Model Predictive Control-Based Fast Charging for Vehicular Batteries
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
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.
Charge transport model to predict intrinsic reliability for dielectric materials
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
Hu Yun-tao
2009-09-01
Full Text Available Abstract Background In recent years, artificial neural network is advocated in modeling complex multivariable relationships due to its ability of fault tolerance; while decision tree of data mining technique was recommended because of its richness of classification arithmetic rules and appeal of visibility. The aim of our research was to compare the performance of ANN and decision tree models in predicting hospital charges on gastric cancer patients. Methods Data about hospital charges on 1008 gastric cancer patients and related demographic information were collected from the First Affiliated Hospital of Anhui Medical University from 2005 to 2007 and preprocessed firstly to select pertinent input variables. Then artificial neural network (ANN and decision tree models, using same hospital charge output variable and same input variables, were applied to compare the predictive abilities in terms of mean absolute errors and linear correlation coefficients for the training and test datasets. The transfer function in ANN model was sigmoid with 1 hidden layer and three hidden nodes. Results After preprocess of the data, 12 variables were selected and used as input variables in two types of models. For both the training dataset and the test dataset, mean absolute errors of ANN model were lower than those of decision tree model (1819.197 vs. 2782.423, 1162.279 vs. 3424.608 and linear correlation coefficients of the former model were higher than those of the latter (0.955 vs. 0.866, 0.987 vs. 0.806. The predictive ability and adaptive capacity of ANN model were better than those of decision tree model. Conclusion ANN model performed better in predicting hospital charges of gastric cancer patients of China than did decision tree model.
Electric vehicle charge planning using Economic Model Predictive Control
Halvgaard, Rasmus; Poulsen, Niels K.; Madsen, Henrik;
2012-01-01
Economic Model Predictive Control (MPC) is very well suited for controlling smart energy systems since electricity price and demand forecasts are easily integrated in the controller. Electric vehicles (EVs) are expected to play a large role in the future Smart Grid. They are expected to provide...... grid services, both for peak reduction and for ancillary services, by absorbing short term variations in the electricity production. In this paper the Economic MPC minimizes the cost of electricity consumption for a single EV. Simulations show savings of 50–60% of the electricity costs compared to...... 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....
Quark-Model Predictions for Axial Charges of Nucleon and N* Resonances
Wagenbrunn R.F.
2010-04-01
Full Text Available We have investigated the axial charges of the nucleon and N* resonances in a relativistic framework. Besides the axial charge of the nucleon, ﬁrst predictions are reported for the axial charges of all well-established N* resonances below ∼1.9 GeV as produced by the relativistic constituent quark models relying on Goldstoneboson-exchange and one-gluon-exchange hyperﬁne interactions. The results for the axial charge of the nucleon are found close to experiment but with somewhat smaller values, similar to modern ﬁndings from quantum chromodynamics on the lattice. The predictions of the axial charges of the negative-parity N* (1535 and N*(1650 resonances also agree with what has most recently become available from lattice calculations. We discuss the roles of the axial charges of the N* resonances for the phenomenon of chiral-symmetry restoration possibly occurring in the higher hadron spectra.
Prediction Model of Battery State of Charge and Control Parameter Optimization for Electric Vehicle
Bambang Wahono; Kristian Ismail; Harutoshi Ogai
2015-01-01
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 t...
Prediction Model of Battery State of Charge and Control Parameter Optimization for Electric Vehicle
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.
Kim, Myung-Hee Y.; Cucinotta, Francis A.; Zeitlin, Cary; Hassler, Donald M.; Ehresmann, Bent; Rafkin, Scot C. R.; Wimmer-Schweingruber, Robert F.; Boettcher, Stephan; Boehm, Eckart; Guo, Jingnan; Koehler, Jan; Martin, Cesar; Reitz, Guenther; Posner, Arik
2014-01-01
Detailed measurements of the energetic particle radiation environment on the surface of Mars have been made by the Radiation Assessment Detector (RAD) on the Curiosity rover since August 2012. RAD is a particle detector that measures the energy spectrum of charged particles (10 to approx. 200 MeV/u) and high energy neutrons (approx 8 to 200 MeV). The data obtained on the surface of Mars for 300 sols are compared to the simulation results using the Badhwar-O'Neill galactic cosmic ray (GCR) environment model and the high-charge and energy transport (HZETRN) code. For the nuclear interactions of primary GCR through Mars atmosphere and Curiosity rover, the quantum multiple scattering theory of nuclear fragmentation (QMSFRG) is used. For describing the daily column depth of atmosphere, daily atmospheric pressure measurements at Gale Crater by the MSL Rover Environmental Monitoring Station (REMS) are implemented into transport calculations. Particle flux at RAD after traversing varying depths of atmosphere depends on the slant angles, and the model accounts for shielding of the RAD "E" dosimetry detector by the rest of the instrument. Detailed comparisons between model predictions and spectral data of various particle types provide the validation of radiation transport models, and suggest that future radiation environments on Mars can be predicted accurately. These contributions lend support to the understanding of radiation health risks to astronauts for the planning of various mission scenarios
A PREDICTING MODEL OF THE LIMITING FLUX FOR THE CHARGED SOLUTE IN ULTRAFILTRATION PROCESS
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.
We present a conduction model aimed at describing bipolar transport and space charge phenomena in low density polyethylene under dc stress. In the first part we recall the basic requirements for the description of charge transport and charge storage in disordered media with emphasis on the case of polyethylene. A quick review of available conduction models is presented and our approach is compared with these models. Then, the bases of the model are described and related assumptions are discussed. Finally, results on external current, trapped and free space charge distributions, field distribution and recombination rate are presented and discussed, considering a constant dc voltage, a step-increase of the voltage, and a polarization-depolarization protocol for the applied voltage. It is shown that the model is able to describe the general features reported for external current, electroluminescence and charge distribution in polyethylene
Highlights: ► Max torque and power values were obtained at 3.5 bar Pch, 1273 K Hst and 1.4:1 r. ► According to ANOVA, the most influential parameter on power was Hst with 48.75%. ► According to ANOVA, the most influential parameter on torque was Hst with 41.78%. ► ANN (R2 = 99.8% for T, P) was superior to regression method (R2 = 92% for T, 81% for P). ► LM was the best learning algorithm in predicting both power and torque. - Abstract: In this study, an artificial neural network (ANN) model was developed to predict the torque and power of a beta-type Stirling engine using helium as the working fluid. The best results were obtained by 5-11-7-1 and 5-13-7-1 network architectures, with double hidden layers for the torque and power respectively. For these network architectures, the Levenberg–Marquardt (LM) learning algorithm was used. Engine performance values predicted with the developed ANN model were compared with the actual performance values measured experimentally, and substantially coinciding results were observed. After ANN training, correlation coefficients (R2) of both engine performance values for testing and training data were very close to 1. Similarly, root-mean-square error (RMSE) and mean error percentage (MEP) values for the testing and training data were less than 0.02% and 3.5% respectively. These results showed that the ANN is an acceptable model for prediction of the torque and power of the beta-type Stirling engine
Pierce, Flint; Grillet, Anne Mary; Grest, Gary Stephen; Lechman, Jeremy B.; Plimpton, Steven James; in' t Veld, Pieter J. (BASF Corporation Ludwigshafen, Germany); Schunk, Peter Randall; Heine, D. R. (Corning, Inc. Corning, NY); Stoltz, C. (Procter and Gamble Co. West Chester, OH); Weiss, Horst (BASF Corporation Ludwigshafen, Germany); Jendrejack, R. (3M Corporation St. Paul, MN); Petersen, Matthew K.
2010-06-01
In this presentation we examine the accuracy and performance of a suite of discrete-element-modeling approaches to predicting equilibrium and dynamic rheological properties of polystyrene suspensions. What distinguishes each approach presented is the methodology of handling the solvent hydrodynamics. Specifically, we compare stochastic rotation dynamics (SRD), fast lubrication dynamics (FLD) and dissipative particle dynamics (DPD). Method-to-method comparisons are made as well as comparisons with experimental data. Quantities examined are equilibrium structure properties (e.g. pair-distribution function), equilibrium dynamic properties (e.g. short- and long-time diffusivities), and dynamic response (e.g. steady shear viscosity). In all approaches we deploy the DLVO potential for colloid-colloid interactions. Comparisons are made over a range of volume fractions and salt concentrations. Our results reveal the utility of such methods for long-time diffusivity prediction can be dubious in certain ranges of volume fraction, and other discoveries regarding the best formulation to use in predicting rheological response.
Modelling airport congestion charges
Janić, Milan
2012-01-01
This article deals with modelling congestion charges at an airport. In this context, congestion charging represents internalizing the cost of marginal delays that a flight imposes on other flights due to congestion. The modelling includes estimating congestion and flight delays, the cost of these delays and the efficiency of particular flights following the introduction ofa congestion charge. The models are applied to an airport / New York LaGuardia / to illustrate their ability to handle mor...
Michor, Edward L; Berg, John C
2012-11-13
This paper presents an extension to current theory regarding charging behavior in apolar, micellar systems. Electrical conductivity in such systems accompanying the formation of neutral reverse micelles is commonly explained by the possibility of intermicellar collisions resulting in a pair of oppositely charged micelles. The sequestration of the resulting charges within the micelles prevents their immediate recombination. The current theory underlying the charging process has thus far been applied in only approximate form, and is only used to validate experimental trends and to abstract values for the fraction of charged micelles. The extended theory proposed here uses knowledge of the solvent and surfactant characteristics, together with water content, to predict solution conductivity in absolute terms. It is verified in experiments with the solvent Isopar-L and surfactants Aerosol OT, OLOA 11000, and Span 80, in which significant differences from the approximate theory are observed. PMID:23098157
Predicting p Ka values from EEM atomic charges.
Vařeková, Radka Svobodová; Geidl, Stanislav; Ionescu, Crina-Maria; Skřehota, Ondřej; Bouchal, Tomáš; Sehnal, David; Abagyan, Ruben; Koča, Jaroslav
2013-01-01
: The acid dissociation constant p Ka is a very important molecular property, and there is a strong interest in the development of reliable and fast methods for p Ka prediction. We have evaluated the p Ka prediction capabilities of QSPR models based on empirical atomic charges calculated by the Electronegativity Equalization Method (EEM). Specifically, we collected 18 EEM parameter sets created for 8 different quantum mechanical (QM) charge calculation schemes. Afterwards, we prepared a training set of 74 substituted phenols. Additionally, for each molecule we generated its dissociated form by removing the phenolic hydrogen. For all the molecules in the training set, we then calculated EEM charges using the 18 parameter sets, and the QM charges using the 8 above mentioned charge calculation schemes. For each type of QM and EEM charges, we created one QSPR model employing charges from the non-dissociated molecules (three descriptor QSPR models), and one QSPR model based on charges from both dissociated and non-dissociated molecules (QSPR models with five descriptors). Afterwards, we calculated the quality criteria and evaluated all the QSPR models obtained. We found that QSPR models employing the EEM charges proved as a good approach for the prediction of p Ka (63% of these models had R2 > 0.9, while the best had R2 = 0.924). As expected, QM QSPR models provided more accurate p Ka predictions than the EEM QSPR models but the differences were not significant. Furthermore, a big advantage of the EEM QSPR models is that their descriptors (i.e., EEM atomic charges) can be calculated markedly faster than the QM charge descriptors. Moreover, we found that the EEM QSPR models are not so strongly influenced by the selection of the charge calculation approach as the QM QSPR models. The robustness of the EEM QSPR models was subsequently confirmed by cross-validation. The applicability of EEM QSPR models for other chemical classes was illustrated by a case study focused on
Electrostatic charge bounds for ball lightning models
Several current theories concerning the nature of ball lightning predict a substantial electrostatic charge in order to account for its observed motion and shape (Turner 1998 Phys. Rep. 293 1; Abrahamson and Dinniss 2000 Nature 403 519). Using charged soap bubbles as a physical model for ball lightning, we show that the magnitude of charge predicted by some of these theories is too high to allow for the types of motion commonly observed in natural ball lightning, which includes horizontal motion above the ground and movement near grounded conductors. Experiments show that at charge levels of only 10-15 nC, 3-cm-diameter soap bubbles tend to be attracted by induced charges to the nearest grounded conductor and rupture. We conclude with a scaling rule that can be used to extrapolate these results to larger objects and surroundings
Arteaga-Velázquez, J. C.; Apel, W. D.; Bekk, K.; Bertaina, M.; Blümer, J.; Bozdog, H.; Brancus, I. M.; Cantoni, E.; Chiavassa, A.; Cossavella, F.; Daumiller, K.; de Souza, V.; Di Pierro, F.; Doll, P.; Engel, R.; Engler, J.; Fuchs, B.; Fuhrmann, D.; Gherghel-Lascu, A.; Gils, H. J.; Glasstetter, R.; Grupen, C.; Haungs, A.; Heck, D.; Hörandel, J. R.; Huber, D.; Huege, T.; Kampert, K.-H.; Kang, D.; Klages, H. O.; Link, K.; Łuczak, P.; Mathes, H. J.; Mayer, H. J.; Milke, J.; Mitrica, B.; Morello, C.; Oehlschläger, J.; Ostapchenko, S.; Palmieri, N.; Petcu, M.; Pierog, T.; Rebel, H.; Roth, M.; Schieler, H.; Schoo, S.; Schröder, F. G.; Sima, O.; Toma, G.; Trinchero, G. C.; Ulrich, H.; Weindl, A.; Wochele, J.; Zabierowski, J.
2015-08-01
KASCADE-Grande was an air-shower experiment designed to study cosmic rays between 1016 and 1018 eV. The instrument was located at the site of the Karlsruhe Institute of Technology, Germany at an altitude of 110 m a.s.l. and covered an area of 0.5 km2. KASCADE-Grande consisted of several detector systems dedicated to measure different components of the EAS generated by the primary cosmic rays, i.e., the muon and the electron contents of the air-shower. With such a number of EAS observables and the precision of the measurements, the KASCADE-Grande data can be used to not only study in detail the properties of cosmic rays but also to test the predictions of hadronic-interaction models. In this work, in particular, the attenuation lengths of the muon number and the charged number of particles of EAS in the atmosphere were extracted from the KASCADE-Grande data and the results were compared with the predictions of the new EPOS-LHC hadronic-interaction model.
Arteaga-Velázquez J.C.
2015-01-01
Full Text Available KASCADE-Grande was an air-shower experiment designed to study cosmic rays between 1016 and 1018 eV. The instrument was located at the site of the Karlsruhe Institute of Technology, Germany at an altitude of 110 m a.s.l. and covered an area of 0.5 km2. KASCADE-Grande consisted of several detector systems dedicated to measure different components of the EAS generated by the primary cosmic rays, i.e., the muon and the electron contents of the air-shower. With such a number of EAS observables and the precision of the measurements, the KASCADE-Grande data can be used to not only study in detail the properties of cosmic rays but also to test the predictions of hadronic-interaction models. In this work, in particular, the attenuation lengths of the muon number and the charged number of particles of EAS in the atmosphere were extracted from the KASCADE-Grande data and the results were compared with the predictions of the new EPOS-LHC hadronic-interaction model.
Charge Prediction of Lipid Fragments in Mass Spectrometry
Schrom, Brian T.; Kangas, Lars J.; Ginovska, Bojana; Metz, Thomas O.; Miller, John H.
2011-12-18
An artificial neural network is developed for predicting which fragment is charged and which fragment is neutral for lipid fragment pairs produced from a liquid chromatography tandem mass spectrometry simulation process. This charge predictor is integrated into software developed at PNNL for in silico spectra generation and identification of metabolites known as Met ISIS. To test the effect of including charge prediction in Met ISIS, 46 lipids are used which show a reduction in false positive identifications when the charge predictor is utilized.
Optimal predictive model selection
Barbieri, Maria Maddalena; Berger, James O.
2004-01-01
Often the goal of model selection is to choose a model for future prediction, and it is natural to measure the accuracy of a future prediction by squared error loss. Under the Bayesian approach, it is commonly perceived that the optimal predictive model is the model with highest posterior probability, but this is not necessarily the case. In this paper we show that, for selection among normal linear models, the optimal predictive model is often the median probability model, which is defined a...
Zhao, L; Cluggish, B; Kim, J S; Pardo, R; Vondrasek, R
2010-02-01
A Monte Carlo charge breeding code (MCBC) is being developed by FAR-TECH, Inc. to model the capture and charge breeding of 1+ ion beam in an electron cyclotron resonance ion source (ECRIS) device. The ECRIS plasma is simulated using the generalized ECRIS model which has two choices of boundary settings, free boundary condition and Bohm condition. The charge state distribution of the extracted beam ions is calculated by solving the steady state ion continuity equations where the profiles of the captured ions are used as source terms. MCBC simulations of the charge breeding of Rb+ showed good agreement with recent charge breeding experiments at Argonne National Laboratory (ANL). MCBC correctly predicted the peak of highly charged ion state outputs under free boundary condition and similar charge state distribution width but a lower peak charge state under the Bohm condition. The comparisons between the simulation results and ANL experimental measurements are presented and discussed. PMID:20192325
New charged anisotropic compact models
Kileba Matondo, D.; Maharaj, S. D.
2016-07-01
We find new exact solutions to the Einstein-Maxwell field equations which are relevant in the description of highly compact stellar objects. The relativistic star is charged and anisotropic with a quark equation of state. Exact solutions of the field equations are found in terms of elementary functions. It is interesting to note that we regain earlier quark models with uncharged and charged matter distributions. A physical analysis indicates that the matter distributions are well behaved and regular throughout the stellar structure. A range of stellar masses are generated for particular parameter values in the electric field. In particular the observed mass for a binary pulsar is regained.
Visualizing Risk Prediction Models
Vanya Van Belle; Ben Van Calster
2015-01-01
Objective Risk prediction models can assist clinicians in making decisions. To boost the uptake of these models in clinical practice, it is important that end-users understand how the model works and can efficiently communicate its results. We introduce novel methods for interpretable model visualization. Methods The proposed visualization techniques are applied to two prediction models from the Framingham Heart Study for the prediction of intermittent claudication and stroke after atrial fib...
Theory and applications of fluctuating-charge models
Chen, Jiahao
2010-01-01
Fluctuating-charge models are computationally efficient methods of treating polarization and charge-transfer phenomena in molecular mechanics and classical molecular dynamics simulations. They are also theoretically appealing as they are minimally parameterized, with parameters corresponding to the chemically important concepts of electronegativities and chemical hardness. However, they are known to overestimate charge transfer for widely separated atoms, leading to qualitative errors in the predicted charge distribution and exaggerated electrostatic properties. We present the charge transfer with polarization current equilibration (QTPIE) model, which solves this problem by introducing distance-dependent electronegativities. A graph-theoretic analysis of the topology of charge transfer allows us to relate the fundamental quantities of charge transfer back to the more familiar variables that represent atomic partial charges. This allows us to formulate a unified theoretical framework for fluctuating-charge mo...
Predictive modeling of complications.
Osorio, Joseph A; Scheer, Justin K; Ames, Christopher P
2016-09-01
Predictive analytic algorithms are designed to identify patterns in the data that allow for accurate predictions without the need for a hypothesis. Therefore, predictive modeling can provide detailed and patient-specific information that can be readily applied when discussing the risks of surgery with a patient. There are few studies using predictive modeling techniques in the adult spine surgery literature. These types of studies represent the beginning of the use of predictive analytics in spine surgery outcomes. We will discuss the advancements in the field of spine surgery with respect to predictive analytics, the controversies surrounding the technique, and the future directions. PMID:27286683
Predictive models of radiative neutrino masses
Julio, J.
2016-06-01
We discuss two models of radiative neutrino mass generation. The first model features one-loop Zee model with Z4 symmetry. The second model is the two-loop neutrino mass model with singly- and doubly-charged scalars. These two models fit neutrino oscillation data well and predict some interesting rates for lepton flavor violation processes.
Borštnik, Norma Susana Mankoč
2016-01-01
The spin-charge-family theory, which is a kind of the Kaluza-Klein theories but with fermions carrying two kinds of spins (no charges), offers the explanation for all the assumptions of the standard model, with the origin of families, the higgs and the Yukawa couplings included. It offers the explanation also for other phenomena, like the origin of the dark matter and of the matter/antimatter asymmetry in the universe. It predicts the existence of the fourth family to the observed three, as w...
Zephyr - the prediction models
Nielsen, Torben Skov; Madsen, Henrik; Nielsen, Henrik Aalborg;
2001-01-01
utilities as partners and users. The new models are evaluated for five wind farms in Denmark as well as one wind farm in Spain. It is shown that the predictions based on conditional parametric models are superior to the predictions obatined by state-of-the-art parametric models....
Halim, Sobia Ahsan; Zaheer-ul-Haq
2015-08-01
Interleukin-2 is an essential cytokine in an innate immune response, and is a promising drug target for several immunological disorders. In the present study, structure-based 3D-QSAR modeling was carried out via Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Index Analysis (CoMSIA) methods. Six different partial charge calculation methods were used in combination with two different alignment methods to scrutinize their effects on the predictive power of 3D-QSAR models. The best CoMFA and CoMSIA models were obtained with the AM1 charges when used with co-conformer based substructure alignment (CCBSA) method. The obtained models posses excellent correlation coefficient value and also exhibited good predictive power (for CoMFA: q(2)=0.619; r(2)=0.890; r(2)Pred=0.765 and for CoMSIA: q(2)=0.607; r(2)=0.884; r(2)Pred=0.655). The developed models were further validated by using a set of another sixteen compounds as external test set 2 and both models showed strong predictive power with r(2)Pred=>0.8. The contour maps obtained from these models better interpret the structure activity relationship; hence the developed models would help to design and optimize more potent IL-2 inhibitors. The results might have implications for rational design of specific anti-inflammatory compounds with improved affinity and selectivity. PMID:26051521
Characterization of wafer charging mechanisms and oxide survival prediction methodology
Unipolar, EEPROM-based peak potential sensors and current sensors have been used to characterize the I-V relationship of charging transients which devices normally experience during the course of ion implantation. The results indicate that the charging sources may appear to behave like current-sources or voltage-sources, depending on the impedance of the load. This behavior may be understood in terms of plasma concepts. The ability to empirically characterize the I-V characteristics of charging sources using the CHARM-2 monitor wafers opens the way for prediction of failure rates of oxides subjected to specific processes, if the oxide Qbd distributions are known
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...
STRATEGY PATTERNS PREDICTION MODEL
Aram Baruch Gonzalez Perez; Jorge Adolfo Ramirez Uresti
2014-01-01
Multi-agent systems are broadly known for being able to simulate real-life situations which require the interaction and cooperation of individuals. Opponent modeling can be used along with multi-agent systems to model complex situations such as competitions like soccer games. In this study, a model for predicting opponent moves based on their target is presented. The model is composed by an offline step (learning phase) and an online one (execution phase). The offline step gets and analyses p...
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. PMID:23423686
STRATEGY PATTERNS PREDICTION MODEL
Aram Baruch Gonzalez Perez
2014-01-01
Full Text Available Multi-agent systems are broadly known for being able to simulate real-life situations which require the interaction and cooperation of individuals. Opponent modeling can be used along with multi-agent systems to model complex situations such as competitions like soccer games. In this study, a model for predicting opponent moves based on their target is presented. The model is composed by an offline step (learning phase and an online one (execution phase. The offline step gets and analyses previous experiences while the online step uses the data generated by offline analysis to predict opponent moves. This model is illustrated by an experiment with the RoboCup 2D Soccer Simulator. The proposed model was tested using 22 games to create the knowledge base and getting an accuracy rate over 80%.
Prediction model Perla presents one of a tool for an evaluation of a stream ecological status. It enables a comparing with a standard. The standard is formed by a dataset of sites from all area of the Czech Republic. The sites were influenced by a human activity as few as possible. 8 variables were used for prediction (distance from source, elevation, stream width and depth, slope, substrate roughness, longitude and latitude. All of them were statistically important for benthic communities. Results do not response ecoregions, but rather stream size (type). B (EQItaxonu), EQISi, EQIASPT a EQIH appears applicable for assessment using the prediction model and for natural and human stress differentiating. Limiting values of the indices for good ecological status are suggested. On the contrary, using of EQIEPT a EQIekoprof indices would be possible only with difficulties. (authors)
Discrete Element Modeling of Triboelectrically Charged Particles
Hogue, Michael D.; Calle, Carlos I.; Weitzman, Peter S.; Curry, David R.
2008-01-01
Tribocharging of particles is common in many processes including fine powder handling and mixing, printer toner transport and dust extraction. In a lunar environment with its high vacuum and lack of water, electrostatic forces are an important factor to consider when designing and operating equipment. Dust mitigation and management is critical to safe and predictable performance of people and equipment. The extreme nature of lunar conditions makes it difficult and costly to carry out experiments on earth which are necessary to better understand how particles gather and transfer charge between each other and with equipment surfaces. DEM (Discrete Element Modeling) provides an excellent virtual laboratory for studying tribocharging of particles as well as for design of devices for dust mitigation and for other purposes related to handling and processing of lunar regolith. Theoretical and experimental work has been performed pursuant to incorporating screened Coulombic electrostatic forces into EDEM, a commercial DEM software package. The DEM software is used to model the trajectories of large numbers of particles for industrial particulate handling and processing applications and can be coupled with other solvers and numerical models to calculate particle interaction with surrounding media and force fields. While simple Coulombic force between two particles is well understood, its operation in an ensemble of particles is more complex. When the tribocharging of particles and surfaces due to frictional contact is also considered, it is necessary to consider longer range of interaction of particles in response to electrostatic charging. The standard DEM algorithm accounts for particle mechanical properties and inertia as a function of particle shape and mass. If fluid drag is neglected, then particle dynamics are governed by contact between particles, between particles and equipment surfaces and gravity forces. Consideration of particle charge and any tribocharging and
Xie, Fei; Turesson, Martin; Woodward, Clifford E; van Gruijthuijsen, Kitty; Stradner, Anna; Forsman, Jan
2016-04-20
We develop a theoretical model to describe structural effects on a specific system of charged colloidal polystyrene particles, upon the addition of non-adsorbing PEG polymers. This system has previously been investigated experimentally, by scattering methods, so we are able to quantitatively compare predicted structure factors with corresponding experimental data. Our aim is to construct a model that is coarse-grained enough to be computationally manageable, yet detailed enough to capture the important physics. To this end, we utilize classical polymer density functional theory, wherein all possible polymer configurations are accounted for, subject to a mean-field Boltzmann weight. We make efforts to counteract drawbacks with this mean-field approach, resulting in structural predictions that agree very well with computationally more demanding simulations. Electrostatic interactions are handled at the fully non-linear Poisson-Boltzmann level, and we demonstrate that a linearization leads to less accurate predictions. The particle charge is an experimentally unknown parameter. We define the surface charge such that the experimental and theoretical gel point at equal polymer concentration coincide. Assuming a fixed surface charge for a certain salt concentration, we find very good agreements between measured and predicted structure factors across a wide range of polymer concentrations. We also present predictions for other structural quantities, such as radial distribution functions, and cluster size distributions. Finally, we demonstrate that our model predicts the occurrence of equilibrium clusters at high polymer concentrations, but low particle volume fractions and salt levels. PMID:27056112
Modeling Charge Collection in Detector Arrays
Hardage, Donna (Technical Monitor); Pickel, J. C.
2003-01-01
A detector array charge collection model has been developed for use as an engineering tool to aid in the design of optical sensor missions for operation in the space radiation environment. This model is an enhancement of the prototype array charge collection model that was developed for the Next Generation Space Telescope (NGST) program. The primary enhancements were accounting for drift-assisted diffusion by Monte Carlo modeling techniques and implementing the modeling approaches in a windows-based code. The modeling is concerned with integrated charge collection within discrete pixels in the focal plane array (FPA), with high fidelity spatial resolution. It is applicable to all detector geometries including monolithc charge coupled devices (CCDs), Active Pixel Sensors (APS) and hybrid FPA geometries based on a detector array bump-bonded to a readout integrated circuit (ROIC).
Candidate Prediction Models and Methods
Nielsen, Henrik Aalborg; Nielsen, Torben Skov; Madsen, Henrik;
2005-01-01
This document lists candidate prediction models for Work Package 3 (WP3) of the PSO-project called ``Intelligent wind power prediction systems'' (FU4101). The main focus is on the models transforming numerical weather predictions into predictions of power production. The document also outlines the...
Melanoma risk prediction models
Nikolić Jelena
2014-01-01
Full Text Available Background/Aim. The lack of effective therapy for advanced stages of melanoma emphasizes the importance of preventive measures and screenings of population at risk. Identifying individuals at high risk should allow targeted screenings and follow-up involving those who would benefit most. The aim of this study was to identify most significant factors for melanoma prediction in our population and to create prognostic models for identification and differentiation of individuals at risk. Methods. This case-control study included 697 participants (341 patients and 356 controls that underwent extensive interview and skin examination in order to check risk factors for melanoma. Pairwise univariate statistical comparison was used for the coarse selection of the most significant risk factors. These factors were fed into logistic regression (LR and alternating decision trees (ADT prognostic models that were assessed for their usefulness in identification of patients at risk to develop melanoma. Validation of the LR model was done by Hosmer and Lemeshow test, whereas the ADT was validated by 10-fold cross-validation. The achieved sensitivity, specificity, accuracy and AUC for both models were calculated. The melanoma risk score (MRS based on the outcome of the LR model was presented. Results. The LR model showed that the following risk factors were associated with melanoma: sunbeds (OR = 4.018; 95% CI 1.724- 9.366 for those that sometimes used sunbeds, solar damage of the skin (OR = 8.274; 95% CI 2.661-25.730 for those with severe solar damage, hair color (OR = 3.222; 95% CI 1.984-5.231 for light brown/blond hair, the number of common naevi (over 100 naevi had OR = 3.57; 95% CI 1.427-8.931, the number of dysplastic naevi (from 1 to 10 dysplastic naevi OR was 2.672; 95% CI 1.572-4.540; for more than 10 naevi OR was 6.487; 95%; CI 1.993-21.119, Fitzpatricks phototype and the presence of congenital naevi. Red hair, phototype I and large congenital naevi were
Hydrodynamic Model for Charge Carriers
Choquet, Isabelle; Degond, Pierre; Schmeiser, Christian
2003-01-01
A set of hydrodynamic equations modeling strong ionization in semiconductors is formally derived from a kinetic framework. To that purpose, a system of Boltzmann transport equations governing the distribution functions of conduction electrons and holes is considered. Apart from impact ionization, the model accounts for phonon, lattice defects, and particle-particle scattering. Also degeneracy effects are included. The band diagram models are approximations close to the extre...
Electrostatic Model Applied to ISS Charged Water Droplet Experiment
Stevenson, Daan; Schaub, Hanspeter; Pettit, Donald R.
2015-01-01
The electrostatic force can be used to create novel relative motion between charged bodies if it can be isolated from the stronger gravitational and dissipative forces. Recently, Coulomb orbital motion was demonstrated on the International Space Station by releasing charged water droplets in the vicinity of a charged knitting needle. In this investigation, the Multi-Sphere Method, an electrostatic model developed to study active spacecraft position control by Coulomb charging, is used to simulate the complex orbital motion of the droplets. When atmospheric drag is introduced, the simulated motion closely mimics that seen in the video footage of the experiment. The electrostatic force's inverse dependency on separation distance near the center of the needle lends itself to analytic predictions of the radial motion.
A predictive theory of charge separation in organic photovoltaics interfaces
Troisi, Alessandro; Liu, Tao; Caruso, Domenico; Cheung, David L.; McMahon, David P.
2012-09-01
The key process in organic photovoltaics cells is the separation of an exciton, close to the donor/acceptor interface into a free hole (in the donor) and a free electron (in the acceptor). In an efficient solar cell, the majority of absorbed photons generate such hole-electron pairs but it is not clear why such a charge separation process is so efficient in some blends (for example in the blend formed by poly(3- hexylthiophene) (P3HT) and a C60 derivative (PCBM)) and how can one design better OPV materials. The electronic and geometric structure of the prototypical polymer:fullerene interface (P3HT:PCBM) is investigated theoretically using a combination of classical and quantum simulation methods. It is shown that the electronic structure of P3HT in contact with PCBM is significantly altered compared to bulk P3HT. Due to the additional free volume of the interface, P3HT chains close to PCBM are more disordered and, consequently, they are characterized by an increased band gap. Excitons and holes are therefore repelled by the interface. This provides a possible explanation of the low recombination efficiency and supports the direct formation of "quasi-free" charge separated species at the interface. This idea is further explored here by using a more general system-independent model Hamiltonian. The long range exciton dissociation rate is computed as a function of the exciton distance from the interface and the average dissociation distance is evaluated by comparing this rate with the exciton migration rate with a kinetic model. The phenomenological model shows that also in a generic interface the direct formation if quasi-free charges is extremely likely.
Quantitative model of radiation induced charge trapping in SiO2
A predictive model of radiation induced oxide charging, based on statistical thermodynamics and electron spin resonance measurements of defects known as E' centers, has been developed. The model is successfully tested on 60Co irradiated MOSFETs
Ostwald ripening of charged supported metal nanoparticles: Schottky model
Zhdanov, Vladimir P.
2015-07-01
Due to high surface area, supported metal nanoparticles are thermodynamically prone to sintering. The experimental studies of this process exhibit sometimes transient bimodal particle size distributions. Such observations may result from the support heterogeneity. Looking retrospectively, one can also find the prediction that in the case of Ostwald ripening this feature can be related to charge of metal nanoparticles. In real systems, this charge is often associated with the metal-support interaction and can be interpreted in the framework of the Schottky model. Using this model, the author shows that the charge redistribution cannot be behind bimodal particle size distributions. Moreover, the corresponding contribution to the driving force for Ostwald ripening is typically much smaller than the conventional one.
Models of charge pair generation in organic solar cells.
Few, Sheridan; Frost, Jarvist M; Nelson, Jenny
2015-01-28
Efficient charge pair generation is observed in many organic photovoltaic (OPV) heterojunctions, despite nominal electron-hole binding energies which greatly exceed the average thermal energy. Empirically, the efficiency of this process appears to be related to the choice of donor and acceptor materials, the resulting sequence of excited state energy levels and the structure of the interface. In order to establish a suitable physical model for the process, a range of different theoretical studies have addressed the nature and energies of the interfacial states, the energetic profile close to the heterojunction and the dynamics of excited state transitions. In this paper, we review recent developments underpinning the theory of charge pair generation and phenomena, focussing on electronic structure calculations, electrostatic models and approaches to excited state dynamics. We discuss the remaining challenges in achieving a predictive approach to charge generation efficiency. PMID:25462189
Geriatric Hip Fractures and Inpatient Services: Predicting Hospital Charges Using the ASA Score
Rachel V. Thakore
2014-01-01
Full Text Available Purpose. To determine if the American Society of Anesthesiologist (ASA score can be used to predict hospital charges for inpatient services. Materials and Methods. A retrospective chart review was conducted at a level I trauma center on 547 patients over the age of 60 who presented with a hip fracture and required operative fixation. Hospital charges associated with inpatient and postoperative services were organized within six categories of care. Analysis of variance and a linear regression model were performed to compare preoperative ASA scores with charges and inpatient services. Results. Inpatient and postoperative charges and services were significantly associated with patients’ ASA scores. Patients with an ASA score of 4 had the highest average inpatient charges of services of $15,555, compared to $10,923 for patients with an ASA score of 2. Patients with an ASA score of 4 had an average of 45.3 hospital services compared to 24.1 for patients with a score of 2. Conclusions. A patient’s ASA score is associated with total and specific hospital charges related to inpatient services. The findings of this study will allow payers to identify the major cost drivers for inpatient services based on a hip fracture patient’s preoperative physical status.
Geriatric Hip Fractures and Inpatient Services: Predicting Hospital Charges Using the ASA Score.
Thakore, Rachel V; Lee, Young M; Sathiyakumar, Vasanth; Obremskey, William T; Sethi, Manish K
2014-01-01
Purpose. To determine if the American Society of Anesthesiologist (ASA) score can be used to predict hospital charges for inpatient services. Materials and Methods. A retrospective chart review was conducted at a level I trauma center on 547 patients over the age of 60 who presented with a hip fracture and required operative fixation. Hospital charges associated with inpatient and postoperative services were organized within six categories of care. Analysis of variance and a linear regression model were performed to compare preoperative ASA scores with charges and inpatient services. Results. Inpatient and postoperative charges and services were significantly associated with patients' ASA scores. Patients with an ASA score of 4 had the highest average inpatient charges of services of $15,555, compared to $10,923 for patients with an ASA score of 2. Patients with an ASA score of 4 had an average of 45.3 hospital services compared to 24.1 for patients with a score of 2. Conclusions. A patient's ASA score is associated with total and specific hospital charges related to inpatient services. The findings of this study will allow payers to identify the major cost drivers for inpatient services based on a hip fracture patient's preoperative physical status. PMID:24876836
Superscaling predictions for neutrino-induced charged-current charged pion production at MiniBooNE
Ivanov, M V; Antonov, A N; Caballero, J A; Barbaro, M B; de Guerra, E Moya
2012-01-01
Superscaling approximation (SuSA) predictions to neutrino-induced charged-current charged pion production in the \\Delta-resonance region are explored under MiniBooNE experimental conditions. The results obtained within SuSA for the flux-averaged double-differential cross sections of the \\pi+ production for the \
Charge State Model of Solar Energetic Particles
Del Peral, L.; Pérez-Peraza, J. A.; Rodríguez Frías, M. D.
2013-05-01
Charge states of heavy ions in Solar Energetic Particle (SEP) events observed at the Earth's neighborhood with experiments on board satellites give us information about physical properties of plasma where acceleration occurs. SEP detection is performed near the Earth, therefore not only physical condition of the plasma source of accelerated particles have to be taken into account. We have developed a charge state model in order to explain the evolution of particle charge states under solar acceleration. Charge-interchange processes between the accelerated ions and the plasma matter in the acceleration region are considered on basis of electron loss and capture cross sections at high energies. We have applied the model to observational data from satellites measuring charge states of SEPs. In contrast with other models that use ionization and recombination cross-sections that require application of thermal equilibrium, our model assumes that the acceleration is so fast that thermal equilibrium can not be applied to the change interchange processes. Therefore we employ in our model high energy cross-sections for electron capture and loss, since the population which is being accelerated acquires a non-thermal spectrum. We have developed temperature dependent cross-sections. Acceleration begins from a thermal distribution. As soon as the particles increase their energy by the acceleration process, they acquire an energy spectrum which differs from the Maxwellian thermal one while interacting with the background thermal matter. Figure 1 presents the results of our model that fit experimental charge states of Fe ions from two impulsive SEP events detected by the SEPICA satellite in July 1999. We obtain good fitting for source temperature of 1.8 \\cdot 106 K and density of 5\\cdot108 cm-3 and acceleration efficiency of 1.8\\cdot 10-2 s-1 for the July 20th 1999 event and 3.3\\cdot 10-2 s-1 for the July 3rd 1999. Good concordance between experimental data and our model have
Continuum modeling of charging process and piezoelectricity of ferroelectrets
Xu, Bai-Xiang; von Seggern, Heinz; Zhukov, Sergey; Gross, Dietmar
2013-09-01
Ferroelectrets in the form of electrically charged micro-porous foams exhibit a very large longitudinal piezoelectric coefficient d33. The structure has hence received wide application interests as sensors particularly in acoustic devices. During charging process, electrical breakdown (Paschen breakdown) takes place in the air pores of the foam and introduces free charge pairs. These charges are separated by electrostatic forces and relocated at the interfaces between the polymer and the electrically broken-down medium, where they are trapped quasistatically. The development of this trapped charge density along the interfaces is key for enabling the piezoelectricity of ferroelectrets. In this article, an internal variable based continuum model is proposed to calculate the charge density development at the interfaces, whereas a Maxwell stress based electromechanical model is used for the bulk behavior, i.e., of the polymer and of the medium where the Paschen breakdown takes place. In the modeling, the electrostatic forces between the separated charge pairs are included, as well as the influence of deformation of the solid layers. The material models are implemented in a nonlinear finite element scheme, which allows a detailed analysis of different geometries. A ferroelectret unit with porous expanded polytetrafluoroethylene (ePTFE) surrounded by fluorinated ethylene propylene is studied first. The simulated hysteresis curves of charge density at the surfaces and the calculated longitudinal piezoelectric constant are in good agreement with experimental results. Simulations show a strong dependency of the interface charge development and thus the remnant charges on the thicknesses of the layers and the permittivity of the materials. According to the calculated relation between d33 and the Young's modulus of ePTFE, the value of the Young's modulus of ePTFE is identified to be around 0.75 MPa, which lies well in the predicted range of 0.45 to 0.80 MPa, determined from
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 ...
Prediction models in complex terrain
Marti, I.; Nielsen, Torben Skov; Madsen, Henrik; Navarro, J.; Barquero, C.G.
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 the...... performance of HIRLAM in particular with respect to wind predictions. To estimate the performance of the model two spatial resolutions (0,5 Deg. and 0.2 Deg.) and different sets of HIRLAM variables were used to predict wind speed and energy production. The predictions of energy production for the wind farms...... are calculated using on-line measurements of power production as well as HIRLAM predictions as input thus taking advantage of the auto-correlation, which is present in the power production for shorter pediction horizons. Statistical models are used to discribe the relationship between observed energy...
Offset prediction for charge-balanced stimulus waveforms
Woods, V M; Triantis, I.; Toumazou, C.
2011-01-01
Functional electrical stimulation with cuff electrodes involves the controlled injection of current into an electrically excitable tissue for sensory or motor rehabilitation. Some charge injected during stimulation is 'lost' at the electrode-electrolyte interface when the charge carrier is translated from an electron to an ion in the solution. The process of charge injection through chemical reactions can reduce electrode longevity and implant biocompatibility. Conventionally, the excess char...
Regge-plus-resonance predictions for charged-kaon photoproduction from the deuteron
Van Cauteren T.
2010-04-01
Full Text Available We present a Regge-inspired eﬀective-Lagrangian framework for charged-kaon photoproduction from the deuteron. Quasi-free kaon production is investigated using the Regge-plus-resonance elementary operator within the non-relativistic plane-wave impulse approximation. The Regge-plus-resonance model was developed to describe photoinduced and electroinduced kaon production oﬀ protons and can be extended to strangeness production oﬀ neutrons. The non-resonant contributions to the amplitude are modelled in terms of K+ (494 and K*+ (892 Regge-trajectory exchange in the t-channel. This amplitude is supplemented with a selection of s-channel resonance-exchange diagrams. We investigate several sources of theoretical uncertainties on the semi-inclusive charged-kaon production cross section. The experimental error bars on the photocoupling helicity amplitudes turn out to put severe limits on the predictive power when considering quasi-free kaon production on a bound neutron.
Confidence scores for prediction models
Gerds, Thomas Alexander; van de Wiel, MA
2011-01-01
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 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...
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.
Prediction of coking dynamics for wet coal charge
Kardaś Dariusz
2015-09-01
Full Text Available A one-dimensional transient mathematical model describing thermal and flow phenomena during coal coking in an oven chamber was studied in the paper. It also accounts for heat conduction in the ceramic oven wall when assuming a constant temperature at the heating channel side. The model was solved numerically using partly implicit methods for gas flow and heat transfer problems. The histories of temperature, gas evolution and internal pressure were presented and analysed. The theoretical predictions of temperature change in the centre plane of the coke oven were compared with industrialscale measurements. Both, the experimental data and obtained numerical results show that moisture content determines the coking process dynamics, lagging the temperature increase above the water steam evaporation temperature and in consequence the total coking time. The phenomenon of internal pressure generation in the context of overlapping effects of simultaneously occurring coal transitions - devolatilisation and coal permeability decrease under plastic stage - was also discussed.
Predictive Models and Computational Embryology
EPA’s ‘virtual embryo’ project is building an integrative systems biology framework for predictive models of developmental toxicity. One schema involves a knowledge-driven adverse outcome pathway (AOP) framework utilizing information from public databases, standardized ontologies...
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.
Predictive Modelling of Cellular Load
Carolan, Emmett; McLoone, Seamus; Farrell, Ronan
2015-01-01
This work examines the temporal dynamics of cellular load in four Irish regions. Large scale underutilisation of network resources is identified both at the regional level and at the level of individual cells. Cellular load is modeled and prediction intervals are generated. These prediction intervals are used to put an upper bound on usage in a particular cell at a particular time. Opportunities for improvements in network utilization by incorporating these upper bounds on usage are identifie...
Atomic charges for modeling metal–organic frameworks: Why and how
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
Atomic charges for modeling metal–organic frameworks: Why and how
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.
A contrail cirrus prediction model
U. Schumann
2012-05-01
Full Text Available A new model to simulate and predict the properties of a large ensemble of contrails as a function of given air traffic and meteorology is described. The model is designed for approximate prediction of contrail cirrus cover and analysis of contrail climate impact, e.g. within aviation system optimization processes. The model simulates the full contrail life-cycle. Contrail segments form between waypoints of individual aircraft tracks in sufficiently cold and humid air masses. The initial contrail properties depend on the aircraft. The advection and evolution of the contrails is followed with a Lagrangian Gaussian plume model. Mixing and bulk cloud processes are treated quasi analytically or with an effective numerical scheme. Contrails disappear when the bulk ice content is sublimating or precipitating. The model has been implemented in a "Contrail Cirrus Prediction Tool" (CoCiP. This paper describes the model assumptions, the equations for individual contrails, and the analysis-method for contrail-cirrus cover derived from the optical depth of the ensemble of contrails and background cirrus. The model has been applied for a case study and compared to the results of other models and in-situ contrail measurements. The simple model reproduces a considerable part of observed contrail properties. Mid-aged contrails provide the largest contributions to the product of optical depth and contrail width, important for climate impact.
A contrail cirrus prediction model
U. Schumann
2011-11-01
Full Text Available A new model to simulate and predict the properties of a large ensemble of contrails as a function of given air traffic and meteorology is described. The model is designed for approximate prediction of contrail cirrus cover and analysis of contrail climate impact, e.g. within aviation system optimization processes. The model simulates the full contrail life-cycle. Contrail segments form between waypoints of individual aircraft tracks in sufficiently cold and humid air masses. The initial contrail properties depend on the aircraft. The advection and evolution of the contrails is followed with a Lagrangian Gaussian plume model. Mixing and bulk cloud processes are treated quasi analytically or with an effective numerical scheme. Contrails disappear when the bulk ice content is sublimating or precipitating. The model has been implemented in a "Contrail Cirrus Prediction Tool" (CoCiP. This paper describes the model assumptions, the equations for individual contrails, and the analysis-method for contrail-cirrus cover derived from the optical depth of the ensemble of contrails and background cirrus. The model has been applied for a case study and compared to the results of other models and in-situ contrail measurements. The simple model reproduces a considerable part of observed contrail properties. Mid-aged contrails provide the largest contributions to the product of optical depth and contrail width, important for climate impact.
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…
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.
Li, Hua; Wang, Bowen; Li, Zhiwei; Liu, De; Lin, Fuchang; Dai, Ling; Zhang, Qin; Chen, Yaohong
2013-10-01
Metallized biaxially oriented polypropylene film (BOPP) capacitors are widely used in pulsed power systems. When the capacitor is used as the energy storage equipment under high electric field, more charges should be provided to maintain the voltage of the capacitor. This should be ascribed to the completion of the slow polarization which may take several hours or even longer. This paper focuses on the stored charge in metallized BOPP film capacitors. The modeling of the stored charge by the equivalent conversion of circuits is conducted to analyse the slow polarization in the BOPP film. The 3-RC network is proposed to represent the time-dependent charge stored in the capacitor. A charging current measurement system is established to investigate the charge storage property of the capacitor. The measurement system can measure the long time charging current with a sampling rate of 300 Hz. The total charge calculated by the charging current indicates that the stored charge in the capacitor under the electric field of 400 V/μm is 13.5% larger than the product of the voltage and the capacitance measured by the AC bridge. The nonlinear effect of the electric field on the slow polarization charge is also demonstrated. And the simulation of charge storage based on the 3-RC network can match well with the trend of the stored charge increasing with the time. PMID:24182144
Modeling taper charge with a non-linear equation
Mcdermott, P. P.
1985-01-01
Work aimed at modeling the charge voltage and current characteristics of nickel-cadmium cells subject to taper charge is presented. Work reported at previous NASA Battery Workshops has shown that the voltage of cells subject to constant current charge and discharge can be modeled very accurately with the equation: voltage = A + (B/(C-X)) + De to the -Ex where A, B, D, and E are fit parameters and x is amp-hr of charge removed during discharge or returned during charge. In a constant current regime, x is also equivalent to time on charge or discharge.
In this paper simple regression equations are proposed to predict the charge characteristics of tubular, adsorbed natural gas storage systems. The regression equations are obtained in terms of relevant, statistically significant non-dimensional numbers. The data required for regression analysis is generated by solving the transient heat and mass transfer equations of adsorbed natural gas (ANG) storage system undergoing charging under constant pressure condition. The governing equations are non-dimensionalized and relevant non-dimensional numbers are identified. Then by fixing suitable ranges for various material related, design and operating parameters, the range of different non-dimensional parameters are found. Then based on a large amount of data obtained in non-dimensional form by numerically solving the heat and mass transfer equations, correlations are developed for 1) the time required for 90% adsorption, 2) total heat transferred during 90% adsorption, and 3) the maximum temperature experienced by the bed during 90% adsorption. The regression equations are compared with the simulated values and it is observed that the difference is within 25% for all the three parameters. It is expected that the proposed regression equations will be useful in fast evaluation of charging performance of the ANG systems. - Highlights: • A transient heat and mass transfer model for adsorbed natural gas (ANG) storage reactor is formulated. • The system of equations are non-dimensionalized • A large amount of data on charging characteristics of the reactor is generated by solving the system of equations. • Regression equations are obtained for estimating the performance in terms of non-dimensional numbers. • Regression equations can be used for quick evaluation of ANG systems under charging
Predicting Abraham model solvent coefficients
Bradley, Jean-Claude; Abraham, Michael H; Acree, William E; Lang, Andrew SID
2015-01-01
Background The Abraham general solvation model can be used in a broad set of scenarios involving partitioning and solubility, yet is limited to a set of solvents with measured Abraham coefficients. Here we extend the range of applicability of Abraham’s model by creating open models that can be used to predict the solvent coefficients for all organic solvents. Results We created open random forest models for the solvent coefficients e, s, a, b, and v that had out-of-bag R2 values of 0.31, 0.77...
Preconditioned Continuation Model Predictive Control
Knyazev, Andrew; Fujii, Yuta; Malyshev, Alexander,
2015-01-01
Model predictive control (MPC) anticipates future events to take appropriate control actions. Nonlinear MPC (NMPC) describes systems with nonlinear models and/or constraints. A Continuation/GMRES Method for NMPC, suggested by T. Ohtsuka in 2004, uses the GMRES iterative algorithm to solve a forward difference approximation $Ax=b$ of the Continuation NMPC (CNMPC) equations on every time step. The coefficient matrix $A$ of the linear system is often ill-conditioned, resulting in poor GMRES conv...
Failure prediction model: Model napovedovanja odpovedi:
Čelan, Štefan; Težak, Oto; Žižek, Adolf
2002-01-01
Preventative maintenance is vital for delicate technical products. Electronic components or the whole system must be changed, and thus need a good model that will indicate failure accurately. In this paper a stochastic stress-strength quantitative model is presented, folowing the five original hypothesis. Proposed new model of failure prediction could be used by the system maintenance. Failure risk could be instantaneosly calculated. The given theory considers the influences of stress on the ...
Modulational instability of charge transport in the Peyrard-Bishop-Holstein model.
Tabi, Conrad Bertrand; Mohamadou, Alidou; Kofané, Timoléon Crépin
2009-08-19
We report on modulational instability (MI) on a DNA charge transfer model known as the Peyrard-Bishop-Holstein (PBH) model. In the continuum approximation, the system reduces to a modified Klein-Gordon-Schrödinger (mKGS) system through which linear stability analysis is performed. This model shows some possibilities for the MI region and the study is carried out for some values of the nearest-neighbor transfer integral. Numerical simulations are then performed, which confirm analytical predictions and give rise to localized structure formation. We show how the spreading of charge deeply depends on the value of the charge-lattice-vibrational coupling. PMID:21828595
Predicted angular distribution of fast charged particles with ionization
Moliere theory of angular distribution for fast charged particles is improved to take into account ionization loss, by using Kamata-Nishimura formulation of the theory. Decrease of the particle energy along the passage hence increase of the screening angle brings a slight different results from those derived by Moliere-Bethe formulation for fixed energies. The present results are reduced to the same Moliere distribution with modified values of the expansion parameter and the unit of Moliere angle. Properties of the new distribution and differences from the traditional one are discussed. Angular distributions of particles penetrating through the mixed or compound substances are also investigated both under the relativistic and the nonrelativistic conditions, together with the Kamata-Nishimura constants characterizing their formulation. (author)
Boulmene, Reda; Boussouf, Karim; Prakash, Muthuramalingam; Komiha, Najia; Al-Mogren, Muneerah M; Hochlaf, Majdi
2016-04-01
Using first-principles methodologies, the equilibrium structures and the relative stability of CO2 @[Zn(q+) Im] (where q=0, 1, 2; Im=imidazole) complexes are studied to understand the nature of the interactions between the CO2 and Zn(q+) -imidazole entities. These complexes are considered as prototype models mimicking the interactions of CO2 with these subunits of zeolitic imidazolate frameworks or Zn enzymes. These computations are performed using both ab initio calculations and density functional theory. Dispersion effects accounting for long-range interactions are considered. Solvent (water) effects were also considered using a polarizable continuum model approach. Natural bond orbital, charge, frontier orbital and vibrational analyses clearly reveal the occurrence of charge transfer through covalent and noncovalent interactions. Moreover, it is found that CO2 can adsorb through more favorable π-type stacking as well as σ-type hydrogen-bonding interactions. The inter-monomer interaction potentials show a significant anisotropy that might induce CO2 orientation and site-selectivity effects in porous materials and in active sites of Zn enzymes. Hence, this study provides valuable information about how CO2 adsorption takes place at the microscopic level within zeolitic imidazolate frameworks and biomolecules. These findings might help in understanding the role of such complexes in chemistry, biology and material science for further development of new materials and industrial applications. PMID:26790137
Gaussian-Charge Polarizable and Nonpolarizable Models for CO2.
Jiang, Hao; Moultos, Othonas A; Economou, Ioannis G; Panagiotopoulos, Athanassios Z
2016-02-11
A polarizable intermolecular potential model using three classical Drude oscillators on the atomic sites has been developed for CO2. The model is rigid with bond lengths and molecular geometries set to their experimental values. Electrostatic interactions are represented by three Gaussian charges connected to the molecular frame by harmonic springs. Nonelectrostatic interactions are represented by the Buckingham exponential-6 potential, with potential parameters optimized to vapor-liquid equilibria (VLE) data. A nonpolarizable CO2 model that shares the other ingredients of the polarizable model was also developed and optimized to VLE data. Gibbs ensemble Monte Carlo and molecular dynamics simulations were used to evaluate the two models with respect to a variety of thermodynamic and transport properties, including the enthalpy of vaporization, second virial coefficient, density in the one-phase fluid region, isobaric and isochoric heat capacities, radial distribution functions, self-diffusion coefficient, and shear viscosity. Excellent agreement between model predictions and experimental data was found for all properties studied. The polarizable and nonpolarizable models provide a similar representation of CO2 properties, which indicates that the properties of pure CO2 fluid are not strongly affected by polarization. The polarizable model, which has an order of magnitude higher computational cost than the nonpolarizable model, will likely be useful for the study of a mixture of CO2 and polar components for which polarization is important. PMID:26788614
Analytical Charge Voltage Model in MOS Inversion Layer Based on Space Charge Capacitance
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.
Modeling of the charging step of metal hydrides tanks for hydrogen storage
The objective of the study presented in this paper is to propose a model able to predict the charging step of a metal hydride (MH) tank in terms of charging duration, charged volume and temperature reached in the tank. The approach followed consists in modelling the whole system from a macroscopic point of view in order to have a global understanding of the charging process. For the model, the tank charging step is divided in two parts: a first one where charging is performed at an imposed flow rate and pressure increases up to the charging pressure and a second phase where the pressure in the tank is close to the charging pressure and the entering hydrogen flow rate is imposed by the adsorption reaction rate. An adsorption reaction kinetic model is also proposed. The results of the developed model were compared with experimental data from three different MH tanks and a good agreement was demonstrated. This model only needs little information from the MH tank and a qualification step. It can then be used to evaluate different operating parameters influence and help to define the optimal operating parameters for MH tank use. (authors)
Neutrino nucleosynthesis in supernovae: Shell model predictions
Almost all of the 3 · 1053 ergs liberated in a core collapse supernova is radiated as neutrinos by the cooling neutron star. I will argue that these neutrinos interact with nuclei in the ejected shells of the supernovae to produce new elements. It appears that this nucleosynthesis mechanism is responsible for the galactic abundances of 7Li, 11B, 19F, 138La, and 180Ta, and contributes significantly to the abundances of about 15 other light nuclei. I discuss shell model predictions for the charged and neutral current allowed and first-forbidden responses of the parent nuclei, as well as the spallation processes that produce the new elements. 18 refs., 1 fig., 1 tab
Prediction of coking dynamics for wet coal charge
Kardaś Dariusz; Polesek-Karczewska Sylwia; Ciżmiński Przemysław; Stelmach Sławomir
2015-01-01
A one-dimensional transient mathematical model describing thermal and flow phenomena during coal coking in an oven chamber was studied in the paper. It also accounts for heat conduction in the ceramic oven wall when assuming a constant temperature at the heating channel side. The model was solved numerically using partly implicit methods for gas flow and heat transfer problems. The histories of temperature, gas evolution and internal pressure were presented and analysed. The theoretical predi...
Electric Vehicle Charging Stations Allocation Model
BAOUCHE, Fouad; Billot, Romain; Trigui, Rochdi; El Faouzi, Nour-Eddin
2014-01-01
In 2009, French authorities launched a national plan for the deployment of charging infrastructure in order to promote the electromobility. Key stakeholders and industrial such car manufacturers, energy distribution companies and researchers were encouraged to propose optimal solutions for the installation of charging stations (CS). These solutions should cover all types of configurations: public roads, parking, and workplace. The French Environmental and Energy Management Agency (ADEME) set ...
Geriatric Hip Fractures and Inpatient Services: Predicting Hospital Charges Using the ASA Score
Thakore, Rachel V.; Young M. Lee; Vasanth Sathiyakumar; Obremskey, William T.; Sethi, Manish K.
2014-01-01
Purpose. To determine if the American Society of Anesthesiologist (ASA) score can be used to predict hospital charges for inpatient services. Materials and Methods. A retrospective chart review was conducted at a level I trauma center on 547 patients over the age of 60 who presented with a hip fracture and required operative fixation. Hospital charges associated with inpatient and postoperative services were organized within six categories of care. Analysis of variance and a linear regression...
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...
Modulated charge patterns and noise effect in a twisted DNA model with solvent interaction
Tabi, C. B.; Dang Koko, A.; Oumarou Doko, R.; Ekobena Fouda, H. P.; Kofané, T. C.
2016-01-01
We modify the Peyrard-Bishop-Holstein model and bring out the influence of the torsion and solvent interactions on charge transport in DNA. Through the linear stability analysis, we detect regions of instability and we compare the results with those of the standard Peyrard-Bishop-Holstein model. There are two regimes where modulated charge patterns can occur: the undertwisted and the overtwisted conformations. Numerical simulations are used to confirm our analytical predictions. Charge patterns are obtained and propagate more easily in an overwinded helix than in an underwinded one. The effects of dissipation and thermal fluctuations are also studied, which confirm the robustness of the obtained modulated patterns. On the one hand, we argue that in the absence of twisting, temperature can lead to the breaking of the hydrogen bonds between bases and prevent charges from propagating. On the other hand, when the molecule is overtwisted, the solvent and the temperature will rather enhance charge spreading patterns with random features.
Symmetrization of mathematical model of charge transport in semiconductors
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.
Leherte, Laurence; Vercauteren, Daniel P
2011-10-01
To generate reduced point charge models of proteins, we developed an original approach to hierarchically locate extrema in charge density distribution functions built from the Poisson equation applied to smoothed molecular electrostatic potential (MEP) functions. A charge fitting program was used to assign charge values to the so-obtained reduced representations. In continuation to a previous work, the Amber99 force field was selected. To easily generate reduced point charge models for protein structures, a library of amino acid templates was designed. Applications to four small peptides, a set of 53 protein structures, and four KcsA ion channel models, are presented. Electrostatic potential and solvation free energy values generated by the reduced models are compared with the corresponding values obtained using the original set of atomic charges. Results are in closer agreement with the original all-atom electrostatic properties than those obtained with a previous reduced model that was directly built from the smoothed MEP functions [Leherte and Vercauteren in J Chem Theory Comput 5:3279-3298, 2009]. PMID:21915750
Charged compact stellar model in Finch-Skea spacetime
Ratanpal, B S; Sharma, R; Das, S
2016-01-01
In this paper a compact charged stellar model in the Finch and Skea background spacetime [{\\it Class. Quantum Gravity} {\\bf6}, 467 (1989)] is presented. The model has been developed by assuming a particular charge distribution within the stellar interior. The model is well behaved and can describe a large class of compact stars. Physical features of the model are studied and in particular we show how the presence of charge can have a non-negligible impact on the mass-radius ($M-R$) relationship of such class of stars.
DC Motor Control Predictive Models
Ravinesh Singh
2006-01-01
Full Text Available DC motor speed and position controls are fundamental in vehicles in general and robotics in particular. This study presents a mathematical model for correlating the interactions of some DC motor control parameters such as duty cycle, terminal voltage, frequency and load on some responses such as output current, voltage and speed by means of response surface methodology. For this exercise, a five-level full factorial design was chosen for experimentation using a peripheral interface controller (PIC-based universal pulse width modulation (PWM H-Bridge motor controller built in-house. The significance of the mathematical model developed was ascertained using regression analysis method. The results obtained show that the mathematical models are useful not only for predicting optimum DC motor parameters for achieving the desired quality but for speed and position optimization. Using the optimal combination of these parameters is useful in minimizing the power consumption and realization of the optimal speed and invariably position control of DC motor operations.
Predictive Modeling of Tokamak Configurations*
Casper, T. A.; Lodestro, L. L.; Pearlstein, L. D.; Bulmer, R. H.; Jong, R. A.; Kaiser, T. B.; Moller, J. M.
2001-10-01
The Corsica code provides comprehensive toroidal plasma simulation and design capabilities with current applications [1] to tokamak, reversed field pinch (RFP) and spheromak configurations. It calculates fixed and free boundary equilibria coupled to Ohm's law, sources, transport models and MHD stability modules. We are exploring operations scenarios for both the DIII-D and KSTAR tokamaks. We will present simulations of the effects of electron cyclotron heating (ECH) and current drive (ECCD) relevant to the Quiescent Double Barrier (QDB) regime on DIII-D exploring long pulse operation issues. KSTAR simulations using ECH/ECCD in negative central shear configurations explore evolution to steady state while shape evolution studies during current ramp up using a hyper-resistivity model investigate startup scenarios and limitations. Studies of high bootstrap fraction operation stimulated by recent ECH/ECCD experiments on DIIID will also be presented. [1] Pearlstein, L.D., et al, Predictive Modeling of Axisymmetric Toroidal Configurations, 28th EPS Conference on Controlled Fusion and Plasma Physics, Madeira, Portugal, June 18-22, 2001. * Work performed under the auspices of the U.S. Department of Energy by the University of California, Lawrence Livermore National Laboratory under contract No. W-7405-Eng-48.
Charge transport models for reliability engineering of semiconductor devices
correlation. This shows that an NMP-based theory of the bias temperature instability can both explain characteristic time constants experimentally found in the drain and the gate current after bias temperature stress as well as the overall threshold voltage shift. These findings imply that for an accurate lifetime prediction an NMP-based theory is a good choice. However, in order to obtain an accurate lifetime prediction information on the threshold voltage shift caused by a single discrete trap created during bias temperature stress needs to be investigated. To this end small area MOSFETs have been investigated on a statistical basis using random discrete doping in order to determine the cumulative distribution function (CFD) of threshold voltage shifts caused by random discrete charged traps as well as their characteristic capture and emission times. It is found that the experimentally observed CFDs of the threshold voltage shifts caused by single charged traps cannot be reproduced using Minimos-NT by considering potential fluctuations alone. Thus further investigations into this subject are needed. Since the study of hot-carrier degradation requires exact information on the energy distribution of charge carriers, a solution of the Boltzmann transport equation is necessary. For detailed investigations into hot-carrier degradation, ViennaSHE, a device simulator based on a spherical harmonics expansion (SHE) of the Boltzmann transport equation, has been extended in the course of this thesis. To compare SHE to moment-based transport models, quantum correction models, variability caused by random discrete dopants, the classical SRH trapping theory as well as a four state degradation model based on non-radiative multi-phonon theory are incorporated into the simulator. These additions to ViennaSHE allow to evaluate the device characteristics of virgin as well as degraded devices under hot-carrier or bias temperature stress or both. Additionally, ViennaSHE is extended by the
Production of Charged Scalars from the Littlest Higgs Model Associated with Top Quark at LHC
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±.
I give a sketch of my recent attempt to test the prediction by Leutwyler and Smilga according to which, for QCD in a finite box with Nf ≥ 2, the combination x = VΣm indicates whether the net topological charge of the gauge background proves relevant (x > 1) for physical observables
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
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.
Poisson-Boltzmann theory of charged colloids: limits of the cell model for salty suspensions
Thermodynamic properties of charge-stabilized colloidal suspensions and polyelectrolyte solutions are commonly modelled by implementing the mean-field Poisson-Boltzmann (PB) theory within a cell model. This approach models a bulk system by a single macroion, together with counterions and salt ions, confined to a symmetrically shaped, electroneutral cell. While easing numerical solution of the nonlinear PB equation, the cell model neglects microion-induced interactions and correlations between macroions, precluding modelling of macroion ordering phenomena. An alternative approach, which avoids the artificial constraints of cell geometry, exploits the mapping of a macroion-microion mixture onto a one-component model of pseudo-macroions governed by effective interparticle interactions. In practice, effective-interaction models are usually based on linear-screening approximations, which can accurately describe strong nonlinear screening only by incorporating an effective (renormalized) macroion charge. Combining charge renormalization and linearized PB theories, in both the cell model and an effective-interaction (cell-free) model, we compute osmotic pressures of highly charged colloids and monovalent microions, in Donnan equilibrium with a salt reservoir, over a range of concentrations. By comparing predictions with primitive model simulation data for salt-free suspensions, and with predictions from nonlinear PB theory for salty suspensions, we chart the limits of both the cell model and linear-screening approximations in modelling bulk thermodynamic properties. Up to moderately strong electrostatic couplings, the cell model proves accurate for predicting osmotic pressures of deionized (counterion-dominated) suspensions. With increasing salt concentration, however, the relative contribution of macroion interactions to the osmotic pressure grows, leading predictions from the cell and effective-interaction models to deviate. No evidence is found for a liquid
Capozza, R.; Vanossi, A.; Benassi, A.; Tosatti, E.
2015-02-01
Electrical charging of parallel plates confining a model ionic liquid down to nanoscale distances yields a variety of charge-induced changes in the structural features of the confined film. That includes even-odd switching of the structural layering and charging-induced solidification and melting, with important changes of local ordering between and within layers, and of squeezout behavior. By means of molecular dynamics simulations, we explore this variety of phenomena in the simplest charged Lennard-Jones coarse-grained model including or excluding the effect a neutral tail giving an anisotropic shape to one of the model ions. Using these models and open conditions permitting the flow of ions in and out of the interplate gap, we simulate the liquid squeezout to obtain the distance dependent structure and forces between the plates during their adiabatic approach under load. Simulations at fixed applied force illustrate an effective electrical pumping of the ionic liquid, from a thick nearly solid film that withstands the interplate pressure for high plate charge to complete squeezout following melting near zero charge. Effective enthalpy curves obtained by integration of interplate forces versus distance show the local minima that correspond to layering and predict the switching between one minimum and another under squeezing and charging.
Thermal Models of the Niger Delta: Implications for Charge Modelling
There are generally three main sources of temperature data-BHT data from log headers, production temperature data, and continuo's temperature logs. Analysis of continuous temperature profiles of over 100 wells in the Niger Delta two main thermal models (single leg and dogleg) are defined with occasional occurrence of a modified dogleg model.The dogleg model is characterised by a shallow interval of low geothermal gradient (3.0.C/100m). This is characteristically developed onshore area is simple, requiring only consideration of heat transients, modelling in the onshore require modelling programmes with built in modules to handle convective heat flow dissipation in the shallow layer. Current work around methods would involve tweaking of thermal conductivity values to mimic the underlying heat flow process effects, or heat flow mapping above and below the depth of gradient change. These methods allow for more realistic thermal modelling, hydrocarbon type prediction, and also more accurate prediction of temperature prior to drilling and for reservoir rock properties. The regional distribution of the models also impact on regional hydrocarbon distribution pattern in the Niger Delta
Fernández, Ariel, E-mail: ariel@afinnovation.com [Argentine Institute of Mathematics (I. A. M.), National Research Council (CONICET), Buenos Aires 1083 (Argentina); Collegium Basilea – Institute for Advanced Study, Basel CH4053 (Switzerland)
2015-10-16
The spontaneous negative charging of aqueous nonpolar interfaces has eluded quantitative first-principle prediction, possibly because it steadfastly challenges the classical Debye dielectric picture. In this work we show that quantitative prediction requires a substantive revision of Debye's linear dielectric ansatz to incorporate an anomalous polarization component yielding electrostatic energy stored as interfacial tension and detailed enough to account for the differences in electronic structure between water and its ionized states. The minimization of this interfacial tension is due to a quantum effect resulting in the reduction in hydrogen-bond frustration that takes place upon hydroxide ion adsorption. The quantitative predictions are validated vis-à-vis measurements of the free energy change associated with hydroxide adsorption obtained using sum-frequency vibrational spectroscopy. - Highlights: • Spontaneous charging of aqueous nonpolar interfaces challenges Debye dielectrics. • A quantum non-Debye theory of interfacial tension is developed. • The minimization of the interfacial tension promotes hydroxide ion adsorption.
The spontaneous negative charging of aqueous nonpolar interfaces has eluded quantitative first-principle prediction, possibly because it steadfastly challenges the classical Debye dielectric picture. In this work we show that quantitative prediction requires a substantive revision of Debye's linear dielectric ansatz to incorporate an anomalous polarization component yielding electrostatic energy stored as interfacial tension and detailed enough to account for the differences in electronic structure between water and its ionized states. The minimization of this interfacial tension is due to a quantum effect resulting in the reduction in hydrogen-bond frustration that takes place upon hydroxide ion adsorption. The quantitative predictions are validated vis-à-vis measurements of the free energy change associated with hydroxide adsorption obtained using sum-frequency vibrational spectroscopy. - Highlights: • Spontaneous charging of aqueous nonpolar interfaces challenges Debye dielectrics. • A quantum non-Debye theory of interfacial tension is developed. • The minimization of the interfacial tension promotes hydroxide ion adsorption
Black Hole Evaporation in a Noncommutative Charged Vaidya Model
Sharif, M.; Javed, Wajiha
2012-01-01
The aim of this paper is to study the black hole evaporation and Hawking radiation for a noncommutative charged Vaidya black hole. For this purpose, we determine spherically symmetric charged Vaidya model and then formulate a noncommutative Reissner-Nordstr$\\ddot{o}$m-like solution of this model which leads to an exact $(t-r)$ dependent metric. The behavior of temporal component of this metric and the corresponding Hawking temperature is investigated. The results are shown in the form of grap...
Tight-binding modeling of charge migration in DNA devices
Cuniberti, G.; Macia, E.; Rodriguez, A.; R.A. Römer
2007-01-01
Long range charge transfer experiments in DNA oligomers and the subsequently measured -- and very diverse -- transport response of DNA wires in solid state experiments exemplifies the need for a thorough theoretical understanding of charge migration in DNA-based natural and artificial materials. Here we present a review of tight-binding models for DNA conduction which have the intrinsic merit of containing more structural information than plain rate-equation models while still retaining suffi...
Computer simulation study of water using a fluctuating charge model
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.
Placement error due to charging in EBL: experimental verification of a new correction model
Babin, Sergey; Borisov, Sergey; Kimura, Yasuki; Kono, Kenji; Militsin, Vladimir; Yamamoto, Ryuuji
2012-06-01
Placement error due to charging in electron beam lithography has been identified as the most important factor limiting placement accuracy in EBL, which is especially important in the fabrication of masks for double patterning. Published results from a few major companies demonstrated that the placement errors due to charging are far larger than 10 nm. Here, we will describe the results of predicting the charging placement error based on a significantly improved physical model. Specially designed patterns were used to characterize the details of the charging placement error. Reference marks were exposed before the exposure of the test pattern, during the exposure, and after the exposure was completed. The experimental results were used to calibrate the parameters of the physical model. Furthermore, the DISPLACE software was used to predict the placement error maps for other experiments. The results of the measurements and simulations are presented in this paper. The results produced by the software were in good agreement with the experimental measurements. When the amplitude and the direction of the placement error due to charging is predicted, it can be easily corrected using readily available software for mask data preparation, or directly in EBL writers.
Nonlinear chaotic model for predicting storm surges
M. Siek
2010-09-01
Full Text Available This paper addresses the use of the methods of nonlinear dynamics and chaos theory for building a predictive chaotic model from time series. The chaotic model predictions are made by the adaptive local models based on the dynamical neighbors found in the reconstructed phase space of the observables. We implemented the univariate and multivariate chaotic models with direct and multi-steps prediction techniques and optimized these models using an exhaustive search method. The built models were tested for predicting storm surge dynamics for different stormy conditions in the North Sea, and are compared to neural network models. The results show that the chaotic models can generally provide reliable and accurate short-term storm surge predictions.
Staying Power of Churn Prediction Models
Risselada, Hans; Verhoef, Peter C.; Bijmolt, Tammo H. A.
2010-01-01
In this paper, we study the staying power of various churn prediction models. Staying power is defined as the predictive performance of a model in a number of periods after the estimation period. We examine two methods, logit models and classification trees, both with and without applying a bagging
DETAILED MODELLING OF CHARGING BEHAVIOUR OF SMART SOLAR TANKS
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...... 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...... influenced by the mesh densities, the distribution of computational cells, the physical model and time steps used in the simulations. The findings of the investigations will be used as guidance for creation of CFD models for optimal design of smart solar tanks....
DETAILED MODELLING OF CHARGING BEHAVIOUR OF SMART SOLAR TANKS
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...... 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...... influenced by the mesh densities, the distribution of computational cells, the physical model and time steps used in the simulations. The findings of the investigations will be used as guidance for creation of CFD models for optimal design of smart solar tanks....
Dynamic battery cell model and state of charge estimation
Wijewardana, S.; Vepa, R.; Shaheed, M. H.
2016-03-01
Mathematical modelling and the dynamic simulation of battery storage systems can be challenging and demanding due to the nonlinear nature of the battery chemistry. This paper introduces a new dynamic battery model, with application to state of charge estimation, considering all possible aspects of environmental conditions and variables. The aim of this paper is to present a suitable convenient, generic dynamic representation of rechargeable battery dynamics that can be used to model any Lithium-ion rechargeable battery. The proposed representation is used to develop a dynamic model considering the thermal balance of heat generation mechanism of the battery cell and the ambient temperature effect including other variables such as storage effects, cyclic charging, battery internal resistance, state of charge etc. The results of the simulations have been used to study the characteristics of a Lithium-ion battery and the proposed battery model is shown to produce responses within 98% of known experimental measurements.
Discrete Element Modeling (DEM) of Triboelectrically Charged Particles: Revised Experiments
Hogue, Michael D.; Calle, Carlos I.; Curry, D. R.; Weitzman, P. S.
2008-01-01
In a previous work, the addition of basic screened Coulombic electrostatic forces to an existing commercial discrete element modeling (DEM) software was reported. Triboelectric experiments were performed to charge glass spheres rolling on inclined planes of various materials. Charge generation constants and the Q/m ratios for the test materials were calculated from the experimental data and compared to the simulation output of the DEM software. In this paper, we will discuss new values of the charge generation constants calculated from improved experimental procedures and data. Also, planned work to include dielectrophoretic, Van der Waals forces, and advanced mechanical forces into the software will be discussed.
Predictive Modelling and Time: An Experiment in Temporal Archaeological Predictive Models
David Ebert
2006-08-01
Full Text Available One of the most common criticisms of archaeological predictive modelling is that it fails to account for temporal or functional differences in sites. However, a practical solution to temporal or functional predictive modelling has proven to be elusive. This article discusses temporal predictive modelling, focusing on the difficulties of employing temporal variables, then introduces and tests a simple methodology for the implementation of temporal modelling. The temporal models thus created are then compared to a traditional predictive model.
Black hole evaporation in a noncommutative charged Vaidya model
Sharif, M., E-mail: msharif.math@pu.edu.pk; Javed, W. [University of the Punjab, Department of Mathematics (Pakistan)
2012-06-15
We study the black hole evaporation and Hawking radiation for a noncommutative charged Vaidya black hole. For this purpose, we determine a spherically symmetric charged Vaidya model and then formulate a noncommutative Reissner-Nordstroem-like solution of this model, which leads to an exact (t - r)-dependent metric. The behavior of the temporal component of this metric and the corresponding Hawking temperature are investigated. The results are shown in the form of graphs. Further, we examine the tunneling process of charged massive particles through the quantum horizon. We find that the tunneling amplitude is modified due to noncommutativity. Also, it turns out that the black hole evaporates completely in the limits of large time and horizon radius. The effect of charge is to reduce the temperature from a maximum value to zero. We note that the final stage of black hole evaporation is a naked singularity.
Black Hole Evaporation in a Noncommutative Charged Vaidya Model
Sharif, M
2012-01-01
The aim of this paper is to study the black hole evaporation and Hawking radiation for a noncommutative charged Vaidya black hole. For this purpose, we determine spherically symmetric charged Vaidya model and then formulate a noncommutative Reissner-Nordstr$\\ddot{o}$m-like solution of this model which leads to an exact $(t-r)$ dependent metric. The behavior of temporal component of this metric and the corresponding Hawking temperature is investigated. The results are shown in the form of graphs. Further, we examine the tunneling process of the charged massive particles through the quantum horizon. It is found that the tunneling amplitude is modified due to noncommutativity. Also, it turns out that black hole evaporates completely in the limits of large time and horizon radius. The effect of charge is to reduce the temperature from maximum value to zero. It is mentioned here that the final stage of black hole evaporation turns out to be a naked singularity.
Black hole evaporation in a noncommutative charged Vaidya model
Sharif, M.; Javed, W.
2012-06-01
We study the black hole evaporation and Hawking radiation for a noncommutative charged Vaidya black hole. For this purpose, we determine a spherically symmetric charged Vaidya model and then formulate a noncommutative Reissner-Nordström-like solution of this model, which leads to an exact ( t - r)-dependent metric. The behavior of the temporal component of this metric and the corresponding Hawking temperature are investigated. The results are shown in the form of graphs. Further, we examine the tunneling process of charged massive particles through the quantum horizon. We find that the tunneling amplitude is modified due to noncommutativity. Also, it turns out that the black hole evaporates completely in the limits of large time and horizon radius. The effect of charge is to reduce the temperature from a maximum value to zero. We note that the final stage of black hole evaporation is a naked singularity.
Black hole evaporation in a noncommutative charged Vaidya model
We study the black hole evaporation and Hawking radiation for a noncommutative charged Vaidya black hole. For this purpose, we determine a spherically symmetric charged Vaidya model and then formulate a noncommutative Reissner-Nordström-like solution of this model, which leads to an exact (t − r)-dependent metric. The behavior of the temporal component of this metric and the corresponding Hawking temperature are investigated. The results are shown in the form of graphs. Further, we examine the tunneling process of charged massive particles through the quantum horizon. We find that the tunneling amplitude is modified due to noncommutativity. Also, it turns out that the black hole evaporates completely in the limits of large time and horizon radius. The effect of charge is to reduce the temperature from a maximum value to zero. We note that the final stage of black hole evaporation is a naked singularity.
Lattice charge models and core level shifts in disordered alloys
Underwood, T. L.; Cole, R. J.
2013-10-01
Differences in core level binding energies between atoms belonging to the same chemical species can be related to differences in their intra- and extra-atomic charge distributions, and differences in how their core holes are screened. With this in mind, we consider the charge-excess functional model (CEFM) for net atomic charges in alloys (Bruno et al 2003 Phys. Rev. Lett. 91 166401). We begin by deriving the CEFM energy function in order to elucidate the approximations which underpin this model. We thereafter consider the particular case of the CEFM in which the strengths of the ‘local interactions’ within all atoms are the same. We show that for binary alloys the ground state charges of this model can be expressed in terms of charge transfer between all pairs of unlike atoms analogously to the linear charge model (Magri et al 1990 Phys. Rev. B 42 11388). Hence, the model considered is a generalization of the linear charge model for alloys containing more than two chemical species. We then determine the model’s unknown ‘geometric factors’ over a wide range of parameter space. These quantities are linked to the nature of charge screening in the model, and we illustrate that the screening becomes increasingly universal as the strength of the local interactions is increased. We then use the model to derive analytical expressions for various physical quantities, including the Madelung energy and the disorder broadening in the core level binding energies. These expressions are applied to ternary random alloys, for which it is shown that the Madelung energy and magnitude of disorder broadening are maximized at the composition at which the two species with the largest ‘electronegativity difference’ are equal, while the remaining species have a vanishing concentration. This result is somewhat counterintuitive with regards to the disorder broadening since it does not correspond to the composition with the highest entropy. Finally, the model is applied to Cu
How to Establish Clinical Prediction Models.
Lee, Yong Ho; Bang, Heejung; Kim, Dae Jung
2016-03-01
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. PMID:26996421
Accurate predictions for charged Higgs production: closing the $m_{H^{\\pm}}\\sim m_t$ window
Degrande, Celine; Hirschi, Valentin; Ubiali, Maria; Wiesemann, Marius; Zaro, Marco
2016-01-01
We present predictions for the total cross section for the production of a charged Higgs boson in a generic type-II two-Higgs-doublet model in the intermediate-mass range ($m_{H^{\\pm}}\\sim m_t$) at the LHC. Results are obtained at next-to-leading order (NLO) accuracy in QCD perturbation theory, by studying the full process $pp\\to H^\\pm W^\\mp b \\bar b$ in the complex-(top)-mass scheme with massive bottom quarks. Compared to lowest-order predictions, NLO corrections have a sizable impact: they increase the cross section by roughly 50% and reduce uncertainties due to scale variations by more than a factor of two. Our computation reliably interpolates between the low- and high-mass regime. Our results provide the first NLO prediction for charged Higgs production in the intermediate-mass range and therefore allow to have NLO accurate predictions in the full $m_{H^{\\pm}}$ range.
Charge State Evolution in the Solar Wind. III. Model Comparison with Observations
Landi, E.; Oran, R.; Lepri, S. T.; Zurbuchen, T. H.; Fisk, L. A.; van der Holst, B.
2014-08-01
We test three theoretical models of the fast solar wind with a set of remote sensing observations and in-situ measurements taken during the minimum of solar cycle 23. First, the model electron density and temperature are compared to SOHO/SUMER spectroscopic measurements. Second, the model electron density, temperature, and wind speed are used to predict the charge state evolution of the wind plasma from the source regions to the freeze-in point. Frozen-in charge states are compared with Ulysses/SWICS measurements at 1 AU, while charge states close to the Sun are combined with the CHIANTI spectral code to calculate the intensities of selected spectral lines, to be compared with SOHO/SUMER observations in the north polar coronal hole. We find that none of the theoretical models are able to completely reproduce all observations; namely, all of them underestimate the charge state distribution of the solar wind everywhere, although the levels of disagreement vary from model to model. We discuss possible causes of the disagreement, namely, uncertainties in the calculation of the charge state evolution and of line intensities, in the atomic data, and in the assumptions on the wind plasma conditions. Last, we discuss the scenario where the wind is accelerated from a region located in the solar corona rather than in the chromosphere as assumed in the three theoretical models, and find that a wind originating from the corona is in much closer agreement with observations.
Charge state evolution in the solar wind. III. Model comparison with observations
Landi, E.; Oran, R.; Lepri, S. T.; Zurbuchen, T. H.; Fisk, L. A.; Van der Holst, B. [Department of Atmospheric, Oceanic and Space Sciences, University of Michigan, Ann Arbor, MI 48109 (United States)
2014-08-01
We test three theoretical models of the fast solar wind with a set of remote sensing observations and in-situ measurements taken during the minimum of solar cycle 23. First, the model electron density and temperature are compared to SOHO/SUMER spectroscopic measurements. Second, the model electron density, temperature, and wind speed are used to predict the charge state evolution of the wind plasma from the source regions to the freeze-in point. Frozen-in charge states are compared with Ulysses/SWICS measurements at 1 AU, while charge states close to the Sun are combined with the CHIANTI spectral code to calculate the intensities of selected spectral lines, to be compared with SOHO/SUMER observations in the north polar coronal hole. We find that none of the theoretical models are able to completely reproduce all observations; namely, all of them underestimate the charge state distribution of the solar wind everywhere, although the levels of disagreement vary from model to model. We discuss possible causes of the disagreement, namely, uncertainties in the calculation of the charge state evolution and of line intensities, in the atomic data, and in the assumptions on the wind plasma conditions. Last, we discuss the scenario where the wind is accelerated from a region located in the solar corona rather than in the chromosphere as assumed in the three theoretical models, and find that a wind originating from the corona is in much closer agreement with observations.
DETAILED MODELLING OF CHARGING BEHAVIOUR OF SMART SOLAR TANKS
Fan, Jianhua; Andersen, Elsa; Furbo, Simon; Perers, Bengt
2010-01-01
The charging behaviour of smart solar tanks for solar combisystems for one-family houses is investigated with detailed Computational Fluid Dynamics (CFD) modelling and Particle Image Velocimetry (PIV) measurements. The smart solar tank can be charged with a variable auxiliary volume fitted to the expected future energy demand. Therefore the heat loss from the tank is decreased and the thermal performance of the solar heating system is increased compared to a traditional system with a fixed au...
Image Charge Undulator: Theoretical Model and Technical Issues
A new device, an image charge undulator, has been proposed recently [1] to utilize this mechanism for generating coherent hard radiation. We demonstrate physics principle of this device by a 2D model of a uniform sheet beam. The transverse image charge wakefields, synchrotron radiation FR-equency and coherent radiation gain length are presented. We discuss a proof-of-principle experiment that takes into consideration such technical issues as grating fabrication, flat beams and beam alignment
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
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.
Return Predictability, Model Uncertainty, and Robust Investment
Lukas, Manuel
2013-01-01
Stock return predictability is subject to great uncertainty. In this paper we usethe model confidence set approach to quantify uncertainty about expected utilityfrom investment, accounting for potential return predictability. For monthly USdata and six representative return prediction models, we find that confidence setsare very wide, change significantly with the predictor variables, and frequentlyinclude expected utilities for which the investor prefers not to invest. The lattermotivates a ...
Sparse preconditioning for model predictive control
Knyazev, Andrew; Malyshev, Alexander,
2015-01-01
We propose fast O(N) preconditioning, where N is the number of gridpoints on the prediction horizon, for iterative solution of (non)-linear systems appearing in model predictive control methods such as forward-difference Newton-Krylov methods. The Continuation/GMRES method for nonlinear model predictive control, suggested by T. Ohtsuka in 2004, is a specific application of the Newton-Krylov method, which uses the GMRES iterative algorithm to solve a forward difference approximation of the opt...
Arbabi, Vahid; Pouran, Behdad; Weinans, Harrie; Zadpoor, Amir A
2016-06-14
Charged and uncharged solutes penetrate through cartilage to maintain the metabolic function of chondrocytes and to possibly restore or further breakdown the cartilage tissue in different stages of osteoarthritis. In this study the transport of charged solutes across the various zones of cartilage was quantified, taken into account the physicochemical interactions between the solute and the cartilage constituents. A multiphasic finite-bath finite element (FE) model was developed to simulate equine cartilage diffusion experiments that used a negatively charged contrast agent (ioxaglate) in combination with serial micro-computed tomography (micro-CT) to measure the diffusion. By comparing the FE model with the experimental data both the diffusion coefficient of ioxaglate and the fixed charge density (FCD) were obtained. In the multiphasic model, cartilage was divided into multiple (three) zones to help understand how diffusion coefficient and FCD vary across cartilage thickness. The direct effects of charged solute-FCD interaction on diffusion were investigated by comparing the diffusion coefficients derived from the multiphasic and biphasic-solute models. We found a relationship between the FCD obtained by the multiphasic model and ioxaglate partitioning obtained from micro-CT experiments. Using our multi-zone multiphasic model, diffusion coefficient of the superficial zone was up to ten-fold higher than that of the middle zone, while the FCD of the middle zone was up to almost two-fold higher than that of the superficial zone. In conclusion, the developed finite-bath multiphasic model provides us with a non-destructive method by which we could obtain both diffusion coefficient and FCD of different cartilage zones. The outcomes of the current work will also help understand how charge of the bath affects the diffusion of a charged molecule and also predict the diffusion behavior of a charged solute across articular cartilage. PMID:27033729
Meta-analysis of clinical prediction models
Debray, T.P.A.
2013-01-01
The past decades there has been a clear shift from implicit to explicit diagnosis and prognosis. This includes appreciation of clinical -diagnostic and prognostic- prediction models, which is likely to increase with the introduction of fully computerized patient records. Prediction models aim to pro
Unreachable Setpoints in Model Predictive Control
Rawlings, James B.; Bonné, Dennis; Jørgensen, John Bagterp;
2008-01-01
In this work, a new model predictive controller is developed that handles unreachable setpoints better than traditional model predictive control methods. The new controller induces an interesting fast/slow asymmetry in the tracking response of the system. Nominal asymptotic stability of the optimal...
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.
Modeling uncertainty: Predictive accuracy as a proxy for predictive confidence
Rich, Robert; Tracy, Joseph
2003-01-01
This paper evaluates current strategies for the empirical modeling of forecast behavior. In particular, we focus on the reliability of using proxies from time series models of heteroskedasticity to describe changes in predictive confidence. We address this issue by examining the relationship between ex post forecast errors and ex ante measures of forecast uncertainty from data on inflation forecasts from the Survey of Professional Forecasters. The results provide little evidence of a strong l...
A space charge model for electrophonic bursters
Beech, M
1999-01-01
The sounds accompanying electrophonic burster meteors are characteristically described as being akin to short duration ``pops'' and staccato--like ``clicks''. As a phenomenon distinct from the enduring electrophonic sounds that occasionally accompany the passage and ablation of large meteoroids in the Earth's lower atmosphere, the bursters have proved stubbornly difficult to explain. A straightforward calculation demonstrates that in contradistinction to the enduring electrophonic sounds, the electrophonic bursters are not generated as a consequence of interactions between the meteoroid ablation plasma and the Earth's geomagnetic field. Here we present a novel and hitherto unrecorded model for the generation of short--duration pulses in an observer's local electrostatic field. Our model is developed according to the generation of a strong electric field across a shock wave propagating in a plasma. In this sense, the electrophonic bursters are associated with the catastrophic disruption of large meteoroids in ...
Prediction of Physical Properties of Nanofiltration Membranes for Neutral and Charged Solutes
Two commercial nanofiltration (NF) membranes viz., NF 300 MWCO and NF 250 MWCO were used for neutral and charged solute species viz., glucose, sodium chloride and magnesium chloride to investigate their rejection rates using Donnan steric pore model (DSPM) and DSPM-dielectric exc...
A zero dimensional model of lithium-sulfur batteries during charge and discharge.
Marinescu, Monica; Zhang, Teng; Offer, Gregory J
2016-01-01
Lithium-sulfur cells present an attractive alternative to Li-ion batteries due to their large energy density, safety, and possible low cost. Their successful commercialisation is dependent on improving their performance, but also on acquiring sufficient understanding of the underlying mechanisms to allow for the development of predictive models for operational cells. To address the latter, we present a zero dimensional model that predicts many of the features observed in the behaviour of a lithium-sulfur cell during charge and discharge. The model accounts for two electrochemical reactions via the Nernst formulation, power limitations through Butler-Volmer kinetics, and precipitation/dissolution of one species, including nucleation. It is shown that the flat shape of the low voltage plateau typical of the lithium-sulfur cell discharge is caused by precipitation. During charge, it is predicted that the dissolution can act as a bottleneck, because for large enough currents the amount that dissolves becomes limited. This results in reduced charge capacity and an earlier onset of the high plateau reaction, such that the two voltage plateaus merge. By including these effects, the model improves on the existing zero dimensional models, while requiring considerably fewer input parameters and computational resources than one dimensional models. The model also predicts that, due to precipitation, the customary way of experimentally obtaining the open circuit voltage from a low rate discharge might not be suitable for lithium-sulfur. This model can provide the basis for mechanistic studies, identification of dominant effects in a real cell, predictions of operational behaviour under realistic loads, and control algorithms for applications. PMID:26618508
Modeling of the charge acceptance of lead-acid batteries
Thele, M.; Schiffer, J.; Sauer, D.U. [Electrochemical Energy Conversion and Storage Systems Group, Institute for Power Electronics and Electrical Drives (ISEA), RWTH Aachen University, Jaegerstrasse 17-19, D-52066 Aachen (Germany); Karden, E.; Surewaard, E. [Ford Research Center Aachen, Aachen (Germany)
2007-05-25
This paper presents a model for flooded and VRLA batteries that is parameterized by impedance spectroscopy and includes the overcharging effects to allow charge-acceptance simulations (e.g. for regenerative-braking drive-cycle profiles). The full dynamic behavior and the short-term charge/discharge history is taken into account. This is achieved by a detailed modeling of the sulfate crystal growth and modeling of the internal gas recombination cycle. The model is applicable in the full realistic temperature and current range of automotive applications. For model validation, several load profiles (covering the dynamics and the current range appearing in electrically assisted or hybrid cars) are examined and the charge-acceptance limiting effects are elaborately discussed. The validation measurements have been performed for different types of lead-acid batteries (flooded and VRLA). The model is therefore an important tool for the development of automotive power nets, but it also allows to analyze different charging strategies and energy gains which can be achieved during regenerative-braking. (author)
Combinatorial Modelling and Learning with Prediction Markets
Hu, Jinli
2012-01-01
Combining models in appropriate ways to achieve high performance is commonly seen in machine learning fields today. Although a large amount of combinatorial models have been created, little attention is drawn to the commons in different models and their connections. A general modelling technique is thus worth studying to understand model combination deeply and shed light on creating new models. Prediction markets show a promise of becoming such a generic, flexible combinatorial model. By reviewing on several popular combinatorial models and prediction market models, this paper aims to show how the market models can generalise different combinatorial stuctures and how they implement these popular combinatorial models in specific conditions. Besides, we will see among different market models, Storkey's \\emph{Machine Learning Markets} provide more fundamental, generic modelling mechanisms than the others, and it has a significant appeal for both theoretical study and application.
Predicting leptonic CP phase by considering deviations in charged lepton and neutrino sectors
Recently, the reactor mixing angle θ13 has been measured precisely by Daya Bay, RENO, and T2K experiments with a moderately large value. However, the standard form of neutrino mixing patterns such as bimaximal, tri-bimaximal, golden ratio of types A and B, hexagonal, etc., which are based on certain flavor symmetries, predict vanishing θ13. Using the fact that the neutrino mixing matrix can be represented as VPMNS=Ul†UνPν, where Ul and Uν result from the diagonalization of the charged lepton and neutrino mass matrices and Pν is a diagonal matrix containing Majorana phases, we explore the possibility of accounting for the large reactor mixing angle by considering deviations both in the charged lepton and neutrino sector. In the charged lepton sector we consider the deviation as an additional rotation in the (12) and (13) planes, whereas in the neutrino sector we consider deviations to various neutrino mixing patterns through (13) and (23) rotations. We find that with the inclusion of these deviations it is possible to accommodate the observed large reactor mixing angle θ13, and one can also obtain limits on the charge-conjugation parity-violating Dirac phaseδCP and Jarlskog invariant JCP for most of the cases. We then explore whether our findings can be tested in the currently running NuMI Off-axis ve Appearance experiment with three years of data taking in neutrino mode followed by three years with the anti-neutrino mode
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...
CERN PS Booster space charge simulations with a realistic model for alignement and field errors
Forte, V; McAteer, M
2014-01-01
The CERN PS Booster is one of the machines of the LHC injector chain which will be upgraded within the LIU (LHC Injectors upgrade) project. The injection energy of the PSB will be increased to 160MeV in order to mitigate direct space charge effects, considered to be the main performance limitation, thus allowing to double the brightness for the LHC beams. In order to better predict the gain to be expected, space charge simulations are being carried out. Efforts to establish a realistic modeling of field and alignment errors aim at extending the basic model of the machine towards a more realistic one. Simulations of beam dynamics with strong direct space charge and realistic errors are presented and analysed in this paper.
Disease Models for Event Prediction
Corley, Courtney D.; Pullum, Laura
2013-01-01
Objective The objective of this manuscript is to present a systematic review of biosurveillance models that operate on select agents and can forecast the occurrence of a disease event. Introduction One of the primary goals of this research was to characterize the viability of biosurveillance models to provide operationally relevant information to decision makers, in order to identify areas for future research. Two critical characteristics differentiate this work from other infectious disease ...
Energy based prediction models for building acoustics
Brunskog, Jonas
2012-01-01
In order to reach robust and simplified yet accurate prediction models, energy based principle are commonly used in many fields of acoustics, especially in building acoustics. This includes simple energy flow models, the framework of statistical energy analysis (SEA) as well as more elaborated...... principles as, e.g., wave intensity analysis (WIA). The European standards for building acoustic predictions, the EN 12354 series, are based on energy flow and SEA principles. In the present paper, different energy based prediction models are discussed and critically reviewed. Special attention is placed on...
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.
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...
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.
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.
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.
Optimal Prediction in Loglinear Models
K.J. van Garderen
2001-01-01
This paper introduces a Laplace inversion technique for deriving unbiased predictors in exponential families. This general technique is applied to derive the exact optimal unbiased predictor in loglinear models with Gaussian disturbances under quadratic loss. An exact unbiased estimator for its vari
Predictive Modeling in Adult Education
Lindner, Charles L.
2011-01-01
The current economic crisis, a growing workforce, the increasing lifespan of workers, and demanding, complex jobs have made organizations highly selective in employee recruitment and retention. It is therefore important, to the adult educator, to develop models of learning that better prepare adult learners for the workplace. The purpose of…
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.
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.
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.
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.
Modeling and Prediction Using Stochastic Differential Equations
Juhl, Rune; Møller, Jan Kloppenborg; Jørgensen, John Bagterp;
2016-01-01
Pharmacokinetic/pharmakodynamic (PK/PD) modeling for a single subject is most often performed using nonlinear models based on deterministic ordinary differential equations (ODEs), and the variation between subjects in a population of subjects is described using a population (mixed effects) setup...... deterministic and can predict the future perfectly. A more realistic approach would be to allow for randomness in the model due to e.g., the model be too simple or errors in input. We describe a modeling and prediction setup which better reflects reality and suggests stochastic differential equations (SDEs) for...
A minimal and predictive $T_7$ lepton flavor 331 model
Hernández, A E Cárcamo
2015-01-01
We present a model based on the $SU(3)_{C}\\otimes SU(3)_{L}\\otimes U(1)_{X}$ gauge group having an extra $T_{7}\\otimes Z_{3}\\otimes Z_{14}$ flavor group, where the light active neutrino masses arise via double seesaw mechanism and the observed charged lepton mass hierarchy is a consequence of the $Z_{14}$ symmetry breaking at very high energy. In our minimal and predictive $T_7$ lepton flavor 331 model, the spectrum of neutrinos includes very light active neutrinos and heavy and very heavy sterile neutrinos. The obtained neutrino mixing parameters and neutrino mass squared splittings are compatible with the neutrino oscillation experimental data, for both normal and inverted hierarchies. The model predicts CP conservation in neutrino oscillations.
Modeling charged defects inside density functional theory band gaps
Density functional theory (DFT) has emerged as an important tool to probe microscopic behavior in materials. The fundamental band gap defines the energy scale for charge transition energy levels of point defects in ionic and covalent materials. The eigenvalue gap between occupied and unoccupied states in conventional DFT, the Kohn–Sham gap, is often half or less of the experimental band gap, seemingly precluding quantitative studies of charged defects. Applying explicit and rigorous control of charge boundary conditions in supercells, we find that calculations of defect energy levels derived from total energy differences give accurate predictions of charge transition energy levels in Si and GaAs, unhampered by a band gap problem. The GaAs system provides a good theoretical laboratory for investigating band gap effects in defect level calculations: depending on the functional and pseudopotential, the Kohn–Sham gap can be as large as 1.1 eV or as small as 0.1 eV. We find that the effective defect band gap, the computed range in defect levels, is mostly insensitive to the Kohn–Sham gap, demonstrating it is often possible to use conventional DFT for quantitative studies of defect chemistry governing interesting materials behavior in semiconductors and oxides despite a band gap problem
Impact of modellers' decisions on hydrological a priori predictions
H. M. Holländer
2013-07-01
Full Text Available The purpose of this paper is to stimulate a re-thinking of how we, the catchment hydrologists, could become reliable forecasters. A group of catchment modellers predicted the hydrological response of a man-made 6 ha catchment in its initial phase (Chicken Creek without having access to the observed records. They used conceptually different model families. Their modelling experience differed largely. The prediction exercise was organized in three steps: (1 for the 1st prediction modellers received a basic data set describing the internal structure of the catchment (somewhat more complete than usually available to a priori predictions in ungauged catchments. They did not obtain time series of stream flow, soil moisture or groundwater response. (2 Before the 2nd improved prediction they inspected the catchment on-site and attended a workshop where the modellers presented and discussed their first attempts. (3 For their improved 3rd prediction they were offered additional data by charging them pro forma with the costs for obtaining this additional information. Holländer et al. (2009 discussed the range of predictions obtained in step 1. Here, we detail the modeller's decisions in accounting for the various processes based on what they learned during the field visit (step 2 and add the final outcome of step 3 when the modellers made use of additional data. We document the prediction progress as well as the learning process resulting from the availability of added information. For the 2nd and 3rd step, the progress in prediction quality could be evaluated in relation to individual modelling experience and costs of added information. We learned (i that soft information such as the modeller's system understanding is as important as the model itself (hard information, (ii that the sequence of modelling steps matters (field visit, interactions between differently experienced experts, choice of model, selection of available data, and methods for parameter
DC Motor Control Predictive Models
Ravinesh Singh; Godfrey C. Onwubolu; Krishnileshwar Singh; Ritnesh Ram
2006-01-01
DC motor speed and position controls are fundamental in vehicles in general and robotics in particular. This study presents a mathematical model for correlating the interactions of some DC motor control parameters such as duty cycle, terminal voltage, frequency and load on some responses such as output current, voltage and speed by means of response surface methodology. For this exercise, a five-level full factorial design was chosen for experimentation using a peripheral interface controller...
Universal Finite Size Corrections and the Central Charge in Non-solvable Ising Models
Giuliani, Alessandro; Mastropietro, Vieri
2013-01-01
We investigate a non solvable two-dimensional ferromagnetic Ising model with nearest neighbor plus weak finite range interactions of strength \\lambda. We rigorously establish one of the predictions of Conformal Field Theory (CFT), namely the fact that at the critical temperature the finite size corrections to the free energy are universal, in the sense that they are exactly independent of the interaction. The corresponding central charge, defined in terms of the coefficient of the first suble...
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)
System Component Modelling of Electric Vehicles and Charging Infrastructure
Tsakmakis, Emanuel
2012-01-01
The objective of this research is to develop a model for the electrical components that are involved in charging and discharging of an electric vehicle (EV). This will enable testing differ-ent energy management strategies that improve energy efficiency, battery lifetime, and ener-gy availability. Furthermore, the model will enable the investigation of vehicle to grid (V2G), thermal preconditioning of vehicles, and an economic analysis and optimization. In order to achieve the above goals,...
A Unified Channel Charges Expression for Analytic MOSFET Modeling
Hugues Murray; Patrick Martin
2012-01-01
Based on a 1D Poissons equation resolution, we present an analytic model of inversion charges allowing calculation of the drain current and transconductance in the Metal Oxide Semiconductor Field Effect Transistor. The drain current and transconductance are described by analytical functions including mobility corrections and short channel effects (CLM, DIBL). The comparison with the Pao-Sah integral shows excellent accuracy of the model in all inversion modes from strong to weak inversion in ...
Models for Energy and Charge Transport and Storage in Biomolecules
Mingaleev, S. F.; Christiansen, P. L.; Gaididei, Yu. B.; M. Johansson; Rasmussen, K.Ø.
1999-01-01
Two models for energy and charge transport and storage in biomolecules are considered. A model based on the discrete nonlinear Schrodinger equation with long-range dispersive interactions (LRI's) between base pairs of DNA is offered for the description of nonlinear dynamics of the DNA molecule. We show that LRI's are responsible for the existence of an interval of bistability where two stable stationary states, a narrow, pinned state and a broad, mobile state, coexist at each value of the tot...
Equivalency and unbiasedness of grey prediction models
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.
Lepton Flavor Violation in Predictive SUSY-GUT Models
Albright, Carl H.; /Northern Illinois U. /Fermilab; Chen, Mu-Chun; /UC, Irvine
2008-02-01
There have been many theoretical models constructed which aim to explain the neutrino masses and mixing patterns. While many of the models will be eliminated once more accurate determinations of the mixing parameters, especially sin{sup 2} 2{theta}{sub 13}, are obtained, charged lepton flavor violation (LFV) experiments are able to differentiate even further among the models. In this paper, they investigate various rare LFV processes, such as {ell}{sub i} {yields} {ell}{sub j} + {gamma} and {mu} - e conversion, in five predictive SUSY SO(10) models and their allowed soft SUSY breaking parameter space in the constrained minimal SUSY standard model (CMSSM). Utilizing the WMAP dark matter constraints, they obtain lower bounds on the branching ratios of these rare processes and find that at least three of the five models they consider give rise to predictions for {mu} {yields} e + {gamma} that will be tested by the MEG collaboration at PSI. in addition, the next generation {mu} - e conversion experiment has sensitivity to the predictions of all five models, making it an even more robust way to test these models. While generic studies have emphasized the dependence of the branching ratios of these rare processes on the reactor neutrino angle, {theta}{sub 13}, and the mass of the heaviest right-handed neutrino, M{sub 3}, they find very massive M{sub 3} is more significant than large {theta}{sub 13} in leading to branching ratios near to the present upper limits.
Mathematical modeling to predict residential solid waste generation
One of the challenges faced by waste management authorities is determining the amount of waste generated by households in order to establish waste management systems, as well as trying to charge rates compatible with the principle applied worldwide, and design a fair payment system for households according to the amount of residential solid waste (RSW) they generate. The goal of this research work was to establish mathematical models that correlate the generation of RSW per capita to the following variables: education, income per household, and number of residents. This work was based on data from a study on generation, quantification and composition of residential waste in a Mexican city in three stages. In order to define prediction models, five variables were identified and included in the model. For each waste sampling stage a different mathematical model was developed, in order to find the model that showed the best linear relation to predict residential solid waste generation. Later on, models to explore the combination of included variables and select those which showed a higher R2 were established. The tests applied were normality, multicolinearity and heteroskedasticity. Another model, formulated with four variables, was generated and the Durban-Watson test was applied to it. Finally, a general mathematical model is proposed to predict residential waste generation, which accounts for 51% of the total
A space charge compensation model for positive DC ion beams
In this paper, we revisit and extend a formula to predict the compensation of space charge in positive DC ion beams of non-relativistic energy, as they are for example found in the injector beam lines of heavy ion accelerator facilities.The original formula was presented in 1975 by Igor Gabovich et al. and takes into account the de-compensation through Coulomb collisions of the primary beam ions and the compensating electrons. We extend its usability to arbitrary (positive) charge states of the ions and non-quasineutral beams.The resulting formula compares well with measurements using a retarding field analyzer and a multi-species generalization of it was incorporated into beam transport simulations using the particle-in-cell code WARP
Return Predictability, Model Uncertainty, and Robust Investment
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...... find that confidence sets are very wide, change significantly with the predictor variables, and frequently include expected utilities for which the investor prefers not to invest. The latter motivates a robust investment strategy maximizing the minimal element of the confidence set. The robust investor...
Predictive technology model for robust nanoelectronic design
Cao, Yu
2011-01-01
Predictive Technology Model for Robust Nanoelectronic Design explains many of the technical mysteries behind the Predictive Technology Model (PTM) that has been adopted worldwide in explorative design research. Through physical derivation and technology extrapolation, PTM is the de-factor device model used in electronic design. This work explains the systematic model development and provides a guide to robust design practice in the presence of variability and reliability issues. Having interacted with multiple leading semiconductor companies and university research teams, the author brings a s
Accuracy assessment of landslide prediction models
The increasing population and expansion of settlements over hilly areas has greatly increased the impact of natural disasters such as landslide. Therefore, it is important to developed models which could accurately predict landslide hazard zones. Over the years, various techniques and models have been developed to predict landslide hazard zones. The aim of this paper is to access the accuracy of landslide prediction models developed by the authors. The methodology involved the selection of study area, data acquisition, data processing and model development and also data analysis. The development of these models are based on nine different landslide inducing parameters i.e. slope, land use, lithology, soil properties, geomorphology, flow accumulation, aspect, proximity to river and proximity to road. Rank sum, rating, pairwise comparison and AHP techniques are used to determine the weights for each of the parameters used. Four (4) different models which consider different parameter combinations are developed by the authors. Results obtained are compared to landslide history and accuracies for Model 1, Model 2, Model 3 and Model 4 are 66.7, 66.7%, 60% and 22.9% respectively. From the results, rank sum, rating and pairwise comparison can be useful techniques to predict landslide hazard zones
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.
Predicting leptonic CP phase by considering deviations in charged lepton and neutrino sectors
Sruthilaya, M.; Soumya, C.; Deepthi, K. N.; Mohanta, R.
2015-08-01
Recently, the reactor mixing angle {θ }13 has been measured precisely by Daya Bay, RENO, and T2K experiments with a moderately large value. However, the standard form of neutrino mixing patterns such as bimaximal, tri-bimaximal, golden ratio of types A and B, hexagonal, etc., which are based on certain flavor symmetries, predict vanishing {θ }13. Using the fact that the neutrino mixing matrix can be represented as {V}{PMNS}={U}l\\dagger {U}ν {P}ν , where Ul and {U}ν result from the diagonalization of the charged lepton and neutrino mass matrices and {P}ν is a diagonal matrix containing Majorana phases, we explore the possibility of accounting for the large reactor mixing angle by considering deviations both in the charged lepton and neutrino sector. In the charged lepton sector we consider the deviation as an additional rotation in the (12) and (13) planes, whereas in the neutrino sector we consider deviations to various neutrino mixing patterns through (13) and (23) rotations. We find that with the inclusion of these deviations it is possible to accommodate the observed large reactor mixing angle {θ }13, and one can also obtain limits on the charge-conjugation parity-violating Dirac phase{δ }{CP} and Jarlskog invariant JCP for most of the cases. We then explore whether our findings can be tested in the currently running NuMI Off-axis ve Appearance experiment with three years of data taking in neutrino mode followed by three years with the anti-neutrino mode.
Prediction of blast-induced air overpressure: a hybrid AI-based predictive model.
Jahed Armaghani, Danial; Hajihassani, Mohsen; Marto, Aminaton; Shirani Faradonbeh, Roohollah; Mohamad, Edy Tonnizam
2015-11-01
Blast operations in the vicinity of residential areas usually produce significant environmental problems which may cause severe damage to the nearby areas. Blast-induced air overpressure (AOp) is one of the most important environmental impacts of blast operations which needs to be predicted to minimize the potential risk of damage. This paper presents an artificial neural network (ANN) optimized by the imperialist competitive algorithm (ICA) for the prediction of AOp induced by quarry blasting. For this purpose, 95 blasting operations were precisely monitored in a granite quarry site in Malaysia and AOp values were recorded in each operation. Furthermore, the most influential parameters on AOp, including the maximum charge per delay and the distance between the blast-face and monitoring point, were measured and used to train the ICA-ANN model. Based on the generalized predictor equation and considering the measured data from the granite quarry site, a new empirical equation was developed to predict AOp. For comparison purposes, conventional ANN models were developed and compared with the ICA-ANN results. The results demonstrated that the proposed ICA-ANN model is able to predict blast-induced AOp more accurately than other presented techniques. PMID:26433903
Hu Bo; Huang Shi-Hua; Wu Feng-Min
2013-01-01
A model based on analysis of the self-consistent Poisson-Schrodinger equation is proposed to investigate the tunneling current of electrons in the inversion layer of a p-type metal-oxide-semiconductor (MOS) structure.In this model,the influences of interface trap charge (ITC) at the Si-SiO2 interface and fixed oxide charge (FOC) in the oxide region are taken into account,and one-band effective mass approximation is used.The tunneling probability is obtained by employing the transfer matrix method.Further,the effects of in-plane momentum on the quantization in the electron motion perpendicular to the Si-SiO2 interface of a MOS device are investigated.Theoretical simulation results indicate that both ITC and FOC have great influence on the tunneling current through a MOS structure when their densities are larger than 1012 cm-2,which results from the great change of bound electrons near the Si-SiO2 interface and the oxide region.Therefore,for real ultrathin MOS structures with ITC and FOC,this model can give a more accurate description for the tunneling current in the inversion layer.
Prediction of PARP Inhibition with Proteochemometric Modelling and Conformal Prediction.
Cortés-Ciriano, Isidro; Bender, Andreas; Malliavin, Thérèse
2015-06-01
Poly(ADP-ribose) polymerases (PARPs) play a key role in DNA damage repair. PARP inhibitors act as chemo- and radio- sensitizers and thus potentiate the cytotoxicity of DNA damaging agents. Although PARP inhibitors are currently investigated as chemotherapeutic agents, their cross-reactivity with other members of the PARP family remains unclear. Here, we apply Proteochemometric Modelling (PCM) to model the activity of 181 compounds on 12 human PARPs. We demonstrate that PCM (R0 (2) test =0.65-0.69; RMSEtest =0.95-1.01 °C) displays higher performance on the test set (interpolation) than Family QSAR and Family QSAM (Tukey's HSD, α 0.05), and outperforms Inductive Transfer knowledge among targets (Tukey's HSD, α 0.05). We benchmark the predictive signal of 8 amino acid and 11 full-protein sequence descriptors, obtaining that all of them (except for SOCN) perform at the same level of statistical significance (Tukey's HSD, α 0.05). The extrapolation power of PCM to new compounds (RMSE=1.02±0.80 °C) and targets (RMSE=1.03±0.50 °C) is comparable to interpolation, although the extrapolation ability is not uniform across the chemical and the target space. For this reason, we also provide confidence intervals calculated with conformal prediction. In addition, we present the R package conformal, which permits the calculation of confidence intervals for regression and classification caret models. PMID:27490382
Single Production of Doubly Charged Higgs Boson via e7 Collision in Higgs Triplet Model
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.
Mathematical model for predicting human vertebral fracture
Benedict, J. V.
1973-01-01
Mathematical model has been constructed to predict dynamic response of tapered, curved beam columns in as much as human spine closely resembles this form. Model takes into consideration effects of impact force, mass distribution, and material properties. Solutions were verified by dynamic tests on curved, tapered, elastic polyethylene beam.
Predictions of nuclear masses in different models
The modern version of the liquid-drop model is compared to the macroscopic Thomas-Fermi (TF) energy and the macroscopic part of the binding energy evaluated within the Hartree-Fock-Bogoliubov theory with the Gogny force and the relativistic mean field theory. The limits of nuclear stability predicted by these models are discussed. (author)
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...
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.
Charge distribution and radii in clusters from nuclear pasta models
We study the consistency of the description of charge distributions and radii of nuclear clusters obtained with semiclassical nuclear pasta models. These nuclei are expected to exist in the low density outer crust of neutron stars. Properties of the arising clusterized nucleon matter can be compared to realistic nuclear properties as experimentally extracted on earth. We focus on non iso-symmetric light clusters with nucleon number 8 ≤ A ≤ 30 and use Monte Carlo many-body techniques. We simulate isotopic chains for a set of selected nuclei using a model Hamiltonian consisting of the usual kinetic term, hadronic nucleon nucleon (NN), Coulomb and an effective density dependent Pauli potential. It is shown that for neutron rich (deficient) clusters neutron (proton) skins develop. Different (matter, neutron, proton, electric charge) radii are computed for this set of non iso-symmetric nuclei. Nuclear binding energies are also analyzed in the isotopic chains. (author)
A Physics-Based Charge-Control Model for InP DHBT Including Current-Blocking Effect
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.
Charged Higgs pair production at the LHC as a probe of the top-seesaw assisted technicolor model
Liu, Guo-Li; Zhou, Ping; Guo, Xiao-Fei; Wu, Kun; Jiang, Ji
2016-07-01
The top-seesaw assisted technicolor (TC) model, which was proposed recently to accommodate the 126 GeV Higgs mass discovered by the Large Hadron Colliders (LHC), predicts light and heavy charged Higgs bosons in addition to the neutral Higgses. In this paper, we will study the pair productions of the charged Higgs, proceeding through gluon-gluon fusion and quark-antiquark annihilation, at the LHC in the frame of the top-seesaw assisted TC model. We find that in a large part of parameter space the production cross-sections of the light charged Higgs pair at the LHC can be quite large compared with the low standard model backgrounds, while it is impossible for the pair production of the heavy ones to be detected with the strong final mass suppression. Therefore, the light charged Higgs pair production may be served as a probe of this new TC model at the LHC.
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.
Efficient particle continuation model predictive control
Knyazev, Andrew; Malyshev, Alexander,
2015-01-01
Continuation model predictive control (MPC), introduced by T. Ohtsuka in 2004, uses Krylov-Newton approaches to solve MPC optimization and is suitable for nonlinear and minimum time problems. We suggest particle continuation MPC in the case, where the system dynamics or constraints can discretely change on-line. We propose an algorithm for on-line controller implementation of continuation MPC for ensembles of predictions corresponding to various anticipated changes and demonstrate its numeric...
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...
Models for Predictive Railway Traffic Management
Kecman, P.
2014-01-01
The potential growth in transport demand in the next decade and beyond requires a change from reactive to proactive traffic control to maintain and improve the reliability of railway traffic. In order to enable an anticipative approach to traffic management, it is necessary to develop the tools for monitoring, prediction and optimisation of the traffic operations. This thesis presents the models that can be used as components for a decision support system for predictive traffic management.
A High Precision Prediction Model Using Hybrid Grey Dynamic Model
Li, Guo-Dong; Yamaguchi, Daisuke; Nagai, Masatake; Masuda, Shiro
2008-01-01
In this paper, we propose a new prediction analysis model which combines the first order one variable Grey differential equation Model (abbreviated as GM(1,1) model) from grey system theory and time series Autoregressive Integrated Moving Average (ARIMA) model from statistics theory. We abbreviate the combined GM(1,1) ARIMA model as ARGM(1,1)…
Caries risk assessment models in caries prediction
Amila Zukanović
2013-01-01
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 ...
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
Current predictions for oil spill models
Development and application of a background field of surface currents and a wind response model for oil spill software programs to predict the motion of an oil spill is described. The model determines the surface, seasonal and baroclinic currents. It uses input from all observed profiles of ocean density data for (in this case) the British Columbia coast. An objective analysis routine is used to prepare the spatially continuous, gridded fields of temperature and salinity from surface to ocean bottom. The model is evaluated by interpolating the wind field from weather buoy observations made in 1991, and a field of surface currents computed from tracks of Loran-C drifters deployed at the same time. Although the combined least squares fit does not fully explain the current variance, it does provide useful prediction based on parameters that can be embedded in search and rescue and oil spill prediction software. 14 refs., 2 tabs., 12 figs
Multi-Model Ensemble Wake Vortex Prediction
Koerner, Stephan; Holzaepfel, Frank; Ahmad, Nash'at N.
2015-01-01
Several multi-model ensemble methods are investigated for predicting wake vortex transport and decay. This study is a joint effort between National Aeronautics and Space Administration and Deutsches Zentrum fuer Luft- und Raumfahrt to develop a multi-model ensemble capability using their wake models. An overview of different multi-model ensemble methods and their feasibility for wake applications is presented. The methods include Reliability Ensemble Averaging, Bayesian Model Averaging, and Monte Carlo Simulations. The methodologies are evaluated using data from wake vortex field experiments.
PREDICTIVE CAPACITY OF ARCH FAMILY MODELS
Raphael Silveira Amaro
2016-03-01
Full Text Available In the last decades, a remarkable number of models, variants from the Autoregressive Conditional Heteroscedastic family, have been developed and empirically tested, making extremely complex the process of choosing a particular model. This research aim to compare the predictive capacity, using the Model Confidence Set procedure, than five conditional heteroskedasticity models, considering eight different statistical probability distributions. The financial series which were used refers to the log-return series of the Bovespa index and the Dow Jones Industrial Index in the period between 27 October 2008 and 30 December 2014. The empirical evidences showed that, in general, competing models have a great homogeneity to make predictions, either for a stock market of a developed country or for a stock market of a developing country. An equivalent result can be inferred for the statistical probability distributions that were used.
A Predictive Model for Root Caries Incidence.
Ritter, André V; Preisser, John S; Puranik, Chaitanya P; Chung, Yunro; Bader, James D; Shugars, Daniel A; Makhija, Sonia; Vollmer, William M
2016-01-01
This study aimed to find the set of risk indicators best able to predict root caries (RC) incidence in caries-active adults utilizing data from the Xylitol for Adult Caries Trial (X-ACT). Five logistic regression models were compared with respect to their predictive performance for incident RC using data from placebo-control participants with exposed root surfaces at baseline and from two study centers with ancillary data collection (n = 155). Prediction performance was assessed from baseline variables and after including ancillary variables [smoking, diet, use of removable partial dentures (RPD), toothbrush use, income, education, and dental insurance]. A sensitivity analysis added treatment to the models for both the control and treatment participants (n = 301) to predict RC for the control participants. Forty-nine percent of the control participants had incident RC. The model including the number of follow-up years at risk, the number of root surfaces at risk, RC index, gender, race, age, and smoking resulted in the best prediction performance, having the highest AUC and lowest Brier score. The sensitivity analysis supported the primary analysis and gave slightly better performance summary measures. The set of risk indicators best able to predict RC incidence included an increased number of root surfaces at risk and increased RC index at baseline, followed by white race and nonsmoking, which were strong nonsignificant predictors. Gender, age, and increased number of follow-up years at risk, while included in the model, were also not statistically significant. The inclusion of health, diet, RPD use, toothbrush use, income, education, and dental insurance variables did not improve the prediction performance. PMID:27160516
Predictions of charged charmonium-like structures with hidden-charm and open-strange channel
Chen, Dian-Yong; Matsuki, Takayuki
2013-01-01
We propose the initial single chiral particle emission (ISChE) mechanism, with which the hidden-charm di-kaon decays of higher charmonia and charmonium-like states are studied. Calculating the distributions of differential decay width, we obtain the line shape of the $J/\\psi K^+$ invariant mass spectrum of $\\psi_i\\to J/\\psi K^+K^-$, where $\\psi_i=\\psi(4415), Y(4660)$, and $\\psi(4790)$. Our numerical results show that there exist enhancement structures with both hidden-charm and open-strange, which are near the $D\\bar{D}_s^*/D^*\\bar{D}_s$ and $D^*\\bar{D}_s^*/\\bar{D}^*{D}_s^*$ thresholds. These charged charmonium-like structures predicted in this paper can be accessible at future experiment, especially BESIII, BelleII and SuperB.
A Unified Channel Charges Expression for Analytic MOSFET Modeling
Hugues Murray
2012-01-01
Full Text Available Based on a 1D Poissons equation resolution, we present an analytic model of inversion charges allowing calculation of the drain current and transconductance in the Metal Oxide Semiconductor Field Effect Transistor. The drain current and transconductance are described by analytical functions including mobility corrections and short channel effects (CLM, DIBL. The comparison with the Pao-Sah integral shows excellent accuracy of the model in all inversion modes from strong to weak inversion in submicronics MOSFET. All calculations are encoded with a simple C program and give instantaneous results that provide an efficient tool for microelectronics users.
Modeling Dendrimers Charge Interaction in Solution: Relevance in Biosystems
Domenico Lombardo
2014-01-01
Full Text Available Dendrimers are highly branched macromolecules obtained by stepwise controlled, reaction sequences. The ability to be designed for specific applications makes dendrimers unprecedented components to control the structural organization of matter during the bottom-up synthesis of functional nanostructures. For their applications in the field of biotechnology the determination of dendrimer structural properties as well as the investigation of the specific interaction with guest components are needed. We show how the analysis of the scattering structure factor S(q, in the framework of current models for charged systems in solution, allows for obtaining important information of the interdendrimers electrostatic interaction potential. The finding of the presented results outlines the important role of the dendrimer charge and the solvent conditions in regulating, through the modulation of the electrostatic interaction potential, great part of the main structural properties. This charge interaction has been indicated by many studies as a crucial factor for a wide range of structural processes involving their biomedical application. Due to their easily controllable properties dendrimers can be considered at the crossroad between traditional colloids, associating polymers, and biological systems and represent then an interesting new technological approach and a suitable model system of molecular organization in biochemistry and related fields.
Predictive coding as a model of cognition.
Spratling, M W
2016-08-01
Previous work has shown that predictive coding can provide a detailed explanation of a very wide range of low-level perceptual processes. It is also widely believed that predictive coding can account for high-level, cognitive, abilities. This article provides support for this view by showing that predictive coding can simulate phenomena such as categorisation, the influence of abstract knowledge on perception, recall and reasoning about conceptual knowledge, context-dependent behavioural control, and naive physics. The particular implementation of predictive coding used here (PC/BC-DIM) has previously been used to simulate low-level perceptual behaviour and the neural mechanisms that underlie them. This algorithm thus provides a single framework for modelling both perceptual and cognitive brain function. PMID:27118562
Predictive Models of Li-ion Battery Lifetime (Presentation)
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.
Modelling the predictive performance of credit scoring
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.
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
Mausumi Dikpati; Peter A. Gilman
2008-03-01
Flux-transport type solar dynamos have achieved considerable success in correctly simulating many solar cycle features, and are now being used for prediction of solar cycle timing and amplitude.We first define flux-transport dynamos and demonstrate how they work. The essential added ingredient in this class of models is meridional circulation, which governs the dynamo period and also plays a crucial role in determining the Sun’s memory about its past magnetic fields.We show that flux-transport dynamo models can explain many key features of solar cycles. Then we show that a predictive tool can be built from this class of dynamo that can be used to predict mean solar cycle features by assimilating magnetic field data from previous cycles.
Grey Model for Stream Flow Prediction
P. Syamala
2012-04-01
Full Text Available Design, operation and planning of water resources, irrigation and water supply systems require estimation of stream flow. A grey system or stochastic approach is required for dealing with the hydrological complexities of mid and long-term stream flow prediction. Generally relatively long period data series of stream flow records is required for the prediction using stochastic methods. In developing countries like India, availability of long period hydrological records is a problem. Grey system theory is applicable in the case of unclear innerrelationship, uncertain mechanisms and insufficient information and requires only small samples for parameter estimation. Stream flow records of Bharathapuzha river basin, Kerala, India is subjected to grey analysis. Model parameters were estimated using least-squares method. Statistical indices for the developed models indicate their ability to predict stream flow in the river under study with reasonable accuracy
An exponential filter model predicts lightness illusions
Astrid eZeman
2015-06-01
Full Text Available Lightness, or perceived reflectance of a surface, is influenced by surrounding context. This is demonstrated by the Simultaneous Contrast Illusion (SCI, where a grey patch is perceived lighter against a black background and vice versa. Conversely, assimilation is where the lightness of the target patch moves towards that of the bounding areas and can be demonstrated in White's effect. Blakeslee and McCourt (2007 introduced an oriented difference-of-Gaussian (ODOG model that is able to account for both contrast and assimilation in a number of lightness illusions and that has been subsequently improved using localized normalization techniques. We introduce a model inspired by image statistics that is based on a family of exponential filters, with kernels spanning across multiple sizes and shapes. We include an optional second stage of normalization based on contrast gain control. Our model was tested on a well-known set of lightness illusions that have previously been used to evaluate ODOG and its variants, and model lightness values were compared with typical human data. We investigate whether predictive success depends on filters of a particular size or shape and whether pooling information across filters can improve performance. The best single filter correctly predicted the direction of lightness effects for 21 out of 27 illusions. Combining two filters together increased the best performance to 23, with asymptotic performance at 24 for an arbitrarily large combination of filter outputs. While normalization improved prediction magnitudes, it only slightly improved overall scores in direction predictions. The prediction performance of 24 out of 27 illusions equals that of the best performing ODOG variant, with greater parsimony. Our model shows that V1-style orientation-selectivity is not necessary to account for lightness illusions and that a low-level model based on image statistics is able to account for a wide range of both contrast and
This paper describes and introduces a new nonlinear predictor and a novel battery model for estimating the state of charge (SoC) of lead-acid batteries for hybrid electric vehicles (HEV). Many problems occur for a traditional SoC indicator, such as offset, drift and long term state divergence, therefore this paper proposes a technique based on the extended Kalman filter (EKF) in order to overcome these problems. The underlying dynamic behavior of each cell is modeled using two capacitors (bulk and surface) and three resistors (terminal, surface and end). The SoC is determined from the voltage present on the bulk capacitor. In this new model, the value of the surface capacitor is constant, whereas the value of the bulk capacitor is not. Although the structure of the model, with two constant capacitors, has been previously reported for lithium-ion cells, this model can also be valid and reliable for lead-acid cells when used in conjunction with an EKF to estimate SoC (with a little variation). Measurements using real-time road data are used to compare the performance of conventional internal resistance (Rint) based methods for estimating SoC with those predicted from the proposed state estimation schemes. The results show that the proposed method is superior to the more traditional techniques, with accuracy in estimating the SoC within 3%
Model Predictive Control of a Tricopter
Barsk, Karl-Johan
2012-01-01
In this master thesis, a real-time control system that stabilizes the rotational rates of a tri-copter, has been studied. The tricopter is a rotorcraft with three rotors. The tricopter has been modelled and identified, using system identification algorithms. The model has been used in a Kalman filter to estimate the state of the system and for design ofa model based controller. The control approach used in this thesis is a model predictive controller, which is a multi-variable controller that...
Simulation error models for improved reservoir prediction
Successful reservoir prediction requires an accurate estimation of parameters to be used in the reservoir model. This research focuses on developing models for simulation error within the petroleum industry, enabling accurate parameter estimation. The standard approach in the oil industry to parameter estimation in a Bayesian framework includes inappropriate assumptions about the error data. This leads to the parameter estimations being biased and overconfident. An error model is designed to significantly reduce the bias effect and to estimate an accurate range of spread. A 2D viscous fingering example problem will be used to demonstrate both construction of the error model, and the benefits gained in doing so
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
Mao, Runfang; Lee, Ming-Tsung; Vishnyakov, Aleksey; Neimark, Alexander V
2015-09-01
Using dissipative particle dynamics (DPD) simulations, we explore the specifics of micellization in the solutions of anionic and cationic surfactants and their mixtures. Anionic surfactant sodium dodecyl sulfate (SDS) and cationic surfactant cetyltrimethylammonium bromide (CTAB) are chosen as characteristic examples. Coarse-grained models of the surfactants are constructed and parameterized using a combination of atomistic molecular simulation and infinite dilution activity coefficient calibration. Electrostatic interactions of charged beads are treated using a smeared charge approximation: the surfactant heads and dissociated counterions are modeled as beads with charges distributed around the bead center in an implicit dielectric medium. The proposed models semiquantitatively describe self-assembly in solutions of SDS and CTAB at various surfactant concentrations and molarities of added electrolyte. In particular, the model predicts a decline in the free surfactant concentration with the increase of the total surfactant loading, as well as characteristic aggregation transitions in single-component surfactant solutions caused by the addition of salt. The calculated values of the critical micelle concentration reasonably agree with experimental observations. Modeling of catanionic SDS-CTAB mixtures show consecutive transitions to worm-like micelles and then to vesicles caused by the addition of CTAB to micellar solution of SDS. PMID:26241704
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.
Linear Model Predictive Control of Induction Machine
Mynář, Z.
2015-01-01
This article presents new control algorithm for induction machine based on linear model predictive control (MPC). Controller works in similar manners as field oriented control (FOC), but control is performed in stator coordinates. This reduces computational demands as Park’s transformation is absent and induction machine mathematical model in stator coordinates contains less nonlinear elements. Another aim of proposed controller was to achieve fast torque response.
Model Predictive Control of Autonomous Vehicles
Zanon, Mario; Frasch, Janick V.; Vukov, Milan; Sager, Sebastian; Diehl, Moritz
2014-01-01
International audience The control of autonomous vehicles is a challenging task that requires advanced control schemes. Nonlinear Model Predictive Control (NMPC) and Moving Horizon Estimation (MHE) are optimization-based control and estimation techniques that are able to deal with highly nonlinear, constrained, unstable and fast dynamic systems. In this chapter, these techniques are detailed, a descriptive nonlinear model is derived and the performance of the proposed control scheme is dem...
Continuation model predictive control on smooth manifolds
Knyazev, Andrew; Malyshev, Alexander,
2015-01-01
Model predictive control (MPC) anticipates future events to take appropriate control actions. Nonlinear MPC (NMPC) describes systems with nonlinear models and/or constraints. Continuation MPC, suggested by T.~Ohtsuka in 2004, uses Krylov-Newton iterations. Continuation MPC is suitable for nonlinear problems and has been recently adopted for minimum time problems. We extend the continuation MPC approach to a case where the state is implicitly constrained to a smooth manifold. We propose an alg...
Preconditioning for continuation model predictive control
Knyazev, Andrew; Malyshev, Alexander,
2015-01-01
Model predictive control (MPC) anticipates future events to take appropriate control actions. Nonlinear MPC (NMPC) deals with nonlinear models and/or constraints. A Continuation/GMRES Method for NMPC, suggested by T. Ohtsuka in 2004, uses the GMRES iterative algorithm to solve a forward difference approximation $Ax=b$ of the original NMPC equations on every time step. We have previously proposed accelerating the GMRES and MINRES convergence by preconditioning the coefficient matrix $A$. We no...
Predictive performance models and multiple task performance
Wickens, Christopher D.; Larish, Inge; Contorer, Aaron
1989-01-01
Five models that predict how performance of multiple tasks will interact in complex task scenarios are discussed. The models are shown in terms of the assumptions they make about human operator divided attention. The different assumptions about attention are then empirically validated in a multitask helicopter flight simulation. It is concluded from this simulation that the most important assumption relates to the coding of demand level of different component tasks.
Cognitive modeling to predict video interpretability
Young, Darrell L.; Bakir, Tariq
2011-06-01
Processing framework for cognitive modeling to predict video interpretability is discussed. Architecture consists of spatiotemporal video preprocessing, metric computation, metric normalization, pooling of like metric groups with masking adjustments, multinomial logistic pooling of Minkowski pooled groups of similar quality metrics, and estimation of confidence interval of final result.
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
Hierarchical Model Predictive Control for Resource Distribution
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...
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. PMID:22310480
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...
Specialized Language Models using Dialogue Predictions
Popovici, C; Popovici, Cosmin; Baggia, Paolo
1996-01-01
This paper analyses language modeling in spoken dialogue systems for accessing a database. The use of several language models obtained by exploiting dialogue predictions gives better results than the use of a single model for the whole dialogue interaction. For this reason several models have been created, each one for a specific system question, such as the request or the confirmation of a parameter. The use of dialogue-dependent language models increases the performance both at the recognition and at the understanding level, especially on answers to system requests. Moreover other methods to increase performance, like automatic clustering of vocabulary words or the use of better acoustic models during recognition, does not affect the improvements given by dialogue-dependent language models. The system used in our experiments is Dialogos, the Italian spoken dialogue system used for accessing railway timetable information over the telephone. The experiments were carried out on a large corpus of dialogues coll...
Caries risk assessment models in caries prediction
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.
Disease prediction models and operational readiness.
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
Model Predictive Control based on Finite Impulse Response Models
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...
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.
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.
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.
STELLA Experiment: Design and Model Predictions
The STaged ELectron Laser Acceleration (STELLA) experiment will be one of the first to examine the critical issue of staging the laser acceleration process. The BNL inverse free electron laser (EEL) will serve as a prebuncher to generate ∼ 1 (micro)m long microbunches. These microbunches will be accelerated by an inverse Cerenkov acceleration (ICA) stage. A comprehensive model of the STELLA experiment is described. This model includes the EEL prebunching, drift and focusing of the microbunches into the ICA stage, and their subsequent acceleration. The model predictions will be presented including the results of a system error study to determine the sensitivity to uncertainties in various system parameters
Models for Energy and Charge Transport, and Storage in Biomolecules
Mingaleev, S F; Gaididei, Yu B; Johansson, M; Rasmussen, K O; Mingaleev, Serge F.; Christiansen, Peter L.; Gaididei, Yuri B.; Johansson, Magnus; Rasmussen, Kim O.
1999-01-01
Two models for energy and charge transport and storage in biomolecules are considered. A model based on the discrete nonlinear Schrodinger equation with long-range dispersive interactions (LRI's) between base pairs of DNA is offered for the description of nonlinear dynamics of the DNA molecule. We show that LRI's are responsible for the existence of an interval of bistability where two stable stationary states, a narrow, pinned state and a broad, mobile state, coexist at each value of the total energy. The possibility of controlled switching between pinned and mobile states is demonstrated. The mechanism could be important for controlling energy storage and transport in DNA molecules. Another model is offered for the description of nonlinear excitations in proteins and other anharmonic biomolecules. We show that in the highly anharmonic systems a bound state of Davydov and Boussinesq solitons can exist.
Performance model to predict overall defect density
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.
Neuro-fuzzy modeling in bankruptcy prediction
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.
Predictive modeling of nanomaterial exposure effects in biological systems
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
Nonlinear potential model of space-charge-limited electron beams
Litz, M.S. [Army Research Lab., Adelphi, MD (United States); Golden, J. [Berkeley Research Associates, Springfield, VA (United States)
1995-11-01
A one-dimensional (1D) time-varying nonlinear theory based on the Duffing equation is applied to space-charge limited beams and specifically vircators. This theory classifies test particle trajectories in a modulated nonlinear potential. Two predictions of the theory that can be directly compared to experiment are the final state of electron trajectories and the oscillation frequency of the electrons m the potential well. Experimental measurements of electron flux recorded along the vircator chamber wall correlates well with the numerically integrated final state of electron trajectory in the 1D theory. The oscillation frequency measured in the experiment is shown to be a better match to the oscillation frequency calculated from the nonlinear potential as compared to a parabolic potential (that results from a linear restoring force). In the experiment, random initial conditions arise from beam thermalization and nonuniform electron emission at the surface of the cathode. However, these characteristics alone do not explain the experimentally observed fluctuations in rf power and frequency. The predictions of the time-varying nonlinear potential theory clearly exhibits trends that were observed in the experimental results, in the form of classes of particle trajectories, fluctuations in particle asymptotic states, and particle motion sensitive to the shape of the virtual cathode.
A Massless-Point-Charge Model for the Electron
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.
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.
Modeling the Hydrogen-Proton Charge-Exchange Process in Global Heliospheric Simulations
DeStefano, A.; Heerikhuisen, J.
2015-12-01
The environment surrounding our Solar System has a vast and dynamic structure. As the Sun rounds the Milky Way galaxy, interstellar dust and gas interact with the Sun's outflow of solar wind. A bubble of hot plasma forms around the Sun due to this interaction, called the heliosphere. In order to understand the structure of the heliosphere, observations and simulations must work in tandem. Within the past decade or so, 3D models of the heliosphere have been developed exhibiting non- symmmetric as well as predicting structures such as the hydrogen wall and the IBEX ribbon. In this poster we explore new ways to compute charge-exchange source terms. The charge-exchange process is the coupling mechanism between the MHD and kinetic theories. The understanding of this process is crucial in order to make valuable predictions. Energy dependant cross section terms will aid in settling non-linear affects coupling the intestellar and solar particles. Through these new ways of computing source terms, resolving fine structures in the plasma in the heliopause may be possible. In addition, other non-trivial situations, such as charge-exchange mediated shocks, may be addressed.
Disease Prediction Models and Operational Readiness
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
Developing Predictive Models of Health Literacy
Martin, Laurie T.; Ruder, Teague; Escarce, José J.; Ghosh-Dastidar, Bonnie; Sherman, Daniel; Elliott, Marc; Bird, Chloe E.; Fremont, Allen; Gasper, Charles; Culbert, Arthur; Lurie, Nicole
2009-01-01
INTRODUCTION Low health literacy (LHL) remains a formidable barrier to improving health care quality and outcomes. Given the lack of precision of single demographic characteristics to predict health literacy, and the administrative burden and inability of existing health literacy measures to estimate health literacy at a population level, LHL is largely unaddressed in public health and clinical practice. To help overcome these limitations, we developed two models to estimate health literacy. ...
Modelling molecular flexibility for crystal structure prediction
Uzoh, O. G.
2015-01-01
In the crystal packing of molecules wherein a single bond links aromatic groups, a change in the torsion angle can optimise close packing of the molecule. The improved intermolecular interactions, Uinter, outweigh the conformational energy penalty, ΔEintra, to give a more stable lattice energy, Elatt = Uinter + ΔEintra. This thesis uses this lattice energy model hierarchically in a new Crystal Structure Prediction (CSP) algorithm, CrystalPredictor version 1.6, which varies the low-barrier tor...
Nonlinear model predictive control using automatic differentiation
Al Seyab, Rihab Khalid Shakir
2006-01-01
Although nonlinear model predictive control (NMPC) might be the best choice for a nonlinear plant, it is still not widely used. This is mainly due to the computational burden associated with solving online a set of nonlinear differential equations and a nonlinear dynamic optimization problem in real time. This thesis is concerned with strategies aimed at reducing the computational burden involved in different stages of the NMPC such as optimization problem, state estimation, an...
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.
On well-posedness of variational models of charged drops
Muratov, Cyrill B
2015-01-01
Electrified liquids are well known to be prone to a variety of interfacial instabilities that result in the onset of apparent interfacial singularities and liquid fragmentation. In the case of electrically conducting liquids, one of the basic models describing the equilibrium interfacial configurations and the onset of instability assumes the liquid to be equipotential and interprets those configurations as local minimizers of the energy consisting of the sum of the surface energy and the electrostatic energy. Here we show that, surprisingly, this classical geometric variational model is mathematically ill-posed irrespectively of the degree to which the liquid is electrified. Specifically, we demonstrate that an isolated spherical droplet is never a local minimizer, no matter how small is the total charge on the droplet, since the energy can always be lowered by a smooth, arbitrarily small distortion of the droplet's surface. This is in sharp contrast with the experimental observations that a critical amount ...
Ugur, Ilke; Marion, Antoine; Parant, Stéphane; Jensen, Jan H; Monard, Gerald
2014-08-25
In a first step toward the development of an efficient and accurate protocol to estimate amino acids' pKa's in proteins, we present in this work how to reproduce the pKa's of alcohol and thiol based residues (namely tyrosine, serine, and cysteine) in aqueous solution from the knowledge of the experimental pKa's of phenols, alcohols, and thiols. Our protocol is based on the linear relationship between computed atomic charges of the anionic form of the molecules (being either phenolates, alkoxides, or thiolates) and their respective experimental pKa values. It is tested with different environment approaches (gas phase or continuum solvent-based approaches), with five distinct atomic charge models (Mulliken, Löwdin, NPA, Merz-Kollman, and CHelpG), and with nine different DFT functionals combined with 16 different basis sets. Moreover, the capability of semiempirical methods (AM1, RM1, PM3, and PM6) to also predict pKa's of thiols, phenols, and alcohols is analyzed. From our benchmarks, the best combination to reproduce experimental pKa's is to compute NPA atomic charge using the CPCM model at the B3LYP/3-21G and M062X/6-311G levels for alcohols (R(2) = 0.995) and thiols (R(2) = 0.986), respectively. The applicability of the suggested protocol is tested with tyrosine and cysteine amino acids, and precise pKa predictions are obtained. The stability of the amino acid pKa's with respect to geometrical changes is also tested by MM-MD and DFT-MD calculations. Considering its strong accuracy and its high computational efficiency, these pKa prediction calculations using atomic charges indicate a promising method for predicting amino acids' pKa in a protein environment. PMID:25089727
Predicting extinction rates in stochastic epidemic models
We investigate the stochastic extinction processes in a class of epidemic models. Motivated by the process of natural disease extinction in epidemics, we examine the rate of extinction as a function of disease spread. We show that the effective entropic barrier for extinction in a susceptible–infected–susceptible epidemic model displays scaling with the distance to the bifurcation point, with an unusual critical exponent. We make a direct comparison between predictions and numerical simulations. We also consider the effect of non-Gaussian vaccine schedules, and show numerically how the extinction process may be enhanced when the vaccine schedules are Poisson distributed
Constructing predictive models of human running.
Maus, Horst-Moritz; Revzen, Shai; Guckenheimer, John; Ludwig, Christian; Reger, Johann; Seyfarth, Andre
2015-02-01
Running is an essential mode of human locomotion, during which ballistic aerial phases alternate with phases when a single foot contacts the ground. The spring-loaded inverted pendulum (SLIP) provides a starting point for modelling running, and generates ground reaction forces that resemble those of the centre of mass (CoM) of a human runner. Here, we show that while SLIP reproduces within-step kinematics of the CoM in three dimensions, it fails to reproduce stability and predict future motions. We construct SLIP control models using data-driven Floquet analysis, and show how these models may be used to obtain predictive models of human running with six additional states comprising the position and velocity of the swing-leg ankle. Our methods are general, and may be applied to any rhythmic physical system. We provide an approach for identifying an event-driven linear controller that approximates an observed stabilization strategy, and for producing a reduced-state model which closely recovers the observed dynamics. PMID:25505131
A predictive model for dimensional errors in fused deposition modeling
Stolfi, A.
2015-01-01
values of L (0.254 mm, 0.330 mm) was produced by comparing predicted values with external face-to-face measurements. After removing outliers, the results show that the developed two-parameter model can serve as tool for modeling the FDM dimensional behavior in a wide range of deposition angles.......This work concerns the effect of deposition angle (a) and layer thickness (L) on the dimensional performance of FDM parts using a predictive model based on the geometrical description of the FDM filament profile. An experimental validation over the whole a range from 0° to 177° at 3° steps and two...
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
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.