization for Economic Cooperation and Development) guidelines. The decision tree forest (DTF) and decision tree boost (DTB) based QSTR models were constructed using a pesticides toxicity dataset in Selenastrum capricornutum and a set of six descriptors. Other six toxicity data sets were used for external validation of the constructed QSTRs. Global QSTR models were also constructed using the combined dataset of all the seven species. The diversity in chemical structures and nonlinearity in the data were evaluated. Model validation was performed deriving several statistical coefficients for the test data and the prediction and generalization abilities of the QSTRs were evaluated. Both the QSTR models identified WPSA1 (weighted charged partial positive surface area) as the most influential descriptor. The DTF and DTB QSTRs performed relatively better than the single decision tree (SDT) and support vector machines (SVM) models used as a benchmark here and yielded R(2) of 0.886 and 0.964 between the measured and predicted toxicity values in the complete dataset (S. capricornutum). The QSTR models applied to six other aquatic species toxicity data yielded R(2) of >0.92 (DTF) and >0.97 (DTB), respectively. The prediction accuracies of the global models were comparable with those of the S. capricornutum models. The results suggest for the appropriateness of the developed QSTR models to reliably predict the aquatic toxicity of chemicals and can be used for regulatory purpose.
A Multistep Chaotic Model for Municipal Solid Waste Generation Prediction.
Song, Jingwei; He, Jiaying
2014-08-01
In this study, a univariate local chaotic model is proposed to make one-step and multistep forecasts for daily municipal solid waste (MSW) generation in Seattle, Washington. For MSW generation prediction with long history data, this forecasting model was created based on a nonlinear dynamic method called phase-space reconstruction. Compared with other nonlinear predictive models, such as artificial neural network (ANN) and partial least square-support vector machine (PLS-SVM), and a commonly used linear seasonal autoregressive integrated moving average (sARIMA) model, this method has demonstrated better prediction accuracy from 1-step ahead prediction to 14-step ahead prediction assessed by both mean absolute percentage error (MAPE) and root mean square error (RMSE). Max error, MAPE, and RMSE show that chaotic models were more reliable than the other three models. As chaotic models do not involve random walk, their performance does not vary while ANN and PLS-SVM make different forecasts in each trial. Moreover, this chaotic model was less time consuming than ANN and PLS-SVM models.
Using Pareto points for model identification in predictive toxicology.
Palczewska, Anna; Neagu, Daniel; Ridley, Mick
2013-03-22
: Predictive toxicology is concerned with the development of models that are able to predict the toxicity of chemicals. A reliable prediction of toxic effects of chemicals in living systems is highly desirable in cosmetics, drug design or food protection to speed up the process of chemical compound discovery while reducing the need for lab tests. There is an extensive literature associated with the best practice of model generation and data integration but management and automated identification of relevant models from available collections of models is still an open problem. Currently, the decision on which model should be used for a new chemical compound is left to users. This paper intends to initiate the discussion on automated model identification. We present an algorithm, based on Pareto optimality, which mines model collections and identifies a model that offers a reliable prediction for a new chemical compound. The performance of this new approach is verified for two endpoints: IGC50 and LogP. The results show a great potential for automated model identification methods in predictive toxicology.
Predictive Modeling: A New Paradigm for Managing Endometrial Cancer.
Bendifallah, Sofiane; Daraï, Emile; Ballester, Marcos
2016-03-01
With the abundance of new options in diagnostic and treatment modalities, a shift in the medical decision process for endometrial cancer (EC) has been observed. The emergence of individualized medicine and the increasing complexity of available medical data has lead to the development of several prediction models. In EC, those clinical models (algorithms, nomograms, and risk scoring systems) have been reported, especially for stratifying and subgrouping patients, with various unanswered questions regarding such things as the optimal surgical staging for lymph node metastasis as well as the assessment of recurrence and survival outcomes. In this review, we highlight existing prognostic and predictive models in EC, with a specific focus on their clinical applicability. We also discuss the methodologic aspects of the development of such predictive models and the steps that are required to integrate these tools into clinical decision making. In the future, the emerging field of molecular or biochemical markers research may substantially improve predictive and treatment approaches. PMID:26577116
A new, accurate predictive model for incident hypertension
DEFF Research Database (Denmark)
Völzke, Henry; Fung, Glenn; Ittermann, Till;
2013-01-01
Data mining represents an alternative approach to identify new predictors of multifactorial diseases. This work aimed at building an accurate predictive model for incident hypertension using data mining procedures....
On the Predictiveness of Single-Field Inflationary Models
Burgess, C P; Trott, Michael
2014-01-01
We re-examine the predictiveness of single-field inflationary models and discuss how an unknown UV completion can complicate determining inflationary model parameters from observations, even from precision measurements. Besides the usual naturalness issues associated with having a shallow inflationary potential, we describe another issue for inflation, namely, unknown UV physics modifies the running of Standard Model (SM) parameters and thereby introduces uncertainty into the potential inflationary predictions. We illustrate this point using the minimal Higgs Inflationary scenario, which is arguably the most predictive single-field model on the market, because its predictions for $A_s$, $r$ and $n_s$ are made using only one new free parameter beyond those measured in particle physics experiments, and run up to the inflationary regime. We find that this issue can already have observable effects. At the same time, this UV-parameter dependence in the Renormalization Group allows Higgs Inflation to occur (in prin...
A Composite Model Predictive Control Strategy for Furnaces
Institute of Scientific and Technical Information of China (English)
Hao Zang; Hongguang Li; Jingwen Huang; Jia Wang
2014-01-01
Tube furnaces are essential and primary energy intensive facilities in petrochemical plants. Operational optimi-zation of furnaces could not only help to improve product quality but also benefit to reduce energy consumption and exhaust emission. Inspired by this idea, this paper presents a composite model predictive control (CMPC) strategy, which, taking advantage of distributed model predictive control architectures, combines tracking nonlinear model predictive control and economic nonlinear model predictive control metrics to keep process running smoothly and optimize operational conditions. The control ers connected with two kinds of communi-cation networks are easy to organize and maintain, and stable to process interferences. A fast solution algorithm combining interior point solvers and Newton's method is accommodated to the CMPC realization, with reason-able CPU computing time and suitable online applications. Simulation for industrial case demonstrates that the proposed approach can ensure stable operations of furnaces, improve heat efficiency, and reduce the emission effectively.
Submission Form for Peer-Reviewed Cancer Risk Prediction Models
If you have information about a peer-reviewd cancer risk prediction model that you would like to be considered for inclusion on this list, submit as much information as possible through the form on this page.
Compensatory versus noncompensatory models for predicting consumer preferences
Directory of Open Access Journals (Sweden)
Anja Dieckmann
2009-04-01
Full Text Available Standard preference models in consumer research assume that people weigh and add all attributes of the available options to derive a decision, while there is growing evidence for the use of simplifying heuristics. Recently, a greedoid algorithm has been developed (Yee, Dahan, Hauser and Orlin, 2007; Kohli and Jedidi, 2007 to model lexicographic heuristics from preference data. We compare predictive accuracies of the greedoid approach and standard conjoint analysis in an online study with a rating and a ranking task. The lexicographic model derived from the greedoid algorithm was better at predicting ranking compared to rating data, but overall, it achieved lower predictive accuracy for hold-out data than the compensatory model estimated by conjoint analysis. However, a considerable minority of participants was better predicted by lexicographic strategies. We conclude that the new algorithm will not replace standard tools for analyzing preferences, but can boost the study of situational and individual differences in preferential choice processes.
Field Driven Charging Dynamics of a Fluidized Granular Bed
Yoshimatsu, R; Shinbrot, T; Herrmann, H J
2016-01-01
A simplified model has previously described the inductive charging of colliding identical grains in the presence of an external electric field. Here we extend that model by including heterogeneous surface charge distributions, grain rotations and electrostatic interactions between grains. We find from this more realistic model that strong heterogeneities in charging can occur in agitated granular beds, and we predict that shielding due to these heterogeneities can dramatically alter the charging rate in such beds.
Application of chaotic prediction model based on wavelet transform on water quality prediction
Zhang, L.; Zou, Z. H.; Zhao, Y. F.
2016-08-01
Dissolved oxygen (DO) is closely related to water self-purification capacity. In order to better forecast its concentration, the chaotic prediction model, based on the wavelet transform, is proposed and applied to a certain monitoring section of the Mentougou area of the Haihe River Basin. The result is compared with the simple application of the chaotic prediction model. The study indicates that the new model aligns better with the real data and has a higher accuracy. Therefore, it will provide significant decision support for water protection and water environment treatment.
Tollenaar, N.; Van der Heijden, P.G.M.
2013-01-01
Using criminal population criminal conviction history information, prediction models are developed that predict three types of criminal recidivism: general recidivism, violent recidivism and sexual recidivism. The research question is whether prediction techniques from modern statistics, data mining
Developing a predictive tropospheric ozone model for Tabriz
Khatibi, Rahman; Naghipour, Leila; Ghorbani, Mohammad A.; Smith, Michael S.; Karimi, Vahid; Farhoudi, Reza; Delafrouz, Hadi; Arvanaghi, Hadi
2013-04-01
Predictive ozone models are becoming indispensable tools by providing a capability for pollution alerts to serve people who are vulnerable to the risks. We have developed a tropospheric ozone prediction capability for Tabriz, Iran, by using the following five modeling strategies: three regression-type methods: Multiple Linear Regression (MLR), Artificial Neural Networks (ANNs), and Gene Expression Programming (GEP); and two auto-regression-type models: Nonlinear Local Prediction (NLP) to implement chaos theory and Auto-Regressive Integrated Moving Average (ARIMA) models. The regression-type modeling strategies explain the data in terms of: temperature, solar radiation, dew point temperature, and wind speed, by regressing present ozone values to their past values. The ozone time series are available at various time intervals, including hourly intervals, from August 2010 to March 2011. The results for MLR, ANN and GEP models are not overly good but those produced by NLP and ARIMA are promising for the establishing a forecasting capability.
Modelling microbial interactions and food structure in predictive microbiology
Malakar, P.K.
2002-01-01
Keywords: modelling, dynamic models, microbial interactions, diffusion, microgradients, colony growth, predictive microbiology. Growth response of microorganisms in foods is a complex process. Innovations in food production and preservation techniques have resulted in adoption of new technologies to ensure food quality and safety. Predictive microbiology is one such technology, where growth responses of homogenous pure broth cultures of microorganism to the environment are quantified. In t...
MACHINE LEARNING MODELS FOR PREDICTING SHELF LIFE OF PROCESSED CHEESE
Sumit, Goyal; Gyanendra, Goyal
2013-01-01
Feedforward multilayer machine learning artificial neural network (ANN) models were established for predicting shelf life of processed cheese stored at 7-8o C. Soluble nitrogen, pH, standard plate count, yeast & mould count, and spore count were input variables, and sensory score was the output variable. Mean Square Error, Root Mean Square Error, Coefficient of Determination and Nash–Sutcliffe Coefficient were used for comparing the prediction ability of the developed models. Feedforward ...
Prediction of cloud droplet number in a general circulation model
Energy Technology Data Exchange (ETDEWEB)
Ghan, S.J.; Leung, L.R. [Pacific Northwest National Lab., Richland, WA (United States)
1996-04-01
We have applied the Colorado State University Regional Atmospheric Modeling System (RAMS) bulk cloud microphysics parameterization to the treatment of stratiform clouds in the National Center for Atmospheric Research Community Climate Model (CCM2). The RAMS predicts mass concentrations of cloud water, cloud ice, rain and snow, and number concnetration of ice. We have introduced the droplet number conservation equation to predict droplet number and it`s dependence on aerosols.
ROBUST MODEL PREDICTIVE CONTROL OF CONTINUOUS UNCERTAIN SYSTEMS
Institute of Scientific and Technical Information of China (English)
Xiaohua LIU; Chunyan HAN
2008-01-01
The authors concern robust model predictive control for linear continuous systems with polytopic uncertainties and input constraints. At each sampling time, a piecewise constant control sequence is obtained by solving a set of linear matrix inequalities. The sufficient conditions on the existence of the model predictive control are given, and the robust stability of the closed-loop systems is guaranteed. A simulation example illustrates the efficiency of the proposed method.
'Bootstrap' charging of surfaces composed of multiple materials
Stannard, P. R.; Katz, I.; Parks, D. E.
1981-01-01
The paper examines the charging of a checkerboard array of two materials, only one of which tends to acquire a negative potential alone, using the NASA Charging Analyzer Program (NASCAP). The influence of the charging material's field causes the otherwise 'non-charging' material to acquire a negative potential due to the suppression of its secondary emission ('bootstrap' charging). The NASCAP predictions for the equilibrium potential difference between the two materials are compared to results based on an analytical model.
Empirical Model for Predicting Rockfall Trajectory Direction
Asteriou, Pavlos; Tsiambaos, George
2016-03-01
A methodology for the experimental investigation of rockfall in three-dimensional space is presented in this paper, aiming to assist on-going research of the complexity of a block's response to impact during a rockfall. An extended laboratory investigation was conducted, consisting of 590 tests with cubical and spherical blocks made of an artificial material. The effects of shape, slope angle and the deviation of the post-impact trajectory are examined as a function of the pre-impact trajectory direction. Additionally, an empirical model is proposed that estimates the deviation of the post-impact trajectory as a function of the pre-impact trajectory with respect to the slope surface and the slope angle. This empirical model is validated by 192 small-scale field tests, which are also presented in this paper. Some important aspects of the three-dimensional nature of rockfall phenomena are highlighted that have been hitherto neglected. The 3D space data provided in this study are suitable for the calibration and verification of rockfall analysis software that has become increasingly popular in design practice.
Residual bias in a multiphase flow model calibration and prediction
Poeter, E.P.; Johnson, R.H.
2002-01-01
When calibrated models produce biased residuals, we assume it is due to an inaccurate conceptual model and revise the model, choosing the most representative model as the one with the best-fit and least biased residuals. However, if the calibration data are biased, we may fail to identify an acceptable model or choose an incorrect model. Conceptual model revision could not eliminate biased residuals during inversion of simulated DNAPL migration under controlled conditions at the Borden Site near Ontario Canada. This paper delineates hypotheses for the source of bias, and explains the evolution of the calibration and resulting model predictions.
Numerical modeling capabilities to predict repository performance
Energy Technology Data Exchange (ETDEWEB)
1979-09-01
This report presents a summary of current numerical modeling capabilities that are applicable to the design and performance evaluation of underground repositories for the storage of nuclear waste. The report includes codes that are available in-house, within Golder Associates and Lawrence Livermore Laboratories; as well as those that are generally available within the industry and universities. The first listing of programs are in-house codes in the subject areas of hydrology, solute transport, thermal and mechanical stress analysis, and structural geology. The second listing of programs are divided by subject into the following categories: site selection, structural geology, mine structural design, mine ventilation, hydrology, and mine design/construction/operation. These programs are not specifically designed for use in the design and evaluation of an underground repository for nuclear waste; but several or most of them may be so used.
Numerical modeling capabilities to predict repository performance
International Nuclear Information System (INIS)
This report presents a summary of current numerical modeling capabilities that are applicable to the design and performance evaluation of underground repositories for the storage of nuclear waste. The report includes codes that are available in-house, within Golder Associates and Lawrence Livermore Laboratories; as well as those that are generally available within the industry and universities. The first listing of programs are in-house codes in the subject areas of hydrology, solute transport, thermal and mechanical stress analysis, and structural geology. The second listing of programs are divided by subject into the following categories: site selection, structural geology, mine structural design, mine ventilation, hydrology, and mine design/construction/operation. These programs are not specifically designed for use in the design and evaluation of an underground repository for nuclear waste; but several or most of them may be so used
Low-temperature charging of lithium-ion cells Part II: Model reduction and application
Remmlinger, Jürgen; Tippmann, Simon; Buchholz, Michael; Dietmayer, Klaus
2014-05-01
Lithium-ion cells, especially when used in electric vehicles at varying operation conditions, require a sophisticated battery management to ensure an optimal operation regarding operation limits, performance, and maximum lifetime. In some cases, the best trade-off between these conflictive goals can only be reached by considering internal, non-measurable cell characteristics. This article presents a data-driven model-reduction method for a strict electrochemical model. The model describes the charging process of a lithium-ion cell and possibly occurring degradation effects in a large temperature range and is presented in Part I of this contribution. The model-reduction process is explained in detail, and the gained model is compared to the original electrochemical model showing a very high approximation quality. This reduced model offers a very low computation complexity and is therefore suitable for the implementation in a battery management system (BMS). Based on this model, an advanced charging strategy is presented and evaluated for possible reductions in charging times especially at low temperatures.
Traffic Prediction Scheme based on Chaotic Models in Wireless Networks
Directory of Open Access Journals (Sweden)
Xiangrong Feng
2013-09-01
Full Text Available Based on the local support vector algorithm of chaotic time series analysis, the Hannan-Quinn information criterion and SAX symbolization are introduced. Then a novel prediction algorithm is proposed, which is successfully applied to the prediction of wireless network traffic. For the correct prediction problems of short-term flow with smaller data set size, the weakness of the algorithms during model construction is analyzed by study and comparison to LDK prediction algorithm. It is verified the Hannan-Quinn information principle can be used to calculate the number of neighbor points to replace pervious empirical method, which uses the number of neighbor points to acquire more accurate prediction model. Finally, actual flow data is applied to confirm the accuracy rate of the proposed algorithm LSDHQ. It is testified by our experiments that it also has higher performance in adaptability than that of LSDHQ algorithm.
A Prediction Model for Taiwan Tourism Industry Stock Index
Directory of Open Access Journals (Sweden)
Han-Chen Huang
2013-12-01
Full Text Available Investors and scholars pay continuous attention to the stock market, as each day, many investors attem pt to use different methods to predict stock price trends . However, as stock price is affected by economy, p olitics, domestic and foreign situations, emergency, human f actor, and other unknown factors, it is difficult t o establish an accurate prediction model. This study used a back-propagation neural network (BPN as the research approach, and input 29 variables, such as international exchange rate, indices of internation al stock markets, Taiwan stock market analysis indicat ors, and overall economic indicators, to predict Taiwan’s monthly tourism industry stock index. The empirical findings show that the BPN prediction mod el has better predictive accuracy, Absolute Relative E rror is 0.090058, and correlation coefficient is 0.944263. The model has low error and high correlat ion, and can serve as reference for investors and relevant industries.
Saglam, Murat
2010-01-01
This study aimed to investigate the models that co-existed in students' cognitive structure to explain the interactions between electric charges and uniform magnetic fields. The sample consisted of 129 first-year civil engineering, geology and geophysics students from a large state university in western Turkey. The students answered five…
Meucci, Andrea; Giusti, Carlotta
2014-01-01
The analysis of charged-current quasielastic neutrino and antineutrino-nucleus scattering cross sections requires relativistic theoretical descriptions also accounting for the role of final-state interactions. We compare the results of the relativistic Green's function model with the data recently published by the MINER$\
Description of light charged particle multiplicities in the framework of dinuclear system model
Directory of Open Access Journals (Sweden)
Antonenko N.V.
2012-12-01
Full Text Available In the framework of dinuclear system (DNS model we calculate the light charged particle (LCP multiplicities produced in fusion and quasifission reactions and their kinetic energy spectra. Calculations indicate that with increasing bombarding energy the ratio of LCP multiplicity from fragments MFF to corresponding LCP multiplicity from compound nucleus (CN MCN strongly increases.
Nuclear charge radii and electric monopole transitions in the interacting boson model
Van Isacker, P
2012-01-01
The interacting boson model (IBM) of Arima and Iachello is applied to calculate nuclear charge radii and electric monopole transitions of even-even nuclei in the rare-earth region. Consistent operators are used for the two observables. A relation between summed M1 strength and $\\rho({\\rm E0})$ values is pointed out.
Using a Prediction Model to Manage Cyber Security Threats.
Jaganathan, Venkatesh; Cherurveettil, Priyesh; Muthu Sivashanmugam, Premapriya
2015-01-01
Cyber-attacks are an important issue faced by all organizations. Securing information systems is critical. Organizations should be able to understand the ecosystem and predict attacks. Predicting attacks quantitatively should be part of risk management. The cost impact due to worms, viruses, or other malicious software is significant. This paper proposes a mathematical model to predict the impact of an attack based on significant factors that influence cyber security. This model also considers the environmental information required. It is generalized and can be customized to the needs of the individual organization. PMID:26065024
Using a Prediction Model to Manage Cyber Security Threats.
Jaganathan, Venkatesh; Cherurveettil, Priyesh; Muthu Sivashanmugam, Premapriya
2015-01-01
Cyber-attacks are an important issue faced by all organizations. Securing information systems is critical. Organizations should be able to understand the ecosystem and predict attacks. Predicting attacks quantitatively should be part of risk management. The cost impact due to worms, viruses, or other malicious software is significant. This paper proposes a mathematical model to predict the impact of an attack based on significant factors that influence cyber security. This model also considers the environmental information required. It is generalized and can be customized to the needs of the individual organization.
Aero-acoustic noise of wind turbines. Noise prediction models
Energy Technology Data Exchange (ETDEWEB)
Maribo Pedersen, B. [ed.
1997-12-31
Semi-empirical and CAA (Computational AeroAcoustics) noise prediction techniques are the subject of this expert meeting. The meeting presents and discusses models and methods. The meeting may provide answers to the following questions: What Noise sources are the most important? How are the sources best modeled? What needs to be done to do better predictions? Does it boil down to correct prediction of the unsteady aerodynamics around the rotor? Or is the difficult part to convert the aerodynamics into acoustics? (LN)
Comparing model predictions for ecosystem-based management
DEFF Research Database (Denmark)
Jacobsen, Nis Sand; Essington, Timothy E.; Andersen, Ken Haste
2016-01-01
Ecosystem modeling is becoming an integral part of fisheries management, but there is a need to identify differences between predictions derived from models employed for scientific and management purposes. Here, we compared two models: a biomass-based food-web model (Ecopath with Ecosim (Ew...... of forage fisheries removal. In both cases, the differences are due to the presumed degree of trophic overlap between juveniles of large-bodied fish and adult stages of forage fish. These differences highlight how each model’s emphasis on distinct details of ecological processes affects its predictions...
Model Predictive Control for an Industrial SAG Mill
DEFF Research Database (Denmark)
Ohan, Valeriu; Steinke, Florian; Metzger, Michael;
2012-01-01
We discuss Model Predictive Control (MPC) based on ARX models and a simple lower order disturbance model. The advantage of this MPC formulation is that it has few tuning parameters and is based on an ARX prediction model that can readily be identied using standard technologies from system...... identication. When applied to MIMO systems we call this controller a MIMO-ARX based MPC. We use an industrial Semi-Autogenous Grinding (SAG) mill to illustrate the performance of this controller. SAG mills are the primary units in a grinding chain and also the most power consuming units. Therefore, improved...
Predictive data modeling of human type II diabetes related statistics
Jaenisch, Kristina L.; Jaenisch, Holger M.; Handley, James W.; Albritton, Nathaniel G.
2009-04-01
During the course of routine Type II treatment of one of the authors, it was decided to derive predictive analytical Data Models of the daily sampled vital statistics: namely weight, blood pressure, and blood sugar, to determine if the covariance among the observed variables could yield a descriptive equation based model, or better still, a predictive analytical model that could forecast the expected future trend of the variables and possibly eliminate the number of finger stickings required to montior blood sugar levels. The personal history and analysis with resulting models are presented.
Research on Drag Torque Prediction Model for the Wet Clutches
Institute of Scientific and Technical Information of China (English)
无
2008-01-01
Considering the surface tension effect and centrifugal effect, a mathematical model based on Reynolds equation for predicting the drag torque of disengage wet clutches is presented. The model indicates that the equivalent radius is a function of clutch speed and flow rate. The drag torque achieves its peak at a critical speed. Above this speed, drag torque drops due to the shrinking of the oil film. The model also points out that viscosity and flow rate effects on drag torque. Experimental results indicate that the model is reasonable and it performs well for predicting the drag torque peak.
Robust Model Predictive Control of a Wind Turbine
DEFF Research Database (Denmark)
Mirzaei, Mahmood; Poulsen, Niels Kjølstad; Niemann, Hans Henrik
2012-01-01
In this work the problem of robust model predictive control (robust MPC) of a wind turbine in the full load region is considered. A minimax robust MPC approach is used to tackle the problem. Nonlinear dynamics of the wind turbine are derived by combining blade element momentum (BEM) theory...... of the uncertain system is employed and a norm-bounded uncertainty model is used to formulate a minimax model predictive control. The resulting optimization problem is simplified by semidefinite relaxation and the controller obtained is applied on a full complexity, high fidelity wind turbine model. Finally...
Model output statistics applied to wind power prediction
Energy Technology Data Exchange (ETDEWEB)
Joensen, A.; Giebel, G.; Landberg, L. [Risoe National Lab., Roskilde (Denmark); Madsen, H.; Nielsen, H.A. [The Technical Univ. of Denmark, Dept. of Mathematical Modelling, Lyngby (Denmark)
1999-03-01
Being able to predict the output of a wind farm online for a day or two in advance has significant advantages for utilities, such as better possibility to schedule fossil fuelled power plants and a better position on electricity spot markets. In this paper prediction methods based on Numerical Weather Prediction (NWP) models are considered. The spatial resolution used in NWP models implies that these predictions are not valid locally at a specific wind farm. Furthermore, due to the non-stationary nature and complexity of the processes in the atmosphere, and occasional changes of NWP models, the deviation between the predicted and the measured wind will be time dependent. If observational data is available, and if the deviation between the predictions and the observations exhibits systematic behavior, this should be corrected for; if statistical methods are used, this approaches is usually referred to as MOS (Model Output Statistics). The influence of atmospheric turbulence intensity, topography, prediction horizon length and auto-correlation of wind speed and power is considered, and to take the time-variations into account, adaptive estimation methods are applied. Three estimation techniques are considered and compared, Extended Kalman Filtering, recursive least squares and a new modified recursive least squares algorithm. (au) EU-JOULE-3. 11 refs.
Development and application of chronic disease risk prediction models.
Oh, Sun Min; Stefani, Katherine M; Kim, Hyeon Chang
2014-07-01
Currently, non-communicable chronic diseases are a major cause of morbidity and mortality worldwide, and a large proportion of chronic diseases are preventable through risk factor management. However, the prevention efficacy at the individual level is not yet satisfactory. Chronic disease prediction models have been developed to assist physicians and individuals in clinical decision-making. A chronic disease prediction model assesses multiple risk factors together and estimates an absolute disease risk for the individual. Accurate prediction of an individual's future risk for a certain disease enables the comparison of benefits and risks of treatment, the costs of alternative prevention strategies, and selection of the most efficient strategy for the individual. A large number of chronic disease prediction models, especially targeting cardiovascular diseases and cancers, have been suggested, and some of them have been adopted in the clinical practice guidelines and recommendations of many countries. Although few chronic disease prediction tools have been suggested in the Korean population, their clinical utility is not as high as expected. This article reviews methodologies that are commonly used for developing and evaluating a chronic disease prediction model and discusses the current status of chronic disease prediction in Korea.
Outcome Prediction in Mathematical Models of Immune Response to Infection.
Directory of Open Access Journals (Sweden)
Manuel Mai
Full Text Available Clinicians need to predict patient outcomes with high accuracy as early as possible after disease inception. In this manuscript, we show that patient-to-patient variability sets a fundamental limit on outcome prediction accuracy for a general class of mathematical models for the immune response to infection. However, accuracy can be increased at the expense of delayed prognosis. We investigate several systems of ordinary differential equations (ODEs that model the host immune response to a pathogen load. Advantages of systems of ODEs for investigating the immune response to infection include the ability to collect data on large numbers of 'virtual patients', each with a given set of model parameters, and obtain many time points during the course of the infection. We implement patient-to-patient variability v in the ODE models by randomly selecting the model parameters from distributions with coefficients of variation v that are centered on physiological values. We use logistic regression with one-versus-all classification to predict the discrete steady-state outcomes of the system. We find that the prediction algorithm achieves near 100% accuracy for v = 0, and the accuracy decreases with increasing v for all ODE models studied. The fact that multiple steady-state outcomes can be obtained for a given initial condition, i.e. the basins of attraction overlap in the space of initial conditions, limits the prediction accuracy for v > 0. Increasing the elapsed time of the variables used to train and test the classifier, increases the prediction accuracy, while adding explicit external noise to the ODE models decreases the prediction accuracy. Our results quantify the competition between early prognosis and high prediction accuracy that is frequently encountered by clinicians.
Development of Interpretable Predictive Models for BPH and Prostate Cancer
Bermejo, Pablo; Vivo, Alicia; Tárraga, Pedro J; Rodríguez-Montes, JA
2015-01-01
BACKGROUND Traditional methods for deciding whether to recommend a patient for a prostate biopsy are based on cut-off levels of stand-alone markers such as prostate-specific antigen (PSA) or any of its derivatives. However, in the last decade we have seen the increasing use of predictive models that combine, in a non-linear manner, several predictives that are better able to predict prostate cancer (PC), but these fail to help the clinician to distinguish between PC and benign prostate hyperplasia (BPH) patients. We construct two new models that are capable of predicting both PC and BPH. METHODS An observational study was performed on 150 patients with PSA ≥3 ng/mL and age >50 years. We built a decision tree and a logistic regression model, validated with the leave-one-out methodology, in order to predict PC or BPH, or reject both. RESULTS Statistical dependence with PC and BPH was found for prostate volume (P-value < 0.001), PSA (P-value < 0.001), international prostate symptom score (IPSS; P-value < 0.001), digital rectal examination (DRE; P-value < 0.001), age (P-value < 0.002), antecedents (P-value < 0.006), and meat consumption (P-value < 0.08). The two predictive models that were constructed selected a subset of these, namely, volume, PSA, DRE, and IPSS, obtaining an area under the ROC curve (AUC) between 72% and 80% for both PC and BPH prediction. CONCLUSION PSA and volume together help to build predictive models that accurately distinguish among PC, BPH, and patients without any of these pathologies. Our decision tree and logistic regression models outperform the AUC obtained in the compared studies. Using these models as decision support, the number of unnecessary biopsies might be significantly reduced. PMID:25780348
Model predictive torque control with an extended prediction horizon for electrical drive systems
Wang, Fengxiang; Zhang, Zhenbin; Kennel, Ralph; Rodríguez, José
2015-07-01
This paper presents a model predictive torque control method for electrical drive systems. A two-step prediction horizon is achieved by considering the reduction of the torque ripples. The electromagnetic torque and the stator flux error between predicted values and the references, and an over-current protection are considered in the cost function design. The best voltage vector is selected by minimising the value of the cost function, which aims to achieve a low torque ripple in two intervals. The study is carried out experimentally. The results show that the proposed method achieves good performance in both steady and transient states.
Gou, Jun; Lee, Anson; Pyko, Jan
2014-10-01
The cranking and charging processes of a VRLA battery during stop-start cycling in micro-hybrid applications were simulated by one dimensional mathematical modeling, to study the formation and distribution of lead sulfate across the cell and analyze the resulting effect on battery aging. The battery focused on in this study represents a conventional VRLA battery without any carbon additives in the electrodes or carbon-based electrodes. The modeling results were validated against experimental data and used to analyze the "sulfation" of negative electrodes - the common failure mode of lead acid batteries under high-rate partial state of charge (HRPSoC) cycling. The analyses were based on two aging mechanisms proposed in previous studies and the predictions showed consistency with the previous teardown observations that the sulfate formed at the negative interface is more difficult to be converted back than anywhere else in the electrodes. The impact of cranking pulses during stop-start cycling on current density and the corresponding sulfate layer production was estimated. The effects of some critical design parameters on sulfate formation, distribution and aging over cycling were investigated, which provided guidelines for developing models and designing of VRLA batteries in micro-hybrid applications.
Zhang, Yan-Ju; Cao, Jun; Zhang, Wen-Qing
2016-09-01
The Higgs Triplet Model (HTM) predicts the existences of the extra neutral scalars H i ( H i = H, A) and the charged Higgs bosons ( H ± and H ±±). In this work, we make a systematic investigation for the associated production of the singly-charged and neutral Higgs bosons via the processes: e+e-→ H+W-H and e+e-→ H+W-A. From the numerical evaluations for the production cross sections and relevant phenomenological analysis we find that (i) the production rates of these processes can reach the level of several fb with reasonable parameter values; (ii) due to the large production rates and small backgrounds, the signals of these scalars might be detected via these processes at the future ILC experiments; and (iii) for the case of m_{Hi}> m_{H^{± }}> m_{H^{± ± }}, the cascade decay modes Hito H^{± }W^{∓ ast } with H^{± }to H^{± ± }W^{∓ ast } would lead to production of H ++ H - accompanied by several virtual W bosons. Such characteristic feature can help us to distinguish the HTM from the Two-Higgs-Doublet Model (2HDM) and the Minimal Supersymmetric Model (MSSM).
The "Spring Predictability Barrier" Phenomenon of ENSO Predictions Generated with the FGOALS-g Model
Institute of Scientific and Technical Information of China (English)
WEI Chao; DUAN Wan-Suo
2010-01-01
Using the sea surface temperature(SST)predicted for the equatorial Pacific Ocean by the Flexible Global Ocean-Atmosphere-Land System Model-gamil (FGOALS-g),an analysis of the prediction errors was performed for the seasonally dependent predictability of SST anomalies both for neutral years and for the growth/decay phase of El Ni(n)o/La Ni(n)a events.The study results indicated that for the SST predictions relating to the growth phase and the decay phase of EI Ni(n)o events,the prediction errors have a seasonally dependent evolution.The largest increase in errors occurred in the spring season,which indicates that a prominent spring predictability barrier(SPB)occurs during an El Ni(n)o-Southern Oscillation(ENSO)warming episode.Furthermore,the SPB associated with the growth-phase prediction is more prominent than that associated with the decay-phase prediction.However,for the neutral years and for the growth and decay phases of La Ni(n)a events,the SPB phenomenon was less prominent.These results indicate that the SPB phenomenon depends extensively on the ENSO events themselves.In particular,the SPB depends on the phases of the ENSO events.These results may provide useful knowledge for improving ENSO forecasting.
Physical chemistry of charged interfaces: multi-scale modelling and applications to energy
International Nuclear Information System (INIS)
This article presents the advantages of a multi-scale modelling strategy for the understanding of systems with charged interfaces. On the one hand, one can simulate a complex system at different levels, depending on the relevant length and time scales for a given physical chemistry problem. On the other hand, one should make the link between the various levels of description, e.g. following a bottom-up approach. The case of charged porous materials, in particular clay minerals, is illustrated here by discussing physical chemistry issues that arise in the context of geological disposal of nuclear wastes and CO2 sequestration. (author)
Energy Technology Data Exchange (ETDEWEB)
Avancini, S.S.; Marinelli, J.R. [Universidade Federal de Santa Catarina Florianopolis, Depto de Fisica - CFM, Florianopolis (Brazil); Carlson, B.V. [Instituto Tecnologico de Aeronautica, Sao Jose dos Campos (Brazil)
2013-06-15
Relativistic models for finite nuclei contain spurious center-of-mass motion in most applications for the nuclear many-body problem, where the nuclear wave function is taken as a single Slater determinant within a space-fixed frame description. We use the Peierls-Yoccoz projection method, previously developed for relativistic approaches together with a reparametrization of the coupling constants that fits binding energies and charge radius and apply our results to calculate elastic electron scattering monopole charge form factors for light nuclei. (orig.)
Fan, Wenkai; Zong, Hong-Shi
2016-01-01
Under the chemical equilibrium and electric charge neutrality conditions, we evaluate the $2$nd to $4$th order baryon, charge and strangeness susceptibilities near a chiral critical point using the Nambu--Jona--Lasinio model. Because of the considerati on of electron chemical potential, up and down quarks are no longer degenerate, but have a chemical potential difference. This isospin chemical potential does not bring new qualitative features in the QCD phase diagram. Furthermore, baryon number susce ptibilities are found to be of the greatest magnitude, offering the strongest signal. Whereas the strangeness susceptibilities have the smallest divergence dominating area, owing to the large strange quark mass.
Two Models Relevant to the Interaction of a Point Charge and a Magnetic Moment
Boyer, Timothy H
2012-01-01
An understanding of the interaction of a point charge and a magnetic moment is crucial for understanding the experiments involving electromagnetic momentum carried by permeable materials as well as the experimentally-observed Aharonov-Bohm and Aharonov-Casher phase shifts. Here we present two simple models for a magnetic moment which have vastly different interactions with a distant point charge. It is suggested that a satisfactory theoretical understanding of the interaction is still lacking and that the "hidden momentum" interpretation has been introduced into the textbook literature prematurely.
Hidden Fermion in Stueckelberg Z' Models as Milli-charged Dark Matter
Cheung, Kingman; Yuan, Tzu-Chiang
2007-01-01
The hidden Stueckelberg Z' model is augmented by a pair of Dirac fermions. If the Z' has a coupling strength comparable to weak scale coupling, one can show that this hidden fermion-antifermion pair could be a milli-charged dark matter candidate with a viable relic density. Monochromatic photon flux coming from the Galactic center due to pair annihilation of these milli-charged particles is calculated and is shown to be within reach of the next generation gamma-ray experiments. Characteristic...
E-commerce business model mining and prediction
Institute of Scientific and Technical Information of China (English)
Zhou-zhou HE; Zhong-fei ZHANG; Chun-ming CHEN; Zheng-gang WANG
2015-01-01
We study the problem of business model mining and prediction in the e-commerce context. Unlike most existing approaches where this is typically formulated as a regression problem or a time-series prediction problem, we take a different formulation to this problem by noting that these existing approaches fail to consider the potential relationships both among the consumers (consumer infl uence) and among the shops (competitions or collaborations). Taking this observation into consideration, we propose a new method for e-commerce business model mining and prediction, called EBMM, which combines regression with community analysis. The challenge is that the links in the network are typically not directly observed, which is addressed by applying information diffusion theory through the consumer-shop network. Extensive evaluations using Alibaba Group e-commerce data demonstrate the promise and superiority of EBMM to the state-of-the-art methods in terms of business model mining and prediction.
Groundwater Level Prediction using M5 Model Trees
Nalarajan, Nitha Ayinippully; Mohandas, C.
2015-01-01
Groundwater is an important resource, readily available and having high economic value and social benefit. Recently, it had been considered a dependable source of uncontaminated water. During the past two decades, increased rate of extraction and other greedy human actions have resulted in the groundwater crisis, both qualitatively and quantitatively. Under prevailing circumstances, the availability of predicted groundwater levels increase the importance of this valuable resource, as an aid in the planning of groundwater resources. For this purpose, data-driven prediction models are widely used in the present day world. M5 model tree (MT) is a popular soft computing method emerging as a promising method for numeric prediction, producing understandable models. The present study discusses the groundwater level predictions using MT employing only the historical groundwater levels from a groundwater monitoring well. The results showed that MT can be successively used for forecasting groundwater levels.
A Fusion Model for CPU Load Prediction in Cloud Computing
Directory of Open Access Journals (Sweden)
Dayu Xu
2013-11-01
Full Text Available Load prediction plays a key role in cost-optimal resource allocation and datacenter energy saving. In this paper, we use real-world traces from Cloud platform and propose a fusion model to forecast the future CPU loads. First, long CPU load time series data are divided into short sequences with same length from the historical data on the basis of cloud control cycle. Then we use kernel fuzzy c-means clustering algorithm to put the subsequences into different clusters. For each cluster, with current load sequence, a genetic algorithm optimized wavelet Elman neural network prediction model is exploited to predict the CPU load in next time interval. Finally, we obtain the optimal cloud computing CPU load prediction results from the cluster and its corresponding predictor with minimum forecasting error. Experimental results show that our algorithm performs better than other models reported in previous works.
Experimental study on prediction model for maximum rebound ratio
Institute of Scientific and Technical Information of China (English)
LEI Wei-dong; TENG Jun; A.HEFNY; ZHAO Jian; GUAN Jiong
2007-01-01
The proposed prediction model for estimating the maximum rebound ratio was applied to a field explosion test, Mandai test in Singapore.The estimated possible maximum Deak particle velocities(PPVs)were compared with the field records.Three of the four available field-recorded PPVs lie exactly below the estimated possible maximum values as expected.while the fourth available field-recorded PPV lies close to and a bit higher than the estimated maximum possible PPV The comparison results show that the predicted PPVs from the proposed prediction model for the maximum rebound ratio match the field.recorded PPVs better than those from two empirical formulae.The very good agreement between the estimated and field-recorded values validates the proposed prediction model for estimating PPV in a rock mass with a set of ipints due to application of a two dimensional compressional wave at the boundary of a tunnel or a borehole.
Modeling, Prediction, and Control of Heating Temperature for Tube Billet
Directory of Open Access Journals (Sweden)
Yachun Mao
2015-01-01
Full Text Available Annular furnaces have multivariate, nonlinear, large time lag, and cross coupling characteristics. The prediction and control of the exit temperature of a tube billet are important but difficult. We establish a prediction model for the final temperature of a tube billet through OS-ELM-DRPLS method. We address the complex production characteristics, integrate the advantages of PLS and ELM algorithms in establishing linear and nonlinear models, and consider model update and data lag. Based on the proposed model, we design a prediction control algorithm for tube billet temperature. The algorithm is validated using the practical production data of Baosteel Co., Ltd. Results show that the model achieves the precision required in industrial applications. The temperature of the tube billet can be controlled within the required temperature range through compensation control method.