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 g...... 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.......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...
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
Liu, Kailong; Li, Kang; Zhang, Cheng
2017-04-01
Battery temperature is a primary factor affecting the battery performance, and suitable battery temperature control in particular internal temperature control can not only guarantee battery safety but also improve its efficiency. This is however challenging as current controller designs for battery charging have no mechanisms to incorporate such information. This paper proposes a novel battery charging control strategy which applies the constrained generalized predictive control (GPC) to charge a LiFePO4 battery based on a newly developed coupled thermoelectric model. The control target primarily aims to maintain the battery cell internal temperature within a desirable range while delivering fast charging. To achieve this, the coupled thermoelectric model is firstly introduced to capture the battery behaviours in particular SOC and internal temperature which are not directly measurable in practice. Then a controlled auto-regressive integrated moving average (CARIMA) model whose parameters are identified by the recursive least squares (RLS) algorithm is developed as an online self-tuning predictive model for a GPC controller. Then the constrained generalized predictive controller is developed to control the charging current. Experiment results confirm the effectiveness of the proposed control strategy. Further, the best region of heat dissipation rate and proper internal temperature set-points are also investigated and analysed.
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.
Predictions of nuclear charge radii
Bao, M.; Lu, Y.; Zhao, Y. M.; Arima, A.
2016-12-01
The nuclear charge radius is a fundamental property of an atomic nucleus. In this article we study the predictive power of empirical relations for experimental nuclear charge radii of neighboring nuclei and predict the unknown charge radii of 1085 nuclei based on the experimental CR2013 database within an uncertainty of 0.03 fm.
Spacecraft Charging and Auroral Boundary Predictions in Low Earth Orbit
Minow, Joseph I.
2016-01-01
Auroral charging of spacecraft is an important class of space weather impacts on technological systems in low Earth orbit. In order for space weather models to accurately specify auroral charging environments, they must provide the appropriate plasma environment characteristics responsible for charging. Improvements in operational space weather prediction capabilities relevant to charging must be tested against charging observations.
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.
Surface Complexation Modeling in Variable Charge Soils: Prediction of Cadmium Adsorption
Giuliano Marchi; Cesar Crispim Vilar; George O’Connor; Letuzia Maria de Oliveira; Adriana Reatto; Thomaz Adolph Rein
2015-01-01
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 Vis...
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
Directory of Open Access Journals (Sweden)
Huan Yang
2015-11-01
Full Text Available Based on charge-discharge cycle tests for commercial nickel-metal hydride (Ni-MH batteries, a nonlinear relationship is found between the discharging capacity (Cdischarge, Ah and the voltage changes in 1 s occurring at the start of the charging process (ΔVcharge, mV. This nonlinear relationship between Cdischarge and ΔVcharge is described with a curve equation, which can be determined using a nonlinear least-squares method. Based on the curve equation, a curve model for the state-of-health (SOH prediction is constructed without battery models and cycle numbers. The validity of the curve model is verified using (Cdischarge, ΔVcharge data groups obtained from the charge-discharge cycle tests at different rates. The results indicate that the curve model can be effectively applied to predict the SOH of the Ni-MH batteries and the best prediction root-mean-square error (RMSE can reach upto 1.2%. Further research is needed to confirm the application of this empirical curve model in practical fields.
Paricaud, Patrice; Predota, Milan; Chialvo, Ariel A; Cummings, Peter T
2005-06-22
Water exhibits many unusual properties that are essential for the existence of life. Water completely changes its character from ambient to supercritical conditions in a way that makes it possible to sustain life at extreme conditions, leading to conjectures that life may have originated in deep-sea vents. Molecular simulation can be very useful in exploring biological and chemical systems, particularly at extreme conditions for which experiments are either difficult or impossible; however this scenario entails an accurate molecular model for water applicable over a wide range of state conditions. Here, we present a Gaussian charge polarizable model (GCPM) based on the model developed earlier by Chialvo and Cummings [Fluid Phase Equilib. 150, 73 (1998)] which is, to our knowledge, the first that satisfies the water monomer and dimer properties, and simultaneously yields very accurate predictions of dielectric, structural, vapor-liquid equilibria, and transport properties, over the entire fluid range. This model would be appropriate for simulating biological and chemical systems at both ambient and extreme conditions. The particularity of the GCPM model is the use of Gaussian distributions instead of points to represent the partial charges on the water molecules. These charge distributions combined with a dipole polarizability and a Buckingham exp-6 potential are found to play a crucial role for the successful and simultaneous predictions of a variety of water properties. This work not only aims at presenting an accurate model for water, but also at proposing strategies to develop classical accurate models for the predictions of structural, dynamic, and thermodynamic properties.
Electric Vehicle Charging Modeling
Grahn, Pia
2014-01-01
With an electrified passenger transportation fleet, carbon dioxide emissions could be reduced significantly depending on the electric power production mix. Increased electric power consumption due to electric vehicle charging demands of electric vehicle fleets may be met by increased amount of renewable power production in the electrical systems. With electric vehicle fleets in the transportation system there is a need for establishing an electric vehicle charging infrastructure that distribu...
Hussain, Mozammil; Natarajan, Raghu N; Chaudhary, Gulafsha; An, Howard S; Andersson, Gunnar B J
2011-05-01
Disc swelling pressure (P(swell)) facilitated by fixed charged density (FCD) of proteoglycans (P(fcd)) and strain-dependent permeability (P(strain)) are of critical significance in the physiological functioning of discs. FCD of proteoglycans prevents any excessive matrix deformation by tissue stiffening, whereas strain-dependent permeability limits the rate of stress transfer from fluid to solid skeleton. To date, studies involving the modeling of FCD of proteoglycans and strain-dependent permeability have not been reported for the cervical discs. The current study objective is to compare the relative contributions of strain-dependent permeability and FCD of proteoglycans in predicting cervical disc biomechanics. Three-dimensional finite element models of a C5-C6 segment with three different disc compositions were analyzed: an SPFP model (strain-dependent permeability and FCD of proteoglycans), an SP model (strain-dependent permeability alone), and an FP model (FCD of proteoglycans alone). The outcomes of the current study suggest that the relative contributions of strain-dependent permeability and FCD of proteoglycans were almost comparable in predicting the physiological behavior of the cervical discs under moment loads. However, under compression, strain-dependent permeability better predicted the in vivo disc response than that of the FCD of proteoglycans. Unlike the FP model (least stiff) in compression, motion behavior of the three models did not vary much from each other and agreed well within the standard deviations of the corresponding in vivo published data. Flexion was recorded with maximum P(fcd) and P(strain), whereas minimum values were found in extension. The study data enhance the understanding of the roles played by the FCD of proteoglycans and strain-dependent permeability and porosity in determining disc tissue swelling behavior. Degenerative changes involving strain-dependent permeability and/or loss of FCD of proteoglycans can further be
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.
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
Variational multiscale models for charge transport.
Wei, Guo-Wei; Zheng, Qiong; Chen, Zhan; Xia, Kelin
2012-01-01
This work presents a few variational multiscale models for charge transport in complex physical, chemical and biological systems and engineering devices, such as fuel cells, solar cells, battery cells, nanofluidics, transistors and ion channels. An essential ingredient of the present models, introduced in an earlier paper (Bulletin of Mathematical Biology, 72, 1562-1622, 2010), is the use of differential geometry theory of surfaces as a natural means to geometrically separate the macroscopic domain from the microscopic domain, meanwhile, dynamically couple discrete and continuum descriptions. Our main strategy is to construct the total energy functional of a charge transport system to encompass the polar and nonpolar free energies of solvation, and chemical potential related energy. By using the Euler-Lagrange variation, coupled Laplace-Beltrami and Poisson-Nernst-Planck (LB-PNP) equations are derived. The solution of the LB-PNP equations leads to the minimization of the total free energy, and explicit profiles of electrostatic potential and densities of charge species. To further reduce the computational complexity, the Boltzmann distribution obtained from the Poisson-Boltzmann (PB) equation is utilized to represent the densities of certain charge species so as to avoid the computationally expensive solution of some Nernst-Planck (NP) equations. Consequently, the coupled Laplace-Beltrami and Poisson-Boltzmann-Nernst-Planck (LB-PBNP) equations are proposed for charge transport in heterogeneous systems. A major emphasis of the present formulation is the consistency between equilibrium LB-PB theory and non-equilibrium LB-PNP theory at equilibrium. Another major emphasis is the capability of the reduced LB-PBNP model to fully recover the prediction of the LB-PNP model at non-equilibrium settings. To account for the fluid impact on the charge transport, we derive coupled Laplace-Beltrami, Poisson-Nernst-Planck and Navier-Stokes equations from the variational principle
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.
Dedenko, L G; Roganova, T M
2015-01-01
It has been shown that muon flux intensities calculated in terms of the EPOS LHC and EPOS 1.99 models at the energy of 10^4 GeV exceed the data of the classical experiments L3+Cosmic, MACRO and LVD on the spectra of atmospheric muons by a factor of 1.9 and below these data at the same energy by a factor of 1.8 in case of the QGSJET II-03 model. It has been concluded that these tested models overestimate (underestimate in case of QGSJET II-03 model) the production of secondary particles with the highest energies in interactions of hadrons by a factor of ~1.5. The LHCf and TOTEM accelerator experiments show also this type of disagreements with these model predictions at highest energies of secondary particles.
Fulton, John L; Bylaska, Eric J; Bogatko, Stuart; Balasubramanian, Mahalingam; Cauët, Emilie; Schenter, Gregory K; Weare, John H
2012-09-20
First-principles dynamics simulations (DFT, PBE96, and PBE0) and electron scattering calculations (FEFF9) provide near-quantitative agreement with new and existing XAFS measurements for a series of transition-metal ions interacting with their hydration shells via complex mechanisms (high spin, covalency, charge transfer, etc.). This analysis does not require either the development of empirical interparticle interaction potentials or structural models of hydration. However, it provides consistent parameter-free analysis and improved agreement with the higher-R scattering region (first- and second-shell structure, symmetry, dynamic disorder, and multiple scattering) for this comprehensive series of ions. DFT+GGA MD methods provide a high level of agreement. However, improvements are observed when exact exchange is included. Higher accuracy in the pseudopotential description of the atomic potential, including core polarization and reducing core radii, was necessary for very detailed agreement. The first-principles nature of this approach supports its application to more complex systems.
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...
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.
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.
Cestari, Andrea
2013-01-01
Predictive modeling is emerging as an important knowledge-based technology in healthcare. The interest in the use of predictive modeling reflects advances on different fronts such as the availability of health information from increasingly complex databases and electronic health records, a better understanding of causal or statistical predictors of health, disease processes and multifactorial models of ill-health and developments in nonlinear computer models using artificial intelligence or neural networks. These new computer-based forms of modeling are increasingly able to establish technical credibility in clinical contexts. The current state of knowledge is still quite young in understanding the likely future direction of how this so-called 'machine intelligence' will evolve and therefore how current relatively sophisticated predictive models will evolve in response to improvements in technology, which is advancing along a wide front. Predictive models in urology are gaining progressive popularity not only for academic and scientific purposes but also into the clinical practice with the introduction of several nomograms dealing with the main fields of onco-urology.
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.
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.
Modeling and Analyzing Electric Vehicle Charging
DEFF Research Database (Denmark)
Andersen, Ove; Krogh, Benjamin Bjerre; Thomsen, Christian
2017-01-01
The combined battery capacity in electric vehicles (EVs) is considered an integral part of balancing a smart power grid in the future. In addition, EVs can reduce the usage of fossil fuels in the transport sector because EVs can be charged using electricity from renewable energy sources......, such as wind turbines. To both enable a smart grid and the use of renewable energy, it is essential to know when and where an EV is plugged into the power grid and what battery capacity is available. In this paper, we present a generic spatio-temporal data-warehouse model for storing detailed information...... on all aspects of charging EVs, including integration with the electricity prices from a spot market. The proposed data warehouse is fully implemented and currently contains 2.5 years of charging data from 176 EVs. We describe the date warehouse model and the implementation including complex operations...
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.
Nominal Model Predictive Control
Grüne, Lars
2014-01-01
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...
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...
Problems in Modelling Charge Output Accelerometers
Directory of Open Access Journals (Sweden)
Tomczyk Krzysztof
2016-12-01
Full Text Available The paper presents major issues associated with the problem of modelling change output accelerometers. The presented solutions are based on the weighted least squares (WLS method using transformation of the complex frequency response of the sensors. The main assumptions of the WLS method and a mathematical model of charge output accelerometers are presented in first two sections of this paper. In the next sections applying the WLS method to estimation of the accelerometer model parameters is discussed and the associated uncertainties are determined. Finally, the results of modelling a PCB357B73 charge output accelerometer are analysed in the last section of this paper. All calculations were executed using the MathCad software program. The main stages of these calculations are presented in Appendices A−E.
Predictive Surface Complexation Modeling
Energy Technology Data Exchange (ETDEWEB)
Sverjensky, Dimitri A. [Johns Hopkins Univ., Baltimore, MD (United States). Dept. of Earth and Planetary Sciences
2016-11-29
Surface complexation plays an important role in the equilibria and kinetics of processes controlling the compositions of soilwaters and groundwaters, the fate of contaminants in groundwaters, and the subsurface storage of CO_{2} and nuclear waste. Over the last several decades, many dozens of individual experimental studies have addressed aspects of surface complexation that have contributed to an increased understanding of its role in natural systems. However, there has been no previous attempt to develop a model of surface complexation that can be used to link all the experimental studies in order to place them on a predictive basis. Overall, my research has successfully integrated the results of the work of many experimentalists published over several decades. For the first time in studies of the geochemistry of the mineral-water interface, a practical predictive capability for modeling has become available. The predictive correlations developed in my research now enable extrapolations of experimental studies to provide estimates of surface chemistry for systems not yet studied experimentally and for natural and anthropogenically perturbed systems.
A nonlinear feedback model for granular and surface charging
Shinbrot, Troy; Kozachkov, Leo; Siu, Theo
2015-03-01
Independent laboratories have experimentally demonstrated that identical materials brought into symmetric contact generate contact charges. Even the most basic features of this odd behavior remain to be explained. In this talk, we provide a simple, Ising-like, model that appears to account for many of the observed phenomena. We calculate the electric field acting on surface molecules in a lattice, and we show that if the molecules are polarizable, then infinitesimal random polarizations typically build exponentially rapidly in time. These polarizations self-assemble to produce surface patterns that come in two types, and we find that one of these types accounts for strong localized charging, while the other produces a weaker persistent surface charge pattern. We summarize predictions for both ideal surfaces and for defects in granular beds. This work was supported by NSF Grant DMR-1404792.
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...
Charge-transport model for conducting polymers
Dongmin Kang, Stephen; Jeffrey Snyder, G.
2016-11-01
The growing technological importance of conducting polymers makes the fundamental understanding of their charge transport extremely important for materials and process design. Various hopping and mobility edge transport mechanisms have been proposed, but their experimental verification is limited to poor conductors. Now that advanced organic and polymer semiconductors have shown high conductivity approaching that of metals, the transport mechanism should be discernible by modelling the transport like a semiconductor with a transport edge and a transport parameter s. Here we analyse the electrical conductivity and Seebeck coefficient together and determine that most polymers (except possibly PEDOT:tosylate) have s = 3 and thermally activated conductivity, whereas s = 1 and itinerant conductivity is typically found in crystalline semiconductors and metals. The different transport in polymers may result from the percolation of charge carriers from conducting ordered regions through poorly conducting disordered regions, consistent with what has been expected from structural studies.
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.
Bardhan, Jaydeep P
2011-09-14
We study the energetics of burying charges, ion pairs, and ionizable groups in a simple protein model using nonlocal continuum electrostatics. Our primary finding is that the nonlocal response leads to markedly reduced solvent screening, comparable to the use of application-specific protein dielectric constants. Employing the same parameters as used in other nonlocal studies, we find that for a sphere of radius 13.4 Å containing a single +1e charge, the nonlocal solvation free energy varies less than 18 kcal/mol as the charge moves from the surface to the center, whereas the difference in the local Poisson model is ∼35 kcal/mol. Because an ion pair (salt bridge) generates a comparatively more rapidly varying Coulomb potential, energetics for salt bridges are even more significantly reduced in the nonlocal model. By varying the central parameter in nonlocal theory, which is an effective length scale associated with correlations between solvent molecules, nonlocal-model energetics can be varied from the standard local results to essentially zero; however, the existence of the reduction in charge-burial penalties is quite robust to variations in the protein dielectric constant and the correlation length. Finally, as a simple exploratory test of the implications of nonlocal response, we calculate glutamate pK(a) shifts and find that using standard protein parameters (ε(protein) = 2-4), nonlocal results match local-model predictions with much higher dielectric constants. Nonlocality may, therefore, be one factor in resolving discrepancies between measured protein dielectric constants and the model parameters often used to match titration experiments. Nonlocal models may hold significant promise to deepen our understanding of macromolecular electrostatics without substantially increasing computational complexity.
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.
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.
New Classes of Charged Spheroidal Models
Directory of Open Access Journals (Sweden)
S. Thirukkanesh
2013-01-01
Full Text Available New classes of exact solutions to the Einstein-Maxwell system is found in closed form by assuming that the hypersurface is spheroidal. This is achieved by choosing a particular form for the electric field intensity. A class of solution is found for all positive spheroidal parameter for a specific form of electric field intensity. In general, the condition of pressure isotropy reduces to a difference equation with variable, rational coefficients that can be solved. Consequently, an explicit solution in series form is found. By placing restrictions on the parameters, it is shown that the series terminates and there exist two classes of solutions in terms of elementary functions. These solutions contain the models found previously in the limit of vanishing charge. Solutions found are directly relating the spheroidal parameter and electric field intensity. Masses obtained are consistent with the previously reported experimental and theoretical studies describing strange stars. A physical analysis indicates that these models may be used to describe a charged sphere.
Poisson-Boltzmann model of electrolytes containing uniformly charged spherical nanoparticles.
Bohinc, Klemen; Volpe Bossa, Guilherme; Gavryushov, Sergei; May, Sylvio
2016-12-21
Like-charged macromolecules typically repel each other in aqueous solutions that contain small mobile ions. The interaction tends to turn attractive if mobile ions with spatially extended charge distributions are added. Such systems can be modeled within the mean-field Poisson-Boltzmann formalism by explicitly accounting for charge-charge correlations within the spatially extended ions. We consider an aqueous solution that contains a mixture of spherical nanoparticles with uniform surface charge density and small mobile salt ions, sandwiched between two like-charged planar surfaces. We perform the minimization of an appropriate free energy functional, which leads to a non-linear integral-differential equation for the electrostatic potential that we solve numerically and compare with predictions from Monte Carlo simulations. Nanoparticles with uniform surface charge density are contrasted with nanoparticles that have all their charges relocated at the center. Our mean-field model predicts that only the former (especially when large and highly charged particles) but not the latter are able to mediate attractive interactions between like-charged planar surfaces. We also demonstrate that at high salt concentration attractive interactions between like-charged planar surfaces turn into repulsion.
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...
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.
Ricardo Infante-Castillo; Samuel P. Hernández-Rivera
2012-01-01
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 re...
Paiement, Jean-François; Grandvalet, Yves; Bengio, Samy
2008-01-01
Modeling long-term dependencies in time series has proved very difficult to achieve with traditional machine learning methods. This problem occurs when considering music data. In this paper, we introduce generative models for melodies. We decompose melodic modeling into two subtasks. We first propose a rhythm model based on the distributions of distances between subsequences. Then, we define a generative model for melodies given chords and rhythms based on modeling sequences of Narmour featur...
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…
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 Dani...
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.
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.
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...
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...
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.
Thirring Model with Non-conserved Chiral Charge
Cabra, D C; Naón, C M
1994-01-01
We study the Abelian Thirring Model when the fermionic fields have non-conserved chiral charge: $\\Delta {\\cal Q}_5 =N$. One of the main features we find for this model is the dependence of the Virasoro central charge on both the Thirring coupling constant and $N$. We show how to evaluate correlation functions and in particular we compute the conformal dimensions for fermions and fermionic bilinears, which depend on the fermionic chiral charge. Finally we build primary fields with arbitrary conformal weight.
Unruh model for the Einstein-Rosen charge: Squealing Wormholes?
Nandi, K K
2004-01-01
We present two kinds of acoustic models for the massless electric charge conceived by Einstein and Rosen in the form of a bridge (wormhole throat). It is found that the first kind of modelling requires a thin layer of exotic matter at the bridge. We also derive an acoustic equation that exclusively characterizes the model. Using a second kind of model, it is demonstrated that the Einstein-Rosen charge has a sonic Hawking-Unruh temperature proportional to +-1/$beta$, where $beta$ is the size of the charge. This suggests that (squealing!) wormholes can also be formally accommodated into Unruh's fluid model.
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...
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.
Circuit Modeling of a MEMS Varactor Including Dielectric Charging Dynamics
Giounanlis, P.; Andrade-Miceli, D.; Gorreta, S.; Pons-Nin, J.; Dominguez-Pumar, M.; Blokhina, E.
2016-10-01
Electrical models for MEMS varactors including the effect of dielectric charging dynamics are not available in commercial circuit simulators. In this paper a circuit model using lumped ideal elements available in the Cadence libraries and a basic Verilog-A model, has been implemented. The model has been used to simulate the dielectric charging in function of time and its effects over the MEMS capacitance value.
The charged particle accelerators subsystems modeling
Averyanov, G. P.; Kobylyatskiy, A. V.
2017-01-01
Presented web-based resource for information support the engineering, science and education in Electrophysics, containing web-based tools for simulation subsystems charged particle accelerators. Formulated the development motivation of Web-Environment for Virtual Electrophysical Laboratories. Analyzes the trends of designs the dynamic web-environments for supporting of scientific research and E-learning, within the framework of Open Education concept.
Charge Migration in DNA: A Double Stranded Model
Institute of Scientific and Technical Information of China (English)
BAO, Han; LU, Jing; FAN, Kang-Nian
2006-01-01
In particular, charge migration phenomena in DNA have attracted much interest because of relevance to the generation of damage and mutations which play important roles in most of life processes. In this paper a theory method was presented in which the DNA chain was treated as a double-stranded system, and the charge migration in DNA based on the donor-bridge-acceptor system was investigated by this model. After having obtained the Hamiltonian, the effects of the surrounding were explained and calculated. The double-strand calculation could lead to good exponential decay curves and this time two different falloff parameters were found respectively before and after 3 or 4 AT base pair bridge lengths as prediction. Lately theoretical study showed this result by addition of more parameter, and sequence effect was then concentrated on. The difference of transfer integral caused the different decay rate of unlike sequences, but bridge length was still proved to be the main factor on the decay rates.
Validation of a predictive model for smart control of electrical energy storage
Homan, Bart; Leeuwen, van Richard P.; Smit, Gerard J.M.; Zhu, Lei; Wit, de Jan B.
2016-01-01
The purpose of this paper is to investigate the applicability of a relatively simple model which is based on energy conservation for model predictions as part of smart control of thermal and electric storage. The paper reviews commonly used predictive models. Model predictions of charging and discha
Modeling of Cooling and Solidification of TNT based Cast High Explosive Charges
Directory of Open Access Journals (Sweden)
A. Srinivas Kumar
2014-07-01
Full Text Available Cast trinitrotoluene (TNT based high explosive charges suffer from different defects such as cracks, voids, etc. One of the quality control measures is to cool the castings gradually, so that the entire charge solidifies without a large temperature gradient from core to the periphery of the cast charge. The fact that the solidification of high explosive casting starts from the periphery (cooler side and travels towards the center enables us to predict the solidification profile of TNT based explosive castings. Growth of solidification thickness and cooling temperature profiles of TNT based cast high explosive charges are predicted as functions of time and space using unsteady state heat transfer principles, associated with heat balance at solid to liquid interface as a moving boundary of solidification. This will enable adoption of proper quality control during solidification of the molten TNT to eliminate inherent drawbacks of cast high explosive charges. The solidification profiles of TNT based cast charges under controlled and natural conditions are predicted and the model is validated against 145 mm diameter TNT cast charge which is found to be in broad agreement with experiments.Defence Science Journal, Vol. 64, No. 4, July 2014, pp.339-343, DOI:http://dx.doi.org/10.14429/dsj.64.4673
What is the "best" atomic charge model to describe through-space charge-transfer excitations?
Jacquemin, Denis; Le Bahers, Tangui; Adamo, Carlo; Ciofini, Ilaria
2012-04-28
We investigate the efficiency of several partial atomic charge models (Mulliken, Hirshfeld, Bader, Natural, Merz-Kollman and ChelpG) for investigating the through-space charge-transfer in push-pull organic compounds with Time-Dependent Density Functional Theory approaches. The results of these models are compared to benchmark values obtained by determining the difference of total densities between the ground and excited states. Both model push-pull oligomers and two classes of "real-life" organic dyes (indoline and diketopyrrolopyrrole) used as sensitisers in solar cell applications have been considered. Though the difference of dipole moments between the ground and excited states is reproduced by most approaches, no atomic charge model is fully satisfactory for reproducing the distance and amount of charge transferred that are provided by the density picture. Overall, the partitioning schemes fitting the electrostatic potential (e.g. Merz-Kollman) stand as the most consistent compromises in the framework of simulating through-space charge-transfer, whereas the other models tend to yield qualitatively inconsistent values.
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}^{+}\
A prediction for |U{sub e3}| from patterns in the charged lepton spectra
Energy Technology Data Exchange (ETDEWEB)
Ferrandis, Javier; Pakvasa, Sandip
2004-09-22
It is shown that empirical relations between the charged lepton spectra and the quark spectra together with a bimaximal or near bimaximal neutrino mixing matrix necessarily imply that there is a contribution to |U{sub e3}| given by {theta}{sub C}/ 3{radical}2 {approx} {radical}(m{sub e}/2m{sub {mu}}) {approx} 0.052, where {theta}{sub C}is the Cabibbo angle. This prediction could be tested in the near future reactor experiments. The charged lepton mixing also generates a less robust prediction for the angle {theta}{sub 23} and a small contribution to the phase {delta}.
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.
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±.
Modeling energy and charge transports in pi-conjugated systems
Shin, Yongwoo
Carbon based pi-conjugated materials, such as conducting polymers, fullerene, carbon nanotubes, graphene, and conjugated dendrimers have attracted wide scientific attentions in the past three decades. This work presents the first unified model Hamiltonian that can accurately capture the low-energy excitations among all these pi-conjugated systems, even with the presence of defects and heterogeneous sites. Two transferable physical parameters are incorporated into the Su-Schrieffer-Heeger Hamiltonian to model conducting polymers beyond polyacetylene: the parameter gamma scales the electronphonon coupling strength in aromatic rings and the other parameter epsilon specifies the heterogeneous core charges. This generic Hamiltonian predicts the fundamental band gaps of polythiophene, polypyrrole, polyfuran, poly-(p-phenylene), poly-(p-phenylene vinylene), polyacenes, fullerene, carbon nanotubes, graphene, and graphene nanoribbons with an accuracy exceeding time-dependent density functional theory. Its computational costs for moderate-length polymer chains are more than eight orders of magnitude lower than first-principles approaches. The charge and energy transports along -conjugated backbones can be modeled on the adiabatic potential energy surface. The adiabatic minimum-energy path of a self-trapped topological soliton is computed for trans-polyacetylene. The frequently cited activation barrier via a ridge shift of the hyper-tangent order parameter overestimates its true value by 14 orders of magnitude. Self-trapped solitons migrate along the Goldstone mode direction with continuously adjusted amplitudes so that a small-width soliton expands and a large-width soliton shrinks when they move uphill. A soliton with the critical width may migrate without any amplitude modifications. In an open chain as solitons move from the chain center toward a chain edge, the minimum-energy path first follows a tilted washboard. Such a generic constrained Goldstone mode relaxation
Phase behavior of polyampholytes from charged hard-sphere chain model.
Jiang, Jianwen; Feng, Jian; Liu, Honglai; Hu, Ying
2006-04-14
A molecular thermodynamic theory is developed for polyampholytes from the coarse-grained charged hard-sphere chain model. The phase behavior of polyampholytes with variations in sequence and chain length is satisfactorily predicted by the theory, consistent with simulation results and experimental observations. At a fixed chain length, the phase envelope expands as the sequence of charge distribution becomes less random. With increasing chain length, the phase envelope expands for diblock and random polyampholytes, but shrinks for zwitterionic polyampholytes. The predicted critical temperature, density, and pressure exhibit scaling relations with chain length for all the three (diblock, random, and zwitterionic) polyampholytes.
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.
Gamma-Ray Pulsars Models and Predictions
Harding, A K
2001-01-01
Pulsed emission from gamma-ray pulsars originates inside the magnetosphere, from radiation by charged particles accelerated near the magnetic poles or in the outer gaps. In polar cap models, the high energy spectrum is cut off by magnetic pair production above an energy that is dependent on the local magnetic field strength. While most young pulsars with surface fields in the range B = 10^{12} - 10^{13} G are expected to have high energy cutoffs around several GeV, the gamma-ray spectra of old pulsars having lower surface fields may extend to 50 GeV. Although the gamma-ray emission of older pulsars is weaker, detecting pulsed emission at high energies from nearby sources would be an important confirmation of polar cap models. Outer gap models predict more gradual high-energy turnovers at around 10 GeV, but also predict an inverse Compton component extending to TeV energies. Detection of pulsed TeV emission, which would not survive attenuation at the polar caps, is thus an important test of outer gap models. N...
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.
New charged shear-free relativistic models with heat flux
Nyonyi, Y.; Maharaj, S. D.; Govinder, K. S.
2013-11-01
We study shear-free spherically symmetric relativistic gravitating fluids with heat flow and electric charge. The solution to the Einstein-Maxwell system is governed by the generalised pressure isotropy condition which contains a contribution from the electric field. This condition is a highly nonlinear partial differential equation. We analyse this master equation using Lie's group theoretic approach. The Lie symmetry generators that leave the equation invariant are found. The first generator is independent of the electromagnetic field. The second generator depends critically on the form of the charge, which is determined explicitly in general. We provide exact solutions to the gravitational potentials using the symmetries admitted by the equation. Our new exact solutions contain earlier results without charge. We show that other charged solutions, related to the Lie symmetries, may be generated using the algorithm of Deng. This leads to new classes of charged Deng models which are generalisations of conformally flat metrics.
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...
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...
Charging of mobile services by mobile payment reference model
Pousttchi, Key; Wiedemann, Dietmar Georg
2005-01-01
The purpose of the paper is to analyze mobile payments in the mobile commerce scenario. Therefore, we first classify the mobile payment in the mobile commerce scenario by explaining general offer models, charging concepts, and intermediaries. Second, we describe the mobile payment reference model, especially, the mobile payment reference organization model and different mobile payment standard types. Finally, we conclude our findings.
Polaron assisted charge transfer in model biological systems
Li, Guangqi; Movaghar, Bijan
2016-11-01
We use a tight binding Hamiltonian to simulate the electron transfer from an initial charge-separating exciton to a final target state through a two-arm transfer model. The structure is copied from the model frequently used to describe electron harvesting in photosynthesis (photosystems I). We use this network to provide proof of principle for dynamics, in quantum system/bath networks, especially those involving interference pathways, and use these results to make predictions on artificially realizable systems. Each site is coupled to the phonon bath via several electron-phonon couplings. The assumed large energy gaps and weak tunneling integrals linking the last 3 sites give rise to"Stark Wannier like" quantum localization; electron transfer to the target cluster becomes impossible without bath coupling. As a result of the electron-phonon coupling, local electronic energies relax when the site is occupied, and transient polaronic states are formed as photo-generated electrons traverse the system. For a symmetric constructively interfering two pathway network, the population is shared equally between two sets of equivalent sites and therefore the polaron energy shift is smaller. The smaller energy shift however makes the tunnel transfer to the last site slower or blocks it altogether. Slight disorder (or thermal noise) can break the symmetry, permitting essentially a "one path", and correspondingly more efficient transfer.
Simple model for fault-charged hydrothermal systems
Energy Technology Data Exchange (ETDEWEB)
Bodvarsson, G.S.; Miller, C.W.; Benson, S.M.
1981-06-01
A two-dimensional transient model of fault-charged hydrothermal systems has been developed. The model can be used to analyze temperature data from fault-charged hydrothermal systems, estimate the recharge rate from the fault, and determine how long the system has been under natural development. The model can also be used for theoretical studies of the development of fault-controlled hydrothermal systems. The model has been tentatively applied to the low-temperature hydrothermal system at Susanville, California. A resonable match was obtained with the observed temperature data, and a hot water recharge rate of 9 x 10{sup -6} m{sup 3}s/m was calculated.
Extended Holstein polaron model for charge transfer in dry DNA
Institute of Scientific and Technical Information of China (English)
Liu Tao; Wang Yi; Wang Ke-Lin
2007-01-01
The variational method is applied to the study of charge transfer in dry DNA by using an extended Holstein small polaron model in two cases: the site-dependent finite-chain discrete case and the site-independent continuous one. The treatments in the two cases are proven to be consistent in theory and calculation. Discrete and continuous treatments of Holstein model both can yield a nonlinear equation to describe the charge migration in an actual long-range DNA chain.Our theoretical results of binding energy Eb, probability amplitude of charge carrier φ and the relation between energy and charge-lattice coupling strength are in accordance with the available experimental results and recent theoretical calculations.
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.
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...
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...
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.
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.
PREDICT : model for prediction of survival in localized prostate cancer
Kerkmeijer, Linda G W; Monninkhof, Evelyn M.; van Oort, Inge M.; van der Poel, Henk G.; de Meerleer, Gert; van Vulpen, Marco
2016-01-01
Purpose: Current models for prediction of prostate cancer-specific survival do not incorporate all present-day interventions. In the present study, a pre-treatment prediction model for patients with localized prostate cancer was developed.Methods: From 1989 to 2008, 3383 patients were treated with I
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.
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.
Modeling, hybridization, and optimal charging of electrical energy storage systems
Parvini, Yasha
The rising rate of global energy demand alongside the dwindling fossil fuel resources has motivated research for alternative and sustainable solutions. Within this area of research, electrical energy storage systems are pivotal in applications including electrified vehicles, renewable power generation, and electronic devices. The approach of this dissertation is to elucidate the bottlenecks of integrating supercapacitors and batteries in energy systems and propose solutions by the means of modeling, control, and experimental techniques. In the first step, the supercapacitor cell is modeled in order to gain fundamental understanding of its electrical and thermal dynamics. The dependence of electrical parameters on state of charge (SOC), current direction and magnitude (20-200 A), and temperatures ranging from -40°C to 60°C was embedded in this computationally efficient model. The coupled electro-thermal model was parameterized using specifically designed temporal experiments and then validated by the application of real world duty cycles. Driving range is one of the major challenges of electric vehicles compared to combustion vehicles. In order to shed light on the benefits of hybridizing a lead-acid driven electric vehicle via supercapacitors, a model was parameterized for the lead-acid battery and combined with the model already developed for the supercapacitor, to build the hybrid battery-supercapacitor model. A hardware in the loop (HIL) setup consisting of a custom built DC/DC converter, micro-controller (muC) to implement the power management strategy, 12V lead-acid battery, and a 16.2V supercapacitor module was built to perform the validation experiments. Charging electrical energy storage systems in an efficient and quick manner, motivated to solve an optimal control problem with the objective of maximizing the charging efficiency for supercapacitors, lead-acid, and lithium ion batteries. Pontryagins minimum principle was used to solve the problems
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).
Predictive Modeling of Cardiac Ischemia
Anderson, Gary T.
1996-01-01
The goal of the Contextual Alarms Management System (CALMS) project is to develop sophisticated models to predict the onset of clinical cardiac ischemia before it occurs. The system will continuously monitor cardiac patients and set off an alarm when they appear about to suffer an ischemic episode. The models take as inputs information from patient history and combine it with continuously updated information extracted from blood pressure, oxygen saturation and ECG lines. Expert system, statistical, neural network and rough set methodologies are then used to forecast the onset of clinical ischemia before it transpires, thus allowing early intervention aimed at preventing morbid complications from occurring. The models will differ from previous attempts by including combinations of continuous and discrete inputs. A commercial medical instrumentation and software company has invested funds in the project with a goal of commercialization of the technology. The end product will be a system that analyzes physiologic parameters and produces an alarm when myocardial ischemia is present. If proven feasible, a CALMS-based system will be added to existing heart monitoring hardware.
Forte, V.; Benedetto, E.; McAteer, M.
2016-12-01
The CERN Proton Synchrotron booster (PSB) is one of the machines of the LHC injector chain which will be upgraded within the LHC Injectors Upgrade (LIU) project. The injection energy of the PSB will be increased to 160 MeV in order to mitigate direct space charge effects, considered to be the main performance limitation, aiming 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. As a first step, benchmarking between simulations and measurements is needed. Efforts to establish a realistic modeling of field and alignment errors aim at extending the basic model of the machine toward a more realistic one. Simulations of beam dynamics with strong space charge and realistic errors are presented and analyzed in this paper.
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.
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.
Exact solutions to model surface and volume charge distributions
Mukhopadhyay, S.; Majumdar, N.; Bhattacharya, P.; Jash, A.; Bhattacharya, D. S.
2016-10-01
Many important problems in several branches of science and technology deal with charges distributed along a line, over a surface and within a volume. Recently, we have made use of new exact analytic solutions of surface charge distributions to develop the nearly exact Boundary Element Method (neBEM) toolkit. This 3D solver has been successful in removing some of the major drawbacks of the otherwise elegant Green's function approach and has been found to be very accurate throughout the computational domain, including near- and far-field regions. Use of truly distributed singularities (in contrast to nodally concentrated ones) on rectangular and right-triangular elements used for discretizing any three-dimensional geometry has essentially removed many of the numerical and physical singularities associated with the conventional BEM. In this work, we will present this toolkit and the development of several numerical models of space charge based on exact closed-form expressions. In one of the models, Particles on Surface (ParSur), the space charge inside a small elemental volume of any arbitrary shape is represented as being smeared on several surfaces representing the volume. From the studies, it can be concluded that the ParSur model is successful in getting the estimates close to those obtained using the first-principles, especially close to and within the cell. In the paper, we will show initial applications of ParSur and other models in problems related to high energy physics.
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...
Model for Charge Transport in Ferroelectric Nanocomposite Film
Directory of Open Access Journals (Sweden)
Meng H. Lean
2015-01-01
Full Text Available This paper describes 3D particle-in-cell simulation of charge injection and transport through nanocomposite film comprised of ferroelectric ceramic nanofillers in an amorphous polymer matrix and/or semicrystalline ferroelectric polymer with varying degrees of crystallinity. The classical electrical double layer model for a monopolar core is extended to represent the nanofiller/nanocrystallite by replacing it with a dipolar core. Charge injection at the electrodes assumes metal-polymer Schottky emission at low to moderate fields and Fowler-Nordheim tunneling at high fields. Injected particles propagate via field-dependent Poole-Frenkel mobility. The simulation algorithm uses a boundary integral equation method for solution of the Poisson equation coupled with a second-order predictor-corrector scheme for robust time integration of the equations of motion. The stability criterion of the explicit algorithm conforms to the Courant-Friedrichs-Levy limit assuring robust and rapid convergence. Simulation results for BaTiO3 nanofiller in amorphous polymer matrix and semicrystalline PVDF with varying degrees of crystallinity indicate that charge transport behavior depends on nanoparticle polarization with antiparallel orientation showing the highest conduction and therefore the lowest level of charge trapping in the interaction zone. Charge attachment to nanofillers and nanocrystallites increases with vol% loading or degree of crystallinity and saturates at 30–40 vol% for the set of simulation parameters.
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 ...
Partial Model of Insulator/Insulator Contact Charging
Hogue, Michael; Calle, C. I.; Buhler, C. R.; Mucciolo, E. R.
2005-01-01
Two papers present a two-phase equilibrium model that partly explains insulator/ insulator contact charging. In this model, a vapor of ions within a gas is in equilibrium with a submonolayer of ions of the same species that have been adsorbed on the surface of an insulator. The surface is modeled as having localized states, each with a certain energy of adsorption for an ion. In an earlier version of the model described in the first paper, the ions do not interact with each other. Using the grand canonical ensemble, the chemical potentials of both vapor and absorbed phases are derived and equated to determine the vapor pressure. If a charge is assigned to the vapor particles (in particular, if single ionization is assumed), then the surface charge density associated with adsorbed ions can be calculated as a function of pressure. In a later version of the model presented in the second paper, the submodel of the vapor phase is extended to include electrostatic interactions between vapor ions and adsorbed ones as well as the screening effect, at a given distance from the surface, of ions closer to the surface. Theoretical values of this model closely match preliminary experimental data on the discharge of insulators as a function of pressure.
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...
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
Predictive Model Assessment for Count Data
2007-09-05
critique count regression models for patent data, and assess the predictive performance of Bayesian age-period-cohort models for larynx cancer counts...the predictive performance of Bayesian age-period-cohort models for larynx cancer counts in Germany. We consider a recent suggestion by Baker and...Figure 5. Boxplots for various scores for patent data count regressions. 11 Table 1 Four predictive models for larynx cancer counts in Germany, 1998–2002
Charge-to-mass dispersion methods for abrasion-ablation fragmentation models
Townsend, L. W.; Norbury, J. W.
1985-01-01
Methods to describe the charge-to-mass dispersion distributions of projectile prefragments are presented and used to determine individual isotope cross-sections or various elements produced in the fragmentation of relativistic argon nuclei by carbon targets. Although slight improvements in predicted cross-sections are obtained for the quantum mechanical giant dipole resonance (GDR) distribution when compared qith the predictions of the geometric GDR model, the closest agreement between theory and experiment continues to be obtained with the simple hypergeometric distribution, which treats the nucleons in the nucleus as completely uncorrelated.
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.
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.
EFFICIENT PREDICTIVE MODELLING FOR ARCHAEOLOGICAL RESEARCH
Balla, A.; Pavlogeorgatos, G.; Tsiafakis, D.; Pavlidis, G.
2014-01-01
The study presents a general methodology for designing, developing and implementing predictive modelling for identifying areas of archaeological interest. The methodology is based on documented archaeological data and geographical factors, geospatial analysis and predictive modelling, and has been applied to the identification of possible Macedonian tombs’ locations in Northern Greece. The model was tested extensively and the results were validated using a commonly used predictive gain,...
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.
How to Establish Clinical Prediction Models
Directory of Open Access Journals (Sweden)
Yong-ho Lee
2016-03-01
Full Text Available A clinical prediction model can be applied to several challenging clinical scenarios: screening high-risk individuals for asymptomatic disease, predicting future events such as disease or death, and assisting medical decision-making and health education. Despite the impact of clinical prediction models on practice, prediction modeling is a complex process requiring careful statistical analyses and sound clinical judgement. Although there is no definite consensus on the best methodology for model development and validation, a few recommendations and checklists have been proposed. In this review, we summarize five steps for developing and validating a clinical prediction model: preparation for establishing clinical prediction models; dataset selection; handling variables; model generation; and model evaluation and validation. We also review several studies that detail methods for developing clinical prediction models with comparable examples from real practice. After model development and vigorous validation in relevant settings, possibly with evaluation of utility/usability and fine-tuning, good models can be ready for the use in practice. We anticipate that this framework will revitalize the use of predictive or prognostic research in endocrinology, leading to active applications in real clinical practice.
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 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.
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.
Comparison of Prediction-Error-Modelling Criteria
DEFF Research Database (Denmark)
Jørgensen, John Bagterp; Jørgensen, Sten Bay
2007-01-01
is a realization of a continuous-discrete multivariate stochastic transfer function model. The proposed prediction error-methods are demonstrated for a SISO system parameterized by the transfer functions with time delays of a continuous-discrete-time linear stochastic system. The simulations for this case suggest......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...... computational resources. The identification method is suitable for predictive control....
Toward a predictive understanding of water and charge transport in proton exchange membranes.
Selvan, Myvizhi Esai; Calvo-Muñoz, Elisa; Keffer, David J
2011-03-31
An analytical model for water and charge transport in highly acidic and highly confined systems such as proton exchange membranes of fuel cells is developed and compared to available experimental data. The model is based on observations from both experiment and multiscale simulation. The model accounts for three factors in the system including acidity, confinement, and connectivity. This model has its basis in the molecular-level mechanisms of water transport but has been coarse-grained to the extent that it can be expressed in an analytical form. The model uses the concentration of H(3)O(+) ion to characterize acidity, interfacial surface area per water molecule to characterize confinement, and percolation theory to describe connectivity. Several important results are presented. First, an integrated multiscale simulation approach including both molecular dynamics simulation and confined random walk theory is capable of quantitatively reproducing experimentally measured self-diffusivities of water in the perfluorinated sulfonic acid proton exchange membrane material, Nafion. The simulations, across a range of hydration conditions from minimally hydrated to fully saturated, have an average error for the self-diffusivity of water of 16% relative to experiment. Second, accounting for three factors-acidity, confinement, and connectivity-is necessary and sufficient to understand the self-diffusivity of water in proton exchange membranes. Third, an analytical model based on percolation theory is capable of quantitatively reproducing experimentally measured self-diffusivities of both water and charge in Nafion across a full range of hydration.
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.
Characterization and dynamic charge dependent modeling of conducting polymer trilayer bending
Farajollahi, Meisam; Sassani, Farrokh; Naserifar, Naser; Fannir, Adelyne; Plesse, Cédric; Nguyen, Giao T. M.; Vidal, Frédéric; Madden, John D. W.
2016-11-01
Trilayer bending actuators are charge driven devices that have the ability to function in air and provide large mechanical amplification. The electronic and mechanical properties of these actuators are known to be functions of their charge state making prediction of their responses more difficult when they operate over their full range of deformation. In this work, a combination of state space representation and a two-dimensional RC transmission line model are used to implement a nonlinear time variant model for conducting polymer-based trilayer actuators. Electrical conductivity and Young’s modulus of electromechanically active PEDOT conducting polymer containing films as a function of applied voltage were measured and incorporated into the model. A 16% drop in Young’s modulus and 24 times increase in conductivity are observed by oxidizing the PEDOT. A closed form formulation for radius of curvature of trilayer actuators considering asymmetric and location dependent Young’s modulus and conductivity in the conducting polymer layers is derived and implemented in the model. The nonlinear model shows the capability to predict the radius of curvature as a function of time and position with reasonable consistency (within 4%). The formulation is useful for general trilayer configurations to calculate the radius of curvature as a function of time. The proposed electrochemical modeling approach may also be useful for modeling energy storage devices.
Case studies in archaeological predictive modelling
Verhagen, Jacobus Wilhelmus Hermanus Philippus
2007-01-01
In this thesis, a collection of papers is put together dealing with various quantitative aspects of predictive modelling and archaeological prospection. Among the issues covered are the effects of survey bias on the archaeological data used for predictive modelling, and the complexities of testing p
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.
Development of a charge-transfer distribution model for stack simulation of solid oxide fuel cells
Onaka, H.; Iwai, H.; Kishimoto, M.; Saito, M.; Yoshida, H.; Brus, G.; Szmyd, J. S.
2016-09-01
An overpotential model for planar solid oxide fuel cells (SOFCs) is developed and applied to a stack numerical simulation. Charge-transfer distribution within the electrodes are approximated using an exponential function, based on which the Ohmic loss and activation overpotential are evaluated. The predicted current-voltage characteristics agree well with the experimental results, and also the overpotentials within the cell can reproduce the results obtained from a numerical analysis where the distribution of the charge-transfer current within the electrodes is fully solved. The proposed model is expected to be useful to maintain the accuracy of SOFC simulations when the cell components, consisting of anode, electrolyte and cathode, are simplified into one layer element.
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.
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...
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...
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.
Directory of Open Access Journals (Sweden)
Giuliano Marchi
2015-10-01
Full Text Available ABSTRACT Intrinsic equilibrium constants of 17 representative Brazilian Oxisols were estimated from potentiometric titration measuring the adsorption of H+ and OH− on amphoteric surfaces in suspensions of varying ionic strength. Equilibrium constants were fitted to two surface complexation models: diffuse layer and constant capacitance. The former was fitted by calculating total site concentration from curve fitting estimates and pH-extrapolation of the intrinsic equilibrium constants to the PZNPC (hand calculation, considering one and two reactive sites, and by the FITEQL software. The latter was fitted only by FITEQL, with one reactive site. Soil chemical and physical properties were correlated to the intrinsic equilibrium constants. Both surface complexation models satisfactorily fit our experimental data, but for results at low ionic strength, optimization did not converge in FITEQL. Data were incorporated in Visual MINTEQ and they provide a modeling system that can predict protonation-dissociation reactions in the soil surface under changing environmental conditions.
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.
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.
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...
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.
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...
Phenomenological Model of Charge Localization in the Layered Manganites
Gray, Kenneth E.; Badica, Elvira
2003-03-01
The connection of magnetic order with charge delocalization in manganites has received considerable interest recently, and the need to go beyond double exchange (DE) to explain the localized state above TC was first introduced by Millis, et al [Phys. Rev. Lett. 74, 5144 (1995)]. In this spirit, we propose a simple model that can explain the various ground states for layered manganites, La_2-2xSr_1+2xMn_2O_7, in terms of the relative energy gain due to DE compared to a phenomenological localization parameter. This model includes antiferromagnetic (AF) superexchange and thus can also be used for layered manganites exhibiting A-type AF order within the bilayer that we find to be either conducting (x=0.54) or insulating (x=0.48). In a magnetic field, the latter case shows a first order metal-insulator transition that is a signature of a crossover of these energies of the localized and delocalized states. Experimentally, localized states seem to be most strongly favored for x 0.50 although the low-temperature state is not always the CE state and quasi-bi-strip charge order has been observed for x=0.48 by Kubota, et al [J. Phys. Soc. Japan, 69, 1986 (2000)].
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 foun- dations. 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 electrody- namics 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” [1, 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 [2] with the theory of the Planck vacuum (PV [3], the basic idea for the model following from [2] with the PV theory adding some important details.
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.
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.
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.
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.
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.
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.
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.
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.
Charged single alpha-helices in proteomes revealed by a consensus prediction approach.
Gáspári, Zoltán; Süveges, Dániel; Perczel, András; Nyitray, László; Tóth, Gábor
2012-04-01
Charged single α-helices (CSAHs) constitute a recently recognized protein structural motif. Its presence and role is characterized in only a few proteins. To explore its general features, a comprehensive study is necessary. We have set up a consensus prediction method available as a web service (at http://csahserver.chem.elte.hu) and downloadable scripts capable of predicting CSAHs from protein sequences. Using our method, we have performed a comprehensive search on the UniProt database. We found that the motif is very rare but seems abundant in proteins involved in symbiosis and RNA binding/processing. Although there are related proteins with CSAH segments, the motif shows no deep conservation in protein families. We conclude that CSAH-containing proteins, although rare, are involved in many key biological processes. Their conservation pattern and prevalence in symbiosis-associated proteins suggest that they might be subjects of relatively rapid molecular evolution and thus can contribute to the emergence of novel functions.
Modeling of protein-anion exchange resin interaction for the human growth hormone charge variants.
Lapelosa, Mauro; Patapoff, Thomas W; Zarraga, Isidro E
2015-12-01
Modeling ion exchange chromatography (IEC) behavior has generated significant interest because of the wide use of IEC as an analytical technique as well as a preparative protein purification process; indeed there is a need for better understanding of what drives the unique behavior of protein charge variants. We hypothesize that a complex protein molecule, which contains both hydrophobic and charged moieties, would interact strongly with an in silico designed resin through charged electrostatic patches on the surface of the protein. In the present work, variants of recombinant human growth hormone that mimic naturally-occurring deamidation products were produced and characterized in silico. The study included these four variants: rhGH, N149D, N152D, and N149D/N152D. Poisson-Boltzmann calculations were used to determine surface electrostatic potential. Metropolis Monte Carlo simulations were carried out with the resulting variants to simulate IEC systems, examining the free energy of the interaction of the protein with an in silico anion exchange column represented by polylysine polypeptide. The results show that the charge variants have different average binding energies and the free energy of interaction can be used to predict the retention time for the different variants.
Posterior Predictive Model Checking in Bayesian Networks
Crawford, Aaron
2014-01-01
This simulation study compared the utility of various discrepancy measures within a posterior predictive model checking (PPMC) framework for detecting different types of data-model misfit in multidimensional Bayesian network (BN) models. The investigated conditions were motivated by an applied research program utilizing an operational complex…
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.
Universal Finite Size Corrections and the Central Charge in Non-solvable Ising Models
Giuliani, Alessandro; Mastropietro, Vieri
2013-11-01
We investigate a non-solvable two-dimensional ferromagnetic Ising model with nearest neighbor plus weak finite range interactions of strength λ. 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 subleading term to the free energy, as proposed by Affleck and Blote-Cardy-Nightingale, is constant and equal to 1/2 for all and λ 0 a small but finite convergence radius. This is one of the very few cases where the predictions of CFT can be rigorously verified starting from a microscopic non solvable statistical model. The proof uses a combination of rigorous renormalization group methods with a novel partition function inequality, valid for ferromagnetic interactions.
Risk terrain modeling predicts child maltreatment.
Daley, Dyann; Bachmann, Michael; Bachmann, Brittany A; Pedigo, Christian; Bui, Minh-Thuy; Coffman, Jamye
2016-12-01
As indicated by research on the long-term effects of adverse childhood experiences (ACEs), maltreatment has far-reaching consequences for affected children. Effective prevention measures have been elusive, partly due to difficulty in identifying vulnerable children before they are harmed. This study employs Risk Terrain Modeling (RTM), an analysis of the cumulative effect of environmental factors thought to be conducive for child maltreatment, to create a highly accurate prediction model for future substantiated child maltreatment cases in the City of Fort Worth, Texas. The model is superior to commonly used hotspot predictions and more beneficial in aiding prevention efforts in a number of ways: 1) it identifies the highest risk areas for future instances of child maltreatment with improved precision and accuracy; 2) it aids the prioritization of risk-mitigating efforts by informing about the relative importance of the most significant contributing risk factors; 3) since predictions are modeled as a function of easily obtainable data, practitioners do not have to undergo the difficult process of obtaining official child maltreatment data to apply it; 4) the inclusion of a multitude of environmental risk factors creates a more robust model with higher predictive validity; and, 5) the model does not rely on a retrospective examination of past instances of child maltreatment, but adapts predictions to changing environmental conditions. The present study introduces and examines the predictive power of this new tool to aid prevention efforts seeking to improve the safety, health, and wellbeing of vulnerable children.
Veronesi, Bellina; de Haar, Colin; Lee, Lseng; Oortgiesen, Marga
2002-02-01
the IL-6 released by each fraction (r2 > or = 0.76) after both 4 and 16 h exposures. The biological effects of each PM were compared with their physicochemical characteristics. No correlation was found between increases in [Ca2+]i or cytokine release and a PM's acidity or the number or size of its visible (> or = 2.0 microm) particles. However, the surface charge of PM field particles, when measured in the KGM exposure medium, showed a high correlation (r2 > or = 0.94) with the IL-6 release by field PM after both 4 and 16 h exposure. Increases in [Ca2+]i also correlated (r2 = 0.85) with the surface charge of PM field particles when measured in KGM. These data indicate that the surface charge (i.e., zeta potential) carried on PM's visible field particles predicts their differential release of the inflammatory cytokine IL-6 in cultures of human respiratory epithelial cells.
Probabilistic modeling of nodal electric vehicle load due to fast charging stations
DEFF Research Database (Denmark)
Tang, Difei; Wang, Peng; Wu, Qiuwei
2016-01-01
station into consideration. Fuzzy logic inference system is applied to simulate the charging decision of EV drivers at fast charging station. Due to increasing EV loads in power system, the potential traffic congestion in fast charging stations is modeled and evaluated by queuing theory with spatial...... operation of both traffic and power systems. This paper proposes a probabilistic approach to model the nodal EV load at fast charging stations in integrated power and transport systems. Following the introduction of the spatial-temporal model of moving EV loads, we extended the model by taking fast charging...
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.
Spatial Economics Model Predicting Transport Volume
Directory of Open Access Journals (Sweden)
Lu Bo
2016-10-01
Full Text Available It is extremely important to predict the logistics requirements in a scientific and rational way. However, in recent years, the improvement effect on the prediction method is not very significant and the traditional statistical prediction method has the defects of low precision and poor interpretation of the prediction model, which cannot only guarantee the generalization ability of the prediction model theoretically, but also cannot explain the models effectively. Therefore, in combination with the theories of the spatial economics, industrial economics, and neo-classical economics, taking city of Zhuanghe as the research object, the study identifies the leading industry that can produce a large number of cargoes, and further predicts the static logistics generation of the Zhuanghe and hinterlands. By integrating various factors that can affect the regional logistics requirements, this study established a logistics requirements potential model from the aspect of spatial economic principles, and expanded the way of logistics requirements prediction from the single statistical principles to an new area of special and regional economics.
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
Precision Plate Plan View Pattern Predictive Model
Institute of Scientific and Technical Information of China (English)
ZHAO Yang; YANG Quan; HE An-rui; WANG Xiao-chen; ZHANG Yun
2011-01-01
According to the rolling features of plate mill, a 3D elastic-plastic FEM （finite element model） based on full restart method of ANSYS/LS-DYNA was established to study the inhomogeneous plastic deformation of multipass plate rolling. By analyzing the simulation results, the difference of head and tail ends predictive models was found and modified. According to the numerical simulation results of 120 different kinds of conditions, precision plate plan view pattern predictive model was established. Based on these models, the sizing MAS （mizushima automatic plan view pattern control system） method was designed and used on a 2 800 mm plate mill. Comparing the rolled plates with and without PVPP （plan view pattern predictive） model, the reduced width deviation indicates that the olate !olan view Dattern predictive model is preeise.
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...... that describes the variation between subjects. The ODE setup implies that the variation for a single subject is described by a single parameter (or vector), namely the variance (covariance) of the residuals. Furthermore the prediction of the states is given as the solution to the ODEs and hence assumed...... 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 lepton flavor-violating transitions in color octet model
Energy Technology Data Exchange (ETDEWEB)
Li, Bin; Ma, Xiao-Dong [Nankai University, School of Physics, Tianjin (China); Liao, Yi [Nankai University, School of Physics, Tianjin (China); Chinese Academy of Sciences, CAS Key Laboratory of Theoretical Physics, Institute of Theoretical Physics, Beijing (China); Peking University, Center for High Energy Physics, Beijing (China)
2016-11-15
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 μ - e conversion in nuclei, and for the singlet case the conversion and the decays μ → 3e, eγ play complementary roles in excluding relatively low-mass regions of the octet particles. (orig.)
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.
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.
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...
Numerical determination of the CFT central charge in the site-diluted Ising model
Belov, P A; Sorokin, A O
2016-01-01
We propose a new numerical method to determine the central charge of the conformal field theory models corresponding to the 2D lattice models. In this method, the free energy of the lattice model on the torus is calculated by the Wang-Landau algorithm and then the central charge is obtained from a free energy scaling with respect to the torus radii. The method is applied for determination of the central charge in the site-diluted Ising model.
A predictive model for smart control of a domestic heat pump and thermal storage
Leeuwen, van R.P.; Gebhardt, I.; Wit, de J.B.; Smit, G.J.M.
2016-01-01
The purpose of this paper is to develop and validate a predictive model of a thermal storage which is charged by a heat pump and used for domestic hot water supply. The model is used for smart grid control purposes and requires measurement signals of flow and temperature at the inlet and outlet of t
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...
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.
Rustad, James R.; Wasserman, Evgeny; Felmy, Andrew R.
1999-03-01
A parameterized classical potential model for the interaction of water and hydroxide with iron oxide was used to calculate the optimal proton arrangement and proton binding energies on the (012) surface of hematite. Energy minimization calculations with the parameterized potential model indicate that approximately 75% of adsorbed water molecules are dissociated on this surface, in agreement with recent TPD and HREELS measurements. Surface protonation/deprotonation energies were calculated from the predicted optimal arrangement of protons on the neutral (012) surface. A supercell geometry with translational symmetry in two dimensions and finite in the third dimension (2-D PBC) was assumed. The calculated surface protonation energies were then used to model the experimentally observed surface-charging curve of hematite in aqueous solution. Excellent agreement was found between the calculated and measured surface charge for ionic strengths ranging from 0.001 to 0.1 M. Our calculations favor the value of 8.5 for the pH of zero charge of hematite over the more recent result of 6.7.
Development of a Charge Adjustment Model for Cardiac Catheterization
Brennan, Andrew; Gauvreau, Kimberlee; Connor, Jean; O’Connell, Cheryl; David, Sthuthi; Almodovar, Melvin; DiNardo, James; Banka, Puja; Mayer, John E.; Marshall, Audrey C.; Bergersen, Lisa
2014-01-01
A methodology that would allow for comparison of charges across institutions has not been developed for catheterization in congenital heart disease. A single institution catheterization database with prospectively collected case characteristics was linked to hospital charges related and limited to an episode of care in the catheterization laboratory for fiscal years 2008–2010. Catheterization charge categories (CCC) were developed to group types of catheterization procedures using a combinati...
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.
Predictive model for segmented poly(urea
Directory of Open Access Journals (Sweden)
Frankl P.
2012-08-01
Full Text Available Segmented poly(urea has been shown to be of significant benefit in protecting vehicles from blast and impact and there have been several experimental studies to determine the mechanisms by which this protective function might occur. One suggested route is by mechanical activation of the glass transition. In order to enable design of protective structures using this material a constitutive model and equation of state are needed for numerical simulation hydrocodes. Determination of such a predictive model may also help elucidate the beneficial mechanisms that occur in polyurea during high rate loading. The tool deployed to do this has been Group Interaction Modelling (GIM – a mean field technique that has been shown to predict the mechanical and physical properties of polymers from their structure alone. The structure of polyurea has been used to characterise the parameters in the GIM scheme without recourse to experimental data and the equation of state and constitutive model predicts response over a wide range of temperatures and strain rates. The shock Hugoniot has been predicted and validated against existing data. Mechanical response in tensile tests has also been predicted and validated.
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.
Modeling Transport in Ultrathin Si Nanowires: Charged versus Neutral Impurities
DEFF Research Database (Denmark)
Rurali, Riccardo; Markussen, Troels; Suné, Jordi;
2008-01-01
of this effect are obtained by computing the electronic transmission through wires with either charged or neutral P and B dopants. The dopant potential is obtained from density functional theory (DFT) calculations. Contrary to the neutral case, the transmission through charged dopants cannot be converged within...
Model-based prediction of monoclonal antibody retention in ion-exchange chromatography.
Guélat, Bertrand; Delegrange, Lydia; Valax, Pascal; Morbidelli, Massimo
2013-07-12
In order to support a model-based process design in ion-exchange chromatography, an adsorption equilibrium model was adapted to predict the protein retention behavior from the amino acid sequence and from structural information on the resin. It is based on the computation of protein-resin interactions with a colloidal model and accounts for the contribution of each ionizable amino acid to the protein charge. As a verification of the protein charge model, the experimental titration curve of a monoclonal antibody was compared to its predicted net charge. Using this protein charge model in the computation of the protein-resin interactions, it is possible to predict the adsorption equilibrium constant (i.e. retention factor or Henry constant) with an explicit pH and salt dependence. The application of the model-based predictions for an in silico screening of the protein retention on various stationary phases or, alternatively, for the comparison of various monoclonal antibodies on a given cation-exchanger was demonstrated. Furthermore, considering the structural differences between charge variants of a monoclonal antibody, it was possible to predict their individual retention times. The selectivity between the side variants and the main isoform of the monoclonal antibody were computed. The comparison with the experimental data showed that the model was reliable with respect to the identification of the operating conditions maximizing the selectivity, i.e. the most promising conditions for a monoclonal antibody variant separation. Such predictions can be useful in reducing the experimental effort to identify the parameter space.
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.
Calibrated predictions for multivariate competing risks models.
Gorfine, Malka; Hsu, Li; Zucker, David M; Parmigiani, Giovanni
2014-04-01
Prediction models for time-to-event data play a prominent role in assessing the individual risk of a disease, such as cancer. Accurate disease prediction models provide an efficient tool for identifying individuals at high risk, and provide the groundwork for estimating the population burden and cost of disease and for developing patient care guidelines. We focus on risk prediction of a disease in which family history is an important risk factor that reflects inherited genetic susceptibility, shared environment, and common behavior patterns. In this work family history is accommodated using frailty models, with the main novel feature being allowing for competing risks, such as other diseases or mortality. We show through a simulation study that naively treating competing risks as independent right censoring events results in non-calibrated predictions, with the expected number of events overestimated. Discrimination performance is not affected by ignoring competing risks. Our proposed prediction methodologies correctly account for competing events, are very well calibrated, and easy to implement.
Modelling language evolution: Examples and predictions
Gong, Tao; Shuai, Lan; Zhang, Menghan
2014-06-01
We survey recent computer modelling research of language evolution, focusing on a rule-based model simulating the lexicon-syntax coevolution and an equation-based model quantifying the language competition dynamics. We discuss four predictions of these models: (a) correlation between domain-general abilities (e.g. sequential learning) and language-specific mechanisms (e.g. word order processing); (b) coevolution of language and relevant competences (e.g. joint attention); (c) effects of cultural transmission and social structure on linguistic understandability; and (d) commonalities between linguistic, biological, and physical phenomena. All these contribute significantly to our understanding of the evolutions of language structures, individual learning mechanisms, and relevant biological and socio-cultural factors. We conclude the survey by highlighting three future directions of modelling studies of language evolution: (a) adopting experimental approaches for model evaluation; (b) consolidating empirical foundations of models; and (c) multi-disciplinary collaboration among modelling, linguistics, and other relevant disciplines.
Modelling language evolution: Examples and predictions.
Gong, Tao; Shuai, Lan; Zhang, Menghan
2014-06-01
We survey recent computer modelling research of language evolution, focusing on a rule-based model simulating the lexicon-syntax coevolution and an equation-based model quantifying the language competition dynamics. We discuss four predictions of these models: (a) correlation between domain-general abilities (e.g. sequential learning) and language-specific mechanisms (e.g. word order processing); (b) coevolution of language and relevant competences (e.g. joint attention); (c) effects of cultural transmission and social structure on linguistic understandability; and (d) commonalities between linguistic, biological, and physical phenomena. All these contribute significantly to our understanding of the evolutions of language structures, individual learning mechanisms, and relevant biological and socio-cultural factors. We conclude the survey by highlighting three future directions of modelling studies of language evolution: (a) adopting experimental approaches for model evaluation; (b) consolidating empirical foundations of models; and (c) multi-disciplinary collaboration among modelling, linguistics, and other relevant disciplines.
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.
Model Predictive Control of Sewer Networks
Pedersen, Einar B.; Herbertsson, Hannes R.; Niemann, Henrik; Poulsen, Niels K.; Falk, Anne K. V.
2017-01-01
The developments in solutions for management of urban drainage are of vital importance, as the amount of sewer water from urban areas continues to increase due to the increase of the world’s population and the change in the climate conditions. How a sewer network is structured, monitored and controlled have thus become essential factors for effcient performance of waste water treatment plants. This paper examines methods for simplified modelling and controlling a sewer network. A practical approach to the problem is used by analysing simplified design model, which is based on the Barcelona benchmark model. Due to the inherent constraints the applied approach is based on Model Predictive Control.
Prediction of charge mobility in organic semiconductors with consideration of the grain-size effect
Park, Jin Woo; Lee, Kyu Il; Choi, Youn-Suk; Kim, Jung-Hwa; Jeong, Daun; Kwon, Young-Nam; Park, Jong-Bong; Ahn, Ho Young; Park, Jeong-Il; Lee, Hyo Sug; Shin, Jaikwang
2016-09-01
A new computational model to predict the hole mobility of poly-crystalline organic semiconductors in thin film was developed (refer to Phys. Chem. Chem. Phys., 2016, DOI: 10.1039/C6CP02993K). Site energy differences and transfer integrals in crystalline morphologies of organic molecules were obtained from quantum chemical calculation, in which the periodic boundary condition was efficiently applied to capture the interactions with the surrounding molecules in the crystalline organic layer. Then the parameters were employed in kinetic Monte Carlo (kMC) simulations to estimate the carrier mobility. Carrier transport in multiple directions has been considered in the kMC simulation to mimic polycrystalline characteristic in thin-film condition. Furthermore, the calculated mobility was corrected with a calibration equation based on the microscopic images of thin films to take the effect of grain boundary into account. As a result, good agreement was observed between the predicted and measured hole mobility values for 21 molecular species: the coefficient of determination (R2) was estimated to be 0.83 and the mean absolute error was 1.32 cm2 V-1 s-1. This numerical approach can be applied to any molecules for which crystal structures are available and will provide a rapid and precise way of predicting the device performance.
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
Raman Model Predicting Hardness of Covalent Crystals
Zhou, Xiang-Feng; Qian, Quang-Rui; Sun, Jian; Tian, Yongjun; Wang, Hui-Tian
2009-01-01
Based on the fact that both hardness and vibrational Raman spectrum depend on the intrinsic property of chemical bonds, we propose a new theoretical model for predicting hardness of a covalent crystal. The quantitative relationship between hardness and vibrational Raman frequencies deduced from the typical zincblende covalent crystals is validated to be also applicable for the complex multicomponent crystals. This model enables us to nondestructively and indirectly characterize the hardness o...
Modelling Chemical Reasoning to Predict Reactions
Segler, Marwin H. S.; Waller, Mark P.
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 outpe...
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.
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
A Predictive Model for MSSW Student Success
Napier, Angela Michele
2011-01-01
This study tested a hypothetical model for predicting both graduate GPA and graduation of University of Louisville Kent School of Social Work Master of Science in Social Work (MSSW) students entering the program during the 2001-2005 school years. The preexisting characteristics of demographics, academic preparedness and culture shock along with…
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...
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
Unreachable Setpoints in Model Predictive Control
DEFF Research Database (Denmark)
Rawlings, James B.; Bonné, Dennis; Jørgensen, John Bagterp
2008-01-01
steady state is established for terminal constraint model predictive control (MPC). The region of attraction is the steerable set. Existing analysis methods for closed-loop properties of MPC are not applicable to this new formulation, and a new analysis method is developed. It is shown how to extend...
Leptogenesis in minimal predictive seesaw models
Björkeroth, Fredrik; Varzielas, Ivo de Medeiros; King, Stephen F
2015-01-01
We estimate the Baryon Asymmetry of the Universe (BAU) arising from leptogenesis within a class of minimal predictive seesaw models involving two right-handed neutrinos and simple Yukawa structures with one texture zero. The two right-handed neutrinos are dominantly responsible for the "atmospheric" and "solar" neutrino masses with Yukawa couplings to $(\
A Model for the Coalescence of Abraded Nucleons in Heavy Charged Particle Collisions
de Wet, Wouter; Townsend, Lawrence; Werneth, Charles; Ford, William
2016-09-01
Accurate nuclear reaction models are required by the radiation transport codes used to predict the radiation field behind shielding in the space radiation environment. The resulting particle spectra and their corresponding biological response functions are used to estimate radiation risk to astronauts. Radiation transport codes use nuclear fragmentation models to describe the breakup of heavy charged particles in collisions with constituent nuclei of spacecraft and astronauts. The Relativistic Abrasion-Ablation and De-Excitation Fragmentation code, or RAADFRG, uses an abrasion-ablation reaction mechanism to calculate total and isotopic production cross sections of fragment species from a projectile nucleus. In this reaction mechanism, a fraction of nucleons, which sheared from the projectile nucleus during the abrasion step, coalesce to form various light ions. As with its predecessors, the Nuclear Fragmentation (NUCFRG) series, RAADFRG is being developed for implementation in NASA's deterministic High Charge (Z) and Energy radiation TRaNsport code, HZETRN. In this work, we derive the formalism used in RAADFRG to handle this process. Also, characterization of the model and its sensitivity to the coalescence radius parameterization are investigated. Work supported by NASA Grant NNX10AD18A.
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.
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.
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
Caries risk assessment models in caries prediction
Directory of Open Access Journals (Sweden)
Amila Zukanović
2013-11-01
Full Text Available Objective. The aim of this research was to assess the efficiency of different multifactor models in caries prediction. Material and methods. Data from the questionnaire and objective examination of 109 examinees was entered into the Cariogram, Previser and Caries-Risk Assessment Tool (CAT multifactor risk assessment models. Caries risk was assessed with the help of all three models for each patient, classifying them as low, medium or high-risk patients. The development of new caries lesions over a period of three years [Decay Missing Filled Tooth (DMFT increment = difference between Decay Missing Filled Tooth Surface (DMFTS index at baseline and follow up], provided for examination of the predictive capacity concerning different multifactor models. Results. The data gathered showed that different multifactor risk assessment models give significantly different results (Friedman test: Chi square = 100.073, p=0.000. Cariogram is the model which identified the majority of examinees as medium risk patients (70%. The other two models were more radical in risk assessment, giving more unfavorable risk –profiles for patients. In only 12% of the patients did the three multifactor models assess the risk in the same way. Previser and CAT gave the same results in 63% of cases – the Wilcoxon test showed that there is no statistically significant difference in caries risk assessment between these two models (Z = -1.805, p=0.071. Conclusions. Evaluation of three different multifactor caries risk assessment models (Cariogram, PreViser and CAT showed that only the Cariogram can successfully predict new caries development in 12-year-old Bosnian children.
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
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......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...
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.
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
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...
Gas explosion prediction using CFD models
Energy Technology Data Exchange (ETDEWEB)
Niemann-Delius, C.; Okafor, E. [RWTH Aachen Univ. (Germany); Buhrow, C. [TU Bergakademie Freiberg Univ. (Germany)
2006-07-15
A number of CFD models are currently available to model gaseous explosions in complex geometries. Some of these tools allow the representation of complex environments within hydrocarbon production plants. In certain explosion scenarios, a correction is usually made for the presence of buildings and other complexities by using crude approximations to obtain realistic estimates of explosion behaviour as can be found when predicting the strength of blast waves resulting from initial explosions. With the advance of computational technology, and greater availability of computing power, computational fluid dynamics (CFD) tools are becoming increasingly available for solving such a wide range of explosion problems. A CFD-based explosion code - FLACS can, for instance, be confidently used to understand the impact of blast overpressures in a plant environment consisting of obstacles such as buildings, structures, and pipes. With its porosity concept representing geometry details smaller than the grid, FLACS can represent geometry well, even when using coarse grid resolutions. The performance of FLACS has been evaluated using a wide range of field data. In the present paper, the concept of computational fluid dynamics (CFD) and its application to gas explosion prediction is presented. Furthermore, the predictive capabilities of CFD-based gaseous explosion simulators are demonstrated using FLACS. Details about the FLACS-code, some extensions made to FLACS, model validation exercises, application, and some results from blast load prediction within an industrial facility are presented. (orig.)
A Study On Distributed Model Predictive Consensus
Keviczky, Tamas
2008-01-01
We investigate convergence properties of a proposed distributed model predictive control (DMPC) scheme, where agents negotiate to compute an optimal consensus point using an incremental subgradient method based on primal decomposition as described in Johansson et al. [2006, 2007]. The objective of the distributed control strategy is to agree upon and achieve an optimal common output value for a group of agents in the presence of constraints on the agent dynamics using local predictive controllers. Stability analysis using a receding horizon implementation of the distributed optimal consensus scheme is performed. Conditions are given under which convergence can be obtained even if the negotiations do not reach full consensus.
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.
NONLINEAR MODEL PREDICTIVE CONTROL OF CHEMICAL PROCESSES
Directory of Open Access Journals (Sweden)
R. G. SILVA
1999-03-01
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.
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...
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.
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.
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.
Electron transport and dielectric breakdown in silicon nitride using a charge transport model
Ogden, Sean P.; Lu, Toh-Ming; Plawsky, Joel L.
2016-10-01
Silicon nitride is an important material used in the electronics industry. As such, the electronic transport and reliability of these materials are important to study and understand. We report on a charge transport model to predict leakage current and failure trends based on previously published data for a stoichiometric silicon nitride dielectric. Failure occurs when the defect density increases to a critical value of approximately 6 × 1025 traps/m3. The model's parameters are determined using voltage ramp data only, and yet, the model is also able to predict constant voltage stress failure over a time scale ranging from minutes to months. The successful fit of the model to the experimental data validates our assumption that the dominant defect in the dielectric is the Si dangling bond, located approximately 2.2 eV below the conduction band. A comparison with previous SiCOH simulations shows SiN and SiCOH have similar defect-related material properties. It is also speculated that, based on the estimated parameter values of 2.75 eV for the defect formation activation energy, the materials' TDDB wear-out are caused by broken Si-H bonds, resulting in Si dangling bond defects.
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.
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.
Pressure prediction model for compression garment design.
Leung, W Y; Yuen, D W; Ng, Sun Pui; Shi, S Q
2010-01-01
Based on the application of Laplace's law to compression garments, an equation for predicting garment pressure, incorporating the body circumference, the cross-sectional area of fabric, applied strain (as a function of reduction factor), and its corresponding Young's modulus, is developed. Design procedures are presented to predict garment pressure using the aforementioned parameters for clinical applications. Compression garments have been widely used in treating burning scars. Fabricating a compression garment with a required pressure is important in the healing process. A systematic and scientific design method can enable the occupational therapist and compression garments' manufacturer to custom-make a compression garment with a specific pressure. The objectives of this study are 1) to develop a pressure prediction model incorporating different design factors to estimate the pressure exerted by the compression garments before fabrication; and 2) to propose more design procedures in clinical applications. Three kinds of fabrics cut at different bias angles were tested under uniaxial tension, as were samples made in a double-layered structure. Sets of nonlinear force-extension data were obtained for calculating the predicted pressure. Using the value at 0° bias angle as reference, the Young's modulus can vary by as much as 29% for fabric type P11117, 43% for fabric type PN2170, and even 360% for fabric type AP85120 at a reduction factor of 20%. When comparing the predicted pressure calculated from the single-layered and double-layered fabrics, the double-layered construction provides a larger range of target pressure at a particular strain. The anisotropic and nonlinear behaviors of the fabrics have thus been determined. Compression garments can be methodically designed by the proposed analytical pressure prediction 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.
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...
How to model the interaction of charged Janus particles
Hieronimus, Reint; Raschke, Simon; Heuer, Andreas
2016-08-01
We analyze the interaction of charged Janus particles including screening effects. The explicit interaction is mapped via a least square method on a variable number n of systematically generated tensors that reflect the angular dependence of the potential. For n = 2 we show that the interaction is equivalent to a model previously described by Erdmann, Kröger, and Hess (EKH). Interestingly, this mapping is for n = 2 not able to capture the subtleties of the interaction for small screening lengths. Rather, a larger number of tensors has to be used. We find that the characteristics of the Janus type interaction plays an important role for the aggregation behavior. We obtained cluster structures up to the size of 13 particles for n = 2 and 36 and screening lengths κ-1 = 0.1 and 1.0 via Monte Carlo simulations. The influence of the screening length is analyzed and the structures are compared to results for an electrostatic-type potential and for the multipole-expanded Derjaguin-Landau-Verwey-Overbeek (DLVO) theory. We find that a dipole-like potential (EKH or dipole DLVO approximation) is not able to sufficiently reproduce the anisotropy effects of the potential. Instead, a higher order expansion has to be used to obtain cluster structures that are compatible with experimental observations. The resulting minimum-energy clusters are compared to those of sticky hard sphere systems. Janus particles with a short-range screened interaction resemble sticky hard sphere clusters for all considered particle numbers, whereas for long-range screening even very small clusters are structurally different.
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.
Nonlinear model predictive control theory and algorithms
Grüne, Lars
2017-01-01
This book offers readers a thorough and rigorous introduction to nonlinear model predictive control (NMPC) for discrete-time and sampled-data systems. NMPC schemes with and without stabilizing terminal constraints are detailed, and intuitive examples illustrate the performance of different NMPC variants. NMPC is interpreted as an approximation of infinite-horizon optimal control so that important properties like closed-loop stability, inverse optimality and suboptimality can be derived in a uniform manner. These results are complemented by discussions of feasibility and robustness. An introduction to nonlinear optimal control algorithms yields essential insights into how the nonlinear optimization routine—the core of any nonlinear model predictive controller—works. Accompanying software in MATLAB® and C++ (downloadable from extras.springer.com/), together with an explanatory appendix in the book itself, enables readers to perform computer experiments exploring the possibilities and limitations of NMPC. T...
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
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.
Predictive Modeling in Actinide Chemistry and Catalysis
Energy Technology Data Exchange (ETDEWEB)
Yang, Ping [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2016-05-16
These are slides from a presentation on predictive modeling in actinide chemistry and catalysis. The following topics are covered in these slides: Structures, bonding, and reactivity (bonding can be quantified by optical probes and theory, and electronic structures and reaction mechanisms of actinide complexes); Magnetic resonance properties (transition metal catalysts with multi-nuclear centers, and NMR/EPR parameters); Moving to more complex systems (surface chemistry of nanomaterials, and interactions of ligands with nanoparticles); Path forward and conclusions.
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...
Mukherjee, Goutam; Patra, Niladri; Barua, Poranjyoti; Jayaram, B
2011-04-15
We report here a new and fast approach [Transferable Partial Atomic Charge Model (TPACM4)-upto four bonds] for deriving the partial atomic charges of small molecules for use in protein/DNA-ligand docking and scoring. We have created a look-up table of 5302 atom types to cover the chemical space of C, H, O, N, S, P, F, Cl, and Br atoms in small molecules together with their quantum mechanical RESP fit charges. The atom types defined span diverse plausible chemical environments of each atom in a molecule. The partial charge on any atom in a given molecule is then assigned by a reference to the look-up table. We tested the sensitivity of the TPACM4 partial charges in estimates of hydrogen bond dimers energies, solvation free energies and protein-ligand binding free energies. An average error ±1.11 kcal/mol and a correlation coefficient of 0.90 is obtained in the calculated protein-ligand binding free energies vis-à-vis an RMS error of ±1.02 kcal/mol and a correlation coefficient of 0.92 obtained with RESP fit charges in comparison to experiment. Similar accuracies are realized in predictions of hydrogen bond energies and solvation free energies of small molecules. For a molecule containing 50-55 atoms, the method takes on the order of milliseconds on a single processor machine to assign partial atomic charges. The TPACM4 programme has been web-enabled and made freely accessible at http://www.scfbio-iitd.res.in/software/drugdesign/charge.jsp.
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.
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 s...... as it pinpoints which decisions to be concerned about when the goal is to predict footbridge response. The studies involve estimating footbridge responses using Monte-Carlo simulations and focus is on estimating vertical structural response to single person loading....
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...
A Simple Holographic Model of a Charged Lattice
Aprile, Francesco
2014-01-01
We use holography to compute the conductivity in an inhomogeneous charged scalar background. We work in the probe limit of the four-dimensional Einstein-Maxwell theory coupled to a charged scalar. The background has zero charge density and is constructed by turning on a scalar source deformation with a striped profile. We solve for fluctuations by making use of a Fourier series expansion. This approach turns out to be useful for understanding which couplings become important in our inhomogeneous background. At zero temperature, the conductivity is computed analytically in a small amplitude expansion. At finite temperature, it is computed numerically by truncating the Fourier series to a relevant set of modes. In the real part of the conductivity along the direction of the stripe, we find a Drude-like peak and a delta function with a negative weight. These features are understood from the point of view of spectral weight transfer.
Screening model for nanowire surface-charge sensors in liquid
DEFF Research Database (Denmark)
Sørensen, Martin Hedegård; Mortensen, Asger; Brandbyge, Mads
2007-01-01
The conductance change of nanowire field-effect transistors is considered a highly sensitive probe for surface charge. However, Debye screening of relevant physiological liquid environments challenge device performance due to competing screening from the ionic liquid and nanowire charge carriers......., and the length of the functionalization molecules. The analytical results are compared to finite-element calculations on a realistic geometry. ©2007 American Institute of Physics........ 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...
Statistical Seasonal Sea Surface based Prediction Model
Suarez, Roberto; Rodriguez-Fonseca, Belen; Diouf, Ibrahima
2014-05-01
The interannual variability of the sea surface temperature (SST) plays a key role in the strongly seasonal rainfall regime on the West African region. The predictability of the seasonal cycle of rainfall is a field widely discussed by the scientific community, with results that fail to be satisfactory due to the difficulty of dynamical models to reproduce the behavior of the Inter Tropical Convergence Zone (ITCZ). To tackle this problem, a statistical model based on oceanic predictors has been developed at the Universidad Complutense of Madrid (UCM) with the aim to complement and enhance the predictability of the West African Monsoon (WAM) as an alternative to the coupled models. The model, called S4CAST (SST-based Statistical Seasonal Forecast) is based on discriminant analysis techniques, specifically the Maximum Covariance Analysis (MCA) and Canonical Correlation Analysis (CCA). Beyond the application of the model to the prediciton of rainfall in West Africa, its use extends to a range of different oceanic, atmospheric and helth related parameters influenced by the temperature of the sea surface as a defining factor of variability.
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.
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.
Multipole correction of atomic monopole models of molecular charge distribution. I. Peptides
Sokalski, W. A.; Keller, D. A.; Ornstein, R. L.; Rein, R.
1993-01-01
The defects in atomic monopole models of molecular charge distribution have been analyzed for several model-blocked peptides and compared with accurate quantum chemical values. The results indicate that the angular characteristics of the molecular electrostatic potential around functional groups capable of forming hydrogen bonds can be considerably distorted within various models relying upon isotropic atomic charges only. It is shown that these defects can be corrected by augmenting the atomic point charge models by cumulative atomic multipole moments (CAMMs). Alternatively, sets of off-center atomic point charges could be automatically derived from respective multipoles, providing approximately equivalent corrections. For the first time, correlated atomic multipoles have been calculated for N-acetyl, N'-methylamide-blocked derivatives of glycine, alanine, cysteine, threonine, leucine, lysine, and serine using the MP2 method. The role of the correlation effects in the peptide molecular charge distribution are discussed.
Charge-state-dependent energy loss of slow ions. II. Statistical atom model
Wilhelm, Richard A.; Möller, Wolfhard
2016-05-01
A model for charge-dependent energy loss of slow ions is developed based on the Thomas-Fermi statistical model of atoms. Using a modified electrostatic potential which takes the ionic charge into account, nuclear and electronic energy transfers are calculated, the latter by an extension of the Firsov model. To evaluate the importance of multiple collisions even in nanometer-thick target materials we use the charge-state-dependent potentials in a Monte Carlo simulation in the binary collision approximation and compare the results to experiment. The Monte Carlo results reproduce the incident charge-state dependence of measured data well [see R. A. Wilhelm et al., Phys. Rev. A 93, 052708 (2016), 10.1103/PhysRevA.93.052708], even though the experimentally observed charge exchange dependence is not included in the model.
Water polarization induced by thermal gradients: the extended simple point charge model (SPC/E).
Armstrong, J A; Bresme, F
2013-07-07
We investigate the non-equilibrium response of extended simple point charge (SPC/E) water to thermal gradients. Using non-equilibrium molecular dynamics simulations, we show that SPC/E water features the thermo-polarization orientation effect, namely, water becomes polarized as a response to a thermal gradient. The polarization field increases linearly with the thermal gradient, in agreement with predictions of non-equilibrium thermodynamics theory. This observation confirms the generality of the thermo-polarization effect, first reported using the Modified Central Force Model (MCFM), and shows this physical effect is present irrespective of the water model details, in particular, dipole moment magnitude and model flexibility. The magnitude of the effect is the same for both models, although the sign of the electrostatic field is reversed in going from the MCFM to the SPC/E model. We further analyze the impact that the molecular geometry and mass distribution has on the magnitude of the polarization. Our results indicate that the thermo-polarization effect should be observed in a wide range of polar fluids, including fluids where hydrogen bonding is not present. Using various molecular models, we show that the polarization of these fluids under appropriate thermodynamic conditions can be of the same order or stronger than in water.
Predictive modeling by the cerebellum improves proprioception.
Bhanpuri, Nasir H; Okamura, Allison M; Bastian, Amy J
2013-09-04
Because sensation is delayed, real-time movement control requires not just sensing, but also predicting limb position, a function hypothesized for the cerebellum. Such cerebellar predictions could contribute to perception of limb position (i.e., proprioception), particularly when a person actively moves the limb. Here we show that human cerebellar patients have proprioceptive deficits compared with controls during active movement, but not when the arm is moved passively. Furthermore, when healthy subjects move in a force field with unpredictable dynamics, they have active proprioceptive deficits similar to cerebellar patients. Therefore, muscle activity alone is likely insufficient to enhance proprioception and predictability (i.e., an internal model of the body and environment) is important for active movement to benefit proprioception. We conclude that cerebellar patients have an active proprioceptive deficit consistent with disrupted movement prediction rather than an inability to generally enhance peripheral proprioceptive signals during action and suggest that active proprioceptive deficits should be considered a fundamental cerebellar impairment of clinical importance.
Johnson, Erin R; Salamone, Michela; Bietti, Massimo; DiLabio, Gino A
2013-02-07
Conventional density-functional theory (DFT) has the potential to overbind radical-molecule complexes because of erroneous charge transfer. We examined this behavior by exploring the ability of various DFT approximations to predict fractional charge transfer and by quantifying the overbinding in a series of complexes. It is demonstrated that too much charge is transferred from molecules to radicals when the radical singly unoccupied molecular orbitals are predicted to be erroneously too low in energy relative to the molecule highest occupied molecular orbitals, leading to excessive Coulombic attraction. In this respect, DFT methods formulated with little or no Hartree-Fock exchange perform most poorly. The present results illustrate that the charge-transfer problem is much broader than may have been previously expected and is not limited to conventional (i.e., molecule-molecule) donor-acceptor complexes.
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...
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.
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.
Modeling Battery Behavior for Accurate State-of-Charge Indication
Pop, V.; Bergveld, H.J.; Veld, op het J.H.G.; Regtien, P.P.L.; Danilov, D.; Notten, P.H.L.
2006-01-01
Li-ion is the most commonly used battery chemistry in portable applications nowadays. Accurate state-of-charge (SOC) and remaining run-time indication for portable devices is important for the user's convenience and to prolong the lifetime of batteries. A new SOC indication system, combining the ele
Hu, Yuan; Sinha, Sudipta Kumar; Patel, Sandeep
2014-10-16
Using the translocation of short, charged cationic oligo-arginine peptides (mono-, di-, and triarginine) from bulk aqueous solution into model DMPC bilayers, we explore the question of the similarity of thermodynamic and structural predictions obtained from molecular dynamics simulations using all-atom and Martini coarse-grain force fields. Specifically, we estimate potentials of mean force associated with translocation using standard all-atom (CHARMM36 lipid) and polarizable and nonpolarizable Martini force fields, as well as a series of modified Martini-based parameter sets. We find that we are able to reproduce qualitative features of potentials of mean force of single amino acid side chain analogues into model bilayers. In particular, modifications of peptide-water and peptide-membrane interactions allow prediction of free energy minima at the bilayer-water interface as obtained with all-atom force fields. In the case of oligo-arginine peptides, the modified parameter sets predict interfacial free energy minima as well as free energy barriers in almost quantitative agreement with all-atom force field based simulations. Interfacial free energy minima predicted by a modified coarse-grained parameter set are -2.51, -4.28, and -5.42 for mono-, di-, and triarginine; corresponding values from all-atom simulations are -0.83, -3.33, and -3.29, respectively, all in units of kcal/mol. We found that a stronger interaction between oligo-arginine and the membrane components and a weaker interaction between oligo-arginine and water are crucial for producing such minima in PMFs using the polarizable CG model. The difference between bulk aqueous and bilayer center states predicted by the modified coarse-grain force field are 11.71, 14.14, and 16.53 kcal/mol, and those by the all-atom model are 6.94, 8.64, and 12.80 kcal/mol; those are of almost the same order of magnitude. Our simulations also demonstrate a remarkable similarity in the structural aspects of the ensemble of
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.
DEFF Research Database (Denmark)
Ugur, Ilke; Marion, Antoine; Parant, Stéphane
2014-01-01
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...... 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...
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.
Optimal feedback scheduling of model predictive controllers
Institute of Scientific and Technical Information of China (English)
Pingfang ZHOU; Jianying XIE; Xiaolong DENG
2006-01-01
Model predictive control (MPC) could not be reliably applied to real-time control systems because its computation time is not well defined. Implemented as anytime algorithm, MPC task allows computation time to be traded for control performance, thus obtaining the predictability in time. Optimal feedback scheduling (FS-CBS) of a set of MPC tasks is presented to maximize the global control performance subject to limited processor time. Each MPC task is assigned with a constant bandwidth server (CBS), whose reserved processor time is adjusted dynamically. The constraints in the FSCBS guarantee scheduler of the total task set and stability of each component. The FS-CBS is shown robust against the variation of execution time of MPC tasks at runtime. Simulation results illustrate its effectiveness.
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.
Sokalski, W. A.; Shibata, M.; Ornstein, R. L.; Rein, R.
1992-01-01
The quality of several atomic charge models based on different definitions has been analyzed using cumulative atomic multipole moments (CAMM). This formalism can generate higher atomic moments starting from any atomic charges, while preserving the corresponding molecular moments. The atomic charge contribution to the higher molecular moments, as well as to the electrostatic potentials, has been examined for CO and HCN molecules at several different levels of theory. The results clearly show that the electrostatic potential obtained from CAMM expansion is convergent up to R-5 term for all atomic charge models used. This illustrates that higher atomic moments can be used to supplement any atomic charge model to obtain more accurate description of electrostatic properties.
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.
Charged Higgs mass bound from the b --> s$\\gamma$ process in the minimal supergravity model
Goto, T; Goto, Toru; Okada, Yasuhiro
1994-01-01
We study the constraint on the mass of the charged Higgs boson in the minimal supergravity model based on the recent measurement of the inclusive b\\rightarrow s\\gamma decay. It is shown that the lower bound for the charged Higgs mass crucially depends on the sign of the higgsino mass parameter (\\mu). For \\mu0 due to cancellations between charged Higgs and supersymmetric particle contributions. For 3\\lsim\\tan\\beta\\lsim5, a charged Higgs lighter than 180 GeV is excluded by this process irrespective of the sign of \\mu.
Prediction models from CAD models of 3D objects
Camps, Octavia I.
1992-11-01
In this paper we present a probabilistic prediction based approach for CAD-based object recognition. Given a CAD model of an object, the PREMIO system combines techniques of analytic graphics and physical models of lights and sensors to predict how features of the object will appear in images. In nearly 4,000 experiments on analytically-generated and real images, we show that in a semi-controlled environment, predicting the detectability of features of the image can successfully guide a search procedure to make informed choices of model and image features in its search for correspondences that can be used to hypothesize the pose of the object. Furthermore, we provide a rigorous experimental protocol that can be used to determine the optimal number of correspondences to seek so that the probability of failing to find a pose and of finding an inaccurate pose are minimized.
Predictive modelling of ferroelectric tunnel junctions
Velev, Julian P.; Burton, John D.; Zhuravlev, Mikhail Ye; Tsymbal, Evgeny Y.
2016-05-01
Ferroelectric tunnel junctions combine the phenomena of quantum-mechanical tunnelling and switchable spontaneous polarisation of a nanometre-thick ferroelectric film into novel device functionality. Switching the ferroelectric barrier polarisation direction produces a sizable change in resistance of the junction—a phenomenon known as the tunnelling electroresistance effect. From a fundamental perspective, ferroelectric tunnel junctions and their version with ferromagnetic electrodes, i.e., multiferroic tunnel junctions, are testbeds for studying the underlying mechanisms of tunnelling electroresistance as well as the interplay between electric and magnetic degrees of freedom and their effect on transport. From a practical perspective, ferroelectric tunnel junctions hold promise for disruptive device applications. In a very short time, they have traversed the path from basic model predictions to prototypes for novel non-volatile ferroelectric random access memories with non-destructive readout. This remarkable progress is to a large extent driven by a productive cycle of predictive modelling and innovative experimental effort. In this review article, we outline the development of the ferroelectric tunnel junction concept and the role of theoretical modelling in guiding experimental work. We discuss a wide range of physical phenomena that control the functional properties of ferroelectric tunnel junctions and summarise the state-of-the-art achievements in the field.
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.
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.
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)
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...
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...... facilitates plug-and-play addition of subsystems without redesign of any controllers. The method is supported by a number of simulations featuring a three-level smart-grid power control system for a small isolated power grid....
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.
Predicting Protein Secondary Structure with Markov Models
DEFF Research Database (Denmark)
Fischer, Paul; Larsen, Simon; Thomsen, Claus
2004-01-01
we are considering here, is to predict the secondary structure from the primary one. To this end we train a Markov model on training data and then use it to classify parts of unknown protein sequences as sheets, helices or coils. We show how to exploit the directional information contained......The primary structure of a protein is the sequence of its amino acids. The secondary structure describes structural properties of the molecule such as which parts of it form sheets, helices or coils. Spacial and other properties are described by the higher order structures. The classification task...
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, ...
Spacecraft Charging Modeling -- Nascap-2k 2014 Annual Report
2014-09-19
more accessible to users, and improve and maintain both the graphical and non -graphical interfaces to the code. The upgraded code is being used to...Geometry and Materials for First Test Case for Charging in LEO with Analytic Currents from a Convected Maxwellian Distribution...code capabilities more accessible to users, and improve and maintain both the graphical and non - graphical interfaces to the code. The upgraded code is
Critical conceptualism in environmental modeling and prediction.
Christakos, G
2003-10-15
Many important problems in environmental science and engineering are of a conceptual nature. Research and development, however, often becomes so preoccupied with technical issues, which are themselves fascinating, that it neglects essential methodological elements of conceptual reasoning and theoretical inquiry. This work suggests that valuable insight into environmental modeling can be gained by means of critical conceptualism which focuses on the software of human reason and, in practical terms, leads to a powerful methodological framework of space-time modeling and prediction. A knowledge synthesis system develops the rational means for the epistemic integration of various physical knowledge bases relevant to the natural system of interest in order to obtain a realistic representation of the system, provide a rigorous assessment of the uncertainty sources, generate meaningful predictions of environmental processes in space-time, and produce science-based decisions. No restriction is imposed on the shape of the distribution model or the form of the predictor (non-Gaussian distributions, multiple-point statistics, and nonlinear models are automatically incorporated). The scientific reasoning structure underlying knowledge synthesis involves teleologic criteria and stochastic logic principles which have important advantages over the reasoning method of conventional space-time techniques. Insight is gained in terms of real world applications, including the following: the study of global ozone patterns in the atmosphere using data sets generated by instruments on board the Nimbus 7 satellite and secondary information in terms of total ozone-tropopause pressure models; the mapping of arsenic concentrations in the Bangladesh drinking water by assimilating hard and soft data from an extensive network of monitoring wells; and the dynamic imaging of probability distributions of pollutants across the Kalamazoo river.
Quek, Su Ying; Khoo, Khoong Hong
2014-11-18
CONSPECTUS: The emerging field of flexible electronics based on organics and two-dimensional (2D) materials relies on a fundamental understanding of charge and spin transport at the molecular and nanoscale. It is desirable to make predictions and shine light on unexplained experimental phenomena independently of experimentally derived parameters. Indeed, density functional theory (DFT), the workhorse of first-principles approaches, has been used extensively to model charge/spin transport at the nanoscale. However, DFT is essentially a ground state theory that simply guarantees correct total energies given the correct charge density, while charge/spin transport is a nonequilibrium phenomenon involving the scattering of quasiparticles. In this Account, we critically assess the validity and applicability of DFT to predict charge/spin transport at the nanoscale. We also describe a DFT-based approach, DFT+Σ, which incorporates corrections to Kohn-Sham energy levels based on many-electron calculations. We focus on single-molecule junctions and then discuss how the important considerations for DFT descriptions of transport can differ in 2D materials. We conclude that when used appropriately, DFT and DFT-based approaches can play an important role in making predictions and gaining insight into transport in these materials. Specifically, we shall focus on the low-bias quasi-equilibrium regime, which is also experimentally most relevant for single-molecule junctions. The next question is how well can the scattering of DFT Kohn-Sham particles approximate the scattering of true quasiparticles in the junction? Quasiparticles are electrons (holes) that are surrounded by a constantly changing cloud of holes (electrons), but Kohn-Sham particles have no physical significance. However, Kohn-Sham particles can often be used as a qualitative approximation to quasiparticles. The errors in standard DFT descriptions of transport arise primarily from errors in the Kohn-Sham energy levels
DEFF Research Database (Denmark)
Jørgensen, John Bagterp; Jørgensen, Sten Bay
2007-01-01
model is realized from a continuous-discrete-time linear stochastic system specified using transfer functions with time-delays. It is argued that the prediction-error criterion should be selected such that it is compatible with the objective function of the predictive controller in which the model......A Prediction-error-method tailored for model based predictive control is presented. The prediction-error method studied are based on predictions using the Kalman filter and Kalman predictors for a linear discrete-time stochastic state space model. The linear discrete-time stochastic state space...
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.
Felmy, Andrew R.; Rustad, James R.
1998-01-01
Molecular statics calculations of proton binding at the hydroxylated faces of goethite are used to guide the development of a thermodynamic model which describes the surface charging properties of goethite in electrolyte solutions. The molecular statics calculations combined with a linear free energy relation between the energies of the hydroxylated surface and the aqueous solvated surface predict that the acidity constants for most singly (aqua or hydroxo), doubly (μ-hydroxo), and triply (μ 3-hydroxo or μ 3-oxo) coordinated surface sites all have similar values. This model which binds protons to the goethite 110 and 021 faces satisfactorily describes the surface charging behavior of goethite, if pair formation between bulk electrolyte species, i.e., Na +, Cl -, and NO 3-, is included in the model. Inclusion of minor species of quite different charging behavior (designed to describe the possible presence of defect species) did not improve our predictions of surface charge since the protonation of the major surface sites changed when these minor species were introduced into the calculations thereby negating the effect of small amounts of defect species on the overall charging behavior. The final thermodynamic model is shown to be consistent with the surface charging properties of goethite over a range of pH values, NaNO 3, and NaCl concentrations.
A Predictive Maintenance Model for Railway Tracks
DEFF Research Database (Denmark)
Li, Rui; Wen, Min; Salling, Kim Bang
2015-01-01
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...... 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...
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.
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.
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
A predictive model for dimensional errors in fused deposition modeling
DEFF Research Database (Denmark)
Stolfi, A.
2015-01-01
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...
Effect on Prediction when Modeling Covariates in Bayesian Nonparametric Models.
Cruz-Marcelo, Alejandro; Rosner, Gary L; Müller, Peter; Stewart, Clinton F
2013-04-01
In biomedical research, it is often of interest to characterize biologic processes giving rise to observations and to make predictions of future observations. Bayesian nonparametric methods provide a means for carrying out Bayesian inference making as few assumptions about restrictive parametric models as possible. There are several proposals in the literature for extending Bayesian nonparametric models to include dependence on covariates. Limited attention, however, has been directed to the following two aspects. In this article, we examine the effect on fitting and predictive performance of incorporating covariates in a class of Bayesian nonparametric models by one of two primary ways: either in the weights or in the locations of a discrete random probability measure. We show that different strategies for incorporating continuous covariates in Bayesian nonparametric models can result in big differences when used for prediction, even though they lead to otherwise similar posterior inferences. When one needs the predictive density, as in optimal design, and this density is a mixture, it is better to make the weights depend on the covariates. We demonstrate these points via a simulated data example and in an application in which one wants to determine the optimal dose of an anticancer drug used in pediatric oncology.
Modelling surface restructuring by slow highly charged ions
Wachter, G.; Tőkési, K.; Betz, G.; Lemell, C.; Burgdörfer, J.
2013-12-01
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.
Modelling surface restructuring by slow highly charged ions
Energy Technology Data Exchange (ETDEWEB)
Wachter, G., E-mail: georg.wachter@tuwien.ac.at [Institute for Theoretical Physics, Vienna University of Technology, Wiedner Hauptstraße 8-10, A-1040 Vienna (Austria); Tőkési, K. [Institute of Nuclear Research of the Hungarian Academy of Science (ATOMKI), H-4001 Debrecen, P.O. Box 51 (Hungary); Betz, G. [Institute for Applied Physics, Vienna University of Technology, Wiedner Hauptstraße 8-10, A-1040 Vienna (Austria); Lemell, C.; Burgdörfer, J. [Institute for Theoretical Physics, Vienna University of Technology, Wiedner Hauptstraße 8-10, A-1040 Vienna (Austria)
2013-12-15
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 CaF{sub 2} (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.
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%.
A unified charge-based model for SOI MOSFETs applicable from intrinsic to heavily doped channel
Institute of Scientific and Technical Information of China (English)
Zhang Jian; Han Yu; Chan Mansun; He Jin; Zhou Xing-Ye; Zhang Li-Ning; Ma Yu-Tao; Chen Qin; Zhang Xu-Kai; Yang Zhang; Wang Rui-Fei
2012-01-01
A unified charge-based model for fully depleted silicon-on-insulator (SOI) metal-oxide semiconductor field-effect transistors (MOSFETs) is presented.The proposed model is accurate and applicable from intrinsic to heavily doped channels with various structure parameters.The framework starts from the one-dimensional Poisson-Boltzmann equation,and based on the full depletion approximation,an accurate inversion charge density equation is obtained.With the inversion charge density solution,the unified drain current expression is derived,and a unified terminal charge and intrinsic capacitance model is also derived in the quasi-static case.The validity and accuracy of the presented analytic model is proved by numerical simulations.
Two criteria for evaluating risk prediction models.
Pfeiffer, R M; Gail, M H
2011-09-01
We propose and study two criteria to assess the usefulness of models that predict risk of disease incidence for screening and prevention, or the usefulness of prognostic models for management following disease diagnosis. The first criterion, the proportion of cases followed PCF (q), is the proportion of individuals who will develop disease who are included in the proportion q of individuals in the population at highest risk. The second criterion is the proportion needed to follow-up, PNF (p), namely the proportion of the general population at highest risk that one needs to follow in order that a proportion p of those destined to become cases will be followed. PCF (q) assesses the effectiveness of a program that follows 100q% of the population at highest risk. PNF (p) assess the feasibility of covering 100p% of cases by indicating how much of the population at highest risk must be followed. We show the relationship of those two criteria to the Lorenz curve and its inverse, and present distribution theory for estimates of PCF and PNF. We develop new methods, based on influence functions, for inference for a single risk model, and also for comparing the PCFs and PNFs of two risk models, both of which were evaluated in the same validation data.
Methods for Handling Missing Variables in Risk Prediction Models
Held, Ulrike; Kessels, Alfons; Aymerich, Judith Garcia; Basagana, Xavier; ter Riet, Gerben; Moons, Karel G. M.; Puhan, Milo A.
2016-01-01
Prediction models should be externally validated before being used in clinical practice. Many published prediction models have never been validated. Uncollected predictor variables in otherwise suitable validation cohorts are the main factor precluding external validation.We used individual patient
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.
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.
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.)
Doping driven metal-insulator transitions and charge orderings in the extended Hubbard model
Kapcia, K J; Capone, M; Amaricci, A
2016-01-01
We perform a thorough study of an extended Hubbard model featuring local and nearest-neighbor Coulomb repulsion. Using dynamical mean-field theory we investigated the zero temperature phase-diagram of this model as a function of the chemical doping. The interplay between local and non-local interaction drives a variety of phase-transitions connecting two distinct charge-ordered insulators, i.e., half-filled and quarter-filled, a charge-ordered metal and a Mott insulating phase. We characterize these transitions and the relative stability of the solutions and we show that the two interactions conspire to stabilize the quarter-filled charge ordered phase.
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.
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...
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.
Modeling Stationary Lithium-Ion Batteries for Optimization and Predictive Control: Preprint
Energy Technology Data Exchange (ETDEWEB)
Raszmann, Emma; Baker, Kyri; Shi, Ying; Christensen, Dane
2017-02-22
Accurately modeling stationary battery storage behavior is crucial to understand and predict its limitations in demand-side management scenarios. In this paper, a lithium-ion battery model was derived to estimate lifetime and state-of-charge for building-integrated use cases. The proposed battery model aims to balance speed and accuracy when modeling battery behavior for real-time predictive control and optimization. In order to achieve these goals, a mixed modeling approach was taken, which incorporates regression fits to experimental data and an equivalent circuit to model battery behavior. A comparison of the proposed battery model output to actual data from the manufacturer validates the modeling approach taken in the paper. Additionally, a dynamic test case demonstrates the effects of using regression models to represent internal resistance and capacity fading.
Estimating the magnitude of prediction uncertainties for the APLE model
Models are often used to predict phosphorus (P) loss from agricultural fields. While it is commonly recognized that model predictions are inherently uncertain, few studies have addressed prediction uncertainties using P loss models. In this study, we conduct an uncertainty analysis for the Annual P ...
SAAMBE: Webserver to Predict the Charge of Binding Free Energy Caused by Amino Acids Mutations.
Petukh, Marharyta; Dai, Luogeng; Alexov, Emil
2016-04-12
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/.
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 ...
Predictive modeling of low solubility semiconductor alloys
Rodriguez, Garrett V.; Millunchick, Joanna M.
2016-09-01
GaAsBi is of great interest for applications in high efficiency optoelectronic devices due to its highly tunable bandgap. However, the experimental growth of high Bi content films has proven difficult. Here, we model GaAsBi film growth using a kinetic Monte Carlo simulation that explicitly takes cation and anion reactions into account. The unique behavior of Bi droplets is explored, and a sharp decrease in Bi content upon Bi droplet formation is demonstrated. The high mobility of simulated Bi droplets on GaAsBi surfaces is shown to produce phase separated Ga-Bi droplets as well as depressions on the film surface. A phase diagram for a range of growth rates that predicts both Bi content and droplet formation is presented to guide the experimental growth of high Bi content GaAsBi films.
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 ...
Leptogenesis in minimal predictive seesaw models
Björkeroth, Fredrik; de Anda, Francisco J.; de Medeiros Varzielas, Ivo; King, Stephen F.
2015-10-01
We estimate the Baryon Asymmetry of the Universe (BAU) arising from leptogenesis within a class of minimal predictive seesaw models involving two right-handed neutrinos and simple Yukawa structures with one texture zero. The two right-handed neutrinos are dominantly responsible for the "atmospheric" and "solar" neutrino masses with Yukawa couplings to ( ν e , ν μ , ν τ ) proportional to (0, 1, 1) and (1, n, n - 2), respectively, where n is a positive integer. The neutrino Yukawa matrix is therefore characterised by two proportionality constants with their relative phase providing a leptogenesis-PMNS link, enabling the lightest right-handed neutrino mass to be determined from neutrino data and the observed BAU. We discuss an SU(5) SUSY GUT example, where A 4 vacuum alignment provides the required Yukawa structures with n = 3, while a {{Z}}_9 symmetry fixes the relatives phase to be a ninth root of unity.
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.
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
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.
Electrical charging effects on the sliding friction of a model nano-confined ionic liquid
Capozza, R.; Benassi, A.; Vanossi, A.; Tosatti, E.
2015-10-01
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
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.
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...
Remaining Useful Lifetime (RUL - Probabilistic Predictive Model
Directory of Open Access Journals (Sweden)
Ephraim Suhir
2011-01-01
Full Text Available Reliability evaluations and assurances cannot be delayed until the device (system is fabricated and put into operation. Reliability of an electronic product should be conceived at the early stages of its design; implemented during manufacturing; evaluated (considering customer requirements and the existing specifications, by electrical, optical and mechanical measurements and testing; checked (screened during manufacturing (fabrication; and, if necessary and appropriate, maintained in the field during the product’s operation Simple and physically meaningful probabilistic predictive model is suggested for the evaluation of the remaining useful lifetime (RUL of an electronic device (system after an appreciable deviation from its normal operation conditions has been detected, and the increase in the failure rate and the change in the configuration of the wear-out portion of the bathtub has been assessed. The general concepts are illustrated by numerical examples. The model can be employed, along with other PHM forecasting and interfering tools and means, to evaluate and to maintain the high level of the reliability (probability of non-failure of a device (system at the operation stage of its lifetime.
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.
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.
Pinto, Thiago M; Wedemann, Roseli S; Cortez, Célia M
2014-01-01
We present a model for the electric potential profile across the membranes of neuronal cells. We considered the resting and action potential states, and analyzed the influence of fixed charges of the membrane on its electric potential, based on experimental values of membrane properties of the spinal ganglion neuron and the neuroblastoma cell. The spinal ganglion neuron represents a healthy neuron, and the neuroblastoma cell, which is tumorous, represents a pathological neuron. We numerically solved the non-linear Poisson-Boltzmann equation for the regions of the membrane model we have adopted, by considering the densities of charges dissolved in an electrolytic solution and fixed on both glycocalyx and cytoplasmic proteins. Our model predicts that there is a difference in the behavior of the electric potential profiles of the two types of cells, in response to changes in charge concentrations in the membrane. Our results also describe an insensitivity of the neuroblastoma cell membrane, as observed in some biological experiments. This electrical property may be responsible for the low pharmacological response of the neuroblastoma to certain chemotherapeutic treatments.
Directory of Open Access Journals (Sweden)
Thiago M Pinto
Full Text Available We present a model for the electric potential profile across the membranes of neuronal cells. We considered the resting and action potential states, and analyzed the influence of fixed charges of the membrane on its electric potential, based on experimental values of membrane properties of the spinal ganglion neuron and the neuroblastoma cell. The spinal ganglion neuron represents a healthy neuron, and the neuroblastoma cell, which is tumorous, represents a pathological neuron. We numerically solved the non-linear Poisson-Boltzmann equation for the regions of the membrane model we have adopted, by considering the densities of charges dissolved in an electrolytic solution and fixed on both glycocalyx and cytoplasmic proteins. Our model predicts that there is a difference in the behavior of the electric potential profiles of the two types of cells, in response to changes in charge concentrations in the membrane. Our results also describe an insensitivity of the neuroblastoma cell membrane, as observed in some biological experiments. This electrical property may be responsible for the low pharmacological response of the neuroblastoma to certain chemotherapeutic treatments.
Charge-based MOSFET model based on the Hermite interpolation polynomial
Colalongo, Luigi; Richelli, Anna; Kovacs, Zsolt
2017-04-01
An accurate charge-based compact MOSFET model is developed using the third order Hermite interpolation polynomial to approximate the relation between surface potential and inversion charge in the channel. This new formulation of the drain current retains the same simplicity of the most advanced charge-based compact MOSFET models such as BSIM, ACM and EKV, but it is developed without requiring the crude linearization of the inversion charge. Hence, the asymmetry and the non-linearity in the channel are accurately accounted for. Nevertheless, the expression of the drain current can be worked out to be analytically equivalent to BSIM, ACM and EKV. Furthermore, thanks to this new mathematical approach the slope factor is rigorously defined in all regions of operation and no empirical assumption is required.
Central Charge of the Parallelogram Lattice Strong Coupling Schwinger Model
Yee, K
1993-01-01
We put forth a Fierzed hopping expansion for strong coupling Wilson fermions. As an application, we show that the strong coupling Schwinger model on parallelogram lattices with nonbacktracking Wilson fermions span, as a function of the lattice skewness angle, the $\\Delta = -1$ critical line of $6$-vertex models. This Fierzed formulation also applies to backtracking Wilson fermions, which as we describe apparently correspond to richer systems. However, we have not been able to identify them with exactly solved models.
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.
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.
Cell survival in carbon beams - comparison of amorphous track model predictions
DEFF Research Database (Denmark)
Grzanka, L.; Greilich, S.; Korcyl, M.
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......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...... by Tsuruoka et al. [4] . Results and conclusion: Preliminary results show a good agreement of models predictions and the experimental data for clinical doses. When investigating the influence of radial dose distributions on inactivation cross section in the Katz model, we found that one of the most important...
Aligia, A A; Anfossi, A; Arrachea, L; Degli Esposti Boschi, C; Dobry, A O; Gazza, C; Montorsi, A; Ortolani, F; Torio, M E
2007-11-16
We determine the quantum phase diagram of the one-dimensional Hubbard model with bond-charge interaction X in addition to the usual Coulomb repulsion U>0 at half-filling. For large enough Xtransition to a spontaneously dimerized bond-ordered wave phase and then a charge transition to a novel phase in which the dominant correlations at large distances correspond to an incommensurate singlet superconductor.
Prediction models : the right tool for the right problem
Kappen, Teus H.; Peelen, Linda M.
2016-01-01
PURPOSE OF REVIEW: Perioperative prediction models can help to improve personalized patient care by providing individual risk predictions to both patients and providers. However, the scientific literature on prediction model development and validation can be quite technical and challenging to unders
Usman, Muhammad; Knapen, Luk; Kochan, Bruno; Yasar, Ansar; Bellemans, Tom; Janssens, Davy; WETS, Geert
2015-01-01
This paper presents the cost optimization model which plans a charging strategy for an electric vehicle. In case of time dependent electric prices an intelligent planner is required which plans the charging strategy only at cheaper moments and places to keep the vehicle charged enough to complete its scheduled travels. This model estimates the required charging energy to travel by the electric vehicle. Then using the time dependent electric prices and available power at each pe...
Prediction Model for the Life of Nickel-cadmium Batteries in Geosynchronous Orbit Satellites
Engleman, J. H.; Zirkes-Falco, M. B.; Bogner, R. S.; Pickett, D. F., Jr.
1984-01-01
A mathematical model is described which predicts the service life of nickel-cadmium batteries designed for geosynchronous orbit satellites. Regression analysis technique is used to analyze orbital data on second generation trickle charged batteries. The model gives average cell voltage as a function of design parameters, operating parameters and time. The voltage model has the properties of providing a good fit to the data, good predictive capability, and agreement with known battery performance characteristics. Average cell voltage can be predicted to within 0.02 volts for up to 8 years. This modeling shows that these batteries will operate reliably for 10 years. Third-generation batteries are expected to operate even longer.
Predictability of the Indian Ocean Dipole in the coupled models
Liu, Huafeng; Tang, Youmin; Chen, Dake; Lian, Tao
2017-03-01
In this study, the Indian Ocean Dipole (IOD) predictability, measured by the Indian Dipole Mode Index (DMI), is comprehensively examined at the seasonal time scale, including its actual prediction skill and potential predictability, using the ENSEMBLES multiple model ensembles and the recently developed information-based theoretical framework of predictability. It was found that all model predictions have useful skill, which is normally defined by the anomaly correlation coefficient larger than 0.5, only at around 2-3 month leads. This is mainly because there are more false alarms in predictions as leading time increases. The DMI predictability has significant seasonal variation, and the predictions whose target seasons are boreal summer (JJA) and autumn (SON) are more reliable than that for other seasons. All of models fail to predict the IOD onset before May and suffer from the winter (DJF) predictability barrier. The potential predictability study indicates that, with the model development and initialization improvement, the prediction of IOD onset is likely to be improved but the winter barrier cannot be overcome. The IOD predictability also has decadal variation, with a high skill during the 1960s and the early 1990s, and a low skill during the early 1970s and early 1980s, which is very consistent with the potential predictability. The main factors controlling the IOD predictability, including its seasonal and decadal variations, are also analyzed in this study.
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.
Nonconvex model predictive control for commercial refrigeration
Gybel Hovgaard, Tobias; Boyd, Stephen; Larsen, Lars F. S.; Bagterp Jørgensen, John
2013-08-01
We consider the control of a commercial multi-zone refrigeration system, consisting of several cooling units that share a common compressor, and is used to cool multiple areas or rooms. In each time period we choose cooling capacity to each unit and a common evaporation temperature. The goal is to minimise 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 function, however, is nonconvex due to the temperature dependence of thermodynamic efficiency. To handle this nonconvexity we propose a sequential convex optimisation method, which typically converges in fewer than 5 or so iterations. We employ a fast convex quadratic programming solver to carry out 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 savings, on the order of 30%, compared to a standard thermostat-based control system. Perhaps more important, we see that the method exhibits sophisticated response to real-time variations in electricity prices. This demand response is critical to help balance real-time uncertainties in generation capacity associated with large penetration of intermittent renewable energy sources in a future smart grid.
QSPR Models for Octane Number Prediction
Directory of Open Access Journals (Sweden)
Jabir H. Al-Fahemi
2014-01-01
Full Text Available Quantitative structure-property relationship (QSPR is performed as a means to predict octane number of hydrocarbons via correlating properties to parameters calculated from molecular structure; such parameters are molecular mass M, hydration energy EH, boiling point BP, octanol/water distribution coefficient logP, molar refractivity MR, critical pressure CP, critical volume CV, and critical temperature CT. Principal component analysis (PCA and multiple linear regression technique (MLR were performed to examine the relationship between multiple variables of the above parameters and the octane number of hydrocarbons. The results of PCA explain the interrelationships between octane number and different variables. Correlation coefficients were calculated using M.S. Excel to examine the relationship between multiple variables of the above parameters and the octane number of hydrocarbons. The data set was split into training of 40 hydrocarbons and validation set of 25 hydrocarbons. The linear relationship between the selected descriptors and the octane number has coefficient of determination (R2=0.932, statistical significance (F=53.21, and standard errors (s =7.7. The obtained QSPR model was applied on the validation set of octane number for hydrocarbons giving RCV2=0.942 and s=6.328.
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.
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.
Modelling the Complex Conductivity of Charged Porous Media using The Grain Polarization Model
Leroy, P.; Revil, A.; Jougnot, D.; Li, S.
2015-12-01
The low-frequency complex conductivity response of charged porous media reflects a combination of three polarization processes occuring at different frequency ranges. One polarization process corresponds to the membrane polarization phenomenon, which is the polarization mechanism associated with the back-diffusion of salt ions through different pore spaces of the porous material (ions-selective zones and zones with no selectivity). This polarization process generally occurs at the lowest frequency range, typically in the frequency range [mHz Hz] because it involves polarization mechanism occurring over different pore spaces (the relaxation frequency is inversely proportional to the length of the polarization process). Another polarization process corresponds to the electrochemical polarization of the electrical double layer coating the surface of the grains. In the grain polarization model, the diffuse layer is assumed to not polarize because it is assumed to form a continuum in the porous medium. The compact Stern layer is assumed to polarize because the Stern layer is assumed to be discontinuous over multiple grains. The electrochemical polarization of the Stern layer typically occurs in the frequency range [Hz kHz]. The last polarization process corresponds to the Maxwell-Wagner polarization mechanism, which is caused by the formation of field-induced free charge distributions near the interface between the phases of the medium. In this presentation, the grain polarization model based on the O'Konski, Schwarz, Schurr and Sen theories and developed later by Revil and co-workers is showed. This spectral induced polarization model was successfully applied to describe the complex conductivity responses of glass beads, sands, clays, clay-sand mixtures and other minerals. The limits of this model and future developments will also be presented.
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.
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.
The Collider Phenomenology Of Supersymmetric Models (charged Higgs Boson, Tau Leptons)
Müller, D J
1998-01-01
The purpose of this study is to investigate the phenomenology of various supersymmetric models. First, the Minimal Supersymmetric Standard Model (MSSM) is investigated. This model contains an extended Higgs sector that includes a charged boson. The effect that this charged Higgs boson has on the signatures for top quark pair production at the Tevatron is investigated. The rest of the work is devoted to the phenomenology of models with gauge mediated supersymmetry breaking (GMSB). In GMSB models, the lighter stau can be the next to lightest supersymmetric particle. The signals at hadronic colliders for GMSB models with minimal visible sector content are explored for this case. A GMSB model with non-minimal visible sector content is also explored. This is the left-right symmetric GMSB model which contains doubly charged bosons and fermions that could be light enough in mass to be produced at Run II of the Tevatron. Findings and conclusions. The presence of a charged Higgs boson that is lighter than the top quar...
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
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.
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.
Penning De Vries, René G.M.; Wallinga, Hans
1984-01-01
The small-signal charge transfer inefficiency (SCTI) of a surface-channel CCD has been studied. The experimentally observed behavior of the SCTI could not be explained by the conventional interface state model. Using the McWhorter model for the interface states, which assumes a distribution of the s
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
Charge transport in high mobility molecular semiconductors: classical models and new theories.
Troisi, Alessandro
2011-05-01
The theories developed since the fifties to describe charge transport in molecular crystals proved to be inadequate for the most promising classes of high mobility molecular semiconductors identified in the recent years, including for example pentacene and rubrene. After reviewing at an elementary level the classical theories, which still provide the language for the understanding of charge transport in these systems, this tutorial review outlines the recent experimental and computational evidence that prompted the development of new theories of charge transport in molecular crystals. A critical discussion will illustrate how very rarely it is possible to assume a charge hopping mechanism for high mobility organic crystals at any temperature. Recent models based on the effect of non-local electron-phonon coupling, dynamic disorder, coexistence of localized and delocalized states are reviewed. Additionally, a few more recent avenues of theoretical investigation, including the study of defect states, are discussed.
Charge fluctuations in chiral models and the QCD phase transition
Skokov, V; Karsch, F; Redlich, K
2011-01-01
We consider the Polyakov loop-extended two flavor chiral quark--meson model and discuss critical phenomena related with the spontaneous breaking of the chiral symmetry. The model is explored beyond the mean-field approximation in the framework of the functional renormalisation group. We discuss properties of the net-quark number density fluctuations as well as their higher cumulants. We show that with the increasing net-quark number density, the higher order cumulants exhibit a strong sensitivity to the chiral crossover transition. We discuss their role as probes of the chiral phase transition in heavy-ion collisions at RHIC and LHC.
Valone, S M; Pilania, G; Liu, X Y; Allen, J R; Wu, T-C; Atlas, S R; Dunlap, D H
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((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.
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.
Allostasis: a model of predictive regulation.
Sterling, Peter
2012-04-12
The premise of the standard regulatory model, "homeostasis", is flawed: the goal of regulation is not to preserve constancy of the internal milieu. Rather, it is to continually adjust the milieu to promote survival and reproduction. Regulatory mechanisms need to be efficient, but homeostasis (error-correction by feedback) is inherently inefficient. Thus, although feedbacks are certainly ubiquitous, they could not possibly serve as the primary regulatory mechanism. A newer model, "allostasis", proposes that efficient regulation requires anticipating needs and preparing to satisfy them before they arise. The advantages: (i) errors are reduced in magnitude and frequency; (ii) response capacities of different components are matched -- to prevent bottlenecks and reduce safety factors; (iii) resources are shared between systems to minimize reserve capacities; (iv) errors are remembered and used to reduce future errors. This regulatory strategy requires a dedicated organ, the brain. The brain tracks multitudinous variables and integrates their values with prior knowledge to predict needs and set priorities. The brain coordinates effectors to mobilize resources from modest bodily stores and enforces a system of flexible trade-offs: from each organ according to its ability, to each organ according to its need. The brain also helps regulate the internal milieu by governing anticipatory behavior. Thus, an animal conserves energy by moving to a warmer place - before it cools, and it conserves salt and water by moving to a cooler one before it sweats. The behavioral strategy requires continuously updating a set of specific "shopping lists" that document the growing need for each key component (warmth, food, salt, water). These appetites funnel into a common pathway that employs a "stick" to drive the organism toward filling the need, plus a "carrot" to relax the organism when the need is satisfied. The stick corresponds broadly to the sense of anxiety, and the carrot broadly to
Electric charge quantization in SU(3)_c X SU(3)_L X U(1)_X model
Abdinov, O B; Rzaeva, S S
2010-01-01
Basing on the general photon eigenstate and anomaly cancellation, it is shown that the electric charge quantization in SU(3)_c X SU(3)_L X U(1)_X model with exotic particles can be obtained independently on parameters alpha and betta. The fixation of hypercharges of fermions fields by the Higgs fields and dependence of the electric charges quantization conditions from the hypercharges of Higgs fields leads to the fact that the electric charge in the considered model can be quantized and fixed only in the presence of Higgs fields. In addition, we have shown that in the considered model the classical constraints following from the Yukawa interactions are equivalent to the conditions following from the parity invariance of electromagnetic interaction. The most general expressions for the gauge bosons masses, eigenstates of neutral fields and the interactions of leptons and quarks with gauge bosons have been derived in the arbitrary case
Comparing model predictions for ecosystem-based management
DEFF Research Database (Denmark)
Jacobsen, Nis Sand; Essington, Timothy E.; Andersen, Ken Haste
2016-01-01
E)) and a size-structured fish community model. The models were compared with respect to predicted ecological consequences of fishing to identify commonalities and differences in model predictions for the California Current fish community. We compared the models regarding direct and indirect responses to fishing...... on one or more species. The size-based model predicted a higher fishing mortality needed to reach maximum sustainable yield than EwE for most species. The size-based model also predicted stronger top-down effects of predator removals than EwE. In contrast, EwE predicted stronger bottom-up effects...... 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...
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.
Charge and Current in the Quantum Hall Matrix Model
2003-01-01
We extend the quantum Hall matrix model to include couplings to external electric and magnetic fields. The associated current suffers from matrix ordering ambiguities even at the classical level. We calculate the linear response at low momenta -- this is unambigously defined. In particular, we obtain the correct fractional quantum Hall conductivity, and the expected density modulations in response to a weak and slowly varying magnetic field. These results show that the classical quantum Hall ...
A prediction model for assessing residential radon concentration in Switzerland
Hauri, D.D.; Huss, A.; Zimmermann, F.; Kuehni, C.E.; Roosli, M.
2012-01-01
Indoor radon is regularly measured in Switzerland. However, a nationwide model to predict residential radon levels has not been developed. The aim of this study was to develop a prediction model to assess indoor radon concentrations in Switzerland. The model was based on 44,631 measurements from the
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…
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...
Vedula, Ravi Pramod Kumar
Scaling of CMOS towards its ultimate limits, where quantum effects and atomistic variability due to fabrication, along with recent emphasis on heterogeneous integration of non-digital devices for increasing the functional diversification presents us with fundamentally new challenges. A comprehensive understanding of design and operation of these nanoscale transistors, and other electronic devices like RF-MEMS, requires an insight into their electronic and mechanical properties that are strongly influenced by underlying atomic structure. Hence, continuum descriptions of materials and use of empirical models at these scales become questionable. This increase in complexity of electronic devices necessitates an understanding at a more fundamental level to accurately predict the performance and reliability of these devices. The objective of this thesis is to outline the application of multiscale predictive modeling methods, ranging from atoms to devices, for addressing these challenges. This capability is demonstrated using two examples: characterization of (i) dielectric charging in RF-MEMS, and (ii) transport properties of Ge-nanofins. For characterizing the dielectric charging phenomenon, a continuum dielectric charging model, augmented by first principles informed trap distributions, is used to predict current transient measurements across a broad range of voltages and temperatures. These simulations demonstrate using ab initio informed model not only reduces the empiricism (number of adjustable parameters) in the model but also leads to a more accurate model over a broad range of operating conditions, and enable the precise determination of additional material parameters. These atomistic calculations also provide detailed information about the nature of charge traps and their trapping mechanisms that are not accessible experimentally; such information could prove invaluable in defect engineering. The second problem addresses the effect of the in-homogeneous strain
Silva, Arnaldo F; da Silva, João V; Haiduke, R L A; Bruns, Roy E
2011-11-17
Infrared fundamental vibrational intensities and quantum theory atoms in molecules (QTAIM) charge-charge flux-dipole flux (CCFDF) contributions to the polar tensors of the fluorochloromethanes have been calculated at the QCISD/cc-pVTZ level. A root-mean-square error of 20.0 km mol(-1) has been found compared to an experimental error estimate of 14.4 and 21.1 km mol(-1) for MP2/6-311++G(3d,3p) results. The errors in the QCISD polar tensor elements and mean dipole moment derivatives are 0.059 e when compared with the experimental values. Both theoretical levels provide results showing that the dynamical charge and dipole fluxes provide significant contributions to the mean dipole moment derivatives and tend to be of opposite signs canceling one another. Although the experimental mean dipole moment derivative values suggest that all the fluorochloromethane molecules have electronic structures consistent with a simple electronegativity model with transferable atomic charges for their terminal atoms, the QTAIM/CCFDF models confirm this only for the fluoromethanes. Whereas the fluorine atom does not suffer a saturation effect in its capacity to drain electronic charge from carbon atoms that are attached to other fluorine and chlorine atoms, the zero flux electronic charge of the chlorine atom depends on the number and kind of the other substituent atoms. Both the QTAIM carbon charges (r = 0.990) and mean dipole moment derivatives (r = 0.996) are found to obey Siegbahn's potential model for carbon 1s electron ionization energies at the QCISD/cc-pVTZ level. The latter is a consequence of the carbon mean derivatives obeying the electronegativity model and not necessarily to their similarities with atomic charges. Atomic dipole contributions to the neighboring atom electrostatic potentials of the fluorochloromethanes are found to be of comparable size to the atomic charge contributions and increase the accuracy of Siegbahn's model for the QTAIM charge model results
Distributional Analysis for Model Predictive Deferrable Load Control
Chen, Niangjun; Gan, Lingwen; Low, Steven H.; Wierman, Adam
2014-01-01
Deferrable load control is essential for handling the uncertainties associated with the increasing penetration of renewable generation. Model predictive control has emerged as an effective approach for deferrable load control, and has received considerable attention. In particular, previous work has analyzed the average-case performance of model predictive deferrable load control. However, to this point, distributional analysis of model predictive deferrable load control has been elusive. In ...
Predicting the Yield Stress of SCC using Materials Modelling
DEFF Research Database (Denmark)
Thrane, Lars Nyholm; Hasholt, Marianne Tange; Pade, Claus
2005-01-01
A conceptual model for predicting the Bingham rheological parameter yield stress of SCC has been established. The model used here is inspired by previous work of Oh et al. (1), predicting that the yield stress of concrete relative to the yield stress of paste is a function of the relative thickness...... and distribution were varied between SCC types. The results indicate that yield stress of SCC may be predicted using the model....
Mrozek, Piotr
2011-08-01
A numerical model explicitly considering the space-charge density evolved both under the mask and in the region of optical structure formation was used to predict the profiles of Ag concentration during field-assisted Ag+--Na+ ion exchange channel waveguide fabrication. The influence of the unequal values of diffusion constants and mobilities of incoming and outgoing ions, the value of a correlation factor (Haven ratio), and particularly space-charge density induced during the ion exchange, on the resulting profiles of Ag concentration was analyzed and discussed. It was shown that the incorporation into the numerical model of a small quantity of highly mobile ions other than exclusively Ag+ and Na+ may considerably affect the range and shape of calculated Ag profiles in the multicomponent glass. The Poisson equation was used to predict the electric field spread evolution in the glass substrate. The results of the numerical analysis were verified by the experimental data of Ag concentration in a channel waveguide fabricated using a field-assisted process.
Fedele, Renato; De Nicola, Sergio; Shukla, P K; Jovanovic, Dusan
2011-01-01
Thermal Wave Model is used to study the strong self-consistent Plasma Wake Field interaction (transverse effects) between a strongly magnetized plasma and a relativistic electron/positron beam travelling along the external magnetic field, in the long beam limit, in terms of a nonlocal NLS equation and the virial equation. In the linear regime, vortices predicted in terms of Laguerre-Gauss beams characterized by non-zero orbital angular momentum (vortex charge). In the nonlinear regime, criteria for collapse and stable oscillations is established and the thin plasma lens mechanism is investigated, for beam size much greater than the plasma wavelength. The beam squeezing and the self-pinching equilibrium is predicted, for beam size much smaller than the plasma wavelength, taking the aberrationless solution of the nonlocal Nonlinear Schroeding equation.
Silva, Arnaldo F; Richter, Wagner E; Meneses, Helen G C; Bruns, Roy E
2014-11-14
Atomic charge transfer-counter polarization effects determine most of the infrared fundamental CH intensities of simple hydrocarbons, methane, ethylene, ethane, propyne, cyclopropane and allene. The quantum theory of atoms in molecules/charge-charge flux-dipole flux model predicted the values of 30 CH intensities ranging from 0 to 123 km mol(-1) with a root mean square (rms) error of only 4.2 km mol(-1) without including a specific equilibrium atomic charge term. Sums of the contributions from terms involving charge flux and/or dipole flux averaged 20.3 km mol(-1), about ten times larger than the average charge contribution of 2.0 km mol(-1). The only notable exceptions are the CH stretching and bending intensities of acetylene and two of the propyne vibrations for hydrogens bound to sp hybridized carbon atoms. Calculations were carried out at four quantum levels, MP2/6-311++G(3d,3p), MP2/cc-pVTZ, QCISD/6-311++G(3d,3p) and QCISD/cc-pVTZ. The results calculated at the QCISD level are the most accurate among the four with root mean square errors of 4.7 and 5.0 km mol(-1) for the 6-311++G(3d,3p) and cc-pVTZ basis sets. These values are close to the estimated aggregate experimental error of the hydrocarbon intensities, 4.0 km mol(-1). The atomic charge transfer-counter polarization effect is much larger than the charge effect for the results of all four quantum levels. Charge transfer-counter polarization effects are expected to also be important in vibrations of more polar molecules for which equilibrium charge contributions can be large.
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.
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.
Predictive modeling of dental pain using neural network.
Kim, Eun Yeob; Lim, Kun Ok; Rhee, Hyun Sill
2009-01-01
The mouth is a part of the body for ingesting food that is the most basic foundation and important part. The dental pain predicted by the neural network model. As a result of making a predictive modeling, the fitness of the predictive modeling of dental pain factors was 80.0%. As for the people who are likely to experience dental pain predicted by the neural network model, preventive measures including proper eating habits, education on oral hygiene, and stress release must precede any dental treatment.
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.
Directory of Open Access Journals (Sweden)
Azhar Ul-Haq
2016-12-01
Full Text Available This paper is aimed at modelling of a distinct smart charging station for electric vehicles (EVs that is suitable for DC quick EV charging while ensuring minimum stress on the power grid. Operation of the charging station is managed in such a way that it is either supplied by photovoltaic (PV power or the power grid, and the vehicle-to-grid (V2G is also implemented for improving the stability of the grid during peak load hours. The PV interfaced DC/DC converter and grid interfaced DC/AC bidirectional converter share a DC bus. A smooth transition of one operating mode to another demonstrates the effectiveness of the employed control strategy. Modelling and control of the different components are explained and are implemented in Simulink. Simulations illustrate the feasible behaviour of the charging station under all operating modes in terms of the four-way interaction among PV, EVs and the grid along with V2G operation. Additionally, a business model is discussed with comprehensive analysis of cost estimation for the deployment of charging facilities in a residential area. It has been recognized that EVs bring new opportunities in terms of providing regulation services and consumption flexibility by varying the recharging power at a certain time instant. The paper also discusses the potential financial incentives required to inspire EV owners for active participation in the demand response mechanism.
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.
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.
Energy Technology Data Exchange (ETDEWEB)
Xiang, T.
2010-05-03
Based on the analysis of the measurement data of angle-resolved photoemission spectroscopy (ARPES) and optics, we show that the charge transfer gap is significantly smaller than the optical one and is reduced by doping in electron doped cuprate superconductors. This leads to a strong charge fluctuation between the Zhang-Rice singlet and the upper Hubbard bands. The basic model for describing this system is a hybridized two-band t-J model. In the symmetric limit where the corresponding intra- and inter-band hopping integrals are equal to each other, this two-band model is equivalent to the Hubbard model with an antiferromagnetic exchange interaction (i.e. the t-U-J model). The mean-field result of the t-U-J model gives a good account for the doping evolution of the Fermi surface and the staggered magnetization.
Nassour, Ayoub; Kubicki, Maciej; Wright, Jonathan; Borowiak, Teresa; Dutkiewicz, Grzegorz; Lecomte, Claude; Jelsch, Christian
2014-04-01
The experimental charge-density distribution in 2-methyl-1,3-cyclopentanedione in the crystal state was analyzed by synchrotron X-ray diffraction data collection at 0.33 Å resolution. The molecule in the crystal is in the enol form. The experimental electron density was refined using the Hansen-Coppens multipolar model and an alternative modeling, based on spherical atoms and additional charges on the covalent bonds and electron lone-pair sites. The crystallographic refinements, charge-density distributions, molecular electrostatic potentials, dipole moments and intermolecular interaction energies obtained from the different charge-density models were compared. The experimental results are also compared with the theoretical charge densities using theoretical structure factors obtained from periodic quantum calculations at the B3LYP/6-31G** level. A strong intermolecular O-H···O hydrogen bond connects molecules along the [001] direction. The deformation density maps show the resonance within the O=C-C=C-OH fragment and merged lone pair lobes on the hydroxyl O atom. This resonance is further confirmed by the analysis of charges and topology of the electron density.
Prediction using patient comparison vs. modeling: a case study for mortality prediction.
Hoogendoorn, Mark; El Hassouni, Ali; Mok, Kwongyen; Ghassemi, Marzyeh; Szolovits, Peter
2016-08-01
Information in Electronic Medical Records (EMRs) can be used to generate accurate predictions for the occurrence of a variety of health states, which can contribute to more pro-active interventions. The very nature of EMRs does make the application of off-the-shelf machine learning techniques difficult. In this paper, we study two approaches to making predictions that have hardly been compared in the past: (1) extracting high-level (temporal) features from EMRs and building a predictive model, and (2) defining a patient similarity metric and predicting based on the outcome observed for similar patients. We analyze and compare both approaches on the MIMIC-II ICU dataset to predict patient mortality and find that the patient similarity approach does not scale well and results in a less accurate model (AUC of 0.68) compared to the modeling approach (0.84). We also show that mortality can be predicted within a median of 72 hours.
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
Improved Nonlinear Model of a Second-Order Charge-Pump Pll
Gillespie, Diarmaid; Kennedy, Michael Peter; Kolumbán, Géza
An improved model of a second-order Charge-Pump Phase-Locked Loop (CP-PLL) is proposed. An event-driven second-order CP-PLL o-model is further developed from that described by Hedayat [1]. This model is made practical by taking account of VCO overload. Transient simulations are shown which illustrate the nature of phase-locking.
The single-zone numerical model of homogeneous charge compression ignition engine performance
Fedyanov, E. A.; Itkis, E. M.; Kuzmin, V. N.; Shumskiy, S. N.
2017-02-01
The single-zone model of methane-air mixture combustion in the Homogeneous Charge Compression Ignition engine was developed. First modeling efforts resulted in the selection of the detailed kinetic reaction mechanism, most appropriate for the conditions of the HCCI process. Then, the model was completed so as to simulate the performance of the four-stroke engine and was coupled by physically reasonable adjusting functions. Validation of calculations against experimental data showed acceptable agreement.
Fuzzy predictive filtering in nonlinear economic model predictive control for demand response
DEFF Research Database (Denmark)
Santos, Rui Mirra; Zong, Yi; Sousa, Joao M. C.;
2016-01-01
The performance of a model predictive controller (MPC) is highly correlated with the model's accuracy. This paper introduces an economic model predictive control (EMPC) scheme based on a nonlinear model, which uses a branch-and-bound tree search for solving the inherent non-convex optimization...... problem. Moreover, to reduce the computation time and improve the controller's performance, a fuzzy predictive filter is introduced. With the purpose of testing the developed EMPC, a simulation controlling the temperature levels of an intelligent office building (PowerFlexHouse), with and without fuzzy...
DEFF Research Database (Denmark)
Bergman, Jorieke E H; Janssen, Nicole; van der Sloot, Almer M;
2012-01-01
difficult for missense variants because most variants in the CHD7 gene are private and a functional assay is not yet available. We have therefore developed a novel classification system to predict the pathogenic effects of CHD7 missense variants that can be used in a diagnostic setting. Our classification...... system combines the results from two computational algorithms (PolyPhen-2 and Align-GVGD) and the prediction of a newly developed structural model of the chromo- and helicase domains of CHD7 with segregation and phenotypic data. The combination of different variables will lead to a more confident...
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.
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.
Xu, Huifang; Dai, Yuehua
2017-02-01
A two-dimensional analytical model of double-gate (DG) tunneling field-effect transistors (TFETs) with interface trapped charges is proposed in this paper. The influence of the channel mobile charges on the potential profile is also taken into account in order to improve the accuracy of the models. On the basis of potential profile, the electric field is derived and the expression for the drain current is obtained by integrating the BTBT generation rate. The model can be used to study the impact of interface trapped charges on the surface potential, the shortest tunneling length, the drain current and the threshold voltage for varying interface trapped charge densities, length of damaged region as well as the structural parameters of the DG TFET and can also be utilized to design the charge trapped memory devices based on TFET. The biggest advantage of this model is that it is more accurate, and in its expression there are no fitting parameters with small calculating amount. Very good agreements for both the potential, drain current and threshold voltage are observed between the model calculations and the simulated results. Project supported by the National Natural Science Foundation of China (No. 61376106), the University Natural Science Research Key Project of Anhui Province (No. KJ2016A169), and the Introduced Talents Project of Anhui Science and Technology University.
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.
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.
Body charge modelling for accurate simulation of small-signal behaviour in floating body SOI
Benson, James; Redman-White, William; D'Halleweyn, Nele V.; Easson, Craig A.; Uren, Michael J.
2002-04-01
We show that careful modelling of body node elements in floating body PD-SOI MOSFET compact models is required in order to obtain accurate small-signal simulation results in the saturation region. The body network modifies the saturation output conductance of the device via the body-source transconductance, resulting in a pole/zero pair being introduced in the conductance-frequency response. We show that neglecting the presence of body charge in the saturation region can often yield inaccurate values for the body capacitances, which in turn can adversely affect the modelling of the output conductance above the pole/zero frequency. We conclude that the underlying cause of this problem is the use of separate models for the intrinsic and extrinsic capacitances. Finally, we present a simple saturation body charge model which can greatly improve small-signal simulation accuracy for floating body devices.
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.
Adaptation of Predictive Models to PDA Hand-Held Devices
Directory of Open Access Journals (Sweden)
Lin, Edward J
2008-01-01
Full Text Available Prediction models using multiple logistic regression are appearing with increasing frequency in the medical literature. Problems associated with these models include the complexity of computations when applied in their pure form, and lack of availability at the bedside. Personal digital assistant (PDA hand-held devices equipped with spreadsheet software offer the clinician a readily available and easily applied means of applying predictive models at the bedside. The purposes of this article are to briefly review regression as a means of creating predictive models and to describe a method of choosing and adapting logistic regression models to emergency department (ED clinical practice.
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
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.
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
Adding propensity scores to pure prediction models fails to improve predictive performance
Directory of Open Access Journals (Sweden)
Amy S. Nowacki
2013-08-01
Full Text Available Background. Propensity score usage seems to be growing in popularity leading researchers to question the possible role of propensity scores in prediction modeling, despite the lack of a theoretical rationale. It is suspected that such requests are due to the lack of differentiation regarding the goals of predictive modeling versus causal inference modeling. Therefore, the purpose of this study is to formally examine the effect of propensity scores on predictive performance. Our hypothesis is that a multivariable regression model that adjusts for all covariates will perform as well as or better than those models utilizing propensity scores with respect to model discrimination and calibration.Methods. The most commonly encountered statistical scenarios for medical prediction (logistic and proportional hazards regression were used to investigate this research question. Random cross-validation was performed 500 times to correct for optimism. The multivariable regression models adjusting for all covariates were compared with models that included adjustment for or weighting with the propensity scores. The methods were compared based on three predictive performance measures: (1 concordance indices; (2 Brier scores; and (3 calibration curves.Results. Multivariable models adjusting for all covariates had the highest average concordance index, the lowest average Brier score, and the best calibration. Propensity score adjustment and inverse probability weighting models without adjustment for all covariates performed worse than full models and failed to improve predictive performance with full covariate adjustment.Conclusion. Propensity score techniques did not improve prediction performance measures beyond multivariable adjustment. Propensity scores are not recommended if the analytical goal is pure prediction modeling.
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…
Modeling and prediction of surgical procedure times
P.S. Stepaniak (Pieter); C. Heij (Christiaan); G. de Vries (Guus)
2009-01-01
textabstractAccurate prediction of medical operation times is of crucial importance for cost efficient operation room planning in hospitals. This paper investigates the possible dependence of procedure times on surgeon factors like age, experience, gender, and team composition. The effect of these f
Active diagnosis of hybrid systems - A model predictive approach
2009-01-01
A method for active diagnosis of hybrid systems is proposed. The main idea is to predict the future output of both normal and faulty model of the system; then at each time step an optimization problem is solved with the objective of maximizing the difference between the predicted normal and faulty outputs constrained by tolerable performance requirements. As in standard model predictive control, the first element of the optimal input is applied to the system and the whole procedure is repeate...
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…
Superconducting, magnetic, and charge correlations in the doped two-chain Hubbard model
Asai, Y
1995-01-01
Superconducting, magnetic, and charge correlation functions and dynamic spin correlation functions of the doped two-chain Hubbard model is studied with the projector Quantum Monte carlo method and Lanczos recursion method. Of the three correlation functions, the interchain singlet superconducting correlation function is the most long range. Our data is not consistent with the Luther-Emery picture.
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.
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
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.
Evaluation of Fast-Time Wake Vortex Prediction Models
Proctor, Fred H.; Hamilton, David W.
2009-01-01
Current fast-time wake models are reviewed and three basic types are defined. Predictions from several of the fast-time models are compared. Previous statistical evaluations of the APA-Sarpkaya and D2P fast-time models are discussed. Root Mean Square errors between fast-time model predictions and Lidar wake measurements are examined for a 24 hr period at Denver International Airport. Shortcomings in current methodology for evaluating wake errors are also discussed.
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
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.
Econometric models for predicting confusion crop ratios
Umberger, D. E.; Proctor, M. H.; Clark, J. E.; Eisgruber, L. M.; Braschler, C. B. (Principal Investigator)
1979-01-01
Results for both the United States and Canada show that econometric models can provide estimates of confusion crop ratios that are more accurate than historical ratios. Whether these models can support the LACIE 90/90 accuracy criterion is uncertain. In the United States, experimenting with additional model formulations could provide improved methods models in some CRD's, particularly in winter wheat. Improved models may also be possible for the Canadian CD's. The more aggressive province/state models outperformed individual CD/CRD models. This result was expected partly because acreage statistics are based on sampling procedures, and the sampling precision declines from the province/state to the CD/CRD level. Declining sampling precision and the need to substitute province/state data for the CD/CRD data introduced measurement error into the CD/CRD models.
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.
Energy Technology Data Exchange (ETDEWEB)
Wiegman, H.L.N. [General Electric Corporate Research and Development, Schenectady, NY (United States)
2000-07-01
Some recent advances in battery modeling were discussed with reference to on-line impedance estimates and power performance predictions for aqueous solution, porous electrode cell structures. The objective was to determine which methods accurately estimate a battery's internal state and power capability while operating a charge and sustaining a hybrid electric vehicle (HEV) over a wide range of driving conditions. The enhancements to the Randles-Ershler equivalent electrical model of common cells with lead-acid, nickel-cadmium and nickel-metal hydride chemistries were described. This study also investigated which impedances are sensitive to boundary layer charge concentrations and mass transport limitations. Non-linear impedances were shown to significantly affect the battery's ability to process power. The main advantage of on-line estimating a battery's impedance state and power capability is that the battery can be optimally sized for any application. refs., tabs., figs., append.
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).
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.
The regional prediction model of PM10 concentrations for Turkey
Güler, Nevin; Güneri İşçi, Öznur
2016-11-01
This study is aimed to predict a regional model for weekly PM10 concentrations measured air pollution monitoring stations in Turkey. There are seven geographical regions in Turkey and numerous monitoring stations at each region. Predicting a model conventionally for each monitoring station requires a lot of labor and time and it may lead to degradation in quality of prediction when the number of measurements obtained from any õmonitoring station is small. Besides, prediction models obtained by this way only reflect the air pollutant behavior of a small area. This study uses Fuzzy C-Auto Regressive Model (FCARM) in order to find a prediction model to be reflected the regional behavior of weekly PM10 concentrations. The superiority of FCARM is to have the ability of considering simultaneously PM10 concentrations measured monitoring stations in the specified region. Besides, it also works even if the number of measurements obtained from the monitoring stations is different or small. In order to evaluate the performance of FCARM, FCARM is executed for all regions in Turkey and prediction results are compared to statistical Autoregressive (AR) Models predicted for each station separately. According to Mean Absolute Percentage Error (MAPE) criteria, it is observed that FCARM provides the better predictions with a less number of models.
A Numerical Model for Ion Charge Distribution of Plasmas in Collisional Radiative Steady State
Institute of Scientific and Technical Information of China (English)
DUAN Yaoyong; GUO Yonghui; QIU Aici; KUAI Bin
2009-01-01
A numerical model for the charge state distribution of plasmas in a collisional ra-diative steady state (CRSS) is established by averaging over the atomic process rate coefficients in universal kinetic equations.It is used to calculate the mean ion charge and ion population for a given temperature and density of the plasmas,ranging from low Z to high Z elements.The comparisons of the calculated results with those of other non-local thermodynamic equilibrium kinetics codes show that this model possesses acceptable precision.Furthermore,the NLTE effects are investigated by virtue of the model,and the differences between CRSS and LTE models for low density plasmas are quite evident.
The charge-asymmetric nonlocally-determined local-electric (CANDLE) solvation model
Sundararaman, Ravishankar
2014-01-01
Many important applications of electronic structure methods involve molecules or solid surfaces in a solvent medium. Since explicit treatment of the solvent in such methods is usually not practical, calculations often employ continuum solvation models to approximate the effect of the solvent. Previous solvation models either involve a parametrization based on atomic radii, which limits the class of applicable solutes, or based on solute electron density, which is more general but less accurate, especially for charged systems. We develop an accurate and general solvation model that includes a cavity that is a nonlocal functional of both solute electron density and potential, local dielectric response on this nonlocally-determined cavity, and nonlocal approximations to the cavity-formation and dispersion energies. The dependence of the cavity on the solute potential enables an explicit treatment of the solvent charge asymmetry. With only three parameters per solvent, this `CANDLE' model simultaneously reproduce...
Search for Charged Higgs Bosons at LEP in General Two Higgs Doublet Models
Abdallah, J; Adam, W; Adzic, P; Albrecht, T; Alderweireld, T; Alemany-Fernandez, R; Allmendinger, T; Allport, P P; Amaldi, Ugo; Amapane, N; Amato, S; Anashkin, E; Andreazza, A; Andringa, S; Anjos, N; Antilogus, P; Apel, W D; Arnoud, Y; Ask, S; Åsman, B; Augustin, J E; Augustinus, A; Baillon, Paul; Ballestrero, A; Bambade, P; Barbier, R; Bardin, Dimitri Yuri; Barker, G; Baroncelli, A; Battaglia, Marco; Baubillier, M; Becks, K H; Begalli, M; Behrmann, A; Ben-Haim, E; Benekos, N C; Benvenuti, Alberto C; Bérat, C; Berggren, M; Berntzon, L; Bertrand, D; Besançon, M; Besson, N; Bloch, D; Blom, M; Bluj, M; Bonesini, M; Boonekamp, M; Booth, P S L; Borisov, G; Botner, O; Bouquet, B; Bowcock, T J V; Boyko, I; Bracko, M; Brenner, R; Brodet, E; Brückman, P; Brunet, J M; Bugge, L; Buschmann, P; Calvi, M; Camporesi, T; Canale, V; Carena, F; Castro, N; Cavallo, F R; Chapkin, M M; Charpentier, P; Checchia, P; Chierici, R; Shlyapnikov, P; Chudoba, J; Chung, S U; Cieslik, K; Collins, P; Contri, R; Cosme, G; Cossutti, F; Costa, M J; Crennell, D J; Cuevas-Maestro, J; D'Hondt, J; Dalmau, J; Da Silva, T; Da Silva, W; Della Ricca, G; De Angelis, A; de Boer, Wim; De Clercq, C; De Lotto, B; De Maria, N; De Min, A; De Paula, L S; Di Ciaccio, L; Di Simone, A; Doroba, K; Drees, J; Dris, M; Eigen, G; Ekelöf, T J C; Ellert, M; Elsing, M; Espirito-Santo, M C; Fanourakis, G K; Fassouliotis, D; Feindt, M; Fernández, J; Ferrer, A; Ferro, F; Flagmeyer, U; Föth, H; Fokitis, E; Fulda-Quenzer, F; Fuster, J A; Gandelman, M; García, C; Gavillet, P; Gazis, E N; Gokieli, R; Golob, B; Gómez-Ceballos, G; Gonçalves, P; Graziani, E; Grosdidier, G; Grzelak, K; Guy, J; Haag, C; Hallgren, A; Hamacher, K; Hamilton, K; Haug, S; Hauler, F; Hedberg, V; Hennecke, M; Herr, H; Hoffman, J; Holmgren, S O; Holt, P J; Houlden, M A; Hultqvist, K; Jackson, J N; Jarlskog, G; Jarry, P; Jeans, D; Johansson, E K; Johansson, P D; Jonsson, P; Joram, C; Jungermann, L; Kapusta, F; Katsanevas, S; Katsoufis, E C; Kernel, G; Kersevan, Borut P; Kerzel, U; Kiiskinen, A P; King, B T; Kjaer, N J; Kluit, P; Kokkinias, P; Kourkoumelis, C; Kuznetsov, O; Krumshtein, Z; Kucharczyk, M; Lamsa, J; Leder, G; Ledroit, F; Leinonen, L; Leitner, R; Lemonne, J; Lepeltier, V; Lesiak, T; Liebig, W; Liko, D; Lipniacka, A; Lopes, J H; López, J M; Loukas, D; Lutz, P; Lyons, L; MacNaughton, J; Malek, A; Maltezos, S; Mandl, F; Marco, J; Marco, R; Maréchal, B; Margoni, M; Marin, J C; Mariotti, C; Markou, A; Martínez-Rivero, C; Masik, J; Mastroyiannopoulos, N; Matorras, F; Matteuzzi, C; Mazzucato, F; Mazzucato, M; McNulty, R; Meroni, C; Migliore, E; Mitaroff, W A; Mjörnmark, U; Moa, T; Moch, M; Mönig, K; Monge, R; Montenegro, J; Moraes, D; Moreno, S; Morettini, P; Müller, U; Münich, K; Mulders, M; Mundim, L M; Murray, W; Muryn, B; Myatt, G; Myklebust, T; Nassiakou, M; Navarria, Francesco Luigi; Nawrocki, K; Nicolaidou, R; Nikolenko, M; Oblakowska-Mucha, A; Obraztsov, V F; Olshevskii, A G; Onofre, A; Orava, R; Österberg, K; Ouraou, A; Oyanguren, A; Paganoni, M; Paiano, S; Palacios, J P; Palka, H; Papadopoulou, T D; Pape, L; Parkes, C; Parodi, F; Parzefall, U; Passeri, A; Passon, O; Peralta, L; Perepelitsa, V F; Perrotta, A; Petrolini, A; Piedra, J; Pieri, L; Pierre, F; Pimenta, M; Piotto, E; Podobnik, T; Poireau, V; Pol, M E; Polok, G; Poropat, P; Pozdnyakov, V; Pukhaeva, N; Pullia, Antonio; Rames, J; Ramler, L; Read, A; Rebecchi, P; Rehn, J; Reid, D; Reinhardt, R; Renton, P B; Richard, F; Rídky, J; Rivero, M; Rodríguez, D; Romero, A; Ronchese, P; Roudeau, Patrick; Rovelli, T; Ruhlmann-Kleider, V; Ryabtchikov, D; Sadovskii, A; Salmi, L; Salt, J; Savoy-Navarro, A; Schwickerath, U; Segar, A; Sekulin, R L; Siebel, M; Sissakian, A N; Smadja, G; Smirnova, O G; Sokolov, A; Sopczak, A; Sosnowski, R; Spassoff, Tz; Stanitzki, M; Stocchi, A; Strauss, J; Stugu, B; Szczekowski, M; Szeptycka, M; Szumlak, T; Tabarelli de Fatis, T; Taffard, A C; Tegenfeldt, F; Timmermans, J; Tkatchev, L G; Tobin, M; Todorovova, S; Tomé, B; Tonazzo, A; Tortosa, P; Travnicek, P; Treille, D; Tristram, G; Trochimczuk, M; Troncon, C; Turluer, M L; Tyapkin, I A; Tyapkin, P; Tzamarias, S; Uvarov, V; Valenti, G; van Dam, P; Van Eldik, J; Van Lysebetten, A; Van Remortel, N; Van Vulpen, I; Vegni, G; Veloso, F; Venus, W A; Verdier, P; Verzi, V; Vilanova, D; Vitale, L; Vrba, V; Wahlen, H; Washbrook, A J; Weiser, C; Wicke, D; Wickens, J H; Wilkinson, G; Winter, M; Witek, M; Yushchenko, O P; Zalewska-Bak, A; Zalewski, P; Zavrtanik, D; Zhuravlov, V; Zimin, N I; Zintchenko, A; Zupan, M
2004-01-01
A search for pair-produced charged Higgs bosons was performed in the data collected by the DELPHI detector at LEP II at centre-of-mass energies from 189 GeV to 209 GeV. Five different final states, tau+ nu_tau tau- anti-nu_tau, c sbar cbar s, c sbar tau- anti-nu_tau, W* A W* A and W* A tau- anti-nu_tau were considered, accounting for the major expected decays in type I and type II Two Higgs Doublet Models. No significant excess of data compared to the expected Standard Model processes was observed. The existence of a charged Higgs boson with mass lower than 76.7 GeV/c^2 (type I) or 74.4 GeV/c^2 (type II) is excluded at the 95% confidence level, for a wide range of the model parameters. Model independent cross-section limits have also been calculated.
Cold phase fluid model of the longitudinal dynamics ofspace-charged dominated beams
Energy Technology Data Exchange (ETDEWEB)
de Hoon, Michiel J.L.; Lee, Edward P.; Barnard, John J.; Friedman, Alex
2002-03-01
The dynamics of a longitudinally cold, charged-particle beam can be simulated by dividing the beam into slices and calculating the motion of the slice boundaries due to the longitudinal electric field generated by the beam. On each time step, the beam charge is deposited onto an (r, z) grid, and an existing (r, z) electrostatic field solver is used to find the longitudinal electric field. Transversely, the beam envelope equation is used for each slice boundary separately. In contrast to the g-factor model, it can be shown analytically that the repulsive electric field of a slice compressed to zero length is bounded. Consequently, this model allows slices to overtake their neighbors, effectively incorporating mixing. The model then effectively describes a cold fluid in longitudinal z, v{sub z} phase space. Longitudinal beam compression calculations based on this cold phase fluid model showed that slice overtaking reflects local mixing, while the global phase space structure is preserved.
Stauffer, D; Dragneva, N; Floriano, W B; Mawhinney, R C; Fanchini, G; French, S; Rubel, O
2014-07-28
Graphene Oxide (GO) has been shown to exhibit properties that are useful in applications such as biomedical imaging, biological sensors, and drug delivery. The binding properties of biomolecules at the surface of GO can provide insight into the potential biocompatibility of GO. Here we assess the intrinsic affinity of amino acids to GO by simulating their adsorption onto a GO surface. The simulation is done using Amber03 force-field molecular dynamics in explicit water. The emphasis is placed on developing an atomic charge model for GO. The adsorption energies are computed using atomic charges obtained from an ab initio electrostatic potential based method. The charges reported here are suitable for simulating peptide adsorption to GO.
Chanda, Manash; Das, Rahul; Kundu, Atanu; Sarkar, Chandan K.
2017-04-01
In this paper charge plasma based dielectric modulated four gated MOSFET (CP-GUDM-MOSFET) has been proposed for the efficacy of label free electrical detection of the biomolecules. To achieve low thermal budgeting, charge-plasma concept is employed using appropriate metal work function electrodes. Extensive simulations have been done using the Sentaurus TCAD to validate the proposed architecture. An analytical modeling has also been done on surface potential and drain current to consolidate the feasibility of the structure. Significant improvements in the on current (ION) and threshold voltage have been observed in presence of the charged biomolecules. The performance of proposed structure is found to be sensitive to gate-oxide thickness variations. High sensitivity of the proposed CP-GUDM-MOSFET based biosensor with low thermal budgeting scheme; simple structure and its compatibility with the existing CMOS processes make it an exciting alternative to the conventional FET-based biosensors.
Scafè, Raffaele; Pellegrini, Rosanna; Cinti, Maria N.; Puccini, Marco; Pani, Roberto
2016-10-01
Present paper describes a method for obtaining the physical quantities characterizing single-events based on fitting experimental 2-D charge-profiles to two analytical models. First results are presented regarding a 10×10 LuYAP:Ce array of 2×2×10 mm3 crystal pixels coupled to a H10966 Hamamatsu 8×8 multi-anode assembly under radio-isotopic irradiations and from self-activity. Results show that a photo multiplier tube with cross plate anode configuration would be preferable than a multi anode one due to uniformity, cost, and connections constraints. Among the results a plot of charge spread Vs. charge is to be cited because it was not yet published in scientific literature.
Coronell, Orlando; Mi, Baoxia; Mariñas, Benito J; Cahill, David G
2013-01-02
We used an extended solution-diffusion model that incorporates Donnan electrostatic exclusion of ions and unhindered advection due to imperfections, and measurements of charge density in the polyamide active layers of reverse osmosis (RO) and nanofiltration (NF) membranes, to predict the rejection of a strong electrolyte (i.e., potassium iodide) and a weak acid (i.e., arsenious acid) as a function of the pH of the feed aqueous solution. Predictions of solute rejection were in agreement with experimental data indicating that (i) the extended solution-diffusion model taking into account Donnan exclusion and unhindered advection due to imperfections satisfactorily describes the effect of pH on solute rejection by RO/NF membranes and (ii) measurement of charge density in active layers provides a valuable characterization of RO/NF membranes. Our results and analysis also indicate that independent ions, and not ion pairs, dominate the permeation of salts.
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.
Finite Field Methods for the Supercell Modelling of Charged Insulator-Electrolyte Interfaces
Zhang, Chao
2016-01-01
Surfaces of ionic solids interacting with an ionic solution can build up charge by exchange of ions. The surface charge is compensated by a strip of excess charge at the border of the electrolyte forming an electric double layer. These electric double layers are very hard to model using the supercells methods of computational condensed phase science. The problem arises when the solid is an electric insulator (as most ionic solids are) permitting a finite interior electric field over the width of the slab representing the solid in the supercell. The slab acts as a capacitor. The stored charge is a deficit in the solution failing to compensate fully for the solid surface charge. Here we show how these problems can be overcome using the finite field methods developed by Stengel, Spaldin and Vanderbilt [Nat. Phys. 5, 304, (2009)]. We also show how the capacitance of the double layer can be computed once overall electric neutrality of the double layer is restored by application of a finite macroscopic field E or a...
Control of intrachain charge transfer in model systems for block copolymer photovoltaic materials.
Johnson, Kerr; Huang, Ya-Shih; Huettner, Sven; Sommer, Michael; Brinkmann, Martin; Mulherin, Rhiannon; Niedzialek, Dorota; Beljonne, David; Clark, Jenny; Huck, Wilhelm T S; Friend, Richard H
2013-04-01
We report the electronic properties of the conjugated coupling between a donor polymer and an acceptor segment serving as a model for the coupling in conjugated donor-acceptor block copolymers. These structures allow the study of possible intrachain photoinduced charge separation, in contrast to the interchain separation achieved in conventional donor-acceptor blends. Depending on the nature of the conjugated linkage, we observe varying degrees of modification of the excited states, including the formation of intrachain charge transfer excitons. The polymers comprise a block (typically 18 repeat units) of P3HT, poly(3-hexyl thiophene), coupled to a single unit of F8-TBT (where F8 is dioctylfluorene, and TBT is thiophene-benzothiadiazole-thiophene). When the P3HT chain is linked to the TBT unit, we observe formation of a localized charge transfer state, with red-shifted absorption and emission. Independent of the excitation energy, this state is formed very rapidly (<40 fs) and efficiently. Because there is only a single TBT unit present, there is little scope for long-range charge separation and it is relatively short-lived, <1 ns. In contrast, when the P3HT chain and TBT unit are separated by the wider bandgap F8 unit, there is little indication for modification of either ground or excited electronic states, and longer-lived charge separated states are observed.
Ground State and Charge Renormalization in a Nonlinear Model of Relativistic Atoms
Gravejat, Philippe; Sere, Eric
2007-01-01
We study the reduced Bogoliubov-Dirac-Fock (BDF) energy which allows to describe relativistic electrons interacting with the Dirac sea, in an external electrostatic potential. The model can be seen as a mean-field approximation of Quantum Electrodynamics (QED) where photons and the so-called exchange term are neglected. A state of the system is described by its one-body density matrix, an infinite rank self-adjoint operator which is a compact perturbation of the negative spectral projector of the free Dirac operator (the Dirac sea). We study the minimization of the reduced BDF energy under a charge constraint. We prove the existence of minimizers for a large range of values of the charge, and any positive value of the coupling constant $\\alpha$. Our result covers neutral and positively charged molecules, provided that the positive charge is not large enough to create electron-positron pairs. We also prove that the density of any minimizer is an $L^1$ function and compute the effective charge of the system, re...
Yao, Yi; Berkowitz, Max L; Kanai, Yosuke
2015-12-28
The translational diffusivity of water in solutions of alkali halide salts depends on the identity of ions, exhibiting dramatically different behavior even in solutions of similar salts of NaCl and KCl. The water diffusion coefficient decreases as the salt concentration increases in NaCl. Yet, in KCl solution, it slightly increases and remains above bulk value as salt concentration increases. Previous classical molecular dynamics simulations have failed to describe this important behavior even when polarizable models were used. Here, we show that inclusion of dynamical charge transfer among water molecules produces results in a quantitative agreement with experiments. Our results indicate that the concentration-dependent diffusivity reflects the importance of many-body effects among the water molecules in aqueous ionic solutions. Comparison with quantum mechanical calculations shows that a heterogeneous and extended distribution of charges on water molecules around the ions due to ion-water and also water-water charge transfer plays a very important role in controlling water diffusivity. Explicit inclusion of the charge transfer allows us to model accurately the difference in the concentration-dependent water diffusivity between Na(+) and K(+) ions in simulations, and it is likely to impact modeling of a wide range of systems for medical and technological applications.
Directory of Open Access Journals (Sweden)
P. Braun-Munzinger
2015-07-01
Full Text Available We construct net baryon number and strangeness susceptibilities as well as correlations between electric charge, strangeness and baryon number from experimental data at midrapidity of the ALICE Collaboration at CERN. The data were taken in central Pb–Pb collisions at sNN=2.76 TeV and cover one unit of rapidity. The resulting fluctuations and correlations are consistent with Lattice QCD results at the chiral crossover pseudocritical temperature Tc≃155 MeV. This agreement lends strong support to the assumption that the fireball created in these collisions is of thermal origin and exhibits characteristic properties expected in QCD at the transition from the quark gluon plasma to the hadronic phase. The volume of the fireball for one unit of rapidity at Tc is found to exceed 3000 fm3. A detailed discussion on uncertainties in the temperature and volume of the fireball is presented. The results are linked to pion interferometry measurements and predictions from percolation theory.
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.
Charged Higgs bosons from the 3-3-1 models and the R (D(*)) anomalies
Ma, Wei; Yue, Chong-Xing
2017-02-01
Several anomalies in the semileptonic B-meson decays such as R (D(*)) have been reported by the BABAR, Belle, and LHCb collaborations recently. In this paper, we investigate the contributions of the charged Higgs bosons from the 3-3-1 models to the R (D(*)) anomalies. We find that, in a wide range of parameter space, the 3-3-1 models might give reasonable explanations to the R (D(*)) anomalies and other analogous anomalies of the B meson's semileptonic decays.
Generalization of Weber's adiabatic bond charge model to amorphous group IV semiconductors
Winer, K.; Wooten, F.
1984-11-01
The generalization of Weber's adiabatic bond charge model to amorphous group IV semiconductors is described. Methods of relaxing the coordinates to their equilibrium configuration and of calculating the dynamical matrix for the phonon spectra are given. Particular emphasis is given to the optimization of the Coulomb subroutines required in this model. Estimates of computation time are included for the calculation of equilibrium configuration on a Cray computer.
Searching the charged Higgs boson of the type III two Higss doublet model
Cardenas, H
2008-01-01
In the framework of the Two Higgs Doublet Model (2HDM) type III appears two charged Higgs boson and recently there are experimental reports from D0 and CDF collaborations searching a particular signature of new physics. We present a review of the analisys done in the region $M_{H^+}>m_t$ by D0 collaboration and we use the ratio $R_\\sigma$ for the region $M_{H^+} < m_t$ in different scenarios of space parameter of this model.
Nonlinear model predictive control of a packed distillation column
Energy Technology Data Exchange (ETDEWEB)
Patwardhan, A.A.; Edgar, T.F. (Univ. of Texas, Austin, TX (United States). Dept. of Chemical Engineering)
1993-10-01
A rigorous dynamic model based on fundamental chemical engineering principles was formulated for a packed distillation column separating a mixture of cyclohexane and n-heptane. This model was simplified to a form suitable for use in on-line model predictive control calculations. A packed distillation column was operated at several operating conditions to estimate two unknown model parameters in the rigorous and simplified models. The actual column response to step changes in the feed rate, distillate rate, and reboiler duty agreed well with dynamic model predictions. One unusual characteristic observed was that the packed column exhibited gain-sign changes, which are very difficult to treat using conventional linear feedback control. Nonlinear model predictive control was used to control the distillation column at an operating condition where the process gain changed sign. An on-line, nonlinear model-based scheme was used to estimate unknown/time-varying model parameters.
Signal modeling of charge sharing effect in simple pixelated CdZnTe detector
Kim, Jae Cheon; Kaye, William R.; He, Zhong
2014-05-01
In order to study the energy resolution degradation in 3D position-sensitive pixelated CdZnTe (CZT) detectors, a detailed detector system modeling package has been developed and used to analyze the detector performance. A 20 × 20 × 15 mm3 CZT crystal with an 11 × 11 simple-pixel anode array and a 1.72 mm pixel pitch was modeled. The VAS UM/TAT4 Application Specific Integrated Circuitry (ASIC) was used for signal read-out. Components of the simulation package include gamma-ray interactions with the CZT crystal, charge induction, electronic noise, pulse shaping, and ASIC triggering procedures. The charge induction model considers charge drift, trapping, diffusion, and sharing between pixels. This system model is used to determine the effects of electron cloud sharing, weighting potential non-uniformity, and weighting potential cross-talk which produce non-uniform signal responses for different gamma-ray interaction positions and ultimately degrade energy resolution. The effect of the decreased weighting potential underneath the gap between pixels on the total pulse amplitude of events has been studied. The transient signals induced by electron clouds collected near the gap between pixels may generate false signals, and the measured amplitude can be even greater than the photopeak. As the number of pixels that collect charge increases, the probability of side-neighbor events due to charge sharing significantly increases. If side-neighbor events are not corrected appropriately, the energy resolution of pixelated CZT detectors in multiple-pixel events degrades rapidly.
Signal modeling of charge sharing effect in simple pixelated CdZnTe detector
Energy Technology Data Exchange (ETDEWEB)
Kim, Jae C.; Kaye, William R.; He, Zhong [University of Michigan, Ann Arbor, MI (United States)
2014-05-15
In order to study the energy resolution degradation in 3D position-sensitive pixelated CdZnTe (CZT) detectors, a detailed detector system modeling package has been developed and used to analyze the detector performance. A 20 x 20 x 15 mm{sup 3} CZT crystal with an 11 x 11 simple-pixel anode array and a 1.72 mm pixel pitch was modeled. The VAS UM/TAT4 Application Specific Integrated Circuitry (ASIC) was used for signal read-out. Components of the simulation package include gamma-ray interactions with the CZT crystal, charge induction, electronic noise, pulse shaping, and ASIC triggering procedures. The charge induction model considers charge drift, trapping, diffusion, and sharing between pixels. This system model is used to determine the effects of electron cloud sharing, weighting potential non-uniformity, and weighting potential cross-talk which produce non-uniform signal responses for different gamma-ray interaction positions and ultimately degrade energy resolution. The effect of the decreased weighting potential underneath the gap between pixels on the total pulse amplitude of events has been studied. The transient signals induced by electron clouds collected near the gap between pixels may generate false signals, and the measured amplitude can be even greater than the photopeak. As the number of pixels that collect charge increases, the probability of side-neighbor events due to charge sharing significantly increases. If side-neighbor events are not corrected appropriately, the energy resolution of pixelated CZT detectors in multiple-pixel events degrades rapidly.
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.
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...... day (using the area under the receiver operating characteristic curve (AUC) and kappa statistics) and by assessing consistency in predictions of range size changes under future climate (using cluster analysis). Results Our analyses show significant differences between predictions from different models......, with predicted changes in range size by 2030 differing in both magnitude and direction (e.g. from 92% loss to 322% gain). We explain differences with reference to two characteristics of the modelling techniques: data input requirements (presence/absence vs. presence-only approaches) and assumptions made by each...
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....... The conferred results show that the prediction errors can be decreased, while the computation time is reduced....
Model Predictive Control for Smart Energy Systems
DEFF Research Database (Denmark)
Halvgaard, Rasmus
load shifting capabilities of the units that adapts to the given price predictions. We furthermore evaluated control performance in terms of economic savings for different control strategies and forecasts. Chapter 5 describes and compares the proposed large-scale Aggregator control strategies....... Aggregators are assumed to play an important role in the future Smart Grid and coordinate a large portfolio of units. The developed economic MPC controllers interfaces each unit directly to an Aggregator. We developed several MPC-based aggregation strategies that coordinates the global behavior of a portfolio...
Osman, Marisol; Vera, C. S.
2016-11-01
This work presents an assessment of the predictability and skill of climate anomalies over South America. The study was made considering a multi-model ensemble of seasonal forecasts for surface air temperature, precipitation and regional circulation, from coupled global circulation models included in the Climate Historical Forecast Project. Predictability was evaluated through the estimation of the signal-to-total variance ratio while prediction skill was assessed computing anomaly correlation coefficients. Both indicators present over the continent higher values at the tropics than at the extratropics for both, surface air temperature and precipitation. Moreover, predictability and prediction skill for temperature are slightly higher in DJF than in JJA while for precipitation they exhibit similar levels in both seasons. The largest values of predictability and skill for both variables and seasons are found over northwestern South America while modest but still significant values for extratropical precipitation at southeastern South America and the extratropical Andes. The predictability levels in ENSO years of both variables are slightly higher, although with the same spatial distribution, than that obtained considering all years. Nevertheless, predictability at the tropics for both variables and seasons diminishes in both warm and cold ENSO years respect to that in all years. The latter can be attributed to changes in signal rather than in the noise. Predictability and prediction skill for low-level winds and upper-level zonal winds over South America was also assessed. Maximum levels of predictability for low-level winds were found were maximum mean values are observed, i.e. the regions associated with the equatorial trade winds, the midlatitudes westerlies and the South American Low-Level Jet. Predictability maxima for upper-level zonal winds locate where the subtropical jet peaks. Seasonal changes in wind predictability are observed that seem to be related to
Zhang, Wen; Wang, Chenyin; Tam, Kin Y
2014-01-01
The objective of this study is to evaluate whether the accumulation model developed by Zarfl et al. (2008) could be used to predict the minimal inhibitory concentration (MIC) of a group of antibacterial fluoroquinolones (FQs) for Escherichia coli (E. coli). Our model, which is based on the "Fick-Nernst-Planck" equation and the permeability of the neutral and charged species as well as the physicochemical parameters of the FQs, could predict 1/MIC90 using a linear function. It is envisaged that in the drug development projects of new FQs, the accumulation model described in this study could be utilized as an effective tool to enable early assessment of MIC value using physiochemical parameters.
Assessment of performance of survival prediction models for cancer prognosis
Directory of Open Access Journals (Sweden)
Chen Hung-Chia
2012-07-01
Full Text Available Abstract Background Cancer survival studies are commonly analyzed using survival-time prediction models for cancer prognosis. A number of different performance metrics are used to ascertain the concordance between the predicted risk score of each patient and the actual survival time, but these metrics can sometimes conflict. Alternatively, patients are sometimes divided into two classes according to a survival-time threshold, and binary classifiers are applied to predict each patient’s class. Although this approach has several drawbacks, it does provide natural performance metrics such as positive and negative predictive values to enable unambiguous assessments. Methods We compare the survival-time prediction and survival-time threshold approaches to analyzing cancer survival studies. We review and compare common performance metrics for the two approaches. We present new randomization tests and cross-validation methods to enable unambiguous statistical inferences for several performance metrics used with the survival-time prediction approach. We consider five survival prediction models consisting of one clinical model, two gene expression models, and two models from combinations of clinical and gene expression models. Results A public breast cancer dataset was used to compare several performance metrics using five prediction models. 1 For some prediction models, the hazard ratio from fitting a Cox proportional hazards model was significant, but the two-group comparison was insignificant, and vice versa. 2 The randomization test and cross-validation were generally consistent with the p-values obtained from the standard performance metrics. 3 Binary classifiers highly depended on how the risk groups were defined; a slight change of the survival threshold for assignment of classes led to very different prediction results. Conclusions 1 Different performance metrics for evaluation of a survival prediction model may give different conclusions in
Combining logistic regression and neural networks to create predictive models.
Spackman, K. A.
1992-01-01
Neural networks are being used widely in medicine and other areas to create predictive models from data. The statistical method that most closely parallels neural networks is logistic regression. This paper outlines some ways in which neural networks and logistic regression are similar, shows how a small modification of logistic regression can be used in the training of neural network models, and illustrates the use of this modification for variable selection and predictive model building wit...
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.
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)
Models of Longitudinal Space-Charge Impedance for the Study of theMicrobunching Instability
Energy Technology Data Exchange (ETDEWEB)
Venturini, Marco
2008-03-10
A 1D model of space-charge impedance, assuming atransversely uniform beam with circular cross-section, has been proposedand is being extensively used in the modelling of the microbunchinginstability of relevance for the beam delivery systems of x-ray FELs. Inthis paper we investigate the limitation of the model when applied tostudying the effect of shot noise--one of the sources of themicrobunching instability. We make comparison witha fully 3D calculationand identify the upper end of the frequency spectrum for applicability ofthe 1D model. Relaxation of the assumptions regarding axis-symmetry anduniformity of the transverse density is also reviewed.
Golden, R. L.; Badhwar, G. D.; Stephens, S. A.
1975-01-01
The continuity equation for cosmic ray propagation is used to derive a set of linear equations interrelating the fluxes of multiply charged nuclei as observed at any particular part of the galaxy. The derivation leads to model independent definitions for cosmic ray storage time, mean density of target nuclei and effective mass traversed. The set of equations form a common framework for comparisons of theories and observations. As an illustration, it is shown that there exists a large class of propagation models which give the same result as the exponential path length model. The formalism is shown to accommodate dynamic as well as equilibrium models of production and propagation.
Modeling Charge-Sign Asymmetric Solvation Free Energies With Nonlinear Boundary Conditions
Bardhan, Jaydeep P
2014-01-01
We show that charge-sign-dependent asymmetric hydration can be modeled accurately using linear Poisson theory but replacing the standard electric-displacement boundary condition with a simple nonlinear boundary condition. Using a single multiplicative scaling factor to determine atomic radii from molecular dynamics Lennard-Jones parameters, the new model accurately reproduces MD free-energy calculations of hydration asymmetries for (i) monatomic ions, (ii) titratable amino acids in both their protonated and unprotonated states, and (iii) the Mobley "bracelet" and "rod" test problems [J. Phys. Chem. B, v. 112:2408, 2008]. Remarkably, the model also justifies the use of linear response expressions for charging free energies. Our boundary-element method implementation demonstrates the ease with which other continuum-electrostatic solvers can be extended to include asymmetry.
Observation of spatial charge and spin correlations in the 2D Fermi-Hubbard model.
Cheuk, Lawrence W; Nichols, Matthew A; Lawrence, Katherine R; Okan, Melih; Zhang, Hao; Khatami, Ehsan; Trivedi, Nandini; Paiva, Thereza; Rigol, Marcos; Zwierlein, Martin W
2016-09-16
Strong electron correlations lie at the origin of high-temperature superconductivity. Its essence is believed to be captured by the Fermi-Hubbard model of repulsively interacting fermions on a lattice. Here we report on the site-resolved observation of charge and spin correlations in the two-dimensional (2D) Fermi-Hubbard model realized with ultracold atoms. Antiferromagnetic spin correlations are maximal at half-filling and weaken monotonically upon doping. At large doping, nearest-neighbor correlations between singly charged sites are negative, revealing the formation of a correlation hole, the suppressed probability of finding two fermions near each other. As the doping is reduced, the correlations become positive, signaling strong bunching of doublons and holes, in agreement with numerical calculations. The dynamics of the doublon-hole correlations should play an important role for transport in the Fermi-Hubbard model.
Application of Gauss's law space-charge limited emission model in iterative particle tracking method
Altsybeyev, V. V.; Ponomarev, V. A.
2016-11-01
The particle tracking method with a so-called gun iteration for modeling the space charge is discussed in the following paper. We suggest to apply the emission model based on the Gauss's law for the calculation of the space charge limited current density distribution using considered method. Based on the presented emission model we have developed a numerical algorithm for this calculations. This approach allows us to perform accurate and low time consumpting numerical simulations for different vacuum sources with the curved emitting surfaces and also in the presence of additional physical effects such as bipolar flows and backscattered electrons. The results of the simulations of the cylindrical diode and diode with elliptical emitter with the use of axysimmetric coordinates are presented. The high efficiency and accuracy of the suggested approach are confirmed by the obtained results and comparisons with the analytical solutions.
A numerical model for charge transport and energy conversion of perovskite solar cells.
Zhou, Yecheng; Gray-Weale, Angus
2016-02-14
Based on the continuity equations and Poisson's equation, we developed a numerical model for perovskite solar cells. Due to different working mechanisms, the model for perovskite solar cells differs from that of silicon solar cells and Dye Sensitized Solar Cells. The output voltage and current are calculated differently, and in a manner suited in particular to perovskite organohalides. We report a test of our equations against experiment with good agreement. Using this numerical model, it was found that performances of solar cells increase with charge carrier's lifetimes, mobilities and diffusion lengths. The open circuit voltage (Voc) of a solar cell is dependent on light intensities, and charge carrier lifetimes. Diffusion length and light intensity determine the saturated current (Jsc). Additionally, three possible guidelines for the design and fabrication of perovskite solar cells are suggested by our calculations. Lastly, we argue that concentrator perovskite solar cells are promising.
Quasi-integrability in deformed sine-Gordon models and infinite towers of conserved charges
Blas, Harold
2016-01-01
We have studied the space-time symmetries of some soliton solutions of deformed sine-Gordon models in the context of the quasi-integrability concept. Considering a dual pair of anomalous Lax representations of the deformed model we compute analytically and numerically an infinite number of alternating conserved and asymptotically conserved charges through a modification of the usual techniques of integrable field theories. The charges associated to two-solitons with a definite parity under space-reflection symmetry, i.e. kink-kink (odd parity) and kink-antikink (even parity) scatterings with equal and opposite velocities, split into two infinite towers of conserved and asymptotically conserved charges. For two-solitons without definite parity under space-reflection symmetry (kink-kink and kink-antikink scatterings with unequal and opposite velocities) our numerical results show the existence of the asymptotically conserved charges only. However, we show that in the center-of-mass reference frame of the two so...
Kloet, Samantha K; Walczak, Agata P; Louisse, Jochem; van den Berg, Hans H J; Bouwmeester, Hans; Tromp, Peter; Fokkink, Remco G; Rietjens, Ivonne M C M
2015-10-01
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 choriocarcinoma grown on a transwell insert forming a cell layer that separates an apical from a basolateral compartment. PS-NPs were characterized with respect to size, surface charge, morphology and protein corona. Translocation of PS-NPs was not related to PS-NP charge. Two PS-NPs were translocated across the BeWo transwell model to a lower extent than amoxicillin, a model compound known to be translocated over the placental barrier to only a limited extent, whereas one PS-NP showed a slightly higher translocation. Studies on the effect of transporter inhibitors on the translocation of the PS-NPs indicated that their translocation was not mediated by known transporters and mainly dependent on passive diffusion. It is concluded that the BeWo b30 model can be used as an efficient method to get an initial qualitative impression about the capacity of NPs to translocate across the placental barrier and set priorities in further in vivo studies on translocation of NPs to the fetus.
Models for short term malaria prediction in Sri Lanka
Directory of Open Access Journals (Sweden)
Galappaththy Gawrie NL
2008-05-01
Full Text Available Abstract Background Malaria in Sri Lanka is unstable and fluctuates in intensity both spatially and temporally. Although the case counts are dwindling at present, given the past history of resurgence of outbreaks despite effective control measures, the control programmes have to stay prepared. The availability of long time series of monitored/diagnosed malaria cases allows for the study of forecasting models, with an aim to developing a forecasting system which could assist in the efficient allocation of resources for malaria control. Methods Exponentially weighted moving average models, autoregressive integrated moving average (ARIMA models with seasonal components, and seasonal multiplicative autoregressive integrated moving average (SARIMA models were compared on monthly time series of district malaria cases for their ability to predict the number of malaria cases one to four months ahead. The addition of covariates such as the number of malaria cases in neighbouring districts or rainfall were assessed for their ability to improve prediction of selected (seasonal ARIMA models. Results The best model for forecasting and the forecasting error varied strongly among the districts. The addition of rainfall as a covariate improved prediction of selected (seasonal ARIMA models modestly in some districts but worsened prediction in other districts. Improvement by adding rainfall was more frequent at larger forecasting horizons. Conclusion Heterogeneity of patterns of malaria in Sri Lanka requires regionally specific prediction models. Prediction error was large at a minimum of 22% (for one of the districts for one month ahead predictions. The modest improvement made in short term prediction by adding rainfall as a covariate to these prediction models may not be sufficient to merit investing in a forecasting system for which rainfall data are routinely processed.
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.
Validating predictions from climate envelope models
Watling, J.; Bucklin, D.; Speroterra, C.; Brandt, L.; Cabal, C.; Romañach, Stephanie S.; Mazzotti, Frank J.
2013-01-01
Climate envelope models are a potentially important conservation tool, but their ability to accurately forecast species’ distributional shifts using independent survey data has not been fully evaluated. We created climate envelope models for 12 species of North American breeding birds previously shown to have experienced poleward range shifts. For each species, we evaluated three different approaches to climate envelope modeling that differed in the way they treated climate-induced range expansion and contraction, using random forests and maximum entropy modeling algorithms. All models were calibrated using occurrence data from 1967–1971 (t1) and evaluated using occurrence data from 1998–2002 (t2). Model sensitivity (the ability to correctly classify species presences) was greater using the maximum entropy algorithm than the random forest algorithm. Although sensitivity did not differ significantly among approaches, for many species, sensitivity was maximized using a hybrid approach that assumed range expansion, but not contraction, in t2. Species for which the hybrid approach resulted in the greatest improvement in sensitivity have been reported from more land cover types than species for which there was little difference in sensitivity between hybrid and dynamic approaches, suggesting that habitat generalists may be buffered somewhat against climate-induced range contractions. Specificity (the ability to correctly classify species absences) was maximized using the random forest algorithm and was lowest using the hybrid approach. Overall, our results suggest cautious optimism for the use of climate envelope models to forecast range shifts, but also underscore the importance of considering non-climate drivers of species range limits. The use of alternative climate envelope models that make different assumptions about range expansion and contraction is a new and potentially useful way to help inform our understanding of climate change effects on species.
Institute of Scientific and Technical Information of China (English)
Cao Meng; Wang Fang; Liu Jing; Zhang Hai-Bo
2012-01-01
We present a novel numerical model and simulate preliminarily the charging process of a polymer subjected to electron irradiation of several 10 keV.The model includes the simultaneous processes of electron scattering and ambipolar transport and the influence of a self-consistent electric field on the scattering distribution of electrons.The dynamic spatial distribution of charges is obtained and validated by existing experimental data.Our simulations show that excess negative charges are concentrated near the edge of the electron range.However,the formed region of high charge density may extend to the surface and bottom of a kapton sample,due to the effects of the electric field on electron scattering and charge transport,respectively.Charge trapping is then demonstrated to significantly influence the charge motion.The charge distribution can be extended to the bottom as the trap density decreases.Charge accumulation is therefore balanced by the appearance and increase of leakage current.Accordingly,our model and numerical simulation provide a comprehensive insight into the charging dynamics of a polymer irradiated by electrons in the complex space environment.
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.
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.
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.
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...
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
Charged-lepton flavour physics
Indian Academy of Sciences (India)
Andreas Hoecker
2012-11-01
This write-up on a talk at the 2011 Lepton–Photon symposium in Mumbai, India, summarizes recent results in the charged-lepton flavour sector. Searches for charged-lepton flavour violation, lepton electric dipole moments and flavour-conserving CP violation are reviewed here. Recent progress in -lepton physics and in the Standard Model prediction of the muon anomalous magnetic moment is also discussed.
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.
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.
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.
Energy Technology Data Exchange (ETDEWEB)
Gomez San Roman, Tomas [Instituto de Investigacion Tecnologica, Universidad Pontificia Comillas, Madrid (Spain); Momber, Ilan, E-mail: ilan.momber@iit.upcomillas.es [Instituto de Investigacion Tecnologica, Universidad Pontificia Comillas, Madrid (Spain); Rivier Abbad, Michel; Sanchez Miralles, Alvaro [Instituto de Investigacion Tecnologica, Universidad Pontificia Comillas, Madrid (Spain)
2011-10-15
Electric vehicles (EVs) present efficiency and environmental advantages over conventional transportation. It is expected that in the next decade this technology will progressively penetrate the market. The integration of plug-in electric vehicles in electric power systems poses new challenges in terms of regulation and business models. This paper proposes a conceptual regulatory framework for charging EVs. Two new electricity market agents, the EV charging manager and the EV aggregator, in charge of developing charging infrastructure and providing charging services are introduced. According to that, several charging modes such as EV home charging, public charging on streets, and dedicated charging stations are formulated. Involved market agents and their commercial relationships are analysed in detail. The paper elaborates the opportunities to formulate more sophisticated business models for vehicle-to-grid applications under which the storage capability of EV batteries is used for providing peak power or frequency regulation to support the power system operation. Finally penetration phase dependent policy and regulatory recommendations are given concerning time-of-use pricing, smart meter deployment, stable and simple regulation for reselling energy on private property, roll-out of public charging infrastructure as well as reviewing of grid codes and operational system procedures for interactions between network operators and vehicle aggregators. - Highlights: > A conceptual regulatory framework for charging EVs is proposed. > 2 new agents, EV charging point manager, EV aggregator and their functions are introduced. > Depending on private or public access of charging points, contractual relations change. > A classification of charging scenarios alludes implications on regulatory topics. > EV penetration phase dependent policy and regulatory recommendations are given.
DEFF Research Database (Denmark)
Christensen, Nikolaj Kruse; Christensen, Steen; Ferre, Ty
constructed from geological and hydrological data. However, geophysical data are increasingly used to inform hydrogeologic models because they are collected at lower cost and much higher density than geological and hydrological data. Despite increased use of geophysics, it is still unclear whether...... the integration of geophysical data in the construction of a groundwater model increases the prediction performance. We suggest that modelers should perform a hydrogeophysical “test-bench” analysis of the likely value of geophysics data for improving groundwater model prediction performance before actually...... collecting geophysical data. At a minimum, an analysis should be conducted assuming settings that are favorable for the chosen geophysical method. If the analysis suggests that data collected by the geophysical method is unlikely to improve model prediction performance under these favorable settings...
Determination of Top Quark charge in CDF experiment
Energy Technology Data Exchange (ETDEWEB)
Bednar, Peter [Comenius Univ., Bratislava (Slovakia)
2007-01-01
This thesis deals with the problematic of top quark charge measurement in CDF experiment at Fermilab. The goal is to determine if the top quark observed on Tevatron experiments is the Standard Model particle with the predicted charge 2/3 or it is some exotic 4th generation quark with the charge of -4/3 as suggested by some alternative theories.
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.
Model Predictive Control of Sewer Networks
DEFF Research Database (Denmark)
Pedersen, Einar B.; Herbertsson, Hannes R.; Niemann, Henrik;
2016-01-01
The developments in solutions for management of urban drainage are of vital importance, as the amount of sewer water from urban areas continues to increase due to the increase of the world’s population and the change in the climate conditions. How a sewer network is structured, monitored...... and controlled have thus become essential factors for efficient performance of waste water treatment plants. This paper examines methods for simplified modelling and controlling a sewer network. A practical approach to the problem is used by analysing simplified design model, which is based on the Barcelona...
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.
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.
Charge quantization and the Standard Model from the CP2 and CP3 nonlinear σ-models
Hellerman, Simeon; Kehayias, John; Yanagida, Tsutomu T.
2014-04-01
We investigate charge quantization in the Standard Model (SM) through a CP2 nonlinear sigma model (NLSM), SU(3/(SU(2×U(1), and a CP3 model, SU(4/(SU(3×U(1). We also generalize to any CPk model. Charge quantization follows from the consistency and dynamics of the NLSM, without a monopole or Grand Unified Theory, as shown in our earlier work on the CP1 model (arXiv:1309.0692). We find that representations of the matter fields under the unbroken non-abelian subgroup dictate their charge quantization under the U(1 factor. In the CP2 model the unbroken group is identified with the weak and hypercharge groups of the SM, and the Nambu-Goldstone boson (NGB) has the quantum numbers of a SM Higgs. There is the intriguing possibility of a connection with the vanishing of the Higgs self-coupling at the Planck scale. Interestingly, with some minor assumptions (no vector-like matter and minimal representations) and starting with a single quark doublet, anomaly cancellation requires the matter structure of a generation in the SM. Similar analysis holds in the CP3 model, with the unbroken group identified with QCD and hypercharge, and the NGB having the up quark as a partner in a supersymmetric model. This can motivate solving the strong CP problem with a vanishing up quark mass.
New Approaches for Channel Prediction Based on Sinusoidal Modeling
Directory of Open Access Journals (Sweden)
Ekman Torbjörn
2007-01-01
Full Text Available Long-range channel prediction is considered to be one of the most important enabling technologies to future wireless communication systems. The prediction of Rayleigh fading channels is studied in the frame of sinusoidal modeling in this paper. A stochastic sinusoidal model to represent a Rayleigh fading channel is proposed. Three different predictors based on the statistical sinusoidal model are proposed. These methods outperform the standard linear predictor (LP in Monte Carlo simulations, but underperform with real measurement data, probably due to nonstationary model parameters. To mitigate these modeling errors, a joint moving average and sinusoidal (JMAS prediction model and the associated joint least-squares (LS predictor are proposed. It combines the sinusoidal model with an LP to handle unmodeled dynamics in the signal. The joint LS predictor outperforms all the other sinusoidal LMMSE predictors in suburban environments, but still performs slightly worse than the standard LP in urban environments.
Predicting Market Impact Costs Using Nonparametric Machine Learning Models.
Directory of Open Access Journals (Sweden)
Saerom Park
Full Text Available Market impact cost is the most significant portion of implicit transaction costs that can reduce the overall transaction cost, although it cannot be measured directly. In this paper, we employed the state-of-the-art nonparametric machine learning models: neural networks, Bayesian neural network, Gaussian process, and support vector regression, to predict market impact cost accurately and to provide the predictive model that is versatile in the number of variables. We collected a large amount of real single transaction data of US stock market from Bloomberg Terminal and generated three independent input variables. As a result, most nonparametric machine learning models outperformed a-state-of-the-art benchmark parametric model such as I-star model in four error measures. Although these models encounter certain difficulties in separating the permanent and temporary cost directly, nonparametric machine learning models can be good alternatives in reducing transaction costs by considerably improving in prediction performance.
Predicting Market Impact Costs Using Nonparametric Machine Learning Models.
Park, Saerom; Lee, Jaewook; Son, Youngdoo
2016-01-01
Market impact cost is the most significant portion of implicit transaction costs that can reduce the overall transaction cost, although it cannot be measured directly. In this paper, we employed the state-of-the-art nonparametric machine learning models: neural networks, Bayesian neural network, Gaussian process, and support vector regression, to predict market impact cost accurately and to provide the predictive model that is versatile in the number of variables. We collected a large amount of real single transaction data of US stock market from Bloomberg Terminal and generated three independent input variables. As a result, most nonparametric machine learning models outperformed a-state-of-the-art benchmark parametric model such as I-star model in four error measures. Although these models encounter certain difficulties in separating the permanent and temporary cost directly, nonparametric machine learning models can be good alternatives in reducing transaction costs by considerably improving in prediction performance.
An evaluation of mathematical models for predicting skin permeability.
Lian, Guoping; Chen, Longjian; Han, Lujia
2008-01-01
A number of mathematical models have been proposed for predicting skin permeability, mostly empirical and very few are deterministic. Early empirical models use simple lipophilicity parameters. The recent trend is to use more complicated molecular structure descriptors. There has been much debate on which models best predict skin permeability. This article evaluates various mathematical models using a comprehensive experimental dataset of skin permeability for 124 chemical compounds compiled from various sources. Of the seven models compared, the deterministic model of Mitragotri gives the best prediction. The simple quantitative structure permeability relationships (QSPR) model of Potts and Guy gives the second best prediction. The two models have many features in common. Both assume the lipid matrix as the pathway of transdermal permeation. Both use octanol-water partition coefficient and molecular size. Even the mathematical formulae are similar. All other empirical QSPR models that use more complicated molecular structure descriptors fail to provide satisfactory prediction. The molecular structure descriptors in the more complicated QSPR models are empirically related to skin permeation. The mechanism on how these descriptors affect transdermal permeation is not clear. Mathematically it is an ill-defined approach to use many colinearly related parameters rather than fewer independent parameters in multi-linear regression.
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.
Quantum phase diagram of the half filled Hubbard model with bond-charge interaction
Energy Technology Data Exchange (ETDEWEB)
Dobry, A.O., E-mail: dobry@ifir-conicet.gov.a [Facultad de Ciencias Exactas Ingenieria y Agrimensura, Universidad Nacional de Rosario and Instituto de Fisica Rosario, Bv. 27 de Febrero 210 bis, 2000 Rosario (Argentina); Aligia, A.A. [Centro Atomico Bariloche and Instituto Balseiro, Comision Nacional de Energia Atomica, 8400 Bariloche (Argentina)
2011-02-21
Using quantum field theory and bosonization, we determine the quantum phase diagram of the one-dimensional Hubbard model with bond-charge interaction X in addition to the usual Coulomb repulsion U at half-filling, for small values of the interactions. We show that it is essential to take into account formally irrelevant terms of order X. They generate relevant terms proportional to X{sup 2} in the flow of the renormalization group (RG). These terms are calculated using operator product expansions. The model shows three phases separated by a charge transition at U=U{sub c} and a spin transition at U=U{sub s}>U{sub c}. For UU{sub s}, the system is in the spin-density wave phase as in the usual Hubbard model. For intermediate values U{sub c}model with X=0. We obtain that the charge transition remains at U{sub c}=0 for X{ne}0. Solving the RG equations for the spin sector, we provide an analytical expression for U{sub s}(X). The results, with only one adjustable parameter, are in excellent agreement with numerical ones for X
Bayesian Age-Period-Cohort Modeling and Prediction - BAMP
Directory of Open Access Journals (Sweden)
Volker J. Schmid
2007-10-01
Full Text Available The software package BAMP provides a method of analyzing incidence or mortality data on the Lexis diagram, using a Bayesian version of an age-period-cohort model. A hierarchical model is assumed with a binomial model in the first-stage. As smoothing priors for the age, period and cohort parameters random walks of first and second order, with and without an additional unstructured component are available. Unstructured heterogeneity can also be included in the model. In order to evaluate the model fit, posterior deviance, DIC and predictive deviances are computed. By projecting the random walk prior into the future, future death rates can be predicted.
Validation of a tuber blight (Phytophthora infestans) prediction model
Potato tuber blight caused by Phytophthora infestans accounts for significant losses in storage. There is limited published quantitative data on predicting tuber blight. We validated a tuber blight prediction model developed in New York with cultivars Allegany, NY 101, and Katahdin using independent...
Prediction of bypass transition with differential Reynolds stress models
Westin, K.J.A.; Henkes, R.A.W.M.
1998-01-01
Boundary layer transition induced by high levels of free stream turbulence (FSl), so called bypass transition, can not be predicted with conventional stability calculations (e.g. the en-method). The use of turbulence models for transition prediction has shown some success for this type of flows, and
Improving Environmental Model Calibration and Prediction
2011-01-18
1. model comparison and selection, 2. identification of the best water management strategies that reflect the likelihood of outcomes, 3. data...comparison and selection, identification of the best water management strategies that reflect the likelihood of outcomes, data collection aimed at
Space Weather: Measurements, Models and Predictions
2014-03-21
Freezes with valid Optional Storm added in fresh AF- GEOSpace session. Results in "invalid storm peak" message. • Raytrace App: Save Model message...plot windows created by LET-APP, RAYTRACE -APP, and PPS causes crash. • LET-APP: Use of "Trapped Protons: CRRESPRO Quiet" or "Active" results in no
Predicting Magazine Audiences with a Loglinear Model.
1987-07-01
important use of e.d. estimates is in media selection ( Aaker 1975; Lee 1962, 1963; Little and Lodish 1969). All advertising campaigns have a budget. It...N.Z. Listener 6061 39.0 4 0 22 References Aaker , D.A. (1975), "ADMOD:An Advertising Decision Model," Journal of Marketing Research, February, 37-45
Weng, Liping; Van Riemsdijk, Willem H; Koopal, Luuk K; Hiemstra, Tjisse
2006-10-15
The LCD model (Ligand and Charge Distribution) has recently been proposed to describe the adsorption of humic substances to oxides, in which the CD-MUSIC model and the NICA model for ion binding to respectively oxides and humic substances are integrated. In this paper, the LCD model is improved by applying the ADAPT model (ADsorption and AdaPTation) to calculate the equilibrium distribution of the humic substances based on the change of the average chemical state of the particles. The improved LCD model is applied to calculate the adsorption of fulvic acid (Strichen) to goethite, in which it is assumed that the carboxylic type of groups of fulvic acid can form innersphere complexes with the surface sites. The charge of the carboxylic groups in the innersphere complexes is distributed between the 0- and d-plane, whereas the charge of the other carboxylic and phenolic groups is located in the d-plane. The average distribution of the carboxylic and phenolic groups among their various chemical states (carboxylic groups: innersphere complex, protonated and deprotonated; phenolic groups: protonated and deprotonated) depends on pH, ionic strength and loading, and are the outcome of the model. The calculation shows that the LCD model can describe sufficiently the effects of pH, ionic strength and loading on the adsorption of fulvic acid, using one adjustable parameter (logK (S,1)). The model calculations indicate that the chemical complexation between fulvic acid and goethite is the main driving force of the adsorption, while the electrostatic repulsion between the particles and the surface is the major limiting factor for further adsorption.
Magnetically charged regular black hole in a model of nonlinear electrodynamics
Ma, Meng-Sen
2015-01-01
We obtain a magnetically charged regular black hole in general relativity. The source to the Einstein field equations is nonlinear electrodynamic field in a physically reasonable model of nonlinear electrodynamics (NED). "Physically" here means the NED model is constructed on the basis of three conditions: the Maxwell asymptotic in the weak electromagnetic field limit; the presence of vacuum birefringence phenomenon; and satisfying the weak energy condition (WEC). In addition, we analyze the thermodynamic properties of the regular black hole in two ways. According to the usual black hole thermodynamics, we calculate the heat capacity at constant charge, from which we know the smaller black hole is more stable. We also employ the horizon thermodynamics to discuss the thermodynamic quantities, especially the heat capacity at constant pressure.
Gutiérrez, R; Caetano, R A; Woiczikowski, B P; Kubar, T; Elstner, M; Cuniberti, G
2009-05-22
We present a hybrid method based on a combination of classical molecular dynamics simulations, quantum-chemical calculations, and a model Hamiltonian approach to describe charge transport through biomolecular wires with variable lengths in presence of a solvent. The core of our approach consists in a mapping of the biomolecular electronic structure, as obtained from density-functional based tight-binding calculations of molecular structures along molecular dynamics trajectories, onto a low-dimensional model Hamiltonian including the coupling to a dissipative bosonic environment. The latter encodes fluctuation effects arising from the solvent and from the molecular conformational dynamics. We apply this approach to the case of pG-pC and pA-pT DNA oligomers as paradigmatic cases and show that the DNA conformational fluctuations are essential in determining and supporting charge transport.
Fuzzy chance constrained linear programming model for scrap charge optimization in steel production
DEFF Research Database (Denmark)
Rong, Aiying; Lahdelma, Risto
2008-01-01
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...... 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...... for solution. Simulation results based on realistic data show that the failure risk can be managed by proper combination of aspiration levels and confidence factors for defining fuzzy numbers. There is a tradeoff between failure risk and material cost. The presented approach applies also for other scrap...
Form Factors and charge radii of heavy flavored mesons in a potential model
Das, T; Bordoloi, N S
2016-01-01
We report the results for charge radii of heavy flavored mesons ($D^+, D^0, D^+_s, B^+, B^0, B^0_s$) in a QCD model with the potential $V(r)=-4\\frac{\\alpha_s}{3r}+br+c$ by incorporating two scales $r^{short}$ and $r^{long}$ as an integration limit so that the perturbative procedure can be improved in a potential model. We also obtain the analytical expressions for Form Factors in terms of momentum transfer ($Q^2$). The obtained results are compared with our earlier works and with the other theoretical models.
Implications of Unitarity and Charge Breaking Minima in Left-Right Symmetric Model
Mondal, Tanmoy; Konar, Partha
2015-01-01
We examine the usefulness of the unitarity conditions in Left-Right symmetric model which can translate into giving a stronger constraint on the model parameters together with the criteria derived from vacuum stability and perturbativity. In this light, we demonstrate the bounds on the masses of the physical scalars present in the model and find the scenario where multiple scalar modes are in the reach of Large Hadron Collider. We also analyse the additional conditions that can come from charge breaking minima in this context.
A Boltzmann-weighted hopping model of charge transport in organic semicrystalline films
Kwiatkowski, Joe J.
2011-01-01
We present a model of charge transport in polycrystalline electronic films, which considers details of the microscopic scale while simultaneously allowing realistically sized films to be simulated. We discuss the approximations and assumptions made by the model, and rationalize its application to thin films of directionally crystallized poly(3-hexylthiophene). In conjunction with experimental data, we use the model to characterize the effects of defects in these films. Our findings support the hypothesis that it is the directional crystallization of these films, rather than their defects, which causes anisotropic mobilities. © 2011 American Institute of Physics.
Scanpath Based N-Gram Models for Predicting Reading Behavior
DEFF Research Database (Denmark)
Mishra, Abhijit; Bhattacharyya, Pushpak; Carl, Michael
2013-01-01
Predicting reading behavior is a difficult task. Reading behavior depends on various linguistic factors (e.g. sentence length, structural complexity etc.) and other factors (e.g individual's reading style, age etc.). Ideally, a reading model should be similar to a language model where the model i...
Model Predictive Control of Wind Turbines using Uncertain LIDAR Measurements
DEFF Research Database (Denmark)
Mirzaei, Mahmood; Soltani, Mohsen; Poulsen, Niels Kjølstad;
2013-01-01
The problem of Model predictive control (MPC) of wind turbines using uncertain LIDAR (LIght Detection And Ranging) measurements is considered. A nonlinear dynamical model of the wind turbine is obtained. We linearize the obtained nonlinear model for different operating points, which are determine...
Hybrid Corporate Performance Prediction Model Considering Technical Capability
Directory of Open Access Journals (Sweden)
Joonhyuck Lee
2016-07-01
Full Text Available Many studies have tried to predict corporate performance and stock prices to enhance investment profitability using qualitative approaches such as the Delphi method. However, developments in data processing technology and machine-learning algorithms have resulted in efforts to develop quantitative prediction models in various managerial subject areas. We propose a quantitative corporate performance prediction model that applies the support vector regression (SVR algorithm to solve the problem of the overfitting of training data and can be applied to regression problems. The proposed model optimizes the SVR training parameters based on the training data, using the genetic algorithm to achieve sustainable predictability in changeable markets and managerial environments. Technology-intensive companies represent an increasing share of the total economy. The performance and stock prices of these companies are affected by their financial standing and their technological capabilities. Therefore, we apply both financial indicators and technical indicators to establish the proposed prediction model. Here, we use time series data, including financial, patent, and corporate performance information of 44 electronic and IT companies. Then, we predict the performance of these companies as an empirical verification of the prediction performance of the proposed model.
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.
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...
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.
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.
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.
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.
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.
Mesoscale Wind Predictions for Wave Model Evaluation
2016-06-07
N0001400WX20041(B) http://www.nrlmry.navy.mil LONG TERM GOALS The long-term goal is to demonstrate the significance and importance of high...ocean waves by an appropriate wave model. OBJECTIVES The main objectives of this project are to: 1. Build the infrastructure to generate the...temperature for all COAMPS grids at the resolution of each of these grids. These analyses are important for the proper 2 specification of the lower
A Predictive Multiscale Model of Wear
2011-03-09
theoretical tensile strength, and by fitting the calculated data to universal binding energy relationships ( UBERs ), which permit the extrapolation of the...calculated results to arbitrary length scales. The results demonstrate the ability of an UBER that accounts for fracture surface relaxation to yield a...materials subjected to shear up to the point at which slip occurs. The model we devised is analogous to the tensile-load UBER and leads to a size
Energy Technology Data Exchange (ETDEWEB)
Yigit, Cemil; Dzubiella, Joachim, E-mail: joachim.dzubiella@helmholtz-berlin.de [Soft Matter and Functional Materials, Helmholtz-Zentrum Berlin, 14109 Berlin (Germany); Helmholtz Virtual Institute “Multifunctional Biomaterials for Medicine,” 14513 Teltow (Germany); Institut für Physik, Humboldt-Universität zu Berlin, 12489 Berlin (Germany); Heyda, Jan [Department of Physical Chemistry, University of Chemistry and Technology, Prague, 166 28 Praha 6 (Czech Republic)
2015-08-14
We introduce a set of charged patchy particle models (CPPMs) in order to systematically study the influence of electrostatic charge patchiness and multipolarity on macromolecular interactions by means of implicit-solvent, explicit-ion Langevin dynamics simulations employing the Gromacs software. We consider well-defined zero-, one-, and two-patched spherical globules each of the same net charge and (nanometer) size which are composed of discrete atoms. The studied mono- and multipole moments of the CPPMs are comparable to those of globular proteins with similar size. We first characterize ion distributions and electrostatic potentials around a single CPPM. Although angle-resolved radial distribution functions reveal the expected local accumulation and depletion of counter- and co-ions around the patches, respectively, the orientation-averaged electrostatic potential shows only a small variation among the various CPPMs due to space charge cancellations. Furthermore, we study the orientation-averaged potential of mean force (PMF), the number of accumulated ions on the patches, as well as the CPPM orientations along the center-to-center distance of a pair of CPPMs. We compare the PMFs to the classical Derjaguin-Verwey-Landau-Overbeek theory and previously introduced orientation-averaged Debye-Hückel pair potentials including dipolar interactions. Our simulations confirm the adequacy of the theories in their respective regimes of validity, while low salt concentrations and large multipolar interactions remain a challenge for tractable theoretical descriptions.
Modeling of direct beam extraction for a high-charge-state fusion driver
Anderson, O. A.; Grant Logan, B.
A newly proposed type of multicharged ion source offers the possibility of an economically advantageous high-charge-state fusion driver. Multiphoton absorption in an intense uniform laser focus can give multiple charge states of high purity, simplifying or eliminating the need for charge-state separation downstream. Very large currents (hundreds of amperes) can be extracted from this type of source. Several arrangements are possible. For example, the laser plasma could be tailored for storage in a magnetic bucket, with beam extracted from the bucket. A different approach, described in this report, is direct beam extraction from the expanding laser plasma. We discuss extraction and focusing for the particular case of a 4.1 MV beam of Xe 16+ ions. The maximum duration of the beam pulse is limited by the total charge in the plasma, while the practical pulse length is determined by the range of plasma radii over which good beam optics can be achieved. The extraction electrode contains a solenoid for beam focusing. Our design studies were carried out first with an envelope code and then with a self-consistent particle code. Results from our initial model showed that hundreds of amperes could be extracted, but that most of this current missed the solenoid entrance or was intercepted by the wall and that only a few amperes were able to pass through. We conclude with an improved design which increases the surviving beam to more than 70 A.
Modeling Seizure Self-Prediction: An E-Diary Study
Haut, Sheryl R.; Hall, Charles B.; Borkowski, Thomas; Tennen, Howard; Lipton, Richard B.
2013-01-01
Purpose A subset of patients with epilepsy successfully self-predicted seizures in a paper diary study. We conducted an e-diary study to ensure that prediction precedes seizures, and to characterize the prodromal features and time windows that underlie self-prediction. Methods Subjects 18 or older with LRE and ≥3 seizures/month maintained an e-diary, reporting AM/PM data daily, including mood, premonitory symptoms, and all seizures. Self-prediction was rated by, “How likely are you to experience a seizure [time frame]”? Five choices ranged from almost certain (>95% chance) to very unlikely. Relative odds of seizure (OR) within time frames was examined using Poisson models with log normal random effects to adjust for multiple observations. Key Findings Nineteen subjects reported 244 eligible seizures. OR for prediction choices within 6hrs was as high as 9.31 (1.92,45.23) for “almost certain”. Prediction was most robust within 6hrs of diary entry, and remained significant up to 12hrs. For 9 best predictors, average sensitivity was 50%. Older age contributed to successful self-prediction, and self-prediction appeared to be driven by mood and premonitory symptoms. In multivariate modeling of seizure occurrence, self-prediction (2.84; 1.68,4.81), favorable change in mood (0.82; 0.67,0.99) and number of premonitory symptoms (1,11; 1.00,1.24) were significant. Significance Some persons with epilepsy can self-predict seizures. In these individuals, the odds of a seizure following a positive prediction are high. Predictions were robust, not attributable to recall bias, and were related to self awareness of mood and premonitory features. The 6-hour prediction window is suitable for the development of pre-emptive therapy. PMID:24111898
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
Wu, H.; Furusawa, Y.; George, K.; Kawata, T.; Cucinotta, F.
Biophysical models addressing the formation of radiation-induced chromosome aberrations are usually based on the assumption that chromosome aberrations are formed by DNA double strand break (DSB) misrejoining, via either the homologous or the non-homologous repair pathway. However, comparing chromosome aberration data with model predictions is not always straightforward. In this paper we discuss some of the aspects that must be considered to make these comparisons meaningful. Firstly, biophysical models are usually applied to DSB rejoining and misrejoining in the G0/G1 phase of the cell cycle, while most chromosome aberration data reported in the literature are analyzed in metaphase. Since cells must progress through the cell cycle check points in order to reach mitosis, model predictions that differ from the metaphase chromosome analysis may actually agree with the aberration data in chromosomes collected in interphase. Secondly, high- LET radiation generally produces more complex aberrations involving exchanges between three or more DSB. While some models have successfully provided quantitative predictions of high-LET radiation induced complex aberrations in human lymphocytes, applying such models to other cell types requires special considerations due to the lack of geometric symmetry of the nucleus. Chromosome aberration data for non-spherical human fibroblast cells bombarded from various directions by high-LET charged particles will be presented, and their implication on physical modeling will be discussed.
Biquaternionic Model of Electro-Gravimagnetic Field, Charges and Currents. Law of Inertia
Alexeyeva, Lyudmila
2016-01-01
One the base of Maxwell and Dirac equations the one biquaternionic model of electro-gravimagnetic (EGM) fields is considered. The closed system of biquaternionic wave equations is constructed for determination of free system of electric and gravimagnetic charges and currents and generated by them EGM-field. By using generalized functions theory the fundamental and regular solutions of this system are determined and some of them are considered (spinors, plane waves, shock EGMwaves and others). The properties of these solutions are investigated.
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.
Model predictive control of P-time event graphs
Hamri, H.; Kara, R.; Amari, S.
2016-12-01
This paper deals with model predictive control of discrete event systems modelled by P-time event graphs. First, the model is obtained by using the dater evolution model written in the standard algebra. Then, for the control law, we used the finite-horizon model predictive control. For the closed-loop control, we used the infinite-horizon model predictive control (IH-MPC). The latter is an approach that calculates static feedback gains which allows the stability of the closed-loop system while respecting the constraints on the control vector. The problem of IH-MPC is formulated as a linear convex programming subject to a linear matrix inequality problem. Finally, the proposed methodology is applied to a transportation system.