Model Predictive Control-Based Fast Charging for Vehicular Batteries
Directory of Open Access Journals (Sweden)
Zhibin Song
2011-08-01
Full Text Available Battery fast charging is one of the most significant and difficult techniques affecting the commercialization of electric vehicles (EVs. In this paper, we propose a fast charge framework based on model predictive control, with the aim of simultaneously reducing the charge duration, which represents the out-of-service time of vehicles, and the increase in temperature, which represents safety and energy efficiency during the charge process. The RC model is employed to predict the future State of Charge (SOC. A single mode lumped-parameter thermal model and a neural network trained by real experimental data are also applied to predict the future temperature in simulations and experiments respectively. A genetic algorithm is then applied to find the best charge sequence under a specified fitness function, which consists of two objectives: minimizing the charging duration and minimizing the increase in temperature. Both simulation and experiment demonstrate that the Pareto front of the proposed method dominates that of the most popular constant current constant voltage (CCCV charge method.
Charge transport model to predict intrinsic reliability for dielectric materials
Energy Technology Data Exchange (ETDEWEB)
Ogden, Sean P. [Howard P. Isermann Department of Chemical and Biological Engineering, Rensselaer Polytechnic Institute, Troy, New York 12180 (United States); GLOBALFOUNDRIES, 400 Stonebreak Rd. Ext., Malta, New York 12020 (United States); Borja, Juan; Plawsky, Joel L., E-mail: plawsky@rpi.edu; Gill, William N. [Howard P. Isermann Department of Chemical and Biological Engineering, Rensselaer Polytechnic Institute, Troy, New York 12180 (United States); Lu, T.-M. [Department of Physics, Rensselaer Polytechnic Institute, Troy, New York 12180 (United States); Yeap, Kong Boon [GLOBALFOUNDRIES, 400 Stonebreak Rd. Ext., Malta, New York 12020 (United States)
2015-09-28
Several lifetime models, mostly empirical in nature, are used to predict reliability for low-k dielectrics used in integrated circuits. There is a dispute over which model provides the most accurate prediction for device lifetime at operating conditions. As a result, there is a need to transition from the use of these largely empirical models to one built entirely on theory. Therefore, a charge transport model was developed to predict the device lifetime of low-k interconnect systems. The model is based on electron transport and donor-type defect formation. Breakdown occurs when a critical defect concentration accumulates, resulting in electron tunneling and the emptying of positively charged traps. The enhanced local electric field lowers the barrier for electron injection into the dielectric, causing a positive feedforward failure. The charge transport model is able to replicate experimental I-V and I-t curves, capturing the current decay at early stress times and the rapid current increase at failure. The model is based on field-driven and current-driven failure mechanisms and uses a minimal number of parameters. All the parameters have some theoretical basis or have been measured experimentally and are not directly used to fit the slope of the time-to-failure versus applied field curve. Despite this simplicity, the model is able to accurately predict device lifetime for three different sources of experimental data. The simulation's predictions at low fields and very long lifetimes show that the use of a single empirical model can lead to inaccuracies in device reliability.
Charge transport model to predict intrinsic reliability for dielectric materials
International Nuclear Information System (INIS)
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
Directory of Open Access Journals (Sweden)
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
DEFF Research Database (Denmark)
Halvgaard, Rasmus; Poulsen, Niels K.; Madsen, Henrik;
2012-01-01
Economic Model Predictive Control (MPC) is very well suited for controlling smart energy systems since electricity price and demand forecasts are easily integrated in the controller. Electric vehicles (EVs) are expected to play a large role in the future Smart Grid. They are expected to provide...... grid services, both for peak reduction and for ancillary services, by absorbing short term variations in the electricity production. In this paper the Economic MPC minimizes the cost of electricity consumption for a single EV. Simulations show savings of 50–60% of the electricity costs compared 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
Directory of Open Access Journals (Sweden)
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
Directory of Open Access Journals (Sweden)
Bambang Wahono
2015-07-01
Full Text Available This paper presents the construction of a battery state of charge (SOC prediction model and the optimization method of the said model to appropriately control the number of parameters in compliance with the SOC as the battery output objectives. Research Centre for Electrical Power and Mechatronics, Indonesian Institute of Sciences has tested its electric vehicle research prototype on the road, monitoring its voltage, current, temperature, time, vehicle velocity, motor speed, and SOC during the operation. Using this experimental data, the prediction model of battery SOC was built. Stepwise method considering multicollinearity was able to efficiently develops the battery prediction model that describes the multiple control parameters in relation to the characteristic values such as SOC. It was demonstrated that particle swarm optimization (PSO succesfully and efficiently calculated optimal control parameters to optimize evaluation item such as SOC based on the model.
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
Institute of Scientific and Technical Information of China (English)
LUO Ming-liang; GUO Yan; PU Chun-sheng; LU Feng-ji
2004-01-01
In the process of ultrafiltration , the occur-rence of the limiting flux is elucidated with the formation of a cake(gel) layer on the membrane surface. Before cake formation, the pressure drop on the concentration polarization layer, as well as the permeate flux, increases with the applied pressure. The pressure drop on the concentration polarization layer, however, will no longer change with the applied pressure after the formation of the cake layer. The limiting flux will be obtained if the hydrodynamic conditions in the filtration channel are not affected by the cake layer. A mathematics model for predicting the limiting flux for the charged solute in ultrafiltration is developed. In this model, a repulsive electric force is taken into account in addition to convection and diffusion when the solute is carrying the same charge as the membrane material. A procedure to correlate the model with experimental ultrafiltration data is also present. The results show that a model in this paper is developed on a more realistic perception of the ultrafiltration system and the predicting data agrees well with experimental data.
International Nuclear Information System (INIS)
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
International Nuclear Information System (INIS)
Highlights: ► Max torque and power values were obtained at 3.5 bar Pch, 1273 K Hst and 1.4:1 r. ► According to ANOVA, the most influential parameter on power was Hst with 48.75%. ► According to ANOVA, the most influential parameter on torque was Hst with 41.78%. ► ANN (R2 = 99.8% for T, P) was superior to regression method (R2 = 92% for T, 81% for P). ► LM was the best learning algorithm in predicting both power and torque. - Abstract: In this study, an artificial neural network (ANN) model was developed to predict the torque and power of a beta-type Stirling engine using helium as the working fluid. The best results were obtained by 5-11-7-1 and 5-13-7-1 network architectures, with double hidden layers for the torque and power respectively. For these network architectures, the Levenberg–Marquardt (LM) learning algorithm was used. Engine performance values predicted with the developed ANN model were compared with the actual performance values measured experimentally, and substantially coinciding results were observed. After ANN training, correlation coefficients (R2) of both engine performance values for testing and training data were very close to 1. Similarly, root-mean-square error (RMSE) and mean error percentage (MEP) values for the testing and training data were less than 0.02% and 3.5% respectively. These results showed that the ANN is an acceptable model for prediction of the torque and power of the beta-type Stirling engine
Energy Technology Data Exchange (ETDEWEB)
Pierce, Flint; Grillet, Anne Mary; Grest, Gary Stephen; Lechman, Jeremy B.; Plimpton, Steven James; in' t Veld, Pieter J. (BASF Corporation Ludwigshafen, Germany); Schunk, Peter Randall; Heine, D. R. (Corning, Inc. Corning, NY); Stoltz, C. (Procter and Gamble Co. West Chester, OH); Weiss, Horst (BASF Corporation Ludwigshafen, Germany); Jendrejack, R. (3M Corporation St. Paul, MN); Petersen, Matthew K.
2010-06-01
In this presentation we examine the accuracy and performance of a suite of discrete-element-modeling approaches to predicting equilibrium and dynamic rheological properties of polystyrene suspensions. What distinguishes each approach presented is the methodology of handling the solvent hydrodynamics. Specifically, we compare stochastic rotation dynamics (SRD), fast lubrication dynamics (FLD) and dissipative particle dynamics (DPD). Method-to-method comparisons are made as well as comparisons with experimental data. Quantities examined are equilibrium structure properties (e.g. pair-distribution function), equilibrium dynamic properties (e.g. short- and long-time diffusivities), and dynamic response (e.g. steady shear viscosity). In all approaches we deploy the DLVO potential for colloid-colloid interactions. Comparisons are made over a range of volume fractions and salt concentrations. Our results reveal the utility of such methods for long-time diffusivity prediction can be dubious in certain ranges of volume fraction, and other discoveries regarding the best formulation to use in predicting rheological response.
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
International Nuclear Information System (INIS)
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.
Directory of Open Access Journals (Sweden)
Arteaga-Velázquez J.C.
2015-01-01
Full Text Available KASCADE-Grande was an air-shower experiment designed to study cosmic rays between 1016 and 1018 eV. The instrument was located at the site of the Karlsruhe Institute of Technology, Germany at an altitude of 110 m a.s.l. and covered an area of 0.5 km2. KASCADE-Grande consisted of several detector systems dedicated to measure different components of the EAS generated by the primary cosmic rays, i.e., the muon and the electron contents of the air-shower. With such a number of EAS observables and the precision of the measurements, the KASCADE-Grande data can be used to not only study in detail the properties of cosmic rays but also to test the predictions of hadronic-interaction models. In this work, in particular, the attenuation lengths of the muon number and the charged number of particles of EAS in the atmosphere were extracted from the KASCADE-Grande data and the results were compared with the predictions of the new EPOS-LHC hadronic-interaction model.
Charge Prediction of Lipid Fragments in Mass Spectrometry
Energy Technology Data Exchange (ETDEWEB)
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
DEFF Research Database (Denmark)
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
International Nuclear Information System (INIS)
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
Directory of Open Access Journals (Sweden)
Aram Baruch Gonzalez Perez
2014-01-01
Full Text Available Multi-agent systems are broadly known for being able to simulate real-life situations which require the interaction and cooperation of individuals. Opponent modeling can be used along with multi-agent systems to model complex situations such as competitions like soccer games. In this study, a model for predicting opponent moves based on their target is presented. The model is composed by an offline step (learning phase and an online one (execution phase. The offline step gets and analyses previous experiences while the online step uses the data generated by offline analysis to predict opponent moves. This model is illustrated by an experiment with the RoboCup 2D Soccer Simulator. The proposed model was tested using 22 games to create the knowledge base and getting an accuracy rate over 80%.
International Nuclear Information System (INIS)
Prediction model Perla presents one of a tool for an evaluation of a stream ecological status. It enables a comparing with a standard. The standard is formed by a dataset of sites from all area of the Czech Republic. The sites were influenced by a human activity as few as possible. 8 variables were used for prediction (distance from source, elevation, stream width and depth, slope, substrate roughness, longitude and latitude. All of them were statistically important for benthic communities. Results do not response ecoregions, but rather stream size (type). B (EQItaxonu), EQISi, EQIASPT a EQIH appears applicable for assessment using the prediction model and for natural and human stress differentiating. Limiting values of the indices for good ecological status are suggested. On the contrary, using of EQIEPT a EQIekoprof indices would be possible only with difficulties. (authors)
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
DEFF Research Database (Denmark)
Nielsen, Henrik Aalborg; Nielsen, Torben Skov; Madsen, Henrik;
2005-01-01
This document lists candidate prediction models for Work Package 3 (WP3) of the PSO-project called ``Intelligent wind power prediction systems'' (FU4101). The main focus is on the models transforming numerical weather predictions into predictions of power production. The document also outlines the...
Melanoma risk prediction models
Directory of Open Access Journals (Sweden)
Nikolić Jelena
2014-01-01
Full Text Available Background/Aim. The lack of effective therapy for advanced stages of melanoma emphasizes the importance of preventive measures and screenings of population at risk. Identifying individuals at high risk should allow targeted screenings and follow-up involving those who would benefit most. The aim of this study was to identify most significant factors for melanoma prediction in our population and to create prognostic models for identification and differentiation of individuals at risk. Methods. This case-control study included 697 participants (341 patients and 356 controls that underwent extensive interview and skin examination in order to check risk factors for melanoma. Pairwise univariate statistical comparison was used for the coarse selection of the most significant risk factors. These factors were fed into logistic regression (LR and alternating decision trees (ADT prognostic models that were assessed for their usefulness in identification of patients at risk to develop melanoma. Validation of the LR model was done by Hosmer and Lemeshow test, whereas the ADT was validated by 10-fold cross-validation. The achieved sensitivity, specificity, accuracy and AUC for both models were calculated. The melanoma risk score (MRS based on the outcome of the LR model was presented. Results. The LR model showed that the following risk factors were associated with melanoma: sunbeds (OR = 4.018; 95% CI 1.724- 9.366 for those that sometimes used sunbeds, solar damage of the skin (OR = 8.274; 95% CI 2.661-25.730 for those with severe solar damage, hair color (OR = 3.222; 95% CI 1.984-5.231 for light brown/blond hair, the number of common naevi (over 100 naevi had OR = 3.57; 95% CI 1.427-8.931, the number of dysplastic naevi (from 1 to 10 dysplastic naevi OR was 2.672; 95% CI 1.572-4.540; for more than 10 naevi OR was 6.487; 95%; CI 1.993-21.119, Fitzpatricks phototype and the presence of congenital naevi. Red hair, phototype I and large congenital naevi were
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
International Nuclear Information System (INIS)
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
Directory of Open Access Journals (Sweden)
Rachel V. Thakore
2014-01-01
Full Text Available Purpose. To determine if the American Society of Anesthesiologist (ASA score can be used to predict hospital charges for inpatient services. Materials and Methods. A retrospective chart review was conducted at a level I trauma center on 547 patients over the age of 60 who presented with a hip fracture and required operative fixation. Hospital charges associated with inpatient and postoperative services were organized within six categories of care. Analysis of variance and a linear regression model were performed to compare preoperative ASA scores with charges and inpatient services. Results. Inpatient and postoperative charges and services were significantly associated with patients’ ASA scores. Patients with an ASA score of 4 had the highest average inpatient charges of services of $15,555, compared to $10,923 for patients with an ASA score of 2. Patients with an ASA score of 4 had an average of 45.3 hospital services compared to 24.1 for patients with a score of 2. Conclusions. A patient’s ASA score is associated with total and specific hospital charges related to inpatient services. The findings of this study will allow payers to identify the major cost drivers for inpatient services based on a hip fracture patient’s preoperative physical status.
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
DEFF Research Database (Denmark)
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
Directory of Open Access Journals (Sweden)
Van Cauteren T.
2010-04-01
Full Text Available We present a Regge-inspired eﬀective-Lagrangian framework for charged-kaon photoproduction from the deuteron. Quasi-free kaon production is investigated using the Regge-plus-resonance elementary operator within the non-relativistic plane-wave impulse approximation. The Regge-plus-resonance model was developed to describe photoinduced and electroinduced kaon production oﬀ protons and can be extended to strangeness production oﬀ neutrons. The non-resonant contributions to the amplitude are modelled in terms of K+ (494 and K*+ (892 Regge-trajectory exchange in the t-channel. This amplitude is supplemented with a selection of s-channel resonance-exchange diagrams. We investigate several sources of theoretical uncertainties on the semi-inclusive charged-kaon production cross section. The experimental error bars on the photocoupling helicity amplitudes turn out to put severe limits on the predictive power when considering quasi-free kaon production on a bound neutron.
Confidence scores for prediction models
DEFF Research Database (Denmark)
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
Directory of Open Access Journals (Sweden)
Kardaś Dariusz
2015-09-01
Full Text Available A one-dimensional transient mathematical model describing thermal and flow phenomena during coal coking in an oven chamber was studied in the paper. It also accounts for heat conduction in the ceramic oven wall when assuming a constant temperature at the heating channel side. The model was solved numerically using partly implicit methods for gas flow and heat transfer problems. The histories of temperature, gas evolution and internal pressure were presented and analysed. The theoretical predictions of temperature change in the centre plane of the coke oven were compared with industrialscale measurements. Both, the experimental data and obtained numerical results show that moisture content determines the coking process dynamics, lagging the temperature increase above the water steam evaporation temperature and in consequence the total coking time. The phenomenon of internal pressure generation in the context of overlapping effects of simultaneously occurring coal transitions - devolatilisation and coal permeability decrease under plastic stage - was also discussed.
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...
Institute of Scientific and Technical Information of China (English)
胡继敏; 金家善; 严志腾
2013-01-01
The thermodynamic charge performance of a variable-mass thermodynamic system was investigated by the simulation modeling and experimental analysis. Three sets of experiments were conducted for various charge time and charge steam flow under three different control strategies of charge valve. Characteristic performance parameters from the average sub-cooled degree and the charging energy coefficient point of views were also defined to evaluate and predict the charge performance of system combined with the simulation model and experimental data. The results show that the average steam flow reflects the average sub-cooled degree qualitatively, while the charging energy coefficients of 74.6%, 69.9% and 100% relate to the end value of the average sub-cooled degree at 2.1, 2.9 and 0 respectively for the three sets of experiments. The mean and maximum deviations of the results predicted from those by experimental data are smaller than 6.8% and 10.8%, respectively. In conclusion, the decrease of average steam flow can effectively increase the charging energy coefficient in the same charge time condition and therefore improve the thermodynamic charge performance of system. While the increase of the charging energy coefficient by extending the charge time needs the consideration of the operating frequency for steam users.
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
International Nuclear Information System (INIS)
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
Energy Technology Data Exchange (ETDEWEB)
Hamad, Said, E-mail: said@upo.es; Balestra, Salvador R.G.; Bueno-Perez, Rocio; Calero, Sofia; Ruiz-Salvador, A. Rabdel
2015-03-15
Atomic partial charges are parameters of key importance in the simulation of Metal–Organic Frameworks (MOFs), since Coulombic interactions decrease with the distance more slowly than van der Waals interactions. But despite its relevance, there is no method to unambiguously assign charges to each atom, since atomic charges are not quantum observables. There are several methods that allow the calculation of atomic charges, most of them starting from the electronic wavefunction or the electronic density or the system, as obtained with quantum mechanics calculations. In this work, we describe the most common methods employed to calculate atomic charges in MOFs. In order to show the influence that even small variations of structure have on atomic charges, we present the results that we obtained for DMOF-1. We also discuss the effect that small variations of atomic charges have on the predicted structural properties of IRMOF-1. - Graphical abstract: We review the different method with which to calculate atomic partial charges that can be used in force field-based calculations. We also present two examples that illustrate the influence of the geometry on the calculated charges and the influence of the charges on structural properties. - Highlights: • The choice of atomic charges is crucial in modeling adsorption and diffusion in MOFs. • Methods for calculating atomic charges in MOFs are reviewed. • We discuss the influence of the framework geometry on the calculated charges. • We discuss the influence of the framework charges on structural the properties.
A contrail cirrus prediction model
Directory of Open Access Journals (Sweden)
U. Schumann
2012-05-01
Full Text Available A new model to simulate and predict the properties of a large ensemble of contrails as a function of given air traffic and meteorology is described. The model is designed for approximate prediction of contrail cirrus cover and analysis of contrail climate impact, e.g. within aviation system optimization processes. The model simulates the full contrail life-cycle. Contrail segments form between waypoints of individual aircraft tracks in sufficiently cold and humid air masses. The initial contrail properties depend on the aircraft. The advection and evolution of the contrails is followed with a Lagrangian Gaussian plume model. Mixing and bulk cloud processes are treated quasi analytically or with an effective numerical scheme. Contrails disappear when the bulk ice content is sublimating or precipitating. The model has been implemented in a "Contrail Cirrus Prediction Tool" (CoCiP. This paper describes the model assumptions, the equations for individual contrails, and the analysis-method for contrail-cirrus cover derived from the optical depth of the ensemble of contrails and background cirrus. The model has been applied for a case study and compared to the results of other models and in-situ contrail measurements. The simple model reproduces a considerable part of observed contrail properties. Mid-aged contrails provide the largest contributions to the product of optical depth and contrail width, important for climate impact.
A contrail cirrus prediction model
Directory of Open Access Journals (Sweden)
U. Schumann
2011-11-01
Full Text Available A new model to simulate and predict the properties of a large ensemble of contrails as a function of given air traffic and meteorology is described. The model is designed for approximate prediction of contrail cirrus cover and analysis of contrail climate impact, e.g. within aviation system optimization processes. The model simulates the full contrail life-cycle. Contrail segments form between waypoints of individual aircraft tracks in sufficiently cold and humid air masses. The initial contrail properties depend on the aircraft. The advection and evolution of the contrails is followed with a Lagrangian Gaussian plume model. Mixing and bulk cloud processes are treated quasi analytically or with an effective numerical scheme. Contrails disappear when the bulk ice content is sublimating or precipitating. The model has been implemented in a "Contrail Cirrus Prediction Tool" (CoCiP. This paper describes the model assumptions, the equations for individual contrails, and the analysis-method for contrail-cirrus cover derived from the optical depth of the ensemble of contrails and background cirrus. The model has been applied for a case study and compared to the results of other models and in-situ contrail measurements. The simple model reproduces a considerable part of observed contrail properties. Mid-aged contrails provide the largest contributions to the product of optical depth and contrail width, important for climate impact.
Schizophrenia and Crime: How Predictable Are Charges, Convictions and Violence?
Heinrichs, R. Walter; Sam, Eleanor P.
2012-01-01
The schizophrenia-crime relationship was studied in 151 research participants meeting DSM-IV criteria for schizophrenia or schizoaffective disorder and with histories positive or negative for criminal charges, convictions and offences involving violence. These crime-related variables were regressed on a block of nine predictors reflecting…
Directory of Open Access Journals (Sweden)
Ricardo Infante-Castillo
2012-01-01
Full Text Available This work presents a new quantitative model to predict the heat of explosion of nitroaromatic compounds using the natural bond orbital (NBO charge and 15N NMR chemical shifts of the nitro groups (15NNitro as structural parameters. The values of the heat of explosion predicted for 21 nitroaromatic compounds using the model described here were compared with experimental data. The prediction ability of the model was assessed by the leave-one-out cross-validation method. The cross-validation results show that the model is significant and stable and that the predicted accuracy is within 0.146 MJ kg−1, with an overall root mean squared error of prediction (RMSEP below 0.183 MJ kg−1. Strong correlations were observed between the heat of explosion and the charges (R2 = 0.9533 and 15N NMR chemical shifts (R2 = 0.9531 of the studied compounds. In addition, the dependence of the heat of explosion on the presence of activating or deactivating groups of nitroaromatic explosives was analyzed. All calculations, including optimizations, NBO charges, and 15NNitro NMR chemical shifts analyses, were performed using density functional theory (DFT and a 6-311+G(2d,p basis set. Based on these results, this practical quantitative model can be used as a tool in the design and development of highly energetic materials (HEM based on nitroaromatic compounds.
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.
International Nuclear Information System (INIS)
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
International Nuclear Information System (INIS)
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
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
The concept of Space Charge Capacitance (SCC) is proposed and used to make a novel analytical charge model of quantized inversion layer in MOS structures. Based on SCC,continuous expressions of surface potential and inversion layer carrier density are derived.Quantum mechanical effects on both inversion layer carrier density and surface potential are extensively included. The accuracy of the model is verified by the numerical solution to Schrodinger and Poisson equation and the model is demonstrated,too.
Modeling of the charging step of metal hydrides tanks for hydrogen storage
International Nuclear Information System (INIS)
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
International Nuclear Information System (INIS)
Almost all of the 3 · 1053 ergs liberated in a core collapse supernova is radiated as neutrinos by the cooling neutron star. I will argue that these neutrinos interact with nuclei in the ejected shells of the supernovae to produce new elements. It appears that this nucleosynthesis mechanism is responsible for the galactic abundances of 7Li, 11B, 19F, 138La, and 180Ta, and contributes significantly to the abundances of about 15 other light nuclei. I discuss shell model predictions for the charged and neutral current allowed and first-forbidden responses of the parent nuclei, as well as the spallation processes that produce the new elements. 18 refs., 1 fig., 1 tab
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
Directory of Open Access Journals (Sweden)
Alexander M. Blokhin
2002-11-01
Full Text Available A mathematical model of charge transport in semiconductors is considered. The model is a quasilinear system of differential equations. A problem of finding an additional entropy conservation law and system symmetrization are solved.
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
Directory of Open Access Journals (Sweden)
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
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correlation. This shows that an NMP-based theory of the bias temperature instability can both explain characteristic time constants experimentally found in the drain and the gate current after bias temperature stress as well as the overall threshold voltage shift. These findings imply that for an accurate lifetime prediction an NMP-based theory is a good choice. However, in order to obtain an accurate lifetime prediction information on the threshold voltage shift caused by a single discrete trap created during bias temperature stress needs to be investigated. To this end small area MOSFETs have been investigated on a statistical basis using random discrete doping in order to determine the cumulative distribution function (CFD) of threshold voltage shifts caused by random discrete charged traps as well as their characteristic capture and emission times. It is found that the experimentally observed CFDs of the threshold voltage shifts caused by single charged traps cannot be reproduced using Minimos-NT by considering potential fluctuations alone. Thus further investigations into this subject are needed. Since the study of hot-carrier degradation requires exact information on the energy distribution of charge carriers, a solution of the Boltzmann transport equation is necessary. For detailed investigations into hot-carrier degradation, ViennaSHE, a device simulator based on a spherical harmonics expansion (SHE) of the Boltzmann transport equation, has been extended in the course of this thesis. To compare SHE to moment-based transport models, quantum correction models, variability caused by random discrete dopants, the classical SRH trapping theory as well as a four state degradation model based on non-radiative multi-phonon theory are incorporated into the simulator. These additions to ViennaSHE allow to evaluate the device characteristics of virgin as well as degraded devices under hot-carrier or bias temperature stress or both. Additionally, ViennaSHE is extended by the
Production of Charged Scalars from the Littlest Higgs Model Associated with Top Quark at LHC
Institute of Scientific and Technical Information of China (English)
LIU Wei-Na; LIU Yao-Bei; LI Ping; SHEN Jie-Fen; GOU Qing-Quan; CUI Xiao-Min; ZHAO Yan-Ping; REN Xiao-Yan
2008-01-01
The littlest Higgs (LH) model is the most economical one among various little Higgs models, which predicts the existence of the charged scalars φ±. In this paper, we study the production of the charged Higgs boson φ- with single top quark via the process gb → tφ- at the CERN Large Hadron Collider (LHC). The numerical results show that the production cross section is smaller than 0.2 pb in most of the parameters space, it is very difficult to observe the signatures of the charged scalars via the process pp → gb + X → tφ- + X at the LHC experiments. However, it can open a window to distinguish the top-pions in the TC2 model or charged Higgs in the MSSM from φ±.
International Nuclear Information System (INIS)
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
International Nuclear Information System (INIS)
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
International Nuclear Information System (INIS)
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
Energy Technology Data Exchange (ETDEWEB)
Fernández, Ariel, E-mail: ariel@afinnovation.com [Argentine Institute of Mathematics (I. A. M.), National Research Council (CONICET), Buenos Aires 1083 (Argentina); Collegium Basilea – Institute for Advanced Study, Basel CH4053 (Switzerland)
2015-10-16
The spontaneous negative charging of aqueous nonpolar interfaces has eluded quantitative first-principle prediction, possibly because it steadfastly challenges the classical Debye dielectric picture. In this work we show that quantitative prediction requires a substantive revision of Debye's linear dielectric ansatz to incorporate an anomalous polarization component yielding electrostatic energy stored as interfacial tension and detailed enough to account for the differences in electronic structure between water and its ionized states. The minimization of this interfacial tension is due to a quantum effect resulting in the reduction in hydrogen-bond frustration that takes place upon hydroxide ion adsorption. The quantitative predictions are validated vis-à-vis measurements of the free energy change associated with hydroxide adsorption obtained using sum-frequency vibrational spectroscopy. - Highlights: • Spontaneous charging of aqueous nonpolar interfaces challenges Debye dielectrics. • A quantum non-Debye theory of interfacial tension is developed. • The minimization of the interfacial tension promotes hydroxide ion adsorption.
International Nuclear Information System (INIS)
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
Indian Academy of Sciences (India)
M Krishnan; A Verma; S Balasubramanian
2001-10-01
Hydrogen bonding in small water clusters is studied through computer simulation methods using a sophisticated, empirical model of interaction developed by Rick et al (S W Rick, S J Stuart and B J Berne 1994 J. Chem. Phys. 101 6141) and others. The model allows for the charges on the interacting sites to fluctuate as a function of time, depending on their local environment. The charge flow is driven by the difference in the electronegativity of the atoms within the water molecule, thus effectively mimicking the effects of polarization of the charge density. The potential model is thus transferable across all phases of water. Using this model, we have obtained the minimum energy structures of water clusters up to a size of ten. The cluster structures agree well with experimental data. In addition, we are able to distinctly identify the hydrogens that form hydrogen bonds based on their charges alone, a feature that is not possible in simulations using fixed charge models. We have also studied the structure of liquid water at ambient conditions using this fluctuating charge model.
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
Directory of Open Access Journals (Sweden)
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
DEFF Research Database (Denmark)
Fan, Jianhua; Andersen, Elsa; Furbo, Simon;
2010-01-01
The charging behaviour of smart solar tanks for solar combisystems for one-family houses is investigated with detailed Computational Fluid Dynamics (CFD) modelling and Particle Image Velocimetry (PIV) measurements. The smart solar tank can be charged with a variable auxiliary volume fitted to the...... 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
DEFF Research Database (Denmark)
Fan, Jianhua; Andersen, Elsa; Furbo, Simon;
The charging behaviour of smart solar tanks for solar combisystems for one-family houses is investigated with detailed Computational Fluid Dynamics (CFD) modelling and Particle Image Velocimetry (PIV) measurements. The smart solar tank can be charged with a variable auxiliary volume fitted to the...... 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
Directory of Open Access Journals (Sweden)
David Ebert
2006-08-01
Full Text Available One of the most common criticisms of archaeological predictive modelling is that it fails to account for temporal or functional differences in sites. However, a practical solution to temporal or functional predictive modelling has proven to be elusive. This article discusses temporal predictive modelling, focusing on the difficulties of employing temporal variables, then introduces and tests a simple methodology for the implementation of temporal modelling. The temporal models thus created are then compared to a traditional predictive model.
Black hole evaporation in a noncommutative charged Vaidya model
Energy Technology Data Exchange (ETDEWEB)
Sharif, M., E-mail: msharif.math@pu.edu.pk; Javed, W. [University of the Punjab, Department of Mathematics (Pakistan)
2012-06-15
We study the black hole evaporation and Hawking radiation for a noncommutative charged Vaidya black hole. For this purpose, we determine a spherically symmetric charged Vaidya model and then formulate a noncommutative Reissner-Nordstroem-like solution of this model, which leads to an exact (t - r)-dependent metric. The behavior of the temporal component of this metric and the corresponding Hawking temperature are investigated. The results are shown in the form of graphs. Further, we examine the tunneling process of charged massive particles through the quantum horizon. We find that the tunneling amplitude is modified due to noncommutativity. Also, it turns out that the black hole evaporates completely in the limits of large time and horizon radius. The effect of charge is to reduce the temperature from a maximum value to zero. We note that the final stage of black hole evaporation is a naked singularity.
Black Hole Evaporation in a Noncommutative Charged Vaidya Model
Sharif, M
2012-01-01
The aim of this paper is to study the black hole evaporation and Hawking radiation for a noncommutative charged Vaidya black hole. For this purpose, we determine spherically symmetric charged Vaidya model and then formulate a noncommutative Reissner-Nordstr$\\ddot{o}$m-like solution of this model which leads to an exact $(t-r)$ dependent metric. The behavior of temporal component of this metric and the corresponding Hawking temperature is investigated. The results are shown in the form of graphs. Further, we examine the tunneling process of the charged massive particles through the quantum horizon. It is found that the tunneling amplitude is modified due to noncommutativity. Also, it turns out that black hole evaporates completely in the limits of large time and horizon radius. The effect of charge is to reduce the temperature from maximum value to zero. It is mentioned here that the final stage of black hole evaporation turns out to be a naked singularity.
Black hole evaporation in a noncommutative charged Vaidya model
Sharif, M.; Javed, W.
2012-06-01
We study the black hole evaporation and Hawking radiation for a noncommutative charged Vaidya black hole. For this purpose, we determine a spherically symmetric charged Vaidya model and then formulate a noncommutative Reissner-Nordström-like solution of this model, which leads to an exact ( t - r)-dependent metric. The behavior of the temporal component of this metric and the corresponding Hawking temperature are investigated. The results are shown in the form of graphs. Further, we examine the tunneling process of charged massive particles through the quantum horizon. We find that the tunneling amplitude is modified due to noncommutativity. Also, it turns out that the black hole evaporates completely in the limits of large time and horizon radius. The effect of charge is to reduce the temperature from a maximum value to zero. We note that the final stage of black hole evaporation is a naked singularity.
Black hole evaporation in a noncommutative charged Vaidya model
International Nuclear Information System (INIS)
We study the black hole evaporation and Hawking radiation for a noncommutative charged Vaidya black hole. For this purpose, we determine a spherically symmetric charged Vaidya model and then formulate a noncommutative Reissner-Nordström-like solution of this model, which leads to an exact (t − r)-dependent metric. The behavior of the temporal component of this metric and the corresponding Hawking temperature are investigated. The results are shown in the form of graphs. Further, we examine the tunneling process of charged massive particles through the quantum horizon. We find that the tunneling amplitude is modified due to noncommutativity. Also, it turns out that the black hole evaporates completely in the limits of large time and horizon radius. The effect of charge is to reduce the temperature from a maximum value to zero. We note that the final stage of black hole evaporation is a naked singularity.
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
Energy Technology Data Exchange (ETDEWEB)
Landi, E.; Oran, R.; Lepri, S. T.; Zurbuchen, T. H.; Fisk, L. A.; Van der Holst, B. [Department of Atmospheric, Oceanic and Space Sciences, University of Michigan, Ann Arbor, MI 48109 (United States)
2014-08-01
We test three theoretical models of the fast solar wind with a set of remote sensing observations and in-situ measurements taken during the minimum of solar cycle 23. First, the model electron density and temperature are compared to SOHO/SUMER spectroscopic measurements. Second, the model electron density, temperature, and wind speed are used to predict the charge state evolution of the wind plasma from the source regions to the freeze-in point. Frozen-in charge states are compared with Ulysses/SWICS measurements at 1 AU, while charge states close to the Sun are combined with the CHIANTI spectral code to calculate the intensities of selected spectral lines, to be compared with SOHO/SUMER observations in the north polar coronal hole. We find that none of the theoretical models are able to completely reproduce all observations; namely, all of them underestimate the charge state distribution of the solar wind everywhere, although the levels of disagreement vary from model to model. We discuss possible causes of the disagreement, namely, uncertainties in the calculation of the charge state evolution and of line intensities, in the atomic data, and in the assumptions on the wind plasma conditions. Last, we discuss the scenario where the wind is accelerated from a region located in the solar corona rather than in the chromosphere as assumed in the three theoretical models, and find that a wind originating from the corona is in much closer agreement with observations.
DETAILED MODELLING OF CHARGING BEHAVIOUR OF SMART SOLAR TANKS
Fan, Jianhua; Andersen, Elsa; Furbo, Simon; Perers, Bengt
2010-01-01
The charging behaviour of smart solar tanks for solar combisystems for one-family houses is investigated with detailed Computational Fluid Dynamics (CFD) modelling and Particle Image Velocimetry (PIV) measurements. The smart solar tank can be charged with a variable auxiliary volume fitted to the expected future energy demand. Therefore the heat loss from the tank is decreased and the thermal performance of the solar heating system is increased compared to a traditional system with a fixed au...
Image Charge Undulator: Theoretical Model and Technical Issues
International Nuclear Information System (INIS)
A new device, an image charge undulator, has been proposed recently [1] to utilize this mechanism for generating coherent hard radiation. We demonstrate physics principle of this device by a 2D model of a uniform sheet beam. The transverse image charge wakefields, synchrotron radiation FR-equency and coherent radiation gain length are presented. We discuss a proof-of-principle experiment that takes into consideration such technical issues as grating fabrication, flat beams and beam alignment
Kiiskinen, A P
2004-01-01
This thesis describes direct searches for pair production of charged Higgs bosons performed in the data collected by the DELPHI detector at the LEP collider at CERN. In addition, the possibilities to discover and study heavy charged Higgs bosons at possible future high-energy linear colliders are presented. The existence of charged Higgs bosons is predicted by many extensions of the Standard Model. A possible discovery of these particles would be a solid proof for physics beyond the Standard Model. Discovery of charged Higgs bosons, and measurement of their properties, would also provide useful information about the structure of the more general theory. New analysis methods were developed for the searches performed at LEP. A large, previously unexplored, mass range for cover but no evidence for the existence of the charged Higgs bosons was found. This allowed setting new lower mass limits for the charged Higgs boson within the framework of general two Higgs doublet models. Results have been interpreted and pr...
Business Models for Solar Powered Charging Stations to Develop Infrastructure for Electric Vehicles
Directory of Open Access Journals (Sweden)
Jessica Robinson
2014-10-01
Full Text Available Electric power must become less dependent on fossil fuels and transportation must become more electric to decrease carbon emissions and mitigate climate change. Increasing availability and accessibility of charging stations is predicted to increase purchases of electric vehicles. In order to address the current inadequate charging infrastructure for electric vehicles, major entities must adopt business models for solar powered charging stations (SPCS. These SPCS should be located in parking lots to produce electricity for the grid and provide an integrated infrastructure for charging electric vehicles. Due to the lack of information related to SPCS business models, this manuscript designs several models for major entities including industry, the federal and state government, utilities, universities, and public parking. A literature review of the available relevant business models and case studies of constructed charging stations was completed to support the proposals. In addition, a survey of a university’s students, staff, and faculty was conducted to provide consumer research on people’s opinion of SPCS construction and preference of business model aspects. Results showed that 69% of respondents would be more willing to invest in an electric vehicle if there was sufficient charging station infrastructure at the university. Among many recommendations, the business models suggest installing level 1 charging for the majority of entities, and to match entities’ current pricing structures for station use. The manuscript discusses the impacts of fossil fuel use, and the benefits of electric car and SPCS use, accommodates for the present gap in available literature on SPCS business models, and provides current consumer data for SPCS and the models proposed.
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
DEFF Research Database (Denmark)
Rawlings, James B.; Bonné, Dennis; Jørgensen, John Bagterp;
2008-01-01
In this work, a new model predictive controller is developed that handles unreachable setpoints better than traditional model predictive control methods. The new controller induces an interesting fast/slow asymmetry in the tracking response of the system. Nominal asymptotic stability of the optimal...
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
Energy Technology Data Exchange (ETDEWEB)
Thele, M.; Schiffer, J.; Sauer, D.U. [Electrochemical Energy Conversion and Storage Systems Group, Institute for Power Electronics and Electrical Drives (ISEA), RWTH Aachen University, Jaegerstrasse 17-19, D-52066 Aachen (Germany); Karden, E.; Surewaard, E. [Ford Research Center Aachen, Aachen (Germany)
2007-05-25
This paper presents a model for flooded and VRLA batteries that is parameterized by impedance spectroscopy and includes the overcharging effects to allow charge-acceptance simulations (e.g. for regenerative-braking drive-cycle profiles). The full dynamic behavior and the short-term charge/discharge history is taken into account. This is achieved by a detailed modeling of the sulfate crystal growth and modeling of the internal gas recombination cycle. The model is applicable in the full realistic temperature and current range of automotive applications. For model validation, several load profiles (covering the dynamics and the current range appearing in electrically assisted or hybrid cars) are examined and the charge-acceptance limiting effects are elaborately discussed. The validation measurements have been performed for different types of lead-acid batteries (flooded and VRLA). The model is therefore an important tool for the development of automotive power nets, but it also allows to analyze different charging strategies and energy gains which can be achieved during regenerative-braking. (author)
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
International Nuclear Information System (INIS)
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
DEFF Research Database (Denmark)
Brunskog, Jonas
2012-01-01
In order to reach robust and simplified yet accurate prediction models, energy based principle are commonly used in many fields of acoustics, especially in building acoustics. This includes simple energy flow models, the framework of statistical energy analysis (SEA) as well as more elaborated...... principles as, e.g., wave intensity analysis (WIA). The European standards for building acoustic predictions, the EN 12354 series, are based on energy flow and SEA principles. In the present paper, different energy based prediction models are discussed and critically reviewed. Special attention is placed on...
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
DEFF Research Database (Denmark)
Juhl, Rune; Møller, Jan Kloppenborg; Jørgensen, John Bagterp;
2016-01-01
Pharmacokinetic/pharmakodynamic (PK/PD) modeling for a single subject is most often performed using nonlinear models based on deterministic ordinary differential equations (ODEs), and the variation between subjects in a population of subjects is described using a population (mixed effects) setup...... deterministic and can predict the future perfectly. A more realistic approach would be to allow for randomness in the model due to e.g., the model be too simple or errors in input. We describe a modeling and prediction setup which better reflects reality and suggests stochastic differential equations (SDEs) 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
International Nuclear Information System (INIS)
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
Directory of Open Access Journals (Sweden)
H. M. Holländer
2013-07-01
Full Text Available The purpose of this paper is to stimulate a re-thinking of how we, the catchment hydrologists, could become reliable forecasters. A group of catchment modellers predicted the hydrological response of a man-made 6 ha catchment in its initial phase (Chicken Creek without having access to the observed records. They used conceptually different model families. Their modelling experience differed largely. The prediction exercise was organized in three steps: (1 for the 1st prediction modellers received a basic data set describing the internal structure of the catchment (somewhat more complete than usually available to a priori predictions in ungauged catchments. They did not obtain time series of stream flow, soil moisture or groundwater response. (2 Before the 2nd improved prediction they inspected the catchment on-site and attended a workshop where the modellers presented and discussed their first attempts. (3 For their improved 3rd prediction they were offered additional data by charging them pro forma with the costs for obtaining this additional information. Holländer et al. (2009 discussed the range of predictions obtained in step 1. Here, we detail the modeller's decisions in accounting for the various processes based on what they learned during the field visit (step 2 and add the final outcome of step 3 when the modellers made use of additional data. We document the prediction progress as well as the learning process resulting from the availability of added information. For the 2nd and 3rd step, the progress in prediction quality could be evaluated in relation to individual modelling experience and costs of added information. We learned (i that soft information such as the modeller's system understanding is as important as the model itself (hard information, (ii that the sequence of modelling steps matters (field visit, interactions between differently experienced experts, choice of model, selection of available data, and methods for parameter
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
Institute of Scientific and Technical Information of China (English)
Bo Zeng; Chuan Li; Guo Chen; Xianjun Long
2015-01-01
In order to deeply research the structure discrepancy and modeling mechanism among different grey prediction mo-dels, the equivalence and unbiasedness of grey prediction mo-dels are analyzed and verified. The results show that al the grey prediction models that are strictly derived from x(0)(k) +az(1)(k) = b have the identical model structure and simulation precision. Moreover, the unbiased simulation for the homoge-neous exponential sequence can be accomplished. However, the models derived from dx(1)/dt+ax(1) =b are only close to those derived from x(0)(k)+az(1)(k)=b provided that|a|has to satisfy|a| < 0.1; neither could the unbiased simulation for the homoge-neous exponential sequence be achieved. The above conclusions are proved and verified through some theorems and examples.
Lepton Flavor Violation in Predictive SUSY-GUT Models
Energy Technology Data Exchange (ETDEWEB)
Albright, Carl H.; /Northern Illinois U. /Fermilab; Chen, Mu-Chun; /UC, Irvine
2008-02-01
There have been many theoretical models constructed which aim to explain the neutrino masses and mixing patterns. While many of the models will be eliminated once more accurate determinations of the mixing parameters, especially sin{sup 2} 2{theta}{sub 13}, are obtained, charged lepton flavor violation (LFV) experiments are able to differentiate even further among the models. In this paper, they investigate various rare LFV processes, such as {ell}{sub i} {yields} {ell}{sub j} + {gamma} and {mu} - e conversion, in five predictive SUSY SO(10) models and their allowed soft SUSY breaking parameter space in the constrained minimal SUSY standard model (CMSSM). Utilizing the WMAP dark matter constraints, they obtain lower bounds on the branching ratios of these rare processes and find that at least three of the five models they consider give rise to predictions for {mu} {yields} e + {gamma} that will be tested by the MEG collaboration at PSI. in addition, the next generation {mu} - e conversion experiment has sensitivity to the predictions of all five models, making it an even more robust way to test these models. While generic studies have emphasized the dependence of the branching ratios of these rare processes on the reactor neutrino angle, {theta}{sub 13}, and the mass of the heaviest right-handed neutrino, M{sub 3}, they find very massive M{sub 3} is more significant than large {theta}{sub 13} in leading to branching ratios near to the present upper limits.
Mathematical modeling to predict residential solid waste generation
International Nuclear Information System (INIS)
One of the challenges faced by waste management authorities is determining the amount of waste generated by households in order to establish waste management systems, as well as trying to charge rates compatible with the principle applied worldwide, and design a fair payment system for households according to the amount of residential solid waste (RSW) they generate. The goal of this research work was to establish mathematical models that correlate the generation of RSW per capita to the following variables: education, income per household, and number of residents. This work was based on data from a study on generation, quantification and composition of residential waste in a Mexican city in three stages. In order to define prediction models, five variables were identified and included in the model. For each waste sampling stage a different mathematical model was developed, in order to find the model that showed the best linear relation to predict residential solid waste generation. Later on, models to explore the combination of included variables and select those which showed a higher R2 were established. The tests applied were normality, multicolinearity and heteroskedasticity. Another model, formulated with four variables, was generated and the Durban-Watson test was applied to it. Finally, a general mathematical model is proposed to predict residential waste generation, which accounts for 51% of the total
A space charge compensation model for positive DC ion beams
International Nuclear Information System (INIS)
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
DEFF Research Database (Denmark)
Lukas, Manuel
Stock return predictability is subject to great uncertainty. In this paper we use the model confidence set approach to quantify uncertainty about expected utility from investment, accounting for potential return predictability. For monthly US data and six representative return prediction models, we...... 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
International Nuclear Information System (INIS)
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
Directory of Open Access Journals (Sweden)
Yin Hua
2015-04-01
Full Text Available Estimation of state of charge (SOC is of great importance for lithium-ion (Li-ion batteries used in electric vehicles. This paper presents a state of charge estimation method using nonlinear predictive filter (NPF and evaluates the proposed method on the lithium-ion batteries with different chemistries. Contrary to most conventional filters which usually assume a zero mean white Gaussian process noise, the advantage of NPF is that the process noise in NPF is treated as an unknown model error and determined as a part of the solution without any prior assumption, and it can take any statistical distribution form, which improves the estimation accuracy. In consideration of the model accuracy and computational complexity, a first-order equivalent circuit model is applied to characterize the battery behavior. The experimental test is conducted on the LiCoO2 and LiFePO4 battery cells to validate the proposed method. The results show that the NPF method is able to accurately estimate the battery SOC and has good robust performance to the different initial states for both cells. Furthermore, the comparison study between NPF and well-established extended Kalman filter for battery SOC estimation indicates that the proposed NPF method has better estimation accuracy and converges faster.
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
Institute of Scientific and Technical Information of China (English)
Hu Bo; Huang Shi-Hua; Wu Feng-Min
2013-01-01
A model based on analysis of the self-consistent Poisson-Schrodinger equation is proposed to investigate the tunneling current of electrons in the inversion layer of a p-type metal-oxide-semiconductor (MOS) structure.In this model,the influences of interface trap charge (ITC) at the Si-SiO2 interface and fixed oxide charge (FOC) in the oxide region are taken into account,and one-band effective mass approximation is used.The tunneling probability is obtained by employing the transfer matrix method.Further,the effects of in-plane momentum on the quantization in the electron motion perpendicular to the Si-SiO2 interface of a MOS device are investigated.Theoretical simulation results indicate that both ITC and FOC have great influence on the tunneling current through a MOS structure when their densities are larger than 1012 cm-2,which results from the great change of bound electrons near the Si-SiO2 interface and the oxide region.Therefore,for real ultrathin MOS structures with ITC and FOC,this model can give a more accurate description for the tunneling current in the inversion layer.
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
Institute of Scientific and Technical Information of China (English)
苏雪松; 岳崇兴; 张娇; 王珏
2011-01-01
The Higgs triplet model （HTM） predicts the existence of a pair of doubly charged Higgs bosons H±±. Single production of H±± via e7 collision at the next generation e＋ e- International Linear Collider （ILC） and the Large Hadron electron Collider （LHeC） is considered. The numerical results show that the production cross sections are very sensitive to the neutrino oscillation parameters. Their values for the inverted hierarchy mass spectrum are larger than those for the normal hierarchy mass spectrum at these two kinds of collider experiments. With reasonable values of the relevant free parameters, the possible signals of the doubly charged Higgs bosons predicted by the HTM might be detected in future ILC experiments.
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
International Nuclear Information System (INIS)
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
International Nuclear Information System (INIS)
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
Institute of Scientific and Technical Information of China (English)
GE Ji; JIN Zhi; SU Yong-Bo; CHENG Wei; WANG Xian-Wai; CHEN Gao-Peng; LIU Xin-Yu
2009-01-01
We develop a physics-based charge-control InP double heterojunction bipolar transistor model including three important effects: current blocking, mobile-charge modulation of the base-collector capacitance and velocity-field modulation in the transit time. The bias-dependent base-collector depletion charge is obtained analytically, which takes into account the mobile-charge modulation. Then, a measurement based voltage-dependent transit time formulation is implemented. As a result, over a wide range of biases, the developed model shows good agreement between the modeled and measured S-parameters and cutoff frequency. Also, the model considering current blocking effect demonstrates more accurate prediction of the output characteristics than conventional vertical bipolar inter company results.
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
International Nuclear Information System (INIS)
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
Directory of Open Access Journals (Sweden)
Raphael Silveira Amaro
2016-03-01
Full Text Available In the last decades, a remarkable number of models, variants from the Autoregressive Conditional Heteroscedastic family, have been developed and empirically tested, making extremely complex the process of choosing a particular model. This research aim to compare the predictive capacity, using the Model Confidence Set procedure, than five conditional heteroskedasticity models, considering eight different statistical probability distributions. The financial series which were used refers to the log-return series of the Bovespa index and the Dow Jones Industrial Index in the period between 27 October 2008 and 30 December 2014. The empirical evidences showed that, in general, competing models have a great homogeneity to make predictions, either for a stock market of a developed country or for a stock market of a developing country. An equivalent result can be inferred for the statistical probability distributions that were used.
A Predictive Model for Root Caries Incidence.
Ritter, André V; Preisser, John S; Puranik, Chaitanya P; Chung, Yunro; Bader, James D; Shugars, Daniel A; Makhija, Sonia; Vollmer, William M
2016-01-01
This study aimed to find the set of risk indicators best able to predict root caries (RC) incidence in caries-active adults utilizing data from the Xylitol for Adult Caries Trial (X-ACT). Five logistic regression models were compared with respect to their predictive performance for incident RC using data from placebo-control participants with exposed root surfaces at baseline and from two study centers with ancillary data collection (n = 155). Prediction performance was assessed from baseline variables and after including ancillary variables [smoking, diet, use of removable partial dentures (RPD), toothbrush use, income, education, and dental insurance]. A sensitivity analysis added treatment to the models for both the control and treatment participants (n = 301) to predict RC for the control participants. Forty-nine percent of the control participants had incident RC. The model including the number of follow-up years at risk, the number of root surfaces at risk, RC index, gender, race, age, and smoking resulted in the best prediction performance, having the highest AUC and lowest Brier score. The sensitivity analysis supported the primary analysis and gave slightly better performance summary measures. The set of risk indicators best able to predict RC incidence included an increased number of root surfaces at risk and increased RC index at baseline, followed by white race and nonsmoking, which were strong nonsignificant predictors. Gender, age, and increased number of follow-up years at risk, while included in the model, were also not statistically significant. The inclusion of health, diet, RPD use, toothbrush use, income, education, and dental insurance variables did not improve the prediction performance. PMID:27160516
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
Directory of Open Access Journals (Sweden)
Hugues Murray
2012-01-01
Full Text Available Based on a 1D Poissons equation resolution, we present an analytic model of inversion charges allowing calculation of the drain current and transconductance in the Metal Oxide Semiconductor Field Effect Transistor. The drain current and transconductance are described by analytical functions including mobility corrections and short channel effects (CLM, DIBL. The comparison with the Pao-Sah integral shows excellent accuracy of the model in all inversion modes from strong to weak inversion in submicronics MOSFET. All calculations are encoded with a simple C program and give instantaneous results that provide an efficient tool for microelectronics users.
Modeling Dendrimers Charge Interaction in Solution: Relevance in Biosystems
Directory of Open Access Journals (Sweden)
Domenico Lombardo
2014-01-01
Full Text Available Dendrimers are highly branched macromolecules obtained by stepwise controlled, reaction sequences. The ability to be designed for specific applications makes dendrimers unprecedented components to control the structural organization of matter during the bottom-up synthesis of functional nanostructures. For their applications in the field of biotechnology the determination of dendrimer structural properties as well as the investigation of the specific interaction with guest components are needed. We show how the analysis of the scattering structure factor S(q, in the framework of current models for charged systems in solution, allows for obtaining important information of the interdendrimers electrostatic interaction potential. The finding of the presented results outlines the important role of the dendrimer charge and the solvent conditions in regulating, through the modulation of the electrostatic interaction potential, great part of the main structural properties. This charge interaction has been indicated by many studies as a crucial factor for a wide range of structural processes involving their biomedical application. Due to their easily controllable properties dendrimers can be considered at the crossroad between traditional colloids, associating polymers, and biological systems and represent then an interesting new technological approach and a suitable model system of molecular organization in biochemistry and related fields.
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)
Energy Technology Data Exchange (ETDEWEB)
Smith, K.; Wood, E.; Santhanagopalan, S.; Kim, G.; Shi, Y.; Pesaran, A.
2014-09-01
Predictive models of Li-ion battery reliability must consider a multiplicity of electrochemical, thermal and mechanical degradation modes experienced by batteries in application environments. Complicating matters, Li-ion batteries can experience several path dependent degradation trajectories dependent on storage and cycling history of the application environment. Rates of degradation are controlled by factors such as temperature history, electrochemical operating window, and charge/discharge rate. Lacking accurate models and tests, lifetime uncertainty must be absorbed by overdesign and warranty costs. Degradation models are needed that predict lifetime more accurately and with less test data. Models should also provide engineering feedback for next generation battery designs. This presentation reviews both multi-dimensional physical models and simpler, lumped surrogate models of battery electrochemical and mechanical degradation. Models are compared with cell- and pack-level aging data from commercial Li-ion chemistries. The analysis elucidates the relative importance of electrochemical and mechanical stress-induced degradation mechanisms in real-world operating environments. Opportunities for extending the lifetime of commercial battery systems are explored.
Modelling the predictive performance of credit scoring
Directory of Open Access Journals (Sweden)
Shi-Wei Shen
2013-02-01
Full Text Available Orientation: The article discussed the importance of rigour in credit risk assessment.Research purpose: The purpose of this empirical paper was to examine the predictive performance of credit scoring systems in Taiwan.Motivation for the study: Corporate lending remains a major business line for financial institutions. However, in light of the recent global financial crises, it has become extremely important for financial institutions to implement rigorous means of assessing clients seeking access to credit facilities.Research design, approach and method: Using a data sample of 10 349 observations drawn between 1992 and 2010, logistic regression models were utilised to examine the predictive performance of credit scoring systems.Main findings: A test of Goodness of fit demonstrated that credit scoring models that incorporated the Taiwan Corporate Credit Risk Index (TCRI, micro- and also macroeconomic variables possessed greater predictive power. This suggests that macroeconomic variables do have explanatory power for default credit risk.Practical/managerial implications: The originality in the study was that three models were developed to predict corporate firms’ defaults based on different microeconomic and macroeconomic factors such as the TCRI, asset growth rates, stock index and gross domestic product.Contribution/value-add: The study utilises different goodness of fits and receiver operator characteristics during the examination of the robustness of the predictive power of these factors.
Modelling language evolution: Examples and predictions
Gong, Tao; Shuai, Lan; Zhang, Menghan
2014-06-01
We survey recent computer modelling research of language evolution, focusing on a rule-based model simulating the lexicon-syntax coevolution and an equation-based model quantifying the language competition dynamics. We discuss four predictions of these models: (a) correlation between domain-general abilities (e.g. sequential learning) and language-specific mechanisms (e.g. word order processing); (b) coevolution of language and relevant competences (e.g. joint attention); (c) effects of cultural transmission and social structure on linguistic understandability; and (d) commonalities between linguistic, biological, and physical phenomena. All these contribute significantly to our understanding of the evolutions of language structures, individual learning mechanisms, and relevant biological and socio-cultural factors. We conclude the survey by highlighting three future directions of modelling studies of language evolution: (a) adopting experimental approaches for model evaluation; (b) consolidating empirical foundations of models; and (c) multi-disciplinary collaboration among modelling, linguistics, and other relevant disciplines.
Global Solar Dynamo Models: Simulations and Predictions
Indian Academy of Sciences (India)
Mausumi Dikpati; Peter A. Gilman
2008-03-01
Flux-transport type solar dynamos have achieved considerable success in correctly simulating many solar cycle features, and are now being used for prediction of solar cycle timing and amplitude.We first define flux-transport dynamos and demonstrate how they work. The essential added ingredient in this class of models is meridional circulation, which governs the dynamo period and also plays a crucial role in determining the Sun’s memory about its past magnetic fields.We show that flux-transport dynamo models can explain many key features of solar cycles. Then we show that a predictive tool can be built from this class of dynamo that can be used to predict mean solar cycle features by assimilating magnetic field data from previous cycles.
Grey Model for Stream Flow Prediction
Directory of Open Access Journals (Sweden)
P. Syamala
2012-04-01
Full Text Available Design, operation and planning of water resources, irrigation and water supply systems require estimation of stream flow. A grey system or stochastic approach is required for dealing with the hydrological complexities of mid and long-term stream flow prediction. Generally relatively long period data series of stream flow records is required for the prediction using stochastic methods. In developing countries like India, availability of long period hydrological records is a problem. Grey system theory is applicable in the case of unclear innerrelationship, uncertain mechanisms and insufficient information and requires only small samples for parameter estimation. Stream flow records of Bharathapuzha river basin, Kerala, India is subjected to grey analysis. Model parameters were estimated using least-squares method. Statistical indices for the developed models indicate their ability to predict stream flow in the river under study with reasonable accuracy
An exponential filter model predicts lightness illusions
Directory of Open Access Journals (Sweden)
Astrid eZeman
2015-06-01
Full Text Available Lightness, or perceived reflectance of a surface, is influenced by surrounding context. This is demonstrated by the Simultaneous Contrast Illusion (SCI, where a grey patch is perceived lighter against a black background and vice versa. Conversely, assimilation is where the lightness of the target patch moves towards that of the bounding areas and can be demonstrated in White's effect. Blakeslee and McCourt (2007 introduced an oriented difference-of-Gaussian (ODOG model that is able to account for both contrast and assimilation in a number of lightness illusions and that has been subsequently improved using localized normalization techniques. We introduce a model inspired by image statistics that is based on a family of exponential filters, with kernels spanning across multiple sizes and shapes. We include an optional second stage of normalization based on contrast gain control. Our model was tested on a well-known set of lightness illusions that have previously been used to evaluate ODOG and its variants, and model lightness values were compared with typical human data. We investigate whether predictive success depends on filters of a particular size or shape and whether pooling information across filters can improve performance. The best single filter correctly predicted the direction of lightness effects for 21 out of 27 illusions. Combining two filters together increased the best performance to 23, with asymptotic performance at 24 for an arbitrarily large combination of filter outputs. While normalization improved prediction magnitudes, it only slightly improved overall scores in direction predictions. The prediction performance of 24 out of 27 illusions equals that of the best performing ODOG variant, with greater parsimony. Our model shows that V1-style orientation-selectivity is not necessary to account for lightness illusions and that a low-level model based on image statistics is able to account for a wide range of both contrast and
International Nuclear Information System (INIS)
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
International Nuclear Information System (INIS)
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
DEFF Research Database (Denmark)
Bendtsen, Jan Dimon; Trangbæk, K; Stoustrup, Jakob
2010-01-01
This paper deals with hierarchichal model predictive control (MPC) of distributed systems. A three level hierachical approach is proposed, consisting of a high level MPC controller, a second level of so-called aggregators, controlled by an online MPC-like algorithm, and a lower level of autonomous...
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
Directory of Open Access Journals (Sweden)
Amila Zukanović
2013-11-01
Full Text Available Objective. The aim of this research was to assess the efficiency of different multifactor models in caries prediction. Material and methods. Data from the questionnaire and objective examination of 109 examinees was entered into the Cariogram, Previser and Caries-Risk Assessment Tool (CAT multifactor risk assessment models. Caries risk was assessed with the help of all three models for each patient, classifying them as low, medium or high-risk patients. The development of new caries lesions over a period of three years [Decay Missing Filled Tooth (DMFT increment = difference between Decay Missing Filled Tooth Surface (DMFTS index at baseline and follow up], provided for examination of the predictive capacity concerning different multifactor models. Results. The data gathered showed that different multifactor risk assessment models give significantly different results (Friedman test: Chi square = 100.073, p=0.000. Cariogram is the model which identified the majority of examinees as medium risk patients (70%. The other two models were more radical in risk assessment, giving more unfavorable risk –profiles for patients. In only 12% of the patients did the three multifactor models assess the risk in the same way. Previser and CAT gave the same results in 63% of cases – the Wilcoxon test showed that there is no statistically significant difference in caries risk assessment between these two models (Z = -1.805, p=0.071. Conclusions. Evaluation of three different multifactor caries risk assessment models (Cariogram, PreViser and CAT showed that only the Cariogram can successfully predict new caries development in 12-year-old Bosnian children.
Disease prediction models and operational readiness.
Directory of Open Access Journals (Sweden)
Courtney D Corley
Full Text Available The objective of this manuscript is to present a systematic review of biosurveillance models that operate on select agents and can forecast the occurrence of a disease event. We define a disease event to be a biological event with focus on the One Health paradigm. These events are characterized by evidence of infection and or disease condition. We reviewed models that attempted to predict a disease event, not merely its transmission dynamics and we considered models involving pathogens of concern as determined by the US National Select Agent Registry (as of June 2011. We searched commercial and government databases and harvested Google search results for eligible models, using terms and phrases provided by public health analysts relating to biosurveillance, remote sensing, risk assessments, spatial epidemiology, and ecological niche modeling. After removal of duplications and extraneous material, a core collection of 6,524 items was established, and these publications along with their abstracts are presented in a semantic wiki at http://BioCat.pnnl.gov. As a result, we systematically reviewed 44 papers, and the results are presented in this analysis. We identified 44 models, classified as one or more of the following: event prediction (4, spatial (26, ecological niche (28, diagnostic or clinical (6, spread or response (9, and reviews (3. The model parameters (e.g., etiology, climatic, spatial, cultural and data sources (e.g., remote sensing, non-governmental organizations, expert opinion, epidemiological were recorded and reviewed. A component of this review is the identification of verification and validation (V&V methods applied to each model, if any V&V method was reported. All models were classified as either having undergone Some Verification or Validation method, or No Verification or Validation. We close by outlining an initial set of operational readiness level guidelines for disease prediction models based upon established Technology
Model Predictive Control based on Finite Impulse Response Models
DEFF Research Database (Denmark)
Prasath, Guru; Jørgensen, John Bagterp
2008-01-01
We develop a regularized l2 finite impulse response (FIR) predictive controller with input and input-rate constraints. Feedback is based on a simple constant output disturbance filter. The performance of the predictive controller in the face of plant-model mismatch is investigated by simulations...
Modeling of mesoscopic electrokinetic phenomena using charged dissipative particle dynamics
Deng, Mingge; Li, Zhen; Karniadakis, George
2015-11-01
In this work, we propose a charged dissipative particle dynamics (cDPD) model for investigation of mesoscopic electrokinetic phenomena. In particular, this particle-based method was designed to simulate micro- or nano- flows which governing by Poisson-Nernst-Planck (PNP) equation coupled with Navier-Stokes (NS) equation. For cDPD simulations of wall-bounded fluid systems, a methodology for imposing correct Dirichlet and Neumann boundary conditions for both PNP and NS equations is developed. To validate the present cDPD model and the corresponding boundary method, we perform cDPD simulations of electrostatic double layer (EDL) in the vicinity of a charged wall, and the results show good agreement with the mean-field theoretical solutions. The capacity density of a parallel plate capacitor in salt solution is also investigated with different salt concentration. Moreover, we utilize the proposed methodology to study the electroosmotic and electroosmotic/pressure-driven flow in a micro-channel. In the last, we simulate the dilute polyelectrolyte solution both in bulk and micro-channel, which show the flexibility and capability of this method in studying complex fluids. This work was sponsored by the Collaboratory on Mathematics for Mesoscopic Modeling of Materials (CM4) supported by DOE.
Directory of Open Access Journals (Sweden)
Giuliano Marchi
2015-10-01
Full Text Available ABSTRACT Intrinsic equilibrium constants of 17 representative Brazilian Oxisols were estimated from potentiometric titration measuring the adsorption of H+ and OH− on amphoteric surfaces in suspensions of varying ionic strength. Equilibrium constants were fitted to two surface complexation models: diffuse layer and constant capacitance. The former was fitted by calculating total site concentration from curve fitting estimates and pH-extrapolation of the intrinsic equilibrium constants to the PZNPC (hand calculation, considering one and two reactive sites, and by the FITEQL software. The latter was fitted only by FITEQL, with one reactive site. Soil chemical and physical properties were correlated to the intrinsic equilibrium constants. Both surface complexation models satisfactorily fit our experimental data, but for results at low ionic strength, optimization did not converge in FITEQL. Data were incorporated in Visual MINTEQ and they provide a modeling system that can predict protonation-dissociation reactions in the soil surface under changing environmental conditions.
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
International Nuclear Information System (INIS)
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
Directory of Open Access Journals (Sweden)
J Venkatesh
2012-08-01
Full Text Available Management by metrics is the expectation from the IT service providers to stay as a differentiator. Given a project, the associated parameters and dynamics, the behaviour and outcome need to be predicted. There is lot of focus on the end state and in minimizing defect leakage as much as possible. In most of the cases, the actions taken are re-active. It is too late in the life cycle. Root cause analysis and corrective actions can be implemented only to the benefit of the next project. The focus has to shift left, towards the execution phase than waiting for lessons to be learnt post the implementation. How do we pro-actively predict defect metrics and have a preventive action plan in place. This paper illustrates the process performance model to predict overall defect density based on data from projects in an organization.
Neuro-fuzzy modeling in bankruptcy prediction
Directory of Open Access Journals (Sweden)
Vlachos D.
2003-01-01
Full Text Available For the past 30 years the problem of bankruptcy prediction had been thoroughly studied. From the paper of Altman in 1968 to the recent papers in the '90s, the progress of prediction accuracy was not satisfactory. This paper investigates an alternative modeling of the system (firm, combining neural networks and fuzzy controllers, i.e. using neuro-fuzzy models. Classical modeling is based on mathematical models that describe the behavior of the firm under consideration. The main idea of fuzzy control, on the other hand, is to build a model of a human control expert who is capable of controlling the process without thinking in a mathematical model. This control expert specifies his control action in the form of linguistic rules. These control rules are translated into the framework of fuzzy set theory providing a calculus, which can stimulate the behavior of the control expert and enhance its performance. The accuracy of the model is studied using datasets from previous research papers.
Predictive modeling of nanomaterial exposure effects in biological systems
Directory of Open Access Journals (Sweden)
Liu X
2013-09-01
Full Text Available Xiong Liu,1 Kaizhi Tang,1 Stacey Harper,2 Bryan Harper,2 Jeffery A Steevens,3 Roger Xu1 1Intelligent Automation, Inc., Rockville, MD, USA; 2Department of Environmental and Molecular Toxicology, School of Chemical, Biological, and Environmental Engineering, Oregon State University, Corvallis, OR, USA; 3ERDC Environmental Laboratory, Vicksburg, MS, USA Background: Predictive modeling of the biological effects of nanomaterials is critical for industry and policymakers to assess the potential hazards resulting from the application of engineered nanomaterials. Methods: We generated an experimental dataset on the toxic effects experienced by embryonic zebrafish due to exposure to nanomaterials. Several nanomaterials were studied, such as metal nanoparticles, dendrimer, metal oxide, and polymeric materials. The embryonic zebrafish metric (EZ Metric was used as a screening-level measurement representative of adverse effects. Using the dataset, we developed a data mining approach to model the toxic endpoints and the overall biological impact of nanomaterials. Data mining techniques, such as numerical prediction, can assist analysts in developing risk assessment models for nanomaterials. Results: We found several important attributes that contribute to the 24 hours post-fertilization (hpf mortality, such as dosage concentration, shell composition, and surface charge. These findings concur with previous studies on nanomaterial toxicity using embryonic zebrafish. We conducted case studies on modeling the overall effect/impact of nanomaterials and the specific toxic endpoints such as mortality, delayed development, and morphological malformations. The results show that we can achieve high prediction accuracy for certain biological effects, such as 24 hpf mortality, 120 hpf mortality, and 120 hpf heart malformation. The results also show that the weighting scheme for individual biological effects has a significant influence on modeling the overall impact of
Nonlinear potential model of space-charge-limited electron beams
Energy Technology Data Exchange (ETDEWEB)
Litz, M.S. [Army Research Lab., Adelphi, MD (United States); Golden, J. [Berkeley Research Associates, Springfield, VA (United States)
1995-11-01
A one-dimensional (1D) time-varying nonlinear theory based on the Duffing equation is applied to space-charge limited beams and specifically vircators. This theory classifies test particle trajectories in a modulated nonlinear potential. Two predictions of the theory that can be directly compared to experiment are the final state of electron trajectories and the oscillation frequency of the electrons m the potential well. Experimental measurements of electron flux recorded along the vircator chamber wall correlates well with the numerically integrated final state of electron trajectory in the 1D theory. The oscillation frequency measured in the experiment is shown to be a better match to the oscillation frequency calculated from the nonlinear potential as compared to a parabolic potential (that results from a linear restoring force). In the experiment, random initial conditions arise from beam thermalization and nonuniform electron emission at the surface of the cathode. However, these characteristics alone do not explain the experimentally observed fluctuations in rf power and frequency. The predictions of the time-varying nonlinear potential theory clearly exhibits trends that were observed in the experimental results, in the form of classes of particle trajectories, fluctuations in particle asymptotic states, and particle motion sensitive to the shape of the virtual cathode.
A Massless-Point-Charge Model for the Electron
Directory of Open Access Journals (Sweden)
Daywitt W. C.
2010-04-01
Full Text Available "It is rather remarkable that the modern concept of electrodynamics is not quite 100 years old and yet still does not rest firmly upon uniformly accepted theoretical foundations. Maxwell's theory of the electromagnetic field is firmly ensconced in modern physics, to be sure, but the details of how charged particles are to be coupled to this field remain somewhat uncertain, despite the enormous advances in quantum electrodynamics over the past 45 years. Our theories remain mathematically ill-posed and mired in conceptual ambiguities which quantum mechanics has only moved to another arena rather than resolve. Fundamentally, we still do not understand just what is a charged particle" (Grandy W.T. Jr. Relativistic quantum mechanics of leptons and fields. Kluwer Academic Publishers, Dordrecht-London, 1991, p.367. As a partial answer to the preceeding quote, this paper presents a new model for the electron that combines the seminal work of Puthoff with the theory of the Planck vacuum (PV, the basic idea for the model following from Puthoff with the PV theory adding some important details.
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
Energy Technology Data Exchange (ETDEWEB)
Corley, Courtney D.; Pullum, Laura L.; Hartley, David M.; Benedum, Corey M.; Noonan, Christine F.; Rabinowitz, Peter M.; Lancaster, Mary J.
2014-03-19
INTRODUCTION: The objective of this manuscript is to present a systematic review of biosurveillance models that operate on select agents and can forecast the occurrence of a disease event. One of the primary goals of this research was to characterize the viability of biosurveillance models to provide operationally relevant information for decision makers to identify areas for future research. Two critical characteristics differentiate this work from other infectious disease modeling reviews. First, we reviewed models that attempted to predict the disease event, not merely its transmission dynamics. Second, we considered models involving pathogens of concern as determined by the US National Select Agent Registry (as of June 2011). Methods: We searched dozens of commercial and government databases and harvested Google search results for eligible models utilizing terms and phrases provided by public health analysts relating to biosurveillance, remote sensing, risk assessments, spatial epidemiology, and ecological niche-modeling, The publication date of search results returned are bound by the dates of coverage of each database and the date in which the search was performed, however all searching was completed by December 31, 2010. This returned 13,767 webpages and 12,152 citations. After de-duplication and removal of extraneous material, a core collection of 6,503 items was established and these publications along with their abstracts are presented in a semantic wiki at http://BioCat.pnnl.gov. Next, PNNL’s IN-SPIRE visual analytics software was used to cross-correlate these publications with the definition for a biosurveillance model resulting in the selection of 54 documents that matched the criteria resulting Ten of these documents, However, dealt purely with disease spread models, inactivation of bacteria, or the modeling of human immune system responses to pathogens rather than predicting disease events. As a result, we systematically reviewed 44 papers and the
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
International Nuclear Information System (INIS)
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
DEFF Research Database (Denmark)
Stolfi, A.
2015-01-01
values of L (0.254 mm, 0.330 mm) was produced by comparing predicted values with external face-to-face measurements. After removing outliers, the results show that the developed two-parameter model can serve as tool for modeling the FDM dimensional behavior in a wide range of deposition angles.......This work concerns the effect of deposition angle (a) and layer thickness (L) on the dimensional performance of FDM parts using a predictive model based on the geometrical description of the FDM filament profile. An experimental validation over the whole a range from 0° to 177° at 3° steps and two...
Modeling and Prediction of Krueger Device Noise
Guo, Yueping; Burley, Casey L.; Thomas, Russell H.
2016-01-01
This paper presents the development of a noise prediction model for aircraft Krueger flap devices that are considered as alternatives to leading edge slotted slats. The prediction model decomposes the total Krueger noise into four components, generated by the unsteady flows, respectively, in the cove under the pressure side surface of the Krueger, in the gap between the Krueger trailing edge and the main wing, around the brackets supporting the Krueger device, and around the cavity on the lower side of the main wing. For each noise component, the modeling follows a physics-based approach that aims at capturing the dominant noise-generating features in the flow and developing correlations between the noise and the flow parameters that control the noise generation processes. The far field noise is modeled using each of the four noise component's respective spectral functions, far field directivities, Mach number dependencies, component amplitudes, and other parametric trends. Preliminary validations are carried out by using small scale experimental data, and two applications are discussed; one for conventional aircraft and the other for advanced configurations. The former focuses on the parametric trends of Krueger noise on design parameters, while the latter reveals its importance in relation to other airframe noise components.
Artificial Neural Network Model for Predicting Compressive
Directory of Open Access Journals (Sweden)
Salim T. Yousif
2013-05-01
Full Text Available Compressive strength of concrete is a commonly used criterion in evaluating concrete. Although testing of the compressive strength of concrete specimens is done routinely, it is performed on the 28th day after concrete placement. Therefore, strength estimation of concrete at early time is highly desirable. This study presents the effort in applying neural network-based system identification techniques to predict the compressive strength of concrete based on concrete mix proportions, maximum aggregate size (MAS, and slump of fresh concrete. Back-propagation neural networks model is successively developed, trained, and tested using actual data sets of concrete mix proportions gathered from literature. The test of the model by un-used data within the range of input parameters shows that the maximum absolute error for model is about 20% and 88% of the output results has absolute errors less than 10%. The parametric study shows that water/cement ratio (w/c is the most significant factor affecting the output of the model. The results showed that neural networks has strong potential as a feasible tool for predicting compressive strength of concrete.
Evaluating predictive models of software quality
International Nuclear Information System (INIS)
Applications from High Energy Physics scientific community are constantly growing and implemented by a large number of developers. This implies a strong churn on the code and an associated risk of faults, which is unavoidable as long as the software undergoes active evolution. However, the necessities of production systems run counter to this. Stability and predictability are of paramount importance; in addition, a short turn-around time for the defect discovery-correction-deployment cycle is required. A way to reconcile these opposite foci is to use a software quality model to obtain an approximation of the risk before releasing a program to only deliver software with a risk lower than an agreed threshold. In this article we evaluated two quality predictive models to identify the operational risk and the quality of some software products. We applied these models to the development history of several EMI packages with intent to discover the risk factor of each product and compare it with its real history. We attempted to determine if the models reasonably maps reality for the applications under evaluation, and finally we concluded suggesting directions for further studies.
Expert Fuzzy Model for Avalanche Prediction
Directory of Open Access Journals (Sweden)
Mohan Vizhakat
2003-10-01
Full Text Available It is imperative that the time required for the analysis and prediction of an extremely volatile event like avalanche needs to be reduced to the minimum. This is particularly critical because of the extremely fast and highly uncertain nature of the event itself. Another peculiar nature of such predictions is that these have to be based almost entirely on the long and intermediate-term data/infomation available, since there would hardly be any short-term warnings (unlike as in the case of a storm that could point towards an imminent prediction. Both the above-mentioned factors favour adoption of such techniques of automated analysis, which are fast, accurate, and employable even under uncertainvoids of information. Apart from empirical and statistical methods, one of the highly promising techniques for developing a practical model for prediction of avalanche is that based on rule-based expert systems. However, development of a realistic rule-based expert system based on conventional logic would imply that one has to firstly define the natural phenomenon being modelled at an extremely high resolution and accuracy. The process of defining a highly uncertain phenomenon like the avalanche at such high resolution, and thereafter, framing extensive rules for all the possibilities is likely to make the system extremely complex, and therefore, unmanageable in many ways. This study attempts tosimplify this problem by proposing a simpler and better technique using an algorithm based on fuzzy logic. This algorithm has the potential to handle even highly complex phenomenon, like that of an avalanche in a fundamentally simple manner. Such potential makes it capable of handling the higher levels of details and still contains the complexity within the manageable limits. Additional details would also make the system more accurate and realistic.
Predictions in multifield models of inflation
International Nuclear Information System (INIS)
This paper presents a method for obtaining an analytic expression for the density function of observables in multifield models of inflation with sum-separable potentials. The most striking result is that the density function in general possesses a sharp peak and the location of this peak is only mildly sensitive to the distribution of initial conditions. A simple argument is given for why this result holds for a more general class of models than just those with sum-separable potentials and why for such models, it is possible to obtain robust predictions for observable quantities. As an example, the joint density function of the spectral index and running in double quadratic inflation is computed. For scales leaving the horizon 55 e-folds before the end of inflation, the density function peaks at ns = 0.967 and α = 0.0006 for the spectral index and running respectively
An analytical model for climatic predictions
International Nuclear Information System (INIS)
A climatic model based upon analytical expressions is presented. This model is capable of making long-range predictions of heat energy variations on regional or global scales. These variations can then be transformed into corresponding variations of some other key climatic parameters since weather and climatic changes are basically driven by differential heating and cooling around the earth. On the basis of the mathematical expressions upon which the model is based, it is shown that the global heat energy structure (and hence the associated climatic system) are characterized by zonally as well as latitudinally propagating fluctuations at frequencies downward of 0.5 day-1. We have calculated the propagation speeds for those particular frequencies that are well documented in the literature. The calculated speeds are in excellent agreement with the measured speeds. (author). 13 refs
Model Predictive Control for Smart Energy Systems
DEFF Research Database (Denmark)
Halvgaard, Rasmus
supply electricity reliably to both residential and industrial consumers around the clock. More and more fluctuating renewable energy sources, like wind and solar, are integrated in the power system. Consequently, uncertainty in production starts to affect an otherwise controllable power production...... actors. Chapter 2 provides linear dynamical models of Smart Grid units: Electric Vehicles, buildings with heat pumps, refrigeration systems, solar collectors, heat storage tanks, power plants, and wind farms. The models can be realized as discrete time state space models that fit into a predictive......In this thesis, we consider control strategies for flexible distributed energy resources in the future intelligent energy system – the Smart Grid. The energy system is a large-scale complex network with many actors and objectives in different hierarchical layers. Specifically the power system must...
Charged Lepton Flavor-violating Transitions in Color Octet Model
Li, Bin; Ma, Xiao-Dong
2016-01-01
We study charged lepton flavor-violating (LFV) transitions in the color octet model that generates neutrino mass and lepton mixing at one loop. By taking into account neutrino oscillation data and assuming octet particles of TeV scale mass, we examine the feasibility to detect these transitions in current and future experiments. We find that for general values of parameters the branching ratios for LFV decays of the Higgs and $Z$ bosons are far below current and even future experimental bounds. For LFV transitions of the muon, the present bounds can be satisfied generally, while future sensitivities could distinguish between the singlet and triplet color-octet fermions. The triplet case could be ruled out by future $\\mu-e$ conversion in nuclei, and for the singlet case the conversion and the decays $\\mu\\to 3e,~e\\gamma$ play complementary roles in excluding relatively low mass regions of the octet particles.
Efficient optimization for Model Predictive Control in reservoir models
Borgesen, Jørgen Frenken
2009-01-01
The purpose of this thesis was to study the use of adjoint methods for gradient calculations in Model Predictive Control (MPC) applications. The goal was to find and test efficient optimization methods to use in MPC on oil reservoir models. Handling output constraints in the optimization problem has been studied closer since they deteriorate the efficiency of the MPC applications greatly. Adjoint- and finite difference approaches for gradient calculations was tested on reservoir models to de...
Modeling the Flux-Charge Relation of Memristor with Neural Network of Smooth Hinge Functions
Directory of Open Access Journals (Sweden)
X. Mu
2014-09-01
Full Text Available The memristor was proposed to characterize the flux-charge relation. We propose the generalized flux-charge relation model of memristor with neural network of smooth hinge functions. There is effective identification algorithm for the neural network of smooth hinge functions. The representation capability of this model is theoretically guaranteed. Any functional flux-charge relation of a memristor can be approximated by the model. We also give application examples to show that the given model can approximate the flux-charge relation of existing piecewise linear memristor model, window function memristor model, and a physical memristor device.
Permafrost, climate, and change: predictive modelling approach.
Anisimov, O.
2003-04-01
Predicted by GCMs enhanced warming of the Arctic will lead to discernible impacts on permafrost and northern environment. Mathematical models of different complexity forced by scenarios of climate change may be used to predict such changes. Permafrost models that are currently in use may be divided into four groups: index-based models (e.g. frost index model, N-factor model); models of intermediate complexity based on equilibrium simplified solution of the Stephan problem ("Koudriavtcev's" model and its modifications), and full-scale comprehensive dynamical models. New approach of stochastic modelling came into existence recently and has good prospects for the future. Important task is to compare the ability of the models that are different in complexity, concept, and input data requirements to capture the major impacts of changing climate on permafrost. A progressive increase in the depth of seasonal thawing (often referred to as the active-layer thickness, ALT) could be a relatively short-term reaction to climatic warming. At regional and local scales, it may produce substantial effects on vegetation, soil hydrology and runoff, as the water storage capacity of near-surface permafrost will be changed. Growing public concerns are associated with the impacts that warming of permafrost may have on engineered infrastructure built upon it. At the global scale, increase of ALT could facilitate further climatic change if more greenhouse gases are released when the upper layer of the permafrost thaws. Since dynamic permafrost models require complete set of forcing data that is not readily available on the circumpolar scale, they could be used most effectively in regional studies, while models of intermediate complexity are currently best tools for the circumpolar assessments. Set of five transient scenarios of climate change for the period 1980 - 2100 has been constructed using outputs from GFDL, NCAR, CCC, HadCM, and ECHAM-4 models. These GCMs were selected in the course
Predictive Modelling Techniques in Radioactive Waste Management
International Nuclear Information System (INIS)
This paper presents the 'state-of-art' computational modelling techniques AMEC Nuclear has used in radioactive waste management projects. These techniques have been employed to conduct option studies and assessments of radioactive waste packages to justify compliance with the UK and IAEA regulations. An important aspect of a safety case for any packaging is its performance under accident conditions. One of the key principles underlying regulations for performance under normal and accident conditions is that activity release should be low and predictable. This paper addresses the challenge faced by designers and manufacturers to predict behaviour of waste of waste packages has usually been demonstrated by test. Carrying out a full-scale drop test or a fire test of a prototype package with a representative simulant wasteform is time consuming, costly, and can lead to variability in the results. The post-test measurements of release are not straightforward and may be difficult to interpret. Furthermore, these tests are unique for a particular design and cannot be easily applied to other designs. Therefore, predictive modelling based on computational techniques like the finite element analysis (FEA) can be of great benefit. Through examples, the paper examples, the paper explains how assessments of radioactive waste packaging under fire and impact hazards have been conducted to calculate release of radioactive nuclides. The examples include computational modeling to assess free drop and transportation loads on a packaging designed to transportation loads on a packaging designed transport a 50 Te steel pot containing radioactive silicate slag. Methodology used to estimate release fractions from a 500 litre drum following a standard fire assessment is also presented
Modeling the Flux-Charge Relation of Memristor with Neural Network of Smooth Hinge Functions
X. Mu; Yu, J.; Wang, S.
2014-01-01
The memristor was proposed to characterize the flux-charge relation. We propose the generalized flux-charge relation model of memristor with neural network of smooth hinge functions. There is effective identification algorithm for the neural network of smooth hinge functions. The representation capability of this model is theoretically guaranteed. Any functional flux-charge relation of a memristor can be approximated by the model. We also give application examples to show that the given model...
Optical resonances in electrically charged particles and their relation to the Drude model
Kocifaj, Miroslav; Kundracik, František; Videen, Gorden; Yuffa, Alex J.; Klačka, Jozef
2016-07-01
The Drude model is conventionally used to explain the average motion of electrons in typical material. In this paper, we analyze the individual terms of the Drude model in order to uncover their influence on the scattering properties of small particles. Namely, a query on whether resonance enhancement is due to optical effects or the conductivity model. This query arose from our earlier theoretical and numerical experiments and still remains unresolved today. We show that certain resonance features are caused primarily by the interaction of the electromagnetic wave with the excess electric charge on the particles. Furthermore, we show that the role of a conductivity model is limited to only establishing the relative importance of the inertial moment of the carriers and the viscous drag forces. For frequencies ω ≤kB T / ℏ , the viscous forces only cause minor damping effects and the change in the peak resonance (along with its amplitude) are caused by the electric and inertial forces. These forces dominate because the viscous forces quickly decay with decreasing temperature. In order to demonstrate the optical behavior of charged water droplets, we construct a Mie-series solution with modified boundary conditions that properly account for the excess electric charge on the droplets. Our solution explains the weak scattering enhancement for frequencies far beyond the resonance, and it also predicts an absorption resonance edge in the long-wavelength limit. Our findings are not only useful to theoreticians who focus on the individual parameters such as the viscous term in the Drude model and/or search for better surface conductivity models, but also to experimentalists who gather as much data as possible in order to ascertain how the numerically determined optical properties compare with the experimental measurements.
Model predictive control of smart microgrids
DEFF Research Database (Denmark)
Hu, Jiefeng; Zhu, Jianguo; Guerrero, Josep M.
2014-01-01
required to realise high-performance of distributed generations and will realise innovative control techniques utilising model predictive control (MPC) to assist in coordinating the plethora of generation and load combinations, thus enable the effective exploitation of the clean renewable energy sources......The exploitation of renewable energy and the development of intelligent electricity network have become the main concerns worldwide. This paper aims to integrate renewable energy sources, local loads, and energy storage devices into smart microgrids. It proposes a new microgrid configuration...
Explicit model predictive control accuracy analysis
Knyazev, Andrew; Zhu, Peizhen; Di Cairano, Stefano
2015-01-01
Model Predictive Control (MPC) can efficiently control constrained systems in real-time applications. MPC feedback law for a linear system with linear inequality constraints can be explicitly computed off-line, which results in an off-line partition of the state space into non-overlapped convex regions, with affine control laws associated to each region of the partition. An actual implementation of this explicit MPC in low cost micro-controllers requires the data to be "quantized", i.e. repre...
Model Predictive Control of Wind Turbines
DEFF Research Database (Denmark)
Henriksen, Lars Christian
Wind turbines play a major role in the transformation from a fossil fuel based energy production to a more sustainable production of energy. Total-cost-of-ownership is an important parameter when investors decide in which energy technology they should place their capital. Modern wind turbines are...... been suggested as an alternative to ground-fixed wind turbines as they can be placed at water depths usually thought outside the realm of wind turbine placement. The special challenges posed by controlling a floating wind turbine have been addressed in this thesis. Model predictive control (MPC) has...
Distributed Model Predictive Control via Dual Decomposition
DEFF Research Database (Denmark)
Biegel, Benjamin; Stoustrup, Jakob; Andersen, Palle
2014-01-01
This chapter presents dual decomposition as a means to coordinate a number of subsystems coupled by state and input constraints. Each subsystem is equipped with a local model predictive controller while a centralized entity manages the subsystems via prices associated with the coupling constraints....... This allows coordination of all the subsystems without the need of sharing local dynamics, objectives and constraints. To illustrate this, an example is included where dual decomposition is used to resolve power grid congestion in a distributed manner among a number of players coupled by distribution...
The Weak Charge of the Proton. A Search For Physics Beyond the Standard Model
International Nuclear Information System (INIS)
The Qweak experiment, which completed running in May of 2012 at Jefferson Laboratory, has measured the parity-violating asymmetry in elastic electron-proton scattering at four-momentum transfer Q2 =0.025 (GeV/c)2 in order to provide the first direct measurement of the proton's weak charge, QW^{p}. The Standard Model makes firm predictions for the weak charge; deviations from the predicted value would provide strong evidence of new physics beyond the Standard Model. Using an 89% polarized electron beam at 145 microA scattering from a 34.4 cm long liquid hydrogen target, scattered electrons were detected using an array of eight fused-silica detectors placed symmetric about the beam axis. The parity-violating asymmetry was then measured by reversing the helicity of the incoming electrons and measuring the normalized difference in rate seen in the detectors. The low Q2 enables a theoretically clean measurement; the higher-order hadronic corrections are constrained using previous parity-violating electron scattering world data. The experimental method will be discussed, with recent results constituting 4% of our total data and projections of our proposed uncertainties on the full data set.
The Weak Charge of the Proton. A Search For Physics Beyond the Standard Model
Energy Technology Data Exchange (ETDEWEB)
MacEwan, Scott J. [Univ. of Manitoba, Winnipeg, MB (Canada)
2015-05-01
The Q_{weak} experiment, which completed running in May of 2012 at Jefferson Laboratory, has measured the parity-violating asymmetry in elastic electron-proton scattering at four-momentum transfer Q^{2} =0.025 (GeV/c)^{2} in order to provide the first direct measurement of the proton's weak charge, Q_{W}^{p}. The Standard Model makes firm predictions for the weak charge; deviations from the predicted value would provide strong evidence of new physics beyond the Standard Model. Using an 89% polarized electron beam at 145 microA scattering from a 34.4 cm long liquid hydrogen target, scattered electrons were detected using an array of eight fused-silica detectors placed symmetric about the beam axis. The parity-violating asymmetry was then measured by reversing the helicity of the incoming electrons and measuring the normalized difference in rate seen in the detectors. The low Q^{2} enables a theoretically clean measurement; the higher-order hadronic corrections are constrained using previous parity-violating electron scattering world data. The experimental method will be discussed, with recent results constituting 4% of our total data and projections of our proposed uncertainties on the full data set.
Predictive modelling of boiler fouling. Final report.
Energy Technology Data Exchange (ETDEWEB)
Chatwani, A
1990-12-31
A spectral element method embodying Large Eddy Simulation based on Re- Normalization Group theory for simulating Sub Grid Scale viscosity was chosen for this work. This method is embodied in a computer code called NEKTON. NEKTON solves the unsteady, 2D or 3D,incompressible Navier Stokes equations by a spectral element method. The code was later extended to include the variable density and multiple reactive species effects at low Mach numbers, and to compute transport of large particles governed by inertia. Transport of small particles is computed by treating them as trace species. Code computations were performed for a number of test conditions typical of flow past a deep tube bank in a boiler. Results indicate qualitatively correct behavior. Predictions of deposition rates and deposit shape evolution also show correct qualitative behavior. These simulations are the first attempts to compute flow field results at realistic flow Reynolds numbers of the order of 10{sup 4}. Code validation was not done; comparison with experiment also could not be made as many phenomenological model parameters, e.g., sticking or erosion probabilities and their dependence on experimental conditions were not known. The predictions however demonstrate the capability to predict fouling from first principles. Further work is needed: use of large or massively parallel machine; code validation; parametric studies, etc.
Combining GPS measurements and IRI model predictions
International Nuclear Information System (INIS)
The free electrons distributed in the ionosphere (between one hundred and thousands of km in height) produce a frequency-dependent effect on Global Positioning System (GPS) signals: a delay in the pseudo-orange and an advance in the carrier phase. These effects are proportional to the columnar electron density between the satellite and receiver, i.e. the integrated electron density along the ray path. Global ionospheric TEC (total electron content) maps can be obtained with GPS data from a network of ground IGS (international GPS service) reference stations with an accuracy of few TEC units. The comparison with the TOPEX TEC, mainly measured over the oceans far from the IGS stations, shows a mean bias and standard deviation of about 2 and 5 TECUs respectively. The discrepancies between the STEC predictions and the observed values show an RMS typically below 5 TECUs (which also includes the alignment code noise). he existence of a growing database 2-hourly global TEC maps and with resolution of 5x2.5 degrees in longitude and latitude can be used to improve the IRI prediction capability of the TEC. When the IRI predictions and the GPS estimations are compared for a three month period around the Solar Maximum, they are in good agreement for middle latitudes. An over-determination of IRI TEC has been found at the extreme latitudes, the IRI predictions being, typically two times higher than the GPS estimations. Finally, local fits of the IRI model can be done by tuning the SSN from STEC GPS observations
Stern, Michael; Williams, Ken; Eddy, David; Kahn, Richard
2008-01-01
OBJECTIVE—To validate the ability of the Archimedes model to accurately predict the risk of developing diabetes in individuals. RESEARCH DESIGN AND METHODS—Subjects were randomly selected from the San Antonio Heart Study population. The area under the receiver operating characteristic (aROC) curve derived from the Archimedes model was calculated and also compared with the aROCs from two published multiple logistic regression models designed to estimate diabetes risk. RESULTS—The aROC for the ...
Predicting Protein Secondary Structure with Markov Models
DEFF Research Database (Denmark)
Fischer, Paul; Larsen, Simon; Thomsen, Claus
2004-01-01
The primary structure of a protein is the sequence of its amino acids. The secondary structure describes structural properties of the molecule such as which parts of it form sheets, helices or coils. Spacial and other properties are described by the higher order structures. The classification tas...... Markov model for this task. Classifications that are purely based on statistical models might not always be biologically meaningful. We present combinatorial methods to incorporate biological background knowledge to enhance the prediction performance.......The primary structure of a protein is the sequence of its amino acids. The secondary structure describes structural properties of the molecule such as which parts of it form sheets, helices or coils. Spacial and other properties are described by the higher order structures. The classification task...
Modeling Reef Hydrodynamics to Predict Coral Bleaching
Bird, James; Steinberg, Craig; Hardy, Tom
2005-11-01
The aim of this study is to use environmental physics to predict water temperatures around and within coral reefs. Anomalously warm water is the leading cause for mass coral bleaching; thus a clearer understanding of the oceanographic mechanisms that control reef water temperatures will enable better reef management. In March 1998 a major coral bleaching event occurred at Scott Reef, a 40 km-wide lagoon 300 km off the northwest coast of Australia. Meteorological and coral cover observations were collected before, during, and after the event. In this study, two hydrodynamic models are applied to Scott Reef and validated against oceanographic data collected between March and June 2003. The models are then used to hindcast the reef hydrodynamics that led up to the 1998 bleaching event. Results show a positive correlation between poorly mixed regions and bleaching severity.
A predictive fitness model for influenza
Łuksza, Marta; Lässig, Michael
2014-03-01
The seasonal human influenza A/H3N2 virus undergoes rapid evolution, which produces significant year-to-year sequence turnover in the population of circulating strains. Adaptive mutations respond to human immune challenge and occur primarily in antigenic epitopes, the antibody-binding domains of the viral surface protein haemagglutinin. Here we develop a fitness model for haemagglutinin that predicts the evolution of the viral population from one year to the next. Two factors are shown to determine the fitness of a strain: adaptive epitope changes and deleterious mutations outside the epitopes. We infer both fitness components for the strains circulating in a given year, using population-genetic data of all previous strains. From fitness and frequency of each strain, we predict the frequency of its descendent strains in the following year. This fitness model maps the adaptive history of influenza A and suggests a principled method for vaccine selection. Our results call for a more comprehensive epidemiology of influenza and other fast-evolving pathogens that integrates antigenic phenotypes with other viral functions coupled by genetic linkage.
Well-conditioned model predictive control.
Dubay, Rickey; Kember, Guy; Pramujati, Bambang
2004-01-01
Model-based predictive control is an advanced control strategy that uses a move suppression factor or constrained optimization methods for achieving satisfactory closed-loop dynamic responses of complex systems. While these approaches are suitable for many processes, they are formulated on the selection of certain parameters that are ambiguous and also computationally demanding which makes them less suited for tight control of fast processes. In this paper, a new dynamic matrix control (DMC) algorithm is proposed that reduces inherent ill-conditioning by allowing the process prediction time step to exceed the control time step. The main feature, that stands in contrast with current DMC approaches, is that the original open-loop data are used to evaluate a "shifting factor" m in the controller matrix where m replaces the move suppression coefficient. The new control algorithm is practically demonstrated on a fast reacting process with better control being realized in comparison with DMC using move suppression. The algorithm also gives improved closed-loop responses for control simulations on a multivariable nonlinear process having variable dead-time, and on other models found in the literature. The shifting factor m is generic and can be effectively applied for any control horizon. PMID:15000134
NASCAP Modeling of GEO Satellites--Spacecraft Charging is Back!
Chock, R.; Ferguson, D. C.; Synder, D. B.
2004-01-01
During the last few years of Solar Minimum, GEO spacecraft charging design practices may have become lax because of paucity of spacecraft charging events. Unfortunately, this has also been the time of great changes in spacecraft design, because of the new emphases on higher power arrays and lower costs. Also unfortunate is the fact that spacecraft charging may lead to failures of solar array strings, panels, or entire spacecraft. One way to prevent satellite failures die to spacecraft charging events is to simulate the effects with a charging code, such as the venerable NASCAP/GEO code. We will discuss the use of NASCAP on the ACTS satellite as well as a newer application dealing with typical recent spacecraft charging anomalies.
Directory of Open Access Journals (Sweden)
D. J. de Ridder
2009-10-01
Full Text Available The occurrence of organic micropollutants in drinking water and its sources has opened up a field of study related to monitoring concentration levels in water sources, evaluating their toxicity and estimating their removal in drinking water treatment processes. Because a large number of organic micropollutants is currently present (although in relatively low concentrations in drinking water sources, a method should be developed to select which micropollutants has to be evaluated with priority. In this paper, a screening model is presented that can predict solute removal by activated carbon, in ultrapure water and in natural water. Solute removal prediction is based on a combination of solute hydrophobicity (expressed as log D, the pH corrected log K_{ow}, solute charge and the carbon dose. Solute molecular weight was also considered as model input parameter, but this solute property appeared to relate insufficiently to solute removal.
Removal of negatively charged solutes by preloaded activated carbon was reduced while the removal of positively charged solutes was increased, compared with freshly regenerated activated carbon. Differences in charged solute removal by freshly regenerated activated carbon were small, indicating that charge interactions are an important mechanism in adsorption onto preloaded carbon. The predicted solute removal was within 20 removal-% deviation of experimentally measured values.
Directory of Open Access Journals (Sweden)
D. J. de Ridder
2009-12-01
Full Text Available The occurrence of organic micropollutants in drinking water and its sources has opened up a field of study related to monitoring concentration levels in water sources, evaluating their toxicity and estimating their removal in drinking water treatment processes. Because a large number of organic micropollutants is currently present (although in relatively low concentrations in drinking water sources, a method should be developed to select which micropollutants has to be evaluated with priority. In this paper, a screening model is presented that can predict solute removal by activated carbon, in ultrapure water and in natural water. Solute removal prediction is based on a combination of solute hydrophobicity (expressed as log D, the pH corrected log K_{ow}, solute charge and the carbon dose. Solute molecular weight was also considered as model input parameter, but this solute property appeared to relate insufficiently to solute removal.
Removal of negatively charged solutes by preloaded activated carbon was reduced while the removal of positively charged solutes was increased, compared with freshly regenerated activated carbon. Differences in charged solute removal by freshly regenerated activated carbon were small, indicating that charge interactions are an important mechanism in adsorption onto preloaded carbon. The predicted solute removal was within 20 removal-% deviation of experimentally measured values for most solutes.
Predictive Capability Maturity Model for computational modeling and simulation.
Energy Technology Data Exchange (ETDEWEB)
Oberkampf, William Louis; Trucano, Timothy Guy; Pilch, Martin M.
2007-10-01
The Predictive Capability Maturity Model (PCMM) is a new model that can be used to assess the level of maturity of computational modeling and simulation (M&S) efforts. The development of the model is based on both the authors experience and their analysis of similar investigations in the past. The perspective taken in this report is one of judging the usefulness of a predictive capability that relies on the numerical solution to partial differential equations to better inform and improve decision making. The review of past investigations, such as the Software Engineering Institute's Capability Maturity Model Integration and the National Aeronautics and Space Administration and Department of Defense Technology Readiness Levels, indicates that a more restricted, more interpretable method is needed to assess the maturity of an M&S effort. The PCMM addresses six contributing elements to M&S: (1) representation and geometric fidelity, (2) physics and material model fidelity, (3) code verification, (4) solution verification, (5) model validation, and (6) uncertainty quantification and sensitivity analysis. For each of these elements, attributes are identified that characterize four increasing levels of maturity. Importantly, the PCMM is a structured method for assessing the maturity of an M&S effort that is directed toward an engineering application of interest. The PCMM does not assess whether the M&S effort, the accuracy of the predictions, or the performance of the engineering system satisfies or does not satisfy specified application requirements.
Charged Scalar Phenomenology in the Bilinear R-Parity Breaking Model
Ferrandis, J
1998-01-01
We consider the charged scalar boson phenomenology in the bilinear R-parity breaking model which induces a mixing between staus and the charged Higgs boson. The charged Higgs boson mass can be lower than expected in the MSSM, even before including radiative corrections. The R-parity violating decay rates can be comparable or even bigger than the R-parity conserving ones. These features could have implications for charged supersymmetric scalar boson searches at future accelerators.
Minow, Joseph I.; Coffey, Victoria N.; Parker, Linda N.; Blackwell, William C., Jr.; Jun, Insoo; Garrett, Henry B.
2007-01-01
The NUMIT 1-dimensional bulk charging model is used as a screening to ol for evaluating time-dependent bulk internal or deep dielectric) ch arging of dielectrics exposed to penetrating electron environments. T he code is modified to accept time dependent electron flux time serie s along satellite orbits for the electron environment inputs instead of using the static electron flux environment input originally used b y the code and widely adopted in bulk charging models. Application of the screening technique ts demonstrated for three cases of spacecraf t exposure within the Earth's radiation belts including a geostationa ry transfer orbit and an Earth-Moon transit trajectory for a range of orbit inclinations. Electric fields and charge densities are compute d for dielectric materials with varying electrical properties exposed to relativistic electron environments along the orbits. Our objectiv e is to demonstrate a preliminary application of the time-dependent e nvironments input to the NUMIT code for evaluating charging risks to exposed dielectrics used on spacecraft when exposed to the Earth's ra diation belts. The results demonstrate that the NUMIT electric field values in GTO orbits with multiple encounters with the Earth's radiat ion belts are consistent with previous studies of charging in GTO orb its and that potential threat conditions for electrostatic discharge exist on lunar transit trajectories depending on the electrical proper ties of the materials exposed to the radiation environment.
Casalicchio, Giuseppe; Bischl, Bernd; Boulesteix, Anne-Laure; Schmid, Matthias
2015-01-01
It is agreed among biostatisticians that prediction models for binary outcomes should satisfy two essential criteria: First, a prediction model should have a high discriminatory power, implying that it is able to clearly separate cases from controls. Second, the model should be well calibrated, meaning that the predicted risks should closely agree with the relative frequencies observed in the data. The focus of this work is on the predictiveness curve, which has been proposed by Huang et ...
Hollenbeck, Dawn; Martini, K. Michael; Langner, Andreas; Ross, David; Harkin, Anthony; Nelson, Edward; Thurston, George
2010-03-01
We study the pattern-specific work of charging for two spherical model proteins in close proximity in ionic solution, using a grand-canonical partition function together with a coarse-grained, linear Debye-Huckel model to calculate the needed work of charging for each possible proton occupancy configuration. We seek to delineate a parameter-space phase diagram to characterize the circumstances under which patterned charge regulation, attractions due to heterogeneous protein charging patterns, and screened net protein charge could individually dominate the electrostatic portion of the interaction between model particles. Within the model, we place titratable residues in accordance with the tertiary protein structure, as is done in the case of a single protein within the Tanford-Kirkwood protein electrostatics model. We use Monte-Carlo simulation and analytical work to evaluate how the local statistics of the charging patterns on each protein respond to close proximity and relative orientation of neighboring proteins.
Charged spin-1 gluons, parton model and the Archimedes effect
International Nuclear Information System (INIS)
In a gauge theory of (SU(2) x U(1))sub(flavour) x SU(3)sub(colour) with unconfined integer-charged quarks and massive inter-charged gluons both quarks and gluons contribute to electro and neutrino-production. The gluon parton contribution to the lepto-production of colour is considered. (author)
The Binding Energy, Spin-Excitation Gap, and Charged Gap in the Boson-Fermion Model
Institute of Scientific and Technical Information of China (English)
YANG Kai-Hua; TIAN Guang-Shan; HAN Ru-Qi
2003-01-01
In this paper, by applying a simplified version of Lieb 's spin-refleetion-positivity method, which was recentlydeveloped by one of us [G.S. Tian and J.G. Wang, J. Phys. A: Math. Gen. 35 (2002) 941], we investigate some generalproperties of the boson-fermion Hamiltonian, which has been widely used as a phenomenological model to describe thereal-space pairing of electrons. On a mathematically rigorous basis, we prove that for either negative or positive couplingV, which represents the spontaneous decay and recombination process between boson and fermion in the model, thepairing energy of electrons is nonzero. Furthermore, we also show that the spin-excitation gap of the boson-fermionHamiltonian is always larger than its charged gap, as predicted by the pre-paired electron theory.
The Binding Energy, Spin－Excitation Gap, and Charged Gap in the Boson－Fermion Model
Institute of Scientific and Technical Information of China (English)
YANGKai-Hua; Guang-Shan; HANRu-Qi
2003-01-01
In this paper, by applying a simplified version of Lieb's spin-reflection-positivity method, which was recently developed by one of us [G.S. Tian and J.G. Wang, J. Phys. A: Math. Gen. 35 (2002) 941], we investigate some general properties of the boeon-fermion Hamiltonlan, which has been widely used as a phenomenological model to describe the real-space pairing of electrons. On a mathematically rigorous basis, we prove that for either negative or positive couping V, which represents the spontaneous decay and recombination process between boson and fermion in the model, the pairing energy of electrons is nonzero. Furthermore, we also show that the spin-excitation gap of the boson-fermion Hamiltonian is always larger than its charged gap, as predicted by the pre-palred electron theory.
Heuristic Modeling for TRMM Lifetime Predictions
Jordan, P. S.; Sharer, P. J.; DeFazio, R. L.
1996-01-01
Analysis time for computing the expected mission lifetimes of proposed frequently maneuvering, tightly altitude constrained, Earth orbiting spacecraft have been significantly reduced by means of a heuristic modeling method implemented in a commercial-off-the-shelf spreadsheet product (QuattroPro) running on a personal computer (PC). The method uses a look-up table to estimate the maneuver frequency per month as a function of the spacecraft ballistic coefficient and the solar flux index, then computes the associated fuel use by a simple engine model. Maneuver frequency data points are produced by means of a single 1-month run of traditional mission analysis software for each of the 12 to 25 data points required for the table. As the data point computations are required only a mission design start-up and on the occasion of significant mission redesigns, the dependence on time consuming traditional modeling methods is dramatically reduced. Results to date have agreed with traditional methods to within 1 to 1.5 percent. The spreadsheet approach is applicable to a wide variety of Earth orbiting spacecraft with tight altitude constraints. It will be particularly useful to such missions as the Tropical Rainfall Measurement Mission scheduled for launch in 1997, whose mission lifetime calculations are heavily dependent on frequently revised solar flux predictions.
Distributed model predictive control made easy
Negenborn, Rudy
2014-01-01
The rapid evolution of computer science, communication, and information technology has enabled the application of control techniques to systems beyond the possibilities of control theory just a decade ago. Critical infrastructures such as electricity, water, traffic and intermodal transport networks are now in the scope of control engineers. The sheer size of such large-scale systems requires the adoption of advanced distributed control approaches. Distributed model predictive control (MPC) is one of the promising control methodologies for control of such systems. This book provides a state-of-the-art overview of distributed MPC approaches, while at the same time making clear directions of research that deserve more attention. The core and rationale of 35 approaches are carefully explained. Moreover, detailed step-by-step algorithmic descriptions of each approach are provided. These features make the book a comprehensive guide both for those seeking an introduction to distributed MPC as well as for those ...
Effect of pipeline rupture transient release modelling on predicted consequences
Energy Technology Data Exchange (ETDEWEB)
Johnston, C.R.; Springer, W.A.J.; Rowe, R.D. [Calgary Univ., Dept. of Mechanical Engineering, Calgary, AB (Canada)
1998-09-01
A mathematical model was developed to predict the consequences of a rupture in a natural gas pipeline. The model was a real-fluid, non-isentropic blowdown (RFB) model. A comparison of this model and the widely accepted double exponential model presented some interesting similarities and differences. The mass flow rates predicted by the two models were in close agreement, but the double exponential model was not able to predict the release of fluid as liquid. The RFB model predicted that 25 per cent of the mass released would be liquid.
Predictive integrated modelling for ITER scenarios
International Nuclear Information System (INIS)
The uncertainty on the prediction of ITER scenarios is evaluated. 2 transport models which have been extensively validated against the multi-machine database are used for the computation of the transport coefficients. The first model is GLF23, the second called Kiauto is a model in which the profile of dilution coefficient is a gyro Bohm-like analytical function, renormalized in order to get profiles consistent with a given global energy confinement scaling. The package of codes CRONOS is used, it gives access to the dynamics of the discharge and allows the study of interplay between heat transport, current diffusion and sources. The main motivation of this work is to study the influence of parameters such plasma current, heat, density, impurities and toroidal moment transport. We can draw the following conclusions: 1) the target Q = 10 can be obtained in ITER hybrid scenario at Ip = 13 MA, using either the DS03 two terms scaling or the GLF23 model based on the same pedestal; 2) Ip = 11.3 MA, Q = 10 can be reached only assuming a very peaked pressure profile and a low pedestal; 3) at fixed Greenwald fraction, Q increases with density peaking; 4) achieving a stationary q-profile with q > 1 requires a large non-inductive current fraction (80%) that could be provided by 20 to 40 MW of LHCD; and 5) owing to the high temperature the q-profile penetration is delayed and q = 1 is reached about 600 s in ITER hybrid scenario at Ip = 13 MA, in the absence of active q-profile control. (A.C.)
Modeling Transport in Ultrathin Si Nanowires: Charged versus Neutral Impurities
DEFF Research Database (Denmark)
Rurali, Riccardo; Markussen, Troels; Suné, Jordi;
2008-01-01
Abstract: At room temperature dopants in semiconducting nanowires are ionized. We show that the long-range electrostatic potential due to charged dopants has a dramatic impact on the transport properties in ultrathin wires and can virtually block minority carriers. Our quantitative estimates of...... this effect are obtained by computing the electronic transmission through wires with either charged or neutral P and B dopants. The dopant potential is obtained from density functional theory (DFT) calculations. Contrary to the neutral case, the transmission through charged dopants cannot be converged...
Coarse Point Charge Models For Proteins From Smoothed Molecular Electrostatic Potentials.
Leherte, Laurence; Vercauteren, Daniel P
2009-12-01
To generate coarse electrostatic models of proteins, we developed an original approach to hierarchically locate maxima and minima in smoothed molecular electrostatic potentials. A charge-fitting program was used to assign charges to the so-obtained reduced representations. Templates are defined to easily generate coarse point charge models for protein structures, in the particular cases of the Amber99 and Gromos43A1 force fields. Applications to four small peptides and to the ion channel KcsA are presented. Electrostatic potential values generated by the reduced models are compared with the corresponding values obtained using the original sets of atomic charges. PMID:26602509
Model predictive control of a wind turbine modelled in Simpack
Jassmann, U.; Berroth, J.; Matzke, D.; Schelenz, R.; Reiter, M.; Jacobs, G.; Abel, D.
2014-06-01
Wind turbines (WT) are steadily growing in size to increase their power production, which also causes increasing loads acting on the turbine's components. At the same time large structures, such as the blades and the tower get more flexible. To minimize this impact, the classical control loops for keeping the power production in an optimum state are more and more extended by load alleviation strategies. These additional control loops can be unified by a multiple-input multiple-output (MIMO) controller to achieve better balancing of tuning parameters. An example for MIMO control, which has been paid more attention to recently by wind industry, is Model Predictive Control (MPC). In a MPC framework a simplified model of the WT is used to predict its controlled outputs. Based on a user-defined cost function an online optimization calculates the optimal control sequence. Thereby MPC can intrinsically incorporate constraints e.g. of actuators. Turbine models used for calculation within the MPC are typically simplified. For testing and verification usually multi body simulations, such as FAST, BLADED or FLEX5 are used to model system dynamics, but they are still limited in the number of degrees of freedom (DOF). Detailed information about load distribution (e.g. inside the gearbox) cannot be provided by such models. In this paper a Model Predictive Controller is presented and tested in a co-simulation with SlMPACK, a multi body system (MBS) simulation framework used for detailed load analysis. The analysis are performed on the basis of the IME6.0 MBS WT model, described in this paper. It is based on the rotor of the NREL 5MW WT and consists of a detailed representation of the drive train. This takes into account a flexible main shaft and its main bearings with a planetary gearbox, where all components are modelled flexible, as well as a supporting flexible main frame. The wind loads are simulated using the NREL AERODYN v13 code which has been implemented as a routine to
Model predictive control of a wind turbine modelled in Simpack
International Nuclear Information System (INIS)
Wind turbines (WT) are steadily growing in size to increase their power production, which also causes increasing loads acting on the turbine's components. At the same time large structures, such as the blades and the tower get more flexible. To minimize this impact, the classical control loops for keeping the power production in an optimum state are more and more extended by load alleviation strategies. These additional control loops can be unified by a multiple-input multiple-output (MIMO) controller to achieve better balancing of tuning parameters. An example for MIMO control, which has been paid more attention to recently by wind industry, is Model Predictive Control (MPC). In a MPC framework a simplified model of the WT is used to predict its controlled outputs. Based on a user-defined cost function an online optimization calculates the optimal control sequence. Thereby MPC can intrinsically incorporate constraints e.g. of actuators. Turbine models used for calculation within the MPC are typically simplified. For testing and verification usually multi body simulations, such as FAST, BLADED or FLEX5 are used to model system dynamics, but they are still limited in the number of degrees of freedom (DOF). Detailed information about load distribution (e.g. inside the gearbox) cannot be provided by such models. In this paper a Model Predictive Controller is presented and tested in a co-simulation with SlMPACK, a multi body system (MBS) simulation framework used for detailed load analysis. The analysis are performed on the basis of the IME6.0 MBS WT model, described in this paper. It is based on the rotor of the NREL 5MW WT and consists of a detailed representation of the drive train. This takes into account a flexible main shaft and its main bearings with a planetary gearbox, where all components are modelled flexible, as well as a supporting flexible main frame. The wind loads are simulated using the NREL AERODYN v13 code which has been implemented as a routine
A Predictive Model of Geosynchronous Magnetopause Crossings
Dmitriev, A; Chao, J -K
2013-01-01
We have developed a model predicting whether or not the magnetopause crosses geosynchronous orbit at given location for given solar wind pressure Psw, Bz component of interplanetary magnetic field (IMF) and geomagnetic conditions characterized by 1-min SYM-H index. The model is based on more than 300 geosynchronous magnetopause crossings (GMCs) and about 6000 minutes when geosynchronous satellites of GOES and LANL series are located in the magnetosheath (so-called MSh intervals) in 1994 to 2001. Minimizing of the Psw required for GMCs and MSh intervals at various locations, Bz and SYM-H allows describing both an effect of magnetopause dawn-dusk asymmetry and saturation of Bz influence for very large southward IMF. The asymmetry is strong for large negative Bz and almost disappears when Bz is positive. We found that the larger amplitude of negative SYM-H the lower solar wind pressure is required for GMCs. We attribute this effect to a depletion of the dayside magnetic field by a storm-time intensification of t...
A THERMODYNAMIC MODEL TO PREDICT WAX FORMATION IN PETROLEUM FLUIDS
Coutinho J.A.P.; Pauly J.; Daridon J.L.
2001-01-01
Some years ago the authors proposed a model for the non-ideality of the solid phase, based on the Predictive Local Composition concept. This was first applied to the Wilson equation and latter extended to NRTL and UNIQUAC models. Predictive UNIQUAC proved to be extraordinarily successful in predicting the behaviour of both model and real hydrocarbon fluids at low temperatures. This work illustrates the ability of Predictive UNIQUAC in the description of the low temperature behaviour of petrol...
Predictive Capabilities of Avalanche Models for Solar Flares
Strugarek, Antoine; Charbonneau, Paul
2014-01-01
We assess the predictive capabilities of various classes of avalanche models for solar flares. We demonstrate that avalanche models cannot generally be used to predict specific events due to their high sensitivity to their embedded stochastic process. We show that deterministically driven models can nevertheless alleviate this caveat and be efficiently used for large events predictions. Our results promote a new approach for large (typically X-class) solar flares predictions based on simple a...
A PEV Charging Service Model for Smart Grids
Mohammed Abdel-Hafez; Ahmed Gaouda; Liren Zhang; Khaled Shuaib
2012-01-01
Plug-in Electric Vehicles (PEVs) are envisioned to be more popular during the next decade as part of Smart Grid implementations. Charging multiple PEVs at the same time within a power distribution area constitutes a major challenge for energy service providers. This paper discusses a priority-based approach for charging PEVs in a Smart Grid environment. In this work, ideas from the communication network paradigm are being utilized and tailored toward achieving the desired objective of monitor...
Modelling die filling with charged particles using DEM/CFD
Institute of Scientific and Technical Information of China (English)
Emmanuel Nkem Nwose; Chunlei Pei; Chuan-Yu Wu
2012-01-01
The effects of electrostatic charge on powder flow behaviour during die filling in a vacuum and in air were analysed using a coupled discrete element method and computational fluid dynamics (DEM/CFD) code,in which long range electrostatic interactions were implemented.The present 2D simulations revealed that both electrostatic charge and the presence of air can affect the powder flow behaviour during die filling.It was found that the electrostatic charge inhibited the flow of powders into the die and induced a loose packing structure.At the same filling speed,increasing the electrostatic charge led to a decrease in the fill ratio which quantifies the volumetric occupancy of powder in the die.In addition,increasing the shoe speed caused a further decrease in the fill ratio,which was characterised using the concept of critical filling speed.When the electrostatic charge was low,the air/particle interaction was strong so that a lower critical filling speed was obtained for die filling in air than in a vacuum.With high electrostatic charge,the electrostatic interactions became dominant.Consequently,similar fill ratio and critical filling speed were obtained for die filling in air and in a vacuum.
Directory of Open Access Journals (Sweden)
Jing Lu
2014-11-01
Full Text Available We propose a weather prediction model in this article based on neural network and fuzzy inference system (NFIS-WPM, and then apply it to predict daily fuzzy precipitation given meteorological premises for testing. The model consists of two parts: the first part is the “fuzzy rule-based neural network”, which simulates sequential relations among fuzzy sets using artificial neural network; and the second part is the “neural fuzzy inference system”, which is based on the first part, but could learn new fuzzy rules from the previous ones according to the algorithm we proposed. NFIS-WPM (High Pro and NFIS-WPM (Ave are improved versions of this model. It is well known that the need for accurate weather prediction is apparent when considering the benefits. However, the excessive pursuit of accuracy in weather prediction makes some of the “accurate” prediction results meaningless and the numerical prediction model is often complex and time-consuming. By adapting this novel model to a precipitation prediction problem, we make the predicted outcomes of precipitation more accurate and the prediction methods simpler than by using the complex numerical forecasting model that would occupy large computation resources, be time-consuming and which has a low predictive accuracy rate. Accordingly, we achieve more accurate predictive precipitation results than by using traditional artificial neural networks that have low predictive accuracy.
Prediction and optimization methods for electric vehicle charging schedules in the EDISON project
DEFF Research Database (Denmark)
Aabrandt, Andreas; Andersen, Peter Bach; Pedersen, Anders Bro;
2012-01-01
project has been launched to investigate various areas relevant to electric vehicle integration. As part of EDISON an electric vehicle aggregator has been developed to demonstrate smart charging of electric vehicles. The emphasis of this paper is the mathematical methods on which the EDISON aggregator is...
Spin-fermion model with overlapping hot spots and charge modulation in cuprates
Volkov, Pavel A.; Efetov, Konstantin B.
2016-02-01
We study particle-hole instabilities in the framework of the spin-fermion (SF) model. In contrast to previous studies, we assume that adjacent hot spots can overlap due to a shallow dispersion of the electron spectrum in the antinodal region. In addition, we take into account effects of a remnant low energy and momentum Coulomb interaction. We demonstrate that at sufficiently small values |ɛ (π ,0 ) - EF|≲Γ , where EF is the Fermi energy, ɛ (π ,0 ) is the energy in the middle of the Brillouin zone edge, and Γ is a characteristic energy of the fermion-fermion interaction due to the antiferromagnetic fluctuations, the leading particle-hole instability is a d -form factor Fermi surface deformation (the Pomeranchuk instability) rather than the charge modulation along the Brillouin zone diagonals predicted within the standard SF model previously. At lower temperatures, we find that the deformed Fermi surface is further unstable to formation of a d -form factor charge density wave (CDW) with a wave vector along the Cu-O-Cu bonds (axes of the Brillouin zone). We show that the remnant Coulomb interaction enhances the d -form-factor symmetry of the CDW. These findings can explain the robustness of this order in the cuprates. The approximations made in the paper are justified by a small parameter that allows one to implement an Eliashberg-like treatment. Comparison with experiments suggests that in many cuprate compounds the prerequisites for the proposed scenario are indeed fulfilled and the results obtained may explain important features of the charge modulations observed recently.
Charge Exchange Induced X-ray Emission of Fe XXV and Fe XXVI via a Streamlined Model
Mullen, P D; Lyons, D; Stancil, P C
2016-01-01
Charge exchange is an important process for the modeling of X-ray spectra obtained by the Chandra, XMM-Newton, and Suzaku X-ray observatories, as well as the anticipated Astro-H mission. The understanding of the observed X-ray spectra produced by many astrophysical environments is hindered by the current incompleteness of available atomic and molecular data -- especially for charge exchange. Here, we implement a streamlined program set that applies quantum defect methods and the Landau-Zener theory to generate total, n-resolved, and nlS-resolved cross sections for any given projectile ion/ target charge exchange collision. Using this data in a cascade model for X-ray emission, theoretical spectra for such systems can be predicted. With these techniques, Fe25+ and Fe26+ charge exchange collisions with H, He, H2, N2, H2O, and CO are studied for single electron capture. These systems have been selected as they illustrate computational difficulties for high projectile charges. Further, Fe XXV and Fe XXVI emission...
Directory of Open Access Journals (Sweden)
Chi-Ho Chan
Full Text Available Optimization of the surface charges is a promising strategy for increasing thermostability of proteins. Electrostatic contribution of ionizable groups to the protein stability can be estimated from the differences between the pKa values in the folded and unfolded states of a protein. Using this pKa-shift approach, we experimentally measured the electrostatic contribution of all aspartate and glutamate residues to the stability of a thermophilic ribosomal protein L30e from Thermococcus celer. The pKa values in the unfolded state were found to be similar to model compound pKas. The pKa values in both the folded and unfolded states obtained at 298 and 333 K were similar, suggesting that electrostatic contribution of ionizable groups to the protein stability were insensitive to temperature changes. The experimental pKa values for the L30e protein in the folded state were used as a benchmark to test the robustness of pKa prediction by various computational methods such as H++, MCCE, MEAD, pKD, PropKa, and UHBD. Although the predicted pKa values were affected by crystal contacts that may alter the side-chain conformation of surface charged residues, most computational methods performed well, with correlation coefficients between experimental and calculated pKa values ranging from 0.49 to 0.91 (p<0.01. The changes in protein stability derived from the experimental pKa-shift approach correlate well (r = 0.81 with those obtained from stability measurements of charge-to-alanine substituted variants of the L30e protein. Our results demonstrate that the knowledge of the pKa values in the folded state provides sufficient rationale for the redesign of protein surface charges leading to improved protein stability.
Foundation Settlement Prediction Based on a Novel NGM Model
Directory of Open Access Journals (Sweden)
Peng-Yu Chen
2014-01-01
Full Text Available Prediction of foundation or subgrade settlement is very important during engineering construction. According to the fact that there are lots of settlement-time sequences with a nonhomogeneous index trend, a novel grey forecasting model called NGM (1,1,k,c model is proposed in this paper. With an optimized whitenization differential equation, the proposed NGM (1,1,k,c model has the property of white exponential law coincidence and can predict a pure nonhomogeneous index sequence precisely. We used two case studies to verify the predictive effect of NGM (1,1,k,c model for settlement prediction. The results show that this model can achieve excellent prediction accuracy; thus, the model is quite suitable for simulation and prediction of approximate nonhomogeneous index sequence and has excellent application value in settlement prediction.
Braun, M A; Kondratev, V P; Vechernin, V V
1999-01-01
We present results of Monte Carlo simulations of charged particles multiplicity distributions and ALICE background conditions in forward region for PbPb collisions at LHC.HIJING event generator [1] results are compared with predictions of Coloured String Fusion Model [2,3].Requirements to the Forward Multiplicity Detector for ALICE arising from these simulations are discussed (multiplicity range, resolution in multiplicity, granularity, timing resolution).References: [1] N.van Eijndhoven et al., ALICE/CERN 95-32, Internal Note 1996[2] M.Braun and C.Pajares, PHys. Rev. D47 (1993) 114-122[2] M.Braun and C.Pajares, PHys. Rev. C51 (1995) 879-889
Comparing model predictions for ecosystem-based management
DEFF Research Database (Denmark)
Jacobsen, Nis Sand; Essington, Timothy E.; Andersen, Ken Haste
2016-01-01
Ecosystem modeling is becoming an integral part of fisheries management, but there is a need to identify differences between predictions derived from models employed for scientific and management purposes. Here, we compared two models: a biomass-based food-web model (Ecopath with Ecosim (EwE)) and...... predictions, underscoring the importance of incorporating knowledge of model assumptions and limitation, possibly through using model ensembles, when providing model-based scientific advice to policy makers....
Modeling charge polarization voltage for large lithium-ion batteries in electric vehicles
Directory of Open Access Journals (Sweden)
Yan Jiang
2013-06-01
Full Text Available Purpose: Polarization voltage of the lithium-ion battery is an important parameter that has direct influence on battery performance. The paper aims to analyze the impedance characteristics of the lithium-ion battery based on EIS data. Design/methodology/approach: The effects of currents, initial SOC of the battery on charge polarization voltage are investigated, which is approximately linear function of charge current. The change of charge polarization voltage is also analyzed with the gradient analytical method in the SOC domain. The charge polarization model with two RC networks is presented, and parts of model parameters like Ohmic resistance and charge transfer impedance are estimated by both EIS method and battery constant current testing method. Findings: This paper reveals that the Ohmic resistance accounts for much contribution to battery total polarization compared to charge transfer impedance. Practical implications: Experimental results demonstrate the efficacy of the model with the proposed identification method, which provides the foundation for battery charging optimization. Originality/value: The paper analyzed the impedance characteristics of the lithium-ion battery based on EIS data, presented a charge polarization model with two RC networks, and estimated parameters like Ohmic resistance and charge transfer impedance.
Liu, Dongxia; Qie, Xiushu; Peng, Liang; Li, Wanli
2014-09-01
Electrification and simple discharge schemes are coupled into a 3D Regional Atmospheric Model System (RAMS) as microphysical parameterizations, in accordance with electrical experiment results. The dynamics, microphysics, and electrification components are fully integrated into the RAMS model, and the inductive and non-inductive electrification mechanisms are considered in the charging process. The results indicate that the thunderstorm mainly had a normal tripole charge structure. The simulated charge structure and lightning frequency are basically consistent with observations of the lightning radiation source distribution. The non-inductive charging mechanism contributed to the electrification during the whole lifetime of the thunderstorm, while the inductive electrification mechanism played a significant role in the development period and the mature stage when the electric field reached a large value. The charge structure in the convective region and the rearward region are analyzed, showing that the charge density in the convective region was double that in the rearward region.
A Globally-Continuous, Charge-Conservative, Non-linear Equivalent Circuit Model For RF MOSFETs
Ó hAnnaidh, Breandán; Brazil, Thomas J.
2003-01-01
A non-linear equivalent circuit model for MOSFETs valid for DC, small and large-signal sim-ulations of high frequency circuit design is presented. The model is valid for a wide range of bias conditions and is globally continuous. Capacitances are derived from a single charge model and charge conservation is taken into account. Simulations of the model, following parameter extraction, are validated by comparisons with experimental data.
Improved Space Charge Modeling for Simulation and Design of Photoinjectors
Energy Technology Data Exchange (ETDEWEB)
Robert H. Jackson, Thuc Bui, John Verboncoeur
2010-04-19
Photoinjectors in advanced high-energy accelerators reduce beam energy spreads and enhance undulator photon fluxes. Photoinjector design is difficult because of the substantial differences in time and spatial scales. This Phase I program explored an innovative technique, the local Taylor polynomial (LTP) formulation, for improving finite difference analysis of photoinjectors. This included improved weighting techniques, systematic formula for high order interpolation and electric field computation, and improved handling of space charge. The Phase I program demonstrated that the approach was powerful, accurate, and efficient. It handles space charge gradients better than currently available technology.
An online railway traffic prediction model
Kecman, P.; Goverde, R.M.P.
2013-01-01
Prediction of train positions in time and space is required for traffic control and passenger information. However, in practice only the last measured train delays are known and dispatchers must predict the arrival times of trains without adequate computer support. This paper presents a real-time to
Charge-state-dependent energy loss of slow ions. II. Statistical atom model
Wilhelm, Richard A.; Möller, Wolfhard
2016-05-01
A model for charge-dependent energy loss of slow ions is developed based on the Thomas-Fermi statistical model of atoms. Using a modified electrostatic potential which takes the ionic charge into account, nuclear and electronic energy transfers are calculated, the latter by an extension of the Firsov model. To evaluate the importance of multiple collisions even in nanometer-thick target materials we use the charge-state-dependent potentials in a Monte Carlo simulation in the binary collision approximation and compare the results to experiment. The Monte Carlo results reproduce the incident charge-state dependence of measured data well [see R. A. Wilhelm et al., Phys. Rev. A 93, 052708 (2016), 10.1103/PhysRevA.93.052708], even though the experimentally observed charge exchange dependence is not included in the model.
Multipole correction of atomic monopole models of molecular charge distribution. I. Peptides
Sokalski, W. A.; Keller, D. A.; Ornstein, R. L.; Rein, R.
1993-01-01
The defects in atomic monopole models of molecular charge distribution have been analyzed for several model-blocked peptides and compared with accurate quantum chemical values. The results indicate that the angular characteristics of the molecular electrostatic potential around functional groups capable of forming hydrogen bonds can be considerably distorted within various models relying upon isotropic atomic charges only. It is shown that these defects can be corrected by augmenting the atomic point charge models by cumulative atomic multipole moments (CAMMs). Alternatively, sets of off-center atomic point charges could be automatically derived from respective multipoles, providing approximately equivalent corrections. For the first time, correlated atomic multipoles have been calculated for N-acetyl, N'-methylamide-blocked derivatives of glycine, alanine, cysteine, threonine, leucine, lysine, and serine using the MP2 method. The role of the correlation effects in the peptide molecular charge distribution are discussed.
Allostasis: a model of predictive regulation.
Sterling, Peter
2012-04-12
The premise of the standard regulatory model, "homeostasis", is flawed: the goal of regulation is not to preserve constancy of the internal milieu. Rather, it is to continually adjust the milieu to promote survival and reproduction. Regulatory mechanisms need to be efficient, but homeostasis (error-correction by feedback) is inherently inefficient. Thus, although feedbacks are certainly ubiquitous, they could not possibly serve as the primary regulatory mechanism. A newer model, "allostasis", proposes that efficient regulation requires anticipating needs and preparing to satisfy them before they arise. The advantages: (i) errors are reduced in magnitude and frequency; (ii) response capacities of different components are matched -- to prevent bottlenecks and reduce safety factors; (iii) resources are shared between systems to minimize reserve capacities; (iv) errors are remembered and used to reduce future errors. This regulatory strategy requires a dedicated organ, the brain. The brain tracks multitudinous variables and integrates their values with prior knowledge to predict needs and set priorities. The brain coordinates effectors to mobilize resources from modest bodily stores and enforces a system of flexible trade-offs: from each organ according to its ability, to each organ according to its need. The brain also helps regulate the internal milieu by governing anticipatory behavior. Thus, an animal conserves energy by moving to a warmer place - before it cools, and it conserves salt and water by moving to a cooler one before it sweats. The behavioral strategy requires continuously updating a set of specific "shopping lists" that document the growing need for each key component (warmth, food, salt, water). These appetites funnel into a common pathway that employs a "stick" to drive the organism toward filling the need, plus a "carrot" to relax the organism when the need is satisfied. The stick corresponds broadly to the sense of anxiety, and the carrot broadly to
Kornbleuth, Marc; Wargelin, Bradford J.; Juda, Michael
2014-06-01
Solar wind charge exchange (SWCX) X-rays are emitted when highly charged solar wind ions such as O7+ collide with neutral gas. The best known examples of this occur around comets, but SWCX emission also arises in the Earth's tenuous outer atmosphere and throughout the heliosphere as neutral H and He from the interstellar medium flows into the solar system. This geocoronal and heliospheric emission comprises much of the soft X-ray background and is seen in every X-ray observation. Geocoronal emission, although usually weaker than heliospheric emission, arises within a few tens of Earth radii and therefore responds much more quickly (on time scales of less than an hour) to changes in solar wind intensity than the widely distributed heliospheric emission.We have studied a dozen Chandra observations when the flux of solar wind protons and O7+ ions was at its highest. These gusts of wind cause correspondingly abrupt changes in geocoronal SWCX X-ray emission,which may or may not be apparent in Chandra data depending on a given observation's line of sight through the magnetosphere. We compare observed changes in the X-ray background with predictions from a fully 3D analysis of SWCX emission based on magnetospheric simulations using the BATS-R-US model.
Screening model for nanowire surface-charge sensors in liquid
DEFF Research Database (Denmark)
Sørensen, Martin Hedegård; Mortensen, Asger; Brandbyge, Mads
2007-01-01
. The authors discuss this effect within Thomas-Fermi and Debye-Hückel theory and derive analytical results for cylindrical wires which can be used to estimate the sensitivity of nanowire surface-charge sensors. They study the interplay between the nanowire radius, the Thomas-Fermi and Debye screening...
Jones, Bleddyn
2015-01-01
The aim of this work is to predict relative biological effectiveness (RBE) for protons and clinically relevant heavier ions, by using a simplified semi-empirical process based on rational expectations and published experimental results using different ion species. The model input parameters are: Z (effective nuclear charge) and radiosensitivity parameters αL and βL of the control low linear energy transfer (LET) radiation. Sequential saturation processes are assumed for: (a) the position of t...
Knapen, Luk; Kochan, Bruno; BELLEMANS, Tom; JANSSENS, Davy; Wets, Geert
2012-01-01
Electric power demand for household generated trafﬁc is estimated as a function of time and space for the region of Flanders. An activity-based model is used to predict trafﬁc demand. Electric vehicle (EV) type and charger characteristics are determined on the basis of car ownership and by assuming that EV categories market shares will be similar to the current ones for internal combustion engine vehicles (ICEV) published in government statistics. Charging opportunities at home and work locat...
Hummer, G; Neumann, M; Hummer, Gerhard; Gr{ø}nbech-Jensen, Niels; Neumann, Martin
1998-01-01
Ewald summation and physically equivalent methods such as particle-mesh Ewald, kubic-harmonic expansions, or Lekner sums are commonly used to calculate long-range electrostatic interactions in computer simulations of polar and charged substances. The calculation of pressures in such systems is investigated. We find that the virial and thermodynamic pressures differ because of the explicit volume dependence of the effective, resummed Ewald potential. The thermodynamic pressure, obtained from the volume derivative of the Helmholtz free energy, can be expressed easily for both ionic and rigid molecular systems. For a system of rigid molecules, the electrostatic energy and the forces at the atom positions are required, both of which are readily available in molecular dynamics codes. We then calculate the virial and thermodynamic pressures for the extended simple point charge (SPC/E) water model at standard conditions. We find that the thermodynamic pressure exhibits considerably less system size dependence than t...
Required Collaborative Work in Online Courses: A Predictive Modeling Approach
Smith, Marlene A.; Kellogg, Deborah L.
2015-01-01
This article describes a predictive model that assesses whether a student will have greater perceived learning in group assignments or in individual work. The model produces correct classifications 87.5% of the time. The research is notable in that it is the first in the education literature to adopt a predictive modeling methodology using data…
Topological charge order and binding in a frustrated XY model and related systems
International Nuclear Information System (INIS)
We prove the existence of a finite temperature Z2 phase transition for the topological charge ordering within the fully frustrated XY model. Our method enables a proof of the topological charge confinement within the conventional XY models from a rather general vista. One of the complications that we face is the non-exact equivalence of the continuous (angular) XY model and its discrete topological charge dual. In reality, the energy spectra of the various topological sectors are highly nested, much unlike that suggested by the discrete dual models. We surmount these difficulties by exploiting the reflection positivity symmetry that this periodic flux phase model possesses. The techniques introduced here may prove binding of topological charges in numerous models and might be applied to examine transitions associated with various topological defects, e.g., the confinement of disclinations in the isotropic to nematic transition. (paper)
Sokalski, W. A.; Shibata, M.; Ornstein, R. L.; Rein, R.
1992-01-01
The quality of several atomic charge models based on different definitions has been analyzed using cumulative atomic multipole moments (CAMM). This formalism can generate higher atomic moments starting from any atomic charges, while preserving the corresponding molecular moments. The atomic charge contribution to the higher molecular moments, as well as to the electrostatic potentials, has been examined for CO and HCN molecules at several different levels of theory. The results clearly show that the electrostatic potential obtained from CAMM expansion is convergent up to R-5 term for all atomic charge models used. This illustrates that higher atomic moments can be used to supplement any atomic charge model to obtain more accurate description of electrostatic properties.
Brain Emotional Learning-Based Prediction Model (For Long-Term Chaotic Prediction Applications)
Parsapoor, Mahboobeh
2016-01-01
This study suggests a new prediction model for chaotic time series inspired by the brain emotional learning of mammals. We describe the structure and function of this model, which is referred to as BELPM (Brain Emotional Learning-Based Prediction Model). Structurally, the model mimics the connection between the regions of the limbic system, and functionally it uses weighted k nearest neighbors to imitate the roles of those regions. The learning algorithm of BELPM is defined using steepest des...
International Nuclear Information System (INIS)
HiggsBounds 2.0.0 is a computer code which tests both neutral and charged Higgs sectors of arbitrary models against the current exclusion bounds from the Higgs searches at LEP and the Tevatron. As input, it requires a selection of model predictions, such as Higgs masses, branching ratios, effective couplings and total decay widths. HiggsBounds 2.0.0 then uses the expected and observed topological cross section limits from the Higgs searches to determine whether a given parameter scenario of a model is excluded at the 95% C.L. by those searches. Version 2.0.0 represents a significant extension of the code since its first release (1.0.0). It includes now 28/53 LEP/Tevatron Higgs search analyses, compared to the 11/22 in the first release, of which many of the ones from the Tevatron are replaced by updates. As a major extension, the code allows now the predictions for (singly) charged Higgs bosons to be confronted with LEP and Tevatron searches. Furthermore, the newly included analyses contain LEP searches for neutral Higgs bosons (H) decaying invisibly or into (non flavour tagged) hadrons as well as decay-mode independent searches for neutral Higgs bosons, LEP searches via the production modes τ+τ-H and b anti bH, and Tevatron searches via t anti tH. Also, all Tevatron results presented at the ICHEP'10 are included in version 2.0.0. As physics applications of HiggsBounds 2.0.0 we study the allowed Higgs mass range for model scenarios with invisible Higgs decays and we obtain exclusion results for the scalar sector of the Randall-Sundrum model using up-to-date LEP and Tevatron direct search results. (orig.)
Dark fermions from the Standard Model via spin-charge separation
Xiong, Chi
2016-01-01
We study a new composite scenario of the lepton sector in the Standard Model by a de-gauging procedure called spin-charge separation and propose that leptons are bound states of some neutral fermions and Higgs bosons. Continuing this procedure we may obtain more fundamental dark fermions. They become the physical leptons by acquiring both charges and masses from some Higgs fields.
Integrated DEM–CFD modeling of the contact charging of pneumatically conveyed powders
Korevaar, M.W.; Padding, J.T.; Hoef, van der M.A.; Kuipers, J.A.M.
2014-01-01
A model is proposed that incorporates contact charging (also known as triboelectric charging) of pneumatically conveyed powders in a DEM–CFD framework, which accounts for the electrostatic interactions, both between particles and between the particles and conducting walls. The simulation results rev
Models of environment and T_1 relaxation in Josephson Charge Qubits
Faoro, Lara; Bergli, Joakim; Altshuler, Boris L.; Galperin, Yuri M.
2004-01-01
A theoretical interpretation of the recent experiments of Astafiev et. al. on the T_1-relaxation rate in Josephson Charge Qubits is proposed. The experimentally observed reproducible nonmonotonic dependence of T_1 on the splitting E_J of the qubit levels suggests further specification of the previously proposed models of the background charge noise. From our point of view the most promising is the ``Andreev fluctuator'' model of the noise. In this model the fluctuator is a Cooper pair that tu...
Modelling Inductive Charging of Battery Electric Vehicles using an Agent-Based Approach
Directory of Open Access Journals (Sweden)
Zain Ul Abedin
2014-09-01
Full Text Available The introduction of battery electric vehicles (BEVs could help to reduce dependence on fossil fuels and emissions from transportation and as such increase energy security and foster sustainable use of energy resources. However a major barrier to the introduction of BEVs is their limited battery capacity and long charging durations. To address these issues of BEVs several solutions are proposed such as battery swapping and fast charging stations. However apart from these stationary modes of charging, recently a new mode of charging has been introduced which is called inductive charging. This allows charging of BEVs as they drive along roads without the need of plugs, using induction. But it is unclear, if and how such technology could be utilized best. In order to investigate the possible impact of the introduction of such inductive charging infrastructure, its potential and its optimal placement, a framework for simulating BEVs using a multi-agent transport simulation was used. This framework was extended by an inductive charging module and initial test runs were performed. In this paper we present the simulation results of these preliminary tests together with analysis which suggests that battery sizes of BEVs could be reduced even if inductive charging technology is implemented only at a small number of high traffic volume links. The paper also demonstrates that our model can effectively support policy and decision making for deploying inductive charging infrastructure.
Testing the predictive power of nuclear mass models
International Nuclear Information System (INIS)
A number of tests are introduced which probe the ability of nuclear mass models to extrapolate. Three models are analyzed in detail: the liquid drop model, the liquid drop model plus empirical shell corrections and the Duflo-Zuker mass formula. If predicted nuclei are close to the fitted ones, average errors in predicted and fitted masses are similar. However, the challenge of predicting nuclear masses in a region stabilized by shell effects (e.g., the lead region) is far more difficult. The Duflo-Zuker mass formula emerges as a powerful predictive tool
A new ensemble model for short term wind power prediction
DEFF Research Database (Denmark)
Madsen, Henrik; Albu, Razvan-Daniel; Felea, Ioan;
2012-01-01
As the objective of this study, a non-linear ensemble system is used to develop a new model for predicting wind speed in short-term time scale. Short-term wind power prediction becomes an extremely important field of research for the energy sector. Regardless of the recent advancements in the re......-search of prediction models, it was observed that different models have different capabilities and also no single model is suitable under all situations. The idea behind EPS (ensemble prediction systems) is to take advantage of the unique features of each subsystem to detain diverse patterns that exist in...
Testing the predictive power of nuclear mass models
Energy Technology Data Exchange (ETDEWEB)
Mendoza-Temis, J.; Morales, I. [Instituto de Ciencias Nucleares, Universidad Nacional Autonoma de Mexico, Apdo. Postal 70-543, Mexico 04510 D.F. (Mexico); Barea, J. [Center for Theoretical Physics, Sloane Physics Laboratory, Yale University, PO Box 208120, New Haven, CT 06520-8120 (United States); Frank, A. [Instituto de Ciencias Nucleares, Universidad Nacional Autonoma de Mexico, Apdo. Postal 70-543, Mexico 04510 D.F. (Mexico); Hirsch, J.G. [Instituto de Ciencias Nucleares, Universidad Nacional Autonoma de Mexico, Apdo. Postal 70-543, Mexico 04510 D.F. (Mexico)], E-mail: hirsch@nucleares.unam.mx; Vieyra, J.C. Lopez [Instituto de Ciencias Nucleares, Universidad Nacional Autonoma de Mexico, Apdo. Postal 70-543, Mexico 04510 D.F. (Mexico); Van Isacker, P. [Grand Accelerateur National d' Ions Lourds, CEA/DSM-CNRS/IN2P3, BP 55027, F-14076 Caen cedex 5 (France); Velazquez, V. [Facultad de Ciencias, Universidad Nacional Autonoma de Mexico, Apdo. Postal 70-543, Mexico 04510 D.F. (Mexico)
2008-11-01
A number of tests are introduced which probe the ability of nuclear mass models to extrapolate. Three models are analyzed in detail: the liquid drop model, the liquid drop model plus empirical shell corrections and the Duflo-Zuker mass formula. If predicted nuclei are close to the fitted ones, average errors in predicted and fitted masses are similar. However, the challenge of predicting nuclear masses in a region stabilized by shell effects (e.g., the lead region) is far more difficult. The Duflo-Zuker mass formula emerges as a powerful predictive tool.
From Predictive Models to Instructional Policies
Rollinson, Joseph; Brunskill, Emma
2015-01-01
At their core, Intelligent Tutoring Systems consist of a student model and a policy. The student model captures the state of the student and the policy uses the student model to individualize instruction. Policies require different properties from the student model. For example, a mastery threshold policy requires the student model to have a way…
Charge transfer along DNA molecule within Peyrard-Bishop-Holstein model
Edirisinghe, Neranjan; Apalkov, Vadym
2010-03-01
Charge transport through DNA molecule is important in many areas ranging from DNA damage repair to molecular nanowires. It is now widely accepted that a phonon mediated hopping of a charge carrier plays a major role in charge transport through DNA. In the present study we investigate system dynamics within Peyrard-Bishop-Holstein model for the charge transfer between donor and acceptor sites. We found that an escape time of a charge, trapped at the donor state of the DNA strand, is very sensitive to the initial value of H-bond stretching. This suggests importance of ensemble averaging. Moreover sharp phase transitions were observed for escape time in parameter space of transfer integrals and phonon-charge coupling constant.
Purdy, R.
1996-01-01
A hierarchical model consisting of quantitative structure-activity relationships based mainly on chemical reactivity was developed to predict the carcinogenicity of organic chemicals to rodents. The model is comprised of quantitative structure-activity relationships, QSARs based on hypothesized mechanisms of action, metabolism, and partitioning. Predictors included octanol/water partition coefficient, molecular size, atomic partial charge, bond angle strain, atomic acceptor delocalizibility, ...
Indian Academy of Sciences (India)
E Coniavitis; A Ferrari
2007-11-01
The minimal supersymmetric extension of the standard model (MSSM) predicts the existence of new charged and neutral Higgs bosons. The pair creation of these new particles at the multi-TeV + − compact linear collider (CLIC), followed by decays into standard model particles, were simulated along with the corresponding background. High-energy beam–beam effects such as ISR, beamstrahlung and hadronic background were included. We have investigated the possibility of using the ratio between the number of events found in various decay channels to determine the MSSM parameter tan and we have derived the corresponding statistical error from the uncertainties on the measured cross-sections and Higgs boson masses.
SAAMBE: Webserver to Predict the Charge of Binding Free Energy Caused by Amino Acids Mutations
Directory of Open Access Journals (Sweden)
Marharyta Petukh
2016-04-01
Full Text Available Predicting the effect of amino acid substitutions on protein–protein affinity (typically evaluated via the change of protein binding free energy is important for both understanding the disease-causing mechanism of missense mutations and guiding protein engineering. In addition, researchers are also interested in understanding which energy components are mostly affected by the mutation and how the mutation affects the overall structure of the corresponding protein. Here we report a webserver, the Single Amino Acid Mutation based change in Binding free Energy (SAAMBE webserver, which addresses the demand for tools for predicting the change of protein binding free energy. SAAMBE is an easy to use webserver, which only requires that a coordinate file be inputted and the user is provided with various, but easy to navigate, options. The user specifies the mutation position, wild type residue and type of mutation to be made. The server predicts the binding free energy change, the changes of the corresponding energy components and provides the energy minimized 3D structure of the wild type and mutant proteins for download. The SAAMBE protocol performance was tested by benchmarking the predictions against over 1300 experimentally determined changes of binding free energy and a Pearson correlation coefficient of 0.62 was obtained. How the predictions can be used for discriminating disease-causing from harmless mutations is discussed. The webserver can be accessed via http://compbio.clemson.edu/saambe_webserver/.
Dynamics of Charged Particulate Systems Modeling, Theory and Computation
Zohdi, Tarek I
2012-01-01
The objective of this monograph is to provide a concise introduction to the dynamics of systems comprised of charged small-scale particles. Flowing, small-scale, particles ("particulates'') are ubiquitous in industrial processes and in the natural sciences. Applications include electrostatic copiers, inkjet printers, powder coating machines, etc., and a variety of manufacturing processes. Due to their small-scale size, external electromagnetic fields can be utilized to manipulate and control charged particulates in industrial processes in order to achieve results that are not possible by purely mechanical means alone. A unique feature of small-scale particulate flows is that they exhibit a strong sensitivity to interparticle near-field forces, leading to nonstandard particulate dynamics, agglomeration and cluster formation, which can strongly affect manufactured product quality. This monograph also provides an introduction to the mathematically-related topic of the dynamics of swarms of interacting objects, ...
Numerical modelling of charged black holes with massive dilaton
International Nuclear Information System (INIS)
The static and spherically symmetric electrically charged black hole solutions in Einstein-Born-Infeld gravity with massive dilaton are investigated numerically. The Continuous Analog of Newton Method is used to solve originated nonlinear boundary-value problems. The corresponding linearized BVPs are solved numerically by means of the spline-collocation scheme of the fourth order. An important class of solutions are the extremal ones. We show that the extremal horizons satisfy some nonlinear system of an algebraic equation. Depending on the charge q and dilaton mass γ the black holes can have either one, two, or three horizons. This allows one to construct a Hermite polynomial of the third order, which real roots describe the number, the kind and the values of the horizons. (author)
Refining the committee approach and uncertainty prediction in hydrological modelling
N. Kayastha
2014-01-01
Due to the complexity of hydrological systems a single model may be unable to capture the full range of a catchment response and accurately predict the streamflows. The multi modelling approach opens up possibilities for handling such difficulties and allows improve the predictive capability of models. One of multi modelling approaches called "committee modelling" is one of the topics in part of this study. Special attention is given to the so-called “fuzzy committee” approach to hydrological...
Exact Baryon, Strangeness and Charge Conservation in Hadronic Gas Models
Cleymans, J; Suhonen, E
1997-01-01
Relativistic heavy ion collisions are studied assuming that particles can be described by a hadron gas in thermal and chemical equilibrium. The exact conservation of baryon number, strangeness and charge are explicitly taken into account. For heavy ions the effect arising from the neutron surplus becomes important and leads to a substantial increase in e.g. the $\\pi^-/\\pi^+$ ratio. A method is developed which is very well suited for the study of small systems.
Effective models for charge transport in DNA nanowires
Gutierrez, Rafael; Cuniberti, Gianaurelio
2006-01-01
The rapid progress in the field of molecular electronics has led to an increasing interest on DNA oligomers as possible components of electronic circuits at the nanoscale. For this, however, an understanding of charge transfer and transport mechanisms in this molecule is required. Experiments show that a large number of factors may influence the electronic properties of DNA. Though full first principle approaches are the ideal tool for a theoretical characterization of the structural and elec...
Real-time multi-model decadal climate predictions
Smith, D.M.; Scaife, A.A.; Boer, G.J.; Caian, M.; Doblas-Reyes, F.J.; Guemas, V.; Hawkins, E.; Hazeleger, W.; Hermanson, L.; Ho, C.K.; Ishii, M.; Kharin, V.; Kimoto, M.; Kirtman, B.; Lean, J.; Matei, D.; Merryfield, W.J.; Muller, W.A.; Pohlmann, H.; Rosati, A.; Wouters, B.; Wyser, K.
2013-01-01
We present the first climate prediction of the coming decade made with multiple models, initialized with prior observations. This prediction accrues from an international activity to exchange decadal predictions in near real-time, in order to assess differences and similarities, provide a consensus
Evaluation of Spatial Agreement of Distinct Landslide Prediction Models
Sterlacchini, S.; Frigerio, I; Bordogna, G,
2013-01-01
The aim of the study was to assess the degree of spatial agreement of different predicted patterns in a majority of coherent landslide prediction maps with almost similar success and prediction rate curves. If two or more models have a similar performance, the choice of the best one is not a trivial operation and cannot be based on success and prediction rate curves only. In fact, it may happen that two or more prediction maps with similar accuracy and predictive power do not have the same de...
Predictive Control for Mechatronic Laboratory Models
Czech Academy of Sciences Publication Activity Database
Belda, Květoslav
Praha: ÚTIA AV ČR, 2006 - (Šmídl., V.), s. 1-6 [International PhD Workshop on Interplay of Societal and Technical Decision-Making, Young Generation Viewpoint /7./. Hrubá Skála (CZ), 25.09.2006-30.09.2006] R&D Projects: GA ČR GA102/05/0271; GA ČR GP102/06/P275 Institutional research plan: CEZ:AV0Z10750506 Keywords : Mechatronic systems * Predictive control * I/O equations of predictions Subject RIV: BC - Control Systems Theory http://library.utia.cas.cz/separaty/historie/belda-0045352.pdf
International Nuclear Information System (INIS)
The vanadium redox flow battery (VRFB) has emerged as a viable grid-scale energy storage technology that offers cost-effective energy storage solutions for renewable energy applications. In this paper, a novel methodology is introduced for modeling of the transport mechanisms of electrolyte flow, species and charge in the VRFB at the pore scale of the electrodes; that is, at the level where individual carbon fiber geometry and electrolyte flow are directly resolved. The detailed geometry of the electrode is obtained using X-ray computed tomography (XCT) and calibrated against experimentally determined pore-scale characteristics (e.g., pore and fiber diameter, porosity, and surface area). The processed XCT data is then used as geometry input for modeling of the electrochemical processes in the VRFB. The flow of electrolyte through the pore space is modeled using the lattice Boltzmann method (LBM) while the finite volume method (FVM) is used to solve the coupled species and charge transport and predict the performance of the VRFB under various conditions. An electrochemical model using the Butler–Volmer equations is used to provide species and charge coupling at the surfaces of the carbon fibers. Results are obtained for the cell potential distribution, as well as local concentration, overpotential and current density profiles under galvanostatic discharge conditions. The cell performance is investigated as a function of the electrolyte flow rate and external drawing current. The model developed here provides a useful tool for building the structure–property–performance relationship of VRFB electrodes.
Predicting Historical Droughts in the US With a Multi-model Seasonal Hydrologic Prediction System
Luo, L.; Wood, E.; Sheffield, J.; Li, H.
2008-12-01
Droughts are as much a part of weather and climate extremes as floods, hurricanes and tornadoes are, but they are the most costly extremes among all natural disasters in the U.S. The estimated annual direct losses to the U.S economy due to droughts are about 6-8 billion, with the drought of 1988 estimated to have damages over $39 billion. Having a seasonal drought prediction system that can accurately predict the onset, development and recovery of drought episodes will significantly help to reduce the loss due to drought. In this study, a seasonal hydrologic ensemble prediction system developed for the eastern United States is used to predict historical droughts in the US retrospectively. The system uses a hydrologic model (i.e., the Variable Infiltration Capacity model) as the central element for producing ensemble predictions of soil moisture, snow, and streamflow with lead times up to six months. One unique feature of this system is in the method for generating ensemble atmospheric forcings for the forecast period. It merges seasonal climate forecasts from multiple climate models with observed climatology in a Bayesian framework, such that the uncertainties related to the atmospheric forcings can be better quantified while the signals from individual models are combined. Simultaneously, climate model forecasts are downscaled to an appropriate spatial scale for hydrologic predictions. When generating daily meteorological forcing, the system uses the rank structures of selected historical forcing records to ensure reasonable weather patterns in space and time. The system is applied to different regions in the US to predict historical drought episodes. These forecasts use seasonal climate forecast from a combination of the NCEP CFS and seven climate models in the European Union's Development of a European Multimodel Ensemble System for Seasonal to-Interannual Prediction (CFS+DEMETER). This study validates the approach of using seasonal climate predictions from
Predictive modeling and reducing cyclic variability in autoignition engines
Energy Technology Data Exchange (ETDEWEB)
Hellstrom, Erik; Stefanopoulou, Anna; Jiang, Li; Larimore, Jacob
2016-08-30
Methods and systems are provided for controlling a vehicle engine to reduce cycle-to-cycle combustion variation. A predictive model is applied to predict cycle-to-cycle combustion behavior of an engine based on observed engine performance variables. Conditions are identified, based on the predicted cycle-to-cycle combustion behavior, that indicate high cycle-to-cycle combustion variation. Corrective measures are then applied to prevent the predicted high cycle-to-cycle combustion variation.
Evaluation of the US Army fallout prediction model
International Nuclear Information System (INIS)
The US Army fallout prediction method was evaluated against an advanced fallout prediction model--SIMFIC (Simplified Fallout Interpretive Code). The danger zone areas of the US Army method were found to be significantly greater (up to a factor of 8) than the areas of corresponding radiation hazard as predicted by SIMFIC. Nonetheless, because the US Army's method predicts danger zone lengths that are commonly shorter than the corresponding hot line distances of SIMFIC, the US Army's method is not reliably conservative
Kumar, Sivakumar Prasanth; Jha, Prakash C; Jasrai, Yogesh T; Pandya, Himanshu A
2016-03-01
The estimation of atomic partial charges of the small molecules to calculate molecular interaction fields (MIFs) is an important process in field-based quantitative structure-activity relationship (QSAR). Several studies showed the influence of partial charge schemes that drastically affects the prediction accuracy of the QSAR model and focused on the selection of appropriate charge models that provide highest cross-validated correlation coefficient ([Formula: see text] or q(2)) to explain the variation in chemical structures against biological endpoints. This study shift this focus in a direction to understand the molecular regions deemed to explain SAR in various charge models and recognize a consensus picture of activity-correlating molecular regions. We selected eleven diverse dataset and developed MIF-based QSAR models using various charge schemes including Gasteiger-Marsili, Del Re, Merck Molecular Force Field, Hückel, Gasteiger-Hückel, and Pullman. The generalized resultant QSAR models were then compared with Open3DQSAR model to interpret the MIF descriptors decisively. We suggest the regions of activity contribution or optimization can be effectively determined by studying various charge-based models to understand SAR precisely. PMID:25997097
Predicting Career Advancement with Structural Equation Modelling
Heimler, Ronald; Rosenberg, Stuart; Morote, Elsa-Sofia
2012-01-01
Purpose: The purpose of this paper is to use the authors' prior findings concerning basic employability skills in order to determine which skills best predict career advancement potential. Design/methodology/approach: Utilizing survey responses of human resource managers, the employability skills showing the largest relationships to career…
Intelligent predictive model of ventilating capacity of imperial smelt furnace
Institute of Scientific and Technical Information of China (English)
唐朝晖; 胡燕瑜; 桂卫华; 吴敏
2003-01-01
In order to know the ventilating capacity of imperial smelt furnace (ISF), and increase the output of plumbum, an intelligent modeling method based on gray theory and artificial neural networks(ANN) is proposed, in which the weight values in the integrated model can be adjusted automatically. An intelligent predictive model of the ventilating capacity of the ISF is established and analyzed by the method. The simulation results and industrial applications demonstrate that the predictive model is close to the real plant, the relative predictive error is 0.72%, which is 50% less than the single model, leading to a notable increase of the output of plumbum.
A model to predict the power output from wind farms
Energy Technology Data Exchange (ETDEWEB)
Landberg, L. [Riso National Lab., Roskilde (Denmark)
1997-12-31
This paper will describe a model that can predict the power output from wind farms. To give examples of input the model is applied to a wind farm in Texas. The predictions are generated from forecasts from the NGM model of NCEP. These predictions are made valid at individual sites (wind farms) by applying a matrix calculated by the sub-models of WASP (Wind Atlas Application and Analysis Program). The actual wind farm production is calculated using the Riso PARK model. Because of the preliminary nature of the results, they will not be given. However, similar results from Europe will be given.
Directory of Open Access Journals (Sweden)
Yongjun Ahn
Full Text Available The charging infrastructure location problem is becoming more significant due to the extensive adoption of electric vehicles. Efficient charging station planning can solve deeply rooted problems, such as driving-range anxiety and the stagnation of new electric vehicle consumers. In the initial stage of introducing electric vehicles, the allocation of charging stations is difficult to determine due to the uncertainty of candidate sites and unidentified charging demands, which are determined by diverse variables. This paper introduces the Estimating the Required Density of EV Charging (ERDEC stations model, which is an analytical approach to estimating the optimal density of charging stations for certain urban areas, which are subsequently aggregated to city level planning. The optimal charging station's density is derived to minimize the total cost. A numerical study is conducted to obtain the correlations among the various parameters in the proposed model, such as regional parameters, technological parameters and coefficient factors. To investigate the effect of technological advances, the corresponding changes in the optimal density and total cost are also examined by various combinations of technological parameters. Daejeon city in South Korea is selected for the case study to examine the applicability of the model to real-world problems. With real taxi trajectory data, the optimal density map of charging stations is generated. These results can provide the optimal number of chargers for driving without driving-range anxiety. In the initial planning phase of installing charging infrastructure, the proposed model can be applied to a relatively extensive area to encourage the usage of electric vehicles, especially areas that lack information, such as exact candidate sites for charging stations and other data related with electric vehicles. The methods and results of this paper can serve as a planning guideline to facilitate the extensive
Model predictive control for wind power gradients
DEFF Research Database (Denmark)
Hovgaard, Tobias Gybel; Boyd, Stephen; Jørgensen, John Bagterp
2015-01-01
We consider the operation of a wind turbine and a connected local battery or other electrical storage device, taking into account varying wind speed, with the goal of maximizing the total energy generated while respecting limits on the time derivative (gradient) of power delivered to the grid. We...... use the turbine inertia as an additional energy storage device, by varying its speed over time, and coordinate the flows of energy to achieve the goal. The control variables are turbine pitch, generator torque and charge/discharge rates for the storage device, each of which can be varied over given...... ranges. The system dynamics are quite non-linear, and the constraints and objectives are not convex functions of the control inputs, so the resulting optimal control problem is difficult to solve globally. In this paper, we show that by a novel change of variables, which focuses on power flows, we can...
BEHAVE : Fire Behavior Prediction and Fuel Modeling System -- FUEL Subsystem
Burgan, Robert E; Rothermel, Richard C
1984-01-01
This manual documents the fuel modeling procedures of BEHAVE - a state-of-the-art wildland fire behavior prediction system. Described are procedures for collecting fuel data, using the data with the program, and testing and adjusting the fuel model.
Model-based uncertainty in species range prediction
DEFF Research Database (Denmark)
Pearson, R. G.; Thuiller, Wilfried; Bastos Araujo, Miguel;
2006-01-01
Aim Many attempts to predict the potential range of species rely on environmental niche (or 'bioclimate envelope') modelling, yet the effects of using different niche-based methodologies require further investigation. Here we investigate the impact that the choice of model can have on predictions......, identify key reasons why model output may differ and discuss the implications that model uncertainty has for policy-guiding applications. Location The Western Cape of South Africa. Methods We applied nine of the most widely used modelling techniques to model potential distributions under current...... and predicted future climate for four species (including two subspecies) of Proteaceae. Each model was built using an identical set of five input variables and distribution data for 3996 sampled sites. We compare model predictions by testing agreement between observed and simulated distributions for the present...
Modelling microbial interactions and food structure in predictive microbiology
Malakar, P.K.
2002-01-01
Keywords: modelling, dynamic models, microbial interactions, diffusion, microgradients, colony growth, predictive microbiology. Growth response of microorganisms in foods is a complex process. Innovations in food production and preservation techniques have resulted in adoption of new technologies
Model selection and paradoxes of prediction (in Russian)
Oleg Itskhoki
2006-01-01
In this essay we postulate a number of theoretical hypotheses allowing one to resolve in some degree the following two prediction paradoxes: (1) why simple linear models often have an advantage in predictive power over more complex nonlinear models that lead to a better in-sample fit; (2) why combinations of forecasts often increase the predictive power of individual forecasts. We also give a numerical example illustrating our theoretical statements.
Depletion models can predict shorebird distribution at different spatial scales.
Gill, J. A.; Sutherland, W. J.; Norris, K.
2001-01-01
Predicting the impact of habitat change on populations requires an understanding of the number of animals that a given area can support. Depletion models enable predictions of the numbers of individuals an area can support from prey density and predator searching efficiency and handling time. Depletion models have been successfully employed to predict patterns of abundance over small spatial scales, but most environmental change occurs over large spatial scales. We test the ability of depleti...
Modelling surface restructuring by slow highly charged ions
International Nuclear Information System (INIS)
We theoretically investigate surface modifications on alkaline earth halides due to highly charged ion impact, focusing on recent experimental evidence for both etch pit and nano-hillock formation on CaF2 (A.S. El-Said et al., Phys. Rev. Lett. 109, (2012) 117602 [1]). We discuss mechanisms for converting the projectile potential and kinetic energies into thermal energy capable of changing the surface structure. A proof-of-principle classical molecular dynamics simulation suggests the existence of two thresholds which we associate with etch pit and nano-hillock formation in qualitative agreement with experiment
Jagannathan, M.; Chandran, K. S. Ravi
2014-02-01
Physically-based analytical models that provide insights into the diffusion and/or interface charge transfer effects in bulk (lithiating/delithiating) electrodes are needed to truly assess the performance/limitations of electrode materials for Li-ion batteries. In this context, an analytical modeling framework is constructed here to predict the electrochemical charge-discharge characteristics during lithiation and delithiation of solid amorphous Si (a-Si) thin film electrodes. The framework includes analytical expressions that satisfy Fick's second law for Li transport and the requisite flux boundary conditions of lithiation and delithiation steps. The expressions are derived here by the method of separation of variables. They enable the determination of transient Li concentration profiles in the thin film electrode as a function of state of charge/discharge. The time-dependent electrode surface concentrations (at the electrode-electrolyte interface) obtained from these profiles were used to determine the activation overpotentials and thus, the non-equilibrium cell potentials, as a function of state of charge/discharge using Butler-Volmer kinetics. The simulated charge/discharge characteristics agreed well with the experimental data of a-Si thin film electrodes obtained at different C-rates. The model offers insights into how the charge-discharge behavior is controlled by diffusion limitation within electrode and/or the activation overpotentials at the interface. The analytical framework is also shown to predict successfully the hysteretic behavior of lithiation/delithiation voltage curves.
Evaluation of Fast-Time Wake Vortex Prediction Models
Proctor, Fred H.; Hamilton, David W.
2009-01-01
Current fast-time wake models are reviewed and three basic types are defined. Predictions from several of the fast-time models are compared. Previous statistical evaluations of the APA-Sarpkaya and D2P fast-time models are discussed. Root Mean Square errors between fast-time model predictions and Lidar wake measurements are examined for a 24 hr period at Denver International Airport. Shortcomings in current methodology for evaluating wake errors are also discussed.
On the importance of nonlinear modeling in computer performance prediction
Garland, Joshua; Bradley, Elizabeth
2013-01-01
Computers are nonlinear dynamical systems that exhibit complex and sometimes even chaotic behavior. The models used in the computer systems community, however, are linear. This paper is an exploration of that disconnect: when linear models are adequate for predicting computer performance and when they are not. Specifically, we build linear and nonlinear models of the processor load of an Intel i7-based computer as it executes a range of different programs. We then use those models to predict ...
Bayesian variable order Markov models: Towards Bayesian predictive state representations
C. Dimitrakakis
2009-01-01
We present a Bayesian variable order Markov model that shares many similarities with predictive state representations. The resulting models are compact and much easier to specify and learn than classical predictive state representations. Moreover, we show that they significantly outperform a more st
Refining the Committee Approach and Uncertainty Prediction in Hydrological Modelling
Kayastha, N.
2014-01-01
Due to the complexity of hydrological systems a single model may be unable to capture the full range of a catchment response and accurately predict the streamflows. The multi modelling approach opens up possibilities for handling such difficulties and allows improve the predictive capability of mode
Refining the committee approach and uncertainty prediction in hydrological modelling
Kayastha, N.
2014-01-01
Due to the complexity of hydrological systems a single model may be unable to capture the full range of a catchment response and accurately predict the streamflows. The multi modelling approach opens up possibilities for handling such difficulties and allows improve the predictive capability of mode
A new, accurate predictive model for incident hypertension
DEFF Research Database (Denmark)
Völzke, Henry; Fung, Glenn; Ittermann, Till; Yu, Shipeng; Baumeister, Sebastian E; Dörr, Marcus; Lieb, Wolfgang; Völker, Uwe; Linneberg, Allan; Jørgensen, Torben; Felix, Stephan B; Rettig, Rainer; Rao, Bharat; Kroemer, Heyo K
2013-01-01
Data mining represents an alternative approach to identify new predictors of multifactorial diseases. This work aimed at building an accurate predictive model for incident hypertension using data mining procedures.......Data mining represents an alternative approach to identify new predictors of multifactorial diseases. This work aimed at building an accurate predictive model for incident hypertension using data mining procedures....
Model for charge/discharge-rate-dependent plastic flow in amorphous battery materials
Khosrownejad, S. M.; Curtin, W. A.
2016-09-01
Plastic flow is an important mechanism for relaxing stresses that develop due to swelling/shrinkage during charging/discharging of battery materials. Amorphous high-storage-capacity Li-Si has lower flow stresses than crystalline materials but there is evidence that the plastic flow stress depends on the conditions of charging and discharging, indicating important non-equilibrium aspects to the flow behavior. Here, a mechanistically-based constitutive model for rate-dependent plastic flow in amorphous materials, such as LixSi alloys, during charging and discharging is developed based on two physical concepts: (i) excess energy is stored in the material during electrochemical charging and discharging due to the inability of the amorphous material to fully relax during the charging/discharging process and (ii) this excess energy reduces the barriers for plastic flow processes and thus reduces the applied stresses necessary to cause plastic flow. The plastic flow stress is thus a competition between the time scales of charging/discharging and the time scales of glassy relaxation. The two concepts, as well as other aspects of the model, are validated using molecular simulations on a model Li-Si system. The model is applied to examine the plastic flow behavior of typical specimen geometries due to combined charging/discharging and stress history, and the results generally rationalize experimental observations.
Verification of FAC prediction model in pipe wall thinning prediction software 'FALSET'
International Nuclear Information System (INIS)
Flow accelerated corrosion (FAC) and liquid droplet impingement erosion (LDI) are the main pipe wall thinning phenomena in piping system of power plants. At present, the management is based on thinning rate and residual lifetime evaluation using pipe wall thickness measurement results. For future improvement of the management, introduction of domestic prediction code is expected. Yoneda et al. have developed original prediction software for pipe wall thinning 'FALSET', which is one-dimensional prediction for maximum thinning rate in each element in pipelines by simplifying their prediction models for local thinning rate of FAC/LDI. In this study, FAC prediction model in FALSET was verified with FAC data in domestic PWR secondary system, and prediction accuracy at present was discussed. (author)
Bilevel linear programming model of charging for effluent based on price control
Institute of Scientific and Technical Information of China (English)
LI Yu-hua; LI Lei; HU Yun-quan; SHAO Hai-hong
2007-01-01
For the optimum price problem of charging for effluent, this paper analyzes the optimal Pigovian Tax and the serious information asymmetry problem existing in the application process of optimal Pigovian Tax,which is predominant in theory. Then the bilevel system optimizing decision-making theory is applied to give bilevel linear programming decision-making model of charging for effluent, in which the government (environmental protection agency) acts as the upper level decision-making unit and the polluting enterprises act as the lower level decision-making unit. To some extent, the model avoids the serious information asymmetry between the government and the polluting enterprises on charging for effluent.
Transverse space charge effect calculation in the Synergia accelerator modeling toolkit
Energy Technology Data Exchange (ETDEWEB)
Okonechnikov, Konstantin; Amundson, James; Macridin, Alexandru; /Fermilab
2009-09-01
This paper describes a transverse space charge effect calculation algorithm, developed in the context of accelerator modeling toolkit Synergia. The introduction to the space charge problem and the Synergia modeling toolkit short description are given. The developed algorithm is explained and the implementation is described in detail. As a result of this work a new space charge solver was developed and integrated into the Synergia toolkit. The solver showed correct results in comparison to existing Synergia solvers and delivered better performance in the regime where it is applicable.
SAAMBE: Webserver to Predict the Charge of Binding Free Energy Caused by Amino Acids Mutations
Marharyta Petukh; Luogeng Dai; Emil Alexov
2016-01-01
Predicting the effect of amino acid substitutions on protein–protein affinity (typically evaluated via the change of protein binding free energy) is important for both understanding the disease-causing mechanism of missense mutations and guiding protein engineering. In addition, researchers are also interested in understanding which energy components are mostly affected by the mutation and how the mutation affects the overall structure of the corresponding protein. Here we report a webserver,...
Predicting Leptonic CP phase by considering deviations in charged lepton and neutrino sectors
M., Sruthilaya; Deepthi, K N; Mohanta, R
2014-01-01
Recently, the reactor mixing angle $\\theta_{13}$ 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 BM, TBM, GRA, GRB, HG etc., which are based on certain flavor symmetries predict vanishing $\\theta_{13}$. Using the fact that the neutrino mixing matrix can be represented as $V_{\\rm PMNS}=U_l^{\\dagger} U_\
OPTIMIZATION OF THE HEAT TREATMENT PROCESS OF A STEEL POROUS CHARGE USING AN INTEGRATED MODELLING
Directory of Open Access Journals (Sweden)
Rafał Wyczółkowski
2014-11-01
Full Text Available The paper discusses the structure and principle of operation of programs for integrated modelling of the processes of heat treatment of porous-structure steel charges, such as long product bundles or strip or wire coils. Consideration is given to the specificity of these models in respect to porous charges. This is associated with their untypical thermal properties, which are expressed using the concept of effective thermal conductivity.
OPTIMIZATION OF THE HEAT TREATMENT PROCESS OF A STEEL POROUS CHARGE USING AN INTEGRATED MODELLING
Rafał Wyczółkowski; Agnieszka Benduch
2014-01-01
The paper discusses the structure and principle of operation of programs for integrated modelling of the processes of heat treatment of porous-structure steel charges, such as long product bundles or strip or wire coils. Consideration is given to the specificity of these models in respect to porous charges. This is associated with their untypical thermal properties, which are expressed using the concept of effective thermal conductivity.
Ouyang, Minggao; Liu, Guangming; Lu, Languang; Li, Jianqiu; Han, Xuebing
2014-12-01
In order to predict the battery remaining discharge energy in electric vehicles, an accurate onboard battery model is needed for the terminal voltage and state of charge (SOC) estimation in the whole SOC range. However, the commonly-used equivalent circuit model (ECM) provides limited accuracy in low-SOC area, which hinders the full use of battery remaining energy. To improve the low-SOC-area performance, this paper presents an extended equivalent circuit model (EECM) based on single-particle electrochemical model. In EECM, the solid-phase diffusion process is represented by the SOC difference within the electrode particle, and the terminal voltage is determined by the surface SOC (SOCsurf) representing the lithium concentration at the particle surface. Based on a large-format lithium-ion battery, the voltage estimation performance of ECM and EECM is compared in the entire SOC range (0-100%) under different load profiles, and the genetic algorithm is implemented in model parameterization. Results imply that the EECM could reduce the voltage error by more than 50% in low-SOC area. The SOC estimation accuracy is then discussed employing the extended Kalman filter, and the EECM also exhibits significant advantage. As a result, the EECM is very potential for real-time applications to enhance the voltage and SOC estimation precision especially for low-SOC cases.
A Model Coupling Method for Shape Prediction
Institute of Scientific and Technical Information of China (English)
WANG Dong-cheng; LIU Hong-min
2012-01-01
The shape of strip is calculated by iterative method which combines strip plastic deformation model with rolls elastic deformation model through their calculation results, which can be called results coupling method. Be- cause the shape and rolling force distribution are very sensitive to strip thickness transverse distribution% variation, the iterative course is rather unstable and sometimes convergence cannot be achieved. In addition, the calculating speed of results coupling method is low, which restricts its usable range. To solve the problem, a new model cou- pling method is developed, which takes the force distribution between rolls, rolling force distribution and strip＇s exit transverse displacement distribution as basic unknowns, and integrates strip plastic deformation model and rolls elas- tic deformation model as a unified linear equations through their internal relation, so the iterative calculation between the strip plastic deformation model and rolls elastic deformation model can be avoided. To prove the effectiveness of the model coupling method, two examples are calculated by results coupling method and model coupling method re- spectively. The results of front tension stress, back tension stress, strip~s exit gauge, the force between rolls and rolling force distribution calculated by model coupling method coincide very well with results coupling method. How- ever the calculation course of model coupling method is more steady than results coupling method, and its calculating speed is about ten times as much as the maximal speed of results coupling method, which validates its practicability and reliability.
Ion-UHMA: a model for simulating the dynamics of neutral and charged aerosol particles.
Energy Technology Data Exchange (ETDEWEB)
Leppae, J.; Kerminen, V.-M. (Finnish Meteorological Institute, Climate Change Research, Helsinki (Finland)); Gagne, S.; Manninen, H. E.; Nieminen, T.; Kulmala, M. (Dept. of Physics, Univ. of Helsinki (Finland)); Laakso, L. (Dept. of Physics, Univ. of Helsinki (Finland); School of Physical and Chemical Sciences, North-West Univ. Potchefstroom (South Africa)); Korhonen, H. (Univ. of Kuopio, Dept. of Physics (Finland)); Lehtinen, K. E. J. (Univ. of Kuopio, Dept. of Physics (Finland); Finnish Meteorological Institute, Kuopio Unit (Finland))
2009-07-01
A new aerosol dynamical box model, Ion-UHMA (University of Helsinki Multicomponent Aerosol model for neutral and charged particles), is introduced in this paper. The model includes basic dynamical processes (condensation, coagulation and deposition) as well as ion-aerosol attachment and ion-ion recombination. The formation of particles is treated as model input or, alternatively, the model can be coupled with an existing nucleation model. Ion-UHMA was found to be able to reproduce qualitatively the measured time evolution of the particle number size distribution, when the particle formation and growth rates as well as concentrations of particles > 20 nm in diameter were taken from measurements. The simulated charging state of freshly formed particles during a new particle formation event evolved towards charge equilibrium in line with previously-derived analytical formulae. We provided a few illustrative examples to demonstrate possible applications, to which the Ion-UHMA model could be used in the near future. (orig.)
Gaussian mixture models as flux prediction method for central receivers
Grobler, Annemarie; Gauché, Paul; Smit, Willie
2016-05-01
Flux prediction methods are crucial to the design and operation of central receiver systems. Current methods such as the circular and elliptical (bivariate) Gaussian prediction methods are often used in field layout design and aiming strategies. For experimental or small central receiver systems, the flux profile of a single heliostat often deviates significantly from the circular and elliptical Gaussian models. Therefore a novel method of flux prediction was developed by incorporating the fitting of Gaussian mixture models onto flux profiles produced by flux measurement or ray tracing. A method was also developed to predict the Gaussian mixture model parameters of a single heliostat for a given time using image processing. Recording the predicted parameters in a database ensures that more accurate predictions are made in a shorter time frame.
First-Principles Prediction of the Charge Mobility in Black Phosphorus Semiconductor Nanoribbons.
Xiao, Jin; Long, Mengqiu; Zhang, Xiaojiao; Zhang, Dan; Xu, Hui; Chan, Kwok Sum
2015-10-15
We have investigated the electronic structure and carrier mobility of monolayer black phosphorus nanoribbons (BPNRs) using density functional theory combined with Boltzmann transport method with relaxation time approximation. It is shown that the calculated ultrahigh electron mobility can even reach the order of 10(3) to 10(7) cm(2) V(-1) s(-1) at room temperature. Owing to the electron mobility being higher than the hole mobility, armchair and diagonal BPNRs behave like n-type semiconductors. Comparing with the bare BPNRs, the difference between the hole and electronic mobilities can be enhanced in ribbons with the edges terminated by H atoms. Moreover, because the hole mobility is about two orders of magnitude larger than the electron mobility, zigzag BPNRs with H termination behave like p-type semiconductors. Our results indicate that BPNRs can be considered as a new kind of nanomaterial for applications in optoelectronics, nanoelectronic devices owing to the intrinsic band gap and ultrahigh charge mobility. PMID:26722789
Indian Academy of Sciences (India)
M E ZOMORRODIAN; M HASHEMINIA; S M ZABIHINPOUR; A MIRJALILI
2016-08-01
Inclusive momentum distributions of charged particles are measured in dijet events. Events were produced at the AMY detector with a centre of mass energy of 60 ${\\rm GeV}$. Our results were compared, on the one hand to those obtained from other $e^+ e^-$, $ep$ as well as CDF data, and on the other hand to the perturbative QCD calculations carried out in the framework of the modified leading log approximation (MLLA) and assuming local parton--hadron duality (LPHD). A fit of the shape of the distributions yields $\\scr Q_{eff} = 263 \\pm 13 {\\rm MeV}$ for the AMY data. In addition, a fit to the evolution of the peak position with dijet mass using all data from different experiments gives $\\scr Q_{eff} = 226 \\pm 18 {\\rm MeV}$. Next, αs was extracted using the shape of the distribution at the Z0 scale, with a value of 0.118 \\pm 0.013. This is consistent, within the statistical errors, with many accurate measurements. We conclude that it is the success of LPHD + MLLA that the extracted value of $\\alpha_{s}$ is correct. Possible explanations for all these features will be presented in this paper.
Application of Nonlinear Predictive Control Based on RBF Network Predictive Model in MCFC Plant
Institute of Scientific and Technical Information of China (English)
CHEN Yue-hua; CAO Guang-yi; ZHU Xin-jian
2007-01-01
This paper described a nonlinear model predictive controller for regulating a molten carbonate fuel cell (MCFC). A detailed mechanism model of output voltage of a MCFC was presented at first. However, this model was too complicated to be used in a control system. Consequently, an off line radial basis function (RBF) network was introduced to build a nonlinear predictive model. And then, the optimal control sequences were obtained by applying golden mean method. The models and controller have been realized in the MATLAB environment. Simulation results indicate the proposed algorithm exhibits satisfying control effect even when the current densities vary largely.
Asymptotically minimax Bayesian predictive densities for multinomial models
Komaki, Fumiyasu
2011-01-01
One-step ahead prediction for the multinomial model is considered. The performance of a predictive density is evaluated by the average Kullback-Leibler divergence from the true density to the predictive density. Asymptotic approximations of risk functions of Bayesian predictive densities based on Dirichlet priors are obtained. It is shown that a Bayesian predictive density based on a specific Dirichlet prior is asymptotically minimax. The asymptotically minimax prior is different from known objective priors such as the Jeffreys prior or the uniform prior.
LHC diphoton Higgs signal predicted by little Higgs models
International Nuclear Information System (INIS)
Little Higgs theory naturally predicts a light Higgs boson whose most important discovery channel at the LHC is the diphoton signal pp→h→γγ. In this work, we perform a comparative study for this signal in some typical little Higgs models, namely, the littlest Higgs model, two littlest Higgs models with T-parity (named LHT-I and LHT-II), and the simplest little Higgs models. We find that compared with the standard model prediction, the diphoton signal rate is always suppressed and the suppression extent can be quite different for different models. The suppression is mild (< or approx. 10%) in the littlest Higgs model but can be quite severe (≅90%) in other three models. This means that discovering the light Higgs boson predicted by the little Higgs theory through the diphoton channel at the LHC will be more difficult than discovering the standard model Higgs boson.
The predictive accuracy of intertemporal-choice models.
Arfer, Kodi B; Luhmann, Christian C
2015-05-01
How do people choose between a smaller reward available sooner and a larger reward available later? Past research has evaluated models of intertemporal choice by measuring goodness of fit or identifying which decision-making anomalies they can accommodate. An alternative criterion for model quality, which is partly antithetical to these standard criteria, is predictive accuracy. We used cross-validation to examine how well 10 models of intertemporal choice could predict behaviour in a 100-trial binary-decision task. Many models achieved the apparent ceiling of 85% accuracy, even with smaller training sets. When noise was added to the training set, however, a simple logistic-regression model we call the difference model performed particularly well. In many situations, between-model differences in predictive accuracy may be small, contrary to long-standing controversy over the modelling question in research on intertemporal choice, but the simplicity and robustness of the difference model recommend it to future use. PMID:25773127
Charge Transport in Dendrimer Melt using Multiscale Modeling Simulation
Bag, Saientan; Maiti, Prabal K
2016-01-01
In this paper we present a theoretical calculation of the charge carrier mobility in two different dendrimeric melt system (Dendritic phenyl azomethine with Triphenyl amine core and Dendritic Carbazole with Cyclic Phenylazomethine as core), which have recently been reported1 to increase the efficiency of Dye-Sensitized solar cells (DSSCs) by interface modification. Our mobility calculation, which is a combination of molecular dynamics simulation, first principles calculation and kinetic Monte Carlo simulation, leads to mobilities that are in quantitative agreement with available experimental data. We also show how the mobility depends on the dendrimer generation. Furthermore, we examine the variation of mobility with external electric field and external reorganization energy. Physical mechanisms behind observed electric field and generation dependencies of mobility are also explored.
Predictive modeling of effects under global change.
Kickert, R N; Tonella, G; Simonov, A; Krupa, S V
1999-01-01
The status of computer simulation models from around the world for evaluating the possible ecological, environmental, and societal consequences of global change is presented in this paper. In addition, a brief synopsis of the state of the science of these impacts is included. Issues considered include future changes in climate and patterns of land use for societal needs. Models discussed relate to vegetation (e.g. crop), soil, bio-geochemistry, water, and wildlife responses to conventional, forecasted changes in temperature and precipitation. Also described are models of these responses, alone and interactively, to increased CO(2), other air pollutants and UV-B radiation, as the state of the science allows. Further, models of land-use change are included. Additionally, global multiple sector models of environment, natural resources, human population dynamics, economics, energy, and political relations are reviewed for integrated impact assessment. To the extent available, information on computer software and hardware requirements is presented for the various models. The paper concludes with comments about using these technologies as they relate to ecological risk assessment for policy decision analysis. Such an effort is hampered by considerable uncertainties with the output of existing models, because of the uncertainties associated with input data and the definitions of their dose-response relationships. The concluding suggestions point the direction for new developments in modeling and analyses that are needed for the 21st century. PMID:15093114
Monte Carlo Shell Model Mass Predictions
International Nuclear Information System (INIS)
The nuclear mass calculation is discussed in terms of large-scale shell model calculations. First, the development and limitations of the conventional shell model calculations are mentioned. In order to overcome the limitations, the Quantum Monte Carlo Diagonalization (QMCD) method has been proposed. The basic formulation and features of the QMCD method are presented as well as its application to the nuclear shell model, referred to as Monte Carlo Shell Model (MCSM). The MCSM provides us with a breakthrough in shell model calculations: the structure of low-lying states can be studied with realistic interactions for a nearly unlimited variety of nuclei. Thus, the MCSM can contribute significantly to the study of nuclear masses. An application to N∼20 unstable nuclei far from the β-stability line is mentioned
Charging effect simulation model used in simulations of plasma etching of silicon
International Nuclear Information System (INIS)
Understanding the consequences of local surface charging on the evolving etching profile is a critical challenge in high density plasma etching. Deflection of the positively charged ions in locally varying electric fields can cause profile defects such as notching, bowing, and microtrenching. We have developed a numerical simulation model capturing the influence of the charging effect over the entire course of the etching process. The model is fully integrated into ViPER (Virtual Plasma Etch Reactor)—a full featured plasma processing simulation software developed at Ilmenau University of Technology. As a consequence, we show that local surface charge concurrently evolves with the feature profile to affect the final shape of the etched feature. Using gas chopping (sometimes called time-multiplexed) etch process for experimental validation of the simulation, we show that the model provides excellent fits to the experimental data and both, bowing and notching effects are captured—as long as the evolving profile and surface charge are simultaneously simulated. In addition, this new model explains that surface scallops, characteristic of gas chopping technique, are eroded and often absent in the final feature profile due to surface charging. The model is general and can be applied across many etching chemistries.
A burnout prediction model based around char morphology
Energy Technology Data Exchange (ETDEWEB)
T. Wu; E. Lester; M. Cloke [University of Nottingham, Nottingham (United Kingdom). Nottingham Energy and Fuel Centre
2005-07-01
Poor burnout in a coal-fired power plant has marked penalties in the form of reduced energy efficiency and elevated waste material that can not be utilized. The prediction of coal combustion behaviour in a furnace is of great significance in providing valuable information not only for process optimization but also for coal buyers in the international market. Coal combustion models have been developed that can make predictions about burnout behaviour and burnout potential. Most of these kinetic models require standard parameters such as volatile content, particle size and assumed char porosity in order to make a burnout prediction. This paper presents a new model called the Char Burnout Model (ChB) that also uses detailed information about char morphology in its prediction. The model can use data input from one of two sources. Both sources are derived from image analysis techniques. The first from individual analysis and characterization of real char types using an automated program. The second from predicted char types based on data collected during the automated image analysis of coal particles. Modelling results were compared with a different carbon burnout kinetic model and burnout data from re-firing the chars in a drop tube furnace operating at 1300{sup o}C, 5% oxygen across several residence times. An improved agreement between ChB model and DTF experimental data proved that the inclusion of char morphology in combustion models can improve model predictions. 27 refs., 4 figs., 4 tabs.
Benchmark analyses of prediction models for pipe wall thinning
International Nuclear Information System (INIS)
In recent years, the importance of utilizing a prediction model or code for the management of pipe wall thinning has been recognized. In Japan Society of Mechanical Engineers (JSME), a working group on prediction methods has been set up within a research committee for studying the management of pipe wall-thinning. Some prediction models for pipe wall thinning were reviewed by benchmark analyses in terms of their prediction characteristics and the specifications required for their use in the management of pipe wall thinning in power generation facilities. This paper introduces the prediction models selected from the existing flow-accelerated corrosion and/or liquid droplet impingement erosion models. The experimental results and example of the results of wall thickness measurement used as benchmark data are also mentioned. (author)
Radioiodine prediction model for nuclear tests
International Nuclear Information System (INIS)
Over a 5-year period, 14 major experiments were conducted to investigate the air-forage-cow-milk system for transfer of radioiodine. The experiments included controlled releases using prepared aerosols, planned releases during Plowshare cratering tests, and releases due to accidental venting of underground nuclear tests. Two or more groups of dairy cows, three to six cows per group, were used in each experiment to study the effect on radioiodine transfer of such factors as: the mode of exposure, the type and state of forage fed, the type of aerosol, and variations in feeding practices. In each experiment, measurements were made of the total radioiodine intake and output in milk of the cows, the concentrations in forage and milk, the gaseous and particulate air concentrations, the open-field gamma exposure rate, and the deposition per unit area. The mean values of the experimental data are assembled in this report and are used to develop the parameters for a standard milk excretion pattern for dairy cows and to develop predictive equations for radioiodine. The resultant equations, for predicting the infinite dose to a 2-gram human thyroid caused by ingestion of 131I, are presented
Arbitrary Order Charge Approximation Event Driven Phase Lock Loop Model
Daniels, Brian; Farrell, Ronan; Baldwin, Gerard
2004-01-01
An alternative technique for the derivation of an event driven phase lock loop (PLL) model is presented enabling the modelling of higher order PLLs. Event driven models have previously been developed for 2nd, and 3rd order PLLs [1,2,3], however for higher order systems (5th, 6th etc.) the derivation of the loop filter difference equations are not amenable. This paper introduces a technique to model PLLs with arbitrary order filters that removes the restriction on the loop...
Galatà, A.; Mascali, D.; Neri, L.; Torrisi, G.; Celona, L.
2016-02-01
A Charge Breeder (CB) is a crucial device of an ISOL facility, allowing post-acceleration of radioactive ions: it accepts an incoming 1+ beam, then multiplying its charge with a highly charged q+ beam as an output. The overall performances of the facility (intensity and attainable final energy) critically depend on the charge breeder optimization. Experimental results collected along the years confirm that the breeding process is still not fully understood and room for improvements still exists: a new numerical approach has been therefore developed and applied to the description of a 85Rb1+ beam capture by the plasma of the 14.5 GHz PHOENIX ECR-based CB, installed at the Laboratoire de Physique Subatomique et de Cosmologie (LPSC), and adopted for the Selective Production of Exotic Species project under construction at Laboratori Nazionali di Legnaro. The results of the numerical simulations, obtained implementing a plasma-target model of increasing accuracy and different values for the plasma potential, will be described along the paper: results very well agree with the theoretical predictions and with the experimental results obtained on the LPSC test bench.
Energy Technology Data Exchange (ETDEWEB)
Galatà, A., E-mail: alessio.galata@lnl.infn.it [INFN–Laboratori Nazionali di Legnaro, Viale dell’Università 2, 35020 Legnaro, Padova (Italy); Mascali, D.; Neri, L.; Torrisi, G.; Celona, L. [INFN–Laboratori Nazionali del Sud, Via S. Sofia 62, 95123 Catania (Italy)
2016-02-15
A Charge Breeder (CB) is a crucial device of an ISOL facility, allowing post-acceleration of radioactive ions: it accepts an incoming 1+ beam, then multiplying its charge with a highly charged q+ beam as an output. The overall performances of the facility (intensity and attainable final energy) critically depend on the charge breeder optimization. Experimental results collected along the years confirm that the breeding process is still not fully understood and room for improvements still exists: a new numerical approach has been therefore developed and applied to the description of a {sup 85}Rb{sup 1+} beam capture by the plasma of the 14.5 GHz PHOENIX ECR-based CB, installed at the Laboratoire de Physique Subatomique et de Cosmologie (LPSC), and adopted for the Selective Production of Exotic Species project under construction at Laboratori Nazionali di Legnaro. The results of the numerical simulations, obtained implementing a plasma-target model of increasing accuracy and different values for the plasma potential, will be described along the paper: results very well agree with the theoretical predictions and with the experimental results obtained on the LPSC test bench.
Galatà, A; Mascali, D; Neri, L; Torrisi, G; Celona, L
2016-02-01
A Charge Breeder (CB) is a crucial device of an ISOL facility, allowing post-acceleration of radioactive ions: it accepts an incoming 1+ beam, then multiplying its charge with a highly charged q+ beam as an output. The overall performances of the facility (intensity and attainable final energy) critically depend on the charge breeder optimization. Experimental results collected along the years confirm that the breeding process is still not fully understood and room for improvements still exists: a new numerical approach has been therefore developed and applied to the description of a (85)Rb(1+) beam capture by the plasma of the 14.5 GHz PHOENIX ECR-based CB, installed at the Laboratoire de Physique Subatomique et de Cosmologie (LPSC), and adopted for the Selective Production of Exotic Species project under construction at Laboratori Nazionali di Legnaro. The results of the numerical simulations, obtained implementing a plasma-target model of increasing accuracy and different values for the plasma potential, will be described along the paper: results very well agree with the theoretical predictions and with the experimental results obtained on the LPSC test bench. PMID:26932060
Benkert, Pascal
2007-01-01
Knowledge of the three-dimensional structure of proteins is of vital importance for understanding their function and for the rational development of new drugs. Homology modelling is currently the most successful method for the prediction of the structure of a protein from its sequence. A structural model is thereby built by incorporating information from experimentally solved proteins showing an evolutionary relationship to the target protein. The accurate prediction of loop regions which fre...
International Nuclear Information System (INIS)
20 years ago fractional charges were imagined to explain values of conductivity in some materials. Recent experiments have proved the existence of charges whose value is the third of the electron charge. This article presents the experimental facts that have led theorists to predict the existence of fractional charges from the motion of quasi-particles in a linear chain of poly-acetylene to the quantum Hall effect. According to the latest theories, fractional charges are neither bosons nor fermions but anyons, they are submitted to an exclusive principle that is less stringent than that for fermions. (A.C.)
A new auto-coherent bias dependent charge model for MESFETs and HEMTs
Valkov, S.; Derzkii, D.; Temcamani, F.; Pouvil, P.
1996-01-01
A nonlinear model of MESFETs and HEMTs capacitances suitable for implementation in commercial circuit design software is presented. The model is based upon the determination of the nonlinear bias dependent charge equations. A comparison is made between capacitance values coming from PHEMT characterization and capacitance values derived from the model.
Physical model for the prediction of pavement polishing
Do, Minh Tan; Kane, Malal; TANG, Zhen Zhong; De Larrard, François
2009-01-01
Works are presented on the development of a model predicting road skid-resistance variations. Influential phenomena are incorporated (aggregate polishing, binder removal and binder ageing due to climate) and represented by simple mathematical functions. Model parameters are obtained by fitting to data provided by laboratory tests. Experimental roads have been tracked for 4 years and data regurlarly collected from extracted cores are used to validate the model. Predictions are satisfactory and...
Model Based Predictive Control of a Fully Parallel Robot
Vivas, Oscar Andrès; Poignet, Philippe
2003-01-01
This paper deals with an efficient application of a model based predictive control in parallel machines. A receding horizon control strategy based on a simplified dynamic model is implemented. Experimental results are shown for the H4 robot, a fully parallel structure providing 3 degrees of freedom (dof) in translation and 1 dof in rotation. The model based predictive control and the commonly used computed torque control strategies are compared. The tracking performances and the robustness wi...
Models of Affective Decision Making: How Do Feelings Predict Choice?
Charpentier, C. J.; De Neve, J. E.; Li, X; Roiser, J. P.; Sharot, T.
2016-01-01
Intuitively, how you feel about potential outcomes will determine your decisions. Indeed, an implicit assumption in one of the most influential theories in psychology, prospect theory, is that feelings govern choice. Surprisingly, however, very little is known about the rules by which feelings are transformed into decisions. Here, we specified a computational model that used feelings to predict choices. We found that this model predicted choice better than existing value-based models, showing...
Predictive Modelling of Contagious Deforestation in the Brazilian Amazon
Rosa, Isabel M. D.; Drew Purves; Carlos Souza; Ewers, Robert M.
2013-01-01
Tropical forests are diminishing in extent due primarily to the rapid expansion of agriculture, but the future magnitude and geographical distribution of future tropical deforestation is uncertain. Here, we introduce a dynamic and spatially-explicit model of deforestation that predicts the potential magnitude and spatial pattern of Amazon deforestation. Our model differs from previous models in three ways: (1) it is probabilistic and quantifies uncertainty around predictions and parameters; (...
A THERMODYNAMIC MODEL TO PREDICT WAX FORMATION IN PETROLEUM FLUIDS
Directory of Open Access Journals (Sweden)
Coutinho J.A.P.
2001-01-01
Full Text Available Some years ago the authors proposed a model for the non-ideality of the solid phase, based on the Predictive Local Composition concept. This was first applied to the Wilson equation and latter extended to NRTL and UNIQUAC models. Predictive UNIQUAC proved to be extraordinarily successful in predicting the behaviour of both model and real hydrocarbon fluids at low temperatures. This work illustrates the ability of Predictive UNIQUAC in the description of the low temperature behaviour of petroleum fluids. It will be shown that using Predictive UNIQUAC in the description of the solid phase non-ideality a complete prediction of the low temperature behaviour of synthetic paraffin solutions, fuels and crude oils is achieved. The composition of both liquid and solid phases, the amount of crystals formed and the cloud points are predicted within the accuracy of the experimental data. The extension of Predictive UNIQUAC to high pressures, by coupling it with an EOS/G E model based on the SRK EOS used with the LCVM mixing rule, is proposed and predictions of phase envelopes for live oils are compared with experimental data.
Currents, charges, and canonical structure of pseudodual chiral models
International Nuclear Information System (INIS)
We discuss the pseudodual chiral model to illustrate a class of two-dimensional theories which have an infinite number of conservation laws but allow particle production, at variance with naive expectations. We describe the symmetries of the pseudodual model, both local and nonlocal, as transmutations of the symmetries of the usual chiral model. We refine the conventional algorithm to more efficiently produce the nonlocal symmetries of the model, and we discuss the complete local current algebra for the pseudodual theory. We also exhibit the canonical transformation which connects the usual chiral model to its fully equivalent dual, further distinguishing the pseudodual theory
Monotone models for prediction in data mining
Velikova, M.V.
2006-01-01
This dissertation studies the incorporation of monotonicity constraints as a type of domain knowledge into a data mining process. Monotonicity constraints are enforced at two stages¿data preparation and data modeling. The main contributions of the research are a novel procedure to test the degree of monotonicity of a real data set, a greedy algorithm to transform non-monotone into monotone data, and extended and novel approaches for building monotone decision models. The results from simulati...
Aggregate driver model to enable predictable behaviour
Chowdhury, A.; Chakravarty, T.; Banerjee, T.; Balamuralidhar, P.
2015-09-01
The categorization of driving styles, particularly in terms of aggressiveness and skill is an emerging area of interest under the broader theme of intelligent transportation. There are two possible discriminatory techniques that can be applied for such categorization; a microscale (event based) model and a macro-scale (aggregate) model. It is believed that an aggregate model will reveal many interesting aspects of human-machine interaction; for example, we may be able to understand the propensities of individuals to carry out a given task over longer periods of time. A useful driver model may include the adaptive capability of the human driver, aggregated as the individual propensity to control speed/acceleration. Towards that objective, we carried out experiments by deploying smartphone based application to be used for data collection by a group of drivers. Data is primarily being collected from GPS measurements including position & speed on a second-by-second basis, for a number of trips over a two months period. Analysing the data set, aggregate models for individual drivers were created and their natural aggressiveness were deduced. In this paper, we present the initial results for 12 drivers. It is shown that the higher order moments of the acceleration profile is an important parameter and identifier of journey quality. It is also observed that the Kurtosis of the acceleration profiles stores major information about the driving styles. Such an observation leads to two different ranking systems based on acceleration data. Such driving behaviour models can be integrated with vehicle and road model and used to generate behavioural model for real traffic scenario.
Validating predictions from climate envelope models.
Watling, James I; Bucklin, David N; Speroterra, Carolina; Brandt, Laura A; Mazzotti, Frank J; Romañach, Stephanie S
2013-01-01
Climate envelope models are a potentially important conservation tool, but their ability to accurately forecast species' distributional shifts using independent survey data has not been fully evaluated. We created climate envelope models for 12 species of North American breeding birds previously shown to have experienced poleward range shifts. For each species, we evaluated three different approaches to climate envelope modeling that differed in the way they treated climate-induced range expansion and contraction, using random forests and maximum entropy modeling algorithms. All models were calibrated using occurrence data from 1967-1971 (t1 ) and evaluated using occurrence data from 1998-2002 (t2). Model sensitivity (the ability to correctly classify species presences) was greater using the maximum entropy algorithm than the random forest algorithm. Although sensitivity did not differ significantly among approaches, for many species, sensitivity was maximized using a hybrid approach that assumed range expansion, but not contraction, in t2. Species for which the hybrid approach resulted in the greatest improvement in sensitivity have been reported from more land cover types than species for which there was little difference in sensitivity between hybrid and dynamic approaches, suggesting that habitat generalists may be buffered somewhat against climate-induced range contractions. Specificity (the ability to correctly classify species absences) was maximized using the random forest algorithm and was lowest using the hybrid approach. Overall, our results suggest cautious optimism for the use of climate envelope models to forecast range shifts, but also underscore the importance of considering non-climate drivers of species range limits. The use of alternative climate envelope models that make different assumptions about range expansion and contraction is a new and potentially useful way to help inform our understanding of climate change effects on species. PMID
Electrical charging effects on the sliding friction of a model nano-confined ionic liquid
International Nuclear Information System (INIS)
Recent measurements suggest the possibility to exploit ionic liquids (ILs) as smart lubricants for nano-contacts, tuning their tribological and rheological properties by charging the sliding interfaces. Following our earlier theoretical study of charging effects on nanoscale confinement and squeezout of a model IL, we present here molecular dynamics simulations of the frictional and lubrication properties of that model under charging conditions. First, we describe the case when two equally charged plates slide while being held together to a confinement distance of a few molecular layers. The shear sliding stress is found to rise strongly and discontinuously as the number of IL layers decreases stepwise. However, the shear stress shows, within each given number of layers, only a weak dependence upon the precise value of the normal load, a result in agreement with data extracted from recent experiments. We subsequently describe the case of opposite charging of the sliding plates and follow the shear stress when the charging is slowly and adiabatically reversed in the course of time, under fixed load. Despite the fixed load, the number and structure of the confined IL layers change with changing charge, and that in turn drives strong friction variations. The latter involves first of all charging-induced freezing of the IL film, followed by a discharging-induced melting, both made possible by the nanoscale confinement. Another mechanism for charging-induced frictional changes is a shift of the plane of maximum shear from mid-film to the plate-film interface, and vice versa. While these occurrences and results invariably depend upon the parameters of the model IL and upon its specific interaction with the plates, the present study helps identifying a variety of possible behavior, obtained under very simple assumptions, while connecting it to an underlying equilibrium thermodynamics picture
Electrical charging effects on the sliding friction of a model nano-confined ionic liquid
Energy Technology Data Exchange (ETDEWEB)
Capozza, R.; Vanossi, A. [International School for Advanced Studies (SISSA), Via Bonomea 265, 34136 Trieste (Italy); CNR-IOM Democritos National Simulation Center, Via Bonomea 265, 34136 Trieste (Italy); Benassi, A. [CNR-IOM Democritos National Simulation Center, Via Bonomea 265, 34136 Trieste (Italy); Institute for Materials Science and Max Bergmann Center of Biomaterials, TU Dresden, 01062 Dresden (Germany); Tosatti, E. [International School for Advanced Studies (SISSA), Via Bonomea 265, 34136 Trieste (Italy); CNR-IOM Democritos National Simulation Center, Via Bonomea 265, 34136 Trieste (Italy); International Centre for Theoretical Physics (ICTP), Strada Costiera 11, 34014 Trieste (Italy)
2015-10-14
Recent measurements suggest the possibility to exploit ionic liquids (ILs) as smart lubricants for nano-contacts, tuning their tribological and rheological properties by charging the sliding interfaces. Following our earlier theoretical study of charging effects on nanoscale confinement and squeezout of a model IL, we present here molecular dynamics simulations of the frictional and lubrication properties of that model under charging conditions. First, we describe the case when two equally charged plates slide while being held together to a confinement distance of a few molecular layers. The shear sliding stress is found to rise strongly and discontinuously as the number of IL layers decreases stepwise. However, the shear stress shows, within each given number of layers, only a weak dependence upon the precise value of the normal load, a result in agreement with data extracted from recent experiments. We subsequently describe the case of opposite charging of the sliding plates and follow the shear stress when the charging is slowly and adiabatically reversed in the course of time, under fixed load. Despite the fixed load, the number and structure of the confined IL layers change with changing charge, and that in turn drives strong friction variations. The latter involves first of all charging-induced freezing of the IL film, followed by a discharging-induced melting, both made possible by the nanoscale confinement. Another mechanism for charging-induced frictional changes is a shift of the plane of maximum shear from mid-film to the plate-film interface, and vice versa. While these occurrences and results invariably depend upon the parameters of the model IL and upon its specific interaction with the plates, the present study helps identifying a variety of possible behavior, obtained under very simple assumptions, while connecting it to an underlying equilibrium thermodynamics picture.
New charge exchange model of GEANT4 for 9Be(p,n)9B reaction
International Nuclear Information System (INIS)
A new data-based charge exchange model of GEANT4 dedicated to the 9Be(p,n)9B reaction is developed by taking the ENDF/B-VII.1 differential cross-section data as input. Our model yields results that are in good agreement with the experimental neutron yield spectrum data obtained for proton beams of energy (20–35) MeV. In particular, in contrast to all the considered GEANT4 hadronic models, the peak structure resulting from the discrete neutrons generated by the charge-exchange reaction is observed to be accurately reproduced in our model
Ab initio charge-carrier mobility model for amorphous molecular semiconductors
Massé, Andrea; Friederich, Pascal; Symalla, Franz; Liu, Feilong; Nitsche, Robert; Coehoorn, Reinder; Wenzel, Wolfgang; Bobbert, Peter A.
2016-05-01
Accurate charge-carrier mobility models of amorphous organic molecular semiconductors are essential to describe the electrical properties of devices based on these materials. The disordered nature of these semiconductors leads to percolative charge transport with a large characteristic length scale, posing a challenge to the development of such models from ab initio simulations. Here, we develop an ab initio mobility model using a four-step procedure. First, the amorphous morphology together with its energy disorder and intermolecular charge-transfer integrals are obtained from ab initio simulations in a small box. Next, the ab initio information is used to set up a stochastic model for the morphology and transfer integrals. This stochastic model is then employed to generate a large simulation box with modeled morphology and transfer integrals, which can fully capture the percolative charge transport. Finally, the charge-carrier mobility in this simulation box is calculated by solving a master equation, yielding a mobility function depending on temperature, carrier concentration, and electric field. We demonstrate the procedure for hole transport in two important molecular semiconductors, α -NPD and TCTA. In contrast to a previous study, we conclude that spatial correlations in the energy disorder are unimportant for α -NPD. We apply our mobility model to two types of hole-only α -NPD devices and find that the experimental temperature-dependent current density-voltage characteristics of all devices can be well described by only slightly decreasing the simulated energy disorder strength.
Evaluation of wave runup predictions from numerical and parametric models
Stockdon, Hilary F.; Thompson, David M.; Plant, Nathaniel G.; Long, Joseph W.
2014-01-01
Wave runup during storms is a primary driver of coastal evolution, including shoreline and dune erosion and barrier island overwash. Runup and its components, setup and swash, can be predicted from a parameterized model that was developed by comparing runup observations to offshore wave height, wave period, and local beach slope. Because observations during extreme storms are often unavailable, a numerical model is used to simulate the storm-driven runup to compare to the parameterized model and then develop an approach to improve the accuracy of the parameterization. Numerically simulated and parameterized runup were compared to observations to evaluate model accuracies. The analysis demonstrated that setup was accurately predicted by both the parameterized model and numerical simulations. Infragravity swash heights were most accurately predicted by the parameterized model. The numerical model suffered from bias and gain errors that depended on whether a one-dimensional or two-dimensional spatial domain was used. Nonetheless, all of the predictions were significantly correlated to the observations, implying that the systematic errors can be corrected. The numerical simulations did not resolve the incident-band swash motions, as expected, and the parameterized model performed best at predicting incident-band swash heights. An assimilated prediction using a weighted average of the parameterized model and the numerical simulations resulted in a reduction in prediction error variance. Finally, the numerical simulations were extended to include storm conditions that have not been previously observed. These results indicated that the parameterized predictions of setup may need modification for extreme conditions; numerical simulations can be used to extend the validity of the parameterized predictions of infragravity swash; and numerical simulations systematically underpredict incident swash, which is relatively unimportant under extreme conditions.
International Nuclear Information System (INIS)
This work will show how the kinetic Monte Carlo (KMC) technique is able to successfully model the defects and diffusion of dopants in Si-based materials for advanced microelectronic devices, especially for non-equilibrium conditions. Charge states of point defects and paired dopants are also simulated, including the dependency of the diffusivities on the Fermi level and charged particle drift coming from the electric field. The KMC method is used to simulate the diffusion of the point defects, and formation and dissolution of extended defects, whereas a quasi-atomistic approach is used to take into account the carrier densities. The simulated mechanisms include the kick-out diffusion mechanism, extended defect formation and the activation/deactivation of dopants through the formation of impurity clusters. Damage accumulation and amorphization are also taken into account. Solid phase epitaxy regrowth is included, and also the dopants redistribution during recrystallization of the amorphized regions. Regarding the charged defects, the model considers the dependencies of charge reactions, electric bias, pairing and break-up reactions according to the local Fermi level. Some aspects of the basic physical mechanisms have also been taken into consideration: how to smooth out the atomistic dopant point charge distribution, avoiding very abrupt and unphysical charge profiles and how to implement the drift of charged particles into the existing electric field. The work will also discuss the efficiency, accuracy and relevance of the method, together with its implementation in a technology computer aided design process simulator
Mondal, Anirban; Balasubramanian, Sundaram
2014-03-27
Quantitative prediction of physical properties of room temperature ionic liquids through nonpolarizable force field based molecular dynamics simulations is a challenging task. The challenge lies in the fact that mean ion charges in the condensed phase can be less than unity due to polarization and charge transfer effects whose magnitude cannot be fully captured through quantum chemical calculations conducted in the gas phase. The present work employed the density-derived electrostatic and chemical (DDEC/c3) charge partitioning method to calculate site charges of ions using electronic charge densities obtained from periodic density functional theory (DFT) calculations of their crystalline phases. The total ion charges obtained thus range between -0.6e for chloride and -0.8e for the PF6 ion. The mean value of the ion charges obtained from DFT calculations of an ionic liquid closely matches that obtained from the corresponding crystal thus confirming the suitability of using crystal site charges in simulations of liquids. These partial charges were deployed within the well-established force field developed by Lopes et al., and consequently, parameters of its nonbonded and torsional interactions were refined to ensure that they reproduced quantum potential energy scans for ion pairs in the gas phase. The refined force field was employed in simulations of seven ionic liquids with six different anions. Nearly quantitative agreement with experimental measurements was obtained for the density, surface tension, enthalpy of vaporization, and ion diffusion coefficients. PMID:24605817
Aerodynamic Noise Prediction Using stochastic Turbulence Modeling
Directory of Open Access Journals (Sweden)
Arash Ahmadzadegan
2008-01-01
Full Text Available Amongst many approaches to determine the sound propagated from turbulent flows, hybrid methods, in which the turbulent noise source field is computed or modeled separately from the far field calculation, are frequently used. For basic estimation of sound propagation, less computationally intensive methods can be developed using stochastic models of the turbulent fluctuations (turbulent noise source field. A simple and easy to use stochastic model for generating turbulent velocity fluctuations called continuous filter white noise (CFWN model was used. This method based on the use of classical Langevian-equation to model the details of fluctuating field superimposed on averaged computed quantities. The resulting sound field due to the generated unsteady flow field was evaluated using Lighthill's acoustic analogy. Volume integral method used for evaluating the acoustic analogy. This formulation presents an advantage, as it confers the possibility to determine separately the contribution of the different integral terms and also integration regions to the radiated acoustic pressure. Our results validated by comparing the directivity and the overall sound pressure level (OSPL magnitudes with the available experimental results. Numerical results showed reasonable agreement with the experiments, both in maximum directivity and magnitude of the OSPL. This method presents a very suitable tool for the noise calculation of different engineering problems in early stages of the design process where rough estimates using cheaper methods are needed for different geometries.
Performance Predictable ServiceBSP Model for Grid Computing
Institute of Scientific and Technical Information of China (English)
TONG Weiqin; MIAO Weikai
2007-01-01
This paper proposes a performance prediction model for grid computing model ServiceBSP to support developing high quality applications in grid environment. In ServiceBSP model,the agents carrying computing tasks are dispatched to the local domain of the selected computation services. By using the IP (integer program) approach, the Service Selection Agent selects the computation services with global optimized QoS (quality of service) consideration. The performance of a ServiceBSP application can be predicted according to the performance prediction model based on the QoS of the selected services. The performance prediction model can help users to analyze their applications and improve them by optimized the factors which affects the performance. The experiment shows that the Service Selection Agent can provide ServiceBSP users with satisfied QoS of applications.
Multikernel linear mixed models for complex phenotype prediction.
Weissbrod, Omer; Geiger, Dan; Rosset, Saharon
2016-07-01
Linear mixed models (LMMs) and their extensions have recently become the method of choice in phenotype prediction for complex traits. However, LMM use to date has typically been limited by assuming simple genetic architectures. Here, we present multikernel linear mixed model (MKLMM), a predictive modeling framework that extends the standard LMM using multiple-kernel machine learning approaches. MKLMM can model genetic interactions and is particularly suitable for modeling complex local interactions between nearby variants. We additionally present MKLMM-Adapt, which automatically infers interaction types across multiple genomic regions. In an analysis of eight case-control data sets from the Wellcome Trust Case Control Consortium and more than a hundred mouse phenotypes, MKLMM-Adapt consistently outperforms competing methods in phenotype prediction. MKLMM is as computationally efficient as standard LMMs and does not require storage of genotypes, thus achieving state-of-the-art predictive power without compromising computational feasibility or genomic privacy. PMID:27302636
Evaluation of battery models for prediction of electric vehicle range
Frank, H. A.; Phillips, A. M.
1977-01-01
Three analytical models for predicting electric vehicle battery output and the corresponding electric vehicle range for various driving cycles were evaluated. The models were used to predict output and range, and then compared with experimentally determined values determined by laboratory tests on batteries using discharge cycles identical to those encountered by an actual electric vehicle while on SAE cycles. Results indicate that the modified Hoxie model gave the best predictions with an accuracy of about 97 to 98% in the best cases and 86% in the worst case. A computer program was written to perform the lengthy iterative calculations required. The program and hardware used to automatically discharge the battery are described.
Sugioka, Hideyuki
2015-10-01
Transient space charge phenomena at high step voltages are interesting since they play a central role in many exotic nonequilibrium phenomena of ion dynamics in an electrolyte. However, the fundamental equations [i.e., the nonsteady Poisson-Nernst-Planck (PNP) equations] have not been solved analytically at high applied voltages because of their large nonlinearity. In this study, on the basis of the steady PNP solution, we propose an electrical circuit model that considers transient space charge effects and find that the dc and ac responses of the total charge of the electrical double layer are in fairly good agreement with the numerical results even at large applied voltages. Furthermore, on the basis of this model, we find approximate analytical solutions for the nonsteady PNP equations that are in good agreement with the numerical solutions of the concentration, charge density, and potential distribution at high applied voltages at each time in a surface region.
Investigation on penetration model of shaped charge jet in water
Shi, Jinwei; Luo, Xingbai; Li, Jinming; Jiang, Jianwei
2016-01-01
To analyze the process of jet penetration in water medium quantitatively, the properties of jet penetration spaced target with water interlayer were studied through test and numerical simulation. Two theoretical models of jet penetration in water were proposed. The theoretical model 1 was established considering the impact of the shock wave, combined with the shock equation Rankine-Hugoniot and the virtual origin calculation method. The theoretical model 2 was obtained by fitting theoretical analysis and numerical simulation results. The effectiveness and universality of the two theoretical models were compared through the numerical simulation results. Both the models can reflect the relationship between the penetration velocity and the penetration distance in water well, and both the deviation and stability of theoretical model 1 are better than 2, the lower penetration velocity, and the larger deviation of the theoretical model 2. Therefore, the theoretical model 1 can reflect the properties of jet penetration in water effectively, and provide the reference of model simulation and theoretical research.
Numerical Modeling and Prediction of Bubbling Fluidized Beds
England, Jonas Andrew
2011-01-01
Numerical modeling and prediction techniques are used to determine pressure drop, minimum fluidization velocity and segregation for bubbling fluidized beds. The computational fluid dynamics (CFD) code Multiphase Flow with Interphase eXchange (MFIX) is used to study a two-stage reactor geometry with a binary mixture. MFIX is demonstrated to accurately predict pressure drop versus inlet gas velocity for binary mixtures. A new method is developed to predict the pressure drop versus inlet gas v...
The impact of business groups on bankruptcy prediction modeling
Dewaelheyns, Nico; Van Hulle, Cynthia
2004-01-01
The bankruptcy prediction literature generally ignores corporate ownership and assumes companies are independent economic entities. In Continental Europe this latter assumption does not hold, due to the importance of business groups. Using a sample of mostly non-quoted Belgian medium and large sized companies, we show that the predictive power of several accounting ratios that are commonly used in bankruptcy prediction models (e.g. performance, leverage, liquidity and efficiency) is different...
Systems models for predicting radioactive waste
International Nuclear Information System (INIS)
This paper illustrates how a model can be constructed to analyze the growth of accumulated spent Light-Water-Reactor fuel using a technique from systems theory which has proved to be capable of describing with a very high degree of accuracy the growth of both human populations and railways, highways, airports, local government revenues, college enrollments and similar technologies and infrastructural elements. The coupled nonlinear equations which describe these phenomena have been treated and numerical examples are displayed. The fundamental nature of the models is found to be logistic, and there is switching at the critical points between growth regimes or phases
Modeling of homogeneous charge compression ignition (HCCI) of methane
Energy Technology Data Exchange (ETDEWEB)
Smith, J.R.; Aceves, S.M.; Westbrook, C.; Pitz, W.
1997-05-01
The operation of piston engines on a compression ignition cycle using a lean, homogeneous charge has many potential attractive features. These include the potential for extremely low NO{sub x} and particulate emissions while maintaining high thermal efficiency and not requiring the expensive high pressure injection system of the typical modem diesel engine. Using the HCT chemical kinetics code to simulate autoignition of methane-air mixtures, we have explored the ignition timing, burn duration, NO{sub x} production, indicated efficiency and power output of an engine with a compression ratio of 15:1 at 1200 and 2400 rpm. HCT was modified to include the effects of heat transfer. This study used a single control volume reaction zone that varies as a function of crank angle. The ignition process is controlled by varying the intake equivalence ratio and varying the residual gas trapping (RGT). RGT is internal exhaust gas recirculation which recycles both heat and combustion product species. It is accomplished by varying the timing of the exhaust valve closure. Inlet manifold temperature was held constant at 330 Kelvins. Results show that there is a narrow range of operational conditions that show promise of achieving the control necessary to vary power output while keeping indicated efficiency above 50% and NO{sub x} levels below 100 ppm.
The application of modeling and prediction with MRA wavelet network
Institute of Scientific and Technical Information of China (English)
LU Shu-ping; YANG Xue-jing; ZHAO Xi-ren
2004-01-01
As there are lots of non-linear systems in the real engineering, it is very important to do more researches on the modeling and prediction of non-linear systems. Based on the multi-resolution analysis (MRA) of wavelet theory, this paper combined the wavelet theory with neural network and established a MRA wavelet network with the scaling function and wavelet function as its neurons. From the analysis in the frequency domain, the results indicated that MRA wavelet network was better than other wavelet networks in the ability of approaching to the signals. An essential research was carried out on modeling and prediction with MRA wavelet network in the non-linear system. Using the lengthwise sway data received from the experiment of ship model, a model of offline prediction was established and was applied to the short-time prediction of ship motion. The simulation results indicated that the forecasting model improved the prediction precision effectively, lengthened the forecasting time and had a better prediction results than that of AR linear model.The research indicates that it is feasible to use the MRA wavelet network in the short -time prediction of ship motion.
A Predictive Model of High Shear Thrombus Growth.
Mehrabadi, Marmar; Casa, Lauren D C; Aidun, Cyrus K; Ku, David N
2016-08-01
The ability to predict the timescale of thrombotic occlusion in stenotic vessels may improve patient risk assessment for thrombotic events. In blood contacting devices, thrombosis predictions can lead to improved designs to minimize thrombotic risks. We have developed and validated a model of high shear thrombosis based on empirical correlations between thrombus growth and shear rate. A mathematical model was developed to predict the growth of thrombus based on the hemodynamic shear rate. The model predicts thrombus deposition based on initial geometric and fluid mechanic conditions, which are updated throughout the simulation to reflect the changing lumen dimensions. The model was validated by comparing predictions against actual thrombus growth in six separate in vitro experiments: stenotic glass capillary tubes (diameter = 345 µm) at three shear rates, the PFA-100(®) system, two microfluidic channel dimensions (heights = 300 and 82 µm), and a stenotic aortic graft (diameter = 5.5 mm). Comparison of the predicted occlusion times to experimental results shows excellent agreement. The model is also applied to a clinical angiography image to illustrate the time course of thrombosis in a stenotic carotid artery after plaque cap rupture. Our model can accurately predict thrombotic occlusion time over a wide range of hemodynamic conditions. PMID:26795978
Prediction of mortality in very premature infants: a systematic review of prediction models.
Directory of Open Access Journals (Sweden)
Stephanie Medlock
Full Text Available CONTEXT: Being born very preterm is associated with elevated risk for neonatal mortality. The aim of this review is to give an overview of prediction models for mortality in very premature infants, assess their quality, identify important predictor variables, and provide recommendations for development of future models. METHODS: Studies were included which reported the predictive performance of a model for mortality in a very preterm or very low birth weight population, and classified as development, validation, or impact studies. For each development study, we recorded the population, variables, aim, predictive performance of the model, and the number of times each model had been validated. Reporting quality criteria and minimum methodological criteria were established and assessed for development studies. RESULTS: We identified 41 development studies and 18 validation studies. In addition to gestational age and birth weight, eight variables frequently predicted survival: being of average size for gestational age, female gender, non-white ethnicity, absence of serious congenital malformations, use of antenatal steroids, higher 5-minute Apgar score, normal temperature on admission, and better respiratory status. Twelve studies met our methodological criteria, three of which have been externally validated. Low reporting scores were seen in reporting of performance measures, internal and external validation, and handling of missing data. CONCLUSIONS: Multivariate models can predict mortality better than birth weight or gestational age alone in very preterm infants. There are validated prediction models for classification and case-mix adjustment. Additional research is needed in validation and impact studies of existing models, and in prediction of mortality in the clinically important subgroup of infants where age and weight alone give only an equivocal prognosis.
Monotone models for prediction in data mining
Velikova, M.V.
2006-01-01
This dissertation studies the incorporation of monotonicity constraints as a type of domain knowledge into a data mining process. Monotonicity constraints are enforced at two stages¿data preparation and data modeling. The main contributions of the research are a novel procedure to test the degree of
Prediction model for spring dust weather frequency in North China
Institute of Scientific and Technical Information of China (English)
2008-01-01
It is of great social and scientific importance and also very difficult to make reliable prediction for dust weather frequency (DWF) in North China. In this paper, the correlation between spring DWF in Beijing and Tianjin observation stations, taken as examples in North China, and seasonally averaged surface air temperature, precipitation, Arctic Oscillation, Antarctic Oscillation, South Oscillation, near surface meridional wind and Eurasian westerly index is respectively calculated so as to construct a prediction model for spring DWF in North China by using these climatic factors. Two prediction models, i.e. model-I and model-II, are then set up respectively based on observed climate data and the 32-year (1970 -2001) extra-seasonal hindcast experiment data as reproduced by the nine-level Atmospheric General Circulation Model developed at the Institute of Atmospheric Physics (IAP9L-AGCM). It is indicated that the correlation coefficient between the observed and predicted DWF reaches 0.933 in the model-I, suggesting a high prediction skill one season ahead. The corresponding value is high up to 0.948 for the subsequent model-II, which involves synchronous spring climate data reproduced by the IAP9L-AGCM relative to the model-I. The model-II can not only make more precise prediction but also can bring forward the lead time of real-time prediction from the model-I’s one season to half year. At last, the real-time predictability of the two models is evaluated. It follows that both the models display high prediction skill for both the interannual variation and linear trend of spring DWF in North China, and each is also featured by different advantages. As for the model-II, the prediction skill is much higher than that of original approach by use of the IAP9L-AGCM alone. Therefore, the prediction idea put forward here should be popularized in other regions in China where dust weather occurs frequently.
Prediction model for spring dust weather frequency in North China
Institute of Scientific and Technical Information of China (English)
LANG XianMei
2008-01-01
It is of great social and scientific importance and also very difficult to make reliable prediction for dust weather frequency (DWF) in North China. In this paper, the correlation between spring DWF in Beijing and Tianjin observation stations, taken as examples in North China, and seasonally averaged surface air temperature, precipitation, Arctic Oscillation, Antarctic Oscillation, South Oscillation, near surface meridional wind and Eurasian westerly index is respectively calculated so as to construct a prediction model for spring DWF in North China by using these climatic factors. Two prediction models, I.e. Model-Ⅰ and model-Ⅱ, are then set up respectively based on observed climate data and the 32-year (1970--2001) extra-seasonal hindcast experiment data as reproduced by the nine-level Atmospheric General Circulation Model developed at the Institute of Atmospheric Physics (IAP9L-AGCM). It is indicated that the correlation coefficient between the observed and predicted DWF reaches 0.933 in the model-Ⅰ, suggesting a high prediction skill one season ahead. The corresponding value is high up to 0.948 for the subsequent model-Ⅱ, which involves synchronous spring climate data reproduced by the IAP9L-AGCM relative to the model-Ⅰ. The model-Ⅱ can not only make more precise prediction but also can bring forward the lead time of real-time prediction from the model-Ⅰ's one season to half year. At last, the real-time predictability of the two models is evaluated. It follows that both the models display high prediction skill for both the interannual variation and linear trend of spring DWF in North China, and each is also featured by different advantages. As for the model-Ⅱ, the prediction skill is much higher than that of original approach by use of the IAP9L-AGCM alone. Therefore, the prediction idea put forward here should be popularized in other regions in China where dust weather occurs frequently.
Solar wind charge exchange X-ray emission from Mars Model and data comparison
Koutroumpa, Dimitra; Modolo, Ronan; Chanteur, Gerard; Chaufray, Jean-Yves; Kharchenko, Vasili; Lallement, Rosine
2012-01-01
Aims. We study the soft X-ray emission induced by charge exchange (CX) collisions between solar-wind, highly charged ions and neutral atoms of the Martian exosphere. Methods. A 3D multi species hybrid simulation model with improved spatial resolution (130 km) is used to describe the interaction between the solar wind and the Martian neutrals. We calculated velocity and density distributions of the solar wind plasma in the Martian environment with realistic planetary ions description, using sp...
Phenomenological lattice model for dynamic spin and charge fluctuations in the cuprates
Vojta, Matthias; Sachdev, Subir
2004-01-01
Motivated by recent neutron scattering experiments on the cuprate superconductors, we present a phenomenological framework describing the dynamics of collective spin excitations coupled to charge/bond order fluctuations. Our quantum lattice model contains two order parameter fields, and can capture spin excitations both in broken-symmetry states with static lattice modulations, as well as in homogeneous states where the charge/bond order is fluctuating. We present results for different types ...
Tzul, Franco O.; Schweiker, Katrina L.; Makhatadze, George I.
2015-01-01
Quantitative understanding of how individual interactions contribute to the kinetics and thermodynamics of protein folding is critical for deciphering the underlying molecular mechanisms that define the energy folding landscape. We applied a structure-based model that explicitly accounts for the interactions between charges, to folding–unfolding of four different protein pairs: rationally stabilized, via optimization of surface charge–charge interactions, variants, and respective wild types. ...
A stochastic-hydrodynamic model of halo formation in charged particle beams
Petroni, Nicola Cufaro; De Martino, Salvatore; De Siena, Silvio; Illuminati, Fabrizio
2003-01-01
The formation of the beam halo in charged particle accelerators is studied in the framework of a stochastic-hydrodynamic model for the collective motion of the particle beam. In such a stochastic-hydrodynamic theory the density and the phase of the charged beam obey a set of coupled nonlinear hydrodynamic equations with explicit time-reversal invariance. This leads to a linearized theory that describes the collective dynamics of the beam in terms of a classical Schr\\"odinger equation. Taking ...
Biodistribution of charged F(ab')2 photoimmunoconjugates in a xenograft model of ovarian cancer.
Duska, L. R.; Hamblin, M R; Bamberg, M. P.; Hasan, T.
1997-01-01
The effect of charge modification of photoimmunoconjugates (PICs) on their biodistribution in a xenograft model of ovarian cancer was investigated. Chlorin(e6)c(e6) was attached site specifically to the F(ab')2 fragment of the murine monoclonal antibody OC125, directed against human ovarian cancer cells, via poly-1-lysine linkers carrying cationic or anionic charges. Preservation of immunoreactivity was checked by enzyme-linked immunosorbent assay (ELISA). PICs were radiolabelled with 125I an...
Adler-type sum rule, charge symmetry and neutral current in general multi-triplet model
International Nuclear Information System (INIS)
We derive Adler-type sum rule extended to general multi-triplet model. Paying attention to roles of the colour degree of freedom, we discuss the charge symmetry property of the weak charged current and the structure functions for ν(ν-)+N→l(l-)+X, and also the structure of the neutral current. A comment is given on implications in our theory of Koike and Konuma's result on the neutral hadronic current. (auth.)
New Approaches for Channel Prediction Based on Sinusoidal Modeling
Directory of Open Access Journals (Sweden)
Ekman Torbjörn
2007-01-01
Full Text Available Long-range channel prediction is considered to be one of the most important enabling technologies to future wireless communication systems. The prediction of Rayleigh fading channels is studied in the frame of sinusoidal modeling in this paper. A stochastic sinusoidal model to represent a Rayleigh fading channel is proposed. Three different predictors based on the statistical sinusoidal model are proposed. These methods outperform the standard linear predictor (LP in Monte Carlo simulations, but underperform with real measurement data, probably due to nonstationary model parameters. To mitigate these modeling errors, a joint moving average and sinusoidal (JMAS prediction model and the associated joint least-squares (LS predictor are proposed. It combines the sinusoidal model with an LP to handle unmodeled dynamics in the signal. The joint LS predictor outperforms all the other sinusoidal LMMSE predictors in suburban environments, but still performs slightly worse than the standard LP in urban environments.
Application of Wavelet Random Coupling Model in Monthly Rainfall Prediction
Institute of Scientific and Technical Information of China (English)
DONG Lili; XU Shuqin; LIU Yang; WANG Yunhe
2011-01-01
A Trous algorithm of wavelet transform was used to decompose wavelet signal, and the cross-correlation analysis was used to analyze the sequence of each wavelet transform, and then the mathematical model correspond with wavelet transform sequence was established, finally wavelet random coupling model was obtained by wavelet reconstruction algorithm. Then, according to the rainfall data in crop growth period of Farm Chahayang from 1956 to 2008, the wavelet random coupling model was established to fit the model prediction test. The results showed that the prediction and fitting accuracy of the model was high, the model could reflect the rainfall variation regulation in the region, and it was a practical prediction model. It was very important for us to determine reasonably irrigation schedule and to use efficiency coefficient of precipitation resource.
Predicting Market Impact Costs Using Nonparametric Machine Learning Models.
Park, Saerom; Lee, Jaewook; Son, Youngdoo
2016-01-01
Market impact cost is the most significant portion of implicit transaction costs that can reduce the overall transaction cost, although it cannot be measured directly. In this paper, we employed the state-of-the-art nonparametric machine learning models: neural networks, Bayesian neural network, Gaussian process, and support vector regression, to predict market impact cost accurately and to provide the predictive model that is versatile in the number of variables. We collected a large amount of real single transaction data of US stock market from Bloomberg Terminal and generated three independent input variables. As a result, most nonparametric machine learning models outperformed a-state-of-the-art benchmark parametric model such as I-star model in four error measures. Although these models encounter certain difficulties in separating the permanent and temporary cost directly, nonparametric machine learning models can be good alternatives in reducing transaction costs by considerably improving in prediction performance. PMID:26926235
A burnout prediction model based around char morphology
Energy Technology Data Exchange (ETDEWEB)
Tao Wu; Edward Lester; Michael Cloke [University of Nottingham, Nottingham (United Kingdom). School of Chemical, Environmental and Mining Engineering
2006-05-15
Several combustion models have been developed that can make predictions about coal burnout and burnout potential. Most of these kinetic models require standard parameters such as volatile content and particle size to make a burnout prediction. This article presents a new model called the char burnout (ChB) model, which also uses detailed information about char morphology in its prediction. The input data to the model is based on information derived from two different image analysis techniques. One technique generates characterization data from real char samples, and the other predicts char types based on characterization data from image analysis of coal particles. The pyrolyzed chars in this study were created in a drop tube furnace operating at 1300{sup o}C, 200 ms, and 1% oxygen. Modeling results were compared with a different carbon burnout kinetic model as well as the actual burnout data from refiring the same chars in a drop tube furnace operating at 1300{sup o}C, 5% oxygen, and residence times of 200, 400, and 600 ms. A good agreement between ChB model and experimental data indicates that the inclusion of char morphology in combustion models could well improve model predictions. 38 refs., 5 figs., 6 tabs.
Predicting Chandra CCD Degradation with the Chandra Radiation Model
Minow, Joseph I.; Blackwell, William C.; DePasquale, Joseph M.; Grant, Catherine E.; O'Dell, Stephen L.; Plucinsky, Paul P.; Schwartz, Daniel A.; Spitzbart, Bradley D.; Wolk, Scott J.
2008-01-01
Not long after launch of the Chandra X-Ray Observatory, it was discovered that the Advanced CCD Imaging Spectrometer (ACIS) detector was rapidly degrading due to radiation. Analysis by Chandra personnel showed that this degradation was due to 10w energy protons (100 - 200 keV) that scattered down the optical path onto the focal plane. In response to this unexpected problem, the Chandra Team developed a radiation-protection program that has been used to manage the radiation damage to the CCDs. This program consists of multiple approaches - scheduled sating of the ACIS detector from the radiation environment during passage through radiation belts, real-time monitoring of space weather conditions, on-board monitoring of radiation environment levels, and the creation of a radiation environment model for use in computing proton flux and fluence at energies that damage the ACIS detector. This radiation mitigation program has been very successful. The initial precipitous increase in the CCDs' charge transfer inefficiency (CTI) resulting from proton damage has been slowed dramatically, with the front-illuminated CCDS having an increase in CTI of only 2.3% per year, allowing the ASIS detector's expected lifetime to exceed requirements. This paper concentrates on one aspect of the Chandra radiation mitigation program, the creation of the Chandra Radiation Model (CRM). Because of Chandra's highly elliptical orbit, the spacecraft spends most of its time outside of the trapped radiation belts that present the severest risks to the ACIS detector. However, there is still a proton flux environment that must be accounted for in all parts of Chandra's orbit. At the time of Chandra's launch there was no engineering model of the radiation environment that could be used in the outer regions of the spacecraft's orbit, so the CRM was developed to provide the flux environment of 100 - 200 keV protons in the outer magnetosphere, magnetosheath, and solar wind regions of geospace. This
Bayesian Age-Period-Cohort Modeling and Prediction - BAMP
Directory of Open Access Journals (Sweden)
Volker J. Schmid
2007-10-01
Full Text Available The software package BAMP provides a method of analyzing incidence or mortality data on the Lexis diagram, using a Bayesian version of an age-period-cohort model. A hierarchical model is assumed with a binomial model in the first-stage. As smoothing priors for the age, period and cohort parameters random walks of first and second order, with and without an additional unstructured component are available. Unstructured heterogeneity can also be included in the model. In order to evaluate the model fit, posterior deviance, DIC and predictive deviances are computed. By projecting the random walk prior into the future, future death rates can be predicted.
Modeling for prediction of restrained shrinkage effect in concrete repair
International Nuclear Information System (INIS)
A general model of autogenous shrinkage caused by chemical reaction (chemical shrinkage) is developed by means of Arrhenius' law and a degree of chemical reaction. Models of tensile creep and relaxation modulus are built based on a viscoelastic, three-element model. Tests of free shrinkage and tensile creep were carried out to determine some coefficients in the models. Two-dimensional FEM analysis based on the models and other constitutions can predict the development of tensile strength and cracking. Three groups of patch-repaired beams were designed for analysis and testing. The prediction from the analysis shows agreement with the test results. The cracking mechanism after repair is discussed
The Standard Model Prediction of the Muon Anomalous Magnetic Moment
Passera, M.
2004-01-01
This article reviews and updates the Standard Model prediction of the muon g-2. QED, electroweak and hadronic contributions are presented, and open questions discussed. The theoretical prediction deviates from the present experimental value by 2-3 standard deviations, if e+e- annihilation data are used to evaluate the leading hadronic term.
A Multi-Criteria Prediction model for project Risk classifications
Laryea, Rueben
2013-01-01
Project distress predictions are essential in project management. Developing appropriate methods to classify projects and building prediction models for multicriteria decisions requires empirical methods to minimise misclassification errors. This paper carries out multicriteria analysis to classify project risks using a preference disaggregation method, UTilit.
Towards Parallel Programming Models for Predictability
Lisper, Björn
2012-01-01
Future embedded systems for performance-demanding applications will be massively parallel. High performance tasks will be parallel programs, running on several cores, rather than single threads running on single cores. For hard real-time applications, WCETs for such tasks must be bounded. Low-level parallel programming models, based on concurrent threads, are notoriously hard to use due to their inherent nondeterminism. Therefore the parallel processing community has long considered high-l...
Haskell financial data modeling and predictive analytics
Ryzhov, Pavel
2013-01-01
This book is a hands-on guide that teaches readers how to use Haskell's tools and libraries to analyze data from real-world sources in an easy-to-understand manner.This book is great for developers who are new to financial data modeling using Haskell. A basic knowledge of functional programming is not required but will be useful. An interest in high frequency finance is essential.
Reliability prediction in model driven development
Rodrigues, G. N.; Rosenblum, D. S.; Uchitel, S.
2005-01-01
Evaluating the implications of an architecture design early in the software development lifecycle is important in order to reduce costs of development. Reliability is an important concern with regard to the correct delivery of software system service. Recently, the UML Profile for Modeling Quality of Service has defined a set of UML extensions to represent dependability concerns (including reliability) and other non-functional requirements in early stages of the software development lif...
Degradation prediction model for friction in highways
Santos, Adriana; Freitas, Elisabete F.; Faria, Susana; Oliveira, Joel; Ana Maria A C Rocha
2014-01-01
The purpose of this paper is to develop a multiple linear regression model that describes the pavement’s friction behaviour using a degradation evo- lution law that also considers the effects of weather, vertical alignment and traf- fic factors. This study is based on real data obtained from two different highways with an approximate total length of 43 km. These sections present different alignment features (plan/profile), different Annual Average Daily Traffic and are subject- ed to differen...
Predictive Modeling for Comfortable Death Outcome Using Electronic Health Records
Lodhi, Muhammad Kamran; Ansari, Rashid; Yao, Yingwei; Keenan, Gail M.; Wilkie, Diana J.; Khokhar, Ashfaq A.
2016-01-01
Electronic health record (EHR) systems are used in healthcare industry to observe the progress of patients. With fast growth of the data, EHR data analysis has become a big data problem. Most EHRs are sparse and multi-dimensional datasets and mining them is a challenging task due to a number of reasons. In this paper, we have used a nursing EHR system to build predictive models to determine what factors impact death anxiety, a significant problem for the dying patients. Different existing modeling techniques have been used to develop coarse-grained as well as fine-grained models to predict patient outcomes. The coarse-grained models help in predicting the outcome at the end of each hospitalization, whereas fine-grained models help in predicting the outcome at the end of each shift, therefore providing a trajectory of predicted outcomes. Based on different modeling techniques, our results show significantly accurate predictions, due to relatively noise-free data. These models can help in determining effective treatments, lowering healthcare costs, and improving the quality of end-of-life (EOL) care.
Wagenbrenner, Natalie S.; Forthofer, Jason M.; Lamb, Brian K.; Shannon, Kyle S.; Butler, Bret W.
2016-04-01
Wind predictions in complex terrain are important for a number of applications. Dynamic downscaling of numerical weather prediction (NWP) model winds with a high-resolution wind model is one way to obtain a wind forecast that accounts for local terrain effects, such as wind speed-up over ridges, flow channeling in valleys, flow separation around terrain obstacles, and flows induced by local surface heating and cooling. In this paper we investigate the ability of a mass-consistent wind model for downscaling near-surface wind predictions from four NWP models in complex terrain. Model predictions are compared with surface observations from a tall, isolated mountain. Downscaling improved near-surface wind forecasts under high-wind (near-neutral atmospheric stability) conditions. Results were mixed during upslope and downslope (non-neutral atmospheric stability) flow periods, although wind direction predictions generally improved with downscaling. This work constitutes evaluation of a diagnostic wind model at unprecedented high spatial resolution in terrain with topographical ruggedness approaching that of typical landscapes in the western US susceptible to wildland fire.
Computational models of an inductive power transfer system for electric vehicle battery charge
Anele, A. O.; Hamam, Y.; Chassagne, L.; Linares, J.; Alayli, Y.; Djouani, K.
2015-09-01
One of the issues to be solved for electric vehicles (EVs) to become a success is the technical solution of its charging system. In this paper, computational models of an inductive power transfer (IPT) system for EV battery charge are presented. Based on the fundamental principles behind IPT systems, 3 kW single phase and 22 kW three phase IPT systems for Renault ZOE are designed in MATLAB/Simulink. The results obtained based on the technical specifications of the lithium-ion battery and charger type of Renault ZOE show that the models are able to provide the total voltage required by the battery. Also, considering the charging time for each IPT model, they are capable of delivering the electricity needed to power the ZOE. In conclusion, this study shows that the designed computational IPT models may be employed as a support structure needed to effectively power any viable EV.
Three-loop Neutrino Mass Model with Doubly Charged Particles from Iso-Doublets
Okada, Hiroshi
2016-01-01
We propose a new type of a three-loop induced neutrino mass model with dark matter candidates which are required for the neutrino mass generation. The smallness of neutrino masses can be naturally explained without introducing super heavy particles, namely, much heavier than a TeV scale and quite small couplings as compared to the gauge couplings. We find that as a bonus, the anomaly of the muon anomalous magnetic moment can simultaneously be explained by loop effects of new particles. In our model, there are doubly charged scalar bosons and leptons from isospin doublet fields which give characteristic collider signatures. In particular, the doubly charged scalar bosons can decay into the same sign dilepton with its chirality of both right-handed or left- and right-handed. This can be a smoking gun signature to identify our model and be useful to distinguish other models with doubly charged scalar bosons at collider experiments.
Submission Form for Peer-Reviewed Cancer Risk Prediction Models
If you have information about a peer-reviewd cancer risk prediction model that you would like to be considered for inclusion on this list, submit as much information as possible through the form on this page.
Predictive Modeling: A New Paradigm for Managing Endometrial Cancer.
Bendifallah, Sofiane; Daraï, Emile; Ballester, Marcos
2016-03-01
With the abundance of new options in diagnostic and treatment modalities, a shift in the medical decision process for endometrial cancer (EC) has been observed. The emergence of individualized medicine and the increasing complexity of available medical data has lead to the development of several prediction models. In EC, those clinical models (algorithms, nomograms, and risk scoring systems) have been reported, especially for stratifying and subgrouping patients, with various unanswered questions regarding such things as the optimal surgical staging for lymph node metastasis as well as the assessment of recurrence and survival outcomes. In this review, we highlight existing prognostic and predictive models in EC, with a specific focus on their clinical applicability. We also discuss the methodologic aspects of the development of such predictive models and the steps that are required to integrate these tools into clinical decision making. In the future, the emerging field of molecular or biochemical markers research may substantially improve predictive and treatment approaches. PMID:26577116
Compensatory versus noncompensatory models for predicting consumer preferences
Directory of Open Access Journals (Sweden)
Anja Dieckmann
2009-04-01
Full Text Available Standard preference models in consumer research assume that people weigh and add all attributes of the available options to derive a decision, while there is growing evidence for the use of simplifying heuristics. Recently, a greedoid algorithm has been developed (Yee, Dahan, Hauser and Orlin, 2007; Kohli and Jedidi, 2007 to model lexicographic heuristics from preference data. We compare predictive accuracies of the greedoid approach and standard conjoint analysis in an online study with a rating and a ranking task. The lexicographic model derived from the greedoid algorithm was better at predicting ranking compared to rating data, but overall, it achieved lower predictive accuracy for hold-out data than the compensatory model estimated by conjoint analysis. However, a considerable minority of participants was better predicted by lexicographic strategies. We conclude that the new algorithm will not replace standard tools for analyzing preferences, but can boost the study of situational and individual differences in preferential choice processes.
Preoperative prediction model of outcome after cholecystectomy for symptomatic gallstones
DEFF Research Database (Denmark)
Borly, L; Anderson, I B; Bardram, Linda; Christensen, E; Sehested, Ane; Kehlet, H; Matzen, Peter; Rehfeld, J F; Stage, P; Toftdahl, D B; Gernow, A; Højgaard, L
1999-01-01
sonography evaluated gallbladder motility, gallstones, and gallbladder volume. Preoperative variables in patients with or without postcholecystectomy pain were compared statistically, and significant variables were combined in a logistic regression model to predict the postoperative outcome. RESULTS: Eighty...
On the Predictiveness of Single-Field Inflationary Models
Burgess, C P; Trott, Michael
2014-01-01
We re-examine the predictiveness of single-field inflationary models and discuss how an unknown UV completion can complicate determining inflationary model parameters from observations, even from precision measurements. Besides the usual naturalness issues associated with having a shallow inflationary potential, we describe another issue for inflation, namely, unknown UV physics modifies the running of Standard Model (SM) parameters and thereby introduces uncertainty into the potential inflationary predictions. We illustrate this point using the minimal Higgs Inflationary scenario, which is arguably the most predictive single-field model on the market, because its predictions for $A_s$, $r$ and $n_s$ are made using only one new free parameter beyond those measured in particle physics experiments, and run up to the inflationary regime. We find that this issue can already have observable effects. At the same time, this UV-parameter dependence in the Renormalization Group allows Higgs Inflation to occur (in prin...
A Composite Model Predictive Control Strategy for Furnaces
Institute of Scientific and Technical Information of China (English)
Hao Zang; Hongguang Li; Jingwen Huang; Jia Wang
2014-01-01
Tube furnaces are essential and primary energy intensive facilities in petrochemical plants. Operational optimi-zation of furnaces could not only help to improve product quality but also benefit to reduce energy consumption and exhaust emission. Inspired by this idea, this paper presents a composite model predictive control (CMPC) strategy, which, taking advantage of distributed model predictive control architectures, combines tracking nonlinear model predictive control and economic nonlinear model predictive control metrics to keep process running smoothly and optimize operational conditions. The control ers connected with two kinds of communi-cation networks are easy to organize and maintain, and stable to process interferences. A fast solution algorithm combining interior point solvers and Newton's method is accommodated to the CMPC realization, with reason-able CPU computing time and suitable online applications. Simulation for industrial case demonstrates that the proposed approach can ensure stable operations of furnaces, improve heat efficiency, and reduce the emission effectively.
Advances in Modeling of Scanning Charged-Particle-Microscopy Images
Cizmar, Petr; Vladar, Andras E.; Postek, Michael T.
2010-01-01
Modeling artificial scanning electron microscope (SEM) and scanning ion microscope images has recently become important. This is because of the need to provide repeatable images with a priori determined parameters. Modeled artificial images are highly useful in the evaluation of new imaging and metrological techniques, like image-sharpness calculation, or drift-corrected image composition (DCIC). Originally, the NIST-developed artificial image generator was designed only to produce the SEM im...
Scalar potential without cubic term in 3-3-1 models without exotic electric charges
Energy Technology Data Exchange (ETDEWEB)
Giraldo, Yithsbey [Universidad de Narino, Departamento de Fisica, A.A. 1175, Pasto (Colombia); Universidad de Antioquia, Instituto de Fisica, A.A. 1226, Medellin (Colombia); Ponce, William A. [Universidad de Antioquia, Instituto de Fisica, A.A. 1226, Medellin (Colombia)
2011-07-15
A detailed study of the criteria for stability of the scalar potential, and the proper electroweak symmetry breaking pattern in some 3-3-1 models without exotic electric charges is presented. In this paper we concentrate in a scalar sector with three Higgs scalar triplets, with a potential that does not include the cubic term, due to the presence of a discrete symmetry. For the analysis we use, and improve, a method previously developed to study the scalar potential in the two-Higgs-doublet extension of the standard model. Our main result is to show the consistency of those 3-3-1 models without exotic electric charges. (orig.)
Lattice Dynamics of II-VI materials using adiabatic bond charge model
Rajput, B. D.; Browne, D. A.
1995-01-01
We extend the adiabatic bond charge model, originally developed for group IV semiconductors and III-V compounds, to study phonons in more ionic II-VI compounds with a zincblende structure. Phonon spectra, density of states and specific heats are calculated for six II-VI compounds and compared with both experimental data and the results of other models. We show that the 6-parameter bond charge model gives a good description of the lattice dynamics of these materials. We also discuss trends in ...
A new model for spherically symmetric charged compact stars of embedding class one
Maurya, S K; Ray, Saibal; Deb, Debabrata
2016-01-01
In the present study we search for a new stellar model with spherically symmetric matter and charged distribution under the general relativistic framework. The model represents a compact star of embedding class one. The solutions obtain here are general in their nature having the following two features: firstly, the metric becomes flat and also the expressions for the pressure, energy density and electric charge become zero in all the cases if we consider the constant $A=0$, which shows that our solutions represent the so-called `electromagnetic mass models'~\\cite{Lorentz1904}, and secondly, the metric function $\
Minow, Joseph I.
2011-01-01
Internal charging is a risk to spacecraft in energetic electron environments. DICTAT, NU MIT computational codes are the most widely used engineering tools for evaluating internal charging of insulator materials exposed to these environments. Engineering tools are designed for rapid evaluation of ESD threats, but there is a need for more physics based models for investigating the science of materials interactions with energetic electron environments. Current tools are limited by the physics included in the models and ease of user implementation .... additional development work is needed to improve models.
Cell survival in carbon beams - comparison of amorphous track model predictions
DEFF Research Database (Denmark)
Grzanka, L.; Greilich, S.; Korcyl, M.;
Introduction: Predictions of the radiobiological effectiveness (RBE) play an essential role in treatment planning with heavy charged particles. Amorphous track models ( [1] , [2] , also referred to as track structure models) provide currently the most suitable description of cell survival under i....... Amorphous track modelling of luminescence detector efficiency in proton and carbon beams. 4.Tsuruoka C, Suzuki M, Kanai T, et al. LET and ion species dependence for cell killing in normal human skin fibroblasts. Radiat Res. 2005;163:494-500.......Introduction: Predictions of the radiobiological effectiveness (RBE) play an essential role in treatment planning with heavy charged particles. Amorphous track models ( [1] , [2] , also referred to as track structure models) provide currently the most suitable description of cell survival under ion...... factors is the normalization of the energy distribution around the particle tracks to the actual LET value. Later on we check what is the effect of radial dose distribution choice on kappa parameter for different types and energy of ions. Outline References 1.Katz R, Sharma SC.Response of cells to fast...
A Predictive Maintenance Model for Railway Tracks
DEFF Research Database (Denmark)
Li, Rui; Wen, Min; Salling, Kim Bang;
2015-01-01
For the modern railways, maintenance is critical for ensuring safety, train punctuality and overall capacity utilization. The cost of railway maintenance in Europe is high, on average between 30,000 – 100,000 Euro per km per year [1]. Aiming to reduce such maintenance expenditure, this paper...... recovery on the track quality after tamping operation and (5) Tamping machine operation factors. A Danish railway track between Odense and Fredericia with 57.2 km of length is applied for a time period of two to four years in the proposed maintenance model. The total cost can be reduced with up to 50...
Quaternion Supergravity predicts the Standard Model
Bird, Paul
2001-01-01
It is shown that extending Osp(4/1) supergravity to quaternion co-ordinates to get HU(4/1) gives the standard model with 3 generations of fermions, U(1)xSU(2)xSU(3) bosons plus 2 gravitinos, 1 graviton, and nothing else. It is shown using the method of components that this is the largest supergravity theory possible. Briefly, we look at how this relates to 16D M-Theory (which I call Q-Theory). I hope others will be encouraged to work on this idea. This paper was replaced because it now includ...
ANN modeling for flood prediction in the upstream Eure's catchment (France)
Kharroubi, Ouissem; masson, Eric; Blanpain, Olivier; Lallahem, Sami
2013-04-01
Rainfall-Runoff relationship at basin scale is strongly depending on the catchment complexity including multi-scale interactions. In extreme events cases (i.e. floods and droughts) this relationship is even more complex and differs from average hydrological conditions making extreme runoff prediction very difficult to achieve. However, flood warning, flood prevention and flood mitigation rely on the possibility to predict both flood peak runoff and lag time. This point is crucial for decision making and flood warning to prevent populations and economical stakes to be damaged by extreme hydrological events. Since 2003 in France, a dedicated state service is in charge of producing flood warning from national level (i.e. SCHAPI) to regional level (i.e. SPC). This flood warning service is combining national weather forecast agency (i.e. Meteo France) together with a fully automated realtime hydrological network (i.e. Rainfall-Runoff) in order to produce a flood warning national map online and provide a set of hydro-meteorological data to the SPC in charge of flood prediction from regional to local scale. The SPC is in fact the flood service delivering hydrological prediction at operational level for decision making about flood alert for municipalities and first help services. Our research in collaboration with the SPC SACN (i.e. "Seine Aval et fleuves Côtiers Normands") is focused on the implementation of an Artificial Neural Network model (ANN) for flood prediction in deferent key points of the Eure's catchment and main subcatchment. Our contribution will focus on the ANN model developed for Saint-Luperce gauging station in the upstream part of the Eure's catchment. Prediction of extreme runoff at Saint-Luperce station is of high importance for flood warning in the Eure's catchment because it gives a good indicator on the extreme status and the downstream propagation of a potential flood event. Despite a good runoff monitoring since 27 years Saint Luperce flood
Prediction Model for Gastric Cancer Incidence in Korean Population
Eom, Bang Wool; Joo, Jungnam; Kim, Sohee; Shin, Aesun; Yang, Hye-Ryung; Park, Junghyun; Choi, Il Ju; Kim, Young-Woo; Kim, Jeongseon; Nam, Byung-Ho
2015-01-01
Background Predicting high risk groups for gastric cancer and motivating these groups to receive regular checkups is required for the early detection of gastric cancer. The aim of this study is was to develop a prediction model for gastric cancer incidence based on a large population-based cohort in Korea. Method Based on the National Health Insurance Corporation data, we analyzed 10 major risk factors for gastric cancer. The Cox proportional hazards model was used to develop gender specific ...
MACHINE LEARNING MODELS FOR PREDICTING SHELF LIFE OF PROCESSED CHEESE
Sumit, Goyal; Gyanendra, Goyal
2013-01-01
Feedforward multilayer machine learning artificial neural network (ANN) models were established for predicting shelf life of processed cheese stored at 7-8o C. Soluble nitrogen, pH, standard plate count, yeast & mould count, and spore count were input variables, and sensory score was the output variable. Mean Square Error, Root Mean Square Error, Coefficient of Determination and Nash–Sutcliffe Coefficient were used for comparing the prediction ability of the developed models. Feedforward ...
Prediction of cloud droplet number in a general circulation model
Energy Technology Data Exchange (ETDEWEB)
Ghan, S.J.; Leung, L.R. [Pacific Northwest National Lab., Richland, WA (United States)
1996-04-01
We have applied the Colorado State University Regional Atmospheric Modeling System (RAMS) bulk cloud microphysics parameterization to the treatment of stratiform clouds in the National Center for Atmospheric Research Community Climate Model (CCM2). The RAMS predicts mass concentrations of cloud water, cloud ice, rain and snow, and number concnetration of ice. We have introduced the droplet number conservation equation to predict droplet number and it`s dependence on aerosols.
Multi-task CNN Model for Attribute Prediction
Abdulnabi, Abrar H.; Wang, Gang; Lu, Jiwen; Jia, Kui
2016-01-01
This paper proposes a joint multi-task learning algorithm to better predict attributes in images using deep convolutional neural networks (CNN). We consider learning binary semantic attributes through a multi-task CNN model, where each CNN will predict one binary attribute. The multi-task learning allows CNN models to simultaneously share visual knowledge among different attribute categories. Each CNN will generate attribute-specific feature representations, and then we apply multi-task learn...
Modelling microbial interactions and food structure in predictive microbiology
Malakar, P.K.
2002-01-01
Keywords: modelling, dynamic models, microbial interactions, diffusion, microgradients, colony growth, predictive microbiology. Growth response of microorganisms in foods is a complex process. Innovations in food production and preservation techniques have resulted in adoption of new technologies to ensure food quality and safety. Predictive microbiology is one such technology, where growth responses of homogenous pure broth cultures of microorganism to the environment are quantified. In t...
Developing a predictive tropospheric ozone model for Tabriz
Khatibi, Rahman; Naghipour, Leila; Ghorbani, Mohammad A.; Smith, Michael S.; Karimi, Vahid; Farhoudi, Reza; Delafrouz, Hadi; Arvanaghi, Hadi
2013-04-01
Predictive ozone models are becoming indispensable tools by providing a capability for pollution alerts to serve people who are vulnerable to the risks. We have developed a tropospheric ozone prediction capability for Tabriz, Iran, by using the following five modeling strategies: three regression-type methods: Multiple Linear Regression (MLR), Artificial Neural Networks (ANNs), and Gene Expression Programming (GEP); and two auto-regression-type models: Nonlinear Local Prediction (NLP) to implement chaos theory and Auto-Regressive Integrated Moving Average (ARIMA) models. The regression-type modeling strategies explain the data in terms of: temperature, solar radiation, dew point temperature, and wind speed, by regressing present ozone values to their past values. The ozone time series are available at various time intervals, including hourly intervals, from August 2010 to March 2011. The results for MLR, ANN and GEP models are not overly good but those produced by NLP and ARIMA are promising for the establishing a forecasting capability.
Empirical Model for Predicting Rockfall Trajectory Direction
Asteriou, Pavlos; Tsiambaos, George
2016-03-01
A methodology for the experimental investigation of rockfall in three-dimensional space is presented in this paper, aiming to assist on-going research of the complexity of a block's response to impact during a rockfall. An extended laboratory investigation was conducted, consisting of 590 tests with cubical and spherical blocks made of an artificial material. The effects of shape, slope angle and the deviation of the post-impact trajectory are examined as a function of the pre-impact trajectory direction. Additionally, an empirical model is proposed that estimates the deviation of the post-impact trajectory as a function of the pre-impact trajectory with respect to the slope surface and the slope angle. This empirical model is validated by 192 small-scale field tests, which are also presented in this paper. Some important aspects of the three-dimensional nature of rockfall phenomena are highlighted that have been hitherto neglected. The 3D space data provided in this study are suitable for the calibration and verification of rockfall analysis software that has become increasingly popular in design practice.
Efficient nonlinear predictive error variance for highly parameterized models
Tonkin, Matthew; Doherty, John; Moore, Catherine
2007-07-01
Predictive error variance analysis attempts to determine how wrong predictions made by a calibrated model may be. Predictive error variance analysis is usually undertaken following calibration using a small number of parameters defined through a priori parsimony. In contrast, we introduce a method for investigating the potential error in predictions made by highly parameterized models calibrated using regularized inversion. Vecchia and Cooley (1987) describe a method of predictive error variance analysis that is constrained by calibration data. We extend this approach to include constraints on parameters that lie within the calibration null space. These constraints are determined by dividing parameter space into combinations of parameters for which estimates can be obtained and those for which they cannot. This enables the contribution to predictive error variance from parameterization simplifications required to solve the inverse problem to be quantified, in addition to the contribution from measurement noise. We also describe a novel technique that restricts the analysis to a strategically defined predictive solution subspace, enabling an approximate predictive error variance analysis to be completed efficiently. The method is illustrated using a synthetic and a real-world groundwater flow and transport model.
Residual bias in a multiphase flow model calibration and prediction
Poeter, E.P.; Johnson, R.H.
2002-01-01
When calibrated models produce biased residuals, we assume it is due to an inaccurate conceptual model and revise the model, choosing the most representative model as the one with the best-fit and least biased residuals. However, if the calibration data are biased, we may fail to identify an acceptable model or choose an incorrect model. Conceptual model revision could not eliminate biased residuals during inversion of simulated DNAPL migration under controlled conditions at the Borden Site near Ontario Canada. This paper delineates hypotheses for the source of bias, and explains the evolution of the calibration and resulting model predictions.
A Prediction Model for Taiwan Tourism Industry Stock Index
Directory of Open Access Journals (Sweden)
Han-Chen Huang
2013-12-01
Full Text Available Investors and scholars pay continuous attention to the stock market, as each day, many investors attem pt to use different methods to predict stock price trends . However, as stock price is affected by economy, p olitics, domestic and foreign situations, emergency, human f actor, and other unknown factors, it is difficult t o establish an accurate prediction model. This study used a back-propagation neural network (BPN as the research approach, and input 29 variables, such as international exchange rate, indices of internation al stock markets, Taiwan stock market analysis indicat ors, and overall economic indicators, to predict Taiwan’s monthly tourism industry stock index. The empirical findings show that the BPN prediction mod el has better predictive accuracy, Absolute Relative E rror is 0.090058, and correlation coefficient is 0.944263. The model has low error and high correlat ion, and can serve as reference for investors and relevant industries.
Traffic Prediction Scheme based on Chaotic Models in Wireless Networks
Directory of Open Access Journals (Sweden)
Xiangrong Feng
2013-09-01
Full Text Available Based on the local support vector algorithm of chaotic time series analysis, the Hannan-Quinn information criterion and SAX symbolization are introduced. Then a novel prediction algorithm is proposed, which is successfully applied to the prediction of wireless network traffic. For the correct prediction problems of short-term flow with smaller data set size, the weakness of the algorithms during model construction is analyzed by study and comparison to LDK prediction algorithm. It is verified the Hannan-Quinn information principle can be used to calculate the number of neighbor points to replace pervious empirical method, which uses the number of neighbor points to acquire more accurate prediction model. Finally, actual flow data is applied to confirm the accuracy rate of the proposed algorithm LSDHQ. It is testified by our experiments that it also has higher performance in adaptability than that of LSDHQ algorithm.
Models for predicting recreational water quality at Lake Erie beaches
Francy, Donna S.; Darner, Robert A.; Bertke, Erin E.
2006-01-01
Data collected from four Lake Erie beaches during the recreational seasons of 2004-05 and from one Lake Erie beach during 2000-2005 were used to develop predictive models for recreational water quality by means of multiple linear regression. The best model for each beach was based on a unique combination of environmental and water-quality explanatory variables including turbidity, rainfall, wave height, water temperature, day of the year, wind direction, and lake level. Two types of outputs were produced from the models: the predicted Escherichia coli concentration and the probability that the bathing-water standard will be exceeded. The model for one of beaches, Huntington Reservation (Huntington), was validated in 2005. For 2005, the Huntington model yielded more correct responses and better predicted exceedance of the standard than did current methods for assessing recreational water quality, which are based on the previous day's E. coli concentration. Predictions based on the Huntington model have been available to the public through an Internet-based 'nowcasting' system since May 30, 2006. The other beach models are being validated for the first time in 2006. The methods used in this study to develop and test predictive models can be applied at other similar coastal beaches.
Numerical modeling capabilities to predict repository performance
Energy Technology Data Exchange (ETDEWEB)
1979-09-01
This report presents a summary of current numerical modeling capabilities that are applicable to the design and performance evaluation of underground repositories for the storage of nuclear waste. The report includes codes that are available in-house, within Golder Associates and Lawrence Livermore Laboratories; as well as those that are generally available within the industry and universities. The first listing of programs are in-house codes in the subject areas of hydrology, solute transport, thermal and mechanical stress analysis, and structural geology. The second listing of programs are divided by subject into the following categories: site selection, structural geology, mine structural design, mine ventilation, hydrology, and mine design/construction/operation. These programs are not specifically designed for use in the design and evaluation of an underground repository for nuclear waste; but several or most of them may be so used.
Numerical modeling capabilities to predict repository performance
International Nuclear Information System (INIS)
This report presents a summary of current numerical modeling capabilities that are applicable to the design and performance evaluation of underground repositories for the storage of nuclear waste. The report includes codes that are available in-house, within Golder Associates and Lawrence Livermore Laboratories; as well as those that are generally available within the industry and universities. The first listing of programs are in-house codes in the subject areas of hydrology, solute transport, thermal and mechanical stress analysis, and structural geology. The second listing of programs are divided by subject into the following categories: site selection, structural geology, mine structural design, mine ventilation, hydrology, and mine design/construction/operation. These programs are not specifically designed for use in the design and evaluation of an underground repository for nuclear waste; but several or most of them may be so used
Using a Prediction Model to Manage Cyber Security Threats.
Jaganathan, Venkatesh; Cherurveettil, Priyesh; Muthu Sivashanmugam, Premapriya
2015-01-01
Cyber-attacks are an important issue faced by all organizations. Securing information systems is critical. Organizations should be able to understand the ecosystem and predict attacks. Predicting attacks quantitatively should be part of risk management. The cost impact due to worms, viruses, or other malicious software is significant. This paper proposes a mathematical model to predict the impact of an attack based on significant factors that influence cyber security. This model also considers the environmental information required. It is generalized and can be customized to the needs of the individual organization. PMID:26065024
Aero-acoustic noise of wind turbines. Noise prediction models
Energy Technology Data Exchange (ETDEWEB)
Maribo Pedersen, B. [ed.
1997-12-31
Semi-empirical and CAA (Computational AeroAcoustics) noise prediction techniques are the subject of this expert meeting. The meeting presents and discusses models and methods. The meeting may provide answers to the following questions: What Noise sources are the most important? How are the sources best modeled? What needs to be done to do better predictions? Does it boil down to correct prediction of the unsteady aerodynamics around the rotor? Or is the difficult part to convert the aerodynamics into acoustics? (LN)
Predictive data modeling of human type II diabetes related statistics
Jaenisch, Kristina L.; Jaenisch, Holger M.; Handley, James W.; Albritton, Nathaniel G.
2009-04-01
During the course of routine Type II treatment of one of the authors, it was decided to derive predictive analytical Data Models of the daily sampled vital statistics: namely weight, blood pressure, and blood sugar, to determine if the covariance among the observed variables could yield a descriptive equation based model, or better still, a predictive analytical model that could forecast the expected future trend of the variables and possibly eliminate the number of finger stickings required to montior blood sugar levels. The personal history and analysis with resulting models are presented.
Research on Drag Torque Prediction Model for the Wet Clutches
Institute of Scientific and Technical Information of China (English)
无
2008-01-01
Considering the surface tension effect and centrifugal effect, a mathematical model based on Reynolds equation for predicting the drag torque of disengage wet clutches is presented. The model indicates that the equivalent radius is a function of clutch speed and flow rate. The drag torque achieves its peak at a critical speed. Above this speed, drag torque drops due to the shrinking of the oil film. The model also points out that viscosity and flow rate effects on drag torque. Experimental results indicate that the model is reasonable and it performs well for predicting the drag torque peak.
Model Predictive Control for an Industrial SAG Mill
DEFF Research Database (Denmark)
Ohan, Valeriu; Steinke, Florian; Metzger, Michael;
2012-01-01
We discuss Model Predictive Control (MPC) based on ARX models and a simple lower order disturbance model. The advantage of this MPC formulation is that it has few tuning parameters and is based on an ARX prediction model that can readily be identied using standard technologies from system...... identication. When applied to MIMO systems we call this controller a MIMO-ARX based MPC. We use an industrial Semi-Autogenous Grinding (SAG) mill to illustrate the performance of this controller. SAG mills are the primary units in a grinding chain and also the most power consuming units. Therefore, improved...
Model Predictive Control of a Wave Energy Converter
DEFF Research Database (Denmark)
Andersen, Palle; Pedersen, Tom Søndergård; Nielsen, Kirsten Mølgaard;
2015-01-01
In this paper reactive control and Model Predictive Control (MPC) for a Wave Energy Converter (WEC) are compared. The analysis is based on a WEC from Wave Star A/S designed as a point absorber. The model predictive controller uses wave models based on the dominating sea states combined with a model...... connecting undisturbed wave sequences to sequences of torque. Losses in the conversion from mechanical to electrical power are taken into account in two ways. Conventional reactive controllers are tuned for each sea state with the assumption that the converter has the same efficiency back and forth. MPC...
Roy, Palas; Jha, Ajay; Dasgupta, Jyotishman
2016-01-01
The device efficiency of bulk heterojunction (BHJ) solar cells is critically dependent on the nano-morphology of the solution-processed polymer : fullerene blend. Active control on blend morphology can only emanate from a detailed understanding of solution structures during the film casting process. Here we use photoinduced charge transfer (CT) rates to probe the effective length scale of the pre-formed solution structures and their energy disorder arising from a mixture of poly(3-hexylthiophene-2,5-diyl) (P3HT) and [6,6]-phenyl-C61-butyric acid methyl ester (PCBM) in three different organic solvents. The observed solvent-dependent ultrafast biphasic rise of the transient polaron state in solution along with changes detected in the C&z.dbd;C stretching frequency of bound PCBM provides direct evidence for film-like P3HT : PCBM interfaces in solution. Using the diffusive component of the charge transfer rate, we deduce ~3-times larger functional nano-domain size in toluene than in chlorobenzene thereby correctly predicting the relative polymer nanofiber widths observed in annealed films. We thus provide first experimental evidence for the postulated polymer : fullerene : solvent ternary phase that seeds the eventual morphology in spin-cast films. Our work motivates the design of new chemical additives to tune the grain size of the evolving polymer : fullerene domains within the solution phase.The device efficiency of bulk heterojunction (BHJ) solar cells is critically dependent on the nano-morphology of the solution-processed polymer : fullerene blend. Active control on blend morphology can only emanate from a detailed understanding of solution structures during the film casting process. Here we use photoinduced charge transfer (CT) rates to probe the effective length scale of the pre-formed solution structures and their energy disorder arising from a mixture of poly(3-hexylthiophene-2,5-diyl) (P3HT) and [6,6]-phenyl-C61-butyric acid methyl ester (PCBM) in three
Model output statistics applied to wind power prediction
Energy Technology Data Exchange (ETDEWEB)
Joensen, A.; Giebel, G.; Landberg, L. [Risoe National Lab., Roskilde (Denmark); Madsen, H.; Nielsen, H.A. [The Technical Univ. of Denmark, Dept. of Mathematical Modelling, Lyngby (Denmark)
1999-03-01
Being able to predict the output of a wind farm online for a day or two in advance has significant advantages for utilities, such as better possibility to schedule fossil fuelled power plants and a better position on electricity spot markets. In this paper prediction methods based on Numerical Weather Prediction (NWP) models are considered. The spatial resolution used in NWP models implies that these predictions are not valid locally at a specific wind farm. Furthermore, due to the non-stationary nature and complexity of the processes in the atmosphere, and occasional changes of NWP models, the deviation between the predicted and the measured wind will be time dependent. If observational data is available, and if the deviation between the predictions and the observations exhibits systematic behavior, this should be corrected for; if statistical methods are used, this approaches is usually referred to as MOS (Model Output Statistics). The influence of atmospheric turbulence intensity, topography, prediction horizon length and auto-correlation of wind speed and power is considered, and to take the time-variations into account, adaptive estimation methods are applied. Three estimation techniques are considered and compared, Extended Kalman Filtering, recursive least squares and a new modified recursive least squares algorithm. (au) EU-JOULE-3. 11 refs.
Time dependent patient no-show predictive modelling development.
Huang, Yu-Li; Hanauer, David A
2016-05-01
Purpose - The purpose of this paper is to develop evident-based predictive no-show models considering patients' each past appointment status, a time-dependent component, as an independent predictor to improve predictability. Design/methodology/approach - A ten-year retrospective data set was extracted from a pediatric clinic. It consisted of 7,291 distinct patients who had at least two visits along with their appointment characteristics, patient demographics, and insurance information. Logistic regression was adopted to develop no-show models using two-thirds of the data for training and the remaining data for validation. The no-show threshold was then determined based on minimizing the misclassification of show/no-show assignments. There were a total of 26 predictive model developed based on the number of available past appointments. Simulation was employed to test the effective of each model on costs of patient wait time, physician idle time, and overtime. Findings - The results demonstrated the misclassification rate and the area under the curve of the receiver operating characteristic gradually improved as more appointment history was included until around the 20th predictive model. The overbooking method with no-show predictive models suggested incorporating up to the 16th model and outperformed other overbooking methods by as much as 9.4 per cent in the cost per patient while allowing two additional patients in a clinic day. Research limitations/implications - The challenge now is to actually implement the no-show predictive model systematically to further demonstrate its robustness and simplicity in various scheduling systems. Originality/value - This paper provides examples of how to build the no-show predictive models with time-dependent components to improve the overbooking policy. Accurately identifying scheduled patients' show/no-show status allows clinics to proactively schedule patients to reduce the negative impact of patient no-shows. PMID:27142954
Chang, We-Fu; Wong, Chi-Fong; Xu, Fanrong
2016-01-01
We considered a neutrino mass generating model which employs a scalar leptoquark, $\\Delta$, and a scalar diquark, $S$. The new scalars $\\Delta$ and $S$ carry the standard model $SU(3)_c\\times SU(2)_L\\times U(1)_Y$ quantum numbers $(3,1,-1/3)$ and $(6,1,-2/3)$ respectively. The neutrino masses are generated at the two-loop level similar to that in the Zee-Babu model\\cite{Zee-Babu}. And $\\Delta/S$ plays the role of the doubly/singly charged scalar in the Zee-Babu model. With a moderate working assumption that the magnitudes of the six Yukawa couplings between $S$ and the down-type quarks are of the same order, strong connections were found between the neutrino masses and the charged lepton flavor violating(cLFV) processes. In particular, $Z\\rightarrow \\overline{l} l'$, and $l\\rightarrow l' \\gamma$ were studied and it was found that some portions of the parameter space of this model are within the reach of the planned cLFV experiments. Interesting lower bounds on the cLFV processes were predicted that $B(Z\\right...
Model predictive torque control with an extended prediction horizon for electrical drive systems
Wang, Fengxiang; Zhang, Zhenbin; Kennel, Ralph; Rodríguez, José
2015-07-01
This paper presents a model predictive torque control method for electrical drive systems. A two-step prediction horizon is achieved by considering the reduction of the torque ripples. The electromagnetic torque and the stator flux error between predicted values and the references, and an over-current protection are considered in the cost function design. The best voltage vector is selected by minimising the value of the cost function, which aims to achieve a low torque ripple in two intervals. The study is carried out experimentally. The results show that the proposed method achieves good performance in both steady and transient states.
Communication: Fragment-based Hamiltonian model of electronic charge-excitation gaps and gap closure
International Nuclear Information System (INIS)
Capturing key electronic properties such as charge excitation gaps within models at or above the atomic scale presents an ongoing challenge to understanding molecular, nanoscale, and condensed phase systems. One strategy is to describe the system in terms of properties of interacting material fragments, but it is unclear how to accomplish this for charge-excitation and charge-transfer phenomena. Hamiltonian models such as the Hubbard model provide formal frameworks for analyzing gap properties but are couched purely in terms of states of electrons, rather than the states of the fragments at the scale of interest. The recently introduced Fragment Hamiltonian (FH) model uses fragments in different charge states as its building blocks, enabling a uniform, quantum-mechanical treatment that captures the charge-excitation gap. These gaps are preserved in terms of inter-fragment charge-transfer hopping integrals T and on-fragment parameters U(FH). The FH model generalizes the standard Hubbard model (a single intra-band hopping integral t and on-site repulsion U) from quantum states for electrons to quantum states for fragments. We demonstrate that even for simple two-fragment and multi-fragment systems, gap closure is enabled once T exceeds the threshold set by U(FH), thus providing new insight into the nature of metal-insulator transitions. This result is in contrast to the standard Hubbard model for 1d rings, for which Lieb and Wu proved that gap closure was impossible, regardless of the choices for t and U
International Nuclear Information System (INIS)
A numerical model for describing bipolar charge transport and storage in polyethylene has been developed recently. The present paper proposes a comparison of the model outputs with experimental data in three different direct current (DC) voltage application protocols (step field increase and polarization/depolarization schemes). Three kinds of measurement have been realized for the three different protocols: space charge distribution using the pulsed electro-acoustic method, external current and electroluminescence. Simulation under AC stress has also been attempted on the basis of the model parameters that were derived from the DC case. Model limitations and possible improvements are discussed
International Nuclear Information System (INIS)
A new way for the modelling of the charge and discharge processes in electrochemical batteries based on the use of integral equations is presented. The proposed method models the charge curves by the so called fractional or cumulative integrals of a certain objective function f(t) that must be sought. The charge figures can be easily fitted by breaking down this objective function as the addition of two different Lorentz type functions: the first one is associated to the own charge process and the second one to the overcharge process. The method allows calculating the starting voltage for overcharge as the intersection between both functions. The curve fitting of this model to different experimental charge curves, by using the Marquart algorithm, has shown very accurate results. In the case of discharge curves, two possible methods for modelling purposes are suggested, well by using the same kind of integral equations, well by the simple subtraction of an objective function f(t) from a constant value VOD. Many other aspects for the study and analysis of this method in order to improve its results in further developments are also discussed. (Author) 10 refs
Chen, Chuan-Hung
2016-01-01
The Higgs-portal lepton flavor violation is studied in a vectorlike lepton model. For evading the constraints from rare $Z\\to \\ell^\\pm_i \\ell^\\mp_j$ decays, we introduce two triplet vectorlike leptons, $(1,3)_{-1}$ and $(1,3)_{0}$. The resultant branching ratio for $h\\to \\mu \\tau$ can be up to $10^{-4}$ when the constraints from the invisible $Z$ decays are applied. As a result, the signal strength for $\\tau\\tau$ channel has a $12\\%$ deviation from the standard model prediction, while the muon $g-2$ is two-order of magnitude smaller than the data and $BR(\\tau\\to \\mu \\gamma)$ is of order of $10^{-12}$. A predicted doubly charged lepton in $pp$ collisions at $\\sqrt{s}=13$ TeV is analyzed and it is found that the interesting production channels are $pp\\to (\\Psi^{--}_{1} \\Psi^{++}_1, \\Psi^{\\pm\\pm}_1 \\Psi^\\mp_1)$. Both single and pair production cross sections of $\\Psi^{++}_1$ are comparable and can be a few hundred fb. The main decay channels for the doubly charged lepton are $\\Psi^{\\pm\\pm} \\to \\ell^\\pm W^\\pm$ an...
Predictive maintenance and modeling of Transformer
Directory of Open Access Journals (Sweden)
Ladani Dhaval H., Sandeep A. Mehta, Pallav Gandhi
2013-04-01
Full Text Available Power transformer is the most important and expensive equipment in Power plant and the Oil has the main roles of insulating and cooling of transformer. The oil condition has to be checked regularly and replaced when it necessary, because to avoid the suddenly failure of the transformer. Large power transformers are the most key components in power system and their correct functioning or maintenance is important to system operation. Power transformers are protected by different protection schemes that use voltages and currents to detect abnormal condition in the different zone of protection. For this type of scheme, a short circuit or increment load accidental it must be to trip a system. Power transformers ageing are one of the most critical issues. Also their replacement will consider amount of time and cost. Therefore, developing a replacement or maintenance strategy of transformer populations is important. This paper presents simulation for life assessment of the transformer per hour, per day, per month using LabView™. Here Load and ambient temperatures are two important factors that affect the life of insulation of transformers. The estimated load factors and ambient temperatures are input and to find out the Hot spot temperature or ageing or rate of change of ageing of transformer to the IEC life consumption models to assess the consumed life of insulation of transformer.