Hopkins, Matthew Morgan; DeChant, Lawrence Justin.; Piekos, Edward Stanley; Pointon, Timothy David
2009-02-01
This report summarizes the work completed during FY2007 and FY2008 for the LDRD project ''Hybrid Plasma Modeling''. The goal of this project was to develop hybrid methods to model plasmas across the non-continuum-to-continuum collisionality spectrum. The primary methodology to span these regimes was to couple a kinetic method (e.g., Particle-In-Cell) in the non-continuum regions to a continuum PDE-based method (e.g., finite differences) in continuum regions. The interface between the two would be adjusted dynamically ased on statistical sampling of the kinetic results. Although originally a three-year project, it became clear during the second year (FY2008) that there were not sufficient resources to complete the project and it was terminated mid-year.
Competitive hybridization models.
Cherepinsky, Vera; Hashmi, Ghazala; Mishra, Bud
2010-11-01
Microarray technology, in its simplest form, allows one to gather abundance data for target DNA molecules, associated with genomes or gene-expressions, and relies on hybridizing the target to many short probe oligonucleotides arrayed on a surface. While for such multiplexed reactions conditions are optimized to make the most of each individual probe-target interaction, subsequent analysis of these experiments is based on the implicit assumption that a given experiment yields the same result regardless of whether it was conducted in isolation or in parallel with many others. It has been discussed in the literature that this assumption is frequently false, and its validity depends on the types of probes and their interactions with each other. We present a detailed physical model of hybridization as a means of understanding probe interactions in a multiplexed reaction. Ultimately, the model can be derived from a system of ordinary differential equations (ODE's) describing kinetic mass action with conservation-of-mass equations completing the system. We examine pairwise probe interactions in detail and present a model of "competition" between the probes for the target--especially, when the target is effectively in short supply. These effects are shown to be predictable from the affinity constants for each of the four probe sequences involved, namely, the match and mismatch sequences for both probes. These affinity constants are calculated from the thermodynamic parameters such as the free energy of hybridization, which are in turn computed according to the nearest neighbor (NN) model for each probe and target sequence. Simulations based on the competitive hybridization model explain the observed variability in the signal of a given probe when measured in parallel with different groupings of other probes or individually. The results of the simulations can be used for experiment design and pooling strategies, based on which probes have been shown to have a strong effect
Competitive hybridization models
NASA Astrophysics Data System (ADS)
Cherepinsky, Vera; Hashmi, Ghazala; Mishra, Bud
2010-11-01
Microarray technology, in its simplest form, allows one to gather abundance data for target DNA molecules, associated with genomes or gene-expressions, and relies on hybridizing the target to many short probe oligonucleotides arrayed on a surface. While for such multiplexed reactions conditions are optimized to make the most of each individual probe-target interaction, subsequent analysis of these experiments is based on the implicit assumption that a given experiment yields the same result regardless of whether it was conducted in isolation or in parallel with many others. It has been discussed in the literature that this assumption is frequently false, and its validity depends on the types of probes and their interactions with each other. We present a detailed physical model of hybridization as a means of understanding probe interactions in a multiplexed reaction. Ultimately, the model can be derived from a system of ordinary differential equations (ODE’s) describing kinetic mass action with conservation-of-mass equations completing the system. We examine pairwise probe interactions in detail and present a model of “competition” between the probes for the target—especially, when the target is effectively in short supply. These effects are shown to be predictable from the affinity constants for each of the four probe sequences involved, namely, the match and mismatch sequences for both probes. These affinity constants are calculated from the thermodynamic parameters such as the free energy of hybridization, which are in turn computed according to the nearest neighbor (NN) model for each probe and target sequence. Simulations based on the competitive hybridization model explain the observed variability in the signal of a given probe when measured in parallel with different groupings of other probes or individually. The results of the simulations can be used for experiment design and pooling strategies, based on which probes have been shown to have a strong
Hybrid2 - The hybrid power system simulation model
Baring-Gould, E.I.; Green, H.J.; Dijk, V.A.P. van; Manwell, J.F.
1996-12-31
There is a large-scale need and desire for energy in remote communities, especially in the developing world; however the lack of a user friendly, flexible performance prediction model for hybrid power systems incorporating renewables hindered the analysis of hybrids as options to conventional solutions. A user friendly model was needed with the versatility to simulate the many system locations, widely varying hardware configurations, and differing control options for potential hybrid power systems. To meet these ends, researchers from the National Renewable Energy Laboratory (NREL) and the University of Massachusetts (UMass) developed the Hybrid2 software. This paper provides an overview of the capabilities, features, and functionality of the Hybrid2 code, discusses its validation and future plans. Model availability and technical support provided to Hybrid2 users are also discussed. 12 refs., 3 figs., 4 tabs.
Hybrid2: The hybrid power system simulation model
Baring-Gould, E I; Green, H J; van Dijk, V A.P.; Manwell, J F
1996-07-01
There is a large-scale need and desire for energy in remote communities, especially in the developing world; however the lack of a user friendly, flexible performance prediction model for hybrid power systems incorporating renewables hindered the analysis of hybrids (including wind turbines, PV, diesel generators, AC/DC energy storage) as options to conventional solutions. A user friendly model was needed with the versatility to simulate the many system locations, widely varying hardware configurations, and differing control options for potential hybrid power systems. To meet these ends, NREL and U. Mass. researchers developed the Hybrid2 software. This paper provides an overview of the capabilities, features, and functionality of the Hybrid2 code, discusses its validation and future plans. Model availability and technical support provided to Hybrid2 users are also discussed.
Hybrid regional air pollution models
Drake, R.L.
1980-03-01
This discussion deals with a family of air quality models for predicting and analyzing the fine particulate loading in the atmosphere, for assessing the extent and degree of visibility impairment, and for determining the potential of pollutants for increasing the acidity of soils and water. The major horizontal scales of interest are from 400km to 2000km; and the time scales may vary from several hours, to days, weeks, and a few months or years, depending on the EPA regulations being addressed. First the role air quality models play in the general family of atmospheric simulation models is described. Then, the characteristics of a well-designed, comprehensive air quality model are discussed. Following this, the specific objectives of this workshop are outlined, and their modeling implications are summarized. There are significant modeling differences produced by the choice of the coordinate system, whether it be the fixed Eulerian system, the moving Lagrangian system, or some hybrid of the two. These three systems are briefly discussed, and a list of hybrid models that are currently in use are given. Finally, the PNL regional transport model is outlined and a number of research needs are listed.
Using Hybrid Modeling to Develop Innovative Activities
ERIC Educational Resources Information Center
Lichtman, Brenda; Avans, Diana
2005-01-01
This article describes a hybrid activities model that physical educators can use with students in grades four and above to create virtually a limitless array of novel games. A brief introduction to the basic theory is followed by descriptions of some hybrid games. Hybrid games are typically the result of merging two traditional sports or other…
Model-Based Prognostics of Hybrid Systems
NASA Technical Reports Server (NTRS)
Daigle, Matthew; Roychoudhury, Indranil; Bregon, Anibal
2015-01-01
Model-based prognostics has become a popular approach to solving the prognostics problem. However, almost all work has focused on prognostics of systems with continuous dynamics. In this paper, we extend the model-based prognostics framework to hybrid systems models that combine both continuous and discrete dynamics. In general, most systems are hybrid in nature, including those that combine physical processes with software. We generalize the model-based prognostics formulation to hybrid systems, and describe the challenges involved. We present a general approach for modeling hybrid systems, and overview methods for solving estimation and prediction in hybrid systems. As a case study, we consider the problem of conflict (i.e., loss of separation) prediction in the National Airspace System, in which the aircraft models are hybrid dynamical systems.
Hadron rapidity spectra within a hybrid model
NASA Astrophysics Data System (ADS)
Khvorostukhin, A. S.; Toneev, V. D.
2017-01-01
A 2-stage hybrid model is proposed that joins the fast initial state of interaction, described by the hadron string dynamics (HSD) model, to subsequent evolution of the expanding system at the second stage, treated within ideal hydrodynamics. The developed hybrid model is assigned to describe heavy-ion collisions in the energy range of the NICA collider under construction in Dubna. Generally, the model is in reasonable agreement with the available data on proton rapidity spectra. However, reproducing proton rapidity spectra, our hybrid model cannot describe the rapidity distributions of pions. The model should be improved by taking into consideration viscosity effects at the hydrodynamical stage of system evolution.
Evaluating the Pedagogical Potential of Hybrid Models
ERIC Educational Resources Information Center
Levin, Tzur; Levin, Ilya
2013-01-01
The paper examines how the use of hybrid models--that consist of the interacting continuous and discrete processes--may assist in teaching system thinking. We report an experiment in which undergraduate students were asked to choose between a hybrid and a continuous solution for a number of control problems. A correlation has been found between…
Modeling hybrid perovskites by molecular dynamics
NASA Astrophysics Data System (ADS)
Mattoni, Alessandro; Filippetti, Alessio; Caddeo, Claudia
2017-02-01
The topical review describes the recent progress in the modeling of hybrid perovskites by molecular dynamics simulations. Hybrid perovskites and in particular methylammonium lead halide (MAPI) have a tremendous technological relevance representing the fastest-advancing solar material to date. They also represent the paradigm of an organic-inorganic crystalline material with some conceptual peculiarities: an inorganic semiconductor for what concerns the electronic and absorption properties with a hybrid and solution processable organic-inorganic body. After briefly explaining the basic concepts of ab initio and classical molecular dynamics, the model potential recently developed for hybrid perovskites is described together with its physical motivation as a simple ionic model able to reproduce the main dynamical properties of the material. Advantages and limits of the two strategies (either ab initio or classical) are discussed in comparison with the time and length scales (from pico to microsecond scale) necessary to comprehensively study the relevant properties of hybrid perovskites from molecular reorientations to electrocaloric effects. The state-of-the-art of the molecular dynamics modeling of hybrid perovskites is reviewed by focusing on a selection of showcase applications of methylammonium lead halide: molecular cations disorder; temperature evolution of vibrations; thermally activated defects diffusion; thermal transport. We finally discuss the perspectives in the modeling of hybrid perovskites by molecular dynamics.
Modeling hybrid perovskites by molecular dynamics.
Mattoni, Alessandro; Filippetti, Alessio; Caddeo, Claudia
2017-02-01
The topical review describes the recent progress in the modeling of hybrid perovskites by molecular dynamics simulations. Hybrid perovskites and in particular methylammonium lead halide (MAPI) have a tremendous technological relevance representing the fastest-advancing solar material to date. They also represent the paradigm of an organic-inorganic crystalline material with some conceptual peculiarities: an inorganic semiconductor for what concerns the electronic and absorption properties with a hybrid and solution processable organic-inorganic body. After briefly explaining the basic concepts of ab initio and classical molecular dynamics, the model potential recently developed for hybrid perovskites is described together with its physical motivation as a simple ionic model able to reproduce the main dynamical properties of the material. Advantages and limits of the two strategies (either ab initio or classical) are discussed in comparison with the time and length scales (from pico to microsecond scale) necessary to comprehensively study the relevant properties of hybrid perovskites from molecular reorientations to electrocaloric effects. The state-of-the-art of the molecular dynamics modeling of hybrid perovskites is reviewed by focusing on a selection of showcase applications of methylammonium lead halide: molecular cations disorder; temperature evolution of vibrations; thermally activated defects diffusion; thermal transport. We finally discuss the perspectives in the modeling of hybrid perovskites by molecular dynamics.
Travelling waves in hybrid chemotaxis models.
Franz, Benjamin; Xue, Chuan; Painter, Kevin J; Erban, Radek
2014-02-01
Hybrid models of chemotaxis combine agent-based models of cells with partial differential equation models of extracellular chemical signals. In this paper, travelling wave properties of hybrid models of bacterial chemotaxis are investigated. Bacteria are modelled using an agent-based (individual-based) approach with internal dynamics describing signal transduction. In addition to the chemotactic behaviour of the bacteria, the individual-based model also includes cell proliferation and death. Cells consume the extracellular nutrient field (chemoattractant), which is modelled using a partial differential equation. Mesoscopic and macroscopic equations representing the behaviour of the hybrid model are derived and the existence of travelling wave solutions for these models is established. It is shown that cell proliferation is necessary for the existence of non-transient (stationary) travelling waves in hybrid models. Additionally, a numerical comparison between the wave speeds of the continuum models and the hybrid models shows good agreement in the case of weak chemotaxis and qualitative agreement for the strong chemotaxis case. In the case of slow cell adaptation, we detect oscillating behaviour of the wave, which cannot be explained by mean-field approximations.
A Hybrid 3D Indoor Space Model
NASA Astrophysics Data System (ADS)
Jamali, Ali; Rahman, Alias Abdul; Boguslawski, Pawel
2016-10-01
GIS integrates spatial information and spatial analysis. An important example of such integration is for emergency response which requires route planning inside and outside of a building. Route planning requires detailed information related to indoor and outdoor environment. Indoor navigation network models including Geometric Network Model (GNM), Navigable Space Model, sub-division model and regular-grid model lack indoor data sources and abstraction methods. In this paper, a hybrid indoor space model is proposed. In the proposed method, 3D modeling of indoor navigation network is based on surveying control points and it is less dependent on the 3D geometrical building model. This research proposes a method of indoor space modeling for the buildings which do not have proper 2D/3D geometrical models or they lack semantic or topological information. The proposed hybrid model consists of topological, geometrical and semantical space.
Hybrid modelling of anaerobic wastewater treatment processes.
Karama, A; Bernard, O; Genovesi, A; Dochain, D; Benhammou, A; Steyer, J P
2001-01-01
This paper presents a hybrid approach for the modelling of an anaerobic digestion process. The hybrid model combines a feed-forward network, describing the bacterial kinetics, and the a priori knowledge based on the mass balances of the process components. We have considered an architecture which incorporates the neural network as a static model of unmeasured process parameters (kinetic growth rate) and an integrator for the dynamic representation of the process using a set of dynamic differential equations. The paper contains a description of the neural network component training procedure. The performance of this approach is illustrated with experimental data.
Weather forecasting based on hybrid neural model
NASA Astrophysics Data System (ADS)
Saba, Tanzila; Rehman, Amjad; AlGhamdi, Jarallah S.
2017-02-01
Making deductions and expectations about climate has been a challenge all through mankind's history. Challenges with exact meteorological directions assist to foresee and handle problems well in time. Different strategies have been investigated using various machine learning techniques in reported forecasting systems. Current research investigates climate as a major challenge for machine information mining and deduction. Accordingly, this paper presents a hybrid neural model (MLP and RBF) to enhance the accuracy of weather forecasting. Proposed hybrid model ensure precise forecasting due to the specialty of climate anticipating frameworks. The study concentrates on the data representing Saudi Arabia weather forecasting. The main input features employed to train individual and hybrid neural networks that include average dew point, minimum temperature, maximum temperature, mean temperature, average relative moistness, precipitation, normal wind speed, high wind speed and average cloudiness. The output layer composed of two neurons to represent rainy and dry weathers. Moreover, trial and error approach is adopted to select an appropriate number of inputs to the hybrid neural network. Correlation coefficient, RMSE and scatter index are the standard yard sticks adopted for forecast accuracy measurement. On individual standing MLP forecasting results are better than RBF, however, the proposed simplified hybrid neural model comes out with better forecasting accuracy as compared to both individual networks. Additionally, results are better than reported in the state of art, using a simple neural structure that reduces training time and complexity.
Hybrid quantum teleportation: A theoretical model
Takeda, Shuntaro; Mizuta, Takahiro; Fuwa, Maria; Yoshikawa, Jun-ichi; Yonezawa, Hidehiro; Furusawa, Akira
2014-12-04
Hybrid quantum teleportation – continuous-variable teleportation of qubits – is a promising approach for deterministically teleporting photonic qubits. We propose how to implement it with current technology. Our theoretical model shows that faithful qubit transfer can be achieved for this teleportation by choosing an optimal gain for the teleporter’s classical channel.
Dynamic modeling of lower hybrid current drive
Ignat, D.W.; Valeo, E.J.; Jardin, S.C.
1993-10-01
A computational model of lower hybrid current drive in the presence of an electric field is described and some results are given. Details of geometry, plasma profiles and circuit equations are treated carefully. Two-dimensional velocity space effects are approximated in a one-dimensional Fokker-Planck treatment.
CORSICA modelling of ITER hybrid operation scenarios
NASA Astrophysics Data System (ADS)
Kim, S. H.; Bulmer, R. H.; Campbell, D. J.; Casper, T. A.; LoDestro, L. L.; Meyer, W. H.; Pearlstein, L. D.; Snipes, J. A.
2016-12-01
The hybrid operating mode observed in several tokamaks is characterized by further enhancement over the high plasma confinement (H-mode) associated with reduced magneto-hydro-dynamic (MHD) instabilities linked to a stationary flat safety factor (q ) profile in the core region. The proposed ITER hybrid operation is currently aiming at operating for a long burn duration (>1000 s) with a moderate fusion power multiplication factor, Q , of at least 5. This paper presents candidate ITER hybrid operation scenarios developed using a free-boundary transport modelling code, CORSICA, taking all relevant physics and engineering constraints into account. The ITER hybrid operation scenarios have been developed by tailoring the 15 MA baseline ITER inductive H-mode scenario. Accessible operation conditions for ITER hybrid operation and achievable range of plasma parameters have been investigated considering uncertainties on the plasma confinement and transport. ITER operation capability for avoiding the poloidal field coil current, field and force limits has been examined by applying different current ramp rates, flat-top plasma currents and densities, and pre-magnetization of the poloidal field coils. Various combinations of heating and current drive (H&CD) schemes have been applied to study several physics issues, such as the plasma current density profile tailoring, enhancement of the plasma energy confinement and fusion power generation. A parameterized edge pedestal model based on EPED1 added to the CORSICA code has been applied to hybrid operation scenarios. Finally, fully self-consistent free-boundary transport simulations have been performed to provide information on the poloidal field coil voltage demands and to study the controllability with the ITER controllers. Extended from Proc. 24th Int. Conf. on Fusion Energy (San Diego, 2012) IT/P1-13.
Hybrid model for QCD deconfining phase boundary
NASA Astrophysics Data System (ADS)
Srivastava, P. K.; Singh, C. P.
2012-06-01
Intensive search for a proper and realistic equations of state (EOS) is still continued for studying the phase diagram existing between quark gluon plasma (QGP) and hadron gas (HG) phases. Lattice calculations provide such EOS for the strongly interacting matter at finite temperature (T) and vanishing baryon chemical potential (μB). These calculations are of limited use at finite μB due to the appearance of notorious sign problem. In the recent past, we had constructed a hybrid model description for the QGP as well as HG phases where we make use of a new excluded-volume model for HG and a thermodynamically-consistent quasiparticle model for the QGP phase and used them further to get QCD phase boundary and a critical point. Since then many lattice calculations have appeared showing various thermal and transport properties of QCD matter at finite T and μB=0. We test our hybrid model by reproducing the entire data for strongly interacting matter and predict our results at finite μB so that they can be tested in future. Finally we demonstrate the utility of the model in fixing the precise location, the order of the phase transition and the nature of CP existing on the QCD phase diagram. We thus emphasize the suitability of the hybrid model as formulated here in providing a realistic EOS for the strongly interacting matter.
Hybrid Energy System Modeling in Modelica
William R. Binder; Christiaan J. J. Paredis; Humberto E. Garcia
2014-03-01
In this paper, a Hybrid Energy System (HES) configuration is modeled in Modelica. Hybrid Energy Systems (HES) have as their defining characteristic the use of one or more energy inputs, combined with the potential for multiple energy outputs. Compared to traditional energy systems, HES provide additional operational flexibility so that high variability in both energy production and consumption levels can be absorbed more effectively. This is particularly important when including renewable energy sources, whose output levels are inherently variable, determined by nature. The specific HES configuration modeled in this paper include two energy inputs: a nuclear plant, and a series of wind turbines. In addition, the system produces two energy outputs: electricity and synthetic fuel. The models are verified through simulations of the individual components, and the system as a whole. The simulations are performed for a range of component sizes, operating conditions, and control schemes.
A Mathematical Model for Suppression Subtractive Hybridization
Gadgil, Chetan; Rink, Anette; Beattie, Craig
2002-01-01
Suppression subtractive hybridization (SSH) is frequently used to unearth differentially expressed genes on a whole-genome scale. Its versatility is based on combining cDNA library subtraction and normalization, which allows the isolation of sequences of varying degrees of abundance and differential expression. SSH is a complex process with many adjustable parameters that affect the outcome of gene isolation.We present a mathematical model of SSH based on DNA hybridization kinetics for assessing the effect of various parameters to facilitate its optimization. We derive an equation for the probability that a particular differentially expressed species is successfully isolated and use this to quantify the effect of the following parameters related to the cDNA sample: (a) mRNA abundance; (b) partial sequence complementarity to other species; and (3) degree of differential expression. We also evaluate the effect of parameters related to the process, including: (a) reaction times; and (b) extent of driver excess used in the two hybridization reactions. The optimum set of process parameters for successful isolation of differentially expressed species depends on transcript abundance. We show that the reaction conditions have a significant effect on the occurrence of false-positives and formulate strategies to isolate specific subsets of differentially expressed genes. We also quantify the effect of non-specific hybridization on the false-positive results and present strategies for spiking cDNA sequences to address this problem. PMID:18629052
Advanced Hybrid Modeling of Hall Thruster Plumes
2010-06-16
LVTF. A direct simulation Monte Carlo (DSMC) method3 is used to model collision dynamics, and a Particle-in-Cell ( PIC ) method4 is used to capture...cell ( PIC ) numerical methods on an axisymmetric grid.7 The code has been found to be effective in creating either time-averaged outputs of performance...here. The HPHall code performs an axisymmetric simulation, commonly referred to as “hybrid- PIC ,” treating the electrons via fluid approximation
Hybrid approaches to physiologic modeling and prediction
NASA Astrophysics Data System (ADS)
Olengü, Nicholas O.; Reifman, Jaques
2005-05-01
This paper explores how the accuracy of a first-principles physiological model can be enhanced by integrating data-driven, "black-box" models with the original model to form a "hybrid" model system. Both linear (autoregressive) and nonlinear (neural network) data-driven techniques are separately combined with a first-principles model to predict human body core temperature. Rectal core temperature data from nine volunteers, subject to four 30/10-minute cycles of moderate exercise/rest regimen in both CONTROL and HUMID environmental conditions, are used to develop and test the approach. The results show significant improvements in prediction accuracy, with average improvements of up to 30% for prediction horizons of 20 minutes. The models developed from one subject's data are also used in the prediction of another subject's core temperature. Initial results for this approach for a 20-minute horizon show no significant improvement over the first-principles model by itself.
A hybrid modeling approach for option pricing
NASA Astrophysics Data System (ADS)
Hajizadeh, Ehsan; Seifi, Abbas
2011-11-01
The complexity of option pricing has led many researchers to develop sophisticated models for such purposes. The commonly used Black-Scholes model suffers from a number of limitations. One of these limitations is the assumption that the underlying probability distribution is lognormal and this is so controversial. We propose a couple of hybrid models to reduce these limitations and enhance the ability of option pricing. The key input to option pricing model is volatility. In this paper, we use three popular GARCH type model for estimating volatility. Then, we develop two non-parametric models based on neural networks and neuro-fuzzy networks to price call options for S&P 500 index. We compare the results with those of Black-Scholes model and show that both neural network and neuro-fuzzy network models outperform Black-Scholes model. Furthermore, comparing the neural network and neuro-fuzzy approaches, we observe that for at-the-money options, neural network model performs better and for both in-the-money and an out-of-the money option, neuro-fuzzy model provides better results.
Fluid and hybrid models for streamers
NASA Astrophysics Data System (ADS)
Bonaventura, Zdeněk
2016-09-01
Streamers are contracted ionizing waves with self-generated field enhancement that propagate into a low-ionized medium exposed to high electric field leaving filamentary trails of plasma behind. The widely used model to study streamer dynamics is based on drift-diffusion equations for electrons and ions, assuming local field approximation, coupled with Poisson's equation. For problems where presence of energetic electrons become important a fluid approach needs to be extended by a particle model, accompanied also with Monte Carlo Collision technique, that takes care of motion of these electrons. A combined fluid-particle approach is used to study an influence of surface emission processes on a fast-pulsed dielectric barrier discharge in air at atmospheric pressure. It is found that fluid-only model predicts substantially faster reignition dynamics compared to coupled fluid-particle model. Furthermore, a hybrid model can be created in which the population of electrons is divided in the energy space into two distinct groups: (1) low energy `bulk' electrons that are treated with fluid model, and (2) high energy `beam' electrons, followed as particles. The hybrid model is then capable not only to deal with streamer discharges in laboratory conditions, but also allows us to study electron acceleration in streamer zone of lighting leaders. There, the production of fast electrons from streamers is investigated, since these (runaway) electrons act as seeds for the relativistic runaway electron avalanche (RREA) mechanism, important for high-energy atmospheric physics phenomena. Results suggest that high energy electrons effect the streamer propagation, namely the velocity, the peak electric field, and thus also the production rate of runaway electrons. This work has been supported by the Czech Science Foundation research project 15-04023S.
A Cause of Ahistorical Science Teaching: Use of Hybrid Models.
ERIC Educational Resources Information Center
Justi, Rosaria; Gilbert, John
1999-01-01
Presents eight historical consensus models for teaching chemical kinetics. Models put forth by teachers and textbooks in a Brazilian secondary classroom were analyzed and discussed and found to be hybrids of the historical models. The existence of hybrid models in science teaching is proposed as a new component in science teachers' training…
Hybrid2: The hybrid system simulation model, Version 1.0, user manual
Baring-Gould, E.I.
1996-06-01
In light of the large scale desire for energy in remote communities, especially in the developing world, the need for a detailed long term performance prediction model for hybrid power systems was seen. To meet these ends, engineers from the National Renewable Energy Laboratory (NREL) and the University of Massachusetts (UMass) have spent the last three years developing the Hybrid2 software. The Hybrid2 code provides a means to conduct long term, detailed simulations of the performance of a large array of hybrid power systems. This work acts as an introduction and users manual to the Hybrid2 software. The manual describes the Hybrid2 code, what is included with the software and instructs the user on the structure of the code. The manual also describes some of the major features of the Hybrid2 code as well as how to create projects and run hybrid system simulations. The Hybrid2 code test program is also discussed. Although every attempt has been made to make the Hybrid2 code easy to understand and use, this manual will allow many organizations to consider the long term advantages of using hybrid power systems instead of conventional petroleum based systems for remote power generation.
Hybrid Concurrent Constraint Simulation Models of Several Systems
NASA Technical Reports Server (NTRS)
Sweet, Adam
2003-01-01
This distribution contains several simulation models created for the hybrid simulation language, Hybrid Concurrent Constraint (HCC). An HCC model contains the information specified in the widely-accepted academic definition of a hybrid system: this includes expressions for the modes of the systems to be simulated and the differential equations that apply in each mode. These expressions are written in the HCC syntax. The models included here were created by either applying basic physical laws or implementing equations listed in previously published papers.
Gyrofluid-Gyrokinetic Hybrid Turbulence Model
NASA Astrophysics Data System (ADS)
Dorland, William; Mandell, Noah
2015-11-01
Gyrofluid models of tokamak turbulence are efficient compared to gyrokinetic models, in three senses. First, it is typically easier to develop one's intuition from fluid equations than kinetic equations. Second, because gyrofluid equations are only three-dimensional (instead of 5D or 6D), simulations with gyrofluid models require less memory than kinetic simulations and can therefore more easily fit on highly-optimized computing hardware, such as graphics processors. The third advantage is a result of the first two: one can develop and test ideas quickly with gyrofluid models. The disadvantage of gyrofluid models is their potential lack of physics fidelity. In this poster, we present our attempt to take full advantage of gyrofluid models, without sacrificing physics fidelity. Our approach is encapsulated in the Gryf-X code, which is an implementation of hybrid gyrofluid/gyrokinetic equations. The key improvements that we have brought to bear are: an improved understanding of the cascade of free energy simultaneously in k⊥ and v⊥ an improved model of zonal flow physics; and an implementation of the equations on modern heterogeneous computing platforms, both as a standalone simulation tool and as a component of TRINITY (a transport modeling code for tokamaks).
Hybrid Modeling Improves Health and Performance Monitoring
NASA Technical Reports Server (NTRS)
2007-01-01
Scientific Monitoring Inc. was awarded a Phase I Small Business Innovation Research (SBIR) project by NASA's Dryden Flight Research Center to create a new, simplified health-monitoring approach for flight vehicles and flight equipment. The project developed a hybrid physical model concept that provided a structured approach to simplifying complex design models for use in health monitoring, allowing the output or performance of the equipment to be compared to what the design models predicted, so that deterioration or impending failure could be detected before there would be an impact on the equipment's operational capability. Based on the original modeling technology, Scientific Monitoring released I-Trend, a commercial health- and performance-monitoring software product named for its intelligent trending, diagnostics, and prognostics capabilities, as part of the company's complete ICEMS (Intelligent Condition-based Equipment Management System) suite of monitoring and advanced alerting software. I-Trend uses the hybrid physical model to better characterize the nature of health or performance alarms that result in "no fault found" false alarms. Additionally, the use of physical principles helps I-Trend identify problems sooner. I-Trend technology is currently in use in several commercial aviation programs, and the U.S. Air Force recently tapped Scientific Monitoring to develop next-generation engine health-management software for monitoring its fleet of jet engines. Scientific Monitoring has continued the original NASA work, this time under a Phase III SBIR contract with a joint NASA-Pratt & Whitney aviation security program on propulsion-controlled aircraft under missile-damaged aircraft conditions.
A Hybrid Teaching and Learning Model
NASA Astrophysics Data System (ADS)
Juhary, Jowati Binti
This paper aims at analysing the needs for a specific teaching and learning model for the National Defence University of Malaysia (NDUM). The main argument is that whether there are differences between teaching and learning for academic component versus military component at the university. It is further argued that in order to achieve excellence, there should be one teaching and learning culture. Data were collected through interviews with military cadets. It is found that there are variations of teaching and learning strategies for academic courses, in comparison to a dominant teaching and learning style for military courses. Thus, in the interest of delivering quality education and training for students at the university, the paper argues that possibly a hybrid model for teaching and learning is fundamental in order to generate a one culture of academic and military excellence for the NDUM.
A Hybrid Tsunami Risk Model for Japan
NASA Astrophysics Data System (ADS)
Haseemkunju, A. V.; Smith, D. F.; Khater, M.; Khemici, O.; Betov, B.; Scott, J.
2014-12-01
Around the margins of the Pacific Ocean, denser oceanic plates slipping under continental plates cause subduction earthquakes generating large tsunami waves. The subducting Pacific and Philippine Sea plates create damaging interplate earthquakes followed by huge tsunami waves. It was a rupture of the Japan Trench subduction zone (JTSZ) and the resultant M9.0 Tohoku-Oki earthquake that caused the unprecedented tsunami along the Pacific coast of Japan on March 11, 2011. EQECAT's Japan Earthquake model is a fully probabilistic model which includes a seismo-tectonic model describing the geometries, magnitudes, and frequencies of all potential earthquake events; a ground motion model; and a tsunami model. Within the much larger set of all modeled earthquake events, fault rupture parameters for about 24000 stochastic and 25 historical tsunamigenic earthquake events are defined to simulate tsunami footprints using the numerical tsunami model COMCOT. A hybrid approach using COMCOT simulated tsunami waves is used to generate inundation footprints, including the impact of tides and flood defenses. Modeled tsunami waves of major historical events are validated against observed data. Modeled tsunami flood depths on 30 m grids together with tsunami vulnerability and financial models are then used to estimate insured loss in Japan from the 2011 tsunami. The primary direct report of damage from the 2011 tsunami is in terms of the number of buildings damaged by municipality in the tsunami affected area. Modeled loss in Japan from the 2011 tsunami is proportional to the number of buildings damaged. A 1000-year return period map of tsunami waves shows high hazard along the west coast of southern Honshu, on the Pacific coast of Shikoku, and on the east coast of Kyushu, primarily associated with major earthquake events on the Nankai Trough subduction zone (NTSZ). The highest tsunami hazard of more than 20m is seen on the Sanriku coast in northern Honshu, associated with the JTSZ.
Modeling material interfaces with hybrid adhesion method
Brown, Nicholas Taylor; Qu, Jianmin; Martinez, Enrique
2017-01-27
A molecular dynamics simulation approach is presented to approximate layered material structures using discrete interatomic potentials through classical mechanics and the underlying principles of quantum mechanics. This method isolates the energetic contributions of the system into two pure material layers and an interfacial region used to simulate the adhesive properties of the diffused interface. The strength relationship of the adhesion contribution is calculated through small-scale separation calculations and applied to the molecular surfaces through an inter-layer bond criterion. By segregating the contributions into three regions and accounting for the interfacial excess energies through the adhesive surface bonds, it is possiblemore » to model each material with an independent potential while maintaining an acceptable level of accuracy in the calculation of mechanical properties. This method is intended for the atomistic study of the delamination mechanics, typically observed in thin-film applications. Therefore, the work presented in this paper focuses on mechanical tensile behaviors, with observations in the elastic modulus and the delamination failure mode. To introduce the hybrid adhesion method, we apply the approach to an ideal bulk copper sample, where an interface is created by disassociating the force potential in the middle of the structure. Various mechanical behaviors are compared to a standard EAM control model to demonstrate the adequacy of this approach in a simple setting. In addition, we demonstrate the robustness of this approach by applying it on (1) a Cu-Cu2O interface with interactions between two atom types, and (2) an Al-Cu interface with two dissimilar FCC lattices. These additional examples are verified against EAM and COMB control models to demonstrate the accurate simulation of failure through delamination, and the formation and propagation of dislocations under loads. Finally, the results conclude that by modeling the energy
A range extender hybrid electric vehicle dynamic model
Powell, B.K.; Pilutti, T.E.
1994-12-31
This paper describes a dynamic model possessing the key system components of a Range Extender Hybrid Electric Vehicle. The model is suitable for dynamic analysis, control law synthesis, and prototype simulation.
Theoretical aspects of hybrid chiral bag models
NASA Astrophysics Data System (ADS)
Mulders, P. J.
1984-09-01
In hybrid chiral bag models (HCBM's) the quarks are the source for the pion field outside the bag. If we want to solve this model with a classical external soliton solution and quantized fermions, it is necessary to evaluate the vacuum expectation values (VEV's) of those operators that contain fermion fields and appear in the boundary conditions. When the external solution is the so-called hedgehog solution, π-->(r-->,t)=fπθ(r)r^, the relevant VEV is i16π<0 | d2s[ψ―,(τ-->.r^)γ5exp(iτ-->.r^γ5θ)ψ] | 0>=2θ16πη+C0(θ)R, where η is a cutoff parameter (η-->0). To obtain this result we have used a multiple-reflection expansion of the Green's function, while C0(θ) is evaluated numerically. We discuss the infinite contribution in the above VEV, and show that 4πC0(θ)R is precisely the derivative of the Casimir energy with respect to θ. We also discuss some solutions of the HCBM for bag radii varying from 0 to ∞.
SCAN-based hybrid and double-hybrid density functionals from models without fitted parameters
NASA Astrophysics Data System (ADS)
Hui, Kerwin; Chai, Jeng-Da
2016-01-01
By incorporating the nonempirical strongly constrained and appropriately normed (SCAN) semilocal density functional [J. Sun, A. Ruzsinszky, and J. P. Perdew, Phys. Rev. Lett. 115, 036402 (2015)] in the underlying expression of four existing hybrid and double-hybrid models, we propose one hybrid (SCAN0) and three double-hybrid (SCAN0-DH, SCAN-QIDH, and SCAN0-2) density functionals, which are free from any fitted parameters. The SCAN-based double-hybrid functionals consistently outperform their parent SCAN semilocal functional for self-interaction problems and noncovalent interactions. In particular, SCAN0-2, which includes about 79% of Hartree-Fock exchange and 50% of second-order Møller-Plesset correlation, is shown to be reliably accurate for a very diverse range of applications, such as thermochemistry, kinetics, noncovalent interactions, and self-interaction problems.
Intensive Scheduling: A Hybrid Model for the Junior High.
ERIC Educational Resources Information Center
McGorry, Eugene; McGorry, Susan Y.
1998-01-01
Discusses Intensive Scheduling as an approach to learning. Describes how educators in the Pocono Mountain School District in Pennsylvania searched for a more effective way to schedule classes. Describes how the junior high administration and teachers piloted a hybrid modified intensive schedule. Presents student opinions about the hybrid model,…
The Hybrid Model for Implementing the Continuing Education Mission.
ERIC Educational Resources Information Center
Hentschel, Doe
1991-01-01
Models through which higher education provides outreach include centralized, decentralized, and hybrid. The latter, academically integrated and administratively decentralized, meshes continuing education programs with the academic mission while maximizing cost effectiveness. (SK)
A Structural Model Decomposition Framework for Hybrid Systems Diagnosis
NASA Technical Reports Server (NTRS)
Daigle, Matthew; Bregon, Anibal; Roychoudhury, Indranil
2015-01-01
Nowadays, a large number of practical systems in aerospace and industrial environments are best represented as hybrid systems that consist of discrete modes of behavior, each defined by a set of continuous dynamics. These hybrid dynamics make the on-line fault diagnosis task very challenging. In this work, we present a new modeling and diagnosis framework for hybrid systems. Models are composed from sets of user-defined components using a compositional modeling approach. Submodels for residual generation are then generated for a given mode, and reconfigured efficiently when the mode changes. Efficient reconfiguration is established by exploiting causality information within the hybrid system models. The submodels can then be used for fault diagnosis based on residual generation and analysis. We demonstrate the efficient causality reassignment, submodel reconfiguration, and residual generation for fault diagnosis using an electrical circuit case study.
Nuclear Hybrid Energy System Modeling: RELAP5 Dynamic Coupling Capabilities
Piyush Sabharwall; Nolan Anderson; Haihua Zhao; Shannon Bragg-Sitton; George Mesina
2012-09-01
The nuclear hybrid energy systems (NHES) research team is currently developing a dynamic simulation of an integrated hybrid energy system. A detailed simulation of proposed NHES architectures will allow initial computational demonstration of a tightly coupled NHES to identify key reactor subsystem requirements, identify candidate reactor technologies for a hybrid system, and identify key challenges to operation of the coupled system. This work will provide a baseline for later coupling of design-specific reactor models through industry collaboration. The modeling capability addressed in this report focuses on the reactor subsystem simulation.
Van Kirk, Robert W; Battle, Laurie; Schrader, William C
2010-03-01
Native salmonid fish have been displaced worldwide by nonnatives through hybridization, competition, and predation, but the dynamics of these factors are poorly understood. We apply stochastic Lotka-Volterra models to the displacement of cutthroat trout by rainbow/hybrid trout in the Snake River, Idaho, USA. Cutthroat trout are susceptible to hybridization in the river but are reproductively isolated in tributaries via removal of migratory rainbow/hybrid spawners at weirs. Based on information-theoretic analysis, population data provide evidence that hybridization was the primary mechanism for cutthroat trout displacement in the first 17 years of the invasion. However, under some parameter values, the data provide evidence for a model in which interaction occurs among fish from both river and tributary subpopulations. This situation is likely to occur when tributary-spawned cutthroat trout out-migrate to the river as fry. The resulting competition with rainbow/hybrid trout can result in the extinction of cutthroat trout even when reproductive segregation is maintained.
Multimedia Learning Design Pedagogy: A Hybrid Learning Model
ERIC Educational Resources Information Center
Tsoi, Mun Fie; Goh, Ngoh Khang; Chia, Lian Sai
2005-01-01
This paper provides insights on a hybrid learning model for multimedia learning design conceptualized from the Piagetian science learning cycle model and the Kolb's experiential learning model. This model represents learning as a cognitive process in a cycle of four phases, namely, Translating, Sculpting, Operationalizing, and Integrating and is…
The development of a mathematical model of a hybrid airship
NASA Astrophysics Data System (ADS)
Abdul Ghaffar, Alia Farhana
The mathematical model of a winged hybrid airship is developed for the analysis of its dynamic stability characteristics. A full nonlinear equation of motion that describes the dynamics of the hybrid airship is determined and for completeness, some of the components in the equations are estimated using the appropriate methods that has been established and used in the past. Adequate assumptions are made in order to apply any relevant computation and estimation methods. While this hybrid airship design is unique, its modeling and stability analysis were done according to the typical procedure of conventional airships and aircrafts. All computations pertaining to the hybrid airship's equation of motion are carried out and any issues related to the integration of the wing to the conventional airship design are discussed in this thesis. The design of the hybrid airship is also slightly modified to suit the demanding requirement of a complete and feasible mathematical model. Then, linearization is performed under a chosen trim condition, and eigenvalue analysis is carried out to determine the general dynamic stability characteristics of the winged hybrid airship. The result shows that the winged hybrid airship possesses dynamic instability in longitudinal pitch motion and lateral-directional slow roll motion. This is due to the strong coupling between the aerostatic lift from the buoyant gas and aerodynamic lift from the wing.
Hybrid modeling of xanthan gum bioproduction in batch bioreactor.
Zabot, Giovani L; Mecca, Jaqueline; Mesomo, Michele; Silva, Marceli F; Prá, Valéria Dal; de Oliveira, Débora; Oliveira, J Vladimir; Castilhos, Fernanda; Treichel, Helen; Mazutti, Marcio A
2011-10-01
This work is focused on hybrid modeling of xanthan gum bioproduction process by Xanthomonas campestris pv. mangiferaeindicae. Experiments were carried out to evaluate the effects of stirred speed and superficial gas velocity on the kinetics of cell growth, lactose consumption and xanthan gum production in a batch bioreactor using cheese whey as substrate. A hybrid model was employed to simulate the bio-process making use of an artificial neural network (ANN) as a kinetic parameter estimator for the phenomenological model. The hybrid modeling of the process provided a satisfactory fitting quality of the experimental data, since this approach makes possible the incorporation of the effects of operational variables on model parameters. The applicability of the validated model was investigated, using the model as a process simulator to evaluate the effects of initial cell and lactose concentration in the xanthan gum production.
Pedestrian navigation data modeling for hybrid travel patterns
NASA Astrophysics Data System (ADS)
Zheng, Jianghua; Tao, Jianwei; Ding, Jianli; Abuliz, Abudukim; Xiang, Hanyu
2008-10-01
At present, navigation data models, such as GDF4.0, KIWI, SDAL and WI 19134, didn't pay attention to form pedestrian transport infrastructure into their models. With the development of navigation, pedestrian navigation has become a hot topic. The research team put forward their pilot research on pedestrian data modeling for hybrid travel patters, mainly including subway, bus and feet. Pedestrian road network modeling was made. Based on this, it carried out the discussion on multi-level navigation data modeling of hybrid travel patterns. It also gave algorithm suggestion to operate the optimal route computing more efficient. The future work is just to focus on demonstrate the algorithm.
Strategies for Energy Efficient Resource Management of Hybrid Programming Models
Li, Dong; Supinski, Bronis de; Schulz, Martin; Nikolopoulos, Dimitrios S; Cameron, Kirk W.
2013-01-01
Many scientific applications are programmed using hybrid programming models that use both message-passing and shared-memory, due to the increasing prevalence of large-scale systems with multicore, multisocket nodes. Previous work has shown that energy efficiency can be improved using software-controlled execution schemes that consider both the programming model and the power-aware execution capabilities of the system. However, such approaches have focused on identifying optimal resource utilization for one programming model, either shared-memory or message-passing, in isolation. The potential solution space, thus the challenge, increases substantially when optimizing hybrid models since the possible resource configurations increase exponentially. Nonetheless, with the accelerating adoption of hybrid programming models, we increasingly need improved energy efficiency in hybrid parallel applications on large-scale systems. In this work, we present new software-controlled execution schemes that consider the effects of dynamic concurrency throttling (DCT) and dynamic voltage and frequency scaling (DVFS) in the context of hybrid programming models. Specifically, we present predictive models and novel algorithms based on statistical analysis that anticipate application power and time requirements under different concurrency and frequency configurations. We apply our models and methods to the NPB MZ benchmarks and selected applications from the ASC Sequoia codes. Overall, we achieve substantial energy savings (8.74% on average and up to 13.8%) with some performance gain (up to 7.5%) or negligible performance loss.
Exact energy conservation in hybrid meshless model/code
NASA Astrophysics Data System (ADS)
Galkin, Sergei A.
2008-11-01
Energy conservation is an important issue for both PIC and hybrid models. In hybrid codes the ions are treated kinetically and the electrons are described as a massless charge-neutralizing fluid. Our recently developed Particle-In-Cloud-Of-Points (PICOP) approach [1], which uses an adaptive meshless technique to compute electromagnetic fields on a cloud of computational points, is applied to a hybrid model. An exact energy conservation numerical scheme, which describes the interaction between geometrical space, where the electromagnetic fields are computed, and particle/velocity space, is presented. Having being utilized in a new PICOP hybrid code, the algorithm had demonstrated accurate energy conservation in the numerical simulation of two counter streaming plasma beams instability. [1] S. A. Galkin, B. P. Cluggish, J. S. Kim, S. Yu. Medvedev ``Advansed PICOP Algorithm with Adaptive Meshless Field Solver'', Published in the IEEE PPPS/ICOP 2007 Conference proceedings, pp. 1445-1448, Albuquerque, New Mexico, June 17-22, 2007.
A Hybridization Model for the Plasmon Response of Complex Nanostructures
NASA Astrophysics Data System (ADS)
Prodan, E.; Radloff, C.; Halas, N. J.; Nordlander, P.
2003-10-01
We present a simple and intuitive picture, an electromagnetic analog of molecular orbital theory, that describes the plasmon response of complex nanostructures of arbitrary shape. Our model can be understood as the interaction or ``hybridization'' of elementary plasmons supported by nanostructures of elementary geometries. As an example, the approach is applied to the important case of a four-layer concentric nanoshell, where the hybridization of the plasmons of the inner and outer nanoshells determines the resonant frequencies of the multilayer nanostructure.
A hybridization model for the plasmon response of complex nanostructures.
Prodan, E; Radloff, C; Halas, N J; Nordlander, P
2003-10-17
We present a simple and intuitive picture, an electromagnetic analog of molecular orbital theory, that describes the plasmon response of complex nanostructures of arbitrary shape. Our model can be understood as the interaction or "hybridization" of elementary plasmons supported by nanostructures of elementary geometries. As an example, the approach is applied to the important case of a four-layer concentric nanoshell, where the hybridization of the plasmons of the inner and outer nanoshells determines the resonant frequencies of the multilayer nanostructure.
Nonlinear lower hybrid modeling in tokamak plasmas
Napoli, F.; Schettini, G.; Castaldo, C.; Cesario, R.
2014-02-12
We present here new results concerning the nonlinear mechanism underlying the observed spectral broadening produced by parametric instabilities occurring at the edge of tokamak plasmas in present day LHCD (lower hybrid current drive) experiments. Low frequency (LF) ion-sound evanescent modes (quasi-modes) are the main parametric decay channel which drives a nonlinear mode coupling of lower hybrid (LH) waves. The spectrum of the LF fluctuations is calculated here considering the beating of the launched LH wave at the radiofrequency (RF) operating line frequency (pump wave) with the noisy background of the RF power generator. This spectrum is calculated in the frame of the kinetic theory, following a perturbative approach. Numerical solutions of the nonlinear LH wave equation show the evolution of the nonlinear mode coupling in condition of a finite depletion of the pump power. The role of the presence of heavy ions in a Deuterium plasma in mitigating the nonlinear effects is analyzed.
Mechanisms Underlying Mammalian Hybrid Sterility in Two Feline Interspecies Models
Davis, Brian W.; Seabury, Christopher M.; Brashear, Wesley A.; Li, Gang; Roelke-Parker, Melody; Murphy, William J.
2015-01-01
The phenomenon of male sterility in interspecies hybrids has been observed for over a century, however, few genes influencing this recurrent phenotype have been identified. Genetic investigations have been primarily limited to a small number of model organisms, thus limiting our understanding of the underlying molecular basis of this well-documented “rule of speciation.” We utilized two interspecies hybrid cat breeds in a genome-wide association study employing the Illumina 63 K single-nucleotide polymorphism array. Collectively, we identified eight autosomal genes/gene regions underlying associations with hybrid male sterility (HMS) involved in the function of the blood-testis barrier, gamete structural development, and transcriptional regulation. We also identified several candidate hybrid sterility regions on the X chromosome, with most residing in close proximity to complex duplicated regions. Differential gene expression analyses revealed significant chromosome-wide upregulation of X chromosome transcripts in testes of sterile hybrids, which were enriched for genes involved in chromatin regulation of gene expression. Our expression results parallel those reported in Mus hybrids, supporting the “Large X-Effect” in mammalian HMS and the potential epigenetic basis for this phenomenon. These results support the value of the interspecies feline model as a powerful tool for comparison to rodent models of HMS, demonstrating unique aspects and potential commonalities that underpin mammalian reproductive isolation. PMID:26006188
Mechanisms Underlying Mammalian Hybrid Sterility in Two Feline Interspecies Models.
Davis, Brian W; Seabury, Christopher M; Brashear, Wesley A; Li, Gang; Roelke-Parker, Melody; Murphy, William J
2015-10-01
The phenomenon of male sterility in interspecies hybrids has been observed for over a century, however, few genes influencing this recurrent phenotype have been identified. Genetic investigations have been primarily limited to a small number of model organisms, thus limiting our understanding of the underlying molecular basis of this well-documented "rule of speciation." We utilized two interspecies hybrid cat breeds in a genome-wide association study employing the Illumina 63 K single-nucleotide polymorphism array. Collectively, we identified eight autosomal genes/gene regions underlying associations with hybrid male sterility (HMS) involved in the function of the blood-testis barrier, gamete structural development, and transcriptional regulation. We also identified several candidate hybrid sterility regions on the X chromosome, with most residing in close proximity to complex duplicated regions. Differential gene expression analyses revealed significant chromosome-wide upregulation of X chromosome transcripts in testes of sterile hybrids, which were enriched for genes involved in chromatin regulation of gene expression. Our expression results parallel those reported in Mus hybrids, supporting the "Large X-Effect" in mammalian HMS and the potential epigenetic basis for this phenomenon. These results support the value of the interspecies feline model as a powerful tool for comparison to rodent models of HMS, demonstrating unique aspects and potential commonalities that underpin mammalian reproductive isolation.
Fitzpatrick, B M
2008-01-01
Speciation may result from 'complementary' genetic differences that cause dysfunction when brought together in hybrids despite having no deleterious effects within pure species genomes. The theory of complementary genes, independently proposed by Dobzhansky and Muller, yields specific predictions about the genetics of hybrid fitness. Here, I show how alternative models of hybrid dysfunction can be compared using a simple multivariate analysis of hybrid indices calculated from molecular markers. I use the approach to fit models of hybrid dysfunction to swimming performance in hybrid tiger salamander larvae. Poor burst-speed performance is a dysfunction suggesting low vigour and could translate directly into low survival. My analyses show that the Dobzhansky-Muller model fits these data better than heterozygote disadvantage. The approach demonstrated here can be applied to a broad array of nonmodel species, potentially leading to important generalizations about the genetics of hybrid dysfunction.
A hybrid agent-based approach for modeling microbiological systems.
Guo, Zaiyi; Sloot, Peter M A; Tay, Joc Cing
2008-11-21
Models for systems biology commonly adopt Differential Equations or Agent-Based modeling approaches for simulating the processes as a whole. Models based on differential equations presuppose phenomenological intracellular behavioral mechanisms, while models based on Multi-Agent approach often use directly translated, and quantitatively less precise if-then logical rule constructs. We propose an extendible systems model based on a hybrid agent-based approach where biological cells are modeled as individuals (agents) while molecules are represented by quantities. This hybridization in entity representation entails a combined modeling strategy with agent-based behavioral rules and differential equations, thereby balancing the requirements of extendible model granularity with computational tractability. We demonstrate the efficacy of this approach with models of chemotaxis involving an assay of 10(3) cells and 1.2x10(6) molecules. The model produces cell migration patterns that are comparable to laboratory observations.
Hybrid Models and Biological Model Reduction with PyDSTool
Clewley, Robert
2012-01-01
The PyDSTool software environment is designed to develop, simulate, and analyze dynamical systems models, particularly for biological applications. Unlike the engineering application focus and graphical specification environments of most general purpose simulation tools, PyDSTool provides a programmatic environment well suited to exploratory data- and hypothesis-driven biological modeling problems. In this work, we show how the environment facilitates the application of hybrid dynamical modeling to the reverse engineering of complex biophysical dynamics; in this case, of an excitable membrane. The example demonstrates how the software provides novel tools that support the inference and validation of mechanistic hypotheses and the inclusion of data constraints in both quantitative and qualitative ways. The biophysical application is broadly relevant to models in the biosciences. The open source and platform-independent PyDSTool package is freely available under the BSD license from http://sourceforge.net/projects/pydstool/. The hosting service provides links to documentation and online forums for user support. PMID:22912566
Diagnosing Hybrid Systems: a Bayesian Model Selection Approach
NASA Technical Reports Server (NTRS)
McIlraith, Sheila A.
2005-01-01
In this paper we examine the problem of monitoring and diagnosing noisy complex dynamical systems that are modeled as hybrid systems-models of continuous behavior, interleaved by discrete transitions. In particular, we examine continuous systems with embedded supervisory controllers that experience abrupt, partial or full failure of component devices. Building on our previous work in this area (MBCG99;MBCG00), our specific focus in this paper ins on the mathematical formulation of the hybrid monitoring and diagnosis task as a Bayesian model tracking algorithm. The nonlinear dynamics of many hybrid systems present challenges to probabilistic tracking. Further, probabilistic tracking of a system for the purposes of diagnosis is problematic because the models of the system corresponding to failure modes are numerous and generally very unlikely. To focus tracking on these unlikely models and to reduce the number of potential models under consideration, we exploit logic-based techniques for qualitative model-based diagnosis to conjecture a limited initial set of consistent candidate models. In this paper we discuss alternative tracking techniques that are relevant to different classes of hybrid systems, focusing specifically on a method for tracking multiple models of nonlinear behavior simultaneously using factored sampling and conditional density propagation. To illustrate and motivate the approach described in this paper we examine the problem of monitoring and diganosing NASA's Sprint AERCam, a small spherical robotic camera unit with 12 thrusters that enable both linear and rotational motion.
Runoff prediction using an integrated hybrid modelling scheme
NASA Astrophysics Data System (ADS)
Remesan, Renji; Shamim, Muhammad Ali; Han, Dawei; Mathew, Jimson
2009-06-01
SummaryRainfall runoff is a very complicated process due to its nonlinear and multidimensional dynamics, and hence difficult to model. There are several options for a modeller to consider, for example: the type of input data to be used, the length of model calibration (training) data and whether or not the input data be treated as signals with different frequency bands so that they can be modelled separately. This paper describes a new hybrid modelling scheme to answer the above mentioned questions. The proposed methodology is based on a hybrid model integrating wavelet transformation, a modelling engine (Artificial Neural Network) and the Gamma Test. First, the Gamma Test is used to decide the required input data dimensions and its length. Second, the wavelet transformation decomposes the input signals into different frequency bands. Finally, a modelling engine (ANN in this study) is used to model the decomposed signals separately. The proposed scheme was tested using the Brue catchment, Southwest England, as a case study and has produced very positive results. The hybrid model outperforms all other models tested. This study has a wider implication in the hydrological modelling field since its general framework could be applied to other model combinations (e.g., model engine could be Support Vector Machines, neuro-fuzzy systems, or even a conceptual model. The signal decomposition could be carried out by Fourier transformation).
A new adaptive hybrid electromagnetic damper: modelling, optimization, and experiment
NASA Astrophysics Data System (ADS)
Asadi, Ehsan; Ribeiro, Roberto; Behrad Khamesee, Mir; Khajepour, Amir
2015-07-01
This paper presents the development of a new electromagnetic hybrid damper which provides regenerative adaptive damping force for various applications. Recently, the introduction of electromagnetic technologies to the damping systems has provided researchers with new opportunities for the realization of adaptive semi-active damping systems with the added benefit of energy recovery. In this research, a hybrid electromagnetic damper is proposed. The hybrid damper is configured to operate with viscous and electromagnetic subsystems. The viscous medium provides a bias and fail-safe damping force while the electromagnetic component adds adaptability and the capacity for regeneration to the hybrid design. The electromagnetic component is modeled and analyzed using analytical (lumped equivalent magnetic circuit) and electromagnetic finite element method (FEM) (COMSOL® software package) approaches. By implementing both modeling approaches, an optimization for the geometric aspects of the electromagnetic subsystem is obtained. Based on the proposed electromagnetic hybrid damping concept and the preliminary optimization solution, a prototype is designed and fabricated. A good agreement is observed between the experimental and FEM results for the magnetic field distribution and electromagnetic damping forces. These results validate the accuracy of the modeling approach and the preliminary optimization solution. An analytical model is also presented for viscous damping force, and is compared with experimental results The results show that the damper is able to produce damping coefficients of 1300 and 0-238 N s m-1 through the viscous and electromagnetic components, respectively.
Nuclear Hybrid Energy Systems FY16 Modeling Efforts at ORNL
Cetiner, Sacit M.; Greenwood, Michael Scott; Harrison, Thomas J.; Qualls, A. L.; Guler Yigitoglu, Askin; Fugate, David W.
2016-09-01
A nuclear hybrid system uses a nuclear reactor as the basic power generation unit. The power generated by the nuclear reactor is utilized by one or more power customers as either thermal power, electrical power, or both. In general, a nuclear hybrid system will couple the nuclear reactor to at least one thermal power user in addition to the power conversion system. The definition and architecture of a particular nuclear hybrid system is flexible depending on local markets needs and opportunities. For example, locations in need of potable water may be best served by coupling a desalination plant to the nuclear system. Similarly, an area near oil refineries may have a need for emission free hydrogen production. A nuclear hybrid system expands the nuclear power plant from its more familiar central power station role by diversifying its immediately and directly connected customer base. The definition, design, analysis, and optimization work currently performed with respect to the nuclear hybrid systems represents the work of three national laboratories. Idaho National Laboratory (INL) is the lead lab working with Argonne National Laboratory (ANL) and Oak Ridge National Laboratory. Each laboratory is providing modeling and simulation expertise for the integration of the hybrid system.
A Lower Hybrid Fluid Model and Asymptotic Solutions
NASA Astrophysics Data System (ADS)
Wang, Xiaogang
2016-10-01
Hall MHD is for ion dynamics with a zero mass electron fluid. EMHD is for electron dynamics with fixed (infinity mass) ions. Also, other approximations such as electron incompressibility and low frequency appraisal (by ignoring the displacement current) have limited the application of EMHD. We then introduce a ``Lower Hybrid Fluid'' model by keeping the higher order mass ratio terms in the two-fluid model to investigate the problems in a hybrid scale range between the electron skin depth and the ion inertial length.
Verification of biological models with Timed Hybrid Petri Nets
NASA Astrophysics Data System (ADS)
Troncale, S.; Comet, J.-P.; Bernot, G.
2007-11-01
The formalism of Hybrid Functional Petri Nets (HFPN) has proved its convenience for simulating biological systems. The drawback of the noticeable expressiveness of HFPN is the difficulty to perform formal verifications of dynamical properties. In this article, we propose a model-checking procedure for Timed Hybrid Petri Nets (THPN), a sub-class of HFPN. This procedure is based on the translation of the THPN model and of the studied property into real-time automata. It is applied to a sub-network involved in amphibian metamorphosis.
Modeling of hybrid vehicle fuel economy and fuel engine efficiency
NASA Astrophysics Data System (ADS)
Wu, Wei
"Near-CV" (i.e., near-conventional vehicle) hybrid vehicles, with an internal combustion engine, and a supplementary storage with low-weight, low-energy but high-power capacity, are analyzed. This design avoids the shortcoming of the "near-EV" and the "dual-mode" hybrid vehicles that need a large energy storage system (in terms of energy capacity and weight). The small storage is used to optimize engine energy management and can provide power when needed. The energy advantage of the "near-CV" design is to reduce reliance on the engine at low power, to enable regenerative braking, and to provide good performance with a small engine. The fuel consumption of internal combustion engines, which might be applied to hybrid vehicles, is analyzed by building simple analytical models that reflect the engines' energy loss characteristics. Both diesel and gasoline engines are modeled. The simple analytical models describe engine fuel consumption at any speed and load point by describing the engine's indicated efficiency and friction. The engine's indicated efficiency and heat loss are described in terms of several easy-to-obtain engine parameters, e.g., compression ratio, displacement, bore and stroke. Engine friction is described in terms of parameters obtained by fitting available fuel measurements on several diesel and spark-ignition engines. The engine models developed are shown to conform closely to experimental fuel consumption and motored friction data. A model of the energy use of "near-CV" hybrid vehicles with different storage mechanism is created, based on simple algebraic description of the components. With powertrain downsizing and hybridization, a "near-CV" hybrid vehicle can obtain a factor of approximately two in overall fuel efficiency (mpg) improvement, without considering reductions in the vehicle load.
Energy-efficient container handling using hybrid model predictive control
NASA Astrophysics Data System (ADS)
Xin, Jianbin; Negenborn, Rudy R.; Lodewijks, Gabriel
2015-11-01
The performance of container terminals needs to be improved to adapt the growth of containers while maintaining sustainability. This paper provides a methodology for determining the trajectory of three key interacting machines for carrying out the so-called bay handling task, involving transporting containers between a vessel and the stacking area in an automated container terminal. The behaviours of the interacting machines are modelled as a collection of interconnected hybrid systems. Hybrid model predictive control (MPC) is proposed to achieve optimal performance, balancing the handling capacity and energy consumption. The underlying control problem is hereby formulated as a mixed-integer linear programming problem. Simulation studies illustrate that a higher penalty on energy consumption indeed leads to improved sustainability using less energy. Moreover, simulations illustrate how the proposed energy-efficient hybrid MPC controller performs under different types of uncertainties.
Battery thermal models for hybrid vehicle simulations
NASA Astrophysics Data System (ADS)
Pesaran, Ahmad A.
This paper summarizes battery thermal modeling capabilities for: (1) an advanced vehicle simulator (ADVISOR); and (2) battery module and pack thermal design. The National Renewable Energy Laboratory's (NREL's) ADVISOR is developed in the Matlab/Simulink environment. There are several battery models in ADVISOR for various chemistry types. Each one of these models requires a thermal model to predict the temperature change that could affect battery performance parameters, such as resistance, capacity and state of charges. A lumped capacitance battery thermal model in the Matlab/Simulink environment was developed that included the ADVISOR battery performance models. For thermal evaluation and design of battery modules and packs, NREL has been using various computer aided engineering tools including commercial finite element analysis software. This paper will discuss the thermal ADVISOR battery model and its results, along with the results of finite element modeling that were presented at the workshop on "Development of Advanced Battery Engineering Models" in August 2001.
Hybrid Scheduling Model for Independent Grid Tasks
Shanthini, J.; Kalaikumaran, T.; Karthik, S.
2015-01-01
Grid computing facilitates the resource sharing through the administrative domains which are geographically distributed. Scheduling in a distributed heterogeneous environment is intrinsically very hard because of the heterogeneous nature of resource collection. Makespan and tardiness are two different measures of scheduling, and many of the previous researches concentrated much on reduction of makespan, which measures the machine utilization. In this paper, we propose a hybrid scheduling algorithm for scheduling independent grid tasks with the objective of reducing total weighted tardiness of grid tasks. Tardiness is to measure the due date performance, which has a direct impact on cost for executing the jobs. In this paper we propose BG_ATC algorithm which is a combination of best gap (BG) search and Apparent Tardiness Cost (ATC) indexing algorithm. Furthermore, we implemented these two algorithms in two different phases of the scheduling process. In addition to that, the comparison was made on results with various benchmark algorithms and the experimental results show that our algorithm outperforms the benchmark algorithms. PMID:26543897
New Models of Hybrid Leadership in Global Higher Education
ERIC Educational Resources Information Center
Tonini, Donna C.; Burbules, Nicholas C.; Gunsalus, C. K.
2016-01-01
This manuscript highlights the development of a leadership preparation program known as the Nanyang Technological University Leadership Academy (NTULA), exploring the leadership challenges unique to a university undergoing rapid growth in a highly multicultural context, and the hybrid model of leadership it developed in response to globalization.…
Incorporating RTI in a Hybrid Model of Reading Disability
ERIC Educational Resources Information Center
Spencer, Mercedes; Wagner, Richard K.; Schatschneider, Christopher; Quinn, Jamie M.; Lopez, Danielle; Petscher, Yaacov
2014-01-01
The present study seeks to evaluate a hybrid model of identification that incorporates response to instruction and intervention (RTI) as one of the key symptoms of reading disability. The 1-year stability of alternative operational definitions of reading disability was examined in a large-scale sample of students who were followed longitudinally…
A New Model for Baryogenesis through Hybrid Inflation
Delepine, D.; Prieto, C. Martinez; Lopez, L. A. Urena
2009-04-17
We propose a hybrid inflation model with a complex waterfall field which contains an interaction term that breaks the U(1) global symmetry associated to the waterfall field charge. The asymmetric evolution of the real and imaginary parts of the complex field during the phase transition at the end of inflation translates into a charge asymmetry.
Hybrid mice as genetic models of high alcohol consumption.
Blednov, Y A; Ozburn, A R; Walker, D; Ahmed, S; Belknap, J K; Harris, R A
2010-01-01
We showed that F1 hybrid genotypes may provide a broader variety of ethanol drinking phenotypes than the inbred progenitor strains used to create the hybrids (Blednov et al. in Alcohol Clin Exp Res 29:1949-1958, 2005). To extend this work, we characterized alcohol consumption as well as intake of other tastants (saccharin, quinine and sodium chloride) in five inbred strains of mice (FVB, SJL, B6, BUB, NZB) and in their reciprocal F1 hybrids with B6 (FVBxB6; B6xFVB; NZBxB6; B6xNZB; BUBxB6; B6xBUB; SJLxB6; B6xSJL). We also compared ethanol intake in these mice for several concentrations before and after two periods of abstinence. F1 hybrid mice derived from the crosses of B6 and FVB and also B6 and SJL drank higher levels of ethanol than their progenitor strains, demonstrating overdominance for two-bottle choice drinking test. The B6 and NZB hybrid showed additivity in two-bottle choice drinking, whereas the hybrid of B6 and BUB demonstrated full or complete dominance. Genealogical origin, as well as non-alcohol taste preferences (sodium chloride), predicted ethanol consumption. Mice derived from the crosses of B6 and FVB showed high sustained alcohol preference and the B6 and NZB hybrids showed reduced alcohol preference after periods of abstinence. These new genetic models offer some advantages over inbred strains because they provide high, sustained, alcohol intake, and should allow mapping of loci important for the genetic architecture of these traits.
Integrated Modelling of Iter Hybrid Scenarios with Eccd
NASA Astrophysics Data System (ADS)
Giruzzi, G.; Artaud, J. F.; Basiuk, V.; Garcia, J.; Imbeaux, F.; Schneider, M.
2009-04-01
ITER hybrid scenarios may require off-axis current drive in order to keep the safety factor above 1. In this type of applications, alignment of the current sources and self-consistency of current and temperature profiles are critical issues, which can only be addressed by integrated modelling. To this end, the CRONOS suite of codes has been applied to the simulation of these scenarios. Results of simulations of ITER hybrid scenarios assisted by ECCD, using the ITER equatorial launcher, for both co- and counter-ECCD, are presented.
A hybrid parallel framework for the cellular Potts model simulations
Jiang, Yi; He, Kejing; Dong, Shoubin
2009-01-01
The Cellular Potts Model (CPM) has been widely used for biological simulations. However, most current implementations are either sequential or approximated, which can't be used for large scale complex 3D simulation. In this paper we present a hybrid parallel framework for CPM simulations. The time-consuming POE solving, cell division, and cell reaction operation are distributed to clusters using the Message Passing Interface (MPI). The Monte Carlo lattice update is parallelized on shared-memory SMP system using OpenMP. Because the Monte Carlo lattice update is much faster than the POE solving and SMP systems are more and more common, this hybrid approach achieves good performance and high accuracy at the same time. Based on the parallel Cellular Potts Model, we studied the avascular tumor growth using a multiscale model. The application and performance analysis show that the hybrid parallel framework is quite efficient. The hybrid parallel CPM can be used for the large scale simulation ({approx}10{sup 8} sites) of complex collective behavior of numerous cells ({approx}10{sup 6}).
Strongly Interacting Matter at Finite Chemical Potential: Hybrid Model Approach
NASA Astrophysics Data System (ADS)
Srivastava, P. K.; Singh, C. P.
2013-06-01
Search for a proper and realistic equation of state (EOS) for strongly interacting matter used in the study of the QCD phase diagram still appears as a challenging problem. Recently, we constructed a hybrid model description for the quark-gluon plasma (QGP) as well as hadron gas (HG) phases where we used an excluded volume model for HG and a thermodynamically consistent quasiparticle model for the QGP phase. The hybrid model suitably describes the recent lattice results of various thermodynamical as well as transport properties of the QCD matter at zero baryon chemical potential (μB). In this paper, we extend our investigations further in obtaining the properties of QCD matter at finite value of μB and compare our results with the most recent results of lattice QCD calculation.
Li, Ben Q; Liu, Changhong
2011-01-15
A hybridization model for the localized surface plasmon resonance of a nanoshell is developed within the framework of long-wave approximation. Compared with the existing hybridization model derived from the hydrodynamic simulation of free electron gas, this approach is much simpler and gives identical results for a concentric nanoshell. Also, with this approach, the limitations associated with the original hybridization model are succinctly stated. Extension of this approach to hybridization modeling of more complicated structures such as multiplayered nanoshells is straightforward.
Hybrid reduced order modeling for assembly calculations
Bang, Youngsuk; Abdel-Khalik, Hany S.; Jessee, Matthew A.; ...
2015-08-14
While the accuracy of assembly calculations has greatly improved due to the increase in computer power enabling more refined description of the phase space and use of more sophisticated numerical algorithms, the computational cost continues to increase which limits the full utilization of their effectiveness for routine engineering analysis. Reduced order modeling is a mathematical vehicle that scales down the dimensionality of large-scale numerical problems to enable their repeated executions on small computing environment, often available to end users. This is done by capturing the most dominant underlying relationships between the model's inputs and outputs. Previous works demonstrated the usemore » of the reduced order modeling for a single physics code, such as a radiation transport calculation. This paper extends those works to coupled code systems as currently employed in assembly calculations. Finally, numerical tests are conducted using realistic SCALE assembly models with resonance self-shielding, neutron transport, and nuclides transmutation/depletion models representing the components of the coupled code system.« less
Hybrid reduced order modeling for assembly calculations
Bang, Youngsuk; Abdel-Khalik, Hany S.; Jessee, Matthew A.; Mertyurek, Ugur
2015-08-14
While the accuracy of assembly calculations has greatly improved due to the increase in computer power enabling more refined description of the phase space and use of more sophisticated numerical algorithms, the computational cost continues to increase which limits the full utilization of their effectiveness for routine engineering analysis. Reduced order modeling is a mathematical vehicle that scales down the dimensionality of large-scale numerical problems to enable their repeated executions on small computing environment, often available to end users. This is done by capturing the most dominant underlying relationships between the model's inputs and outputs. Previous works demonstrated the use of the reduced order modeling for a single physics code, such as a radiation transport calculation. This paper extends those works to coupled code systems as currently employed in assembly calculations. Finally, numerical tests are conducted using realistic SCALE assembly models with resonance self-shielding, neutron transport, and nuclides transmutation/depletion models representing the components of the coupled code system.
Multiview coding mode decision with hybrid optimal stopping model.
Zhao, Tiesong; Kwong, Sam; Wang, Hanli; Wang, Zhou; Pan, Zhaoqing; Kuo, C-C Jay
2013-04-01
In a generic decision process, optimal stopping theory aims to achieve a good tradeoff between decision performance and time consumed, with the advantages of theoretical decision-making and predictable decision performance. In this paper, optimal stopping theory is employed to develop an effective hybrid model for the mode decision problem, which aims to theoretically achieve a good tradeoff between the two interrelated measurements in mode decision, as computational complexity reduction and rate-distortion degradation. The proposed hybrid model is implemented and examined with a multiview encoder. To support the model and further promote coding performance, the multiview coding mode characteristics, including predicted mode probability and estimated coding time, are jointly investigated with inter-view correlations. Exhaustive experimental results with a wide range of video resolutions reveal the efficiency and robustness of our method, with high decision accuracy, negligible computational overhead, and almost intact rate-distortion performance compared to the original encoder.
A Hybrid Tool for User Interface Modeling and Prototyping
NASA Astrophysics Data System (ADS)
Trætteberg, Hallvard
Although many methods have been proposed, model-based development methods have only to some extent been adopted for UI design. In particular, they are not easy to combine with user-centered design methods. In this paper, we present a hybrid UI modeling and GUI prototyping tool, which is designed to fit better with IS development and UI design traditions. The tool includes a diagram editor for domain and UI models and an execution engine that integrates UI behavior, live UI components and sample data. Thus, both model-based user interface design and prototyping-based iterative design are supported
Hybrid modeling of tumor-induced angiogenesis
NASA Astrophysics Data System (ADS)
Bonilla, L. L.; Capasso, V.; Alvaro, M.; Carretero, M.
2014-12-01
When modeling of tumor-driven angiogenesis, a major source of analytical and computational complexity is the strong coupling between the kinetic parameters of the relevant stochastic branching-and-growth of the capillary network, and the family of interacting underlying fields. To reduce this complexity, we take advantage of the system intrinsic multiscale structure: we describe the stochastic dynamics of the cells at the vessel tip at their natural mesoscale, whereas we describe the deterministic dynamics of the underlying fields at a larger macroscale. Here, we set up a conceptual stochastic model including branching, elongation, and anastomosis of vessels and derive a mean field approximation for their densities. This leads to a deterministic integropartial differential system that describes the formation of the stochastic vessel network. We discuss the proper capillary injecting boundary conditions and include the results of relevant numerical simulations.
Hybrid configuration mixing model for odd nuclei
NASA Astrophysics Data System (ADS)
Colò, G.; Bortignon, P. F.; Bocchi, G.
2017-03-01
In this work, we introduce a new approach which is meant to be a first step towards complete self-consistent low-lying spectroscopy of odd nuclei. So far, we essentially limit ourselves to the description of a double-magic core plus an extra nucleon. The model does not contain any free adjustable parameter and is instead based on a Hartree-Fock (HF) description of the particle states in the core, together with self-consistent random-phase approximation (RPA) calculations for the core excitations. We include both collective and noncollective excitations, with proper care of the corrections due to the overlap between them (i.e., due to the nonorthonormality of the basis). As a consequence, with respect to traditional particle-vibration coupling calculations in which one can only address single-nucleon states and particle-vibration multiplets, we can also describe states of shell-model types like 2 particle-1 hole. We will report results for 49Ca and 133Sb and discuss future perspectives.
A hybrid (numerical-physical) model of the left ventricle.
Ferrari, G; Kozarski, M; De Lazzari, C; Clemente, F; Merolli, M; Tosti, G; Guaragno, M; Mimmo, R; Ambrosi, D; Glapinski, J
2001-07-01
Hydraulic models of the circulation are used to test mechanical devices and for training and research purposes; when compared to numerical models, however, they are not flexible enough and rather expensive. The solution proposed here is to merge the characteristics and the flexibility of numerical models with the functions of physical models. The result is a hybrid model with numerical and physical sections connected by an electro-hydraulic interface - which is to some extent the main problem since the numerical model can be easily changed or modified. The concept of hybrid model is applied to the representation of ventricular function by a variable elastance numerical model. This prototype is an open loop circuit and the physical section is built out of a reservoir (atrium) and a modified windkessel (arterial tree). The corresponding equations are solved numerically using the variables (atrial and arterial pressures) coming from the physical circuit. Ventricular output flow is the computed variable and is sent to a servo amplifier connected to a DC motor-gear pump system. The gear pump, behaving roughly as a flow source, is the interface to the physical circuit. Results obtained under different hemodynamic conditions demonstrate the behaviour of the ventricular model on the pressure-volume plane and the time course of output flow and arterial pressure.
Controllability in Hybrid Kinetic Equations Modeling Nonequilibrium Multicellular Systems
Bianca, Carlo
2013-01-01
This paper is concerned with the derivation of hybrid kinetic partial integrodifferential equations that can be proposed for the mathematical modeling of multicellular systems subjected to external force fields and characterized by nonconservative interactions. In order to prevent an uncontrolled time evolution of the moments of the solution, a control operator is introduced which is based on the Gaussian thermostat. Specifically, the analysis shows that the moments are solution of a Riccati-type differential equation. PMID:24191137
Electric/hybrid vehicle model for establishing optimal battery requirements
NASA Astrophysics Data System (ADS)
Marr, W. W.; Walsh, W. J.
1986-04-01
A microcomputer program (HELEN) for establishing battery requirements for a heat engine/battery hybrid vehicle is described. The program permits least-cost analyses to identify the optimum combination of battery and heat engine characteristics for different vehicle types and missions. It can also be used for cost comparisons between heat-engine vehicles, all-electric (battery) vehicles, and hybrid vehicles. Simplified models are used for the transmission, motor/generator, controller, and other vehicle components, while a rather comprehensive model is employed for the battery. The heat engine performance model is based on engineering data for a production engine. A series/parallel configuration for the hybrid vehicle system is presently simulated. Energy management in the operation of the vehicle depends on the specified mission requirements, type and size of the battery, allowable battery depth of discharge, type and size of the heat engine, and the energy management strategy used. The program is written in PL/I language and can be run interactively on an IBM PC, COMPAQ, or other compatible microcomputer.
Hybrid Surface Mesh Adaptation for Climate Modeling
Ahmed Khamayseh; Valmor de Almeida; Glen Hansen
2008-10-01
Solution-driven mesh adaptation is becoming quite popular for spatial error control in the numerical simulation of complex computational physics applications, such as climate modeling. Typically, spatial adaptation is achieved by element subdivision (h adaptation) with a primary goal of resolving the local length scales of interest. A second, less-popular method of spatial adaptivity is called “mesh motion” (r adaptation); the smooth repositioning of mesh node points aimed at resizing existing elements to capture the local length scales. This paper proposes an adaptation method based on a combination of both element subdivision and node point repositioning (rh adaptation). By combining these two methods using the notion of a mobility function, the proposed approach seeks to increase the flexibility and extensibility of mesh motion algorithms while providing a somewhat smoother transition between refined regions than is produced by element subdivision alone. Further, in an attempt to support the requirements of a very general class of climate simulation applications, the proposed method is designed to accommodate unstructured, polygonal mesh topologies in addition to the most popular mesh types.
A hybrid double-observer sightability model for aerial surveys
Griffin, Paul C.; Lubow, Bruce C.; Jenkins, Kurt J.; Vales, David J.; Moeller, Barbara J.; Reid, Mason; Happe, Patricia J.; Mccorquodale, Scott M.; Tirhi, Michelle J.; Schaberi, Jim P.; Beirne, Katherine
2013-01-01
Raw counts from aerial surveys make no correction for undetected animals and provide no estimate of precision with which to judge the utility of the counts. Sightability modeling and double-observer (DO) modeling are 2 commonly used approaches to account for detection bias and to estimate precision in aerial surveys. We developed a hybrid DO sightability model (model MH) that uses the strength of each approach to overcome the weakness in the other, for aerial surveys of elk (Cervus elaphus). The hybrid approach uses detection patterns of 2 independent observer pairs in a helicopter and telemetry-based detections of collared elk groups. Candidate MH models reflected hypotheses about effects of recorded covariates and unmodeled heterogeneity on the separate front-seat observer pair and back-seat observer pair detection probabilities. Group size and concealing vegetation cover strongly influenced detection probabilities. The pilot's previous experience participating in aerial surveys influenced detection by the front pair of observers if the elk group was on the pilot's side of the helicopter flight path. In 9 surveys in Mount Rainier National Park, the raw number of elk counted was approximately 80–93% of the abundance estimated by model MH. Uncorrected ratios of bulls per 100 cows generally were low compared to estimates adjusted for detection bias, but ratios of calves per 100 cows were comparable whether based on raw survey counts or adjusted estimates. The hybrid method was an improvement over commonly used alternatives, with improved precision compared to sightability modeling and reduced bias compared to DO modeling.
HYBRIST Mobility Model - A Novel Hybrid Mobility Model for VANET Simulations
NASA Astrophysics Data System (ADS)
ManfeDanquah, Wiseborn; Turgay Altilar, D.
2014-01-01
Simulations play a vital role in implementing, testing and validating proposed algorithms and protocols in VANET. Mobility model, defined as the movement pattern of vehicles, is one of the main factors that contribute towards the efficient implementation of VANET algorithms and protocols. Using near reality mobility models ensure that accurate results are obtained from simulations. Mobility models that have been proposed and used to implement and test VANET protocols and algorithms are either the urban mobility model or highway mobility model. Algorithms and protocols implemented using urban or highway mobility models may not produce accurate results in hybrid mobility models without enhancement due to the vast differences in mobility patterns. It is on this score the Hybrist, a novel hybrid mobility model is proposed. The realistic mobility pattern trace file of the proposed Hybrist hybrid mobility model can be imported to VANET simulators such as Veins and network simulators such as ns2 and Qualnet to simulate VANET algorithms and protocols.
NASA Technical Reports Server (NTRS)
Uccellini, L. W.; Johnson, D. R.; Schlesinger, R. E.
1979-01-01
A solution is presented for matching boundary conditions across the interface of an isentropic and sigma coordinate hybrid model. A hybrid model based on the flux form of the primitive equations is developed which allows direct vertical exchange between the model domains, satisfies conservation principles with respect to transport processes, and maintains a smooth transition across the interface without need for artificial adjustment or parameterization schemes. The initial hybrid model simulations of a jet streak propagating in a zonal channel are used to test the feasibility of the hybrid model approach. High efficiency of the hybrid model is demonstrated.
Transient Modeling of Hybrid Rocket Low Frequency Instabilities
NASA Technical Reports Server (NTRS)
Karabeyoglu, M. Arif; DeZilwa, Shane; Cantwell, Brian; Zilliac, Greg
2003-01-01
A comprehensive dynamic model of a hybrid rocket has been developed in order to understand and predict the transient behavior including instabilities. A linearized version of the transient model predicted the low-frequency chamber pressure oscillations that are commonly observed in hybrids. The source of the instabilities is based on a complex coupling of thermal transients in the solid fuel, wall heat transfer blocking due to fuel regression rate and the transients in the boundary layer that forms on the fuel surface. The oscillation frequencies predicted by the linearized theory are in very good agreement with 43 motor test results obtained from the hybrid propulsion literature. The motor test results used in the comparison cover a very wide spectrum of parameters including: 1) four separate research and development programs, 2) three different oxidizers (LOX, GOX, N2O), 3) a wide range of motor dimensions (i.e. from 5 inch diameter to 72 inch diameter) and operating conditions and 4) several fuel formulations. A simple universal scaling formula for the frequency of the primary oscillation mode is suggested.
RCS and antenna modeling with MOM using hybrid meshes
Putnam, J.M.; Kotulski, J.D.
1997-02-01
In this presentation, the authors will investigate the use of hybrid meshes for modeling RCS and antenna problems in three dimensions. They will consider two classes of hybrid basis functions. These include combinations of quadrilateral and triangular meshes for arbitrary 3D geometries, and combinations of axisymmetric body-of-revolution (BOR) basis functions and triangular facets. In particular, they will focus on the problem of enforcing current continuity between two surfaces which are represented by different types of surface discretizations and unknown basis function representations. They will illustrate the use of an operator-based code architecture for the implementation of these formulations, and how it facilitates the incorporation of the various types of boundary conditions in the code. Both serial and parallel code implementation issues for the formulations will be discussed. Results will be presented for both scattering and antenna problems. The emphasis will be on accuracy, and robustness of the techniques. Comparisons of accuracy between triangular meshed and quadrilateral meshed geometries will be shown. The use of hybrid meshes for modeling BORs with attached appendages will also be presented.
Hybrid first-principles/neural networks model for column flotation
Gupta, S.; Liu, P.H.; Svoronos, S.A.; Sharma, R.; Abdel-Khalek, N.A.; Cheng, Y.; El-Shall, H.
1999-03-01
A new model for phosphate column flotation is presented which for the first time relates the effects of operating variables such as frother concentration on column performance. This is a hybrid model that combines a first-principles model with artificial neural networks. The first-principles model is obtained from material balances on both phosphate particles and gangue (undesired material containing mostly silica). First-order rates of net attachment are assumed for both. Artificial neural networks relate the attachment rate constants to the operating variables. Experiments were conducted in a 6-in.-dia. (152-mm-dia.) laboratory column to provide data for neural network training and model validation. The model successfully predicts the effects of frother concentration, particle size, air flow rate and bubble diameter on grade and recovery.
A new hybrid star model in Krori-Barua spacetime
NASA Astrophysics Data System (ADS)
Bhar, Piyali
2015-05-01
Present paper provides a new model of hybrid star with strange quark matter along with normal baryonic matter. The relation between pressure and density of the quark matter is given by the MIT bag model equation of state. The model is developed in the framework of Krori and Barua (KB) ansatz (Krori and Barua, Phys. A, Math. Gen. 8:508, 1975). All the physical requirements are satisfied by our model. The value of mass calculated from our model is close to the observational data which gives the validity of our present model. We match our interior solution to the exterior Schwarzschild metric where negative surface pressure is required to hold the thin shell against collapsing.
System Modeling and Diagnostics for Liquefying-Fuel Hybrid Rockets
NASA Technical Reports Server (NTRS)
Poll, Scott; Iverson, David; Ou, Jeremy; Sanderfer, Dwight; Patterson-Hine, Ann
2003-01-01
A Hybrid Combustion Facility (HCF) was recently built at NASA Ames Research Center to study the combustion properties of a new fuel formulation that burns approximately three times faster than conventional hybrid fuels. Researchers at Ames working in the area of Integrated Vehicle Health Management recognized a good opportunity to apply IVHM techniques to a candidate technology for next generation launch systems. Five tools were selected to examine various IVHM techniques for the HCF. Three of the tools, TEAMS (Testability Engineering and Maintenance System), L2 (Livingstone2), and RODON, are model-based reasoning (or diagnostic) systems. Two other tools in this study, ICS (Interval Constraint Simulator) and IMS (Inductive Monitoring System) do not attempt to isolate the cause of the failure but may be used for fault detection. Models of varying scope and completeness were created, both qualitative and quantitative. In each of the models, the structure and behavior of the physical system are captured. In the qualitative models, the temporal aspects of the system behavior and the abstraction of sensor data are handled outside of the model and require the development of additional code. In the quantitative model, less extensive processing code is also necessary. Examples of fault diagnoses are given.
Pope, Bernard J; Fitch, Blake G; Pitman, Michael C; Rice, John J; Reumann, Matthias
2011-01-01
Future multiscale and multiphysics models must use the power of high performance computing (HPC) systems to enable research into human disease, translational medical science, and treatment. Previously we showed that computationally efficient multiscale models will require the use of sophisticated hybrid programming models, mixing distributed message passing processes (e.g. the message passing interface (MPI)) with multithreading (e.g. OpenMP, POSIX pthreads). The objective of this work is to compare the performance of such hybrid programming models when applied to the simulation of a lightweight multiscale cardiac model. Our results show that the hybrid models do not perform favourably when compared to an implementation using only MPI which is in contrast to our results using complex physiological models. Thus, with regards to lightweight multiscale cardiac models, the user may not need to increase programming complexity by using a hybrid programming approach. However, considering that model complexity will increase as well as the HPC system size in both node count and number of cores per node, it is still foreseeable that we will achieve faster than real time multiscale cardiac simulations on these systems using hybrid programming models.
A New Hybrid STEP/Coulomb model for Aftershock Forecasting
NASA Astrophysics Data System (ADS)
Steacy, S.; Jimenez, A.; Gerstenberger, M.
2014-12-01
Aftershock forecasting models tend to fall into two classes - purely statistical approaches based on clustering, b-value, and the Omori-Utsu law; and Coulomb rate-state models which relate the forecast increase in rate to the magnitude of the Coulomb stress change. Recently, hybrid models combining physical and statistical forecasts have begun to be developed, for example by Bach and Hainzl (2012) and Steacy et al. (2013). The latter approach combined Coulomb stress patterns with the STEP (short-term earthquake probability) model by redistributing expected rate from areas with decreased stress to regions where the stress had increased. The chosen 'Coulomb Redistribution Parameter' (CRP) was 0.93, based on California earthquakes, which meant that 93% of the total rate was expected to occur where the stress had increased. The model was tested against the Canterbury sequence and the main result was that the new model performed at least as well as, and often better than, STEP when tested against retrospective data but that STEP was generally better in pseudo-prospective tests that involved data actually available within the first 10 days of each event of interest. The authors suggested that the major reason for this discrepancy was uncertainty in the slip models and, particularly, in the geometries of the faults involved in each complex major event. Here we develop a variant of the STEP/Coulomb model in which the CRP varies based on the percentage of aftershocks that occur in the positively stressed areas during the forecast learning period. We find that this variant significantly outperforms both STEP and the previous hybrid model in almost all cases, even when the input Coulomb model is quite poor. Our results suggest that this approach might be more useful than Coulomb rate-state when the underlying slip model is not well constrained due to the dependence of that method on the magnitude of the Coulomb stress change.
Hybrid Adaptive Flight Control with Model Inversion Adaptation
NASA Technical Reports Server (NTRS)
Nguyen, Nhan
2011-01-01
This study investigates a hybrid adaptive flight control method as a design possibility for a flight control system that can enable an effective adaptation strategy to deal with off-nominal flight conditions. The hybrid adaptive control blends both direct and indirect adaptive control in a model inversion flight control architecture. The blending of both direct and indirect adaptive control provides a much more flexible and effective adaptive flight control architecture than that with either direct or indirect adaptive control alone. The indirect adaptive control is used to update the model inversion controller by an on-line parameter estimation of uncertain plant dynamics based on two methods. The first parameter estimation method is an indirect adaptive law based on the Lyapunov theory, and the second method is a recursive least-squares indirect adaptive law. The model inversion controller is therefore made to adapt to changes in the plant dynamics due to uncertainty. As a result, the modeling error is reduced that directly leads to a decrease in the tracking error. In conjunction with the indirect adaptive control that updates the model inversion controller, a direct adaptive control is implemented as an augmented command to further reduce any residual tracking error that is not entirely eliminated by the indirect adaptive control.
Multiobjective muffler shape optimization with hybrid acoustics modeling.
Airaksinen, Tuomas; Heikkola, Erkki
2011-09-01
This paper considers the combined use of a hybrid numerical method for the modeling of acoustic mufflers and a genetic algorithm for multiobjective optimization. The hybrid numerical method provides accurate modeling of sound propagation in uniform waveguides with non-uniform obstructions. It is based on coupling a wave based modal solution in the uniform sections of the waveguide to a finite element solution in the non-uniform component. Finite element method provides flexible modeling of complicated geometries, varying material parameters, and boundary conditions, while the wave based solution leads to accurate treatment of non-reflecting boundaries and straightforward computation of the transmission loss (TL) of the muffler. The goal of optimization is to maximize TL at multiple frequency ranges simultaneously by adjusting chosen shape parameters of the muffler. This task is formulated as a multiobjective optimization problem with the objectives depending on the solution of the simulation model. NSGA-II genetic algorithm is used for solving the multiobjective optimization problem. Genetic algorithms can be easily combined with different simulation methods, and they are not sensitive to the smoothness properties of the objective functions. Numerical experiments demonstrate the accuracy and feasibility of the model-based optimization method in muffler design.
Experimental Validation of a Thermoelastic Model for SMA Hybrid Composites
NASA Technical Reports Server (NTRS)
Turner, Travis L.
2001-01-01
This study presents results from experimental validation of a recently developed model for predicting the thermomechanical behavior of shape memory alloy hybrid composite (SMAHC) structures, composite structures with an embedded SMA constituent. The model captures the material nonlinearity of the material system with temperature and is capable of modeling constrained, restrained, or free recovery behavior from experimental measurement of fundamental engineering properties. A brief description of the model and analysis procedures is given, followed by an overview of a parallel effort to fabricate and characterize the material system of SMAHC specimens. Static and dynamic experimental configurations for the SMAHC specimens are described and experimental results for thermal post-buckling and random response are presented. Excellent agreement is achieved between the measured and predicted results, fully validating the theoretical model for constrained recovery behavior of SMAHC structures.
Probabilistic logic modeling of network reliability for hybrid network architectures
Wyss, G.D.; Schriner, H.K.; Gaylor, T.R.
1996-10-01
Sandia National Laboratories has found that the reliability and failure modes of current-generation network technologies can be effectively modeled using fault tree-based probabilistic logic modeling (PLM) techniques. We have developed fault tree models that include various hierarchical networking technologies and classes of components interconnected in a wide variety of typical and atypical configurations. In this paper we discuss the types of results that can be obtained from PLMs and why these results are of great practical value to network designers and analysts. After providing some mathematical background, we describe the `plug-and-play` fault tree analysis methodology that we have developed for modeling connectivity and the provision of network services in several current- generation network architectures. Finally, we demonstrate the flexibility of the method by modeling the reliability of a hybrid example network that contains several interconnected ethernet, FDDI, and token ring segments. 11 refs., 3 figs., 1 tab.
Design, test and model of a hybrid magnetostrictive hydraulic actuator
NASA Astrophysics Data System (ADS)
Chaudhuri, Anirban; Yoo, Jin-Hyeong; Wereley, Norman M.
2009-08-01
The basic operation of hybrid hydraulic actuators involves high frequency bi-directional operation of an active material that is converted to uni-directional motion of hydraulic fluid using valves. A hybrid actuator was developed using magnetostrictive material Terfenol-D as the driving element and hydraulic oil as the working fluid. Two different lengths of Terfenol-D rod, 51 and 102 mm, with the same diameter, 12.7 mm, were used. Tests with no load and with load were carried out to measure the performance for uni-directional motion of the output piston at different pumping frequencies. The maximum no-load flow rates were 24.8 cm3 s-1 and 22.7 cm3 s-1 with the 51 mm and 102 mm long rods respectively, and the peaks were noted around 325 Hz pumping frequency. The blocked force of the actuator was close to 89 N in both cases. A key observation was that, at these high pumping frequencies, the inertial effects of the fluid mass dominate over the viscous effects and the problem becomes unsteady in nature. In this study, we also develop a mathematical model of the hydraulic hybrid actuator in the time domain to show the basic operational principle under varying conditions and to capture phenomena affecting system performance. Governing equations for the pumping piston and output shaft were obtained from force equilibrium considerations, while compressibility of the working fluid was taken into account by incorporating the bulk modulus. Fluid inertia was represented by a lumped parameter approach to the transmission line model, giving rise to strongly coupled ordinary differential equations. The model was then used to calculate the no-load velocities of the actuator at different pumping frequencies and simulation results were compared with experimental data for model validation.
Model-adaptive hybrid dynamic control for robotic assembly tasks
Austin, D.J.; McCarragher, B.J.
1999-10-01
A new task-level adaptive controller is presented for the hybrid dynamic control of robotic assembly tasks. Using a hybrid dynamic model of the assembly task, velocity constraints are derived from which satisfactory velocity commands are obtained. Due to modeling errors and parametric uncertainties, the velocity commands may be erroneous and may result in suboptimal performance. Task-level adaptive control schemes, based on the occurrence of discrete events, are used to change the model parameters from which the velocity commands are determined. Two adaptive schemes are presented: the first is based on intuitive reasoning about the vector spaces involved whereas the second uses a search region that is reduced with each iteration. For the first adaptation law, asymptotic convergence to the correct model parameters is proven except for one case. This weakness motivated the development of the second adaptation law, for which asymptotic convergence is proven in all cases. Automated control of a peg-in-hole assembly task is given as an example, and simulations and experiments for this task are presented. These results demonstrate the success of the method and also indicate properties for rapid convergence.
Constructing biological pathway models with hybrid functional Petri nets.
Doi, Atsushi; Fujita, Sachie; Matsuno, Hiroshi; Nagasaki, Masao; Miyano, Satoru
2004-01-01
In many research projects on modeling and analyzing biological pathways, the Petri net has been recognized as a promising method for representing biological pathways. From the pioneering works by Reddy et al., 1993, and Hofestädt, 1994, that model metabolic pathways by traditional Petri net, several enhanced Petri nets such as colored Petri net, stochastic Petri net, and hybrid Petri net have been used for modeling biological phenomena. Recently, Matsuno et al., 2003b, introduced the hybrid functional Petri net (HFPN) in order to give a more intuitive and natural modeling method for biological pathways than these existing Petri nets. Although the paper demonstrates the effectiveness of HFPN with two examples of gene regulation mechanism for circadian rhythms and apoptosis signaling pathway, there has been no detailed explanation about the method of HFPN construction for these examples. The purpose of this paper is to describe method to construct biological pathways with the HFPN step-by-step. The method is demonstrated by the well-known glycolytic pathway controlled by the lac operon gene regulatory mechanism.
Constructing biological pathway models with hybrid functional petri nets.
Doi, Atsushi; Fujita, Sachie; Matsuno, Hiroshi; Nagasaki, Masao; Miyano, Satoru
2011-01-01
In many research projects on modeling and analyzing biological pathways, the Petri net has been recognized as a promising method for representing biological pathways. From the pioneering works by Reddy et al., 1993, and Hofestädt, 1994, that model metabolic pathways by traditional Petri net, several enhanced Petri nets such as colored Petri net, stochastic Petri net, and hybrid Petri net have been used for modeling biological phenomena. Recently, Matsuno et al., 2003b, introduced the hybrid functional Petri net (HFPN) in order to give a more intuitive and natural modeling method for biological pathways than these existing Petri nets. Although the paper demonstrates the effectiveness of HFPN with two examples of gene regulation mechanism for circadian rhythms and apoptosis signaling pathway, there has been no detailed explanation about the method of HFPN construction for these examples. The purpose of this paper is to describe method to construct biological pathways with the HFPN step-by-step. The method is demonstrated by the well-known glycolytic pathway controlled by the lac operon gene regulatory mechanism.
Hybrid perturbation methods based on statistical time series models
NASA Astrophysics Data System (ADS)
San-Juan, Juan Félix; San-Martín, Montserrat; Pérez, Iván; López, Rosario
2016-04-01
In this work we present a new methodology for orbit propagation, the hybrid perturbation theory, based on the combination of an integration method and a prediction technique. The former, which can be a numerical, analytical or semianalytical theory, generates an initial approximation that contains some inaccuracies derived from the fact that, in order to simplify the expressions and subsequent computations, not all the involved forces are taken into account and only low-order terms are considered, not to mention the fact that mathematical models of perturbations not always reproduce physical phenomena with absolute precision. The prediction technique, which can be based on either statistical time series models or computational intelligence methods, is aimed at modelling and reproducing missing dynamics in the previously integrated approximation. This combination results in the precision improvement of conventional numerical, analytical and semianalytical theories for determining the position and velocity of any artificial satellite or space debris object. In order to validate this methodology, we present a family of three hybrid orbit propagators formed by the combination of three different orders of approximation of an analytical theory and a statistical time series model, and analyse their capability to process the effect produced by the flattening of the Earth. The three considered analytical components are the integration of the Kepler problem, a first-order and a second-order analytical theories, whereas the prediction technique is the same in the three cases, namely an additive Holt-Winters method.
Ionocovalency and applications 1. Ionocovalency model and orbital hybrid scales.
Zhang, Yonghe
2010-11-03
Ionocovalency (IC), a quantitative dual nature of the atom, is defined and correlated with quantum-mechanical potential to describe quantitatively the dual properties of the bond. Orbiotal hybrid IC model scale, IC, and IC electronegativity scale, X(IC), are proposed, wherein the ionicity and the covalent radius are determined by spectroscopy. Being composed of the ionic function I and the covalent function C, the model describes quantitatively the dual properties of bond strengths, charge density and ionic potential. Based on the atomic electron configuration and the various quantum-mechanical built-up dual parameters, the model formed a Dual Method of the multiple-functional prediction, which has much more versatile and exceptional applications than traditional electronegativity scales and molecular properties. Hydrogen has unconventional values of IC and X(IC), lower than that of boron. The IC model can agree fairly well with the data of bond properties and satisfactorily explain chemical observations of elements throughout the Periodic Table.
Nonlinear Thermoelastic Model for SMAs and SMA Hybrid Composites
NASA Technical Reports Server (NTRS)
Turner, Travis L.
2004-01-01
A constitutive mathematical model has been developed that predicts the nonlinear thermomechanical behaviors of shape-memory-alloys (SMAs) and of shape-memory-alloy hybrid composite (SMAHC) structures, which are composite-material structures that contain embedded SMA actuators. SMAHC structures have been investigated for their potential utility in a variety of applications in which there are requirements for static or dynamic control of the shapes of structures, control of the thermoelastic responses of structures, or control of noise and vibrations. The present model overcomes deficiencies of prior, overly simplistic or qualitative models that have proven ineffective or intractable for engineering of SMAHC structures. The model is sophisticated enough to capture the essential features of the mechanics of SMAHC structures yet simple enough to accommodate input from fundamental engineering measurements and is in a form that is amenable to implementation in general-purpose structural analysis environments.
Flood Estimation at Ungauged Sites Using a New Hybrid Model
NASA Astrophysics Data System (ADS)
Hassanpour Kashani, Mahsa; Montaseri, Majid; Lotfollahi Yaghin, Mohammad Ali
As flood forecasting in ungauged basins has been an area of extensive research, new techniques have been introduced to minimize the forecast errors and to issue more accurate forecasts. The use of Artificial Neural Networks (ANNs) in flood forecasting is new and still in the evolution stage. In this study, MLP and Elman networks and also a new nonlinear regression model are applied and combined with each other for T-year flood estimation in western basins of Urmia Lake. At first, these networks used physiographic and climatic data selected from the regression model, to train. Finally, the best structure of the networks is chosen based on correlation coefficient between observed and estimated discharges. In order to train the models well, the return period variable is considered as one of the input variables of them. The obtained results have proved the ability of the hybrid model to predict T-year flood events and the effect of networks types on prediction precision.
Computational modeling of brain tumors: discrete, continuum or hybrid?
NASA Astrophysics Data System (ADS)
Wang, Zhihui; Deisboeck, Thomas S.
In spite of all efforts, patients diagnosed with highly malignant brain tumors (gliomas), continue to face a grim prognosis. Achieving significant therapeutic advances will also require a more detailed quantitative understanding of the dynamic interactions among tumor cells, and between these cells and their biological microenvironment. Data-driven computational brain tumor models have the potential to provide experimental tumor biologists with such quantitative and cost-efficient tools to generate and test hypotheses on tumor progression, and to infer fundamental operating principles governing bidirectional signal propagation in multicellular cancer systems. This review highlights the modeling objectives of and challenges with developing such in silico brain tumor models by outlining two distinct computational approaches: discrete and continuum, each with representative examples. Future directions of this integrative computational neuro-oncology field, such as hybrid multiscale multiresolution modeling are discussed.
A High Precision Prediction Model Using Hybrid Grey Dynamic Model
ERIC Educational Resources Information Center
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)…
Exploring the lambda model of the hybrid superstring
NASA Astrophysics Data System (ADS)
Schmidtt, David M.
2016-10-01
The purpose of this contribution is to initiate the study of integrable deformations for different superstring theory formalisms that manifest the property of (classical) integrability. In this paper we choose the hybrid formalism of the superstring in the background AdS 2 × S 2 and explore in detail the most immediate consequences of its λ-deformation. The resulting action functional corresponds to the λ-model of the matter part of the fairly more sophisticated pure spinor formalism, which is also known to be classical integrable. In particular, the deformation preserves the integrability and the one-loop conformal invariance of its parent theory, hence being a marginal deformation.
Causality in Psychiatry: A Hybrid Symptom Network Construct Model.
Young, Gerald
2015-01-01
Causality or etiology in psychiatry is marked by standard biomedical, reductionistic models (symptoms reflect the construct involved) that inform approaches to nosology, or classification, such as in the DSM-5 [Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition; (1)]. However, network approaches to symptom interaction [i.e., symptoms are formative of the construct; e.g., (2), for posttraumatic stress disorder (PTSD)] are being developed that speak to bottom-up processes in mental disorder, in contrast to the typical top-down psychological construct approach. The present article presents a hybrid top-down, bottom-up model of the relationship between symptoms and mental disorder, viewing symptom expression and their causal complex as a reciprocally dynamic system with multiple levels, from lower-order symptoms in interaction to higher-order constructs affecting them. The hybrid model hinges on good understanding of systems theory in which it is embedded, so that the article reviews in depth non-linear dynamical systems theory (NLDST). The article applies the concept of emergent circular causality (3) to symptom development, as well. Conclusions consider that symptoms vary over several dimensions, including: subjectivity; objectivity; conscious motivation effort; and unconscious influences, and the degree to which individual (e.g., meaning) and universal (e.g., causal) processes are involved. The opposition between science and skepticism is a complex one that the article addresses in final comments.
Hybrid CFD/CAA Modeling for Liftoff Acoustic Predictions
NASA Technical Reports Server (NTRS)
Strutzenberg, Louise L.; Liever, Peter A.
2011-01-01
This paper presents development efforts at the NASA Marshall Space flight Center to establish a hybrid Computational Fluid Dynamics and Computational Aero-Acoustics (CFD/CAA) simulation system for launch vehicle liftoff acoustics environment analysis. Acoustic prediction engineering tools based on empirical jet acoustic strength and directivity models or scaled historical measurements are of limited value in efforts to proactively design and optimize launch vehicles and launch facility configurations for liftoff acoustics. CFD based modeling approaches are now able to capture the important details of vehicle specific plume flow environment, identifY the noise generation sources, and allow assessment of the influence of launch pad geometric details and sound mitigation measures such as water injection. However, CFD methodologies are numerically too dissipative to accurately capture the propagation of the acoustic waves in the large CFD models. The hybrid CFD/CAA approach combines the high-fidelity CFD analysis capable of identifYing the acoustic sources with a fast and efficient Boundary Element Method (BEM) that accurately propagates the acoustic field from the source locations. The BEM approach was chosen for its ability to properly account for reflections and scattering of acoustic waves from launch pad structures. The paper will present an overview of the technology components of the CFD/CAA framework and discuss plans for demonstration and validation against test data.
A Concept Analysis of Holistic Care by Hybrid Model
Jasemi, Madineh; Valizadeh, Leila; Zamanzadeh, Vahid; Keogh, Brian
2017-01-01
Purpose: Even though holistic care has been widely discussed in the health care and professional nursing literature, there is no comprehensive definition of it. Therefore, the aim of this article is to present a concept analysis of holistic care which was developed using the hybrid model. Methods: The hybrid model comprises three phases. In the theoretical phase, characteristics of holistic care were identified through a review of the literature from CINAHL, MEDLINE, PubMed, OVID, and Google Scholar databases. During the fieldwork phase, in-depth interviews were conducted with eight nurses who were purposely selected. Finally, following an analysis of the literature and the qualitative interviews, a theoretical description of the concept of holistic care was extracted. Results: Two main themes were extracted of analytical phase: “Holistic care for offering a comprehensive model for caring” and “holistic care for improving patients' and nurses' conditions.” Conclusion: By undertaking a conceptual analysis of holistic care, its meaning can be clarified which will encourage nursing educators to include holistic care in nursing syllabi, and consequently facilitate its provision in practice. PMID:28216867
NASA Astrophysics Data System (ADS)
Fahimi, Farzad; Yaseen, Zaher Mundher; El-shafie, Ahmed
2016-02-01
Since the middle of the twentieth century, artificial intelligence (AI) models have been used widely in engineering and science problems. Water resource variable modeling and prediction are the most challenging issues in water engineering. Artificial neural network (ANN) is a common approach used to tackle this problem by using viable and efficient models. Numerous ANN models have been successfully developed to achieve more accurate results. In the current review, different ANN models in water resource applications and hydrological variable predictions are reviewed and outlined. In addition, recent hybrid models and their structures, input preprocessing, and optimization techniques are discussed and the results are compared with similar previous studies. Moreover, to achieve a comprehensive view of the literature, many articles that applied ANN models together with other techniques are included. Consequently, coupling procedure, model evaluation, and performance comparison of hybrid models with conventional ANN models are assessed, as well as, taxonomy and hybrid ANN models structures. Finally, current challenges and recommendations for future researches are indicated and new hybrid approaches are proposed.
Coarse-grained DNA modeling: Hybridization and ionic effects
NASA Astrophysics Data System (ADS)
Hinckley, Daniel M.
Deoxyribonucleic acid (DNA) is a biopolymer of enormous significance in living systems. The utility of DNA in such systems is derived from the programmable nature of DNA and its unique mechanical properties. Recently, material scientists have harnessed these properties in order to create systems that spontaneous self-assemble on the nanoscale. Both biologists and material scientists are hindered by an incomplete understanding of the physical interactions that together govern DNA's behavior. Computer simulations, especially those at the coarse-grained (CG) level, can potentially complete this understanding by resolving details indiscernible with current experimental techniques. In this thesis, we advance the state-of-the-art of DNA CG simulations by first reviewing the relevant theory and the evolution of CG DNA models since their inception. Then we present 3SPN.2, an improved CG model for DNA that should provide new insights into biological and nanotechnological systems which incorporate DNA. We perform forward flux sampling simulations in order to examine the effect of sequence, oligomer length, and ionic strength on DNA oligomer hybridization. Due to the limitations inherent in continuum treatments of electrostatic interactions in biological systems, we generate a CG model of biological ions for use with 3SPN.2 and other CG models. Lastly, we illustrate the potential of 3SPN.2 and CG ions by using the models in simulations of viral capsid packaging experiments. The models and results described in this thesis will be useful in future modeling efforts that seek to identify the fundamental physics that govern behavior such as nucleosome positioning, DNA hybridization, and DNA nanoassembly.
Efficient Vaccine Distribution Based on a Hybrid Compartmental Model
Yu, Zhiwen; Liu, Jiming; Wang, Xiaowei; Zhu, Xianjun; Wang, Daxing; Han, Guoqiang
2016-01-01
To effectively and efficiently reduce the morbidity and mortality that may be caused by outbreaks of emerging infectious diseases, it is very important for public health agencies to make informed decisions for controlling the spread of the disease. Such decisions must incorporate various kinds of intervention strategies, such as vaccinations, school closures and border restrictions. Recently, researchers have paid increased attention to searching for effective vaccine distribution strategies for reducing the effects of pandemic outbreaks when resources are limited. Most of the existing research work has been focused on how to design an effective age-structured epidemic model and to select a suitable vaccine distribution strategy to prevent the propagation of an infectious virus. Models that evaluate age structure effects are common, but models that additionally evaluate geographical effects are less common. In this paper, we propose a new SEIR (susceptible—exposed—infectious šC recovered) model, named the hybrid SEIR-V model (HSEIR-V), which considers not only the dynamics of infection prevalence in several age-specific host populations, but also seeks to characterize the dynamics by which a virus spreads in various geographic districts. Several vaccination strategies such as different kinds of vaccine coverage, different vaccine releasing times and different vaccine deployment methods are incorporated into the HSEIR-V compartmental model. We also design four hybrid vaccination distribution strategies (based on population size, contact pattern matrix, infection rate and infectious risk) for controlling the spread of viral infections. Based on data from the 2009–2010 H1N1 influenza epidemic, we evaluate the effectiveness of our proposed HSEIR-V model and study the effects of different types of human behaviour in responding to epidemics. PMID:27233015
Hybrid modeling method for a DEP based particle manipulation.
Miled, Mohamed Amine; Gagne, Antoine; Sawan, Mohamad
2013-01-30
In this paper, a new modeling approach for Dielectrophoresis (DEP) based particle manipulation is presented. The proposed method fulfills missing links in finite element modeling between the multiphysic simulation and the biological behavior. This technique is amongst the first steps to develop a more complex platform covering several types of manipulations such as magnetophoresis and optics. The modeling approach is based on a hybrid interface using both ANSYS and MATLAB to link the propagation of the electrical field in the micro-channel to the particle motion. ANSYS is used to simulate the electrical propagation while MATLAB interprets the results to calculate cell displacement and send the new information to ANSYS for another turn. The beta version of the proposed technique takes into account particle shape, weight and its electrical properties. First obtained results are coherent with experimental results.
Building Hybrid Rover Models for NASA: Lessons Learned
NASA Technical Reports Server (NTRS)
Willeke, Thomas; Dearden, Richard
2004-01-01
Particle filters have recently become popular for diagnosis and monitoring of hybrid systems. In this paper we describe our experiences using particle filters on a real diagnosis problem, the NASA Ames Research Center's K-9 rover. As well as the challenge of modelling the dynamics of the system, there are two major issues in applying a particle filter to such a model. The first is the asynchronous nature of the system-observations from different subsystems arrive at different rates, and occasionally out of order, leading to large amounts of uncertainty in the state of the system. The second issue is data interpretation. The particle filter produces a probability distribution over the state of the system, from which summary statistics that can be used for control or higher-level diagnosis must be extracted. We describe our approaches to both these problems, as well as other modelling issues that arose in this domain.
COSMIC RAY MODULATION BEYOND THE HELIOPAUSE: A HYBRID MODELING APPROACH
Strauss, R. D.; Potgieter, M. S.; Ferreira, S. E. S.; Fichtner, H.; Scherer, K.
2013-03-01
Results from a newly developed hybrid cosmic ray (CR) modulation model are presented. In this approach, the transport of CRs is computed by incorporating the plasma flow from a magnetohydrodynamic model for the heliospheric environment, resulting in representative CR transport. The model is applied to the modulation of CRs beyond the heliopause (HP) and we show that (1) CR modulation persists beyond the HP, so it is unlikely that the Voyager spacecraft will measure the pristine local interstellar spectra of galactic CRs when crossing the HP. (2) CR modulation in the outer heliosheath could maintain solar-cycle-related changes. (3) The modulation of CRs in the outer heliosheath is primarily determined by the ratio of perpendicular to parallel diffusion, so that the value of the individual diffusion coefficients cannot be determined uniquely using this approach. (4) CRs can efficiently diffuse between the nose and tail regions of the heliosphere.
Proposal: A Hybrid Dictionary Modelling Approach for Malay Tweet Normalization
NASA Astrophysics Data System (ADS)
Muhamad, Nor Azlizawati Binti; Idris, Norisma; Arshi Saloot, Mohammad
2017-02-01
Malay Twitter message presents a special deviation from the original language. Malay Tweet widely used currently by Twitter users, especially at Malaya archipelago. Thus, it is important to make a normalization system which can translated Malay Tweet language into the standard Malay language. Some researchers have conducted in natural language processing which mainly focuses on normalizing English Twitter messages, while few studies have been done for normalize Malay Tweets. This paper proposes an approach to normalize Malay Twitter messages based on hybrid dictionary modelling methods. This approach normalizes noisy Malay twitter messages such as colloquially language, novel words, and interjections into standard Malay language. This research will be used Language Model and N-grams model.
Hybrid Models of Reactive Transport in Porous and Fractured Media
Battiato, Ilenia; Tartakovsky, Daniel M.; Tartakovsky, Alexandre M.; Scheibe, Timothy D.
2011-02-02
Darcy-scale models of flow and transport in porous media often fail to describe experimentally observed phenomena, while their pore-scale counterparts are accu- rate but can be computationally prohibitive. Most numerical multi-scale models, which seek to combine these two descriptions, require empirical closures and/or assumptions on the behavior of pore-scale quantities at the continuum (Darcy) scale. We present a general formulation of an iterative hybrid numerical method that links these two scales without resorting to such approximations. The algorithm treats the fluxes exchanged at the internal boundaries between the pore- and continuum-scale domains as unknown, and allows for iteratively determined boundary conditions to be applied at the pore-scale in order to guarantee their continuity. While the algorithm proposed is general, we use it to model Taylor dispersion in a fracture with chemically reactive walls. Results show significant improvement upon standard continuum-scale formulations.
Design, modeling and performance of a hybrid portable gamma camera
NASA Astrophysics Data System (ADS)
Smith, Leon Eric
The combination of a mechanically-collimated gamma-ray camera with an electronically-collimated gamma camera offers both the high efficiency and good angular resolution typical in a mechanically-collimated camera for lower photon energies and the uncoupling of spatial resolution and efficiency provided by an electronically-collimated camera at higher energies. The design, construction, performance modeling and measured performance of the Hybrid Portable Gamma Camera (HPGC) are presented here. Intended for industrial use, the HPGC offers good angular resolution and efficiency over a broad energy range (50 keV to 2 MeV) by combining a MURA coded aperture camera with a Compton scatter camera in a single system. The HPGC consists of two detector modules: (1) a NaI(Tl) scintillator with Anger logic readout and (2) a CsI(Na) pixellated crystal viewed by a position-sensitive photomultiplier tube. Analytical calculations of angular resolution components and efficiency for the HPGC were compared to Monte Carlo calculations of the same quantities. The predicted angular resolution performance for on-axis point sources, a central scattering angle of 45sp° and a detector separation distance of 35 cm ranges from 3.5-6sp° FWHM over the sensitive energy range. The mechanical collimation intrinsic efficiency for energies up to 800 keV varies from 0.50 to 0.05 while the electronic collimation intrinsic efficiency for energies above 400 keV is 7.0×10sp{-4} to 5×10sp{-5}. The experimentally measured angular resolution and efficiency values show good agreement with the modeling predictions for incident energies of 412 keV and 662 keV. Although work has been done on mechanical collimation cameras and electronic collimation cameras operating independently, no truly hybrid imaging system has been constructed that uses the same gamma ray for both mechanical collimation and electronic collimation information. This dissertation compares the relative information per photon for three
Hybrid Air Quality Modeling Approach For Use in the Near ...
The Near-road EXposures to Urban air pollutant Study (NEXUS) investigated whether children with asthma living in close proximity to major roadways in Detroit, MI, (particularly near roadways with high diesel traffic) have greater health impacts associated with exposure to air pollutants than those living farther away. A major challenge in such health and exposure studies is the lack of information regarding pollutant exposure characterization. Air quality modeling can provide spatially and temporally varying exposure estimates for examining relationships between traffic-related air pollutants and adverse health outcomes. This paper presents a hybrid air quality modeling approach and its application in NEXUS in order to provide spatial and temporally varying exposure estimates and identification of the mobile source contribution to the total pollutant exposure. Model-based exposure metrics, associated with local variations of emissions and meteorology, were estimated using a combination of the AERMOD and R-LINE dispersion models, local emission source information from the National Emissions Inventory, detailed road network locations and traffic activity, and meteorological data from the Detroit City Airport. The regional background contribution was estimated using a combination of the Community Multiscale Air Quality (CMAQ) model and the Space/Time Ordinary Kriging (STOK) model. To capture the near-road pollutant gradients, refined “mini-grids” of model recep
Estimation of Flood Inundation Extent Using Hybrid Models (Invited)
NASA Astrophysics Data System (ADS)
Chang, L.; Wang, Y.; Shen, H.
2009-12-01
We present a two-stage procedure underlying CHIM (clustering-based hybrid inundation model), which is composed of the linear regression models and ANNs to build the regional flood inundation estimation model. The two-stage procedure includes data preprocessing and model building stages. In the data preprocessing stage, the K-means clustering is used to categorize the data points of the different flooding characteristics and to identify the control point(s) from individual flooding cluster(s). In the model building stage, three classes of flood depth estimation models are built in each cluster: the back-propagation neural network (BPNN) for each control point, the linear regression models for the grids those have highly linear correlation with the control point, and a multi-grid BPNN for the grids those do not exist highly linear correlation with the control point. The effectiveness of the proposed approach is tested in the Dacun township in Taiwan. The results show that the CHIM can continuously and adequately provide one-hour-ahead flood inundation maps and effectively reduce 99% CPU time.
Modeling Integrated Cellular Machinery Using Hybrid Petri-Boolean Networks
Berestovsky, Natalie; Zhou, Wanding; Nagrath, Deepak; Nakhleh, Luay
2013-01-01
The behavior and phenotypic changes of cells are governed by a cellular circuitry that represents a set of biochemical reactions. Based on biological functions, this circuitry is divided into three types of networks, each encoding for a major biological process: signal transduction, transcription regulation, and metabolism. This division has generally enabled taming computational complexity dealing with the entire system, allowed for using modeling techniques that are specific to each of the components, and achieved separation of the different time scales at which reactions in each of the three networks occur. Nonetheless, with this division comes loss of information and power needed to elucidate certain cellular phenomena. Within the cell, these three types of networks work in tandem, and each produces signals and/or substances that are used by the others to process information and operate normally. Therefore, computational techniques for modeling integrated cellular machinery are needed. In this work, we propose an integrated hybrid model (IHM) that combines Petri nets and Boolean networks to model integrated cellular networks. Coupled with a stochastic simulation mechanism, the model simulates the dynamics of the integrated network, and can be perturbed to generate testable hypotheses. Our model is qualitative and is mostly built upon knowledge from the literature and requires fine-tuning of very few parameters. We validated our model on two systems: the transcriptional regulation of glucose metabolism in human cells, and cellular osmoregulation in S. cerevisiae. The model produced results that are in very good agreement with experimental data, and produces valid hypotheses. The abstract nature of our model and the ease of its construction makes it a very good candidate for modeling integrated networks from qualitative data. The results it produces can guide the practitioner to zoom into components and interconnections and investigate them using such more
Modeling integrated cellular machinery using hybrid Petri-Boolean networks.
Berestovsky, Natalie; Zhou, Wanding; Nagrath, Deepak; Nakhleh, Luay
2013-01-01
The behavior and phenotypic changes of cells are governed by a cellular circuitry that represents a set of biochemical reactions. Based on biological functions, this circuitry is divided into three types of networks, each encoding for a major biological process: signal transduction, transcription regulation, and metabolism. This division has generally enabled taming computational complexity dealing with the entire system, allowed for using modeling techniques that are specific to each of the components, and achieved separation of the different time scales at which reactions in each of the three networks occur. Nonetheless, with this division comes loss of information and power needed to elucidate certain cellular phenomena. Within the cell, these three types of networks work in tandem, and each produces signals and/or substances that are used by the others to process information and operate normally. Therefore, computational techniques for modeling integrated cellular machinery are needed. In this work, we propose an integrated hybrid model (IHM) that combines Petri nets and Boolean networks to model integrated cellular networks. Coupled with a stochastic simulation mechanism, the model simulates the dynamics of the integrated network, and can be perturbed to generate testable hypotheses. Our model is qualitative and is mostly built upon knowledge from the literature and requires fine-tuning of very few parameters. We validated our model on two systems: the transcriptional regulation of glucose metabolism in human cells, and cellular osmoregulation in S. cerevisiae. The model produced results that are in very good agreement with experimental data, and produces valid hypotheses. The abstract nature of our model and the ease of its construction makes it a very good candidate for modeling integrated networks from qualitative data. The results it produces can guide the practitioner to zoom into components and interconnections and investigate them using such more
A numerical oil spill model based on a hybrid method.
Guo, W J; Wang, Y X
2009-05-01
The purpose of this paper is the development of a hybrid particle tracking/Eulerian-Lagrangian approach for the simulation of spilled oil in coastal areas. Oil discharge from the source is modeled by the release of particles. When the oil slick thickness or the oil concentration reaches a critical value, particles are mapped on slick thickness or node concentrations, and the calculations proceed in the Eulerian-Lagrangian mode. To acquire accurate environment information, the model is coupled with the 3-D free-surface hydrodynamics model (POM) and the third-generation wave model (SWAN). By simulating the oil processes of spreading, advection, turbulent diffusion, evaporation, emulsification, dissolution and shoreline deposition, it has the ability to predict the horizontal movement of surface oil slick, the vertical distribution of oil particles, the concentration in the water column and the mass balance of spilled oil. An accidental oil release near Dalian coastal waters is simulated to validate the developed model. Compared with the satellite images of oil slicks on the surface, the numerical results indicate that the model has a reasonable accuracy.
A new approach to flow simulation using hybrid models
NASA Astrophysics Data System (ADS)
Solgi, Abazar; Zarei, Heidar; Nourani, Vahid; Bahmani, Ramin
2017-01-01
The necessity of flow prediction in rivers, for proper management of water resource, and the need for determining the inflow to the dam reservoir, designing efficient flood warning systems and so forth, have always led water researchers to think about models with high-speed response and low error. In the recent years, the development of Artificial Neural Networks and Wavelet theory and using the combination of models help researchers to estimate the river flow better and better. In this study, daily and monthly scales were used for simulating the flow of Gamasiyab River, Nahavand, Iran. The first simulation was done using two types of ANN and ANFIS models. Then, using wavelet theory and decomposing input signals of the used parameters, sub-signals were obtained and were fed into the ANN and ANFIS to obtain hybrid models of WANN and WANFIS. In this study, in addition to the parameters of precipitation and flow, parameters of temperature and evaporation were used to analyze their effects on the simulation. The results showed that using wavelet transform improved the performance of the models in both monthly and daily scale. However, it had a better effect on the monthly scale and the WANFIS was the best model.
Hybrid Transureteral Nephrectomy in a Survival Porcine Model
Anderson, Kirk M.; Alsyouf, Muhannad; Richards, Gideon; Agarwal, Gautum; Heldt, Jonathan P.; Schlaifer, Amy E.
2014-01-01
Background and Objectives: Natural-orifice approaches for nephrectomy have included access via the stomach, vagina, bladder, and rectum. Recently, the feasibility of using the ureter as a natural orifice for natural-orifice transluminal endoscopic surgery nephrectomy has been demonstrated in a nonsurvival porcine model. The purpose of this study was to assess the outcomes of transureteral laparoscopic natural-orifice transluminal endoscopic surgery nephrectomy in a survival porcine model. Methods: Three pigs underwent hybrid transureteral natural-orifice transluminal endoscopic surgery nephrectomy. An experimental balloon/dilating sheath was inserted over a wire to dilate the urethra, ureteral orifice, and ureter. Through a bariatric 12-mm laparoscopic port, the ureter was opened medially and the hilar dissection was performed. Next, 2 needlescopic ports were placed transabdominally to facilitate hilar transection. The kidney was morcellated using a bipolar sealing device and extracted via the ureter using the housing of a bariatric stapling device. The ureteral orifice was closed with a laparoscopic suturing device. The bladder was drained by a catheter for 10 to 14 days postoperatively. Pigs were euthanized on postoperative day 21. Results: All surgical procedures were successfully completed, with no intraoperative complications. One pig had an episode of postoperative clot retention that resolved with catheter irrigation. Each pig was healthy and eating a normal diet prior to euthanasia. Conclusions: This study demonstrates the feasibility of a hybrid transureteral approach to nephrectomy in a survival porcine model. This technique avoids the intentional violation of a second organ system and the risk for peritoneal contamination. Improved instrumentation is needed prior to implementation in the human population. PMID:25489210
NASA Astrophysics Data System (ADS)
Tang, Xiaolin; Yang, Wei; Hu, Xiaosong; Zhang, Dejiu
2017-02-01
In this study, based on our previous work, a novel simplified torsional vibration dynamic model is established to study the torsional vibration characteristics of a compound planetary hybrid propulsion system. The main frequencies of the hybrid driveline are determined. In contrast to vibration characteristics of the previous 16-degree of freedom model, the simplified model can be used to accurately describe the low-frequency vibration property of this hybrid powertrain. This study provides a basis for further vibration control of the hybrid powertrain during the process of engine start/stop.
Modeling and simulation of a hybrid ship power system
NASA Astrophysics Data System (ADS)
Doktorcik, Christopher J.
2011-12-01
Optimizing the performance of naval ship power systems requires integrated design and coordination of the respective subsystems (sources, converters, and loads). A significant challenge in the system-level integration is solving the Power Management Control Problem (PMCP). The PMCP entails deciding on subsystem power usages for achieving a trade-off between the error in tracking a desired position/velocity profile, minimizing fuel consumption, and ensuring stable system operation, while at the same time meeting performance limitations of each subsystem. As such, the PMCP naturally arises at a supervisory level of a ship's operation. In this research, several critical steps toward the solution of the PMCP for surface ships have been undertaken. First, new behavioral models have been developed for gas turbine engines, wound rotor synchronous machines, DC super-capacitors, induction machines, and ship propulsion systems. Conventional models describe system inputs and outputs in terms of physical variables such as voltage, current, torque, and force. In contrast, the behavioral models developed herein express system inputs and outputs in terms of power whenever possible. Additionally, the models have been configured to form a hybrid system-level power model (HSPM) of a proposed ship electrical architecture. Lastly, several simulation studies have been completed to expose the capabilities and limitations of the HSPM.
Quasicycles in the stochastic hybrid Morris-Lecar neural model
NASA Astrophysics Data System (ADS)
Brooks, Heather A.; Bressloff, Paul C.
2015-07-01
Intrinsic noise arising from the stochastic opening and closing of voltage-gated ion channels has been shown experimentally and mathematically to have important effects on a neuron's function. Study of classical neuron models with stochastic ion channels is becoming increasingly important, especially in understanding a cell's ability to produce subthreshold oscillations and to respond to weak periodic stimuli. While it is known that stochastic models can produce oscillations (quasicycles) in parameter regimes where the corresponding deterministic model has only a stable fixed point, little analytical work has been done to explore these connections within the context of channel noise. Using a stochastic hybrid Morris-Lecar (ML) model, we combine a system-size expansion in K+ and a quasi-steady-state (QSS) approximation in persistent Na+ in order to derive an effective Langevin equation that preserves the low-dimensional (planar) structure of the underlying deterministic ML model. (The QSS analysis exploits the fact that persistent Na+ channels are fast.) By calculating the corresponding power spectrum, we determine analytically how noise significantly extends the parameter regime in which subthreshold oscillations occur.
HALM: A Hybrid Asperity Likelihood Model for Italy
NASA Astrophysics Data System (ADS)
Gulia, L.; Wiemer, S.
2009-04-01
The Asperity Likelihood Model (ALM), first developed and currently tested for California, hypothesizes that small-scale spatial variations in the b-value of the Gutenberg and Richter relationship play a central role in forecasting future seismicity (Wiemer and Schorlemmer, SRL, 2007). The physical basis of the model is the concept that the local b-value is inversely dependent on applied shear stress. Thus low b-values (b < 0.7) characterize the locked paches of faults -asperities- from which future mainshocks are more likely to be generated, whereas the high b-values (b > 1.1) found for example in creeping section of faults suggest a lower seismic hazard. To test this model in a reproducible and prospective way suitable for the requirements of the CSEP initiative (www.cseptesting.org), the b-value variability is mapped on a grid. First, using the entire dataset above the overall magnitude of completeness, the regional b-value is estimated. This value is then compared to the one locally estimated at each grid-node for a number of radii, we use the local value if its likelihood score, corrected for the degrees of freedom using the Akaike Information Criterion, suggest to do so. We are currently calibrating the ALM model for implementation in the Italian testing region, the first region within the CSEP EU testing Center (eu.cseptesting.org) for which fully prospective tests of earthquake likelihood models will commence in Europe. We are also developing a modified approach, ‘hybrid' between a grid-based and a zoning one: the HALM (Hybrid Asperity Likelihood Model). According to HALM, the Italian territory is divided in three distinct regions depending on the main tectonic elements, combined with knowledge derived from GPS networks, seismic profile interpretation, borehole breakouts and the focal mechanisms of the event. The local b-value variability was thus mapped using three independent overall b-values. We evaluate the performance of the two models in
NASA Astrophysics Data System (ADS)
Mekonnen, B.; Nazemi, A.; Elshorbagy, A.; Mazurek, K.; Putz, G.
2012-04-01
Modeling the hydrological response in prairie regions, characterized by flat and undulating terrain, and thus, large non-contributing areas, is a known challenge. The hydrological response (runoff) is the combination of the traditional runoff from the hydrologically contributing area and the occasional overflow from the non-contributing area. This study provides a unique opportunity to analyze the issue of fusing the Soil and Water Assessment Tool (SWAT) and Artificial Neural Networks (ANNs) in a hybrid structure to model the hydrological response in prairie regions. A hybrid SWAT-ANN model is proposed, where the SWAT component and the ANN module deal with the effective (contributing) area and the non-contributing area, respectively. The hybrid model is applied to the case study of Moose Jaw watershed, located in southern Saskatchewan, Canada. As an initial exploration, a comparison between ANN and SWAT models is established based on addressing the daily runoff (streamflow) prediction accuracy using multiple error measures. This is done to identify the merits and drawbacks of each modeling approach. It has been found out that the SWAT model has better performance during the low flow periods but with degraded efficiency during periods of high flows. The case is different for the ANN model as ANNs exhibit improved simulation during high flow periods but with biased estimates during low flow periods. The modelling results show that the new hybrid SWAT-ANN model is capable of exploiting the strengths of both SWAT and ANN models in an integrated framrwork. The new hybrid SWAT-ANN model simulates daily runoff quite satisfactorily with NSE measures of 0.80 and 0.83 during calibration and validation periods, respectively. Furthermore, an experimental assessment was performed to identify the effects of the ANN training method on the performance of the hybrid model as well as the parametric identifiability. Overall, the results obtained in this study suggest that the fusion
Hybrid Eulerian-Lagrangian Vortex Model for Turbulent Reacting Flows
NASA Astrophysics Data System (ADS)
Royero, John; Ahmed, Kareem
2016-11-01
A hybrid Eulerian-Lagrangian model for three dimensional large eddy simulations of turbulent reacting flows is presented. The method utilizes a Eulerian grid to resolve large scale flow features and the Lagrangian vortex element method to capture smaller subgrid scale effects and carry out reactions which are then communicated back to the Eulerian grid after a set number of Lagrangian time steps. Lagrangian influences are localized in order to reduce computational cost. The Lagrangian vortex method which utilizes the Helmholtz decomposition of the velocity into potential, expansive, and solenoidal components allows the separation of the various mechanisms contributing to vorticity including gas expansion, diffusion, external body forces and baroclinic torque and is coupled with the Eulerian solver allowing easier implementation in arbitrary reacting flows at a reduced computational cost compared to a pure Lagrangian solver.
Development of a hybrid cloud parameterization for general circulation models
Kao, C.Y.J.; Kristjansson, J.E.; Langley, D.L.
1995-04-01
We have developed a cloud package with state-of-the-art physical schemes that can parameterize low-level stratus or stratocumulus, penetrative cumulus, and high-level cirrus. Such parameterizations will improve cloud simulations in general circulation models (GCMs). The principal tool in this development comprises the physically based Arakawa-Schubert scheme for convective clouds and the Sundqvist scheme for layered, nonconvective clouds. The term {open_quotes}hybrid{close_quotes} addresses the fact that the generation of high-attitude layered clouds can be associated with preexisting convective clouds. Overall, the cloud parameterization package developed should better determine cloud heating and drying effects in the thermodynamic budget, realistic precipitation patterns, cloud coverage and liquid/ice water content for radiation purposes, and the cloud-induced transport and turbulent diffusion for atmospheric trace gases.
Recent developments on the UrQMD hybrid model
Steinheimer, J. Nahrgang, M. Gerhard, J. Schramm, S. Bleicher, M.
2012-06-15
We present recent results from the UrQMD hybrid approach investigating the influence of a deconfinement phase transition on the dynamics of hot and dense nuclear matter. In the hydrodynamic stage an equation of state that incorporates a critical end-point (CEP) in line with lattice data is used. The equation of state describes chiral restoration as well as the deconfinement phase transition. We compare the results from this new equation of state to results obtained by applying a hadron resonance gas equation of state, focusing on bulk observables. Furthermore we will discuss future improvements of the hydrodynamic model. This includes the formulation of chiral fluid dynamics to be able to study the effects of a chiral critical point as well as considerable improvements in terms of computational time which would open up possibilities for observables that require high statistics.
Modeling and optimization of a hybrid solar combined cycle (HYCS)
NASA Astrophysics Data System (ADS)
Eter, Ahmad Adel
2011-12-01
The main objective of this thesis is to investigate the feasibility of integrating concentrated solar power (CSP) technology with the conventional combined cycle technology for electric generation in Saudi Arabia. The generated electricity can be used locally to meet the annual increasing demand. Specifically, it can be utilized to meet the demand during the hours 10 am-3 pm and prevent blackout hours, of some industrial sectors. The proposed CSP design gives flexibility in the operation system. Since, it works as a conventional combined cycle during night time and it switches to work as a hybrid solar combined cycle during day time. The first objective of the thesis is to develop a thermo-economical mathematical model that can simulate the performance of a hybrid solar-fossil fuel combined cycle. The second objective is to develop a computer simulation code that can solve the thermo-economical mathematical model using available software such as E.E.S. The developed simulation code is used to analyze the thermo-economic performance of different configurations of integrating the CSP with the conventional fossil fuel combined cycle to achieve the optimal integration configuration. This optimal integration configuration has been investigated further to achieve the optimal design of the solar field that gives the optimal solar share. Thermo-economical performance metrics which are available in the literature have been used in the present work to assess the thermo-economic performance of the investigated configurations. The economical and environmental impact of integration CSP with the conventional fossil fuel combined cycle are estimated and discussed. Finally, the optimal integration configuration is found to be solarization steam side in conventional combined cycle with solar multiple 0.38 which needs 29 hectare and LEC of HYCS is 63.17 $/MWh under Dhahran weather conditions.
Hybrid Models for Trajectory Error Modelling in Urban Environments
NASA Astrophysics Data System (ADS)
Angelatsa, E.; Parés, M. E.; Colomina, I.
2016-06-01
This paper tackles the first step of any strategy aiming to improve the trajectory of terrestrial mobile mapping systems in urban environments. We present an approach to model the error of terrestrial mobile mapping trajectories, combining deterministic and stochastic models. Due to urban specific environment, the deterministic component will be modelled with non-continuous functions composed by linear shifts, drifts or polynomial functions. In addition, we will introduce a stochastic error component for modelling residual noise of the trajectory error function. First step for error modelling requires to know the actual trajectory error values for several representative environments. In order to determine as accurately as possible the trajectories error, (almost) error less trajectories should be estimated using extracted nonsemantic features from a sequence of images collected with the terrestrial mobile mapping system and from a full set of ground control points. Once the references are estimated, they will be used to determine the actual errors in terrestrial mobile mapping trajectory. The rigorous analysis of these data sets will allow us to characterize the errors of a terrestrial mobile mapping system for a wide range of environments. This information will be of great use in future campaigns to improve the results of the 3D points cloud generation. The proposed approach has been evaluated using real data. The data originate from a mobile mapping campaign over an urban and controlled area of Dortmund (Germany), with harmful GNSS conditions. The mobile mapping system, that includes two laser scanner and two cameras, was mounted on a van and it was driven over a controlled area around three hours. The results show the suitability to decompose trajectory error with non-continuous deterministic and stochastic components.
Modelling human perception processes in pedestrian dynamics: a hybrid approach
Colombi, A.
2017-01-01
In this paper, we present a hybrid mathematical model describing crowd dynamics. More specifically, our approach is based on the well-established Helbing-like discrete model, where each pedestrian is individually represented as a dimensionless point and set to move in order to reach a target destination, with deviations deriving from both physical and social forces. In particular, physical forces account for interpersonal collisions, whereas social components include the individual desire to remain sufficiently far from other walkers (the so-called territorial effect). In this respect, the repulsive behaviour of pedestrians is here set to be different from traditional Helbing-like methods, as it is assumed to be largely determined by how they perceive the presence and the position of neighbouring individuals, i.e. either objectively as pointwise/localized entities or subjectively as spatially distributed masses. The resulting modelling environment is then applied to specific scenarios, that first reproduce a real-world experiment, specifically designed to derive our model hypothesis. Sets of numerical realizations are also run to analyse in more details the pedestrian paths resulting from different types of perception of small groups of static individuals. Finally, analytical investigations formalize and validate from a mathematical point of view selected simulation outcomes.
An Efficient Model-based Diagnosis Engine for Hybrid Systems Using Structural Model Decomposition
NASA Technical Reports Server (NTRS)
Bregon, Anibal; Narasimhan, Sriram; Roychoudhury, Indranil; Daigle, Matthew; Pulido, Belarmino
2013-01-01
Complex hybrid systems are present in a large range of engineering applications, like mechanical systems, electrical circuits, or embedded computation systems. The behavior of these systems is made up of continuous and discrete event dynamics that increase the difficulties for accurate and timely online fault diagnosis. The Hybrid Diagnosis Engine (HyDE) offers flexibility to the diagnosis application designer to choose the modeling paradigm and the reasoning algorithms. The HyDE architecture supports the use of multiple modeling paradigms at the component and system level. However, HyDE faces some problems regarding performance in terms of complexity and time. Our focus in this paper is on developing efficient model-based methodologies for online fault diagnosis in complex hybrid systems. To do this, we propose a diagnosis framework where structural model decomposition is integrated within the HyDE diagnosis framework to reduce the computational complexity associated with the fault diagnosis of hybrid systems. As a case study, we apply our approach to a diagnostic testbed, the Advanced Diagnostics and Prognostics Testbed (ADAPT), using real data.
Status and modeling improvements of hybrid wind/PV/diesel power systems for Brazilian applications
McGowan, J.G.; Manwell, J.F.; Avelar, C.; Taylor, R.
1997-12-31
This paper present a summary of the ongoing work on the modeling and system design of hybrid wind/PV/diesel systems for two different sites in the Amazonia region of Brazil. The work incorporates the latest resource data and is based on the use of the Hybrid2 simulation code developed by the University of Massachusetts and NREL. Details of the baseline operating hybrid systems are reviewed, and the results of the latest detailed hybrid system evaluation for each site are summarized. Based on the system modeling results, separate recommendations for system modification and improvements are made.
Comprehensive thermal modeling of a power-split hybrid powertrain using battery cell model
NASA Astrophysics Data System (ADS)
Mayyas, Abdel Raouf; Omar, Mohammed; Pisu, Pierluigi; Al-Ahmer, Ali; Mayyas, Ahmad; Montes, Carlos; Dongri, Shan
2011-08-01
This manuscript discusses the development of a 3D thermal model for a power-split hybrid powertrain, including its battery modules and power electronics. The 3D model utilizes a finite differencing (FD) heat transfer algorithm, complemented with experimental boundary conditions. The experimental setup is configured to acquire the battery current, voltage, and its inner and surface temperatures in discrete and in full-field scans. The power-split hybrid configuration is tested using a standard and artificial driving cycles. A battery resistance model is then used to couple the experimental boundary conditions with the finite differencing code, which employed a cell-based internal heat generation model to describe the pack chemical reaction mechanism. This study presents a complete analysis based on battery current and voltage in relation to vehicle speed. The proposed model also predicts the powertrain spatial and temporal temperature profiles in agreement with the vehicle actual conditions as indicated by the On-Board Diagnosis (OBD) module.
Tracer Modeling with the Hybrid Coordinates Ocean Model (hycom)
NASA Astrophysics Data System (ADS)
Garraffo, Z. D.; Kim, H.; Li, B.; Mehra, A.; Rivin, I.; Spindler, T.; Tolman, H. L.
2012-12-01
A series of tracer simulations have been started at NCEP/NWS aiming to a variety of applications, from dispersion of contaminants in estimations motivated by the Japanese nuclear accident near Fukushima, to nutrient estimations. The tracer capabilities of HYCOM are used, in regional domains, nested to daily nowcast/forecast fields from 1/12 HYCOM (RTOFS-Global) model output. A Fukushima Cs-137 simulation is now run in operational mode (RTOFS_ET). The simulation was initialized at the time of the Fukushima nuclear accident, and includes atmospheric deposition of Cs-137 and coastal discharge from a high resolution coastal model (ROMS done at NOAA/NOS). Almost all tracer moved offshore before the end of the first year after the accident. The tracer initially deposited in the Pacific ocean through the atmosphere slowly moves eastward and to deeper waters following the 3D ocean circulation. A series of simulations were started for nutrient estimations in the Gulf Stream and Mid Atlantic Bight region. Initially the capabilities implemented in HYCOM are used. The work aims to monitoring nutrients in the chosen region. Work is done in collaboration with Victoria Coles of U. Maryland.
Mobile phone use while driving: a hybrid modeling approach.
Márquez, Luis; Cantillo, Víctor; Arellana, Julián
2015-05-01
The analysis of the effects that mobile phone use produces while driving is a topic of great interest for the scientific community. There is consensus that using a mobile phone while driving increases the risk of exposure to traffic accidents. The purpose of this research is to evaluate the drivers' behavior when they decide whether or not to use a mobile phone while driving. For that, a hybrid modeling approach that integrates a choice model with the latent variable "risk perception" was used. It was found that workers and individuals with the highest education level are more prone to use a mobile phone while driving than others. Also, "risk perception" is higher among individuals who have been previously fined and people who have been in an accident or almost been in an accident. It was also found that the tendency to use mobile phones while driving increases when the traffic speed reduces, but it decreases when the fine increases. Even though the urgency of the phone call is the most important explanatory variable in the choice model, the cost of the fine is an important attribute in order to control mobile phone use while driving.
Weighted Hybrid Decision Tree Model for Random Forest Classifier
NASA Astrophysics Data System (ADS)
Kulkarni, Vrushali Y.; Sinha, Pradeep K.; Petare, Manisha C.
2016-06-01
Random Forest is an ensemble, supervised machine learning algorithm. An ensemble generates many classifiers and combines their results by majority voting. Random forest uses decision tree as base classifier. In decision tree induction, an attribute split/evaluation measure is used to decide the best split at each node of the decision tree. The generalization error of a forest of tree classifiers depends on the strength of the individual trees in the forest and the correlation among them. The work presented in this paper is related to attribute split measures and is a two step process: first theoretical study of the five selected split measures is done and a comparison matrix is generated to understand pros and cons of each measure. These theoretical results are verified by performing empirical analysis. For empirical analysis, random forest is generated using each of the five selected split measures, chosen one at a time. i.e. random forest using information gain, random forest using gain ratio, etc. The next step is, based on this theoretical and empirical analysis, a new approach of hybrid decision tree model for random forest classifier is proposed. In this model, individual decision tree in Random Forest is generated using different split measures. This model is augmented by weighted voting based on the strength of individual tree. The new approach has shown notable increase in the accuracy of random forest.
Modeling, hybridization, and optimal charging of electrical energy storage systems
NASA Astrophysics Data System (ADS)
Parvini, Yasha
The rising rate of global energy demand alongside the dwindling fossil fuel resources has motivated research for alternative and sustainable solutions. Within this area of research, electrical energy storage systems are pivotal in applications including electrified vehicles, renewable power generation, and electronic devices. The approach of this dissertation is to elucidate the bottlenecks of integrating supercapacitors and batteries in energy systems and propose solutions by the means of modeling, control, and experimental techniques. In the first step, the supercapacitor cell is modeled in order to gain fundamental understanding of its electrical and thermal dynamics. The dependence of electrical parameters on state of charge (SOC), current direction and magnitude (20-200 A), and temperatures ranging from -40°C to 60°C was embedded in this computationally efficient model. The coupled electro-thermal model was parameterized using specifically designed temporal experiments and then validated by the application of real world duty cycles. Driving range is one of the major challenges of electric vehicles compared to combustion vehicles. In order to shed light on the benefits of hybridizing a lead-acid driven electric vehicle via supercapacitors, a model was parameterized for the lead-acid battery and combined with the model already developed for the supercapacitor, to build the hybrid battery-supercapacitor model. A hardware in the loop (HIL) setup consisting of a custom built DC/DC converter, micro-controller (muC) to implement the power management strategy, 12V lead-acid battery, and a 16.2V supercapacitor module was built to perform the validation experiments. Charging electrical energy storage systems in an efficient and quick manner, motivated to solve an optimal control problem with the objective of maximizing the charging efficiency for supercapacitors, lead-acid, and lithium ion batteries. Pontryagins minimum principle was used to solve the problems
Kalman Filtered Bio Heat Transfer Model Based Self-adaptive Hybrid Magnetic Resonance Thermometry.
Zhang, Yuxin; Chen, Shuo; Deng, Kexin; Chen, Bingyao; Wei, Xing; Yang, Jiafei; Wang, Shi; Ying, Kui
2017-01-01
To develop a self-adaptive and fast thermometry method by combining the original hybrid magnetic resonance thermometry method and the bio heat transfer equation (BHTE) model. The proposed Kalman filtered Bio Heat Transfer Model Based Self-adaptive Hybrid Magnetic Resonance Thermometry, abbreviated as KalBHT hybrid method, introduced the BHTE model to synthesize a window on the regularization term of the hybrid algorithm, which leads to a self-adaptive regularization both spatially and temporally with change of temperature. Further, to decrease the sensitivity to accuracy of the BHTE model, Kalman filter is utilized to update the window at each iteration time. To investigate the effect of the proposed model, computer heating simulation, phantom microwave heating experiment and dynamic in-vivo model validation of liver and thoracic tumor were conducted in this study. The heating simulation indicates that the KalBHT hybrid algorithm achieves more accurate results without adjusting λ to a proper value in comparison to the hybrid algorithm. The results of the phantom heating experiment illustrate that the proposed model is able to follow temperature changes in the presence of motion and the temperature estimated also shows less noise in the background and surrounding the hot spot. The dynamic in-vivo model validation with heating simulation demonstrates that the proposed model has a higher convergence rate, more robustness to susceptibility problem surrounding the hot spot and more accuracy of temperature estimation. In the healthy liver experiment with heating simulation, the RMSE of the hot spot of the proposed model is reduced to about 50% compared to the RMSE of the original hybrid model and the convergence time becomes only about one fifth of the hybrid model. The proposed model is able to improve the accuracy of the original hybrid algorithm and accelerate the convergence rate of MR temperature estimation.
Forecasting Stock Exchange Movements Using Artificial Neural Network Models and Hybrid Models
NASA Astrophysics Data System (ADS)
Güreşen, Erkam; Kayakutlu, Gülgün
Forecasting stock exchange rates is an important financial problem that is receiving increasing attention. During the last few years, a number of neural network models and hybrid models have been proposed for obtaining accurate prediction results, in an attempt to outperform the traditional linear and nonlinear approaches. This paper evaluates the effectiveness of neural network models; recurrent neural network (RNN), dynamic artificial neural network (DAN2) and the hybrid neural networks which use generalized autoregressive conditional heteroscedasticity (GARCH) and exponential generalized autoregressive conditional heteroscedasticity (EGARCH) to extract new input variables. The comparison for each model is done in two view points: MSE and MAD using real exchange daily rate values of Istanbul Stock Exchange (ISE) index XU10).
Vector/dyad notation in computer symbolic modeling of hybrid parameter mechanical systems
Barhorst, A.A.
1996-11-01
In this paper, computer symbolic algebra based algorithms written to take advantage of engineering vector notation, as applied to hybrid parameter mechanical systems, are demonstrated. The symbolic manipulation tools are utilized to implement a hybrid parameter system modeling algorithm previously developed by the author. The modeling algorithm produces minimal holonomic and nonholonomic equations of motion for hybrid systems of any continuum dimension and kinematic topology. Boundary conditions are rigorously supplied by the modeling method. The system model presented as an example is a hybrid parameter planar two link model of a robot manipulator. A complete analysis from model to simulation and animation in a Mathematica notebook is presented. The modeling tools presented herein are applicable for researchers, practicing engineers, and students in advanced dynamic system modeling and control courses.
A formal hybrid modeling scheme for handling discontinuities in physical system models
Mosterman, P.J.; Biswas, G.
1996-12-31
Physical systems are by nature continuous, but often exhibit nonlinearities that make behavior generation complex and hard to analyze. Complexity is often reduced by linearizing model constraints and by abstracting the time scale for behavior generation. In either case, the physical components are modeled to operate in multiple modes, with abrupt changes between modes. This paper discusses a hybrid modeling methodology and analysis algorithms that combine continuous energy flow modeling and localized discrete signal flow modeling to generate complex, multi-mode behavior in a consistent and correct manner. Energy phase space analysis is employed to demonstrate the correctness of the algorithm, and the reachability of a continuous mode.
Hybrid E-Learning Acceptance Model: Learner Perceptions
ERIC Educational Resources Information Center
Ahmed, Hassan M. Selim
2010-01-01
E-learning tools and technologies have been used to supplement conventional courses in higher education institutions creating a "hybrid" e-learning module that aims to enhance the learning experiences of students. Few studies have addressed the acceptance of hybrid e-learning by learners and the factors affecting the learners'…
Development of hybrid 3-D hydrological modeling for the NCAR Community Earth System Model (CESM)
Zeng, Xubin; Troch, Peter; Pelletier, Jon; Niu, Guo-Yue; Gochis, David
2015-11-15
This is the Final Report of our four-year (3-year plus one-year no cost extension) collaborative project between the University of Arizona (UA) and the National Center for Atmospheric Research (NCAR). The overall objective of our project is to develop and evaluate the first hybrid 3-D hydrological model with a horizontal grid spacing of 1 km for the NCAR Community Earth System Model (CESM).
Hybrid Network Defense Model Based on Fuzzy Evaluation
2014-01-01
With sustained and rapid developments in the field of information technology, the issue of network security has become increasingly prominent. The theme of this study is network data security, with the test subject being a classified and sensitive network laboratory that belongs to the academic network. The analysis is based on the deficiencies and potential risks of the network's existing defense technology, characteristics of cyber attacks, and network security technologies. Subsequently, a distributed network security architecture using the technology of an intrusion prevention system is designed and implemented. In this paper, first, the overall design approach is presented. This design is used as the basis to establish a network defense model, an improvement over the traditional single-technology model that addresses the latter's inadequacies. Next, a distributed network security architecture is implemented, comprising a hybrid firewall, intrusion detection, virtual honeynet projects, and connectivity and interactivity between these three components. Finally, the proposed security system is tested. A statistical analysis of the test results verifies the feasibility and reliability of the proposed architecture. The findings of this study will potentially provide new ideas and stimuli for future designs of network security architecture. PMID:24574870
Hybrid CMS methods with model reduction for assembly of structures
NASA Technical Reports Server (NTRS)
Farhat, Charbel
1991-01-01
Future on-orbit structures will be designed and built in several stages, each with specific control requirements. Therefore there must be a methodology which can predict the dynamic characteristics of the assembled structure, based on the dynamic characteristics of the subassemblies and their interfaces. The methodology developed by CSC to address this issue is Hybrid Component Mode Synthesis (HCMS). HCMS distinguishes itself from standard component mode synthesis algorithms in the following features: (1) it does not require the subcomponents to have displacement compatible models, which makes it ideal for analyzing the deployment of heterogeneous flexible multibody systems, (2) it incorporates a second-level model reduction scheme at the interface, which makes it much faster than other algorithms and therefore suitable for control purposes, and (3) it does answer specific questions such as 'how does the global fundamental frequency vary if I change the physical parameters of substructure k by a specified amount?'. Because it is based on an energy principle rather than displacement compatibility, this methodology can also help the designer to define an assembly process. Current and future efforts are devoted to applying the HCMS method to design and analyze docking and berthing procedures in orbital construction.
A Hybrid Fuzzy Model for Lean Product Development Performance Measurement
NASA Astrophysics Data System (ADS)
Osezua Aikhuele, Daniel; Mohd Turan, Faiz
2016-02-01
In the effort for manufacturing companies to meet up with the emerging consumer demands for mass customized products, many are turning to the application of lean in their product development process, and this is gradually moving from being a competitive advantage to a necessity. However, due to lack of clear understanding of the lean performance measurements, many of these companies are unable to implement and fully integrated the lean principle into their product development process. Extensive literature shows that only few studies have focus systematically on the lean product development performance (LPDP) evaluation. In order to fill this gap, the study therefore proposed a novel hybrid model based on Fuzzy Reasoning Approach (FRA), and the extension of Fuzzy-AHP and Fuzzy-TOPSIS methods for the assessment of the LPDP. Unlike the existing methods, the model considers the importance weight of each of the decision makers (Experts) since the performance criteria/attributes are required to be rated, and these experts have different level of expertise. The rating is done using a new fuzzy Likert rating scale (membership-scale) which is designed such that it can address problems resulting from information lost/distortion due to closed-form scaling and the ordinal nature of the existing Likert scale.
Hybrid network defense model based on fuzzy evaluation.
Cho, Ying-Chiang; Pan, Jen-Yi
2014-01-01
With sustained and rapid developments in the field of information technology, the issue of network security has become increasingly prominent. The theme of this study is network data security, with the test subject being a classified and sensitive network laboratory that belongs to the academic network. The analysis is based on the deficiencies and potential risks of the network's existing defense technology, characteristics of cyber attacks, and network security technologies. Subsequently, a distributed network security architecture using the technology of an intrusion prevention system is designed and implemented. In this paper, first, the overall design approach is presented. This design is used as the basis to establish a network defense model, an improvement over the traditional single-technology model that addresses the latter's inadequacies. Next, a distributed network security architecture is implemented, comprising a hybrid firewall, intrusion detection, virtual honeynet projects, and connectivity and interactivity between these three components. Finally, the proposed security system is tested. A statistical analysis of the test results verifies the feasibility and reliability of the proposed architecture. The findings of this study will potentially provide new ideas and stimuli for future designs of network security architecture.
Hybrid Simulation Modeling to Estimate U.S. Energy Elasticities
NASA Astrophysics Data System (ADS)
Baylin-Stern, Adam C.
This paper demonstrates how an U.S. application of CIMS, a technologically explicit and behaviourally realistic energy-economy simulation model which includes macro-economic feedbacks, can be used to derive estimates of elasticity of substitution (ESUB) and autonomous energy efficiency index (AEEI) parameters. The ability of economies to reduce greenhouse gas emissions depends on the potential for households and industry to decrease overall energy usage, and move from higher to lower emissions fuels. Energy economists commonly refer to ESUB estimates to understand the degree of responsiveness of various sectors of an economy, and use estimates to inform computable general equilibrium models used to study climate policies. Using CIMS, I have generated a set of future, 'pseudo-data' based on a series of simulations in which I vary energy and capital input prices over a wide range. I then used this data set to estimate the parameters for transcendental logarithmic production functions using regression techniques. From the production function parameter estimates, I calculated an array of elasticity of substitution values between input pairs. Additionally, this paper demonstrates how CIMS can be used to calculate price-independent changes in energy-efficiency in the form of the AEEI, by comparing energy consumption between technologically frozen and 'business as usual' simulations. The paper concludes with some ideas for model and methodological improvement, and how these might figure into future work in the estimation of ESUBs from CIMS. Keywords: Elasticity of substitution; hybrid energy-economy model; translog; autonomous energy efficiency index; rebound effect; fuel switching.
Modeling and design of a high-performance hybrid actuator
NASA Astrophysics Data System (ADS)
Aloufi, Badr; Behdinan, Kamran; Zu, Jean
2016-12-01
This paper presents the model and design of a novel hybrid piezoelectric actuator which provides high active and passive performances for smart structural systems. The actuator is composed of a pair of curved pre-stressed piezoelectric actuators, so-called commercially THUNDER actuators, installed opposite each other using two clamping mechanisms constructed of in-plane fixable hinges, grippers and solid links. A fully mathematical model is developed to describe the active and passive dynamics of the actuator and investigate the effects of its geometrical parameters on the dynamic stiffness, free displacement and blocked force properties. Among the literature that deals with piezoelectric actuators in which THUNDER elements are used as a source of electromechanical power, the proposed study is unique in that it presents a mathematical model that has the ability to predict the actuator characteristics and achieve other phenomena, such as resonances, mode shapes, phase shifts, dips, etc. For model validation, the measurements of the free dynamic response per unit voltage and passive acceleration transmissibility of a particular actuator design are used to check the accuracy of the results predicted by the model. The results reveal that there is a good agreement between the model and experiment. Another experiment is performed to teste the linearity of the actuator system by examining the variation of the output dynamic responses with varying forces and voltages at different frequencies. From the results, it can be concluded that the actuator acts approximately as a linear system at frequencies up to 1000 Hz. A parametric study is achieved here by applying the developed model to analyze the influence of the geometrical parameters of the fixable hinges on the active and passive actuator properties. The model predictions in the frequency range of 0-1000 Hz show that the hinge thickness, radius, and opening angle parameters have great effects on the frequency dynamic
Three hybridization models based on local search scheme for job shop scheduling problem
NASA Astrophysics Data System (ADS)
Balbi Fraga, Tatiana
2015-05-01
This work presents three different hybridization models based on the general schema of Local Search Heuristics, named Hybrid Successive Application, Hybrid Neighborhood, and Hybrid Improved Neighborhood. Despite similar approaches might have already been presented in the literature in other contexts, in this work these models are applied to analyzes the solution of the job shop scheduling problem, with the heuristics Taboo Search and Particle Swarm Optimization. Besides, we investigate some aspects that must be considered in order to achieve better solutions than those obtained by the original heuristics. The results demonstrate that the algorithms derived from these three hybrid models are more robust than the original algorithms and able to get better results than those found by the single Taboo Search.
Advances in modeling of lower hybrid current drive
NASA Astrophysics Data System (ADS)
Peysson, Y.; Decker, J.; Nilsson, E.; Artaud, J.-F.; Ekedahl, A.; Goniche, M.; Hillairet, J.; Ding, B.; Li, M.; Bonoli, P. T.; Shiraiwa, S.; Madi, M.
2016-04-01
First principle modeling of the lower hybrid (LH) current drive in tokamak plasmas is a longstanding activity, which is gradually gaining in accuracy thanks to quantitative comparisons with experimental observations. The ability to reproduce simulatenously the plasma current and the non-thermal bremsstrahlung radial profiles in the hard x-ray (HXR) photon energy range represents in this context a significant achievement. Though subject to limitations, ray tracing calculations are commonly used for describing wave propagation in conjunction with Fokker-Planck codes, as it can capture prominent features of the LH wave dynamics in a tokamak plasma-like toroidal refraction. This tool has been validated on several machines when the full absorption of the LH wave requires the transfer of a small fraction of power from the main lobes of the launched power spectrum to a tail at a higher parallel refractive index. Conversely, standard modeling based on toroidal refraction only becomes more challenging when the spectral gap is large, except if other physical mechanisms may dominate to bridge it, like parametric instabilities, as suggested for JET LH discharges (Cesario et al 2004 Phys. Rev. Lett. 92 175002), or fast fluctuations of the launched power spectrum or ‘tail’ LH model, as shown for Tore Supra (Decker et al 2014 Phys. Plasma 21 092504). The applicability of the heuristic ‘tail’ LH model is investigated for a broader range of plasma parameters as compared to the Tore Supra study and with different LH wave characteristics. Discrepancies and agreements between simulations and experiments depending upon the different models used are discussed. The existence of a ‘tail’ in the launched power spectrum significantly improves the agreement between modeling and experiments in plasma conditions for which the spectral gap is large in EAST and Alcator C-Mod tokamaks. For the Alcator C-Mod tokamak, the experimental evolution of the HXR profiles with density suggests
Field Test of a Hybrid Finite-Difference and Analytic Element Regional Model.
Abrams, D B; Haitjema, H M; Feinstein, D T; Hunt, R J
2016-01-01
Regional finite-difference models often have cell sizes that are too large to sufficiently model well-stream interactions. Here, a steady-state hybrid model is applied whereby the upper layer or layers of a coarse MODFLOW model are replaced by the analytic element model GFLOW, which represents surface waters and wells as line and point sinks. The two models are coupled by transferring cell-by-cell leakage obtained from the original MODFLOW model to the bottom of the GFLOW model. A real-world test of the hybrid model approach is applied on a subdomain of an existing model of the Lake Michigan Basin. The original (coarse) MODFLOW model consists of six layers, the top four of which are aggregated into GFLOW as a single layer, while the bottom two layers remain part of MODFLOW in the hybrid model. The hybrid model and a refined "benchmark" MODFLOW model simulate similar baseflows. The hybrid and benchmark models also simulate similar baseflow reductions due to nearby pumping when the well is located within the layers represented by GFLOW. However, the benchmark model requires refinement of the model grid in the local area of interest, while the hybrid approach uses a gridless top layer and is thus unaffected by grid discretization errors. The hybrid approach is well suited to facilitate cost-effective retrofitting of existing coarse grid MODFLOW models commonly used for regional studies because it leverages the strengths of both finite-difference and analytic element methods for predictions in mildly heterogeneous systems that can be simulated with steady-state conditions.
Predicting System Accidents with Model Analysis During Hybrid Simulation
NASA Technical Reports Server (NTRS)
Malin, Jane T.; Fleming, Land D.; Throop, David R.
2002-01-01
Standard discrete event simulation is commonly used to identify system bottlenecks and starving and blocking conditions in resources and services. The CONFIG hybrid discrete/continuous simulation tool can simulate such conditions in combination with inputs external to the simulation. This provides a means for evaluating the vulnerability to system accidents of a system's design, operating procedures, and control software. System accidents are brought about by complex unexpected interactions among multiple system failures , faulty or misleading sensor data, and inappropriate responses of human operators or software. The flows of resource and product materials play a central role in the hazardous situations that may arise in fluid transport and processing systems. We describe the capabilities of CONFIG for simulation-time linear circuit analysis of fluid flows in the context of model-based hazard analysis. We focus on how CONFIG simulates the static stresses in systems of flow. Unlike other flow-related properties, static stresses (or static potentials) cannot be represented by a set of state equations. The distribution of static stresses is dependent on the specific history of operations performed on a system. We discuss the use of this type of information in hazard analysis of system designs.
Data driven components in a model of inner shelf sorted bedforms: a new hybrid model
NASA Astrophysics Data System (ADS)
Goldstein, E. B.; Coco, G.; Murray, A. B.; Green, M. O.
2013-10-01
Numerical models rely on the parameterization of processes that often lack a deterministic description. In this contribution we demonstrate the applicability of using machine learning, optimization tools from the discipline of computer science, to develop parameterizations when extensive data sets exist. We develop a new predictor for near bed suspended sediment reference concentration under unbroken waves using genetic programming, a machine learning technique. This newly developed parameterization performs better than existing empirical predictors. We add this new predictor into an established model for inner shelf sorted bedforms. Additionally we incorporate a previously reported machine learning derived predictor for oscillatory flow ripples into the sorted bedform model. This new "hybrid" sorted bedform model, whereby machine learning components are integrated into a numerical model, demonstrates a method of incorporating observational data (filtered through a machine learning algorithm) directly into a numerical model. Results suggest that the new hybrid model is able to capture dynamics previously absent from the model, specifically, the two observed pattern modes of sorted bedforms. However, caveats exist when data driven components do not have parity with traditional theoretical components of morphodynamic models, and we discuss the challenges of integrating these disparate pieces and the future of this type of modeling.
Rezvani, Alireza; Khalili, Abbas; Mazareie, Alireza; Gandomkar, Majid
2016-07-01
Nowadays, photovoltaic (PV) generation is growing increasingly fast as a renewable energy source. Nevertheless, the drawback of the PV system is its dependence on weather conditions. Therefore, battery energy storage (BES) can be considered to assist for a stable and reliable output from PV generation system for loads and improve the dynamic performance of the whole generation system in grid connected mode. In this paper, a novel topology of intelligent hybrid generation systems with PV and BES in a DC-coupled structure is presented. Each photovoltaic cell has a specific point named maximum power point on its operational curve (i.e. current-voltage or power-voltage curve) in which it can generate maximum power. Irradiance and temperature changes affect these operational curves. Therefore, the nonlinear characteristic of maximum power point to environment has caused to development of different maximum power point tracking techniques. In order to capture the maximum power point (MPP), a hybrid fuzzy-neural maximum power point tracking (MPPT) method is applied in the PV system. Obtained results represent the effectiveness and superiority of the proposed method, and the average tracking efficiency of the hybrid fuzzy-neural is incremented by approximately two percentage points in comparison to the conventional methods. It has the advantages of robustness, fast response and good performance. A detailed mathematical model and a control approach of a three-phase grid-connected intelligent hybrid system have been proposed using Matlab/Simulink.
Clifton, Shari; Jo, Phill
2016-01-01
To facilitate systematic learning and to complement the limitations of conventional one-shot library instruction sessions, a hybrid embedded instruction model was designed and implemented for undergraduate students and residents in three disciplines at the University of Oklahoma Health Sciences Center. Variations of hybrid instruction are explored, including models that combine face-to-face interactions, online content delivery, flipped instruction techniques, and individual consultations. The hybrid model highlights benefits of collaborative teaching between course faculty members and librarians and enhances the relevance of library instruction for users.
A hybrid model to simulate the annual runoff of the Kaidu River in northwest China
NASA Astrophysics Data System (ADS)
Xu, Jianhua; Chen, Yaning; Bai, Ling; Xu, Yiwen
2016-04-01
Fluctuant and complicated hydrological processes can result in the uncertainty of runoff forecasting. Thus, it is necessary to apply the multi-method integrated modeling approaches to simulate runoff. Integrating the ensemble empirical mode decomposition (EEMD), the back-propagation artificial neural network (BPANN) and the nonlinear regression equation, we put forward a hybrid model to simulate the annual runoff (AR) of the Kaidu River in northwest China. We also validate the simulated effects by using the coefficient of determination (R2) and the Akaike information criterion (AIC) based on the observed data from 1960 to 2012 at the Dashankou hydrological station. The average absolute and relative errors show the high simulation accuracy of the hybrid model. R2 and AIC both illustrate that the hybrid model has a much better performance than the single BPANN. The hybrid model and integrated approach elicited by this study can be applied to simulate the annual runoff of similar rivers in northwest China.
A Hybrid Sensitivity Analysis Approach for Agent-based Disease Spread Models
Pullum, Laura L; Cui, Xiaohui
2012-01-01
Agent-based models (ABM) have been widely deployed in different fields for studying the collective behavior of large numbers of interacting agents. Of particular interest lately is the application of agent-based and hybrid models to epidemiology, specifically Agent-based Disease Spread Models (ABDSM). Validation (one aspect of the means to achieve dependability) of ABDSM simulation models is extremely important. It ensures that the right model has been built and lends confidence to the use of that model to inform critical decisions. In this report, we describe our preliminary efforts in ABDSM validation by using hybrid model fusion technology.
Ordóñez, Fco. Javier; de Toledo, Paula; Sanchis, Araceli
2013-01-01
Activities of daily living are good indicators of elderly health status, and activity recognition in smart environments is a well-known problem that has been previously addressed by several studies. In this paper, we describe the use of two powerful machine learning schemes, ANN (Artificial Neural Network) and SVM (Support Vector Machines), within the framework of HMM (Hidden Markov Model) in order to tackle the task of activity recognition in a home setting. The output scores of the discriminative models, after processing, are used as observation probabilities of the hybrid approach. We evaluate our approach by comparing these hybrid models with other classical activity recognition methods using five real datasets. We show how the hybrid models achieve significantly better recognition performance, with significance level p < 0.05, proving that the hybrid approach is better suited for the addressed domain. PMID:23615583
An integrated hybrid spatial-compartmental modeling approach is presented for analyzing the dynamic distribution of chemicals in the multimedia environment. Information obtained from such analysis, which includes temporal chemical concentration profiles in various media, mass ...
Validation of a hybrid two-site gamma model for naphthalene desorption kinetics
Ahn, I.S.; Lion, L.W.; Shuler, M.L.
1999-09-15
Three models for sorption/desorption of polycyclic aromatic hydrocarbon (PAH) contaminants from soil were compared for their ability to predict the transport of PAH in soil: a gamma model, a two-site/two-region nonequilibrium model, and a hybrid model. In the hybrid model, soil organic matter was conceptually divided into two compartments; a fraction with rapid sorption/desorption kinetics and a compartment with mass-transfer-limited kinetics. Contaminant sorbed in the rapid compartment was assumed to be in instantaneous equilibrium with the aqueous phase, while the release of contaminant from the slow fraction was assumed to be governed by a gamma distribution of rate coefficients. The hybrid model successfully described the initial rapid release of a model PAH contaminant, naphthalene, from a sieved soil sample of moderate organic content ({approx_equal} 2.3%) as well as the following slow release observed over 25 days in batch desorption experiments. Other necessary model parameters, such as the hydrodynamic dispersion coefficient of naphthalene and the macropore porosity, were evaluated in separate experiments. A transport model incorporating the hybrid model for naphthalene sorption/desorption successfully predicted the elution profile of naphthalene in independent soil-column experiments with no adjustable parameters. The success of the hybrid model suggests that a wide array of rate controls govern PAH desorption. This conclusion is consistent with the view of soils as consisting of a mix of different sorptive constituents and heterogeneous physical constraints on PAH release.
Formal methods for modeling and analysis of hybrid systems
NASA Technical Reports Server (NTRS)
Tiwari, Ashish (Inventor); Lincoln, Patrick D. (Inventor)
2009-01-01
A technique based on the use of a quantifier elimination decision procedure for real closed fields and simple theorem proving to construct a series of successively finer qualitative abstractions of hybrid automata is taught. The resulting abstractions are always discrete transition systems which can then be used by any traditional analysis tool. The constructed abstractions are conservative and can be used to establish safety properties of the original system. The technique works on linear and non-linear polynomial hybrid systems: the guards on discrete transitions and the continuous flows in all modes can be specified using arbitrary polynomial expressions over the continuous variables. An exemplar tool in the SAL environment built over the theorem prover PVS is detailed. The technique scales well to large and complex hybrid systems.
Assar, Rodrigo; Montecino, Martín A; Maass, Alejandro; Sherman, David J
2014-07-01
In order to describe the dynamic behavior of a complex biological system, it is useful to combine models integrating processes at different levels and with temporal dependencies. Such combinations are necessary for modeling acclimatization, a phenomenon where changes in environmental conditions can induce drastic changes in the behavior of a biological system. In this article we formalize the use of hybrid systems as a tool to model this kind of biological behavior. A modeling scheme called strong switches is proposed. It allows one to take into account both minor adjustments to the coefficients of a continuous model, and, more interestingly, large-scale changes to the structure of the model. We illustrate the proposed methodology with two applications: acclimatization in wine fermentation kinetics, and acclimatization of osteo-adipo differentiation system linking stimulus signals to bone mass.
Nandola, Naresh N.; Rivera, Daniel E.
2011-01-01
This paper presents a data-centric modeling and predictive control approach for nonlinear hybrid systems. System identification of hybrid systems represents a challenging problem because model parameters depend on the mode or operating point of the system. The proposed algorithm applies Model-on-Demand (MoD) estimation to generate a local linear approximation of the nonlinear hybrid system at each time step, using a small subset of data selected by an adaptive bandwidth selector. The appeal of the MoD approach lies in the fact that model parameters are estimated based on a current operating point; hence estimation of locations or modes governed by autonomous discrete events is achieved automatically. The local MoD model is then converted into a mixed logical dynamical (MLD) system representation which can be used directly in a model predictive control (MPC) law for hybrid systems using multiple-degree-of-freedom tuning. The effectiveness of the proposed MoD predictive control algorithm for nonlinear hybrid systems is demonstrated on a hypothetical adaptive behavioral intervention problem inspired by Fast Track, a real-life preventive intervention for improving parental function and reducing conduct disorder in at-risk children. Simulation results demonstrate that the proposed algorithm can be useful for adaptive intervention problems exhibiting both nonlinear and hybrid character. PMID:21874087
NASA Astrophysics Data System (ADS)
Kobayashi, Koichi; Hiraishi, Kunihiko
The model predictive/optimal control problem for hybrid systems is reduced to a mixed integer quadratic programming (MIQP) problem. However, the MIQP problem has one serious weakness, i.e., the computation time to solve the MIQP problem is too long for practical plants. For overcoming this technical issue, there are several approaches. In this paper, a modeling of mode transition constraints, which are expressed by a directed graph, is focused, and a new method to represent a directed graph is proposed. The effectiveness of the proposed method is shown by numerical examples on linear switched systems and piecewise linear systems.
Modern constraints on F-term SUSY hybrid inflation models
NASA Astrophysics Data System (ADS)
Civiletti, Matthew
We study modifications of supersymmetric hybrid inflation, which continues to be one of the most popular inflationary models. The seminal formulation considered the VG+Delta V potential, in which one can show that [special characters ommitted], which indicates that the breaking scale M ˜ 1016 GeV. This is a non-trivial fact, and provides a clue the group may be a Grand Unified Theory (GUT). Inspired by this, we consider inflating while constraining the breaking scale M at the MSSM gauge coupling unification scale, 2.86 x 1016 GeV. We show that one can inflate successfully; in particular, we use non-minimal Kahler to achieve, for the recent Planck bounds 0.945 < ns < 0.975, r ≃ 3 x 10--4 in the case where V is bounded from below, and r ≃ 1 x 10--2 where this condition is relaxed. Unfortunately, GUTs tend to predict topological defects. To ameliorate this problem, we consider the addition of a Planck-suppressed term which gives rise to shifted inflation, where one inflates in a similar way except that ∥φ∥ ≠ 0. We show that one can inflate successfully; one achieves similar results as in the standard case, including the large r solutions particular to non-minimal Kahler contributions. We achieve r ≃ 0.02, which is similar to the non-minimal standard case. Finally, we consider a generalization of the model to include Planck-suppressed R-symmetry violation, parametrized by alpha. One can generate masses more naturally in MSSM by treating R-symmetry as approximate, and we discover that, keeping to the standard inflationary track ∥φ∥ = 0, the effect is to raise r in the preferred ns range by about four orders of magnitude as compared with the standard case, for alpha ≃ 10--9. By considering alpha ≃ 10--7, one can achieve r ≃ 10 --4. This is fairly remarkable in that it is done with only minimal Kahler.
Synthesis of a hybrid model of the VSC FACTS devices and HVDC technologies
NASA Astrophysics Data System (ADS)
Borovikov, Yu S.; Gusev, A. S.; Sulaymanov, A. O.; Ufa, R. A.
2014-10-01
The motivation of the presented research is based on the need for development of new methods and tools for adequate simulation of FACTS devices and HVDC systems as part of real electric power systems (EPS). The Research object: An alternative hybrid approach for synthesizing VSC-FACTS and -HVDC hybrid model is proposed. The results: the VSC- FACTS and -HVDC hybrid model is designed in accordance with the presented concepts of hybrid simulation. The developed model allows us to carry out adequate simulation in real time of all the processes in HVDC, FACTS devices and EPS as a whole without any decomposition and limitation on their duration, and also use the developed tool for effective solution of a design, operational and research tasks of EPS containing such devices.
FISH-ing for Genes: Modeling Fluorescence "in situ" Hybridization
ERIC Educational Resources Information Center
Baker, William P.; Jones, Carleton Buck
2006-01-01
Teaching methods of genetic analysis such as fluorescence in situ hybridization (FISH) can be an important part of instructional units in biology, microbiology, and biotechnology. Experience, however, indicates that these topics are difficult for many students. The authors of this article describe how they created an activity that effectively…
Applying a Hybrid Model: Can It Enhance Student Learning Outcomes?
ERIC Educational Resources Information Center
Potter, Jodi
2015-01-01
There has been a marked increase in the use of online learning over the past decade. There remains conflict in the current body of research on the efficacy of online versus face to face learning in these environments. One resolution of these issues is the hybrid learning option which is a combination of face-to-face classroom instruction with…
Hybrid resist model to enhance continuous process window model for OPC
NASA Astrophysics Data System (ADS)
Zhang, Qiaolin; Lucas, Kevin
2008-05-01
As the semiconductor industry enters the 45nm node and beyond, the tolerable lithography process window significantly shrinks due to the decreasing k1 factor and increasing lens NA required to meet product shrink goals. The usable depth of focus at the 45nm node for critical layer is less than 200nm and for the 32nm node it will approach 100nm. Consequently, process window aware Optical Proximity Correction (OPC) and Lithography Rule Check (LRC) become crucial to ensure the robustness of OPC to focus and dose variation. An accurately calibrated continuous process window model is the corner stone for successful process variation aware OPC and LRC. For ease of use, this calibrated model should be a continuous function of defocus and dose and able to interpolate and extrapolate in the usable process window. Lithographic proximity effects have an optical component and a resist component. As state of the art OPC simulation tool is capable of precise and fast optical simulation, however its treatment of chemical amplified resist effects is relatively crude and does not capture the complex behavior during acid & quencher reaction, diffusion and development. This in turn causes difficulties for a continuous process window model where the resist component plays an important role. We proposed a hybrid resist model, which is a superposition of a traditional OPC chemical amplified resist model and a first order resist bias model. Using Synopsys' OPC modeling software package-ProGen, we incorporated this hybrid resist model into the continuous process window (PW) modeling module, and very good model calibration performance was achieved.
Cao, J.; Bharathan, D.; Emadi, A.
2007-01-01
Isolated gate bipolar transistors (IGBTs) are widely used in power electronic applications including electric, hybrid electric, and plug-in hybrid electric vehicles (EVs, HEVs, and PHEVs). The trend towards more electric vehicles (MEVs) has demanded the need for power electronic devices capable of handling power in the range of 10-100 kW. However, the converter losses in this power range are of critical importance. Therefore, thermal management of the power electronic devices/converters is crucial for the reliability and longevity of the advanced vehicles. To aid the design of heat exchangers for the IGBT modules used in propulsion motor drives, a loss model for the IGBTs is necessary. The loss model of the IGBTs will help in the process of developing new heat exchangers and advanced thermal interface materials by reducing cost and time. This paper deals with the detailed loss modeling of IGBTs for advanced electrical propulsion systems. An experimental based loss model is proposed. The proposed loss calculation method utilizes the experimental data to reconstruct the loss surface of the power electronic devices by means of curve fitting and linear extrapolating. This enables the calculation of thermal losses in different voltage, current, and temperature conditions of operation. To verify the calculation method, an experimental test set-up was designed and built. The experimental set-up is an IGBT based bi-directional DC/DC converter. In addition, simulation results are presented to verify the proposed calculation method.
Hybrid Model for Cascading Outage in a Power System: A Numerical Study
NASA Astrophysics Data System (ADS)
Susuki, Yoshihiko; Takatsuji, Yu; Hikihara, Takashi
Analysis of cascading outages in power systems is important for understanding why large blackouts emerge and how to prevent them. Cascading outages are complex dynamics of power systems, and one cause of them is the interaction between swing dynamics of synchronous machines and protection operation of relays and circuit breakers. This paper uses hybrid dynamical systems as a mathematical model for cascading outages caused by the interaction. Hybrid dynamical systems can combine families of flows describing swing dynamics with switching rules that are based on protection operation. This paper refers to data on a cascading outage in the September 2003 blackout in Italy and shows a hybrid dynamical system by which propagation of outages reproduced is consistent with the data. This result suggests that hybrid dynamical systems can provide an effective model for the analysis of cascading outages in power systems.
Hybrid experimental/analytical models of structural dynamics - Creation and use for predictions
NASA Technical Reports Server (NTRS)
Balmes, Etienne
1993-01-01
An original complete methodology for the construction of predictive models of damped structural vibrations is introduced. A consistent definition of normal and complex modes is given which leads to an original method to accurately identify non-proportionally damped normal mode models. A new method to create predictive hybrid experimental/analytical models of damped structures is introduced, and the ability of hybrid models to predict the response to system configuration changes is discussed. Finally a critical review of the overall methodology is made by application to the case of the MIT/SERC interferometer testbed.
Validation of biological models with temporal logic and Timed Hybrid Petri Nets.
Troncale, Sylvie; Comet, Jean-Paul; Bernot, Gilles
2007-01-01
The Hybrid Functional Petri Nets (HFPN) formalism has shown its convenience for modelling biological systems. This class of models has been fruitfully applied in biology but the remarkable expressiveness of HFPN often leads to incomplete validations. In this paper, we propose a logical framework for Timed Hybrid Petri Nets (THPN), a sub-class of HFPN. We propose an extension of Event Clock Logic dedicated to THPN and a procedure to convert a THPN into a real-time automaton. A small biological model shows that our framework allows us to formally prove properties by a well suited model-checking procedure.
A hybridization model for the plasmon response of complex nanostructures
NASA Astrophysics Data System (ADS)
Prodan, Emil; Radloff, Corey; Halas, Naomi; Nordlander, Peter
2004-03-01
We discuss a simple and intuitive method, an electromagnetic analog of molecular orbital theory, to describe the plasmon response of complex nanostructures of arbitrary shape, (Science 302(2003)419-422). The method expresses the plasmon response of complex or composite nanoparticles as resulting from the interaction or "hybridization" of elementary plasmons supported by nanostructures of elementary geometries. As an example, the approach is applied to the important cases of metallic nanoshells and concentric multishell structures, nanomatryushkas. For the nanoshell, the plasmons can be described as resulting from the interaction between the cavity plasmon localized around the inner surface of the shell and a solid sphere plasmon localized around the outer surface of the shell. For the multishell structure, the plasmons can be viewed as resulting from the hybridization of the individual nanoshell plasmons on the different metallic shells. Work supported by ARO, TATP and the Robert A. Welch Foundation
Optimization of ultrasonic array inspections using an efficient hybrid model and real crack shapes
NASA Astrophysics Data System (ADS)
Felice, Maria V.; Velichko, Alexander; Wilcox, Paul D.; Barden, Tim; Dunhill, Tony
2015-03-01
Models which simulate the interaction of ultrasound with cracks can be used to optimize ultrasonic array inspections, but this approach can be time-consuming. To overcome this issue an efficient hybrid model is implemented which includes a finite element method that requires only a single layer of elements around the crack shape. Scattering Matrices are used to capture the scattering behavior of the individual cracks and a discussion on the angular degrees of freedom of elastodynamic scatterers is included. Real crack shapes are obtained from X-ray Computed Tomography images of cracked parts and these shapes are inputted into the hybrid model. The effect of using real crack shapes instead of straight notch shapes is demonstrated. An array optimization methodology which incorporates the hybrid model, an approximate single-scattering relative noise model and the real crack shapes is then described.
NASA Astrophysics Data System (ADS)
Kuo, K. A.; Verbraken, H.; Degrande, G.; Lombaert, G.
2016-07-01
Along with the rapid expansion of urban rail networks comes the need for accurate predictions of railway induced vibration levels at grade and in buildings. Current computational methods for making predictions of railway induced ground vibration rely on simplifying modelling assumptions and require detailed parameter inputs, which lead to high levels of uncertainty. It is possible to mitigate against these issues using a combination of field measurements and state-of-the-art numerical methods, known as a hybrid model. In this paper, two hybrid models are developed, based on the use of separate source and propagation terms that are quantified using in situ measurements or modelling results. These models are implemented using term definitions proposed by the Federal Railroad Administration and assessed using the specific illustration of a surface railway. It is shown that the limitations of numerical and empirical methods can be addressed in a hybrid procedure without compromising prediction accuracy.
Optimization of ultrasonic array inspections using an efficient hybrid model and real crack shapes
Felice, Maria V.; Velichko, Alexander Wilcox, Paul D.; Barden, Tim; Dunhill, Tony
2015-03-31
Models which simulate the interaction of ultrasound with cracks can be used to optimize ultrasonic array inspections, but this approach can be time-consuming. To overcome this issue an efficient hybrid model is implemented which includes a finite element method that requires only a single layer of elements around the crack shape. Scattering Matrices are used to capture the scattering behavior of the individual cracks and a discussion on the angular degrees of freedom of elastodynamic scatterers is included. Real crack shapes are obtained from X-ray Computed Tomography images of cracked parts and these shapes are inputted into the hybrid model. The effect of using real crack shapes instead of straight notch shapes is demonstrated. An array optimization methodology which incorporates the hybrid model, an approximate single-scattering relative noise model and the real crack shapes is then described.
Ishishita, Satoshi; Matsuda, Yoichi
2016-10-13
Hybrid incompatibility is important in speciation as it prevents gene flow between closely related populations. Reduced fitness from hybrid incompatibility may also reinforce prezygotic reproductive isolation between sympatric populations. However, the genetic and developmental basis of hybrid incompatibility in higher vertebrates remains poorly understood. Mammals and birds, both amniotes, have similar developmental processes, but marked differences in development such as the XY/ZW sex determination systems and the presence or absence of genomic imprinting. Here, we review the sterile phenotype of hybrids between the Phodopus dwarf hamsters P. campbelli and P. sungorus, and the inviable phenotype of hybrids between two birds of the family Phasianidae, chicken (Gallus gallus domesticus) and Japanese quail (Coturnix japonica). We propose hypotheses for developmental defects that are associated with these hybrid incompatibilities. In addition, we discuss the genetic and developmental basis for these defects in conjunction with recent findings from mouse and avian models of genetics, reproductive biology and genomics. We suggest that these hybrids are ideal animal models for studying the genetic and developmental basis of hybrid incompatibility in amniotes.
Ocean Prediction with the Hybrid Coordinate Ocean Model (HYCOM)
2006-01-01
into hybrid approaches. Isopycnal (density tracking) layers are best in the deep stratified ocean, z-levels (constant fixed depths) are best used to...when this would lead to excessive crowding of coordinate surfaces. Thus, vertical grid points can be geometrically constrained to remain at a fixed depth...isopycnal in the open stratified ocean, but smoothly reverts to a terrain-following (a) coordinate in shallow coastal regions and to fixed pressure
Charging and hybridization in the finite cluster model
NASA Technical Reports Server (NTRS)
Bauschlicher, C. W., Jr.; Bagus, P. S.; Nelin, C. J.
1984-01-01
Cluster wavefunctions which have appropriate hybridization and polarization lead to reasonable properties for the interaction of an adsorbate with a solid surface. However, for Al clusters, it was found that the atomic change distribution is not uniform. The finite cluster size leads to changes not representative for an extended system. This effect appears to be dependent on the particular materials being studied; it does not occur in all cases.
Hybrid [sigma]-p Coordinate Choices for a Global Model
2009-01-01
Arakawa–Lamb hybrid, which remains intrinsically less stable than the others. Impacts of different coordinates on forecast skill are neutral or...unclassified Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18 mons and Strüfing (1981) and Simmons and Burridge (1981) tested different ...0. This coordinate is defined by vertical profiles of the two coefficients, A and B, which control, respectively, its isobaric and terrain
Almeida Filho, J E; Tardin, F D; Guimarães, J F R; Resende, M D V; Silva, F F; Simeone, M L; Menezes, C B; Queiroz, V A V
2016-02-26
The breeding of sorghum, Sorghum bicolor (L.) Moench, aimed at improving its nutritional quality, is of great interest, since it can be used as a highly nutritive alternative food source and can possibly be cultivated in regions with low rainfall. The objective of the present study was to evaluate the potential and genetic diversity of grain-sorghum hybrids for traits of agronomic and nutritional interest. To this end, the traits grain yield and flowering, and concentrations of protein, potassium, calcium, magnesium, sulfur, iron, manganese, and zinc in the grain were evaluated in 25 grain-sorghum hybrids, comprising 18 experimental hybrids of Embrapa Milho e Sorgo and seven commercial hybrids. The genetic potential was analyzed by a multi-trait best linear unbiased prediction (BLUP) model, and cluster analysis was accomplished by squared Mahalanobis distance using the predicted genotypic values. Hybrids 0306037 and 0306034 stood out in the agronomic evaluation. The hybrids with agronomic prominence, however, did not stand out for the traits related to the nutritional quality of the grain. Three clusters were formed from the dendrogram obtained with the unweighted pair group method with arithmetic mean method. From the results of the genotypic BLUP and the analysis of the dendrogram, hybrids 0577337, 0441347, 0307651, and 0306037 were identified as having the potential to establish a population that can aggregate alleles for all the evaluated traits of interest.
Sherer, Eric A; Sale, Mark E; Pollock, Bruce G; Belani, Chandra P; Egorin, Merrill J; Ivy, Percy S; Lieberman, Jeffrey A; Manuck, Stephen B; Marder, Stephen R; Muldoon, Matthew F; Scher, Howard I; Solit, David B; Bies, Robert R
2012-08-01
A limitation in traditional stepwise population pharmacokinetic model building is the difficulty in handling interactions between model components. To address this issue, a method was previously introduced which couples NONMEM parameter estimation and model fitness evaluation to a single-objective, hybrid genetic algorithm for global optimization of the model structure. In this study, the generalizability of this approach for pharmacokinetic model building is evaluated by comparing (1) correct and spurious covariate relationships in a simulated dataset resulting from automated stepwise covariate modeling, Lasso methods, and single-objective hybrid genetic algorithm approaches to covariate identification and (2) information criteria values, model structures, convergence, and model parameter values resulting from manual stepwise versus single-objective, hybrid genetic algorithm approaches to model building for seven compounds. Both manual stepwise and single-objective, hybrid genetic algorithm approaches to model building were applied, blinded to the results of the other approach, for selection of the compartment structure as well as inclusion and model form of inter-individual and inter-occasion variability, residual error, and covariates from a common set of model options. For the simulated dataset, stepwise covariate modeling identified three of four true covariates and two spurious covariates; Lasso identified two of four true and 0 spurious covariates; and the single-objective, hybrid genetic algorithm identified three of four true covariates and one spurious covariate. For the clinical datasets, the Akaike information criterion was a median of 22.3 points lower (range of 470.5 point decrease to 0.1 point decrease) for the best single-objective hybrid genetic-algorithm candidate model versus the final manual stepwise model: the Akaike information criterion was lower by greater than 10 points for four compounds and differed by less than 10 points for three
A Hybrid Acoustic and Pronunciation Model Adaptation Approach for Non-native Speech Recognition
NASA Astrophysics Data System (ADS)
Oh, Yoo Rhee; Kim, Hong Kook
In this paper, we propose a hybrid model adaptation approach in which pronunciation and acoustic models are adapted by incorporating the pronunciation and acoustic variabilities of non-native speech in order to improve the performance of non-native automatic speech recognition (ASR). Specifically, the proposed hybrid model adaptation can be performed at either the state-tying or triphone-modeling level, depending at which acoustic model adaptation is performed. In both methods, we first analyze the pronunciation variant rules of non-native speakers and then classify each rule as either a pronunciation variant or an acoustic variant. The state-tying level hybrid method then adapts pronunciation models and acoustic models by accommodating the pronunciation variants in the pronunciation dictionary and by clustering the states of triphone acoustic models using the acoustic variants, respectively. On the other hand, the triphone-modeling level hybrid method initially adapts pronunciation models in the same way as in the state-tying level hybrid method; however, for the acoustic model adaptation, the triphone acoustic models are then re-estimated based on the adapted pronunciation models and the states of the re-estimated triphone acoustic models are clustered using the acoustic variants. From the Korean-spoken English speech recognition experiments, it is shown that ASR systems employing the state-tying and triphone-modeling level adaptation methods can relatively reduce the average word error rates (WERs) by 17.1% and 22.1% for non-native speech, respectively, when compared to a baseline ASR system.
NASA Astrophysics Data System (ADS)
Szolgayova, Elena
2010-05-01
Hybrid modelling, used for simulation and forecasting of hydrological time series, involving both process-based and data-driven types of models combines the available domain knowledge and process physics with the recent advances in data driven tools. In this way, complex hydrological processes can be modelled and forecasted by decomposing the problem into several smaller sub - problems and using process physics based models where these are most appropriate, and data dictated tools (such as ANN, time series models or traditional statistics) for the residual data, when necessary. The fitting and forecasting performance of such models have to be explored case based. So far, only a few attempts to apply various nonlinear time series models within such a framework were reported in the hydrological modelling literature. This contribution presents results concerning the possibility to use GARCH type of models for such purposes. More specifically, error time series from two hydrological conceptual models were analyzed (applied on time series measured from the Hron and Morava Rivers in Slovakia), concentrating on the improvement of the modelling and forecasting performance of these models. The goal of investigation was to try to expand the knowledge in the time series modelling of hydrological model error time series with the aim to test and develop appropriate methods for various time steps from the GARCH family of models. In order to achieve this, following steps were taken: 1. The presence of heteroscedasticity was verified in time series. 2. A model from the GARCH family was fitted on the data, comparing the fit with a fit of an ARMA model. 3. One - step - ahead forecasts from the fitted models were produced, performing comparisons. The investigation of model properties and performances was thoroughly tested under various conditions of their future practical applications. In general, heteroscedasticity was present in the majority of the error time series of the
A hybrid model for mapping simplified seismic response via a GIS-metamodel approach
NASA Astrophysics Data System (ADS)
Grelle, G.; Bonito, L.; Revellino, P.; Guerriero, L.; Guadagno, F. M.
2014-07-01
In earthquake-prone areas, site seismic response due to lithostratigraphic sequence plays a key role in seismic hazard assessment. A hybrid model, consisting of GIS and metamodel (model of model) procedures, was introduced aimed at estimating the 1-D spatial seismic site response in accordance with spatial variability of sediment parameters. Inputs and outputs are provided and processed by means of an appropriate GIS model, named GIS Cubic Model (GCM). This consists of a block-layered parametric structure aimed at resolving a predicted metamodel by means of pixel to pixel vertical computing. The metamodel, opportunely calibrated, is able to emulate the classic shape of the spectral acceleration response in relation to the main physical parameters that characterize the spectrum itself. Therefore, via the GCM structure and the metamodel, the hybrid model provides maps of normalized acceleration response spectra. The hybrid model was applied and tested on the built-up area of the San Giorgio del Sannio village, located in a high-risk seismic zone of southern Italy. Efficiency tests showed a good correspondence between the spectral values resulting from the proposed approach and the 1-D physical computational models. Supported by lithology and geophysical data and corresponding accurate interpretation regarding modelling, the hybrid model can be an efficient tool in assessing urban planning seismic hazard/risk.
NASA Astrophysics Data System (ADS)
Ismail, S.; Samsudin, R.; Shabri, A.
2010-10-01
Successful river flow time series forecasting is a major goal and an essential procedure that is necessary in water resources planning and management. This study introduced a new hybrid model based on a combination of two familiar non-linear method of mathematical modeling: Self Organizing Map (SOM) and Least Square Support Vector Machine (LSSVM) model referred as SOM-LSSVM model. The hybrid model uses the SOM algorithm to cluster the training data into several disjointed clusters and the individual LSSVM is used to forecast the river flow. The feasibility of this proposed model is evaluated to actual river flow data from Bernam River located in Selangor, Malaysia. Their results have been compared to those obtained using LSSVM and artificial neural networks (ANN) models. The experiment results show that the SOM-LSSVM model outperforms other models for forecasting river flow. It also indicates that the proposed model can forecast more precisely and provides a promising alternative technique in river flow forecasting.
NASA Technical Reports Server (NTRS)
Hadden, Cameron M.; Klimek-McDonald, Danielle R.; Pineda, Evan J.; King, Julie A.; Reichanadter, Alex M.; Miskioglu, Ibrahim; Gowtham, S.; Odegard, Gregory M.
2015-01-01
Because of the relatively high specific mechanical properties of carbon fiber/epoxy composite materials, they are often used as structural components in aerospace applications. Graphene nanoplatelets (GNPs) can be added to the epoxy matrix to improve the overall mechanical properties of the composite. The resulting GNP/carbon fiber/epoxy hybrid composites have been studied using multiscale modeling to determine the influence of GNP volume fraction, epoxy crosslink density, and GNP dispersion on the mechanical performance. The hierarchical multiscale modeling approach developed herein includes Molecular Dynamics (MD) and micromechanical modeling, and it is validated with experimental testing of the same hybrid composite material system. The results indicate that the multiscale modeling approach is accurate and provides physical insight into the composite mechanical behavior. Also, the results quantify the substantial impact of GNP volume fraction and dispersion on the transverse mechanical properties of the hybrid composite, while the effect on the axial properties is shown to be insignificant.
A Hybrid Approach for Efficient Modeling of Medium-Frequency Propagation in Coal Mines
Brocker, Donovan E.; Sieber, Peter E.; Waynert, Joseph A.; Li, Jingcheng; Werner, Pingjuan L.; Werner, Douglas H.
2015-01-01
An efficient procedure for modeling medium frequency (MF) communications in coal mines is introduced. In particular, a hybrid approach is formulated and demonstrated utilizing ideal transmission line equations to model MF propagation in combination with full-wave sections used for accurate simulation of local antenna-line coupling and other near-field effects. This work confirms that the hybrid method accurately models signal propagation from a source to a load for various system geometries and material compositions, while significantly reducing computation time. With such dramatic improvement to solution times, it becomes feasible to perform large-scale optimizations with the primary motivation of improving communications in coal mines both for daily operations and emergency response. Furthermore, it is demonstrated that the hybrid approach is suitable for modeling and optimizing large communication networks in coal mines that may otherwise be intractable to simulate using traditional full-wave techniques such as moment methods or finite-element analysis. PMID:26478686
NASA Technical Reports Server (NTRS)
Hadden, C. M.; Klimek-McDonald, D. R.; Pineda, E. J.; King, J. A.; Reichanadter, A. M.; Miskioglu, I.; Gowtham, S.; Odegard, G. M.
2015-01-01
Because of the relatively high specific mechanical properties of carbon fiber/epoxy composite materials, they are often used as structural components in aerospace applications. Graphene nanoplatelets (GNPs) can be added to the epoxy matrix to improve the overall mechanical properties of the composite. The resulting GNP/carbon fiber/epoxy hybrid composites have been studied using multiscale modeling to determine the influence of GNP volume fraction, epoxy crosslink density, and GNP dispersion on the mechanical performance. The hierarchical multiscale modeling approach developed herein includes Molecular Dynamics (MD) and micromechanical modeling, and it is validated with experimental testing of the same hybrid composite material system. The results indicate that the multiscale modeling approach is accurate and provides physical insight into the composite mechanical behavior. Also, the results quantify the substantial impact of GNP volume fraction and dispersion on the transverse mechanical properties of the hybrid composite while the effect on the axial properties is shown to be insignificant.
NASA Technical Reports Server (NTRS)
Hadden, C. M.; Klimek-McDonald, D. R.; Pineda, E. J.; King, J. A.; Reichanadter, A. M.; Miskioglu, I.; Gowtham, S.; Odegard, G. M.
2015-01-01
Because of the relatively high specific mechanical properties of carbon fiber/epoxy composite materials, they are often used as structural components in aerospace applications. Graphene nanoplatelets (GNPs) can be added to the epoxy matrix to improve the overall mechanical properties of the composite. The resulting GNP/carbon fiber/epoxy hybrid composites have been studied using multiscale modeling to determine the influence of GNP volume fraction, epoxy crosslink density, and GNP dispersion on the mechanical performance. The hierarchical multiscale modeling approach developed herein includes Molecular Dynamics (MD) and micromechanical modeling, and it is validated with experimental testing of the same hybrid composite material system. The results indicate that the multiscale modeling approach is accurate and provides physical insight into the composite mechanical behavior. Also, the results quantify the substantial impact of GNP volume fraction and dispersion on the transverse mechanical properties of the hybrid composite, while the effect on the axial properties is shown to be insignificant.
Optimized Treatment of Fibromyalgia Using System Identification and Hybrid Model Predictive Control
Deshpande, Sunil; Nandola, Naresh N.; Rivera, Daniel E.; Younger, Jarred W.
2014-01-01
The term adaptive intervention is used in behavioral health to describe individually-tailored strategies for preventing and treating chronic, relapsing disorders. This paper describes a system identification approach for developing dynamical models from clinical data, and subsequently, a hybrid model predictive control scheme for assigning dosages of naltrexone as treatment for fibromyalgia, a chronic pain condition. A simulation study that includes conditions of significant plant-model mismatch demonstrates the benefits of hybrid predictive control as a decision framework for optimized adaptive interventions. This work provides insights on the design of novel personalized interventions for chronic pain and related conditions in behavioral health. PMID:25506132
Optimized Treatment of Fibromyalgia Using System Identification and Hybrid Model Predictive Control.
Deshpande, Sunil; Nandola, Naresh N; Rivera, Daniel E; Younger, Jarred W
2014-12-01
The term adaptive intervention is used in behavioral health to describe individually-tailored strategies for preventing and treating chronic, relapsing disorders. This paper describes a system identification approach for developing dynamical models from clinical data, and subsequently, a hybrid model predictive control scheme for assigning dosages of naltrexone as treatment for fibromyalgia, a chronic pain condition. A simulation study that includes conditions of significant plant-model mismatch demonstrates the benefits of hybrid predictive control as a decision framework for optimized adaptive interventions. This work provides insights on the design of novel personalized interventions for chronic pain and related conditions in behavioral health.
Modeling hydraulic regenerative hybrid vehicles using AMESim and Matlab/Simulink
NASA Astrophysics Data System (ADS)
Lynn, Alfred; Smid, Edzko; Eshraghi, Moji; Caldwell, Niall; Woody, Dan
2005-05-01
This paper presents the overview of the simulation modeling of a hydraulic system with regenerative braking used to improve vehicle emissions and fuel economy. Two simulation software packages were used together to enhance the simulation capability for fuel economy results and development of vehicle and hybrid control strategy. AMESim, a hydraulic simulation software package modeled the complex hydraulic circuit and component hardware and was interlinked with a Matlab/Simulink model of the vehicle, engine and the control strategy required to operate the vehicle and the hydraulic hybrid system through various North American and European drive cycles.
A research using hybrid RBF/Elman neural networks for intrusion detection system secure model
NASA Astrophysics Data System (ADS)
Tong, Xiaojun; Wang, Zhu; Yu, Haining
2009-10-01
A hybrid RBF/Elman neural network model that can be employed for both anomaly detection and misuse detection is presented in this paper. The IDSs using the hybrid neural network can detect temporally dispersed and collaborative attacks effectively because of its memory of past events. The RBF network is employed as a real-time pattern classification and the Elman network is employed to restore the memory of past events. The IDSs using the hybrid neural network are evaluated against the intrusion detection evaluation data sponsored by U.S. Defense Advanced Research Projects Agency (DARPA). Experimental results are presented in ROC curves. Experiments show that the IDSs using this hybrid neural network improve the detection rate and decrease the false positive rate effectively.
A Hybrid Model for the Computationally-Efficient Simulation of the Cerebellar Granular Layer
Cattani, Anna; Solinas, Sergio; Canuto, Claudio
2016-01-01
The aim of the present paper is to efficiently describe the membrane potential dynamics of neural populations formed by species having a high density difference in specific brain areas. We propose a hybrid model whose main ingredients are a conductance-based model (ODE system) and its continuous counterpart (PDE system) obtained through a limit process in which the number of neurons confined in a bounded region of the brain tissue is sent to infinity. Specifically, in the discrete model, each cell is described by a set of time-dependent variables, whereas in the continuum model, cells are grouped into populations that are described by a set of continuous variables. Communications between populations, which translate into interactions among the discrete and the continuous models, are the essence of the hybrid model we present here. The cerebellum and cerebellum-like structures show in their granular layer a large difference in the relative density of neuronal species making them a natural testing ground for our hybrid model. By reconstructing the ensemble activity of the cerebellar granular layer network and by comparing our results to a more realistic computational network, we demonstrate that our description of the network activity, even though it is not biophysically detailed, is still capable of reproducing salient features of neural network dynamics. Our modeling approach yields a significant computational cost reduction by increasing the simulation speed at least 270 times. The hybrid model reproduces interesting dynamics such as local microcircuit synchronization, traveling waves, center-surround, and time-windowing. PMID:27148027
Multiple model predictive control for a hybrid proton exchange membrane fuel cell system
NASA Astrophysics Data System (ADS)
Chen, Qihong; Gao, Lijun; Dougal, Roger A.; Quan, Shuhai
This paper presents a hierarchical predictive control strategy to optimize both power utilization and oxygen control simultaneously for a hybrid proton exchange membrane fuel cell/ultracapacitor system. The control employs fuzzy clustering-based modeling, constrained model predictive control, and adaptive switching among multiple models. The strategy has three major advantages. First, by employing multiple piecewise linear models of the nonlinear system, we are able to use linear models in the model predictive control, which significantly simplifies implementation and can handle multiple constraints. Second, the control algorithm is able to perform global optimization for both the power allocation and oxygen control. As a result, we can achieve the optimization from the entire system viewpoint, and a good tradeoff between transient performance of the fuel cell and the ultracapacitor can be obtained. Third, models of the hybrid system are identified using real-world data from the hybrid fuel cell system, and models are updated online. Therefore, the modeling mismatch is minimized and high control accuracy is achieved. Study results demonstrate that the control strategy is able to appropriately split power between fuel cell and ultracapacitor, avoid oxygen starvation, and so enhance the transient performance and extend the operating life of the hybrid system.
Learning fuzzy information in a hybrid connectionist, symbolic model
NASA Technical Reports Server (NTRS)
Romaniuk, Steve G.; Hall, Lawrence O.
1993-01-01
An instance-based learning system is presented. SC-net is a fuzzy hybrid connectionist, symbolic learning system. It remembers some examples and makes groups of examples into exemplars. All real-valued attributes are represented as fuzzy sets. The network representation and learning method is described. To illustrate this approach to learning in fuzzy domains, an example of segmenting magnetic resonance images of the brain is discussed. Clearly, the boundaries between human tissues are ill-defined or fuzzy. Example fuzzy rules for recognition are generated. Segmentations are presented that provide results that radiologists find useful.
Design and Implementation of “Many Parallel Task” Hybrid Subsurface Model
Agarwal, Khushbu; Chase, Jared M.; Schuchardt, Karen L.; Scheibe, Timothy D.; Palmer, Bruce J.; Elsethagen, Todd O.
2011-11-01
Continuum scale models have been used to study subsurface flow, transport, and reactions for many years. Recently, pore scale models, which operate at scales of individual soil grains, have been developed to more accurately model pore scale phenomena, such as precipitation, that may not be well represented at the continuum scale. However, particle-based models become prohibitively expensive for modeling realistic domains. Instead, we are developing a hybrid model that simulates the full domain at continuum scale and applies the pore model only to areas of high reactivity. The hybrid model uses a dimension reduction approach to formulate the mathematical exchange of information across scales. Since the location, size, and number of pore regions in the model varies, an adaptive Pore Generator is being implemented to define pore regions at each iteration. A fourth code will provide data transformation from the pore scale back to the continuum scale. These components are coupled into a single hybrid model using the SWIFT workflow system. Our hybrid model workflow simulates a kinetic controlled mixing reaction in which multiple pore-scale simulations occur for every continuum scale timestep. Each pore-scale simulation is itself parallel, thus exhibiting multi-level parallelism. Our workflow manages these multiple parallel tasks simultaneously, with the number of tasks changing across iterations. It also supports dynamic allocation of job resources and visualization processing at each iteration. We discuss the design, implementation and challenges associated with building a scalable, Many Parallel Task, hybrid model to run efficiently on thousands to tens of thousands of processors.
A four-stage hybrid model for hydrological time series forecasting.
Di, Chongli; Yang, Xiaohua; Wang, Xiaochao
2014-01-01
Hydrological time series forecasting remains a difficult task due to its complicated nonlinear, non-stationary and multi-scale characteristics. To solve this difficulty and improve the prediction accuracy, a novel four-stage hybrid model is proposed for hydrological time series forecasting based on the principle of 'denoising, decomposition and ensemble'. The proposed model has four stages, i.e., denoising, decomposition, components prediction and ensemble. In the denoising stage, the empirical mode decomposition (EMD) method is utilized to reduce the noises in the hydrological time series. Then, an improved method of EMD, the ensemble empirical mode decomposition (EEMD), is applied to decompose the denoised series into a number of intrinsic mode function (IMF) components and one residual component. Next, the radial basis function neural network (RBFNN) is adopted to predict the trend of all of the components obtained in the decomposition stage. In the final ensemble prediction stage, the forecasting results of all of the IMF and residual components obtained in the third stage are combined to generate the final prediction results, using a linear neural network (LNN) model. For illustration and verification, six hydrological cases with different characteristics are used to test the effectiveness of the proposed model. The proposed hybrid model performs better than conventional single models, the hybrid models without denoising or decomposition and the hybrid models based on other methods, such as the wavelet analysis (WA)-based hybrid models. In addition, the denoising and decomposition strategies decrease the complexity of the series and reduce the difficulties of the forecasting. With its effective denoising and accurate decomposition ability, high prediction precision and wide applicability, the new model is very promising for complex time series forecasting. This new forecast model is an extension of nonlinear prediction models.
Creating a Learning Flow: A Hybrid Course Model for High-Failure-Rate Math Classes
ERIC Educational Resources Information Center
Stevenson, Katherine; Zweier, Louis
2011-01-01
Higher education in the United States is facing a failure-rate crisis in entry-level mathematics courses. In this article, the authors describe an innovative, technology-enhanced hybrid course model that has significantly improved course completion and content mastery outcomes in general education (GE) mathematics courses. The model relies on five…
Reentrant excitation in an analog-digital hybrid circuit model of cardiac tissue
NASA Astrophysics Data System (ADS)
Mahmud, Farhanahani; Shiozawa, Naruhiro; Makikawa, Masaaki; Nomura, Taishin
2011-06-01
We propose an analog-digital hybrid circuit model of one-dimensional cardiac tissue with hardware implementation that allows us to perform real-time simulations of spatially conducting cardiac action potentials. Each active nodal compartment of the tissue model is designed using analog circuits and a dsPIC microcontroller, by which the time-dependent and time-independent nonlinear current-voltage relationships of six types of ion channel currents employed in the Luo-Rudy phase I (LR-I) model for a single mammalian cardiac ventricular cell can be reproduced quantitatively. Here, we perform real-time simulations of reentrant excitation conduction in a ring-shaped tissue model that includes eighty nodal compartments. In particular, we show that the hybrid tissue model can exhibit real-time dynamics for initiation of reentries induced by uni-directional block, as well as those for phase resetting that leads to annihilation of the reentry in response to impulsive current stimulations at appropriate nodes and timings. The dynamics of the hybrid model are comparable to those of a spatially distributed tissue model with LR-I compartments. Thus, it is conceivable that the hybrid model might be a useful tool for large scale simulations of cardiac tissue dynamics, as an alternative to numerical simulations, leading toward further understanding of the reentrant mechanisms.
Hybrid modelling framework by using mathematics-based and information-based methods
NASA Astrophysics Data System (ADS)
Ghaboussi, J.; Kim, J.; Elnashai, A.
2010-06-01
Mathematics-based computational mechanics involves idealization in going from the observed behaviour of a system into mathematical equations representing the underlying mechanics of that behaviour. Idealization may lead mathematical models that exclude certain aspects of the complex behaviour that may be significant. An alternative approach is data-centric modelling that constitutes a fundamental shift from mathematical equations to data that contain the required information about the underlying mechanics. However, purely data-centric methods often fail for infrequent events and large state changes. In this article, a new hybrid modelling framework is proposed to improve accuracy in simulation of real-world systems. In the hybrid framework, a mathematical model is complemented by information-based components. The role of informational components is to model aspects which the mathematical model leaves out. The missing aspects are extracted and identified through Autoprogressive Algorithms. The proposed hybrid modelling framework has a wide range of potential applications for natural and engineered systems. The potential of the hybrid methodology is illustrated through modelling highly pinched hysteretic behaviour of beam-to-column connections in steel frames.
Modeling and Analysis of Facility Systems for A Hybrid Materials Test Program
NASA Technical Reports Server (NTRS)
Congiardo, Jared F.
2007-01-01
Analytic modeling and analysis processes employed at NASA-SSC in rocket propulsion systems testing are discussed in this paper with application to test facility propellant supply system design, activation and test of a hybrid rocket motor provided. This paper discusses the analytic model employed, its utilization across project phases and reviews performance results.
Hybrid modeling in biochemical systems theory by means of functional petri nets.
Wu, Jialiang; Voit, Eberhard
2009-02-01
Many biological systems are genuinely hybrids consisting of interacting discrete and continuous components and processes that often operate at different time scales. It is therefore desirable to create modeling frameworks capable of combining differently structured processes and permitting their analysis over multiple time horizons. During the past 40 years, Biochemical Systems Theory (BST) has been a very successful approach to elucidating metabolic, gene regulatory, and signaling systems. However, its foundation in ordinary differential equations has precluded BST from directly addressing problems containing switches, delays, and stochastic effects. In this study, we extend BST to hybrid modeling within the framework of Hybrid Functional Petri Nets (HFPN). First, we show how the canonical GMA and S-system models in BST can be directly implemented in a standard Petri Net framework. In a second step we demonstrate how to account for different types of time delays as well as for discrete, stochastic, and switching effects. Using representative test cases, we validate the hybrid modeling approach through comparative analyses and simulations with other approaches and highlight the feasibility, quality, and efficiency of the hybrid method.
Hybrid Analytical and Data-Driven Modeling for Feed-Forward Robot Control †.
Reinhart, René Felix; Shareef, Zeeshan; Steil, Jochen Jakob
2017-02-08
Feed-forward model-based control relies on models of the controlled plant, e.g., in robotics on accurate knowledge of manipulator kinematics or dynamics. However, mechanical and analytical models do not capture all aspects of a plant's intrinsic properties and there remain unmodeled dynamics due to varying parameters, unmodeled friction or soft materials. In this context, machine learning is an alternative suitable technique to extract non-linear plant models from data. However, fully data-based models suffer from inaccuracies as well and are inefficient if they include learning of well known analytical models. This paper thus argues that feed-forward control based on hybrid models comprising an analytical model and a learned error model can significantly improve modeling accuracy. Hybrid modeling here serves the purpose to combine the best of the two modeling worlds. The hybrid modeling methodology is described and the approach is demonstrated for two typical problems in robotics, i.e., inverse kinematics control and computed torque control. The former is performed for a redundant soft robot and the latter for a rigid industrial robot with redundant degrees of freedom, where a complete analytical model is not available for any of the platforms.
Hybrid Analytical and Data-Driven Modeling for Feed-Forward Robot Control †
Reinhart, René Felix; Shareef, Zeeshan; Steil, Jochen Jakob
2017-01-01
Feed-forward model-based control relies on models of the controlled plant, e.g., in robotics on accurate knowledge of manipulator kinematics or dynamics. However, mechanical and analytical models do not capture all aspects of a plant’s intrinsic properties and there remain unmodeled dynamics due to varying parameters, unmodeled friction or soft materials. In this context, machine learning is an alternative suitable technique to extract non-linear plant models from data. However, fully data-based models suffer from inaccuracies as well and are inefficient if they include learning of well known analytical models. This paper thus argues that feed-forward control based on hybrid models comprising an analytical model and a learned error model can significantly improve modeling accuracy. Hybrid modeling here serves the purpose to combine the best of the two modeling worlds. The hybrid modeling methodology is described and the approach is demonstrated for two typical problems in robotics, i.e., inverse kinematics control and computed torque control. The former is performed for a redundant soft robot and the latter for a rigid industrial robot with redundant degrees of freedom, where a complete analytical model is not available for any of the platforms. PMID:28208697
Hybrid Continuum and Molecular Modeling of Nano-scale Flows
NASA Astrophysics Data System (ADS)
Povitsky, Alex; Zhao, Shunliu
2010-11-01
A novel hybrid method combining the continuum approach based on boundary singularity method (BSM) and the molecular approach based on the direct simulation Monte Carlo (DSMC) is developed and then used to study viscous fibrous filtration flows in the transition flow regime, Kn>0.25. The DSMC is applied to a Knudsen layer enclosing the fiber and the BSM is employed to the entire flow domain. The parameters used in the DSMC and the coupling procedure, such as the number of simulated particles, the cell size and the size of the coupling zone are determined. Results are compared to the experiments measuring pressure drop and flowfield in filters. The optimal location of singularities outside of flow domain was determined and results are compared to those obtained by regularized Stokeslets. The developed hybrid method is parallelized by using MPI and extended to multi-fiber filtration flows. The multi-fiber filter flows considered are in the partial-slip and transition regimes. For Kn˜1, the computed velocity near fibers changes significantly that confirms the need of molecular methods in evaluation of the flow slip in transitional regime.
Modeling of Divertor Plates in the Compact Toroidal Hybrid
NASA Astrophysics Data System (ADS)
Hartwell, G. J.; Small, C. M.; Ennis, D. A.; Hanson, J. D.; Knowlton, S. F.; Maurer, D. A.
2014-10-01
In long pulse length stellarator experiments, edge island divertors can be used as a method of plasma particle and heat exhaust. Knowledge of the detailed power loading on these structures and its relationship to the long connection length scrape off layer physics is a new Compact Toroidal Hybrid research thrust. We report the results of connection length studies for divertor plates to be installed in the Compact Toroidal Hybrid (CTH), a five field period torsatron with R0 = 0 . 75 m, ap ~ 0 . 2 m, and B <= 0 . 7 T. For these studies, CTH will be operated as a pure stellarator with no ohmically generated plasma current. The CTH edge rotational transform can be varied from tvac (a) = 0.02-0.35 by adjusting the ratio of currents in the helical and toroidal field coils. A poloidal field coil is used to adjust the shear of the rotational transform profile, and hence the size of edge islands, while the phase of the island is rotated with a set of five error coils producing an n = 1 perturbation. For the studies conducted, a magnetic configuration with a large n = 1, m = 3 magnetic island at the edge is generated. Results from multiple possible divertor plate locations relative to the island structure will be presented. This work is supported by U.S. Department of Energy Grant No. DE-FG02-00ER54610.
Analysis of a model of fuel cell - gas turbine hybrid power system for enhanced energy efficiency
NASA Astrophysics Data System (ADS)
Calay, Rajnish K.; Mustafa, Mohamad Y.; Virk, Mohammad S.; Mustafa, Mahmoud F.
2012-11-01
A simple mathematical model to evaluate the performance of FC-GT hybrid system is presented in this paper. The model is used to analyse the influence of various parameters on the performance of a typical hybrid system, where excess heat rejected from the solid-oxide fuel cell stack is utilised to generate additional power through a gas turbine system and to provide heat energy for space heating. The model is based on thermodynamic analysis of various components of the plant and can be adapted for various configurations of the plant components. Because there are many parameters defining the efficiency and work output of the hybrid system, the technique is based on mathematical and graphical optimisation of various parameters; to obtain the maximum efficiency for a given plant configuration.
Hybrid neural network modeling of a full-scale industrial wastewater treatment process.
Lee, Dae Sung; Jeon, Che Ok; Park, Jong Moon; Chang, Kun Soo
2002-06-20
In recent years, hybrid neural network approaches, which combine mechanistic and neural network models, have received considerable attention. These approaches are potentially very efficient for obtaining more accurate predictions of process dynamics by combining mechanistic and neural network models in such a way that the neural network model properly accounts for unknown and nonlinear parts of the mechanistic model. In this work, a full-scale coke-plant wastewater treatment process was chosen as a model system. Initially, a process data analysis was performed on the actual operational data by using principal component analysis. Next, a simplified mechanistic model and a neural network model were developed based on the specific process knowledge and the operational data of the coke-plant wastewater treatment process, respectively. Finally, the neural network was incorporated into the mechanistic model in both parallel and serial configurations. Simulation results showed that the parallel hybrid modeling approach achieved much more accurate predictions with good extrapolation properties as compared with the other modeling approaches even in the case of process upset caused by, for example, shock loading of toxic compounds. These results indicate that the parallel hybrid neural modeling approach is a useful tool for accurate and cost-effective modeling of biochemical processes, in the absence of other reasonably accurate process models.
HyDE Framework for Stochastic and Hybrid Model-Based Diagnosis
NASA Technical Reports Server (NTRS)
Narasimhan, Sriram; Brownston, Lee
2012-01-01
Hybrid Diagnosis Engine (HyDE) is a general framework for stochastic and hybrid model-based diagnosis that offers flexibility to the diagnosis application designer. The HyDE architecture supports the use of multiple modeling paradigms at the component and system level. Several alternative algorithms are available for the various steps in diagnostic reasoning. This approach is extensible, with support for the addition of new modeling paradigms as well as diagnostic reasoning algorithms for existing or new modeling paradigms. HyDE is a general framework for stochastic hybrid model-based diagnosis of discrete faults; that is, spontaneous changes in operating modes of components. HyDE combines ideas from consistency-based and stochastic approaches to model- based diagnosis using discrete and continuous models to create a flexible and extensible architecture for stochastic and hybrid diagnosis. HyDE supports the use of multiple paradigms and is extensible to support new paradigms. HyDE generates candidate diagnoses and checks them for consistency with the observations. It uses hybrid models built by the users and sensor data from the system to deduce the state of the system over time, including changes in state indicative of faults. At each time step when observations are available, HyDE checks each existing candidate for continued consistency with the new observations. If the candidate is consistent, it continues to remain in the candidate set. If it is not consistent, then the information about the inconsistency is used to generate successor candidates while discarding the candidate that was inconsistent. The models used by HyDE are similar to simulation models. They describe the expected behavior of the system under nominal and fault conditions. The model can be constructed in modular and hierarchical fashion by building component/subsystem models (which may themselves contain component/ subsystem models) and linking them through shared variables/parameters. The
Active control of high-frequency vibration: Optimisation using the hybrid modelling method
NASA Astrophysics Data System (ADS)
Muthalif, Asan G. A.; Langley, Robin S.
2012-06-01
This work presents active control of high-frequency vibration using skyhook dampers. The choice of the damper gain and its optimal location is crucial for the effective implementation of active vibration control. In vibration control, certain sensor/actuator locations are preferable for reducing structural vibration while using minimum control effort. In order to perform optimisation on a general built-up structure to control vibration, it is necessary to have a good modelling technique to predict the performance of the controller. The present work exploits the hybrid modelling approach, which combines the finite element method (FEM) and statistical energy analysis (SEA) to provide efficient response predictions at medium to high frequencies. The hybrid method is implemented here for a general network of plates, coupled via springs, to allow study of a variety of generic control design problems. By combining the hybrid method with numerical optimisation using a genetic algorithm, optimal skyhook damper gains and locations are obtained. The optimal controller gain and location found from the hybrid method are compared with results from a deterministic modelling method. Good agreement between the results is observed, whereas results from the hybrid method are found in a significantly reduced amount of time.
Modeling, analysis and control of fuel cell hybrid power systems
NASA Astrophysics Data System (ADS)
Suh, Kyung Won
Transient performance is a key characteristic of fuel cells, that is sometimes more critical than efficiency, due to the importance of accepting unpredictable electric loads. To fulfill the transient requirement in vehicle propulsion and portable fuel cell applications, a fuel cell stack is typically coupled with a battery through a DC/DC converter to form a hybrid power system. Although many power management strategies already exist, they all rely on low level controllers that realize the power split. In this dissertation we design controllers that realize various power split strategies by directly manipulating physical actuators (low level commands). We maintain the causality of the electric dynamics (voltage and current) and investigate how the electric architecture affects the hybridization level and the power management. We first establish the performance limitations associated with a stand-alone and power-autonomous fuel cell system that is not supplemented by an additional energy storage and powers all its auxiliary components by itself. Specifically, we examine the transient performance in fuel cell power delivery as it is limited by the air supplied by a compressor driven by the fuel cell itself. The performance limitations arise from the intrinsic coupling in the fluid and electrical domain between the compressor and the fuel cell stack. Feedforward and feedback control strategies are used to demonstrate these limitations analytically and with simulations. Experimental tests on a small commercial fuel cell auxiliary power unit (APU) confirm the dynamics and the identified limitations. The dynamics associated with the integration of a fuel cell system and a DC/DC converter is then investigated. Decentralized and fully centralized (using linear quadratic techniques) controllers are designed to regulate the power system voltage and to prevent fuel cell oxygen starvation. Regulating these two performance variables is a difficult task and requires a compromise
Modeling of Nonacoustic Combustion Instability in Simulations of Hybrid Motor Tests
NASA Technical Reports Server (NTRS)
Rocker, M.
2000-01-01
A transient model of a hybrid motor was formulated to study the cause and elimination of nonacoustic combustion instability. The transient model was used to simulate four key tests out of a series of seventeen hybrid motor tests conducted by Thiokol, Rocketdyne, and Martin Marietta at NASA Marshall Space Flight Center (MSFC). These tests were performed under the Hybrid Propulsion Technology for Launch Vehicle Boosters (HPTLVB) program. The first test resulted in stable combustion. The second test resulted in large-amplitude, 6.5-Hz chamber pressure oscillations that gradually damped away by the end of the test. The third test resulted in large-amplitude, 7.5-Hz chamber pressure oscillations that were sustained throughout the test. The seventh test resulted in elimination of combustion instability with the installation of an orifice immediately upstream of the injector. Formulation and implementation of the model are the scope of this presentation. The current model is an independent continuation of modeling presented previously by joint Thiokol-Rocketdyne collaborators Boardman, Hawkins, Wassom. and Claflin. The previous model simulated an unstable independent research and development (IR&D) hybrid motor test performed by Thiokol. There was very good agreement between the model and test data. Like the previous model, the current model was developed using Matrix-x simulation software. However, tests performed at MSFC under the HPTLVB program were actually simulated. ln the current model, the hybrid motor, consisting of the liquid oxygen (lox) injector, the multiport solid fuel grain, and nozzle, was simulated. The lox feedsystem, consisting of the tank, venturi. valve, and feed lines, was also simulated in the model. All components of the hybrid motor and lox feedsystem are treated by a lumped-parameter approach. Agreement between the results of the transient model and actual test data was very good. This agreement between simulated and actual test data indicated
A hybrid model for predicting carbon monoxide from vehicular exhausts in urban environments
NASA Astrophysics Data System (ADS)
Gokhale, Sharad; Khare, Mukesh
Several deterministic-based air quality models evaluate and predict the frequently occurring pollutant concentration well but, in general, are incapable of predicting the 'extreme' concentrations. In contrast, the statistical distribution models overcome the above limitation of the deterministic models and predict the 'extreme' concentrations. However, the environmental damages are caused by both extremes as well as by the sustained average concentration of pollutants. Hence, the model should predict not only 'extreme' ranges but also the 'middle' ranges of pollutant concentrations, i.e. the entire range. Hybrid modelling is one of the techniques that estimates/predicts the 'entire range' of the distribution of pollutant concentrations by combining the deterministic based models with suitable statistical distribution models ( Jakeman, et al., 1988). In the present paper, a hybrid model has been developed to predict the carbon monoxide (CO) concentration distributions at one of the traffic intersections, Income Tax Office (ITO), in the Delhi city, where the traffic is heterogeneous in nature and meteorology is 'tropical'. The model combines the general finite line source model (GFLSM) as its deterministic, and log logistic distribution (LLD) model, as its statistical components. The hybrid (GFLSM-LLD) model is then applied at the ITO intersection. The results show that the hybrid model predictions match with that of the observed CO concentration data within the 5-99 percentiles range. The model is further validated at different street location, i.e. Sirifort roadway. The validation results show that the model predicts CO concentrations fairly well ( d=0.91) in 10-95 percentiles range. The regulatory compliance is also developed to estimate the probability of exceedance of hourly CO concentration beyond the National Ambient Air Quality Standards (NAAQS) of India. It consists of light vehicles, heavy vehicles, three- wheelers (auto rickshaws) and two
Numerical modeling of lower hybrid heating and current drive
Valeo, E.J.; Eder, D.C.
1986-03-01
The generation of currents in toroidal plasma by application of waves in the lower hybrid frequency range involves the interplay of several physical phenomena which include: wave propagation in toroidal geometry, absorption via wave-particle resonances, the quasilinear generation of strongly nonequilibrium electron and ion distribution functions, and the self-consistent evolution of the current density in such a nonequilibrium plasma. We describe a code, LHMOD, which we have developed to treat these aspects of current drive and heating in tokamaks. We present results obtained by applying the code to a computation of current ramp-up and to an investigation of the possible importance of minority hydrogen absorption in a deuterium plasma as the ''density limit'' to current drive is approached.
Bifurcation analysis on a hybrid systems model of intermittent hormonal therapy for prostate cancer
NASA Astrophysics Data System (ADS)
Tanaka, Gouhei; Tsumoto, Kunichika; Tsuji, Shigeki; Aihara, Kazuyuki
2008-10-01
Hybrid systems are widely used to model dynamical phenomena that are characterized by interplay between continuous dynamics and discrete events. An example of biomedical application is modeling of disease progression of prostate cancer under intermittent hormonal therapy, where continuous tumor dynamics is switched by interruption and reinstitution of medication. In the present paper, we study a hybrid systems model representing intermittent androgen suppression (IAS) therapy for advanced prostate cancer. Intermittent medication with switching between on-treatment and off-treatment periods is intended to possibly prevent a prostatic tumor from developing into a hormone-refractory state and is anticipated as a possible strategy for delaying or hopefully averting a cancer relapse which most patients undergo as a result of long-term hormonal suppression. Clinical efficacy of IAS therapy for prostate cancer is still under investigation but at least worth considering in terms of reduction of side effects and economic costs during off-treatment periods. In the model of IAS therapy, it depends on some clinically controllable parameters whether a relapse of prostate cancer occurs or not. Therefore, we examine nonlinear dynamics and bifurcation structure of the model by exploiting a numerical method to clarify bifurcation sets in the hybrid system. Our results suggest that adjustment of the normal androgen level in combination with appropriate medication scheduling could enhance the possibility of relapse prevention. Moreover, a two-dimensional piecewise-linear system reduced from the original model highlights the origin of nonlinear phenomena specific to the hybrid system.
A hybrid MC-FEM model for analysis of light propagation in highly scattering medium
NASA Astrophysics Data System (ADS)
Kurihara, Kazuki; Wu, Xue; Okada, Eiji; Dehghani, Hamid
2013-06-01
The hemodynamic change related to the brain activation can be located by the diffuse optical tomography (DOT) using the near-infrared spectroscopy (NIRS) signals and the spatial sensitivity profiles (SSP). Monte Carlo (MC) method and finite element method (FEM) have been used to predict the SSPs. The computation time for MC method is much longer than that for the FEM, however, the accurate solution in the region close to the light source cannot be obtained by FEM solutions of the diffusion equation. In this study, a hybrid MC-FEM model is proposed for fast and accurate simulation of light propagation in a highly scattering medium. In the hybrid model, the solution in the region close to the light source is calculated by the MC method whereas that in the region far from the light source is calculated by the FEM. The solutions by the FEM in hemispherical models were compared with thoseby the MC method to determine the region in which diffusion approximation does not hold and the number of photons for the MC method for the hybrid model. The results demonstratethat theproposed hybrid model can calculatethe accurate solutionswithin reasonable computation time for a multi-layered model.
Physical and JIT Model Based Hybrid Modeling Approach for Building Thermal Load Prediction
NASA Astrophysics Data System (ADS)
Iino, Yutaka; Murai, Masahiko; Murayama, Dai; Motoyama, Ichiro
Energy conservation in building fields is one of the key issues in environmental point of view as well as that of industrial, transportation and residential fields. The half of the total energy consumption in a building is occupied by HVAC (Heating, Ventilating and Air Conditioning) systems. In order to realize energy conservation of HVAC system, a thermal load prediction model for building is required. This paper propose a hybrid modeling approach with physical and Just-in-Time (JIT) model for building thermal load prediction. The proposed method has features and benefits such as, (1) it is applicable to the case in which past operation data for load prediction model learning is poor, (2) it has a self checking function, which always supervises if the data driven load prediction and the physical based one are consistent or not, so it can find if something is wrong in load prediction procedure, (3) it has ability to adjust load prediction in real-time against sudden change of model parameters and environmental conditions. The proposed method is evaluated with real operation data of an existing building, and the improvement of load prediction performance is illustrated.
Modeling of plasma in a hybrid electric propulsion for small satellites
NASA Astrophysics Data System (ADS)
Jugroot, Manish; Christou, Alex
2016-09-01
As space flight becomes more available and reliable, space-based technology is allowing for smaller and more cost-effective satellites to be produced. Working in large swarms, many small satellites can provide additional capabilities while reducing risk. These satellites require efficient, long term propulsion for manoeuvres, orbit maintenance and de-orbiting. The high exhaust velocity and propellant efficiency of electric propulsion makes it ideally suited for low thrust missions. The two dominant types of electric propulsion, namely ion thrusters and Hall thrusters, excel in different mission types. In this work, a novel electric hybrid propulsion design is modelled to enhance understanding of key phenomena and evaluate performance. Specifically, the modelled hybrid thruster seeks to overcome issues with existing Ion and Hall thruster designs. Scaling issues and optimization of the design will be discussed and will investigate a conceptual design of a hybrid spacecraft plasma engine.
NASA Astrophysics Data System (ADS)
Hu, Y.; Balachandran, S.; Pachon, J. E.; Baek, J.; Ivey, C.; Holmes, H.; Odman, M. T.; Mulholland, J. A.; Russell, A. G.
2013-10-01
A hybrid fine particulate matter (PM2.5) source apportionment approach based on a receptor-model (RM) species balance and species specific source impacts from a chemical transport model (CTM) equipped with a sensitivity analysis tool is developed to provide physically- and chemically-consistent relationships between source emissions and receptor impacts. This hybrid approach enhances RM results by providing initial estimates of source impacts from a much larger number of sources than are typically used in RMs, and provides source-receptor relationships for secondary species. Further, the method addresses issues of source collinearities, and accounts for emissions uncertainties. Hybrid method results also provide information on the resulting source impact uncertainties. We apply this hybrid approach to conduct PM2.5 source apportionment at Chemical Speciation Network (CSN) sites across the US. Ambient PM2.5 concentrations at these receptor sites were apportioned to 33 separate sources. Hybrid method results led to large changes of impacts from CTM estimates for sources such as dust, woodstove, and other biomass burning sources, but limited changes to others. The refinements reduced the differences between CTM-simulated and observed concentrations of individual PM2.5 species by over 98% when using a weighted least squared error minimization. The rankings of source impacts changed from the initial estimates, revealing that CTM-only results should be evaluated with observations. Assessment with RM results at six US locations showed that the hybrid results differ somewhat from commonly resolved sources. The hybrid method also resolved sources that typical RM methods do not capture without extra measurement information on unique tracers. The method can be readily applied to large domains and long (such as multi-annual) time periods to provide source impact estimates for management- and health-related studies.
Hybrid OPC modeling with SEM contour technique for 10nm node process
NASA Astrophysics Data System (ADS)
Hitomi, Keiichiro; Halle, Scott; Miller, Marshal; Graur, Ioana; Saulnier, Nicole; Dunn, Derren; Okai, Nobuhiro; Hotta, Shoji; Yamaguchi, Atsuko; Komuro, Hitoshi; Ishimoto, Toru; Koshihara, Shunsuke; Hojo, Yutaka
2014-03-01
Hybrid OPC modeling is investigated using both CDs from 1D and simple 2D structures and contours extracted from complex 2D structures, which are obtained by a Critical Dimension-Scanning Electron Microscope (CD-SEM). Recent studies have addressed some of key issues needed for the implementation of contour extraction, including an edge detection algorithm consistent with conventional CD measurements, contour averaging and contour alignment. Firstly, pattern contours obtained from CD-SEM images were used to complement traditional site driven CD metrology for the calibration of OPC models for both metal and contact layers of 10 nm-node logic device, developed in Albany Nano-Tech. The accuracy of hybrid OPC model was compared with that of conventional OPC model, which was created with only CD data. Accuracy of the model, defined as total error root-mean-square (RMS), was improved by 23% with the use of hybrid OPC modeling for contact layer and 18% for metal layer, respectively. Pattern specific benefit of hybrid modeling was also examined. Resist shrink correction was applied to contours extracted from CD-SEM images in order to improve accuracy of the contours, and shrink corrected contours were used for OPC modeling. The accuracy of OPC model with shrink correction was compared with that without shrink correction, and total error RMS was decreased by 0.2nm (12%) with shrink correction technique. Variation of model accuracy among 8 modeling runs with different model calibration patterns was reduced by applying shrink correction. The shrink correction of contours can improve accuracy and stability of OPC model.
A Comparison of Different Hybrid Methods on the Lorenz 1963 Model
NASA Astrophysics Data System (ADS)
Goodliff, Michael; van Leeuwen, Peter Jan; Amezcua, Javier
2014-05-01
Hybrid data assimilation schemes are becoming more widely used in Numerical Weather Prediction (NWP). These methods combine ideas from successful schemes such as 4DVAR and the ensemble transform Kalman filter (ETKF). The motivation behind hybrid schemes is to make use of a flow-dependent background error covariance matrix (Pb) in a variational setting. Although some of these hybrid schemes are being used operationally now, several basic questions on the reasons behind their performance are still open. Hybrid methods mainly differ in their use of Pb. Here we study 3 formulations. The first scheme, ETKF-4DVAR, uses Pb from the ETKF and combines it (weighted) with the climatological background error covariance matrix in 4DVAR (Bclim), at the start of each assimilation window. The second scheme, 4DVAR-BEN, is similar to ETKF-4DVAR but has zero weighting on Bclim. The third scheme, 4DENVAR, uses a the 4-dimensional covariance from the ensemble that alleviates the need for the tangent-linear and adjoint model in the 4DVar. We systematically compare the performance of ETKF-4DVAR, 4DVAR-BEN and 4DENVAR with respect to two traditional schemes (4DVAR and ETKF) on the Lorenz 1963 model. Using the analysis root mean square error (RMSE) as a metric, these schemes have been compared considering (1) assimilation window length and observation interval size, (2) ensemble size and (3) inflation of the climatological background error covariance matrix. For short assimilation windows, hybrid schemes are shown to outperform traditional methods. As the assimilation window length increases, sequential schemes become more accurate over both traditional variational and hybrid schemes which use an adjoint model. The 4DENVAR scheme performs slightly better in most cases than the ETKF over longer assimilation windows, which suggests that replacing the adjoint model by 4D-covariances from sequential schemes can increase the accuracy of variational schemes.
Hybrid Incompatibility Arises in a Sequence-Based Bioenergetic Model of Transcription Factor Binding
Tulchinsky, Alexander Y.; Johnson, Norman A.; Watt, Ward B.; Porter, Adam H.
2014-01-01
Postzygotic isolation between incipient species results from the accumulation of incompatibilities that arise as a consequence of genetic divergence. When phenotypes are determined by regulatory interactions, hybrid incompatibility can evolve even as a consequence of parallel adaptation in parental populations because interacting genes can produce the same phenotype through incompatible allelic combinations. We explore the evolutionary conditions that promote and constrain hybrid incompatibility in regulatory networks using a bioenergetic model (combining thermodynamics and kinetics) of transcriptional regulation, considering the bioenergetic basis of molecular interactions between transcription factors (TFs) and their binding sites. The bioenergetic parameters consider the free energy of formation of the bond between the TF and its binding site and the availability of TFs in the intracellular environment. Together these determine fractional occupancy of the TF on the promoter site, the degree of subsequent gene expression and in diploids, and the degree of dominance among allelic interactions. This results in a sigmoid genotype–phenotype map and fitness landscape, with the details of the shape determining the degree of bioenergetic evolutionary constraint on hybrid incompatibility. Using individual-based simulations, we subjected two allopatric populations to parallel directional or stabilizing selection. Misregulation of hybrid gene expression occurred under either type of selection, although it evolved faster under directional selection. Under directional selection, the extent of hybrid incompatibility increased with the slope of the genotype–phenotype map near the derived parental expression level. Under stabilizing selection, hybrid incompatibility arose from compensatory mutations and was greater when the bioenergetic properties of the interaction caused the space of nearly neutral genotypes around the stable expression level to be wide. F2’s showed
NASA Astrophysics Data System (ADS)
Curci, Vita; Dassisti, Michele; Josefa, Mula Bru; Manuel, Díaz Madroñero
2014-10-01
Supply chain model (SCM) are potentially capable to integrate different aspects in supporting decision making for enterprise management tasks. The aim of the paper is to propose an hybrid mathematical programming model for optimization of production requirements resources planning. The preliminary model was conceived bottom-up from a real industrial case analysed oriented to maximize cash flow. Despite the intense computational effort required to converge to a solution, optimisation done brought good result in solving the objective function.
2015-10-27
principal components, hybrid model, helium model, neutral composition, low-Earth orbit 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18...overtakes N2, O2, and O as the dominant species. Generally this occurs between 400 and 800 km, depending on season, location, and solar flux. At this...difficult force to determine and predict, in the orbit propagation model of low earth orbiting satellites [36]. The drag acceleration vector, ~a
NASA Astrophysics Data System (ADS)
Johnson, Erik A.; Elhaddad, Wael M.; Wojtkiewicz, Steven F.
2016-04-01
A variety of strategies have been developed over the past few decades to determine controllable damping device forces to mitigate the response of structures and mechanical systems to natural hazards and other excitations. These "smart" damping devices produce forces through passive means but have properties that can be controlled in real time, based on sensor measurements of response across the structure, to dramatically reduce structural motion by exploiting more than the local "information" that is available to purely passive devices. A common strategy is to design optimal damping forces using active control approaches and then try to reproduce those forces with the smart damper. However, these design forces, for some structures and performance objectives, may achieve high performance by selectively adding energy, which cannot be replicated by a controllable damping device, causing the smart damper performance to fall far short of what an active system would provide. The authors have recently demonstrated that a model predictive control strategy using hybrid system models, which utilize both continuous and binary states (the latter to capture the switching behavior between dissipative and non-dissipative forces), can provide reductions in structural response on the order of 50% relative to the conventional clipped-optimal design strategy. This paper explores the robustness of this newly proposed control strategy through evaluating controllable damper performance when the structure model differs from the nominal one used to design the damping strategy. Results from the application to a two-degree-of-freedom structure model confirms the robustness of the proposed strategy.
Development of hybrid 3-D hydrological modeling for the NCAR Community Earth System Model (CESM)
Zeng, Xubin; Troch, Peter; Pelletier, Jon; Niu, Guo-Yue; Gochis, David
2015-11-15
This is the Final Report of our four-year (3-year plus one-year no cost extension) collaborative project between the University of Arizona (UA) and the National Center for Atmospheric Research (NCAR). The overall objective of our project is to develop and evaluate the first hybrid 3-D hydrological model with a horizontal grid spacing of 1 km for the NCAR Community Earth System Model (CESM). We have made substantial progress in model development and evaluation, computational efficiencies and software engineering, and data development and evaluation, as discussed in Sections 2-4. Section 5 presents our success in data dissemination, while Section 6 discusses the scientific impacts of our work. Section 7 discusses education and mentoring success of our project, while Section 8 lists our relevant DOE services. All peer-reviewed papers that acknowledged this project are listed in Section 9. Highlights of our achievements include: • We have finished 20 papers (most published already) on model development and evaluation, computational efficiencies and software engineering, and data development and evaluation • The global datasets developed under this project have been permanently archived and publicly available • Some of our research results have already been implemented in WRF and CLM • Patrick Broxton and Michael Brunke have received their Ph.D. • PI Zeng has served on DOE proposal review panels and DOE lab scientific focus area (SFA) review panels
Modeling of plasma and thermo-fluid transport in hybrid welding
NASA Astrophysics Data System (ADS)
Ribic, Brandon D.
Hybrid welding combines a laser beam and electrical arc in order to join metals within a single pass at welding speeds on the order of 1 m min -1. Neither autonomous laser nor arc welding can achieve the weld geometry obtained from hybrid welding for the same process parameters. Depending upon the process parameters, hybrid weld depth and width can each be on the order of 5 mm. The ability to produce a wide weld bead increases gap tolerance for square joints which can reduce machining costs and joint fitting difficulty. The weld geometry and fast welding speed of hybrid welding make it a good choice for application in ship, pipeline, and aerospace welding. Heat transfer and fluid flow influence weld metal mixing, cooling rates, and weld bead geometry. Cooling rate affects weld microstructure and subsequent weld mechanical properties. Fluid flow and heat transfer in the liquid weld pool are affected by laser and arc energy absorption. The laser and arc generate plasmas which can influence arc and laser energy absorption. Metal vapors introduced from the keyhole, a vapor filled cavity formed near the laser focal point, influence arc plasma light emission and energy absorption. However, hybrid welding plasma properties near the opening of the keyhole are not known nor is the influence of arc power and heat source separation understood. A sound understanding of these processes is important to consistently achieving sound weldments. By varying process parameters during welding, it is possible to better understand their influence on temperature profiles, weld metal mixing, cooling rates, and plasma properties. The current literature has shown that important process parameters for hybrid welding include: arc power, laser power, and heat source separation distance. However, their influence on weld temperatures, fluid flow, cooling rates, and plasma properties are not well understood. Modeling has shown to be a successful means of better understanding the influence of
Modeling and control of a hybrid-electric vehicle for drivability and fuel economy improvements
NASA Astrophysics Data System (ADS)
Koprubasi, Kerem
The gradual decline of oil reserves and the increasing demand for energy over the past decades has resulted in automotive manufacturers seeking alternative solutions to reduce the dependency on fossil-based fuels for transportation. A viable technology that enables significant improvements in the overall tank-to-wheel vehicle energy conversion efficiencies is the hybridization of electrical and conventional drive systems. Sophisticated hybrid powertrain configurations require careful coordination of the actuators and the onboard energy sources for optimum use of the energy saving benefits. The term optimality is often associated with fuel economy, although other measures such as drivability and exhaust emissions are also equally important. This dissertation focuses on the design of hybrid-electric vehicle (HEV) control strategies that aim to minimize fuel consumption while maintaining good vehicle drivability. In order to facilitate the design of controllers based on mathematical models of the HEV system, a dynamic model that is capable of predicting longitudinal vehicle responses in the low-to-mid frequency region (up to 10 Hz) is developed for a parallel HEV configuration. The model is validated using experimental data from various driving modes including electric only, engine only and hybrid. The high fidelity of the model makes it possible to accurately identify critical drivability issues such as time lags, shunt, shuffle, torque holes and hesitation. Using the information derived from the vehicle model, an energy management strategy is developed and implemented on a test vehicle. The resulting control strategy has a hybrid structure in the sense that the main mode of operation (the hybrid mode) is occasionally interrupted by event-based rules to enable the use of the engine start-stop function. The changes in the driveline dynamics during this transition further contribute to the hybrid nature of the system. To address the unique characteristics of the HEV
Strategy and gaps for modeling, simulation, and control of hybrid systems
Rabiti, Cristian; Garcia, Humberto E.; Hovsapian, Rob; Kinoshita, Robert; Mesina, George L.; Bragg-Sitton, Shannon M.; Boardman, Richard D.
2015-04-01
The purpose of this report is to establish a strategy for modeling and simulation of candidate hybrid energy systems. Modeling and simulation is necessary to design, evaluate, and optimize the system technical and economic performance. Accordingly, this report first establishes the simulation requirements to analysis candidate hybrid systems. Simulation fidelity levels are established based on the temporal scale, real and synthetic data availability or needs, solution accuracy, and output parameters needed to evaluate case-specific figures of merit. Accordingly, the associated computational and co-simulation resources needed are established; including physical models when needed, code assembly and integrated solutions platforms, mathematical solvers, and data processing. This report first attempts to describe the figures of merit, systems requirements, and constraints that are necessary and sufficient to characterize the grid and hybrid systems behavior and market interactions. Loss of Load Probability (LOLP) and effective cost of Effective Cost of Energy (ECE), as opposed to the standard Levelized Cost of Electricty (LCOE), are introduced as technical and economical indices for integrated energy system evaluations. Financial assessment methods are subsequently introduced for evaluation of non-traditional, hybrid energy systems. Algorithms for coupled and iterative evaluation of the technical and economic performance are subsequently discussed. This report further defines modeling objectives, computational tools, solution approaches, and real-time data collection and processing (in some cases using real test units) that will be required to model, co-simulate, and optimize; (a) an energy system components (e.g., power generation unit, chemical process, electricity management unit), (b) system domains (e.g., thermal, electrical or chemical energy generation, conversion, and transport), and (c) systems control modules. Co-simulation of complex, tightly coupled
Comparative study of hybrid RANS-LES models for separated flows
NASA Astrophysics Data System (ADS)
Kumar, G.; Lakshmanan, S. K.; Gopalan, H.; De, A.
2016-06-01
Hybrid RANS-LES models are proven to be capable of predicting massively separated flows with reasonable computation cost. In this paper, Spalart-Allmaras (S-A) based detached eddy simulation (DES) model and three SST based hybrid models with different RANS to LES switching criteriaare investigated. The flow over periodic hill at Re = 10,595 is chosen as the benchmark for comparing the performance of the different models due to the complex flow physics and reasonablecomputational cost. The model performances are evaluated based on their prediction capabilities of velocity and stress profiles, and separation and reattachment point. The simulated results are validatedagainst experimental and numerical results available in literature. The S-A DES model predicted separation bubble accurately at the top of the hill, as reported earlier in experiments and other numerical results. This model also correctly predicted velocity and stress profiles in recirculation region. However, the performance of this model was poor in the post reattachment region. On the other hand, the k-ω SST based hybrid models performed poorly in recirculation region, but it fairly predicted stress profiles in post reattachment region.
Photonic states mixing beyond the plasmon hybridization model
NASA Astrophysics Data System (ADS)
Suryadharma, Radius N. S.; Iskandar, Alexander A.; Tjia, May-On
2016-07-01
A study is performed on a photonic-state mixing-pattern in an insulator-metal-insulator cylindrical silver nanoshell and its rich variations induced by changes in the geometry and dielectric media of the system, representing the combined influences of plasmon coupling strength and cavity effects. This study is performed in terms of the photonic local density of states (LDOS) calculated using the Green tensor method, in order to elucidate those combined effects. The energy profiles of LDOS inside the dielectric core are shown to exhibit consistently growing number of redshifted photonic states due to an enhanced plasmon coupling induced state mixing arising from decreased shell thickness, increased cavity size effect, and larger symmetry breaking effect induced by increased permittivity difference between the core and the background media. Further, an increase in cavity size leads to increased additional peaks that spread out toward the lower energy regime. A systematic analysis of those variations for a silver nanoshell with a fixed inner radius in vacuum background reveals a certain pattern of those growing number of redshifted states with an analytic expression for the corresponding energy downshifts, signifying a photonic state mixing scheme beyond the commonly adopted plasmon hybridization scheme. Finally, a remarkable correlation is demonstrated between the LDOS energy profiles outside the shell and the corresponding scattering efficiencies.
An Optimization Model for Plug-In Hybrid Electric Vehicles
Malikopoulos, Andreas; Smith, David E
2011-01-01
The necessity for environmentally conscious vehicle designs in conjunction with increasing concerns regarding U.S. dependency on foreign oil and climate change have induced significant investment towards enhancing the propulsion portfolio with new technologies. More recently, plug-in hybrid electric vehicles (PHEVs) have held great intuitive appeal and have attracted considerable attention. PHEVs have the potential to reduce petroleum consumption and greenhouse gas (GHG) emissions in the commercial transportation sector. They are especially appealing in situations where daily commuting is within a small amount of miles with excessive stop-and-go driving. The research effort outlined in this paper aims to investigate the implications of motor/generator and battery size on fuel economy and GHG emissions in a medium-duty PHEV. An optimization framework is developed and applied to two different parallel powertrain configurations, e.g., pre-transmission and post-transmission, to derive the optimal design with respect to motor/generator and battery size. A comparison between the conventional and PHEV configurations with equivalent size and performance under the same driving conditions is conducted, thus allowing an assessment of the fuel economy and GHG emissions potential improvement. The post-transmission parallel configuration yields higher fuel economy and less GHG emissions compared to pre-transmission configuration partly attributable to the enhanced regenerative braking efficiency.
Fuzzy logic-based analogue forecasting and hybrid modelling of horizontal visibility
NASA Astrophysics Data System (ADS)
Tuba, Zoltán; Bottyán, Zsolt
2017-02-01
Forecasting visibility is one of the greatest challenges in aviation meteorology. At the same time, high accuracy visibility forecasts can significantly reduce or make avoidable weather-related risk in aviation as well. To improve forecasting visibility, this research links fuzzy logic-based analogue forecasting and post-processed numerical weather prediction model outputs in hybrid forecast. Performance of analogue forecasting model was improved by the application of Analytic Hierarchy Process. Then, linear combination of the mentioned outputs was applied to create ultra-short term hybrid visibility prediction which gradually shifts the focus from statistical to numerical products taking their advantages during the forecast period. It gives the opportunity to bring closer the numerical visibility forecast to the observations even it is wrong initially. Complete verification of categorical forecasts was carried out; results are available for persistence and terminal aerodrome forecasts (TAF) as well in order to compare. The average value of Heidke Skill Score (HSS) of examined airports of analogue and hybrid forecasts shows very similar results even at the end of forecast period where the rate of analogue prediction in the final hybrid output is 0.1-0.2 only. However, in case of poor visibility (1000-2500 m), hybrid (0.65) and analogue forecasts (0.64) have similar average of HSS in the first 6 h of forecast period, and have better performance than persistence (0.60) or TAF (0.56). Important achievement that hybrid model takes into consideration physics and dynamics of the atmosphere due to the increasing part of the numerical weather prediction. In spite of this, its performance is similar to the most effective visibility forecasting methods and does not follow the poor verification results of clearly numerical outputs.
Analysis and Modeling of DIII-D Hybrid Discharges and their Extrapolation to ITER
Makowski, M A; Casper, T A; Jayakumar, R J; Pearlstein, L D; Petty, C C; Wade, M R
2006-06-16
Recent experiments on tokamaks around the world [1-5] have demonstrated discharges with moderately high performance in which the q-profile remains stationary, as measured by the motional Stark effect diagnostic, for periods up to several {tau}{sub R}. Hybrid discharges are characterize by q{sub min} {approx} 1, high {beta}{sub N}, and good confinement. These discharges have been termed hybrid because of their intermediate nature between that of an ordinary H-mode and advanced tokamak discharges. They form an attractive scenario for ITER as the normalized fusion performance ({beta}{sub N}H{sub 89P}/q{sub 95}{sup 2}) is at or above that for the ITER baseline Q{sub fus} = 10 scenario, even for q{sub 95} as high as 4.6. The startup phase is thought to be crucial to the ultimate evolution of the hybrid discharge. An open question is how hybrid discharges achieve and maintain their stationary state during the initial startup phase. To investigate this aspect of hybrid discharges, we have used the CORSICA code to model the early stages of a discharge. Results clearly indicate that neoclassical current evolution alone is insufficient to account for the time evolution of the q-profile and that an addition of non-inductive current source must be incorporated into the model to reproduce the experimental time history. We include non-inductive neutral beam and bootstrap current sources in the model, and investigate the difference between simulations with these sources and the experimentally inferred q-profile. Further, we have made preliminary estimates of the spatial structure of the current needed to bring the simulation and experiment into agreement. This additional non-inductive source has not been tied to any physical mechanism as yet. We present these results and discuss the implications for hybrid startup on ITER.
Separable Transition Density in the Hybrid Model for Tumor-Immune System Competition
Cattani, Carlo; Ciancio, Armando
2012-01-01
A hybrid model, on the competition tumor cells immune system, is studied under suitable hypotheses. The explicit form for the equations is obtained in the case where the density function of transition is expressed as the product of separable functions. A concrete application is given starting from a modified Lotka-Volterra system of equations. PMID:22291853
Hybrid Model of Inhomogeneous Solar Wind Plasma Heating by Alfven Wave Spectrum: Parametric Studies
NASA Technical Reports Server (NTRS)
Ofman, L.
2010-01-01
Observations of the solar wind plasma at 0.3 AU and beyond show that a turbulent spectrum of magnetic fluctuations is present. Remote sensing observations of the corona indicate that heavy ions are hotter than protons and their temperature is anisotropic (T(sub perpindicular / T(sub parallel) >> 1). We study the heating and the acceleration of multi-ion plasma in the solar wind by a turbulent spectrum of Alfvenic fluctuations using a 2-D hybrid numerical model. In the hybrid model the protons and heavy ions are treated kinetically as particles, while the electrons are included as neutralizing background fluid. This is the first two-dimensional hybrid parametric study of the solar wind plasma that includes an input turbulent wave spectrum guided by observation with inhomogeneous background density. We also investigate the effects of He++ ion beams in the inhomogeneous background plasma density on the heating of the solar wind plasma. The 2-D hybrid model treats parallel and oblique waves, together with cross-field inhomogeneity, self-consistently. We investigate the parametric dependence of the perpendicular heating, and the temperature anisotropy in the H+-He++ solar wind plasma. It was found that the scaling of the magnetic fluctuations power spectrum steepens in the higher-density regions, and the heating is channeled to these regions from the surrounding lower-density plasma due to wave refraction. The model parameters are applicable to the expected solar wind conditions at about 10 solar radii.
HYBRID SNCR-SCR TECHNOLOGIES FOR NOX CONTROL: MODELING AND EXPERIMENT
The hybrid process of homogeneous gas-phase selective non-catalytic reduction (SNCR) followed by selective catalytic reduction (SCR) of nitric oxide (NO) was investigated through experimentation and modeling. Measurements, using NO-doped flue gas from a gas-fired 29 kW test combu...
NASA Astrophysics Data System (ADS)
Shen, Yanfeng; Cesnik, Carlos E. S.
2016-09-01
This paper presents a new hybrid modeling technique for the efficient simulation of guided wave generation, propagation, and interaction with damage in complex composite structures. A local finite element model is deployed to capture the piezoelectric effects and actuation dynamics of the transmitter, while the global domain wave propagation and interaction with structural complexity (structure features and damage) are solved utilizing a local interaction simulation approach (LISA). This hybrid approach allows the accurate modeling of the local dynamics of the transducers and keeping the LISA formulation in an explicit format, which facilitates its readiness for parallel computing. The global LISA framework was extended through the 3D Kelvin-Voigt viscoelasticity theory to include anisotropic damping effects for composite structures, as an improvement over the existing LISA formulation. The global LISA framework was implemented using the compute unified device architecture running on graphic processing units. A commercial preprocessor is integrated seamlessly with the computational framework for grid generation and material property allocation to handle complex structures. The excitability and damping effects are successfully captured by this hybrid model, with experimental validation using the scanning laser doppler vibrometry. To demonstrate the capability of our hybrid approach for complex structures, guided wave propagation and interaction with a delamination in a composite panel with stiffeners is presented.
Ocean U.S. GODAE: Global Ocean Prediction with the HYbrid Coordinate Ocean Model (HYCOM)
2008-10-01
Ocean U.S. GODAE: Global Ocean Prediction with the HYbrid Coordinate Ocean Model (HYCOM) By Eric P. Chassignet1 and Harley E. Hurlburt2 1 COAPS ...UAcademia:U Florida State University/Center for Ocean-Atmospheric Prediction Studies ( COAPS ); University of Miami/Rosenstiel School of Marine and
ERIC Educational Resources Information Center
Hannah, David R.; Venkatachary, Ranga
2010-01-01
In this article, the authors present a retrospective analysis of an instructor's multiyear redesign of a course on organization theory into what is called a hybrid Classroom-as-Organization model. It is suggested that this new course design served to apprentice students to function in quasi-real organizational structures. The authors further argue…
A Design Perspective on the School-Work Boundary: A Hybrid Curriculum Model
ERIC Educational Resources Information Center
Zitter, Ilya; Hoeve, Aimée; de Bruijn, Elly
2016-01-01
This article proposes a model for the design of a hybrid VET curriculum across the school-work boundary. VET-curricula are designed on the basis of two main types of learning arrangements, namely, the plan for learning in school and for learning at the workplace. A challenge for curriculum development is creating consistency between different…
ERIC Educational Resources Information Center
Grable, John E.
2011-01-01
Innovation in doctoral degree program development and delivery provides an effective counterpoint to the expert-apprentice model established in the Middle Ages. The author outlines the importance of innovation in reaching adult learners and describes an innovative hybrid PhD program designed to allow aspiring doctoral adult-age students to pursue…
Rhombic micro-displacement amplifier for piezoelectric actuator and its linear and hybrid model
NASA Astrophysics Data System (ADS)
Chen, Jinglong; Zhang, Chunlin; Xu, Minglong; Zi, Yanyang; Zhang, Xinong
2015-01-01
This paper proposes rhombic micro-displacement amplifier (RMDA) for piezoelectric actuator (PA). First, the geometric amplification relations are analyzed and linear model is built to analyze the mechanical and electrical properties of this amplifier. Next, the accurate modeling method of amplifier is studied for important application of precise servo control. The classical Preisach model (CPM) is generally implemented using a numerical technique based on the first-order reversal curves (FORCs). The accuracy of CPM mainly depends on the number of FORCs. However, it is generally difficult to achieve enough number of FORCs in practice. So, Support Vector Machine (SVM) is employed in the work to circumvent the deficiency of the CPM. Then the hybrid model, which is based on discrete CPM and SVM is developed to account for hysteresis and dynamic effects. Finally, experimental validation is carried out. The analyzed result shows that this amplifier with the hybrid model is suitable for control application.
A zero-equation turbulence model for two-dimensional hybrid Hall thruster simulations
Cappelli, Mark A. Young, Christopher V.; Cha, Eunsun; Fernandez, Eduardo
2015-11-15
We present a model for electron transport across the magnetic field of a Hall thruster and integrate this model into 2-D hybrid particle-in-cell simulations. The model is based on a simple scaling of the turbulent electron energy dissipation rate and the assumption that this dissipation results in Ohmic heating. Implementing the model into 2-D hybrid simulations is straightforward and leverages the existing framework for solving the electron fluid equations. The model recovers the axial variation in the mobility seen in experiments, predicting the generation of a transport barrier which anchors the region of plasma acceleration. The predicted xenon neutral and ion velocities are found to be in good agreement with laser-induced fluorescence measurements.
Modeling and Simulation of Metallurgical Process Based on Hybrid Petri Net
NASA Astrophysics Data System (ADS)
Ren, Yujuan; Bao, Hong
2016-11-01
In order to achieve the goals of energy saving and emission reduction of iron and steel enterprises, an increasing number of modeling and simulation technologies are used to research and analyse metallurgical production process. In this paper, the basic principle of Hybrid Petri net is used to model and analyse the Metallurgical Process. Firstly, the definition of Hybrid Petri Net System of Metallurgical Process (MPHPNS) and its modeling theory are proposed. Secondly, the model of MPHPNS based on material flow is constructed. The dynamic flow of materials and the real-time change of each technological state in metallurgical process are simulated vividly by using this model. The simulation process can implement interaction between the continuous event dynamic system and the discrete event dynamic system at the same level, and play a positive role in the production decision.
One hybrid model combining singular spectrum analysis and LS + ARMA for polar motion prediction
NASA Astrophysics Data System (ADS)
Shen, Yi; Guo, Jinyun; Liu, Xin; Wei, Xiaobei; Li, Wudong
2017-01-01
Accurate real-time polar motion parameters play an important role in satellite navigation and positioning and spacecraft tracking. To meet the needs for real-time and high-accuracy polar motion prediction, a hybrid model that integrated singular spectrum analysis (SSA), least-squares (LS) extrapolation and an autoregressive moving average (ARMA) model was proposed. SSA was applied to separate the trend, the annual and the Chandler components from a given polar motion time series. LS extrapolation models were constructed for the separated trend, annual and Chandler components. An ARMA model was established for a synthetic sequence that contained the remaining SSA component and the residual series of LS fitting. In applying this hybrid model, multiple sets of polar motion predictions with lead times of 360 days were made based on an IERS 08 C04 series. The results showed that the proposed method could effectively predict the polar motion parameters.
Hybrid ensemble 4DVar assimilation of stratospheric ozone using a global shallow water model
NASA Astrophysics Data System (ADS)
Allen, Douglas R.; Hoppel, Karl W.; Kuhl, David D.
2016-07-01
Wind extraction from stratospheric ozone (O3) assimilation is examined using a hybrid ensemble 4-D variational assimilation (4DVar) shallow water model (SWM) system coupled to the tracer advection equation. Stratospheric radiance observations are simulated using global observations of the SWM fluid height (Z), while O3 observations represent sampling by a typical polar-orbiting satellite. Four ensemble sizes were examined (25, 50, 100, and 1518 members), with the largest ensemble equal to the number of dynamical state variables. The optimal length scale for ensemble localization was found by tuning an ensemble Kalman filter (EnKF). This scale was then used for localizing the ensemble covariances that were blended with conventional covariances in the hybrid 4DVar experiments. Both optimal length scale and optimal blending coefficient increase with ensemble size, with optimal blending coefficients varying from 0.2-0.5 for small ensembles to 0.5-1.0 for large ensembles. The hybrid system outperforms conventional 4DVar for all ensemble sizes, while for large ensembles the hybrid produces similar results to the offline EnKF. Assimilating O3 in addition to Z benefits the winds in the hybrid system, with the fractional improvement in global vector wind increasing from ˜ 35 % with 25 and 50 members to ˜ 50 % with 1518 members. For the smallest ensembles (25 and 50 members), the hybrid 4DVar assimilation improves the zonal wind analysis over conventional 4DVar in the Northern Hemisphere (winter-like) region and also at the Equator, where Z observations alone have difficulty constraining winds due to lack of geostrophy. For larger ensembles (100 and 1518 members), the hybrid system results in both zonal and meridional wind error reductions, relative to 4DVar, across the globe.
Simulation-optimization framework for multi-site multi-season hybrid stochastic streamflow modeling
NASA Astrophysics Data System (ADS)
Srivastav, Roshan; Srinivasan, K.; Sudheer, K. P.
2016-11-01
A simulation-optimization (S-O) framework is developed for the hybrid stochastic modeling of multi-site multi-season streamflows. The multi-objective optimization model formulated is the driver and the multi-site, multi-season hybrid matched block bootstrap model (MHMABB) is the simulation engine within this framework. The multi-site multi-season simulation model is the extension of the existing single-site multi-season simulation model. A robust and efficient evolutionary search based technique, namely, non-dominated sorting based genetic algorithm (NSGA - II) is employed as the solution technique for the multi-objective optimization within the S-O framework. The objective functions employed are related to the preservation of the multi-site critical deficit run sum and the constraints introduced are concerned with the hybrid model parameter space, and the preservation of certain statistics (such as inter-annual dependence and/or skewness of aggregated annual flows). The efficacy of the proposed S-O framework is brought out through a case example from the Colorado River basin. The proposed multi-site multi-season model AMHMABB (whose parameters are obtained from the proposed S-O framework) preserves the temporal as well as the spatial statistics of the historical flows. Also, the other multi-site deficit run characteristics namely, the number of runs, the maximum run length, the mean run sum and the mean run length are well preserved by the AMHMABB model. Overall, the proposed AMHMABB model is able to show better streamflow modeling performance when compared with the simulation based SMHMABB model, plausibly due to the significant role played by: (i) the objective functions related to the preservation of multi-site critical deficit run sum; (ii) the huge hybrid model parameter space available for the evolutionary search and (iii) the constraint on the preservation of the inter-annual dependence. Split-sample validation results indicate that the AMHMABB model is
A hybrid model for short-term bacillary dysentery prediction in Yichang City, China.
Yan, Weirong; Xu, Yong; Yang, Xiaobing; Zhou, Yikai
2010-07-01
Bacillary dysentery is still a common and serious public health problem in China. This paper is aimed at developing and evaluating an innovative hybrid model, which combines the seasonal autoregressive integrated moving average (SARIMA) and the generalized regression neural network (GRNN) models, for bacillary dysentery forecasting. Data of monthly bacillary dysentery incidence in Yichang City from 2000-2007 was obtained from Yichang Disease Control and Prevention Center. The SARIMA and SARIMA-GRNN model were developed and validated by dividing the data file into two data sets: data from the past 5 years was used to construct the models, and data from January to June of the 6th year was used to validate them. Simulation and forecasting performance was evaluated and compared between the two models. The hybrid SARIMA-GRNN model was found to outperform the SARIMA model with the lower mean square error, mean absolute error, and mean absolute percentage error in simulation and prediction results. Developing and applying the SARIMA-GRNN hybrid model is an effective decision supportive method for producing reliable forecasts of bacillary dysentery for the study area.
A hybrid finite-difference and analytic element groundwater model.
Haitjema, H M; Feinstein, D T; Hunt, R J; Gusyev, M A
2010-01-01
Regional finite-difference models tend to have large cell sizes, often on the order of 1-2 km on a side. Although the regional flow patterns in deeper formations may be adequately represented by such a model, the intricate surface water and groundwater interactions in the shallower layers are not. Several stream reaches and nearby wells may occur in a single cell, precluding any meaningful modeling of the surface water and groundwater interactions between the individual features. We propose to replace the upper MODFLOW layer or layers, in which the surface water and groundwater interactions occur, by an analytic element model (GFLOW) that does not employ a model grid; instead, it represents wells and surface waters directly by the use of point-sinks and line-sinks. For many practical cases it suffices to provide GFLOW with the vertical leakage rates calculated in the original coarse MODFLOW model in order to obtain a good representation of surface water and groundwater interactions. However, when the combined transmissivities in the deeper (MODFLOW) layers dominate, the accuracy of the GFLOW solution diminishes. For those cases, an iterative coupling procedure, whereby the leakages between the GFLOW and MODFLOW model are updated, appreciably improves the overall solution, albeit at considerable computational cost. The coupled GFLOW-MODFLOW model is applicable to relatively large areas, in many cases to the entire model domain, thus forming an attractive alternative to local grid refinement or inset models.
Modelling grain-scattered ultrasound in austenitic stainless-steel welds: A hybrid model
Nowers, O.; Duxbury, D. J.; Velichko, A.; Drinkwater, B. W.
2015-03-31
The ultrasonic inspection of austenitic stainless steel welds can be challenging due to their coarse grain structure, charaterised by preferentially oriented, elongated grains. The anisotropy of the weld is manifested as both a ‘steering’ of the beam and the back-scatter of energy due to the macroscopic granular structure of the weld. However, the influence of weld properties, such as mean grain size and orientation distribution, on the magnitude of scattered ultrasound is not well understood. A hybrid model has been developed to allow the study of grain-scatter effects in austenitic welds. An efficient 2D Finite Element (FE) method is used to calculate the complete scattering response from a single elliptical austenitic grain of arbitrary length and width as a function of the specific inspection frequency. A grain allocation model of the weld is presented to approximate the characteristic structures observed in austenitic welds and the complete scattering behaviour of each grain calculated. This model is incorporated into a semi-analytical framework for a single-element inspection of a typical weld in immersion. Experimental validation evidence is demonstrated indicating excellent qualitative agreement of SNR as a function of frequency and a minimum SNR difference of 2 dB at a centre frequency of 2.25 MHz. Additionally, an example Monte-Carlo study is presented detailing the variation of SNR as a function of the anisotropy distribution of the weld, and the application of confidence analysis to inform inspection development.
Early experiments with the OpenMP/MPI hybrid programming model.
Lusk, E.; Chan, A.; Mathematics and Computer Science; Univ. of Chicago
2008-01-01
The paper describes some very early experiments on new architectures that support the hybrid programming model. The results are promising in that OpenMP threads interact with MPI as desired, allowing OpenMP-agnostic tools to be used. They explore three environments: a 'typical' Linux cluster, a new large-scale machine from SiCortex, and the new IBM BG/P, which have quite different compilers and runtime systems for both OpenMP and MPI. They look at a few simple, diagnostic programs, and one 'application-like' test program. They demonstrate the use of a tool that can examine the detailed sequence of events in a hybrid program and illustrate that a hybrid computation might not always proceed as expected.
Bootstrap data methodology for sequential hybrid model building
NASA Technical Reports Server (NTRS)
Volponi, Allan J. (Inventor); Brotherton, Thomas (Inventor)
2007-01-01
A method for modeling engine operation comprising the steps of: 1. collecting a first plurality of sensory data, 2. partitioning a flight envelope into a plurality of sub-regions, 3. assigning the first plurality of sensory data into the plurality of sub-regions, 4. generating an empirical model of at least one of the plurality of sub-regions, 5. generating a statistical summary model for at least one of the plurality of sub-regions, 6. collecting an additional plurality of sensory data, 7. partitioning the second plurality of sensory data into the plurality of sub-regions, 8. generating a plurality of pseudo-data using the empirical model, and 9. concatenating the plurality of pseudo-data and the additional plurality of sensory data to generate an updated empirical model and an updated statistical summary model for at least one of the plurality of sub-regions.
The HYCOM (HYbrid Coordinate Ocean Model) Data Assimilative System
2007-06-01
predictability of coastal and regional subsystems, and z-levels (constant fixed depths) are best used to initial conditions for climate forecast models...dynamically smooth transition to a coordinates Lagrangian layer model in the sense that the MICOM in shallow coastal regions and to fixed pressure-level...models with fixed z- and a-coordinates greatest extent possible while enforcing the minimum that use the continuity equation to diagnose vertical
A hybrid deep neural network and physically based distributed model for river stage prediction
NASA Astrophysics Data System (ADS)
hitokoto, Masayuki; sakuraba, Masaaki
2016-04-01
We developed the real-time river stage prediction model, using the hybrid deep neural network and physically based distributed model. As the basic model, 4 layer feed-forward artificial neural network (ANN) was used. As a network training method, the deep learning technique was applied. To optimize the network weight, the stochastic gradient descent method based on the back propagation method was used. As a pre-training method, the denoising autoencoder was used. Input of the ANN model is hourly change of water level and hourly rainfall, output data is water level of downstream station. In general, the desirable input of the ANN has strong correlation with the output. In conceptual hydrological model such as tank model and storage-function model, river discharge is governed by the catchment storage. Therefore, the change of the catchment storage, downstream discharge subtracted from rainfall, can be the potent input candidate of the ANN model instead of rainfall. From this point of view, the hybrid deep neural network and physically based distributed model was developed. The prediction procedure of the hybrid model is as follows; first, downstream discharge was calculated by the distributed model, and then estimates the hourly change of catchment storage form rainfall and calculated discharge as the input of the ANN model, and finally the ANN model was calculated. In the training phase, hourly change of catchment storage can be calculated by the observed rainfall and discharge data. The developed model was applied to the one catchment of the OOYODO River, one of the first-grade river in Japan. The modeled catchment is 695 square km. For the training data, 5 water level gauging station and 14 rain-gauge station in the catchment was used. The training floods, superior 24 events, were selected during the period of 2005-2014. Prediction was made up to 6 hours, and 6 models were developed for each prediction time. To set the proper learning parameters and network
Data-driven components in a model of inner-shelf sorted bedforms: a new hybrid model
NASA Astrophysics Data System (ADS)
Goldstein, E. B.; Coco, G.; Murray, A. B.; Green, M. O.
2014-01-01
Numerical models rely on the parameterization of processes that often lack a deterministic description. In this contribution we demonstrate the applicability of using machine learning, a class of optimization tools from the discipline of computer science, to develop parameterizations when extensive data sets exist. We develop a new predictor for near-bed suspended sediment reference concentration under unbroken waves using genetic programming, a machine learning technique. We demonstrate that this newly developed parameterization performs as well or better than existing empirical predictors, depending on the chosen error metric. We add this new predictor into an established model for inner-shelf sorted bedforms. Additionally we incorporate a previously reported machine-learning-derived predictor for oscillatory flow ripples into the sorted bedform model. This new "hybrid" sorted bedform model, whereby machine learning components are integrated into a numerical model, demonstrates a method of incorporating observational data (filtered through a machine learning algorithm) directly into a numerical model. Results suggest that the new hybrid model is able to capture dynamics previously absent from the model - specifically, two observed pattern modes of sorted bedforms. Lastly we discuss the challenge of integrating data-driven components into morphodynamic models and the future of hybrid modeling.
Photoionization models of the CALIFA H II regions. I. Hybrid models
NASA Astrophysics Data System (ADS)
Morisset, C.; Delgado-Inglada, G.; Sánchez, S. F.; Galbany, L.; García-Benito, R.; Husemann, B.; Marino, R. A.; Mast, D.; Roth, M. M.
2016-10-01
Photoionization models of H ii regions require as input a description of the ionizing spectral energy distribution (SED) and of the gas distribution, in terms of ionization parameter U and chemical abundances (e.g., O/H and N/O).A strong degeneracy exists between the hardness of the SED and U, which in turn leads to high uncertainties in the determination of the other parameters, including abundances. One way to resolve the degeneracy is to fix one of the parameters using additional information. For each of the ~20 000 sources of the CALIFA H ii regions catalog, a grid of photoionization models is computed assuming the ionizing SED to be described by the underlying stellar population obtained from spectral synthesis modeling. The ionizing SED is then defined as the sum of various stellar bursts of different ages and metallicities. This solves the degeneracy between the shape of the ionizing SED and U. The nebular metallicity (associated with O/H) is defined using the classical strong line method O3N2 (which gives our models the status of "hybrids"). The remaining free parameters are the abundance ratio N/O and the ionization parameter U, which are determined by looking for the model fitting [N ii]/Hα and [O iii]/Hβ. The models are also selected to fit [O ii]/Hβ. This process leads to a set of ~3200 models that reproduce the three observations simultaneously. We find that the regions associated with young stellar bursts (i.e., ionized by OB stars) are affected by leaking of ionizing photons,the proportion of escaping photons having a median of 80%. The set of photoionization models satisfactorily reproduces the electron temperature derived from the [O iii]λ4363/5007 line ratio. We determine new relations between the nebular parameters, like the ionization parameter U and the [O ii]/[O iii] or [S ii]/[S iii] line ratios. A new relation between N/O and O/H is obtained, mostly compatible with previous empirical determinations (and not with previous results obtained
NASA Astrophysics Data System (ADS)
Hu, Y.; Balachandran, S.; Pachon, J. E.; Baek, J.; Ivey, C.; Holmes, H.; Odman, M. T.; Mulholland, J. A.; Russell, A. G.
2014-06-01
A hybrid fine particulate matter (PM2.5) source apportionment approach based on a receptor model (RM) species balance and species specific source impacts from a chemical transport model (CTM) equipped with a sensitivity analysis tool is developed to provide physically and chemically consistent relationships between source emissions and receptor impacts. This hybrid approach enhances RM results by providing initial estimates of source impacts from a much larger number of sources than are typically used in RMs, and provides source-receptor relationships for secondary species. Further, the method addresses issues of source collinearities and accounts for emissions uncertainties. We apply this hybrid approach to conduct PM2.5 source apportionment at Chemical Speciation Network (CSN) sites across the US. Ambient PM2.5 concentrations at these receptor sites were apportioned to 33 separate sources. Hybrid method results led to large changes of impacts from CTM estimates for sources such as dust, woodstoves, and other biomass-burning sources, but limited changes to others. The refinements reduced the differences between CTM-simulated and observed concentrations of individual PM2.5 species by over 98% when using a weighted least-squares error minimization. The rankings of source impacts changed from the initial estimates, further demonstrating that CTM-only results should be evaluated with observations. Assessment with RM results at six US locations showed that the hybrid results differ somewhat from commonly resolved sources. The hybrid method also resolved sources that typical RM methods do not capture without extra measurement information for unique tracers. The method can be readily applied to large domains and long (such as multi-annual) time periods to provide source impact estimates for management- and health-related studies.
NASA Astrophysics Data System (ADS)
Cardelli, E.; Faba, A.; Laudani, A.; Lozito, G. M.; Riganti Fulginei, F.; Salvini, A.
2016-04-01
This paper presents a hybrid neural network approach to model magnetic hysteresis at macro-magnetic scale. That approach aims to be coupled together with numerical treatments of magnetic hysteresis such as FEM numerical solvers of the Maxwell's equations in time domain, as in case of the non-linear dynamic analysis of electrical machines, and other similar devices, allowing a complete computer simulation with acceptable run times. The proposed Hybrid Neural System consists of four inputs representing the magnetic induction and magnetic field components at each time step and it is trained by 2D and scalar measurements performed on the magnetic material to be modeled. The magnetic induction B is assumed as entry point and the output of the Hybrid Neural System returns the predicted value of the field H at the same time step. Within the Hybrid Neural System, a suitably trained neural network is used for predicting the hysteretic behavior of the material to be modeled. Validations with experimental tests and simulations for symmetric, non-symmetric and minor loops are presented.
Enhanced hybrid search algorithm for protein structure prediction using the 3D-HP lattice model.
Zhou, Changjun; Hou, Caixia; Zhang, Qiang; Wei, Xiaopeng
2013-09-01
The problem of protein structure prediction in the hydrophobic-polar (HP) lattice model is the prediction of protein tertiary structure. This problem is usually referred to as the protein folding problem. This paper presents a method for the application of an enhanced hybrid search algorithm to the problem of protein folding prediction, using the three dimensional (3D) HP lattice model. The enhanced hybrid search algorithm is a combination of the particle swarm optimizer (PSO) and tabu search (TS) algorithms. Since the PSO algorithm entraps local minimum in later evolution extremely easily, we combined PSO with the TS algorithm, which has properties of global optimization. Since the technologies of crossover and mutation are applied many times to PSO and TS algorithms, so enhanced hybrid search algorithm is called the MCMPSO-TS (multiple crossover and mutation PSO-TS) algorithm. Experimental results show that the MCMPSO-TS algorithm can find the best solutions so far for the listed benchmarks, which will help comparison with any future paper approach. Moreover, real protein sequences and Fibonacci sequences are verified in the 3D HP lattice model for the first time. Compared with the previous evolutionary algorithms, the new hybrid search algorithm is novel, and can be used effectively to predict 3D protein folding structure. With continuous development and changes in amino acids sequences, the new algorithm will also make a contribution to the study of new protein sequences.
NASA Astrophysics Data System (ADS)
Huang, Mingzhi; Zhang, Tao; Ruan, Jujun; Chen, Xiaohong
2017-01-01
A new efficient hybrid intelligent approach based on fuzzy wavelet neural network (FWNN) was proposed for effectively modeling and simulating biodegradation process of Dimethyl phthalate (DMP) in an anaerobic/anoxic/oxic (AAO) wastewater treatment process. With the self learning and memory abilities of neural networks (NN), handling uncertainty capacity of fuzzy logic (FL), analyzing local details superiority of wavelet transform (WT) and global search of genetic algorithm (GA), the proposed hybrid intelligent model can extract the dynamic behavior and complex interrelationships from various water quality variables. For finding the optimal values for parameters of the proposed FWNN, a hybrid learning algorithm integrating an improved genetic optimization and gradient descent algorithm is employed. The results show, compared with NN model (optimized by GA) and kinetic model, the proposed FWNN model have the quicker convergence speed, the higher prediction performance, and smaller RMSE (0.080), MSE (0.0064), MAPE (1.8158) and higher R2 (0.9851) values. which illustrates FWNN model simulates effluent DMP more accurately than the mechanism model.
Teixeira, A; Cunha, A E; Clemente, J J; Moreira, J L; Cruz, H J; Alves, P M; Carrondo, M J T; Oliveira, R
2005-08-22
In this work a model-based optimization study of fed-batch BHK-21 cultures expressing the human fusion glycoprotein IgG1-IL2 was performed. It was concluded that due to the complexity of the BHK metabolism it is rather difficult to develop a kinetic model with sufficient accuracy for optimization studies. Many kinetic expressions and a large number of parameters are involved resulting in a complex identification problem. For this reason, an alternative more cost-effective methodology based on hybrid grey-box models was adopted. Several model structures combining the a priori reliable first principles knowledge with black-box models were investigated using data from batch and fed-batch experiments. It has been reported in previous studies that the BHK metabolism exhibits modulation particularities when compared to other mammalian cell lines. It was concluded that these mechanisms were effectively captured by the hybrid model, this being of crucial importance for the successful optimization of the process operation. A method was proposed to monitor the risk of hybrid model unreliability and to constraint the optimization results to acceptable risk levels. From the optimization study it was concluded that the process productivity may be considerably increased if the glutamine and glucose concentrations are maintained at low levels during the growth phase and then glutamine feeding is increased.
Huang, Mingzhi; Zhang, Tao; Ruan, Jujun; Chen, Xiaohong
2017-01-01
A new efficient hybrid intelligent approach based on fuzzy wavelet neural network (FWNN) was proposed for effectively modeling and simulating biodegradation process of Dimethyl phthalate (DMP) in an anaerobic/anoxic/oxic (AAO) wastewater treatment process. With the self learning and memory abilities of neural networks (NN), handling uncertainty capacity of fuzzy logic (FL), analyzing local details superiority of wavelet transform (WT) and global search of genetic algorithm (GA), the proposed hybrid intelligent model can extract the dynamic behavior and complex interrelationships from various water quality variables. For finding the optimal values for parameters of the proposed FWNN, a hybrid learning algorithm integrating an improved genetic optimization and gradient descent algorithm is employed. The results show, compared with NN model (optimized by GA) and kinetic model, the proposed FWNN model have the quicker convergence speed, the higher prediction performance, and smaller RMSE (0.080), MSE (0.0064), MAPE (1.8158) and higher R2 (0.9851) values. which illustrates FWNN model simulates effluent DMP more accurately than the mechanism model. PMID:28120889
A Toolkit for Building Hybrid, Multi-Resolution PMESII Models
2007-11-01
Ptolemy Integration 23 4. Support for Interoperable PMESII Modeling 31 5. Support for PMESII Model Verification and Validation 34 5.1 Verification 34...terrorist leader behavior .............................................. 20 Figure 3-2: Editors for Two Ptolemy Components in the GRADE Edit Workspace...27 Figure 3-3: Selecting the Customize→Ports Context Menu Item in the Ptolemy Component Editor
Two-field axion-monodromy hybrid inflation model: Dante's Waterfall
NASA Astrophysics Data System (ADS)
Carone, Christopher D.; Erlich, Joshua; Sensharma, Anuraag; Wang, Zhen
2015-02-01
We describe a hybrid axion-monodromy inflation model motivated by the Dante's Inferno scenario. In Dante's Inferno, a two-field potential features a stable trench along which a linear combination of the two fields slowly rolls, rendering the dynamics essentially identical to that of single-field chaotic inflation. A shift symmetry allows for the Lyth bound to be effectively evaded as in other axion-monodromy models. In our proposal, the potential is concave downward near the origin and the inflaton trajectory is a gradual downward spiral, ending at a point where the trench becomes unstable. There, the fields begin falling rapidly towards the minimum of the potential and inflation terminates as in a hybrid model. We find parameter choices that reproduce observed features of the cosmic microwave background, and discuss our model in light of recent results from the BICEP2 and Planck experiments.
Accurate modeling of switched reluctance machine based on hybrid trained WNN
NASA Astrophysics Data System (ADS)
Song, Shoujun; Ge, Lefei; Ma, Shaojie; Zhang, Man
2014-04-01
According to the strong nonlinear electromagnetic characteristics of switched reluctance machine (SRM), a novel accurate modeling method is proposed based on hybrid trained wavelet neural network (WNN) which combines improved genetic algorithm (GA) with gradient descent (GD) method to train the network. In the novel method, WNN is trained by GD method based on the initial weights obtained per improved GA optimization, and the global parallel searching capability of stochastic algorithm and local convergence speed of deterministic algorithm are combined to enhance the training accuracy, stability and speed. Based on the measured electromagnetic characteristics of a 3-phase 12/8-pole SRM, the nonlinear simulation model is built by hybrid trained WNN in Matlab. The phase current and mechanical characteristics from simulation under different working conditions meet well with those from experiments, which indicates the accuracy of the model for dynamic and static performance evaluation of SRM and verifies the effectiveness of the proposed modeling method.
A linear dispersion relation for the hybrid kinetic-ion/fluid-electron model of plasma physics
NASA Astrophysics Data System (ADS)
Told, D.; Cookmeyer, J.; Astfalk, P.; Jenko, F.
2016-07-01
A dispersion relation for a commonly used hybrid model of plasma physics is developed, which combines fully kinetic ions and a massless-electron fluid description. Although this model and variations of it have been used to describe plasma phenomena for about 40 years, to date there exists no general dispersion relation to describe the linear wave physics contained in the model. Previous efforts along these lines are extended here to retain arbitrary wave propagation angles, temperature anisotropy effects, as well as additional terms in the generalized Ohm’s law which determines the electric field. A numerical solver for the dispersion relation is developed, and linear wave physics is benchmarked against solutions of a full Vlasov-Maxwell dispersion relation solver. This work opens the door to a more accurate interpretation of existing and future wave and turbulence simulations using this type of hybrid model.
A hybrid model of the CO2 geochemical cycle and its application to large impact events
NASA Technical Reports Server (NTRS)
Kasting, J. F.; Pollack, J. B.; Toon, O. B.; Richardson, S. M.
1986-01-01
The effects of a large asteriod or comet impact on modern and ancient marine biospheres are analyzed. A hybrid model of the carbonate-silicate geochemical cycle, which is capable of calculating the concentrations of carbon dioxide in the atmosphere, ocean, and sedimentary rocks, is described. The differences between the Keir and Berger (1983) model and the hybrid model are discussed. Equilibrium solutions are derived for the preindustrial atmosphere/ocean system and for a system similar to that of the late Cretaceous Period. The model data reveal that globl darkening caused by a stratospheric dust veil could destroy the existing phytoplankton within a period of several weeks or months, nd the dissolution of atmospheric NO(x) compounds would lower the pH of ocean surface waters and release CO2 into the atmosphere. It is noted that the surface temperatures could be increased by several degrees and surface oceans would be uninhabitable for calcaerous organisms for approximately 20 years.
Accurate modeling of switched reluctance machine based on hybrid trained WNN
Song, Shoujun Ge, Lefei; Ma, Shaojie; Zhang, Man
2014-04-15
According to the strong nonlinear electromagnetic characteristics of switched reluctance machine (SRM), a novel accurate modeling method is proposed based on hybrid trained wavelet neural network (WNN) which combines improved genetic algorithm (GA) with gradient descent (GD) method to train the network. In the novel method, WNN is trained by GD method based on the initial weights obtained per improved GA optimization, and the global parallel searching capability of stochastic algorithm and local convergence speed of deterministic algorithm are combined to enhance the training accuracy, stability and speed. Based on the measured electromagnetic characteristics of a 3-phase 12/8-pole SRM, the nonlinear simulation model is built by hybrid trained WNN in Matlab. The phase current and mechanical characteristics from simulation under different working conditions meet well with those from experiments, which indicates the accuracy of the model for dynamic and static performance evaluation of SRM and verifies the effectiveness of the proposed modeling method.
A regional hybrid GSI/ETKF data assimilation scheme for the WRF/ARW model
NASA Astrophysics Data System (ADS)
Mizzi, A. P.
2011-12-01
A regional hybrid GSI/ETKF data assimilation scheme for the WRF/ARW model Arthur P. Mizzi National Center for Atmospheric Research Boulder, CO 80307 303-497-8987 mizzi@ucar.edu Recently, there has been increased interest in hybrid variational data assimilation due to its ability to improve numerical weather forecast accuracy by incorporating ensemble error information into the data assimilation process (Buehner, 2010a, b; Wang 2010). In this paper, we introduce a GSI/ETKF regional hybrid (Mizzi, 2011). The GSI/ETKF regional hybrid uses a modified version of NOAA/EMC's GSI global hybrid (Wang, 2010) for the ensemble mean analysis and an ETKF (Bishop, et. al., 2001) to update the ensemble perturbations. We tested the GSI/ETKF regional hybrid by applying it to cycling experiments with WRF/ARW on a coarse-resolution domain covering the continental United States (CONUS) that: (i) compared different ETKF schemes, and (ii) reduced and held the number of ETKF observations constant. The results from those experiments showed that: (i) the ETKF scheme requiring the least amount of inflation provided the lowest 12-hr forecast RMSEs (ii) holding the number of ETKF observations constant removed the oscillation in the posterior ETKF ensemble spread noted by Bowler et al., (2008), and (iii) reducing the number of ETKF observations lowered the 12-hr forecast RMSEs. Presently, we are extending this work to a comparison of the GSI/ETKF regional hybrid with a GSI/LETKF regional hybrid based on the LETKF of Ott, et. al., (2004) and a GSI/EnKF regional hybrid based on the DART EnKF (Anderson et. al., 2009). Generally, the GSI/LETKF and GSI/EnKF schemes require less ensemble spread inflation compared to the GSI/ETKF scheme. Consequently, we expect the GSI/LETKF and GSI/EnKF schemes to provide lower 12-hr forecast RMSEs compared to the GSI/ETKF results. Our preliminary results are consistent with that supposition.
Suited and Unsuited Hybrid III Impact Testing and Finite Element Model Characterization
NASA Technical Reports Server (NTRS)
Lawrence, C.; Somers, J. T.; Baldwin, M. A.; Wells, J. A.; Newby, N.; Currie, N. J.
2016-01-01
NASA spacecraft design requirements for occupant protection are a combination of the Brinkley Dynamic Response Criteria and injury assessment reference values (IARV) extracted from anthropomorphic test devices (ATD). For the ATD IARVs, the requirements specify the use of the 5th percentile female Hybrid III and the 95th percentile male Hybrid III. Each of these ATDs is required to be fitted with an articulating pelvis (also known as the aerospace pelvis) and a straight spine. The articulating pelvis is necessary for the ATD to fit into spacecraft seats, while the straight spine is required as injury metrics for vertical accelerations are better defined for this configuration. Sled testing of the Hybrid III 5th Percentile Female Anthropomorphic Test Device (ATD) was performed at Wright-Patterson Air Force Base (WAPFB). Two 5th Percentile ATDs were tested, the Air Force Research Lab (AFRL) and NASA owned Hybrid III ATDs with aerospace pelvises. Testing was also conducted with a NASA-owned 95th Percentile Male Hybrid III with aerospace pelvis at WPAFB. Testing was performed using an Orion seat prototype provided by Johnson Space Center (JSC). A 5-point harness comprised of 2 inch webbing was also provided by JSC. For suited runs, a small and extra-large Advanced Crew Escape System (ACES) suit and helmet were also provided by JSC. Impact vectors were combined frontal/spinal and rear/lateral. Some pure spinal and rear axis testing was also performed for model validation. Peak accelerations ranged between 15 and 20-g. This range was targeted because the ATD responses fell close to the IARV defined in the Human-Systems Integration Requirements (HSIR) document. Rise times varied between 70 and 110 ms to assess differences in ATD responses and model correlation for different impact energies. The purpose of the test series was to evaluate the Hybrid III ATD models in Orion-specific landing orientations both with and without a spacesuit. The results of these tests were used
Temperature analysis of induction motors using a hybrid thermal model with distributed heat sources
NASA Astrophysics Data System (ADS)
Mukhopadhyay, S. C.; Pal, S. K.
1998-06-01
The article presents a hybrid thermal model for the accurate estimation of temperature distribution of induction motors. The developed model is a combination of lumped and distributed thermal parameters which are obtained from motor dimensions and other constants such as material density, specific heats, thermal conductivity, etc. The model is especially suited for the derating of induction motors operating under distorted and unbalanced supply condition. The model have been applied to a small (2hp, 415 V, 3-phase) cage rotor induction motor. The performance of the model is confirmed by experimental temperature data from the body and the conductor inside the slots of the motor.
Chen, Yumiao; Yang, Zhongliang
2017-01-01
Recently, several researchers have considered the problem of reconstruction of handwriting and other meaningful arm and hand movements from surface electromyography (sEMG). Although much progress has been made, several practical limitations may still affect the clinical applicability of sEMG-based techniques. In this paper, a novel three-step hybrid model of coordinate state transition, sEMG feature extraction and gene expression programming (GEP) prediction is proposed for reconstructing drawing traces of 12 basic one-stroke shapes from multichannel surface electromyography. Using a specially designed coordinate data acquisition system, we recorded the coordinate data of drawing traces collected in accordance with the time series while 7-channel EMG signals were recorded. As a widely-used time domain feature, Root Mean Square (RMS) was extracted with the analysis window. The preliminary reconstruction models can be established by GEP. Then, the original drawing traces can be approximated by a constructed prediction model. Applying the three-step hybrid model, we were able to convert seven channels of EMG activity recorded from the arm muscles into smooth reconstructions of drawing traces. The hybrid model can yield a mean accuracy of 74% in within-group design (one set of prediction models for all shapes) and 86% in between-group design (one separate set of prediction models for each shape), averaged for the reconstructed x and y coordinates. It can be concluded that it is feasible for the proposed three-step hybrid model to improve the reconstruction ability of drawing traces from sEMG. PMID:28261041
Chen, Yumiao; Yang, Zhongliang
2017-01-01
Recently, several researchers have considered the problem of reconstruction of handwriting and other meaningful arm and hand movements from surface electromyography (sEMG). Although much progress has been made, several practical limitations may still affect the clinical applicability of sEMG-based techniques. In this paper, a novel three-step hybrid model of coordinate state transition, sEMG feature extraction and gene expression programming (GEP) prediction is proposed for reconstructing drawing traces of 12 basic one-stroke shapes from multichannel surface electromyography. Using a specially designed coordinate data acquisition system, we recorded the coordinate data of drawing traces collected in accordance with the time series while 7-channel EMG signals were recorded. As a widely-used time domain feature, Root Mean Square (RMS) was extracted with the analysis window. The preliminary reconstruction models can be established by GEP. Then, the original drawing traces can be approximated by a constructed prediction model. Applying the three-step hybrid model, we were able to convert seven channels of EMG activity recorded from the arm muscles into smooth reconstructions of drawing traces. The hybrid model can yield a mean accuracy of 74% in within-group design (one set of prediction models for all shapes) and 86% in between-group design (one separate set of prediction models for each shape), averaged for the reconstructed x and y coordinates. It can be concluded that it is feasible for the proposed three-step hybrid model to improve the reconstruction ability of drawing traces from sEMG.
Hybrid Modeling and Diagnosis in the Real World: A Case Study
2002-05-04
mapped to system components case study of an aircraft fuel system, and discuss and parameters. The relations in the model are employed to methodologies for...UNCLASSIFIED Defense Technical Information Center Compilation Part Notice ADP012687 TITLE: Hybrid Modeling and Diagnosis in the Real World : A Case...Study DISTRIBUTION: Approved for public release, distribution unlimited This paper is part of the following report: TITLE: Thirteenth International
NASA Astrophysics Data System (ADS)
Geli, H. M. E.
2015-12-01
Estimates of actual crop evapotranspiration (ETa) at field scale over the growing season are required for improving agricultural water management, particularly in water limited and drought prone regions. Remote sensing data from multiple platforms such as airborne and Landsat-based sensors can be used to provide these estimates. Combining these data with surface energy balance models can provide ETa estimates at sub- field scale as well as information on vegetation stress and soil moisture conditions. However, the temporal resolution of airborne and Landsat data does not allow for a continuous ETa monitoring over the course of the growing season. This study presents the application of a hybrid ETa modeling approach developed for monitoring daily ETa and root zone available water at high spatial resolutions. The hybrid ETa modeling approach couples a thermal-based energy balance model with a water balance-based scheme using data assimilation. The two source energy balance (TSEB) model is used to estimate instantaneous ETa which can be extrapolated to daily ETa using a water balance model modified to use the reflectance-based basal crop coefficient for interpolating ETa in between airborne and/or Landsat overpass dates. Moreover, since it is a water balance model, the soil moisture profile is also estimated. The hybrid ETa approach is applied over vineyard fields in central California. High resolution airborne and Landsat imagery were used to drive the hybrid model. These images were collected during periods that represented different vine phonological stages in 2013 growing season. Estimates of daily ETa and surface energy balance fluxes will be compared with ground-based eddy covariance tower measurements. Estimates of soil moisture at multiple depths will be compared with measurements.
THYME: Toolkit for Hybrid Modeling of Electric Power Systems
Nutaro Kalyan Perumalla, James Joseph
2011-01-01
THYME is an object oriented library for building models of wide area control and communications in electric power systems. This software is designed as a module to be used with existing open source simulators for discrete event systems in general and communication systems in particular. THYME consists of a typical model for simulating electro-mechanical transients (e.g., as are used in dynamic stability studies), data handling objects to work with CDF and PTI formatted power flow data, and sample models of discrete sensors and controllers.
Hybrid modeling of microbial exopolysaccharide (EPS) production: The case of Enterobacter A47.
Marques, Rodolfo; von Stosch, Moritz; Portela, Rui M C; Torres, Cristiana A V; Antunes, Sílvia; Freitas, Filomena; Reis, Maria A M; Oliveira, Rui
2017-03-20
Enterobacter A47 is a bacterium that produces high amounts of a fucose-rich exopolysaccharide (EPS) from glycerol residue of the biodiesel industry. The fed-batch process is characterized by complex non-linear dynamics with highly viscous pseudo-plastic rheology due to the accumulation of EPS in the culture medium. In this paper, we study hybrid modeling as a methodology to increase the predictive power of models for EPS production optimization. We compare six hybrid structures that explore different levels of knowledge-based and machine-learning model components. Knowledge-based components consist of macroscopic material balances, Monod type kinetics, cardinal temperature and pH (CTP) dependency and power-law viscosity models. Unknown dependencies are set to be identified by a feedforward artificial neural network (ANN). A semiparametric identification schema is applied resorting to a data set of 13 independent fed-batch experiments. A parsimonious hybrid model was identified that describes the dynamics of the 13 experiments with the same parameterization. The final model is specific to Enterobacter A47 but can be easily extended to other microbial EPS processes.
Pope, Bernard J; Fitch, Blake G; Pitman, Michael C; Rice, John J; Reumann, Matthias
2011-10-01
Future multiscale and multiphysics models that support research into human disease, translational medical science, and treatment can utilize the power of high-performance computing (HPC) systems. We anticipate that computationally efficient multiscale models will require the use of sophisticated hybrid programming models, mixing distributed message-passing processes [e.g., the message-passing interface (MPI)] with multithreading (e.g., OpenMP, Pthreads). The objective of this study is to compare the performance of such hybrid programming models when applied to the simulation of a realistic physiological multiscale model of the heart. Our results show that the hybrid models perform favorably when compared to an implementation using only the MPI and, furthermore, that OpenMP in combination with the MPI provides a satisfactory compromise between performance and code complexity. Having the ability to use threads within MPI processes enables the sophisticated use of all processor cores for both computation and communication phases. Considering that HPC systems in 2012 will have two orders of magnitude more cores than what was used in this study, we believe that faster than real-time multiscale cardiac simulations can be achieved on these systems.
Hybrid Scheme for Modeling Local Field Potentials from Point-Neuron Networks.
Hagen, Espen; Dahmen, David; Stavrinou, Maria L; Lindén, Henrik; Tetzlaff, Tom; van Albada, Sacha J; Grün, Sonja; Diesmann, Markus; Einevoll, Gaute T
2016-12-01
With rapidly advancing multi-electrode recording technology, the local field potential (LFP) has again become a popular measure of neuronal activity in both research and clinical applications. Proper understanding of the LFP requires detailed mathematical modeling incorporating the anatomical and electrophysiological features of neurons near the recording electrode, as well as synaptic inputs from the entire network. Here we propose a hybrid modeling scheme combining efficient point-neuron network models with biophysical principles underlying LFP generation by real neurons. The LFP predictions rely on populations of network-equivalent multicompartment neuron models with layer-specific synaptic connectivity, can be used with an arbitrary number of point-neuron network populations, and allows for a full separation of simulated network dynamics and LFPs. We apply the scheme to a full-scale cortical network model for a ∼1 mm(2) patch of primary visual cortex, predict laminar LFPs for different network states, assess the relative LFP contribution from different laminar populations, and investigate effects of input correlations and neuron density on the LFP. The generic nature of the hybrid scheme and its public implementation in hybridLFPy form the basis for LFP predictions from other and larger point-neuron network models, as well as extensions of the current application with additional biological detail.
NASA Astrophysics Data System (ADS)
Ho, Kuan-Ying; Lu, I.-Hsin; Wu, Yuh-Renn
2016-03-01
A numerical model for PEDOT:PSS/SiNW hybrid solar cell has been developed and the structure has been simulated and analyzed. The limiting factor leading to low open circuit voltage (Voc) in PEDOT:PSS/SiNW hybrid solar cell is investigated. By adding a p-type silicon layer into the device to create an electric field in the silicon layer, the recombination at interface is improved and the Voc increases. The efficiency is improved to over 15% and more optimized work can be done in the future.
Plasma Simulation Using Gyrokinetic-Gyrofluid Hybrid Models
Scott Parker
2009-04-09
We are developing kinetic ion models for the simulation of extended MHD phenomena. The model they have developed uses full Lorentz force ions, and either drift-kinetic or gyro-kinetic electrons. Quasi-neutrality is assumed and the displacement current is neglected. They are also studying alpha particle driven Toroidal Alfven Eigenmodes (TAE) in the GEM gyrokinetic code [Chen 07]. The basic kinetic ion MHD model was recently reported in an invited talk given by Dan Barnes at the 2007 American Physical Society - Division of Plasma Physics (APS-DPP) and it has been published [Jones 04, Barnes 08]. The model uses an Ohm's law that includes the Hall term, pressure term and the electron inertia [Jones 04]. These results focused on the ion physics and assumed an isothermal electron closure. It is found in conventional gyrokinetic turbulence simulations that the timestep cannot be made much greater than the ion cyclotron period. However, the kinetic ion MHD model has the compressional mode, which further limits the timestep. They have developed an implicit scheme to avoid this timestep constraint. They have also added drift kinetic electrons. This model has been benchmarked linearly. Waves investigated where shear and compressional Alfven, whisterl, ion acoustic, and drift waves, including the kinetic damping rates. This work is ongoing and was first reported at the 2008 Sherwood Fusion Theory Conference [Chen 08] and they are working on a publication. They have also formulated an integrated gyrokinetic electron model, which is of interest for studying electron gradient instabilities and weak guide-field magnetic reconnection.
NASA Astrophysics Data System (ADS)
Sun, Xiaoqiang; Cai, Yingfeng; Wang, Shaohua; Liu, Yanling; Chen, Long
2016-01-01
The control problems associated with vehicle height adjustment of electronically controlled air suspension (ECAS) still pose theoretical challenges for researchers, which manifest themselves in the publications on this subject over the last years. This paper deals with modeling and control of a vehicle height adjustment system for ECAS, which is an example of a hybrid dynamical system due to the coexistence and coupling of continuous variables and discrete events. A mixed logical dynamical (MLD) modeling approach is chosen for capturing enough details of the vehicle height adjustment process. The hybrid dynamic model is constructed on the basis of some assumptions and piecewise linear approximation for components nonlinearities. Then, the on-off statuses of solenoid valves and the piecewise approximation process are described by propositional logic, and the hybrid system is transformed into the set of linear mixed-integer equalities and inequalities, denoted as MLD model, automatically by HYSDEL. Using this model, a hybrid model predictive controller (HMPC) is tuned based on online mixed-integer quadratic optimization (MIQP). Two different scenarios are considered in the simulation, whose results verify the height adjustment effectiveness of the proposed approach. Explicit solutions of the controller are computed to control the vehicle height adjustment system in realtime using an offline multi-parametric programming technology (MPT), thus convert the controller into an equivalent explicit piecewise affine form. Finally, bench experiments for vehicle height lifting, holding and lowering procedures are conducted, which demonstrate that the HMPC can adjust the vehicle height by controlling the on-off statuses of solenoid valves directly. This research proposes a new modeling and control method for vehicle height adjustment of ECAS, which leads to a closed-loop system with favorable dynamical properties.
NASA Astrophysics Data System (ADS)
Maclay, James D.; Brouwer, Jacob; Samuelsen, G. Scott
A model of a photovoltaic (PV) powered residence in stand-alone configuration was developed and evaluated. The model assesses the sizing, capital costs, control strategies, and efficiencies of reversible fuel cells (RFC), batteries, and ultra-capacitors (UC) both individually, and in combination, as hybrid energy storage devices. The choice of control strategy for a hybrid energy storage system is found to have a significant impact on system efficiency, hydrogen production and component utilization. A hybrid energy storage system comprised of batteries and RFC has the advantage of reduced cost (compared to using a RFC as the sole energy storage device), high system efficiency and hydrogen energy production capacity. A control strategy that preferentially used the RFC before the battery in meeting load demand allows both grid independent operation and better RFC utilization compared to a system that preferentially used the battery before the RFC. Ultra-capacitors coupled with a RFC in a hybrid energy storage system contain insufficient energy density to meet dynamic power demands typical of residential applications.
Qualitative Fault Isolation of Hybrid Systems: A Structural Model Decomposition-Based Approach
NASA Technical Reports Server (NTRS)
Bregon, Anibal; Daigle, Matthew; Roychoudhury, Indranil
2016-01-01
Quick and robust fault diagnosis is critical to ensuring safe operation of complex engineering systems. A large number of techniques are available to provide fault diagnosis in systems with continuous dynamics. However, many systems in aerospace and industrial environments are best represented as hybrid systems that consist of discrete behavioral modes, each with its own continuous dynamics. These hybrid dynamics make the on-line fault diagnosis task computationally more complex due to the large number of possible system modes and the existence of autonomous mode transitions. This paper presents a qualitative fault isolation framework for hybrid systems based on structural model decomposition. The fault isolation is performed by analyzing the qualitative information of the residual deviations. However, in hybrid systems this process becomes complex due to possible existence of observation delays, which can cause observed deviations to be inconsistent with the expected deviations for the current mode in the system. The great advantage of structural model decomposition is that (i) it allows to design residuals that respond to only a subset of the faults, and (ii) every time a mode change occurs, only a subset of the residuals will need to be reconfigured, thus reducing the complexity of the reasoning process for isolation purposes. To demonstrate and test the validity of our approach, we use an electric circuit simulation as the case study.
NASA Technical Reports Server (NTRS)
Baurle, R. A.
2015-01-01
Steady-state and scale-resolving simulations have been performed for flow in and around a model scramjet combustor flameholder. The cases simulated corresponded to those used to examine this flowfield experimentally using particle image velocimetry. A variety of turbulence models were used for the steady-state Reynolds-averaged simulations which included both linear and non-linear eddy viscosity models. The scale-resolving simulations used a hybrid Reynolds-averaged / large eddy simulation strategy that is designed to be a large eddy simulation everywhere except in the inner portion (log layer and below) of the boundary layer. Hence, this formulation can be regarded as a wall-modeled large eddy simulation. This effort was undertaken to formally assess the performance of the hybrid Reynolds-averaged / large eddy simulation modeling approach in a flowfield of interest to the scramjet research community. The numerical errors were quantified for both the steady-state and scale-resolving simulations prior to making any claims of predictive accuracy relative to the measurements. The steady-state Reynolds-averaged results showed a high degree of variability when comparing the predictions obtained from each turbulence model, with the non-linear eddy viscosity model (an explicit algebraic stress model) providing the most accurate prediction of the measured values. The hybrid Reynolds-averaged/large eddy simulation results were carefully scrutinized to ensure that even the coarsest grid had an acceptable level of resolution for large eddy simulation, and that the time-averaged statistics were acceptably accurate. The autocorrelation and its Fourier transform were the primary tools used for this assessment. The statistics extracted from the hybrid simulation strategy proved to be more accurate than the Reynolds-averaged results obtained using the linear eddy viscosity models. However, there was no predictive improvement noted over the results obtained from the explicit
Spatial self-organization in hybrid models of multicellular adhesion
NASA Astrophysics Data System (ADS)
Bonforti, Adriano; Duran-Nebreda, Salva; Montañez, Raúl; Solé, Ricard
2016-10-01
Spatial self-organization emerges in distributed systems exhibiting local interactions when nonlinearities and the appropriate propagation of signals are at work. These kinds of phenomena can be modeled with different frameworks, typically cellular automata or reaction-diffusion systems. A different class of dynamical processes involves the correlated movement of agents over space, which can be mediated through chemotactic movement or minimization of cell-cell interaction energy. A classic example of the latter is given by the formation of spatially segregated assemblies when cells display differential adhesion. Here, we consider a new class of dynamical models, involving cell adhesion among two stochastically exchangeable cell states as a minimal model capable of exhibiting well-defined, ordered spatial patterns. Our results suggest that a whole space of pattern-forming rules is hosted by the combination of physical differential adhesion and the value of probabilities modulating cell phenotypic switching, showing that Turing-like patterns can be obtained without resorting to reaction-diffusion processes. If the model is expanded allowing cells to proliferate and die in an environment where diffusible nutrient and toxic waste are at play, different phases are observed, characterized by regularly spaced patterns. The analysis of the parameter space reveals that certain phases reach higher population levels than other modes of organization. A detailed exploration of the mean-field theory is also presented. Finally, we let populations of cells with different adhesion matrices compete for reproduction, showing that, in our model, structural organization can improve the fitness of a given cell population. The implications of these results for ecological and evolutionary models of pattern formation and the emergence of multicellularity are outlined.
Spatial self-organization in hybrid models of multicellular adhesion.
Bonforti, Adriano; Duran-Nebreda, Salva; Montañez, Raúl; Solé, Ricard
2016-10-01
Spatial self-organization emerges in distributed systems exhibiting local interactions when nonlinearities and the appropriate propagation of signals are at work. These kinds of phenomena can be modeled with different frameworks, typically cellular automata or reaction-diffusion systems. A different class of dynamical processes involves the correlated movement of agents over space, which can be mediated through chemotactic movement or minimization of cell-cell interaction energy. A classic example of the latter is given by the formation of spatially segregated assemblies when cells display differential adhesion. Here, we consider a new class of dynamical models, involving cell adhesion among two stochastically exchangeable cell states as a minimal model capable of exhibiting well-defined, ordered spatial patterns. Our results suggest that a whole space of pattern-forming rules is hosted by the combination of physical differential adhesion and the value of probabilities modulating cell phenotypic switching, showing that Turing-like patterns can be obtained without resorting to reaction-diffusion processes. If the model is expanded allowing cells to proliferate and die in an environment where diffusible nutrient and toxic waste are at play, different phases are observed, characterized by regularly spaced patterns. The analysis of the parameter space reveals that certain phases reach higher population levels than other modes of organization. A detailed exploration of the mean-field theory is also presented. Finally, we let populations of cells with different adhesion matrices compete for reproduction, showing that, in our model, structural organization can improve the fitness of a given cell population. The implications of these results for ecological and evolutionary models of pattern formation and the emergence of multicellularity are outlined.
Online motor fault detection and diagnosis using a hybrid FMM-CART model.
Seera, Manjeevan; Lim, Chee Peng
2014-04-01
In this brief, a hybrid model combining the fuzzy min-max (FMM) neural network and the classification and regression tree (CART) for online motor detection and diagnosis tasks is described. The hybrid model, known as FMM-CART, exploits the advantages of both FMM and CART for undertaking data classification and rule extraction problems. To evaluate the applicability of the proposed FMM-CART model, an evaluation with a benchmark data set pertaining to electrical motor bearing faults is first conducted. The results obtained are equivalent to those reported in the literature. Then, a laboratory experiment for detecting and diagnosing eccentricity faults in an induction motor is performed. In addition to producing accurate results, useful rules in the form of a decision tree are extracted to provide explanation and justification for the predictions from FMM-CART. The experimental outcome positively shows the potential of FMM-CART in undertaking online motor fault detection and diagnosis tasks.
Model-Invariant Hybrid Computations of Separated Flows for RCA Standard Test Cases
NASA Technical Reports Server (NTRS)
Woodruff, Stephen
2016-01-01
NASA's Revolutionary Computational Aerosciences (RCA) subproject has identified several smooth-body separated flows as standard test cases to emphasize the challenge these flows present for computational methods and their importance to the aerospace community. Results of computations of two of these test cases, the NASA hump and the FAITH experiment, are presented. The computations were performed with the model-invariant hybrid LES-RANS formulation, implemented in the NASA code VULCAN-CFD. The model- invariant formulation employs gradual LES-RANS transitions and compensation for model variation to provide more accurate and efficient hybrid computations. Comparisons revealed that the LES-RANS transitions employed in these computations were sufficiently gradual that the compensating terms were unnecessary. Agreement with experiment was achieved only after reducing the turbulent viscosity to mitigate the effect of numerical dissipation. The stream-wise evolution of peak Reynolds shear stress was employed as a measure of turbulence dynamics in separated flows useful for evaluating computations.
Modelling Nonlinear Dynamic Textures using Hybrid DWT-DCT and Kernel PCA with GPU
NASA Astrophysics Data System (ADS)
Ghadekar, Premanand Pralhad; Chopade, Nilkanth Bhikaji
2016-12-01
Most of the real-world dynamic textures are nonlinear, non-stationary, and irregular. Nonlinear motion also has some repetition of motion, but it exhibits high variation, stochasticity, and randomness. Hybrid DWT-DCT and Kernel Principal Component Analysis (KPCA) with YCbCr/YIQ colour coding using the Dynamic Texture Unit (DTU) approach is proposed to model a nonlinear dynamic texture, which provides better results than state-of-art methods in terms of PSNR, compression ratio, model coefficients, and model size. Dynamic texture is decomposed into DTUs as they help to extract temporal self-similarity. Hybrid DWT-DCT is used to extract spatial redundancy. YCbCr/YIQ colour encoding is performed to capture chromatic correlation. KPCA is applied to capture nonlinear motion. Further, the proposed algorithm is implemented on Graphics Processing Unit (GPU), which comprise of hundreds of small processors to decrease time complexity and to achieve parallelism.
Daily reservoir inflow forecasting using multiscale deep feature learning with hybrid models
NASA Astrophysics Data System (ADS)
Bai, Yun; Chen, Zhiqiang; Xie, Jingjing; Li, Chuan
2016-01-01
Inflow forecasting applies data supports for the operations and managements of reservoirs. A multiscale deep feature learning (MDFL) method with hybrid models is proposed in this paper to deal with the daily reservoir inflow forecasting. Ensemble empirical mode decomposition and Fourier spectrum are first employed to extract multiscale (trend, period and random) features, which are then represented by three deep belief networks (DBNs), respectively. The weights of each DBN are subsequently applied to initialize a neural network (D-NN). The outputs of the three-scale D-NNs are finally reconstructed using a sum-up strategy toward the forecasting results. A historical daily inflow series (from 1/1/2000 to 31/12/2012) of the Three Gorges reservoir, China, is investigated by the proposed MDFL with hybrid models. For comparison, four peer models are adopted for the same task. The results show that, the present model overwhelms all the peer models in terms of mean absolute percentage error (MAPE = 11.2896%), normalized root-mean-square error (NRMSE = 0.2292), determination coefficient criteria (R2 = 0.8905), and peak percent threshold statistics (PPTS(5) = 10.0229%). The addressed method integrates the deep framework with multiscale and hybrid observations, and therefore being good at exploring sophisticated natures in the reservoir inflow forecasting.
Multiscale Modeling of Graphite/CNT/Epoxy Hybrid Composites
2016-03-09
A - Approved for Public Release 13. SUPPLEMENTARY NOTES 14. ABSTRACT Incorporation of carbon nanotubes (CNTs) into epoxy-based composites for...materials with higher moduli and strength characteristics. 15. SUBJECT TERMS Molecular Dynamics, Carbon Nanotubes , Multi-scale Modeling, Micromechanics...Gregory M. Odegard Michigan Technological University Introduction This project was inspired from the AFOSR-sponsored workshop “ Nanotube
Using a hybrid genetic algorithm and fuzzy logic for metabolic modeling
Yen, J.; Lee, B.; Liao, J.C.
1996-12-31
The identification of metabolic systems is a complex task due to the complexity of the system and limited knowledge about the model. Mathematical equations and ODE`s have been used to capture the structure of the model, and the conventional optimization techniques have been used to identify the parameters of the model. In general, however, a pure mathematical formulation of the model is difficult due to parametric uncertainty and incomplete knowledge of mechanisms. In this paper, we propose a modeling approach that (1) uses fuzzy rule-based model to augment algebraic enzyme models that are incomplete, and (2) uses a hybrid genetic algorithm to identify uncertain parameters in the model. The hybrid genetic algorithm (GA) integrates a GA with the simplex method in functional optimization to improve the GA`s convergence rate. We have applied this approach to modeling the rate of three enzyme reactions in E. coli central metabolism. The proposed modeling strategy allows (1) easy incorporation of qualitative insights into a pure mathematical model and (2) adaptive identification and optimization of key parameters to fit system behaviors observed in biochemical experiments.
Real time hybrid simulation with online model updating: An analysis of accuracy
NASA Astrophysics Data System (ADS)
Ou, Ge; Dyke, Shirley J.; Prakash, Arun
2017-02-01
In conventional hybrid simulation (HS) and real time hybrid simulation (RTHS) applications, the information exchanged between the experimental substructure and numerical substructure is typically restricted to the interface boundary conditions (force, displacement, acceleration, etc.). With additional demands being placed on RTHS and recent advances in recursive system identification techniques, an opportunity arises to improve the fidelity by extracting information from the experimental substructure. Online model updating algorithms enable the numerical model of components (herein named the target model), that are similar to the physical specimen to be modified accordingly. This manuscript demonstrates the power of integrating a model updating algorithm into RTHS (RTHSMU) and explores the possible challenges of this approach through a practical simulation. Two Bouc-Wen models with varying levels of complexity are used as target models to validate the concept and evaluate the performance of this approach. The constrained unscented Kalman filter (CUKF) is selected for using in the model updating algorithm. The accuracy of RTHSMU is evaluated through an estimation output error indicator, a model updating output error indicator, and a system identification error indicator. The results illustrate that, under applicable constraints, by integrating model updating into RTHS, the global response accuracy can be improved when the target model is unknown. A discussion on model updating parameter sensitivity to updating accuracy is also presented to provide guidance for potential users.
ERIC Educational Resources Information Center
Delialioglu, Omer; Yildirim, Zahide
2008-01-01
Using the model for learning and teaching activities (MOLTA), a new technology enhanced hybrid instruction was designed, developed and implemented. The effectiveness of the hybrid instruction in regard to students' achievement, knowledge retention, attitudes towards the subject, and course satisfaction was evaluated in comparison to traditional…
NASA Astrophysics Data System (ADS)
Mantovanelli, Ivana C. C.; Rivera, Elmer Ccopa; da Costa, Aline C.; Filho, Rubens Maciel
In this work a procedure for the development of a robust mathematical model for an industrial alcoholic fermentation process was evaluated. The proposed model is a hybrid neural model, which combines mass and energy balance equations with functional link networks to describe the kinetics. These networks have been shown to have a good nonlinear approximation capability, although the estimation of its weights is linear. The proposed model considers the effect of temperature on the kinetics and has the neural network weights reestimated always so that a change in operational conditions occurs. This allow to follow the system behavior when changes in operating conditions occur.
Neutrino masses, leptogenesis, and dark matter in a hybrid seesaw model
Gu Peihong; Hirsch, M.; Valle, J. W. F.
2009-02-01
We suggest a hybrid seesaw model where relatively light right-handed neutrinos give no contribution to neutrino mass matrix due to a special symmetry. This allows their Yukawa couplings to the standard model particles to be relatively strong, so that the standard model Higgs boson can decay dominantly to a left- and a right-handed neutrino, leaving another stable right-handed neutrino as cold dark matter. In our model neutrino masses arise via the type-II seesaw mechanism, the Higgs triplet scalars being also responsible for the generation of the matter-antimatter asymmetry via the leptogenesis mechanism.
Dynamical analysis of Parkinsonian state emulated by hybrid Izhikevich neuron models
NASA Astrophysics Data System (ADS)
Liu, Chen; Wang, Jiang; Yu, Haitao; Deng, Bin; Wei, Xile; Li, Huiyan; Loparo, Kenneth A.; Fietkiewicz, Chris
2015-11-01
Computational models play a significant role in exploring novel theories to complement the findings of physiological experiments. Various computational models have been developed to reveal the mechanisms underlying brain functions. Particularly, in the development of therapies to modulate behavioral and pathological abnormalities, computational models provide the basic foundations to exhibit transitions between physiological and pathological conditions. Considering the significant roles of the intrinsic properties of the globus pallidus and the coupling connections between neurons in determining the firing patterns and the dynamical activities of the basal ganglia neuronal network, we propose a hypothesis that pathological behaviors under the Parkinsonian state may originate from combined effects of intrinsic properties of globus pallidus neurons and synaptic conductances in the whole neuronal network. In order to establish a computational efficient network model, hybrid Izhikevich neuron model is used due to its capacity of capturing the dynamical characteristics of the biological neuronal activities. Detailed analysis of the individual Izhikevich neuron model can assist in understanding the roles of model parameters, which then facilitates the establishment of the basal ganglia-thalamic network model, and contributes to a further exploration of the underlying mechanisms of the Parkinsonian state. Simulation results show that the hybrid Izhikevich neuron model is capable of capturing many of the dynamical properties of the basal ganglia-thalamic neuronal network, such as variations of the firing rates and emergence of synchronous oscillations under the Parkinsonian condition, despite the simplicity of the two-dimensional neuronal model. It may suggest that the computational efficient hybrid Izhikevich neuron model can be used to explore basal ganglia normal and abnormal functions. Especially it provides an efficient way of emulating the large-scale neuron network
An Advanced Hierarchical Hybrid Environment for Reliability and Performance Modeling
NASA Technical Reports Server (NTRS)
Ciardo, Gianfranco
2003-01-01
The key issue we intended to address in our proposed research project was the ability to model and study logical and probabilistic aspects of large computer systems. In particular, we wanted to focus mostly on automatic solution algorithms based on a state-space exploration as their first step, in addition to the more traditional discrete-event simulation approaches commonly employed in industry. One explicitly-stated goal was to extend by several orders of magnitude the size of models that can be solved exactly, using a combination of techniques: 1) Efficient exploration and storage of the state space using new data structures that require an amount of memory sublinear in the number states; and 2) Exploitation of the existing symmetries in the matrices describing the system behavior using Kronecker operators. Not only we have been successful in achieving the above goals, but we exceeded them in many respects.
Modeling and Density Estimation of an Urban Freeway Network Based on Dynamic Graph Hybrid Automata.
Chen, Yangzhou; Guo, Yuqi; Wang, Ying
2017-03-29
In this paper, in order to describe complex network systems, we firstly propose a general modeling framework by combining a dynamic graph with hybrid automata and thus name it Dynamic Graph Hybrid Automata (DGHA). Then we apply this framework to model traffic flow over an urban freeway network by embedding the Cell Transmission Model (CTM) into the DGHA. With a modeling procedure, we adopt a dual digraph of road network structure to describe the road topology, use linear hybrid automata to describe multi-modes of dynamic densities in road segments and transform the nonlinear expressions of the transmitted traffic flow between two road segments into piecewise linear functions in terms of multi-mode switchings. This modeling procedure is modularized and rule-based, and thus is easily-extensible with the help of a combination algorithm for the dynamics of traffic flow. It can describe the dynamics of traffic flow over an urban freeway network with arbitrary topology structures and sizes. Next we analyze mode types and number in the model of the whole freeway network, and deduce a Piecewise Affine Linear System (PWALS) model. Furthermore, based on the PWALS model, a multi-mode switched state observer is designed to estimate the traffic densities of the freeway network, where a set of observer gain matrices are computed by using the Lyapunov function approach. As an example, we utilize the PWALS model and the corresponding switched state observer to traffic flow over Beijing third ring road. In order to clearly interpret the principle of the proposed method and avoid computational complexity, we adopt a simplified version of Beijing third ring road. Practical application for a large-scale road network will be implemented by decentralized modeling approach and distributed observer designing in the future research.
A Hybrid Latent Class Analysis Modeling Approach to Analyze Urban Expressway Crash Risk.
Yu, Rongjie; Wang, Xuesong; Abdel-Aty, Mohamed
2017-04-01
Crash risk analysis is rising as a hot research topic as it could reveal the relationships between traffic flow characteristics and crash occurrence risk, which is beneficial to understand crash mechanisms which would further refine the design of Active Traffic Management System (ATMS). However, the majority of the current crash risk analysis studies have ignored the impact of geometric characteristics on crash risk estimation while recent studies proved that crash occurrence risk was affected by the various alignment features. In this study, a hybrid Latent Class Analysis (LCA) modeling approach was proposed to account for the heterogeneous effects of geometric characteristics. Crashes were first segmented into homogenous subgroups, where the optimal number of latent classes was identified based on bootstrap likelihood ratio tests. Then, separate crash risk analysis models were developed using Bayesian random parameter logistic regression technique; data from Shanghai urban expressway system were employed to conduct the empirical study. Different crash risk contributing factors were unveiled by the hybrid LCA approach and better model goodness-of-fit was obtained while comparing to an overall total crash model. Finally, benefits of the proposed hybrid LCA approach were discussed.
Models to estimate the minimum ignition temperature of dusts and hybrid mixtures.
Addai, Emmanuel Kwasi; Gabel, Dieter; Krause, Ulrich
2016-03-05
The minimum ignition temperatures (MIT) of hybrid mixtures have been investigated by performing several series of tests in a modified Godbert-Greenwald furnace. Five dusts as well as three perfect gases and three real were used in different combinations as test samples. Further, seven mathematical models for prediction of the MIT of dust/air mixtures were presented of which three were chosen for deeper study and comparison with the experimental results based on the availability of the input quantities needed and their applicability. Additionally, two alternative models were proposed to calculate the MIT of hybrid mixtures and were validated against the experimental results. A significant decrease of the minimum ignition temperature of either the gas or the vapor as well as an increase in the explosion likelihood could be observed when a small amount of dust which was either below its minimum explosible concentration or not ignitable itself at that particular temperature was mixed with the gas. The various models developed by Cassel, Krishma and Mitsui to predict the MIT of dust were in good agreement with the experimental results as well as the two models proposed to predict the MIT of hybrid mixtures were also in agreement with the experimental value.
A Hybrid Causal Search Algorithm for Latent Variable Models
Ogarrio, Juan Miguel; Spirtes, Peter; Ramsey, Joe
2017-01-01
Existing score-based causal model search algorithms such as GES (and a speeded up version, FGS) are asymptotically correct, fast, and reliable, but make the unrealistic assumption that the true causal graph does not contain any unmeasured confounders. There are several constraint-based causal search algorithms (e.g RFCI, FCI, or FCI+) that are asymptotically correct without assuming that there are no unmeasured confounders, but often perform poorly on small samples. We describe a combined score and constraint-based algorithm, GFCI, that we prove is asymptotically correct. On synthetic data, GFCI is only slightly slower than RFCI but more accurate than FCI, RFCI and FCI+. PMID:28239434
Hybrid fluid/kinetic model for parallel heat conduction
Callen, J.D.; Hegna, C.C.; Held, E.D.
1998-12-31
It is argued that in order to use fluid-like equations to model low frequency ({omega} < {nu}) phenomena such as neoclassical tearing modes in low collisionality ({nu} < {omega}{sub b}) tokamak plasmas, a Chapman-Enskog-like approach is most appropriate for developing an equation for the kinetic distortion (F) of the distribution function whose velocity-space moments lead to the needed fluid moment closure relations. Further, parallel heat conduction in a long collision mean free path regime can be described through a combination of a reduced phase space Chapman-Enskog-like approach for the kinetics and a multiple-time-scale analysis for the fluid and kinetic equations.
NASA Astrophysics Data System (ADS)
Jian, Weilin; He, Daohang; Song, Shaoyun
2016-08-01
Natural stilbenes (especially resveratrol) play important roles in plant protection by acting as both constitutive and inducible defenses. However, their exogenous applications on crops as fungicidal agents are challenged by their oxidative degradation and limited availability. In this study, a new class of resveratrol-inspired oxadiazole-stilbene hybrids was synthesized via Wittig-Horner reaction. Bioassay results indicated that some of the compounds exhibited potent fungicidal activity against Botrytis cinerea in vitro. Among these stilbene hybrids, compounds 11 showed promising inhibitory activity with the EC50 value of 144.6 μg/mL, which was superior to that of resveratrol (315.6 μg/mL). Remarkably, the considerably abnormal mycelial morphology was observed in the presence of compound 11. The inhibitory profile was further proposed by homology modeling and molecular docking studies, which showed the possible interaction of resveratrol and oxadiazole-stilbene hybrids with the cytochrome P450-dependent sterol 14α-demethylase from B. cinerea (BcCYP51) for the first time. Taken together, these results would provide new insights into the fungicidal mechanism of stilbenes, as well as an important clue for biology-oriented synthesis of stilbene hybrids with improved bioactivity against plant pathogenic fungi in crop protection.
Extensive heterosis in growth of yeast hybrids is explained by a combination of genetic models.
Shapira, R; Levy, T; Shaked, S; Fridman, E; David, L
2014-10-01
Heterosis, also known as hybrid vigor, is the superior performance of a heterozygous hybrid relative to its homozygous parents. Despite the scientific curiosity of this phenotypic phenomenon and its significance for food production in agriculture, its genetic basis is insufficiently understood. Studying heterosis in yeast can potentially yield insights into its genetic basis, can allow one to test the different hypotheses that have been proposed to explain the phenomenon and allows better understanding of how to take advantage of this phenomenon to enhance food production. We therefore crossed 16 parental yeast strains to form 120 yeast hybrids, and measured their growth rates under five environmental conditions. A considerable amount of dominant genetic variation was found in growth performance, and heterosis was measured in 35% of the hybrid-condition combinations. Despite previous reports of correlations between heterosis and measures of sequence divergence between parents, we detected no such relationship. We used several analyses to examine which genetic model might explain heterosis. We found that dominance complementation of recessive alleles, overdominant interactions within loci and epistatic interactions among loci each contribute to heterosis. We concluded that in yeast heterosis is a complex phenotype created by the combined contribution of different genetic interactions.
Jian, Weilin; He, Daohang; Song, Shaoyun
2016-01-01
Natural stilbenes (especially resveratrol) play important roles in plant protection by acting as both constitutive and inducible defenses. However, their exogenous applications on crops as fungicidal agents are challenged by their oxidative degradation and limited availability. In this study, a new class of resveratrol-inspired oxadiazole-stilbene hybrids was synthesized via Wittig-Horner reaction. Bioassay results indicated that some of the compounds exhibited potent fungicidal activity against Botrytis cinerea in vitro. Among these stilbene hybrids, compounds 11 showed promising inhibitory activity with the EC50 value of 144.6 μg/mL, which was superior to that of resveratrol (315.6 μg/mL). Remarkably, the considerably abnormal mycelial morphology was observed in the presence of compound 11. The inhibitory profile was further proposed by homology modeling and molecular docking studies, which showed the possible interaction of resveratrol and oxadiazole-stilbene hybrids with the cytochrome P450-dependent sterol 14α-demethylase from B. cinerea (BcCYP51) for the first time. Taken together, these results would provide new insights into the fungicidal mechanism of stilbenes, as well as an important clue for biology-oriented synthesis of stilbene hybrids with improved bioactivity against plant pathogenic fungi in crop protection. PMID:27530962
An advanced environment for hybrid modeling of biological systems based on modelica.
Pross, Sabrina; Bachmann, Bernhard
2011-01-20
Biological systems are often very complex so that an appropriate formalism is needed for modeling their behavior. Hybrid Petri Nets, consisting of time-discrete Petri Net elements as well as continuous ones, have proven to be ideal for this task. Therefore, a new Petri Net library was implemented based on the object-oriented modeling language Modelica which allows the modeling of discrete, stochastic and continuous Petri Net elements by differential, algebraic and discrete equations. An appropriate Modelica-tool performs the hybrid simulation with discrete events and the solution of continuous differential equations. A special sub-library contains so-called wrappers for specific reactions to simplify the modeling process. The Modelica-models can be connected to Simulink-models for parameter optimization, sensitivity analysis and stochastic simulation in Matlab. The present paper illustrates the implementation of the Petri Net component models, their usage within the modeling process and the coupling between the Modelica-tool Dymola and Matlab/Simulink. The application is demonstrated by modeling the metabolism of Chinese Hamster Ovary Cells.
Li, Bing Keong; Liu, Feng; Weber, Ewald; Padhi, Shantanu; Crozier, Stuart
2007-01-01
In this work, an improved hybrid MoM/FDTD algorithm for modeling low to ultra high field MRI RF coil/sample interactions has been proposed. In our previous hybrid MoM/FDTD method, the accuracy of modeling MRI RF coils is generally hindered by two major issues, staircasing errors and rough approximation of the coil current distortions by electromagnetic reflections from sample. In view of this, a Huygen's equivalent surface method has been proposed to effectively bridge MoM and FDTD. In the improved hybrid MoM/FDTD algorithm, staircasing errors are eliminated, and most importantly the complex coil/tissue interactions are explicitly accounted for. The accuracy of the improved hybrid MoM/FDTD method is numerically verified with a well established hybrid Green function/MoM solution and also experimentally underpinned with MR images obtained using a prototype rotary phased array head coil.
Hybrid method for numerical modelling of LWR coolant chemistry
NASA Astrophysics Data System (ADS)
Swiatla-Wojcik, Dorota
2016-10-01
A comprehensive approach is proposed to model radiation chemistry of the cooling water under exposure to neutron and gamma radiation at 300 °C. It covers diffusion-kinetic processes in radiation tracks and secondary reactions in the bulk coolant. Steady-state concentrations of the radiolytic products have been assessed based on the simulated time dependent concentration profiles. The principal reactions contributing to the formation of H2, O2 and H2O2 were indicated. Simulation was carried out depending on the amount of extra hydrogen dissolved in the coolant to reduce concentration of corrosive agents. High sensitivity to the rate of reaction H+H2O=OH+H2 is shown and discussed.
Fernandez-Lozano, C; Canto, C; Gestal, M; Andrade-Garda, J M; Rabuñal, J R; Dorado, J; Pazos, A
2013-01-01
Given the background of the use of Neural Networks in problems of apple juice classification, this paper aim at implementing a newly developed method in the field of machine learning: the Support Vector Machines (SVM). Therefore, a hybrid model that combines genetic algorithms and support vector machines is suggested in such a way that, when using SVM as a fitness function of the Genetic Algorithm (GA), the most representative variables for a specific classification problem can be selected.
Fernandez-Lozano, C.; Canto, C.; Gestal, M.; Andrade-Garda, J. M.; Rabuñal, J. R.; Dorado, J.; Pazos, A.
2013-01-01
Given the background of the use of Neural Networks in problems of apple juice classification, this paper aim at implementing a newly developed method in the field of machine learning: the Support Vector Machines (SVM). Therefore, a hybrid model that combines genetic algorithms and support vector machines is suggested in such a way that, when using SVM as a fitness function of the Genetic Algorithm (GA), the most representative variables for a specific classification problem can be selected. PMID:24453933
A hybrid programming model for compressible gas dynamics using openCL
Bergen, Benjamin Karl; Daniels, Marcus G; Weber, Paul M
2010-01-01
The current trend towards multicore/manycore and accelerated architectures presents challenges, both in portability, and also in the choices that developers must make on how to use the resources that these architectures provide. This paper explores some of the possibilities that are enabled by the Open Computing Language (OpenCL), and proposes a programming model that allows developers and scientists to more fully subscribe hybrid compute nodes, while, at the same time, reducing the impact of system failure.
Value-Driven Design and Sensitivity Analysis of Hybrid Energy Systems using Surrogate Modeling
Wenbo Du; Humberto E. Garcia; William R. Binder; Christiaan J. J. Paredis
2001-10-01
A surrogate modeling and analysis methodology is applied to study dynamic hybrid energy systems (HES). The effect of battery size on the smoothing of variability in renewable energy generation is investigated. Global sensitivity indices calculated using surrogate models show the relative sensitivity of system variability to dynamic properties of key components. A value maximization approach is used to consider the tradeoff between system variability and required battery size. Results are found to be highly sensitive to the renewable power profile considered, demonstrating the importance of accurate renewable resource modeling and prediction. The documented computational framework and preliminary results represent an important step towards a comprehensive methodology for HES evaluation, design, and optimization.
Modeling and Analysis of Asynchronous Systems Using SAL and Hybrid SAL
NASA Technical Reports Server (NTRS)
Tiwari, Ashish; Dutertre, Bruno
2013-01-01
We present formal models and results of formal analysis of two different asynchronous systems. We first examine a mid-value select module that merges the signals coming from three different sensors that are each asynchronously sampling the same input signal. We then consider the phase locking protocol proposed by Daly, Hopkins, and McKenna. This protocol is designed to keep a set of non-faulty (asynchronous) clocks phase locked even in the presence of Byzantine-faulty clocks on the network. All models and verifications have been developed using the SAL model checking tools and the Hybrid SAL abstractor.
An Approach of Bio-inspired Hybrid Model for Financial Markets
NASA Astrophysics Data System (ADS)
Simić, Dragan; Gajić, Vladeta; Simić, Svetlana
Biological systems are inspiration for the design of optimisation and classification models. Applying various forms of bio-inspired algorithms may be a very high-complex system. Modelling of financial markets is challenging for several reasons, because many plausible factors impact on it. An automated trading on financial market is not a new phenomenon. The model of bio-inspired hybrid adaptive trading system based on technical indicators usage by grammatical evolution and moving window is presented in this paper. The proposed system is just one of possible bio-inspired system which can be used in financial forecast, corporate failure prediction or bond rating company.
1D-3D hybrid modeling-from multi-compartment models to full resolution models in space and time.
Grein, Stephan; Stepniewski, Martin; Reiter, Sebastian; Knodel, Markus M; Queisser, Gillian
2014-01-01
Investigation of cellular and network dynamics in the brain by means of modeling and simulation has evolved into a highly interdisciplinary field, that uses sophisticated modeling and simulation approaches to understand distinct areas of brain function. Depending on the underlying complexity, these models vary in their level of detail, in order to cope with the attached computational cost. Hence for large network simulations, single neurons are typically reduced to time-dependent signal processors, dismissing the spatial aspect of each cell. For single cell or networks with relatively small numbers of neurons, general purpose simulators allow for space and time-dependent simulations of electrical signal processing, based on the cable equation theory. An emerging field in Computational Neuroscience encompasses a new level of detail by incorporating the full three-dimensional morphology of cells and organelles into three-dimensional, space and time-dependent, simulations. While every approach has its advantages and limitations, such as computational cost, integrated and methods-spanning simulation approaches, depending on the network size could establish new ways to investigate the brain. In this paper we present a hybrid simulation approach, that makes use of reduced 1D-models using e.g., the NEURON simulator-which couples to fully resolved models for simulating cellular and sub-cellular dynamics, including the detailed three-dimensional morphology of neurons and organelles. In order to couple 1D- and 3D-simulations, we present a geometry-, membrane potential- and intracellular concentration mapping framework, with which graph- based morphologies, e.g., in the swc- or hoc-format, are mapped to full surface and volume representations of the neuron and computational data from 1D-simulations can be used as boundary conditions for full 3D simulations and vice versa. Thus, established models and data, based on general purpose 1D-simulators, can be directly coupled to the
Analysis of the PEDOT:PSS/Si nanowire hybrid solar cell with a tail state model
NASA Astrophysics Data System (ADS)
Ho, Kuan-Ying; Li, Chi-Kang; Syu, Hong-Jhang; Lai, Yi; Lin, Ching-Fuh; Wu, Yuh-Renn
2016-12-01
In this paper, the electrical properties of the poly(3,4-ethylenedioxythiophene): poly(styrenesulfonate) (PEDOT:PSS)/silicon nanowire hybrid solar cell have been analyzed and an optimized structure is proposed. In addition, the planar PEDOT:PSS/c-Si hybrid solar cell is also modeled for comparison. We first developed a simulation software which is capable of modeling organic/inorganic hybrid solar cells by including Gaussian shape density of states into Poisson and drift-diffusion solver to present the tail states and trap states in the organic material. Therefore, the model can handle carrier transport, generation, and recombination in both organic and inorganic materials. Our results show that at the applied voltage near open-circuit voltage (Voc), the recombination rate becomes much higher at the PEDOT:PSS/Si interface region, which limits the fill factor and Voc. Hence, a modified structure with a p-type amorphous silicon (a-Si) layer attached on the interface of Si layer and an n+-type Si layer inserted near the bottom contact are proposed. The highest conversion efficiency of 16.10% can be achieved if both structures are applied.
Fontenete, Sílvia; Guimarães, Nuno; Wengel, Jesper; Azevedo, Nuno Filipe
2016-01-01
The thermodynamics and kinetics of DNA hybridization, i.e. the process of self-assembly of one, two or more complementary nucleic acid strands, has been studied for many years. The appearance of the nearest-neighbor model led to several theoretical and experimental papers on DNA thermodynamics that provide reasonably accurate thermodynamic information on nucleic acid duplexes and allow estimation of the melting temperature. Because there are no thermodynamic models specifically developed to predict the hybridization temperature of a probe used in a fluorescence in situ hybridization (FISH) procedure, the melting temperature is used as a reference, together with corrections for certain compounds that are used during FISH. However, the quantitative relation between melting and experimental FISH temperatures is poorly described. In this review, various models used to predict the melting temperature for rRNA targets, for DNA oligonucleotides and for nucleic acid mimics (chemically modified oligonucleotides), will be addressed in detail, together with a critical assessment of how this information should be used in FISH.
Advanced 3D electromagnetic and particle-in-cell modeling on structured/unstructured hybrid grids
Seidel, D.B.; Pasik, M.F.; Kiefer, M.L.; Riley, D.J.; Turner, C.D.
1998-01-01
New techniques have been recently developed that allow unstructured, free meshes to be embedded into standard 3-dimensional, rectilinear, finite-difference time-domain grids. The resulting hybrid-grid modeling capability allows the higher resolution and fidelity of modeling afforded by free meshes to be combined with the simplicity and efficiency of rectilinear techniques. Integration of these new methods into the full-featured, general-purpose QUICKSILVER electromagnetic, Particle-In-Cell (PIC) code provides new modeling capability for a wide variety of electromagnetic and plasma physics problems. To completely exploit the integration of this technology into QUICKSILVER for applications requiring the self-consistent treatment of charged particles, this project has extended existing PIC methods for operation on these hybrid unstructured/rectilinear meshes. Several technical issues had to be addressed in order to accomplish this goal, including the location of particles on the unstructured mesh, adequate conservation of charge, and the proper handling of particles in the transition region between structured and unstructured portions of the hybrid grid.
Hybrid Structural Model of the Complete Human ESCRT-0 Complex
Ren, Xuefeng; Kloer, Daniel P.; Kim, Young C.; Ghirlando, Rodolfo; Saidi, Layla F.; Hummer, Gerhard; Hurley, James H.
2009-03-31
The human Hrs and STAM proteins comprise the ESCRT-0 complex, which sorts ubiquitinated cell surface receptors to lysosomes for degradation. Here we report a model for the complete ESCRT-0 complex based on the crystal structure of the Hrs-STAM core complex, previously solved domain structures, hydrodynamic measurements, and Monte Carlo simulations. ESCRT-0 expressed in insect cells has a hydrodynamic radius of R{sub H} = 7.9 nm and is a 1:1 heterodimer. The 2.3 {angstrom} crystal structure of the ESCRT-0 core complex reveals two domain-swapped GAT domains and an antiparallel two-stranded coiled-coil, similar to yeast ESCRT-0. ESCRT-0 typifies a class of biomolecular assemblies that combine structured and unstructured elements, and have dynamic and open conformations to ensure versatility in target recognition. Coarse-grained Monte Carlo simulations constrained by experimental R{sub H} values for ESCRT-0 reveal a dynamic ensemble of conformations well suited for diverse functions.
Inferring methane fluxes at a larch forest using Lagrangian, Eulerian, and hybrid inverse models
NASA Astrophysics Data System (ADS)
Ueyama, Masahito; Takanashi, Satoru; Takahashi, Yoshiyuki
2014-10-01
Measuring methane (CH4) flux at upland forests is challenging due to high levels of heterogeneity in upscaling chamber measurements and the detection limits of currently available micrometeorological methods. We estimated CH4 fluxes in an upland forest from vertical concentration profiles using three different inverse multilayer models: the Lagrangian localized near field theory, Eulerian, and hybrid Lagrangian-Eulerian models. The approach could estimate spatially representative fluxes, and use of higher gradients within canopies than above them could minimize uncertainties associated with sensor noises. Comparing fluxes by the models and measurements by the micrometeorological hyperbolic relaxed eddy accumulation and chamber methods, daytime fluxes were reasonably reproduced, but nighttime fluxes were overestimated most likely due to an underestimation of stable conditions and storage effects. The models and measurements show that the forest acted as a CH4 sink during the study period, and the soil acted as the dominant sink. The estimated sink increased with increasing soil temperatures and decreasing soil water content. The CH4 sink estimated during the study period were 1.5 ± 0.2 nmol m-2 s-1 by the micrometeorological method, 2.4 ± 0.5 nmol m-2 s-1 by chambers, 2.8 ± 1.1 nmol m-2 s-1 by the Lagrangian model, 2.7 ± 1.0 nmol m-2 s-1 by the Eulerian model, and 3.7 ± 2.8 nmol m-2 s-1 by the hybrid model. The performance of the Lagrangian and hybrid models increased when the CH4 sink/source was assumed to only exist in the soil.
Effects of Na+ and He+ pickup ions on the lunar plasma environment: 3D hybrid modeling
NASA Astrophysics Data System (ADS)
Lipatov, A. S.; Cooper, J. F.; Sittler, E. C.; Hartle, R. E.; Sarantos, M.
2011-12-01
The hybrid kinetic model used here supports comprehensive simulation of the interaction between different spatial and energetic elements of the moon-solar wind-magnetosphere of the Earth system. There is a set of MHD,kinetic, hybrid, drift kinetic, electrostatic and full kinetic modeling of the lunar plasma environment [1]. However, observations show the existence of several species of the neutrals and pickup ions like Na, He, K, O etc., (see e.g., [2,3,4]). The solar wind parameters are chosen from the ARTEMIS observations [5]. The Na+, He+ lunar exosphere's parameters are chosen from [6,7]. The hybrid kinetic model allows us to take into account the finite gyroradius effects of pickup ions and to correctly estimate the ions velocity distribution and the fluxes along the magnetic field, and on the lunar surface. Modeling shows the formation of the asymmetric Mach cone, the structuring of the pickup ion tails, and presents another type of lunar-solar wind interaction. We will compare the results of our modeling with observed distributions. References [1] Lipatov, A.S., and Cooper, J.F., Hybrid kinetic modeling of the Lunar plasma environment: Past, present and future. In: Lunar Dust, Plasma and Atmosphere: The Next Steps, January 27-29, 2010, Boulder, Colorado, Abstracts/lpa2010.colorado.edu/. [2] Potter, A.E., and Morgan, T.H., Discovery of sodium and potassium vapor in the atmosphere of the Moon, Science, 241, 675-680, doi:10.1126/science.241.4866.675, 1988. [3] Tyler, A.L., et al., Observations of sodium in the tenuous lunar atmosphere, Geophys. Res. Lett., 15(10), 1141-1144, doi:10.1029/GL015i010p01141, 1988. [4] Tanaka, T., et al., First in situ observation of the Moon-originating ions in the Earth's Magnetosphere by MAP-PACE on SELENE (KAGUYA), Geophys. Res. Lett., 36, L22106, doi:10.1029/2009GL040682, 2009. [5] Wiehle, S., et al., First Lunar Wake Passage of ARTEMIS: Discrimination of Wake Effects and Solar Wind Fluctuations by 3D Hybrid Simulations, Planet
Continuing Development of a Hybrid Model (VSH) of the Neutral Thermosphere
NASA Technical Reports Server (NTRS)
Burns, Alan
1996-01-01
We propose to continue the development of a new operational model of neutral thermospheric density, composition, temperatures and winds to improve current engineering environment definitions of the neutral thermosphere. This model will be based on simulations made with the National Center for Atmospheric Research (NCAR) Thermosphere-Ionosphere- Electrodynamic General Circulation Model (TIEGCM) and on empirical data. It will be capable of using real-time geophysical indices or data from ground-based and satellite inputs and provides neutral variables at specified locations and times. This "hybrid" model will be based on a Vector Spherical Harmonic (VSH) analysis technique developed (over the last 8 years) at the University of Michigan that permits the incorporation of the TIGCM outputs and data into the model. The VSH model will be a more accurate version of existing models of the neutral thermospheric, and will thus improve density specification for satellites flying in low Earth orbit (LEO).
Cilfone, Nicholas A.; Kirschner, Denise E.; Linderman, Jennifer J.
2015-01-01
Biologically related processes operate across multiple spatiotemporal scales. For computational modeling methodologies to mimic this biological complexity, individual scale models must be linked in ways that allow for dynamic exchange of information across scales. A powerful methodology is to combine a discrete modeling approach, agent-based models (ABMs), with continuum models to form hybrid models. Hybrid multi-scale ABMs have been used to simulate emergent responses of biological systems. Here, we review two aspects of hybrid multi-scale ABMs: linking individual scale models and efficiently solving the resulting model. We discuss the computational choices associated with aspects of linking individual scale models while simultaneously maintaining model tractability. We demonstrate implementations of existing numerical methods in the context of hybrid multi-scale ABMs. Using an example model describing Mycobacterium tuberculosis infection, we show relative computational speeds of various combinations of numerical methods. Efficient linking and solution of hybrid multi-scale ABMs is key to model portability, modularity, and their use in understanding biological phenomena at a systems level. PMID:26366228
NASA Astrophysics Data System (ADS)
McLarty, Dustin Fogle
Distributed energy systems are a promising means by which to reduce both emissions and costs. Continuous generators must be responsive and highly efficiency to support building dynamics and intermittent on-site renewable power. Fuel cell -- gas turbine hybrids (FC/GT) are fuel-flexible generators capable of ultra-high efficiency, ultra-low emissions, and rapid power response. This work undertakes a detailed study of the electrochemistry, chemistry and mechanical dynamics governing the complex interaction between the individual systems in such a highly coupled hybrid arrangement. The mechanisms leading to the compressor stall/surge phenomena are studied for the increased risk posed to particular hybrid configurations. A novel fuel cell modeling method introduced captures various spatial resolutions, flow geometries, stack configurations and novel heat transfer pathways. Several promising hybrid configurations are analyzed throughout the work and a sensitivity analysis of seven design parameters is conducted. A simple estimating method is introduced for the combined system efficiency of a fuel cell and a turbine using component performance specifications. Existing solid oxide fuel cell technology is capable of hybrid efficiencies greater than 75% (LHV) operating on natural gas, and existing molten carbonate systems greater than 70% (LHV). A dynamic model is calibrated to accurately capture the physical coupling of a FC/GT demonstrator tested at UC Irvine. The 2900 hour experiment highlighted the sensitivity to small perturbations and a need for additional control development. Further sensitivity studies outlined the responsiveness and limits of different control approaches. The capability for substantial turn-down and load following through speed control and flow bypass with minimal impact on internal fuel cell thermal distribution is particularly promising to meet local demands or provide dispatchable support for renewable power. Advanced control and dispatch
Stroke maximizing and high efficient hysteresis hybrid modeling for a rhombic piezoelectric actuator
NASA Astrophysics Data System (ADS)
Shao, Shubao; Xu, Minglong; Zhang, Shuwen; Xie, Shilin
2016-06-01
Rhombic piezoelectric actuator (RPA), which employs a rhombic mechanism to amplify the small stroke of PZT stack, has been widely used in many micro-positioning machineries due to its remarkable properties such as high displacement resolution and compact structure. In order to achieve large actuation range along with high accuracy, the stroke maximizing and compensation for the hysteresis are two concerns in the use of RPA. However, existing maximization methods based on theoretical model can hardly accurately predict the maximum stroke of RPA because of approximation errors that are caused by the simplifications that must be made in the analysis. Moreover, despite the high hysteresis modeling accuracy of Preisach model, its modeling procedure is trivial and time-consuming since a large set of experimental data is required to determine the model parameters. In our research, to improve the accuracy of theoretical model of RPA, the approximation theory is employed in which the approximation errors can be compensated by two dimensionless coefficients. To simplify the hysteresis modeling procedure, a hybrid modeling method is proposed in which the parameters of Preisach model can be identified from only a small set of experimental data by using the combination of discrete Preisach model (DPM) with particle swarm optimization (PSO) algorithm. The proposed novel hybrid modeling method can not only model the hysteresis with considerable accuracy but also significantly simplified the modeling procedure. Finally, the inversion of hysteresis is introduced to compensate for the hysteresis non-linearity of RPA, and consequently a pseudo-linear system can be obtained.
Ozmutlu, H. Cenk
2014-01-01
We developed mixed integer programming (MIP) models and hybrid genetic-local search algorithms for the scheduling problem of unrelated parallel machines with job sequence and machine-dependent setup times and with job splitting property. The first contribution of this paper is to introduce novel algorithms which make splitting and scheduling simultaneously with variable number of subjobs. We proposed simple chromosome structure which is constituted by random key numbers in hybrid genetic-local search algorithm (GAspLA). Random key numbers are used frequently in genetic algorithms, but it creates additional difficulty when hybrid factors in local search are implemented. We developed algorithms that satisfy the adaptation of results of local search into the genetic algorithms with minimum relocation operation of genes' random key numbers. This is the second contribution of the paper. The third contribution of this paper is three developed new MIP models which are making splitting and scheduling simultaneously. The fourth contribution of this paper is implementation of the GAspLAMIP. This implementation let us verify the optimality of GAspLA for the studied combinations. The proposed methods are tested on a set of problems taken from the literature and the results validate the effectiveness of the proposed algorithms. PMID:24977204
Lithio, Andrew; Nettleton, Dan
2016-01-01
The performance of inbred and hybrid genotypes is of interest in plant breeding and genetics. High-throughput sequencing of RNA (RNA-seq) has proven to be a useful tool in the study of the molecular genetic responses of inbreds and hybrids to environmental stresses. Commonly used experimental designs and sequencing methods lead to complex data structures that require careful attention in data analysis. We demonstrate an analysis of RNA-seq data from a split-plot design involving drought stress applied to two inbred genotypes and two hybrids formed by crosses between the inbreds. Our generalized linear modeling strategy incorporates random effects for whole-plot experimental units and uses negative binomial distributions to allow for overdispersion in count responses for split-plot experimental units. Variations in gene length and base content, as well as differences in sequencing intensity across experimental units, are also accounted for. Hierarchical modeling with thoughtful parameterization and prior specification allows for borrowing of information across genes to improve estimation of dispersion parameters, genotype effects, treatment effects, and interaction effects of primary interest. PMID:27110090
A novel hybrid forecasting model for PM₁₀ and SO₂ daily concentrations.
Wang, Ping; Liu, Yong; Qin, Zuodong; Zhang, Guisheng
2015-02-01
Air-quality forecasting in urban areas is difficult because of the uncertainties in describing both the emission and meteorological fields. The use of incomplete information in the training phase restricts practical air-quality forecasting. In this paper, we propose a hybrid artificial neural network and a hybrid support vector machine, which effectively enhance the forecasting accuracy of an artificial neural network (ANN) and support vector machine (SVM) by revising the error term of the traditional methods. The hybrid methodology can be described in two stages. First, we applied the ANN or SVM forecasting system with historical data and exogenous parameters, such as meteorological variables. Then, the forecasting target was revised by the Taylor expansion forecasting model using the residual information of the error term in the previous stage. The innovation involved in this approach is that it sufficiently and validly utilizes the useful residual information on an incomplete input variable condition. The proposed method was evaluated by experiments using a 2-year dataset of daily PM₁₀ (particles with a diameter of 10 μm or less) concentrations and SO₂ (sulfur dioxide) concentrations from four air pollution monitoring stations located in Taiyuan, China. The theoretical analysis and experimental results demonstrated that the forecasting accuracy of the proposed model is very promising.
Toward real-time three-dimensional mapping of surficial aquifers using a hybrid modeling approach
NASA Astrophysics Data System (ADS)
Friedel, Michael J.; Esfahani, Akbar; Iwashita, Fabio
2016-02-01
A hybrid modeling approach is proposed for near real-time three-dimensional (3D) mapping of surficial aquifers. First, airborne frequency-domain electromagnetic (FDEM) measurements are numerically inverted to obtain subsurface resistivities. Second, a machine-learning (ML) algorithm is trained using the FDEM measurements and inverted resistivity profiles, and borehole geophysical and hydrogeologic data. Third, the trained ML algorithm is used together with independent FDEM measurements to map the spatial distribution of the aquifer system. Efficacy of the hybrid approach is demonstrated for mapping a heterogeneous surficial aquifer and confining unit in northwestern Nebraska, USA. For this case, independent performance testing reveals that aquifer mapping is unbiased with a strong correlation (0.94) among numerically inverted and ML-estimated binary (clay-silt or sand-gravel) layer resistivities (5-20 ohm-m or 21-5,000 ohm-m), and an intermediate correlation (0.74) for heterogeneous (clay, silt, sand, gravel) layer resistivities (5-5,000 ohm-m). Reduced correlation for the heterogeneous model is attributed to over-estimating the under-sampled high-resistivity gravels (about 0.5 % of the training data), and when removed the correlation increases (0.87). Independent analysis of the numerically inverted and ML-estimated resistivities finds that the hybrid procedure preserves both univariate and spatial statistics for each layer. Following training, the algorithms can map 3D surficial aquifers as fast as leveled FDEM measurements are presented to the ML network.
Eroglu, Duygu Yilmaz; Ozmutlu, H Cenk
2014-01-01
We developed mixed integer programming (MIP) models and hybrid genetic-local search algorithms for the scheduling problem of unrelated parallel machines with job sequence and machine-dependent setup times and with job splitting property. The first contribution of this paper is to introduce novel algorithms which make splitting and scheduling simultaneously with variable number of subjobs. We proposed simple chromosome structure which is constituted by random key numbers in hybrid genetic-local search algorithm (GAspLA). Random key numbers are used frequently in genetic algorithms, but it creates additional difficulty when hybrid factors in local search are implemented. We developed algorithms that satisfy the adaptation of results of local search into the genetic algorithms with minimum relocation operation of genes' random key numbers. This is the second contribution of the paper. The third contribution of this paper is three developed new MIP models which are making splitting and scheduling simultaneously. The fourth contribution of this paper is implementation of the GAspLAMIP. This implementation let us verify the optimality of GAspLA for the studied combinations. The proposed methods are tested on a set of problems taken from the literature and the results validate the effectiveness of the proposed algorithms.
Hybrid-space density matrix renormalization group study of the doped two-dimensional Hubbard model
NASA Astrophysics Data System (ADS)
Ehlers, G.; White, S. R.; Noack, R. M.
2017-03-01
The performance of the density matrix renormalization group (DMRG) is strongly influenced by the choice of the local basis of the underlying physical lattice. We demonstrate that, for the two-dimensional Hubbard model, the hybrid-real-momentum-space formulation of the DMRG is computationally more efficient than the standard real-space formulation. In particular, we show that the computational cost for fixed bond dimension of the hybrid-space DMRG is approximately independent of the width of the lattice, in contrast to the real-space DMRG, for which it is proportional to the width squared. We apply the hybrid-space algorithm to calculate the ground state of the doped two-dimensional Hubbard model on cylinders of width four and six sites; at n =0.875 filling, the ground state exhibits a striped charge-density distribution with a wavelength of eight sites for both U /t =4.0 and 8.0 . We find that the strength of the charge ordering depends on U /t and on the boundary conditions. Furthermore, we investigate the magnetic ordering as well as the decay of the static spin, charge, and pair-field correlation functions.
Nandola, Naresh N.; Rivera, Daniel E.
2013-01-01
We consider an improved model predictive control (MPC) formulation for linear hybrid systems described by mixed logical dynamical (MLD) models. The algorithm relies on a multiple-degree-of-freedom parametrization that enables the user to adjust the speed of setpoint tracking, measured disturbance rejection and unmeasured disturbance rejection independently in the closed-loop system. Consequently, controller tuning is more flexible and intuitive than relying on objective function weights (such as move suppression) traditionally used in MPC schemes. The controller formulation is motivated by the needs of non-traditional control applications that are suitably described by hybrid production-inventory systems. Two applications are considered in this paper: adaptive, time-varying interventions in behavioral health, and inventory management in supply chains under conditions of limited capacity. In the adaptive intervention application, a hypothetical intervention inspired by the Fast Track program, a real-life preventive intervention for reducing conduct disorder in at-risk children, is examined. In the inventory management application, the ability of the algorithm to judiciously alter production capacity under conditions of varying demand is presented. These case studies demonstrate that MPC for hybrid systems can be tuned for desired performance under demanding conditions involving noise and uncertainty. PMID:24348004
Lithio, Andrew; Nettleton, Dan
2015-12-01
The performance of inbred and hybrid genotypes is of interest in plant breeding and genetics. High-throughput sequencing of RNA (RNA-seq) has proven to be a useful tool in the study of the molecular genetic responses of inbreds and hybrids to environmental stresses. Commonly used experimental designs and sequencing methods lead to complex data structures that require careful attention in data analysis. We demonstrate an analysis of RNA-seq data from a split-plot design involving drought stress applied to two inbred genotypes and two hybrids formed by crosses between the inbreds. Our generalized linear modeling strategy incorporates random effects for whole-plot experimental units and uses negative binomial distributions to allow for overdispersion in count responses for split-plot experimental units. Variations in gene length and base content, as well as differences in sequencing intensity across experimental units, are also accounted for. Hierarchical modeling with thoughtful parameterization and prior specification allows for borrowing of information across genes to improve estimation of dispersion parameters, genotype effects, treatment effects, and interaction effects of primary interest.
Cao, H Q; Kang, L S; Guo, T; Chen, Y P; de Garis, H
2000-01-01
This paper presents a new algorithm for modeling one-dimensional (1-D) dynamic systems by higher-order ordinary differential equation (HODE) models instead of the ARMA models as used in traditional time series analysis. A two-level hybrid evolutionary modeling algorithm (THEMA) is used to approach the modeling problem of HODE's for dynamic systems. The main idea of this modeling algorithm is to embed a genetic algorithm (GA) into genetic programming (GP), where GP is employed to optimize the structure of a model (the upper level), while a GA is employed to optimize the parameters of the model (the lower level). In the GA, we use a novel crossover operator based on a nonconvex linear combination of multiple parents which works efficiently and quickly in parameter optimization tasks. Two practical examples of time series are used to demonstrate the THEMA's effectiveness and advantages.
Studies of the hybrid star structure within 2 +1 flavors NJL model
NASA Astrophysics Data System (ADS)
Li, Cheng-Ming; Zhang, Jin-Li; Zhao, Tong; Zhao, Ya-Peng; Zong, Hong-Shi
2017-03-01
In this paper, we use the equation of state (EOS) of the 2 +1 flavors Nambu-Jona-Lasinio (NJL) model to study the structure of compact stars. To avoid the ultraviolet divergence, we employ the proper-time regularization (PTR) with an ultraviolet cutoff. For comparison, we fix three sets of parameters, where the constraints of chemical equilibrium and electric charge neutrality conditions are taken into consideration. With a certain interpolation method in the crossover region, we construct three corresponding hybrid EOSs but find that the maximum masses of hybrid stars in the three different cases do not differ too much. It should be pointed out that the results we get are in accordance with the recent astro-observation PSR J 0348 +0432 , PSR J 1614 -2230 , PSR J 1946 +3417 .
Hybrid Model-Based and Data-Driven Fault Detection and Diagnostics for Commercial Buildings
Frank, Stephen; Heaney, Michael; Jin, Xin; Robertson, Joseph; Cheung, Howard; Elmore, Ryan; Henze, Gregor
2016-08-26
Commercial buildings often experience faults that produce undesirable behavior in building systems. Building faults waste energy, decrease occupants' comfort, and increase operating costs. Automated fault detection and diagnosis (FDD) tools for buildings help building owners discover and identify the root causes of faults in building systems, equipment, and controls. Proper implementation of FDD has the potential to simultaneously improve comfort, reduce energy use, and narrow the gap between actual and optimal building performance. However, conventional rule-based FDD requires expensive instrumentation and valuable engineering labor, which limit deployment opportunities. This paper presents a hybrid, automated FDD approach that combines building energy models and statistical learning tools to detect and diagnose faults noninvasively, using minimal sensors, with little customization. We compare and contrast the performance of several hybrid FDD algorithms for a small security building. Our results indicate that the algorithms can detect and diagnose several common faults, but more work is required to reduce false positive rates and improve diagnosis accuracy.
Frank, Stephen; Heaney, Michael; Jin, Xin; Robertson, Joseph; Cheung, Howard; Elmore, Ryan; Henze, Gregor
2016-08-01
Commercial buildings often experience faults that produce undesirable behavior in building systems. Building faults waste energy, decrease occupants' comfort, and increase operating costs. Automated fault detection and diagnosis (FDD) tools for buildings help building owners discover and identify the root causes of faults in building systems, equipment, and controls. Proper implementation of FDD has the potential to simultaneously improve comfort, reduce energy use, and narrow the gap between actual and optimal building performance. However, conventional rule-based FDD requires expensive instrumentation and valuable engineering labor, which limit deployment opportunities. This paper presents a hybrid, automated FDD approach that combines building energy models and statistical learning tools to detect and diagnose faults noninvasively, using minimal sensors, with little customization. We compare and contrast the performance of several hybrid FDD algorithms for a small security building. Our results indicate that the algorithms can detect and diagnose several common faults, but more work is required to reduce false positive rates and improve diagnosis accuracy.
NASA Astrophysics Data System (ADS)
Kumar, Mano Ranjan; Ghosh, Subhojit; Das, Shantanu
2016-12-01
The usage of ultracapacitors for development of energy storage devices and alternative power sources is increasing at a very rapid rate. However accuracy in selection of ultracapacitor model parameter plays key role in the design of such devices, especially in applications involving wide operating frequency. Ultracapacitors are known to exhibit fractional dynamics and the model parameters vary significantly with frequency. This paper proposes a piecewise modelling and parameter estimation approach for ultracapacitors using a hybrid optimization and fuzzy clustering approach. The proposed modelling technique has been applied over impedance frequency response data acquired from a commercially available ultracapacitor. The model is able to represent the experimental data over different operating points with reduced number of model parameters. Comparative numerical simulations have been carried out to validate the benefits of the proposed approach. The estimated parameters revealed the disparity in the frequency dependent behavior of ultracapacitors and standard electrolytic capacitors.
Evaluation of a general hybrid RANS/LES model in smooth wall reattachment
NASA Astrophysics Data System (ADS)
Haering, Sigfried; Moser, Robert
2016-11-01
Hybrid RANS/LES modeling approaches often exhibit deficiencies when used for common problems of engineering interest containing flow features such as unsteady smooth-wall separation and reattachment with non-trivial domains and discretization. Often, problem specific modifications and tuning must be employed rendering these models ineffective as generally predictive tools. A new broadly applicable hybrid RANS/LES modeling approach that is being developed to specifically address challenges associated with complex geometries and flows is presented. In general, the approach seeks to a balance between theoretical and actual modeled turbulent kinetic energy provided information from the underlying turbulence model, the resolved turbulence, and the available resolution. Anisotropy in the grid and resolved field are directly integrated into this balance. Here, we examine model performance with the case of a wall-mounted smooth hump of Greenblatt et al.. Excellent agreement with experimental results is attained while significantly outperforming delayed detached eddy simulation (DDES) for nearly the same computational expense and without any problem-specific modifications.
Hybrid internal model control and proportional control of chaotic dynamical systems.
Qi, Dong-lian; Yao, Liang-bin
2004-01-01
A new chaos control method is proposed to take advantage of chaos or avoid it. The hybrid Internal Model Control and Proportional Control learning scheme are introduced. In order to gain the desired robust performance and ensure the system's stability, Adaptive Momentum Algorithms are also developed. Through properly designing the neural network plant model and neural network controller, the chaotic dynamical systems are controlled while the parameters of the BP neural network are modified. Taking the Lorenz chaotic system as example, the results show that chaotic dynamical systems can be stabilized at the desired orbits by this control strategy.
Shi, Yimin; Wu, Min
2016-01-01
Previous studies have mostly considered the competing risks to be independent even when the interpretation of the failure modes implies dependency. This paper studies the dependent competing risks model from Gompertz distribution under Type-I progressively hybrid censoring scheme. We derive the maximum likelihood estimations of the model parameters, and then the asymptotic likelihood theory and Bootstrap method are used to obtain the confidence intervals. The simulation results are provided to investigate the effects of different dependence structures on the estimations of parameters. Finally, one data set was used for illustrative purpose.
Application of the hybrid-Trefftz finite element model to thin shell analysis
NASA Astrophysics Data System (ADS)
Voros, Gabor
The paper presents the results of a preliminary study on thin shallow shell element based on the hybrid-Trefftz (HT) model. This model adopts an assumed nonconforming displacement field which satisfies a priori the governing differential equations. The interelement continuity and the boundary conditions are enforced by frame fields defined in terms of the conventional nodal freedoms. In the p-extension, the frame functions involve an optional number of hierarchic displacement modes. Numerical results present the capability of the new shell element which can be implemented in existing finite element codes.
NASA Astrophysics Data System (ADS)
Kowsika, Murthy V. S. L. N.
In this study, investigation was performed to comprehend the influence of hybridization on the impact performance in terms of the energy absorption characteristics and delamination fracture toughness of pultruded uni-directional composite materials. In order to evaluate the improvements/changes in the impact performance as a result of hybridization, apart from considering mono-fiber reinforced all-graphite and all-glass composites, several types of sandwich hybrid composites comprising of both graphite as well as glass fibers were included in the investigation. By keeping a constant overall fiber content, the lay-up sequence and the volume fraction of each type of fiber are altered in these pultruded composites to determine the trend in the mechanical behavior as a result of hybridization. The response of pultruded all-graphite, all-glass and glass-graphite hybrid composites is evaluated under two different incident impact energy conditions. A high incident energy (HIE) and a low incident energy (LIE) of impact are chosen to cause either complete fracture or induce delamination, respectively, for assessing the energy absorption characteristics (crashworthiness) and delamination fracture toughness of these composites. Finite element modeling is performed under static as well as dynamic loading conditions to simulate the stress distribution and to predict the energy absorption behavior of composites. Progressive damage due to sequential ply failure was modeled by utilizing the failure strain data obtained from static and HTE impact tests for analyzing the post-initial ply failure characteristics of pultruded composites. Finite element modeling was also performed to simulate delamination crack propagation at various levels through the thickness. The strain energy release rate computed using the virtual crack closure technique was monitored to determine the likelihood of delamination crack propagation with increment in crack growth for the pultruded composites under
NASA Astrophysics Data System (ADS)
Humphrey, Greer B.; Gibbs, Matthew S.; Dandy, Graeme C.; Maier, Holger R.
2016-09-01
Monthly streamflow forecasts are needed to support water resources decision making in the South East of South Australia, where baseflow represents a significant proportion of the total streamflow and soil moisture and groundwater are important predictors of runoff. To address this requirement, the utility of a hybrid monthly streamflow forecasting approach is explored, whereby simulated soil moisture from the GR4J conceptual rainfall-runoff model is used to represent initial catchment conditions in a Bayesian artificial neural network (ANN) statistical forecasting model. To assess the performance of this hybrid forecasting method, a comparison is undertaken of the relative performances of the Bayesian ANN, the GR4J conceptual model and the hybrid streamflow forecasting approach for producing 1-month ahead streamflow forecasts at three key locations in the South East of South Australia. Particular attention is paid to the quantification of uncertainty in each of the forecast models and the potential for reducing forecast uncertainty by using the hybrid approach is considered. Case study results suggest that the hybrid models developed in this study are able to take advantage of the complementary strengths of both the ANN models and the GR4J conceptual models. This was particularly the case when forecasting high flows, where the hybrid models were shown to outperform the two individual modelling approaches in terms of the accuracy of the median forecasts, as well as reliability and resolution of the forecast distributions. In addition, the forecast distributions generated by the hybrid models were up to 8 times more precise than those based on climatology; thus, providing a significant improvement on the information currently available to decision makers.
Hybrid pathwise sensitivity methods for discrete stochastic models of chemical reaction systems
Wolf, Elizabeth Skubak; Anderson, David F.
2015-01-21
Stochastic models are often used to help understand the behavior of intracellular biochemical processes. The most common such models are continuous time Markov chains (CTMCs). Parametric sensitivities, which are derivatives of expectations of model output quantities with respect to model parameters, are useful in this setting for a variety of applications. In this paper, we introduce a class of hybrid pathwise differentiation methods for the numerical estimation of parametric sensitivities. The new hybrid methods combine elements from the three main classes of procedures for sensitivity estimation and have a number of desirable qualities. First, the new methods are unbiased for a broad class of problems. Second, the methods are applicable to nearly any physically relevant biochemical CTMC model. Third, and as we demonstrate on several numerical examples, the new methods are quite efficient, particularly if one wishes to estimate the full gradient of parametric sensitivities. The methods are rather intuitive and utilize the multilevel Monte Carlo philosophy of splitting an expectation into separate parts and handling each in an efficient manner.
Sadowsky, Ofri; Lee, Junghoon; Sutter, E. Grant; Wall, Simon J.; Prince, Jerry L.; Taylor, Russell H.
2012-01-01
We propose a method for improving the quality of cone-beam tomographic reconstruction done with a C-arm. C-arm scans frequently suffer from incomplete information due to image truncation, limited scan length, or other limitations. Our proposed “hybrid reconstruction” method injects information from a prior anatomical model, derived from a subject-specific CT or from a statistical database (atlas), where the C-arm x-ray data is missing. This significantly reduces reconstruction artifacts with little loss of true information from the x-ray projections. The methods consist of constructing anatomical models, fast rendering of digitally reconstructed radiograph (DRR) projections of the models, rigid or deformable registration of the model and the x-ray images, and fusion of the DRR and x-ray projections, all prior to a conventional filtered back-projection algorithm. Our experiments, conducted with a mobile image intensifier C-arm, demonstrate visually and quantitatively the contribution of data fusion to image quality, which we assess through comparison to a “ground truth” CT. Importantly, we show that a significantly improved reconstruction can be obtained from a C-arm scan as short as 90° by complementing the observed projections with DRRs of two prior models, namely an atlas and a pre-operative same-patient CT. The hybrid reconstruction principles are applicable to other types of C-arms as well. PMID:20667807
Hybrid pathwise sensitivity methods for discrete stochastic models of chemical reaction systems.
Wolf, Elizabeth Skubak; Anderson, David F
2015-01-21
Stochastic models are often used to help understand the behavior of intracellular biochemical processes. The most common such models are continuous time Markov chains (CTMCs). Parametric sensitivities, which are derivatives of expectations of model output quantities with respect to model parameters, are useful in this setting for a variety of applications. In this paper, we introduce a class of hybrid pathwise differentiation methods for the numerical estimation of parametric sensitivities. The new hybrid methods combine elements from the three main classes of procedures for sensitivity estimation and have a number of desirable qualities. First, the new methods are unbiased for a broad class of problems. Second, the methods are applicable to nearly any physically relevant biochemical CTMC model. Third, and as we demonstrate on several numerical examples, the new methods are quite efficient, particularly if one wishes to estimate the full gradient of parametric sensitivities. The methods are rather intuitive and utilize the multilevel Monte Carlo philosophy of splitting an expectation into separate parts and handling each in an efficient manner.
Measured and modelled carbon and water fluxes in hybrid willows grown for biofuel production
NASA Astrophysics Data System (ADS)
Wertin, T. M.; LeBauer, D.; Volk, T.; Long, S.; Leakey, A. D.
2014-12-01
Biofuels have the potential to meet future energy needs. Worldwide, up to 75% of biofuels produced are derived from woody sources. Coppiced hybrid willow is among the most promising woody biofuel sources due to its ability to rapidly regenerate after cutting, high biomass yields, low nutrient requirements and ability to be grown on marginal land, abandoned land and land easily erodible under annual cultivation. However, models used to assess the potential viability and sustainability of commercial biomass production by willow in the northeastern, northern and northwestern USA remain unsophisticated and lack key parameterization data. Most significantly, models do not explicitly represent the coppiced growth form. This study tests the ability of a canopy model to predict carbon and water fluxes in two highly productive, but structurally distinct hybrid willows (Salix miyabeana and Salix purpurea) grown in central NY. S. miyaneana has only a few, large diameter stems per stool prior to harvest, while S. purpurea maintains numerous, small diameter stems until harvest. Canopy structure also varies substantially within a growing season. For example, in S. miyabeana stem number decreased by 40% while total basal area increased by 50% within year 2 of the third coppice cycle. Model predictions of water use are compared with stand transpiration measured by sap flow. Model predictions of biomass production are compared to destructive harvest data. Sensitivity of predicted fluxes to variation between genotypes in key physiological parameters is also tested.
Hybrid modeling of time-dependent solar wind-comet interactions
NASA Astrophysics Data System (ADS)
Alho, Markku; Wedlund, Cyril Simon; Kallio, Esa; Nilsson, Hans
2016-04-01
Global hybrid plasma modelling of cometary environments is an essential tool in understanding the global implications of point measurements performed by the Rosetta probe in the vicinity of 67P/Churyumov-Gerasimenko. A 3-D, global hybrid plasma model, including the effects of plasma-driven ionization of cometary neutrals, has been employed to model an approximation of 67P's environment around perihelion conditions. Model inputs include solar wind upstream parameters, a simple cometary neutral model and a H2O+-bound photochemistry. In this work we present results on the responses of a cometary plasma environment when impinged upon by a time-dependent solar wind. Stepwise upward and downward density changes as well as linear ramps are investigated, along with tangential discontinuities in the interplanetary magnetic field. As the production rates of cometary ions are coupled to solar wind parameters through e.g. charge exchange and electron impact ionization, solar wind variations create non-trivial transient phenomena in the cometary environment. Implications for CME impacts and tail disconnection events are explored, giving insight on how these events may appear in the observational datasets (magnetometer, ion spectrometer) from past missions and from Rosetta.
An Investigation of a Hybrid Mixing Timescale Model for PDF Simulations of Turbulent Premixed Flames
NASA Astrophysics Data System (ADS)
Zhou, Hua; Kuron, Mike; Ren, Zhuyin; Lu, Tianfeng; Chen, Jacqueline H.
2016-11-01
Transported probability density function (TPDF) method features the generality for all combustion regimes, which is attractive for turbulent combustion simulations. However, the modeling of micromixing due to molecular diffusion is still considered to be a primary challenge for TPDF method, especially in turbulent premixed flames. Recently, a hybrid mixing rate model for TPDF simulations of turbulent premixed flames has been proposed, which recovers the correct mixing rates in the limits of flamelet regime and broken reaction zone regime while at the same time aims to properly account for the transition in between. In this work, this model is employed in TPDF simulations of turbulent premixed methane-air slot burner flames. The model performance is assessed by comparing the results from both direct numerical simulation (DNS) and conventional constant mechanical-to-scalar mixing rate model. This work is Granted by NSFC 51476087 and 91441202.
Development of Parametric Mass and Volume Models for an Aerospace SOFC/Gas Turbine Hybrid System
NASA Technical Reports Server (NTRS)
Tornabene, Robert; Wang, Xiao-yen; Steffen, Christopher J., Jr.; Freeh, Joshua E.
2005-01-01
In aerospace power systems, mass and volume are key considerations to produce a viable design. The utilization of fuel cells is being studied for a commercial aircraft electrical power unit. Based on preliminary analyses, a SOFC/gas turbine system may be a potential solution. This paper describes the parametric mass and volume models that are used to assess an aerospace hybrid system design. The design tool utilizes input from the thermodynamic system model and produces component sizing, performance, and mass estimates. The software is designed such that the thermodynamic model is linked to the mass and volume model to provide immediate feedback during the design process. It allows for automating an optimization process that accounts for mass and volume in its figure of merit. Each component in the system is modeled with a combination of theoretical and empirical approaches. A description of the assumptions and design analyses is presented.
Estimating biofilm reaction kinetics using hybrid mechanistic-neural network rate function model.
Kumar, B Shiva; Venkateswarlu, Ch
2012-01-01
This work describes an alternative method for estimation of reaction rate of a biofilm process without using a model equation. A first principles model of the biofilm process is integrated with artificial neural networks to derive a hybrid mechanistic-neural network rate function model (HMNNRFM), and this combined model structure is used to estimate the complex kinetics of the biofilm process as a consequence of the validation of its steady state solution. The performance of the proposed methodology is studied with the aid of the experimental data of an anaerobic fixed bed biofilm reactor. The statistical significance of the method is also analyzed by means of the coefficient of determination (R2) and model efficiency (ME). The results demonstrate the effectiveness of HMNNRFM for estimating the complex kinetics of the biofilm process involved in the treatment of industry wastewater.
A comparison of simulated precipitation by hybrid isentropic-sigma and sigma models
NASA Technical Reports Server (NTRS)
Johnson, Donald R.; Zapotocny, Tom H.; Reames, Fred M.; Wolf, Bart J.; Pierce, R. B.
1993-01-01
Simulations of dry and moist baroclinic development from 10- and 22-layer hybrid isentropic-sigma coordinate models are compared with those from 11-, 27-, and 35-layer sigma coordinate models. The ability of the models to transport water vapor and simulate equivalent potential temperature is examined. Predictions of the timing, location, and amount of precipitation are compared. Several analytical distributions of water vapor are specified initially. It is shown that when the relative humidity is vertically uniform through a substantial extent of the atmosphere, all the models produce very similar precipitation distributions. However, when water vapor is confined to relatively shallow layers, the ability of the sigma coordinate models to simulate the timing, location, and amount of precipitation is severely compromised.
Systems biology by the rules: hybrid intelligent systems for pathway modeling and discovery
Bosl, William J
2007-01-01
Background Expert knowledge in journal articles is an important source of data for reconstructing biological pathways and creating new hypotheses. An important need for medical research is to integrate this data with high throughput sources to build useful models that span several scales. Researchers traditionally use mental models of pathways to integrate information and development new hypotheses. Unfortunately, the amount of information is often overwhelming and these are inadequate for predicting the dynamic response of complex pathways. Hierarchical computational models that allow exploration of semi-quantitative dynamics are useful systems biology tools for theoreticians, experimentalists and clinicians and may provide a means for cross-communication. Results A novel approach for biological pathway modeling based on hybrid intelligent systems or soft computing technologies is presented here. Intelligent hybrid systems, which refers to several related computing methods such as fuzzy logic, neural nets, genetic algorithms, and statistical analysis, has become ubiquitous in engineering applications for complex control system modeling and design. Biological pathways may be considered to be complex control systems, which medicine tries to manipulate to achieve desired results. Thus, hybrid intelligent systems may provide a useful tool for modeling biological system dynamics and computational exploration of new drug targets. A new modeling approach based on these methods is presented in the context of hedgehog regulation of the cell cycle in granule cells. Code and input files can be found at the Bionet website: www.chip.ord/~wbosl/Software/Bionet. Conclusion This paper presents the algorithmic methods needed for modeling complicated biochemical dynamics using rule-based models to represent expert knowledge in the context of cell cycle regulation and tumor growth. A notable feature of this modeling approach is that it allows biologists to build complex models from
Data sensitivity in a hybrid STEP/Coulomb model for aftershock forecasting
NASA Astrophysics Data System (ADS)
Steacy, S.; Jimenez Lloret, A.; Gerstenberger, M.
2014-12-01
Operational earthquake forecasting is rapidly becoming a 'hot topic' as civil protection authorities seek quantitative information on likely near future earthquake distributions during seismic crises. At present, most of the models in public domain are statistical and use information about past and present seismicity as well as b-value and Omori's law to forecast future rates. A limited number of researchers, however, are developing hybrid models which add spatial constraints from Coulomb stress modeling to existing statistical approaches. Steacy et al. (2013), for instance, recently tested a model that combines Coulomb stress patterns with the STEP (short-term earthquake probability) approach against seismicity observed during the 2010-2012 Canterbury earthquake sequence. They found that the new model performed at least as well as, and often better than, STEP when tested against retrospective data but that STEP was generally better in pseudo-prospective tests that involved data actually available within the first 10 days of each event of interest. They suggested that the major reason for this discrepancy was uncertainty in the slip models and, in particular, in the geometries of the faults involved in each complex major event. Here we test this hypothesis by developing a number of retrospective forecasts for the Landers earthquake using hypothetical slip distributions developed by Steacy et al. (2004) to investigate the sensitivity of Coulomb stress models to fault geometry and earthquake slip, and we also examine how the choice of receiver plane geometry affects the results. We find that the results are strongly sensitive to the slip models and moderately sensitive to the choice of receiver orientation. We further find that comparison of the stress fields (resulting from the slip models) with the location of events in the learning period provides advance information on whether or not a particular hybrid model will perform better than STEP.
Bernard, P S; Pritham, G H; Wittwer, C T
1999-09-10
Fluorescent hybridization probes were multiplexed for color genotyping of the apolipoprotein E locus using model oligonucleotide targets. Fluorescence resonance energy transfer was observed during adjacent hybridization of 3'-fluorescein-labeled "donor" probes paired with 5'-labeled "acceptor" probes with different emission spectra reporting at codons 112 and 158. The acceptor dyes emitted at either 640 nm (LightCycler Red 640) or 705 nm (LightCycler Red 705) and were monitored with a LightCycler, a thermal cycler with an integrated fluorimeter. The color of the acceptor dye identified each site and the characteristic melting temperatures of the fluorescein-labeled probes identified single base changes within each codon. Color compensation of temperature-dependent spectral overlap was applied to completely separate each channel. Competition between the probes and the complementary strand for the target sequence decreased resonance energy transfer, indicating an advantage of single-stranded target. Hybridization probes of the same length, but different GC content are T(m) shifted by the same amount during A:C mismatch duplex melting. Genotyping was optimal at both sites if melting curve analysis was preceded by a slow (1 degrees C/s) annealing phase. Although each site preferred different concentrations of Mg(2+) and target strand for optimal genotyping, conditions for multiplexing were found. This method, along with an appropriate amplification technique, should allow real-time multiplex genotyping from genomic DNA.
NASA Astrophysics Data System (ADS)
Beeri, Ofer; Rotem, Oded; Hazan, Eden; Katz, Eugene A.; Braun, Avi; Gelbstein, Yaniv
2015-09-01
An experimental demonstration of the combined photovoltaic (PV) and thermoelectric conversion of concentrated sunlight (with concentration factor, X, up to ˜300) into electricity is presented. The hybrid system is based on a multi-junction PV cell and a thermoelectric generator (TEG). The latter increases the electric power of the system and dissipates some of the excessive heat. For X ≤ 200, the system's maximal efficiency, ˜32%, was mostly due to the contribution from the PV cell. With increasing X and system temperature, the PV cell's efficiency decreased while that of the TEG increased. Accordingly, the direct electrical contribution of the TEG started to dominate in the total system power, reaching ˜20% at X ≈ 290. Using a simple steady state finite element modeling, the cooling effect of the TEG on the hybrid system's efficiency was proved to be even more significant than its direct electrical contribution for high solar concentrations. As a result, the total efficiency contribution of the TEG reached ˜40% at X ≈ 200. This suggests a new system optimization concept that takes into account the PV cell's temperature dependence and the trade-off between the direct electrical generation and cooling capabilities of the TEG. It is shown that the hybrid system has a real potential to exceed 50% total efficiency by using more advanced PV cells and TE materials.
A Two-Stage Procedure Toward the Efficient Implementation of PANS and Other Hybrid Turbulence Models
NASA Technical Reports Server (NTRS)
Abdol-Hamid, Khaled S.; Girimaji, Sharath S.
2004-01-01
The main objective of this article is to introduce and to show the implementation of a novel two-stage procedure to efficiently estimate the level of scale resolution possible for a given flow on a given grid for Partial Averaged Navier-Stokes (PANS) and other hybrid models. It has been found that the prescribed scale resolution can play a major role in obtaining accurate flow solutions. The first step is to solve the unsteady or steady Reynolds Averaged Navier-Stokes (URANS/RANS) equations. From this preprocessing step, the turbulence length-scale field is obtained. This is then used to compute the characteristic length-scale ratio between the turbulence scale and the grid spacing. Based on this ratio, we can assess the finest scale resolution that a given grid for a given flow can support. Along with other additional criteria, we are able to analytically identify the appropriate hybrid solver resolution for different regions of the flow. This procedure removes the grid dependency issue that affects the results produced by different hybrid procedures in solving unsteady flows. The formulation, implementation methodology, and validation example are presented. We implemented this capability in a production Computational Fluid Dynamics (CFD) code, PAB3D, for the simulation of unsteady flows.
Extensive heterosis in growth of yeast hybrids is explained by a combination of genetic models
Shapira, R; Levy, T; Shaked, S; Fridman, E; David, L
2014-01-01
Heterosis, also known as hybrid vigor, is the superior performance of a heterozygous hybrid relative to its homozygous parents. Despite the scientific curiosity of this phenotypic phenomenon and its significance for food production in agriculture, its genetic basis is insufficiently understood. Studying heterosis in yeast can potentially yield insights into its genetic basis, can allow one to test the different hypotheses that have been proposed to explain the phenomenon and allows better understanding of how to take advantage of this phenomenon to enhance food production. We therefore crossed 16 parental yeast strains to form 120 yeast hybrids, and measured their growth rates under five environmental conditions. A considerable amount of dominant genetic variation was found in growth performance, and heterosis was measured in 35% of the hybrid–condition combinations. Despite previous reports of correlations between heterosis and measures of sequence divergence between parents, we detected no such relationship. We used several analyses to examine which genetic model might explain heterosis. We found that dominance complementation of recessive alleles, overdominant interactions within loci and epistatic interactions among loci each contribute to heterosis. We concluded that in yeast heterosis is a complex phenotype created by the combined contribution of different genetic interactions. PMID:24690755
NASA Astrophysics Data System (ADS)
Chen, Xueli; Liang, Jimin; Hu, Hao; Qu, Xiaochao; Yang, Defu; Chen, Duofang; Zhu, Shouping; Tian, Jie
2012-03-01
Gastric cancer is the second cause of cancer-related death in the world, and it remains difficult to cure because it has been in late-stage once that is found. Early gastric cancer detection becomes an effective approach to decrease the gastric cancer mortality. Bioluminescence tomography (BLT) has been applied to detect early liver cancer and prostate cancer metastasis. However, the gastric cancer commonly originates from the gastric mucosa and grows outwards. The bioluminescent light will pass through a non-scattering region constructed by gastric pouch when it transports in tissues. Thus, the current BLT reconstruction algorithms based on the approximation model of radiative transfer equation are not optimal to handle this problem. To address the gastric cancer specific problem, this paper presents a novel reconstruction algorithm that uses a hybrid light transport model to describe the bioluminescent light propagation in tissues. The radiosity theory integrated with the diffusion equation to form the hybrid light transport model is utilized to describe light propagation in the non-scattering region. After the finite element discretization, the hybrid light transport model is converted into a minimization problem which fuses an l1 norm based regularization term to reveal the sparsity of bioluminescent source distribution. The performance of the reconstruction algorithm is first demonstrated with a digital mouse based simulation with the reconstruction error less than 1mm. An in situ gastric cancer-bearing nude mouse based experiment is then conducted. The primary result reveals the ability of the novel BLT reconstruction algorithm in early gastric cancer detection.
The role of electron polarization current in the hybrid simulation model
NASA Astrophysics Data System (ADS)
Amano, T.; Higashimori, K.; Shirakawa, K.
2013-12-01
The hybrid model (kinetic ions and fluid electrons) has been considered to be a useful numerical method to study nonlinear plasma phenomena in which the macroscopic MHD approximation breaks down due to ion-scale kinetic physics. It is, however, known that this method is vulnerable to a numerical instability when dealing with short-wavelength whistler waves. Although it formally allows such ion-scale physics to play a role, this instability severely limits the applicability of simulations to relatively large scales. Overcoming this problem certainly makes it much more useful. Here we consider the role of electrons that can physically stabilize the simulation. By analyzing the linearlized magnetic field induction equation including the Hall term, we find that the problem of advancing the magnetic field from ion moment quantities becomes ill-conditioned for waves on the whistler mode dispersion. Namely, even a small error contained in the ion fluid velocity would be amplified substantially, implying the existence of a numerical instability. Physically, the reason for this is due to the lack of the electron polarization current in the conventional hybrid model, which is indeed the dominant current for the whistler mode waves. One must therefore take into account a finite electron inertia effect in an appropriate manner to avoid the numerical problem. We propose a method that incorporates the electron polarization current without loosing advantages of the hybrid model. For this purpose, we have to resolve very high frequency electric-field fluctuations because averaging over them gives the slow polarization drift. This can be made possible by using the analytic solution to the full set of Maxwell's equations including the displacement current under some reasonable assumptions. We think the method can readily apply also to the Hall-MHD model as well.
Tulchinsky, Alexander Y; Johnson, Norman A; Porter, Adam H
2014-12-01
Hybrid incompatibility can result from gene misregulation produced by divergence in trans-acting regulatory factors and their cis-regulatory targets. However, change in trans-acting factors may be constrained by pleiotropy, which would in turn limit the evolution of incompatibility. We employed a mechanistically explicit bioenergetic model of gene expression wherein parameter combinations (number of transcription factor molecules, energetic properties of binding to the regulatory site, and genomic background size) determine the shape of the genotype-phenotype (G-P) map, and interacting allelic variants of mutable cis and trans sites determine the phenotype along that map. Misregulation occurs when the phenotype differs from its optimal value. We simulated a pleiotropic regulatory pathway involving a positively selected and a conserved trait regulated by a shared transcription factor (TF), with two populations evolving in parallel. Pleiotropic constraints shifted evolution in the positively selected trait to its cis-regulatory locus. We nevertheless found that the TF genotypes often evolved, accompanied by compensatory evolution in the conserved trait, and both traits contributed to hybrid misregulation. Compensatory evolution resulted in "developmental system drift," whereby the regulatory basis of the conserved phenotype changed although the phenotype itself did not. Pleiotropic constraints became stronger and in some cases prohibitive when the bioenergetic properties of the molecular interaction produced a G-P map that was too steep. Likewise, compensatory evolution slowed and hybrid misregulation was not evident when the G-P map was too shallow. A broad pleiotropic "sweet spot" nevertheless existed where evolutionary constraints were moderate to weak, permitting substantial hybrid misregulation in both traits. None of these pleiotropic constraints manifested when the TF contained nonrecombining domains independently regulating the respective traits.
Tulchinsky, Alexander Y.; Johnson, Norman A.; Porter, Adam H.
2014-01-01
Hybrid incompatibility can result from gene misregulation produced by divergence in trans-acting regulatory factors and their cis-regulatory targets. However, change in trans-acting factors may be constrained by pleiotropy, which would in turn limit the evolution of incompatibility. We employed a mechanistically explicit bioenergetic model of gene expression wherein parameter combinations (number of transcription factor molecules, energetic properties of binding to the regulatory site, and genomic background size) determine the shape of the genotype–phenotype (G-P) map, and interacting allelic variants of mutable cis and trans sites determine the phenotype along that map. Misregulation occurs when the phenotype differs from its optimal value. We simulated a pleiotropic regulatory pathway involving a positively selected and a conserved trait regulated by a shared transcription factor (TF), with two populations evolving in parallel. Pleiotropic constraints shifted evolution in the positively selected trait to its cis-regulatory locus. We nevertheless found that the TF genotypes often evolved, accompanied by compensatory evolution in the conserved trait, and both traits contributed to hybrid misregulation. Compensatory evolution resulted in “developmental system drift,” whereby the regulatory basis of the conserved phenotype changed although the phenotype itself did not. Pleiotropic constraints became stronger and in some cases prohibitive when the bioenergetic properties of the molecular interaction produced a G-P map that was too steep. Likewise, compensatory evolution slowed and hybrid misregulation was not evident when the G-P map was too shallow. A broad pleiotropic “sweet spot” nevertheless existed where evolutionary constraints were moderate to weak, permitting substantial hybrid misregulation in both traits. None of these pleiotropic constraints manifested when the TF contained nonrecombining domains independently regulating the respective traits
Ettarh, Rajunor
2016-05-06
Significant changes have been implemented in the way undergraduate medical education is structured. One of the challenges for component courses such as histology in medical and dental curricula is to restructure and deliver training within new frameworks. This article describes the process of aligning the purpose and experience in histology laboratory to the goal of applying knowledge gained to team-based medical practice at Tulane University School of Medicine. Between 2011 and 2015, 711 medical students took either a traditional laboratory-based histology course (353 students) or a team-based hybrid histology course with active learning in laboratory (358 students). The key difference was in the laboratory component of the hybrid course - interactive table conferences in histology-during which students developed new competencies by working in teams, reviewing images, solving problems by applying histology concepts, and sharing learning. Content, faculty and online resources for microscopy were the same in both courses. More student-student and student-faculty interactions were evident during the hybrid course but student evaluation ratings and grades showed reductions following introduction of table conferences when compared to previous ratings. However, outcomes at National Board of Medical Examiners(®) (NBME(®) ) Subject Examination in Histology and Cell Biology showed significant improvement (72.4 ± 9.04 and 76.44 ± 9.36 for percent correct answers, traditional and hybrid courses, respectively, P < 0.0001). This model of table conferences to augment the traditional histology laboratory experience exemplifies the extent that restructuring enhancements can be used in currently taught courses in the undergraduate medical curriculum. Anat Sci Educ 9: 286-294. © 2016 American Association of Anatomists.
Development of a Solid-Oxide Fuel Cell/Gas Turbine Hybrid System Model for Aerospace Applications
NASA Technical Reports Server (NTRS)
Freeh, Joshua E.; Pratt, Joseph W.; Brouwer, Jacob
2004-01-01
Recent interest in fuel cell-gas turbine hybrid applications for the aerospace industry has led to the need for accurate computer simulation models to aid in system design and performance evaluation. To meet this requirement, solid oxide fuel cell (SOFC) and fuel processor models have been developed and incorporated into the Numerical Propulsion Systems Simulation (NPSS) software package. The SOFC and reformer models solve systems of equations governing steady-state performance using common theoretical and semi-empirical terms. An example hybrid configuration is presented that demonstrates the new capability as well as the interaction with pre-existing gas turbine and heat exchanger models. Finally, a comparison of calculated SOFC performance with experimental data is presented to demonstrate model validity. Keywords: Solid Oxide Fuel Cell, Reformer, System Model, Aerospace, Hybrid System, NPSS
von Stosch, Moritz; Davy, Steven; Francois, Kjell; Galvanauskas, Vytautas; Hamelink, Jan-Martijn; Luebbert, Andreas; Mayer, Martin; Oliveira, Rui; O'Kennedy, Ronan; Rice, Paul; Glassey, Jarka
2014-06-01
This report highlights the drivers, challenges, and enablers of the hybrid modeling applications in biopharmaceutical industry. It is a summary of an expert panel discussion of European academics and industrialists with relevant scientific and engineering backgrounds. Hybrid modeling is viewed in its broader sense, namely as the integration of different knowledge sources in form of parametric and nonparametric models into a hybrid semi-parametric model, for instance the integration of fundamental and data-driven models. A brief description of the current state-of-the-art and industrial uptake of the methodology is provided. The report concludes with a number of recommendations to facilitate further developments and a wider industrial application of this modeling approach. These recommendations are limited to further exploiting the benefits of this methodology within process analytical technology (PAT) applications in biopharmaceutical industry.
Aristotelous, Andreas C; Haider, Mansoor A
2014-08-01
Macroscopic models accounting for cellular effects in natural or engineered tissues may involve unknown constitutive terms that are highly dependent on interactions at the scale of individual cells. Hybrid discrete models, which represent cells individually, were used to develop and apply techniques for modeling diffusive nutrient transport and cellular uptake to identify a nonlinear nutrient loss term in a macroscopic reaction-diffusion model of the system. Flexible and robust numerical methods were used, based on discontinuous Galerkin finite elements in space and a Crank-Nicolson temporal discretization. Scales were bridged via averaging operations over a complete set of subdomains yielding data for identification of a macroscopic nutrient loss term that was accurately captured via a fifth-order polynomial. Accuracy of the identified macroscopic model was demonstrated by direct, quantitative comparisons of the tissue and cellular scale models in terms of three error norms computed on a mesoscale mesh.
Ostermann, Lars; Seidel, Christian
2015-03-10
The numerical analysis of hydro power stations is an important method of the hydraulic design and is used for the development and optimisation of hydro power stations in addition to the experiments with the physical submodel of a full model in the hydraulic laboratory. For the numerical analysis, 2D and 3D models are appropriate and commonly used.The 2D models refer mainly to the shallow water equations (SWE), since for this flow model a large experience on a wide field of applications for the flow analysis of numerous problems in hydraulic engineering already exists. Often, the flow model is verified by in situ measurements. In order to consider 3D flow phenomena close to singularities like weirs, hydro power stations etc. the development of a hybrid fluid model is advantageous to improve the quality and significance of the global model. Here, an extended hybrid flow model based on the principle of the SWE is presented. The hybrid flow model directly links the numerical model with the experimental data, which may originate from physical full models, physical submodels and in-situ measurements. Hence a wide field of application of the hybrid model emerges including the improvement of numerical models and the strong coupling of numerical and experimental analysis.
Scheibe, Timothy D.; Murphy, Ellyn M.; Chen, Xingyuan; Rice, Amy K.; Carroll, Kenneth C.; Palmer, Bruce J.; Tartakovsky, Alexandre M.; Battiato, Ilenia; Wood, Brian D.
2015-01-01
One of the most significant challenges facing hydrogeologic modelers is the disparity between those spatial and temporal scales at which fundamental flow, transport and reaction processes can best be understood and quantified (e.g., microscopic to pore scales, seconds to days) and those at which practical model predictions are needed (e.g., plume to aquifer scales, years to centuries). While the multiscale nature of hydrogeologic problems is widely recognized, technological limitations in computational and characterization restrict most practical modeling efforts to fairly coarse representations of heterogeneous properties and processes. For some modern problems, the necessary level of simplification is such that model parameters may lose physical meaning and model predictive ability is questionable for any conditions other than those to which the model was calibrated. Recently, there has been broad interest across a wide range of scientific and engineering disciplines in simulation approaches that more rigorously account for the multiscale nature of systems of interest. In this paper, we review a number of such approaches and propose a classification scheme for defining different types of multiscale simulation methods and those classes of problems to which they are most applicable. Our classification scheme is presented in terms of a flow chart (Multiscale Analysis Platform or MAP), and defines several different motifs of multiscale simulation. Within each motif, the member methods are reviewed and example applications are discussed. We focus attention on hybrid multiscale methods, in which two or more models with different physics described at fundamentally different scales are directly coupled within a single simulation. Very recently these methods have begun to be applied to groundwater flow and transport simulations, and we discuss these applications in the context of our classification scheme. As computational and characterization capabilities continue to
Exact hybrid particle/population simulation of rule-based models of biochemical systems.
Hogg, Justin S; Harris, Leonard A; Stover, Lori J; Nair, Niketh S; Faeder, James R
2014-04-01
Detailed modeling and simulation of biochemical systems is complicated by the problem of combinatorial complexity, an explosion in the number of species and reactions due to myriad protein-protein interactions and post-translational modifications. Rule-based modeling overcomes this problem by representing molecules as structured objects and encoding their interactions as pattern-based rules. This greatly simplifies the process of model specification, avoiding the tedious and error prone task of manually enumerating all species and reactions that can potentially exist in a system. From a simulation perspective, rule-based models can be expanded algorithmically into fully-enumerated reaction networks and simulated using a variety of network-based simulation methods, such as ordinary differential equations or Gillespie's algorithm, provided that the network is not exceedingly large. Alternatively, rule-based models can be simulated directly using particle-based kinetic Monte Carlo methods. This "network-free" approach produces exact stochastic trajectories with a computational cost that is independent of network size. However, memory and run time costs increase with the number of particles, limiting the size of system that can be feasibly simulated. Here, we present a hybrid particle/population simulation method that combines the best attributes of both the network-based and network-free approaches. The method takes as input a rule-based model and a user-specified subset of species to treat as population variables rather than as particles. The model is then transformed by a process of "partial network expansion" into a dynamically equivalent form that can be simulated using a population-adapted network-free simulator. The transformation method has been implemented within the open-source rule-based modeling platform BioNetGen, and resulting hybrid models can be simulated using the particle-based simulator NFsim. Performance tests show that significant memory savings
Thermal evolution of hybrid stars within the framework of a nonlocal Nambu-Jona-Lasinio model
NASA Astrophysics Data System (ADS)
de Carvalho, S. M.; Negreiros, R.; Orsaria, M.; Contrera, G. A.; Weber, F.; Spinella, W.
2015-09-01
We study the thermal evolution of neutron stars containing deconfined quark matter in their core. Such objects are generally referred to as quark-hybrid stars. The confined hadronic matter in their core is described in the framework of nonlinear relativistic nuclear field theory. For the quark phase we use a nonlocal extension of the SU(3) Nambu-Jona-Lasinio model with vector interactions. The Gibbs condition is used to model phase equilibrium between confined hadronic matter and deconfined quark matter. Our study indicates that high-mass neutron stars may contain between 35 and 40% deconfined quark-hybrid matter in their cores. Neutron stars with canonical masses of around 1.4 M⊙ would not contain deconfined quark matter. The central proton fractions of the stars are found to be high, enabling them to cool rapidly. Very good agreement with the temperature evolution established for the neutron star in Cassiopeia A (Cas A) is obtained for one of our models (based on the popular NL3 nuclear parametrization), if the protons in the core of our stellar models are strongly paired, the repulsion among the quarks is mildly repulsive, and the mass of Cas A has a canonical value of 1.4 M⊙ .
Multistep-Ahead Air Passengers Traffic Prediction with Hybrid ARIMA-SVMs Models
Ming, Wei; Xiong, Tao
2014-01-01
The hybrid ARIMA-SVMs prediction models have been established recently, which take advantage of the unique strength of ARIMA and SVMs models in linear and nonlinear modeling, respectively. Built upon this hybrid ARIMA-SVMs models alike, this study goes further to extend them into the case of multistep-ahead prediction for air passengers traffic with the two most commonly used multistep-ahead prediction strategies, that is, iterated strategy and direct strategy. Additionally, the effectiveness of data preprocessing approaches, such as deseasonalization and detrending, is investigated and proofed along with the two strategies. Real data sets including four selected airlines' monthly series were collected to justify the effectiveness of the proposed approach. Empirical results demonstrate that the direct strategy performs better than iterative one in long term prediction case while iterative one performs better in the case of short term prediction. Furthermore, both deseasonalization and detrending can significantly improve the prediction accuracy for both strategies, indicating the necessity of data preprocessing. As such, this study contributes as a full reference to the planners from air transportation industries on how to tackle multistep-ahead prediction tasks in the implementation of either prediction strategy. PMID:24723814
Fuzzy-logic modeling of land suitability for hybrid poplar across the Prairie Provinces of Canada.
Joss, B N; Hall, R J; Sidders, D M; Keddy, T J
2008-06-01
Determining the feasibility of a large-scale afforestation program is one approach being investigated by the Government of Canada to increase Canada's potential to sequester carbon from the atmosphere. Large-scale afforestation, however, requires knowledge of where it is suitable to establish and grow trees. Spatial models based on Boolean logic and/or statistical models within a geographic information system may be used for this purpose, but empirical environmental data are often lacking, and the association of these data to land suitability is most often a subjective process. As a solution to this problem, this paper presents a fuzzy-logic modeling approach to assess land suitability for afforestation of hybrid poplar (Populus spp.) over the Prairie Provinces of Canada. Expert knowledge regarding the selection and magnitudes of environmental variables were integrated into fuzzy rule sets from which estimates of land suitability were generated and presented in map form. The environmental variables selected included growing season precipitation, climate moisture index, growing degree days, and Canada Land Inventory capability for agriculture and elevation. Approximately 150,000 km2, or 28% of the eligible land base within the Prairie Provinces was found to be suitable for afforestation. Accuracy assessments conducted with fuzzy accuracy methods provided a more descriptive assessment of the resulting land suitability map than figures generated from a more conventional Boolean-based accuracy measure. Modeling, mapping and accuracy assessment issues were identified for future extension of this work to map hybrid poplar land suitability over Canada.
Modeling wall effects in a micro-scale shock tube using hybrid MD-DSMC algorithm
NASA Astrophysics Data System (ADS)
Watvisave, D. S.; Puranik, B. P.; Bhandarkar, U. V.
2016-07-01
Wall effects in a micro-scale shock tube are investigated using the Direct Simulation Monte Carlo method as well as a hybrid Molecular Dynamics-Direct Simulation Monte Carlo algorithm. In the Direct Simulation Monte Carlo simulations, the Cercignani-Lampis-Lord model of gas-surface interactions is employed to incorporate the wall effects, and it is shown that the shock attenuation is significantly affected by the choice of the values of tangential momentum accommodation coefficient. A loosely coupled Molecular Dynamics-Direct Simulation Monte Carlo approach is then employed to demonstrate incomplete accommodation in micro-scale shock tube flows. This approach uses fixed values of the accommodation coefficients in the gas-surface interaction model, with their values determined from a separate dynamically similar Molecular Dynamics simulation. Finally, a completely coupled Molecular Dynamics-Direct Simulation Monte Carlo algorithm is used, wherein the bulk of the flow is modeled using Direct Simulation Monte Carlo, while the interaction of gas molecules with the shock tube walls is modeled using Molecular Dynamics. The two regions are separate and coupled both ways using buffer zones and a bootstrap coupling algorithm that accounts for the mismatch of the number of molecules in both regions. It is shown that the hybrid method captures the effect of local properties that cannot be captured using a single value of accommodation coefficient for the entire domain.
Tikare, Veena; Hernandez-Rivera, Efrain; Madison, Jonathan D.; Holm, Elizabeth Ann; Patterson, Burton R.; Homer, Eric R.
2013-09-01
Most materials microstructural evolution processes progress with multiple processes occurring simultaneously. In this work, we have concentrated on the processes that are active in nuclear materials, in particular, nuclear fuels. These processes are coarsening, nucleation, differential diffusion, phase transformation, radiation-induced defect formation and swelling, often with temperature gradients present. All these couple and contribute to evolution that is unique to nuclear fuels and materials. Hybrid model that combines elements from the Potts Monte Carlo, phase-field models and others have been developed to address these multiple physical processes. These models are described and applied to several processes in this report. An important feature of the models developed are that they are coded as applications within SPPARKS, a Sandiadeveloped framework for simulation at the mesoscale of microstructural evolution processes by kinetic Monte Carlo methods. This makes these codes readily accessible and adaptable for future applications.
Improving offline handwritten text recognition with hybrid HMM/ANN models.
España-Boquera, Salvador; Castro-Bleda, Maria Jose; Gorbe-Moya, Jorge; Zamora-Martinez, Francisco
2011-04-01
This paper proposes the use of hybrid Hidden Markov Model (HMM)/Artificial Neural Network (ANN) models for recognizing unconstrained offline handwritten texts. The structural part of the optical models has been modeled with Markov chains, and a Multilayer Perceptron is used to estimate the emission probabilities. This paper also presents new techniques to remove slope and slant from handwritten text and to normalize the size of text images with supervised learning methods. Slope correction and size normalization are achieved by classifying local extrema of text contours with Multilayer Perceptrons. Slant is also removed in a nonuniform way by using Artificial Neural Networks. Experiments have been conducted on offline handwritten text lines from the IAM database, and the recognition rates achieved, in comparison to the ones reported in the literature, are among the best for the same task.
An Investigation of a Hybrid Mixing Model for PDF Simulations of Turbulent Premixed Flames
NASA Astrophysics Data System (ADS)
Zhou, Hua; Li, Shan; Wang, Hu; Ren, Zhuyin
2015-11-01
Predictive simulations of turbulent premixed flames over a wide range of Damköhler numbers in the framework of Probability Density Function (PDF) method still remain challenging due to the deficiency in current micro-mixing models. In this work, a hybrid micro-mixing model, valid in both the flamelet regime and broken reaction zone regime, is proposed. A priori testing of this model is first performed by examining the conditional scalar dissipation rate and conditional scalar diffusion in a 3-D direct numerical simulation dataset of a temporally evolving turbulent slot jet flame of lean premixed H2-air in the thin reaction zone regime. Then, this new model is applied to PDF simulations of the Piloted Premixed Jet Burner (PPJB) flames, which are a set of highly shear turbulent premixed flames and feature strong turbulence-chemistry interaction at high Reynolds and Karlovitz numbers. Supported by NSFC 51476087 and NSFC 91441202.
NASA Technical Reports Server (NTRS)
Tamma, Kumar K.; Railkar, Sudhir B.
1988-01-01
The present paper describes the applicability of hybrid transfinite element modeling/analysis formulations for nonlinear heat conduction problems involving phase change. The methodology is based on application of transform approaches and classical Galerkin schemes with finite element formulations to maintain the modeling versatility and numerical features for computational analysis. In addition, in conjunction with the above, the effects due to latent heat are modeled using enthalpy formulations to enable a physically realistic approximation to be dealt computationally for materials exhibiting phase change within a narrow band of temperatures. Pertinent details of the approach and computational scheme adapted are described in technical detail. Numerical test cases of comparative nature are presented to demonstrate the applicability of the proposed formulations for numerical modeling/analysis of nonlinear heat conduction problems involving phase change.
Modeling is a useful tool for quantifying ecosystem services and understanding their temporal dynamics. Here we describe a hybrid regional modeling approach for sub-basins of the Calapooia watershed that incorporates both a precipitation-runoff model and an indexed regression mo...
Jason D. Hales; Veena Tikare
2014-04-01
The Used Fuel Disposition (UFD) program has initiated a project to develop a hydride formation modeling tool using a hybrid Pottsphase field approach. The Potts model is incorporated in the SPPARKS code from Sandia National Laboratories. The phase field model is provided through MARMOT from Idaho National Laboratory.
NASA Astrophysics Data System (ADS)
Enayatifar, Rasul; Sadaei, Hossein Javedani; Abdullah, Abdul Hanan; Lee, Malrey; Isnin, Ismail Fauzi
2015-08-01
Currently, there are many studies have conducted on developing security of the digital image in order to protect such data while they are sending on the internet. This work aims to propose a new approach based on a hybrid model of the Tinkerbell chaotic map, deoxyribonucleic acid (DNA) and cellular automata (CA). DNA rules, DNA sequence XOR operator and CA rules are used simultaneously to encrypt the plain-image pixels. To determine rule number in DNA sequence and also CA, a 2-dimension Tinkerbell chaotic map is employed. Experimental results and computer simulations, both confirm that the proposed scheme not only demonstrates outstanding encryption, but also resists various typical attacks.
Chiral bag plus skyrmion hybrid model with vector mesons for nucleon
NASA Astrophysics Data System (ADS)
Takashita, H.; Yoro, S.; Toki, H.
1988-08-01
The chiral bag plus skyrmion hybrid model (CSH) is extended to include the vector mesons (ω and ϱ mesons) following the hidden local symmetry prescription for nucleon. The hedgehog ansatz is taken for π, ω and ϱ meson fields and the coupled differential equations for quarks and mesons are solved numerically. It is found that the magnitude of the rho-meson field drops suddenly at R ≈ 0.2 fm as the bag radius increases. The hedgehog masses and the axial coupling gA are calculated as a function of the bag radius. It is found that gA behaves non-monotonically with the bag radius.
Model-Invariant Hybrid LES-RANS Computation of Separated Flow Past Periodic Hills
NASA Technical Reports Server (NTRS)
Woodruff, Stephen
2014-01-01
The requirement that physical quantities not vary with a hybrid LESRANS model's blending parameter imposes conditions on the computation that lead to better results across LES-RANS transitions. This promises to allow placement of those transitions so that LES is performed only where required by the physics, improving computational efficiency. The approach is applied to separated flow past periodic hills, where good predictions of separation-bubble size are seen due to the gradual, controlled, LES-RANS transition and the resulting enhanced near-wall eddy viscosity.
Asymmetric magnetic reconnection with out-of-plane shear flows in a two dimensional hybrid model
Wang, Lin; Wang, Xiao-Gang; Wang, Xian-Qu; Liu, Yue
2015-05-15
Effects of out-of-plane shear flows on asymmetric magnetic reconnect are investigated in a two-dimensional (2D) hybrid model with an initial Harris sheet equilibrium. It is found that the out-of-plane flow with an in-plane shear can significantly change the asymmetric reconnection process as well as the related geometry. The magnetic flux, out-of-plane magnetic field, in-plane flow vorticity, plasma density, and the reconnection rate are discussed in detail. The results are in comparison with the cases without the shear flows to further understand the effect.
Bourgeois, Isabelle; Hart, Rebecca E; Townsend, Shannon H; Gagné, Marc
2011-08-01
The ongoing need for public sector organizations to enhance their internal evaluation capacity is increasingly resulting in the use of hybrid evaluation project models, where internal evaluators work with external contracted evaluators to complete evaluative work. This paper first seeks to identify what is currently known about internal evaluation through a synthesis of the literature in this area. It then presents a case narrative illustrating how internal and external evaluation approaches may be used together to strengthen an evaluation project and to develop the evaluation capacity of the organization. Lessons learned include the need to integrate internal and external resources throughout the evaluation and to clarify expectations at the outset of the project.
A hybrid model for simulating rogue waves in random seas on a large temporal and spatial scale
NASA Astrophysics Data System (ADS)
Wang, Jinghua; Ma, Q. W.; Yan, S.
2016-05-01
A hybrid model for simulating rogue waves in random seas on a large temporal and spatial scale is proposed in this paper. It is formed by combining the derived fifth order Enhanced Nonlinear Schrödinger Equation based on Fourier transform, the Enhanced Spectral Boundary Integral (ESBI) method and its simplified version. The numerical techniques and algorithm for coupling three models on time scale are suggested. Using the algorithm, the switch between the three models during the computation is triggered automatically according to wave nonlinearities. Numerical tests are carried out and the results indicate that this hybrid model could simulate rogue waves both accurately and efficiently. In some cases discussed, the hybrid model is more than 10 times faster than just using the ESBI method, and it is also much faster than other methods reported in the literature.
Eylenceoğlu, E.; Rafatov, I.; Kudryavtsev, A. A.
2015-01-15
Two-dimensional hybrid Monte Carlo–fluid numerical code is developed and applied to model the dc glow discharge. The model is based on the separation of electrons into two parts: the low energetic (slow) and high energetic (fast) electron groups. Ions and slow electrons are described within the fluid model using the drift-diffusion approximation for particle fluxes. Fast electrons, represented by suitable number of super particles emitted from the cathode, are responsible for ionization processes in the discharge volume, which are simulated by the Monte Carlo collision method. Electrostatic field is obtained from the solution of Poisson equation. The test calculations were carried out for an argon plasma. Main properties of the glow discharge are considered. Current-voltage curves, electric field reversal phenomenon, and the vortex current formation are developed and discussed. The results are compared to those obtained from the simple and extended fluid models. Contrary to reports in the literature, the analysis does not reveal significant advantages of existing hybrid methods over the extended fluid model.
Modeling of hybridized infrared arrays for characterization of interpixel capacitive coupling
NASA Astrophysics Data System (ADS)
Donlon, Kevan; Ninkov, Zoran; Baum, Stefi; Cheng, Linpeng
2017-02-01
Interpixel capacitance (IPC) is a deterministic electronic coupling resulting in a portion of signal incident on one pixel of a hybridized detector array being measured in adjacent pixels. Data collected by light sensitive HgCdTe arrays that exhibit this coupling typically goes uncorrected or is corrected by treating the coupling as a fixed point spread function. Evidence suggests that this coupling is not uniform across signal and background levels. Subarrays of pixels using design parameters based upon HgCdTe indium hybridized arrays akin to those contained in the James Webb Space Telescope's NIRcam have been modeled from first principles using Lumerical DEVICE Software. This software simultaneously solves Poisson's equation and the drift diffusion equations yielding charge distributions and electric fields. Modeling of this sort generates the local point spread function across a range of detector parameters. This results in predictive characterization of IPC across scene and device parameters that would permit proper photometric correction and signal restoration to the data. Additionally, the ability to visualize potential distributions and couplings as generated by the models yields insight that can be used to minimize IPC coupling in the design of future detectors.
Effective-mass model and magneto-optical properties in hybrid perovskites
Yu, Z. G.
2016-01-01
Hybrid inorganic-organic perovskites have proven to be a revolutionary material for low-cost photovoltaic applications. They also exhibit many other interesting properties, including giant Rashba splitting, large-radius Wannier excitons, and novel magneto-optical effects. Understanding these properties as well as the detailed mechanism of photovoltaics requires a reliable and accessible electronic structure, on which models of transport, excitonic, and magneto-optical properties can be efficiently developed. Here we construct an effective-mass model for the hybrid perovskites based on the group theory, experiment, and first-principles calculations. Using this model, we relate the Rashba splitting with the inversion-asymmetry parameter in the tetragonal perovskites, evaluate anisotropic g-factors for both conduction and valence bands, and elucidate the magnetic-field effect on photoluminescence and its dependence on the intensity of photoexcitation. The diamagnetic effect of exciton is calculated for an arbitrarily strong magnetic field. The pronounced excitonic peak emerged at intermediate magnetic fields in cyclotron resonance is assigned to the 3D±2 states, whose splitting can be used to estimate the difference in the effective masses of electron and hole. PMID:27338834
de Jong, Tom J; Hesse, Elze
2012-06-01
Pollen of the crop oilseed rape (Brassica napus, AACC) can cross-fertilize ovules of Brassica rapa (AA), which leads to an influx of unpaired C-chromosomes into wild B. rapa populations. The presence of such extra chromosomes is thought to be an indicator of introgression. Backcrosses and F(1) hybrids were found in Danish populations but, surprisingly, only F(1) hybrids were found in the UK and the Netherlands. Here, a model tests how the level of selection and biased vs unbiased transmission affect the population frequency of C-chromosomes. In the biased-transmission scenario the experimental results of the first backcross are extrapolated to estimate survival of gametes with different numbers of C-chromosomes from all crosses in the population. With biased transmission, the frequency of C-chromosomes always rapidly declines to zero. With unbiased transmission, the continued presence of plants with extra C-chromosomes depends on selection in the adult stage and we argue that this is the most realistic option for modeling populations. We suggest that selection in the field against plants with unpaired C-chromosomes is strong in Dutch and UK populations. The model highlights what we do not know and makes suggestions for further research on introgression.
High performance hybrid functional Petri net simulations of biological pathway models on CUDA.
Chalkidis, Georgios; Nagasaki, Masao; Miyano, Satoru
2011-01-01
Hybrid functional Petri nets are a wide-spread tool for representing and simulating biological models. Due to their potential of providing virtual drug testing environments, biological simulations have a growing impact on pharmaceutical research. Continuous research advancements in biology and medicine lead to exponentially increasing simulation times, thus raising the demand for performance accelerations by efficient and inexpensive parallel computation solutions. Recent developments in the field of general-purpose computation on graphics processing units (GPGPU) enabled the scientific community to port a variety of compute intensive algorithms onto the graphics processing unit (GPU). This work presents the first scheme for mapping biological hybrid functional Petri net models, which can handle both discrete and continuous entities, onto compute unified device architecture (CUDA) enabled GPUs. GPU accelerated simulations are observed to run up to 18 times faster than sequential implementations. Simulating the cell boundary formation by Delta-Notch signaling on a CUDA enabled GPU results in a speedup of approximately 7x for a model containing 1,600 cells.
NASA Astrophysics Data System (ADS)
Sun, Hao; Wang, Cheng; Wang, Boliang
2011-02-01
We present a hybrid generative-discriminative learning method for human action recognition from video sequences. Our model combines a bag-of-words component with supervised latent topic models. A video sequence is represented as a collection of spatiotemporal words by extracting space-time interest points and describing these points using both shape and motion cues. The supervised latent Dirichlet allocation (sLDA) topic model, which employs discriminative learning using labeled data under a generative framework, is introduced to discover the latent topic structure that is most relevant to action categorization. The proposed algorithm retains most of the desirable properties of generative learning while increasing the classification performance though a discriminative setting. It has also been extended to exploit both labeled data and unlabeled data to learn human actions under a unified framework. We test our algorithm on three challenging data sets: the KTH human motion data set, the Weizmann human action data set, and a ballet data set. Our results are either comparable to or significantly better than previously published results on these data sets and reflect the promise of hybrid generative-discriminative learning approaches.
Effective-mass model and magneto-optical properties in hybrid perovskites
NASA Astrophysics Data System (ADS)
Yu, Z. G.
2016-06-01
Hybrid inorganic-organic perovskites have proven to be a revolutionary material for low-cost photovoltaic applications. They also exhibit many other interesting properties, including giant Rashba splitting, large-radius Wannier excitons, and novel magneto-optical effects. Understanding these properties as well as the detailed mechanism of photovoltaics requires a reliable and accessible electronic structure, on which models of transport, excitonic, and magneto-optical properties can be efficiently developed. Here we construct an effective-mass model for the hybrid perovskites based on the group theory, experiment, and first-principles calculations. Using this model, we relate the Rashba splitting with the inversion-asymmetry parameter in the tetragonal perovskites, evaluate anisotropic g-factors for both conduction and valence bands, and elucidate the magnetic-field effect on photoluminescence and its dependence on the intensity of photoexcitation. The diamagnetic effect of exciton is calculated for an arbitrarily strong magnetic field. The pronounced excitonic peak emerged at intermediate magnetic fields in cyclotron resonance is assigned to the 3D±2 states, whose splitting can be used to estimate the difference in the effective masses of electron and hole.
Effective-mass model and magneto-optical properties in hybrid perovskites.
Yu, Z G
2016-06-24
Hybrid inorganic-organic perovskites have proven to be a revolutionary material for low-cost photovoltaic applications. They also exhibit many other interesting properties, including giant Rashba splitting, large-radius Wannier excitons, and novel magneto-optical effects. Understanding these properties as well as the detailed mechanism of photovoltaics requires a reliable and accessible electronic structure, on which models of transport, excitonic, and magneto-optical properties can be efficiently developed. Here we construct an effective-mass model for the hybrid perovskites based on the group theory, experiment, and first-principles calculations. Using this model, we relate the Rashba splitting with the inversion-asymmetry parameter in the tetragonal perovskites, evaluate anisotropic g-factors for both conduction and valence bands, and elucidate the magnetic-field effect on photoluminescence and its dependence on the intensity of photoexcitation. The diamagnetic effect of exciton is calculated for an arbitrarily strong magnetic field. The pronounced excitonic peak emerged at intermediate magnetic fields in cyclotron resonance is assigned to the 3D±2 states, whose splitting can be used to estimate the difference in the effective masses of electron and hole.
Hybrid LCA model for assessing the embodied environmental impacts of buildings in South Korea
Jang, Minho; Hong, Taehoon; Ji, Changyoon
2015-01-15
The assessment of the embodied environmental impacts of buildings can help decision-makers plan environment-friendly buildings and reduce environmental impacts. For a more comprehensive assessment of the embodied environmental impacts of buildings, a hybrid life cycle assessment model was developed in this study. The developed model can assess the embodied environmental impacts (global warming, ozone layer depletion, acidification, eutrophication, photochemical ozone creation, abiotic depletion, and human toxicity) generated directly and indirectly in the material manufacturing, transportation, and construction phases. To demonstrate the application and validity of the developed model, the environmental impacts of an elementary school building were assessed using the developed model and compared with the results of a previous model used in a case study. The embodied environmental impacts from the previous model were lower than those from the developed model by 4.6–25.2%. Particularly, human toxicity potential (13 kg C{sub 6}H{sub 6} eq.) calculated by the previous model was much lower (1965 kg C{sub 6}H{sub 6} eq.) than what was calculated by the developed model. The results indicated that the developed model can quantify the embodied environmental impacts of buildings more comprehensively, and can be used by decision-makers as a tool for selecting environment-friendly buildings. - Highlights: • The model was developed to assess the embodied environmental impacts of buildings. • The model evaluates GWP, ODP, AP, EP, POCP, ADP, and HTP as environmental impacts. • The model presents more comprehensive results than the previous model by 4.6–100%. • The model can present the HTP of buildings, which the previous models cannot do. • Decision-makers can use the model for selecting environment-friendly buildings.
Hybrid wavelet-support vector machine approach for modelling rainfall-runoff process.
Komasi, Mehdi; Sharghi, Soroush
2016-01-01
Because of the importance of water resources management, the need for accurate modeling of the rainfall-runoff process has rapidly grown in the past decades. Recently, the support vector machine (SVM) approach has been used by hydrologists for rainfall-runoff modeling and the other fields of hydrology. Similar to the other artificial intelligence models, such as artificial neural network (ANN) and adaptive neural fuzzy inference system, the SVM model is based on the autoregressive properties. In this paper, the wavelet analysis was linked to the SVM model concept for modeling the rainfall-runoff process of Aghchai and Eel River watersheds. In this way, the main time series of two variables, rainfall and runoff, were decomposed to multiple frequent time series by wavelet theory; then, these time series were imposed as input data on the SVM model in order to predict the runoff discharge one day ahead. The obtained results show that the wavelet SVM model can predict both short- and long-term runoff discharges by considering the seasonality effects. Also, the proposed hybrid model is relatively more appropriate than classical autoregressive ones such as ANN and SVM because it uses the multi-scale time series of rainfall and runoff data in the modeling process.
A Hybrid Windkessel Model of Blood Flow in Arterial Tree Using Velocity Profile Method
NASA Astrophysics Data System (ADS)
Aboelkassem, Yasser; Virag, Zdravko
2016-11-01
For the study of pulsatile blood flow in the arterial system, we derived a coupled Windkessel-Womersley mathematical model. Initially, a 6-elements Windkessel model is proposed to describe the hemodynamics transport in terms of constant resistance, inductance and capacitance. This model can be seen as a two compartment model, in which the compartments are connected by a rigid pipe, modeled by one inductor and resistor. The first viscoelastic compartment models proximal part of the aorta, the second elastic compartment represents the rest of the arterial tree and aorta can be seen as the connection pipe. Although the proposed 6-elements lumped model was able to accurately reconstruct the aortic pressure, it can't be used to predict the axial velocity distribution in the aorta and the wall shear stress and consequently, proper time varying pressure drop. We then modified this lumped model by replacing the connection pipe circuit elements with a vessel having a radius R and a length L. The pulsatile flow motions in the vessel are resolved instantaneously along with the Windkessel like model enable not only accurate prediction of the aortic pressure but also wall shear stress and frictional pressure drop. The proposed hybrid model has been validated using several in-vivo aortic pressure and flow rate data acquired from different species such as, humans, dogs and pigs. The method accurately predicts the time variation of wall shear stress and frictional pressure drop. Institute for Computational Medicine, Dept. Biomedical Engineering.
Flow-radiation coupling for atmospheric entries using a Hybrid Statistical Narrow Band model
NASA Astrophysics Data System (ADS)
Soucasse, Laurent; Scoggins, James B.; Rivière, Philippe; Magin, Thierry E.; Soufiani, Anouar
2016-09-01
In this study, a Hybrid Statistical Narrow Band (HSNB) model is implemented to make fast and accurate predictions of radiative transfer effects on hypersonic entry flows. The HSNB model combines a Statistical Narrow Band (SNB) model for optically thick molecular systems, a box model for optically thin molecular systems and continua, and a Line-By-Line (LBL) description of atomic radiation. Radiative transfer calculations are coupled to a 1D stagnation-line flow model under thermal and chemical nonequilibrium. Earth entry conditions corresponding to the FIRE 2 experiment, as well as Titan entry conditions corresponding to the Huygens probe, are considered in this work. Thermal nonequilibrium is described by a two temperature model, although non-Boltzmann distributions of electronic levels provided by a Quasi-Steady State model are also considered for radiative transfer. For all the studied configurations, radiative transfer effects on the flow, the plasma chemistry and the total heat flux at the wall are analyzed in detail. The HSNB model is shown to reproduce LBL results with an accuracy better than 5% and a speed up of the computational time around two orders of magnitude. Concerning molecular radiation, the HSNB model provides a significant improvement in accuracy compared to the Smeared-Rotational-Band model, especially for Titan entries dominated by optically thick CN radiation.
Hybrid Mathematical Model of Cardiomyocyte Turnover in the Adult Human Heart
Elser, Jeremy A.; Margulies, Kenneth B.
2012-01-01
Rationale The capacity for cardiomyocyte regeneration in the healthy adult human heart is fundamentally relevant for both myocardial homeostasis and cardiomyopathy therapeutics. However, estimates of cardiomyocyte turnover rates conflict greatly, with a study employing C14 pulse-chase methodology concluding 1% annual turnover in youth declining to 0.5% with aging and another using cell population dynamics indicating substantial, age-increasing turnover (4% increasing to 20%). Objective Create a hybrid mathematical model to critically examine rates of cardiomyocyte turnover derived from alternative methodologies. Methods and Results Examined in isolation, the cell population analysis exhibited severe sensitivity to a stem cell expansion exponent (20% variation causing 2-fold turnover change) and apoptosis rate. Similarly, the pulse-chase model was acutely sensitive to assumptions of instantaneous incorporation of atmospheric C14 into the body (4-fold impact on turnover in young subjects) while numerical restrictions precluded otherwise viable solutions. Incorporating considerations of primary variable sensitivity and controversial model assumptions, an unbiased numerical solver identified a scenario of significant, age-increasing turnover (4–6% increasing to 15–22% with age) that was compatible with data from both studies, provided that successive generations of cardiomyocytes experienced higher attrition rates than predecessors. Conclusions Assignment of histologically-observed stem/progenitor cells into discrete regenerative phenotypes in the cell population model strongly influenced turnover dynamics without being directly testable. Alternatively, C14 trafficking assumptions and restrictive models in the pulse-chase model artificially eliminated high-turnover solutions. Nevertheless, discrepancies among recent cell turnover estimates can be explained and reconciled. The hybrid mathematical model provided herein permits further examination of these and
Corresponding-states behavior of SPC/E-based modified (bent and hybrid) water models
NASA Astrophysics Data System (ADS)
Weiss, Volker C.
2017-02-01
The remarkable and sometimes anomalous properties of water can be traced back at the molecular level to the tetrahedral coordination of molecules due to the ability of a water molecule to form four hydrogen bonds to its neighbors; this feature allows for the formation of a network that greatly influences the thermodynamic behavior. Computer simulations are becoming increasingly important for our understanding of water. Molecular models of water, such as SPC/E, are needed for this purpose, and they have proved to capture many important features of real water. Modifications of the SPC/E model have been proposed, some changing the H-O-H angle (bent models) and others increasing the importance of dispersion interactions (hybrid models), to study the structural features that set water apart from other polar fluids and from simple fluids such as argon. Here, we focus on the properties at liquid-vapor equilibrium and study the coexistence curve, the interfacial tension, and the vapor pressure in a corresponding-states approach. In particular, we calculate Guggenheim's ratio for the reduced apparent enthalpy of vaporization and Guldberg's ratio for the reduced normal boiling point. This analysis offers additional insight from a more macroscopic, thermodynamic perspective and augments that which has already been learned at the molecular level from simulations. In the hybrid models, the relative importance of dispersion interactions is increased, which turns the modified water into a Lennard-Jones-like fluid. Consequently, in a corresponding-states framework, the typical behavior of simple fluids, such as argon, is seen to be approached asymptotically. For the bent models, decreasing the bond angle turns the model essentially into a polar diatomic fluid in which the particles form linear molecular arrangements; as a consequence, characteristic features of the corresponding-states behavior of hydrogen halides emerge.
Corresponding-states behavior of SPC/E-based modified (bent and hybrid) water models.
Weiss, Volker C
2017-02-07
The remarkable and sometimes anomalous properties of water can be traced back at the molecular level to the tetrahedral coordination of molecules due to the ability of a water molecule to form four hydrogen bonds to its neighbors; this feature allows for the formation of a network that greatly influences the thermodynamic behavior. Computer simulations are becoming increasingly important for our understanding of water. Molecular models of water, such as SPC/E, are needed for this purpose, and they have proved to capture many important features of real water. Modifications of the SPC/E model have been proposed, some changing the H-O-H angle (bent models) and others increasing the importance of dispersion interactions (hybrid models), to study the structural features that set water apart from other polar fluids and from simple fluids such as argon. Here, we focus on the properties at liquid-vapor equilibrium and study the coexistence curve, the interfacial tension, and the vapor pressure in a corresponding-states approach. In particular, we calculate Guggenheim's ratio for the reduced apparent enthalpy of vaporization and Guldberg's ratio for the reduced normal boiling point. This analysis offers additional insight from a more macroscopic, thermodynamic perspective and augments that which has already been learned at the molecular level from simulations. In the hybrid models, the relative importance of dispersion interactions is increased, which turns the modified water into a Lennard-Jones-like fluid. Consequently, in a corresponding-states framework, the typical behavior of simple fluids, such as argon, is seen to be approached asymptotically. For the bent models, decreasing the bond angle turns the model essentially into a polar diatomic fluid in which the particles form linear molecular arrangements; as a consequence, characteristic features of the corresponding-states behavior of hydrogen halides emerge.
Hybrid fluid/kinetic modeling of Pluto’s escaping atmosphere
NASA Astrophysics Data System (ADS)
Erwin, Justin; Tucker, O. J.; Johnson, Robert E.
2013-09-01
Predicting the rate of escape and thermal structure of Pluto’s upper atmosphere in preparation for the New Horizons Spacecraft encounter in 2015 is important for planning and interpreting the expected measurements. Having a moderate Jeans parameter Pluto’s atmosphere does not fit the classic definition of Jeans escape for light species escaping from the terrestrial planets, nor does it fit the hydrodynamic outflow from comets and certain exoplanets. It has been proposed for some time that Pluto lies in the region of slow hydrodynamic escape. Using a hybrid fluid/molecular-kinetic model, we previously demonstrated the typical implementation of this model fails to correctly describe the appropriate temperature structure for the upper atmosphere for solar minimum conditions. Here we use a time-dependent solver to allow us to extend those simulations to higher heating rates and we examine fluid models in which Jeans-like escape expressions are used for the upper boundary conditions. We compare these to hybrid simulations of the atmosphere under heating conditions roughly representative of solar minimum and mean conditions as these bracket conditions expected during the New Horizon encounter. Although we find escape rates comparable to those previously estimated by the slow hydrodynamic escape model, and roughly consistent with energy limited escape, our model produces a much more extended atmosphere with higher temperatures roughly consistent with recent observations of CO. Such an extended atmosphere will be affected by Charon and will affect Pluto’s interaction with the solar wind at the New Horizon encounter. For the parameter space covered, we also find an inverse relationship between exobase temperature and altitude and the Jeans escape rate that is consistent with the energy limited escape rate. Since we have previously shown that such models can be scaled, these results have implications for modeling exoplanet atmospheres for which the energy limited
NASA Astrophysics Data System (ADS)
van der Swaluw, Eric; de Vries, Wilco; Sauter, Ferd; Aben, Jan; Velders, Guus; van Pul, Addo
2017-04-01
We present high-resolution model results of air pollution and deposition over the Netherlands with three models, the Eulerian grid model LOTOS-EUROS, the Gaussian plume model OPS and the hybrid model LEO. The latter combines results from LOTOS-EUROS and OPS using source apportionment techniques. The hybrid modelling combines the efficiency of calculating at high-resolution around sources with the plume model, and the accuracy of taking into account long-range transport and chemistry with a Eulerian grid model. We compare calculations from all three models with measurements for the period 2009-2011 for ammonia, NOx, secondary inorganic aerosols, particulate matter (PM10) and wet deposition of acidifying and eutrophying components (ammonium, nitrate and sulfate). It is found that concentrations of ammonia, NOx and the wet deposition components are best represented by the Gaussian plume model OPS. Secondary inorganic aerosols are best modelled with the LOTOS-EUROS model, and PM10 is best described with the LEO model. Subsequently for the year 2011, PM10 concentration and reduced nitrogen dry deposition maps are presented with respectively the OPS and LEO model. Using the LEO calculations for the production of the PM10 map, yields an overall better result than using the OPS calculations for this application. This is mainly due to the fact that the spatial distribution of the secondary inorganic aerosols is better described in the LEO model than in OPS, and because more (natural induced) PM10 sources are included in LEO, i.e. the contribution to PM10 of sea-salt and wind-blown dust as calculated by the LOTOS-EUROS model. Finally, dry deposition maps of reduced nitrogen over the Netherlands are compared as calculated by respectively the OPS and LEO model. The differences between both models are overall small (±100 mol/ha) with respect to the peak values observed in the maps (>2000 mol/ha). This is due to the fact that the contribution of dry deposition of reduced
A hybrid model for three-dimensional simulations of sprouting angiogenesis.
Milde, Florian; Bergdorf, Michael; Koumoutsakos, Petros
2008-10-01
Recent advances in cancer research have identified critical angiogenic signaling pathways and the influence of the extracellular matrix on endothelial cell migration. These findings provide us with insight into the process of angiogenesis that can facilitate the development of effective computational models of sprouting angiogenesis. In this work, we present the first three-dimensional model of sprouting angiogenesis that considers explicitly the effect of the extracellular matrix and of the soluble as well as matrix-bound growth factors on capillary growth. The computational model relies on a hybrid particle-mesh representation of the blood vessels and it introduces an implicit representation of the vasculature that can accommodate detailed descriptions of nutrient transport. Extensive parametric studies reveal the role of the extracellular matrix structure and the distribution of the different vascular endothelial growth factors isoforms on the dynamics and the morphology of the generated vascular networks.
A Hybrid Model for Three-Dimensional Simulations of Sprouting Angiogenesis
Milde, Florian; Bergdorf, Michael; Koumoutsakos, Petros
2008-01-01
Recent advances in cancer research have identified critical angiogenic signaling pathways and the influence of the extracellular matrix on endothelial cell migration. These findings provide us with insight into the process of angiogenesis that can facilitate the development of effective computational models of sprouting angiogenesis. In this work, we present the first three-dimensional model of sprouting angiogenesis that considers explicitly the effect of the extracellular matrix and of the soluble as well as matrix-bound growth factors on capillary growth. The computational model relies on a hybrid particle-mesh representation of the blood vessels and it introduces an implicit representation of the vasculature that can accommodate detailed descriptions of nutrient transport. Extensive parametric studies reveal the role of the extracellular matrix structure and the distribution of the different vascular endothelial growth factors isoforms on the dynamics and the morphology of the generated vascular networks. PMID:18586846
First Principles Molecular Modeling of Sensing Material Selection for Hybrid Biomimetic Nanosensors
NASA Astrophysics Data System (ADS)
Blanco, Mario; McAlpine, Michael C.; Heath, James R.
Hybrid biomimetic nanosensors use selective polymeric and biological materials that integrate flexible recognition moieties with nanometer size transducers. These sensors have the potential to offer the building blocks for a universal sensing platform. Their vast range of chemistries and high conformational flexibility present both a problem and an opportunity. Nonetheless, it has been shown that oligopeptide aptamers from sequenced genes can be robust substrates for the selective recognition of specific chemical species. Here we present first principles molecular modeling approaches tailored to peptide sequences suitable for the selective discrimination of small molecules on nanowire arrays. The modeling strategy is fully atomistic. The excellent performance of these sensors, their potential biocompatibility combined with advanced mechanistic modeling studies, could potentially lead to applications such as: unobtrusive implantable medical sensors for disease diagnostics, light weight multi-purpose sensing devices for aerospace applications, ubiquitous environmental monitoring devices in urban and rural areas, and inexpensive smart packaging materials for active in-situ food safety labeling.
Application of a hybrid collisional radiative model to recombining argon plasmas
NASA Astrophysics Data System (ADS)
Benoy, D. A.; van der Mullen, J. A. M.; van de Sanden, M. C. M.; van der Sijde, B.; Schram, D. C.
1993-02-01
A collisional radiative model, in which a hybrid cut-off technique is used, is applied to recombining plasmas to study the atomic state distribution (ASDF) and the recombination coefficient. Computations of the ASDF using semi-empirical rate coefficients of Vriens and Smeets (V-S) and Drawin (D) are compared with experimental values measured at various positions in a free expanding argon arc jet. Apart from the shock position, where the calculated results are too low, the model calculations are higher than the experimental results. The volumetric recombination coefficient has a Te exp -4 and a Te exp -4.8 dependence when semiempirical rate coefficients of, respectively, V-S and D are used. The differences between the models based on the rate coefficients of V-S and D indicate that the recombination flow is sensitive to the low temperature behavior of the rate coefficients.
Supergravity Analysis of Hybrid Inflation Model from D3--D7 System
Koyama, Fumikazu; Tachikawa, Yuji; Watari, Taizan
2003-11-20
The slow-roll inflation is a beautiful paradigm, yet the inflaton potential can hardly be sufficiently flat when unknown gravitational effects are taken into account. However, the hybrid inflation models constructed in D = 4 N = 1 supergravity can be consistent with N = 2 supersymmetry, and can be naturally embedded into string theory. This article discusses the gravitational effects carefully in the string model, using D = 4 supergravity description. We adopt the D3--D7 system of Type IIB string theory compactified on K3 x T^2/Z_2 orientifold for definiteness. It turns out that the slow-roll parameter can be sufficiently small despite the non-minimal Kahler potential of the model. The conditions for this to happen are clarified in terms of string vacua. We also find that the geometry obtained by blowing up singularity, which is necessary for the positive vacuum energy, is stabilized by introducing certain 3-form fluxes.
Hybrid Model for Plasma Thruster Plume Simulation Including PIC-MCC Electrons Treatment
Alexandrov, A. L.; Bondar, Ye. A.; Schweigert, I. V.
2008-12-31
The simulation of stationary plasma thruster plume is important for spacecraft design due to possible interaction plume with spacecraft surface. Such simulations are successfully performed using the particle-in-cell technique for describing the motion of charged particles, namely the propellant ions. In conventional plume models the electrons are treated using various fluid approaches. In this work, we suggest an alternative approach, where the electron kinetics is considered 'ab initio', using the particle-in-cell--Monte Carlo collision method. To avoid the large computational expenses due to small time steps, the relaxation of simulated plume plasma is split into the fast relaxation of the electrons distribution function and the slow one of the ions. The model is self-consistent but hybrid, since the simultaneous electron and ion motion is not really modeled. The obtained electron temperature profile is in good agreement with experiment.
Edwards, Kevin Dean; Wagner, Robert M; Chakravarthy, Veerathu K; Daw, C Stuart; Green Jr, Johney Boyd
2006-01-01
Internal combustion engines are operated under conditions of high exhaust gas recirculation (EGR) to reduce NO x emissions and promote enhanced combustion modes such as HCCI. However, high EGR under certain conditions also promotes nonlinear feedback between cycles, leading to the development of combustion instabilities and cyclic variability. We employ a two-zone phenomenological combustion model to simulate the onset of combustion instabilities under highly dilute conditions and to illustrate the impact of these instabilities on emissions and fuel efficiency. The two-zone in-cylinder combustion model is coupled to a WAVE engine-simulation code through a Simulink interface, allowing rapid simulation of several hundred successive engine cycles with many external engine parametric effects included. We demonstrate how this hybrid model can be used to study strategies for adaptive feedback control to reduce cyclic combustion instabilities and, thus, preserve fuel efficiency and reduce emissions.
A Hybrid EAV-Relational Model for Consistent and Scalable Capture of Clinical Research Data.
Khan, Omar; Lim Choi Keung, Sarah N; Zhao, Lei; Arvanitis, Theodoros N
2014-01-01
Many clinical research databases are built for specific purposes and their design is often guided by the requirements of their particular setting. Not only does this lead to issues of interoperability and reusability between research groups in the wider community but, within the project itself, changes and additions to the system could be implemented using an ad hoc approach, which may make the system difficult to maintain and even more difficult to share. In this paper, we outline a hybrid Entity-Attribute-Value and relational model approach for modelling data, in light of frequently changing requirements, which enables the back-end database schema to remain static, improving the extensibility and scalability of an application. The model also facilitates data reuse. The methods used build on the modular architecture previously introduced in the CURe project.
Ma, Lu; Wang, Guan; Yan, Xuedong; Weng, Jinxian
2016-04-01
Debates on the ordering patterns of crash injury severity are ongoing in the literature. Models without proper econometrical structures for accommodating the complex ordering patterns of injury severity could result in biased estimations and misinterpretations of factors. This study proposes a hybrid finite mixture (HFM) model aiming to capture heterogeneous ordering patterns of driver injury severity while enhancing modeling flexibility. It attempts to probabilistically partition samples into two groups in which one group represents an unordered/nominal data-generating process while the other represents an ordered data-generating process. Conceptually, the newly developed model offers flexible coefficient settings for mining additional information from crash data, and more importantly it allows the coexistence of multiple ordering patterns for the dependent variable. A thorough modeling performance comparison is conducted between the HFM model, and the multinomial logit (MNL), ordered logit (OL), finite mixture multinomial logit (FMMNL) and finite mixture ordered logit (FMOL) models. According to the empirical results, the HFM model presents a strong ability to extract information from the data, and more importantly to uncover heterogeneous ordering relationships between factors and driver injury severity. In addition, the estimated weight parameter associated with the MNL component in the HFM model is greater than the one associated with the OL component, which indicates a larger likelihood of the unordered pattern than the ordered pattern for driver injury severity.
UDEC-AUTODYN Hybrid Modeling of a Large-Scale Underground Explosion Test
NASA Astrophysics Data System (ADS)
Deng, X. F.; Chen, S. G.; Zhu, J. B.; Zhou, Y. X.; Zhao, Z. Y.; Zhao, J.
2015-03-01
In this study, numerical modeling of a large-scale decoupled underground explosion test with 10 tons of TNT in Älvdalen, Sweden is performed by combining DEM and FEM with codes UDEC and AUTODYN. AUTODYN is adopted to model the explosion process, blast wave generation, and its action on the explosion chamber surfaces, while UDEC modeling is focused on shock wave propagation in jointed rock masses surrounding the explosion chamber. The numerical modeling results with the hybrid AUTODYN-UDEC method are compared with empirical estimations, purely AUTODYN modeling results, and the field test data. It is found that in terms of peak particle velocity, empirical estimations are much smaller than the measured data, while purely AUTODYN modeling results are larger than the test data. The UDEC-AUTODYN numerical modeling results agree well with the test data. Therefore, the UDEC-AUTODYN method is appropriate in modeling a large-scale explosive detonation in a closed space and the following wave propagation in jointed rock masses. It should be noted that joint mechanical and spatial properties adopted in UDEC-AUTODYN modeling are determined with empirical equations and available geological data, and they may not be sufficiently accurate.
NASA Astrophysics Data System (ADS)
Rosenbaum, Joyce E.
2011-12-01
Commercial air traffic is anticipated to increase rapidly in the coming years. The impact of aviation noise on communities surrounding airports is, therefore, a growing concern. Accurate prediction of noise can help to mitigate the impact on communities and foster smoother integration of aerospace engineering advances. The problem of accurate sound level prediction requires careful inclusion of all mechanisms that affect propagation, in addition to correct source characterization. Terrain, ground type, meteorological effects, and source directivity can have a substantial influence on the noise level. Because they are difficult to model, these effects are often included only by rough approximation. This dissertation presents a model designed for sound propagation over uneven terrain, with mixed ground type and realistic meteorological conditions. The model is a hybrid of two numerical techniques: the parabolic equation (PE) and fast field program (FFP) methods, which allow for physics-based inclusion of propagation effects and ensure the low frequency content, a factor in community impact, is predicted accurately. Extension of the hybrid model to a pseudo-three-dimensional representation allows it to produce aviation noise contour maps in the standard form. In order for the model to correctly characterize aviation noise sources, a method of representing arbitrary source directivity patterns was developed for the unique form of the parabolic equation starting field. With this advancement, the model can represent broadband, directional moving sound sources, traveling along user-specified paths. This work was prepared for possible use in the research version of the sound propagation module in the Federal Aviation Administration's new standard predictive tool.
Free Energy Landscapes of Alanine Oligopeptides in Rigid-Body and Hybrid Water Models.
Nayar, Divya; Chakravarty, Charusita
2015-08-27
Replica exchange molecular dynamics is used to study the effect of different rigid-body (mTIP3P, TIP4P, SPC/E) and hybrid (H1.56, H3.00) water models on the conformational free energy landscape of the alanine oligopeptides (acAnme and acA5nme), in conjunction with the CHARMM22 force field. The free energy landscape is mapped out as a function of the Ramachandran angles. In addition, various secondary structure metrics, solvation shell properties, and the number of peptide-solvent hydrogen bonds are monitored. Alanine dipeptide is found to have similar free energy landscapes in different solvent models, an insensitivity which may be due to the absence of possibilities for forming i-(i + 4) or i-(i + 3) intrapeptide hydrogen bonds. The pentapeptide, acA5nme, where there are three intrapeptide backbone hydrogen bonds, shows a conformational free energy landscape with a much greater degree of sensitivity to the choice of solvent model, though the three rigid-body water models differ only quantitatively. The pentapeptide prefers nonhelical, non-native PPII and β-sheet populations as the solvent is changed from SPC/E to the less tetrahedral liquid (H1.56) to an LJ-like liquid (H3.00). The pentapeptide conformational order metrics indicate a preference for open, solvent-exposed, non-native structures in hybrid solvent models at all temperatures of study. The possible correlations between the properties of solvent models and secondary structure preferences of alanine oligopeptides are discussed, and the competition between intrapeptide, peptide-solvent, and solvent-solvent hydrogen bonding is shown to be crucial in the relative free energies of different conformers.
"Antelope": a hybrid-logic model checker for branching-time Boolean GRN analysis
2011-01-01
.g., NuSMV) cannot. This additional expressiveness is achieved by employing a logic extending the standard Computation-Tree Logic (CTL) with hybrid-logic operators. Conclusions We illustrate the advantages of Antelope when (a) modeling incomplete networks and environment interaction, (b) exhibiting the set of all states having a given property, and (c) representing Boolean GRN properties with hybrid CTL. PMID:22192526
Animal model for ultraviolet radiation-induced melanoma: platyfish-swordtail hybrid.
Setlow, R B; Woodhead, A D; Grist, E
1989-01-01
Sunlight exposure is strongly indicated as one of the important etiologic agents in human cutaneous malignant melanoma. However, because of the absence of good animal models, it has not been possible to estimate the wavelengths or wavelength regions involved. We have developed a useful animal model from crosses and backcrosses of platyfish (Xiphophorus maculatus) and swordtails (Xiphophorus helleri). Two strains of these fish are susceptible to invasive melanoma induction by exposure to filtered radiation from sunlamps in the wavelength ranges lambda greater than 290 nm and lambda greater than 304 nm. Multiple exposures on 5-20 consecutive days beginning on day 5 after birth or a single exposure of approximately 200 J/(m2.day) of lambda greater than 304 nm result in a tumor prevalence of 20% to 40% at 4 months of age compared with a background rate of 12% in one strain and 2% in another. Exposure of the fish to visible light after UV exposure reduces the prevalence to background. The melanomas are similar in many respects to mammalian melanomas, as judged by light and electron microscopy. The genetics of the crosses determined by others and the high sensitivity of the hybrids to melanoma induction indicate that the UV radiation probably inactivates the one tumor repressor gene (or a small number of tumor repressor genes) in the hybrid fish. The small size of the animals and their high susceptibility to melanoma induction make them ideal for action spectroscopy. Images PMID:2813430
Nandola, Naresh N.; Rivera, Daniel E.
2010-01-01
This paper presents a novel model predictive control (MPC) formulation for linear hybrid systems. The algorithm relies on a multiple-degree-of-freedom formulation that enables the user to adjust the speed of setpoint tracking, measured disturbance rejection and unmeasured disturbance rejection independently in the closed-loop system. Consequently, controller tuning is more flexible and intuitive than relying on move suppression weights as traditionally used in MPC schemes. The formulation is motivated by the need to achieve robust performance in using the algorithm in emerging applications, for instance, as a decision policy for adaptive, time-varying interventions used in behavioral health. The proposed algorithm is demonstrated on a hypothetical adaptive intervention problem inspired by the Fast Track program, a real-life preventive intervention for improving parental function and reducing conduct disorder in at-risk children. Simulation results in the presence of simultaneous disturbances and significant plant-model mismatch are presented. These demonstrate that a hybrid MPC-based approach for this class of interventions can be tuned for desired performance under demanding conditions that resemble participant variability that is experienced in practice when applying an adaptive intervention to a population. PMID:20830213
Thermo-Mechanical Modeling of Laser-Mig Hybrid Welding (lmhw)
NASA Astrophysics Data System (ADS)
Kounde, Ludovic; Engel, Thierry; Bergheau, Jean-Michel; Boisselier, Didier
2011-01-01
Hybrid welding is a combination of two different technologies such as laser (Nd: YAG, CO2…) and electric arc welding (MIG, MAG / TIG …) developed to assemble thick metal sheets (over 3 mm) in order to reduce the required laser power. As a matter of fact, hybrid welding is a lso used in the welding of thin materials to benefit from process, deep penetration and gap limit. But the thermo-mechanical behaviour of thin parts assembled by LMHW technology for railway cars production is far from being controlled the modeling and simulation contribute to the assessment of the causes and effects of the thermo mechanical behaviour in the assembled parts. In order to reproduce the morphology of melted and heat-affected zones, two analytic functions were combined to model the heat source of LMHW. On one hand, we applied a so-called "diaboloïd" (DB) which is a modified hyperboloid, based on experimental parameters and the analysis of the macrographs of the welds. On the other hand, we used a so-called "double ellipsoïd" (DE) which takes the MIG only contribution including the bead into account. The comparison between experimental result and numerical result shows a good agreement.
A finite element modeling of a multifunctional hybrid composite beam with viscoelastic materials
NASA Astrophysics Data System (ADS)
Wang, Ya; Inman, Daniel J.
2013-04-01
The multifunctional hybrid composite structure studied here consists of a ceramic outer layer capable of withstanding high temperatures, a functionally graded ceramic layer combining shape memory alloy (SMA) properties of NiTi together with Ti2AlC (called Graded Ceramic/Metal Composite, or GCMeC), and a high temperature sensor patch, followed by a polymer matrix composite laced with vascular cooling channels all held together with various epoxies. Due to the recoverable nature of SMA and adhesive properties of Ti2AlC, the damping behavior of the GCMeC is largely viscoelastic. This paper presents a finite element formulation for this multifunctional hybrid structure with embedded viscoelastic material. In order to implement the viscoelastic model into the finite element formulation, a second order three parameter Golla-Hughes-McTavish (GHM) method is used to describe the viscoelastic behavior. Considering the parameter identification, a strategy to estimate the fractional order of the time derivative and the relaxation time is outlined. The curve-fitting aspects of both GHM and ADF show good agreement with experimental data obtained from dynamic mechanics analysis. The performance of the finite element of the layered multifunctional beam is verified through experimental model analysis.
Comparison of hybrid three-dimensional modeling with measurements on the continental shelf.
Heaney, Kevin D; Campbell, Richard L; Murray, James J
2012-02-01
During the CALOPS 2007 experiment, off the coast of Fort Lauderdale, Florida, three-dimensional (3D) multipath was observed using a bottom mounted horizontal line array during source tows along the 200 m isobath [Kevin D. Heaney and James J. Murray, J. Acoust. Soc. Am. 125(4), 1394-1402 (2008)]. In this paper a hybrid modeling approach is presented to model the 3D sound on the Florida shelf, nearly shaped like the canonical wedge. The hybrid approach combines vertical acoustic normal modes with the parabolic equation solution (in range/cross-range). The approach is shown to satisfy the 3D Cartesian-coordinate wave equation in the limit of adiabatic mode propagation. In the adiabatic mode parabolic equation (AMPE) approach modal phase speeds vs position are used as the input to the parabolic equation computation with dimensions of easting (km) and northing (km). Vertical adiabatic modes and horizontal rays are also computed to illustrate the 3D multipath arrival. The AMPE field is computed for all the modes for each element of the horizontal array. Beamforming vs source range is then conducted and excellent agreement with data is achieved.
Development of a hybrid wave based-transfer matrix model for sound transmission analysis.
Dijckmans, A; Vermeir, G
2013-04-01
In this paper, a hybrid wave based-transfer matrix model is presented that allows for the investigation of the sound transmission through finite multilayered structures placed between two reverberant rooms. The multilayered structure may consist of an arbitrary configuration of fluid, elastic, or poro-elastic layers. The field variables (structural displacements and sound pressures) are expanded in terms of structural and acoustic wave functions. The boundary and continuity conditions in the rooms determine the participation factors in the pressure expansions. The displacement of the multilayered structure is determined by the mechanical impedance matrix, which gives a relation between the pressures and transverse displacements at both sides of the structure. The elements of this matrix are calculated with the transfer matrix method. First, the hybrid model is numerically validated. Next a comparison is made with sound transmission loss measurements of a hollow brick wall and a sandwich panel. Finally, numerical simulations show the influence of structural damping, room dimensions and plate dimensions on the sound transmission loss of multilayered structures.
A hybrid model for the neural representation of complex mental processing in the human brain.
Fehr, Thorsten
2013-04-01
In the present conceptual review several theoretical and empirical sources of information were integrated, and a hybrid model of the neural representation of complex mental processing in the human brain was proposed. Based on empirical evidence for strategy-related and inter-individually different task-related brain activation networks, and further based on empirical evidence for a remarkable overlap of fronto-parietal activation networks across different complex mental processes, it was concluded by the author that there might be innate and modular organized neuro-developmental starting regions, for example, in intra-parietal, and both medial and middle frontal brain regions, from which the neural organization of different kinds of complex mental processes emerge differently during individually shaped learning histories. Thus, the here proposed model provides a hybrid of both massive modular and holistic concepts of idiosyncratic brain physiological elaboration of complex mental processing. It is further concluded that 3-D information, obtained by respective methodological approaches, are not appropriate to identify the non-linear spatio-temporal dynamics of complex mental process-related brain activity in a sufficient way. How different participating network parts communicate with each other seems to be an indispensable aspect, which has to be considered in particular to improve our understanding of the neural organization of complex cognition.
A formally verified algorithm for interactive consistency under a hybrid fault model
NASA Technical Reports Server (NTRS)
Lincoln, Patrick; Rushby, John
1993-01-01
Consistent distribution of single-source data to replicated computing channels is a fundamental problem in fault-tolerant system design. The 'Oral Messages' (OM) algorithm solves this problem of Interactive Consistency (Byzantine Agreement) assuming that all faults are worst-cass. Thambidurai and Park introduced a 'hybrid' fault model that distinguished three fault modes: asymmetric (Byzantine), symmetric, and benign; they also exhibited, along with an informal 'proof of correctness', a modified version of OM. Unfortunately, their algorithm is flawed. The discipline of mechanically checked formal verification eventually enabled us to develop a correct algorithm for Interactive Consistency under the hybrid fault model. This algorithm withstands $a$ asymmetric, $s$ symmetric, and $b$ benign faults simultaneously, using $m+1$ rounds, provided $n is greater than 2a + 2s + b + m$, and $m\\geg a$. We present this algorithm, discuss its subtle points, and describe its formal specification and verification in PVS. We argue that formal verification systems such as PVS are now sufficiently effective that their application to fault-tolerance algorithms should be considered routine.
Two hybrid Artificial Intelligence approaches for modeling rainfall-runoff process
NASA Astrophysics Data System (ADS)
Nourani, Vahid; Kisi, Özgür; Komasi, Mehdi
2011-05-01
SummaryThe need for accurate modeling of the rainfall-runoff process has grown rapidly in the past decades. However, considering the high stochastic property of the process, many models are still being developed in order to define such a complex phenomenon. Recently, Artificial Intelligence (AI) techniques such as the Artificial Neural Network (ANN) and the Adaptive Neural-Fuzzy Inference System (ANFIS) have been extensively used by hydrologists for rainfall-runoff modeling as well as for other fields of hydrology. In this paper, two hybrid AI-based models which are reliable in capturing the periodicity features of the process are introduced for watershed rainfall-runoff modeling. In the first model, the SARIMAX (Seasonal Auto Regressive Integrated Moving Average with exogenous input)-ANN model, an ANN is used to find the non-linear relationship among the residuals of the fitted linear SARIMAX model. In the second model, the wavelet-ANFIS model, wavelet transform is linked to the ANFIS concept and the main time series of two variables (rainfall and runoff) are decomposed into some multi-frequency time series by wavelet transform. Afterwards, these time series are imposed as input data to the ANFIS to predict the runoff discharge one time step ahead. The obtained results of the models applications for the rainfall-runoff modeling of two watersheds (located in Azerbaijan, Iran) show that, although the proposed models can predict both short and long terms runoff discharges by considering seasonality effects, the second model is relatively more appropriate because it uses the multi-scale time series of rainfall and runoff data in the ANFIS input layer.
Establishment of a hybrid rainfall-runoff model for use in the Noah LSM
NASA Astrophysics Data System (ADS)
Xu, Jingwen; Zhang, Wanchang; Zheng, Ziyan; Chen, Jing; Jiao, Meiyan
2012-02-01
There is an increasing trend to incorporate the basin hydrological model into the traditional land surface model (LSM) to improve the description of hydrological processes in them. For incorporating with the Noah LSM, a new rainfall-runoff model named XXT (the first X stands for Xinanjiang, the second X stands for hybrid, and T stands for TOPMODEL) was developed and presented in this study, based on the soil moisture storage capacity distribution curve (SMSCC), some essential modules of the Xinanjiang model, together with the simple model framework of the TOPMODEL (a topography based hydrological model). The innovation of XXT is that the water table is incorporated into SMSCC and it connects the surface runoff production with base flow production. This improves the description of the dynamically varying saturated areas that produce runoff and also captures the physical underground water level. XXT was tested in a small-scale watershed Youshuijie (946 km2) and a large-scale watershed Yinglouxia (10009 km2) in China. The results show that XXT has better performance against the TOPMODEL and the Xinanjiang model for the two watersheds in both the calibration period and the validation period in terms of the Nash-Sutcliffe efficiency. Moreover, XXT captures the largest peak flow well for both the small- and large-scale watersheds during the validation period, while the TOPMODEL produces significant overestimates or underestimates, so does the Xinanjiang model.
A hybrid cellular automaton model of solid tumor growth and bioreductive drug transport.
Kazmi, Nabila; Hossain, M A; Phillips, Roger M
2012-01-01
Bioreductive drugs are a class of hypoxia selective drugs that are designed to eradicate the hypoxic fraction of solid tumors. Their activity depends upon a number of biological and pharmacological factors and we used a mathematical modeling approach to explore the dynamics of tumor growth, infusion, and penetration of the bioreductive drug Tirapazamine (TPZ). An in-silico model is implemented to calculate the tumor mass considering oxygen and glucose as key microenvironmental parameters. The next stage of the model integrated extra cellular matrix (ECM), cell-cell adhesion, and cell movement parameters as growth constraints. The tumor microenvironments strongly influenced tumor morphology and growth rates. Once the growth model was established, a hybrid model was developed to study drug dynamics inside the hypoxic regions of tumors. The model used 10, 50 and 100 \\mu {\\rm M} as TPZ initial concentrations and determined TPZ pharmacokinetic (PK) (transport) and pharmacodynamics (cytotoxicity) properties inside hypoxic regions of solid tumor. The model results showed that diminished drug transport is a reason for TPZ failure and recommend the optimization of the drug transport properties in the emerging TPZ generations. The modeling approach used in this study is novel and can be a step to explore the behavioral dynamics of TPZ.
A simple and transferable all-atom/coarse-grained hybrid model to study membrane processes.
Genheden, Samuel; Essex, Jonathan W
2015-10-13
We present an efficient all-atom/coarse-grained hybrid model and apply it to membrane processes. This model is an extension of the all-atom/ELBA model applied previously to processes in water. Here, we improve the efficiency of the model by implementing a multiple-time step integrator that allows the atoms and the coarse-grained beads to be propagated at different timesteps. Furthermore, we fine-tune the interaction between the atoms and the coarse-grained beads by computing the potential of mean force of amino acid side chain analogs along the membrane normal and comparing to atomistic simulations. The model was independently validated on the calculation of small-molecule partition coefficients. Finally, we apply the model to membrane peptides. We studied the tilt angle of the Walp23 and Kalp23 helices in two different model membranes and the stability of the glycophorin A dimer. The model is efficient, accurate, and straightforward to use, as it does not require any extra interaction particles, layers of atomistic solvent molecules or tabulated potentials, thus offering a novel, simple approach to study membrane processes.
NASA Astrophysics Data System (ADS)
Zarafshan, P.; Moosavian, S. Ali A.
2013-10-01
Dynamics modelling and control of multi-body space robotic systems composed of rigid and flexible elements is elaborated here. Control of such systems is highly complicated due to severe under-actuated condition caused by flexible elements, and an inherent uneven nonlinear dynamics. Therefore, developing a compact dynamics model with the requirement of limited computations is extremely useful for controller design, also to develop simulation studies in support of design improvement, and finally for practical implementations. In this paper, the Rigid-Flexible Interactive dynamics Modelling (RFIM) approach is introduced as a combination of Lagrange and Newton-Euler methods, in which the motion equations of rigid and flexible members are separately developed in an explicit closed form. These equations are then assembled and solved simultaneously at each time step by considering the mutual interaction and constraint forces. The proposed approach yields a compact model rather than common accumulation approach that leads to a massive set of equations in which the dynamics of flexible elements is united with the dynamics equations of rigid members. To reveal such merits of this new approach, a Hybrid Suppression Control (HSC) for a cooperative object manipulation task will be proposed, and applied to usual space systems. A Wheeled Mobile Robotic (WMR) system with flexible appendages as a typical space rover is considered which contains a rigid main body equipped with two manipulating arms and two flexible solar panels, and next a Space Free Flying Robotic system (SFFR) with flexible members is studied. Modelling verification of these complicated systems is vigorously performed using ANSYS and ADAMS programs, while the limited computations of RFIM approach provides an efficient tool for the proposed controller design. Furthermore, it will be shown that the vibrations of the flexible solar panels results in disturbing forces on the base which may produce undesirable errors
3D hybrid modeling of the plasma environment near Titan for T5 encounter
NASA Astrophysics Data System (ADS)
Lipatov, A. S.; Sittler, E. C., Jr.; Hartle, R. E.; Cooper, J. F.; Sarantos, M.
2012-09-01
Wave-particle interactions play a very important role in the plasma dynamics near Titan: mass loading, excitation of low-frequency waves and formation of the particle velocity distribution function (e.g. ring/shelllike distributions, etc.) The kinetic approach is important for estimating collision processes; e.g., charge exchange. In this report we discuss results of 3D hybrid modeling of the interaction between Saturn's magnetosphere and Titan's atmosphere/ionosphere for T5 encounter. T5 flyby is the only encounter when the 2 main ionizating sources of Titan atmosphere, solar radiation and corotating plasma, align quasi-antiparallel. The modeling is based on recent analysis of the Cassini Plasma Spectrometer (CAPS) and the Cassini Ion, and Neutral Mass Spectrometer (INMS) measurements during the T5 flyby through Titan's ram-side and polar ionosphere [1, 2]. Magnetic field data was used from the MAG instrument [3]. In our model the background ions (O+, H+), all pickup ions, and ionospheric ions are considered as a particles, whereas the electrons are described as a fluid (see e.g. [4]). Inhomogeneous photoionization (in the dayside ionosphere), electron-impact ionization, and charge exchange are included in our model. The temperature of the background electrons and pickup electrons was also incorporated into the generalized Ohm's law. We also take into account collisions between ions and neutrals. In our hybrid simulations we use Chamberlain profiles for the exosphere's components. The moon is considered as a weakly conducting body. The first results of our hybridmodeling show a strong asymmetry in the background (H+, O+) and pickup (H+2 , N+2 ,CH+4 ) ion density profiles. Such strong asymmetry cannot be explained by a single-fluid multi-species 3D MHD model [5], which included complex chemistry but does not produce finite gyroradius and kinetic effects.
NASA Astrophysics Data System (ADS)
Schwarm, Fritz-Walter; Schönherr, G.; Becker, P. A.; Wolff, M. T.; Wilms, J.; Ferrigno, C.; West, B.
2013-04-01
A physical model for the radiation emitted from accretion columns of neutron stars with magnetic fields on the order of 1012 G has to reflect the large-scale dynamical structure of the inflowing matter as well as the quantum mechanical scattering processes leading to the formation of cyclotron resonant scattering features (CRSFs). Becker & Wolff (B&W) developed an analytic model for the broadband continuum while the CRSFs have been investigated by Schönherr & Schwarm (S&S). While both models describe the separate trends seen in observational data very well, a fully self-consistent fitting approach to determine the physical parameters (e.g., accretion rate, magnetic field strength) of the accretion column in accreting X-ray pulsars requires accounting for both processes in one unified model. We present our first approach towards such an unified hybrid model covering both the macro- and the microphysics of the accreting plasma. We assume a cylinder symmetrical dual layer structure of the accretion column. The inner layer reflects the dynamical structure described by the B&W model while the optical thin outer layer acts as a CRSF forming region similar to a photosphere. We adopt the parameters from a fit of the B&W model to Her X-1 and calculate the emergent radiation as well as the dynamical properties such as bulk velocity within the core of the accretion column. Radiation escaping the optical thick core region is further altered by the outer shell, a thin layer with an optical depth on the order of 10-4-10-2 Thomson optical depth, adding cyclotron lines by processing it through the S&S model. This hybrid model is only a first step towards an unified model for accreting neutron stars with strong magnetic fields. In the future we will investigate the insertion of a third layer in the middle as a transition region, parameter boundaries, and also incorporate general relativity with the ultimate goal to use this new tool to model phase-resolved spectroscopy of
The paper presents a hybrid air quality modeling approach and its application in NEXUS in order to provide spatial and temporally varying exposure estimates and identification of the mobile source contribution to the total pollutant exposure. Model-based exposure metrics, associa...
NASA Astrophysics Data System (ADS)
Suzuki, Kensuke
A new analysis tool, an unsteady Hybrid Navier-Stokes/Vortex Model, for a horizontal axis wind turbine (HAWT) in yawed flow is presented, and its convergence and low cost computational performance are demonstrated. In earlier work, a steady Hybrid Navier-Stokes/Vortex Model was developed with a view to improving simulation results obtained by participants of the NASA Ames blind comparison workshop, following the NREL Unsteady Aerodynamics Experiment. The hybrid method was shown to better predict rotor torque and power over the range of wind speeds, from fully attached to separated flows. A decade has passed since the workshop was held and three dimensional unsteady Navier-Stokes analyses have become available using super computers. In the first chapter, recent results of unsteady Euler and Navier-Stokes computations are reviewed as standard references of what is currently possible and are contrasted with results of the Hybrid Navier-Stokes/Vortex Model in steady flow. In Chapter 2, the computational method for the unsteady Hybrid model is detailed. The grid generation procedure, using ICEM CFD, is presented in Chapter 3. Steady and unsteady analysis results for the NREL Phase IV rotor and for a modified "swept NREL rotor" are presented in Chapter 4-Chapter 7.
Dunn, Barbara; Paulish, Terry; Stanbery, Alison; Piotrowski, Jeff; Koniges, Gregory; Kroll, Evgueny; Louis, Edward J.; Liti, Gianni; Sherlock, Gavin; Rosenzweig, Frank
2013-01-01
Genome rearrangements are associated with eukaryotic evolutionary processes ranging from tumorigenesis to speciation. Rearrangements are especially common following interspecific hybridization, and some of these could be expected to have strong selective value. To test this expectation we created de novo interspecific yeast hybrids between two diverged but largely syntenic Saccharomyces species, S. cerevisiae and S. uvarum, then experimentally evolved them under continuous ammonium limitation. We discovered that a characteristic interspecific genome rearrangement arose multiple times in independently evolved populations. We uncovered nine different breakpoints, all occurring in a narrow ∼1-kb region of chromosome 14, and all producing an “interspecific fusion junction” within the MEP2 gene coding sequence, such that the 5′ portion derives from S. cerevisiae and the 3′ portion derives from S. uvarum. In most cases the rearrangements altered both chromosomes, resulting in what can be considered to be an introgression of a several-kb region of S. uvarum into an otherwise intact S. cerevisiae chromosome 14, while the homeologous S. uvarum chromosome 14 experienced an interspecific reciprocal translocation at the same breakpoint within MEP2, yielding a chimaeric chromosome; these events result in the presence in the cell of two MEP2 fusion genes having identical breakpoints. Given that MEP2 encodes for a high-affinity ammonium permease, that MEP2 fusion genes arise repeatedly under ammonium-limitation, and that three independent evolved isolates carrying MEP2 fusion genes are each more fit than their common ancestor, the novel MEP2 fusion genes are very likely adaptive under ammonium limitation. Our results suggest that, when homoploid hybrids form, the admixture of two genomes enables swift and otherwise unavailable evolutionary innovations. Furthermore, the architecture of the MEP2 rearrangement suggests a model for rapid introgression, a phenomenon seen in
Assessing the impact of policy changes in the Icelandic cod fishery using a hybrid simulation model.
Sigurðardóttir, Sigríður; Johansson, Björn; Margeirsson, Sveinn; Viðarsson, Jónas R
2014-01-01
Most of the Icelandic cod is caught in bottom trawlers or longliners. These two fishing methods are fundamentally different and have different economic, environmental, and even social effects. In this paper we present a hybrid-simulation framework to assess the impact of changing the ratio between cod quota allocated to vessels with longlines and vessels with bottom trawls. It makes use of conventional bioeconomic models and discrete event modelling and provides a framework for simulating life cycle assessment (LCA) for a cod fishery. The model consists of two submodels, a system dynamics model describing the biological aspect of the fishery and a discrete event model for fishing activities. The model was run multiple times for different quota allocation scenarios and results are presented where different scenarios are presented in the three dimensions of sustainability: environmental, social, and economic. The optimal allocation strategy depends on weighing the three different factors. The results were encouraging first-steps towards a useful modelling method but the study would benefit greatly from better data on fishing activities.
NASA Astrophysics Data System (ADS)
Jenicka, S.; Suruliandi, A.
2014-01-01
Accuracy of land cover classification in remotely sensed images relies on the utilized classifier and extracted features. Texture features are significant in land cover classification. Traditional texture models capture only patterns with discrete boundaries, whereas fuzzy patterns should be classified by assigning due weightage to uncertainty. When a remotely sensed image contains noise, the image may have fuzzy patterns characterizing land covers and fuzzy boundaries separating them. Therefore, a fuzzy texture model is proposed for the effective classification of land covers in remotely sensed images. The model uses a Sugeno fuzzy inference system. A support vector machine (SVM) is used for the precise, fast classification of image pixels. The model is a hybrid of a fuzzy texture model and an SVM for the land cover classification of remotely sensed images. To support this proposal, experiments were conducted in three steps. In the first two steps, the proposed texture model was validated for supervised classifications and segmentation of a standard benchmark database. In the third step, the land cover classification of a remotely sensed image of LISS-IV (an Indian remote sensing satellite) is performed using a multivariate version of the proposed model. The classified image has 95.54% classification accuracy.
Ronen, M; Shabtai, Y; Guterman, H
2002-02-15
This paper suggests a model building methodology for dealing with new processes. The methodology, called Hybrid Fuzzy Neural Networks (HFNN), combines unsupervised fuzzy clustering and supervised neural networks in order to create simple and flexible models. Fuzzy clustering was used to define relevant domains on the input space. Then, sets of multilayer perceptrons (MLP) were trained (one for each domain) to map input-output relations, creating, in the process, a set of specified sub-models. The estimated output of the model was obtained by fusing the different sub-model outputs weighted by their predicted possibilities. On-line reinforcement learning enabled improvement of the model. The determination of the optimal number of clusters is fundamental to the success of the HFNN approach. The effectiveness of several validity measures was compared to the generalization capability of the model and information criteria. The validity measures were tested with fermentation simulations and real fermentations of a yeast-like fungus, Aureobasidium pullulans. The results outline the criteria limitations. The learning capability of the HFNN was tested with the fermentation data. The results underline the advantages of HFNN over a single neural network.
A Hybrid Model for Erythrocyte Membrane: A Single Unit of Protein Network Coupled with Lipid Bilayer
Zhu, Qiang; Vera, Carlos; Asaro, Robert J.; Sche, Paul; Sung, L. Amy
2007-01-01
To investigate the nanomechanics of the erythrocyte membrane we developed a hybrid model that couples the actin-spectrin network to the lipid bilayer. This model features a Fourier space Brownian dynamics model of the bilayer, a Brownian dynamics model of the actin protofilament, and a modified wormlike-chain model of the spectrin (including a cable-dynamics model to predict the oscillation in tension). This model enables us to predict the nanomechanics of single or multiple units of the protein network, the lipid bilayer, and the effect of their interactions. The present work is focused on the attitude of the actin protofilament at the equilibrium states coupled with the elevations of the lipid bilayer through their primary linkage at the suspension complex in deformations. Two different actin-spectrin junctions are considered at the junctional complex. With a point-attachment junction, large pitch angles and bifurcation of yaw angles are predicted. Thermal fluctuations at bifurcation may lead to mode-switching, which may affect the network and the physiological performance of the membrane. In contrast, with a wrap-around junction, pitch angles remain small, and the occurrence of bifurcation is greatly reduced. These simulations suggest the importance of three-dimensional molecular junctions and the lipid bilayer/protein network coupling on cell membrane mechanics. PMID:17449663
NASA Astrophysics Data System (ADS)
Consalvi, Jean-Louis
2017-01-01
The time-averaged Radiative Transfer Equation (RTE) introduces two unclosed terms, known as `absorption Turbulence Radiation Interaction (TRI)' and `emission TRI'. Emission TRI is related to the non-linear coupling between fluctuations of the absorption coefficient and fluctuations of the Planck function and can be described without introduction any approximation by using a transported PDF method. In this study, a hybrid flamelet/ Stochastic Eulerian Field Model is used to solve the transport equation of the one-point one-time PDF. In this formulation, the steady laminar flamelet model (SLF) is coupled to a joint Probability Density Function (PDF) of mixture fraction, enthalpy defect, scalar dissipation rate, and soot quantities and the PDF transport equation is solved by using a Stochastic Eulerian Field (SEF) method. Soot production is modeled by a semi-empirical model and the spectral dependence of the radiatively participating species, namely combustion products and soot, are computed by using a Narrow Band Correlated-k (NBCK) model. The model is applied to simulate an ethylene/methane turbulent jet flame burning in an oxygen-enriched environment. Model results are compared with the experiments and the effects of taken into account Emission TRI on flame structure, soot production and radiative loss are discussed.
A Hybrid Approach for Highly Coarse-grained Lipid Bilayer Models.
Srivastava, Anand; Voth, Gregory A
2013-01-08
We present a systematic methodology to develop highly coarse-grained (CG) lipid models for large scale bio-membrane simulations, in which we derive CG interactions using a powerful combination of the multiscale coarse-graining (MS-CG) method, and an analytical form of the CG potential to model interactions at short range. The resulting hybrid coarse-graining (HCG) methodology is used to develop a three-site solvent-free model for 1,2-dilauroyl-sn-glycero-3-phosphocholine (DLPC), 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC), and a 1:1 mixture of 1,2-dioleoyl-sn-glycero-3-phospho-L-serine (DOPS) and DOPC. In addition, we developed a four-site model of DOPC, demonstrating the capability of the HCG methodology in designing model lipid systems of a desired resolution. We carried out microsecond-scale molecular dynamics (MD) simulations of large vesicles, highlighting the ability of the model to study systems at mesoscopic length and time scales. The models of DLPC, DOPC and DOPC-DOPS have elastic properties consistent with experiment and structural properties such as the radial distribution functions (RDF), bond and angle distributions, and the z-density distributions that compare well with reference all-atom systems.
Clustering-based hybrid inundation model for forecasting flood inundation depths
NASA Astrophysics Data System (ADS)
Chang, Li-Chiu; Shen, Hung-Yu; Wang, Yi-Fung; Huang, Jing-Yu; Lin, Yen-Tso
2010-05-01
SummaryEstimation of flood depths and extents may provide disaster information for dealing with contingency and alleviating risk and loss of life and property. We present a two-stage procedure underlying CHIM (clustering-based hybrid inundation model), which is composed of linear regression models and ANNs (artificial neural networks) to build the regional flood inundation forecasting model. The two-stage procedure mainly includes data preprocessing and model building stages. In the data preprocessing stage, K-means clustering is used to categorize the data points of the different flooding characteristics in the study area and to identify the control point(s) from individual flooding cluster(s). In the model building stage, three classes of flood depth forecasting models are built in each cluster: the back-propagation neural network (BPNN) for each control point, the linear regression models for the grids that have highly linear correlation with the control point, and a multi-grid BPNN for the grids that do not have highly linear correlation with the control point. The practicability and effectiveness of the proposed approach is tested in the Dacun Township, Changhua County in Central Taiwan. The results show that the proposed CHIM can continuously and adequately provide 1-h-ahead flood inundation maps that well match the simulation flood inundation results and very effectively reduce 99% CPU time.
Hybrid modeling of the mega-tsunami runup in Lituya Bay after half a century
NASA Astrophysics Data System (ADS)
Weiss, Robert; Fritz, Hermann M.; Wünnemann, Kai
2009-05-01
The largest mega-tsunami dates back half a century to 10 July 1958, when almost unnoticed by the general public, an earthquake of M w 8.3 at the Fairweather Fault triggered a rockslide into Lituya Bay. The rockslide impact generated a giant tsunami at the head of Lituya Bay resulting in an unprecedented tsunami runup of 524 m on a spur ridge in direct prolongation of the slide axis. A forest trim line and erosion down to bedrock mark the largest runup in recorded history. While these observations have not been challenged directly, they have been largely ignored in hazard mitigation studies, because of the difficulties of even posing - much less solving - a well-defined physical problem for investigation. We study the mega-tsunami runup with a hybrid modeling approach applying physical and numerical models of slide processes of deformable bodies into a U-shaped trench similar to the geometry found at Lituya Bay.
Development of a hybrid kinetic-fluid model for line radiation transport in magnetic fusion plasmas
NASA Astrophysics Data System (ADS)
Rosato, J.; Marandet, Y.; Reiter, D.; Stamm, R.
2017-03-01
We report on a transport model for the Lyman line radiation in optically thick divertor plasma conditions encountered in exhaust systems in magnetic fusion devices. The model is designed to switch automatically between a kinetic and a continuum description according to the plasma conditions and to the spectral range. A kinetic treatment is retained for photons with a large mean free path (line wings), whereas a continuum description of the radiation field is invoked in highly absorbing or scattering regions (core photons). Prototypical calculations of this so-called δf Monte Carlo type of the Lyman α photo-excitation rate in slab geometry are performed as an illustration. The hybrid method is suggested as a candidate for speeding up the kinetic transport codes currently involved in magnetic fusion research for ITER and DEMO divertor (power and particle exhaust system) design.
Local tetrahedron modeling of microelectronics using the finite-volume hybrid-grid technique
Riley, D.J.; Turner, C.D.
1995-12-01
The finite-volume hybrid-grid (FVHG) technique uses both structured and unstructured grid regions in obtaining a solution to the time-domain Maxwell`s equations. The method is based on explicit time differencing and utilizes rectilinear finite-difference time-domain (FDTD) and nonorthogonal finite-volume time-domain (FVTD). The technique directly couples structured FDTD grids with unstructured FVTD grids without the need for spatial interpolation across grid interfaces. In this paper, the FVHG method is applied to simple planar microelectronic devices. Local tetrahedron grids are used to model portions of the device under study, with the remainder of the problem space being modeled with cubical hexahedral cells. The accuracy of propagating microstrip-guided waves from a low-density hexahedron region through a high-density tetrahedron grid is investigated.
NASA Astrophysics Data System (ADS)
Naseri Kouzehgarani, Asal
2009-12-01
Most models of aircraft trajectories are non-linear and stochastic in nature; and their internal parameters are often poorly defined. The ability to model, simulate and analyze realistic air traffic management conflict detection scenarios in a scalable, composable, multi-aircraft fashion is an extremely difficult endeavor. Accurate techniques for aircraft mode detection are critical in order to enable the precise projection of aircraft conflicts, and for the enactment of altitude separation resolution strategies. Conflict detection is an inherently probabilistic endeavor; our ability to detect conflicts in a timely and accurate manner over a fixed time horizon is traded off against the increased human workload created by false alarms---that is, situations that would not develop into an actual conflict, or would resolve naturally in the appropriate time horizon-thereby introducing a measure of probabilistic uncertainty in any decision aid fashioned to assist air traffic controllers. The interaction of the continuous dynamics of the aircraft, used for prediction purposes, with the discrete conflict detection logic gives rise to the hybrid nature of the overall system. The introduction of the probabilistic element, common to decision alerting and aiding devices, places the conflict detection and resolution problem in the domain of probabilistic hybrid phenomena. A hidden Markov model (HMM) has two stochastic components: a finite-state Markov chain and a finite set of output probability distributions. In other words an unobservable stochastic process (hidden) that can only be observed through another set of stochastic processes that generate the sequence of observations. The problem of self separation in distributed air traffic management reduces to the ability of aircraft to communicate state information to neighboring aircraft, as well as model the evolution of aircraft trajectories between communications, in the presence of probabilistic uncertain dynamics as well
Wake modeling in complex terrain using a hybrid Eulerian-Lagrangian Split Solver
NASA Astrophysics Data System (ADS)
Fuchs, Franz G.; Rasheed, Adil; Tabib, Mandar; Fonn, Eivind
2016-09-01
Wake vortices (WVs) generated by aircraft are a source of risk to the following aircraft. The probability of WV related accidents increases in the vicinity of airport runways due to the shorter time of recovery after a WV encounter. Hence, solutions that can reduce the risk of WV encounters are needed to ensure increased flight safety. In this work we propose an interesting approach to model such wake vortices in real time using a hybrid Eulerian- Lagrangian approach. We derive an appropriate mathematical model, and show a comparison of the different types of solvers. We will conclude with a real life application of the methodology by simulating how wake vortices left behind by an aircraft at the Vffirnes airport in Norway get transported and decay under the influence of a background wind and turbulence field. Although the work demonstrates the application in an aviation context the same approach can be used in a wind energy context.
Hybrid Wing Body Model Identification Using Forced-Oscillation Water Tunnel Data
NASA Technical Reports Server (NTRS)
Murphy, Patrick C.; Vicroy, Dan D.; Kramer, Brian; Kerho, Michael
2014-01-01
Static and dynamic testing of the NASA 0.7 percent scale Hybrid Wing Body (HWB) configuration was conducted in the Rolling Hills Research Corporation water tunnel to investigate aerodynamic behavior over a large range of angle-of-attack and to develop models that can predict aircraft response in nonlinear unsteady flight regimes. This paper reports primarily on the longitudinal axis results. Flow visualization tests were also performed. These tests provide additional static data and new dynamic data that complement tests conducted at NASA Langley 14- by 22-Foot Subsonic Tunnel. HWB was developed to support the NASA Environmentally Responsible Aviation Project goals of lower noise, emissions, and fuel burn. This study also supports the NASA Aviation Safety Program efforts to model and control advanced transport configurations in loss-of-control conditions.
Botros, Y Y; Volakis, J L; VanBaren, P; Ebbini, E S
1997-11-01
A computationally efficient hybrid ray-physical optics (HRPO) model is presented for the analysis and synthesis of multiple-focus ultrasound heating patterns through the human rib cage. In particular, a ray method is used to propagate the ultrasound fields from the source to the frontal plane of the rib cage. The physical-optics integration method is then employed to obtain the intensity pattern inside the rib cage. The solution of the matrix system is carried out by using the pseudo inverse technique to synthesize the desired heating pattern. The proposed technique guides the fields through the intercostal spacings between the solid ribs and, thus, minimal intensity levels are observed over the solid ribs. This simulation model allows for the design and optimization of large-aperture phased-array applicator systems for noninvasive ablative thermal surgery in the heart and liver through the rib cage.
NASA Technical Reports Server (NTRS)
Venkatesan, C.; Friedmann, P. P.
1984-01-01
Hybrid Heavy Lift Airship (HHLA) is a proposed candidate vehicle aimed at providing heavy lift capability at low cost. This vehicle consists of a buoyant envelope attached to a supporting structure to which four rotor systems, taken from existing helicopters are attached. Nonlinear equations of motion capable of modelling the dynamics of this coupled multi-rotor/support frame/vehicle system have been developed. Using these equations of motion the aeroelastic and aeromechanical stability analysis is performed aimed at identifying potential instabilities which could occur for this type of vehicle. The coupling between various blade, supporting structure and rigid body modes is identified. Furthermore, the effects of changes in buoyancy ratio (Buoyant lift/total weight) on the dynamic characteristics of the vehicle are studied. The dynamic effects found are of considerable importance for the design of such vehicles. The analytical model developed is also useful for studying the aeromechanical stability of single rotor and tandem rotor coupled rotor/fuselage systems.
Equation of state and transition temperatures in the quark-hadron hybrid model
NASA Astrophysics Data System (ADS)
Miyahara, Akihisa; Torigoe, Yuhei; Kouno, Hiroaki; Yahiro, Masanobu
2016-07-01
We analyze the equation of state of 2 +1 flavor lattice QCD at zero baryon density by constructing a simple quark-hadron hybrid model that has both quark and hadron components simultaneously. We calculate the hadron and quark contributions separately and parameterize those to match with lattice QCD data. Lattice data on the equation of state are decomposed into hadron and quark components by using the model. The transition temperature is defined by the temperature at which the hadron component is equal to the quark one in the equation of state. The transition temperature thus obtained is about 215 MeV; this is somewhat higher than the chiral and the deconfinement pseudocritical temperatures defined by the temperature at which the susceptibility or the absolute value of the derivative of the order parameter with respect to temperature becomes maximum.
COMPUTATIONAL LYMPHATIC NODE MODELS IN PEDIATRIC AND ADULT HYBRID PHANTOMS FOR RADIATION DOSIMETRY
Lee, Choonsik; Lamart, Stephanie; Moroz, Brian E.
2013-01-01
We developed models of lymphatic nodes for 6 pediatric and 2 adult hybrid computational phantoms to calculate the lymphatic node dose estimates from external and internal radiation exposures. We derived the number of lymphatic nodes from the recommendations in International Commission on Radiological Protection (ICRP) Publications 23 and 89 at 16 cluster locations for the lymphatic nodes: extrathoracic, cervical, thoracic (upper and lower), breast (left and right), mesentery (left and right), axillary (left and right), cubital (left and right), inguinal (left and right), and popliteal (left and right), for different ages (newborn, 1-, 5-, 10-, 15-year-old, and adult). We modeled each lymphatic node within the voxel format of the hybrid phantoms by assuming that all nodes have identical size derived from published data except narrow cluster sites. The lymph nodes were generated by the following algorithm: (1) selection of the lymph node site among the 16 cluster sites; (2) random sampling of the location of the lymph node within a spherical space centered at the chosen cluster site; (3) creation of the sphere or ovoid of tissue representing the node based on lymphatic node characteristics defined in ICRP Publications 23 and 89. We created lymph nodes until the pre-defined number of lymphatic nodes at the selected cluster site was reached. This algorithm was applied to pediatric (newborn, 1-, 5-, and 10-year-old male, and 15-year-old males) and adult male and female ICRP-compliant hybrid phantoms after voxelization. To assess the performance of our models for internal dosimetry, we calculated dose conversion coefficients, called S values, for selected organs and tissues with Iodine-131 distributed in 6 lymphatic node cluster sites using MCNPX2.6, a well validated Monte Carlo radiation transport code. Our analysis of the calculations indicates that the S values were significantly affected by the location of the lymph node clusters and that the values increased for
Computational lymphatic node models in pediatric and adult hybrid phantoms for radiation dosimetry
NASA Astrophysics Data System (ADS)
Lee, Choonsik; Lamart, Stephanie; Moroz, Brian E.
2013-03-01
We developed models of lymphatic nodes for six pediatric and two adult hybrid computational phantoms to calculate the lymphatic node dose estimates from external and internal radiation exposures. We derived the number of lymphatic nodes from the recommendations in International Commission on Radiological Protection (ICRP) Publications 23 and 89 at 16 cluster locations for the lymphatic nodes: extrathoracic, cervical, thoracic (upper and lower), breast (left and right), mesentery (left and right), axillary (left and right), cubital (left and right), inguinal (left and right) and popliteal (left and right), for different ages (newborn, 1-, 5-, 10-, 15-year-old and adult). We modeled each lymphatic node within the voxel format of the hybrid phantoms by assuming that all nodes have identical size derived from published data except narrow cluster sites. The lymph nodes were generated by the following algorithm: (1) selection of the lymph node site among the 16 cluster sites; (2) random sampling of the location of the lymph node within a spherical space centered at the chosen cluster site; (3) creation of the sphere or ovoid of tissue representing the node based on lymphatic node characteristics defined in ICRP Publications 23 and 89. We created lymph nodes until the pre-defined number of lymphatic nodes at the selected cluster site was reached. This algorithm was applied to pediatric (newborn, 1-, 5-and 10-year-old male, and 15-year-old males) and adult male and female ICRP-compliant hybrid phantoms after voxelization. To assess the performance of our models for internal dosimetry, we calculated dose conversion coefficients, called S values, for selected organs and tissues with Iodine-131 distributed in six lymphatic node cluster sites using MCNPX2.6, a well validated Monte Carlo radiation transport code. Our analysis of the calculations indicates that the S values were significantly affected by the location of the lymph node clusters and that the values increased for
One-Dimensional Hybrid Satellite Track Model for the Dynamics Explorer 2 (DE 2) Satellite
NASA Technical Reports Server (NTRS)
Deng, Wei; Killeen, T. L.; Burns, A. G.; Johnson, R. M.; Emery, B. A.; Roble, R. G.; Winningham, J. D.; Gary, J. B.
1995-01-01
A one-dimensional hybrid satellite track model has been developed to calculate the high-latitude thermospheric/ionospheric structure below the satellite altitude using Dynamics Explorer 2 (DE 2) satellite measurements and theory. This model is based on Emery et al. satellite track code but also includes elements of Roble et al. global mean thermosphere/ionosphere model. A number of parameterizations and data handling techniques are used to input satellite data from several DE 2 instruments into this model. Profiles of neutral atmospheric densities are determined from the MSIS-90 model and measured neutral temperatures. Measured electron precipitation spectra are used in an auroral model to calculate particle impact ionization rates below the satellite. These rates are combined with a solar ionization rate profile and used to solve the O(+) diffusion equation, with the measured electron density as an upper boundary condition. The calculated O(+) density distribution, as well as the ionization profiles, are then used in a photochemical equilibrium model to calculate the electron and molecular ion densities. The electron temperature is also calculated by solving the electron energy equation with an upper boundary condition determined by the DE 2 measurement. The model enables calculations of altitude profiles of conductivity and Joule beating rate along and below the satellite track. In a first application of the new model, a study is made of thermospheric and ionospheric structure below the DE 2 satellite for a single orbit which occurred on October 25, 1981. The field-aligned Poynting flux, which is independently obtained for this orbit, is compared with the model predictions of the height-integrated energy conversion rate. Good quantitative agreement between these two estimates has been reached. In addition, measurements taken at the incoherent scatter radar site at Chatanika (65.1 deg N, 147.4 deg W) during a DE 2 overflight are compared with the model
Modeling and energy management control design for a fuel cell hybrid passenger bus
NASA Astrophysics Data System (ADS)
Simmons, Kyle; Guezennec, Yann; Onori, Simona
2014-01-01
This paper presents the modeling and supervisory energy management design of a hybrid fuel cell/battery-powered passenger bus. With growing concerns about petroleum usage and greenhouse gas emissions in the transportation sector, finding alternative methods for vehicle propulsion is necessary. Proton Exchange Membrane (PEM) fuel cell systems are viable possibilities for energy converters due to their high efficiencies and zero emissions. It has been shown that the benefits of PEM fuel cell systems can be greatly improved through hybridization. In this work, the challenge of developing an on-board energy management strategy with near-optimal performance is addressed by a two-step process. First, an optimal control based on Pontryagin's Minimum Principle (PMP) is implemented to find the global optimal solution which minimizes fuel consumption, for different drive cycles, with and without grade. The optimal solutions are analyzed in order to aid in development of a practical controller suitable for on-board implementation, in the form of an Auto-Regressive Moving Average (ARMA) regulator. Simulation results show that the ARMA controller is capable of achieving fuel economy within 3% of the PMP controller while being able to limit the transient demand on the fuel cell system.
Biogas desulfurization and biogas upgrading using a hybrid membrane system--modeling study.
Makaruk, A; Miltner, M; Harasek, M
2013-01-01
Membrane gas permeation using glassy membranes proved to be a suitable method for biogas upgrading and natural gas substitute production on account of low energy consumption and high compactness. Glassy membranes are very effective in the separation of bulk carbon dioxide and water from a methane-containing stream. However, the content of hydrogen sulfide can be lowered only partially. This work employs process modeling based upon the finite difference method to evaluate a hybrid membrane system built of a combination of rubbery and glassy membranes. The former are responsible for the separation of hydrogen sulfide and the latter separate carbon dioxide to produce standard-conform natural gas substitute. The evaluation focuses on the most critical upgrading parameters like achievable gas purity, methane recovery and specific energy consumption. The obtained results indicate that the evaluated hybrid membrane configuration is a potentially efficient system for the biogas processing tasks that do not require high methane recoveries, and allows effective desulfurization for medium and high hydrogen sulfide concentrations without additional process steps.
SWNT-DNA and SWNT-polyC hybrids: AFM study and computer modeling.
Karachevtsev, M V; Lytvyn, O S; Stepanian, S G; Leontiev, V S; Adamowicz, L; Karachevtsev, V A
2008-03-01
Hybrids of carbon single-walled nanotubes (SWNT) with fragmented single or double-stranded DNA (fss- or fds-DNA) or polyC were studied by Atom Force Microscopy (AFM) and computer modeling. It was found that fragments of the polymer wrap in several layers around the nanotube, forming a strand-like spindle. In contrast to the fss-DNA, the fds-DNA also forms compact structures near the tube surface due to the formation of self-assembly structures consisting of a few DNA fragments. The hybrids of SWNT with wrapped single-, double- or triple strands of the biopolymer were simulated, and it was shown that such structures are stable. To explain the reason of multi-layer polymeric coating of the nanotube surface, the energy of the intermolecular interactions between different components of polyC was calculated at the MP2/6-31++G** level as well as the interaction energy in the SWNT-cytosine complex.
Effects of correlated hybridization in the single-impurity Anderson model
NASA Astrophysics Data System (ADS)
Líbero, Valter; Veiga, Rodrigo
2013-03-01
The development of new materials often dependents on the theoretical foundations which study the microscopic matter, i.e., the way atoms interact and create distinct configurations. Among the interesting materials, those with partially filled d or f orbitals immersed in nonmagnetic metals have been described by the Anderson model, which takes into account Coulomb correlation (U) when a local level (energy Ed) is doubled occupied, and an electronic hybridization between local levels and conduction band states. In addition, here we include a correlated hybridization term, which depends on the local-level occupation number involved. This term breaks particle-hole symmetry (even when U + 2Ed = 0), enhances charge fluctuations on local levels and as a consequence strongly modifies the crossover between the Hamiltonian fixed-points, even suppressing one or other. We exemplify these behaviors showing data obtained from the Numerical Renormalization Group (NRG) computation for the impurity temperature-dependent specific heat, entropy and magnetic susceptibility. The interleaving procedure is used to recover the continuum spectrum after the NRG-logarithmic discretization of the conduction band. Fundação de Amparo à Pesquisa do Estado de São Paulo - FAPESP.
Hybrid ontology for semantic information retrieval model using keyword matching indexing system.
Uthayan, K R; Mala, G S Anandha
2015-01-01
Ontology is the process of growth and elucidation of concepts of an information domain being common for a group of users. Establishing ontology into information retrieval is a normal method to develop searching effects of relevant information users require. Keywords matching process with historical or information domain is significant in recent calculations for assisting the best match for specific input queries. This research presents a better querying mechanism for information retrieval which integrates the ontology queries with keyword search. The ontology-based query is changed into a primary order to predicate logic uncertainty which is used for routing the query to the appropriate servers. Matching algorithms characterize warm area of researches in computer science and artificial intelligence. In text matching, it is more dependable to study semantics model and query for conditions of semantic matching. This research develops the semantic matching results between input queries and information in ontology field. The contributed algorithm is a hybrid method that is based on matching extracted instances from the queries and information field. The queries and information domain is focused on semantic matching, to discover the best match and to progress the executive process. In conclusion, the hybrid ontology in semantic web is sufficient to retrieve the documents when compared to standard ontology.
Hybrid-PIC Modeling of a High-Voltage, High-Specific-Impulse Hall Thruster
NASA Technical Reports Server (NTRS)
Smith, Brandon D.; Boyd, Iain D.; Kamhawi, Hani; Huang, Wensheng
2013-01-01
The primary life-limiting mechanism of Hall thrusters is the sputter erosion of the discharge channel walls by high-energy propellant ions. Because of the difficulty involved in characterizing this erosion experimentally, many past efforts have focused on numerical modeling to predict erosion rates and thruster lifespan, but those analyses were limited to Hall thrusters operating in the 200-400V discharge voltage range. Thrusters operating at higher discharge voltages (V(sub d) >= 500 V) present an erosion environment that may differ greatly from that of the lower-voltage thrusters modeled in the past. In this work, HPHall, a well-established hybrid-PIC code, is used to simulate NASA's High-Voltage Hall Accelerator (HiVHAc) at discharge voltages of 300, 400, and 500V as a first step towards modeling the discharge channel erosion. It is found that the model accurately predicts the thruster performance at all operating conditions to within 6%. The model predicts a normalized plasma potential profile that is consistent between all three operating points, with the acceleration zone appearing in the same approximate location. The expected trend of increasing electron temperature with increasing discharge voltage is observed. An analysis of the discharge current oscillations shows that the model predicts oscillations that are much greater in amplitude than those measured experimentally at all operating points, suggesting that the differences in oscillation amplitude are not strongly associated with discharge voltage.
Hybrid Gyrofluid/Gyrokinetic Modeling of Tokamak Turbulence with GryfX
NASA Astrophysics Data System (ADS)
Mandell, Noah; Dorland, Bill; Highcock, Edmund; Hammett, Greg
2016-10-01
Gyrofluid models are more efficient than gyrokinetic models, but have a disadvantage in their potential lack of physics fidelity. Here we present three major improvements to the physics fidelity and speed of gyrofluid models, which we encapsulate in the GryfX gyrofluid turbulence code. First, we implement a new nonlinear closure to model the cascade of free energy simultaneously in k⊥ and v⊥ via nonlinear phase-mixing (NLPM). Second, we use a hybrid algorithm that improves zonal flow physics by simulating zonal flow modes with a fully gyrokinetic model. These two improvements bring heat flux predictions from nonlinear GryfX simulations into agreement with the gyrokinetic code GS2. Third, we implement the equations on modern heterogeneous computing platforms, both as a standalone simulation tool that exploits the power of GPUs and as a component of TRINITY (a transport modeling code for tokamaks). GryfX has a roughly 1,200 times performance advantage over GS2 due to the combination of GPU acceleration and the reduction of hundreds of velocity space grid points to six gyrofluid moments. This makes GryfX ideal for large parameter scans, and enables the use of the TRINITY-GryfX system for efficient multi-scale analysis of tokamak turbulence on transport time scales. Present address: Chalmers University, Gothenburg, Sweden.
Predictive-model-based dynamic coordination control strategy for power-split hybrid electric bus
NASA Astrophysics Data System (ADS)
Zeng, Xiaohua; Yang, Nannan; Wang, Junnian; Song, Dafeng; Zhang, Nong; Shang, Mingli; Liu, Jianxin
2015-08-01
Parameter-matching methods and optimal control strategies of the top-selling hybrid electric vehicle (HEV), namely, power-split HEV, are widely studied. In particular, extant research on control strategy focuses on the steady-state energy management strategy to obtain better fuel economy. However, given that multi-power sources are highly coupled in power-split HEVs and influence one another during mode shifting, conducting research on dynamic coordination control strategy (DCCS) to achieve riding comfort is also important. This paper proposes a predictive-model-based DCCS. First, the dynamic model of the objective power-split HEV is built and the mode shifting process is analyzed based on the developed model to determine the reason for the system shock generated. Engine torque estimation algorithm is then designed according to the principle of the nonlinear observer, and the prediction model of the degree of shock is established based on the theory of model predictive control. Finally, the DCCS with adaptation for a complex driving cycle is realized by combining the feedback control and the predictive model. The presented DCCS is validated on the co-simulation platform of AMESim and Simulink. Results show that the shock during mode shifting is well controlled, thereby improving riding comfort.
Matching cometary ejection processes to the Leonids 1998-2001 using a hybrid numerical model
NASA Astrophysics Data System (ADS)
Welch, P. G.
2003-07-01
A new scheme for simulating meteor showers is introduced, based on a hybridization of current numerical modelling techniques. It involves an iterative method that generates particles which hit a real-scale Earth, removing the spatial and temporal blurring common to other modelling techniques. The scheme is applied to the activity profile of the Leonids 2001 using three different models of meteoroid ejection velocity and then applied to the Leonids 1998-2000 using the most favourable models. It is shown that to reproduce the observed meteor activity profiles there must be a strong concentration of ejection around perihelion. The modelling also implies that meteoroid density must be towards the higher end of the currently acceptable range, although the derived limits are not independent of the ejection velocity model. We also find that the extreme narrowness of Leonid activity peaks is not easily reproduced with outgassing over the entire day side of the comet but it is fitted well by outgassing in a restricted direction as one would expect from an outgassing jet. In addition, we show that double-peaked features, corresponding to a semihollow meteoroid streamlet, can arise in a meteor shower activity profile from outgassing during a single perihelion passage of the parent comet. It is suggested that this process caused the double-peaked feature in the first maxima of the 2001 Leonids.
Hybrid modeling of spatial continuity for application to numerical inverse problems
Friedel, Michael J.; Iwashita, Fabio
2013-01-01
A novel two-step modeling approach is presented to obtain optimal starting values and geostatistical constraints for numerical inverse problems otherwise characterized by spatially-limited field data. First, a type of unsupervised neural network, called the self-organizing map (SOM), is trained to recognize nonlinear relations among environmental variables (covariates) occurring at various scales. The values of these variables are then estimated at random locations across the model domain by iterative minimization of SOM topographic error vectors. Cross-validation is used to ensure unbiasedness and compute prediction uncertainty for select subsets of the data. Second, analytical functions are fit to experimental variograms derived from original plus resampled SOM estimates producing model variograms. Sequential Gaussian simulation is used to evaluate spatial uncertainty associated with the analytical functions and probable range for constraining variables. The hybrid modeling of spatial continuity is demonstrated using spatially-limited hydrologic measurements at different scales in Brazil: (1) physical soil properties (sand, silt, clay, hydraulic conductivity) in the 42 km2 Vargem de Caldas basin; (2) well yield and electrical conductivity of groundwater in the 132 km2 fractured crystalline aquifer; and (3) specific capacity, hydraulic head, and major ions in a 100,000 km2 transboundary fractured-basalt aquifer. These results illustrate the benefits of exploiting nonlinear relations among sparse and disparate data sets for modeling spatial continuity, but the actual application of these spatial data to improve numerical inverse modeling requires testing.
Venus-solar wind interaction in a hybrid plasma simulation model
NASA Astrophysics Data System (ADS)
Jarvinen, R.; Kallio, E.; Barabash, S.; Zhang, T. L.; Fedorov, A.; Sillanpää, I.; Janhunen, P.
2007-08-01
We present a study of the plasma interaction between Venus and the solar wind. In the study we use a computer simulation model to interpret recerently acquired insitu data by the Venus Express spacecraft. The numerical simulation is based on a 3-dimensional hybrid model, which consists of particle ions, a charge neutralizing massless electron fluid and non-radiative electrodynamics. This arrangement makes it possible to study self-consistently coupled ion kinetics and electromagnetism in a global planetary scale. In the model, the Venusian upper atmosphere and exosphere are modelled as a perfectly conducting ionospheric medium and hydrogen and oxygen photoion production. Given the upstream conditions and the spatial planetary ion distributions the model provides, for example, the escape rates of the atmospheric ion populations and the geometry of the interplanetary magnetic field draped around the planet. Here the model is used to study ion observations from the ASPERA-4 plasma instrument and magnetic field measurements from the MAG magnetometer on Venus Express.
NASA Astrophysics Data System (ADS)
Farkašovský, Pavol
2017-04-01
We study the combined effects of local and nonlocal hybridization on the formation and condensation of the excitonic bound states in the extended Falicov-Kimball model by the density-matrix-renormalization-group (DMRG) method. Analysing the resultant behaviours of the excitonic momentum distribution N(q) we found, that unlike the local hybridization V, which supports the formation of the q=0 momentum condensate, the nonlocal hybridization Vn supports the formation of the q = π momentum condensate. The combined effect of local and nonlocal hybridization further enhances the excitonic correlations in q=0 as well as q = π state, especially for V and Vn values from the charge-density-wave (CDW) region. Strong effects of local and nonlocal hybridization are observed also for other ground-state quantities of the model such as the f-electron density, or the density of unbound d-electrons, which are generally enhanced with increasing V and Vn. The same calculations performed for nonzero values of f-level energy Ef revealed that this model can yield a reasonable explanation for the pressure-induced resistivity anomaly observed experimentally in TmSe0.45Te0.55 compound.
Wave dispersion in the hybrid-Vlasov model: Verification of Vlasiator
Kempf, Yann; Pokhotelov, Dimitry; Koskinen, Hannu E. J.; Alfthan, Sebastian von; Palmroth, Minna; Vaivads, Andris
2013-11-15
Vlasiator is a new hybrid-Vlasov plasma simulation code aimed at simulating the entire magnetosphere of the Earth. The code treats ions (protons) kinetically through Vlasov's equation in the six-dimensional phase space while electrons are a massless charge-neutralizing fluid [M. Palmroth et al., J. Atmos. Sol.-Terr. Phys. 99, 41 (2013); A. Sandroos et al., Parallel Comput. 39, 306 (2013)]. For first global simulations of the magnetosphere, it is critical to verify and validate the model by established methods. Here, as part of the verification of Vlasiator, we characterize the low-β plasma wave modes described by this model and compare with the solution computed by the Waves in Homogeneous, Anisotropic Multicomponent Plasmas (WHAMP) code [K. Rönnmark, Kiruna Geophysical Institute Reports No. 179, 1982], using dispersion curves and surfaces produced with both programs. The match between the two fundamentally different approaches is excellent in the low-frequency, long wavelength range which is of interest in global magnetospheric simulations. The left-hand and right-hand polarized wave modes as well as the Bernstein modes in the Vlasiator simulations agree well with the WHAMP solutions. Vlasiator allows a direct investigation of the importance of the Hall term by including it in or excluding it from Ohm's law in simulations. This is illustrated showing examples of waves o