A hybrid receptor model is a specified mathematical procedure which uses not only the ambient species concentration measurements that form the input data for a pure receptor model, but in addition source emission rates or atmospheric dispersion or transformation information chara...
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
Models for asymmetric hybrid brane
NASA Astrophysics Data System (ADS)
Bazeia, D.; Marques, M. A.; Menezes, R.
2015-10-01
We deal with relativistic models described by a single real scalar field, searching for topological structures that behave asymmetrically, connecting minima with a distinct profile. We use such features to build a new braneworld scenario, in which the source scalar field contributes to generate asymmetric hybrid brane.
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.
Photocarcinogenesis in Xiphophorus hybrid models.
Mitchell, David L; Nairn, Rodney S
2006-01-01
The poeciliid fish genus Xiphophorus provides important models for investigating the etiology and genetics of sunlight-induced melanoma. Interspecific hybrids generated among platyfish and swordtails have been used as genetic tumor models, particularly for cutaneous malignant melanoma (CMM), for more than 6 decades. Oncogene and tumor suppressor gene involvement in a variety of spontaneous and carcinogen-induced tumors has been and continues to be extensively studied. Select hybrids develop melanoma spontaneously or after acute or chronic exposure to ultraviolet radiation. Many scientists believe that the etiology of CMM and particularly its initiation is different from other types of sunlight-induced skin cancers, and may involve free radical chemistry rather than the direct absorption of UVB by DNA. Xiphophorus offers a unique platform to scrutinize this question and determine the types of DNA damage that are involved, the solar wavelength ranges that are important, and the role of DNA repair genes in early tumorigenesis. The diverse photochemical and photobiological responses observed in the different Xiphophorus species and interspecies hybrids suggest that heritable traits governing DNA damage induction and repair may be involved in the susceptibility of Xiphophorus hybrids to melanomagenesis. PMID:18377212
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.
Hybrid model for solidification and convection
NASA Technical Reports Server (NTRS)
Oldenburg, Curtis M.; Spera, Frank J.
1992-01-01
A hybrid model for continuum phase-change problems is presented. The hybrid model accounts for flow in regions of concentrated mush, dilute mush, and single-phase liquid. Scale analysis shows that, in dilute mush, the Blake-Kozeny-Carman relation may lead to inaccuracy in the continuum formulation for certain values of the Rayleigh and Darcy numbers. The hybrid model uses arctangent switching functions to switch on the Darcy flow and variable viscosity terms depending on the local value of the fraction solid. Two-dimensional example calculations suggest that the hybrid model more accurately accounts for transport in the dilute mush region.
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…
Hybrid rocket engine, theoretical model and experiment
NASA Astrophysics Data System (ADS)
Chelaru, Teodor-Viorel; Mingireanu, Florin
2011-06-01
The purpose of this paper is to build a theoretical model for the hybrid rocket engine/motor and to validate it using experimental results. The work approaches the main problems of the hybrid motor: the scalability, the stability/controllability of the operating parameters and the increasing of the solid fuel regression rate. At first, we focus on theoretical models for hybrid rocket motor and compare the results with already available experimental data from various research groups. A primary computation model is presented together with results from a numerical algorithm based on a computational model. We present theoretical predictions for several commercial hybrid rocket motors, having different scales and compare them with experimental measurements of those hybrid rocket motors. Next the paper focuses on tribrid rocket motor concept, which by supplementary liquid fuel injection can improve the thrust controllability. A complementary computation model is also presented to estimate regression rate increase of solid fuel doped with oxidizer. Finally, the stability of the hybrid rocket motor is investigated using Liapunov theory. Stability coefficients obtained are dependent on burning parameters while the stability and command matrixes are identified. The paper presents thoroughly the input data of the model, which ensures the reproducibility of the numerical results by independent researchers.
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
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.
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.
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.
Hybrid Concurrent Constraint Simulation Models of Several Systems
NASA Technical Reports Server (NTRS)
Sweet, Adam
2003-01-01
This distribution contains several simulation models created for the hybrid simulation language, Hybrid Concurrent Constraint (HCC). An HCC model contains the information specified in the widely-accepted academic definition of a hybrid system: this includes expressions for the modes of the systems to be simulated and the differential equations that apply in each mode. These expressions are written in the HCC syntax. The models included here were created by either applying basic physical laws or implementing equations listed in previously published papers.
Gyrofluid-Gyrokinetic Hybrid Turbulence Model
NASA Astrophysics Data System (ADS)
Dorland, William; Mandell, Noah
2015-11-01
Gyrofluid models of tokamak turbulence are efficient compared to gyrokinetic models, in three senses. First, it is typically easier to develop one's intuition from fluid equations than kinetic equations. Second, because gyrofluid equations are only three-dimensional (instead of 5D or 6D), simulations with gyrofluid models require less memory than kinetic simulations and can therefore more easily fit on highly-optimized computing hardware, such as graphics processors. The third advantage is a result of the first two: one can develop and test ideas quickly with gyrofluid models. The disadvantage of gyrofluid models is their potential lack of physics fidelity. In this poster, we present our attempt to take full advantage of gyrofluid models, without sacrificing physics fidelity. Our approach is encapsulated in the Gryf-X code, which is an implementation of hybrid gyrofluid/gyrokinetic equations. The key improvements that we have brought to bear are: an improved understanding of the cascade of free energy simultaneously in k⊥ and v⊥ an improved model of zonal flow physics; and an implementation of the equations on modern heterogeneous computing platforms, both as a standalone simulation tool and as a component of TRINITY (a transport modeling code for tokamaks).
Hybrid Modeling Improves Health and Performance Monitoring
NASA Technical Reports Server (NTRS)
2007-01-01
Scientific Monitoring Inc. was awarded a Phase I Small Business Innovation Research (SBIR) project by NASA's Dryden Flight Research Center to create a new, simplified health-monitoring approach for flight vehicles and flight equipment. The project developed a hybrid physical model concept that provided a structured approach to simplifying complex design models for use in health monitoring, allowing the output or performance of the equipment to be compared to what the design models predicted, so that deterioration or impending failure could be detected before there would be an impact on the equipment's operational capability. Based on the original modeling technology, Scientific Monitoring released I-Trend, a commercial health- and performance-monitoring software product named for its intelligent trending, diagnostics, and prognostics capabilities, as part of the company's complete ICEMS (Intelligent Condition-based Equipment Management System) suite of monitoring and advanced alerting software. I-Trend uses the hybrid physical model to better characterize the nature of health or performance alarms that result in "no fault found" false alarms. Additionally, the use of physical principles helps I-Trend identify problems sooner. I-Trend technology is currently in use in several commercial aviation programs, and the U.S. Air Force recently tapped Scientific Monitoring to develop next-generation engine health-management software for monitoring its fleet of jet engines. Scientific Monitoring has continued the original NASA work, this time under a Phase III SBIR contract with a joint NASA-Pratt & Whitney aviation security program on propulsion-controlled aircraft under missile-damaged aircraft conditions.
Hybrid adaptive control of a dragonfly model
NASA Astrophysics Data System (ADS)
Couceiro, Micael S.; Ferreira, Nuno M. F.; Machado, J. A. Tenreiro
2012-02-01
Dragonflies show unique and superior flight performances than most of other insect species and birds. They are equipped with two pairs of independently controlled wings granting an unmatchable flying performance and robustness. In this paper, it is presented an adaptive scheme controlling a nonlinear model inspired in a dragonfly-like robot. It is proposed a hybrid adaptive ( HA) law for adjusting the parameters analyzing the tracking error. At the current stage of the project it is considered essential the development of computational simulation models based in the dynamics to test whether strategies or algorithms of control, parts of the system (such as different wing configurations, tail) as well as the complete system. The performance analysis proves the superiority of the HA law over the direct adaptive ( DA) method in terms of faster and improved tracking and parameter convergence.
A Hybrid Teaching and Learning Model
NASA Astrophysics Data System (ADS)
Juhary, Jowati Binti
This paper aims at analysing the needs for a specific teaching and learning model for the National Defence University of Malaysia (NDUM). The main argument is that whether there are differences between teaching and learning for academic component versus military component at the university. It is further argued that in order to achieve excellence, there should be one teaching and learning culture. Data were collected through interviews with military cadets. It is found that there are variations of teaching and learning strategies for academic courses, in comparison to a dominant teaching and learning style for military courses. Thus, in the interest of delivering quality education and training for students at the university, the paper argues that possibly a hybrid model for teaching and learning is fundamental in order to generate a one culture of academic and military excellence for the NDUM.
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.
Stochastic hybrid modeling of intracellular calcium dynamics
NASA Astrophysics Data System (ADS)
Choi, TaiJung; Maurya, Mano Ram; Tartakovsky, Daniel M.; Subramaniam, Shankar
2010-10-01
Deterministic models of biochemical processes at the subcellular level might become inadequate when a cascade of chemical reactions is induced by a few molecules. Inherent randomness of such phenomena calls for the use of stochastic simulations. However, being computationally intensive, such simulations become infeasible for large and complex reaction networks. To improve their computational efficiency in handling these networks, we present a hybrid approach, in which slow reactions and fluxes are handled through exact stochastic simulation and their fast counterparts are treated partially deterministically through chemical Langevin equation. The classification of reactions as fast or slow is accompanied by the assumption that in the time-scale of fast reactions, slow reactions do not occur and hence do not affect the probability of the state. Our new approach also handles reactions with complex rate expressions such as Michaelis-Menten kinetics. Fluxes which cannot be modeled explicitly through reactions, such as flux of Ca2+ from endoplasmic reticulum to the cytosol through inositol 1,4,5-trisphosphate receptor channels, are handled deterministically. The proposed hybrid algorithm is used to model the regulation of the dynamics of cytosolic calcium ions in mouse macrophage RAW 264.7 cells. At relatively large number of molecules, the response characteristics obtained with the stochastic and deterministic simulations coincide, which validates our approach in the limit of large numbers. At low doses, the response characteristics of some key chemical species, such as levels of cytosolic calcium, predicted with stochastic simulations, differ quantitatively from their deterministic counterparts. These observations are ubiquitous throughout dose response, sensitivity, and gene-knockdown response analyses. While the relative differences between the peak-heights of the cytosolic [Ca2+] time-courses obtained from stochastic (mean of 16 realizations) and deterministic
Mathematical modelling of the anaerobic hybrid reactor.
Soroa, S; Gomez, J; Ayesa, E; Garcia-Heras, J L
2006-01-01
This paper presents a new mathematical model for the anaerobic hybrid reactor (AHR) (a UASB reactor and an anaerobic filter in series) and its experimental calibration and verification. The model includes a biochemical part and a mass transport one, which considers the AHR as two contact reactors in series. The anaerobic process transformations are described by the model developed by Siegrist et al. The fraction (F) of solids in the clarification zone of the UASB reactor that leaves this first reactor is the key physical parameter to be estimated. The main parameters of the model were calibrated using experimental results from a bench-scale AHR fed with real slaughterhouse wastewater. The fraction of inert particulate COD in the influent and the factor F were estimated by a trial and error procedure comparing experimental and simulated results of the mass of solids in the lower tank and the VSS concentration in the AHR effluent. A good fit was obtained. The final verification was carried out by comparing a set of experiments with simulated data. The model's capability to predict the process performance was thus proved. PMID:16939085
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
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
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
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.
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.
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.
A hybrid model of cell cycle in mammals.
Behaegel, Jonathan; Comet, Jean-Paul; Bernot, Gilles; Cornillon, Emilien; Delaunay, Franck
2016-02-01
Time plays an essential role in many biological systems, especially in cell cycle. Many models of biological systems rely on differential equations, but parameter identification is an obstacle to use differential frameworks. In this paper, we present a new hybrid modeling framework that extends René Thomas' discrete modeling. The core idea is to associate with each qualitative state "celerities" allowing us to compute the time spent in each state. This hybrid framework is illustrated by building a 5-variable model of the mammalian cell cycle. Its parameters are determined by applying formal methods on the underlying discrete model and by constraining parameters using timing observations on the cell cycle. This first hybrid model presents the most important known behaviors of the cell cycle, including quiescent phase and endoreplication. PMID:26708052
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
2015-10-01
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
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 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.
Conceiving a hybrid model of a weighting device
NASA Astrophysics Data System (ADS)
Oanta, Emil M.; Panait, Cornel; Lazaroiu, Gheorghe; Raicu, Alexandra; Axinte, Tiberiu; Dascalescu, Anca-Elena
2015-02-01
Research and design engineers usually use three sources of information: analytic models, numerical models and experimental studies. Analytic and numerical models are theoretical models which must be calibrated and verified regarding the accuracy of their results using the data acquired from experimental studies. If these models are deeply integrated from the beginning, the overview result is a hybrid model. From this standpoint, the paper presents the underlying concepts and studies employed to create a hybrid model of a weighting device. The paper presents the analytic background of the problem to be solved, the numerical model and the dimensioning of the experimental device. The study is still in progress, the following stages being the manufacturing of the device and calibration of the weighting platform.
Incorporating RTI in a Hybrid Model of Reading Disability.
Spencer, Mercedes; Wagner, Richard K; Schatschneider, Christopher; Quinn, Jamie; Lopez, Danielle; Petscher, Yaacov
2014-08-01
The present study seeks to evaluate a hybrid model of identification that incorporates response-to-intervention (RTI) as a one of the key symptoms of reading disability. The one-year stability of alternative operational definitions of reading disability was examined in a large scale sample of students who were followed longitudinally from first to second grade. The results confirmed previous findings of limited stability for single-criterion based operational definitions of reading disability. However, substantially greater stability was obtained for a hybrid model of reading disability that incorporates RTI with other common symptoms of reading disability. PMID:25422531
Modeling of hybrid vehicle fuel economy and fuel engine efficiency
NASA Astrophysics Data System (ADS)
Wu, Wei
"Near-CV" (i.e., near-conventional vehicle) hybrid vehicles, with an internal combustion engine, and a supplementary storage with low-weight, low-energy but high-power capacity, are analyzed. This design avoids the shortcoming of the "near-EV" and the "dual-mode" hybrid vehicles that need a large energy storage system (in terms of energy capacity and weight). The small storage is used to optimize engine energy management and can provide power when needed. The energy advantage of the "near-CV" design is to reduce reliance on the engine at low power, to enable regenerative braking, and to provide good performance with a small engine. The fuel consumption of internal combustion engines, which might be applied to hybrid vehicles, is analyzed by building simple analytical models that reflect the engines' energy loss characteristics. Both diesel and gasoline engines are modeled. The simple analytical models describe engine fuel consumption at any speed and load point by describing the engine's indicated efficiency and friction. The engine's indicated efficiency and heat loss are described in terms of several easy-to-obtain engine parameters, e.g., compression ratio, displacement, bore and stroke. Engine friction is described in terms of parameters obtained by fitting available fuel measurements on several diesel and spark-ignition engines. The engine models developed are shown to conform closely to experimental fuel consumption and motored friction data. A model of the energy use of "near-CV" hybrid vehicles with different storage mechanism is created, based on simple algebraic description of the components. With powertrain downsizing and hybridization, a "near-CV" hybrid vehicle can obtain a factor of approximately two in overall fuel efficiency (mpg) improvement, without considering reductions in the vehicle load.
Decompactifications and massless D-branes in hybrid models
NASA Astrophysics Data System (ADS)
Aspinwall, Paul S.; Ronen Plesser, M.
2010-07-01
A method of determining the mass spectrum of BPS D-branes in any phase limit of a gauged linear sigma model is introduced. A ring associated to monodromy is defined and one considers K-theory to be a module over this ring. A simple but interesting class of hybrid models with Landau-Ginzburg fibres over {mathbb{P}^n} are analyzed using special Kähler geometry and D-brane probes. In some cases the hybrid limit is an infinite distance in moduli space and corresponds to a decompactification. In other cases the hybrid limit isat a finite distance and acquires massless D-branes. An example studied appears to correspond to a novel theory of supergravity with an SU(2) gauge symmetry where the gauge and gravitational couplings are necessarily tied to each other.
Fatigue reliability based on residual strength model with hybrid uncertain parameters
NASA Astrophysics Data System (ADS)
Wang, Jun; Qiu, Zhi-Ping
2012-02-01
The aim of this paper is to evaluate the fatigue reliability with hybrid uncertain parameters based on a residual strength model. By solving the non-probabilistic set-based reliability problem and analyzing the reliability with randomness, the fatigue reliability with hybrid parameters can be obtained. The presented hybrid model can adequately consider all uncertainties affecting the fatigue reliability with hybrid uncertain parameters. A comparison among the presented hybrid model, non-probabilistic set-theoretic model and the conventional random model is made through two typical numerical examples. The results show that the presented hybrid model, which can ensure structural security, is effective and practical.
Battery thermal models for hybrid vehicle simulations
NASA Astrophysics Data System (ADS)
Pesaran, Ahmad A.
This paper summarizes battery thermal modeling capabilities for: (1) an advanced vehicle simulator (ADVISOR); and (2) battery module and pack thermal design. The National Renewable Energy Laboratory's (NREL's) ADVISOR is developed in the Matlab/Simulink environment. There are several battery models in ADVISOR for various chemistry types. Each one of these models requires a thermal model to predict the temperature change that could affect battery performance parameters, such as resistance, capacity and state of charges. A lumped capacitance battery thermal model in the Matlab/Simulink environment was developed that included the ADVISOR battery performance models. For thermal evaluation and design of battery modules and packs, NREL has been using various computer aided engineering tools including commercial finite element analysis software. This paper will discuss the thermal ADVISOR battery model and its results, along with the results of finite element modeling that were presented at the workshop on "Development of Advanced Battery Engineering Models" in August 2001.
Hybrid Scheduling Model for Independent Grid Tasks
Shanthini, J.; Kalaikumaran, T.; Karthik, S.
2015-01-01
Grid computing facilitates the resource sharing through the administrative domains which are geographically distributed. Scheduling in a distributed heterogeneous environment is intrinsically very hard because of the heterogeneous nature of resource collection. Makespan and tardiness are two different measures of scheduling, and many of the previous researches concentrated much on reduction of makespan, which measures the machine utilization. In this paper, we propose a hybrid scheduling algorithm for scheduling independent grid tasks with the objective of reducing total weighted tardiness of grid tasks. Tardiness is to measure the due date performance, which has a direct impact on cost for executing the jobs. In this paper we propose BG_ATC algorithm which is a combination of best gap (BG) search and Apparent Tardiness Cost (ATC) indexing algorithm. Furthermore, we implemented these two algorithms in two different phases of the scheduling process. In addition to that, the comparison was made on results with various benchmark algorithms and the experimental results show that our algorithm outperforms the benchmark algorithms. PMID:26543897
Hohlraum Modeling of Hybrid Shock Ignition Target
NASA Astrophysics Data System (ADS)
Dodd, E. S.; Baumgaertel, J. A.; Loomis, E. N.
2014-10-01
Hybrid Shock Ignition (HSI) combines a hohlraum driven capsule with a directly driven shock for heating. Unlike standard Shock Ignition, the capsule is imploded with X-rays from a laser driven hohlraum to compress the fuel, which is too cold to ignite. However, as in Shock Ignition, the compressed fuel is subsequently heated to ignition temperatures with a directly-driven shock. The use of indirect and direct drive in the same target necessitates complex beam geometry, and thus HSI is being pursued with spherical hohlraums. More importantly for the NIF, the beam repointing required for polar direct drive will not be needed for the implosion phase with this target. Spherical hohlraums have been fielded previously at the OMEGA laser as a part of the Tetrahedral Hohlraum Campaign. They were originally proposed as an alternative to cylindrical hohlraums to achieve highly symmetric radiation drive. The new HSI hohlraums will require six laser entrance holes in hexahedral symmetry to accommodate all beams. This presentation will show radiation-hydrodynamic calculations of the current hexahedral OMEGA hohlraum design, as well as benchmark calculations of the old tetrahedral targets. Supported under the US DOE by the Los Alamos National Security, LLC under Contract DE-AC52-06NA25396. LA-UR-14-24945.
Attitudes and Satisfaction with a Hybrid Model of Counseling Supervision
ERIC Educational Resources Information Center
Conn, Steven R.; Roberts, Richard L.; Powell, Barbara M.
2009-01-01
The authors investigated the relationship between type of group supervision (hybrid model vs. face-to-face) and attitudes toward technology, toward use of technology in professional practice, and toward quality of supervision among a sample of school counseling interns. Participants (N = 76) experienced one of two types of internship supervision:…
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.
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…
NASA Astrophysics Data System (ADS)
Li, Dandan; Liu, Fugui; Li, Yongjian; Zhao, Zhigang; Zhang, Changgeng; Yang, Qingxin
2014-05-01
A 2-D vector hybrid hysteresis model for a soft magnetic composite (SMC) material is established, which is combined with classical Preisach model and Stoner-Wohlfarth (S-W) model. The rotational magnetic properties of SMC materials were studied using the vector model, and the computed results were compared with the experimental measurement. It is shown that the vector hybrid model can effectively simulate the rotational magnetic properties under low magnetization fields.
Hierarchical hybrid modelling and control of an unmanned helicopter
NASA Astrophysics Data System (ADS)
Karimoddini, Ali; Lin, Hai; Chen, Ben M.; Lee, Tong H.
2014-09-01
In this paper, we propose a hybrid modelling and control design scheme for an unmanned helicopter. This control structure has a hierarchical form with three layers: the regulation layer, the motion planning layer, and the supervision layer. For each layer, a separate hybrid controller has been developed. Then, a composition operator is adopted to capture the interactions between these layers. The resulting closed-loop system can flexibly command the helicopter to perform different tasks, autonomously. The designed controller is embedded in the avionic system of an unmanned helicopter, and actual flight test results are presented to demonstrate the effectiveness of the proposed control structure.
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 models of cell and tissue dynamics in tumor growth.
Kim, Yangjin; Othmer, Hans G
2015-12-01
Hybrid models of tumor growth, in which some regions are described at the cell level and others at the continuum level, provide a flexible description that allows alterations of cell-level properties and detailed descriptions of the interaction with the tumor environment, yet retain the computational advantages of continuum models where appropriate. We review aspects of the general approach and discuss applications to breast cancer and glioblastoma. PMID:26775860
Hierarchical models and iterative optimization of hybrid systems
NASA Astrophysics Data System (ADS)
Rasina, Irina V.; Baturina, Olga V.; Nasatueva, Soelma N.
2016-06-01
A class of hybrid control systems on the base of two-level discrete-continuous model is considered. The concept of this model was proposed and developed in preceding works as a concretization of the general multi-step system with related optimality conditions. A new iterative optimization procedure for such systems is developed on the base of localization of the global optimality conditions via contraction the control set.
Precompound decay in heavy ion reactions via the hybrid model
Blann, M.
1987-04-01
The hybrid model for precompound decay is applied to the calculation of neutron spectra following the /sup 20/Ne and /sup 12/C bombardment of /sup 165/Ho at 220, 292, (/sup 20/Ne), and 300 (/sup 12/C) MeV. Results are compared with experimentally deduced angle integrated spectra and with results of the Boltzmann master equation. Both models give excellent agreement with experimentally deduced spectra.
Bridging paradigms: hybrid mechanistic-discriminative predictive models.
Doyle, Orla M; Tsaneva-Atansaova, Krasimira; Harte, James; Tiffin, Paul A; Tino, Peter; Díaz-Zuccarini, Vanessa
2013-03-01
Many disease processes are extremely complex and characterized by multiple stochastic processes interacting simultaneously. Current analytical approaches have included mechanistic models and machine learning (ML), which are often treated as orthogonal viewpoints. However, to facilitate truly personalized medicine, new perspectives may be required. This paper reviews the use of both mechanistic models and ML in healthcare as well as emerging hybrid methods, which are an exciting and promising approach for biologically based, yet data-driven advanced intelligent systems. PMID:23392334
Comparison of linear and nonlinear subgrid scale model for hybrid RANS/LES modelling
NASA Astrophysics Data System (ADS)
Straka, Petr
2016-06-01
The contribution deals with application of the hybrid RANS/LES model for calculation of flow around the circular cylinder. Used hybrid RANS/LES model is based on transport equation for the kinetic energy which is shared in both RANS and LES modes. The linear and the nonlinear closure formulas are described in the paper. Numerical results are compared with the experimental data. Results show that the nonlinear model predicts development of the wake behind the cylinder better than the linear model.
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, Y.; Abdel-Khalik, H. S.; Jessee, M. A.; Mertyurek, U.
2013-07-01
While the accuracy of assembly calculations has considerably 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 manuscript extends those works to coupled code systems as currently employed in assembly calculations. 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. (authors)
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
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.
Modeling river plume dynamics with the HYbrid Coordinate Ocean Model
NASA Astrophysics Data System (ADS)
Schiller, Rafael V.; Kourafalou, Vassiliki H.
The dynamics of large-scale river plumes are investigated in idealized numerical experiments using the HYbrid Coordinate Ocean Model (HYCOM). The focus of this study is to address how the development and structure of a buoyant plume are affected by the outflow properties, as impacted by processes within the estuary and at the point of discharge to the coastal basin. Changes in the outflow properties involved vertical and horizontal redistribution of the river inflow and enhanced vertical mixing inside an idealized estuary. The development of the buoyant plume was evaluated in a rectangular, f-plane basin with flat and sloping bottom conditions and in the absence of other external forcing. The general behavior of a mid-latitude river plume was reproduced, with the development of a surface anticyclonic bulge off the estuary mouth and a surface along-shore coastal current which flows in the direction of Kelvin wave propagation ("downstream"); the momentum balance was predominantly geostrophic. Conditions within the estuary and the outflow properties at the river mouth (where observed profiles may be available) greatly impacted the fate of riverine waters. In flat bottom conditions, larger mixing at the freshwater source enhanced the estuarine gravitational circulation, promoting larger upward entrainment and stronger outflow velocities. Although the overall geostrophic balance was maintained, estuarine mixing led to an asymmetry of the currents reaching the river mouth and to a sharp anticyclonic veering within the estuary, resulting in reduced upstream flow and enhanced downstream coastal current. These patterns were altered when the plumes evolved in the presence of a bottom slope. The anticyclonic veering of the buoyant outflow was suppressed, the offshore intrusion decreased and the recirculating bulge was displaced upstream. The sloping bottom impacts were accompanied by enhanced transport and increased downstream extent of the coastal current in most cases. No
Hybrid Speaker Recognition Using Universal Acoustic Model
NASA Astrophysics Data System (ADS)
Nishimura, Jun; Kuroda, Tadahiro
We propose a novel speaker recognition approach using a speaker-independent universal acoustic model (UAM) for sensornet applications. In sensornet applications such as “Business Microscope”, interactions among knowledge workers in an organization can be visualized by sensing face-to-face communication using wearable sensor nodes. In conventional studies, speakers are detected by comparing energy of input speech signals among the nodes. However, there are often synchronization errors among the nodes which degrade the speaker recognition performance. By focusing on property of the speaker's acoustic channel, UAM can provide robustness against the synchronization error. The overall speaker recognition accuracy is improved by combining UAM with the energy-based approach. For 0.1s speech inputs and 4 subjects, speaker recognition accuracy of 94% is achieved at the synchronization error less than 100ms.
Assessment of scanning model observers with hybrid SPECT images
NASA Astrophysics Data System (ADS)
Gifford, H. C.; Pretorius, P. H.; King, M. A.
2008-03-01
The purpose of this work was to test procedures for applying scanning model observers in order to predict human-observer lesion-detection performance with hybrid images. Hybrid images consist of clinical backgrounds with simulated abnormalities. The basis for this investigation was detection and localization of solitary pulmonary nodules (SPN) in SPECT lung images, and our overall goal has been to determine the extent to which detection of SPN could be improved by proper modeling of the acquisition physics during the iterative reconstruction process. Towards this end, we conducted human-observer localization ROC (LROC) studies to optimize the number of iterations and the postfiltering of four rescaled block-iterative (RBI) reconstruction strategies with various combinations of attenuation correction (AC), scatter correction (SC), and system-resolution correction (RC). This observer data was then used to evaluate a scanning channelized nonprewhitening model observer. A standard "background-known-exactly" (BKE) task formulation overstated the prior knowledge and training that human observers had about the hybrid images. Results from a quasi-BKE task that preserved some degree of structural noise in the detection task demonstrated better agreement with the humans.
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.
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
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
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.
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.
HYBRIST Mobility Model - A Novel Hybrid Mobility Model for VANET Simulations
NASA Astrophysics Data System (ADS)
ManfeDanquah, Wiseborn; Turgay Altilar, D.
2014-01-01
Simulations play a vital role in implementing, testing and validating proposed algorithms and protocols in VANET. Mobility model, defined as the movement pattern of vehicles, is one of the main factors that contribute towards the efficient implementation of VANET algorithms and protocols. Using near reality mobility models ensure that accurate results are obtained from simulations. Mobility models that have been proposed and used to implement and test VANET protocols and algorithms are either the urban mobility model or highway mobility model. Algorithms and protocols implemented using urban or highway mobility models may not produce accurate results in hybrid mobility models without enhancement due to the vast differences in mobility patterns. It is on this score the Hybrist, a novel hybrid mobility model is proposed. The realistic mobility pattern trace file of the proposed Hybrist hybrid mobility model can be imported to VANET simulators such as Veins and network simulators such as ns2 and Qualnet to simulate VANET algorithms and protocols.
RCS and antenna modeling with MOM using hybrid meshes
Putnam, J.M.; Kotulski, J.D.
1997-02-01
In this presentation, the authors will investigate the use of hybrid meshes for modeling RCS and antenna problems in three dimensions. They will consider two classes of hybrid basis functions. These include combinations of quadrilateral and triangular meshes for arbitrary 3D geometries, and combinations of axisymmetric body-of-revolution (BOR) basis functions and triangular facets. In particular, they will focus on the problem of enforcing current continuity between two surfaces which are represented by different types of surface discretizations and unknown basis function representations. They will illustrate the use of an operator-based code architecture for the implementation of these formulations, and how it facilitates the incorporation of the various types of boundary conditions in the code. Both serial and parallel code implementation issues for the formulations will be discussed. Results will be presented for both scattering and antenna problems. The emphasis will be on accuracy, and robustness of the techniques. Comparisons of accuracy between triangular meshed and quadrilateral meshed geometries will be shown. The use of hybrid meshes for modeling BORs with attached appendages will also be presented.
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.
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.
Hybrid first-principles/neural networks model for column flotation
Gupta, S.; Liu, P.H.; Svoronos, S.A.; Sharma, R.; Abdel-Khalek, N.A.; Cheng, Y.; El-Shall, H.
1999-03-01
A new model for phosphate column flotation is presented which for the first time relates the effects of operating variables such as frother concentration on column performance. This is a hybrid model that combines a first-principles model with artificial neural networks. The first-principles model is obtained from material balances on both phosphate particles and gangue (undesired material containing mostly silica). First-order rates of net attachment are assumed for both. Artificial neural networks relate the attachment rate constants to the operating variables. Experiments were conducted in a 6-in.-dia. (152-mm-dia.) laboratory column to provide data for neural network training and model validation. The model successfully predicts the effects of frother concentration, particle size, air flow rate and bubble diameter on grade and recovery.
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.
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. PMID:22254341
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.
Hybrid automata as a unifying framework for modeling excitable cells.
Ye, P; Entcheva, E; Smolka, S A; True, M R; Grosu, R
2006-01-01
We propose hybrid automata (HA) as a unifying framework for computational models of excitable cells. HA, which combine discrete transition graphs with continuous dynamics, can be naturally used to obtain a piecewise, possibly linear, approximation of a nonlinear excitable-cell model. We first show how HA can be used to efficiently capture the action-potential morphology--as well as reproduce typical excitable-cell characteristics such as refractoriness and restitution--of the dynamic Luo-Rudy model of a guinea-pig ventricular myocyte. We then recast two well-known computational models, Biktashev's and Fenton-Karma, as HA without any loss of expressiveness. Given that HA possess an intuitive graphical representation and are supported by a rich mathematical theory and numerous analysis tools, we argue that they are well positioned as a computational model for biological processes. PMID:17947070
A hybrid modelling approach for assessing solar radiation
NASA Astrophysics Data System (ADS)
Shamim, M. A.; Bray, M.; Remesan, R.; Han, D.
2015-11-01
A hybrid technique for solar radiation estimation, a core part of hydrological cycle, is presented in this study which parameterises the cloud cover effect (cloud cover index) not just from the geostationary satellites but also the PSU/NCAR's Mesoscale Modelling system (MM5) model. This, together with output from a global clear sky radiation model and observed datasets of temperature and precipitation are used as inputs within the Gamma test (GT) environment for the development of nonlinear models for global solar radiation estimation. The study also explores the ability of Gamma test to determine the optimum input combination and data length selection. Artificial neural network- and local linear regression-based nonlinear techniques are used to test the proposed methodology, and the results have shown a high degree of correlation between the observed and estimated values. It is believed that this study will initiate further exploration of GT for improving informed data and model selection.
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
Model-adaptive hybrid dynamic control for robotic assembly tasks
Austin, D.J.; McCarragher, B.J.
1999-10-01
A new task-level adaptive controller is presented for the hybrid dynamic control of robotic assembly tasks. Using a hybrid dynamic model of the assembly task, velocity constraints are derived from which satisfactory velocity commands are obtained. Due to modeling errors and parametric uncertainties, the velocity commands may be erroneous and may result in suboptimal performance. Task-level adaptive control schemes, based on the occurrence of discrete events, are used to change the model parameters from which the velocity commands are determined. Two adaptive schemes are presented: the first is based on intuitive reasoning about the vector spaces involved whereas the second uses a search region that is reduced with each iteration. For the first adaptation law, asymptotic convergence to the correct model parameters is proven except for one case. This weakness motivated the development of the second adaptation law, for which asymptotic convergence is proven in all cases. Automated control of a peg-in-hole assembly task is given as an example, and simulations and experiments for this task are presented. These results demonstrate the success of the method and also indicate properties for rapid convergence.
Constructing biological pathway models with hybrid functional Petri nets.
Doi, Atsushi; Fujita, Sachie; Matsuno, Hiroshi; Nagasaki, Masao; Miyano, Satoru
2004-01-01
In many research projects on modeling and analyzing biological pathways, the Petri net has been recognized as a promising method for representing biological pathways. From the pioneering works by Reddy et al., 1993, and Hofestädt, 1994, that model metabolic pathways by traditional Petri net, several enhanced Petri nets such as colored Petri net, stochastic Petri net, and hybrid Petri net have been used for modeling biological phenomena. Recently, Matsuno et al., 2003b, introduced the hybrid functional Petri net (HFPN) in order to give a more intuitive and natural modeling method for biological pathways than these existing Petri nets. Although the paper demonstrates the effectiveness of HFPN with two examples of gene regulation mechanism for circadian rhythms and apoptosis signaling pathway, there has been no detailed explanation about the method of HFPN construction for these examples. The purpose of this paper is to describe method to construct biological pathways with the HFPN step-by-step. The method is demonstrated by the well-known glycolytic pathway controlled by the lac operon gene regulatory mechanism. 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.
Modeling the Mixture of IRT and Pattern Responses by a Modified HYBRID Model.
ERIC Educational Resources Information Center
Yamamoto, Kentaro; Everson, Howard T.
This study demonstrates the utility of a HYBRID psychometric model, which incorporates both item response theoretic and latent class models, for detecting test speededness. The model isolates where in a sequence of test items examinee response patterns shift from one providing reasonable estimates of ability to those best characterized by a random…
A hybrid spatiotemporal drought forecasting model for operational use
NASA Astrophysics Data System (ADS)
Vasiliades, L.; Loukas, A.
2010-09-01
Drought forecasting plays an important role in the planning and management of natural resources and water resource systems in a river basin. Early and timelines forecasting of a drought event can help to take proactive measures and set out drought mitigation strategies to alleviate the impacts of drought. Spatiotemporal data mining is the extraction of unknown and implicit knowledge, structures, spatiotemporal relationships, or patterns not explicitly stored in spatiotemporal databases. As one of data mining techniques, forecasting is widely used to predict the unknown future based upon the patterns hidden in the current and past data. This study develops a hybrid spatiotemporal scheme for integrated spatial and temporal forecasting. Temporal forecasting is achieved using feed-forward neural networks and the temporal forecasts are extended to the spatial dimension using a spatial recurrent neural network model. The methodology is demonstrated for an operational meteorological drought index the Standardized Precipitation Index (SPI) calculated at multiple timescales. 48 precipitation stations and 18 independent precipitation stations, located at Pinios river basin in Thessaly region, Greece, were used for the development and spatiotemporal validation of the hybrid spatiotemporal scheme. Several quantitative temporal and spatial statistical indices were considered for the performance evaluation of the models. Furthermore, qualitative statistical criteria based on contingency tables between observed and forecasted drought episodes were calculated. The results show that the lead time of forecasting for operational use depends on the SPI timescale. The hybrid spatiotemporal drought forecasting model could be operationally used for forecasting up to three months ahead for SPI short timescales (e.g. 3-6 months) up to six months ahead for large SPI timescales (e.g. 24 months). The above findings could be useful in developing a drought preparedness plan in the region.
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)…
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.
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
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
Hybrid Modelling of the Economical Consequences of Extreme Magnitude Earthquakes
NASA Astrophysics Data System (ADS)
Chavez, M.; Cabrera, E.; Ashworth, M.; Garcia, S.; Emerson, D.; Perea, N.; Salazar, A.; Moulinec, C.
2013-05-01
A hybrid modelling methodology is proposed to estimate the probability of exceedance of the intensities of extreme magnitude earthquakes (PEI) and of their direct economical consequences (PEDEC). The hybrid modeling uses 3D seismic wave propagation (3DWP) combined with empirical Green function (EGF) and Neural Network (NN) techniques in order to estimate the seismic hazard (PEIs) of extreme earthquakes (plausible) scenarios corresponding to synthetic seismic sources. 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. The PEDEC are computed by using appropriate vulnerability functions combined with the scenario intensity samples, and Monte Carlo simulation. The methodology is validated for Mw 8 magnitude 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 Pacific Coast. The results obtained with the proposed methodology, such as those of the PEDECs in terms of the joint event "damage Cost (C) - maximum ground intensities", of the conditional return period of C given that the maximum intensity exceeds a certain value, could be used by decision makers to allocate funds or to implement policies, to mitigate the impact associated to the plausible occurrence of future extreme magnitude earthquakes.
Coarse-grained DNA modeling: Hybridization and ionic effects
NASA Astrophysics Data System (ADS)
Hinckley, Daniel M.
Deoxyribonucleic acid (DNA) is a biopolymer of enormous significance in living systems. The utility of DNA in such systems is derived from the programmable nature of DNA and its unique mechanical properties. Recently, material scientists have harnessed these properties in order to create systems that spontaneous self-assemble on the nanoscale. Both biologists and material scientists are hindered by an incomplete understanding of the physical interactions that together govern DNA's behavior. Computer simulations, especially those at the coarse-grained (CG) level, can potentially complete this understanding by resolving details indiscernible with current experimental techniques. In this thesis, we advance the state-of-the-art of DNA CG simulations by first reviewing the relevant theory and the evolution of CG DNA models since their inception. Then we present 3SPN.2, an improved CG model for DNA that should provide new insights into biological and nanotechnological systems which incorporate DNA. We perform forward flux sampling simulations in order to examine the effect of sequence, oligomer length, and ionic strength on DNA oligomer hybridization. Due to the limitations inherent in continuum treatments of electrostatic interactions in biological systems, we generate a CG model of biological ions for use with 3SPN.2 and other CG models. Lastly, we illustrate the potential of 3SPN.2 and CG ions by using the models in simulations of viral capsid packaging experiments. The models and results described in this thesis will be useful in future modeling efforts that seek to identify the fundamental physics that govern behavior such as nucleosome positioning, DNA hybridization, and DNA nanoassembly.
Efficient Vaccine Distribution Based on a Hybrid Compartmental Model
Yu, Zhiwen; Liu, Jiming; Wang, Xiaowei; Zhu, Xianjun; Wang, Daxing; Han, Guoqiang
2016-01-01
To effectively and efficiently reduce the morbidity and mortality that may be caused by outbreaks of emerging infectious diseases, it is very important for public health agencies to make informed decisions for controlling the spread of the disease. Such decisions must incorporate various kinds of intervention strategies, such as vaccinations, school closures and border restrictions. Recently, researchers have paid increased attention to searching for effective vaccine distribution strategies for reducing the effects of pandemic outbreaks when resources are limited. Most of the existing research work has been focused on how to design an effective age-structured epidemic model and to select a suitable vaccine distribution strategy to prevent the propagation of an infectious virus. Models that evaluate age structure effects are common, but models that additionally evaluate geographical effects are less common. In this paper, we propose a new SEIR (susceptible—exposed—infectious šC recovered) model, named the hybrid SEIR-V model (HSEIR-V), which considers not only the dynamics of infection prevalence in several age-specific host populations, but also seeks to characterize the dynamics by which a virus spreads in various geographic districts. Several vaccination strategies such as different kinds of vaccine coverage, different vaccine releasing times and different vaccine deployment methods are incorporated into the HSEIR-V compartmental model. We also design four hybrid vaccination distribution strategies (based on population size, contact pattern matrix, infection rate and infectious risk) for controlling the spread of viral infections. Based on data from the 2009–2010 H1N1 influenza epidemic, we evaluate the effectiveness of our proposed HSEIR-V model and study the effects of different types of human behaviour in responding to epidemics. PMID:27233015
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.
Gravitational-wave generation in hybrid quintessential inflationary models
Sa, Paulo M.; Henriques, Alfredo B.
2010-06-15
We investigate the generation of gravitational waves in the hybrid quintessential inflationary model. The full gravitational-wave energy spectrum is calculated using the method of continuous Bogoliubov coefficients. The postinflationary kination period, characteristic of quintessential inflationary models, leaves a clear signature on the spectrum, namely, a peak at high frequencies. The maximum of the peak is firmly located at the megahertz-gigahertz region of the spectrum and corresponds to {Omega}{sub GW{approx_equal}}10{sup -12}. This peak is substantially smaller than the one appearing in the gravitational-wave energy spectrum of the original quintessential inflationary model, therefore avoiding any conflict with the nucleosynthesis constraint on {Omega}{sub GW}.
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
Hybrid Models of Reactive Transport in Porous and Fractured Media
Battiato, Ilenia; Tartakovsky, Daniel M.; Tartakovsky, Alexandre M.; Scheibe, Timothy D.
2011-02-02
Darcy-scale models of flow and transport in porous media often fail to describe experimentally observed phenomena, while their pore-scale counterparts are accu- rate but can be computationally prohibitive. Most numerical multi-scale models, which seek to combine these two descriptions, require empirical closures and/or assumptions on the behavior of pore-scale quantities at the continuum (Darcy) scale. We present a general formulation of an iterative hybrid numerical method that links these two scales without resorting to such approximations. The algorithm treats the fluxes exchanged at the internal boundaries between the pore- and continuum-scale domains as unknown, and allows for iteratively determined boundary conditions to be applied at the pore-scale in order to guarantee their continuity. While the algorithm proposed is general, we use it to model Taylor dispersion in a fracture with chemically reactive walls. Results show significant improvement upon standard continuum-scale formulations.
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.
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. PMID:19435679
A Real-Time Hybrid Heliospheric Modeling System
NASA Astrophysics Data System (ADS)
Detman, T.; Arge, C.; Fry, C.; Dryer, M.; Smith, Z.; Pizzo, V.
2001-12-01
The Hybrid Heliospheric Modeling System (HHMS) is a combination of existing models linked together to predict solar wind conditions at Earth and associated geomagnetic activity from solar observations. The HHMS consists of four models, two physics based and two empirical, hence the term hybrid. The primary input driving the system is daily magnetograms composed into global magnetic maps of the solar photosphere. These maps are used as input to the Potential Field Source Surface model of Wang and Sheeley. The output source surface maps are modified using the Current Sheet Model of Ken Shatten. The resulting Source Surface Current Sheet (SSCS) maps are used (via an intervening empirical translation model) to drive a time dependent 3D numerical MHD solar wind model. The solar wind model gives a predicted time series of solar wind and IMF (MHD parameters) at Earth and is verified using satellite measurements such as from Omni, Wind and ACE. Subsequent empirical (data based) models can use the predicted MHD time series at Earth to predict space weather effects such as the Ap and Dst indices, geosynchronous magnetopause crossings, and relativistic (killer) electron fluxes in geosynchronous orbit. Verification of HHMS predicted Ap indices against historical observations will be shown. The MHD time series at Earth could also be used as a driver for existing physics based magnetospheric models. The HHMS also has the potential to give a predicted solar wind time series at other locations such as Mercury or Mars. The HHMS has two modes of operation. The background mode uses only the SSCS maps as described above. This mode computes an evolving background state of the solar wind in the inner heliosphere (it could be extended outward). In the event mode, a second type of input is combined with the background mode to simulate the effect of solar transient events by perturbing the input boundary of the MHD solar wind model directly. At its current grid resolution of 5° x5° (to
HYBRID FAST HANKEL TRANSFORM ALGORITHM FOR ELECTROMAGNETIC MODELING
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 ...
Estimation of Flood Inundation Extent Using Hybrid Models (Invited)
NASA Astrophysics Data System (ADS)
Chang, L.; Wang, Y.; Shen, H.
2009-12-01
We present a two-stage procedure underlying CHIM (clustering-based hybrid inundation model), which is composed of the linear regression models and ANNs to build the regional flood inundation estimation model. The two-stage procedure includes data preprocessing and model building stages. In the data preprocessing stage, the K-means clustering is used to categorize the data points of the different flooding characteristics and to identify the control point(s) from individual flooding cluster(s). In the model building stage, three classes of flood depth estimation models are built in each cluster: the back-propagation neural network (BPNN) for each control point, the linear regression models for the grids those have highly linear correlation with the control point, and a multi-grid BPNN for the grids those do not exist highly linear correlation with the control point. The effectiveness of the proposed approach is tested in the Dacun township in Taiwan. The results show that the CHIM can continuously and adequately provide one-hour-ahead flood inundation maps and effectively reduce 99% CPU time.
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.
Quasicycles in the stochastic hybrid Morris-Lecar neural model.
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. PMID:26274200
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.
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
HALM: A Hybrid Asperity Likelihood Model for Italy
NASA Astrophysics Data System (ADS)
Gulia, L.; Wiemer, S.
2009-04-01
The Asperity Likelihood Model (ALM), first developed and currently tested for California, hypothesizes that small-scale spatial variations in the b-value of the Gutenberg and Richter relationship play a central role in forecasting future seismicity (Wiemer and Schorlemmer, SRL, 2007). The physical basis of the model is the concept that the local b-value is inversely dependent on applied shear stress. Thus low b-values (b < 0.7) characterize the locked paches of faults -asperities- from which future mainshocks are more likely to be generated, whereas the high b-values (b > 1.1) found for example in creeping section of faults suggest a lower seismic hazard. To test this model in a reproducible and prospective way suitable for the requirements of the CSEP initiative (www.cseptesting.org), the b-value variability is mapped on a grid. First, using the entire dataset above the overall magnitude of completeness, the regional b-value is estimated. This value is then compared to the one locally estimated at each grid-node for a number of radii, we use the local value if its likelihood score, corrected for the degrees of freedom using the Akaike Information Criterion, suggest to do so. We are currently calibrating the ALM model for implementation in the Italian testing region, the first region within the CSEP EU testing Center (eu.cseptesting.org) for which fully prospective tests of earthquake likelihood models will commence in Europe. We are also developing a modified approach, ‘hybrid' between a grid-based and a zoning one: the HALM (Hybrid Asperity Likelihood Model). According to HALM, the Italian territory is divided in three distinct regions depending on the main tectonic elements, combined with knowledge derived from GPS networks, seismic profile interpretation, borehole breakouts and the focal mechanisms of the event. The local b-value variability was thus mapped using three independent overall b-values. We evaluate the performance of the two models in
Development of a hybrid cloud parameterization for general circulation models
Kao, C.Y.J.; Kristjansson, J.E.; Langley, D.L.
1995-04-01
We have developed a cloud package with state-of-the-art physical schemes that can parameterize low-level stratus or stratocumulus, penetrative cumulus, and high-level cirrus. Such parameterizations will improve cloud simulations in general circulation models (GCMs). The principal tool in this development comprises the physically based Arakawa-Schubert scheme for convective clouds and the Sundqvist scheme for layered, nonconvective clouds. The term {open_quotes}hybrid{close_quotes} addresses the fact that the generation of high-attitude layered clouds can be associated with preexisting convective clouds. Overall, the cloud parameterization package developed should better determine cloud heating and drying effects in the thermodynamic budget, realistic precipitation patterns, cloud coverage and liquid/ice water content for radiation purposes, and the cloud-induced transport and turbulent diffusion for atmospheric trace gases.
Modeling and optimization of a hybrid solar combined cycle (HYCS)
NASA Astrophysics Data System (ADS)
Eter, Ahmad Adel
2011-12-01
The main objective of this thesis is to investigate the feasibility of integrating concentrated solar power (CSP) technology with the conventional combined cycle technology for electric generation in Saudi Arabia. The generated electricity can be used locally to meet the annual increasing demand. Specifically, it can be utilized to meet the demand during the hours 10 am-3 pm and prevent blackout hours, of some industrial sectors. The proposed CSP design gives flexibility in the operation system. Since, it works as a conventional combined cycle during night time and it switches to work as a hybrid solar combined cycle during day time. The first objective of the thesis is to develop a thermo-economical mathematical model that can simulate the performance of a hybrid solar-fossil fuel combined cycle. The second objective is to develop a computer simulation code that can solve the thermo-economical mathematical model using available software such as E.E.S. The developed simulation code is used to analyze the thermo-economic performance of different configurations of integrating the CSP with the conventional fossil fuel combined cycle to achieve the optimal integration configuration. This optimal integration configuration has been investigated further to achieve the optimal design of the solar field that gives the optimal solar share. Thermo-economical performance metrics which are available in the literature have been used in the present work to assess the thermo-economic performance of the investigated configurations. The economical and environmental impact of integration CSP with the conventional fossil fuel combined cycle are estimated and discussed. Finally, the optimal integration configuration is found to be solarization steam side in conventional combined cycle with solar multiple 0.38 which needs 29 hectare and LEC of HYCS is 63.17 $/MWh under Dhahran weather conditions.
Hybrid 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.
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.
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. PMID:22487981
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.
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. PMID:25746167
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.
Comparison of hybrid Hall thruster model to experimental measurements
Scharfe, Michelle K.; Gascon, Nicolas; Cappelli, Mark A.; Fernandez, Eduardo
2006-08-15
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.
Hybrid modeling of electrical and optical behavior in the heart
NASA Astrophysics Data System (ADS)
Roth, Bradley J.; Pertsov, Arkady M.
2009-06-01
Optical mapping of transmembrane potential using voltage-sensitive dyes has revolutionized cardiac electrophysiology by enabling the visualization of electrical excitation waves in the heart. However, the interpretation of the optical mapping data is complicated by the fact that the optical signal arises not just from the surface, but also from some depth into the heart wall. Here, we review modeling efforts, in which the diffusion of photons is incorporated into the computer simulations of cardiac electrical activity (“hybrid” modeling), with the goal of improving our understanding of optical signals. We discuss the major accomplishments of hybrid modeling which include: (i) the explanation of the optical action potential upstroke morphology and prediction of its dependence on the subsurface wave front angle, (ii) the unexpectedly low magnitudes of optically recorded surface potentials during electrical shocks, and (iii) the “depolarization” of the core of the spiral wave and odd dual-humped optical action potentials during reentrant activation. We critically examine current optical mapping techniques and controversies in our understanding of electroporation during defibrillation. Finally, we provide a brief overview of recent theoretical studies aimed at extending optical mapping techniques for imaging intramural excitation to include transillumination imaging of scroll wave filaments and depth-resolved optical tomographic methods.
Simulation-optimization framework for multi-season hybrid stochastic models
NASA Astrophysics Data System (ADS)
Srivastav, R. K.; Srinivasan, K.; Sudheer, K. P.
2011-07-01
SummaryA novel simulation-optimization framework is proposed that enables the automation of the hybrid stochastic modeling process for synthetic generation of multi-season streamflows. This framework aims to minimize the drudgery, judgment and subjectivity involved in the selection of the most appropriate hybrid stochastic model. It consists of a multi-objective optimization model as the driver and the hybrid multi-season stochastic streamflow generation model, hybrid matched block boostrap (HMABB) as the simulation engine. For the estimation of the hybrid model parameters, the proposed framework employs objective functions that aim to minimize the overall errors in the preservation of storage capacities at various demand levels, unlike the traditional approaches that are simulation based. Moreover this framework yields a number of competent hybrid stochastic models in a single run of the simulation-optimization framework. The efficacy of the proposed simulation-optimization framework is brought out through application to two monthly streamflow data sets from USA of varying sample sizes that exhibit multi-modality and a complex dependence structure. The results show that the hybrid models obtained from the proposed framework are able to preserve the statistical characteristics as well as the storage characteristics better than the simulation based HMABB model, while minimizing the manual effort and the subjectivity involved in the modeling process. The proposed framework can be easily extended to model multi-site multi-season streamflow data.
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 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
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 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.
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
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 modelling approach for effective simulation of reactive pollutants like Ozone
NASA Astrophysics Data System (ADS)
Sharma, Sumit; Sharma, Prateek; Khare, Mukesh
2013-12-01
Prediction of air quality is an important component of any air quality management programme. Broadly, two approaches are used to predict the ambient air quality - the deterministic and the statistical approach, with each approach having its own merits and demerits. While the models based on the deterministic approach accurately predict the concentrations of air pollutants in the middle percentile range, the statistical models provide a better estimate of concentrations in the extreme percentile ranges. However, the statistical models are site specific and are not able generate ‘what-if' scenarios; the deterministic models on the other hand are general in character and useful in creating alternative scenarios. An alternative approach - hybrid modelling is a technique which aggregates the benefits of the two techniques and predicts the ‘entire range' of the distribution. While in the past there were attempts to predict the concentrations of inert pollutants using hybrid modelling approach, this paper shows the hybrid model applications for reactive secondary pollutants like ground level Ozone (GLO). This study presents the development of a hybrid model that concatenates the results of CMAQ (community multi-scale air quality model) as its deterministic component with statistical distribution model (based on the specific area category and timeframe) to predict the entire range of GLO concentrations. Predictions have been made using both purely deterministic and hybrid approaches at a receptor location near a major traffic intersection. The performance of the model has been found to improve from an index of agreement from 0.77 (deterministic model) to 0.91 (hybrid model). In order to assess the predictive capability of the hybrid approach, the model has been tested at an entirely different location for different set of temporal data. The results show an improvement in the predictions using the hybrid model over the deterministic model.
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.
Three hybridization models based on local search scheme for job shop scheduling problem
NASA Astrophysics Data System (ADS)
Balbi Fraga, Tatiana
2015-05-01
This work presents three different hybridization models based on the general schema of Local Search Heuristics, named Hybrid Successive Application, Hybrid Neighborhood, and Hybrid Improved Neighborhood. Despite similar approaches might have already been presented in the literature in other contexts, in this work these models are applied to analyzes the solution of the job shop scheduling problem, with the heuristics Taboo Search and Particle Swarm Optimization. Besides, we investigate some aspects that must be considered in order to achieve better solutions than those obtained by the original heuristics. The results demonstrate that the algorithms derived from these three hybrid models are more robust than the original algorithms and able to get better results than those found by the single Taboo Search.
Duenez-Guzman, Edgar A; Mavárez, Jesus; Vose, Michael D; Gavrilets, Sergey
2009-10-01
We build a spatial individual-based multilocus model of homoploid hybrid speciation tailored for a tentative case of hybrid origin of Heliconius heurippa from H. melpomene and H. cydno in South America. Our model attempts to account for empirical patterns and data on genetic incompatibility, mating preferences and selection by predation (both based on coloration patterns), habitat preference, and local adaptation for all three Heliconius species. Using this model, we study the likelihood of recombinational speciation and identify the effects of various ecological and genetic parameters on the dynamics, patterns, and consequences of hybrid ecological speciation. Overall, our model supports the possibility of hybrid origin of H. heurippa under certain conditions. The most plausible scenario would include hybridization between H. melpomene and H. cydno in an area geographically isolated from the rest of both parental species with subsequent long-lasting geographic isolation of the new hybrid species, followed by changes in the species ranges, the secondary contact, and disappearance of H. melpomene-type ecomorph in the hybrid species. However, much more work (both empirical and theoretical) is necessary to be able to make more definite conclusions on the importance of homoploid hybrid speciation in animals. PMID:19545268
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. PMID:25628100
A Hybrid Model for Automatic Emotion Recognition in Suicide Notes
Yang, Hui; Willis, Alistair; de Roeck, Anne; Nuseibeh, Bashar
2012-01-01
We describe the Open University team’s submission to the 2011 i2b2/VA/Cincinnati Medical Natural Language Processing Challenge, Track 2 Shared Task for sentiment analysis in suicide notes. This Shared Task focused on the development of automatic systems that identify, at the sentence level, affective text of 15 specific emotions from suicide notes. We propose a hybrid model that incorporates a number of natural language processing techniques, including lexicon-based keyword spotting, CRF-based emotion cue identification, and machine learning-based emotion classification. The results generated by different techniques are integrated using different vote-based merging strategies. The automated system performed well against the manually-annotated gold standard, and achieved encouraging results with a micro-averaged F-measure score of 61.39% in textual emotion recognition, which was ranked 1st place out of 24 participant teams in this challenge. The results demonstrate that effective emotion recognition by an automated system is possible when a large annotated corpus is available. PMID:22879757
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.
Data driven components in a model of inner shelf sorted bedforms: a new hybrid model
NASA Astrophysics Data System (ADS)
Goldstein, E. B.; Coco, G.; Murray, A. B.; Green, M. O.
2013-10-01
Numerical models rely on the parameterization of processes that often lack a deterministic description. In this contribution we demonstrate the applicability of using machine learning, optimization tools from the discipline of computer science, to develop parameterizations when extensive data sets exist. We develop a new predictor for near bed suspended sediment reference concentration under unbroken waves using genetic programming, a machine learning technique. This newly developed parameterization performs better than existing empirical predictors. We add this new predictor into an established model for inner shelf sorted bedforms. Additionally we incorporate a previously reported machine learning derived predictor for oscillatory flow ripples into the sorted bedform model. This new "hybrid" sorted bedform model, whereby machine learning components are integrated into a numerical model, demonstrates a method of incorporating observational data (filtered through a machine learning algorithm) directly into a numerical model. Results suggest that the new hybrid model is able to capture dynamics previously absent from the model, specifically, the two observed pattern modes of sorted bedforms. However, caveats exist when data driven components do not have parity with traditional theoretical components of morphodynamic models, and we discuss the challenges of integrating these disparate pieces and the future of this type of modeling.
Rezvani, Alireza; Khalili, Abbas; Mazareie, Alireza; Gandomkar, Majid
2016-07-01
Nowadays, photovoltaic (PV) generation is growing increasingly fast as a renewable energy source. Nevertheless, the drawback of the PV system is its dependence on weather conditions. Therefore, battery energy storage (BES) can be considered to assist for a stable and reliable output from PV generation system for loads and improve the dynamic performance of the whole generation system in grid connected mode. In this paper, a novel topology of intelligent hybrid generation systems with PV and BES in a DC-coupled structure is presented. Each photovoltaic cell has a specific point named maximum power point on its operational curve (i.e. current-voltage or power-voltage curve) in which it can generate maximum power. Irradiance and temperature changes affect these operational curves. Therefore, the nonlinear characteristic of maximum power point to environment has caused to development of different maximum power point tracking techniques. In order to capture the maximum power point (MPP), a hybrid fuzzy-neural maximum power point tracking (MPPT) method is applied in the PV system. Obtained results represent the effectiveness and superiority of the proposed method, and the average tracking efficiency of the hybrid fuzzy-neural is incremented by approximately two percentage points in comparison to the conventional methods. It has the advantages of robustness, fast response and good performance. A detailed mathematical model and a control approach of a three-phase grid-connected intelligent hybrid system have been proposed using Matlab/Simulink. PMID:26961319
A circuit model for the hybrid resonance modes of paired SRR metamaterials.
Poo, Yin; Wu, Rui-xin; Liu, Min; Wang, Ling
2014-01-27
To better understand the resonance modes caused by the interelement couplings in the building block of metamaterials, we propose a circuit model for the hybrid resonance modes of paired split ring resonators. The model identifies the electromagnetic coupling between the paired rings by electric and magnetic coupling networks and well explains the variation of hybrid resonance modes with respect to the distance and the twist angle between the rings. The predictions of our model are further proved by experiments. PMID:24515201
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. PMID:27391181
A hybrid model to simulate the annual runoff of the Kaidu River in northwest China
NASA Astrophysics Data System (ADS)
Xu, Jianhua; Chen, Yaning; Bai, Ling; Xu, Yiwen
2016-04-01
Fluctuant and complicated hydrological processes can result in the uncertainty of runoff forecasting. Thus, it is necessary to apply the multi-method integrated modeling approaches to simulate runoff. Integrating the ensemble empirical mode decomposition (EEMD), the back-propagation artificial neural network (BPANN) and the nonlinear regression equation, we put forward a hybrid model to simulate the annual runoff (AR) of the Kaidu River in northwest China. We also validate the simulated effects by using the coefficient of determination (R2) and the Akaike information criterion (AIC) based on the observed data from 1960 to 2012 at the Dashankou hydrological station. The average absolute and relative errors show the high simulation accuracy of the hybrid model. R2 and AIC both illustrate that the hybrid model has a much better performance than the single BPANN. The hybrid model and integrated approach elicited by this study can be applied to simulate the annual runoff of similar rivers in northwest China.
A Hybrid Sensitivity Analysis Approach for Agent-based Disease Spread Models
Pullum, Laura L; Cui, Xiaohui
2012-01-01
Agent-based models (ABM) have been widely deployed in different fields for studying the collective behavior of large numbers of interacting agents. Of particular interest lately is the application of agent-based and hybrid models to epidemiology, specifically Agent-based Disease Spread Models (ABDSM). Validation (one aspect of the means to achieve dependability) of ABDSM simulation models is extremely important. It ensures that the right model has been built and lends confidence to the use of that model to inform critical decisions. In this report, we describe our preliminary efforts in ABDSM validation by using hybrid model fusion technology.
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 ...
Hybrid quantization of an inflationary model: The flat case
NASA Astrophysics Data System (ADS)
Fernández-Méndez, Mikel; Mena Marugán, Guillermo A.; Olmedo, Javier
2013-08-01
We present a complete quantization of an approximately homogeneous and isotropic universe with small scalar perturbations. We consider the case in which the matter content is a minimally coupled scalar field and the spatial sections are flat and compact, with the topology of a three-torus. The quantization is carried out along the lines that were put forward by the authors in a previous work for spherical topology. The action of the system is truncated at second order in perturbations. The local gauge freedom is fixed at the classical level, although different gauges are discussed and shown to lead to equivalent conclusions. Moreover, descriptions in terms of gauge-invariant quantities are considered. The reduced system is proven to admit a symplectic structure, and its dynamical evolution is dictated by a Hamiltonian constraint. Then, the background geometry is polymerically quantized, while a Fock representation is adopted for the inhomogeneities. The latter is selected by uniqueness criteria adapted from quantum field theory in curved spacetimes, which determine a specific scaling of the perturbations. In our hybrid quantization, we promote the Hamiltonian constraint to an operator on the kinematical Hilbert space. If the zero mode of the scalar field is interpreted as a relational time, a suitable ansatz for the dependence of the physical states on the polymeric degrees of freedom leads to a quantum wave equation for the evolution of the perturbations. Alternatively, the solutions to the quantum constraint can be characterized by their initial data on the minimum-volume section of each superselection sector. The physical implications of this model will be addressed in a future work, in order to check whether they are compatible with observations.
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
SOFC-Gas Turbine Hybrid System for Aircraft Applications: Modeling and Performance Analysis
NASA Astrophysics Data System (ADS)
Srivastava, Nischal
2005-11-01
There is a growing interest in fuel cells for aircraft applications. Fuel cells when combined with conventional turbine power plants offer high fuel efficiencies. The feature of fuel cells (SOFC, MCFC) used in aircraft applications, which makes them suitable for hybrid systems, is their high operating temperature. Their dynamic nature, both electrical and thermodynamic, demands a dynamic study of the complete hybrid cycle. In this paper we present a model for a SOFC/Gas Turbine hybrid system and its implementation in Matlab-Simulink. The main focus of the paper is on the dynamic analysis of the combined SOFC/GT cycle. Various configurations of the hybrid system are proposed and simulated. A comparative study of the simulated configurations, based on the first and second laws of thermodynamics, is presented. An exergy analysis for the chosen configuration is used to perform a parametric study of the overall hybrid system performance.
Addressing Cognitive Processes in e-learning: TSOI Hybrid Learning Model
ERIC Educational Resources Information Center
Tsoi, Mun Fie; Goh, Ngoh Khang
2008-01-01
The development of e-learning materials for teaching and learning often needs to be guided by appropriate educational theories or models. As such, this paper provides alternative e-learning design pedagogy, the TSOI Hybrid Learning Model as a pedagogic model for the design of e-learning cognitively in science and chemistry education. This model is…
A new hybrid electro-numerical model of the left ventricle.
Kozarski, Maciej; Ferrari, Gianfranco; Zieliński, Krzysztof; Górczyńska, Krystyna; Pałko, Krzysztof J; Tokarz, Arkadiusz; Darowski, Marek
2008-09-01
The paper presents a new project of a hybrid numerical-physical model of the left ventricle. A physical part of the model can be based on electrical or hydraulic structures. Four variants of the model with numerical and physical heart valves have been designed to investigate an effect of a heart assistance connected in series and in parallel to the natural heart. The LabVIEW real time environment has been used in the model to increase its accuracy and reliability. A prototype of the hybrid electro-numerical model of the left ventricle has been tested in an open loop and closed loop configuration. PMID:18762290
FISH-ing for Genes: Modeling Fluorescence "in situ" Hybridization
ERIC Educational Resources Information Center
Baker, William P.; Jones, Carleton Buck
2006-01-01
Teaching methods of genetic analysis such as fluorescence in situ hybridization (FISH) can be an important part of instructional units in biology, microbiology, and biotechnology. Experience, however, indicates that these topics are difficult for many students. The authors of this article describe how they created an activity that effectively…
Applying a Hybrid Model: Can It Enhance Student Learning Outcomes?
ERIC Educational Resources Information Center
Potter, Jodi
2015-01-01
There has been a marked increase in the use of online learning over the past decade. There remains conflict in the current body of research on the efficacy of online versus face to face learning in these environments. One resolution of these issues is the hybrid learning option which is a combination of face-to-face classroom instruction with…
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 I.; Lin, Guang; Tartakovsky, Alexandre M.
2012-04-23
Recently there has been interest in developing efficient ways to model heterogeneous surface reactions with hybrid computational models that couple a 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 also 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.
NASA Astrophysics Data System (ADS)
Kusnandar, Dadan; Mara, Muhlasah Novitasari; Debataraja, Naomi Nessyana
2015-12-01
A diagnostics model was proposed to estimate the mean sea level change by hybridizing exponential smoothing and neural network. The model integrated the linear characteristics of the exponential smoothing model and the nonlinear pattern of the neural network. Mean sea level data were obtained from the measurements of Jason-2 satellite altimeter mission from 2008 - 2014. The results showed that the diagnostic model obtained by hybridization of the exponential smoothing and neural network model provide an alternative prediction model for the mean sea level change in South China Sea.
NASA Astrophysics Data System (ADS)
Rath, S.; Sengupta, P. P.; Singh, A. P.; Marik, A. K.; Talukdar, P.
2013-03-01
Accurate prediction of roll force during hot strip rolling is essential for model based operation of hot strip mills. Traditionally, mathematical models based on theory of plastic deformation have been used for prediction of roll force. In the last decade, data driven models like artificial neural network have been tried for prediction of roll force. Pure mathematical models have accuracy limitations whereas data driven models have difficulty in convergence when applied to industrial conditions. Hybrid models by integrating the traditional mathematical formulations and data driven methods are being developed in different parts of world. This paper discusses the methodology of development of an innovative hybrid mathematical-artificial neural network model. In mathematical model, the most important factor influencing accuracy is flow stress of steel. Coefficients of standard flow stress equation, calculated by parameter estimation technique, have been used in the model. The hybrid model has been trained and validated with input and output data collected from finishing stands of Hot Strip Mill, Bokaro Steel Plant, India. It has been found that the model accuracy has been improved with use of hybrid model, over the traditional mathematical model.
A model-based method for identifying species hybrids using multilocus genetic data.
Anderson, E C; Thompson, E A
2002-01-01
We present a statistical method for identifying species hybrids using data on multiple, unlinked markers. The method does not require that allele frequencies be known in the parental species nor that separate, pure samples of the parental species be available. The method is suitable for both markers with fixed allelic differences between the species and markers without fixed differences. The probability model used is one in which parentals and various classes of hybrids (F(1)'s, F(2)'s, and various backcrosses) form a mixture from which the sample is drawn. Using the framework of Bayesian model-based clustering allows us to compute, by Markov chain Monte Carlo, the posterior probability that each individual belongs to each of the distinct hybrid classes. We demonstrate the method on allozyme data from two species of hybridizing trout, as well as on two simulated data sets. PMID:11901135
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.
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.
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.
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.
Optimization of ultrasonic array inspections using an efficient hybrid model and real crack shapes
NASA Astrophysics Data System (ADS)
Felice, Maria V.; Velichko, Alexander; Wilcox, Paul D.; Barden, Tim; Dunhill, Tony
2015-03-01
Models which simulate the interaction of ultrasound with cracks can be used to optimize ultrasonic array inspections, but this approach can be time-consuming. To overcome this issue an efficient hybrid model is implemented which includes a finite element method that requires only a single layer of elements around the crack shape. Scattering Matrices are used to capture the scattering behavior of the individual cracks and a discussion on the angular degrees of freedom of elastodynamic scatterers is included. Real crack shapes are obtained from X-ray Computed Tomography images of cracked parts and these shapes are inputted into the hybrid model. The effect of using real crack shapes instead of straight notch shapes is demonstrated. An array optimization methodology which incorporates the hybrid model, an approximate single-scattering relative noise model and the real crack shapes is then described.
Higher Order Modeling In the BEM/FEM Hybrid Formulation
NASA Technical Reports Server (NTRS)
Fink, Patrick W.; Wilton, Don R.
2000-01-01
Hybrid formulations using low order curl-conforming bases to represent the total electric field within a finite element region and low order divergence-conforming bases to represent equivalent electric and magnetic currents on the boundary are well known. However, higher-order divergence and curl-conforming bases have been shown to provide significant benefits in convergence rates and accuracy when employed in strictly integral equation and strictly finite element formulations. In this paper, a hybrid electric field formulation employing higher order bases is presented. The paper addresses benefits and issues associated with using higher order divergence-and curl-conforming bases in the hybrid finite element/boundary element electric field formulation. The method of singularity subtraction may be used to compute the self terms of the boundary integral when the bases are of low order. But this method becomes laborious and requires great care when the divergence conforming bases are of higher order. In order to handle these singularities simply and accurately, a generalized Gaussian quadrature method is employed in which the expansion functions account for the singularity. In preliminary tests of the higher order hybrid formulation, the equivalent electric current induced by scattering of a plane wave from a square dielectric cylinder is examined. Accurate results are obtained using only a two-triangle mesh when the current basis is of order 4 or 5. Additional results are presented comparing the error obtained using higher order bases to that obtained using lower order bases when the number of unknowns is approximately equal. Also, convergence rates obtained with higher order bases are compared to those obtained with lower order bases for selected sample problems.
Charging and hybridization in the finite cluster model
NASA Technical Reports Server (NTRS)
Bauschlicher, C. W., Jr.; Bagus, P. S.; Nelin, C. J.
1984-01-01
Cluster wavefunctions which have appropriate hybridization and polarization lead to reasonable properties for the interaction of an adsorbate with a solid surface. However, for Al clusters, it was found that the atomic change distribution is not uniform. The finite cluster size leads to changes not representative for an extended system. This effect appears to be dependent on the particular materials being studied; it does not occur in all cases.
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
A Hybrid Model for Predicting the Prevalence of Schistosomiasis in Humans of Qianjiang City, China
Wang, Ying; Lu, Zhouqin; Tian, Lihong; Tan, Li; Shi, Yun; Nie, Shaofa; Liu, Li
2014-01-01
Backgrounds/Objective Schistosomiasis is still a major public health problem in China, despite the fact that the government has implemented a series of strategies to prevent and control the spread of the parasitic disease. Advanced warning and reliable forecasting can help policymakers to adjust and implement strategies more effectively, which will lead to the control and elimination of schistosomiasis. Our aim is to explore the application of a hybrid forecasting model to track the trends of the prevalence of schistosomiasis in humans, which provides a methodological basis for predicting and detecting schistosomiasis infection in endemic areas. Methods A hybrid approach combining the autoregressive integrated moving average (ARIMA) model and the nonlinear autoregressive neural network (NARNN) model to forecast the prevalence of schistosomiasis in the future four years. Forecasting performance was compared between the hybrid ARIMA-NARNN model, and the single ARIMA or the single NARNN model. Results The modelling mean square error (MSE), mean absolute error (MAE) and mean absolute percentage error (MAPE) of the ARIMA-NARNN model was 0.1869×10−4, 0.0029, 0.0419 with a corresponding testing error of 0.9375×10−4, 0.0081, 0.9064, respectively. These error values generated with the hybrid model were all lower than those obtained from the single ARIMA or NARNN model. The forecasting values were 0.75%, 0.80%, 0.76% and 0.77% in the future four years, which demonstrated a no-downward trend. Conclusion The hybrid model has high quality prediction accuracy in the prevalence of schistosomiasis, which provides a methodological basis for future schistosomiasis monitoring and control strategies in the study area. It is worth attempting to utilize the hybrid detection scheme in other schistosomiasis-endemic areas including other infectious diseases. PMID:25119882
Almeida Filho, J E; Tardin, F D; Guimarães, J F R; Resende, M D V; Silva, F F; Simeone, M L; Menezes, C B; Queiroz, V A V
2016-01-01
The breeding of sorghum, Sorghum bicolor (L.) Moench, aimed at improving its nutritional quality, is of great interest, since it can be used as a highly nutritive alternative food source and can possibly be cultivated in regions with low rainfall. The objective of the present study was to evaluate the potential and genetic diversity of grain-sorghum hybrids for traits of agronomic and nutritional interest. To this end, the traits grain yield and flowering, and concentrations of protein, potassium, calcium, magnesium, sulfur, iron, manganese, and zinc in the grain were evaluated in 25 grain-sorghum hybrids, comprising 18 experimental hybrids of Embrapa Milho e Sorgo and seven commercial hybrids. The genetic potential was analyzed by a multi-trait best linear unbiased prediction (BLUP) model, and cluster analysis was accomplished by squared Mahalanobis distance using the predicted genotypic values. Hybrids 0306037 and 0306034 stood out in the agronomic evaluation. The hybrids with agronomic prominence, however, did not stand out for the traits related to the nutritional quality of the grain. Three clusters were formed from the dendrogram obtained with the unweighted pair group method with arithmetic mean method. From the results of the genotypic BLUP and the analysis of the dendrogram, hybrids 0577337, 0441347, 0307651, and 0306037 were identified as having the potential to establish a population that can aggregate alleles for all the evaluated traits of interest. PMID:26985915
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
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.
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.
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
Modeling hydraulic regenerative hybrid vehicles using AMESim and Matlab/Simulink
NASA Astrophysics Data System (ADS)
Lynn, Alfred; Smid, Edzko; Eshraghi, Moji; Caldwell, Niall; Woody, Dan
2005-05-01
This paper presents the overview of the simulation modeling of a hydraulic system with regenerative braking used to improve vehicle emissions and fuel economy. Two simulation software packages were used together to enhance the simulation capability for fuel economy results and development of vehicle and hybrid control strategy. AMESim, a hydraulic simulation software package modeled the complex hydraulic circuit and component hardware and was interlinked with a Matlab/Simulink model of the vehicle, engine and the control strategy required to operate the vehicle and the hydraulic hybrid system through various North American and European drive cycles.
Optimized Treatment of Fibromyalgia Using System Identification and Hybrid Model Predictive Control
Deshpande, Sunil; Nandola, Naresh N.; Rivera, Daniel E.; Younger, Jarred W.
2014-01-01
The term adaptive intervention is used in behavioral health to describe individually-tailored strategies for preventing and treating chronic, relapsing disorders. This paper describes a system identification approach for developing dynamical models from clinical data, and subsequently, a hybrid model predictive control scheme for assigning dosages of naltrexone as treatment for fibromyalgia, a chronic pain condition. A simulation study that includes conditions of significant plant-model mismatch demonstrates the benefits of hybrid predictive control as a decision framework for optimized adaptive interventions. This work provides insights on the design of novel personalized interventions for chronic pain and related conditions in behavioral health. PMID:25506132
A research using hybrid RBF/Elman neural networks for intrusion detection system secure model
NASA Astrophysics Data System (ADS)
Tong, Xiaojun; Wang, Zhu; Yu, Haining
2009-10-01
A hybrid RBF/Elman neural network model that can be employed for both anomaly detection and misuse detection is presented in this paper. The IDSs using the hybrid neural network can detect temporally dispersed and collaborative attacks effectively because of its memory of past events. The RBF network is employed as a real-time pattern classification and the Elman network is employed to restore the memory of past events. The IDSs using the hybrid neural network are evaluated against the intrusion detection evaluation data sponsored by U.S. Defense Advanced Research Projects Agency (DARPA). Experimental results are presented in ROC curves. Experiments show that the IDSs using this hybrid neural network improve the detection rate and decrease the false positive rate effectively.
A hybrid modeling with data assimilation to evaluate human exposure level
NASA Astrophysics Data System (ADS)
Koo, Y. S.; Cheong, H. K.; Choi, D.; Kim, A. L.; Yun, H. Y.
2015-12-01
Exposure models are designed to better represent human contact with PM (Particulate Matter) and other air pollutants such as CO, SO2, O3, and NO2. The exposure concentrations of the air pollutants to human are determined by global and regional long range transport of global and regional scales from Europe and China as well as local emissions from urban and road vehicle sources. To assess the exposure level in detail, the multiple scale influence from background to local sources should be considered. A hybrid air quality modeling methodology combing a grid-based chemical transport model with a local plume dispersion model was used to provide spatially and temporally resolved air quality concentration for human exposure levels in Korea. In the hybrid modeling approach, concentrations from a grid-based chemical transport model and a local plume dispersion model are added to provide contributions from photochemical interactions, long-range (regional) transport and local-scale dispersion. The CAMx (Comprehensive Air quality Model with Extensions was used for the background concentrations from anthropogenic and natural emissions in East Asia including Korea while the road dispersion by vehicle emission was calculated by CALPUFF model. The total exposure level of the pollutants was finally assessed by summing the background and road contributions. In the hybrid modeling, the data assimilation method based on the optimal interpolation was applied to overcome the discrepancies between the model predicted concentrations and observations. The air quality data from the air quality monitoring stations in Korea. The spatial resolution of the hybrid model was 50m for the Seoul Metropolitan Ares. This example clearly demonstrates that the exposure level could be estimated to the fine scale for the exposure assessment by using the hybrid modeling approach with data assimilation.
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
A hybrid conceptual-fuzzy inference streamflow modelling for the Letaba River system in South Africa
NASA Astrophysics Data System (ADS)
Katambara, Zacharia; Ndiritu, John G.
There has been considerable water resources developments in South Africa and other regions in the world in order to meet the ever-increasing water demands. These developments have not been matched with a similar development of hydrological monitoring systems and hence there is inadequate data for managing the developed water resources systems. The Letaba River system ( Fig. 1) is a typical case of such a system in South Africa. The available water on this river is over-allocated and reliable daily streamflow modelling of the Letaba River that adequately incorporates the main components and processes would be an invaluable aid to optimal operation of the system. This study describes the development of a calibrated hybrid conceptual-fuzzy-logic model and explores its capability in reproducing the natural processes and human effects on the daily stream flow in the Letaba River. The model performance is considered satisfactory in view of the complexity of the system and inadequacy of relevant data. Performance in modelling streamflow improves towards the downstream and matches that of a stand-alone fuzzy-logic model. The hybrid model obtains realistic estimates of the major system components and processes including the capacities of the farm dams and storage weirs and their trajectories. This suggests that for complex data-scarce River systems, hybrid conceptual-fuzzy-logic modelling may be used for more detailed and dependable operational and planning analysis than stand-alone fuzzy modelling. Further work will include developing and testing other hybrid model configurations.
A hybrid-3D hillslope hydrological model for use in Earth system models
NASA Astrophysics Data System (ADS)
Hazenberg, P.; Fang, Y.; Broxton, P.; Gochis, D.; Niu, G.-Y.; Pelletier, J. D.; Troch, P. A.; Zeng, X.
2015-10-01
Hillslope-scale rainfall-runoff processes leading to a fast catchment response are not explicitly included in land surface models (LSMs) for use in earth system models (ESMs) due to computational constraints. This study presents a hybrid-3D hillslope hydrological model (h3D) that couples a 1-D vertical soil column model with a lateral pseudo-2D saturated zone and overland flow model for use in ESMs. By representing vertical and lateral responses separately at different spatial resolutions, h3D is computationally efficient. The h3D model was first tested for three different hillslope planforms (uniform, convergent and divergent). We then compared h3D (with single and multiple soil columns) with a complex physically based 3-D model and a simple 1-D soil moisture model coupled with an unconfined aquifer (as typically used in LSMs). It is found that simulations obtained by the simple 1-D model vary considerably from the complex 3-D model and are not able to represent hillslope-scale variations in the lateral flow response. In contrast, the single soil column h3D model shows a much better performance and saves computational time by 2-3 orders of magnitude compared with the complex 3-D model. When multiple vertical soil columns are implemented, the resulting hydrological responses (soil moisture, water table depth, and base flow along the hillslope) from h3D are nearly identical to those predicted by the complex 3-D model, but still saves computational time. As such, the computational efficiency of the h3D model provides a valuable and promising approach to incorporating hillslope-scale hydrological processes into continental and global-scale ESMs.
Solutions of contact problems by the assumed stress hybrid model
NASA Technical Reports Server (NTRS)
Kubomura, K.; Pian, T. H. H.
1980-01-01
A method was developed for contact problems which may be either frictional or frictionless and may involve extensive sliding between deformable bodies. It was based on an assumed stress hybrid approach and on an incremental variational principle for which the Euler's equations of the functional include the equilibrium and compatibility conditions at the contact surface. The tractions at an assumed contact surface were introduced as Lagrangian multipliers in the formulation. It was concluded from the results of several example solutions that the extensive sliding contact between deformable bodies can be solved by the present method.
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
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…
Modeling and Analysis of Facility Systems for A Hybrid Materials Test Program
NASA Technical Reports Server (NTRS)
Congiardo, Jared F.
2007-01-01
Analytic modeling and analysis processes employed at NASA-SSC in rocket propulsion systems testing are discussed in this paper with application to test facility propellant supply system design, activation and test of a hybrid rocket motor provided. This paper discusses the analytic model employed, its utilization across project phases and reviews performance results.
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…
Reentrant excitation in an analog-digital hybrid circuit model of cardiac tissue
NASA Astrophysics Data System (ADS)
Mahmud, Farhanahani; Shiozawa, Naruhiro; Makikawa, Masaaki; Nomura, Taishin
2011-06-01
We propose an analog-digital hybrid circuit model of one-dimensional cardiac tissue with hardware implementation that allows us to perform real-time simulations of spatially conducting cardiac action potentials. Each active nodal compartment of the tissue model is designed using analog circuits and a dsPIC microcontroller, by which the time-dependent and time-independent nonlinear current-voltage relationships of six types of ion channel currents employed in the Luo-Rudy phase I (LR-I) model for a single mammalian cardiac ventricular cell can be reproduced quantitatively. Here, we perform real-time simulations of reentrant excitation conduction in a ring-shaped tissue model that includes eighty nodal compartments. In particular, we show that the hybrid tissue model can exhibit real-time dynamics for initiation of reentries induced by uni-directional block, as well as those for phase resetting that leads to annihilation of the reentry in response to impulsive current stimulations at appropriate nodes and timings. The dynamics of the hybrid model are comparable to those of a spatially distributed tissue model with LR-I compartments. Thus, it is conceivable that the hybrid model might be a useful tool for large scale simulations of cardiac tissue dynamics, as an alternative to numerical simulations, leading toward further understanding of the reentrant mechanisms.
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…
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 Three-Dimensional Global Hybrid Model of the Magnetosphere
NASA Astrophysics Data System (ADS)
Wang, X.; Lin, Y.; Lu, S.; Perez, J. D.; Lu, Q.
2013-12-01
A 3-D global hybrid simulation code with domain including both the dayside and night side magnetosphere of the Earth has been developed to study the coupling between the solar wind and the magnetosphere. A Cartesian coordinate system is used, with the simulation domain extends from x = -60 RE to +23RE, y = -30 RE to 30RE, and z = -30 RE to 30RE. Nonuniform cell grids are used, with a higher resolution around the regions of the near-Earth plasma sheet. The inner boundary is located at r =3.5 RE. In the simulation, ions are treated as fully kinetic particles, where electrons are treated as a massless fluid. In addition, a cold ion fluid is assumed in the inner magnetosphere within r<6RE. The bow shock and the Earth's magnetosphere form from the interaction between the solar wind and the dipole geomagnetic field. The solar wind carrying the IMF flows into domain from the upstream boundary at x=23RE, while the free conditions are applied at all the other sides of the boundaries. The inner boundary condition at r= 3.5Re is determined by mapping the parallel currents and electric field to the ionosphere. The details of hybrid code and its benchmark are presented. The global structure of the magnetosphere is shown for various solar wind and IMF conditions.
Analysis of a model of fuel cell - gas turbine hybrid power system for enhanced energy efficiency
NASA Astrophysics Data System (ADS)
Calay, Rajnish K.; Mustafa, Mohamad Y.; Virk, Mohammad S.; Mustafa, Mahmoud F.
2012-11-01
A simple mathematical model to evaluate the performance of FC-GT hybrid system is presented in this paper. The model is used to analyse the influence of various parameters on the performance of a typical hybrid system, where excess heat rejected from the solid-oxide fuel cell stack is utilised to generate additional power through a gas turbine system and to provide heat energy for space heating. The model is based on thermodynamic analysis of various components of the plant and can be adapted for various configurations of the plant components. Because there are many parameters defining the efficiency and work output of the hybrid system, the technique is based on mathematical and graphical optimisation of various parameters; to obtain the maximum efficiency for a given plant configuration.
HyDE Framework for Stochastic and Hybrid Model-Based Diagnosis
NASA Technical Reports Server (NTRS)
Narasimhan, Sriram; Brownston, Lee
2012-01-01
Hybrid Diagnosis Engine (HyDE) is a general framework for stochastic and hybrid model-based diagnosis that offers flexibility to the diagnosis application designer. The HyDE architecture supports the use of multiple modeling paradigms at the component and system level. Several alternative algorithms are available for the various steps in diagnostic reasoning. This approach is extensible, with support for the addition of new modeling paradigms as well as diagnostic reasoning algorithms for existing or new modeling paradigms. HyDE is a general framework for stochastic hybrid model-based diagnosis of discrete faults; that is, spontaneous changes in operating modes of components. HyDE combines ideas from consistency-based and stochastic approaches to model- based diagnosis using discrete and continuous models to create a flexible and extensible architecture for stochastic and hybrid diagnosis. HyDE supports the use of multiple paradigms and is extensible to support new paradigms. HyDE generates candidate diagnoses and checks them for consistency with the observations. It uses hybrid models built by the users and sensor data from the system to deduce the state of the system over time, including changes in state indicative of faults. At each time step when observations are available, HyDE checks each existing candidate for continued consistency with the new observations. If the candidate is consistent, it continues to remain in the candidate set. If it is not consistent, then the information about the inconsistency is used to generate successor candidates while discarding the candidate that was inconsistent. The models used by HyDE are similar to simulation models. They describe the expected behavior of the system under nominal and fault conditions. The model can be constructed in modular and hierarchical fashion by building component/subsystem models (which may themselves contain component/ subsystem models) and linking them through shared variables/parameters. The
A hybrid approach to test-analysis-model development for large space structures
NASA Technical Reports Server (NTRS)
Kammer, D. C.
1991-01-01
The present FEM reduction method for the generation of test-analysis-models (TAMs) in test-analysis correlation addresses contentions that the current modal TAM is hypersensitive to differences between test model shapes and analysis mode shapes, thereby generating large off-diagonal terms within the orthogonality and cross-orthogonality matrices employed in test-analysis mode-shape correlation. A hybrid TAM methodology is accordingly developed which combines the exact representation of the FEM target modes from the modal TAM with the more accurate TAM representation of the residual modes; the superior residual dynamics representation of the hybrid TAM is demonstrated for a detailed representation of a large space structure.
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
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
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
NASA Astrophysics Data System (ADS)
Yeganeh, B.; Motlagh, M. Shafie Pour; Rashidi, Y.; Kamalan, H.
2012-08-01
Due to the health impacts caused by exposures to air pollutants in urban areas, monitoring and forecasting of air quality parameters have become popular as an important topic in atmospheric and environmental research today. The knowledge on the dynamics and complexity of air pollutants behavior has made artificial intelligence models as a useful tool for a more accurate pollutant concentration prediction. This paper focuses on an innovative method of daily air pollution prediction using combination of Support Vector Machine (SVM) as predictor and Partial Least Square (PLS) as a data selection tool based on the measured values of CO concentrations. The CO concentrations of Rey monitoring station in the south of Tehran, from Jan. 2007 to Feb. 2011, have been used to test the effectiveness of this method. The hourly CO concentrations have been predicted using the SVM and the hybrid PLS-SVM models. Similarly, daily CO concentrations have been predicted based on the aforementioned four years measured data. Results demonstrated that both models have good prediction ability; however the hybrid PLS-SVM has better accuracy. In the analysis presented in this paper, statistic estimators including relative mean errors, root mean squared errors and the mean absolute relative error have been employed to compare performances of the models. It has been concluded that the errors decrease after size reduction and coefficients of determination increase from 56 to 81% for SVM model to 65-85% for hybrid PLS-SVM model respectively. Also it was found that the hybrid PLS-SVM model required lower computational time than SVM model as expected, hence supporting the more accurate and faster prediction ability of hybrid PLS-SVM model.
Numerical modeling of lower hybrid heating and current drive
Valeo, E.J.; Eder, D.C.
1986-03-01
The generation of currents in toroidal plasma by application of waves in the lower hybrid frequency range involves the interplay of several physical phenomena which include: wave propagation in toroidal geometry, absorption via wave-particle resonances, the quasilinear generation of strongly nonequilibrium electron and ion distribution functions, and the self-consistent evolution of the current density in such a nonequilibrium plasma. We describe a code, LHMOD, which we have developed to treat these aspects of current drive and heating in tokamaks. We present results obtained by applying the code to a computation of current ramp-up and to an investigation of the possible importance of minority hydrogen absorption in a deuterium plasma as the ''density limit'' to current drive is approached.
Bifurcation analysis on a hybrid systems model of intermittent hormonal therapy for prostate cancer
NASA Astrophysics Data System (ADS)
Tanaka, Gouhei; Tsumoto, Kunichika; Tsuji, Shigeki; Aihara, Kazuyuki
2008-10-01
Hybrid systems are widely used to model dynamical phenomena that are characterized by interplay between continuous dynamics and discrete events. An example of biomedical application is modeling of disease progression of prostate cancer under intermittent hormonal therapy, where continuous tumor dynamics is switched by interruption and reinstitution of medication. In the present paper, we study a hybrid systems model representing intermittent androgen suppression (IAS) therapy for advanced prostate cancer. Intermittent medication with switching between on-treatment and off-treatment periods is intended to possibly prevent a prostatic tumor from developing into a hormone-refractory state and is anticipated as a possible strategy for delaying or hopefully averting a cancer relapse which most patients undergo as a result of long-term hormonal suppression. Clinical efficacy of IAS therapy for prostate cancer is still under investigation but at least worth considering in terms of reduction of side effects and economic costs during off-treatment periods. In the model of IAS therapy, it depends on some clinically controllable parameters whether a relapse of prostate cancer occurs or not. Therefore, we examine nonlinear dynamics and bifurcation structure of the model by exploiting a numerical method to clarify bifurcation sets in the hybrid system. Our results suggest that adjustment of the normal androgen level in combination with appropriate medication scheduling could enhance the possibility of relapse prevention. Moreover, a two-dimensional piecewise-linear system reduced from the original model highlights the origin of nonlinear phenomena specific to the hybrid system.
Modeling & power management of standalone PV-Wind Hybrid energy system for remote location
NASA Astrophysics Data System (ADS)
Shawon, M. J. A.
This thesis mainly focuses on a novel design of a standalone PV-Wind hybrid energy system for remote locations where grid extension is not feasible or is expensive. The Hybrid PV-Wind standalone energy system shows higher reliability compared to Wind or PV standalone systems as wind and solar are complementary. A Matlab/Simulink model of an integrated standalone PV-Wind hybrid system using a battery for storage and backup protection is presented. The individual component of the system is discussed and modeled. A novel and unique control strategy is designed and simulated to control the power flow of the system while maintaining the battery charging and discharging limit. In addition, different converter design and maximum power point tracking control are applied to ensure efficient and reliable power supply under various atmospheric and loading conditions.
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.
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.
Development of hybrid 3-D hydrological modeling for the NCAR Community Earth System Model (CESM)
Zeng, Xubin; Troch, Peter; Pelletier, Jon; Niu, Guo-Yue; Gochis, David
2015-11-15
This is the Final Report of our four-year (3-year plus one-year no cost extension) collaborative project between the University of Arizona (UA) and the National Center for Atmospheric Research (NCAR). The overall objective of our project is to develop and evaluate the first hybrid 3-D hydrological model with a horizontal grid spacing of 1 km for the NCAR Community Earth System Model (CESM). We have made substantial progress in model development and evaluation, computational efficiencies and software engineering, and data development and evaluation, as discussed in Sections 2-4. Section 5 presents our success in data dissemination, while Section 6 discusses the scientific impacts of our work. Section 7 discusses education and mentoring success of our project, while Section 8 lists our relevant DOE services. All peer-reviewed papers that acknowledged this project are listed in Section 9. Highlights of our achievements include: • We have finished 20 papers (most published already) on model development and evaluation, computational efficiencies and software engineering, and data development and evaluation • The global datasets developed under this project have been permanently archived and publicly available • Some of our research results have already been implemented in WRF and CLM • Patrick Broxton and Michael Brunke have received their Ph.D. • PI Zeng has served on DOE proposal review panels and DOE lab scientific focus area (SFA) review panels
Modeling of plasma and thermo-fluid transport in hybrid welding
NASA Astrophysics Data System (ADS)
Ribic, Brandon D.
Hybrid welding combines a laser beam and electrical arc in order to join metals within a single pass at welding speeds on the order of 1 m min -1. Neither autonomous laser nor arc welding can achieve the weld geometry obtained from hybrid welding for the same process parameters. Depending upon the process parameters, hybrid weld depth and width can each be on the order of 5 mm. The ability to produce a wide weld bead increases gap tolerance for square joints which can reduce machining costs and joint fitting difficulty. The weld geometry and fast welding speed of hybrid welding make it a good choice for application in ship, pipeline, and aerospace welding. Heat transfer and fluid flow influence weld metal mixing, cooling rates, and weld bead geometry. Cooling rate affects weld microstructure and subsequent weld mechanical properties. Fluid flow and heat transfer in the liquid weld pool are affected by laser and arc energy absorption. The laser and arc generate plasmas which can influence arc and laser energy absorption. Metal vapors introduced from the keyhole, a vapor filled cavity formed near the laser focal point, influence arc plasma light emission and energy absorption. However, hybrid welding plasma properties near the opening of the keyhole are not known nor is the influence of arc power and heat source separation understood. A sound understanding of these processes is important to consistently achieving sound weldments. By varying process parameters during welding, it is possible to better understand their influence on temperature profiles, weld metal mixing, cooling rates, and plasma properties. The current literature has shown that important process parameters for hybrid welding include: arc power, laser power, and heat source separation distance. However, their influence on weld temperatures, fluid flow, cooling rates, and plasma properties are not well understood. Modeling has shown to be a successful means of better understanding the influence of
Modeling and control of a hybrid-electric vehicle for drivability and fuel economy improvements
NASA Astrophysics Data System (ADS)
Koprubasi, Kerem
The gradual decline of oil reserves and the increasing demand for energy over the past decades has resulted in automotive manufacturers seeking alternative solutions to reduce the dependency on fossil-based fuels for transportation. A viable technology that enables significant improvements in the overall tank-to-wheel vehicle energy conversion efficiencies is the hybridization of electrical and conventional drive systems. Sophisticated hybrid powertrain configurations require careful coordination of the actuators and the onboard energy sources for optimum use of the energy saving benefits. The term optimality is often associated with fuel economy, although other measures such as drivability and exhaust emissions are also equally important. This dissertation focuses on the design of hybrid-electric vehicle (HEV) control strategies that aim to minimize fuel consumption while maintaining good vehicle drivability. In order to facilitate the design of controllers based on mathematical models of the HEV system, a dynamic model that is capable of predicting longitudinal vehicle responses in the low-to-mid frequency region (up to 10 Hz) is developed for a parallel HEV configuration. The model is validated using experimental data from various driving modes including electric only, engine only and hybrid. The high fidelity of the model makes it possible to accurately identify critical drivability issues such as time lags, shunt, shuffle, torque holes and hesitation. Using the information derived from the vehicle model, an energy management strategy is developed and implemented on a test vehicle. The resulting control strategy has a hybrid structure in the sense that the main mode of operation (the hybrid mode) is occasionally interrupted by event-based rules to enable the use of the engine start-stop function. The changes in the driveline dynamics during this transition further contribute to the hybrid nature of the system. To address the unique characteristics of the HEV
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
NASA Astrophysics Data System (ADS)
Deeter, M. N.; Evans, K. F.
1998-10-01
A novel radiative transfer model for a scattering layer in a plane-parallel thermally emitting atmosphere is described. The model is designed for computing radiances in iterative remote-sensing methods where computational efficiency is of utmost importance. The model combines a single-scatter method with the standard Eddington's second approximation technique, which is required for higher-order scattering. The single-scattering model uses tabulated scattering properties. The accuracy of the hybrid model, relative to an exact doubling-adding model, is compared with three other approximate methods (nonscattering, single-scattering, and Eddington). Brightness temperature errors for simulated ice and water clouds are shown for various particle size distributions in both microwave (1-50 cm-1) and infrared (300-3000 cm-1) parts of the spectrum. As indicated by a root-mean-square measure of brightness temperature error over outgoing directions, the hybrid model is a significant improvement over the standard Eddington model in the regions of the infrared where scattering is important. Computer source code (written in FORTRAN) for implementing the hybrid scattering model is available from the authors.
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.
Hybrid continuum-molecular modelling of multiscale internal gas flows
NASA Astrophysics Data System (ADS)
Patronis, Alexander; Lockerby, Duncan A.; Borg, Matthew K.; Reese, Jason M.
2013-12-01
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.
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.
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.
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 Design Perspective on the School-Work Boundary: A Hybrid Curriculum Model
ERIC Educational Resources Information Center
Zitter, Ilya; Hoeve, Aimée; de Bruijn, Elly
2016-01-01
This article proposes a model for the design of a hybrid VET curriculum across the school-work boundary. VET-curricula are designed on the basis of two main types of learning arrangements, namely, the plan for learning in school and for learning at the workplace. A challenge for curriculum development is creating consistency between different…
ERIC Educational Resources Information Center
Grable, John E.
2011-01-01
Innovation in doctoral degree program development and delivery provides an effective counterpoint to the expert-apprentice model established in the Middle Ages. The author outlines the importance of innovation in reaching adult learners and describes an innovative hybrid PhD program designed to allow aspiring doctoral adult-age students to pursue…
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.
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…
HYBRID SNCR-SCR TECHNOLOGIES FOR NOX CONTROL: MODELING AND EXPERIMENT
The hybrid process of homogeneous gas-phase selective non-catalytic reduction (SNCR) followed by selective catalytic reduction (SCR) of nitric oxide (NO) was investigated through experimentation and modeling. Measurements, using NO-doped flue gas from a gas-fired 29 kW test combu...
NASA Astrophysics Data System (ADS)
Shen, Yanfeng; Cesnik, Carlos E. S.
2016-09-01
This paper presents a new hybrid modeling technique for the efficient simulation of guided wave generation, propagation, and interaction with damage in complex composite structures. A local finite element model is deployed to capture the piezoelectric effects and actuation dynamics of the transmitter, while the global domain wave propagation and interaction with structural complexity (structure features and damage) are solved utilizing a local interaction simulation approach (LISA). This hybrid approach allows the accurate modeling of the local dynamics of the transducers and keeping the LISA formulation in an explicit format, which facilitates its readiness for parallel computing. The global LISA framework was extended through the 3D Kelvin–Voigt viscoelasticity theory to include anisotropic damping effects for composite structures, as an improvement over the existing LISA formulation. The global LISA framework was implemented using the compute unified device architecture running on graphic processing units. A commercial preprocessor is integrated seamlessly with the computational framework for grid generation and material property allocation to handle complex structures. The excitability and damping effects are successfully captured by this hybrid model, with experimental validation using the scanning laser doppler vibrometry. To demonstrate the capability of our hybrid approach for complex structures, guided wave propagation and interaction with a delamination in a composite panel with stiffeners is presented.
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.
Noise propagation in hybrid models of nonlinear systems: The Ginzburg–Landau equation
Taverniers, Søren; Alexander, Francis J.; Tartakovsky, Daniel M.
2014-04-01
Every physical phenomenon can be described by multiple models with varying degrees of fidelity. The computational cost of higher fidelity models (e.g., molecular dynamics simulations) is invariably higher than that of their lower fidelity counterparts (e.g., a continuum model based on differential equations). While the former might not be suitable for large-scale simulations, the latter are not universally valid. Hybrid algorithms provide a compromise between the computational efficiency of a coarse-scale model and the representational accuracy of a fine-scale description. This is achieved by conducting a fine-scale computation in subdomains where it is absolutely required (e.g., due to a local breakdown of a continuum model) and coupling it with a coarse-scale computation in the rest of a computational domain. We analyze the effects of random fluctuations generated by the fine-scale component of a nonlinear hybrid on the hybrid's overall accuracy and stability. Two variants of the time-dependent Ginzburg–Landau equation (GLE) and their discrete representations provided by a nearest-neighbor Ising model serve as a computational testbed. Our analysis shows that coupling these descriptions in a one-dimensional simulation leads to erroneous results. Adding a random source term to the GLE provides accurate prediction of the mean behavior of the quantity of interest (magnetization). It also allows the two GLE variants to correctly capture the strength of the microscale fluctuations. Our work demonstrates the importance of fine-scale noise in hybrid simulations, and suggests the need for replacing an otherwise deterministic coarse-scale component of the hybrid with its stochastic counterpart.
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.