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
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; 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.
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.
Energy based hybrid turbulence modeling
NASA Astrophysics Data System (ADS)
Haering, Sigfried; Moser, Robert
2015-11-01
Traditional hybrid approaches exhibit deficiencies when used for fluctuating smooth-wall separation and reattachment necessitating ad-hoc delaying functions and model tuning making them no longer useful as a predictive tool. Additionally, complex geometries and flows often require high cell aspect-ratios and large grid gradients as a compromise between resolution and cost. Such transitions and inconsistencies in resolution detrimentally effect the fidelity of the simulation. We present the continued development of a new hybrid RANS/LES modeling approach specifically developed to address these challenges. In general, modeled turbulence is returned to resolved scales by reduced or negative model viscosity until a balance between theoretical and actual modeled turbulent kinetic energy is attained provided the available resolution. Anisotropy in the grid and resolved field are directly integrated into this balance. A viscosity-based correction is proposed to account for resolution inhomogeneities. Both the hybrid framework and resolution gradient corrections are energy conserving through an exchange of resolved and modeled turbulence.
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.
Explaining the explosion: modelling hybrid invasions.
Hall, Richard J; Hastings, Alan; Ayres, Debra R
2006-06-01
The emergence of hybrids between native and introduced species is an increasingly widespread problem which can alter entire ecosystems. We present a general model for the hybridization of two plant species to investigate the conditions under which hybrid invasions can occur, and the ecological and genetic consequences of such hybridizations. We find that parental compatibility and fecundity are important determinants of whether (and at what rate) hybrid genotypes emerge. Enhanced hybrid fitness traits affect both the population's genetic structure and total rate of increase, with rapid selection for the fittest genotype. Conversely, if different genotypes maximize different life-history characteristics, the ensuing population can be genetically very variable. The model provides a novel approach to evaluate the contributions of population dynamic and genetic processes in the study of hybrid invasions.
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…
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 kinetic model for subtractive hybridization.
Milner, J J; Cecchini, E; Dominy, P J
1995-01-01
Nucleic acid sequences that differ in abundance between two populations (target sequences) can be cloned by multiple rounds of subtractive hybridization and amplification by PCR. These sequences can be cDNAs representing up-regulated mRNAs, or genomic DNAs from deletion mutants. We have derived an equation that describes the recovery of such sequences, and have used this to simulate the outcome of up to 10 rounds of subtractive hybridization and PCR amplification. When the model was tested by comparing its predictions with the published results from genomic and cDNA subtractions, the predictions of the model were generally in good agreement with the published data. We have modelled the outcomes of genomic subtractions, for a variety of genomes, and have used it to compare various strategies for enriching targets. The model predicts that for genomes of less than 5 x 10(8) bp, deletions of as small as 1 kbp should represent > 99% of the DNA after three to six rounds of hybridization (depending on the enrichment procedure). As genomes increase in size, the kinetics of hybridization become an important limiting factor. However, even for genomes as large as 3 x 10(9) bp, it should be possible to isolate deletions of 5 kbp using the appropriate conditions. These simulations suggest that such methods offer a realistic alternative to chromosome walking for identifying genomic deletions for which there are known phenotypes, thereby considerably reducing time and effort. For cDNA subtractive hybridization, the model predicts that after six rounds of hybridization, sequences that do not differ in abundance between the tester and driver populations (the background) will represent < 1% of the subtracted population, and even quite modestly upregulated cDNAs should be successfully enriched. Where several up-regulated cDNAs are present, the predicted final representation is dependent on both the initial abundance and the degree of up-regulation. PMID:7870584
Hybrid models in loop quantum cosmology
NASA Astrophysics Data System (ADS)
Elizaga Navascués, Beatriz; Martín-Benito, Mercedes; Mena Marugán, Guillermo A.
2016-06-01
In the framework of Loop Quantum Cosmology (LQC), inhomogeneous models are usually quantized by means of a hybrid approach that combines loop quantization techniques with standard quantum field theory methods. This approach is based on a splitting of the phase space in a homogeneous sector, formed by global, zero-modes and an inhomogeneous sector, formed by the remaining, infinite number of modes, that describe the local degrees of freedom. Then, the hybrid quantization is attained by adopting a loop representation for the homogeneous gravitational sector, while a Fock representation is used for the inhomogeneities. The zero-mode of the Hamiltonian constraint operator couples the homogeneous and inhomogeneous sectors. The hybrid approach, therefore, is expected to provide a suitable quantum theory in regimes where the main quantum effects of the geometry are those affecting the zero-modes, while the inhomogeneities, still being quantum, can be treated in a more conventional way. This hybrid strategy was first proposed for the simplest cosmological midisuperspaces: the Gowdy models, and it has been later applied to the case of cosmological perturbations. This paper reviews the construction and main applications of hybrid LQC.
Hybrid modeling in computational neuropsychiatry.
Marin-Sanguino, A; Mendoza, E R
2008-09-01
The aim of building mathematical models is to provide a formal structure to explain the behaviour of a whole in terms of its parts. In the particular case of neuropsychiatry, the available information upon which models are to be built is distributed over several fields of expertise. Molecular and cellular biologists, physiologists and clinicians all hold valuable information about the system which has to be distilled into a unified view. Furthermore, modelling is not a sequential process in which the roles of field and modelling experts are separated. Model building is done through iterations in which all the parts have to keep an active role. This work presents some modelling techniques and guidelines on how they can be combined in order to simplify modelling efforts in neuropsychiatry. The proposed approach involves two well known modelling techniques, Petri nets and Biochemical System Theory that provide a general well proven structured definition for biological models.
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.
Hybrid quantum teleportation: A theoretical model
NASA Astrophysics Data System (ADS)
Takeda, Shuntaro; Mizuta, Takahiro; Fuwa, Maria; Yoshikawa, Jun-ichi; Yonezawa, Hidehiro; Furusawa, Akira
2014-12-01
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.
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
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.
Estimating Resolution Lengths of Hybrid Turbulence Models
NASA Technical Reports Server (NTRS)
Abdol-Hamid, Khaled S.; Girimaji, Sharath S.
2006-01-01
A two-stage procedure has been devised for estimating the spatial resolution achievable in the simulation of a given flow on a given computational grid by a computational fluid dynamics (CFD) code that incorporates a hybrid model of turbulence. The hybrid models to which this procedure is especially relevant are those of the Reynolds-averaged Navier-Stokes (RANS) and the partial-averaged Navier-Stokes (PANS) approaches. This procedure represents the first step toward adding variable-resolution turbulence-modeling capabilities to CFD codes as part of a continuing effort to increase the accuracy and robustness of CFD simulations of unsteady flows. Some background information is prerequisite to a meaningful summary of the procedure. Among experts in CFD, it is well known that combination of the Reynolds-averaged Navier-Stokes (RANS) approach and eddy-viscosity turbulence models offers limited capability for simulating unsteady and complex flows. The RANS approach includes an assumption that most of the energy in a given flow is modeled through turbulence-transport equations and is resolved in a computational grid used to simulate the flow. RANS also overpredicts eddy viscosity, thereby yielding excessive damping of unsteady motion. The eddy viscosity attains an unphysically large value because of unresolved scales, and suppresses most temporal and spatial fluctuations in the resolved flow field. One approach used to overcome this deficiency is to provide a mechanism for the RANS equations to resolve motion only on the largest scales and to use a hybrid model to represent effects at smaller scales. The RANS approach involves the use of a standard two-equation turbulence model in which the effect of turbulence is summarized by a viscosity that is a function of (1) the time-averaged kinetic- energy density (k) associated with the local fluctuating (turbulent) component of flow and (2) the time-averaged rate of dissipation of the turbulent-kinetic- energy density ( ). In
Lorentz Nonreciprocal Model for Hybrid Magnetoplasmonics
NASA Astrophysics Data System (ADS)
Floess, Dominik; Weiss, Thomas; Tikhodeev, Sergei; Giessen, Harald
2016-08-01
Using localized surface plasmons, the magneto-optical response of dielectric thin films can be resonantly amplified and spectrally tailored. While the experimental realization and numerical simulation of such systems received considerable attention, so far, there is no analytical theoretical description. Here, we present a simple, intrinsically Lorentz nonreciprocal coupled oscillator model that reveals the underlying physics inside such systems and yields analytical expressions for the resonantly enhanced magneto-optical response. The predictions of the model are in good agreement with rigorous numerical solutions of Maxwell's equations for typical sample geometries. Our ansatz is transferable to other complex and hybrid nanooptical systems and will significantly facilitate device design.
Modeling hybrid stars with an SU(3) nonlinear {sigma} model
Negreiros, Rodrigo; Dexheimer, V. A.; Schramm, S.
2010-09-15
We study the behavior of hybrid stars by using an extended hadronic and quark SU(3) nonlinear sigma model. The degrees of freedom change naturally, in this model, from hadrons to quarks as the density/temperature increases. At zero temperature, we reproduce massive neutron stars, which contain cores of hybrid matter of 2 km for the nonrotating case and 1.18 and 0.87 km, in the equatorial and polar directions, respectively, for stars that rotate at the Kepler frequency (physical cases lie in between). The cooling of such stars is also analyzed.
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.
Models of transition regions in hybrid stars
NASA Technical Reports Server (NTRS)
Brosius, J. W.; Mullan, D. J.
1986-01-01
Models for the transition regions of six hybrid stars, four bright giants and two supergiants, are calculated. The models include mass loss and prescribe Alfven waves as the source of mechanical energy. The momentum and energy deposition rates required at each level of the atmosphere are evaluated. The final models for all six stars have mass loss rates lying below the current VLA upper limits by factors of two to ten, and have densities which agree with those derived by density-sensitive line ratios. The density vs. temperature structure in Alpha TrA agree well with that derived by Hartmann et al. (1985). Wave amplitudes and magnetic field strengths are derived as functions of height, and the amplitudes are found to agree well with the observed line widths in Alpha TrA.
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.
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.
Extreme Earthquake Risk Estimation by Hybrid Modeling
NASA Astrophysics Data System (ADS)
Chavez, M.; Cabrera, E.; Ashworth, M.; Garcia, S.; Emerson, D.; Perea, N.; Salazar, A.; Moulinec, C.
2012-12-01
The estimation of the hazard and the economical consequences i.e. the risk associated to the occurrence of extreme magnitude earthquakes in the neighborhood of urban or lifeline infrastructure, such as the 11 March 2011 Mw 9, Tohoku, Japan, represents a complex challenge as it involves the propagation of seismic waves in large volumes of the earth crust, from unusually large seismic source ruptures up to the infrastructure location. The large number of casualties and huge economic losses observed for those earthquakes, some of which have a frequency of occurrence of hundreds or thousands of years, calls for the development of new paradigms and methodologies in order to generate better estimates, both of the seismic hazard, as well as of its consequences, and if possible, to estimate the probability distributions of their ground intensities and of their economical impacts (direct and indirect losses), this in order to implement technological and economical policies to mitigate and reduce, as much as possible, the mentioned consequences. Herewith, we propose a hybrid modeling which uses 3D seismic wave propagation (3DWP) and neural network (NN) modeling in order to estimate the seismic risk of extreme earthquakes. The 3DWP modeling is achieved by using a 3D finite difference code run in the ~100 thousands cores Blue Gene Q supercomputer of the STFC Daresbury Laboratory of UK, combined with empirical Green function (EGF) techniques and NN algorithms. In particular the 3DWP is used to generate broadband samples of the 3D wave propagation of extreme earthquakes (plausible) scenarios corresponding to synthetic seismic sources and to enlarge those samples by using feed-forward NN. We present the results of the validation of the proposed hybrid modeling for Mw 8 subduction events, and show examples of its application for the estimation of the hazard and the economical consequences, for extreme Mw 8.5 subduction earthquake scenarios with seismic sources in the Mexican
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.
Retrospective tests of hybrid operational earthquake forecasting models for Canterbury
NASA Astrophysics Data System (ADS)
Rhoades, D. A.; Liukis, M.; Christophersen, A.; Gerstenberger, M. C.
2016-01-01
The Canterbury, New Zealand, earthquake sequence, which began in September 2010, occurred in a region of low crustal deformation and previously low seismicity. Because, the ensuing seismicity in the region is likely to remain above previous levels for many years, a hybrid operational earthquake forecasting model for Canterbury was developed to inform decisions on building standards and urban planning for the rebuilding of Christchurch. The model estimates occurrence probabilities for magnitudes M ≥ 5.0 in the Canterbury region for each of the next 50 yr. It combines two short-term, two medium-term and four long-term forecasting models. The weight accorded to each individual model in the operational hybrid was determined by an expert elicitation process. A retrospective test of the operational hybrid model and of an earlier informally developed hybrid model in the whole New Zealand region has been carried out. The individual and hybrid models were installed in the New Zealand Earthquake Forecast Testing Centre and used to make retrospective annual forecasts of earthquakes with magnitude M > 4.95 from 1986 on, for time-lags up to 25 yr. All models underpredict the number of earthquakes due to an abnormally large number of earthquakes in the testing period since 2008 compared to those in the learning period. However, the operational hybrid model is more informative than any of the individual time-varying models for nearly all time-lags. Its information gain relative to a reference model of least information decreases as the time-lag increases to become zero at a time-lag of about 20 yr. An optimal hybrid model with the same mathematical form as the operational hybrid model was computed for each time-lag from the 26-yr test period. The time-varying component of the optimal hybrid is dominated by the medium-term models for time-lags up to 12 yr and has hardly any impact on the optimal hybrid model for greater time-lags. The optimal hybrid model is considerably more
Hybrid Associative Memories And Metric Data Models
NASA Astrophysics Data System (ADS)
Goldfarb, Lev; Verma, Raj
1988-08-01
An approach to the design of associative memories and pattern recognition systems which utilizes efficiently hybrid architectures is illustrated. By associative memory we mean a database organization that supports retrieval by content and not only by name (or address), as is the case with practically all existing database systems. The approach is based on a general, metric, model for pattern recognition which was developed to unify in a single model two basic approaches to pattern recognition-geometric and structural-preserving the advantages of each one. The metric model offers the designer a complete freedom in the choice of both the object representation and the dissimilarity measure, and at the same time provides a single analytical framework for combining several object representations in a very efficient recognition scheme. It is our fervent hope that the paper will attract researchers interested in the development of associative memories or image recognition systems to experiment with various optical dissimilarity measures (between two images) the need for which becomes so acute with the realization of the possibilities offered by the metric model.
HYBRID2: A versatile model of the performance of hybrid power systems
NASA Astrophysics Data System (ADS)
Green, H. James; Manwell, James
1995-04-01
In 1993, the National Renewable Laboratory (NREL) made an assessment of the available tools from the United States and Europe for predicting the long-term performance of hybrid power systems. By hybrid power the authors mean combinations of two or more power sources wind turbines, photovoltaics (PV), diesel gensets, or other generators into integrated systems for electric power generation in remote locations. Their conclusion was that there was no single, user-friendly tool capable of modeling the full range of hybrid power technologies being considered for the 1990s and beyond. The existing tools were, in particular, lacking flexibility in system configuration and in dispatch of components. As a result, NREL developed a specification for a model, called HYBRID2, for making comparisons of competing technology options on a level playing field. This specification was prepared with a range of potential users in mind including not only the US Department of Energy (DOE) renewable energy programs, but also the US wind industry, technical consultants, international development institutions/banks, and rural electrification programs in developing countries. During 1994, NREL and subcontractor, the University of Massachusetts (UMass), began development of HYBRID2 with funding from the DOE Wind Energy Program. It builds on the wind/diesel model, HYBRID1, developed previously by UMass, and expands that model to accommodate the wider array of technologies used in hybrid power systems. This paper will provide an overview of the model's features, functions, and status.
SCAN-based hybrid and double-hybrid density functionals from models without fitted parameters.
Hui, Kerwin; Chai, Jeng-Da
2016-01-28
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. PMID:26827209
A framework of fuzzy hybrid systems for modelling and control
NASA Astrophysics Data System (ADS)
Cheng, Shu; Dong, Ruijun; Pedrycz, Witold
2010-02-01
This paper presents a new approach to modelling and control of hybrid systems with both continuous variables and discrete events. Applying the fuzzy set theory, a hierarchical fuzzy hybrid structure consisting of a fuzzy discrete event dynamic system and a continuous variable dynamic system is constructed, which not only captures the hybrid continuous/discrete dynamics but also handles the uncertainties in states and state transitions. The identification of continuous and discrete components is developed, and the hybrid control is then synthesised by fuzzy IF-THEN rules embedded in the fuzzy interface. An example of the optimisation of a production line in manufacturing shows the efficacy of the proposed approach.
Hybrid discrete choice models: Gained insights versus increasing effort.
Mariel, Petr; Meyerhoff, Jürgen
2016-10-15
Hybrid choice models expand the standard models in discrete choice modelling by incorporating psychological factors as latent variables. They could therefore provide further insights into choice processes and underlying taste heterogeneity but the costs of estimating these models often significantly increase. This paper aims at comparing the results from a hybrid choice model and a classical random parameter logit. Point of departure for this analysis is whether researchers and practitioners should add hybrid choice models to their suite of models routinely estimated. Our comparison reveals, in line with the few prior studies, that hybrid models gain in efficiency by the inclusion of additional information. The use of one of the two proposed approaches, however, depends on the objective of the analysis. If disentangling preference heterogeneity is most important, hybrid model seems to be preferable. If the focus is on predictive power, a standard random parameter logit model might be the better choice. Finally, we give recommendations for an adequate use of hybrid choice models based on known principles of elementary scientific inference. PMID:27310534
Hybrid discrete choice models: Gained insights versus increasing effort.
Mariel, Petr; Meyerhoff, Jürgen
2016-10-15
Hybrid choice models expand the standard models in discrete choice modelling by incorporating psychological factors as latent variables. They could therefore provide further insights into choice processes and underlying taste heterogeneity but the costs of estimating these models often significantly increase. This paper aims at comparing the results from a hybrid choice model and a classical random parameter logit. Point of departure for this analysis is whether researchers and practitioners should add hybrid choice models to their suite of models routinely estimated. Our comparison reveals, in line with the few prior studies, that hybrid models gain in efficiency by the inclusion of additional information. The use of one of the two proposed approaches, however, depends on the objective of the analysis. If disentangling preference heterogeneity is most important, hybrid model seems to be preferable. If the focus is on predictive power, a standard random parameter logit model might be the better choice. Finally, we give recommendations for an adequate use of hybrid choice models based on known principles of elementary scientific inference.
Hybrid nonlinear model of the angular vestibulo-ocular reflex.
Ranjbaran, Mina; Galiana, Henrietta L
2013-01-01
A hybrid nonlinear bilateral model for the horizontal angular vestibulo-ocular reflex (AVOR) is presented in this paper. The model relies on known interconnections between saccadic burst circuits in the brainstem and ocular premotor areas in the vestibular nuclei during slow and fast phase intervals. A viable switching strategy for the timing of nystagmus events is proposed. Simulations show that this hybrid model replicates AVOR nystagmus patterns that are observed in experimentally recorded data.
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.
A hybrid deformable model for real-time surgical simulation.
Zhu, Bo; Gu, Lixu
2012-07-01
Modeling organ deformation in real remains a challenge in virtual minimally invasive (MIS) surgery simulation. In this paper, we propose a new hybrid deformable model to simulate deformable organs in the real-time surgical training system. Our hybrid model uses boundary element method (BEM) to compute global deformation based on a coarse surface mesh and uses a mass-spring model to simulate the dynamic behaviors of soft tissue interacting with surgical instruments. The simulation result is coupled with a high-resolution rendering mesh through a particle surface interpolation algorithm. Accurate visual and haptic feedbacks are provided in real time and temporal behaviors of biological soft tissues including viscosity and creeping are modeled as well. We prove our model to be suitable to work in complex virtual surgical environment by integrating it into a MIS training system. The hybrid model is evaluated with respect to efficiency, accuracy and robustness by a series of experiments. PMID:22483053
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.
A multivariate prediction model for microarray cross-hybridization
Chen, Yian A; Chou, Cheng-Chung; Lu, Xinghua; Slate, Elizabeth H; Peck, Konan; Xu, Wenying; Voit, Eberhard O; Almeida, Jonas S
2006-01-01
Background Expression microarray analysis is one of the most popular molecular diagnostic techniques in the post-genomic era. However, this technique faces the fundamental problem of potential cross-hybridization. This is a pervasive problem for both oligonucleotide and cDNA microarrays; it is considered particularly problematic for the latter. No comprehensive multivariate predictive modeling has been performed to understand how multiple variables contribute to (cross-) hybridization. Results We propose a systematic search strategy using multiple multivariate models [multiple linear regressions, regression trees, and artificial neural network analyses (ANNs)] to select an effective set of predictors for hybridization. We validate this approach on a set of DNA microarrays with cytochrome p450 family genes. The performance of our multiple multivariate models is compared with that of a recently proposed third-order polynomial regression method that uses percent identity as the sole predictor. All multivariate models agree that the 'most contiguous base pairs between probe and target sequences,' rather than percent identity, is the best univariate predictor. The predictive power is improved by inclusion of additional nonlinear effects, in particular target GC content, when regression trees or ANNs are used. Conclusion A systematic multivariate approach is provided to assess the importance of multiple sequence features for hybridization and of relationships among these features. This approach can easily be applied to larger datasets. This will allow future developments of generalized hybridization models that will be able to correct for false-positive cross-hybridization signals in expression experiments. PMID:16509965
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.
Hybrid modeling, HMM/NN architectures, and protein applications.
Baldi, P; Chauvin, Y
1996-10-01
We describe a hybrid modeling approach where the parameters of a mode are calculated and modulated by another model, typically a neural network (NN), to avoid both overfitting and underfitting. We develop the approach for the case of Hidden Markov Models (HMMs), by deriving a class of hybrid HMM/NN architectures. These architectures can be trained with unified algorithms that blend HMM dynamic programming with NN backpropagation. In the case of complex data, mixtures of HMMs or modulated HMMs must be used. NNs can then be applied both to the parameters of each single HMM, and to the switching or modulatation of the models, as a function of input or context. Hybrid HMM/NN architectures provide a flexible NN parameterization for the control of model structure and complexity. At the same time, they can capture distributions that, in practice, are inaccessible to single HMMs. The HMM/NN hybrid approach is tested, in its simplest form, by constructing a model of the immunoglobulin protein family. A hybrid model is trained, and a multiple alignment derived, with less than a fourth of the number of parameters used with previous single HMMs.
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. 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.
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.
A study on intrusion detection model based on hybrid classifier
NASA Astrophysics Data System (ADS)
Liu, Kewen; Yang, Qingbo
2013-03-01
In order to improve the accuracy of classification problem in intrusion detection, a hybrid classifier which was composed by KPCA, BPNN and QGA, has been proposed in this paper. In the hybrid classifier, KPCA was used to reduce dimensions, and then QGA was used to search the best parameters for BPNN. BPNN which has been got the best weights matrix and thresholds by QGA, was used to train classification model. The main core factors of original dataset can be preserved by KPCA, and greatly reduced the computations. The weakness of BPNN, which was usually easy to get stuck in local minimum, can be solved by QGA. Finally, the effectiveness of hybrid classifier was proved by experiments. Compared with traditional methods, the hybrid classifier has better performance in reducing the classify errors.
Spatial, Non-Spatial and Hybrid Models for Scaling
ERIC Educational Resources Information Center
Carroll, J. Douglas
1976-01-01
Hierarchical and non-hierarchical tree structures as models of similarity data are proposed and procedures for fitting both types of trees to data are discussed. Trees are viewed as intermediate between multidimensional scaling and simple clustering. Multiple tree structures and hybrid models are discussed and examples are presented. (Author/JKS)
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.
Hybrid numerical model of shock waves in collisionless plasma
NASA Astrophysics Data System (ADS)
Vshivkova, L.; Dudnikova, G.; Vshivkov, K.
2016-10-01
We present a 2D hybrid numerical plasma model of generation and structure of collisionless shock waves in plasma and ion acceleration on their front considering physical processes in supernova remnant shock precursor. In modeling a shock wave is generated by sending a supersonic flow against a reflecting wall. The consequent interaction between incoming and reflected plasma flows lead to formation of waves, the structure of which depends on a flow velocity. The hybrid approach reduces the computational expenses relative to a fully kinetic one, and on the other hand, permits to model ions with a greater accuracy than the magnetohydrodynamics (MHD) allows. Also, another important advantage of the hybrid approach is the possibility to study the important instabilities on an ion time scale, neglecting the modes associated with electrons. In the current work a new computational scheme where stability condition allows carry out computations on more wide set of computational and physical parameters is presented.
Hybrid Model for XeCl Laser Discharges
NASA Astrophysics Data System (ADS)
Lamrous, Omar; Mitiche, Moh Djerdjer; Gaouar, Adil; Yousfi, Mohamed
1997-09-01
Our aim is to present an hybrid model to study the plasma characteristics of XeCl laser impulsionnel discharge. This model is a coupling of electric circuit equations (electricmodel), electron Boltzmann equation (particle model) and kinetic equations of both charged particles and the main neutral or excited species (kinetics model). The corresponding results (electron distribution functions, reaction rates, species created, reduced field discharge) are reported and discussed.
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.
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
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
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.
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
Ozburn, A. R.; Walker, D.; Ahmed, S.; Belknap, J. K.; Harris, R. A.
2011-01-01
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. PMID:19798565
Brain Anatomical Structure Segmentation by Hybrid Discriminative/Generative Models
Tu, Zhuowen; Narr, Katherine L.; Dollár, Piotr; Dinov, Ivo; Thompson, Paul M.; Toga, Arthur W.
2008-01-01
In this paper, a hybrid discriminative/generative model for brain anatomical structure segmentation is proposed. The learning aspect of the approach is emphasized. In the discriminative appearance models, various cues such as intensity and curvatures are combined to locally capture the complex appearances of different anatomical structures. A probabilistic boosting tree (PBT) framework is adopted to learn multi-class discriminative models that combine hundreds of features across different scales. On the generative model side, both global and local shape models are used to capture the shape information about each anatomical structure. The parameters to combine the discriminative appearance and generative shape models are also automatically learned. Thus low-level and high-level information is learned and integrated in a hybrid model. Segmentations are obtained by minimizing an energy function associated with the proposed hybrid model. Finally, a grid-face structure is designed to explicitly represent the 3D region topology. This representation handles an arbitrary number of regions and facilitates fast surface evolution. Our system was trained and tested on a set of 3D MRI volumes and the results obtained are encouraging. PMID:18390346
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}).
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.
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 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
Spatial Rainfall Prediction Based on PGD-MRF Hybrid Model
NASA Astrophysics Data System (ADS)
Li, Y.; Chang, J.
2015-12-01
It is of great significance for decision making in water resources planning and management to predict climate variation, especially rainfall, accurately. The main goal of this study is to put forward a PGD-MRF hybrid model for monthly rainfall forecast, which is based on Poisson Gamma Distribution (PGD) and Markov Random Field(MRF) models, to make up for the deficiency of the atmospheric general circulation model (GCM) in low spatial resolution and difficultly simulating regional climate change. The Wei River Basin was taken as an case study to investigate the accuracy of PGD-MRF hybrid model. Based on the monthly rainfall data from 1960 to 2010 at eight meteorological stations, the PGD model was firstly set up to fit the statistical relationship between monthly precipitation and GCM output factors. Then the monthly rainfall data in historical period of 1960-2010 were simulated through the spatial correlation of monthly rainfall analyzed by MRF model. The statistical downscaling model (SDSM) was also employed to evaluate the performance of the PGD-MRF model. The comparison of results revealed that the PGD-MRF model had provided a superior alternative to SDSM for forecasting monthly rainfall at all these eight meteorological stations. To further illustrate the stability and representativeness of the PGD-MRF model, the monthly rainfall data from 2001 to 2010 at Huashan station were used to verify the model. The results showed that the PGD-MRF model had a good stability and great representativeness as well as a high prediction precision.
A simplified model for hybrid rocket performance prediction
NASA Astrophysics Data System (ADS)
Wolf, Robert S.; Wagner, John W.
1992-02-01
A computer code to predict hybrid rocket performance was developed and validated. The algorithm used is a simplification of the model derived by Marxman and Wooldridge. This model assumes the fuel regression rate to be controlled by convective heat transfer to the solid fuel from a relatively thin diffusion flame in a turbulent boundary layer. The model further assumes that the Reynolds analogy applies with mass addition at the wall. The computer code incorporates variable combustion product properties (temperature, molecular weight, and ratio of specific heats) as a function of the instantaneous global oxidizer/fuel ratio. The code was validated by constructing and firing a hybrid rocket motor. This motor used gaseous oxygen and hydroxyl-terminated polybutadiene as propellants. The oxygen flow rate used in the test was given as an input to the computer code, which then calculated chamber pressures and thrust. The agreement between test data and computer predictions was excellent.
Hybrid continuum-atomistic approach to model electrokinetics in nanofluidics.
Amani, Ehsan; Movahed, Saeid
2016-06-01
In this study, for the first time, a hybrid continuum-atomistic based model is proposed for electrokinetics, electroosmosis and electrophoresis, through nanochannels. Although continuum based methods are accurate enough to model fluid flow and electric potential in nanofluidics (in dimensions larger than 4 nm), ionic concentration is too low in nanochannels for the continuum assumption to be valid. On the other hand, the non-continuum based approaches are too time-consuming and therefore is limited to simple geometries, in practice. Here, to propose an efficient hybrid continuum-atomistic method of modelling the electrokinetics in nanochannels; the fluid flow and electric potential are computed based on continuum hypothesis coupled with an atomistic Lagrangian approach for the ionic transport. The results of the model are compared to and validated by the results of the molecular dynamics technique for a couple of case studies. Then, the influences of bulk ionic concentration, external electric field, size of nanochannel, and surface electric charge on the electrokinetic flow and ionic mass transfer are investigated, carefully. The hybrid continuum-atomistic method is a promising approach to model more complicated geometries and investigate more details of the electrokinetics in nanofluidics. PMID:27155300
A hybrid likelihood algorithm for risk modelling.
Kellerer, A M; Kreisheimer, M; Chmelevsky, D; Barclay, D
1995-03-01
The risk of radiation-induced cancer is assessed through the follow-up of large cohorts, such as atomic bomb survivors or underground miners who have been occupationally exposed to radon and its decay products. The models relate to the dose, age and time dependence of the excess tumour rates, and they contain parameters that are estimated in terms of maximum likelihood computations. The computations are performed with the software package EPI-CURE, which contains the two main options of person-by person regression or of Poisson regression with grouped data. The Poisson regression is most frequently employed, but there are certain models that require an excessive number of cells when grouped data are used. One example involves computations that account explicitly for the temporal distribution of continuous exposures, as they occur with underground miners. In past work such models had to be approximated, but it is shown here that they can be treated explicitly in a suitably reformulated person-by person computation of the likelihood. The algorithm uses the familiar partitioning of the log-likelihood into two terms, L1 and L0. The first term, L1, represents the contribution of the 'events' (tumours). It needs to be evaluated in the usual way, but constitutes no computational problem. The second term, L0, represents the event-free periods of observation. It is, in its usual form, unmanageable for large cohorts. However, it can be reduced to a simple form, in which the number of computational steps is independent of cohort size. The method requires less computing time and computer memory, but more importantly it leads to more stable numerical results by obviating the need for grouping the data. The algorithm may be most relevant to radiation risk modelling, but it can facilitate the modelling of failure-time data in general. PMID:7604154
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.
A hybrid modelling approach for predicting ground vibration from trains
NASA Astrophysics Data System (ADS)
Triepaischajonsak, N.; Thompson, D. J.
2015-01-01
The prediction of ground vibration from trains presents a number of difficulties. The ground is effectively an infinite medium, often with a layered structure and with properties that may vary greatly from one location to another. The vibration from a passing train forms a transient event, which limits the usefulness of steady-state frequency domain models. Moreover, there is often a need to consider vehicle/track interaction in more detail than is commonly used in frequency domain models, such as the 2.5D approach, while maintaining the computational efficiency of the latter. However, full time-domain approaches involve large computation times, particularly where three-dimensional ground models are required. Here, a hybrid modelling approach is introduced. The vehicle/track interaction is calculated in the time domain in order to be able t account directly for effects such as the discrete sleeper spacing. Forces acting on the ground are extracted from this first model and used in a second model to predict the ground response at arbitrary locations. In the present case the second model is a layered ground model operating in the frequency domain. Validation of the approach is provided by comparison with an existing frequency domain model. The hybrid model is then used to study the sleeper-passing effect, which is shown to be less significant than excitation due to track unevenness in all the cases considered.
Reverse engineering cellular decisions for hybrid reconfigurable network modeling
NASA Astrophysics Data System (ADS)
Blair, Howard A.; Saranak, Jureepan; Foster, Kenneth W.
2011-06-01
Cells as microorganisms and within multicellular organisms make robust decisions. Knowing how these complex cells make decisions is essential to explain, predict or mimic their behavior. The discovery of multi-layer multiple feedback loops in the signaling pathways of these modular hybrid systems suggests their decision making is sophisticated. Hybrid systems coordinate and integrate signals of various kinds: discrete on/off signals, continuous sensory signals, and stochastic and continuous fluctuations to regulate chemical concentrations. Such signaling networks can form reconfigurable networks of attractors and repellors giving them an extra level of organization that has resilient decision making built in. Work on generic attractor and repellor networks and on the already identified feedback networks and dynamic reconfigurable regulatory topologies in biological cells suggests that biological systems probably exploit such dynamic capabilities. We present a simple behavior of the swimming unicellular alga Chlamydomonas that involves interdependent discrete and continuous signals in feedback loops. We show how to rigorously verify a hybrid dynamical model of a biological system with respect to a declarative description of a cell's behavior. The hybrid dynamical systems we use are based on a unification of discrete structures and continuous topologies developed in prior work on convergence spaces. They involve variables of discrete and continuous types, in the sense of type theory in mathematical logic. A unification such as afforded by convergence spaces is necessary if one wants to take account of the affect of the structural relationships within each type on the dynamics of the system.
Hybrid models of the neuromusculoskeletal system improve subject-specificity
Higginson, Jill S; Ramsay, John W; Buchanan, Thomas S
2013-01-01
Muscle-actuated simulations of pathological gait have the capacity to identify muscle impairments and compensatory strategies, but the lack of subject-specific solutions prevents the prescription of personalized therapies. Conversely, electromyographic-driven models are limited to muscles for which data are available but can capture the true neural drive initiated by an individual subject. In order to improve subject-specificity and enforce physiological constraints on muscle activity, we propose a hybrid strategy for the optimization of subject-specific muscle patterns that involves forward dynamic simulation of whole body movement coupled with electromyographic-driven models of muscle subsets. In this paper we apply the hybrid approach to an example of post-stroke gait and demonstrate its unique ability to account for the unusual muscle activation patterns and muscle properties in patients with neuromuscular impairments. PMID:22468463
Hybrid Modeling of Elastic Wave Scattering in a Welded Cylinder
NASA Astrophysics Data System (ADS)
Mahmoud, A.; Shah, A. H.; Popplewell, N.
2003-03-01
In the present study, a 3D hybrid method, which couples the finite element region with guided elastic wave modes, is formulated to investigate the scattering by a non-axisymmetric crack in a welded steel pipe. The algorithm is implemented on a parallel computing platform. Implementation is facilitated by the dynamic memory allocation capabilities of Fortran 90™ and the parallel processing directives of OpenMp™. The algorithm is validated against available numerical results. The agreement with a previous 2D hybrid model is excellent. Novel results are presented for the scattering of the first longitudinal mode from different non-axisymmetric cracks. The trend of the new results is consistent with the previous findings for the axisymmetric case. The developed model has potential application in ultrasonic nondestructive evaluation of welded steel pipes.
Stochastic linear hybrid systems: Modeling, estimation, and application
NASA Astrophysics Data System (ADS)
Seah, Chze Eng
Hybrid systems are dynamical systems which have interacting continuous state and discrete state (or mode). Accurate modeling and state estimation of hybrid systems are important in many applications. We propose a hybrid system model, known as the Stochastic Linear Hybrid System (SLHS), to describe hybrid systems with stochastic linear system dynamics in each mode and stochastic continuous-state-dependent mode transitions. We then develop a hybrid estimation algorithm, called the State-Dependent-Transition Hybrid Estimation (SDTHE) algorithm, to estimate the continuous state and discrete state of the SLHS from noisy measurements. It is shown that the SDTHE algorithm is more accurate or more computationally efficient than existing hybrid estimation algorithms. Next, we develop a performance analysis algorithm to evaluate the performance of the SDTHE algorithm in a given operating scenario. We also investigate sufficient conditions for the stability of the SDTHE algorithm. The proposed SLHS model and SDTHE algorithm are illustrated to be useful in several applications. In Air Traffic Control (ATC), to facilitate implementations of new efficient operational concepts, accurate modeling and estimation of aircraft trajectories are needed. In ATC, an aircraft's trajectory can be divided into a number of flight modes. Furthermore, as the aircraft is required to follow a given flight plan or clearance, its flight mode transitions are dependent of its continuous state. However, the flight mode transitions are also stochastic due to navigation uncertainties or unknown pilot intents. Thus, we develop an aircraft dynamics model in ATC based on the SLHS. The SDTHE algorithm is then used in aircraft tracking applications to estimate the positions/velocities of aircraft and their flight modes accurately. Next, we develop an aircraft conformance monitoring algorithm to detect any deviations of aircraft trajectories in ATC that might compromise safety. In this application, the SLHS
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.
Hybrid Surface Mesh Adaptation for Climate Modeling
Khamayseh, Ahmed K; de Almeida, Valmor F; Hansen, Glen
2008-01-01
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.
Swine hybrid aneurysm model for endovascular surgery training.
Namba, K; Mashio, K; Kawamura, Y; Higaki, A; Nemoto, S
2013-06-01
The aim of this study was to develop a technically simple swine aneurysm-training model by inserting a silicone aneurysm circuit in the cervical vessels. A silicone aneurysm circuit was created by designing multiple aneurysms in size and configuration on a silicone vessel. Five swine underwent surgical implantation of this circuit in the cervical vessels: one end in the common carotid artery and the other in the external jugular vein. Using this model, an aneurysm coiling procedure was simulated under fluoroscopic guidance, roadmapping and digital subtraction angiography. Creating an aneurysm model for training purposes by this method was technically simple and enabled the formation of a wide variety of aneurysms in a single procedure. The quality of the model was uniform and the model was reproducible. Coiling training using this model resembled a realistic clinical situation. The swine hybrid aneurysm-training model was advantageous from the standpoint of technical simplicity in the creation and variety of aneurysms it provided. The swine hybrid aneurysm model may be an additional option for aneurysm coiling training. PMID:23693037
Swine Hybrid Aneurysm Model for Endovascular Surgery Training
Namba, K.; Mashio, K.; Kawamura, Y.; Higaki, A.; Nemoto, S.
2013-01-01
Summary The aim of this study was to develop a technically simple swine aneurysm-training model by inserting a silicone aneurysm circuit in the cervical vessels. A silicone aneurysm circuit was created by designing multiple aneurysms in size and configuration on a silicone vessel. Five swine underwent surgical implantation of this circuit in the cervical vessels: one end in the common carotid artery and the other in the external jugular vein. Using this model, an aneurysm coiling procedure was simulated under fluoroscopic guidance, roadmapping and digital subtraction angiography. Creating an aneurysm model for training purposes by this method was technically simple and enabled the formation of a wide variety of aneurysms in a single procedure. The quality of the model was uniform and the model was reproducible. Coiling training using this model resembled a realistic clinical situation. The swine hybrid aneurysm-training model was advantageous from the standpoint of technical simplicity in the creation and variety of aneurysms it provided. The swine hybrid aneurysm model may be an additional option for aneurysm coiling training. PMID:23693037
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.
Hybrid and adaptive meta-model-based global optimization
NASA Astrophysics Data System (ADS)
Gu, J.; Li, G. Y.; Dong, Z.
2012-01-01
As an efficient and robust technique for global optimization, meta-model-based search methods have been increasingly used in solving complex and computation intensive design optimization problems. In this work, a hybrid and adaptive meta-model-based global optimization method that can automatically select appropriate meta-modelling techniques during the search process to improve search efficiency is introduced. The search initially applies three representative meta-models concurrently. Progress towards a better performing model is then introduced by selecting sample data points adaptively according to the calculated values of the three meta-models to improve modelling accuracy and search efficiency. To demonstrate the superior performance of the new algorithm over existing search methods, the new method is tested using various benchmark global optimization problems and applied to a real industrial design optimization example involving vehicle crash simulation. The method is particularly suitable for design problems involving computation intensive, black-box analyses and simulations.
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.
Towards a hybrid dynamo model for the Milky Way
NASA Astrophysics Data System (ADS)
Gressel, Oliver; Elstner, Detlef; Ziegler, Udo
2013-12-01
Context. Based on the rapidly increasing all-sky data of Faraday rotation measures and polarised synchrotron radiation, the Milky Way's magnetic field can now be modelled with an unprecedented level of detail and complexity. Aims: We aim to complement this phenomenological approach with a physically motivated, quantitative dynamo model - a model that moreover allows for the evolution of the system as a whole, instead of just solving the induction equation for a fixed static disc. Methods: Building on the framework of mean-field magnetohydrodynamics and extending it to the realm of a hybrid evolution, we performed three-dimensional global simulations of the Galactic disc. To eliminate free parameters, closure coefficients embodying the mean-field dynamo were calibrated against resolved local simulations of supernova-driven interstellar turbulence. Results: The emerging dynamo solutions comprise a mixture of the dominant axisymmetric S0 mode with even parity, and a subdominant A0 mode with odd parity. Notably, this superposition of modes creates a strong localised vertical field on one side of the Galactic disc. Moreover, we found significant radial pitch angles that decay with radius, which can be explained by flaring of the disc. In accordance with previous work, magnetic instabilities appear to be restricted to the calmer outer Galactic disc. Their main effect is to create strong fields at large radii such that the radial scale length of the magnetic field increases from 4 kpc (for a mean-field dynamo alone) to about 10 kpc in the hybrid models - the latter being in much better agreement with observations. Conclusions: There remain aspects (e.g., spiral arms, X-shaped halo fields, fluctuating fields) that are not captured by the current model and that will require further development towards a fully dynamical evolution. Nevertheless, we demonstrate that a hybrid modelling of the Galactic dynamo is feasible and can serve as a foundation for future efforts.
Hybrid modeling and receding horizon control of sewer networks
NASA Astrophysics Data System (ADS)
Joseph-Duran, Bernat; Ocampo-Martinez, Carlos; Cembrano, Gabriela
2014-11-01
In this work, a control-oriented sewer network model is presented based on a hybrid linear modeling framework. The model equations are described independently for each network element, thus allowing the model to be applied to a broad class of networks. A parameter calibration procedure using data obtained from simulation software that solves the physically based model equations is described and validation results are given for a case study. Using the control model equations, an optimal control problem to minimize flooding and pollution is formulated to be solved by means of mixed-integer linear or quadratic programming. A receding horizon control strategy based on this optimal control problem is applied to the case study using the simulation software as a virtual reality. Results of this closed-loop simulation tests show the effectiveness of the proposed approach in fulfilling the control objectives while complying with physical and operational constraints.
Distributed Hybridization Model for Quantum Critical Behavior in Magnetic Quasicrystals
NASA Astrophysics Data System (ADS)
Otsuki, Junya; Kusunose, Hiroaki
2016-07-01
A quantum critical behavior of the magnetic susceptibility was observed in a quasicrystal containing ytterbium. At the same time, a mixed-valence feature of Yb ions was reported, which appears to be incompatible with the magnetic instability. We derive the magnetic susceptibility by expressing the quasiperiodicity as the distributed hybridization strength between Yb 4f and conduction electrons. Assuming a wide distribution of the hybridization strength, the most f electrons behave as renormalized paramagnetic states in the Kondo or mixed-valence regime, but a small number of f moments remain unscreened. As a result, the bulk magnetic susceptibility exhibits a nontrivial power-law-like behavior, while the average f-electron occupation is that of mixed-valence systems. This model thus resolves two contradictory properties of Yb quasicrystals.
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.
A hybrid routing model for mitigating congestion in networks
NASA Astrophysics Data System (ADS)
He, Kun; Xu, Zhongzhi; Wang, Pu
2015-08-01
Imbalance between fast-growing transport demand and limited network supply has resulted in severe congestion in many transport networks. Increasing network supply or reducing transport demand could mitigate congestion, but these remedies are usually associated with high implementation cost. Combining shortest path (SP) routing and minimum cost (MC) routing, we developed a hybrid routing model to alleviate congestion in networks. This model requires only a small fraction of the total number of agents to use MC routes, and effectively mitigates congestion in networks under homogeneous or heterogeneous transport demand, offering new insights for improving the efficiency of practical transport networks.
Hybrid system modeling, simulation, and visualization: a crane system
NASA Astrophysics Data System (ADS)
Hiniduma Udugama Gamage, Sahan S.; Palmer, Patrick R.
2003-08-01
Modeling and visualization of a complex hybrid system with different domains of energy flow and signal flow are described in this paper. It is a crane system situated in a barge complete with the load, electrical power, drive and control systems. A dynamically and functionally accurate model of the crane was developed. The implementation is in the freely available software suit of Virtual Test Bed (VTB) for simulation and Visual Extension Engine (VXE) for visualization. The bidirectional interaction of simulator and visualizer is fully utilized in this application. The further challenges confronted in implementing this particular system and any other complex system are discussed and possible solutions are suggested.
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.
KGEOID12: A new hybrid geoid model in Korea
NASA Astrophysics Data System (ADS)
Lee, D. H.; Sim, S.
2014-12-01
This study describes in brief the development of a new hybrid geoid model, KGEOID12, which can be used as an accurate vertical datum in Korea. The hybrid geoid model is generally determined by fitting the gravimetric geoid to the geometric geoid undulations from GPS/Levelling data which were presented the local vertical level. For developing the gravimetric geoid model, we performed an optimal remove-restore technique based on the earth gravitaional model 2008 (EGM2008) reference surface. In remove-restore technique, EGM2008 model was analyzed up to harmonic degree and order 2,160, 4-band spherical fast fourier transformation (FFT) with modified stokes kernel and residual terrain model (RTM) reduction method were used for calculating the long, middle and short-frequency part of gravimetric geoid, respectively. A number of land and shipborne gravity data were compiled for modelling the middle-frequency part. A digital elevation model (DEM) gridded by 100m×100m were used for short-frequency part. The accuracy of gravimetric geoid model were evaluated by comparison with geometric geoid ontained from all available GPS/Levelling data in Korea which was about ± 0.107 m with a mean value of -0.360 m. Finally, we developed the hybrid geoid model in Korea, KGEOID12, corrected to gravimetric geoid model with a correction term derived from GPS/leveling data. The correction term is modelled using differences between gravimetric and geometric geoidal undulations at 1,185 GPS/Leveling data. The stochastic model used in the calculation of correction term is a least square collocation method based on second-order Markov covariance function. The post-fit error (mean and std. dev.) of the KGEOID12 was evaluated as 0.001 m ± 0.043 m. This result indicated that KGEOID12 can be used as a vertical datum to determine the height information with a few cm-leveled precision by combining a GNSS positioning technique in Korea.
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.
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.
Application of continuum- and hybrid models in karst spring catchments
NASA Astrophysics Data System (ADS)
Rehrl, Christoph; Birk, Steffen
2010-05-01
Flow in karst aquifers is concentrated along highly permeable solution conduits embedded in the much less permeable fissured system of the surrounding rock. This complex and heterogeneous flow regime can be conceptualized as dual flow systems composed of slow, laminar flow in the fractured porous matrix as opposed to rapid, often turbulent flow in solution conduits. Flow in the fractured porous rock can be treated as a continuous flow field (continuum model), whereas flow in the conduit system is spatially localized and can be modelled by a discrete pipe network model. Hybrid models couple both flow systems and have frequently been employed in basic research, e.g., to simulate and analyse the mechanism of speleogenesis. In many practical applications, however, continuum models are employed. In these models the two flow components are lumped together and the conduits are represented by highly permeable cells (smeared conduit approach). Standard groundwater models imply that conduit flow is represented by a Darcian approach, thus ignoring potential effects of turbulent flow. On this account the USGS has recently released a MODFLOW-2005 Conduit Flow Process (CFP), which makes it possible to account for turbulent flow in the continuum approach (CFP mode 2). Additionally a discrete pipe network model can be coupled to MODFLOW. This hybrid model (CFP mode 1) employs the Darcy-Weisbach equation to represent turbulent flow in the karst conduits. In this work, it is attempted to simulate the discharge hydrographs of a hypothetical karst spring catchment in which conduit systems are embedded in fissured porous rock using both the single-continuum approach (CFP mode 2) and the hybrid model (CFP mode 1). This study shows that the hydraulic response of the spring signal is influenced by the flow conditions in the conduit, i.e. the shape of the spring hydrograph predicted by a model that accounts for turbulent flow differs from that obtained with a laminar flow model. This
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. PMID:15724280
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
2010-01-01
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, XIC, 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 XIC, 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. PMID:21151444
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.
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)…
A hybrid model for improving response time in distributed data mining.
Krishnaswamy, Shonali; Loke, Seng W; Zaslasvky, Arkady
2004-12-01
This paper presents a hybrid distributed data mining (DDM) model for optimization of response time. The model combines a mobile agent approach with client server strategies to reduce the overall response time. The hybrid model proposes and develops accurate a priori estimates of the computation and communication components of response time as the costing strategy to support optimization. Experimental evaluation of the hybrid model is presented. PMID:15619946
A hybrid model for improving response time in distributed data mining.
Krishnaswamy, Shonali; Loke, Seng W; Zaslasvky, Arkady
2004-12-01
This paper presents a hybrid distributed data mining (DDM) model for optimization of response time. The model combines a mobile agent approach with client server strategies to reduce the overall response time. The hybrid model proposes and develops accurate a priori estimates of the computation and communication components of response time as the costing strategy to support optimization. Experimental evaluation of the hybrid model is presented.
ANN hybrid model versus ARIMA and ARIMAX models of runoff coefficient
NASA Astrophysics Data System (ADS)
Pektaş, Ali Osman; Kerem Cigizoglu, H.
2013-09-01
In this study, monthly runoff coefficients of seven southern large basins are calculated and modeled to forecast a holdout dataset by using univariate autoregressive integrated moving average (ARIMA), multivariate ARIMA (ARIMAX), and Artificial neural network (ANN) models. The applied traditional model performances are found insufficient, since the characteristic behaviors of the time series of direct runoff coefficients are very complicated. Therefore, a new Hybrid approach is adopted by using time series decomposition procedure and ANN. ARIMA, ARIMAX, ANN, and Hybrid models are compared with each other. The results indicate that the new generated Hybrid approach can be generalized to boost the prediction capability of ANNs in complicated time series data. It is seen that the new model captures the physical behavior of the direct runoff coefficient time series. The semi-random spikes of the direct runoff coefficient series are approximated sufficiently.
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.
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.
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. PMID:26635639
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
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
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.
Krasnopolsky, Vladimir M; Fox-Rabinovitz, Michael S
2006-03-01
A new practical application of neural network (NN) techniques to environmental numerical modeling has been developed. Namely, a new type of numerical model, a complex hybrid environmental model based on a synergetic combination of deterministic and machine learning model components, has been introduced. Conceptual and practical possibilities of developing hybrid models are discussed in this paper for applications to climate modeling and weather prediction. The approach presented here uses NN as a statistical or machine learning technique to develop highly accurate and fast emulations for time consuming model physics components (model physics parameterizations). The NN emulations of the most time consuming model physics components, short and long wave radiation parameterizations or full model radiation, presented in this paper are combined with the remaining deterministic components (like model dynamics) of the original complex environmental model--a general circulation model or global climate model (GCM)--to constitute a hybrid GCM (HGCM). The parallel GCM and HGCM simulations produce very similar results but HGCM is significantly faster. The speed-up of model calculations opens the opportunity for model improvement. Examples of developed HGCMs illustrate the feasibility and efficiency of the new approach for modeling complex multidimensional interdisciplinary systems.
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.
Hybrid Modeling Method for a DEP Based Particle Manipulation
Miled, Mohamed Amine; Gagne, Antoine; Sawan, Mohamad
2013-01-01
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. PMID:23364197
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.
Axelrod Model of Social Influence with Cultural Hybridization
NASA Astrophysics Data System (ADS)
Radillo-Díaz, Alejandro; Pérez, Luis A.; Del Castillo-Mussot, Marcelo
2012-10-01
Since cultural interactions between a pair of social agents involve changes in both individuals, we present simulations of a new model based on Axelrod's homogenization mechanism that includes hybridization or mixture of the agents' features. In this new hybridization model, once a cultural feature of a pair of agents has been chosen for the interaction, the average of the values for this feature is reassigned as the new value for both agents after interaction. Moreover, a parameter representing social tolerance is implemented in order to quantify whether agents are similar enough to engage in interaction, as well as to determine whether they belong to the same cluster of similar agents after the system has reached the frozen state. The transitions from a homogeneous state to a fragmented one decrease in abruptness as tolerance is increased. Additionally, the entropy associated to the system presents a maximum within the transition, the width of which increases as tolerance does. Moreover, a plateau was found inside the transition for a low-tolerance system of agents with only two cultural features.
A convergent hybrid decomposition algorithm model for SVM training.
Lucidi, Stefano; Palagi, Laura; Risi, Arnaldo; Sciandrone, Marco
2009-06-01
Training of support vector machines (SVMs) requires to solve a linearly constrained convex quadratic problem. In real applications, the number of training data may be very huge and the Hessian matrix cannot be stored. In order to take into account this issue, a common strategy consists in using decomposition algorithms which at each iteration operate only on a small subset of variables, usually referred to as the working set. Training time can be significantly reduced by using a caching technique that allocates some memory space to store the columns of the Hessian matrix corresponding to the variables recently updated. The convergence properties of a decomposition method can be guaranteed by means of a suitable selection of the working set and this can limit the possibility of exploiting the information stored in the cache. We propose a general hybrid algorithm model which combines the capability of producing a globally convergent sequence of points with a flexible use of the information in the cache. As an example of a specific realization of the general hybrid model, we describe an algorithm based on a particular strategy for exploiting the information deriving from a caching technique. We report the results of computational experiments performed by simple implementations of this algorithm. The numerical results point out the potentiality of the approach.
Numerical modeling of DNA-chip hybridization with chaotic advection
Raynal, Florence; Beuf, Aurélien; Carrière, Philippe
2013-01-01
We present numerical simulations of DNA-chip hybridization, both in the “static” and “dynamical” cases. In the static case, transport of free targets is limited by molecular diffusion; in the dynamical case, an efficient mixing is achieved by chaotic advection, with a periodic protocol using pumps in a rectangular chamber. This protocol has been shown to achieve rapid and homogeneous mixing. We suppose in our model that all free targets are identical; the chip has different spots on which the probes are fixed, also all identical, and complementary to the targets. The reaction model is an infinite sink potential of width dh, i.e., a target is captured as soon as it comes close enough to a probe, at a distance lower than dh. Our results prove that mixing with chaotic advection enables much more rapid hybridization than the static case. We show and explain why the potential width dh does not play an important role in the final results, and we discuss the role of molecular diffusion. We also recover realistic reaction rates in the static case. PMID:24404027
A versatile optical model for hybrid rendering of volume data.
Yang, Fei; Li, Qingde; Xiang, Dehui; Cao, Yong; Tian, Jie
2012-06-01
In volume rendering, most optical models currently in use are based on the assumptions that a volumetric object is a collection of particles and that the macro behavior of particles, when they interact with light rays, can be predicted based on the behavior of each individual particle. However, such models are not capable of characterizing the collective optical effect of a collection of particles which dominates the appearance of the boundaries of dense objects. In this paper, we propose a generalized optical model that combines particle elements and surface elements together to characterize both the behavior of individual particles and the collective effect of particles. The framework based on a new model provides a more powerful and flexible tool for hybrid rendering of isosurfaces and transparent clouds of particles in a single scene. It also provides a more rational basis for shading, so the problem of normal-based shading in homogeneous regions encountered in conventional volume rendering can be easily avoided. The model can be seen as an extension to the classical model. It can be implemented easily, and most of the advanced numerical estimation methods previously developed specifically for the particle-based optical model, such as preintegration, can be applied to the new model to achieve high-quality rendering results.
Hybrid modeling of direct and inverse problems of heat conduction
NASA Astrophysics Data System (ADS)
Matsevityi, Yu. M.
1981-02-01
The article explains the method of solving nonlinear problems of heat conduction with the aid of hybrid computer systems. It examines the possibility of using hybrid systems for realizing the method of optimum dynamic filtration.
Titan's Midrange Magnetotail from Cassini Observations and Hybrid Modeling
NASA Astrophysics Data System (ADS)
Feyerabend, M.; Simon, S.; Saur, J.; Motschmann, U. M.
2014-12-01
We study Titan's plasma interaction during Cassini's midrange tail encounters T9, T63 and T75. During each of these flybys, the Cassini Plasma Spectrometer detected a peculiar split signature in Titan's pickup tail, i.e. the spacecraft passed through two spatially separated cold ion populations of different masses. Whether this might be an omnipresent feature of Titan's plasma interacting or a result of non-stationary upstream conditions is still unclear. To explain these features, we apply the hybrid simulation code AIKEF. The latest version of this code includes chemical reactions, a realistic and statistically consistent photoionization model and recombination for a sophisticated description of the ionospheric composition of Titan. To validate the ionosphere model, we compare its output against measurements of the magnetic field and the electron density from the T70 flyby, which reached the lowest altitude of all flybys and had nearly ideal upstream conditions with the magnetic field pointing southward.
Buckling induced delamination of graphene composites through hybrid molecular modeling
NASA Astrophysics Data System (ADS)
Cranford, Steven W.
2013-01-01
The efficiency of graphene-based composites relies on mechanical stability and cooperativity, whereby separation of layers (i.e., delamination) can severely hinder performance. Here we study buckling induced delamination of mono- and bilayer graphene-based composites, utilizing a hybrid full atomistic and coarse-grained molecular dynamics approach. The coarse-grain model allows exploration of an idealized model material to facilitate parametric variation beyond any particular molecular structure. Through theoretical and simulation analyses, we show a critical delamination condition, where ΔD∝kL4, where ΔD is the change in bending stiffness (eV), k the stiffness of adhesion (eV/Å4), and L the length of the adhered section (Å).
Evaluating gene set enrichment analysis via a hybrid data model.
Hua, Jianping; Bittner, Michael L; Dougherty, Edward R
2014-01-01
Gene set enrichment analysis (GSA) methods have been widely adopted by biological labs to analyze data and generate hypotheses for validation. Most of the existing comparison studies focus on whether the existing GSA methods can produce accurate P-values; however, practitioners are often more concerned with the correct gene-set ranking generated by the methods. The ranking performance is closely related to two critical goals associated with GSA methods: the ability to reveal biological themes and ensuring reproducibility, especially for small-sample studies. We have conducted a comprehensive simulation study focusing on the ranking performance of seven representative GSA methods. We overcome the limitation on the availability of real data sets by creating hybrid data models from existing large data sets. To build the data model, we pick a master gene from the data set to form the ground truth and artificially generate the phenotype labels. Multiple hybrid data models can be constructed from one data set and multiple data sets of smaller sizes can be generated by resampling the original data set. This approach enables us to generate a large batch of data sets to check the ranking performance of GSA methods. Our simulation study reveals that for the proposed data model, the Q2 type GSA methods have in general better performance than other GSA methods and the global test has the most robust results. The properties of a data set play a critical role in the performance. For the data sets with highly connected genes, all GSA methods suffer significantly in performance.
A hybrid absorbing boundary condition for frequency-domain finite-difference modelling
NASA Astrophysics Data System (ADS)
Ren, Zhiming; Liu, Yang
2013-10-01
Liu and Sen (2010 Geophysics 75 A1-6 2012 Geophys. Prospect. 60 1114-32) proposed an efficient hybrid scheme to significantly absorb boundary reflections for acoustic and elastic wave modelling in the time domain. In this paper, we extend the hybrid absorbing boundary condition (ABC) into the frequency domain and develop specific strategies for regular-grid and staggered-grid modelling, respectively. Numerical modelling tests of acoustic, visco-acoustic, elastic and vertically transversely isotropic (VTI) equations show significant absorptions for frequency-domain modelling. The modelling results of the Marmousi model and the salt model also demonstrate the effectiveness of the hybrid ABC. For elastic modelling, the hybrid Higdon ABC and the hybrid Clayton and Engquist (CE) ABC are implemented, respectively. Numerical simulations show that the hybrid Higdon ABC gets better absorption than the hybrid CE ABC, especially for S-waves. We further compare the hybrid ABC with the classical perfectly matched layer (PML). Results show that the two ABCs cost the same computation time and memory space for the same absorption width. However, the hybrid ABC is more effective than the PML for the same small absorption width and the absorption effects of the two ABCs gradually become similar when the absorption width is increased.
Protein modeling with hybrid Hidden Markov Model/Neurel network architectures
Baldi, P.; Chauvin, Y.
1995-12-31
Hidden Markov Models (HMMs) are useful in a number of tasks in computational molecular biology, and in particular to model and align protein families. We argue that HMMs are somewhat optimal within a certain modeling hierarchy. Single first order HMMs, however, have two potential limitations: a large number of unstructured parameters, and a built-in inability to deal with long-range dependencies. Hybrid HMM/Neural Network (NN) architectures attempt to overcome these limitations. In hybrid HMM/NN, the HMM parameters are computed by a NN. This provides a reparametrization that allows for flexible control of model complexity, and incorporation of constraints. The approach is tested on the immunoglobulin family. A hybrid model is trained, and a multiple alignment derived, with less than a fourth of the number of parameters used with previous single HMMs. To capture dependencies, however, one must resort to a larger hybrid model class, where the data is modeled by multiple HMMs. The parameters of the HMMs, and their modulation as a function of input or context, is again calculated by a NN.
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 Hybrid Micro-Scale Model for Transport in Connected Macro-Pores in Porous Media
Ryan, Emily M.; Tartakovsky, Alexandre M.
2011-07-13
This paper presents a multi-scale approach for modeling the transport of species in fractured porous media. The multi-scale approach consists of a hybrid model and a pore-scale model that is used to parameterize the hybrid model. The hybrid model explicitly models the advection and diffusion of species in the fracture and treats the porous matrix as a continuum with effective transport properties. The pore-scale model is used to calculate the effective transport properties of the hybrid model. This approach negates the need to calibrate the hybrid model against experimental data, which is common for continuum-scale models of porous media, and allows an arbitrary microstructure to be considered. The paper presents the multi-scale modeling approach along with the details of the hybrid and pore-scale models. Validation of the model is also presented along with several case studies investigating the applicability of the multi-scale modeling approach to different geometries and transport conditions. The case studies show that the multi-scale modeling approach is accurate for various fracture geometries given that the matrix porosity is sufficiently small. The accuracy of the hybrid model decreases with increasing porosity of the matrix.
A hybrid scalar model for sooting turbulent flames
Aksit, I.M.; Moss, J.B.
2006-04-15
A Lagrangian Monte Carlo solution of the joint scalar pdf transport equation for mixture fraction and representative soot properties, coupled with an Eulerian solution for the turbulent flow field and here described as a 'hybrid model,' has been developed. The modeling of soot formation and destruction employs an existing description of the key processes based on two soot variables-the soot volume fraction (or mass concentration) and the particle number density. The gas-phase chemistry is introduced through flamelet-state relationships. The simulation strategy is based on tracing the evolution of reactive stochastic particles within the computational domain. The ensemble of these particles at a fixed location and time then describes the joint scalar pdf. Soot rate equations, represented as functions of mixture fraction, soot mass concentration, and number density, are solved exactly in terms of the scalar values of each individual stochastic particle and the associated gas-phase properties derived from laminar flamelet-state relationships. The solution for the turbulent flow field provides the mean velocity and mixing frequency required for the transport of the stochastic particles in both physical and compositional space, while the Monte Carlo simulation returns the computed mean density field to the CFD code. Density-weighted mean values are approximated by ensemble averages over the scalar values of the stochastic particles in individual computational cells. The principal objective of the hybrid model is the improved treatment of nonlinear soot formation and oxidation, in particular, the capture of the intermittency in the oxidation process associated with the noncoexistence of soot and the principal oxidizing species. Significant computational economies accompany the adoption of the laminar flamelet approach for the source terms in the soot rate equations and the reduced number of scalars computed stochastically. (author)
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.
Hybrid Plume Dispersion Model (HPDM) development and evaluation
Hanna, S.R.; Paine, R.J.
1989-03-01
The Hybrid Plume Dispersion Model (HPDM) was developed for application to tall stack plumes dispersing over nearly flat terrain. Emphasis is on convective and high-wind conditions. The meteorological component is based on observational and modeling studies of the planetary boundary layer. The dispersion estimates for the convective boundary layer (CBL) were developed from laboratory experiments and field studies and incorporate convecting scaling, i.e., the convective velocity scale w/sub */, and the CBL height, h, which are the relevant velocity and length scales of the turbulence. The model has a separate component to handle the dispersion of highly buoyant plumes that remain near the top of the CBL and resist downward mixing. For convective conditions, the vertical concentration distribution is non-Gaussian, but for neutral and stable conditions it is assumed to be Gaussian. The HPDM performance is assessed with extensive ground-level concentration measurements around the Kincaid, Illinois, and Bull Run, Tennessee, power plants. It was also tested with limited data during high-winded conditions at five other power plants. The model is found to be an improvement over the standard regulatory model, MPTER, during light-wind convective conditions and high-wind neutral conditions.
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.
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 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.
Hybrid Reduced Order Modeling Algorithms for Reactor Physics Calculations
NASA Astrophysics Data System (ADS)
Bang, Youngsuk
hybrid ROM algorithms which can be readily integrated into existing methods and offer higher computational efficiency and defendable accuracy of the reduced models. For example, the snapshots ROM algorithm is hybridized with the range finding algorithm to render reduction in the state space, e.g. the flux in reactor calculations. In another implementation, the perturbation theory used to calculate first order derivatives of responses with respect to parameters is hybridized with a forward sensitivity analysis approach to render reduction in the parameter space. Reduction at the state and parameter spaces can be combined to render further reduction at the interface between different physics codes in a multi-physics model with the accuracy quantified in a similar manner to the single physics case. Although the proposed algorithms are generic in nature, we focus here on radiation transport models used in support of the design and analysis of nuclear reactor cores. In particular, we focus on replacing the traditional assembly calculations by ROM models to facilitate the generation of homogenized cross-sections for downstream core calculations. The implication is that assembly calculations could be done instantaneously therefore precluding the need for the expensive evaluation of the few-group cross-sections for all possible core conditions. Given the generic natures of the algorithms, we make an effort to introduce the material in a general form to allow non-nuclear engineers to benefit from this work.
A hybrid multiview stereo algorithm for modeling urban scenes.
Lafarge, Florent; Keriven, Renaud; Brédif, Mathieu; Vu, Hoang-Hiep
2013-01-01
We present an original multiview stereo reconstruction algorithm which allows the 3D-modeling of urban scenes as a combination of meshes and geometric primitives. The method provides a compact model while preserving details: Irregular elements such as statues and ornaments are described by meshes, whereas regular structures such as columns and walls are described by primitives (planes, spheres, cylinders, cones, and tori). We adopt a two-step strategy consisting first in segmenting the initial meshbased surface using a multilabel Markov Random Field-based model and second in sampling primitive and mesh components simultaneously on the obtained partition by a Jump-Diffusion process. The quality of a reconstruction is measured by a multi-object energy model which takes into account both photo-consistency and semantic considerations (i.e., geometry and shape layout). The segmentation and sampling steps are embedded into an iterative refinement procedure which provides an increasingly accurate hybrid representation. Experimental results on complex urban structures and large scenes are presented and compared to state-of-the-art multiview stereo meshing algorithms.
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.
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.
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.
Comparison of hybrid Hall thruster model to experimental measurements
NASA Astrophysics Data System (ADS)
Scharfe, Michelle K.; Gascon, Nicolas; Cappelli, Mark A.; Fernandez, Eduardo
2006-08-01
A two-dimensional hybrid particle-in-cell numerical model has been constructed in the radial-axial plane with the intent of examining the physics governing Hall thruster operation. The electrons are treated as a magnetized quasi-one-dimensional fluid and the ions are treated as collisionless, unmagnetized discrete particles. The anomalously high electron conductivity experimentally observed in Hall thrusters is accounted for using experimental measurements of electron mobility in the Stanford Hall Thruster. While an experimental mobility results in improved simulation of electron temperature and electric potential relative to a Bohm-type model, results suggest that energy losses due to electron wall interactions may also be an important factor in accurately simulating plasma properties. Using a simplified electron wall damping model modified to produce general agreement with experimental measurements, an evaluation is made of differing treatments of electron mobility, background gas, neutral wall interactions, and charge exchange collisions. Although background gas results in two populations of neutrals, the increased neutral density has little effect on other plasma properties. Diffuse neutral wall interactions are in better agreement with experimental measurements than specular scattering. Also, charge exchange collisions result in an increase in average neutral velocity of 11% and a decrease in average ion velocity of 4% near the exit plane. The momentum exchange that occurs during charge exchange collisions is found to be negligible.
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.
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).
Thermal-mechanical modeling of laser ablation hybrid machining
NASA Astrophysics Data System (ADS)
Matin, Mohammad Kaiser
2001-08-01
Hard, brittle and wear-resistant materials like ceramics pose a problem when being machined using conventional machining processes. Machining ceramics even with a diamond cutting tool is very difficult and costly. Near net-shape processes, like laser evaporation, produce micro-cracks that require extra finishing. Thus it is anticipated that ceramic machining will have to continue to be explored with new-sprung techniques before ceramic materials become commonplace. This numerical investigation results from the numerical simulations of the thermal and mechanical modeling of simultaneous material removal from hard-to-machine materials using both laser ablation and conventional tool cutting utilizing the finite element method. The model is formulated using a two dimensional, planar, computational domain. The process simulation acronymed, LAHM (Laser Ablation Hybrid Machining), uses laser energy for two purposes. The first purpose is to remove the material by ablation. The second purpose is to heat the unremoved material that lies below the ablated material in order to ``soften'' it. The softened material is then simultaneously removed by conventional machining processes. The complete solution determines the temperature distribution and stress contours within the material and tracks the moving boundary that occurs due to material ablation. The temperature distribution is used to determine the distance below the phase change surface where sufficient ``softening'' has occurred, so that a cutting tool may be used to remove additional material. The model incorporated for tracking the ablative surface does not assume an isothermal melt phase (e.g. Stefan problem) for laser ablation. Both surface absorption and volume absorption of laser energy as function of depth have been considered in the models. LAHM, from the thermal and mechanical point of view is a complex machining process involving large deformations at high strain rates, thermal effects of the laser, removal of
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'…
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. PMID:24574870
Tracking Inter-Regional Carbon Flows: A Hybrid Network Model.
Chen, Shaoqing; Chen, Bin
2016-05-01
The mitigation of anthropogenic carbon emissions has moved beyond the local scale because they diffuse across boundaries, and the consumption that triggers emissions has become regional and global. A precondition of effective mitigation is to explicitly assess inter-regional transfer of emissions. This study presents a hybrid network model to track inter-regional carbon flows by combining network analysis and input-output analysis. The direct, embodied, and controlled emissions associated with regions are quantified for assessing various types of carbon flow. The network-oriented metrics called "controlled emissions" is proposed to cover the amount of carbon emissions that can be mitigated within a region by adjusting its consumption. The case study of the Jing-Jin-Ji Area suggests that CO2 emissions embodied in products are only partially controlled by a region from a network perspective. Controlled carbon accounted for about 70% of the total embodied carbon flows, while household consumption only controlled about 25% of Beijing's emissions, much lower than its proportion of total embodied carbon. In addition to quantifying emissions, the model can pinpoint the dominant processes and sectors of emissions transfer across regions. This technique is promising for searching efficient pathways of coordinated emissions control across various regions connected by trade. PMID:27063784
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 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 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.
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.
Futile Care; Concept Analysis Based on a Hybrid Model
Bahramnezhad, Fatemeh; Cheraghi, Mohammad Ali; Salsali, Mahvash; Asgari, Parvaneh; Fomani, Fatemeh Khoshnavay; Sanjari, Mahnaz; Afshar, Pouya Farokhnezhad
2014-01-01
Background: Making decision about what kind of caring is entitled as futile care requires the presentation of a clear definition of such caretaking. Objective: To report an analysis of the concept of futile care. Design: The analysis in this research was carried out through hybrid model in three stages. At the theoretical stage: a review of the available literature. At the work-in-field stage: semi-structured interviews. Setting: Data collection was on cancer unit and palliative care unit. Participants: A total of 7 participants were recruited in the study. The inclusion criteria were: having at least a bachelor’s degree in nursing, having at least 5 years of experience in critical care or cancer units, and being willing to participate in the study. Results: Three themes emerged: “low quality of life”, “lack physiologic return to life” and “performing non-professional duties”. Conclusion: Futile care consists giving clinical cares irrelevant to a nurse’s job and giving cares through which the return of patient would be impossible both physiologically and qualitatively. PMID:25168995
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.
Island Divertor Plate Modeling for the Compact Toroidal Hybrid Experiment
NASA Astrophysics Data System (ADS)
Hartwell, G. J.; Massidda, S. D.; Ennis, D. A.; Knowlton, S. F.; Maurer, D. A.; Bader, A.
2015-11-01
Edge magnetic island divertors can be used as a method of plasma particle and heat exhaust in long pulse stellarator experiments. Detailed power loading on these structures and its relationship to the long connection length scrape off layer physics is a new Compact Toroidal Hybrid (CTH) research thrust. CTH is a five field period, l = 2 torsatron with R0 = 0 . 75 m, ap ~ 0 . 2 m, and | B | <= 0 . 7 T. For these studies CTH is configured as a pure stellarator using a 28 GHz, 200 kW gyrotron operating at 2nd harmonic for ECRH. We report the results of EMC3-EIRENE modeling of divertor plates near magnetic island structures. The edge rotational transform is varied by adjusting the ratio of currents in the helical and toroidal field coils. A poloidal field coil adjusts the shear of the rotational transform profile, and width of the magnetic island, 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 potential divertor plate locations will be presented and discussed. This work is supported by U.S. Department of Energy Grant No. DE-FG02-00ER54610.
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. PMID:26961319
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.
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.
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.
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.
A hybrid fast Hankel transform algorithm for electromagnetic modeling
Anderson, W.L.
1989-01-01
A hybrid fast Hankel transform algorithm has been developed that uses several complementary features of two existing algorithms: Anderson's digital filtering or fast Hankel transform (FHT) algorithm and Chave's quadrature and continued fraction algorithm. A hybrid FHT subprogram (called HYBFHT) written in standard Fortran-77 provides a simple user interface to call either subalgorithm. The hybrid approach is an attempt to combine the best features of the two subalgorithms to minimize the user's coding requirements and to provide fast execution and good accuracy for a large class of electromagnetic problems involving various related Hankel transform sets with multiple arguments. Special cases of Hankel transforms of double-order and double-argument are discussed, where use of HYBFHT is shown to be advantageous for oscillatory kernal functions. -Author
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…
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…
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.
Effect of nonlinearity in hybrid kinetic Monte Carlo-continuum models.
Balter, Ariel; Lin, Guang; Tartakovsky, Alexandre M
2012-01-01
Recently there has been interest in developing efficient ways to model heterogeneous surface reactions with hybrid computational models that couple a kinetic Monte Carlo (KMC) model for a surface to a finite-difference model for bulk diffusion in a continuous domain. We consider two representative problems that validate a hybrid method and show that this method captures the combined effects of nonlinearity and stochasticity. We first validate a simple deposition-dissolution model with a linear rate showing that the KMC-continuum hybrid agrees with both a fully deterministic model and its analytical solution. We then study a deposition-dissolution model including competitive adsorption, which leads to a nonlinear rate, and show that in this case the KMC-continuum hybrid and fully deterministic simulations do not agree. However, we are able to identify the difference as a natural result of the stochasticity coming from the KMC surface process. Because KMC captures inherent fluctuations, we consider it to be more realistic than a purely deterministic model. Therefore, we consider the KMC-continuum hybrid to be more representative of a real system.
Application of a RG hybrid RANS/LES model to swirling confined turbulent jets
NASA Astrophysics Data System (ADS)
de Langhe, C.; Merci, B.; Dick, E.
A renormalization group (RG) based hybrid RANS/LES model is validated for turbulent swirling confined jets. The results are compared with the experimental data of Dellenback et al. (1988, Measurements in turbulent swirling flow through an abrupt axisymmetric expansion. AIAA Journal, 26(6), 669 681) and results for the same flows of an unsteady second-moment closure RANS simulation. A general quality/cost comparison is made between the hybrid RANS/LES and the second-moment closure simulations. In the final section, the hybrid RANS/LES result is further compared to a detached-eddy simulation, dynamic -equation LES and dynamic Smagorinsky LES for one of the flows, and the overall good quality of the RG hybrid RANS/LES model demonstrated.
Stevens, J.E.; von Goeler, S.; Bernabei, S.; Bitter, M.; Chu, T.K.; Efthimion, P.; Fisch, N.; Hooke, W.; Hosea, J.; Jobes, F.
1985-03-01
Lower hybrid current drive requires the generation of a high energy electron tail anisotropic in velocity. Measurements of bremsstrahlung emission produced by this tail are compared with the calculated emission from reasonable model distributions. The physical basis and the sensitivity of this modeling process are described and the plasma properties of current driven discharges which can be derived from the model are discussed.
Rajagopalan, A.; Washington, G.; Rizzoni, G.; Guezennec, Y.
2003-12-01
This report describes the development of new control strategies and models for Hybrid Electric Vehicles (HEV) by the Ohio State University. The report indicates results from models created in NREL's ADvanced VehIcle SimulatOR (ADVISOR 3.2), and results of a scalable IC Engine model, called in Willan's Line technique, implemented in ADVISOR 3.2.
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.
Calibration of visual model for space manipulator with a hybrid LM-GA algorithm
NASA Astrophysics Data System (ADS)
Jiang, Wensong; Wang, Zhongyu
2016-01-01
A hybrid LM-GA algorithm is proposed to calibrate the camera system of space manipulator to improve its locational accuracy. This algorithm can dynamically fuse the Levenberg-Marqurdt (LM) algorithm and Genetic Algorithm (GA) together to minimize the error of nonlinear camera model. LM algorithm is called to optimize the initial camera parameters that are generated by genetic process previously. Iteration should be stopped if the optimized camera parameters meet the accuracy requirements. Otherwise, new populations are generated again by GA and optimized afresh by LM algorithm until the optimal solutions meet the accuracy requirements. A novel measuring machine of space manipulator is designed to on-orbit dynamic simulation and precision test. The camera system of space manipulator, calibrated by hybrid LM-GA algorithm, is used for locational precision test in this measuring instrument. The experimental results show that the mean composite errors are 0.074 mm for hybrid LM-GA camera calibration model, 1.098 mm for LM camera calibration model, and 1.202 mm for GA camera calibration model. Furthermore, the composite standard deviations are 0.103 mm for the hybrid LM-GA camera calibration model, 1.227 mm for LM camera calibration model, and 1.351 mm for GA camera calibration model. The accuracy of hybrid LM-GA camera calibration model is more than 10 times higher than that of other two methods. All in all, the hybrid LM-GA camera calibration model is superior to both the LM camera calibration model and GA camera calibration model.
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
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.
A state-space free-vortex hybrid wake model for helicopter rotors
NASA Astrophysics Data System (ADS)
Wasileski, Bryan J.
This paper presents the development of a new hybrid wake model merging two distinctly different modeling approaches into a single, more comprehensive solution. The objective of the work was to leverage the strengths of each individual wake model creating a more flexible and extensible solution that could be used across the entire flight envelope of a helicopter. The results of the work indicate that the two wakes models can be successfully merged. The results also show that hybrid wake provides a mechanism by which finite-state wake imparts a level of stability on the free wake solution allowing the free wake to provide consistent, repeatable results from hover through high speed forward flight. While the new hybrid wake includes the geometric distortion needed for predicting the off-axis control response, the new model, as configured in this work, shows no sign of improvement in this area.
Mathematical and computational model for the analysis of micro hybrid rocket motor
NASA Astrophysics Data System (ADS)
Stoia-Djeska, Marius; Mingireanu, Florin
2012-11-01
The hybrid rockets use a two-phase propellant system. In the present work we first develop a simplified model of the coupling of the hybrid combustion process with the complete unsteady flow, starting from the combustion port and ending with the nozzle. The physical and mathematical model are adapted to the simulations of micro hybrid rocket motors. The flow model is based on the one-dimensional Euler equations with source terms. The flow equations and the fuel regression rate law are solved in a coupled manner. The platform of the numerical simulations is an implicit fourth-order Runge-Kutta second order cell-centred finite volume method. The numerical results obtained with this model show a good agreement with published experimental and numerical results. The computational model developed in this work is simple, computationally efficient and offers the advantage of taking into account a large number of functional and constructive parameters that are used by the engineers.
Xiphophorus interspecies hybrids as genetic models of induced neoplasia.
Walter, R B; Kazianis, S
2001-01-01
Fishes of the genus Xiphophorus (platyfishes and swordtails) are small, internally fertilizing, livebearing, and derived from freshwater habitats in Mexico, Guatemala, Belize, and Honduras. Scientists have used these fishes in cancer research studies for more than 70 yr. The genus is presently composed of 22 species that are quite divergent in their external morphology. Most cancer studies using Xiphophorus use hybrids, which can be easily produced by artificial insemination. Phenotypic traits, such as macromelanophore pigment patterns, are often drastically altered as a result of lack of gene regulation within hybrid fishes. These fish can develop large exophytic melanomas as a result of upregulated expression of these pigment patterns. Because backcross hybrid fish are susceptible to the development of melanoma and other neoplasms, they can be subjected to potentially deleterious chemical and physical agents. It is thus possible to use gene mapping and cloning methodologies to identify and characterize oncogenes and tumor suppressors implicated in spontaneous or induced neoplasia. This article reviews the history of cancer research using Xiphophorus and recent developments regarding DNA repair capabilities, mapping, and cloning of candidate genes involved in neoplastic phenotypes. The particular genetic complexity of melanoma in these fishes is analyzed and reviewed. PMID:11581522
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.
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)
Zhang, Xiaoli; Peng, Yong; Zhang, Chi; Wang, Bende
2015-11-01
A number of hydrological studies have proven the superior prediction performance of hybrid models coupled with data preprocessing techniques. However, many studies first decompose the entire data series into components and later divide each component into calibration and validation datasets to establish models, which sends some amount of future information into the decomposition and reconstruction processes. As a consequence, the resulting components used to forecast the value of a particular moment are computed using information from future values, which are not available at that particular moment in a forecasting exercise. Since most papers don't present their model framework in detail, it is difficult to identify whether they are performing a real forecast or not. Even though several other papers have explicitly stated which experiment they are performing, a comparison between results in the hindcast and forecast experiments is still missing. Therefore, it is necessary to investigate and compare the performance of these hybrid models in the two experiments in order to estimate whether they are suitable for real forecasting. With the combination of three preprocessing techniques, such as wavelet analysis (WA), empirical mode decomposition (EMD) and singular spectrum analysis (SSA), and two modeling methods (i.e. ANN model and ARMA model), six hybrid models are developed in this study, including WA-ANN, WA-ARMA, EMD-ANN, EMD-ARMA, SSA-ANN and SSA-ARMA. Preprocessing techniques are used to decompose the data series into sub-series, and then these sub-series are modeled using ANN and ARMA models. These models are examined in hindcasting and forecasting of the monthly streamflow of two sites in the Yangtze River of China. The results of this study indicate that the six hybrid models perform better in the hindcast experiment compared with the original ANN and ARMA models, while the hybrid models in the forecast experiment perform worse than the original models and the
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.
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.
Energization of Oxygen Ions at Mars: Comparison of a Global Hybrid Model to In Situ Observations
NASA Astrophysics Data System (ADS)
Jarvinen, R.; Brain, D. A.; Fedorov, A.; Holmstrom, M.; Modolo, R.
2015-12-01
We study the energization of planetary oxygen ions escaping from the atmosphere of Mars in a global hybrid model for the Mars-solar wind interaction. In the hybrid approach ions are modelled as particles moving under the Lorentz force and electrons are a charge-neutralizing fluid. Thus, electric and magnetic field are self-consistently coupled with ion dynamics. We identify ion energization regions in the induced magnetosphere of Mars in the model. Further, we study electric and magnetic fields associated with the ion acceleration processes. Finally, we compare our simulation results to in situ particle and magnetic field observations on the MAVEN and Mars Express missions.
Hybrid neural modelling of an anaerobic digester with respect to biological constraints.
Karama, A; Bernard, O; Gouzé, J L; Benhammou, A; Dochain, D
2001-01-01
A hybrid model for an anaerobic digestion process is proposed. The fermentation is assumed to be performed in two steps, acidogenesis and methanogenesis, by two bacterial populations. The model is based on mass balance equations, and the bacterial growth rates are represented by neural networks. In order to guarantee the biological meaning of the hybrid model (positivity of the concentrations, boundedness, saturation or inhibition of the growth rates) outside the training data set, a method that imposes constraints in the neural network is proposed. The method is applied to experimental data from a fixed bed reactor.
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
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
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.
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. PMID:25111782
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…
Assessing the Therapeutic Environment in Hybrid Models of Treatment: Prisoner Perceptions of Staff
ERIC Educational Resources Information Center
Kubiak, Sheryl Pimlott
2009-01-01
Hybrid treatment models within prisons are staffed by both criminal justice and treatment professionals. Because these models may be indicative of future trends, examining the perceptions of prisoners/participants may provide important information. This study examines the perceptions of male and female inmates in three prisons, comparing those in…
Applying TSOI Hybrid Learning Model to Enhance Blended Learning Experience in Science Education
ERIC Educational Resources Information Center
Tsoi, Mun Fie
2009-01-01
Purpose: Research on the nature of blended learning and its features has led to a variety of approaches to the practice of blended learning. The purpose of this paper is to provide an alternative practice model, the TSOI hybrid learning model (HLM) to enhance the blended learning experiences in science education. Design/methodology/approach: The…
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.
Investigation of the Magnetotail and Inner Magnetosphere with Combined Global Hybrid and CIMI Models
NASA Astrophysics Data System (ADS)
Lin, Y.; Wang, X.; Perez, J. D.; Fok, M. C. H.
2014-12-01
The interconnection between the Earth's inner and outer magnetospheric regions is calculated by coupling an existing 3-D global hybrid simulation code to an existing ring current and radiation belt code, the Comprehensive Inner Magnetosphere/Ionosphere (CIMI) model. In the hybrid simulation, the global dynamics are driven by the solar wind and a southward IMF, and the simulation domain includes the plasma regions from x=-60RE to +20RE . Evolution of the magnetotail is revealed in the hybrid simulation. The response of the ring current and radiation belts is calculated by coupling the CIMI model to the global hybrid model. The hybrid simulation results provide the CIMI model with the magnetic field and electric potential at the high-latitude ionosphere boundary and plasma density and full ion phase space distribution function at the outer boundary at the equator. Our simulation shows that the ion velocity distributions in the tail are non-Maxwellian, with the existence of multiple ion beams, which have a significant impact on the ring current and the convection electric field. Detailed results will be presented for cases with various IMF and solar wind conditions, and the simulation will be compared with satellite observations.
Bergström, J S; Rimnac, C M; Kurtz, S M
2003-04-01
The development of theoretical failure, fatigue, and wear models for ultra-high molecular weight polyethylene (UHMWPE) used in joint replacements has been hindered by the lack of a validated constitutive model that can accurately predict large deformation mechanical behavior under clinically relevant, multiaxial loading conditions. Recently, a new Hybrid constitutive model for unirradiated UHMWPE was developed Bergström et al., (Biomaterials 23 (2002) 2329) based on a physics-motivated framework which incorporates the governing micro-mechanisms of polymers into an effective and accurate continuum representation. The goal of the present study was to compare the predictive capability of the new Hybrid model with the J(2)-plasticity model for four conventional and highly crosslinked UHMWPE materials during multiaxial loading. After calibration under uniaxial loading, the predictive capabilities of the J(2)-plasticity and Hybrid model were tested by comparing the load-displacement curves from experimental multiaxial (small punch) tests with simulated load-displacement curves calculated using a finite element model of the experimental apparatus. The quality of the model predictions was quantified using the coefficient of determination (r(2)). The results of the study demonstrate that the Hybrid model outperforms the J(2)-plasticity model both for combined uniaxial tension and compression predictions and for simulating multiaxial large deformation mechanical behavior produced by the small punch test. The results further suggest that the parameters of the HM may be generalizable for a wide range of conventional, highly crosslinked, and thermally treated UHMWPE materials, based on the characterization of four material properties related to the elastic modulus, yield stress, rate of strain hardening, and locking stretch of the polymer chains. Most importantly, from a practical perspective, these four key material properties for the Hybrid constitutive model can be measured
A Hybrid LDA+gCCA Model for fMRI Data Classification and Visualization.
Afshin-Pour, Babak; Shams, Seyed-Mohammad; Strother, Stephen
2015-05-01
Linear predictive models are applied to functional MRI (fMRI) data to estimate boundaries that predict experimental task states for scans. These boundaries are visualized as statistical parametric maps (SPMs) and range from low to high spatial reproducibility across subjects (e.g., Strother , 2004; LaConte , 2003). Such inter-subject pattern reproducibility is an essential characteristic of interpretable SPMs that generalize across subjects. Therefore, we introduce a flexible hybrid model that optimizes reproducibility by simultaneously enhancing the prediction power and reproducibility. This hybrid model is formed by a weighted summation of the optimization functions of a linear discriminate analysis (LDA) model and a generalized canonical correlation (gCCA) model (Afshin-Pour , 2012). LDA preserves the model's ability to discriminate the fMRI scans of multiple brain states while gCCA finds a linear combination for each subject's scans such that the estimated boundary map is reproducible. The hybrid model is implemented in a split-half resampling framework (Strother , 2010) which provides reproducibility (r) and prediction (p) quality metrics. Then the model was compared with LDA, and Gaussian Naive Bayes (GNB). For simulated fMRI data, the hybrid model outperforms the other two techniques in terms of receiver operating characteristic (ROC) curves, particularly for detecting less predictable but spatially reproducible networks. These techniques were applied to real fMRI data to estimate the maps for two task contrasts. Our results indicate that compared to LDA and GNB, the hybrid model can provide maps with large increases in reproducibility for small reductions in prediction, which are jointly closer to the ideal performance point of (p=1, r=1).
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
Using a Hybrid Model to Forecast the Prevalence of Schistosomiasis in Humans
Zhou, Lingling; Xia, Jing; Yu, Lijing; Wang, Ying; Shi, Yun; Cai, Shunxiang; Nie, Shaofa
2016-01-01
Background: We previously proposed a hybrid model combining both the autoregressive integrated moving average (ARIMA) and the nonlinear autoregressive neural network (NARNN) models in forecasting schistosomiasis. Our purpose in the current study was to forecast the annual prevalence of human schistosomiasis in Yangxin County, using our ARIMA-NARNN model, thereby further certifying the reliability of our hybrid model. Methods: We used the ARIMA, NARNN and ARIMA-NARNN models to fit and forecast the annual prevalence of schistosomiasis. The modeling time range included was the annual prevalence from 1956 to 2008 while the testing time range included was from 2009 to 2012. The mean square error (MSE), mean absolute error (MAE) and mean absolute percentage error (MAPE) were used to measure the model performance. We reconstructed the hybrid model to forecast the annual prevalence from 2013 to 2016. Results: The modeling and testing errors generated by the ARIMA-NARNN model were lower than those obtained from either the single ARIMA or NARNN models. The predicted annual prevalence from 2013 to 2016 demonstrated an initial decreasing trend, followed by an increase. Conclusions: The ARIMA-NARNN model can be well applied to analyze surveillance data for early warning systems for the control and elimination of schistosomiasis. PMID:27023573
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
Zero-dimensional hybrid model for analysis of discharge excited XeCl lasers
NASA Astrophysics Data System (ADS)
Lamrous, O.; Gaouar, A.; Yousfi, M.
1996-05-01
A powerful zero-dimensional hybrid model to study the positive column of a glow discharge used as an excitation medium for XeCl lasers is presented. This model was employed using a numerical code including three strongly coupled parts: electric circuit equations (electric model), electron Boltzmann equation (particle model), and kinetics equations (chemical kinetics model). From this hybrid model, kinetics and electrical parameters of Ne-Xe-HCl laser discharge mixtures have been discussed and analyzed. Calculated discharge current and voltage are also compared with available theoretical and experimental results. The good qualitative agreement observed shows the validity of the present model which can used as an efficient tool for the investigation of the homogeneous excimer laser discharge.
Robust dynamics in minimal hybrid models of genetic networks.
Perkins, Theodore J; Wilds, Roy; Glass, Leon
2010-11-13
Many gene-regulatory networks necessarily display robust dynamics that are insensitive to noise and stable under evolution. We propose that a class of hybrid systems can be used to relate the structure of these networks to their dynamics and provide insight into the origin of robustness. In these systems, the genes are represented by logical functions, and the controlling transcription factor protein molecules are real variables, which are produced and destroyed. As the transcription factor concentrations cross thresholds, they control the production of other transcription factors. We discuss mathematical analysis of these systems and show how the concepts of robustness and minimality can be used to generate putative logical organizations based on observed symbolic sequences. We apply the methods to control of the cell cycle in yeast.
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.
Modelling of hybrid scenario: from present-day experiments towards ITER
NASA Astrophysics Data System (ADS)
Litaudon, X.; Voitsekhovitch, I.; Artaud, J. F.; Belo, P.; Bizarro, João P. S.; Casper, T.; Citrin, J.; Fable, E.; Ferreira, J.; Garcia, J.; Garzotti, L.; Giruzzi, G.; Hobirk, J.; Hogeweij, G. M. D.; Imbeaux, F.; Joffrin, E.; Koechl, F.; Liu, F.; Lönnroth, J.; Moreau, D.; Parail, V.; Schneider, M.; Snyder, P. B.; the ASDEX-Upgrade Team; Contributors, JET-EFDA; the EU-ITM ITER Scenario Modelling Group
2013-07-01
The ‘hybrid’ scenario is an attractive operating scenario for ITER since it combines long plasma duration with the reliability of the reference H-mode regime. We review the recent European modelling effort carried out within the Integrated Scenario Modelling group which aims at (i) understanding the underlying physics of the hybrid regime in ASDEX-Upgrade and JET and (ii) extrapolating them towards ITER. JET and ASDEX-Upgrade hybrid scenarios performed under different experimental conditions have been simulated in an interpretative and predictive way in order to address the current profile dynamics and its link with core confinement, the relative importance of magnetic shear, s, and E × B flow shear on the core turbulence, pedestal stability and H-L transition. The correlation of the improved confinement with an increased s/q at outer radii observed in JET and ASDEX-Upgrade discharges is consistent with the predictions based on the GLF23 model applied in the simulations of the ion and electron kinetic profiles. Projections to ITER hybrid scenarios have been carried out focusing on optimization of the heating/current drive schemes to reach and ultimately control the desired plasma equilibrium using ITER actuators. Firstly, access condition to the hybrid-like q-profiles during the current ramp-up phase has been investigated. Secondly, from the interpreted role of the s/q ratio, ITER hybrid scenario flat-top performance has been optimized through tailoring the q-profile shape and pedestal conditions. EPED predictions of pedestal pressure and width have been used as constraints in the interpretative modelling while the core heat transport is predicted by GLF23. Finally, model-based approach for real-time control of advanced tokamak scenarios has been applied to ITER hybrid regime for simultaneous magnetic and kinetic profile control.
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.
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.
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.
Lattice model of oligonucleotide hybridization in solution. II. Specificity and cooperativity
NASA Astrophysics Data System (ADS)
Araque, J. C.; Robert, M. A.
2016-03-01
Because oligonucleotides are short sequences of nucleic acid bases, their association in solution with complementary strands (hybridization) is often seen to conform to a simple two-state model. However, experimental evidence suggests that, despite their short length, oligonucleotides may hybridize through multiple states involving intermediates. We investigate whether these apparently contradictory scenarios are possible by imposing different levels of sequence specificity on a lattice model of oligonucleotides in solution, which we introduced in Part I [J. C. Araque et al., J. Chem. Phys. 134, 165103 (2011)]. We find that both multiple-intermediate (weakly cooperative) and two-state (strongly cooperative) transitions are possible and that these are directly linked to the level of sequence specificity. Sequences with low specificity hybridize (base-by-base) by way of multiple stable intermediates with increasing number of paired bases. Such intermediate states are weakly cooperative because the energetic gain from adding an additional base pair is outweighed by the conformational entropy loss. Instead, sequences with high specificity hybridize through multiple metastable intermediates which easily bridge the configurational and energetic gaps between single- and double-stranded states. These metastable intermediates interconvert with minimal loss of conformational entropy leading to a strongly cooperative hybridization. The possibility of both scenarios, multiple- and two-states, is therefore encoded in the specificity of the sequence which in turn defines the level of cooperativity.
Trapped gyro-Landau-fluid transport modeling of DIII-D hybrid discharges
Kinsey, J. E.; Staebler, G. M.; Petty, C. C.
2010-12-15
Previous work has summarized the physics and first results of benchmarking the trapped gyro-Landau-fluid (TGLF) model for turbulent transport driven by trapped ion and electron modes, ion and electron temperature gradient (ETG) modes, and electromagnetic kinetic ballooning modes including the effects of shaped geometry. Recently, an improved collision model was implemented which provides a more accurate fit to a transport database of nonlinear collisional GYRO[J. Candy and R. E. Waltz, J. Comput. Phys. 186, 545 (2003)] simulations of long wavelength driftwave turbulence. The impact of the new collision model on TGLF modeling results was unknown. Using the improved TGLF model we obtain excellent agreement with the ion and electron temperature profiles from 30 DIII-D [A. Mahdavi and J. L. Luxon, Fusion Sci. Technol. 48, 2 (2005)] hybrid discharges. The transport results show that the electron energy transport tends to be dominated by short wavelength ETG modes in cases where the ion energy transport approaches neoclassical levels. The hybrid regime has significant energy confinement improvement from ExB velocity shear which is well predicted by TGLF. Weak magnetic shear and low safety factor are also shown to enhance the hybrid regime energy confinement. In high normalized {beta} hybrids, we find that finite {beta} effects noticably reduce the predicted electron energy transport and improve agreement with the measured electron temperature profiles.
Trapped gyro-Landau-fluid transport modeling of DIII-D hybrid discharges
NASA Astrophysics Data System (ADS)
Kinsey, J. E.; Staebler, G. M.; Petty, C. C.
2010-12-01
Previous work has summarized the physics and first results of benchmarking the trapped gyro-Landau-fluid (TGLF) model for turbulent transport driven by trapped ion and electron modes, ion and electron temperature gradient (ETG) modes, and electromagnetic kinetic ballooning modes including the effects of shaped geometry. Recently, an improved collision model was implemented which provides a more accurate fit to a transport database of nonlinear collisional GYRO [J. Candy and R. E. Waltz, J. Comput. Phys. 186, 545 (2003)] simulations of long wavelength driftwave turbulence. The impact of the new collision model on TGLF modeling results was unknown. Using the improved TGLF model we obtain excellent agreement with the ion and electron temperature profiles from 30 DIII-D [A. Mahdavi and J. L. Luxon, Fusion Sci. Technol. 48, 2 (2005)] hybrid discharges. The transport results show that the electron energy transport tends to be dominated by short wavelength ETG modes in cases where the ion energy transport approaches neoclassical levels. The hybrid regime has significant energy confinement improvement from E ×B velocity shear which is well predicted by TGLF. Weak magnetic shear and low safety factor are also shown to enhance the hybrid regime energy confinement. In high normalized β hybrids, we find that finite β effects noticably reduce the predicted electron energy transport and improve agreement with the measured electron temperature profiles.
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
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.
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.
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
ERIC Educational Resources Information Center
Jackson, Chris; Baguma, Peter; Furnham, Adrian
2009-01-01
Jackson developed a hybrid model of learning in personality, known as the Learning Styles Profiler (LSP), which seeks to explain personality in terms of biological, socio-cognitive and experiential processes. The hybrid model argues that functional learning outcomes can be understood in terms of how cognitions and experiences re-express sensation…
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.
Reduced-size kernel models for nonlinear hybrid system identification.
Le, Van Luong; Bloch, Grard; Lauer, Fabien
2011-12-01
This brief paper focuses on the identification of nonlinear hybrid dynamical systems, i.e., systems switching between multiple nonlinear dynamical behaviors. Thus the aim is to learn an ensemble of submodels from a single set of input-output data in a regression setting with no prior knowledge on the grouping of the data points into similar behaviors. To be able to approximate arbitrary nonlinearities, kernel submodels are considered. However, in order to maintain efficiency when applying the method to large data sets, a preprocessing step is required in order to fix the submodel sizes and limit the number of optimization variables. This brief paper proposes four approaches, respectively inspired by the fixed-size least-squares support vector machines, the feature vector selection method, the kernel principal component regression and a modification of the latter, in order to deal with this issue and build sparse kernel submodels. These are compared in numerical experiments, which show that the proposed approach achieves the simultaneous classification of data points and approximation of the nonlinear behaviors in an efficient and accurate manner.
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.
Hybrid continuum–molecular modelling of multiscale internal gas flows
Patronis, Alexander; Lockerby, Duncan A.; Borg, Matthew K.; Reese, Jason M.
2013-12-15
We develop and apply an efficient multiscale method for simulating a large class of low-speed internal rarefied gas flows. The method is an extension of the hybrid atomistic–continuum approach proposed by Borg et al. (2013) [28] for the simulation of micro/nano flows of high-aspect ratio. The major new extensions are: (1) incorporation of fluid compressibility; (2) implementation using the direct simulation Monte Carlo (DSMC) method for dilute rarefied gas flows, and (3) application to a broader range of geometries, including periodic, non-periodic, pressure-driven, gravity-driven and shear-driven internal flows. The multiscale method is applied to micro-scale gas flows through a periodic converging–diverging channel (driven by an external acceleration) and a non-periodic channel with a bend (driven by a pressure difference), as well as the flow between two eccentric cylinders (with the inner rotating relative to the outer). In all these cases there exists a wide variation of Knudsen number within the geometries, as well as substantial compressibility despite the Mach number being very low. For validation purposes, our multiscale simulation results are compared to those obtained from full-scale DSMC simulations: very close agreement is obtained in all cases for all flow variables considered. Our multiscale simulation is an order of magnitude more computationally efficient than the full-scale DSMC for the first and second test cases, and two orders of magnitude more efficient for the third case.
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.
Ares 1X Hybrid Modeling with Comparisons to Flight Data
NASA Technical Reports Server (NTRS)
Niedermaier, Dan; Kaouk, Mo
2010-01-01
This slide presentation reviews the Ares 1X test flight and compares the resultant flight data with the results of modeled data from siumulations of the flight. It includes: (1) Ares 1X Flight Summary, (2) Ares 1X Data Summary (3) Model Descriptions (4) Model Comparisons to Flight Data in three areas: (a) Liftoff, (b) Transonic and (c) Roll Control Firings (RCS) Firings.
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.
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.
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…
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…
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…
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...
Edge gradients evaluation for 2D hybrid finite volume method model
Technology Transfer Automated Retrieval System (TEKTRAN)
In this study, a two-dimensional depth-integrated hydrodynamic model was developed using FVM on a hybrid unstructured collocated mesh system. To alleviate the negative effects of mesh irregularity and non-uniformity, a conservative evaluation method for edge gradients based on the second-order Tayl...
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.
Elsheikh, Ahmed H.; Wheeler, Mary F.; Hoteit, Ibrahim
2014-02-01
A Hybrid Nested Sampling (HNS) algorithm is proposed for efficient Bayesian model calibration and prior model selection. The proposed algorithm combines, Nested Sampling (NS) algorithm, Hybrid Monte Carlo (HMC) sampling and gradient estimation using Stochastic Ensemble Method (SEM). NS is an efficient sampling algorithm that can be used for Bayesian calibration and estimating the Bayesian evidence for prior model selection. Nested sampling has the advantage of computational feasibility. Within the nested sampling algorithm, a constrained sampling step is performed. For this step, we utilize HMC to reduce the correlation between successive sampled states. HMC relies on the gradient of the logarithm of the posterior distribution, which we estimate using a stochastic ensemble method based on an ensemble of directional derivatives. SEM only requires forward model runs and the simulator is then used as a black box and no adjoint code is needed. The developed HNS algorithm is successfully applied for Bayesian calibration and prior model selection of several nonlinear subsurface flow problems.
Zhu, Wen; Li, Meng
2014-01-01
A series of zwitterionic hybrid membranes were prepared via the ring opening of 1,3-propanesultone with the amine groups in the chains of TMSPEDA and a subsequent sol-gel process. Their kinetic models for strontium removal were investigated using three two-parameter kinetic equations (i.e., Lagergren pseudo-first order, pseudo-second order, and Elovich models). Adsorption mechanism was evaluated using intraparticle diffusion model, diffusion-chemisorption model, and Boyd equation. It was found that the adsorption of strontium ions on these zwitterionic hybrid membranes fitted well with the Lagergren pseudo-second order model. Mechanism insights suggested that diffusion-chemisorption was one of the main adsorption mechanisms. Boyd equation exhibited that film-diffusion mechanism might be the control process during the starting period. These findings are very useful in strontium removal from the stimulated radioactive wastewater. PMID:25405224
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.
Shaik, Fahimuddin; Sharma, Anil Kumar; Ahmed, Syed Musthak
2016-01-01
At present image processing methods hold a noteworthy position in unravelling various medical imaging challenges. The high risk disorders such as diabetic cardiomyopathy and diabetic retinopathy are considered as applications for proposed method. The dictum of this paper is on observing enhancement and segmentation of the cross sectional view of a blood capillary of a right coronary artery image of a diabetic patient and also retinal images. A hybrid model using hybrid morphological reconstruction technique as pre-processing with watershed segmentation method as post-processing is developed in this work. PMID:27186471
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.
Modelling grain-scattered ultrasound in austenitic stainless-steel welds: A hybrid model
NASA Astrophysics Data System (ADS)
Nowers, O.; Duxbury, D. J.; Velichko, A.; Drinkwater, B. W.
2015-03-01
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.
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.
Quilodrán, Claudio S.; Currat, Mathias; Montoya-Burgos, Juan I.
2014-01-01
Interspecific hybridization is common in nature but can be increased in frequency or even originated by human actions, such as species introduction or habitat modification, which may threaten species persistence. When hybridization occurs between distantly related species, referred to as “distant hybridization,” the resulting hybrids are generally infertile or fertile but do not undergo chromosomal recombination during gametogenesis. Here, we present a model describing this frequent but poorly studied interspecific hybridization to assess its consequences on parental species and to anticipate the conditions under which they can reach extinction. Our general model fully incorporates three important processes: density-dependent competition, dominance/recessivity inheritance of traits and assortative mating. We demonstrate its use and flexibility by assessing population extinction risk between Atlantic salmon and brown trout in Norway, whose interbreeding has recently increased due to farmed fish releases into the wild. We identified the set of conditions under which hybridization may threaten salmonid species. Thanks to the flexibility of our model, we evaluated the effect of an additional risk factor, a parasitic disease, and showed that the cumulative effects dramatically increase the extinction risk. The consequences of distant hybridization are not genetically, but demographically mediated. Our general model is useful to better comprehend the evolution of such hybrid systems and we demonstrated its importance in the field of conservation biology to set up management recommendations when this increasingly frequent type of hybridization is in action. PMID:25003336
Quilodrán, Claudio S; Currat, Mathias; Montoya-Burgos, Juan I
2014-01-01
Interspecific hybridization is common in nature but can be increased in frequency or even originated by human actions, such as species introduction or habitat modification, which may threaten species persistence. When hybridization occurs between distantly related species, referred to as "distant hybridization," the resulting hybrids are generally infertile or fertile but do not undergo chromosomal recombination during gametogenesis. Here, we present a model describing this frequent but poorly studied interspecific hybridization to assess its consequences on parental species and to anticipate the conditions under which they can reach extinction. Our general model fully incorporates three important processes: density-dependent competition, dominance/recessivity inheritance of traits and assortative mating. We demonstrate its use and flexibility by assessing population extinction risk between Atlantic salmon and brown trout in Norway, whose interbreeding has recently increased due to farmed fish releases into the wild. We identified the set of conditions under which hybridization may threaten salmonid species. Thanks to the flexibility of our model, we evaluated the effect of an additional risk factor, a parasitic disease, and showed that the cumulative effects dramatically increase the extinction risk. The consequences of distant hybridization are not genetically, but demographically mediated. Our general model is useful to better comprehend the evolution of such hybrid systems and we demonstrated its importance in the field of conservation biology to set up management recommendations when this increasingly frequent type of hybridization is in action.
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.
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
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
Application of Equilibrium Models of Solution Hybridization to Microarray Design and Analysis
Gharaibeh, Raad Z.; Newton, Joshua M.; Weller, Jennifer W.; Gibas, Cynthia J.
2010-01-01
Background The probe percent bound value, calculated using multi-state equilibrium models of solution hybridization, is shown to be useful in understanding the hybridization behavior of microarray probes having 50 nucleotides, with and without mismatches. These longer oligonucleotides are in widespread use on microarrays, but there are few controlled studies of their interactions with mismatched targets compared to 25-mer based platforms. Principal Findings 50-mer oligonucleotides with centrally placed single, double and triple mismatches were spotted on an array. Over a range of target concentrations it was possible to discriminate binding to perfect matches and mismatches, and the type of mismatch could be predicted accurately in the concentration midrange (100 pM to 200 pM) using solution hybridization modeling methods. These results have implications for microarray design, optimization and analysis methods. Conclusions Our results highlight the importance of incorporating biophysical factors in both the design and the analysis of microarrays. Use of the probe “percent bound” value predicted by equilibrium models of hybridization is confirmed to be important for predicting and interpreting the behavior of long oligonucleotide arrays, as has been shown for short oligonucleotide arrays. PMID:20548788
Time-dependent Mott transition in the periodic Anderson model with nonlocal hybridization
NASA Astrophysics Data System (ADS)
Hofmann, Felix; Potthoff, Michael
2016-08-01
The time-dependent Mott transition in a periodic Anderson model with off-site, nearest-neighbor hybridization is studied within the framework of nonequilibrium self-energy functional theory. Using the two-site dynamical-impurity approximation, we compute the real-time dynamics of the optimal variational parameter and of different observables initiated by sudden quenches of the Hubbard-U and identify the critical interaction. The time-dependent transition is orbital selective, i.e., in the final state, reached in the long-time limit after the quench to the critical interaction, the Mott gap opens in the spectral function of the localized orbitals only. We discuss the dependence of the critical interaction and of the final-state effective temperature on the hybridization strength and point out the various similarities between the nonequilibrium and the equilibrium Mott transition. It is shown that these can also be smoothly connected to each other by increasing the duration of a U-ramp from a sudden quench to a quasi-static process. The physics found for the model with off-site hybridization is compared with the dynamical Mott transition in the single-orbital Hubbard model and with the dynamical crossover found for the real-time dynamics of the conventional Anderson lattice with on-site hybridization.
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. PMID:23824509
APT: Costs and Benefits of a Hybrid Model
ERIC Educational Resources Information Center
Dijkstra, Ton; Haverkort, Marco
2004-01-01
In their keynote contribution, Truscott and Sharwood Smith offer a general model of language development from a processing perspective. As they state, their model is very ambitious: Their "acquisition by processing" theory (APT) aims not only at explaining both first and second language acquisition but also real-time processing in language…
Coupled equilibrium model of hybridization error for the DNA microarray and tag-antitag systems.
Rose, John A; Deaton, Russell J; Hagiya, Masami; Suyama, Akira
2007-03-01
In this work, a detailed coupled equilibrium model is presented for predicting the ensemble average probability of hybridization error per chip-hybridized input strand, providing the first ensemble average method for estimating postannealing microarray/TAT system error rates. Following a detailed presentation of the model and implementation via the software package NucleicPark, under a mismatched statistical zipper model of duplex formation, error response is simulated for both mean-energy and randomly encoded TAT systems versus temperature and input concentration. Limiting expressions and simulated model behavior indicate the occurrence of a transition in hybridization error response, from a logarithmically convex function of temperature for excess inputs (high-error behavior), to a monotonic, log-linear function of temperature for dilute inputs (low-error behavior), a novel result unpredicted by uncoupled equilibrium models. Model scaling behavior for random encodings is investigated versus system size and strand-length. Application of the model to TAT system design is also undertaken, via the in silico evolution of a high-fidelity 100-strand TAT system, with an error response improved by nine standard deviations over the performance of the mean random encoding. PMID:17393846
Hybrid scaled structural dynamic models and their use in damping prediction
NASA Technical Reports Server (NTRS)
Crawley, Edward F.; Sigler, Jonathan L.; Van Schoor, Marthinus C.; Gronet, Marc J.
1990-01-01
Analytical and experimental techniques for the prediction and ground verification of the damped structural dynamics of space structures are developed. The options available for similarity-scaled model testing, including replica and multiple scale approaches, are reviewed. For the case when the distortion of potentially dissipative or nonlinear joints, which would be required in multiple-scale modeling, is impractical, a new type of modeling is introduced, which uses a hybrid of joints at replica scale and connecting elements at a modified multiple scale. The model design requirements for replica, multiple-scale, and hybrid models are developed, and the expected scaling of nonlinear dissipation in joints is derived. A damping prediction scheme is developed that relies on a finite element model of the undamped structure and measurements of the individual joint properties to predict the modal damping of the truss attributable to the joints. A hybrid-scaled model of a segment of the Space Station was built and dynamically tested. The predicted and measured truss damping compared favorably.
Coupled equilibrium model of hybridization error for the DNA microarray and tag-antitag systems.
Rose, John A; Deaton, Russell J; Hagiya, Masami; Suyama, Akira
2007-03-01
In this work, a detailed coupled equilibrium model is presented for predicting the ensemble average probability of hybridization error per chip-hybridized input strand, providing the first ensemble average method for estimating postannealing microarray/TAT system error rates. Following a detailed presentation of the model and implementation via the software package NucleicPark, under a mismatched statistical zipper model of duplex formation, error response is simulated for both mean-energy and randomly encoded TAT systems versus temperature and input concentration. Limiting expressions and simulated model behavior indicate the occurrence of a transition in hybridization error response, from a logarithmically convex function of temperature for excess inputs (high-error behavior), to a monotonic, log-linear function of temperature for dilute inputs (low-error behavior), a novel result unpredicted by uncoupled equilibrium models. Model scaling behavior for random encodings is investigated versus system size and strand-length. Application of the model to TAT system design is also undertaken, via the in silico evolution of a high-fidelity 100-strand TAT system, with an error response improved by nine standard deviations over the performance of the mean random encoding.
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.
2014-02-01
An hybrid model, consisting of GIS and metamodel (model of model) procedures, was introduced with the aim of estimating the 1-D spatial seismic site response. Inputs and outputs are provided and processed by means of an appropriate GIS model, named GIS Cubic Model (GCM). This discretizes the seismic underground half-space in a pseudo-tridimensional way. GCM consists of a layered parametric structure aimed at resolving a predicted metamodel by means of pixel to pixel vertical computing. The metamodel leading to the determination of a bilinear-polynomial function is able to design the classic shape of the spectral acceleration response in relation to the main physical parameters that characterize the spectrum itself. The main physical parameters consist of (i) the average shear wave velocity of the shallow layer, (ii) the fundamental period and, (iii) the period where the spatial spectral response is required. The metamodel is calibrated on theoretical spectral accelerations regarding the local likely Vs-profiles, which are obtained using the Monte Carlo simulation technique on the basis of the GCM information. 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.
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 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.
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.
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.
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
THYME: Toolkit for Hybrid Modeling of Electric Power Systems
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 flowmore » data, and sample models of discrete sensors and controllers.« less
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.
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.
Fractional snow cover mapping from MODIS data using wavelet-artificial intelligence hybrid models
NASA Astrophysics Data System (ADS)
Moosavi, Vahid; Malekinezhad, Hossein; Shirmohammadi, Bagher
2014-04-01
This study was carried out to evaluate the wavelet-artificial intelligence hybrid models to produce fractional snow cover maps. At first, cloud cover was removed from MODIS data and cloud free images were produced. SVM-based binary classified ETM+ imagery were then used as reference maps in order to obtain train and test data for sub-pixel classification models. ANN and ANFIS-based modeling were performed using raw data (without wavelet-based preprocessing). In the next step, several mother wavelets and levels were used in order to decompose the original data to obtain wavelet coefficients. Then, the decomposed data were used for further modeling processes. ANN, ANFIS, wavelet-ANN and wavelet-ANFIS models were compared to evaluate the effect of wavelet transformation on the ability of artificial intelligence models. It was demonstrated that wavelet transformation as a preprocessing approach can significantly enhance the performance of ANN and ANFIS models. This study indicated an overall accuracy of 92.45% for wavelet-ANFIS model, 86.13% for wavelet-ANN, 72.23% for ANFIS model and 66.78% for ANN model. In fact, hybrid wavelet-artificial intelligence models can extract the characteristics of the original signals (i.e. model inputs) accurately through decomposing the non-stationary and complex signals into several stationary and simpler signals. The positive effect of fuzzification as well as wavelet transformation in the wavelet-ANFIS model was also confirmed.
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.
Application of explicit model predictive control to a hybrid battery-ultracapacitor power source
NASA Astrophysics Data System (ADS)
Hredzak, Branislav; Agelidis, Vassilios G.; Demetriades, Georgios
2015-03-01
An explicit model predictive control (EMPC) system for a hybrid battery-ultracapacitor power source is proposed and experimentally verified in this paper. The main advantage of using the EMPC system is that the control law computation is reduced to evaluation of an explicitly defined piecewise linear function of the states. Separate EMPC systems for the total output current loop, the battery loop and the ultracapacitor loop are designed. This modular design approach allows evaluation of the performance of each individual EMPC system separately and also improves the convergence of the EMPC system design algorithm as the models used to design each loop are smaller. In order to protect the hybrid power source, the designed EMPC systems maintain operation of the hybrid power source within specified constraints, namely, battery and ultracapacitor current constraints, battery state of charge constraints and ultracapacitor voltage constraints. At the same time, the total output current EMPC system allocates high frequency current changes to the ultracapacitor and the low frequency current changes to the battery thus extending the battery lifetime. Presented experimental results verify that the hybrid power source operates within the specified constraints while allocating high and low frequency current changes to the ultracapacitor and battery respectively.
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
Modelling Nonlinear Dynamic Textures using Hybrid DWT-DCT and Kernel PCA with GPU
NASA Astrophysics Data System (ADS)
Ghadekar, Premanand Pralhad; Chopade, Nilkanth Bhikaji
2016-06-01
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.
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.
A hybrid phenomenological model for ferroelectroelastic ceramics. Part II: Morphotropic PZT ceramics
NASA Astrophysics Data System (ADS)
Stark, S.; Neumeister, P.; Balke, H.
2016-10-01
In this part II of a two part series, the rate-independent hybrid phenomenological constitutive model introduced in part I is modified to account for the material behavior of morphotropic lead zirconate titanate ceramics (PZT ceramics). The modifications are based on a discussion of the available literature results regarding the micro-structure of these materials. In particular, a monoclinic phase and a highly simplified representation of the hierarchical structure of micro-domains and nano-domains observed experimentally are incorporated into the model. It is shown that experimental data for the commercially available morphotropic PZT material PIC151 (PI Ceramic GmbH, Lederhose, Germany) can be reproduced and predicted based on the modified hybrid model.
Preliminary analysis on hybrid Box-Jenkins - GARCH modeling in forecasting gold price
NASA Astrophysics Data System (ADS)
Yaziz, Siti Roslindar; Azizan, Noor Azlinna; Ahmad, Maizah Hura; Zakaria, Roslinazairimah; Agrawal, Manju; Boland, John
2015-02-01
Gold has been regarded as a valuable precious metal and the most popular commodity as a healthy return investment. Hence, the analysis and prediction of gold price become very significant to investors. This study is a preliminary analysis on gold price and its volatility that focuses on the performance of hybrid Box-Jenkins models together with GARCH in analyzing and forecasting gold price. The Box-Cox formula is used as the data transformation method due to its potential best practice in normalizing data, stabilizing variance and reduces heteroscedasticity using 41-year daily gold price data series starting 2nd January 1973. Our study indicates that the proposed hybrid model ARIMA-GARCH with t-innovation can be a new potential approach in forecasting gold price. This finding proves the strength of GARCH in handling volatility in the gold price as well as overcomes the non-linear limitation in the Box-Jenkins modeling.
A hybrid model describing ion induced kinetic electron emission
NASA Astrophysics Data System (ADS)
Hanke, S.; Duvenbeck, A.; Heuser, C.; Weidtmann, B.; Wucher, A.
2015-06-01
We present a model to describe the kinetic internal and external electron emission from an ion bombarded metal target. The model is based upon a molecular dynamics treatment of the nuclear degree of freedom, the electronic system is assumed as a quasi-free electron gas characterized by its Fermi energy, electron temperature and a characteristic attenuation length. In a series of previous works we have employed this model, which includes the local kinetic excitation as well as the rapid spread of the generated excitation energy, in order to calculate internal and external electron emission yields within the framework of a Richardson-Dushman-like thermionic emission model. However, this kind of treatment turned out to fail in the realistic prediction of experimentally measured internal electron yields mainly due to the restriction of the treatment of electronic transport to a diffusive manner. Here, we propose a slightly modified approach additionally incorporating the contribution of hot electrons which are generated in the bulk material and undergo ballistic transport towards the emitting interface.
Ranjbaran, Mina; Galiana, Henrietta L
2015-01-01
The vestibulo-ocular reflex (VOR) is an involuntary eye movement evoked by head movements. It is also influenced by viewing distance. This paper presents a hybrid nonlinear bilateral model for the horizontal angular vestibulo-ocular reflex (AVOR) in the dark. The model is based on known interconnections between saccadic burst circuits in the brainstem and ocular premotor areas in the vestibular nuclei during fast and slow phase intervals of nystagmus. We implemented a viable switching strategy for the timing of nystagmus events to allow emulation of real nystagmus data. The performance of the hybrid model is evaluated with simulations, and results are consistent with experimental observations. The hybrid model replicates realistic AVOR nystagmus patterns during sinusoidal or step head rotations in the dark and during interactions with vergence, e.g., fixation distance. By simply assigning proper nonlinear neural computations at the premotor level, the model replicates all reported experimental observations. This work sheds light on potential underlying neural mechanisms driving the context dependent AVOR and explains contradictory results in the literature. Moreover, context-dependent behaviors in more complex motor systems could also rely on local nonlinear neural computations.
Ranjbaran, Mina; Galiana, Henrietta L.
2015-01-01
The vestibulo-ocular reflex (VOR) is an involuntary eye movement evoked by head movements. It is also influenced by viewing distance. This paper presents a hybrid nonlinear bilateral model for the horizontal angular vestibulo-ocular reflex (AVOR) in the dark. The model is based on known interconnections between saccadic burst circuits in the brainstem and ocular premotor areas in the vestibular nuclei during fast and slow phase intervals of nystagmus. We implemented a viable switching strategy for the timing of nystagmus events to allow emulation of real nystagmus data. The performance of the hybrid model is evaluated with simulations, and results are consistent with experimental observations. The hybrid model replicates realistic AVOR nystagmus patterns during sinusoidal or step head rotations in the dark and during interactions with vergence, e.g., fixation distance. By simply assigning proper nonlinear neural computations at the premotor level, the model replicates all reported experimental observations. This work sheds light on potential underlying neural mechanisms driving the context dependent AVOR and explains contradictory results in the literature. Moreover, context-dependent behaviors in more complex motor systems could also rely on local nonlinear neural computations. PMID:25709578
Bottom friction optimization for barotropic tide modelling using the HYbrid Coordinate Ocean Model
NASA Astrophysics Data System (ADS)
Boutet, Martial; Lathuilière, Cyril; Baraille, Rémy; Son Hoang, Hong; Morel, Yves
2014-05-01
tested and validated with the HYbrid Coordinate Ocean Model (HYCOM) in barotropic mode (one isopycnal layer), using twin experiments (the observations are obtained with the direct model, prescribing the reference parameter distribution). The modeled area is the Bay of Biscay and the English Channel and the estimated parameter is the bottom roughness (z0).
Hybrid Modeling of Multiphase Flow in Porous Media: Coupling Darcy and Pore-Scale Description
NASA Astrophysics Data System (ADS)
Tomin, P.; Lunati, I.
2012-12-01
Flow through porous media is usually modeled employing Darcy's law to relate the macroscopic velocity (volumetric flux density) to the pressure gradient. This relationship represents the momentum balance equation and provides a reliable description under the assumptions of short relaxation times and scale separation. In case of multiphase flow, however, the interaction between the nonlinear interface dynamics and the complexity of pore structure generates a variety of flow regimes and can lead to situations, in which these assumptions are not satisfied and Darcy's law might become inadequate. In this case, multiphysics models that combine the Darcy and pore-scale description become attractive. Here, we use the Multiscale Finite Volume method (MsFV) as a framework for construction a hybrid algorithm that couples a Darcy description of the flow with a pore-scale description. The Navier-Stokes equations are solved to compute the velocity field in the pore geometry; the dynamics of the fluid-fluid interface is described by the Volume Of Fluid method (VOF) in combination with the Continuum Surface Force model (a classic diffuse-interface model for surface tension). A Darcy-like model based on conservation principles is used to construct the approximate coarse-scale problem. The results of the hybrid algorithm (Hybrid Multiscale Finite Volume method, HMsFV) are compared with full pore-scale simulations for several flow regimes to assess the robustness of the method with respect to changes in the morphology of fluid distribution. As the reconstruction of the fine-scale details can be done adaptively, the HMsFV method offers a flexible framework for hybrid modeling of different coexisting flow regimes.
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.
Medical Image Segmentation Based on a Hybrid Region-Based Active Contour Model
Liu, Tingting; Xu, Haiyong; Liu, Zhen; Zhao, Yiming; Tian, Wenzhe
2014-01-01
A novel hybrid region-based active contour model is presented to segment medical images with intensity inhomogeneity. The energy functional for the proposed model consists of three weighted terms: global term, local term, and regularization term. The total energy is incorporated into a level set formulation with a level set regularization term, from which a curve evolution equation is derived for energy minimization. Experiments on some synthetic and real images demonstrate that our model is more efficient compared with the localizing region-based active contours (LRBAC) method, proposed by Lankton, and more robust compared with the Chan-Vese (C-V) active contour model. PMID:25028593
The characteristic analysis of a hybrid multifluid turbulent-mix model
Cheng, B.; Cranfill, C.W.
1998-07-13
A thorough analysis of the characteristics of a multifluid turbulent mix model in the case of one-dimensional two phase flows is presented under various physical circumstances. It has been found that the new hybrid multifluid turbulent mix model has all real characteristics if either real or turbulent viscosity is present. When real viscosity vanishes, the model still has all real characteristics for zero relative motion between fluids. For nonzero relative motions between fluids, the model will have all real characteristics if the disordered motions and turbulent viscosity together are generated with the nonzero relative motions simultaneously. The implications of the results are further discussed.
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…
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
Hybrid methodology for situation assessment model development within an air operations center domain
NASA Astrophysics Data System (ADS)
Ho, Stephen; Gonsalves, Paul; Call, Catherine
2007-04-01
Within the dynamic environment of an Air Operations Center (AOC), effective decision-making is highly dependent on timely and accurate situation assessment. In previous research efforts the capabilities and potential of a Bayesian belief network (BN) model-based approach to support situation assessment have been demonstrated. In our own prior research, we have presented and formalized a hybrid process for situation assessment model development that seeks to ameliorate specific concerns and drawbacks associated with using a BN-based model construct. Specifically, our hybrid methodology addresses the significant knowledge acquisition requirements and the associated subjective nature of using subject matter experts (SMEs) for model development. Our methodology consists of two distinct functional elements: an off-line mechanism for rapid construction of a Bayesian belief network (BN) library of situation assessment models tailored to different situations and derived from knowledge elicitation with SMEs; and an on-line machine-learning-based mechanism to learn, tune, or adapt BN model parameters and structure. The adaptation supports the ability to adjust the models over time to respond to novel situations not initially available or anticipated during initial model construction, thus ensuring that the models continue to meet the dynamic requirements of performing the situation assessment function within dynamic application environments such as an AOC. In this paper, we apply and demonstrate the hybrid approach within the specific context of an AOC-based air campaign monitoring scenario. We detail both the initial knowledge elicitation and subsequent machine learning phases of the model development process, as well as demonstrate model performance within an operational context.
Singularity avoidance in the hybrid quantization of the Gowdy model
NASA Astrophysics Data System (ADS)
Tarrío, Paula; Fernández-Méndez, Mikel; Mena Marugán, Guillermo A.
2013-10-01
One of the most remarkable phenomena in loop quantum cosmology is that, at least for homogeneous cosmological models, the big bang is replaced with a big bounce that connects our Universe with a previous branch without passing through a cosmological singularity. The goal of this work is to study the existence of singularities in loop quantum cosmology, including inhomogeneities, and check whether the behavior obtained in the purely homogeneous setting continues to be valid. With this aim, we focus our attention on the three-torus Gowdy cosmologies with linearly polarized gravitational waves and use effective dynamics to carry out the analysis. For this model, we prove that all the potential cosmological singularities are avoided, generalizing the results about resolution of singularities to this scenario with inhomogeneities. We also demonstrate that, if a bounce in the (Bianchi background) volume occurs, the inhomogeneities increase the value of this volume at the bounce with respect to its counterpart in the homogeneous case.
Reduction and identification for hybrid dynamical models of terrestrial locomotion
NASA Astrophysics Data System (ADS)
Burden, Samuel A.; Sastry, S. Shankar
2013-06-01
The study of terrestrial locomotion has compelling applications ranging from design of legged robots to development of novel prosthetic devices. From a first-principles perspective, the dynamics of legged locomotion seem overwhelmingly complex as nonlinear rigid body dynamics couple to a granular substrate through viscoelastic limbs. However, a surfeit of empirical data demonstrates that animals use a small fraction of their available degrees-of-freedom during locomotion on regular terrain, suggesting that a reduced-order model can accurately describe the dynamical variation observed during steady-state locomotion. Exploiting this emergent phenomena has the potential to dramatically simplify design and control of micro-scale legged robots. We propose a paradigm for studying dynamic terrestrial locomotion using empirically-validated reduced{order models.
Empirical Analysis of Stochastic Volatility Model by Hybrid Monte Carlo Algorithm
NASA Astrophysics Data System (ADS)
Takaishi, Tetsuya
2013-04-01
The stochastic volatility model is one of volatility models which infer latent volatility of asset returns. The Bayesian inference of the stochastic volatility (SV) model is performed by the hybrid Monte Carlo (HMC) algorithm which is superior to other Markov Chain Monte Carlo methods in sampling volatility variables. We perform the HMC simulations of the SV model for two liquid stock returns traded on the Tokyo Stock Exchange and measure the volatilities of those stock returns. Then we calculate the accuracy of the volatility measurement using the realized volatility as a proxy of the true volatility and compare the SV model with the GARCH model which is one of other volatility models. Using the accuracy calculated with the realized volatility we find that empirically the SV model performs better than the GARCH model.
A hybrid gene team model and its application to genome analysis.
Kim, Sun; Choi, Jeong-Hyeon; Saple, Amit; Yang, Jiong
2006-04-01
It is well-known that functionally related genes occur in a physically clustered form, especially operons in bacteria. By leveraging on this fact, there has recently been an interesting problem formulation known as gene team model, which searches for a set of genes that co-occur in a pair of closely related genomes. However, many gene teams, even experimentally verified operons, frequently scatter within other genomes. Thus, the gene team model should be refined to reflect this observation. In this paper, we generalized the gene team model, that looks for gene clusters in a physically clustered form, to multiple genome cases with relaxed constraints. We propose a novel hybrid pattern model that combines the set and the sequential pattern models. Our model searches for gene clusters with and/or without physical proximity constraint. This model is implemented and tested with 97 genomes (120 replicons). The result was analyzed to show the usefulness of our model. We also compared the result from our hybrid model to those from the traditional gene team model. We also show that predicted gene teams can be used for various genome analysis: operon prediction, phylogenetic analysis of organisms, contextual sequence analysis and genome annotation. Our program is fast enough to provide a service on the web at http://platcom.informatics.indiana.edu/platcom/. Users can select any combination of 97 genomes to predict gene teams.
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.
An Evolutionary Hybrid Cellular Automaton Model of Solid Tumour Growth
Gerlee, P.; Anderson, A.R.A.
2007-01-01
We propose a cellular automaton model of solid tumour growth, in which each cell is equipped with a micro-environment response network. This network is modelled using a feed-forward artificial neural network, that takes environmental variables as an input and from these determines the cellular behaviour as the output. The response of the network is determined by connection weights and thresholds in the network, which are subject to mutations when the cells divide. As both available space and nutrients are limited resources for the tumour this gives rise to clonal evolution where only the fittest cells survive. Using this approach we have investigated the impact of the tissue oxygen concentration on the growth and evolutionary dynamics of the tumour. The results show that the oxygen concentration affects the selection pressure, cell population diversity and morphology of the tumour. A low oxygen concentration in the tissue gives rise to a tumour with a fingered morphology that contains aggressive phenotypes with a small apoptotic potential, while a high oxygen concentration in the tissue gives rise to a tumour with a round morphology containing less evolved phenotypes. The tissue oxygen concentration thus affects the tumour at both the morphological level and on the phenotype level. PMID:17374383
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
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
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.
NASA Astrophysics Data System (ADS)
Kushner, Mark J.; Grapperhaus, Michael J.
1996-10-01
Inductively Coupled Plasma (ICP) reactors have the potential for scaling to large area substrates while maintaining azimuthal symmetry or side-to-side uniformity across the wafer. Asymmetric etch properties in these devices have been attributed to transmission line properties of the coil, internal structures (such as wafer clamps) and non-uniform gas injection or pumping. To investigate the origins of asymmetric etch properties, a 3-dimensional hybrid model has been developed. The hybrid model contains electromagnetic, electric circuit, electron energy equation, and fluid modules. Continuity and momentum equations are solved in the fluid module along with Poisson's equation. We will discuss results for ion and radical flux uniformity to the substrate while varying the transmission line characteristics of the coil, symmetry of gas inlets/pumping, and internal structures. Comparisons will be made to expermental measurements of etch rates. ^*Work supported by SRC, NSF, ARPA/AFOSR and LAM Research.
Initial Results From the 3D Hybrid Heliospheric Modeling System With Pickup Protons
NASA Astrophysics Data System (ADS)
Detman, T. R.; Intriligator, D.; Dryer, M.; Sun, W.; Deehr, C.; Intriligator, J.
2008-12-01
Interstellar neutral hydrogen flows into the heliosphere and becomes ionized by photoionization and by charge exchange with solar wind protons. These "pickup" protons cause a slowing and heating of the solar wind flow in the outer heliosphere. We are adding the physics of these processes to our time-dependent 3D Hybrid Heliospheric Modeling System. We plan to present initial results for the "Halloween" 2003 events, and to show comparisons with both ACE and Ulysses observations and with our previous results (without pickup protons). This work is sponsored by NASA Grant NNX08AE40G and by Carmel Research Center. Detman et al., 2006, A hybrid heliospheric modeling system: Background solar wind, J. Geophys. Res., V 111, doi:10.1029/2005JA011340
Nonlinear electromagnetic gyrokinetic particle simulations with the electron hybrid model
NASA Astrophysics Data System (ADS)
Nishimura, Y.; Lin, Z.; Chen, L.; Hahm, T.; Wang, W.; Lee, W.
2006-10-01
The electromagnetic model with fluid electrons is successfully implemented into the global gyrokinetic code GTC. In the ideal MHD limit, shear Alfven wave oscillation and continuum damping is demonstrated. Nonlinear electromagnetic simulation is further pursued in the presence of finite ηi. Turbulence transport in the AITG unstable β regime is studied. This work is supported by Department of Energy (DOE) Grant DE-FG02-03ER54724, Cooperative Agreement No. DE-FC02-04ER54796 (UCI), DOE Contract No. DE-AC02-76CH03073 (PPPL), and in part by SciDAC Center for Gyrokinetic Particle Simulation of Turbulent Transport in Burning Plasmas. Z. Lin, et al., Science 281, 1835 (1998). F. Zonca and L. Chen, Plasma Phys. Controlled Fusion 30, 2240 (1998); G. Zhao and L. Chen, Phys. Plasmas 9, 861 (2002).
A Hybrid Aerodynamic and Aeroacoustic Modeling for Small Wind Turbines
NASA Astrophysics Data System (ADS)
Stoica, C.; Dumitrescu, H.; Dumitrache, Al.
2010-09-01
Stall control and pitch control are the most commonly used methods of regulating power. However, through the opportunities presented by the flexible (or teetered) hub of a two-bladed teetered rotor one can also utilize yaw control to regulate power. This is achieved by adjusting the capture area of the rotor disk relative to the prevailing wind direction. This paper presents the aerodynamic and aeroacoustic results obtained from theoretical models for such a rotor when is yawed to the undisturbed flow. The non-axial flow operating conditions results in a variation in the power output and noise spectrum. Some comparisons between calculated and measured noise spectra of a yaw controlled wind turbine show good agreement over all angles up to 60 degrees of yaw.
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.
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.
NASA Astrophysics Data System (ADS)
Holod, I.; Lin, Z.
2013-03-01
The fluid-kinetic hybrid electron model is verified in global gyrokinetic particle simulation of linear electromagnetic drift-Alfvénic instabilities in tokamak. In particular, we have recovered the β-stabilization of the ion temperature gradient mode, transition to collisionless trapped electron mode, and the onset of kinetic ballooning mode as βe (ratio of electron kinetic pressure to magnetic pressure) increases.
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.
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
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.
From CAD to Digital Modeling: the Necessary Hybridization of Processes
NASA Astrophysics Data System (ADS)
Massari, G. A.; Bernardi, F.; Cristofolini, A.
2011-09-01
The essay deals with the themes of digital representation of architecture starting from several years of teaching activity which is growing within the course of Automatic Design of the degree course in Engineering/Architecture in the University of Trento. With the development of CAD systems, architectural representation lies less in the tracking of a simple graph and drawn deeper into a series of acts of building a complex digital model, which can be used as a data base on which to report all the stages of project and interpretation work, and from which to derive final drawings and documents. The advent of digital technology has led to increasing difficulty in finding explicit connections between one type of operation and the subsequent outcome; thereby increasing need for guidelines, the need to understand in order to precede the changes, the desire not to be overwhelmed by uncontrollable influences brought by technological hardware and software systems to use only in accordance with the principle of maximum productivity. Formation occupies a crucial role because has the ability to direct the profession toward a thoughtful and selective use of specific applications; teaching must build logical routes in the fluid world of info-graphics and the only way to do so is to describe its contours through method indications: this will consist in understanding, studying and divulging what in its mobility does not change, as procedural issues, rather than what is transitory in its fixity, as manual questions.
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.
Numerical Modelling of Staged Combustion Aft-Injected Hybrid Rocket Motors
NASA Astrophysics Data System (ADS)
Nijsse, Jeff
The staged combustion aft-injected hybrid (SCAIH) rocket motor is a promising design for the future of hybrid rocket propulsion. Advances in computational fluid dynamics and scientific computing have made computational modelling an effective tool in hybrid rocket motor design and development. The focus of this thesis is the numerical modelling of the SCAIH rocket motor in a turbulent combustion, high-speed, reactive flow framework accounting for solid soot transport and radiative heat transfer. The SCAIH motor is modelled with a shear coaxial injector with liquid oxygen injected in the center at sub-critical conditions: 150 K and 150 m/s (Mach ≈ 0.9), and a gas-generator gas-solid mixture of one-third carbon soot by mass injected in the annual opening at 1175 K and 460 m/s (Mach ≈ 0.6). Flow conditions in the near injector region and the flame anchoring mechanism are of particular interest. Overall, the flow is shown to exhibit instabilities and the flame is shown to anchor directly on the injector faceplate with temperatures in excess of 2700 K.
An exact stochastic hybrid model of excitable membranes including spatio-temporal evolution.
Buckwar, Evelyn; Riedler, Martin G
2011-12-01
In this paper, we present a mathematical description for excitable biological membranes, in particular neuronal membranes. We aim to model the (spatio-) temporal dynamics, e.g., the travelling of an action potential along the axon, subject to noise, such as ion channel noise. Using the framework of Piecewise Deterministic Processes (PDPs) we provide an exact mathematical description-in contrast to pseudo-exact algorithms considered in the literature-of the stochastic process one obtains coupling a continuous time Markov chain model with a deterministic dynamic model of a macroscopic variable, that is coupling Markovian channel dynamics to the time-evolution of the transmembrane potential. We extend the existing framework of PDPs in finite dimensional state space to include infinite-dimensional evolution equations and thus obtain a stochastic hybrid model suitable for modelling spatio-temporal dynamics. We derive analytic results for the infinite-dimensional process, such as existence, the strong Markov property and its extended generator. Further, we exemplify modelling of spatially extended excitable membranes with PDPs by a stochastic hybrid version of the Hodgkin-Huxley model of the squid giant axon. Finally, we discuss the advantages of the PDP formulation in view of analytical and numerical investigations as well as the application of PDPs to structurally more complex models of excitable membranes. PMID:21243359
A hybrid phenomenological model for ferroelectroelastic ceramics. Part I: Single phased materials
NASA Astrophysics Data System (ADS)
Stark, S.; Neumeister, P.; Balke, H.
2016-10-01
In this part I of a two part series, a rate-independent hybrid phenomenological constitutive model applicable for single phased polycrystalline ferroelectroelastic ceramics is presented. The term "hybrid" refers to the fact that features from macroscopic phenomenological models and micro-electromechanical phenomenological models are combined. In particular, functional forms for a switching function and the Helmholtz free energy are assumed as in many macroscopic phenomenological models; and the volume fractions of domain variants are used to describe the internal material state, which is a key feature of micro-electromechanical phenomenological models. The approach described in this paper is an attempt to combine the advantages of macroscopic and micro-electromechanical material models. Its potential is demonstrated by comparison with experimental data for barium titanate. Finally, it is shown that the model for single phased materials cannot reproduce the material behavior of morphotropic PZT ceramics based on a realistic choice for the material parameters. This serves as a motivation for part II of the series, which deals with the modeling of morphotropic PZT ceramics taking into account the micro-structural specifics of these materials.
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
Wu, Wei; Guo, Junqiao; An, Shuyi; Guan, Peng; Ren, Yangwu; Xia, Linzi; Zhou, Baosen
2015-01-01
Background Cases of hemorrhagic fever with renal syndrome (HFRS) are widely distributed in eastern Asia, especially in China, Russia, and Korea. It is proved to be a difficult task to eliminate HFRS completely because of the diverse animal reservoirs and effects of global warming. Reliable forecasting is useful for the prevention and control of HFRS. Methods Two hybrid models, one composed of nonlinear autoregressive neural network (NARNN) and autoregressive integrated moving average (ARIMA) the other composed of generalized regression neural network (GRNN) and ARIMA were constructed to predict the incidence of HFRS in the future one year. Performances of the two hybrid models were compared with ARIMA model. Results The ARIMA, ARIMA-NARNN ARIMA-GRNN model fitted and predicted the seasonal fluctuation well. Among the three models, the mean square error (MSE), mean absolute error (MAE) and mean absolute percentage error (MAPE) of ARIMA-NARNN hybrid model was the lowest both in modeling stage and forecasting stage. As for the ARIMA-GRNN hybrid model, the MSE, MAE and MAPE of modeling performance and the MSE and MAE of forecasting performance were less than the ARIMA model, but the MAPE of forecasting performance did not improve. Conclusion Developing and applying the ARIMA-NARNN hybrid model is an effective method to make us better understand the epidemic characteristics of HFRS and could be helpful to the prevention and control of HFRS. PMID:26270814
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.
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
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. 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.
Elenchezhiyan, M; Prakash, J
2015-09-01
In this work, state estimation schemes for non-linear hybrid dynamic systems subjected to stochastic state disturbances and random errors in measurements using interacting multiple-model (IMM) algorithms are formulated. In order to compute both discrete modes and continuous state estimates of a hybrid dynamic system either an IMM extended Kalman filter (IMM-EKF) or an IMM based derivative-free Kalman filters is proposed in this study. The efficacy of the proposed IMM based state estimation schemes is demonstrated by conducting Monte-Carlo simulation studies on the two-tank hybrid system and switched non-isothermal continuous stirred tank reactor system. Extensive simulation studies reveal that the proposed IMM based state estimation schemes are able to generate fairly accurate continuous state estimates and discrete modes. In the presence and absence of sensor bias, the simulation studies reveal that the proposed IMM unscented Kalman filter (IMM-UKF) based simultaneous state and parameter estimation scheme outperforms multiple-model UKF (MM-UKF) based simultaneous state and parameter estimation scheme.
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
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.
Hwang, Wonjun; Wang, Haitao; Kim, Hyunwoo; Kee, Seok-Cheol; Kim, Junmo
2011-04-01
The authors present a robust face recognition system for large-scale data sets taken under uncontrolled illumination variations. The proposed face recognition system consists of a novel illumination-insensitive preprocessing method, a hybrid Fourier-based facial feature extraction, and a score fusion scheme. First, in the preprocessing stage, a face image is transformed into an illumination-insensitive image, called an "integral normalized gradient image," by normalizing and integrating the smoothed gradients of a facial image. Then, for feature extraction of complementary classifiers, multiple face models based upon hybrid Fourier features are applied. The hybrid Fourier features are extracted from different Fourier domains in different frequency bandwidths, and then each feature is individually classified by linear discriminant analysis. In addition, multiple face models are generated by plural normalized face images that have different eye distances. Finally, to combine scores from multiple complementary classifiers, a log likelihood ratio-based score fusion scheme is applied. The proposed system using the face recognition grand challenge (FRGC) experimental protocols is evaluated; FRGC is a large available data set. Experimental results on the FRGC version 2.0 data sets have shown that the proposed method shows an average of 81.49% verification rate on 2-D face images under various environmental variations such as illumination changes, expression changes, and time elapses. PMID:20923738
Mixed model approaches for the identification of QTLs within a maize hybrid breeding program.
van Eeuwijk, Fred A; Boer, Martin; Totir, L Radu; Bink, Marco; Wright, Deanne; Winkler, Christopher R; Podlich, Dean; Boldman, Keith; Baumgarten, Andy; Smalley, Matt; Arbelbide, Martin; ter Braak, Cajo J F; Cooper, Mark
2010-01-01
Two outlines for mixed model based approaches to quantitative trait locus (QTL) mapping in existing maize hybrid selection programs are presented: a restricted maximum likelihood (REML) and a Bayesian Markov Chain Monte Carlo (MCMC) approach. The methods use the in-silico-mapping procedure developed by Parisseaux and Bernardo (2004) as a starting point. The original single-point approach is extended to a multi-point approach that facilitates interval mapping procedures. For computational and conceptual reasons, we partition the full set of relationships from founders to parents of hybrids into two types of relations by defining so-called intermediate founders. QTL effects are defined in terms of those intermediate founders. Marker based identity by descent relationships between intermediate founders define structuring matrices for the QTL effects that change along the genome. The dimension of the vector of QTL effects is reduced by the fact that there are fewer intermediate founders than parents. Furthermore, additional reduction in the number of QTL effects follows from the identification of founder groups by various algorithms. As a result, we obtain a powerful mixed model based statistical framework to identify QTLs in genetic backgrounds relevant to the elite germplasm of a commercial breeding program. The identification of such QTLs will provide the foundation for effective marker assisted and genome wide selection strategies. Analyses of an example data set show that QTLs are primarily identified in different heterotic groups and point to complementation of additive QTL effects as an important factor in hybrid performance.
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
Shape memory alloy micro-actuator performance prediction using a hybrid constitutive model
NASA Astrophysics Data System (ADS)
Wong, Franklin C.; Boissonneault, Olivier
2006-03-01
The volume and weight budgets in missiles and gun-launched munitions have decreased with the military forces' emphasis on soldier-centric systems and rapid deployability. Reduction in the size of control actuation systems employed in today's aerospace vehicles would enhance overall vehicle performance as long as there is no detrimental impact on flight performance. Functional materials such as shape memory alloys (SMA's) offer the opportunity to create compact, solid-state actuation systems for flight applications. A hybrid SMA model was developed for designing micro-actuated flow effectors. It was based on a combination of concepts originally presented by Likhatchev for microstructural modelling and Brinson for modelling of transformation kinetics. The phase diagram for a 0.1mm SMA wire was created by carrying out tensile tests in a Rheometrics RSA-II solids analyser over a range of temperatures from 30°C to 130°C. The characterization parameters were used in the hybrid model to predict the displacement-time trajectories for the wire. Experimental measurements were made for a SMA wire that was subjected to a constant 150g load and short, intense 4.5 to 10V pulses. Actuation frequency was limited by the cooling rate rather than the heating rate. A second set of experiments studied the performance of SMA wires in an antagonistic micro-actuator set-up. A series of 2 or 3V step inputs were alternately injected into each wire to characterize the peak to peak displacement and the motion time constant. A maximum frequency of 0.25Hz was observed. An antagonistic actuator model based on the hybrid SMA model predicted reasonably well the displacement-time results.
The hybrid RANS/LES of partially premixed supersonic combustion using G/Z flamelet model
NASA Astrophysics Data System (ADS)
Wu, Jinshui; Wang, Zhenguo; Bai, Xuesong; Sun, Mingbo; Wang, Hongbo
2016-10-01
In order to describe partially premixed supersonic combustion numerically, G/Z flamelet model is developed and compared with finite rate model in hybrid RANS/LES simulation to study the strut-injection supersonic combustion flow field designed by the German Aerospace Center. A new temperature calculation method based on time-splitting method of total energy is introduced in G/Z flamelet model. Simulation results show that temperature predictions in partially premixed zone by G/Z flamelet model are more consistent with experiment than finite rate model. It is worth mentioning that low temperature reaction zone behind the strut is well reproduced. Other quantities such as average velocity and average velocity fluctuation obtained by developed G/Z flamelet model are also in good agreement with experiment. Besides, simulation results by G/Z flamelet also reveal the mechanism of partially premixed supersonic combustion by the analyses of the interaction between turbulent burning velocity and flow field.
Calibration of interphase fluorescence in situ hybridization cutoff by mathematical models.
Du, Qinghua; Li, Qingshan; Sun, Daochun; Chen, Xiaoyan; Yu, Bizhen; Ying, Yi
2016-03-01
Fluorescence in situ hybridization (FISH) continues to play an important role in clinical investigations. Laboratories may create their own cutoff, a percentage of positive nuclei to determine whether a specimen is positive or negative, to eliminate false positives that are created by signal overlap in most cases. In some cases, it is difficult to determine the cutoff value because of differences in both the area of nuclei and the number of signals. To address these problems, we established two mathematical models using probability theory. To verify these two models, normal disomy cells from healthy individuals were used to simulate cells with different numbers of signals by hybridization with different probes. We used an X/Y probe to obtain the average distance between two signals and the probability of signal overlap in different nuclei area. Frequencies of all signal patterns were scored and compared with theoretical frequencies, and models were assessed using a goodness of fit test. We used five BCR/ABL1-positive samples, 20 BCR/ABL1-negative samples and two samples with ambiguous results to verify the cutoff calibrated by these two models. The models were in agreement with experimental results. The dynamic cutoff can classify cases in routine analysis correctly, and it can also correct for influences from nuclei area and the number of signals in some ambiguous cases. The probability models can be used to assess the effect of signal overlap and calibrate the cutoff. PMID:26580488
NASA Astrophysics Data System (ADS)
Wen, De-Qi; Liu, Wei; Gao, Fei; Lieberman, M. A.; Wang, You-Nian
2016-08-01
A hybrid model, i.e. a global model coupled bidirectionally with a parallel Monte-Carlo collision (MCC) sheath model, is developed to investigate an inductively coupled discharge with a bias source. This hybrid model can self-consistently reveal the interaction between the bulk plasma and the radio frequency (rf) bias sheath. More specifically, the plasma parameters affecting characteristics of rf bias sheath (sheath length and self-bias) are calculated by a global model and the effect of the rf bias sheath on the bulk plasma is determined by the voltage drop of the rf bias sheath. Moreover, specific numbers of ions are tracked in the rf bias sheath and ultimately the ion energy distribution function (IEDF) incident on the bias electrode is obtained. To validate this model, both bulk plasma density and IEDF on the bias electrode in an argon discharge are compared with experimental measurements, and a good agreement is obtained. The advantage of this model is that it can quickly calculate the bulk plasma density and IEDF on the bias electrode, which are of practical interest in industrial plasma processing, and the model could be easily extended to serve for industrial gases.
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 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.
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.
A canine hybrid double-bundle model for study of arthroscopic ACL reconstruction.
Cook, James L; Smith, Patrick A; Stannard, James P; Pfeiffer, Ferris M; Kuroki, Keiichi; Bozynski, Chantelle C; Cook, Cristi R
2015-08-01
Development and validation of a large animal model for pre-clinical studies of intra-articular anterior cruciate ligament (ACL) reconstruction that addresses current limitations is highly desirable. The objective of the present study was to investigate a translational canine model for ACL reconstruction. With institutional approval, adult research hounds underwent arthroscopic debridement of the anteromedial bundle (AMB) of the ACL, and then either received a tendon autograft for "hybrid double-bundle" ACL reconstruction (n = 12) or no graft to remain ACL/AMB-deficient (n = 6). Contralateral knees were used as non-operated controls (n = 18) and matched canine cadaveric knees were used as biomechanical controls (n = 6). Dogs were assessed using functional, diagnostic imaging, gross, biomechanical, and histologic outcome measures required for pre-clinical animal models. The data suggest that this canine model was able to overcome the major limitations of large animal models used for translational research in ACL reconstruction and closely follow clinical aspects of human ACL reconstruction. The "hybrid double-bundle" ACL reconstruction allowed for sustained knee function without the development of osteoarthritis and for significantly improved functional, diagnostic imaging, gross, biomechanical, and histologic outcomes in grafted knees compared to ACL/AMB-deficient knees.
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.
A hybrid method for modelling two dimensional non-breaking and breaking waves
NASA Astrophysics Data System (ADS)
Sriram, V.; Ma, Q. W.; Schlurmann, T.
2014-09-01
This is the first paper to present a hybrid method coupling an Improved Meshless Local Petrov Galerkin method with Rankine source solution (IMLPG_R) based on the Navier-Stokes (NS) equations, with a finite element method (FEM) based on the fully nonlinear potential flow theory (FNPT) in order to efficiently simulate the violent waves and their interaction with marine structures. The two models are strongly coupled in space and time domains using a moving overlapping zone, wherein the information from both the solvers is exchanged. In the time domain, the Runge-Kutta 2nd order method is nested with a predictor-corrector scheme. In the space domain, numerical techniques including ‘Feeding Particles’ and two-layer particle interpolation with relaxation coefficients are introduced to achieve the robust coupling of the two models. The properties and behaviours of the new hybrid model are tested by modelling a regular wave, solitary wave and Cnoidal wave including breaking and overtopping. It is validated by comparing the results of the method with analytical solutions, results from other methods and experimental data. The paper demonstrates that the method can produce satisfactory results but uses much less computational time compared with a method based on the full NS model.
A new self-consistent hybrid chemistry model for Mars and cometary environments
NASA Astrophysics Data System (ADS)
Wedlund, Cyril Simon; Kallio, Esa; Jarvinen, Riku; Dyadechkin, Sergey; Alho, Markku
2014-05-01
Over the last 15 years, a 3-D hybrid-PIC planetary plasma interaction modelling platform, named HYB, has been developed, which was applied to several planetary environment such as those of Mars, Venus, Mercury, and more recently, the Moon. We present here another evolution of HYB including a fully consistent ionospheric-chemistry package designed to reproduce the main ions in the lower boundary of the model. This evolution, also permitted by the increase in computing power and the switch to spherical coordinates for higher spatial resolution (Dyadechkin et al., 2013), is motivated by the imminent arrival of the Rosetta spacecraft in the vicinity of comet 67P/Churyumov-Gerasimenko. In this presentation we show the application of the new HYB-ionosphere model to 1D and 2D hybrid simulations at Mars above 100 km altitude and demonstrate that with a limited number of chemical reactions, good agreement with 1D kinetic models may be found. This is a first validation step before applying the model to the 67P/CG comet environment, which, like Mars, is expected be rich in carbon oxide compounds.
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.
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
NASA Astrophysics Data System (ADS)
Meyer, C. A.; Swanson, E. S.
2015-05-01
A review of the theoretical and experimental status of hybrid hadrons is presented. The states π1(1400) , π1(1600) , and π1(2015) are thoroughly reviewed, along with experimental results from GAMS, VES, Obelix, COMPASS, KEK, CLEO, Crystal Barrel, CLAS, and BNL. Theoretical lattice results on the gluelump spectrum, adiabatic potentials, heavy and light hybrids, and transition matrix elements are discussed. These are compared with bag, string, flux tube, and constituent gluon models. Strong and electromagnetic decay models are described and compared to lattice gauge theory results. We conclude that while good evidence for the existence of a light isovector exotic meson exists, its confirmation as a hybrid meson awaits discovery of its iso-partners. We also conclude that lattice gauge theory rules out a number of hybrid models and provides a reference to judge the success of others.
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.
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.
Phase Resetting and Phase Locking in Hybrid Circuits of One Model and One Biological Neuron
Oprisan, S. A.; Prinz, A. A.; Canavier, C. C.
2004-01-01
To determine why elements of central pattern generators phase lock in a particular pattern under some conditions but not others, we tested a theoretical pattern prediction method. The method is based on the tabulated open loop pulsatile interactions of bursting neurons on a cycle-by-cycle basis and was tested in closed loop hybrid circuits composed of one bursting biological neuron and one bursting model neuron coupled using the dynamic clamp. A total of 164 hybrid networks were formed by varying the synaptic conductances. The prediction of 1:1 phase locking agreed qualitatively with the experimental observations, except in three hybrid circuits in which 1:1 locking was predicted but not observed. Correct predictions sometimes required consideration of the second order phase resetting, which measures the change in the timing of the second burst after the perturbation. The method was robust to offsets between the initiation of bursting in the presynaptic neuron and the activation of the synaptic coupling with the postsynaptic neuron. The quantitative accuracy of the predictions fell within the variability (10%) in the experimentally observed intrinsic period and phase resetting curve (PRC), despite changes in the burst duration of the neurons between open and closed loop conditions. PMID:15454430
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.
Ettarh, Rajunor
2016-05-01
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.
Ettarh, Rajunor
2016-05-01
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. PMID:26749245
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.
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
Hybrid modeling of plasmas and applications to fusion and space physics
NASA Astrophysics Data System (ADS)
Kazeminejad, Farzad
Since the early days of controlled fusion research, plasma physicists have encountered great challenges in obtaining solutions to the highly nonlinear equations which govern the behavior of fusion plasmas; with the growth of other applications of plasma physics these problems have grown in importance. Obtaining reasonable solutions to the nonlinear equations is crucial to understanding the behavior of plasmas. With the advent of high speed computers, computer modeling of plasmas has moved into the front row of the tools used in research of their nonlinear plasma dynamics. There are roughly speaking two types of plasma models, particle models and fluid models. Particle models in general require larger memory for the computer due to the massive amounts of data associated with the particles' kinematical variables. Fluid models are better fit to handle large scales and long times. The drawback of fluid models however, is that they miss the physical phenomena taking place at the microscale and these phenomena can influence the properties of the fluids. Another approach is to start with fluid models and incorporate more physics. Such models are referred to as hybrid models: two such models are discussed. They are then applied to two problems; the first is a simulation of the artificial comet generated by the AMPTE experiment; the second is the production of enhanced noise in fusion plasmas by injected energetic ions or by fusion reaction products. In both cases, the models demonstrate qualitative agreement with the experimental observations.
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
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.
Fatty acid membrane assembly on coacervate microdroplets as a step towards a hybrid protocell model.
Dora Tang, T-Y; Rohaida Che Hak, C; Thompson, Alexander J; Kuimova, Marina K; Williams, D S; Perriman, Adam W; Mann, Stephen
2014-06-01
Mechanisms of prebiotic compartmentalization are central to providing insights into how protocellular systems emerged on the early Earth. Protocell models are based predominantly on the membrane self-assembly of fatty-acid vesicles, although membrane-free scenarios that involve liquid-liquid microphase separation (coacervation) have also been considered. Here we integrate these alternative models of prebiotic compartmentalization and develop a hybrid protocell model based on the spontaneous self-assembly of a continuous fatty-acid membrane at the surface of preformed coacervate microdroplets prepared from cationic peptides/polyelectrolytes and adenosine triphosphate or oligo/polyribonucleotides. We show that the coacervate-supported membrane is multilamellar, and mediates the selective uptake or exclusion of small and large molecules. The coacervate interior can be disassembled without loss of membrane integrity, and fusion and growth of the hybrid protocells can be induced under conditions of high ionic strength. Our results highlight how notions of membrane-mediated compartmentalization, chemical enrichment and internalized structuration can be integrated in protocell models via simple chemical and physical processes.
Fatty acid membrane assembly on coacervate microdroplets as a step towards a hybrid protocell model
NASA Astrophysics Data System (ADS)
Dora Tang, T.-Y.; Rohaida Che Hak, C.; Thompson, Alexander J.; Kuimova, Marina K.; Williams, D. S.; Perriman, Adam W.; Mann, Stephen
2014-06-01
Mechanisms of prebiotic compartmentalization are central to providing insights into how protocellular systems emerged on the early Earth. Protocell models are based predominantly on the membrane self-assembly of fatty-acid vesicles, although membrane-free scenarios that involve liquid-liquid microphase separation (coacervation) have also been considered. Here we integrate these alternative models of prebiotic compartmentalization and develop a hybrid protocell model based on the spontaneous self-assembly of a continuous fatty-acid membrane at the surface of preformed coacervate microdroplets prepared from cationic peptides/polyelectrolytes and adenosine triphosphate or oligo/polyribonucleotides. We show that the coacervate-supported membrane is multilamellar, and mediates the selective uptake or exclusion of small and large molecules. The coacervate interior can be disassembled without loss of membrane integrity, and fusion and growth of the hybrid protocells can be induced under conditions of high ionic strength. Our results highlight how notions of membrane-mediated compartmentalization, chemical enrichment and internalized structuration can be integrated in protocell models via simple chemical and physical processes.
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
Fatty acid membrane assembly on coacervate microdroplets as a step towards a hybrid protocell model.
Dora Tang, T-Y; Rohaida Che Hak, C; Thompson, Alexander J; Kuimova, Marina K; Williams, D S; Perriman, Adam W; Mann, Stephen
2014-06-01
Mechanisms of prebiotic compartmentalization are central to providing insights into how protocellular systems emerged on the early Earth. Protocell models are based predominantly on the membrane self-assembly of fatty-acid vesicles, although membrane-free scenarios that involve liquid-liquid microphase separation (coacervation) have also been considered. Here we integrate these alternative models of prebiotic compartmentalization and develop a hybrid protocell model based on the spontaneous self-assembly of a continuous fatty-acid membrane at the surface of preformed coacervate microdroplets prepared from cationic peptides/polyelectrolytes and adenosine triphosphate or oligo/polyribonucleotides. We show that the coacervate-supported membrane is multilamellar, and mediates the selective uptake or exclusion of small and large molecules. The coacervate interior can be disassembled without loss of membrane integrity, and fusion and growth of the hybrid protocells can be induced under conditions of high ionic strength. Our results highlight how notions of membrane-mediated compartmentalization, chemical enrichment and internalized structuration can be integrated in protocell models via simple chemical and physical processes. PMID:24848239
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.
Modeling human cancer-related regulatory modules by GA-RNN hybrid algorithms
Chiang, Jung-Hsien; Chao, Shih-Yi
2007-01-01
Background Modeling cancer-related regulatory modules from gene expression profiling of cancer tissues is expected to contribute to our understanding of cancer biology as well as developments of new diagnose and therapies. Several mathematical models have been used to explore the phenomena of transcriptional regulatory mechanisms in Saccharomyces cerevisiae. However, the contemplating on controlling of feed-forward and feedback loops in transcriptional regulatory mechanisms is not resolved adequately in Saccharomyces cerevisiae, nor is in human cancer cells. Results In this study, we introduce a Genetic Algorithm-Recurrent Neural Network (GA-RNN) hybrid method for finding feed-forward regulated genes when given some transcription factors to construct cancer-related regulatory modules in human cancer microarray data. This hybrid approach focuses on the construction of various kinds of regulatory modules, that is, Recurrent Neural Network has the capability of controlling feed-forward and feedback loops in regulatory modules and Genetic Algorithms provide the ability of global searching of common regulated genes. This approach unravels new feed-forward connections in regulatory models by modified multi-layer RNN architectures. We also validate our approach by demonstrating that the connections in our cancer-related regulatory modules have been most identified and verified by previously-published biological documents. Conclusion The major contribution provided by this approach is regarding the chain influences upon a set of genes sequentially. In addition, this inverse modeling correctly identifies known oncogenes and their interaction genes in a purely data-driven way. PMID:17359522
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.
2015-07-01
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 Cercingani-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.
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.
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.
The ObjECTS: Framework for Integrated Assessment: Hybrid Modeling of Transportation
Kim, Son H.; Edmonds, James A.; Lurz, Joshua; Smith, Steven J.; Wise, Marshall A.
2006-09-01
Technology is a central issue for the global climate change problem, requiring analysis tools that can examine the impact of specific technologies with a long-term, global context. This paper describes the architecture of the ObjECTS-MiniCAM integrated assessment model, which implements a long-term, global model of energy, economy, agriculture, land-use, atmosphere, and climate change in a framework that allows the flexible incorporation of explicit technology detail. We describe the implementation of a ''bottom-up'' representation of the transportation sector as an illustration of this approach, in which the resulting hybrid model is fully integrated, internally consistent and theoretically compatible with the regional and global modeling framework. The analysis of the transportation sector presented here supports and clarifies the need for a comprehensive strategy promoting advanced vehicle technologies and an economy-wide carbon policy to cost-effectively reduce carbon emissions from the transportation sector in the long-term.
An isothermal model of a hybrid Stirling/reverse-Brayton cryocooler
NASA Astrophysics Data System (ADS)
Nellis, G. F.; Maddocks, J. R.
2003-01-01
This paper presents a model of a cryogenic refrigerator that integrates a reverse-Brayton lower temperature stage with a 2-piston Stirling upper temperature stage using a rectification system of check valves and buffer volumes. The numerical model extends the isothermal Schmidt analysis of the Stirling cycle by deriving the additional dimensionless governing equations that characterize the recuperative system. Numerical errors are quantified and the results are verified against analytical solutions in the appropriate limits. The model is used to explore the effect of the rectification system's characteristics on the overall cycle's behavior. Finally, the model is used to optimize the hybrid system's design by varying the swept volume ratio and phase angle in order to maximize the refrigeration per unit of heat transfer in the recuperator and regenerator.
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.
Implementation of 3D wave forcing terms in the HYbrid Coordinate Ocean Model
NASA Astrophysics Data System (ADS)
Ody, Cédric; Filipot, Jean-François; Pichon, Annick; Lathuilière, Cyril; Baraille, Rémy
2013-04-01
Waves may influence the circulation in coastal regions at temporal and spatial scales that are larger than the periods and wavelengths of the waves respectively. The setup of the mean sea surface level or longshore currents are two examples of coastal processes that are generated by the mean effects of waves. Although simple models have been shown to provide reasonable estimates of setup and mean currents, the prediction of such wave-induced mechanisms has been improved since the recent development of theories on 3D wave-current interactions. Amongst these theories, the works of Ardhuin et al. (2008) and Mc Williams et al. (2004) give rise to forcing terms that may be used in existing circulation models. Under some assumptions on the shear of the mean current, the two previous works derive similar expressions for the wave forcing terms. In this talk, we will detail and discuss the implementation of these 3D terms in the HYbrid Coordinate Ocean Model (HYCOM, Bleck 2002). We will focus in particular on the hybrid and layered features of the code. The hybrid coordinate, which allows to use distinct vertical coordinates in a same simulation, requires to reformulate the wave forcing terms with a generalised vertical coordinate. Then, these terms must be averaged on each layer of the water column. Two academic tests are investigated to validate the numerical implementation : the gently sloping bottom of Ardhuin (2008) and the plane beach of Haas and Warner (2009). Forcing terms are calculated with simple numerical methods under classical assumptions on conservation of wave properties. The results obtained with distinct configurations are shown to agree with the analytical or numerical known solutions. To conclude, we will discuss the impact of wetting and drying in numerical simulations.
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.
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...
Jovian's plasma torus interaction with Europa. E12 pass: 3D hybrid kinetic modeling
NASA Astrophysics Data System (ADS)
Lipatov, A. S.; Cooper, J. F.; Sittler, E. C., Jr.; Paterson, W. R.; Hartle, R. E.
2012-09-01
The hybrid kinetic model supports comprehensive simulation of the interaction between different spatial and energetic elements of the Europa moonmagnetosphere system with respect to variable upstream magnetic field and flux or density distributions of plasma and energetic ions, electrons, and neutral atoms. This capability is critical for improving the interpretation of the existing Europa flybymeasurements from Galileo orbital mission and for planning flyby and orbital measurements for future missions. The simulations are based on recent models of the atmosphere of Europa [1, 2, 3]. The upstream parameters have been chosen from the plasma and magnetic field Galileo E12 observations, [4, 5]. In contrast to previous approaches with MHD simulations, the hybrid model allows us to fully take into account the finite gyroradius effect and electron pressure, and to correctly estimate the ions velocity distribution and the fluxes along themagnetic field [6]. Photoionization, electron-impact ionization and charge exchange are included in our model. The temperature of the background electrons and pickup electrons was also included into the generalized Ohm's law. The background plasma contains heavy (Mi/Qi = 16) and light (Mi/Qi = 1) ions [4]. In our modeling we take into account only O+ ions for magnetospheric plasma. The pickup ions were created from the atmosphere. The majority of O2 atmosphere is thermal with an extended non-thermal population [1]. The moon is modeled in this initial work as a weakly conducting body. The critical point of E12 pass is the extremely high density in upstream plasma, e.g. n0 = 70-571 cm-3 for ions with Mi/Qi ratio equals 16. This density results in to the superAlfvénic flow and it will change the physics of the interaction between Jovianmagnetosphere and Europa. The modeling show the formation of the Mach cone instead of the Alfv'en wing which was observed in hybrid modeling of E4 pass [6]. The modeling shows that the effective size of the
NASA Astrophysics Data System (ADS)
Dehmollaian, Mojtaba
This thesis focuses on the application of radio waves for detection and recognition of visually obscured targets. To provide practical solutions, comprehensive forward and inverse models are needed to capture and exploit the physical phenomena involved. These models must accurately simulate wave propagation in the environment in which the target is imbedded, scattering from the target and wave interaction of the medium scatterers and the target. In this dissertation, two problems of major importance are investigated. The first problem is detection of complex targets camouflaged inside forest and the second problem pertains to imaging of building interiors and detection of targets within. In the early chapters, a hybrid target-foliage model is developed to investigate the scattering behavior of hard targets embedded inside a forest canopy. This model is composed of two parts, one for foliage and the other for hard targets. The connection between these two models that accounts for the first-order interaction between the foliage scatterers and the target is accomplished through the application of the reciprocity theorem. The foliage penetration model is based on the coherent single scattering theory, developed previously. The target scattering model is based on either exact numerical finite difference time domain technique or high frequency asymptotic iterative physical optics approximation. Having the hybrid target-foliage model, a polarization synthesis optimization method for improving signal to clutter ratio is presented, using genetic algorithms. In the later chapters, the problem of through-wall imaging using the synthetic aperture radar technique by employing ultra wideband antennas and scanning over a wide range of incidence angles is investigated. Theoretical and experimental studies on the effects of different walls on point target images are carried out and refocusing approaches are introduced to remove the wall effects and restore the image resolution
NASA Astrophysics Data System (ADS)
Holmstrom, M.; Wang, X.-D.
2015-10-01
A hybrid plasma solver treats ions as particles and electrons as a fluid. We have implemented a parallel hybrid solver in the FLASH open source software framework. The solver has been applied to studies of the interaction between the solar wind and planets. Here we discuss the implementation of different model features, such as permanent magnetic fields, ionospheric chemistry, and exospheres. Mars is used as an example.
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.
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.
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.
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.
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.
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
NASA Technical Reports Server (NTRS)
Carros, R. J.; Boissevain, A. G.; Aoyagi, K.
1975-01-01
Data are presented from an investigation of the aerodynamic characteristics of large-scale wind tunnel aircraft model that utilized a hybrid-upper surface blown flap to augment lift. The hybrid concept of this investigation used a portion of the turbofan exhaust air for blowing over the trailing edge flap to provide boundary layer control. The model, tested in the Ames 40- by 80-foot Wind Tunnel, had a 27.5 deg swept wing of aspect ratio 8 and 4 turbofan engines mounted on the upper surface of the wing. The lift of the model was augmented by turbofan exhaust impingement on the wind upper-surface and flap system. Results were obtained for three flap deflections, for some variation of engine nozzle configuration and for jet thrust coefficients from 0 to 3.0. Six-component longitudinal and lateral data are presented with four engine operation and with the critical engine out. In addition, a limited number of cross-plots of the data are presented. All of the tests were made with a downwash rake installed instead of a horizontal tail. Some of these downwash data are also presented.
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
A new hybrid model for exploring the adoption of online nursing courses.
Tung, Feng-Cheng; Chang, Su-Chao
2008-04-01
With the advancement in educational technology and internet access in recent years, nursing academia is searching for ways to widen nurses' educational opportunities. The online nursing courses are drawing more attention as well. The online nursing courses are very important e-learning tools for nursing students. The research combines the innovation diffusion theory and technology acceptance model, and adds two research variables, perceived financial cost and computer self-efficacy to propose a new hybrid technology acceptance model to study nursing students' behavioral intentions to use the online nursing courses. Based on 267 questionnaires collected from six universities in Taiwan, the research finds that studies strongly support this new hybrid technology acceptance model in predicting nursing students' behavioral intentions to use the online nursing courses. This research finds that compatibility, perceived usefulness, perceived ease of use, perceived financial cost and computer self-efficacy are critical factors for nursing students' behavioral intentions to use the online nursing courses. By explaining nursing students' behavioral intentions from a user's perspective, the findings of this research help to develop more user friendly online nursing courses and also provide insight into the best way to promote new e-learning tools for nursing students. This research finds that compatibility is the most important research variable that affects the behavioral intention to use the online nursing courses.
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.
Dynamic modeling and motion simulation for a winged hybrid-driven underwater glider
NASA Astrophysics Data System (ADS)
Wang, Shu-Xin; Sun, Xiu-Jun; Wang, Yan-Hui; Wu, Jian-Guo; Wang, Xiao-Ming
2011-03-01
PETREL, a winged hybrid-driven underwater glider is a novel and practical marine survey platform which combines the features of legacy underwater glider and conventional AUV (autonomous underwater vehicle). It can be treated as a multi-rigid-body system with a floating base and a particular hydrodynamic profile. In this paper, theorems on linear and angular momentum are used to establish the dynamic equations of motion of each rigid body and the effect of translational and rotational motion of internal masses on the attitude control are taken into consideration. In addition, due to the unique external shape with fixed wings and deflectable rudders and the dual-drive operation in thrust and glide modes, the approaches of building dynamic model of conventional AUV and hydrodynamic model of submarine are introduced, and the tailored dynamic equations of the hybrid glider are formulated. Moreover, the behaviors of motion in glide and thrust operation are analyzed based on the simulation and the feasibility of the dynamic model is validated by data from lake field trials.
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.
NASA Astrophysics Data System (ADS)
Singh Pradhan, Ananta Man; Kang, Hyo-Sub; Kim, Yun-Tae
2016-04-01
This study uses a physically based approach to evaluate the factor of safety of the hillslope for different hydrological conditions, in Mt Umyeon, south of Seoul. The hydrological conditions were determined using intensity and duration of whole Korea of known landslide inventory data. Quantile regression statistical method was used to ascertain different probability warning levels on the basis of rainfall thresholds. Physically based models are easily interpreted and have high predictive capabilities but rely on spatially explicit and accurate parameterization, which is commonly not possible. Statistical probabilistic methods can include other causative factors which influence the slope stability such as forest, soil and geology, but rely on good landslide inventories of the site. In this study a hybrid approach has described that combines the physically-based landslide susceptibility for different hydrological conditions. A presence-only based maximum entropy model was used to hybrid and analyze relation of landslide with conditioning factors. About 80% of the landslides were listed among the unstable sites identified in the proposed model, thereby presenting its effectiveness and accuracy in determining unstable areas and areas that require evacuation. These cumulative rainfall thresholds provide a valuable reference to guide disaster prevention authorities in the issuance of warning levels with the ability to reduce losses and save lives.
Non-singular string cosmology in a 2d hybrid model
NASA Astrophysics Data System (ADS)
Florakis, I.; Kounnas, C.; Partouche, H.; Toumbas, N.
2011-03-01
The existence of non-singular string cosmologies is established in a class of two-dimensional supersymmetric Hybrid models at finite temperature. The left-moving sector of the Hybrid models gives rise to 16 real (N=4) spacetime supercharges as in the usual superstring models. The right-moving sector is non-supersymmetric at the massless level, but is characterized by MSDS symmetry, which ensures boson/fermion degeneracy of the right-moving massive levels. Finite temperature configurations, which are free of Hagedorn instabilities, are constructed in the presence of non-trivial “gravito-magnetic” fluxes. These fluxes inject non-trivial winding charge into the thermal vacuum and restore the thermal T-duality symmetry associated with the Euclidean time circle. Thanks to the unbroken right-moving MSDS symmetry, the one-loop string partition function is exactly calculable beyond any α‧-approximation. At the self-dual point new massless thermal states appear, sourcing localized spacelike branes, which can be used to connect a contracting thermal Universe to an expanding one. The resulting bouncing cosmology is free of any curvature singularities and the string coupling remains perturbative throughout the cosmological evolution.
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. PMID:27120649
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 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.
NASA Astrophysics Data System (ADS)
Pohjola, Valter; Kallio, Esa; Jarvinen, Riku
We have developed a fully kinetic electromagnetic model to study instabilities and waves in planetary plasma environments. In the particle-in-a-cell (PIC) model both ions and electrons are modeled as particles. An important feature of the developed global kinetic model, called HYB-em, compared to other electromagnetic codes is that it is built up on an earlier quasi-neutral hybrid simulation platform called HYB and that it can be used in conjunction with earlier hybrid models. The HYB models have been used during the past ten years to study globally the flowing plasma interaction with various Solar System objects: Mercury, Venus, the Moon, Mars, Saturnian moon Titan and asteroids. The new model enables us to (1) study the stability of various planetary plasma regions in three dimensional space, (2) analyze the propa-gation of waves in a plasma environment derived from the other global HYB models. All particle processes in a multi-ion plasma which are implemented on the HYB platform(e.g. ion-neutral collisions, chemical processes, particle loss and production processes) are also automatically included in HYB-em model. In this presentation we study the developed approach by analyzing the propagation of high frequency electromagnetic waves in non-magnetized plasma in two cases: We study (1) expan-sion of a spherical wave generated from a point source and (2) propagation of a plane wave in plasma. We demonstrate that the HYB-em model is capable of describing these space plasma situations successfully. The analysis suggests the potential of the developed model to study both high density-high magnetic field plasma environments, such as Mercury, and low density-low magnetic field plasma environments, such as Venus and Mars.
NASA Astrophysics Data System (ADS)
Pohjola, Valter; Kallio, Esa
2010-05-01
We have developed a fully kinetic electromagnetic model to study instabilities and waves in planetary plasma environments. In the particle-in-a-cell (PIC) model both ions and electrons are modeled as particles. An important feature of the developed global kinetic model, called HYB-em, compared to other electromagnetic codes is that it is built up on an earlier quasi-neutral hybrid simulation platform called HYB and that it can be used in conjunction with earlier hybrid models. The HYB models have been used during the past ten years to study globally the flowing plasma interaction with various Solar System objects: Mercury, Venus, the Moon, Mars, Saturnian moon Titan and asteroids. The new model enables us to (1) study the stability of various planetary plasma regions in three dimensional space, (2) analyze the propagation of waves in a plasma environment derived from the other global HYB models. All particle processes in a multi-ion plasma which are implemented on the HYB platform (e.g. ion-neutral-collisions, chemical processes, particle loss and production processes) are also automatically included in HYB-em model. In this presentation we study the developed approach by analyzing the propagation of high frequency electromagnetic waves in non-magnetized plasma in two cases: We study (1) expansion of a spherical wave generated from a point source and (2) propagation of a plane wave in plasma. We demonstrate that the HYB-em model is capable of describing these space plasma situations successfully. The analysis suggests the potential of the developed model to study both high density-high magnetic field plasma environments, such as Mercury, and low density-low magnetic field plasma environments, such as Venus and Mars.
Two kinds of attention in Pavlovian conditioning: evidence for a hybrid model of learning.
Haselgrove, Mark; Esber, Guillem R; Pearce, John M; Jones, Peter M
2010-10-01
Four appetitive Pavlovian conditioning experiments with rats examined the rate at which the discrimination between compounds AY and AX was solved relative to the discrimination between compounds AY and BY. In Experiments 1 and 2, these discriminations were preceded by training in which A and B were continuously reinforced and X and Y were partially reinforced. Consistent with the Pearce and Hall (1980) model, the results showed that the AY/AX discrimination was solved more readily than the AY/BY discrimination. In Experiments 3 and 4, the discriminations were preceded by feature-positive training in which trials with AX and BY signaled food but trials with X and Y did not. Consistent with the Mackintosh (1975) model, the results showed that the AY/BY discrimination was solved more readily than the AY/AX discrimination. These results are discussed with respect to a hybrid model of conditioning and attention.
Determining the regimes of cold and warm inflation in the supersymmetric hybrid model
Bastero-Gil, Mar; Berera, Arjun
2005-03-15
The SUSY hybrid inflation model is found to dissipate radiation during the inflationary period. Analysis is made of parameter regimes in which these dissipative effects are significant. The scalar spectral index, its running, and the tensor-scalar ratio are computed in the entire parameter range of the model. A clear prediction for strong dissipative warm inflation is found for n{sub S}-1{approx_equal}0.98 and a low tensor-scalar ratio much below 10{sup -6}. The strong dissipative warm inflation regime also is found to have no {eta} problem and the field amplitude much below the Planck scale. As will be discussed, this has important theoretical implications in permitting a much wider variety of SUGRA extensions to the basic model.
ISG hybrid powertrain: a rule-based driver model incorporating look-ahead information
NASA Astrophysics Data System (ADS)
Shen, Shuiwen; Zhang, Junzhi; Chen, Xiaojiang; Zhong, Qing-Chang; Thornton, Roger
2010-03-01
According to European regulations, if the amount of regenerative braking is determined by the travel of the brake pedal, more stringent standards must be applied, otherwise it may adversely affect the existing vehicle safety system. The use of engine or vehicle speed to derive regenerative braking is one way to avoid strict design standards, but this introduces discontinuity in powertrain torque when the driver releases the acceleration pedal or applies the brake pedal. This is shown to cause oscillations in the pedal input and powertrain torque when a conventional driver model is adopted. Look-ahead information, together with other predicted vehicle states, are adopted to control the vehicle speed, in particular, during deceleration, and to improve the driver model so that oscillations can be avoided. The improved driver model makes analysis and validation of the control strategy for an integrated starter generator (ISG) hybrid powertrain possible.
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.
Coupled Hybrid Continuum-Discrete Model of Tumor Angiogenesis and Growth
Lyu, Jie; Cao, Jinfeng; Zhang, Peiming; Liu, Yang; Cheng, Hongtao
2016-01-01
The processes governing tumor growth and angiogenesis are codependent. To study the relationship between them, we proposed a coupled hybrid continuum-discrete model. In this model, tumor cells, their microenvironment (extracellular matrixes, matrix-degrading enzymes, and tumor angiogenic factors), and their network of blood vessels, described by a series of discrete points, were considered. The results of numerical simulation reveal the process of tumor growth and the change in microenvironment from avascular to vascular stage, indicating that the network of blood vessels develops gradually as the tumor grows. Our findings also reveal that a tumor is divided into three regions: necrotic, semi-necrotic, and well-vascularized. The results agree well with the previous relevant studies and physiological facts, and this model represents a platform for further investigations of tumor therapy. PMID:27701426
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.
Callisto plasma interactions: Hybrid modeling including induction by a subsurface ocean
NASA Astrophysics Data System (ADS)
Lindkvist, Jesper; Holmström, Mats; Khurana, Krishan K.; Fatemi, Shahab; Barabash, Stas
2015-06-01
By using a hybrid plasma solver (ions as particles and electrons as a fluid), we have modeled the interaction between Callisto and Jupiter's magnetosphere for variable ambient plasma parameters. We compared the results with the magnetometer data from flybys (C3, C9, and C10) by the Galileo spacecraft. Modeling the interaction between Callisto and Jupiter's magnetosphere is important to establish the origin of the magnetic field perturbations observed by Galileo and thought to be related to a subsurface ocean. Using typical upstream magnetospheric plasma parameters and a magnetic dipole corresponding to the inductive response inside the moon, we show that the model results agree well with observations for the C3 and C9 flybys, but agrees poorly with the C10 flyby close to Callisto. The study does support the existence of a subsurface ocean at Callisto.
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.
Prediction of hot spots in protein interfaces using a random forest model with hybrid features.
Wang, Lin; Liu, Zhi-Ping; Zhang, Xiang-Sun; Chen, Luonan
2012-03-01
Prediction of hot spots in protein interfaces provides crucial information for the research on protein-protein interaction and drug design. Existing machine learning methods generally judge whether a given residue is likely to be a hot spot by extracting features only from the target residue. However, hot spots usually form a small cluster of residues which are tightly packed together at the center of protein interface. With this in mind, we present a novel method to extract hybrid features which incorporate a wide range of information of the target residue and its spatially neighboring residues, i.e. the nearest contact residue in the other face (mirror-contact residue) and the nearest contact residue in the same face (intra-contact residue). We provide a novel random forest (RF) model to effectively integrate these hybrid features for predicting hot spots in protein interfaces. Our method can achieve accuracy (ACC) of 82.4% and Matthew's correlation coefficient (MCC) of 0.482 in Alanine Scanning Energetics Database, and ACC of 77.6% and MCC of 0.429 in Binding Interface Database. In a comparison study, performance of our RF model exceeds other existing methods, such as Robetta, FOLDEF, KFC, KFC2, MINERVA and HotPoint. Of our hybrid features, three physicochemical features of target residues (mass, polarizability and isoelectric point), the relative side-chain accessible surface area and the average depth index of mirror-contact residues are found to be the main discriminative features in hot spots prediction. We also confirm that hot spots tend to form large contact surface areas between two interacting proteins. Source data and code are available at: http://www.aporc.org/doc/wiki/HotSpot. PMID:22258275
Hybrid modeling of nitrate fate in large catchments using fuzzy-rules
NASA Astrophysics Data System (ADS)
van der Heijden, Sven; Haberlandt, Uwe
2010-05-01
Especially for nutrient balance simulations, physically based ecohydrological modeling needs an abundance of measured data and model parameters, which for large catchments all too often are not available in sufficient spatial or temporal resolution or are simply unknown. For efficient large-scale studies it is thus beneficial to have methods at one's disposal which are parsimonious concerning the number of model parameters and the necessary input data. One such method is fuzzy-rule based modeling, which compared to other machine-learning techniques has the advantages to produce models (the fuzzy-rules) which are physically interpretable to a certain extent, and to allow the explicit introduction of expert knowledge through pre-defined rules. The study focuses on the application of fuzzy-rule based modeling for nitrate simulation in large catchments, in particular concerning decision support. Fuzzy-rule based modeling enables the generation of simple, efficient, easily understandable models with nevertheless satisfactory accuracy for problems of decision support. The chosen approach encompasses a hybrid metamodeling, which includes the generation of fuzzy-rules with data originating from physically based models as well as a coupling with a physically based water balance model. For the generation of the needed training data and also as coupled water balance model the ecohydrological model SWAT is employed. The conceptual model divides the nitrate pathway into three parts. The first fuzzy-module calculates nitrate leaching with the percolating water from soil surface to groundwater, the second module simulates groundwater passage, and the final module replaces the in-stream processes. The aim of this modularization is to create flexibility for using each of the modules on its own, for changing or completely replacing it. For fuzzy-rule based modeling this can explicitly mean that the re-training of one of the modules with newly available data will be possible without
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.
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.
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.
"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
Hybrid Modeling of Hydrogen Energetic Neutral Atoms from Mars: Emission from Subsolar Magnetosheath
NASA Astrophysics Data System (ADS)
Wang, Xiao-Dong; Kallio, Esa; Barabash, Stas; Futaana, Yoshifumi
2015-04-01
We simulated the hydrogen energetic neutral atom (ENA) emission from the subsolar magnetosheath of Mars using a hybrid scheme in order to reproduce multiple features of the statistical features obtained from statistical observations of the Neutral Particle Detectors on the Mars Express spacecraft. We track the charge exchange reaction between the ions produced by the hybrid plasma model under a Martian neutral exosphere model. The simulation exhibits a directional emission of hydrogen ENAs from dayside magnetosheath. Particularly, the stronger ENA emission in the opposite direction of the solar wind convection electric field is reproduced, being consistent with the observations, by a corresponding asymmetry in the proton flux at the lower magnetosheath. This proton flux asymmetry is caused by the mass loading of ionospheric heavy ions in the direction of the convection electric field. We also investigate the influences of the upstream solar wind dynamic pressure. We demonstrate that higher dynamic pressure causes stronger and more anisotropic ENA emission, besides the influence of the proton flux. This dependence suggests that the induced magnetic boundary is lower during higher dynamic pressure, where the sheath protons can access to a denser exosphere and thus the charge exchange rate is higher.
Modeling plasma-assisted growth of graphene-carbon nanotube hybrid
NASA Astrophysics Data System (ADS)
Tewari, Aarti
2016-08-01
A theoretical model describing the growth of graphene-CNT hybrid in a plasma medium is presented. Using the model, the growth of carbon nanotube (CNT) on a catalyst particle and thereafter the growth of the graphene on the CNT is studied under the purview of plasma sheath and number density kinetics of different plasma species. It is found that the plasma parameter such as ion density; gas ratios and process parameter such as source power affect the CNT and graphene dimensions. The variation in growth rates of graphene and CNT under different plasma power, gas ratios, and ion densities is analyzed. Based on the results obtained, it can be concluded that higher hydrocarbon ion densities and gas ratios of hydrocarbon to hydrogen favor the growth of taller CNTs and graphene, respectively. In addition, the CNT tip radius reduces with hydrogen ion density and higher plasma power favors graphene with lesser thickness. The present study can help in better understanding of the graphene-CNT hybrid growth in a plasma medium.
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.
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.
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.
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
Wang, Yanyan; Zhang, Xiang; Wang, Qiuru; Zhang, Bing; Liu, Jindun
2014-01-01
We used natural resources of halloysite nanotubes and alginate to prepare a novel porous adsorption material of organic-inorganic hybrid beads. The adsorption behaviour of Cu(II) onto the hybrid beads was examined by a continuous fixed bed column adsorption experiment. Meanwhile, the factors affecting the adsorption capacity such as bed height, influent concentration and flow rate were investigated. The adsorption capacity (Q0) reached 74.13 mg/g when the initial inlet concentration was 100 mg/L with a bed height of 12 cm and flow rate of 3 ml/min. The Thomas model and bed-depth service time fitted well with the experimental data. In the regeneration experiment, the hybrid beads retained high adsorption capacity after three adsorption-desorption cycles. Over the whole study, the new hybrid beads showed excellent adsorption and regeneration properties as well as favourable stability. PMID:25051464
Modeling dynamic urban growth using hybrid cellular automata and particle swarm optimization
NASA Astrophysics Data System (ADS)
Rabbani, Amirhosein; Aghababaee, Hossein; Rajabi, Mohammad A.
2012-01-01
Conventional raster-based cellular automata (CA) confront many difficulties because of cell size and neighborhood sensitivity. Alternatively, vector CA-based models are very complex and difficult to implement. We present a hybrid cellular automata (HCA) model as a combination of cellular structure and vector concept. The space is still defined by a set of cells, but rasterized spatial objects are also utilized in the structure of transition rules. Particle swarm optimization (PSO) is also used to calculate the urbanization probability of cells based on their distance from the development parameters. The proposed model is applied to Landsat satellite imagery of the city of Tehran, Iran with 28.5-m spatial resolution to simulate the urban growth from 1988 to 2010. Statistical comparison of the ground truth and the simulated image using a kappa coefficient shows an accuracy of 83.42% in comparison to the 81.13% accuracy for the conventional Geo-CA model. Moreover, decreasing the spatial resolution by a factor of one-fourth has reduced the accuracy of the HCA and Geo-CA models by 1.19% and 3.04%, respectively, which shows the lower scale sensitivity of the proposed model. The HCA model is developed to have the simplicity of cellular structure together with optimum features of vector models.
NASA Astrophysics Data System (ADS)
Ezzedine, S. M.; Lomov, I.; Ryerson, F. J.; Glascoe, L. G.
2011-12-01
Numerical simulations become increasingly widespread to support decision-making and policy-making processes in energy-related emerging technologies such as enhanced geothermal systems, extraction of tight-gas to name a few. However, numerical models typically have uncertainty associated with their inputs (parametric, conceptual and structural), leading to uncertainty in model outputs. Effective abstraction of model results to decision-making requires proper characterization, propagation, and analysis of that uncertainty. Propagation of uncertainty often relies on complex multiphysics models. For instance, fluid-induced fracturing calls for hydro-mechanical, or hydro-thermal-mechanical or hydro-thermal-mechanical-chemical coupling. For the past decade several complex coupled deterministic models have been proposed to address the hydro-fracking problem with moderate successes. Despite that these models can be used as drivers for the uncertainty quantification, they are numerically and computationally cumbersome. In this paper, we present a surrogate model that can handle, for instance, 1) the hydromechanical coupling with minimum computational costs, 2) the tracking of simultaneous propagation of hundreds of fracture tips, with propagation velocities proportional to the stress intensity factor at each crack tip, 3) and the propagation of uncertainty from inputs to outputs, for example via Monte Carlo simulation. We also present a novel hybrid modeling scheme designed for propagating uncertainty and performing a global sensitivity analysis, while maintaining the quantitative rigor of the analysis by providing confidence intervals on predictions. (Prepared by LLNL under Contract DE-AC52-07NA27344).
A computationally efficient hybrid 2D/3D thin film dislocation model
NASA Astrophysics Data System (ADS)
Sarrafan, Siavash
Substantial research has been devoted to attempting to understand how dislocation structures evolve and how they affect device properties. However, current dislocation simulation methods are only able to model highly idealized systems accurately. The three-dimensional discrete dislocation dynamics models, in particular, are too computationally intensive for modelling high dislocation densities and their resultant deformations that are observed in some real applications. In this thesis, we propose a novel method to exploit the quasi-two-dimensional nature of three-dimensional dislocation loops in a thin film to model their behaviors. For most film configurations, simulation performance can be greatly enhanced by implementing a hybrid two-dimensional/three-dimensional model without losing significant fidelity. In this technique, misfits stress fields are modeled by superposing multiple two-dimensional models. Threads are modeled with a more traditional three-dimensional implementation as they move through the misfit stress field. Using this innovative technique, much higher strains and/or dislocation densities could be studied.
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. PMID:26574264
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
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...
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
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.
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. PMID:24778597
Ultraviolet A does not induce melanomas in a Xiphophorus hybrid fish model
Mitchell, David L.; Fernandez, André A.; Nairn, Rodney S.; Garcia, Rachel; Paniker, Lakshmi; Trono, David; Thames, Howard D.; Gimenez-Conti, Irma
2010-01-01
We examined the wavelength dependence of ultraviolet (UV) ra-diation (UVR)-induced melanoma in a Xiphophorus backcross hybrid model previously reported to be susceptible to melanoma induction by ultraviolet A (UVA) and visible light. Whereas ultraviolet B (UVB) irradiation of neonates yielded high frequencies of melanomas in pigmented fish, UVA irradiation resulted in melanoma frequencies that were not significantly different from unirradiated fish. Spontaneous and UV-induced melanoma frequencies correlated with the degree of pigmentation as expected from previous studies, and the histopathology phenotypes of the melanomas were not found in significantly different proportions in UV-treated and -untreated tumor-bearing fish. Our results support the conclusion that a brief early-life exposure to UVB radiation causes melanoma formation in this animal model. These data are consistent with an essential role for direct DNA damage, including cyclobutane dimers and (6-4) photoproducts, in the etiology of melanoma. PMID:20439744
Ultraviolet A does not induce melanomas in a Xiphophorus hybrid fish model.
Mitchell, David L; Fernandez, André A; Nairn, Rodney S; Garcia, Rachel; Paniker, Lakshmi; Trono, David; Thames, Howard D; Gimenez-Conti, Irma
2010-05-18
We examined the wavelength dependence of ultraviolet (UV) ra-diation (UVR)-induced melanoma in a Xiphophorus backcross hybrid model previously reported to be susceptible to melanoma induction by ultraviolet A (UVA) and visible light. Whereas ultraviolet B (UVB) irradiation of neonates yielded high frequencies of melanomas in pigmented fish, UVA irradiation resulted in melanoma frequencies that were not significantly different from unirradiated fish. Spontaneous and UV-induced melanoma frequencies correlated with the degree of pigmentation as expected from previous studies, and the histopathology phenotypes of the melanomas were not found in significantly different proportions in UV-treated and -untreated tumor-bearing fish. Our results support the conclusion that a brief early-life exposure to UVB radiation causes melanoma formation in this animal model. These data are consistent with an essential role for direct DNA damage, including cyclobutane dimers and (6-4) photoproducts, in the etiology of melanoma.
Adaptive hybrid likelihood model for visual tracking based on Gaussian particle filter
NASA Astrophysics Data System (ADS)
Wang, Yong; Tan, Yihua; Tian, Jinwen
2010-07-01
We present a new scheme based on multiple-cue integration for visual tracking within a Gaussian particle filter framework. The proposed method integrates the color, shape, and texture cues of an object to construct a hybrid likelihood model. During the measurement step, the likelihood model can be switched adaptively according to environmental changes, which improves the object representation to deal with the complex disturbances, such as appearance changes, partial occlusions, and significant clutter. Moreover, the confidence weights of the cues are adjusted online through the estimation using a particle filter, which ensures the tracking accuracy and reliability. Experiments are conducted on several real video sequences, and the results demonstrate that the proposed method can effectively track objects in complex scenarios. Compared with previous similar approaches through some quantitative and qualitative evaluations, the proposed method performs better in terms of tracking robustness and precision.
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)
Tang, Xian-Zhu; McDevitt, C. J.; Guo, Zehua; Berk, H. L.
2014-03-01
Inertial confinement fusion requires an imploded target in which a central hot spot is surrounded by a cold and dense pusher. The hot spot/pusher interface can take complicated shape in three dimensions due to hydrodynamic mix. It is also a transition region where the Knudsen and inverse Knudsen layer effect can significantly modify the fusion reactivity in comparison with the commonly used value evaluated with background Maxwellians. Here, we describe a hybrid model that couples the kinetic correction of fusion reactivity to global hydrodynamic implosion simulations. The key ingredient is a non-perturbative treatment of the tail ions in the interface region where the Gamow ion Knudsen number approaches or surpasses order unity. The accuracy of the coupling scheme is controlled by the precise criteria for matching the non-perturbative kinetic model to perturbative solutions in both configuration space and velocity space.
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.
A hybrid skull-stripping algorithm based on adaptive balloon snake models
NASA Astrophysics Data System (ADS)
Liu, Hung-Ting; Sheu, Tony W. H.; Chang, Herng-Hua
2013-02-01
Skull-stripping is one of the most important preprocessing steps in neuroimage analysis. We proposed a hybrid algorithm based on an adaptive balloon snake model to handle this challenging task. The proposed framework consists of two stages: first, the fuzzy possibilistic c-means (FPCM) is used for voxel clustering, which provides a labeled image for the snake contour initialization. In the second stage, the contour is initialized outside the brain surface based on the FPCM result and evolves under the guidance of the balloon snake model, which drives the contour with an adaptive inward normal force to capture the boundary of the brain. The similarity indices indicate that our method outperformed the BSE and BET methods in skull-stripping the MR image volumes in the IBSR data set. Experimental results show the effectiveness of this new scheme and potential applications in a wide variety of skull-stripping applications.
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.
PWR hybrid computer model for assessing the safety implications of control systems
Smith, O L; Renier, J P; Difilippo, F C; Clapp, N E; Sozer, A; Booth, R S; Craddick, W G; Morris, D G
1986-03-01
The ORNL study of safety-related aspects of nuclear power plant control systems consists of two interrelated tasks: (1) failure mode and effects analysis (FMEA) that identified single and multiple component failures that might lead to significant plant upsets and (2) computer models that used these failures as initial conditions and traced the dynamic impact on the control system and remainder of the plant. This report describes the simulation of Oconee Unit 1, the first plant analyzed. A first-principles, best-estimate model was developed and implemented on a hybrid computer consisting of AD-4 analog and PDP-10 digital machines. Controls were placed primarily on the analog to use its interactive capability to simulate operator action. 48 refs., 138 figs., 15 tabs.
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
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
Computational lymphatic node models in pediatric and adult hybrid phantoms for radiation dosimetry.
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
Exact Hybrid Particle/Population Simulation of Rule-Based Models of Biochemical Systems
Stover, Lori J.; Nair, Niketh S.; Faeder, James R.
2014-01-01
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
NASA Astrophysics Data System (ADS)
Matichard, Fabrice; Gaudiller, Luc
2006-12-01
The hybrid modal nodal (HMN) method, designed for multibody smart structure model reduction and feedback control development, is based on the independent modeling of structural and electromechanical behavior. Firstly, this approach permits reducing the model of substructures independently of the electromechanical behavior. This allows choosing the most adapted component mode synthesis (CMS) method and corresponding code for any application, something that is not permitted by classical multi-physics projection-based methods. Thus, the substructuring process used in this paper is based on super-elements directly adapted for multibody dynamics modeling. Secondly, the electromechanical behavior of distributed components is introduced into the structural modal model via a nodal formulation. Its independence of any projection guarantees accuracy and its formulation is valid whatever the multibody assembly and its modal shapes. The proposed application is composed of successive developments and experiments designed to validate the model reduction method, its implementation and its use for modal feedback control, i.e. a smart beam, actively controlled by piezoelectric ceramics. It is successively clamped to illustrate the electromechanical coupling reduction, articulated to introduce the rigid-body/flexible mode coupling reduction and, finally, bi-articulated in order to deal with the nonlinear problem.
Stochastic Time-lapse Seismic Inversion with a Hybrid Starting Model and Double-difference Data
NASA Astrophysics Data System (ADS)
Tao, Y.; Sen, M. K.; Zhang, R.; Spikes, K.
2012-12-01
We propose a robust stochastic time-lapse seismic inversion strategy with an application of monitoring a CO2 injection site. This workflow involves a baseline inversion using a hybrid starting model that combines a fractal prior and the low-frequency prior from well log data. This starting model extracts fractal statistics of the well data to provide an estimate of the null space. A second step of this workflow is to use a double-difference inversion scheme to focus on the local areas where time-lapse changes have occurred as a result of injecting CO2 into the reservoir. For this step, simulated data using the inverted prior from the baseline model and the difference between the baseline and repeat data are summed to produce the virtual repeat data. We use an error function that incorporates the model norms to regularize the inversion process. The seismic data are pre-processed using a local correlation based warping method to register different time-lapse datasets. The stochastic optimization method used here is very fast simulated annealing, where the updated model parameters are drawn from a temperature dependent Cauchy-like perturbation of current model parameters. Synthetic data show that double-difference inversion shows better result than a conventional two-pass approach. Inverted field data from Cranfield site shows time-lapse impedance changes that are consistent with CO2 injection effects.
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.
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.
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.
Hybrid Ontology for Semantic Information Retrieval Model Using Keyword Matching Indexing System
Uthayan, K. R.; Anandha Mala, G. S.
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. PMID:25922851
Engelmann, Julia C; Rahmann, Sven; Wolf, Matthias; Schultz, Jörg; Fritzilas, Epameinondas; Kneitz, Susanne; Dandekar, Thomas; Müller, Tobias
2009-01-01
DNA microarrays are a popular technique for the detection of microorganisms. Several approaches using specific oligomers targeting one or a few marker genes for each species have been proposed. Data analysis is usually limited to call a species present when its oligomer exceeds a certain intensity threshold. While this strategy works reasonably well for distantly related species, it does not work well for very closely related species: Cross-hybridization of nontarget DNA prevents a simple identification based on signal intensity. The majority of species of the same genus has a sequence similarity of over 90%. For biodiversity studies down to the species level, it is therefore important to increase the detection power of closely related species. We propose a simple, cost-effective and robust approach for biodiversity studies using DNA microarray technology and demonstrate it on scenedesmacean green algae. The internal transcribed spacer 2 (ITS2) rDNA sequence was chosen as marker because it is suitable to distinguish all eukaryotic species even though parts of it are virtually identical in closely related species. We show that by modelling hybridization behaviour with a matrix algebra approach, we are able to identify closely related species that cannot be distinguished with a threshold on signal intensity. Thus this proof-of-concept study shows that by adding a simple and robust data analysis step to the evaluation of DNA microarrays, species detection can be significantly improved for closely related species with a high sequence similarity.
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.
Jin, Zhongyuan; Liu, Baoan; Feng, Deyun; Chen, Chen; Li, Xiang; Hu, Yongbin; Peng, Jinwu; Liu, Yu; Du, Jing; Fu, Chunyan; Wen, Jifang
2008-08-01
The critical molecular mechanism in the development of the pulmonary fibrosis remains unknown, leaving diagnosed patients with a poor prognosis. To isolate the genes specifically up-regulated in pulmonary fibrosis, we established a rat silicosis model 360 d after treatment with crystalline silica suspension. Radiographs of chests showed that some scattered high-density shadows appeared in the lung field. Typical microscopic fibrosing silicotic nodules formed in the lung, alveolar epithelial cells and bronchial epithelial cells, particularly around the partial fibrosing silicotic nodules; some of them showed atypical hyperplasia that suggested a correlation between silicosis and lung cancer. Suppression subtractive hybridization analysis was performed to compare gene expression in lung tissue with silicosis and normal lung tissue. Reverse transcription-polymerase chain reaction showed that the expressions of seven novel cDNA sequences identified by suppression subtractive hybridization in lung tissue with silicosis differed from normal lung tissue. Bioinformatics analysis showed that 47 positive clones represented 35 genes containing two putative proteins and four predicted similar proteins. The analysis also showed that some screened genes in silicosis, such as prolyl 4-hydroxylases, actin-related protein-2/3 complex and acidic mammalian chitinase, have not been previously reported. These genes may provide new clues for investigating the molecular mechanisms in the development of pulmonary fibrosis. PMID:18685790
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 neutron stars with the Dyson-Schwinger quark model and various quark-gluon vertices
NASA Astrophysics Data System (ADS)
Chen, H.; Wei, J.-B.; Baldo, M.; Burgio, G. F.; Schulze, H.-J.
2015-05-01
We study cold dense quark matter and hybrid neutron stars with a Dyson-Schwinger quark model and various choices of the quark-gluon vertex. We obtain the equation of state of quark matter in beta equilibrium and investigate the hadron-quark phase transition in combination with a hadronic equation of state derived within the Brueckner-Hartree-Fock many-body theory. Comparing with the results for quark matter within the rainbow approximation, the Ball-Chiu (BC) Ansatz and the 1BC Ansatz for the quark-gluon vertex lead to a reduction of the effective interaction at finite chemical potential, qualitatively similar to the effect of our gluon propagator. We find that the phase transition and the equation of state of the quark or mixed phase and consequently the resulting hybrid star mass and radius depend mainly on a global reduction of the effective interaction due to effects of both the quark-gluon vertex and gluon propagator, but are not sensitive to details of the vertex Ansatz.
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. PMID:25922851
NASA Astrophysics Data System (ADS)
Zhao, Yingru; Chen, Jincan
A theoretical modeling approach is presented, which describes the behavior of a typical fuel cell-heat engine hybrid system in steady-state operating condition based on an existing solid oxide fuel cell model, to provide useful fundamental design characteristics as well as potential critical problems. The different sources of irreversible losses, such as the electrochemical reaction, electric resistances, finite-rate heat transfer between the fuel cell and the heat engine, and heat-leak from the fuel cell to the environment are specified and investigated. Energy and entropy analyses are used to indicate the multi-irreversible losses and to assess the work potentials of the hybrid system. Expressions for the power output and efficiency of the hybrid system are derived and the performance characteristics of the system are presented and discussed in detail. The effects of the design parameters and operating conditions on the system performance are studied numerically. It is found that there exist certain optimum criteria for some important parameters. The results obtained here may provide a theoretical basis for both the optimal design and operation of real fuel cell-heat engine hybrid systems. This new approach can be easily extended to other fuel cell hybrid systems to develop irreversible models suitable for the investigation and optimization of similar energy conversion settings and electrochemistry systems.
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 obtained using the ideal Ohm's law and Ohm's law including the Hall term. Our analysis emphasizes the role of the Hall term in Ohm's law in obtaining wave modes departing from ideal magnetohydrodynamics in the hybrid-Vlasov model.
Bellazzi, R; Guglielmann, R; Ironi, L; Patrini, C
2001-08-01
Models of the dynamics of complex metabolic systems offer potential benefits to the deep comprehension of the system under study as well as for the performance of certain tasks. Unfortunately, dynamic modeling of a great deal of metabolic systems may be problematic due to the incompleteness of the available knowledge about the underlying mechanisms and to the lack of an adequate observational data set. In theory, a valid alternative to classical structural modeling through ordinary differential equations could be represented by input-output approaches. But, in practice, such methods, which learn the nonlinear dynamics of the system from input-output data, fail when the experimental data set is poor either in size or in quality. Such a situation is not rare in the case of metabolic systems. This paper deals with a hybrid approach which aims at overcoming the problems addressed above. More specifically, it allows us to solve the identification problems of the intracellular thiamine kinetics in the intestine tissue. The method, which is half way between the structural and input-output approach, uses the outcomes of the simulation of a qualitative structural model to build a good initialization of a fuzzy system identifier. Such an initialization allows us to efficiently cope with both the incompleteness of knowledge and the inadequacy of the available data set, and to derive an input-output model of the intracellular thiamine kinetics in the intestine tissue. The comparison of the predictions of the intracellular thiamine kinetics obtained by the application of such a model with those obtained by traditional approaches, namely compartmental models, neural networks, and fuzzy systems, highlighted a better performance of our model. As the structural assumptions are relaxed, we obtained a model slightly less informative than a purely structural one but robust enough to be used as a simulator. The paper also discusses the interpretative potential offered by such a model
Aunai, Nicolas; Hesse, Michael; Kuznetsova, Maria; Black, Carrie; Evans, Rebekah; Zenitani, Seiji; Smets, Roch
2013-02-15
Magnetic reconnection occurring in collisionless environments is a multi-scale process involving both ion and electron kinetic processes. Because of their small mass, the electron scales are difficult to resolve in numerical and satellite data, it is therefore critical to know whether the overall evolution of the reconnection process is influenced by the kinetic nature of the electrons, or is unchanged when assuming a simpler, fluid, electron model. This paper investigates this issue in the general context of an asymmetric current sheet, where both the magnetic field amplitude and the density vary through the discontinuity. A comparison is made between fully kinetic and hybrid kinetic simulations of magnetic reconnection in coplanar and guide field systems. The models share the initial condition but differ in their electron modeling. It is found that the overall evolution of the system, including the reconnection rate, is very similar between both models. The best agreement is found in the guide field system, which confines particle better than the coplanar one, where the locality of the moments is violated by the electron bounce motion. It is also shown that, contrary to the common understanding, reconnection is much faster in the guide field system than in the coplanar one. Both models show this tendency, indicating that the phenomenon is driven by ion kinetic effects and not electron ones.
Design and implementation of a hybrid MPI-CUDA model for the Smith-Waterman algorithm.
Khaled, Heba; Faheem, Hossam El Deen Mostafa; El Gohary, Rania
2015-01-01
This paper provides a novel hybrid model for solving the multiple pair-wise sequence alignment problem combining message passing interface and CUDA, the parallel computing platform and programming model invented by NVIDIA. The proposed model targets homogeneous cluster nodes equipped with similar Graphical Processing Unit (GPU) cards. The model consists of the Master Node Dispatcher (MND) and the Worker GPU Nodes (WGN). The MND distributes the workload among the cluster working nodes and then aggregates the results. The WGN performs the multiple pair-wise sequence alignments using the Smith-Waterman algorithm. We also propose a modified implementation to the Smith-Waterman algorithm based on computing the alignment matrices row-wise. The experimental results demonstrate a considerable reduction in the running time by increasing the number of the working GPU nodes. The proposed model achieved a performance of about 12 Giga cell updates per second when we tested against the SWISS-PROT protein knowledge base running on four nodes. PMID:26510289
Design and implementation of a hybrid MPI-CUDA model for the Smith-Waterman algorithm.
Khaled, Heba; Faheem, Hossam El Deen Mostafa; El Gohary, Rania
2015-01-01
This paper provides a novel hybrid model for solving the multiple pair-wise sequence alignment problem combining message passing interface and CUDA, the parallel computing platform and programming model invented by NVIDIA. The proposed model targets homogeneous cluster nodes equipped with similar Graphical Processing Unit (GPU) cards. The model consists of the Master Node Dispatcher (MND) and the Worker GPU Nodes (WGN). The MND distributes the workload among the cluster working nodes and then aggregates the results. The WGN performs the multiple pair-wise sequence alignments using the Smith-Waterman algorithm. We also propose a modified implementation to the Smith-Waterman algorithm based on computing the alignment matrices row-wise. The experimental results demonstrate a considerable reduction in the running time by increasing the number of the working GPU nodes. The proposed model achieved a performance of about 12 Giga cell updates per second when we tested against the SWISS-PROT protein knowledge base running on four nodes.
Hybrid Modeling of Plasmas and Applications to Fusion and Space Physics.
NASA Astrophysics Data System (ADS)
Kazeminejad, Farzad
Since the early days of controlled fusion research, plasma physicists have encountered great challenges in obtaining solutions to the highly nonlinear equations which govern the behavior of fusion plasmas; with the growth of other applications of plasma physics (space plasmas, plasma accelerators, ... etc.) these problems have grown in importance. Obtaining reasonable solutions to the nonlinear equations is crucial to our understanding of the behavior of plasmas. With the advent of high speed computers, computer modeling of plasmas has moved into the front row of the tools used in research of their nonlinear plasma dynamics. There are roughly speaking two types of plasma models, particle models and fluid models. Particle models try to emulate nature by following the motion of a large number of charged particles in their self consistent electromagnetic fields. Fluid models on the other hand use macroscopic fluid equations to model the plasma. MHD models are typical of this type. Particle models in general require larger memory for the computer due to the massive amounts of data associated with the particles' kinematical variables. Particle models are generally limited to studying small regions of plasma for relatively short time intervals. Fluid models are better fit to handle large scales and long times; i.e., quite often the complete plasma involved in an experiment. The drawback of the fluid models however is that, they miss the physical phenomenon taking place at the microscale and these phenomenon can influence the properties of fluid; i.e., its resistivity, viscosity, heat transport, etc. One can attempt to put these effects in as phenomenological coefficients, but such approaches are always somewhat ad hoc. Another approach is to start with fluid models and incorporate more physics. Such models are referred to as hybrid models. In this thesis, two such models are discussed. They are then applied to two problems; the first is a simulation of the artificial
Spatiotemporal groundwater level modeling using hybrid artificial intelligence-meshless method
NASA Astrophysics Data System (ADS)
Nourani, Vahid; Mousavi, Shahram
2016-05-01
Uncertainties of the field parameters, noise of the observed data and unknown boundary conditions are the main factors involved in the groundwater level (GL) time series which limit the modeling and simulation of GL. This paper presents a hybrid artificial intelligence-meshless model for spatiotemporal GL modeling. In this way firstly time series of GL observed in different piezometers were de-noised using threshold-based wavelet method and the impact of de-noised and noisy data was compared in temporal GL modeling by artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS). In the second step, both ANN and ANFIS models were calibrated and verified using GL data of each piezometer, rainfall and runoff considering various input scenarios to predict the GL at one month ahead. In the final step, the simulated GLs in the second step of modeling were considered as interior conditions for the multiquadric radial basis function (RBF) based solve of governing partial differential equation of groundwater flow to estimate GL at any desired point within the plain where there is not any observation. In order to evaluate and compare the GL pattern at different time scales, the cross-wavelet coherence was also applied to GL time series of piezometers. The results showed that the threshold-based wavelet de-noising approach can enhance the performance of the modeling up to 13.4%. Also it was found that the accuracy of ANFIS-RBF model is more reliable than ANN-RBF model in both calibration and validation steps.
Effect of data quality on a hybrid Coulomb/STEP model for earthquake forecasting
NASA Astrophysics Data System (ADS)
Steacy, Sandy; Jimenez, Abigail; Gerstenberger, Matt; Christophersen, Annemarie
2014-05-01
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. Specifically, we consider slip models based on the NEIC location, the CMT solution, surface rupture, and published inversions and find significant variation in the relative performance of the models depending upon the input data.
Chatfield, M W H; Kozak, K H; Fitzpatrick, B M; Tucker, P K
2010-10-01
Hybrid zones have yielded considerable insight into many evolutionary processes, including speciation and the maintenance of species boundaries. Presented here are analyses from a hybrid zone that occurs among three salamanders -Plethodon jordani, Plethodon metcalfi and Plethodon teyahalee- from the southern Appalachian Mountains. Using a novel statistical approach for analysis of non-clinal, multispecies hybrid zones, we examined spatial patterns of variation at four markers: single-nucleotide polymorphisms (SNPs) located in the mtDNA ND2 gene and the nuclear DNA ILF3 gene, and the morphological markers of red cheek pigmentation and white flecks. Concordance of the ILF3 marker and both morphological markers across four transects is observed. In three of the four transects, however, the pattern of mtDNA is discordant from all other markers, with a higher representation of P. metcalfi mtDNA in the northern and lower elevation localities than is expected given the ILF3 marker and morphology. To explore whether climate plays a role in the position of the hybrid zone, we created ecological niche models for P. jordani and P. metcalfi. Modelling results suggest that hybrid zone position is not determined by steep gradients in climatic suitability for either species. Instead, the hybrid zone lies in a climatically homogenous region that is broadly suitable for both P. jordani and P. metcalfi. We discuss various selective (natural selection associated with climate) and behavioural processes (sex-biased dispersal, asymmetric reproductive isolation) that might explain the discordance in the extent to which mtDNA and nuclear DNA and colour-pattern traits have moved across this hybrid zone. PMID:20819165
Higher Order, Hybrid BEM/FEM Methods Applied to Antenna Modeling
NASA Technical Reports Server (NTRS)
Fink, P. W.; Wilton, D. R.; Dobbins, J. A.
2002-01-01
In this presentation, the authors address topics relevant to higher order modeling using hybrid BEM/FEM formulations. The first of these is the limitation on convergence rates imposed by geometric modeling errors in the analysis of scattering by a dielectric sphere. The second topic is the application of an Incomplete LU Threshold (ILUT) preconditioner to solve the linear system resulting from the BEM/FEM formulation. The final tOpic is the application of the higher order BEM/FEM formulation to antenna modeling problems. The authors have previously presented work on the benefits of higher order modeling. To achieve these benefits, special attention is required in the integration of singular and near-singular terms arising in the surface integral equation. Several methods for handling these terms have been presented. It is also well known that achieving he high rates of convergence afforded by higher order bases may als'o require the employment of higher order geometry models. A number of publications have described the use of quadratic elements to model curved surfaces. The authors have shown in an EFIE formulation, applied to scattering by a PEC .sphere, that quadratic order elements may be insufficient to prevent the domination of modeling errors. In fact, on a PEC sphere with radius r = 0.58 Lambda(sub 0), a quartic order geometry representation was required to obtain a convergence benefi.t from quadratic bases when compared to the convergence rate achieved with linear bases. Initial trials indicate that, for a dielectric sphere of the same radius, - requirements on the geometry model are not as severe as for the PEC sphere. The authors will present convergence results for higher order bases as a function of the geometry model order in the hybrid BEM/FEM formulation applied to dielectric spheres. It is well known that the system matrix resulting from the hybrid BEM/FEM formulation is ill -conditioned. For many real applications, a good preconditioner is required
Hybrid-Space Density Matrix Renormalization Group Study of the Two-Dimensional Hubbard Model
NASA Astrophysics Data System (ADS)
Ehlers, Georg; Noack, Reinhard M.
We investigate the ground state of the two-dimensional Hubbard model on a cylinder geometry at intermediate coupling and weak doping. We study properties such as the behavior of the ground-state energy, pair-field correlations, and the appearance of stripes. We find striped ground states generically, with the width of the stripes depending on the filling, the boundary conditions, and the circumference of the cylinder. Furthermore, we analyse the interplay between the different stripe configurations and the decay of the pairing correlations. Our analysis is based on a hybrid-space density matrix renormalization group (DMRG) approach, which uses a momentum-space representation in the transverse and a real-space representation in the longitudinal direction. Exploiting the transverse momentum quantum number makes significant speedup and memory savings compared to the real-space DMRG possible. In particular, we obtain computational costs that are independent of the cylinder width for fixed size of the truncated Hilbert space.
Zhao, Weizhao; Li, Xiping; Chen, Hairong; Manns, Fabrice
2012-01-01
Medical Imaging is a key training component in Biomedical Engineering programs. Medical imaging education is interdisciplinary training, involving physics, mathematics, chemistry, electrical engineering, computer engineering, and applications in biology and medicine. Seeking an efficient teaching method for instructors and an effective learning environment for students has long been a goal for medical imaging education. By the support of NSF grants, we developed the medical imaging teaching software (MITS) and associated dynamic assessment tracking system (DATS). The MITS/DATS system has been applied to junior and senior medical imaging classes through a hybrid teaching model. The results show that student's learning gain improved, particularly in concept understanding and simulation project completion. The results also indicate disparities in subjective perception between junior and senior classes. Three institutions are collaborating to expand the courseware system and plan to apply it to different class settings.
Zhao, Weizhao; Li, Xiping; Chen, Hairong; Manns, Fabrice
2012-01-01
Medical Imaging is a key training component in Biomedical Engineering programs. Medical imaging education is interdisciplinary training, involving physics, mathematics, chemistry, electrical engineering, computer engineering, and applications in biology and medicine. Seeking an efficient teaching method for instructors and an effective learning environment for students has long been a goal for medical imaging education. By the support of NSF grants, we developed the medical imaging teaching software (MITS) and associated dynamic assessment tracking system (DATS). The MITS/DATS system has been applied to junior and senior medical imaging classes through a hybrid teaching model. The results show that student's learning gain improved, particularly in concept understanding and simulation project completion. The results also indicate disparities in subjective perception between junior and senior classes. Three institutions are collaborating to expand the courseware system and plan to apply it to different class settings. PMID:23367069
VALENTINE, DANIEL T.
2015-01-01
This study assessed outcomes in stuttering intervention across three service delivery models: direct, hybrid, and telepractice for two 11-year old children who stutter. The goal of the study was to investigate whether short-term goals were maintained through the telepractice sessions. The Stuttering Severity Instrument, Fourth Edition (SSI-4) was administered to each child before and after each intervention period and weekly fluency samples (percentage of stuttered syllables in a monologue) were obtained in each of the 10-week intervention periods. In addition, the Communication Attitudes Test-Revised was used to assess the children’s attitudes toward speaking. Following the telepractice period, parents and children completed a questionnaire concerning the therapy experience via telepractice. Both children continued to improve fluency as measured by the weekly fluency samples. SSI-4 severity ratings improved for one child and remained consistent for the other. These outcomes appear to demonstrate that telepractice is viable for improving and maintaining fluency. PMID:25945229
Applications integration in a hybrid cloud computing environment: modelling and platform
NASA Astrophysics Data System (ADS)
Li, Qing; Wang, Ze-yuan; Li, Wei-hua; Li, Jun; Wang, Cheng; Du, Rui-yang
2013-08-01
With the development of application services providers and cloud computing, more and more small- and medium-sized business enterprises use software services and even infrastructure services provided by professional information service companies to replace all or part of their information systems (ISs). These information service companies provide applications, such as data storage, computing processes, document sharing and even management information system services as public resources to support the business process management of their customers. However, no cloud computing service vendor can satisfy the full functional IS requirements of an enterprise. As a result, enterprises often have to simultaneously use systems distributed in different clouds and their intra enterprise ISs. Thus, this article presents a framework to integrate applications deployed in public clouds and intra ISs. A run-time platform is developed and a cross-computing environment process modelling technique is also developed to improve the feasibility of ISs under hybrid cloud computing environments.
A Hybrid Model for Individual Identification Based on Keystroke Data in Japanese Free Text Typing
NASA Astrophysics Data System (ADS)
Samura, Toshiharu; Nishimura, Haruhiko
We have investigated several characteristics of keystroke dynamics in Japanese free text typing. We performed experiments on 189 subjects, representing three groups according to the number of letters they could type in five minutes. In this experiment, we extracted the feature indices from the keystroke timing for each alphabet single letter and for two-letter combinations composed of consonant and vowel pairs in Japanese text. Taking into account two identification methods using weighted Euclidean distance (WED) and Vector Disorder (VD), we proposed their hybrid model for individual identification based on keystroke data in Japanese free text typing. By evaluating the personal identification for the three groups, its high performance was confirmed in proportion to the typing level of the group.
Optimal control on hybrid ode systems with application to a tick disease model.
Ding, Wandi
2007-10-01
We are considering an optimal control problem for a type of hybrid system involving ordinary differential equations and a discrete time feature. One state variable has dynamics in only one season of the year and has a jump condition to obtain the initial condition for that corresponding season in the next year. The other state variable has continuous dynamics. Given a general objective functional, existence, necessary conditions and uniqueness for an optimal control are established. We apply our approach to a tick-transmitted disease model with age structure in which the tick dynamics changes seasonally while hosts have continuous dynamics. The goal is to maximize disease-free ticks and minimize infected ticks through an optimal control strategy of treatment with acaricide. Numerical examples are given to illustrate the results.
NASA Astrophysics Data System (ADS)
Oddo, Paolo; Storto, Andrea; Dobricic, Srdjan; Russo, Aniello; Lewis, Craig; Onken, Reiner; Coelho, Emanuel
2016-10-01
A hybrid variational-ensemble data assimilation scheme to estimate the vertical and horizontal parts of the background error covariance matrix for an ocean variational data assimilation system is presented and tested in a limited-area ocean model implemented in the western Mediterranean Sea. An extensive data set collected during the Recognized Environmental Picture Experiments conducted in June 2014 by the Centre for Maritime Research and Experimentation has been used for assimilation and validation. The hybrid scheme is used to both correct the systematic error introduced in the system from the external forcing (initialisation, lateral and surface open boundary conditions) and model parameterisation, and improve the representation of small-scale errors in the background error covariance matrix. An ensemble system is run offline for further use in the hybrid scheme, generated through perturbation of assimilated observations. Results of four different experiments have been compared. The reference experiment uses the classical stationary formulation of the background error covariance matrix and has no systematic error correction. The other three experiments account for, or not, systematic error correction and hybrid background error covariance matrix combining the static and the ensemble-derived errors of the day. Results show that the hybrid scheme when used in conjunction with the systematic error correction reduces the mean absolute error of temperature and salinity misfit by 55 and 42 % respectively, versus statistics arising from standard climatological covariances without systematic error correction.
Dynamic modeling of hybrid renewable energy systems for off-grid applications
NASA Astrophysics Data System (ADS)
Hasemeyer, Mark David
The volatile prices of fossil fuels and their contribution to global warming have caused many people to turn to renewable energy systems. Many developing communities are forced to use these systems as they are too far from electrical distribution. As a result, numerous software models have been developed to simulate hybrid renewable energy systems. However almost, if not all, implementations are static in design. A static design limits the ability of the model to account for changes over time. Dynamic modeling can be used to fill the gaps where other modeling techniques fall short. This modeling practice allows the user to account for the effects of technological and economic factors over time. These factors can include changes in energy demand, energy production, and income level. Dynamic modeling can be particularly useful for developing communities who are off-grid and developing at rapid rates. In this study, a dynamic model was used to evaluate a real world system. A non-governmental organization interested in improving their current infrastructure was selected. Five different scenarios were analyzed and compared in order to discover which factors the model is most sensitive to. In four of the scenarios, a new energy system was purchased in order to account for the opening of a restaurant that would be used as a source of local income generation. These scenarios were then compared to a base case in which a new system was not purchased, and the restaurant was not opened. Finally, the results were used to determine which variables had the greatest impact on the various outputs of the simulation.
Zou, Weizhong; Larson, Ronald G
2016-08-10
We present a hybrid model for polymeric glasses under deformation that combines a minimal model of segmental dynamics with a beads-and-springs model of a polymer, solved by Brownian dynamics (BD) simulations, whose relaxation is coupled to the segmental dynamics through the drag coefficient of the beads. This coarse-grained model allows simulations that are much faster than molecular dynamics and successfully capture the entire range of mechanical response including yielding, plastic flow, strain-hardening, and incomplete strain recovery. The beads-and-springs model improves upon the dumbbell model for glassy polymers proposed by Fielding et al. (Phys. Rev. Lett., 2012, 108, 048301) by capturing the small elastic recoil seen experimentally without the use of ad hoc adjustments of parameters required in the model of Fielding et al. With appropriate choice of parameters, predictions of creep, recovery, and segmental relaxation are found to be in good agreement with poly(methylmethacrylate) (PMMA) data of Lee et al. (Science, 2009, 323, 231-234). Our model shows dramatic differences in behavior of the segmental relaxation time between extensional creep and steady extension, and between extension and shear. The non-monotonic response of the segmental relaxation time to extensional creep and the small elastic recovery after removal of stress are shown to arise from sub-chains that are trapped between folds, and that become highly oriented and stretched at strains of order unity, connecting the behavior of glassy polymers under creep to that of dilute polymer solutions under fast extensional flows. We are also able to predict the effects of polymer pre-orientation in the parallel or orthogonal direction on the subsequent response to extensional deformation. PMID:27453365
Testing the hybrid-3D Hillslope Hydrological Model in a Real-World Controlled Environment
NASA Astrophysics Data System (ADS)
Hazenberg, P.; Broxton, P. D.; Gochis, D. J.; Niu, G. Y.; Pelletier, J. D.; Troch, P. A. A.; Zeng, X.
2015-12-01
Hillslopes play an important role for converting rainfall into runoff, and as such, influence theterrestrial dynamics of the Earth's climate system. Recently, we have developed a hybrid-3D (h3D) hillslope hydrological model that couples a 1D vertical soil column model with a lateral pseudo-2D saturated zone and overland flow model. The h3D model gives similar results as the CATchment HYdrological model (CATHY), which simulates the subsurface movement of water with the 3D Richards equation, though the runtime efficiency of the h3D model is about 2-3 orders of magnitude faster. In the current work, the ability of the h3D model to predict real-world hydrological dynamics is assessed using a number of recharge-drainage experiments within the Landscape Evolution Observatory (LEO) at the Biosphere 2 near Tucson, Arizona, USA. LEO offers accurate and high-resolution (both temporally and spatially) observations of the inputs, outputs and storage dynamics of several hillslopes. The level of detail of these observations is generally not possible with real-world hillslope studies. Therefore, LEO offers an optimal environment to test the h3D model. The h3D model captures the observed storage, baseflow, and overland flow dynamics of both a larger and a smaller hillslope. Furthermore, it simulates overland flow better than CATHY. The h3D model has difficulties correctly representing the height of the saturated zone close to the seepage face of the smaller hillslope, though. There is a gravel layer near this seepage face, and the numerical boundary condition of the h3D model is insufficient to capture the hydrological dynamics within this region. In addition, the h3D model is used to test the hypothesis that model parameters change through time due to the migration of soil particles during the recharge-drainage experiments. An in depth calibration of the h3D model parameters reveals that the best results are obtained by applying an event-based optimization procedure as compared
A hybrid oscillatory interference/continuous attractor network model of grid cell firing.
Bush, Daniel; Burgess, Neil
2014-04-01
Grid cells in the rodent medial entorhinal cortex exhibit remarkably regular spatial firing patterns that tessellate all environments visited by the animal. Two theoretical mechanisms that could generate this spatially periodic activity pattern have been proposed: oscillatory interference and continuous attractor dynamics. Although a variety of evidence has been cited in support of each, some aspects of the two mechanisms are complementary, suggesting that a combined model may best account for experimental data. The oscillatory interference model proposes that the grid pattern is formed from linear interference patterns or "periodic bands" in which velocity-controlled oscillators integrate self-motion to code displacement along preferred directions. However, it also allows the use of symmetric recurrent connectivity between grid cells to provide relative stability and continuous attractor dynamics. Here, we present simulations of this type of hybrid model, demonstrate that it generates intracellular membrane potential profiles that closely match those observed in vivo, addresses several criticisms aimed at pure oscillatory interference and continuous attractor models, and provides testable predictions for future empirical studies. PMID:24695724
Molecular modeling of porous carbons using the hybrid reverse Monte Carlo method.
Jain, Surendra K; Pellenq, Roland J-M; Pikunic, Jorge P; Gubbins, Keith E
2006-11-21
We apply a simulation protocol based on the reverse Monte Carlo (RMC) method, which incorporates an energy constraint, to model porous carbons. This method is called hybrid reverse Monte Carlo (HRMC), since it combines the features of the Monte Carlo and reverse Monte Carlo methods. The use of the energy constraint term helps alleviate the problem of the presence of unrealistic features (such as three- and four-membered carbon rings), reported in previous RMC studies of carbons, and also correctly describes the local environment of carbon atoms. The HRMC protocol is used to develop molecular models of saccharose-based porous carbons in which hydrogen atoms are taken into account explicitly in addition to the carbon atoms. We find that the model reproduces the experimental pair correlation function with good accuracy. The local structure differs from that obtained with a previous model (Pikunic, J.; Clinard, C.; Cohaut, N.; Gubbins, K. E.; Guet, J. M.; Pellenq, R. J.-M.; Rannou, I.; Rouzaud, J. N. Langmuir 2003, 19 (20), 8565). We study the local structure by calculating the nearest neighbor distribution, bond angle distribution, and ring statistics. PMID:17106983
Wireless sensors in complex networks: study and performance evaluation of a new hybrid model
NASA Astrophysics Data System (ADS)
Curia, Vincenzo; Santamaria, Amilcare Francesco; Sottile, Cesare; Voznak, Miroslav
2014-05-01
Many recent research efforts have confirmed that, given the natural evolution of telecommunication systems, they can be approached by a new modeling technique, not based yet on traditional approach of graphs theory. The branch of complex networking, although young, is able to introduce a new and strong way of networks modeling, nevertheless they are social, telecommunication or friendship networks. In this paper we propose a new modeling technique applied to Wireless Sensor Networks (WSNs). The modeling has the purpose of ensuring an improvement of the distributed communication, quantifying it in terms of clustering coefficient and average diameter of the entire network. The main idea consists in the introduction of hybrid Data Mules, able to enhance the whole connectivity of the entire network. The distribution degree of individual nodes in the network will follow a logarithmic trend, meaning that the most of the nodes are not necessarily adjacent but, for each pair of them, there exists a relatively short path that connects them. The effectiveness of the proposed idea has been validated thorough a deep campaign of simulations, proving also the power of complex and small-world networks.
A hybrid model for computing nonthermal ion distributions in a long mean-free-path plasma
NASA Astrophysics Data System (ADS)
Tang, Xianzhu; McDevitt, Chris; Guo, Zehua; Berk, Herb
2014-10-01
Non-thermal ions, especially the suprathermal ones, are known to make a dominant contribution to a number of important physics such as the fusion reactivity in controlled fusion, the ion heat flux, and in the case of a tokamak, the ion bootstrap current. Evaluating the deviation from a local Maxwellian distribution of these non-thermal ions can be a challenging task in the context of a global plasma fluid model that evolves the plasma density, flow, and temperature. Here we describe a hybrid model for coupling such constrained kinetic calculation to global plasma fluid models. The key ingredient is a non-perturbative treatment of the tail ions where the ion Knudsen number approaches or surpasses order unity. This can be sharply constrasted with the standard Chapman-Enskog approach which relies on a perturbative treatment that is frequently invalidated. The accuracy of our coupling scheme is controlled by the precise criteria for matching the non-perturbative kinetic model to perturbative solutions in both configuration space and velocity space. Although our specific application examples will be drawn from laboratory controlled fusion experiments, the general approach is applicable to space and astrophysical plasmas as well. Work supported by DOE.
A new hybrid kinetic electron model for full-f gyrokinetic simulations
NASA Astrophysics Data System (ADS)
Idomura, Y.
2016-05-01
A new hybrid kinetic electron model is developed for electrostatic full-f gyrokinetic simulations of the ion temperature gradient driven trapped electron mode (ITG-TEM) turbulence at the ion scale. In the model, a full kinetic electron model is applied to the full-f gyrokinetic equation, the multi-species linear Fokker-Planck collision operator, and an axisymmetric part of the gyrokinetic Poisson equation, while in a non-axisymmetric part of the gyrokinetic Poisson equation, turbulent fluctuations are determined only by kinetic trapped electrons responses. By using this approach, the so-called ωH mode is avoided with keeping important physics such as the ITG-TEM, the neoclassical transport, the ambipolar condition, and particle trapping and detrapping processes. The model enables full-f gyrokinetic simulations of ITG-TEM turbulence with a reasonable computational cost. Comparisons between flux driven ITG turbulence simulations with kinetic and adiabatic electrons are presented. Although the similar ion temperature gradients with nonlinear upshift from linear critical gradients are sustained in quasi-steady states, parallel flows and radial electric fields are qualitatively different with kinetic electrons.
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
Modeling and control of hybrid wind/photovoltaic/fuel cell distributed generation systems
NASA Astrophysics Data System (ADS)
Wang, Caisheng
Due to ever increasing energy consumption, rising public awareness of environmental protection, and steady progress in power deregulation, alternative (i.e., renewable and fuel cell based) distributed generation (DG) systems have attracted increased interest. Wind and photovoltaic (PV) power generation are two of the most promising renewable energy technologies. Fuel cell (FC) systems also show great potential in DG applications of the future due to their fast technology development and many merits they have, such as high efficiency, zero or low emission (of pollutant gases) and flexible modular structure. The modeling and control of a hybrid wind/PV/FC DG system is addressed in this dissertation. Different energy sources in the system are integrated through an AC bus. Dynamic models for the main system components, namely, wind energy conversion system (WECS), PV energy conversion system (PVECS), fuel cell, electrolyzer, power electronic interfacing circuits, battery, hydrogen storage tank, gas compressor and gas pressure regulator, are developed. Two types of fuel cells have been modeled in this dissertation: proton exchange membrane fuel cell (PEMFC) and solid oxide fuel cell (SOFC). Power control of a grid-connected FC system as well as load mitigation control of a stand-alone FC system are investigated. The pitch angle control for WECS, the maximum power point tracking (MPPT) control for PVECS, and the control for electrolyzer and power electronic devices, are also addressed in the dissertation. Based on the dynamic component models, a simulation model for the proposed hybrid energy system has been developed using MATLAB/Simulink. The overall power management strategy for coordinating the power flows among the different energy sources is presented in the dissertation. Simulation studies have been carried out to verify the system performance under different scenarios using a practical load profile and real weather data. The results show that the overall power
Hybrid approaches for multiple-species stochastic reaction–diffusion models
Spill, Fabian; Guerrero, Pilar; Alarcon, Tomas; Maini, Philip K.; Byrne, Helen
2015-10-15
Reaction–diffusion models are used to describe systems in fields as diverse as physics, chemistry, ecology and biology. The fundamental quantities in such models are individual entities such as atoms and molecules, bacteria, cells or animals, which move and/or react in a stochastic manner. If the number of entities is large, accounting for each individual is inefficient, and often partial differential equation (PDE) models are used in which the stochastic behaviour of individuals is replaced by a description of the averaged, or mean behaviour of the system. In some situations the number of individuals is large in certain regions and small in others. In such cases, a stochastic model may be inefficient in one region, and a PDE model inaccurate in another. To overcome this problem, we develop a scheme which couples a stochastic reaction–diffusion system in one part of the domain with its mean field analogue, i.e. a discretised PDE model, in the other part of the domain. The interface in between the two domains occupies exactly one lattice site and is chosen such that the mean field description is still accurate there. In this way errors due to the flux between the domains are small. Our scheme can account for multiple dynamic interfaces separating multiple stochastic and deterministic domains, and the coupling between the domains conserves the total number of particles. The method preserves stochastic features such as extinction not observable in the mean field description, and is significantly faster to simulate on a computer than the pure stochastic model. - Highlights: • A novel hybrid stochastic/deterministic reaction–diffusion simulation method is given. • Can massively speed up stochastic simulations while preserving stochastic effects. • Can handle multiple reacting species. • Can handle moving boundaries.
H2RM: A Hybrid Rough Set Reasoning Model for Prediction and Management of Diabetes Mellitus
Ali, Rahman; Hussain, Jamil; Siddiqi, Muhammad Hameed; Hussain, Maqbool; Lee, Sungyoung
2015-01-01
Diabetes is a chronic disease characterized by high blood glucose level that results either from a deficiency of insulin produced by the body, or the body’s resistance to the effects of insulin. Accurate and precise reasoning and prediction models greatly help physicians to improve diagnosis, prognosis and treatment procedures of different diseases. Though numerous models have been proposed to solve issues of diagnosis and management of diabetes, they have the following drawbacks: (1) restricted one type of diabetes; (2) lack understandability and explanatory power of the techniques and decision; (3) limited either to prediction purpose or management over the structured contents; and (4) lack competence for dimensionality and vagueness of patient’s data. To overcome these issues, this paper proposes a novel hybrid rough set reasoning model (H2RM) that resolves problems of inaccurate prediction and management of type-1 diabetes mellitus (T1DM) and type-2 diabetes mellitus (T2DM). For verification of the proposed model, experimental data from fifty patients, acquired from a local hospital in semi-structured format, is used. First, the data is transformed into structured format and then used for mining prediction rules. Rough set theory (RST) based techniques and algorithms are used to mine the prediction rules. During the online execution phase of the model, these rules are used to predict T1DM and T2DM for new patients. Furthermore, the proposed model assists physicians to manage diabetes using knowledge extracted from online diabetes guidelines. Correlation-based trend analysis techniques are used to manage diabetic observations. Experimental results demonstrate that the proposed model outperforms the existing methods with 95.9% average and balanced accuracies. PMID:26151207
Pandey, G.R.; Cayan, D.R.; Dettinger, M.D.; Georgakakos, K.P.
2000-01-01
A hybrid (physical-statistical) scheme is developed to resolve the finescale distribution of daily precipitation over complex terrain. The scheme generates precipitation by combining information from the upper-air conditions and from sparsely distributed station measurements; thus, it proceeds in two steps. First, an initial estimate of the precipitation is made using a simplified orographic precipitation model. It is a steady-state, multilayer, and two-dimensional model following the concepts of Rhea. The model is driven by the 2.5?? ?? 2.5?? gridded National Oceanic and Atmospheric Administration-National Centers for Environmental Prediction upper-air profiles, and its parameters are tuned using the observed precipitation structure of the region. Precipitation is generated assuming a forced lifting of the air parcels as they cross the mountain barrier following a straight trajectory. Second, the precipitation is adjusted using errors between derived precipitation and observations from nearby sites. The study area covers the northern half of California, including coastal mountains, central valley, and the Sierra Nevada. The model is run for a 5-km rendition of terrain for days of January-March over the period of 1988-95. A jackknife analysis demonstrates the validity of the approach. The spatial and temporal distributions of the simulated precipitation field agree well with the observed precipitation. Further, a mapping of model performance indices (correlation coefficients, model bias, root-mean-square error, and threat scores) from an array of stations from the region indicates that the model performs satisfactorily in resolving daily precipitation at 5-km resolution.
H2RM: A Hybrid Rough Set Reasoning Model for Prediction and Management of Diabetes Mellitus.
Ali, Rahman; Hussain, Jamil; Siddiqi, Muhammad Hameed; Hussain, Maqbool; Lee, Sungyoung
2015-07-03
Diabetes is a chronic disease characterized by high blood glucose level that results either from a deficiency of insulin produced by the body, or the body's resistance to the effects of insulin. Accurate and precise reasoning and prediction models greatly help physicians to improve diagnosis, prognosis and treatment procedures of different diseases. Though numerous models have been proposed to solve issues of diagnosis and management of diabetes, they have the following drawbacks: (1) restricted one type of diabetes; (2) lack understandability and explanatory power of the techniques and decision; (3) limited either to prediction purpose or management over the structured contents; and (4) lack competence for dimensionality and vagueness of patient's data. To overc