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.
Hybrid quantum teleportation: A theoretical model
Takeda, Shuntaro; Mizuta, Takahiro; Fuwa, Maria; Yoshikawa, Jun-ichi; Yonezawa, Hidehiro; Furusawa, Akira
2014-12-04
Hybrid quantum teleportation – continuous-variable teleportation of qubits – is a promising approach for deterministically teleporting photonic qubits. We propose how to implement it with current technology. Our theoretical model shows that faithful qubit transfer can be achieved for this teleportation by choosing an optimal gain for the teleporter’s classical channel.
Dynamic modeling of lower hybrid current drive
Ignat, D.W.; Valeo, E.J.; Jardin, S.C.
1993-10-01
A computational model of lower hybrid current drive in the presence of an electric field is described and some results are given. Details of geometry, plasma profiles and circuit equations are treated carefully. Two-dimensional velocity space effects are approximated in a one-dimensional Fokker-Planck treatment.
Hybrid 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.
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.
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…
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}).
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.
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
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
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.
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.
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
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.
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.
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.
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.
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
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.
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.
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
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.
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.
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.
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
NASA Astrophysics Data System (ADS)
Fahimi, Farzad; Yaseen, Zaher Mundher; El-shafie, Ahmed
2016-02-01
Since the middle of the twentieth century, artificial intelligence (AI) models have been used widely in engineering and science problems. Water resource variable modeling and prediction are the most challenging issues in water engineering. Artificial neural network (ANN) is a common approach used to tackle this problem by using viable and efficient models. Numerous ANN models have been successfully developed to achieve more accurate results. In the current review, different ANN models in water resource applications and hydrological variable predictions are reviewed and outlined. In addition, recent hybrid models and their structures, input preprocessing, and optimization techniques are discussed and the results are compared with similar previous studies. Moreover, to achieve a comprehensive view of the literature, many articles that applied ANN models together with other techniques are included. Consequently, coupling procedure, model evaluation, and performance comparison of hybrid models with conventional ANN models are assessed, as well as, taxonomy and hybrid ANN models structures. Finally, current challenges and recommendations for future researches are indicated and new hybrid approaches are proposed.
Coarse-grained DNA modeling: Hybridization and ionic effects
NASA Astrophysics Data System (ADS)
Hinckley, Daniel M.
Deoxyribonucleic acid (DNA) is a biopolymer of enormous significance in living systems. The utility of DNA in such systems is derived from the programmable nature of DNA and its unique mechanical properties. Recently, material scientists have harnessed these properties in order to create systems that spontaneous self-assemble on the nanoscale. Both biologists and material scientists are hindered by an incomplete understanding of the physical interactions that together govern DNA's behavior. Computer simulations, especially those at the coarse-grained (CG) level, can potentially complete this understanding by resolving details indiscernible with current experimental techniques. In this thesis, we advance the state-of-the-art of DNA CG simulations by first reviewing the relevant theory and the evolution of CG DNA models since their inception. Then we present 3SPN.2, an improved CG model for DNA that should provide new insights into biological and nanotechnological systems which incorporate DNA. We perform forward flux sampling simulations in order to examine the effect of sequence, oligomer length, and ionic strength on DNA oligomer hybridization. Due to the limitations inherent in continuum treatments of electrostatic interactions in biological systems, we generate a CG model of biological ions for use with 3SPN.2 and other CG models. Lastly, we illustrate the potential of 3SPN.2 and CG ions by using the models in simulations of viral capsid packaging experiments. The models and results described in this thesis will be useful in future modeling efforts that seek to identify the fundamental physics that govern behavior such as nucleosome positioning, DNA hybridization, and DNA nanoassembly.
Efficient Vaccine Distribution Based on a Hybrid Compartmental Model
Yu, Zhiwen; Liu, Jiming; Wang, Xiaowei; Zhu, Xianjun; Wang, Daxing; Han, Guoqiang
2016-01-01
To effectively and efficiently reduce the morbidity and mortality that may be caused by outbreaks of emerging infectious diseases, it is very important for public health agencies to make informed decisions for controlling the spread of the disease. Such decisions must incorporate various kinds of intervention strategies, such as vaccinations, school closures and border restrictions. Recently, researchers have paid increased attention to searching for effective vaccine distribution strategies for reducing the effects of pandemic outbreaks when resources are limited. Most of the existing research work has been focused on how to design an effective age-structured epidemic model and to select a suitable vaccine distribution strategy to prevent the propagation of an infectious virus. Models that evaluate age structure effects are common, but models that additionally evaluate geographical effects are less common. In this paper, we propose a new SEIR (susceptible—exposed—infectious šC recovered) model, named the hybrid SEIR-V model (HSEIR-V), which considers not only the dynamics of infection prevalence in several age-specific host populations, but also seeks to characterize the dynamics by which a virus spreads in various geographic districts. Several vaccination strategies such as different kinds of vaccine coverage, different vaccine releasing times and different vaccine deployment methods are incorporated into the HSEIR-V compartmental model. We also design four hybrid vaccination distribution strategies (based on population size, contact pattern matrix, infection rate and infectious risk) for controlling the spread of viral infections. Based on data from the 2009–2010 H1N1 influenza epidemic, we evaluate the effectiveness of our proposed HSEIR-V model and study the effects of different types of human behaviour in responding to epidemics. PMID:27233015
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 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.
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
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
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.
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 ...
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
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
Modeling and simulation of a hybrid ship power system
NASA Astrophysics Data System (ADS)
Doktorcik, Christopher J.
2011-12-01
Optimizing the performance of naval ship power systems requires integrated design and coordination of the respective subsystems (sources, converters, and loads). A significant challenge in the system-level integration is solving the Power Management Control Problem (PMCP). The PMCP entails deciding on subsystem power usages for achieving a trade-off between the error in tracking a desired position/velocity profile, minimizing fuel consumption, and ensuring stable system operation, while at the same time meeting performance limitations of each subsystem. As such, the PMCP naturally arises at a supervisory level of a ship's operation. In this research, several critical steps toward the solution of the PMCP for surface ships have been undertaken. First, new behavioral models have been developed for gas turbine engines, wound rotor synchronous machines, DC super-capacitors, induction machines, and ship propulsion systems. Conventional models describe system inputs and outputs in terms of physical variables such as voltage, current, torque, and force. In contrast, the behavioral models developed herein express system inputs and outputs in terms of power whenever possible. Additionally, the models have been configured to form a hybrid system-level power model (HSPM) of a proposed ship electrical architecture. Lastly, several simulation studies have been completed to expose the capabilities and limitations of the HSPM.
Quasicycles in the stochastic hybrid Morris-Lecar neural model
NASA Astrophysics Data System (ADS)
Brooks, Heather A.; Bressloff, Paul C.
2015-07-01
Intrinsic noise arising from the stochastic opening and closing of voltage-gated ion channels has been shown experimentally and mathematically to have important effects on a neuron's function. Study of classical neuron models with stochastic ion channels is becoming increasingly important, especially in understanding a cell's ability to produce subthreshold oscillations and to respond to weak periodic stimuli. While it is known that stochastic models can produce oscillations (quasicycles) in parameter regimes where the corresponding deterministic model has only a stable fixed point, little analytical work has been done to explore these connections within the context of channel noise. Using a stochastic hybrid Morris-Lecar (ML) model, we combine a system-size expansion in K+ and a quasi-steady-state (QSS) approximation in persistent Na+ in order to derive an effective Langevin equation that preserves the low-dimensional (planar) structure of the underlying deterministic ML model. (The QSS analysis exploits the fact that persistent Na+ channels are fast.) By calculating the corresponding power spectrum, we determine analytically how noise significantly extends the parameter regime in which subthreshold oscillations occur.
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.
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
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).
A formal hybrid modeling scheme for handling discontinuities in physical system models
Mosterman, P.J.; Biswas, G.
1996-12-31
Physical systems are by nature continuous, but often exhibit nonlinearities that make behavior generation complex and hard to analyze. Complexity is often reduced by linearizing model constraints and by abstracting the time scale for behavior generation. In either case, the physical components are modeled to operate in multiple modes, with abrupt changes between modes. This paper discusses a hybrid modeling methodology and analysis algorithms that combine continuous energy flow modeling and localized discrete signal flow modeling to generate complex, multi-mode behavior in a consistent and correct manner. Energy phase space analysis is employed to demonstrate the correctness of the algorithm, and the reachability of a continuous mode.
Hybrid E-Learning Acceptance Model: Learner Perceptions
ERIC Educational Resources Information Center
Ahmed, Hassan M. Selim
2010-01-01
E-learning tools and technologies have been used to supplement conventional courses in higher education institutions creating a "hybrid" e-learning module that aims to enhance the learning experiences of students. Few studies have addressed the acceptance of hybrid e-learning by learners and the factors affecting the learners'…
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 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 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
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.
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
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
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 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
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…
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…
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
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
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
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
NASA Astrophysics Data System (ADS)
Zhang, Xiaoli; Peng, Yong; Zhang, Chi; Wang, Bende
2015-11-01
A number of hydrological studies have proven the superior prediction performance of hybrid models coupled with data preprocessing techniques. However, many studies first decompose the entire data series into components and later divide each component into calibration and validation datasets to establish models, which sends some amount of future information into the decomposition and reconstruction processes. As a consequence, the resulting components used to forecast the value of a particular moment are computed using information from future values, which are not available at that particular moment in a forecasting exercise. Since most papers don't present their model framework in detail, it is difficult to identify whether they are performing a real forecast or not. Even though several other papers have explicitly stated which experiment they are performing, a comparison between results in the hindcast and forecast experiments is still missing. Therefore, it is necessary to investigate and compare the performance of these hybrid models in the two experiments in order to estimate whether they are suitable for real forecasting. With the combination of three preprocessing techniques, such as wavelet analysis (WA), empirical mode decomposition (EMD) and singular spectrum analysis (SSA), and two modeling methods (i.e. ANN model and ARMA model), six hybrid models are developed in this study, including WA-ANN, WA-ARMA, EMD-ANN, EMD-ARMA, SSA-ANN and SSA-ARMA. Preprocessing techniques are used to decompose the data series into sub-series, and then these sub-series are modeled using ANN and ARMA models. These models are examined in hindcasting and forecasting of the monthly streamflow of two sites in the Yangtze River of China. The results of this study indicate that the six hybrid models perform better in the hindcast experiment compared with the original ANN and ARMA models, while the hybrid models in the forecast experiment perform worse than the original models and the
A Hybrid Approach for Efficient Modeling of Medium-Frequency Propagation in Coal Mines
Brocker, Donovan E.; Sieber, Peter E.; Waynert, Joseph A.; Li, Jingcheng; Werner, Pingjuan L.; Werner, Douglas H.
2015-01-01
An efficient procedure for modeling medium frequency (MF) communications in coal mines is introduced. In particular, a hybrid approach is formulated and demonstrated utilizing ideal transmission line equations to model MF propagation in combination with full-wave sections used for accurate simulation of local antenna-line coupling and other near-field effects. This work confirms that the hybrid method accurately models signal propagation from a source to a load for various system geometries and material compositions, while significantly reducing computation time. With such dramatic improvement to solution times, it becomes feasible to perform large-scale optimizations with the primary motivation of improving communications in coal mines both for daily operations and emergency response. Furthermore, it is demonstrated that the hybrid approach is suitable for modeling and optimizing large communication networks in coal mines that may otherwise be intractable to simulate using traditional full-wave techniques such as moment methods or finite-element analysis. PMID:26478686
NASA Technical Reports Server (NTRS)
Hadden, 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.
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
Modeling hydraulic regenerative hybrid vehicles using AMESim and Matlab/Simulink
NASA Astrophysics Data System (ADS)
Lynn, Alfred; Smid, Edzko; Eshraghi, Moji; Caldwell, Niall; Woody, Dan
2005-05-01
This paper presents the overview of the simulation modeling of a hydraulic system with regenerative braking used to improve vehicle emissions and fuel economy. Two simulation software packages were used together to enhance the simulation capability for fuel economy results and development of vehicle and hybrid control strategy. AMESim, a hydraulic simulation software package modeled the complex hydraulic circuit and component hardware and was interlinked with a Matlab/Simulink model of the vehicle, engine and the control strategy required to operate the vehicle and the hydraulic hybrid system through various North American and European drive cycles.
A research using hybrid RBF/Elman neural networks for intrusion detection system secure model
NASA Astrophysics Data System (ADS)
Tong, Xiaojun; Wang, Zhu; Yu, Haining
2009-10-01
A hybrid RBF/Elman neural network model that can be employed for both anomaly detection and misuse detection is presented in this paper. The IDSs using the hybrid neural network can detect temporally dispersed and collaborative attacks effectively because of its memory of past events. The RBF network is employed as a real-time pattern classification and the Elman network is employed to restore the memory of past events. The IDSs using the hybrid neural network are evaluated against the intrusion detection evaluation data sponsored by U.S. Defense Advanced Research Projects Agency (DARPA). Experimental results are presented in ROC curves. Experiments show that the IDSs using this hybrid neural network improve the detection rate and decrease the false positive rate effectively.
A hybrid 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 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 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-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
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.
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.
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…
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…
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.
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
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
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
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
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
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.
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
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.
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…
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.
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.
A zero-equation turbulence model for two-dimensional hybrid Hall thruster simulations
Cappelli, Mark A. Young, Christopher V.; Cha, Eunsun; Fernandez, Eduardo
2015-11-15
We present a model for electron transport across the magnetic field of a Hall thruster and integrate this model into 2-D hybrid particle-in-cell simulations. The model is based on a simple scaling of the turbulent electron energy dissipation rate and the assumption that this dissipation results in Ohmic heating. Implementing the model into 2-D hybrid simulations is straightforward and leverages the existing framework for solving the electron fluid equations. The model recovers the axial variation in the mobility seen in experiments, predicting the generation of a transport barrier which anchors the region of plasma acceleration. The predicted xenon neutral and ion velocities are found to be in good agreement with laser-induced fluorescence measurements.
A zero-equation turbulence model for two-dimensional hybrid Hall thruster simulations
NASA Astrophysics Data System (ADS)
Cappelli, Mark A.; Young, Christopher V.; Cha, Eunsun; Fernandez, Eduardo
2015-11-01
We present a model for electron transport across the magnetic field of a Hall thruster and integrate this model into 2-D hybrid particle-in-cell simulations. The model is based on a simple scaling of the turbulent electron energy dissipation rate and the assumption that this dissipation results in Ohmic heating. Implementing the model into 2-D hybrid simulations is straightforward and leverages the existing framework for solving the electron fluid equations. The model recovers the axial variation in the mobility seen in experiments, predicting the generation of a transport barrier which anchors the region of plasma acceleration. The predicted xenon neutral and ion velocities are found to be in good agreement with laser-induced fluorescence measurements.
Zhu, Wen; Li, Meng
2014-01-01
A series of zwitterionic hybrid membranes were prepared via the ring opening of 1,3-propanesultone with the amine groups in the chains of TMSPEDA and a subsequent sol-gel process. Their kinetic models for strontium removal were investigated using three two-parameter kinetic equations (i.e., Lagergren pseudo-first order, pseudo-second order, and Elovich models). Adsorption mechanism was evaluated using intraparticle diffusion model, diffusion-chemisorption model, and Boyd equation. It was found that the adsorption of strontium ions on these zwitterionic hybrid membranes fitted well with the Lagergren pseudo-second order model. Mechanism insights suggested that diffusion-chemisorption was one of the main adsorption mechanisms. Boyd equation exhibited that film-diffusion mechanism might be the control process during the starting period. These findings are very useful in strontium removal from the stimulated radioactive wastewater. PMID:25405224
Elsheikh, Ahmed H.; Wheeler, Mary F.; Hoteit, Ibrahim
2014-02-01
A Hybrid Nested Sampling (HNS) algorithm is proposed for efficient Bayesian model calibration and prior model selection. The proposed algorithm combines, Nested Sampling (NS) algorithm, Hybrid Monte Carlo (HMC) sampling and gradient estimation using Stochastic Ensemble Method (SEM). NS is an efficient sampling algorithm that can be used for Bayesian calibration and estimating the Bayesian evidence for prior model selection. Nested sampling has the advantage of computational feasibility. Within the nested sampling algorithm, a constrained sampling step is performed. For this step, we utilize HMC to reduce the correlation between successive sampled states. HMC relies on the gradient of the logarithm of the posterior distribution, which we estimate using a stochastic ensemble method based on an ensemble of directional derivatives. SEM only requires forward model runs and the simulator is then used as a black box and no adjoint code is needed. The developed HNS algorithm is successfully applied for Bayesian calibration and prior model selection of several nonlinear subsurface flow problems.
Rhombic micro-displacement amplifier for piezoelectric actuator and its linear and hybrid model
NASA Astrophysics Data System (ADS)
Chen, Jinglong; Zhang, Chunlin; Xu, Minglong; Zi, Yanyang; Zhang, Xinong
2015-01-01
This paper proposes rhombic micro-displacement amplifier (RMDA) for piezoelectric actuator (PA). First, the geometric amplification relations are analyzed and linear model is built to analyze the mechanical and electrical properties of this amplifier. Next, the accurate modeling method of amplifier is studied for important application of precise servo control. The classical Preisach model (CPM) is generally implemented using a numerical technique based on the first-order reversal curves (FORCs). The accuracy of CPM mainly depends on the number of FORCs. However, it is generally difficult to achieve enough number of FORCs in practice. So, Support Vector Machine (SVM) is employed in the work to circumvent the deficiency of the CPM. Then the hybrid model, which is based on discrete CPM and SVM is developed to account for hysteresis and dynamic effects. Finally, experimental validation is carried out. The analyzed result shows that this amplifier with the hybrid model is suitable for control application.
Shaik, Fahimuddin; Sharma, Anil Kumar; Ahmed, Syed Musthak
2016-01-01
At present image processing methods hold a noteworthy position in unravelling various medical imaging challenges. The high risk disorders such as diabetic cardiomyopathy and diabetic retinopathy are considered as applications for proposed method. The dictum of this paper is on observing enhancement and segmentation of the cross sectional view of a blood capillary of a right coronary artery image of a diabetic patient and also retinal images. A hybrid model using hybrid morphological reconstruction technique as pre-processing with watershed segmentation method as post-processing is developed in this work. PMID:27186471
Hybrid model for long-term prediction of the ionospheric global TEC
NASA Astrophysics Data System (ADS)
Andonov, Borislav; Mukhtarov, Plamen; Pancheva, Dora
2014-05-01
A new hybrid model for long-term prediction of the global TEC was developed. It is based on the global empirical background TEC model constructed by Mukhtarov et al. (2013a,b) and the availability of regularly arriving fresh CODE TEC data. The cornerstone of the hybrid model consists of applying the method of autocorrelation prediction of the error and the respective correction of the background model with the predicted error. An important question is how the efficiency of the correction procedure depends on the given offset, i.e. the time distance between the dates for which the prediction is made to that with real data. It was found that the correction is really effective if the error prediction is made for a date with a distance up to 60 days from the date with real data. Then the RMSE decreases from 3.2 TECU (for the global background TEC model) to 2.76 TECU (for the hybrid model) which demonstrates the advantage of the presented in this paper hybrid model for long-term prediction with respect to the originally built background TEC model. REFERENCES Mukhtarov, P., Pancheva, D., Andonov, B., Pashova, L. Global TEC maps based on GNSS data: 1. Empirical background TEC model. J. Geophys. Res., 118, 4609-4617, doi:10.1002/jgra.50413, 2013a. Mukhtarov, P., Pancheva, D., Andonov, B., Pashova, L. Global TEC maps based on GNSS data: 2. Model evaluation. J. Geophys. Res., 118, 4594-4608, doi:10.1002/jgra.50412, 2013b.
Quilodrán, Claudio S; Currat, Mathias; Montoya-Burgos, Juan I
2014-01-01
Interspecific hybridization is common in nature but can be increased in frequency or even originated by human actions, such as species introduction or habitat modification, which may threaten species persistence. When hybridization occurs between distantly related species, referred to as "distant hybridization," the resulting hybrids are generally infertile or fertile but do not undergo chromosomal recombination during gametogenesis. Here, we present a model describing this frequent but poorly studied interspecific hybridization to assess its consequences on parental species and to anticipate the conditions under which they can reach extinction. Our general model fully incorporates three important processes: density-dependent competition, dominance/recessivity inheritance of traits and assortative mating. We demonstrate its use and flexibility by assessing population extinction risk between Atlantic salmon and brown trout in Norway, whose interbreeding has recently increased due to farmed fish releases into the wild. We identified the set of conditions under which hybridization may threaten salmonid species. Thanks to the flexibility of our model, we evaluated the effect of an additional risk factor, a parasitic disease, and showed that the cumulative effects dramatically increase the extinction risk. The consequences of distant hybridization are not genetically, but demographically mediated. Our general model is useful to better comprehend the evolution of such hybrid systems and we demonstrated its importance in the field of conservation biology to set up management recommendations when this increasingly frequent type of hybridization is in action. PMID:25003336
Quilodrán, Claudio S.; Currat, Mathias; Montoya-Burgos, Juan I.
2014-01-01
Interspecific hybridization is common in nature but can be increased in frequency or even originated by human actions, such as species introduction or habitat modification, which may threaten species persistence. When hybridization occurs between distantly related species, referred to as “distant hybridization,” the resulting hybrids are generally infertile or fertile but do not undergo chromosomal recombination during gametogenesis. Here, we present a model describing this frequent but poorly studied interspecific hybridization to assess its consequences on parental species and to anticipate the conditions under which they can reach extinction. Our general model fully incorporates three important processes: density-dependent competition, dominance/recessivity inheritance of traits and assortative mating. We demonstrate its use and flexibility by assessing population extinction risk between Atlantic salmon and brown trout in Norway, whose interbreeding has recently increased due to farmed fish releases into the wild. We identified the set of conditions under which hybridization may threaten salmonid species. Thanks to the flexibility of our model, we evaluated the effect of an additional risk factor, a parasitic disease, and showed that the cumulative effects dramatically increase the extinction risk. The consequences of distant hybridization are not genetically, but demographically mediated. Our general model is useful to better comprehend the evolution of such hybrid systems and we demonstrated its importance in the field of conservation biology to set up management recommendations when this increasingly frequent type of hybridization is in action. PMID:25003336
Modelling grain-scattered ultrasound in austenitic stainless-steel welds: A hybrid model
Nowers, O.; Duxbury, D. J.; Velichko, A.; Drinkwater, B. W.
2015-03-31
The ultrasonic inspection of austenitic stainless steel welds can be challenging due to their coarse grain structure, charaterised by preferentially oriented, elongated grains. The anisotropy of the weld is manifested as both a ‘steering’ of the beam and the back-scatter of energy due to the macroscopic granular structure of the weld. However, the influence of weld properties, such as mean grain size and orientation distribution, on the magnitude of scattered ultrasound is not well understood. A hybrid model has been developed to allow the study of grain-scatter effects in austenitic welds. An efficient 2D Finite Element (FE) method is used to calculate the complete scattering response from a single elliptical austenitic grain of arbitrary length and width as a function of the specific inspection frequency. A grain allocation model of the weld is presented to approximate the characteristic structures observed in austenitic welds and the complete scattering behaviour of each grain calculated. This model is incorporated into a semi-analytical framework for a single-element inspection of a typical weld in immersion. Experimental validation evidence is demonstrated indicating excellent qualitative agreement of SNR as a function of frequency and a minimum SNR difference of 2 dB at a centre frequency of 2.25 MHz. Additionally, an example Monte-Carlo study is presented detailing the variation of SNR as a function of the anisotropy distribution of the weld, and the application of confidence analysis to inform inspection development.
Modelling grain-scattered ultrasound in austenitic stainless-steel welds: A hybrid model
NASA Astrophysics Data System (ADS)
Nowers, O.; Duxbury, D. J.; Velichko, A.; Drinkwater, B. W.
2015-03-01
The ultrasonic inspection of austenitic stainless steel welds can be challenging due to their coarse grain structure, charaterised by preferentially oriented, elongated grains. The anisotropy of the weld is manifested as both a `steering' of the beam and the back-scatter of energy due to the macroscopic granular structure of the weld. However, the influence of weld properties, such as mean grain size and orientation distribution, on the magnitude of scattered ultrasound is not well understood. A hybrid model has been developed to allow the study of grain-scatter effects in austenitic welds. An efficient 2D Finite Element (FE) method is used to calculate the complete scattering response from a single elliptical austenitic grain of arbitrary length and width as a function of the specific inspection frequency. A grain allocation model of the weld is presented to approximate the characteristic structures observed in austenitic welds and the complete scattering behaviour of each grain calculated. This model is incorporated into a semi-analytical framework for a single-element inspection of a typical weld in immersion. Experimental validation evidence is demonstrated indicating excellent qualitative agreement of SNR as a function of frequency and a minimum SNR difference of 2 dB at a centre frequency of 2.25 MHz. Additionally, an example Monte-Carlo study is presented detailing the variation of SNR as a function of the anisotropy distribution of the weld, and the application of confidence analysis to inform inspection development.
A hybrid finite-difference and analytic element groundwater model.
Haitjema, H M; Feinstein, D T; Hunt, R J; Gusyev, M A
2010-01-01
Regional finite-difference models tend to have large cell sizes, often on the order of 1-2 km on a side. Although the regional flow patterns in deeper formations may be adequately represented by such a model, the intricate surface water and groundwater interactions in the shallower layers are not. Several stream reaches and nearby wells may occur in a single cell, precluding any meaningful modeling of the surface water and groundwater interactions between the individual features. We propose to replace the upper MODFLOW layer or layers, in which the surface water and groundwater interactions occur, by an analytic element model (GFLOW) that does not employ a model grid; instead, it represents wells and surface waters directly by the use of point-sinks and line-sinks. For many practical cases it suffices to provide GFLOW with the vertical leakage rates calculated in the original coarse MODFLOW model in order to obtain a good representation of surface water and groundwater interactions. However, when the combined transmissivities in the deeper (MODFLOW) layers dominate, the accuracy of the GFLOW solution diminishes. For those cases, an iterative coupling procedure, whereby the leakages between the GFLOW and MODFLOW model are updated, appreciably improves the overall solution, albeit at considerable computational cost. The coupled GFLOW-MODFLOW model is applicable to relatively large areas, in many cases to the entire model domain, thus forming an attractive alternative to local grid refinement or inset models. PMID:20132324
NASA Astrophysics Data System (ADS)
Smith, Wilford; Nunez, Patrick
2005-05-01
This paper describes the work being performed under the RDECOM Power and Energy (P&E) program (formerly the Combat Hybrid Power System (CHPS) program) developing hybrid power system models and integrating them into larger simulations, such as OneSAF, that can be used to find duty cycles to feed designers of hybrid power systems. This paper also describes efforts underway to link the TARDEC P&E System Integration Lab (SIL) in San Jose CA to the TARDEC Ground Vehicle Simulation Lab (GVSL) in Warren, MI. This linkage is being performed to provide a methodology for generating detailed driver profiles for use in the development of vignettes and mission profiles for system design excursions.
Bootstrap data methodology for sequential hybrid model building
NASA Technical Reports Server (NTRS)
Volponi, Allan J. (Inventor); Brotherton, Thomas (Inventor)
2007-01-01
A method for modeling engine operation comprising the steps of: 1. collecting a first plurality of sensory data, 2. partitioning a flight envelope into a plurality of sub-regions, 3. assigning the first plurality of sensory data into the plurality of sub-regions, 4. generating an empirical model of at least one of the plurality of sub-regions, 5. generating a statistical summary model for at least one of the plurality of sub-regions, 6. collecting an additional plurality of sensory data, 7. partitioning the second plurality of sensory data into the plurality of sub-regions, 8. generating a plurality of pseudo-data using the empirical model, and 9. concatenating the plurality of pseudo-data and the additional plurality of sensory data to generate an updated empirical model and an updated statistical summary model for at least one of the plurality of sub-regions.
Rainfall-runoff modeling through hybrid intelligent system
NASA Astrophysics Data System (ADS)
Nayak, P. C.; Sudheer, K. P.; Jain, S. K.
2007-07-01
This study explores the potential of integrating two different artificial intelligence techniques, namely neural network and fuzzy logic, effectively to model the rainfall-runoff process from rainfall and runoff information. The integration is achieved through representing fuzzy system computations in a generic artificial neural network (ANN) architecture, which is functionally equivalent to a fuzzy inference system. The model is initialized by a hyperellipsoidal fuzzy clustering (HEC) procedure, which identifies suitable numbers of fuzzy if-then rules through proper partition of the input space. The parameters of the membership functions are optimized using a nonlinear optimization procedure. The consequent functions are chosen to be linear in their parameters, and a standard least squares error method is employed for parameter estimation. The proposed model is tested on two case studies: Narmada basin in India and Kentucky basin in the United States. The results are highly encouraging as the model is able to explain more than 92% of the variance. The performance of the proposed model is found to be comparable to that of an adaptive neural based fuzzy inference system (ANFIS) developed for both the basins. The number of parameters in the proposed model is fewer compared to ANFIS, and the former can be trained in lesser time. It is also observed that the proposed model simulates the peak flow better than ANFIS. Overall, the study suggests that the proposed model can potentially be a viable alternative to ANFIS for use as an operational tool for rainfall runoff modeling purposes.
Data-driven components in a model of inner-shelf sorted bedforms: a new hybrid model
NASA Astrophysics Data System (ADS)
Goldstein, E. B.; Coco, G.; Murray, A. B.; Green, M. O.
2014-01-01
Numerical models rely on the parameterization of processes that often lack a deterministic description. In this contribution we demonstrate the applicability of using machine learning, a class of optimization tools from the discipline of computer science, to develop parameterizations when extensive data sets exist. We develop a new predictor for near-bed suspended sediment reference concentration under unbroken waves using genetic programming, a machine learning technique. We demonstrate that this newly developed parameterization performs as well or better than existing empirical predictors, depending on the chosen error metric. We add this new predictor into an established model for inner-shelf sorted bedforms. Additionally we incorporate a previously reported machine-learning-derived predictor for oscillatory flow ripples into the sorted bedform model. This new "hybrid" sorted bedform model, whereby machine learning components are integrated into a numerical model, demonstrates a method of incorporating observational data (filtered through a machine learning algorithm) directly into a numerical model. Results suggest that the new hybrid model is able to capture dynamics previously absent from the model - specifically, two observed pattern modes of sorted bedforms. Lastly we discuss the challenge of integrating data-driven components into morphodynamic models and the future of hybrid modeling.
A hybrid deep neural network and physically based distributed model for river stage prediction
NASA Astrophysics Data System (ADS)
hitokoto, Masayuki; sakuraba, Masaaki
2016-04-01
We developed the real-time river stage prediction model, using the hybrid deep neural network and physically based distributed model. As the basic model, 4 layer feed-forward artificial neural network (ANN) was used. As a network training method, the deep learning technique was applied. To optimize the network weight, the stochastic gradient descent method based on the back propagation method was used. As a pre-training method, the denoising autoencoder was used. Input of the ANN model is hourly change of water level and hourly rainfall, output data is water level of downstream station. In general, the desirable input of the ANN has strong correlation with the output. In conceptual hydrological model such as tank model and storage-function model, river discharge is governed by the catchment storage. Therefore, the change of the catchment storage, downstream discharge subtracted from rainfall, can be the potent input candidate of the ANN model instead of rainfall. From this point of view, the hybrid deep neural network and physically based distributed model was developed. The prediction procedure of the hybrid model is as follows; first, downstream discharge was calculated by the distributed model, and then estimates the hourly change of catchment storage form rainfall and calculated discharge as the input of the ANN model, and finally the ANN model was calculated. In the training phase, hourly change of catchment storage can be calculated by the observed rainfall and discharge data. The developed model was applied to the one catchment of the OOYODO River, one of the first-grade river in Japan. The modeled catchment is 695 square km. For the training data, 5 water level gauging station and 14 rain-gauge station in the catchment was used. The training floods, superior 24 events, were selected during the period of 2005-2014. Prediction was made up to 6 hours, and 6 models were developed for each prediction time. To set the proper learning parameters and network
Enhanced hybrid search algorithm for protein structure prediction using the 3D-HP lattice model.
Zhou, Changjun; Hou, Caixia; Zhang, Qiang; Wei, Xiaopeng
2013-09-01
The problem of protein structure prediction in the hydrophobic-polar (HP) lattice model is the prediction of protein tertiary structure. This problem is usually referred to as the protein folding problem. This paper presents a method for the application of an enhanced hybrid search algorithm to the problem of protein folding prediction, using the three dimensional (3D) HP lattice model. The enhanced hybrid search algorithm is a combination of the particle swarm optimizer (PSO) and tabu search (TS) algorithms. Since the PSO algorithm entraps local minimum in later evolution extremely easily, we combined PSO with the TS algorithm, which has properties of global optimization. Since the technologies of crossover and mutation are applied many times to PSO and TS algorithms, so enhanced hybrid search algorithm is called the MCMPSO-TS (multiple crossover and mutation PSO-TS) algorithm. Experimental results show that the MCMPSO-TS algorithm can find the best solutions so far for the listed benchmarks, which will help comparison with any future paper approach. Moreover, real protein sequences and Fibonacci sequences are verified in the 3D HP lattice model for the first time. Compared with the previous evolutionary algorithms, the new hybrid search algorithm is novel, and can be used effectively to predict 3D protein folding structure. With continuous development and changes in amino acids sequences, the new algorithm will also make a contribution to the study of new protein sequences. PMID:23824509
Diagnosis and Modeling of the Lower Hybrid Wave Injection on MST
NASA Astrophysics Data System (ADS)
Burke, David; Goetz, John; Kaufman, Michael; Almagri, Abdulgader; Anderson, Jay; Prager, Stewart; Carlsson, Johan
2007-11-01
RF current drive is predicted to reduce tearing fluctuations in reversed field pinches. Lower hybrid experiments with coupled power up to 125 kW have been undertaken on the Madison Symmetric Torus. The lower hybrid antenna exhibits good coupling under a variety of plasma conditions. Experimental studies have been undertaken to determine the optimal conditions for antenna operation. Additionally, an effort is underway to model plasma loading and launch spectrum using AORSA and RANT. Thirteen CdZnTe detectors are used in conjunction with a 16-channel CdZnTe camera in order to diagnose lower hybrid discharges. X-rays with energies over 60 keV are detected during such discharges. This x-ray emission is observed to be toroidally localized to the area within 60^o of the lower hybrid antenna. The spectrum also shows a dependence on launch direction. In order to expand our understanding of these results, several different plasmas have been modeled with GENRAY and CQL3D. Experimental results with source power up to 200 kW and current modeling results will be presented.
Time-dependent Mott transition in the periodic Anderson model with nonlocal hybridization
NASA Astrophysics Data System (ADS)
Hofmann, Felix; Potthoff, Michael
2016-08-01
The time-dependent Mott transition in a periodic Anderson model with off-site, nearest-neighbor hybridization is studied within the framework of nonequilibrium self-energy functional theory. Using the two-site dynamical-impurity approximation, we compute the real-time dynamics of the optimal variational parameter and of different observables initiated by sudden quenches of the Hubbard-U and identify the critical interaction. The time-dependent transition is orbital selective, i.e., in the final state, reached in the long-time limit after the quench to the critical interaction, the Mott gap opens in the spectral function of the localized orbitals only. We discuss the dependence of the critical interaction and of the final-state effective temperature on the hybridization strength and point out the various similarities between the nonequilibrium and the equilibrium Mott transition. It is shown that these can also be smoothly connected to each other by increasing the duration of a U-ramp from a sudden quench to a quasi-static process. The physics found for the model with off-site hybridization is compared with the dynamical Mott transition in the single-orbital Hubbard model and with the dynamical crossover found for the real-time dynamics of the conventional Anderson lattice with on-site hybridization.
Application of Equilibrium Models of Solution Hybridization to Microarray Design and Analysis
Gharaibeh, Raad Z.; Newton, Joshua M.; Weller, Jennifer W.; Gibas, Cynthia J.
2010-01-01
Background The probe percent bound value, calculated using multi-state equilibrium models of solution hybridization, is shown to be useful in understanding the hybridization behavior of microarray probes having 50 nucleotides, with and without mismatches. These longer oligonucleotides are in widespread use on microarrays, but there are few controlled studies of their interactions with mismatched targets compared to 25-mer based platforms. Principal Findings 50-mer oligonucleotides with centrally placed single, double and triple mismatches were spotted on an array. Over a range of target concentrations it was possible to discriminate binding to perfect matches and mismatches, and the type of mismatch could be predicted accurately in the concentration midrange (100 pM to 200 pM) using solution hybridization modeling methods. These results have implications for microarray design, optimization and analysis methods. Conclusions Our results highlight the importance of incorporating biophysical factors in both the design and the analysis of microarrays. Use of the probe “percent bound” value predicted by equilibrium models of hybridization is confirmed to be important for predicting and interpreting the behavior of long oligonucleotide arrays, as has been shown for short oligonucleotide arrays. PMID:20548788
NASA Astrophysics Data System (ADS)
Cardelli, E.; Faba, A.; Laudani, A.; Lozito, G. M.; Riganti Fulginei, F.; Salvini, A.
2016-04-01
This paper presents a hybrid neural network approach to model magnetic hysteresis at macro-magnetic scale. That approach aims to be coupled together with numerical treatments of magnetic hysteresis such as FEM numerical solvers of the Maxwell's equations in time domain, as in case of the non-linear dynamic analysis of electrical machines, and other similar devices, allowing a complete computer simulation with acceptable run times. The proposed Hybrid Neural System consists of four inputs representing the magnetic induction and magnetic field components at each time step and it is trained by 2D and scalar measurements performed on the magnetic material to be modeled. The magnetic induction B is assumed as entry point and the output of the Hybrid Neural System returns the predicted value of the field H at the same time step. Within the Hybrid Neural System, a suitably trained neural network is used for predicting the hysteretic behavior of the material to be modeled. Validations with experimental tests and simulations for symmetric, non-symmetric and minor loops are presented.
Coupled equilibrium model of hybridization error for the DNA microarray and tag-antitag systems.
Rose, John A; Deaton, Russell J; Hagiya, Masami; Suyama, Akira
2007-03-01
In this work, a detailed coupled equilibrium model is presented for predicting the ensemble average probability of hybridization error per chip-hybridized input strand, providing the first ensemble average method for estimating postannealing microarray/TAT system error rates. Following a detailed presentation of the model and implementation via the software package NucleicPark, under a mismatched statistical zipper model of duplex formation, error response is simulated for both mean-energy and randomly encoded TAT systems versus temperature and input concentration. Limiting expressions and simulated model behavior indicate the occurrence of a transition in hybridization error response, from a logarithmically convex function of temperature for excess inputs (high-error behavior), to a monotonic, log-linear function of temperature for dilute inputs (low-error behavior), a novel result unpredicted by uncoupled equilibrium models. Model scaling behavior for random encodings is investigated versus system size and strand-length. Application of the model to TAT system design is also undertaken, via the in silico evolution of a high-fidelity 100-strand TAT system, with an error response improved by nine standard deviations over the performance of the mean random encoding. PMID:17393846
A hybrid model of the CO2 geochemical cycle and its application to large impact events
NASA Technical Reports Server (NTRS)
Kasting, J. F.; Pollack, J. B.; Toon, O. B.; Richardson, S. M.
1986-01-01
The effects of a large asteriod or comet impact on modern and ancient marine biospheres are analyzed. A hybrid model of the carbonate-silicate geochemical cycle, which is capable of calculating the concentrations of carbon dioxide in the atmosphere, ocean, and sedimentary rocks, is described. The differences between the Keir and Berger (1983) model and the hybrid model are discussed. Equilibrium solutions are derived for the preindustrial atmosphere/ocean system and for a system similar to that of the late Cretaceous Period. The model data reveal that globl darkening caused by a stratospheric dust veil could destroy the existing phytoplankton within a period of several weeks or months, nd the dissolution of atmospheric NO(x) compounds would lower the pH of ocean surface waters and release CO2 into the atmosphere. It is noted that the surface temperatures could be increased by several degrees and surface oceans would be uninhabitable for calcaerous organisms for approximately 20 years.
A linear dispersion relation for the hybrid kinetic-ion/fluid-electron model of plasma physics
NASA Astrophysics Data System (ADS)
Told, D.; Cookmeyer, J.; Astfalk, P.; Jenko, F.
2016-07-01
A dispersion relation for a commonly used hybrid model of plasma physics is developed, which combines fully kinetic ions and a massless-electron fluid description. Although this model and variations of it have been used to describe plasma phenomena for about 40 years, to date there exists no general dispersion relation to describe the linear wave physics contained in the model. Previous efforts along these lines are extended here to retain arbitrary wave propagation angles, temperature anisotropy effects, as well as additional terms in the generalized Ohm’s law which determines the electric field. A numerical solver for the dispersion relation is developed, and linear wave physics is benchmarked against solutions of a full Vlasov–Maxwell dispersion relation solver. This work opens the door to a more accurate interpretation of existing and future wave and turbulence simulations using this type of hybrid model.
Two-field axion-monodromy hybrid inflation model: Dante's Waterfall
NASA Astrophysics Data System (ADS)
Carone, Christopher D.; Erlich, Joshua; Sensharma, Anuraag; Wang, Zhen
2015-02-01
We describe a hybrid axion-monodromy inflation model motivated by the Dante's Inferno scenario. In Dante's Inferno, a two-field potential features a stable trench along which a linear combination of the two fields slowly rolls, rendering the dynamics essentially identical to that of single-field chaotic inflation. A shift symmetry allows for the Lyth bound to be effectively evaded as in other axion-monodromy models. In our proposal, the potential is concave downward near the origin and the inflaton trajectory is a gradual downward spiral, ending at a point where the trench becomes unstable. There, the fields begin falling rapidly towards the minimum of the potential and inflation terminates as in a hybrid model. We find parameter choices that reproduce observed features of the cosmic microwave background, and discuss our model in light of recent results from the BICEP2 and Planck experiments.
Action recognition using spatiotemporal features and hybrid generative/discriminative models
NASA Astrophysics Data System (ADS)
Liu, Jia; Yang, Jie
2012-04-01
We propose a new method for human action recognition based on multiple features and a hybrid generative/discriminative model. Specifically, we propose a new action representation based on computing a rich set of descriptors from Affine-SIFT key point trajectories. A new hybrid generative/discriminative approach based on support vector machine and topic model is proposed using Fisher kernel method for action recognition. Fisher score for the topic model is evaluated by the variational inference algorithm. To obtain efficient and compact representations for actions, we develop a feature fusion method to combine spatial-temporal local motion descriptors and demonstrate how this kernel framework can be used to combine different types of features and models into a single classifier. Our experiments, conducted on a number of popular datasets, show performance improvements over the corresponding generative approach and are competitive with the best results reported in the literature.
Accurate modeling of switched reluctance machine based on hybrid trained WNN
Song, Shoujun Ge, Lefei; Ma, Shaojie; Zhang, Man
2014-04-15
According to the strong nonlinear electromagnetic characteristics of switched reluctance machine (SRM), a novel accurate modeling method is proposed based on hybrid trained wavelet neural network (WNN) which combines improved genetic algorithm (GA) with gradient descent (GD) method to train the network. In the novel method, WNN is trained by GD method based on the initial weights obtained per improved GA optimization, and the global parallel searching capability of stochastic algorithm and local convergence speed of deterministic algorithm are combined to enhance the training accuracy, stability and speed. Based on the measured electromagnetic characteristics of a 3-phase 12/8-pole SRM, the nonlinear simulation model is built by hybrid trained WNN in Matlab. The phase current and mechanical characteristics from simulation under different working conditions meet well with those from experiments, which indicates the accuracy of the model for dynamic and static performance evaluation of SRM and verifies the effectiveness of the proposed modeling method.
Hybrid models of hysteresis for mixed hysteretic loops in heterogeneous magnetic materials
NASA Astrophysics Data System (ADS)
Dimian, M.; Andrei, P.; Grayson, M.
2014-05-01
The mixed hysteresis behavior of counter-clockwise and clockwise loops has recently attracted the attention of the magnetics community, due to several experimental findings in inhomogeneous and hetero-structure magnetic systems. Various hybrid models are proposed here to address this behavior based on the superposition of standard hysteresis models and their newly developed clockwise variants. A special attention is also devoted to Bouc-Wen model, a typical clockwise often used by applied mechanics community, and to its relevance for mixed hysteresis. These clockwise and hybrid models have been implemented in an open-access academic software and their performance is illustrated by examples of hysteretic loops, first order reversal curves and diagrams simulated in this framework.
APT: Costs and Benefits of a Hybrid Model
ERIC Educational Resources Information Center
Dijkstra, Ton; Haverkort, Marco
2004-01-01
In their keynote contribution, Truscott and Sharwood Smith offer a general model of language development from a processing perspective. As they state, their model is very ambitious: Their "acquisition by processing" theory (APT) aims not only at explaining both first and second language acquisition but also real-time processing in language…
Hybrid model for wireless mobility management using IPv6
NASA Astrophysics Data System (ADS)
Howie, Douglas P.; Sun, Junzhao; Koivisto, Antti T.
2001-07-01
Within the coming decade, there will be a dramatic increase in the availability of inexpensive, computationally powerful mobile devices running applications which use the Internet Protocol (IP) to access multimedia services over broad-band wireless connections. To this end, there has been extensive research and standardization in the areas of Mobile IP and IPv6. The purpose of this paper is to apply this work to the issues involved in designing a mobility model able to adapt to different wireless mobile IP scenarios. We describe the usefulness of this model in the 4th generation mobile multimedia systems to come. This new model has been synthesized through a comparative analysis of current mobile IP models where particular attention has been given to the problems of mobile IP handoff and mobility management and their impact on QoS. By applying a unique perspective to these problems, our model is used to set a roadmap for future mobile IPv6 testbed construction.
Suited and Unsuited Hybrid III Impact Testing and Finite Element Model Characterization
NASA Technical Reports Server (NTRS)
Lawrence, C.; Somers, J. T.; Baldwin, M. A.; Wells, J. A.; Newby, N.; Currie, N. J.
2016-01-01
NASA spacecraft design requirements for occupant protection are a combination of the Brinkley Dynamic Response Criteria and injury assessment reference values (IARV) extracted from anthropomorphic test devices (ATD). For the ATD IARVs, the requirements specify the use of the 5th percentile female Hybrid III and the 95th percentile male Hybrid III. Each of these ATDs is required to be fitted with an articulating pelvis (also known as the aerospace pelvis) and a straight spine. The articulating pelvis is necessary for the ATD to fit into spacecraft seats, while the straight spine is required as injury metrics for vertical accelerations are better defined for this configuration. Sled testing of the Hybrid III 5th Percentile Female Anthropomorphic Test Device (ATD) was performed at Wright-Patterson Air Force Base (WAPFB). Two 5th Percentile ATDs were tested, the Air Force Research Lab (AFRL) and NASA owned Hybrid III ATDs with aerospace pelvises. Testing was also conducted with a NASA-owned 95th Percentile Male Hybrid III with aerospace pelvis at WPAFB. Testing was performed using an Orion seat prototype provided by Johnson Space Center (JSC). A 5-point harness comprised of 2 inch webbing was also provided by JSC. For suited runs, a small and extra-large Advanced Crew Escape System (ACES) suit and helmet were also provided by JSC. Impact vectors were combined frontal/spinal and rear/lateral. Some pure spinal and rear axis testing was also performed for model validation. Peak accelerations ranged between 15 and 20-g. This range was targeted because the ATD responses fell close to the IARV defined in the Human-Systems Integration Requirements (HSIR) document. Rise times varied between 70 and 110 ms to assess differences in ATD responses and model correlation for different impact energies. The purpose of the test series was to evaluate the Hybrid III ATD models in Orion-specific landing orientations both with and without a spacesuit. The results of these tests were used
NASA Astrophysics Data System (ADS)
Geli, H. M. E.
2015-12-01
Estimates of actual crop evapotranspiration (ETa) at field scale over the growing season are required for improving agricultural water management, particularly in water limited and drought prone regions. Remote sensing data from multiple platforms such as airborne and Landsat-based sensors can be used to provide these estimates. Combining these data with surface energy balance models can provide ETa estimates at sub- field scale as well as information on vegetation stress and soil moisture conditions. However, the temporal resolution of airborne and Landsat data does not allow for a continuous ETa monitoring over the course of the growing season. This study presents the application of a hybrid ETa modeling approach developed for monitoring daily ETa and root zone available water at high spatial resolutions. The hybrid ETa modeling approach couples a thermal-based energy balance model with a water balance-based scheme using data assimilation. The two source energy balance (TSEB) model is used to estimate instantaneous ETa which can be extrapolated to daily ETa using a water balance model modified to use the reflectance-based basal crop coefficient for interpolating ETa in between airborne and/or Landsat overpass dates. Moreover, since it is a water balance model, the soil moisture profile is also estimated. The hybrid ETa approach is applied over vineyard fields in central California. High resolution airborne and Landsat imagery were used to drive the hybrid model. These images were collected during periods that represented different vine phonological stages in 2013 growing season. Estimates of daily ETa and surface energy balance fluxes will be compared with ground-based eddy covariance tower measurements. Estimates of soil moisture at multiple depths will be compared with measurements.
A hybrid decomposition method for integrating coal supply and demand models
Shapiro, J.F.; White, D.E.
1982-09-01
A number of large scale models have been proposed and implemented in recent years to study the anticipated expansion of coal production and utilization in the United States. This paper reports on the application of mathematical programming decomposition methods to the constructive integration and optimization of these models. In particular, it was found that an implemented hybrid decomposition approach, part resource directed and part price directed, exhibited fast convergence to an optimal solution. (23 refs.)
A hybrid approach to multi-scale modelling of cancer.
Osborne, J M; Walter, A; Kershaw, S K; Mirams, G R; Fletcher, A G; Pathmanathan, P; Gavaghan, D; Jensen, O E; Maini, P K; Byrne, H M
2010-11-13
In this paper, we review multi-scale models of solid tumour growth and discuss a middle-out framework that tracks individual cells. By focusing on the cellular dynamics of a healthy colorectal crypt and its invasion by mutant, cancerous cells, we compare a cell-centre, a cell-vertex and a continuum model of cell proliferation and movement. All models reproduce the basic features of a healthy crypt: cells proliferate near the crypt base, they migrate upwards and are sloughed off near the top. The models are used to establish conditions under which mutant cells are able to colonize the crypt either by top-down or by bottom-up invasion. While the continuum model is quicker and easier to implement, it can be difficult to relate system parameters to measurable biophysical quantities. Conversely, the greater detail inherent in the multi-scale models means that experimentally derived parameters can be incorporated and, therefore, these models offer greater scope for understanding normal and diseased crypts, for testing and identifying new therapeutic targets and for predicting their impacts. PMID:20921009
THYME: Toolkit for Hybrid Modeling of Electric Power Systems
Nutaro Kalyan Perumalla, James Joseph
2011-01-01
THYME is an object oriented library for building models of wide area control and communications in electric power systems. This software is designed as a module to be used with existing open source simulators for discrete event systems in general and communication systems in particular. THYME consists of a typical model for simulating electro-mechanical transients (e.g., as are used in dynamic stability studies), data handling objects to work with CDF and PTI formatted power flow data, and sample models of discrete sensors and controllers.
THYME: Toolkit for Hybrid Modeling of Electric Power Systems
2011-01-01
THYME is an object oriented library for building models of wide area control and communications in electric power systems. This software is designed as a module to be used with existing open source simulators for discrete event systems in general and communication systems in particular. THYME consists of a typical model for simulating electro-mechanical transients (e.g., as are used in dynamic stability studies), data handling objects to work with CDF and PTI formatted power flowmore » data, and sample models of discrete sensors and controllers.« less
Fractional snow cover mapping from MODIS data using wavelet-artificial intelligence hybrid models
NASA Astrophysics Data System (ADS)
Moosavi, Vahid; Malekinezhad, Hossein; Shirmohammadi, Bagher
2014-04-01
This study was carried out to evaluate the wavelet-artificial intelligence hybrid models to produce fractional snow cover maps. At first, cloud cover was removed from MODIS data and cloud free images were produced. SVM-based binary classified ETM+ imagery were then used as reference maps in order to obtain train and test data for sub-pixel classification models. ANN and ANFIS-based modeling were performed using raw data (without wavelet-based preprocessing). In the next step, several mother wavelets and levels were used in order to decompose the original data to obtain wavelet coefficients. Then, the decomposed data were used for further modeling processes. ANN, ANFIS, wavelet-ANN and wavelet-ANFIS models were compared to evaluate the effect of wavelet transformation on the ability of artificial intelligence models. It was demonstrated that wavelet transformation as a preprocessing approach can significantly enhance the performance of ANN and ANFIS models. This study indicated an overall accuracy of 92.45% for wavelet-ANFIS model, 86.13% for wavelet-ANN, 72.23% for ANFIS model and 66.78% for ANN model. In fact, hybrid wavelet-artificial intelligence models can extract the characteristics of the original signals (i.e. model inputs) accurately through decomposing the non-stationary and complex signals into several stationary and simpler signals. The positive effect of fuzzification as well as wavelet transformation in the wavelet-ANFIS model was also confirmed.
Pope, Bernard J; Fitch, Blake G; Pitman, Michael C; Rice, John J; Reumann, Matthias
2011-10-01
Future multiscale and multiphysics models that support research into human disease, translational medical science, and treatment can utilize the power of high-performance computing (HPC) systems. We anticipate that computationally efficient multiscale models will require the use of sophisticated hybrid programming models, mixing distributed message-passing processes [e.g., the message-passing interface (MPI)] with multithreading (e.g., OpenMP, Pthreads). The objective of this study is to compare the performance of such hybrid programming models when applied to the simulation of a realistic physiological multiscale model of the heart. Our results show that the hybrid models perform favorably when compared to an implementation using only the MPI and, furthermore, that OpenMP in combination with the MPI provides a satisfactory compromise between performance and code complexity. Having the ability to use threads within MPI processes enables the sophisticated use of all processor cores for both computation and communication phases. Considering that HPC systems in 2012 will have two orders of magnitude more cores than what was used in this study, we believe that faster than real-time multiscale cardiac simulations can be achieved on these systems. PMID:21768044
Quilodrán, Claudio S; Montoya-Burgos, Juan I; Currat, Mathias
2015-01-01
Interspecific hybridization occurs in nature but can also be caused by human actions. It often leads to infertile or fertile hybrids that exclude one parental genome during gametogenesis, escaping genetic recombination and introgression. The threat that genome-exclusion hybridization might represent on parental species is poorly understood, especially when invasive species are involved. Here, we show how to assess the effects of genome-exclusion hybridization and how to elaborate conservation actions by simulating scenarios using a model of nonintrogressive hybridization. We examine the case of the frog Pelophylax ridibundus, introduced in Western Europe, which can hybridize with the native Pelophylax lessonae and the pre-existing hybrid Pelophylax esculentus, maintained by hybridogenesis. If translocated from Southern Europe, P. ridibundus produces new sterile hybrids and we show that it mainly threatens P. esculentus. Translocation from Central Europe leads to new fertile hybrids, threatening all native waterfrogs. Local extinction is demographically mediated via wasted reproductive potential or via demographic flow through generations towards P. ridibundus. We reveal that enlarging the habitat size of the native P. lessonae relative to that of the invader is a promising conservation strategy, avoiding the difficulties of fighting the invader. We finally stress that nonintrogressive hybridization is to be considered in conservation programmes. PMID:25685194
NASA Astrophysics Data System (ADS)
Sun, Xiaoqiang; Cai, Yingfeng; Wang, Shaohua; Liu, Yanling; Chen, Long
2016-01-01
The control problems associated with vehicle height adjustment of electronically controlled air suspension (ECAS) still pose theoretical challenges for researchers, which manifest themselves in the publications on this subject over the last years. This paper deals with modeling and control of a vehicle height adjustment system for ECAS, which is an example of a hybrid dynamical system due to the coexistence and coupling of continuous variables and discrete events. A mixed logical dynamical (MLD) modeling approach is chosen for capturing enough details of the vehicle height adjustment process. The hybrid dynamic model is constructed on the basis of some assumptions and piecewise linear approximation for components nonlinearities. Then, the on-off statuses of solenoid valves and the piecewise approximation process are described by propositional logic, and the hybrid system is transformed into the set of linear mixed-integer equalities and inequalities, denoted as MLD model, automatically by HYSDEL. Using this model, a hybrid model predictive controller (HMPC) is tuned based on online mixed-integer quadratic optimization (MIQP). Two different scenarios are considered in the simulation, whose results verify the height adjustment effectiveness of the proposed approach. Explicit solutions of the controller are computed to control the vehicle height adjustment system in realtime using an offline multi-parametric programming technology (MPT), thus convert the controller into an equivalent explicit piecewise affine form. Finally, bench experiments for vehicle height lifting, holding and lowering procedures are conducted, which demonstrate that the HMPC can adjust the vehicle height by controlling the on-off statuses of solenoid valves directly. This research proposes a new modeling and control method for vehicle height adjustment of ECAS, which leads to a closed-loop system with favorable dynamical properties.
Plasma Simulation Using Gyrokinetic-Gyrofluid Hybrid Models
Scott Parker
2009-04-09
We are developing kinetic ion models for the simulation of extended MHD phenomena. The model they have developed uses full Lorentz force ions, and either drift-kinetic or gyro-kinetic electrons. Quasi-neutrality is assumed and the displacement current is neglected. They are also studying alpha particle driven Toroidal Alfven Eigenmodes (TAE) in the GEM gyrokinetic code [Chen 07]. The basic kinetic ion MHD model was recently reported in an invited talk given by Dan Barnes at the 2007 American Physical Society - Division of Plasma Physics (APS-DPP) and it has been published [Jones 04, Barnes 08]. The model uses an Ohm's law that includes the Hall term, pressure term and the electron inertia [Jones 04]. These results focused on the ion physics and assumed an isothermal electron closure. It is found in conventional gyrokinetic turbulence simulations that the timestep cannot be made much greater than the ion cyclotron period. However, the kinetic ion MHD model has the compressional mode, which further limits the timestep. They have developed an implicit scheme to avoid this timestep constraint. They have also added drift kinetic electrons. This model has been benchmarked linearly. Waves investigated where shear and compressional Alfven, whisterl, ion acoustic, and drift waves, including the kinetic damping rates. This work is ongoing and was first reported at the 2008 Sherwood Fusion Theory Conference [Chen 08] and they are working on a publication. They have also formulated an integrated gyrokinetic electron model, which is of interest for studying electron gradient instabilities and weak guide-field magnetic reconnection.
Qualitative Fault Isolation of Hybrid Systems: A Structural Model Decomposition-Based Approach
NASA Technical Reports Server (NTRS)
Bregon, Anibal; Daigle, Matthew; Roychoudhury, Indranil
2016-01-01
Quick and robust fault diagnosis is critical to ensuring safe operation of complex engineering systems. A large number of techniques are available to provide fault diagnosis in systems with continuous dynamics. However, many systems in aerospace and industrial environments are best represented as hybrid systems that consist of discrete behavioral modes, each with its own continuous dynamics. These hybrid dynamics make the on-line fault diagnosis task computationally more complex due to the large number of possible system modes and the existence of autonomous mode transitions. This paper presents a qualitative fault isolation framework for hybrid systems based on structural model decomposition. The fault isolation is performed by analyzing the qualitative information of the residual deviations. However, in hybrid systems this process becomes complex due to possible existence of observation delays, which can cause observed deviations to be inconsistent with the expected deviations for the current mode in the system. The great advantage of structural model decomposition is that (i) it allows to design residuals that respond to only a subset of the faults, and (ii) every time a mode change occurs, only a subset of the residuals will need to be reconfigured, thus reducing the complexity of the reasoning process for isolation purposes. To demonstrate and test the validity of our approach, we use an electric circuit simulation as the case study.
Application of explicit model predictive control to a hybrid battery-ultracapacitor power source
NASA Astrophysics Data System (ADS)
Hredzak, Branislav; Agelidis, Vassilios G.; Demetriades, Georgios
2015-03-01
An explicit model predictive control (EMPC) system for a hybrid battery-ultracapacitor power source is proposed and experimentally verified in this paper. The main advantage of using the EMPC system is that the control law computation is reduced to evaluation of an explicitly defined piecewise linear function of the states. Separate EMPC systems for the total output current loop, the battery loop and the ultracapacitor loop are designed. This modular design approach allows evaluation of the performance of each individual EMPC system separately and also improves the convergence of the EMPC system design algorithm as the models used to design each loop are smaller. In order to protect the hybrid power source, the designed EMPC systems maintain operation of the hybrid power source within specified constraints, namely, battery and ultracapacitor current constraints, battery state of charge constraints and ultracapacitor voltage constraints. At the same time, the total output current EMPC system allocates high frequency current changes to the ultracapacitor and the low frequency current changes to the battery thus extending the battery lifetime. Presented experimental results verify that the hybrid power source operates within the specified constraints while allocating high and low frequency current changes to the ultracapacitor and battery respectively.
NASA Astrophysics Data System (ADS)
Maclay, James D.; Brouwer, Jacob; Samuelsen, G. Scott
A model of a photovoltaic (PV) powered residence in stand-alone configuration was developed and evaluated. The model assesses the sizing, capital costs, control strategies, and efficiencies of reversible fuel cells (RFC), batteries, and ultra-capacitors (UC) both individually, and in combination, as hybrid energy storage devices. The choice of control strategy for a hybrid energy storage system is found to have a significant impact on system efficiency, hydrogen production and component utilization. A hybrid energy storage system comprised of batteries and RFC has the advantage of reduced cost (compared to using a RFC as the sole energy storage device), high system efficiency and hydrogen energy production capacity. A control strategy that preferentially used the RFC before the battery in meeting load demand allows both grid independent operation and better RFC utilization compared to a system that preferentially used the battery before the RFC. Ultra-capacitors coupled with a RFC in a hybrid energy storage system contain insufficient energy density to meet dynamic power demands typical of residential applications.
NASA Technical Reports Server (NTRS)
Baurle, R. A.
2015-01-01
Steady-state and scale-resolving simulations have been performed for flow in and around a model scramjet combustor flameholder. The cases simulated corresponded to those used to examine this flowfield experimentally using particle image velocimetry. A variety of turbulence models were used for the steady-state Reynolds-averaged simulations which included both linear and non-linear eddy viscosity models. The scale-resolving simulations used a hybrid Reynolds-averaged / large eddy simulation strategy that is designed to be a large eddy simulation everywhere except in the inner portion (log layer and below) of the boundary layer. Hence, this formulation can be regarded as a wall-modeled large eddy simulation. This effort was undertaken to formally assess the performance of the hybrid Reynolds-averaged / large eddy simulation modeling approach in a flowfield of interest to the scramjet research community. The numerical errors were quantified for both the steady-state and scale-resolving simulations prior to making any claims of predictive accuracy relative to the measurements. The steady-state Reynolds-averaged results showed a high degree of variability when comparing the predictions obtained from each turbulence model, with the non-linear eddy viscosity model (an explicit algebraic stress model) providing the most accurate prediction of the measured values. The hybrid Reynolds-averaged/large eddy simulation results were carefully scrutinized to ensure that even the coarsest grid had an acceptable level of resolution for large eddy simulation, and that the time-averaged statistics were acceptably accurate. The autocorrelation and its Fourier transform were the primary tools used for this assessment. The statistics extracted from the hybrid simulation strategy proved to be more accurate than the Reynolds-averaged results obtained using the linear eddy viscosity models. However, there was no predictive improvement noted over the results obtained from the explicit
A hybrid model to calculate the forward delay time of heterojunction bipolar transistors
NASA Astrophysics Data System (ADS)
Kumar, T.; Cahay, M.; Shi, S.; Roenker, K.; Stanchina, W. E.
1995-07-01
The forward delay time (τ F) of heterojunction bipolar transistors (HBTs) is calculated using a hybrid model of carrier transport. A rigorous quantum-mechanical treatment of electron tunneling and thermionic emission across the spike at the emitter-base junction is used to determine the energy of the electron flux injected into the base region. This flux is used as an initial distribution in a regional Monte Carlo simulator to model electron transport from base to sub-collector. In this paper, we estimate the base transit time using the impulse response technique and the collector delay time using the expression of Laux and Lai (IEEE Electron Device Letters, 11, 174, 1990). Improvements to the hybrid model proposed here to reduce some of the discrepancies between measured and calculated values of ƒ τ for some InAlAs/InGaAs and InP/InGaAs structures reported in the literature are discussed.
Model-Invariant Hybrid Computations of Separated Flows for RCA Standard Test Cases
NASA Technical Reports Server (NTRS)
Woodruff, Stephen
2016-01-01
NASA's Revolutionary Computational Aerosciences (RCA) subproject has identified several smooth-body separated flows as standard test cases to emphasize the challenge these flows present for computational methods and their importance to the aerospace community. Results of computations of two of these test cases, the NASA hump and the FAITH experiment, are presented. The computations were performed with the model-invariant hybrid LES-RANS formulation, implemented in the NASA code VULCAN-CFD. The model- invariant formulation employs gradual LES-RANS transitions and compensation for model variation to provide more accurate and efficient hybrid computations. Comparisons revealed that the LES-RANS transitions employed in these computations were sufficiently gradual that the compensating terms were unnecessary. Agreement with experiment was achieved only after reducing the turbulent viscosity to mitigate the effect of numerical dissipation. The stream-wise evolution of peak Reynolds shear stress was employed as a measure of turbulence dynamics in separated flows useful for evaluating computations.
Preliminary analysis on hybrid Box-Jenkins - GARCH modeling in forecasting gold price
NASA Astrophysics Data System (ADS)
Yaziz, Siti Roslindar; Azizan, Noor Azlinna; Ahmad, Maizah Hura; Zakaria, Roslinazairimah; Agrawal, Manju; Boland, John
2015-02-01
Gold has been regarded as a valuable precious metal and the most popular commodity as a healthy return investment. Hence, the analysis and prediction of gold price become very significant to investors. This study is a preliminary analysis on gold price and its volatility that focuses on the performance of hybrid Box-Jenkins models together with GARCH in analyzing and forecasting gold price. The Box-Cox formula is used as the data transformation method due to its potential best practice in normalizing data, stabilizing variance and reduces heteroscedasticity using 41-year daily gold price data series starting 2nd January 1973. Our study indicates that the proposed hybrid model ARIMA-GARCH with t-innovation can be a new potential approach in forecasting gold price. This finding proves the strength of GARCH in handling volatility in the gold price as well as overcomes the non-linear limitation in the Box-Jenkins modeling.
Functional Model of Carbon Nanotube Programmable Resistors for Hybrid Nano/CMOS Circuit Design
NASA Astrophysics Data System (ADS)
Zhao, Weisheng; Agnus, Guillaume; Derycke, Vincent; Filoramo, Ariana; Gamrat, Christian; Bourgoin, Jean-Philippe
Hybrid Nano (e.g. Nanotube and Nanowire) /CMOS circuits combine both the advantages of Nano-devices and CMOS technologies; they have thus become the most promising candidates to relax the intrinsic drawbacks of CMOS circuits beyond Moore’s law. A functional simulation model for an hybrid Nano/CMOS design is presented in this paper. It is based on Optically Gated Carbon NanoTube Field Effect Transistors (OG-CNTFET), which can be used as 2-terminal programmable resistors. Their resistance can be adjusted precisely, reproducibly and in a non-volatile way, over three orders of magnitude. These interesting behaviors of OG-CNTFET promise great potential for developing the non-volatile memory and neuromorphic adaptive computing circuits. The model is developed in Verilog-A language and implemented on Cadence Virtuoso platform with Spectre 5.1.41 simulator. Many experimental parameters are included in this model to improve the simulation accuracy.
Online motor fault detection and diagnosis using a hybrid FMM-CART model.
Seera, Manjeevan; Lim, Chee Peng
2014-04-01
In this brief, a hybrid model combining the fuzzy min-max (FMM) neural network and the classification and regression tree (CART) for online motor detection and diagnosis tasks is described. The hybrid model, known as FMM-CART, exploits the advantages of both FMM and CART for undertaking data classification and rule extraction problems. To evaluate the applicability of the proposed FMM-CART model, an evaluation with a benchmark data set pertaining to electrical motor bearing faults is first conducted. The results obtained are equivalent to those reported in the literature. Then, a laboratory experiment for detecting and diagnosing eccentricity faults in an induction motor is performed. In addition to producing accurate results, useful rules in the form of a decision tree are extracted to provide explanation and justification for the predictions from FMM-CART. The experimental outcome positively shows the potential of FMM-CART in undertaking online motor fault detection and diagnosis tasks. PMID:24807956
Modelling Nonlinear Dynamic Textures using Hybrid DWT-DCT and Kernel PCA with GPU
NASA Astrophysics Data System (ADS)
Ghadekar, Premanand Pralhad; Chopade, Nilkanth Bhikaji
2016-06-01
Most of the real-world dynamic textures are nonlinear, non-stationary, and irregular. Nonlinear motion also has some repetition of motion, but it exhibits high variation, stochasticity, and randomness. Hybrid DWT-DCT and Kernel Principal Component Analysis (KPCA) with YCbCr/YIQ colour coding using the Dynamic Texture Unit (DTU) approach is proposed to model a nonlinear dynamic texture, which provides better results than state-of-art methods in terms of PSNR, compression ratio, model coefficients, and model size. Dynamic texture is decomposed into DTUs as they help to extract temporal self-similarity. Hybrid DWT-DCT is used to extract spatial redundancy. YCbCr/YIQ colour encoding is performed to capture chromatic correlation. KPCA is applied to capture nonlinear motion. Further, the proposed algorithm is implemented on Graphics Processing Unit (GPU), which comprise of hundreds of small processors to decrease time complexity and to achieve parallelism.
ERIC Educational Resources Information Center
Delialioglu, Omer; Yildirim, Zahide
2008-01-01
Using the model for learning and teaching activities (MOLTA), a new technology enhanced hybrid instruction was designed, developed and implemented. The effectiveness of the hybrid instruction in regard to students' achievement, knowledge retention, attitudes towards the subject, and course satisfaction was evaluated in comparison to traditional…
A hybrid model describing ion induced kinetic electron emission
NASA Astrophysics Data System (ADS)
Hanke, S.; Duvenbeck, A.; Heuser, C.; Weidtmann, B.; Wucher, A.
2015-06-01
We present a model to describe the kinetic internal and external electron emission from an ion bombarded metal target. The model is based upon a molecular dynamics treatment of the nuclear degree of freedom, the electronic system is assumed as a quasi-free electron gas characterized by its Fermi energy, electron temperature and a characteristic attenuation length. In a series of previous works we have employed this model, which includes the local kinetic excitation as well as the rapid spread of the generated excitation energy, in order to calculate internal and external electron emission yields within the framework of a Richardson-Dushman-like thermionic emission model. However, this kind of treatment turned out to fail in the realistic prediction of experimentally measured internal electron yields mainly due to the restriction of the treatment of electronic transport to a diffusive manner. Here, we propose a slightly modified approach additionally incorporating the contribution of hot electrons which are generated in the bulk material and undergo ballistic transport towards the emitting interface.
Using a hybrid genetic algorithm and fuzzy logic for metabolic modeling
Yen, J.; Lee, B.; Liao, J.C.
1996-12-31
The identification of metabolic systems is a complex task due to the complexity of the system and limited knowledge about the model. Mathematical equations and ODE`s have been used to capture the structure of the model, and the conventional optimization techniques have been used to identify the parameters of the model. In general, however, a pure mathematical formulation of the model is difficult due to parametric uncertainty and incomplete knowledge of mechanisms. In this paper, we propose a modeling approach that (1) uses fuzzy rule-based model to augment algebraic enzyme models that are incomplete, and (2) uses a hybrid genetic algorithm to identify uncertain parameters in the model. The hybrid genetic algorithm (GA) integrates a GA with the simplex method in functional optimization to improve the GA`s convergence rate. We have applied this approach to modeling the rate of three enzyme reactions in E. coli central metabolism. The proposed modeling strategy allows (1) easy incorporation of qualitative insights into a pure mathematical model and (2) adaptive identification and optimization of key parameters to fit system behaviors observed in biochemical experiments.
Medical Image Segmentation Based on a Hybrid Region-Based Active Contour Model
Liu, Tingting; Xu, Haiyong; Liu, Zhen; Zhao, Yiming; Tian, Wenzhe
2014-01-01
A novel hybrid region-based active contour model is presented to segment medical images with intensity inhomogeneity. The energy functional for the proposed model consists of three weighted terms: global term, local term, and regularization term. The total energy is incorporated into a level set formulation with a level set regularization term, from which a curve evolution equation is derived for energy minimization. Experiments on some synthetic and real images demonstrate that our model is more efficient compared with the localizing region-based active contours (LRBAC) method, proposed by Lankton, and more robust compared with the Chan-Vese (C-V) active contour model. PMID:25028593
NASA Astrophysics Data System (ADS)
Mantovanelli, Ivana C. C.; Rivera, Elmer Ccopa; da Costa, Aline C.; Filho, Rubens Maciel
In this work a procedure for the development of a robust mathematical model for an industrial alcoholic fermentation process was evaluated. The proposed model is a hybrid neural model, which combines mass and energy balance equations with functional link networks to describe the kinetics. These networks have been shown to have a good nonlinear approximation capability, although the estimation of its weights is linear. The proposed model considers the effect of temperature on the kinetics and has the neural network weights reestimated always so that a change in operational conditions occurs. This allow to follow the system behavior when changes in operating conditions occur.
The characteristic analysis of a hybrid multifluid turbulent-mix model
Cheng, B.; Cranfill, C.W.
1998-07-13
A thorough analysis of the characteristics of a multifluid turbulent mix model in the case of one-dimensional two phase flows is presented under various physical circumstances. It has been found that the new hybrid multifluid turbulent mix model has all real characteristics if either real or turbulent viscosity is present. When real viscosity vanishes, the model still has all real characteristics for zero relative motion between fluids. For nonzero relative motions between fluids, the model will have all real characteristics if the disordered motions and turbulent viscosity together are generated with the nonzero relative motions simultaneously. The implications of the results are further discussed.
Neutrino masses, leptogenesis, and dark matter in a hybrid seesaw model
Gu Peihong; Hirsch, M.; Valle, J. W. F.
2009-02-01
We suggest a hybrid seesaw model where relatively light right-handed neutrinos give no contribution to neutrino mass matrix due to a special symmetry. This allows their Yukawa couplings to the standard model particles to be relatively strong, so that the standard model Higgs boson can decay dominantly to a left- and a right-handed neutrino, leaving another stable right-handed neutrino as cold dark matter. In our model neutrino masses arise via the type-II seesaw mechanism, the Higgs triplet scalars being also responsible for the generation of the matter-antimatter asymmetry via the leptogenesis mechanism.
Dynamical analysis of Parkinsonian state emulated by hybrid Izhikevich neuron models
NASA Astrophysics Data System (ADS)
Liu, Chen; Wang, Jiang; Yu, Haitao; Deng, Bin; Wei, Xile; Li, Huiyan; Loparo, Kenneth A.; Fietkiewicz, Chris
2015-11-01
Computational models play a significant role in exploring novel theories to complement the findings of physiological experiments. Various computational models have been developed to reveal the mechanisms underlying brain functions. Particularly, in the development of therapies to modulate behavioral and pathological abnormalities, computational models provide the basic foundations to exhibit transitions between physiological and pathological conditions. Considering the significant roles of the intrinsic properties of the globus pallidus and the coupling connections between neurons in determining the firing patterns and the dynamical activities of the basal ganglia neuronal network, we propose a hypothesis that pathological behaviors under the Parkinsonian state may originate from combined effects of intrinsic properties of globus pallidus neurons and synaptic conductances in the whole neuronal network. In order to establish a computational efficient network model, hybrid Izhikevich neuron model is used due to its capacity of capturing the dynamical characteristics of the biological neuronal activities. Detailed analysis of the individual Izhikevich neuron model can assist in understanding the roles of model parameters, which then facilitates the establishment of the basal ganglia-thalamic network model, and contributes to a further exploration of the underlying mechanisms of the Parkinsonian state. Simulation results show that the hybrid Izhikevich neuron model is capable of capturing many of the dynamical properties of the basal ganglia-thalamic neuronal network, such as variations of the firing rates and emergence of synchronous oscillations under the Parkinsonian condition, despite the simplicity of the two-dimensional neuronal model. It may suggest that the computational efficient hybrid Izhikevich neuron model can be used to explore basal ganglia normal and abnormal functions. Especially it provides an efficient way of emulating the large-scale neuron network
Hybrid methodology for situation assessment model development within an air operations center domain
NASA Astrophysics Data System (ADS)
Ho, Stephen; Gonsalves, Paul; Call, Catherine
2007-04-01
Within the dynamic environment of an Air Operations Center (AOC), effective decision-making is highly dependent on timely and accurate situation assessment. In previous research efforts the capabilities and potential of a Bayesian belief network (BN) model-based approach to support situation assessment have been demonstrated. In our own prior research, we have presented and formalized a hybrid process for situation assessment model development that seeks to ameliorate specific concerns and drawbacks associated with using a BN-based model construct. Specifically, our hybrid methodology addresses the significant knowledge acquisition requirements and the associated subjective nature of using subject matter experts (SMEs) for model development. Our methodology consists of two distinct functional elements: an off-line mechanism for rapid construction of a Bayesian belief network (BN) library of situation assessment models tailored to different situations and derived from knowledge elicitation with SMEs; and an on-line machine-learning-based mechanism to learn, tune, or adapt BN model parameters and structure. The adaptation supports the ability to adjust the models over time to respond to novel situations not initially available or anticipated during initial model construction, thus ensuring that the models continue to meet the dynamic requirements of performing the situation assessment function within dynamic application environments such as an AOC. In this paper, we apply and demonstrate the hybrid approach within the specific context of an AOC-based air campaign monitoring scenario. We detail both the initial knowledge elicitation and subsequent machine learning phases of the model development process, as well as demonstrate model performance within an operational context.
Singularity avoidance in the hybrid quantization of the Gowdy model
NASA Astrophysics Data System (ADS)
Tarrío, Paula; Fernández-Méndez, Mikel; Mena Marugán, Guillermo A.
2013-10-01
One of the most remarkable phenomena in loop quantum cosmology is that, at least for homogeneous cosmological models, the big bang is replaced with a big bounce that connects our Universe with a previous branch without passing through a cosmological singularity. The goal of this work is to study the existence of singularities in loop quantum cosmology, including inhomogeneities, and check whether the behavior obtained in the purely homogeneous setting continues to be valid. With this aim, we focus our attention on the three-torus Gowdy cosmologies with linearly polarized gravitational waves and use effective dynamics to carry out the analysis. For this model, we prove that all the potential cosmological singularities are avoided, generalizing the results about resolution of singularities to this scenario with inhomogeneities. We also demonstrate that, if a bounce in the (Bianchi background) volume occurs, the inhomogeneities increase the value of this volume at the bounce with respect to its counterpart in the homogeneous case.
An Advanced Hierarchical Hybrid Environment for Reliability and Performance Modeling
NASA Technical Reports Server (NTRS)
Ciardo, Gianfranco
2003-01-01
The key issue we intended to address in our proposed research project was the ability to model and study logical and probabilistic aspects of large computer systems. In particular, we wanted to focus mostly on automatic solution algorithms based on a state-space exploration as their first step, in addition to the more traditional discrete-event simulation approaches commonly employed in industry. One explicitly-stated goal was to extend by several orders of magnitude the size of models that can be solved exactly, using a combination of techniques: 1) Efficient exploration and storage of the state space using new data structures that require an amount of memory sublinear in the number states; and 2) Exploitation of the existing symmetries in the matrices describing the system behavior using Kronecker operators. Not only we have been successful in achieving the above goals, but we exceeded them in many respects.
Empirical Analysis of Stochastic Volatility Model by Hybrid Monte Carlo Algorithm
NASA Astrophysics Data System (ADS)
Takaishi, Tetsuya
2013-04-01
The stochastic volatility model is one of volatility models which infer latent volatility of asset returns. The Bayesian inference of the stochastic volatility (SV) model is performed by the hybrid Monte Carlo (HMC) algorithm which is superior to other Markov Chain Monte Carlo methods in sampling volatility variables. We perform the HMC simulations of the SV model for two liquid stock returns traded on the Tokyo Stock Exchange and measure the volatilities of those stock returns. Then we calculate the accuracy of the volatility measurement using the realized volatility as a proxy of the true volatility and compare the SV model with the GARCH model which is one of other volatility models. Using the accuracy calculated with the realized volatility we find that empirically the SV model performs better than the GARCH model.
Identification and automatic segmentation of multiphasic cell growth using a linear hybrid model.
Hartmann, András; Neves, Ana Rute; Lemos, João M; Vinga, Susana
2016-09-01
This article considers a new mathematical model for the description of multiphasic cell growth. A linear hybrid model is proposed and it is shown that the two-parameter logistic model with switching parameters can be represented by a Switched affine AutoRegressive model with eXogenous inputs (SARX). The growth phases are modeled as continuous processes, while the switches between the phases are considered to be discrete events triggering a change in growth parameters. This framework provides an easily interpretable model, because the intrinsic behavior is the same along all the phases but with a different parameterization. Another advantage of the hybrid model is that it offers a simpler alternative to recent more complex nonlinear models. The growth phases and parameters from datasets of different microorganisms exhibiting multiphasic growth behavior such as Lactococcus lactis, Streptococcus pneumoniae, and Saccharomyces cerevisiae, were inferred. The segments and parameters obtained from the growth data are close to the ones determined by the experts. The fact that the model could explain the data from three different microorganisms and experiments demonstrates the strength of this modeling approach for multiphasic growth, and presumably other processes consisting of multiple phases. PMID:27424949
2013-01-01
Background The extraction of brain tissue from cerebral MRI volume is an important pre-procedure for neuroimage analyses. The authors have developed an accurate and robust brain extraction method using a hybrid level set based active contour neighborhood model. Methods The method uses a nonlinear speed function in the hybrid level set model to eliminate boundary leakage. When using the new hybrid level set model an active contour neighborhood model is applied iteratively in the neighborhood of brain boundary. A slice by slice contour initial method is proposed to obtain the neighborhood of the brain boundary. The method was applied to the internet brain MRI data provided by the Internet Brain Segmentation Repository (IBSR). Results In testing, a mean Dice similarity coefficient of 0.95±0.02 and a mean Hausdorff distance of 12.4±4.5 were obtained when performing our method across the IBSR data set (18 × 1.5 mm scans). The results obtained using our method were very similar to those produced using manual segmentation and achieved the smallest mean Hausdorff distance on the IBSR data. Conclusions An automatic method of brain extraction from cerebral MRI volume was achieved and produced competitively accurate results. PMID:23587217
Models to estimate the minimum ignition temperature of dusts and hybrid mixtures.
Addai, Emmanuel Kwasi; Gabel, Dieter; Krause, Ulrich
2016-03-01
The minimum ignition temperatures (MIT) of hybrid mixtures have been investigated by performing several series of tests in a modified Godbert-Greenwald furnace. Five dusts as well as three perfect gases and three real were used in different combinations as test samples. Further, seven mathematical models for prediction of the MIT of dust/air mixtures were presented of which three were chosen for deeper study and comparison with the experimental results based on the availability of the input quantities needed and their applicability. Additionally, two alternative models were proposed to calculate the MIT of hybrid mixtures and were validated against the experimental results. A significant decrease of the minimum ignition temperature of either the gas or the vapor as well as an increase in the explosion likelihood could be observed when a small amount of dust which was either below its minimum explosible concentration or not ignitable itself at that particular temperature was mixed with the gas. The various models developed by Cassel, Krishma and Mitsui to predict the MIT of dust were in good agreement with the experimental results as well as the two models proposed to predict the MIT of hybrid mixtures were also in agreement with the experimental value. PMID:26546706
Hybrid fluid/kinetic model for parallel heat conduction
Callen, J.D.; Hegna, C.C.; Held, E.D.
1998-12-31
It is argued that in order to use fluid-like equations to model low frequency ({omega} < {nu}) phenomena such as neoclassical tearing modes in low collisionality ({nu} < {omega}{sub b}) tokamak plasmas, a Chapman-Enskog-like approach is most appropriate for developing an equation for the kinetic distortion (F) of the distribution function whose velocity-space moments lead to the needed fluid moment closure relations. Further, parallel heat conduction in a long collision mean free path regime can be described through a combination of a reduced phase space Chapman-Enskog-like approach for the kinetics and a multiple-time-scale analysis for the fluid and kinetic equations.
A hybrid finite element approach to modeling sound radiation from circular and rectangular ducts.
Duan, Wenbo; Kirby, Ray
2012-05-01
A numerical model based on a hybrid finite element method is developed that seeks to join sound pressure fields in interior and exterior regions. The hybrid method is applied to the analysis of sound radiation from open pipes, or ducts, and uses mode matching to couple a finite element discretization of the region surrounding the open end of the duct to wave based modal expansions for adjoining interior and exterior regions. The hybrid method facilitates the analysis of ducts of arbitrary but uniform cross section as well the study of conical flanges and here a modal expansion based on spherical harmonics is applied. Predictions are benchmarked against analytic solutions for the limiting cases of flanged and unflanged circular ducts and excellent agreement between the two methods is observed. Predictions are also presented for flanged and unflanged rectangular ducts, and because the hybrid method retains the sparse banded and symmetric matrices of the traditional finite element method, it is shown that predictions can be obtained within an acceptable time frame even for a three dimensional problem. PMID:22559341
Jian, Weilin; He, Daohang; Song, Shaoyun
2016-01-01
Natural stilbenes (especially resveratrol) play important roles in plant protection by acting as both constitutive and inducible defenses. However, their exogenous applications on crops as fungicidal agents are challenged by their oxidative degradation and limited availability. In this study, a new class of resveratrol-inspired oxadiazole-stilbene hybrids was synthesized via Wittig-Horner reaction. Bioassay results indicated that some of the compounds exhibited potent fungicidal activity against Botrytis cinerea in vitro. Among these stilbene hybrids, compounds 11 showed promising inhibitory activity with the EC50 value of 144.6 μg/mL, which was superior to that of resveratrol (315.6 μg/mL). Remarkably, the considerably abnormal mycelial morphology was observed in the presence of compound 11. The inhibitory profile was further proposed by homology modeling and molecular docking studies, which showed the possible interaction of resveratrol and oxadiazole-stilbene hybrids with the cytochrome P450-dependent sterol 14α-demethylase from B. cinerea (BcCYP51) for the first time. Taken together, these results would provide new insights into the fungicidal mechanism of stilbenes, as well as an important clue for biology-oriented synthesis of stilbene hybrids with improved bioactivity against plant pathogenic fungi in crop protection. PMID:27530962
An Evolutionary Hybrid Cellular Automaton Model of Solid Tumour Growth
Gerlee, P.; Anderson, A.R.A.
2007-01-01
We propose a cellular automaton model of solid tumour growth, in which each cell is equipped with a micro-environment response network. This network is modelled using a feed-forward artificial neural network, that takes environmental variables as an input and from these determines the cellular behaviour as the output. The response of the network is determined by connection weights and thresholds in the network, which are subject to mutations when the cells divide. As both available space and nutrients are limited resources for the tumour this gives rise to clonal evolution where only the fittest cells survive. Using this approach we have investigated the impact of the tissue oxygen concentration on the growth and evolutionary dynamics of the tumour. The results show that the oxygen concentration affects the selection pressure, cell population diversity and morphology of the tumour. A low oxygen concentration in the tissue gives rise to a tumour with a fingered morphology that contains aggressive phenotypes with a small apoptotic potential, while a high oxygen concentration in the tissue gives rise to a tumour with a round morphology containing less evolved phenotypes. The tissue oxygen concentration thus affects the tumour at both the morphological level and on the phenotype level. PMID:17374383
NASA Astrophysics Data System (ADS)
Kushner, Mark J.; Grapperhaus, Michael J.
1996-10-01
Inductively Coupled Plasma (ICP) reactors have the potential for scaling to large area substrates while maintaining azimuthal symmetry or side-to-side uniformity across the wafer. Asymmetric etch properties in these devices have been attributed to transmission line properties of the coil, internal structures (such as wafer clamps) and non-uniform gas injection or pumping. To investigate the origins of asymmetric etch properties, a 3-dimensional hybrid model has been developed. The hybrid model contains electromagnetic, electric circuit, electron energy equation, and fluid modules. Continuity and momentum equations are solved in the fluid module along with Poisson's equation. We will discuss results for ion and radical flux uniformity to the substrate while varying the transmission line characteristics of the coil, symmetry of gas inlets/pumping, and internal structures. Comparisons will be made to expermental measurements of etch rates. ^*Work supported by SRC, NSF, ARPA/AFOSR and LAM Research.
Initial Results From the 3D Hybrid Heliospheric Modeling System With Pickup Protons
NASA Astrophysics Data System (ADS)
Detman, T. R.; Intriligator, D.; Dryer, M.; Sun, W.; Deehr, C.; Intriligator, J.
2008-12-01
Interstellar neutral hydrogen flows into the heliosphere and becomes ionized by photoionization and by charge exchange with solar wind protons. These "pickup" protons cause a slowing and heating of the solar wind flow in the outer heliosphere. We are adding the physics of these processes to our time-dependent 3D Hybrid Heliospheric Modeling System. We plan to present initial results for the "Halloween" 2003 events, and to show comparisons with both ACE and Ulysses observations and with our previous results (without pickup protons). This work is sponsored by NASA Grant NNX08AE40G and by Carmel Research Center. Detman et al., 2006, A hybrid heliospheric modeling system: Background solar wind, J. Geophys. Res., V 111, doi:10.1029/2005JA011340
A hybrid programming model for compressible gas dynamics using openCL
Bergen, Benjamin Karl; Daniels, Marcus G; Weber, Paul M
2010-01-01
The current trend towards multicore/manycore and accelerated architectures presents challenges, both in portability, and also in the choices that developers must make on how to use the resources that these architectures provide. This paper explores some of the possibilities that are enabled by the Open Computing Language (OpenCL), and proposes a programming model that allows developers and scientists to more fully subscribe hybrid compute nodes, while, at the same time, reducing the impact of system failure.
Fernandez-Lozano, C.; Canto, C.; Gestal, M.; Andrade-Garda, J. M.; Rabuñal, J. R.; Dorado, J.; Pazos, A.
2013-01-01
Given the background of the use of Neural Networks in problems of apple juice classification, this paper aim at implementing a newly developed method in the field of machine learning: the Support Vector Machines (SVM). Therefore, a hybrid model that combines genetic algorithms and support vector machines is suggested in such a way that, when using SVM as a fitness function of the Genetic Algorithm (GA), the most representative variables for a specific classification problem can be selected. PMID:24453933
Holod, I.; Lin, Z.
2013-03-15
The fluid-kinetic hybrid electron model is verified in global gyrokinetic particle simulation of linear electromagnetic drift-Alfvenic instabilities in tokamak. In particular, we have recovered the {beta}-stabilization of the ion temperature gradient mode, transition to collisionless trapped electron mode, and the onset of kinetic ballooning mode as {beta}{sub e} (ratio of electron kinetic pressure to magnetic pressure) increases.
Modeling and Analysis of Asynchronous Systems Using SAL and Hybrid SAL
NASA Technical Reports Server (NTRS)
Tiwari, Ashish; Dutertre, Bruno
2013-01-01
We present formal models and results of formal analysis of two different asynchronous systems. We first examine a mid-value select module that merges the signals coming from three different sensors that are each asynchronously sampling the same input signal. We then consider the phase locking protocol proposed by Daly, Hopkins, and McKenna. This protocol is designed to keep a set of non-faulty (asynchronous) clocks phase locked even in the presence of Byzantine-faulty clocks on the network. All models and verifications have been developed using the SAL model checking tools and the Hybrid SAL abstractor.
Development and Evaluation of a Hybrid Eulerian-Lagrangian Modeling Approach
NASA Astrophysics Data System (ADS)
Choi, Y.; Czader, B.; Percell, P.; Byun, D.
2014-12-01
A hybrid Lagrangian-Eulerian modeling tool has been developed using the CMAQ code. It is a moving nest domain that resides in a base Eulerian model with the same vertical CMAQ structure and physical and chemical interactions. It may follow the trajectory defined by the mean mixed-layer wind or any other user defined trajectory. It was developed as a computationally efficient 3-D grid sub-model for the purpose of evaluations of the source-receptor relationship. The correctness of the algorithms and the overall performance was evaluated against CMAQ simulation results.
An Approach of Bio-inspired Hybrid Model for Financial Markets
NASA Astrophysics Data System (ADS)
Simić, Dragan; Gajić, Vladeta; Simić, Svetlana
Biological systems are inspiration for the design of optimisation and classification models. Applying various forms of bio-inspired algorithms may be a very high-complex system. Modelling of financial markets is challenging for several reasons, because many plausible factors impact on it. An automated trading on financial market is not a new phenomenon. The model of bio-inspired hybrid adaptive trading system based on technical indicators usage by grammatical evolution and moving window is presented in this paper. The proposed system is just one of possible bio-inspired system which can be used in financial forecast, corporate failure prediction or bond rating company.
Value-Driven Design and Sensitivity Analysis of Hybrid Energy Systems using Surrogate Modeling
Wenbo Du; Humberto E. Garcia; William R. Binder; Christiaan J. J. Paredis
2001-10-01
A surrogate modeling and analysis methodology is applied to study dynamic hybrid energy systems (HES). The effect of battery size on the smoothing of variability in renewable energy generation is investigated. Global sensitivity indices calculated using surrogate models show the relative sensitivity of system variability to dynamic properties of key components. A value maximization approach is used to consider the tradeoff between system variability and required battery size. Results are found to be highly sensitive to the renewable power profile considered, demonstrating the importance of accurate renewable resource modeling and prediction. The documented computational framework and preliminary results represent an important step towards a comprehensive methodology for HES evaluation, design, and optimization.
Fontenete, Sílvia; Guimarães, Nuno; Wengel, Jesper; Azevedo, Nuno Filipe
2016-06-01
The thermodynamics and kinetics of DNA hybridization, i.e. the process of self-assembly of one, two or more complementary nucleic acid strands, has been studied for many years. The appearance of the nearest-neighbor model led to several theoretical and experimental papers on DNA thermodynamics that provide reasonably accurate thermodynamic information on nucleic acid duplexes and allow estimation of the melting temperature. Because there are no thermodynamic models specifically developed to predict the hybridization temperature of a probe used in a fluorescence in situ hybridization (FISH) procedure, the melting temperature is used as a reference, together with corrections for certain compounds that are used during FISH. However, the quantitative relation between melting and experimental FISH temperatures is poorly described. In this review, various models used to predict the melting temperature for rRNA targets, for DNA oligonucleotides and for nucleic acid mimics (chemically modified oligonucleotides), will be addressed in detail, together with a critical assessment of how this information should be used in FISH. PMID:25586037
Advanced 3D electromagnetic and particle-in-cell modeling on structured/unstructured hybrid grids
Seidel, D.B.; Pasik, M.F.; Kiefer, M.L.; Riley, D.J.; Turner, C.D.
1998-01-01
New techniques have been recently developed that allow unstructured, free meshes to be embedded into standard 3-dimensional, rectilinear, finite-difference time-domain grids. The resulting hybrid-grid modeling capability allows the higher resolution and fidelity of modeling afforded by free meshes to be combined with the simplicity and efficiency of rectilinear techniques. Integration of these new methods into the full-featured, general-purpose QUICKSILVER electromagnetic, Particle-In-Cell (PIC) code provides new modeling capability for a wide variety of electromagnetic and plasma physics problems. To completely exploit the integration of this technology into QUICKSILVER for applications requiring the self-consistent treatment of charged particles, this project has extended existing PIC methods for operation on these hybrid unstructured/rectilinear meshes. Several technical issues had to be addressed in order to accomplish this goal, including the location of particles on the unstructured mesh, adequate conservation of charge, and the proper handling of particles in the transition region between structured and unstructured portions of the hybrid grid.
Numerical Modelling of Staged Combustion Aft-Injected Hybrid Rocket Motors
NASA Astrophysics Data System (ADS)
Nijsse, Jeff
The staged combustion aft-injected hybrid (SCAIH) rocket motor is a promising design for the future of hybrid rocket propulsion. Advances in computational fluid dynamics and scientific computing have made computational modelling an effective tool in hybrid rocket motor design and development. The focus of this thesis is the numerical modelling of the SCAIH rocket motor in a turbulent combustion, high-speed, reactive flow framework accounting for solid soot transport and radiative heat transfer. The SCAIH motor is modelled with a shear coaxial injector with liquid oxygen injected in the center at sub-critical conditions: 150 K and 150 m/s (Mach ≈ 0.9), and a gas-generator gas-solid mixture of one-third carbon soot by mass injected in the annual opening at 1175 K and 460 m/s (Mach ≈ 0.6). Flow conditions in the near injector region and the flame anchoring mechanism are of particular interest. Overall, the flow is shown to exhibit instabilities and the flame is shown to anchor directly on the injector faceplate with temperatures in excess of 2700 K.
From CAD to Digital Modeling: the Necessary Hybridization of Processes
NASA Astrophysics Data System (ADS)
Massari, G. A.; Bernardi, F.; Cristofolini, A.
2011-09-01
The essay deals with the themes of digital representation of architecture starting from several years of teaching activity which is growing within the course of Automatic Design of the degree course in Engineering/Architecture in the University of Trento. With the development of CAD systems, architectural representation lies less in the tracking of a simple graph and drawn deeper into a series of acts of building a complex digital model, which can be used as a data base on which to report all the stages of project and interpretation work, and from which to derive final drawings and documents. The advent of digital technology has led to increasing difficulty in finding explicit connections between one type of operation and the subsequent outcome; thereby increasing need for guidelines, the need to understand in order to precede the changes, the desire not to be overwhelmed by uncontrollable influences brought by technological hardware and software systems to use only in accordance with the principle of maximum productivity. Formation occupies a crucial role because has the ability to direct the profession toward a thoughtful and selective use of specific applications; teaching must build logical routes in the fluid world of info-graphics and the only way to do so is to describe its contours through method indications: this will consist in understanding, studying and divulging what in its mobility does not change, as procedural issues, rather than what is transitory in its fixity, as manual questions.
Hybrid Structural Model of the Complete Human ESCRT-0 Complex
Ren, Xuefeng; Kloer, Daniel P.; Kim, Young C.; Ghirlando, Rodolfo; Saidi, Layla F.; Hummer, Gerhard; Hurley, James H.
2009-03-31
The human Hrs and STAM proteins comprise the ESCRT-0 complex, which sorts ubiquitinated cell surface receptors to lysosomes for degradation. Here we report a model for the complete ESCRT-0 complex based on the crystal structure of the Hrs-STAM core complex, previously solved domain structures, hydrodynamic measurements, and Monte Carlo simulations. ESCRT-0 expressed in insect cells has a hydrodynamic radius of R{sub H} = 7.9 nm and is a 1:1 heterodimer. The 2.3 {angstrom} crystal structure of the ESCRT-0 core complex reveals two domain-swapped GAT domains and an antiparallel two-stranded coiled-coil, similar to yeast ESCRT-0. ESCRT-0 typifies a class of biomolecular assemblies that combine structured and unstructured elements, and have dynamic and open conformations to ensure versatility in target recognition. Coarse-grained Monte Carlo simulations constrained by experimental R{sub H} values for ESCRT-0 reveal a dynamic ensemble of conformations well suited for diverse functions.
Hybrid structural model of the complete human ESCRT-0 complex.
Ren, Xuefeng; Kloer, Daniel P; Kim, Young C; Ghirlando, Rodolfo; Saidi, Layla F; Hummer, Gerhard; Hurley, James H
2009-03-11
The human Hrs and STAM proteins comprise the ESCRT-0 complex, which sorts ubiquitinated cell surface receptors to lysosomes for degradation. Here we report a model for the complete ESCRT-0 complex based on the crystal structure of the Hrs-STAM core complex, previously solved domain structures, hydrodynamic measurements, and Monte Carlo simulations. ESCRT-0 expressed in insect cells has a hydrodynamic radius of RH = 7.9 nm and is a 1:1 heterodimer. The 2.3 Angstroms crystal structure of the ESCRT-0 core complex reveals two domain-swapped GAT domains and an antiparallel two-stranded coiled-coil, similar to yeast ESCRT-0. ESCRT-0 typifies a class of biomolecular assemblies that combine structured and unstructured elements, and have dynamic and open conformations to ensure versatility in target recognition. Coarse-grained Monte Carlo simulations constrained by experimental RH values for ESCRT-0 reveal a dynamic ensemble of conformations well suited for diverse functions. PMID:19278655
Effects of Na+ and He+ pickup ions on the lunar plasma environment: 3D hybrid modeling
NASA Astrophysics Data System (ADS)
Lipatov, A. S.; Cooper, J. F.; Sittler, E. C.; Hartle, R. E.; Sarantos, M.
2011-12-01
The hybrid kinetic model used here supports comprehensive simulation of the interaction between different spatial and energetic elements of the moon-solar wind-magnetosphere of the Earth system. There is a set of MHD,kinetic, hybrid, drift kinetic, electrostatic and full kinetic modeling of the lunar plasma environment [1]. However, observations show the existence of several species of the neutrals and pickup ions like Na, He, K, O etc., (see e.g., [2,3,4]). The solar wind parameters are chosen from the ARTEMIS observations [5]. The Na+, He+ lunar exosphere's parameters are chosen from [6,7]. The hybrid kinetic model allows us to take into account the finite gyroradius effects of pickup ions and to correctly estimate the ions velocity distribution and the fluxes along the magnetic field, and on the lunar surface. Modeling shows the formation of the asymmetric Mach cone, the structuring of the pickup ion tails, and presents another type of lunar-solar wind interaction. We will compare the results of our modeling with observed distributions. References [1] Lipatov, A.S., and Cooper, J.F., Hybrid kinetic modeling of the Lunar plasma environment: Past, present and future. In: Lunar Dust, Plasma and Atmosphere: The Next Steps, January 27-29, 2010, Boulder, Colorado, Abstracts/lpa2010.colorado.edu/. [2] Potter, A.E., and Morgan, T.H., Discovery of sodium and potassium vapor in the atmosphere of the Moon, Science, 241, 675-680, doi:10.1126/science.241.4866.675, 1988. [3] Tyler, A.L., et al., Observations of sodium in the tenuous lunar atmosphere, Geophys. Res. Lett., 15(10), 1141-1144, doi:10.1029/GL015i010p01141, 1988. [4] Tanaka, T., et al., First in situ observation of the Moon-originating ions in the Earth's Magnetosphere by MAP-PACE on SELENE (KAGUYA), Geophys. Res. Lett., 36, L22106, doi:10.1029/2009GL040682, 2009. [5] Wiehle, S., et al., First Lunar Wake Passage of ARTEMIS: Discrimination of Wake Effects and Solar Wind Fluctuations by 3D Hybrid Simulations, Planet
Continuing Development of a Hybrid Model (VSH) of the Neutral Thermosphere
NASA Technical Reports Server (NTRS)
Burns, Alan
1996-01-01
We propose to continue the development of a new operational model of neutral thermospheric density, composition, temperatures and winds to improve current engineering environment definitions of the neutral thermosphere. This model will be based on simulations made with the National Center for Atmospheric Research (NCAR) Thermosphere-Ionosphere- Electrodynamic General Circulation Model (TIEGCM) and on empirical data. It will be capable of using real-time geophysical indices or data from ground-based and satellite inputs and provides neutral variables at specified locations and times. This "hybrid" model will be based on a Vector Spherical Harmonic (VSH) analysis technique developed (over the last 8 years) at the University of Michigan that permits the incorporation of the TIGCM outputs and data into the model. The VSH model will be a more accurate version of existing models of the neutral thermospheric, and will thus improve density specification for satellites flying in low Earth orbit (LEO).
A Hybrid Resynthesis Model for Hammer-String Interaction of Piano Tones
NASA Astrophysics Data System (ADS)
Bensa, Julien; Jensen, Kristoffer; Kronland-Martinet, Richard
2004-12-01
This paper presents a source/resonator model of hammer-string interaction that produces realistic piano sound. The source is generated using a subtractive signal model. Digital waveguides are used to simulate the propagation of waves in the resonator. This hybrid model allows resynthesis of the vibration measured on an experimental setup. In particular, the nonlinear behavior of the hammer-string interaction is taken into account in the source model and is well reproduced. The behavior of the model parameters (the resonant part and the excitation part) is studied with respect to the velocities and the notes played. This model exhibits physically and perceptually related parameters, allowing easy control of the sound produced. This research is an essential step in the design of a complete piano model.
Cilfone, Nicholas A.; Kirschner, Denise E.; Linderman, Jennifer J.
2015-01-01
Biologically related processes operate across multiple spatiotemporal scales. For computational modeling methodologies to mimic this biological complexity, individual scale models must be linked in ways that allow for dynamic exchange of information across scales. A powerful methodology is to combine a discrete modeling approach, agent-based models (ABMs), with continuum models to form hybrid models. Hybrid multi-scale ABMs have been used to simulate emergent responses of biological systems. Here, we review two aspects of hybrid multi-scale ABMs: linking individual scale models and efficiently solving the resulting model. We discuss the computational choices associated with aspects of linking individual scale models while simultaneously maintaining model tractability. We demonstrate implementations of existing numerical methods in the context of hybrid multi-scale ABMs. Using an example model describing Mycobacterium tuberculosis infection, we show relative computational speeds of various combinations of numerical methods. Efficient linking and solution of hybrid multi-scale ABMs is key to model portability, modularity, and their use in understanding biological phenomena at a systems level. PMID:26366228
Yilmaz, L. Safak; Loy, Alexander; Wright, Erik S.; Wagner, Michael; Noguera, Daniel R.
2012-01-01
Application of high-density microarrays to the diagnostic analysis of microbial communities is challenged by the optimization of oligonucleotide probe sensitivity and specificity, as it is generally unfeasible to experimentally test thousands of probes. This study investigated the adjustment of hybridization stringency using formamide with the idea that sensitivity and specificity can be optimized during probe design if the hybridization efficiency of oligonucleotides with target and non-target molecules can be predicted as a function of formamide concentration. Sigmoidal denaturation profiles were obtained using fluorescently labeled and fragmented 16S rRNA gene amplicon of Escherichia coli as the target with increasing concentrations of formamide in the hybridization buffer. A linear free energy model (LFEM) was developed and microarray-specific nearest neighbor rules were derived. The model simulated formamide melting with a denaturant m-value that increased hybridization free energy (ΔG°) by 0.173 kcal/mol per percent of formamide added (v/v). Using the LFEM and specific probe sets, free energy rules were systematically established to predict the stability of single and double mismatches, including bulged and tandem mismatches. The absolute error in predicting the position of experimental denaturation profiles was less than 5% formamide for more than 90 percent of probes, enabling a practical level of accuracy in probe design. The potential of the modeling approach for probe design and optimization is demonstrated using a dataset including the 16S rRNA gene of Rhodobacter sphaeroides as an additional target molecule. The LFEM and thermodynamic databases were incorporated into a computational tool (ProbeMelt) that is freely available at http://DECIPHER.cee.wisc.edu. PMID:22952791
Huda, Shamsul; Yearwood, John; Togneri, Roberto
2014-10-01
The expectation maximization (EM) is the standard training algorithm for hidden Markov model (HMM). However, EM faces a local convergence problem in HMM estimation. This paper attempts to overcome this problem of EM and proposes hybrid metaheuristic approaches to EM for HMM. In our earlier research, a hybrid of a constraint-based evolutionary learning approach to EM (CEL-EM) improved HMM estimation. In this paper, we propose a hybrid simulated annealing stochastic version of EM (SASEM) that combines simulated annealing (SA) with EM. The novelty of our approach is that we develop a mathematical reformulation of HMM estimation by introducing a stochastic step between the EM steps and combine SA with EM to provide better control over the acceptance of stochastic and EM steps for better HMM estimation. We also extend our earlier work and propose a second hybrid which is a combination of an EA and the proposed SASEM, (EA-SASEM). The proposed EA-SASEM uses the best constraint-based EA strategies from CEL-EM and stochastic reformulation of HMM. The complementary properties of EA and SA and stochastic reformulation of HMM of SASEM provide EA-SASEM with sufficient potential to find better estimation for HMM. To the best of our knowledge, this type of hybridization and mathematical reformulation have not been explored in the context of EM and HMM training. The proposed approaches have been evaluated through comprehensive experiments to justify their effectiveness in signal modeling using the speech corpus: TIMIT. Experimental results show that proposed approaches obtain higher recognition accuracies than the EM algorithm and CEL-EM as well. PMID:24686310
NASA Astrophysics Data System (ADS)
Economou, J. T.; Knowles, K.; Tsourdos, A.; White, B. A.
2011-02-01
In this article, the fuzzy-hybrid modelling (FHM) approach is used and compared to the input-output system Takagi-Sugeno (TS) modelling approach which correlates the drivetrain power flow equations with the vehicle dynamics. The output power relations were related to the drivetrain bounded efficiencies and also to the wheel slips. The model relates also to the wheel and ground interactions via suitable friction coefficient models relative to the wheel slip profiles. The wheel slip had a significant efficiency contribution to the overall driveline system efficiency. The peak friction slip and peak coefficient of friction values are known a priori during the analysis. Lastly, the rigid body dynamical power has been verified through both simulation and experimental results. The mathematical analysis has been supported throughout the paper via experimental data for a specific electric robotic vehicle. The identification of the localised and input-output TS models for the fuzzy hybrid and the experimental data were obtained utilising the subtractive clustering (SC) methodology. These results were also compared to a real-time TS SC approach operating on periodic time windows. This article concludes with the benefits of the real-time FHM method for the vehicle electric driveline due to the advantage of both the analytical TS sub-model and the physical system modelling for the remaining process which can be clearly utilised for control purposes.
NASA Astrophysics Data System (ADS)
McLarty, Dustin Fogle
Distributed energy systems are a promising means by which to reduce both emissions and costs. Continuous generators must be responsive and highly efficiency to support building dynamics and intermittent on-site renewable power. Fuel cell -- gas turbine hybrids (FC/GT) are fuel-flexible generators capable of ultra-high efficiency, ultra-low emissions, and rapid power response. This work undertakes a detailed study of the electrochemistry, chemistry and mechanical dynamics governing the complex interaction between the individual systems in such a highly coupled hybrid arrangement. The mechanisms leading to the compressor stall/surge phenomena are studied for the increased risk posed to particular hybrid configurations. A novel fuel cell modeling method introduced captures various spatial resolutions, flow geometries, stack configurations and novel heat transfer pathways. Several promising hybrid configurations are analyzed throughout the work and a sensitivity analysis of seven design parameters is conducted. A simple estimating method is introduced for the combined system efficiency of a fuel cell and a turbine using component performance specifications. Existing solid oxide fuel cell technology is capable of hybrid efficiencies greater than 75% (LHV) operating on natural gas, and existing molten carbonate systems greater than 70% (LHV). A dynamic model is calibrated to accurately capture the physical coupling of a FC/GT demonstrator tested at UC Irvine. The 2900 hour experiment highlighted the sensitivity to small perturbations and a need for additional control development. Further sensitivity studies outlined the responsiveness and limits of different control approaches. The capability for substantial turn-down and load following through speed control and flow bypass with minimal impact on internal fuel cell thermal distribution is particularly promising to meet local demands or provide dispatchable support for renewable power. Advanced control and dispatch
Stroke maximizing and high efficient hysteresis hybrid modeling for a rhombic piezoelectric actuator
NASA Astrophysics Data System (ADS)
Shao, Shubao; Xu, Minglong; Zhang, Shuwen; Xie, Shilin
2016-06-01
Rhombic piezoelectric actuator (RPA), which employs a rhombic mechanism to amplify the small stroke of PZT stack, has been widely used in many micro-positioning machineries due to its remarkable properties such as high displacement resolution and compact structure. In order to achieve large actuation range along with high accuracy, the stroke maximizing and compensation for the hysteresis are two concerns in the use of RPA. However, existing maximization methods based on theoretical model can hardly accurately predict the maximum stroke of RPA because of approximation errors that are caused by the simplifications that must be made in the analysis. Moreover, despite the high hysteresis modeling accuracy of Preisach model, its modeling procedure is trivial and time-consuming since a large set of experimental data is required to determine the model parameters. In our research, to improve the accuracy of theoretical model of RPA, the approximation theory is employed in which the approximation errors can be compensated by two dimensionless coefficients. To simplify the hysteresis modeling procedure, a hybrid modeling method is proposed in which the parameters of Preisach model can be identified from only a small set of experimental data by using the combination of discrete Preisach model (DPM) with particle swarm optimization (PSO) algorithm. The proposed novel hybrid modeling method can not only model the hysteresis with considerable accuracy but also significantly simplified the modeling procedure. Finally, the inversion of hysteresis is introduced to compensate for the hysteresis non-linearity of RPA, and consequently a pseudo-linear system can be obtained.
Lithio, Andrew; Nettleton, Dan
2016-01-01
The performance of inbred and hybrid genotypes is of interest in plant breeding and genetics. High-throughput sequencing of RNA (RNA-seq) has proven to be a useful tool in the study of the molecular genetic responses of inbreds and hybrids to environmental stresses. Commonly used experimental designs and sequencing methods lead to complex data structures that require careful attention in data analysis. We demonstrate an analysis of RNA-seq data from a split-plot design involving drought stress applied to two inbred genotypes and two hybrids formed by crosses between the inbreds. Our generalized linear modeling strategy incorporates random effects for whole-plot experimental units and uses negative binomial distributions to allow for overdispersion in count responses for split-plot experimental units. Variations in gene length and base content, as well as differences in sequencing intensity across experimental units, are also accounted for. Hierarchical modeling with thoughtful parameterization and prior specification allows for borrowing of information across genes to improve estimation of dispersion parameters, genotype effects, treatment effects, and interaction effects of primary interest. PMID:27110090
Eroglu, Duygu Yilmaz; Ozmutlu, H Cenk
2014-01-01
We developed mixed integer programming (MIP) models and hybrid genetic-local search algorithms for the scheduling problem of unrelated parallel machines with job sequence and machine-dependent setup times and with job splitting property. The first contribution of this paper is to introduce novel algorithms which make splitting and scheduling simultaneously with variable number of subjobs. We proposed simple chromosome structure which is constituted by random key numbers in hybrid genetic-local search algorithm (GAspLA). Random key numbers are used frequently in genetic algorithms, but it creates additional difficulty when hybrid factors in local search are implemented. We developed algorithms that satisfy the adaptation of results of local search into the genetic algorithms with minimum relocation operation of genes' random key numbers. This is the second contribution of the paper. The third contribution of this paper is three developed new MIP models which are making splitting and scheduling simultaneously. The fourth contribution of this paper is implementation of the GAspLAMIP. This implementation let us verify the optimality of GAspLA for the studied combinations. The proposed methods are tested on a set of problems taken from the literature and the results validate the effectiveness of the proposed algorithms. PMID:24977204
Nandola, Naresh N; Rivera, Daniel E
2013-01-01
We consider an improved model predictive control (MPC) formulation for linear hybrid systems described by mixed logical dynamical (MLD) models. The algorithm relies on a multiple-degree-of-freedom parametrization that enables the user to adjust the speed of setpoint tracking, measured disturbance rejection and unmeasured disturbance rejection independently in the closed-loop system. Consequently, controller tuning is more flexible and intuitive than relying on objective function weights (such as move suppression) traditionally used in MPC schemes. The controller formulation is motivated by the needs of non-traditional control applications that are suitably described by hybrid production-inventory systems. Two applications are considered in this paper: adaptive, time-varying interventions in behavioral health, and inventory management in supply chains under conditions of limited capacity. In the adaptive intervention application, a hypothetical intervention inspired by the Fast Track program, a real-life preventive intervention for reducing conduct disorder in at-risk children, is examined. In the inventory management application, the ability of the algorithm to judiciously alter production capacity under conditions of varying demand is presented. These case studies demonstrate that MPC for hybrid systems can be tuned for desired performance under demanding conditions involving noise and uncertainty. PMID:24348004
Mixed model approaches for the identification of QTLs within a maize hybrid breeding program.
van Eeuwijk, Fred A; Boer, Martin; Totir, L Radu; Bink, Marco; Wright, Deanne; Winkler, Christopher R; Podlich, Dean; Boldman, Keith; Baumgarten, Andy; Smalley, Matt; Arbelbide, Martin; ter Braak, Cajo J F; Cooper, Mark
2010-01-01
Two outlines for mixed model based approaches to quantitative trait locus (QTL) mapping in existing maize hybrid selection programs are presented: a restricted maximum likelihood (REML) and a Bayesian Markov Chain Monte Carlo (MCMC) approach. The methods use the in-silico-mapping procedure developed by Parisseaux and Bernardo (2004) as a starting point. The original single-point approach is extended to a multi-point approach that facilitates interval mapping procedures. For computational and conceptual reasons, we partition the full set of relationships from founders to parents of hybrids into two types of relations by defining so-called intermediate founders. QTL effects are defined in terms of those intermediate founders. Marker based identity by descent relationships between intermediate founders define structuring matrices for the QTL effects that change along the genome. The dimension of the vector of QTL effects is reduced by the fact that there are fewer intermediate founders than parents. Furthermore, additional reduction in the number of QTL effects follows from the identification of founder groups by various algorithms. As a result, we obtain a powerful mixed model based statistical framework to identify QTLs in genetic backgrounds relevant to the elite germplasm of a commercial breeding program. The identification of such QTLs will provide the foundation for effective marker assisted and genome wide selection strategies. Analyses of an example data set show that QTLs are primarily identified in different heterotic groups and point to complementation of additive QTL effects as an important factor in hybrid performance. PMID:19921142
Toward real-time three-dimensional mapping of surficial aquifers using a hybrid modeling approach
NASA Astrophysics Data System (ADS)
Friedel, Michael J.; Esfahani, Akbar; Iwashita, Fabio
2016-02-01
A hybrid modeling approach is proposed for near real-time three-dimensional (3D) mapping of surficial aquifers. First, airborne frequency-domain electromagnetic (FDEM) measurements are numerically inverted to obtain subsurface resistivities. Second, a machine-learning (ML) algorithm is trained using the FDEM measurements and inverted resistivity profiles, and borehole geophysical and hydrogeologic data. Third, the trained ML algorithm is used together with independent FDEM measurements to map the spatial distribution of the aquifer system. Efficacy of the hybrid approach is demonstrated for mapping a heterogeneous surficial aquifer and confining unit in northwestern Nebraska, USA. For this case, independent performance testing reveals that aquifer mapping is unbiased with a strong correlation (0.94) among numerically inverted and ML-estimated binary (clay-silt or sand-gravel) layer resistivities (5-20 ohm-m or 21-5,000 ohm-m), and an intermediate correlation (0.74) for heterogeneous (clay, silt, sand, gravel) layer resistivities (5-5,000 ohm-m). Reduced correlation for the heterogeneous model is attributed to over-estimating the under-sampled high-resistivity gravels (about 0.5 % of the training data), and when removed the correlation increases (0.87). Independent analysis of the numerically inverted and ML-estimated resistivities finds that the hybrid procedure preserves both univariate and spatial statistics for each layer. Following training, the algorithms can map 3D surficial aquifers as fast as leveled FDEM measurements are presented to the ML network.
Improved Hybrid Monte Carlo/n-Moment Transport Equations Model for the Polar Wind
NASA Astrophysics Data System (ADS)
Barakat, A. R.; Ji, J.; Schunk, R. W.
2013-12-01
In many space plasma problems (e.g. terrestrial polar wind, solar wind, etc.), the plasma gradually evolves from dense collision-dominated into rarified collisionless conditions. For decades, numerous attempts were made in order to address this type of problem using simulations based on one of two approaches. These approaches are: (1) the (fluid-like) Generalized Transport Equations, GTE, and (2) the particle-based Monte Carlo (MC) techniques. In contrast to the computationally intensive MC, the GTE approach can be considerably more efficient but its validity is questionable outside the collision-dominated region depending on the number of transport parameters considered. There have been several attempts to develop hybrid models that combine the strengths of both approaches. In particular, low-order GTE formulations were applied within the collision-dominated region, while an MC simulation was applied within the collisionless region and in the collisional-to-collisionless transition region. However, attention must be paid to assuring the consistency of the two approaches in the region where they are matched. Contrary to all previous studies, our model pays special attention to the ';matching' issue, and hence eliminates the discontinuities/inaccuracies associated with mismatching. As an example, we applied our technique to the Coulomb-Milne problem because of its relevance to the problem of space plasma flow from high- to low-density regions. We will compare the velocity distribution function and its moments (density, flow velocity, temperature, etc.) from the following models: (1) the pure MC model, (2) our hybrid model, and (3) previously published hybrid models. We will also consider a wide range of the test-to-background mass ratio.
Shape memory alloy micro-actuator performance prediction using a hybrid constitutive model
NASA Astrophysics Data System (ADS)
Wong, Franklin C.; Boissonneault, Olivier
2006-03-01
The volume and weight budgets in missiles and gun-launched munitions have decreased with the military forces' emphasis on soldier-centric systems and rapid deployability. Reduction in the size of control actuation systems employed in today's aerospace vehicles would enhance overall vehicle performance as long as there is no detrimental impact on flight performance. Functional materials such as shape memory alloys (SMA's) offer the opportunity to create compact, solid-state actuation systems for flight applications. A hybrid SMA model was developed for designing micro-actuated flow effectors. It was based on a combination of concepts originally presented by Likhatchev for microstructural modelling and Brinson for modelling of transformation kinetics. The phase diagram for a 0.1mm SMA wire was created by carrying out tensile tests in a Rheometrics RSA-II solids analyser over a range of temperatures from 30°C to 130°C. The characterization parameters were used in the hybrid model to predict the displacement-time trajectories for the wire. Experimental measurements were made for a SMA wire that was subjected to a constant 150g load and short, intense 4.5 to 10V pulses. Actuation frequency was limited by the cooling rate rather than the heating rate. A second set of experiments studied the performance of SMA wires in an antagonistic micro-actuator set-up. A series of 2 or 3V step inputs were alternately injected into each wire to characterize the peak to peak displacement and the motion time constant. A maximum frequency of 0.25Hz was observed. An antagonistic actuator model based on the hybrid SMA model predicted reasonably well the displacement-time results.
A Hybrid PIC/DSMC Model of Breakdown in Triggered Vacuum Spark Gaps
NASA Astrophysics Data System (ADS)
Moore, Stan G.; Moore, Christopher H.; Boerner, Jeremiah J.
2014-10-01
Triggered vacuum spark gaps (TVSGs) can be used as high voltage, high current switches with a fast switching time and a variable operating voltage, such as in pulsed power applications and crowbar circuits that protect against overvoltage conditions. Hybrid particle-in-cell (PIC) and direct simulation Monte Carlo (DSMC) methods can be used to simulate breakdown in TVSGs. In this talk, we present results of a one-dimensional hybrid PIC/DSMC model and show that changing the density and velocity of injected neutral particles (which can be related to the surface temperature) significantly changes both the time to breakdown and the existence of a short-lived starvation mode in the current waveform. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.
Communication: Double-hybrid functionals from adiabatic-connection: The QIDH model
NASA Astrophysics Data System (ADS)
Brémond, Éric; Sancho-García, Juan Carlos; Pérez-Jiménez, Ángel José; Adamo, Carlo
2014-07-01
A new approach stemming from the adiabatic-connection (AC) formalism is proposed to derive parameter-free double-hybrid (DH) exchange-correlation functionals. It is based on a quadratic form that models the integrand of the coupling parameter, whose components are chosen to satisfy several well-known limiting conditions. Its integration leads to DHs containing a single parameter controlling the amount of exact exchange, which is determined by requiring it to depend on the weight of the MP2 correlation contribution. Two new parameter-free DHs functionals are derived in this way, by incorporating the non-empirical PBE and TPSS functionals in the underlying expression. Their extensive testing using the GMTKN30 benchmark indicates that they are in competition with state-of-the-art DHs, yet providing much better self-interaction errors and opening a new avenue towards the design of accurate double-hybrid exchange-correlation functionals departing from the AC integrand.
Calibration of interphase fluorescence in situ hybridization cutoff by mathematical models.
Du, Qinghua; Li, Qingshan; Sun, Daochun; Chen, Xiaoyan; Yu, Bizhen; Ying, Yi
2016-03-01
Fluorescence in situ hybridization (FISH) continues to play an important role in clinical investigations. Laboratories may create their own cutoff, a percentage of positive nuclei to determine whether a specimen is positive or negative, to eliminate false positives that are created by signal overlap in most cases. In some cases, it is difficult to determine the cutoff value because of differences in both the area of nuclei and the number of signals. To address these problems, we established two mathematical models using probability theory. To verify these two models, normal disomy cells from healthy individuals were used to simulate cells with different numbers of signals by hybridization with different probes. We used an X/Y probe to obtain the average distance between two signals and the probability of signal overlap in different nuclei area. Frequencies of all signal patterns were scored and compared with theoretical frequencies, and models were assessed using a goodness of fit test. We used five BCR/ABL1-positive samples, 20 BCR/ABL1-negative samples and two samples with ambiguous results to verify the cutoff calibrated by these two models. The models were in agreement with experimental results. The dynamic cutoff can classify cases in routine analysis correctly, and it can also correct for influences from nuclei area and the number of signals in some ambiguous cases. The probability models can be used to assess the effect of signal overlap and calibrate the cutoff. © 2015 International Society for Advancement of Cytometry. PMID:26580488
NASA Astrophysics Data System (ADS)
Fiorenti, Simone; Guanetti, Jacopo; Guezennec, Yann; Onori, Simona
2013-11-01
This paper presents the development and experimental validation of a dynamic model of a Hybridized Energy Storage System (HESS) consisting of a parallel connection of a lead acid (PbA) battery and double layer capacitors (DLCs), for automotive applications. The dynamic modeling of both the PbA battery and the DLC has been tackled via the equivalent electric circuit based approach. Experimental tests are designed for identification purposes. Parameters of the PbA battery model are identified as a function of state of charge and current direction, whereas parameters of the DLC model are identified for different temperatures. A physical HESS has been assembled at the Center for Automotive Research The Ohio State University and used as a test-bench to validate the model against a typical current profile generated for Start&Stop applications. The HESS model is then integrated into a vehicle simulator to assess the effects of the battery hybridization on the vehicle fuel economy and mitigation of the battery stress.
Application of the hybrid-Trefftz finite element model to thin shell analysis
NASA Astrophysics Data System (ADS)
Voros, Gabor
The paper presents the results of a preliminary study on thin shallow shell element based on the hybrid-Trefftz (HT) model. This model adopts an assumed nonconforming displacement field which satisfies a priori the governing differential equations. The interelement continuity and the boundary conditions are enforced by frame fields defined in terms of the conventional nodal freedoms. In the p-extension, the frame functions involve an optional number of hierarchic displacement modes. Numerical results present the capability of the new shell element which can be implemented in existing finite element codes.
NASA Astrophysics Data System (ADS)
Wen, De-Qi; Liu, Wei; Gao, Fei; Lieberman, M. A.; Wang, You-Nian
2016-08-01
A hybrid model, i.e. a global model coupled bidirectionally with a parallel Monte-Carlo collision (MCC) sheath model, is developed to investigate an inductively coupled discharge with a bias source. This hybrid model can self-consistently reveal the interaction between the bulk plasma and the radio frequency (rf) bias sheath. More specifically, the plasma parameters affecting characteristics of rf bias sheath (sheath length and self-bias) are calculated by a global model and the effect of the rf bias sheath on the bulk plasma is determined by the voltage drop of the rf bias sheath. Moreover, specific numbers of ions are tracked in the rf bias sheath and ultimately the ion energy distribution function (IEDF) incident on the bias electrode is obtained. To validate this model, both bulk plasma density and IEDF on the bias electrode in an argon discharge are compared with experimental measurements, and a good agreement is obtained. The advantage of this model is that it can quickly calculate the bulk plasma density and IEDF on the bias electrode, which are of practical interest in industrial plasma processing, and the model could be easily extended to serve for industrial gases.
NASA Astrophysics Data System (ADS)
Humphrey, Greer B.; Gibbs, Matthew S.; Dandy, Graeme C.; Maier, Holger R.
2016-09-01
Monthly streamflow forecasts are needed to support water resources decision making in the South East of South Australia, where baseflow represents a significant proportion of the total streamflow and soil moisture and groundwater are important predictors of runoff. To address this requirement, the utility of a hybrid monthly streamflow forecasting approach is explored, whereby simulated soil moisture from the GR4J conceptual rainfall-runoff model is used to represent initial catchment conditions in a Bayesian artificial neural network (ANN) statistical forecasting model. To assess the performance of this hybrid forecasting method, a comparison is undertaken of the relative performances of the Bayesian ANN, the GR4J conceptual model and the hybrid streamflow forecasting approach for producing 1-month ahead streamflow forecasts at three key locations in the South East of South Australia. Particular attention is paid to the quantification of uncertainty in each of the forecast models and the potential for reducing forecast uncertainty by using the hybrid approach is considered. Case study results suggest that the hybrid models developed in this study are able to take advantage of the complementary strengths of both the ANN models and the GR4J conceptual models. This was particularly the case when forecasting high flows, where the hybrid models were shown to outperform the two individual modelling approaches in terms of the accuracy of the median forecasts, as well as reliability and resolution of the forecast distributions. In addition, the forecast distributions generated by the hybrid models were up to 8 times more precise than those based on climatology; thus, providing a significant improvement on the information currently available to decision makers.
A hybrid method for modelling two dimensional non-breaking and breaking waves
NASA Astrophysics Data System (ADS)
Sriram, V.; Ma, Q. W.; Schlurmann, T.
2014-09-01
This is the first paper to present a hybrid method coupling an Improved Meshless Local Petrov Galerkin method with Rankine source solution (IMLPG_R) based on the Navier-Stokes (NS) equations, with a finite element method (FEM) based on the fully nonlinear potential flow theory (FNPT) in order to efficiently simulate the violent waves and their interaction with marine structures. The two models are strongly coupled in space and time domains using a moving overlapping zone, wherein the information from both the solvers is exchanged. In the time domain, the Runge-Kutta 2nd order method is nested with a predictor-corrector scheme. In the space domain, numerical techniques including ‘Feeding Particles’ and two-layer particle interpolation with relaxation coefficients are introduced to achieve the robust coupling of the two models. The properties and behaviours of the new hybrid model are tested by modelling a regular wave, solitary wave and Cnoidal wave including breaking and overtopping. It is validated by comparing the results of the method with analytical solutions, results from other methods and experimental data. The paper demonstrates that the method can produce satisfactory results but uses much less computational time compared with a method based on the full NS model.
Measured and modelled carbon and water fluxes in hybrid willows grown for biofuel production
NASA Astrophysics Data System (ADS)
Wertin, T. M.; LeBauer, D.; Volk, T.; Long, S.; Leakey, A. D.
2014-12-01
Biofuels have the potential to meet future energy needs. Worldwide, up to 75% of biofuels produced are derived from woody sources. Coppiced hybrid willow is among the most promising woody biofuel sources due to its ability to rapidly regenerate after cutting, high biomass yields, low nutrient requirements and ability to be grown on marginal land, abandoned land and land easily erodible under annual cultivation. However, models used to assess the potential viability and sustainability of commercial biomass production by willow in the northeastern, northern and northwestern USA remain unsophisticated and lack key parameterization data. Most significantly, models do not explicitly represent the coppiced growth form. This study tests the ability of a canopy model to predict carbon and water fluxes in two highly productive, but structurally distinct hybrid willows (Salix miyabeana and Salix purpurea) grown in central NY. S. miyaneana has only a few, large diameter stems per stool prior to harvest, while S. purpurea maintains numerous, small diameter stems until harvest. Canopy structure also varies substantially within a growing season. For example, in S. miyabeana stem number decreased by 40% while total basal area increased by 50% within year 2 of the third coppice cycle. Model predictions of water use are compared with stand transpiration measured by sap flow. Model predictions of biomass production are compared to destructive harvest data. Sensitivity of predicted fluxes to variation between genotypes in key physiological parameters is also tested.
Hybrid pathwise sensitivity methods for discrete stochastic models of chemical reaction systems
Wolf, Elizabeth Skubak; Anderson, David F.
2015-01-21
Stochastic models are often used to help understand the behavior of intracellular biochemical processes. The most common such models are continuous time Markov chains (CTMCs). Parametric sensitivities, which are derivatives of expectations of model output quantities with respect to model parameters, are useful in this setting for a variety of applications. In this paper, we introduce a class of hybrid pathwise differentiation methods for the numerical estimation of parametric sensitivities. The new hybrid methods combine elements from the three main classes of procedures for sensitivity estimation and have a number of desirable qualities. First, the new methods are unbiased for a broad class of problems. Second, the methods are applicable to nearly any physically relevant biochemical CTMC model. Third, and as we demonstrate on several numerical examples, the new methods are quite efficient, particularly if one wishes to estimate the full gradient of parametric sensitivities. The methods are rather intuitive and utilize the multilevel Monte Carlo philosophy of splitting an expectation into separate parts and handling each in an efficient manner.
Hybridization modeling of oligonucleotide SNP arrays for accurate DNA copy number estimation
Wan, Lin; Sun, Kelian; Ding, Qi; Cui, Yuehua; Li, Ming; Wen, Yalu; Elston, Robert C.; Qian, Minping; Fu, Wenjiang J
2009-01-01
Affymetrix SNP arrays have been widely used for single-nucleotide polymorphism (SNP) genotype calling and DNA copy number variation inference. Although numerous methods have achieved high accuracy in these fields, most studies have paid little attention to the modeling of hybridization of probes to off-target allele sequences, which can affect the accuracy greatly. In this study, we address this issue and demonstrate that hybridization with mismatch nucleotides (HWMMN) occurs in all SNP probe-sets and has a critical effect on the estimation of allelic concentrations (ACs). We study sequence binding through binding free energy and then binding affinity, and develop a probe intensity composite representation (PICR) model. The PICR model allows the estimation of ACs at a given SNP through statistical regression. Furthermore, we demonstrate with cell-line data of known true copy numbers that the PICR model can achieve reasonable accuracy in copy number estimation at a single SNP locus, by using the ratio of the estimated AC of each sample to that of the reference sample, and can reveal subtle genotype structure of SNPs at abnormal loci. We also demonstrate with HapMap data that the PICR model yields accurate SNP genotype calls consistently across samples, laboratories and even across array platforms. PMID:19586935
Development of Parametric Mass and Volume Models for an Aerospace SOFC/Gas Turbine Hybrid System
NASA Technical Reports Server (NTRS)
Tornabene, Robert; Wang, Xiao-yen; Steffen, Christopher J., Jr.; Freeh, Joshua E.
2005-01-01
In aerospace power systems, mass and volume are key considerations to produce a viable design. The utilization of fuel cells is being studied for a commercial aircraft electrical power unit. Based on preliminary analyses, a SOFC/gas turbine system may be a potential solution. This paper describes the parametric mass and volume models that are used to assess an aerospace hybrid system design. The design tool utilizes input from the thermodynamic system model and produces component sizing, performance, and mass estimates. The software is designed such that the thermodynamic model is linked to the mass and volume model to provide immediate feedback during the design process. It allows for automating an optimization process that accounts for mass and volume in its figure of merit. Each component in the system is modeled with a combination of theoretical and empirical approaches. A description of the assumptions and design analyses is presented.
Systems biology by the rules: hybrid intelligent systems for pathway modeling and discovery
Bosl, William J
2007-01-01
Background Expert knowledge in journal articles is an important source of data for reconstructing biological pathways and creating new hypotheses. An important need for medical research is to integrate this data with high throughput sources to build useful models that span several scales. Researchers traditionally use mental models of pathways to integrate information and development new hypotheses. Unfortunately, the amount of information is often overwhelming and these are inadequate for predicting the dynamic response of complex pathways. Hierarchical computational models that allow exploration of semi-quantitative dynamics are useful systems biology tools for theoreticians, experimentalists and clinicians and may provide a means for cross-communication. Results A novel approach for biological pathway modeling based on hybrid intelligent systems or soft computing technologies is presented here. Intelligent hybrid systems, which refers to several related computing methods such as fuzzy logic, neural nets, genetic algorithms, and statistical analysis, has become ubiquitous in engineering applications for complex control system modeling and design. Biological pathways may be considered to be complex control systems, which medicine tries to manipulate to achieve desired results. Thus, hybrid intelligent systems may provide a useful tool for modeling biological system dynamics and computational exploration of new drug targets. A new modeling approach based on these methods is presented in the context of hedgehog regulation of the cell cycle in granule cells. Code and input files can be found at the Bionet website: www.chip.ord/~wbosl/Software/Bionet. Conclusion This paper presents the algorithmic methods needed for modeling complicated biochemical dynamics using rule-based models to represent expert knowledge in the context of cell cycle regulation and tumor growth. A notable feature of this modeling approach is that it allows biologists to build complex models from
NASA Astrophysics Data System (ADS)
Chang, Keh-Chin; Chen, Ching-Shun
1993-03-01
A hybrid k-epsilon turbulence model, based on the concept that the modification of anisotropic effects should not be made in the flow regions inherent to small streamline curvatures, has been developed and examined with the swirling recirculating flows, with the swirl levels ranging from 0.6 to 1.23 in an abrupt pipe expansion. A fairly satisfactory agreement of model predictions with the experimental data shows that this hybrid k-epsilon model can perform better simulation of swirling recirculating flows as compared to the standard k-epsilon model and the modified k-epsilon model proposed by Abujelala and Lilley (1984).
NASA Astrophysics Data System (ADS)
Mõttus, Matti; Stenberg, Pauline; Rautiainen, Miina
2007-02-01
Photon recollision probability, or the probability by which a photon scattered from a phytoelement in the canopy will interact within the canopy again, has previously been shown to approximate well the fractions of radiation scattered and absorbed by homogeneous plant covers. To test the applicability of the recollision probability theory to more complicated canopy structures, a set of modeled stands was generated using allometric relations for Scots pine trees growing in central Finland. A hybrid geometric-optical model (FRT, or the Kuusk-Nilson model) was used to simulate the reflectance and transmittance of the modeled forests consisting of ellipsoidal tree crowns and, on the basis of the simulations, the recollision probability (p) was calculated for the canopies. As the recollision probability theory assumes energy conservation, a method to check and ensure energy conservation in the model was first developed. The method enabled matching the geometric-optical and two-stream submodels of the hybrid FRT model, and more importantly, allowed calculation of the recollision probability from model output. Next, to assess the effect of canopy structure on the recollision probability, the obtained p-values were compared to those calculated for structureless (homogeneous) canopies with similar effective LAI using a simple two-stream radiation transfer model. Canopy structure was shown to increase the recollision probability, implying that structured canopies absorb more efficiently the radiation interacting with the canopy, and it also changed the escape probabilities for different scattering orders. Most importantly, the study demonstrated that the concept of recollision probability is coherent with physically based canopy reflectance models which use the classical radiative transfer theory. Furthermore, it was shown that as a first approximation, the recollision probability can be considered to be independent of wavelength. Finally, different algorithms for
Data sensitivity in a hybrid STEP/Coulomb model for aftershock forecasting
NASA Astrophysics Data System (ADS)
Steacy, S.; Jimenez Lloret, A.; Gerstenberger, M.
2014-12-01
Operational earthquake forecasting is rapidly becoming a 'hot topic' as civil protection authorities seek quantitative information on likely near future earthquake distributions during seismic crises. At present, most of the models in public domain are statistical and use information about past and present seismicity as well as b-value and Omori's law to forecast future rates. A limited number of researchers, however, are developing hybrid models which add spatial constraints from Coulomb stress modeling to existing statistical approaches. Steacy et al. (2013), for instance, recently tested a model that combines Coulomb stress patterns with the STEP (short-term earthquake probability) approach against seismicity observed during the 2010-2012 Canterbury earthquake sequence. They found that the new model performed at least as well as, and often better than, STEP when tested against retrospective data but that STEP was generally better in pseudo-prospective tests that involved data actually available within the first 10 days of each event of interest. They suggested that the major reason for this discrepancy was uncertainty in the slip models and, in particular, in the geometries of the faults involved in each complex major event. Here we test this hypothesis by developing a number of retrospective forecasts for the Landers earthquake using hypothetical slip distributions developed by Steacy et al. (2004) to investigate the sensitivity of Coulomb stress models to fault geometry and earthquake slip, and we also examine how the choice of receiver plane geometry affects the results. We find that the results are strongly sensitive to the slip models and moderately sensitive to the choice of receiver orientation. We further find that comparison of the stress fields (resulting from the slip models) with the location of events in the learning period provides advance information on whether or not a particular hybrid model will perform better than STEP.
NASA Astrophysics Data System (ADS)
Beeri, Ofer; Rotem, Oded; Hazan, Eden; Katz, Eugene A.; Braun, Avi; Gelbstein, Yaniv
2015-09-01
An experimental demonstration of the combined photovoltaic (PV) and thermoelectric conversion of concentrated sunlight (with concentration factor, X, up to ˜300) into electricity is presented. The hybrid system is based on a multi-junction PV cell and a thermoelectric generator (TEG). The latter increases the electric power of the system and dissipates some of the excessive heat. For X ≤ 200, the system's maximal efficiency, ˜32%, was mostly due to the contribution from the PV cell. With increasing X and system temperature, the PV cell's efficiency decreased while that of the TEG increased. Accordingly, the direct electrical contribution of the TEG started to dominate in the total system power, reaching ˜20% at X ≈ 290. Using a simple steady state finite element modeling, the cooling effect of the TEG on the hybrid system's efficiency was proved to be even more significant than its direct electrical contribution for high solar concentrations. As a result, the total efficiency contribution of the TEG reached ˜40% at X ≈ 200. This suggests a new system optimization concept that takes into account the PV cell's temperature dependence and the trade-off between the direct electrical generation and cooling capabilities of the TEG. It is shown that the hybrid system has a real potential to exceed 50% total efficiency by using more advanced PV cells and TE materials.
Extensive heterosis in growth of yeast hybrids is explained by a combination of genetic models
Shapira, R; Levy, T; Shaked, S; Fridman, E; David, L
2014-01-01
Heterosis, also known as hybrid vigor, is the superior performance of a heterozygous hybrid relative to its homozygous parents. Despite the scientific curiosity of this phenotypic phenomenon and its significance for food production in agriculture, its genetic basis is insufficiently understood. Studying heterosis in yeast can potentially yield insights into its genetic basis, can allow one to test the different hypotheses that have been proposed to explain the phenomenon and allows better understanding of how to take advantage of this phenomenon to enhance food production. We therefore crossed 16 parental yeast strains to form 120 yeast hybrids, and measured their growth rates under five environmental conditions. A considerable amount of dominant genetic variation was found in growth performance, and heterosis was measured in 35% of the hybrid–condition combinations. Despite previous reports of correlations between heterosis and measures of sequence divergence between parents, we detected no such relationship. We used several analyses to examine which genetic model might explain heterosis. We found that dominance complementation of recessive alleles, overdominant interactions within loci and epistatic interactions among loci each contribute to heterosis. We concluded that in yeast heterosis is a complex phenotype created by the combined contribution of different genetic interactions. PMID:24690755
Hybrid-Trefftz six-node triangular finite element models for Helmholtz problem
NASA Astrophysics Data System (ADS)
Sze, K. Y.; Liu, G. H.
2010-08-01
In this paper, six-node hybrid-Trefftz triangular finite element models which can readily be incorporated into the standard finite element program framework in the form of additional element subroutines are devised via a hybrid variational principle for Helmholtz problem. In these elements, domain and boundary variables are independently assumed. The former is truncated from the Trefftz solution sets and the latter is obtained by the standard polynomial-based nodal interpolation. The equality of the two variables are enforced along the element boundary. Both the plane-wave solutions and Bessel solutions are employed to construct the domain variable. For full rankness of the element matrix, a minimal of six domain modes are required. By using local coordinates and directions, rank sufficient and invariant elements with six plane-wave modes, six Bessel solution modes and seven Bessel solution modes are devised. Numerical studies indicate that the hybrid-Trefftz elements are typically 50% less erroneous than their continuous Galerkin element counterpart.
Probing hybridization parameters from microarray experiments: nearest-neighbor model and beyond
Hadiwikarta, W. W.; Walter, J.-C.; Hooyberghs, J.; Carlon, E.
2012-01-01
In this article, it is shown how optimized and dedicated microarray experiments can be used to study the thermodynamics of DNA hybridization for a large number of different conformations in a highly parallel fashion. In particular, free energy penalties for mismatches are obtained in two independent ways and are shown to be correlated with values from melting experiments in solution reported in the literature. The additivity principle, which is at the basis of the nearest-neighbor model, and according to which the penalty for two isolated mismatches is equal to the sum of the independent penalties, is thoroughly tested. Additivity is shown to break down for a mismatch distance below 5 nt. The behavior of mismatches in the vicinity of the helix edges, and the behavior of tandem mismatches are also investigated. Finally, some thermodynamic outlying sequences are observed and highlighted. These sequences contain combinations of GA mismatches. The analysis of the microarray data reported in this article provides new insights on the DNA hybridization parameters and can help to increase the accuracy of hybridization-based technologies. PMID:22661582
A Two-Stage Procedure Toward the Efficient Implementation of PANS and Other Hybrid Turbulence Models
NASA Technical Reports Server (NTRS)
Abdol-Hamid, Khaled S.; Girimaji, Sharath S.
2004-01-01
The main objective of this article is to introduce and to show the implementation of a novel two-stage procedure to efficiently estimate the level of scale resolution possible for a given flow on a given grid for Partial Averaged Navier-Stokes (PANS) and other hybrid models. It has been found that the prescribed scale resolution can play a major role in obtaining accurate flow solutions. The first step is to solve the unsteady or steady Reynolds Averaged Navier-Stokes (URANS/RANS) equations. From this preprocessing step, the turbulence length-scale field is obtained. This is then used to compute the characteristic length-scale ratio between the turbulence scale and the grid spacing. Based on this ratio, we can assess the finest scale resolution that a given grid for a given flow can support. Along with other additional criteria, we are able to analytically identify the appropriate hybrid solver resolution for different regions of the flow. This procedure removes the grid dependency issue that affects the results produced by different hybrid procedures in solving unsteady flows. The formulation, implementation methodology, and validation example are presented. We implemented this capability in a production Computational Fluid Dynamics (CFD) code, PAB3D, for the simulation of unsteady flows.
NASA Astrophysics Data System (ADS)
Chen, Xueli; Liang, Jimin; Hu, Hao; Qu, Xiaochao; Yang, Defu; Chen, Duofang; Zhu, Shouping; Tian, Jie
2012-03-01
Gastric cancer is the second cause of cancer-related death in the world, and it remains difficult to cure because it has been in late-stage once that is found. Early gastric cancer detection becomes an effective approach to decrease the gastric cancer mortality. Bioluminescence tomography (BLT) has been applied to detect early liver cancer and prostate cancer metastasis. However, the gastric cancer commonly originates from the gastric mucosa and grows outwards. The bioluminescent light will pass through a non-scattering region constructed by gastric pouch when it transports in tissues. Thus, the current BLT reconstruction algorithms based on the approximation model of radiative transfer equation are not optimal to handle this problem. To address the gastric cancer specific problem, this paper presents a novel reconstruction algorithm that uses a hybrid light transport model to describe the bioluminescent light propagation in tissues. The radiosity theory integrated with the diffusion equation to form the hybrid light transport model is utilized to describe light propagation in the non-scattering region. After the finite element discretization, the hybrid light transport model is converted into a minimization problem which fuses an l1 norm based regularization term to reveal the sparsity of bioluminescent source distribution. The performance of the reconstruction algorithm is first demonstrated with a digital mouse based simulation with the reconstruction error less than 1mm. An in situ gastric cancer-bearing nude mouse based experiment is then conducted. The primary result reveals the ability of the novel BLT reconstruction algorithm in early gastric cancer detection.
Ettarh, Rajunor
2016-05-01
Significant changes have been implemented in the way undergraduate medical education is structured. One of the challenges for component courses such as histology in medical and dental curricula is to restructure and deliver training within new frameworks. This article describes the process of aligning the purpose and experience in histology laboratory to the goal of applying knowledge gained to team-based medical practice at Tulane University School of Medicine. Between 2011 and 2015, 711 medical students took either a traditional laboratory-based histology course (353 students) or a team-based hybrid histology course with active learning in laboratory (358 students). The key difference was in the laboratory component of the hybrid course - interactive table conferences in histology-during which students developed new competencies by working in teams, reviewing images, solving problems by applying histology concepts, and sharing learning. Content, faculty and online resources for microscopy were the same in both courses. More student-student and student-faculty interactions were evident during the hybrid course but student evaluation ratings and grades showed reductions following introduction of table conferences when compared to previous ratings. However, outcomes at National Board of Medical Examiners(®) (NBME(®) ) Subject Examination in Histology and Cell Biology showed significant improvement (72.4 ± 9.04 and 76.44 ± 9.36 for percent correct answers, traditional and hybrid courses, respectively, P < 0.0001). This model of table conferences to augment the traditional histology laboratory experience exemplifies the extent that restructuring enhancements can be used in currently taught courses in the undergraduate medical curriculum. Anat Sci Educ 9: 286-294. © 2016 American Association of Anatomists. PMID:26749245
Development of a Solid-Oxide Fuel Cell/Gas Turbine Hybrid System Model for Aerospace Applications
NASA Technical Reports Server (NTRS)
Freeh, Joshua E.; Pratt, Joseph W.; Brouwer, Jacob
2004-01-01
Recent interest in fuel cell-gas turbine hybrid applications for the aerospace industry has led to the need for accurate computer simulation models to aid in system design and performance evaluation. To meet this requirement, solid oxide fuel cell (SOFC) and fuel processor models have been developed and incorporated into the Numerical Propulsion Systems Simulation (NPSS) software package. The SOFC and reformer models solve systems of equations governing steady-state performance using common theoretical and semi-empirical terms. An example hybrid configuration is presented that demonstrates the new capability as well as the interaction with pre-existing gas turbine and heat exchanger models. Finally, a comparison of calculated SOFC performance with experimental data is presented to demonstrate model validity. Keywords: Solid Oxide Fuel Cell, Reformer, System Model, Aerospace, Hybrid System, NPSS
Ostermann, Lars; Seidel, Christian
2015-03-10
The numerical analysis of hydro power stations is an important method of the hydraulic design and is used for the development and optimisation of hydro power stations in addition to the experiments with the physical submodel of a full model in the hydraulic laboratory. For the numerical analysis, 2D and 3D models are appropriate and commonly used.The 2D models refer mainly to the shallow water equations (SWE), since for this flow model a large experience on a wide field of applications for the flow analysis of numerous problems in hydraulic engineering already exists. Often, the flow model is verified by in situ measurements. In order to consider 3D flow phenomena close to singularities like weirs, hydro power stations etc. the development of a hybrid fluid model is advantageous to improve the quality and significance of the global model. Here, an extended hybrid flow model based on the principle of the SWE is presented. The hybrid flow model directly links the numerical model with the experimental data, which may originate from physical full models, physical submodels and in-situ measurements. Hence a wide field of application of the hybrid model emerges including the improvement of numerical models and the strong coupling of numerical and experimental analysis.
Hybrid modeling of plasmas and applications to fusion and space physics
NASA Astrophysics Data System (ADS)
Kazeminejad, Farzad
Since the early days of controlled fusion research, plasma physicists have encountered great challenges in obtaining solutions to the highly nonlinear equations which govern the behavior of fusion plasmas; with the growth of other applications of plasma physics these problems have grown in importance. Obtaining reasonable solutions to the nonlinear equations is crucial to understanding the behavior of plasmas. With the advent of high speed computers, computer modeling of plasmas has moved into the front row of the tools used in research of their nonlinear plasma dynamics. There are roughly speaking two types of plasma models, particle models and fluid models. Particle models in general require larger memory for the computer due to the massive amounts of data associated with the particles' kinematical variables. Fluid models are better fit to handle large scales and long times. The drawback of fluid models however, is that they miss the physical phenomena taking place at the microscale and these phenomena can influence the properties of the fluids. Another approach is to start with fluid models and incorporate more physics. Such models are referred to as hybrid models: two such models are discussed. They are then applied to two problems; the first is a simulation of the artificial comet generated by the AMPTE experiment; the second is the production of enhanced noise in fusion plasmas by injected energetic ions or by fusion reaction products. In both cases, the models demonstrate qualitative agreement with the experimental observations.
Scheibe, Timothy D.; Murphy, Ellyn M.; Chen, Xingyuan; Rice, Amy K.; Carroll, Kenneth C.; Palmer, Bruce J.; Tartakovsky, Alexandre M.; Battiato, Ilenia; Wood, Brian D.
2015-01-01
One of the most significant challenges facing hydrogeologic modelers is the disparity between those spatial and temporal scales at which fundamental flow, transport and reaction processes can best be understood and quantified (e.g., microscopic to pore scales, seconds to days) and those at which practical model predictions are needed (e.g., plume to aquifer scales, years to centuries). While the multiscale nature of hydrogeologic problems is widely recognized, technological limitations in computational and characterization restrict most practical modeling efforts to fairly coarse representations of heterogeneous properties and processes. For some modern problems, the necessary level of simplification is such that model parameters may lose physical meaning and model predictive ability is questionable for any conditions other than those to which the model was calibrated. Recently, there has been broad interest across a wide range of scientific and engineering disciplines in simulation approaches that more rigorously account for the multiscale nature of systems of interest. In this paper, we review a number of such approaches and propose a classification scheme for defining different types of multiscale simulation methods and those classes of problems to which they are most applicable. Our classification scheme is presented in terms of a flow chart (Multiscale Analysis Platform or MAP), and defines several different motifs of multiscale simulation. Within each motif, the member methods are reviewed and example applications are discussed. We focus attention on hybrid multiscale methods, in which two or more models with different physics described at fundamentally different scales are directly coupled within a single simulation. Very recently these methods have begun to be applied to groundwater flow and transport simulations, and we discuss these applications in the context of our classification scheme. As computational and characterization capabilities continue to
Thermal evolution of hybrid stars within the framework of a nonlocal Nambu-Jona-Lasinio model
NASA Astrophysics Data System (ADS)
de Carvalho, S. M.; Negreiros, R.; Orsaria, M.; Contrera, G. A.; Weber, F.; Spinella, W.
2015-09-01
We study the thermal evolution of neutron stars containing deconfined quark matter in their core. Such objects are generally referred to as quark-hybrid stars. The confined hadronic matter in their core is described in the framework of nonlinear relativistic nuclear field theory. For the quark phase we use a nonlocal extension of the SU(3) Nambu-Jona-Lasinio model with vector interactions. The Gibbs condition is used to model phase equilibrium between confined hadronic matter and deconfined quark matter. Our study indicates that high-mass neutron stars may contain between 35 and 40% deconfined quark-hybrid matter in their cores. Neutron stars with canonical masses of around 1.4 M⊙ would not contain deconfined quark matter. The central proton fractions of the stars are found to be high, enabling them to cool rapidly. Very good agreement with the temperature evolution established for the neutron star in Cassiopeia A (Cas A) is obtained for one of our models (based on the popular NL3 nuclear parametrization), if the protons in the core of our stellar models are strongly paired, the repulsion among the quarks is mildly repulsive, and the mass of Cas A has a canonical value of 1.4 M⊙ .
Fatty acid membrane assembly on coacervate microdroplets as a step towards a hybrid protocell model
NASA Astrophysics Data System (ADS)
Dora Tang, T.-Y.; Rohaida Che Hak, C.; Thompson, Alexander J.; Kuimova, Marina K.; Williams, D. S.; Perriman, Adam W.; Mann, Stephen
2014-06-01
Mechanisms of prebiotic compartmentalization are central to providing insights into how protocellular systems emerged on the early Earth. Protocell models are based predominantly on the membrane self-assembly of fatty-acid vesicles, although membrane-free scenarios that involve liquid-liquid microphase separation (coacervation) have also been considered. Here we integrate these alternative models of prebiotic compartmentalization and develop a hybrid protocell model based on the spontaneous self-assembly of a continuous fatty-acid membrane at the surface of preformed coacervate microdroplets prepared from cationic peptides/polyelectrolytes and adenosine triphosphate or oligo/polyribonucleotides. We show that the coacervate-supported membrane is multilamellar, and mediates the selective uptake or exclusion of small and large molecules. The coacervate interior can be disassembled without loss of membrane integrity, and fusion and growth of the hybrid protocells can be induced under conditions of high ionic strength. Our results highlight how notions of membrane-mediated compartmentalization, chemical enrichment and internalized structuration can be integrated in protocell models via simple chemical and physical processes.
Fatty acid membrane assembly on coacervate microdroplets as a step towards a hybrid protocell model.
Dora Tang, T-Y; Rohaida Che Hak, C; Thompson, Alexander J; Kuimova, Marina K; Williams, D S; Perriman, Adam W; Mann, Stephen
2014-06-01
Mechanisms of prebiotic compartmentalization are central to providing insights into how protocellular systems emerged on the early Earth. Protocell models are based predominantly on the membrane self-assembly of fatty-acid vesicles, although membrane-free scenarios that involve liquid-liquid microphase separation (coacervation) have also been considered. Here we integrate these alternative models of prebiotic compartmentalization and develop a hybrid protocell model based on the spontaneous self-assembly of a continuous fatty-acid membrane at the surface of preformed coacervate microdroplets prepared from cationic peptides/polyelectrolytes and adenosine triphosphate or oligo/polyribonucleotides. We show that the coacervate-supported membrane is multilamellar, and mediates the selective uptake or exclusion of small and large molecules. The coacervate interior can be disassembled without loss of membrane integrity, and fusion and growth of the hybrid protocells can be induced under conditions of high ionic strength. Our results highlight how notions of membrane-mediated compartmentalization, chemical enrichment and internalized structuration can be integrated in protocell models via simple chemical and physical processes. PMID:24848239
Modeling wall effects in a micro-scale shock tube using hybrid MD-DSMC algorithm
NASA Astrophysics Data System (ADS)
Watvisave, D. S.; Puranik, B. P.; Bhandarkar, U. V.
2015-07-01
Wall effects in a micro-scale shock tube are investigated using the Direct Simulation Monte Carlo method as well as a hybrid Molecular Dynamics-Direct Simulation Monte Carlo algorithm. In the Direct Simulation Monte Carlo simulations, the Cercingani-Lampis-Lord model of gas-surface interactions is employed to incorporate the wall effects, and it is shown that the shock attenuation is significantly affected by the choice of the values of tangential momentum accommodation coefficient. A loosely coupled Molecular Dynamics-Direct Simulation Monte Carlo approach is then employed to demonstrate incomplete accommodation in micro-scale shock tube flows. This approach uses fixed values of the accommodation coefficients in the gas-surface interaction model, with their values determined from a separate dynamically similar Molecular Dynamics simulation. Finally, a completely coupled Molecular Dynamics-Direct Simulation Monte Carlo algorithm is used, wherein the bulk of the flow is modeled using Direct Simulation Monte Carlo, while the interaction of gas molecules with the shock tube walls is modeled using Molecular Dynamics. The two regions are separate and coupled both ways using buffer zones and a bootstrap coupling algorithm that accounts for the mismatch of the number of molecules in both regions. It is shown that the hybrid method captures the effect of local properties that cannot be captured using a single value of accommodation coefficient for the entire domain.
Multistep-Ahead Air Passengers Traffic Prediction with Hybrid ARIMA-SVMs Models
Ming, Wei; Xiong, Tao
2014-01-01
The hybrid ARIMA-SVMs prediction models have been established recently, which take advantage of the unique strength of ARIMA and SVMs models in linear and nonlinear modeling, respectively. Built upon this hybrid ARIMA-SVMs models alike, this study goes further to extend them into the case of multistep-ahead prediction for air passengers traffic with the two most commonly used multistep-ahead prediction strategies, that is, iterated strategy and direct strategy. Additionally, the effectiveness of data preprocessing approaches, such as deseasonalization and detrending, is investigated and proofed along with the two strategies. Real data sets including four selected airlines' monthly series were collected to justify the effectiveness of the proposed approach. Empirical results demonstrate that the direct strategy performs better than iterative one in long term prediction case while iterative one performs better in the case of short term prediction. Furthermore, both deseasonalization and detrending can significantly improve the prediction accuracy for both strategies, indicating the necessity of data preprocessing. As such, this study contributes as a full reference to the planners from air transportation industries on how to tackle multistep-ahead prediction tasks in the implementation of either prediction strategy. PMID:24723814
A dynamic hybrid RANS/LES modeling methodology for turbulent/transitional flow field prediction
NASA Astrophysics Data System (ADS)
Alam, Mohammad Faridul
A dynamic hybrid Reynolds-averaged Navier-Stokes (RANS)-Large Eddy Simulation (LES) modeling framework has been investigated and further developed to improve the Computational Fluid Dynamics (CFD) prediction of turbulent flow features along with laminar-to-turbulent transitional phenomena. In recent years, the use of hybrid RANS/LES (HRL) models has become more common in CFD simulations, since HRL models offer more accuracy than RANS in regions of flow separation at a reduced cost relative to LES in attached boundary layers. The first part of this research includes evaluation and validation of a dynamic HRL (DHRL) model that aims to address issues regarding the RANS-to-LES zonal transition and explicit grid dependence, both of which are inherent to most current HRL models. Simulations of two test cases---flow over a backward facing step and flow over a wing with leading-edge ice accretion---were performed to assess the potential of the DHRL model for predicting turbulent features involved in mainly unsteady separated flow. The DHRL simulation results are compared with experimental data, along with the computational results for other HRL and RANS models. In summary, these comparisons demonstrate that the DHRL framework does address many of the weaknesses inherent in most current HRL models. Although HRL models are widely used in turbulent flow simulations, they have limitations for transitional flow predictions. Most HRL models include a fully turbulent RANS component for attached boundary layer regions. The small number of HRL models that do include transition-sensitive RANS models have issues related to the RANS model itself and to the zonal transition between RANS and LES. In order to address those issues, a new transition-sensitive HRL modeling methodology has been developed that includes the DHRL methodology and a physics-based transition-sensitive RANS model. The feasibility of the transition-sensitive dynamic HRL (TDHRL) model has been investigated by
NASA Technical Reports Server (NTRS)
Tamma, Kumar K.; Railkar, Sudhir B.
1988-01-01
The present paper describes the applicability of hybrid transfinite element modeling/analysis formulations for nonlinear heat conduction problems involving phase change. The methodology is based on application of transform approaches and classical Galerkin schemes with finite element formulations to maintain the modeling versatility and numerical features for computational analysis. In addition, in conjunction with the above, the effects due to latent heat are modeled using enthalpy formulations to enable a physically realistic approximation to be dealt computationally for materials exhibiting phase change within a narrow band of temperatures. Pertinent details of the approach and computational scheme adapted are described in technical detail. Numerical test cases of comparative nature are presented to demonstrate the applicability of the proposed formulations for numerical modeling/analysis of nonlinear heat conduction problems involving phase change.
An Investigation of a Hybrid Mixing Model for PDF Simulations of Turbulent Premixed Flames
NASA Astrophysics Data System (ADS)
Zhou, Hua; Li, Shan; Wang, Hu; Ren, Zhuyin
2015-11-01
Predictive simulations of turbulent premixed flames over a wide range of Damköhler numbers in the framework of Probability Density Function (PDF) method still remain challenging due to the deficiency in current micro-mixing models. In this work, a hybrid micro-mixing model, valid in both the flamelet regime and broken reaction zone regime, is proposed. A priori testing of this model is first performed by examining the conditional scalar dissipation rate and conditional scalar diffusion in a 3-D direct numerical simulation dataset of a temporally evolving turbulent slot jet flame of lean premixed H2-air in the thin reaction zone regime. Then, this new model is applied to PDF simulations of the Piloted Premixed Jet Burner (PPJB) flames, which are a set of highly shear turbulent premixed flames and feature strong turbulence-chemistry interaction at high Reynolds and Karlovitz numbers. Supported by NSFC 51476087 and NSFC 91441202.
NASA Astrophysics Data System (ADS)
Zhu, Jiulong; Wang, Shijun
Presently water resource in most watersheds in China is distributed in terms of administrative instructions. This kind of allocation method has many disadvantages and hampers the instructional effect of market mechanism on water allocation. The paper studies South-to-North Water Transfer Project and discusses water allocation of the node lakes along the Project. Firstly, it advanced four assumptions. Secondly, it analyzed constraint conditions of water allocation in terms of present state of water allocation in China. Thirdly, it established a goal model of water allocation and set up a systematic model from the angle of comprehensive profits of water utilization and profits of the node lakes. Fourthly, it discussed calculation method of the model by means of Simulated Annealing Hybrid Genetic Algorithm (SHGA). Finally, it validated the rationality and validity of the model by a simulation testing.
Tikare, Veena; Hernandez-Rivera, Efrain; Madison, Jonathan D.; Holm, Elizabeth Ann; Patterson, Burton R.; Homer, Eric R.
2013-09-01
Most materials microstructural evolution processes progress with multiple processes occurring simultaneously. In this work, we have concentrated on the processes that are active in nuclear materials, in particular, nuclear fuels. These processes are coarsening, nucleation, differential diffusion, phase transformation, radiation-induced defect formation and swelling, often with temperature gradients present. All these couple and contribute to evolution that is unique to nuclear fuels and materials. Hybrid model that combines elements from the Potts Monte Carlo, phase-field models and others have been developed to address these multiple physical processes. These models are described and applied to several processes in this report. An important feature of the models developed are that they are coded as applications within SPPARKS, a Sandiadeveloped framework for simulation at the mesoscale of microstructural evolution processes by kinetic Monte Carlo methods. This makes these codes readily accessible and adaptable for future applications.
Jason D. Hales; Veena Tikare
2014-04-01
The Used Fuel Disposition (UFD) program has initiated a project to develop a hydride formation modeling tool using a hybrid Pottsphase field approach. The Potts model is incorporated in the SPPARKS code from Sandia National Laboratories. The phase field model is provided through MARMOT from Idaho National Laboratory.
Modeling is a useful tool for quantifying ecosystem services and understanding their temporal dynamics. Here we describe a hybrid regional modeling approach for sub-basins of the Calapooia watershed that incorporates both a precipitation-runoff model and an indexed regression mo...
A hybrid beach morphology model applied to a high energy sandy beach
NASA Astrophysics Data System (ADS)
Karunarathna, Harshinie; Ranasinghe, Roshanka; Reeve, Dominic E.
2015-11-01
In this paper, the application of a hybrid coastal morphodynamic model to forecast inter-annual beach change is discussed through the prediction of beach change in a high energy sandy beach over a period of 5 years. The modelling approach combines a `reduced-physics' formulation with a data-driven approach through an inverse technique to form the hybrid coastal morphodynamic model. The beach considered for the demonstration of the model is the Narrabeen Beach, which is a dynamic sand beach located in New South Wales, Australia. Despite its simplicity, we find that the model is able to capture beach change at Narrabeen Beach at inter-annual timescales with root mean square error between measured and computed beach profiles less than 0.4 m on average. Even though the model is used to forecast inter-annual beach change in this study, its ability to predict beach change is not limited to that timescale but depends on the frequency of historic beach profile measurements available to determine key unknown parameters of the model. Also, the length of profile forecasts largely depends on the length of available historic measurements where longer data sets allow longer predictions within a range of beach behaviour contained in the observations. The ability of the model to reliably forecast coastal change at inter-annual and potentially at other timescales, and its high efficiency make it possible to be used in providing multiple simulations required for probabilistic coastal change forecasts which will be very useful for coastal management purposes.
NASA Astrophysics Data System (ADS)
Dehmollaian, Mojtaba
This thesis focuses on the application of radio waves for detection and recognition of visually obscured targets. To provide practical solutions, comprehensive forward and inverse models are needed to capture and exploit the physical phenomena involved. These models must accurately simulate wave propagation in the environment in which the target is imbedded, scattering from the target and wave interaction of the medium scatterers and the target. In this dissertation, two problems of major importance are investigated. The first problem is detection of complex targets camouflaged inside forest and the second problem pertains to imaging of building interiors and detection of targets within. In the early chapters, a hybrid target-foliage model is developed to investigate the scattering behavior of hard targets embedded inside a forest canopy. This model is composed of two parts, one for foliage and the other for hard targets. The connection between these two models that accounts for the first-order interaction between the foliage scatterers and the target is accomplished through the application of the reciprocity theorem. The foliage penetration model is based on the coherent single scattering theory, developed previously. The target scattering model is based on either exact numerical finite difference time domain technique or high frequency asymptotic iterative physical optics approximation. Having the hybrid target-foliage model, a polarization synthesis optimization method for improving signal to clutter ratio is presented, using genetic algorithms. In the later chapters, the problem of through-wall imaging using the synthetic aperture radar technique by employing ultra wideband antennas and scanning over a wide range of incidence angles is investigated. Theoretical and experimental studies on the effects of different walls on point target images are carried out and refocusing approaches are introduced to remove the wall effects and restore the image resolution
Jovian's plasma torus interaction with Europa. E12 pass: 3D hybrid kinetic modeling
NASA Astrophysics Data System (ADS)
Lipatov, A. S.; Cooper, J. F.; Sittler, E. C., Jr.; Paterson, W. R.; Hartle, R. E.
2012-09-01
The hybrid kinetic model supports comprehensive simulation of the interaction between different spatial and energetic elements of the Europa moonmagnetosphere system with respect to variable upstream magnetic field and flux or density distributions of plasma and energetic ions, electrons, and neutral atoms. This capability is critical for improving the interpretation of the existing Europa flybymeasurements from Galileo orbital mission and for planning flyby and orbital measurements for future missions. The simulations are based on recent models of the atmosphere of Europa [1, 2, 3]. The upstream parameters have been chosen from the plasma and magnetic field Galileo E12 observations, [4, 5]. In contrast to previous approaches with MHD simulations, the hybrid model allows us to fully take into account the finite gyroradius effect and electron pressure, and to correctly estimate the ions velocity distribution and the fluxes along themagnetic field [6]. Photoionization, electron-impact ionization and charge exchange are included in our model. The temperature of the background electrons and pickup electrons was also included into the generalized Ohm's law. The background plasma contains heavy (Mi/Qi = 16) and light (Mi/Qi = 1) ions [4]. In our modeling we take into account only O+ ions for magnetospheric plasma. The pickup ions were created from the atmosphere. The majority of O2 atmosphere is thermal with an extended non-thermal population [1]. The moon is modeled in this initial work as a weakly conducting body. The critical point of E12 pass is the extremely high density in upstream plasma, e.g. n0 = 70-571 cm-3 for ions with Mi/Qi ratio equals 16. This density results in to the superAlfvénic flow and it will change the physics of the interaction between Jovianmagnetosphere and Europa. The modeling show the formation of the Mach cone instead of the Alfv'en wing which was observed in hybrid modeling of E4 pass [6]. The modeling shows that the effective size of the
Asymmetric magnetic reconnection with out-of-plane shear flows in a two dimensional hybrid model
Wang, Lin; Wang, Xiao-Gang; Wang, Xian-Qu; Liu, Yue
2015-05-15
Effects of out-of-plane shear flows on asymmetric magnetic reconnect are investigated in a two-dimensional (2D) hybrid model with an initial Harris sheet equilibrium. It is found that the out-of-plane flow with an in-plane shear can significantly change the asymmetric reconnection process as well as the related geometry. The magnetic flux, out-of-plane magnetic field, in-plane flow vorticity, plasma density, and the reconnection rate are discussed in detail. The results are in comparison with the cases without the shear flows to further understand the effect.
Hybrid Parallel Programming Models for AMR Neutron Monte-Carlo Transport
NASA Astrophysics Data System (ADS)
Dureau, David; Poëtte, Gaël
2014-06-01
This paper deals with High Performance Computing (HPC) applied to neutron transport theory on complex geometries, thanks to both an Adaptive Mesh Refinement (AMR) algorithm and a Monte-Carlo (MC) solver. Several Parallelism models are presented and analyzed in this context, among them shared memory and distributed memory ones such as Domain Replication and Domain Decomposition, together with Hybrid strategies. The study is illustrated by weak and strong scalability tests on complex benchmarks on several thousands of cores thanks to the petaflopic supercomputer Tera100.
NASA Astrophysics Data System (ADS)
Enayatifar, Rasul; Sadaei, Hossein Javedani; Abdullah, Abdul Hanan; Lee, Malrey; Isnin, Ismail Fauzi
2015-08-01
Currently, there are many studies have conducted on developing security of the digital image in order to protect such data while they are sending on the internet. This work aims to propose a new approach based on a hybrid model of the Tinkerbell chaotic map, deoxyribonucleic acid (DNA) and cellular automata (CA). DNA rules, DNA sequence XOR operator and CA rules are used simultaneously to encrypt the plain-image pixels. To determine rule number in DNA sequence and also CA, a 2-dimension Tinkerbell chaotic map is employed. Experimental results and computer simulations, both confirm that the proposed scheme not only demonstrates outstanding encryption, but also resists various typical attacks.
Anisotropic modified holographic Ricci dark energy cosmological model with hybrid expansion law
NASA Astrophysics Data System (ADS)
Das, Kanika; Sultana, Tazmin
2015-11-01
Here in this paper we present a locally rotationally symmetric Bianchi type-II metric filled with dark matter and anisotropic modified holographic Ricci dark energy. To solve the Einstein's field equations we have taken the hybrid expansion law (HEL) which exhibits a cosmic transition of the universe from decelerating to accelerating phase. We have investigated the physical and geometrical properties of the model. It is observed that the anisotropy of the universe and that of the modified holographic Ricci dark energy tends to zero at later times and the universe becomes homogeneous, isotropic and flat. We have also studied the cosmic jerk parameter.
Core-corona separation in the UrQMD hybrid model
Steinheimer, J.; Bleicher, M.
2011-08-15
We employ the UrQMD transport + hydrodynamics hybrid model to estimate the effects of a separation of the hot equilibrated core and the dilute corona created in high-energy heavy-ion collisions. It is shown that the fraction of the system that can be regarded as an equilibrated fireball changes over a wide range of energies. This has an impact, especially on strange particle abundances. We show that such a core corona separation allows for an improvement in the description of strange particle ratios and flow as a function of beam energy as well as strange particle yields as a function of centrality.
Model-Invariant Hybrid LES-RANS Computation of Separated Flow Past Periodic Hills
NASA Technical Reports Server (NTRS)
Woodruff, Stephen
2014-01-01
The requirement that physical quantities not vary with a hybrid LESRANS model's blending parameter imposes conditions on the computation that lead to better results across LES-RANS transitions. This promises to allow placement of those transitions so that LES is performed only where required by the physics, improving computational efficiency. The approach is applied to separated flow past periodic hills, where good predictions of separation-bubble size are seen due to the gradual, controlled, LES-RANS transition and the resulting enhanced near-wall eddy viscosity.
A hybrid model for simulating rogue waves in random seas on a large temporal and spatial scale
NASA Astrophysics Data System (ADS)
Wang, Jinghua; Ma, Q. W.; Yan, S.
2016-05-01
A hybrid model for simulating rogue waves in random seas on a large temporal and spatial scale is proposed in this paper. It is formed by combining the derived fifth order Enhanced Nonlinear Schrödinger Equation based on Fourier transform, the Enhanced Spectral Boundary Integral (ESBI) method and its simplified version. The numerical techniques and algorithm for coupling three models on time scale are suggested. Using the algorithm, the switch between the three models during the computation is triggered automatically according to wave nonlinearities. Numerical tests are carried out and the results indicate that this hybrid model could simulate rogue waves both accurately and efficiently. In some cases discussed, the hybrid model is more than 10 times faster than just using the ESBI method, and it is also much faster than other methods reported in the literature.
Eylenceoğlu, E.; Rafatov, I.; Kudryavtsev, A. A.
2015-01-15
Two-dimensional hybrid Monte Carlo–fluid numerical code is developed and applied to model the dc glow discharge. The model is based on the separation of electrons into two parts: the low energetic (slow) and high energetic (fast) electron groups. Ions and slow electrons are described within the fluid model using the drift-diffusion approximation for particle fluxes. Fast electrons, represented by suitable number of super particles emitted from the cathode, are responsible for ionization processes in the discharge volume, which are simulated by the Monte Carlo collision method. Electrostatic field is obtained from the solution of Poisson equation. The test calculations were carried out for an argon plasma. Main properties of the glow discharge are considered. Current-voltage curves, electric field reversal phenomenon, and the vortex current formation are developed and discussed. The results are compared to those obtained from the simple and extended fluid models. Contrary to reports in the literature, the analysis does not reveal significant advantages of existing hybrid methods over the extended fluid model.
Dynamic modeling and motion simulation for a winged hybrid-driven underwater glider
NASA Astrophysics Data System (ADS)
Wang, Shu-Xin; Sun, Xiu-Jun; Wang, Yan-Hui; Wu, Jian-Guo; Wang, Xiao-Ming
2011-03-01
PETREL, a winged hybrid-driven underwater glider is a novel and practical marine survey platform which combines the features of legacy underwater glider and conventional AUV (autonomous underwater vehicle). It can be treated as a multi-rigid-body system with a floating base and a particular hydrodynamic profile. In this paper, theorems on linear and angular momentum are used to establish the dynamic equations of motion of each rigid body and the effect of translational and rotational motion of internal masses on the attitude control are taken into consideration. In addition, due to the unique external shape with fixed wings and deflectable rudders and the dual-drive operation in thrust and glide modes, the approaches of building dynamic model of conventional AUV and hydrodynamic model of submarine are introduced, and the tailored dynamic equations of the hybrid glider are formulated. Moreover, the behaviors of motion in glide and thrust operation are analyzed based on the simulation and the feasibility of the dynamic model is validated by data from lake field trials.
NASA Astrophysics Data System (ADS)
Singh Pradhan, Ananta Man; Kang, Hyo-Sub; Kim, Yun-Tae
2016-04-01
This study uses a physically based approach to evaluate the factor of safety of the hillslope for different hydrological conditions, in Mt Umyeon, south of Seoul. The hydrological conditions were determined using intensity and duration of whole Korea of known landslide inventory data. Quantile regression statistical method was used to ascertain different probability warning levels on the basis of rainfall thresholds. Physically based models are easily interpreted and have high predictive capabilities but rely on spatially explicit and accurate parameterization, which is commonly not possible. Statistical probabilistic methods can include other causative factors which influence the slope stability such as forest, soil and geology, but rely on good landslide inventories of the site. In this study a hybrid approach has described that combines the physically-based landslide susceptibility for different hydrological conditions. A presence-only based maximum entropy model was used to hybrid and analyze relation of landslide with conditioning factors. About 80% of the landslides were listed among the unstable sites identified in the proposed model, thereby presenting its effectiveness and accuracy in determining unstable areas and areas that require evacuation. These cumulative rainfall thresholds provide a valuable reference to guide disaster prevention authorities in the issuance of warning levels with the ability to reduce losses and save lives.
Effective-mass model and magneto-optical properties in hybrid perovskites
Yu, Z. G.
2016-01-01
Hybrid inorganic-organic perovskites have proven to be a revolutionary material for low-cost photovoltaic applications. They also exhibit many other interesting properties, including giant Rashba splitting, large-radius Wannier excitons, and novel magneto-optical effects. Understanding these properties as well as the detailed mechanism of photovoltaics requires a reliable and accessible electronic structure, on which models of transport, excitonic, and magneto-optical properties can be efficiently developed. Here we construct an effective-mass model for the hybrid perovskites based on the group theory, experiment, and first-principles calculations. Using this model, we relate the Rashba splitting with the inversion-asymmetry parameter in the tetragonal perovskites, evaluate anisotropic g-factors for both conduction and valence bands, and elucidate the magnetic-field effect on photoluminescence and its dependence on the intensity of photoexcitation. The diamagnetic effect of exciton is calculated for an arbitrarily strong magnetic field. The pronounced excitonic peak emerged at intermediate magnetic fields in cyclotron resonance is assigned to the 3D±2 states, whose splitting can be used to estimate the difference in the effective masses of electron and hole. PMID:27338834
Effective-mass model and magneto-optical properties in hybrid perovskites
NASA Astrophysics Data System (ADS)
Yu, Z. G.
2016-06-01
Hybrid inorganic-organic perovskites have proven to be a revolutionary material for low-cost photovoltaic applications. They also exhibit many other interesting properties, including giant Rashba splitting, large-radius Wannier excitons, and novel magneto-optical effects. Understanding these properties as well as the detailed mechanism of photovoltaics requires a reliable and accessible electronic structure, on which models of transport, excitonic, and magneto-optical properties can be efficiently developed. Here we construct an effective-mass model for the hybrid perovskites based on the group theory, experiment, and first-principles calculations. Using this model, we relate the Rashba splitting with the inversion-asymmetry parameter in the tetragonal perovskites, evaluate anisotropic g-factors for both conduction and valence bands, and elucidate the magnetic-field effect on photoluminescence and its dependence on the intensity of photoexcitation. The diamagnetic effect of exciton is calculated for an arbitrarily strong magnetic field. The pronounced excitonic peak emerged at intermediate magnetic fields in cyclotron resonance is assigned to the 3D±2 states, whose splitting can be used to estimate the difference in the effective masses of electron and hole.
NASA Astrophysics Data System (ADS)
Sun, Hao; Wang, Cheng; Wang, Boliang
2011-02-01
We present a hybrid generative-discriminative learning method for human action recognition from video sequences. Our model combines a bag-of-words component with supervised latent topic models. A video sequence is represented as a collection of spatiotemporal words by extracting space-time interest points and describing these points using both shape and motion cues. The supervised latent Dirichlet allocation (sLDA) topic model, which employs discriminative learning using labeled data under a generative framework, is introduced to discover the latent topic structure that is most relevant to action categorization. The proposed algorithm retains most of the desirable properties of generative learning while increasing the classification performance though a discriminative setting. It has also been extended to exploit both labeled data and unlabeled data to learn human actions under a unified framework. We test our algorithm on three challenging data sets: the KTH human motion data set, the Weizmann human action data set, and a ballet data set. Our results are either comparable to or significantly better than previously published results on these data sets and reflect the promise of hybrid generative-discriminative learning approaches.
A new hybrid model for exploring the adoption of online nursing courses.
Tung, Feng-Cheng; Chang, Su-Chao
2008-04-01
With the advancement in educational technology and internet access in recent years, nursing academia is searching for ways to widen nurses' educational opportunities. The online nursing courses are drawing more attention as well. The online nursing courses are very important e-learning tools for nursing students. The research combines the innovation diffusion theory and technology acceptance model, and adds two research variables, perceived financial cost and computer self-efficacy to propose a new hybrid technology acceptance model to study nursing students' behavioral intentions to use the online nursing courses. Based on 267 questionnaires collected from six universities in Taiwan, the research finds that studies strongly support this new hybrid technology acceptance model in predicting nursing students' behavioral intentions to use the online nursing courses. This research finds that compatibility, perceived usefulness, perceived ease of use, perceived financial cost and computer self-efficacy are critical factors for nursing students' behavioral intentions to use the online nursing courses. By explaining nursing students' behavioral intentions from a user's perspective, the findings of this research help to develop more user friendly online nursing courses and also provide insight into the best way to promote new e-learning tools for nursing students. This research finds that compatibility is the most important research variable that affects the behavioral intention to use the online nursing courses. PMID:17706842
NASA Technical Reports Server (NTRS)
Carros, R. J.; Boissevain, A. G.; Aoyagi, K.
1975-01-01
Data are presented from an investigation of the aerodynamic characteristics of large-scale wind tunnel aircraft model that utilized a hybrid-upper surface blown flap to augment lift. The hybrid concept of this investigation used a portion of the turbofan exhaust air for blowing over the trailing edge flap to provide boundary layer control. The model, tested in the Ames 40- by 80-foot Wind Tunnel, had a 27.5 deg swept wing of aspect ratio 8 and 4 turbofan engines mounted on the upper surface of the wing. The lift of the model was augmented by turbofan exhaust impingement on the wind upper-surface and flap system. Results were obtained for three flap deflections, for some variation of engine nozzle configuration and for jet thrust coefficients from 0 to 3.0. Six-component longitudinal and lateral data are presented with four engine operation and with the critical engine out. In addition, a limited number of cross-plots of the data are presented. All of the tests were made with a downwash rake installed instead of a horizontal tail. Some of these downwash data are also presented.
Effective-mass model and magneto-optical properties in hybrid perovskites.
Yu, Z G
2016-01-01
Hybrid inorganic-organic perovskites have proven to be a revolutionary material for low-cost photovoltaic applications. They also exhibit many other interesting properties, including giant Rashba splitting, large-radius Wannier excitons, and novel magneto-optical effects. Understanding these properties as well as the detailed mechanism of photovoltaics requires a reliable and accessible electronic structure, on which models of transport, excitonic, and magneto-optical properties can be efficiently developed. Here we construct an effective-mass model for the hybrid perovskites based on the group theory, experiment, and first-principles calculations. Using this model, we relate the Rashba splitting with the inversion-asymmetry parameter in the tetragonal perovskites, evaluate anisotropic g-factors for both conduction and valence bands, and elucidate the magnetic-field effect on photoluminescence and its dependence on the intensity of photoexcitation. The diamagnetic effect of exciton is calculated for an arbitrarily strong magnetic field. The pronounced excitonic peak emerged at intermediate magnetic fields in cyclotron resonance is assigned to the 3D±2 states, whose splitting can be used to estimate the difference in the effective masses of electron and hole. PMID:27338834
Hybrid LCA model for assessing the embodied environmental impacts of buildings in South Korea
Jang, Minho; Hong, Taehoon; Ji, Changyoon
2015-01-15
The assessment of the embodied environmental impacts of buildings can help decision-makers plan environment-friendly buildings and reduce environmental impacts. For a more comprehensive assessment of the embodied environmental impacts of buildings, a hybrid life cycle assessment model was developed in this study. The developed model can assess the embodied environmental impacts (global warming, ozone layer depletion, acidification, eutrophication, photochemical ozone creation, abiotic depletion, and human toxicity) generated directly and indirectly in the material manufacturing, transportation, and construction phases. To demonstrate the application and validity of the developed model, the environmental impacts of an elementary school building were assessed using the developed model and compared with the results of a previous model used in a case study. The embodied environmental impacts from the previous model were lower than those from the developed model by 4.6–25.2%. Particularly, human toxicity potential (13 kg C{sub 6}H{sub 6} eq.) calculated by the previous model was much lower (1965 kg C{sub 6}H{sub 6} eq.) than what was calculated by the developed model. The results indicated that the developed model can quantify the embodied environmental impacts of buildings more comprehensively, and can be used by decision-makers as a tool for selecting environment-friendly buildings. - Highlights: • The model was developed to assess the embodied environmental impacts of buildings. • The model evaluates GWP, ODP, AP, EP, POCP, ADP, and HTP as environmental impacts. • The model presents more comprehensive results than the previous model by 4.6–100%. • The model can present the HTP of buildings, which the previous models cannot do. • Decision-makers can use the model for selecting environment-friendly buildings.
Flow-radiation coupling for atmospheric entries using a Hybrid Statistical Narrow Band model
NASA Astrophysics Data System (ADS)
Soucasse, Laurent; Scoggins, James B.; Rivière, Philippe; Magin, Thierry E.; Soufiani, Anouar
2016-09-01
In this study, a Hybrid Statistical Narrow Band (HSNB) model is implemented to make fast and accurate predictions of radiative transfer effects on hypersonic entry flows. The HSNB model combines a Statistical Narrow Band (SNB) model for optically thick molecular systems, a box model for optically thin molecular systems and continua, and a Line-By-Line (LBL) description of atomic radiation. Radiative transfer calculations are coupled to a 1D stagnation-line flow model under thermal and chemical nonequilibrium. Earth entry conditions corresponding to the FIRE 2 experiment, as well as Titan entry conditions corresponding to the Huygens probe, are considered in this work. Thermal nonequilibrium is described by a two temperature model, although non-Boltzmann distributions of electronic levels provided by a Quasi-Steady State model are also considered for radiative transfer. For all the studied configurations, radiative transfer effects on the flow, the plasma chemistry and the total heat flux at the wall are analyzed in detail. The HSNB model is shown to reproduce LBL results with an accuracy better than 5% and a speed up of the computational time around two orders of magnitude. Concerning molecular radiation, the HSNB model provides a significant improvement in accuracy compared to the Smeared-Rotational-Band model, especially for Titan entries dominated by optically thick CN radiation.
Hybrid wavelet-support vector machine approach for modelling rainfall-runoff process.
Komasi, Mehdi; Sharghi, Soroush
2016-01-01
Because of the importance of water resources management, the need for accurate modeling of the rainfall-runoff process has rapidly grown in the past decades. Recently, the support vector machine (SVM) approach has been used by hydrologists for rainfall-runoff modeling and the other fields of hydrology. Similar to the other artificial intelligence models, such as artificial neural network (ANN) and adaptive neural fuzzy inference system, the SVM model is based on the autoregressive properties. In this paper, the wavelet analysis was linked to the SVM model concept for modeling the rainfall-runoff process of Aghchai and Eel River watersheds. In this way, the main time series of two variables, rainfall and runoff, were decomposed to multiple frequent time series by wavelet theory; then, these time series were imposed as input data on the SVM model in order to predict the runoff discharge one day ahead. The obtained results show that the wavelet SVM model can predict both short- and long-term runoff discharges by considering the seasonality effects. Also, the proposed hybrid model is relatively more appropriate than classical autoregressive ones such as ANN and SVM because it uses the multi-scale time series of rainfall and runoff data in the modeling process. PMID:27120649
Prediction of hot spots in protein interfaces using a random forest model with hybrid features.
Wang, Lin; Liu, Zhi-Ping; Zhang, Xiang-Sun; Chen, Luonan
2012-03-01
Prediction of hot spots in protein interfaces provides crucial information for the research on protein-protein interaction and drug design. Existing machine learning methods generally judge whether a given residue is likely to be a hot spot by extracting features only from the target residue. However, hot spots usually form a small cluster of residues which are tightly packed together at the center of protein interface. With this in mind, we present a novel method to extract hybrid features which incorporate a wide range of information of the target residue and its spatially neighboring residues, i.e. the nearest contact residue in the other face (mirror-contact residue) and the nearest contact residue in the same face (intra-contact residue). We provide a novel random forest (RF) model to effectively integrate these hybrid features for predicting hot spots in protein interfaces. Our method can achieve accuracy (ACC) of 82.4% and Matthew's correlation coefficient (MCC) of 0.482 in Alanine Scanning Energetics Database, and ACC of 77.6% and MCC of 0.429 in Binding Interface Database. In a comparison study, performance of our RF model exceeds other existing methods, such as Robetta, FOLDEF, KFC, KFC2, MINERVA and HotPoint. Of our hybrid features, three physicochemical features of target residues (mass, polarizability and isoelectric point), the relative side-chain accessible surface area and the average depth index of mirror-contact residues are found to be the main discriminative features in hot spots prediction. We also confirm that hot spots tend to form large contact surface areas between two interacting proteins. Source data and code are available at: http://www.aporc.org/doc/wiki/HotSpot. PMID:22258275
First Principles Molecular Modeling of Sensing Material Selection for Hybrid Biomimetic Nanosensors
NASA Astrophysics Data System (ADS)
Blanco, Mario; McAlpine, Michael C.; Heath, James R.
Hybrid biomimetic nanosensors use selective polymeric and biological materials that integrate flexible recognition moieties with nanometer size transducers. These sensors have the potential to offer the building blocks for a universal sensing platform. Their vast range of chemistries and high conformational flexibility present both a problem and an opportunity. Nonetheless, it has been shown that oligopeptide aptamers from sequenced genes can be robust substrates for the selective recognition of specific chemical species. Here we present first principles molecular modeling approaches tailored to peptide sequences suitable for the selective discrimination of small molecules on nanowire arrays. The modeling strategy is fully atomistic. The excellent performance of these sensors, their potential biocompatibility combined with advanced mechanistic modeling studies, could potentially lead to applications such as: unobtrusive implantable medical sensors for disease diagnostics, light weight multi-purpose sensing devices for aerospace applications, ubiquitous environmental monitoring devices in urban and rural areas, and inexpensive smart packaging materials for active in-situ food safety labeling.
Callisto plasma interactions: Hybrid modeling including induction by a subsurface ocean
NASA Astrophysics Data System (ADS)
Lindkvist, Jesper; Holmström, Mats; Khurana, Krishan K.; Fatemi, Shahab; Barabash, Stas
2015-06-01
By using a hybrid plasma solver (ions as particles and electrons as a fluid), we have modeled the interaction between Callisto and Jupiter's magnetosphere for variable ambient plasma parameters. We compared the results with the magnetometer data from flybys (C3, C9, and C10) by the Galileo spacecraft. Modeling the interaction between Callisto and Jupiter's magnetosphere is important to establish the origin of the magnetic field perturbations observed by Galileo and thought to be related to a subsurface ocean. Using typical upstream magnetospheric plasma parameters and a magnetic dipole corresponding to the inductive response inside the moon, we show that the model results agree well with observations for the C3 and C9 flybys, but agrees poorly with the C10 flyby close to Callisto. The study does support the existence of a subsurface ocean at Callisto.
Application of a hybrid collisional radiative model to recombining argon plasmas
NASA Astrophysics Data System (ADS)
Benoy, D. A.; van der Mullen, J. A. M.; van de Sanden, M. C. M.; van der Sijde, B.; Schram, D. C.
1993-02-01
A collisional radiative model, in which a hybrid cut-off technique is used, is applied to recombining plasmas to study the atomic state distribution (ASDF) and the recombination coefficient. Computations of the ASDF using semi-empirical rate coefficients of Vriens and Smeets (V-S) and Drawin (D) are compared with experimental values measured at various positions in a free expanding argon arc jet. Apart from the shock position, where the calculated results are too low, the model calculations are higher than the experimental results. The volumetric recombination coefficient has a Te exp -4 and a Te exp -4.8 dependence when semiempirical rate coefficients of, respectively, V-S and D are used. The differences between the models based on the rate coefficients of V-S and D indicate that the recombination flow is sensitive to the low temperature behavior of the rate coefficients.
Supergravity Analysis of Hybrid Inflation Model from D3--D7 System
Koyama, Fumikazu; Tachikawa, Yuji; Watari, Taizan
2003-11-20
The slow-roll inflation is a beautiful paradigm, yet the inflaton potential can hardly be sufficiently flat when unknown gravitational effects are taken into account. However, the hybrid inflation models constructed in D = 4 N = 1 supergravity can be consistent with N = 2 supersymmetry, and can be naturally embedded into string theory. This article discusses the gravitational effects carefully in the string model, using D = 4 supergravity description. We adopt the D3--D7 system of Type IIB string theory compactified on K3 x T^2/Z_2 orientifold for definiteness. It turns out that the slow-roll parameter can be sufficiently small despite the non-minimal Kahler potential of the model. The conditions for this to happen are clarified in terms of string vacua. We also find that the geometry obtained by blowing up singularity, which is necessary for the positive vacuum energy, is stabilized by introducing certain 3-form fluxes.
A New Hybrid Viscoelastic Soft Tissue Model based on Meshless Method for Haptic Surgical Simulation
Bao, Yidong; Wu, Dongmei; Yan, Zhiyuan; Du, Zhijiang
2013-01-01
This paper proposes a hybrid soft tissue model that consists of a multilayer structure and many spheres for surgical simulation system based on meshless. To improve accuracy of the model, tension is added to the three-parameter viscoelastic structure that connects the two spheres. By using haptic device, the three-parameter viscoelastic model (TPM) produces accurate deformationand also has better stress-strain, stress relaxation and creep properties. Stress relaxation and creep formulas have been obtained by mathematical formula derivation. Comparing with the experimental results of the real pig liver which were reported by Evren et al. and Amy et al., the curve lines of stress-strain, stress relaxation and creep of TPM are close to the experimental data of the real liver. Simulated results show that TPM has better real-time, stability and accuracy. PMID:24339837
Hybrid Model for Plasma Thruster Plume Simulation Including PIC-MCC Electrons Treatment
Alexandrov, A. L.; Bondar, Ye. A.; Schweigert, I. V.
2008-12-31
The simulation of stationary plasma thruster plume is important for spacecraft design due to possible interaction plume with spacecraft surface. Such simulations are successfully performed using the particle-in-cell technique for describing the motion of charged particles, namely the propellant ions. In conventional plume models the electrons are treated using various fluid approaches. In this work, we suggest an alternative approach, where the electron kinetics is considered 'ab initio', using the particle-in-cell--Monte Carlo collision method. To avoid the large computational expenses due to small time steps, the relaxation of simulated plume plasma is split into the fast relaxation of the electrons distribution function and the slow one of the ions. The model is self-consistent but hybrid, since the simultaneous electron and ion motion is not really modeled. The obtained electron temperature profile is in good agreement with experiment.
Hybrid modeling of nitrate fate in large catchments using fuzzy-rules
NASA Astrophysics Data System (ADS)
van der Heijden, Sven; Haberlandt, Uwe
2010-05-01
Especially for nutrient balance simulations, physically based ecohydrological modeling needs an abundance of measured data and model parameters, which for large catchments all too often are not available in sufficient spatial or temporal resolution or are simply unknown. For efficient large-scale studies it is thus beneficial to have methods at one's disposal which are parsimonious concerning the number of model parameters and the necessary input data. One such method is fuzzy-rule based modeling, which compared to other machine-learning techniques has the advantages to produce models (the fuzzy-rules) which are physically interpretable to a certain extent, and to allow the explicit introduction of expert knowledge through pre-defined rules. The study focuses on the application of fuzzy-rule based modeling for nitrate simulation in large catchments, in particular concerning decision support. Fuzzy-rule based modeling enables the generation of simple, efficient, easily understandable models with nevertheless satisfactory accuracy for problems of decision support. The chosen approach encompasses a hybrid metamodeling, which includes the generation of fuzzy-rules with data originating from physically based models as well as a coupling with a physically based water balance model. For the generation of the needed training data and also as coupled water balance model the ecohydrological model SWAT is employed. The conceptual model divides the nitrate pathway into three parts. The first fuzzy-module calculates nitrate leaching with the percolating water from soil surface to groundwater, the second module simulates groundwater passage, and the final module replaces the in-stream processes. The aim of this modularization is to create flexibility for using each of the modules on its own, for changing or completely replacing it. For fuzzy-rule based modeling this can explicitly mean that the re-training of one of the modules with newly available data will be possible without
Transient Modeling of the NETL Hybrid Fuel Cell/Gas Turbine Facility and Experimental Validation
Mario L. Ferrari; Eric Liese; David Tucker; Larry Lawson; Alberto Traverso; Aristide F. Massardo
2007-10-01
This paper describes the experimental validation of two different transient models of the hybrid fuel cell/gas turbine facility of the U.S. DOE-NETL at Morgantown. The first part of this work is devoted to the description of the facility, designed to experimentally investigate these plants with real components, except the fuel cell. The behavior of the SOFC is obtained with apt volumes (for the stack and the off-gas burner) and using a combustor to generate similar thermal effects. The second part of this paper shows the facility real-time transient model developed at the U.S. DOE-NETL and the detailed transient modeling activity using the TRANSEO program developed at TPG. The results obtained with both models are successfully compared with the experimental data of two different load step decreases. The more detailed model agrees more closely with the experimental data, which, of course, is more time consuming than the real-time model (the detailed model operates with a calculation over calculated time ratio around 6). Finally, the TPG model has been used to discuss the importance of performance map precision for both compressor and turbine. This is an important analysis to better understand the steady-state difference between the two models.
Transient Modeling of the NETL Hybrid Fuel Cell/Gas Turbine Facility and Experimental Validation
Ferrari, M.L.; Liese, E.A.; Tucker, D.A.; Lawson, L.O.; Traverso, A.; Massardo, A.F.
2007-10-01
This paper describes the experimental validation of two different transient models of the hybrid fuel cell/gas turbine facility of the U.S. DOE-NETL at Morgantown. The first part of this work is devoted to the description of the facility, designed to experimentally investigate these plants with real components, except the fuel cell. The behavior of the SOFC is obtained with apt volumes (for the stack and the off-gas burner) and using a combustor to generate similar thermal effects. The second part of this paper shows the facility real-time transient model developed at the U.S. DOE-NETL and the detailed transient modeling activity using the TRANSEO program developed at TPG. The results obtained with both models are successfully compared with the experimental data of two different load step decreases. The more detailed model agrees more closely with the experimental data, which, of course, is more time consuming than the real-time model (the detailed model operates with a calculation over calculated time ratio around 6). Finally, the TPG model has been used to discuss the importance of performance map precision for both compressor and turbine. This is an important analysis to better understand the steady-state difference between the two models
A hybrid stochastic-deconvolution model for large-eddy simulation of particle-laden flow
Michałek, W. R.; Kuerten, J. G. M.; Zeegers, J. C. H.; Liew, R.; Pozorski, J.; Geurts, B. J.
2013-12-15
We develop a hybrid model for large-eddy simulation of particle-laden turbulent flow, which is a combination of the approximate deconvolution model for the resolved scales and a stochastic model for the sub-grid scales. The stochastic model incorporates a priori results of direct numerical simulation of turbulent channel flow, which showed that the parameters in the stochastic model are quite independent of Reynolds and Stokes number. In order to correctly predict the flux of particles towards the walls an extra term should be included in the stochastic model, which corresponds to the term related to the well-mixed condition in Langevin models for particle dispersion in inhomogeneous turbulent flow. The model predictions are compared with results of direct numerical simulation of channel flow at a frictional Reynolds number of 950. The inclusion of the stochastic forcing is shown to yield a significant improvement over the approximate deconvolution model for the particles alone when combined with a Stokes dependent weight-factor for the well-mixed term.
Ma, Lu; Wang, Guan; Yan, Xuedong; Weng, Jinxian
2016-04-01
Debates on the ordering patterns of crash injury severity are ongoing in the literature. Models without proper econometrical structures for accommodating the complex ordering patterns of injury severity could result in biased estimations and misinterpretations of factors. This study proposes a hybrid finite mixture (HFM) model aiming to capture heterogeneous ordering patterns of driver injury severity while enhancing modeling flexibility. It attempts to probabilistically partition samples into two groups in which one group represents an unordered/nominal data-generating process while the other represents an ordered data-generating process. Conceptually, the newly developed model offers flexible coefficient settings for mining additional information from crash data, and more importantly it allows the coexistence of multiple ordering patterns for the dependent variable. A thorough modeling performance comparison is conducted between the HFM model, and the multinomial logit (MNL), ordered logit (OL), finite mixture multinomial logit (FMMNL) and finite mixture ordered logit (FMOL) models. According to the empirical results, the HFM model presents a strong ability to extract information from the data, and more importantly to uncover heterogeneous ordering relationships between factors and driver injury severity. In addition, the estimated weight parameter associated with the MNL component in the HFM model is greater than the one associated with the OL component, which indicates a larger likelihood of the unordered pattern than the ordered pattern for driver injury severity. PMID:26809075
Fast numerical algorithms for fitting multiresolution hybrid shape models to brain MRI.
Vemuri, B C; Guo, Y; Lai, S H; Leonard, C M
1997-09-01
In this paper, we present new and fast numerical algorithms for shape recovery from brain MRI using multiresolution hybrid shape models. In this modeling framework, shapes are represented by a core rigid shape characterized by a superquadric function and a superimposed displacement function which is characterized by a membrane spline discretized using the finite-element method. Fitting the model to brain MRI data is cast as an energy minimization problem which is solved numerically. We present three new computational methods for model fitting to data. These methods involve novel mathematical derivations that lead to efficient numerical solutions of the model fitting problem. The first method involves using the nonlinear conjugate gradient technique with a diagonal Hessian preconditioner. The second method involves the nonlinear conjugate gradient in the outer loop for solving global parameters of the model and a preconditioned conjugate gradient scheme for solving the local parameters of the model. The third method involves the nonlinear conjugate gradient in the outer loop for solving the global parameters and a combination of the Schur complement formula and the alternating direction-implicit method for solving the local parameters of the model. We demonstrate the efficiency of our model fitting methods via experiments on several MR brain scans. PMID:9873915
UDEC-AUTODYN Hybrid Modeling of a Large-Scale Underground Explosion Test
NASA Astrophysics Data System (ADS)
Deng, X. F.; Chen, S. G.; Zhu, J. B.; Zhou, Y. X.; Zhao, Z. Y.; Zhao, J.
2015-03-01
In this study, numerical modeling of a large-scale decoupled underground explosion test with 10 tons of TNT in Älvdalen, Sweden is performed by combining DEM and FEM with codes UDEC and AUTODYN. AUTODYN is adopted to model the explosion process, blast wave generation, and its action on the explosion chamber surfaces, while UDEC modeling is focused on shock wave propagation in jointed rock masses surrounding the explosion chamber. The numerical modeling results with the hybrid AUTODYN-UDEC method are compared with empirical estimations, purely AUTODYN modeling results, and the field test data. It is found that in terms of peak particle velocity, empirical estimations are much smaller than the measured data, while purely AUTODYN modeling results are larger than the test data. The UDEC-AUTODYN numerical modeling results agree well with the test data. Therefore, the UDEC-AUTODYN method is appropriate in modeling a large-scale explosive detonation in a closed space and the following wave propagation in jointed rock masses. It should be noted that joint mechanical and spatial properties adopted in UDEC-AUTODYN modeling are determined with empirical equations and available geological data, and they may not be sufficiently accurate.
NASA Astrophysics Data System (ADS)
Rosenbaum, Joyce E.
2011-12-01
Commercial air traffic is anticipated to increase rapidly in the coming years. The impact of aviation noise on communities surrounding airports is, therefore, a growing concern. Accurate prediction of noise can help to mitigate the impact on communities and foster smoother integration of aerospace engineering advances. The problem of accurate sound level prediction requires careful inclusion of all mechanisms that affect propagation, in addition to correct source characterization. Terrain, ground type, meteorological effects, and source directivity can have a substantial influence on the noise level. Because they are difficult to model, these effects are often included only by rough approximation. This dissertation presents a model designed for sound propagation over uneven terrain, with mixed ground type and realistic meteorological conditions. The model is a hybrid of two numerical techniques: the parabolic equation (PE) and fast field program (FFP) methods, which allow for physics-based inclusion of propagation effects and ensure the low frequency content, a factor in community impact, is predicted accurately. Extension of the hybrid model to a pseudo-three-dimensional representation allows it to produce aviation noise contour maps in the standard form. In order for the model to correctly characterize aviation noise sources, a method of representing arbitrary source directivity patterns was developed for the unique form of the parabolic equation starting field. With this advancement, the model can represent broadband, directional moving sound sources, traveling along user-specified paths. This work was prepared for possible use in the research version of the sound propagation module in the Federal Aviation Administration's new standard predictive tool.
"Antelope": a hybrid-logic model checker for branching-time Boolean GRN analysis
2011-01-01
.g., NuSMV) cannot. This additional expressiveness is achieved by employing a logic extending the standard Computation-Tree Logic (CTL) with hybrid-logic operators. Conclusions We illustrate the advantages of Antelope when (a) modeling incomplete networks and environment interaction, (b) exhibiting the set of all states having a given property, and (c) representing Boolean GRN properties with hybrid CTL. PMID:22192526
Stable hybrid stars within a SU(3) quark-meson-model
NASA Astrophysics Data System (ADS)
Zacchi, Andreas; Hanauske, Matthias; Schaffner-Bielich, Jürgen
2016-03-01
The inner regions of the most massive compact stellar objects might be occupied by a phase of quarks. Since the observations of the massive pulsars PSR J1614-2230 and PSR J 0348 +0432 with about two solar masses, the equations of state constructing relativistic stellar models have to be constrained respecting these new limits. We discuss stable hybrid stars, i.e. compact objects with an outer layer composed of nuclear matter and with a core consisting of quark matter (QM). For the outer nuclear layer we utilize a density dependent nuclear equation of state and we use a chiral SU(3) quark-meson model with a vacuum energy pressure to describe the object's core. The appearance of a disconnected mass-radius branch emerging from the hybrid star branch implies the existence of a third family of compact stars, so-called twin stars. Twin stars did not emerge as the transition pressure has to be relatively small with a large jump in energy density, which could not be satisfied within our approach. This is, among other reasons, due to the fact that the speed of sound in QM has to be relatively high, which can be accomplished by an increase of the repulsive coupling. This increase on the other hand yields transition pressures that are too high for twins stars to appear.
Development of a hybrid wave based-transfer matrix model for sound transmission analysis.
Dijckmans, A; Vermeir, G
2013-04-01
In this paper, a hybrid wave based-transfer matrix model is presented that allows for the investigation of the sound transmission through finite multilayered structures placed between two reverberant rooms. The multilayered structure may consist of an arbitrary configuration of fluid, elastic, or poro-elastic layers. The field variables (structural displacements and sound pressures) are expanded in terms of structural and acoustic wave functions. The boundary and continuity conditions in the rooms determine the participation factors in the pressure expansions. The displacement of the multilayered structure is determined by the mechanical impedance matrix, which gives a relation between the pressures and transverse displacements at both sides of the structure. The elements of this matrix are calculated with the transfer matrix method. First, the hybrid model is numerically validated. Next a comparison is made with sound transmission loss measurements of a hollow brick wall and a sandwich panel. Finally, numerical simulations show the influence of structural damping, room dimensions and plate dimensions on the sound transmission loss of multilayered structures. PMID:23556585
A formally verified algorithm for interactive consistency under a hybrid fault model
NASA Technical Reports Server (NTRS)
Lincoln, Patrick; Rushby, John
1993-01-01
Consistent distribution of single-source data to replicated computing channels is a fundamental problem in fault-tolerant system design. The 'Oral Messages' (OM) algorithm solves this problem of Interactive Consistency (Byzantine Agreement) assuming that all faults are worst-cass. Thambidurai and Park introduced a 'hybrid' fault model that distinguished three fault modes: asymmetric (Byzantine), symmetric, and benign; they also exhibited, along with an informal 'proof of correctness', a modified version of OM. Unfortunately, their algorithm is flawed. The discipline of mechanically checked formal verification eventually enabled us to develop a correct algorithm for Interactive Consistency under the hybrid fault model. This algorithm withstands $a$ asymmetric, $s$ symmetric, and $b$ benign faults simultaneously, using $m+1$ rounds, provided $n is greater than 2a + 2s + b + m$, and $m\\geg a$. We present this algorithm, discuss its subtle points, and describe its formal specification and verification in PVS. We argue that formal verification systems such as PVS are now sufficiently effective that their application to fault-tolerance algorithms should be considered routine.
Thermo-Mechanical Modeling of Laser-Mig Hybrid Welding (lmhw)
NASA Astrophysics Data System (ADS)
Kounde, Ludovic; Engel, Thierry; Bergheau, Jean-Michel; Boisselier, Didier
2011-01-01
Hybrid welding is a combination of two different technologies such as laser (Nd: YAG, CO2…) and electric arc welding (MIG, MAG / TIG …) developed to assemble thick metal sheets (over 3 mm) in order to reduce the required laser power. As a matter of fact, hybrid welding is a lso used in the welding of thin materials to benefit from process, deep penetration and gap limit. But the thermo-mechanical behaviour of thin parts assembled by LMHW technology for railway cars production is far from being controlled the modeling and simulation contribute to the assessment of the causes and effects of the thermo mechanical behaviour in the assembled parts. In order to reproduce the morphology of melted and heat-affected zones, two analytic functions were combined to model the heat source of LMHW. On one hand, we applied a so-called "diaboloïd" (DB) which is a modified hyperboloid, based on experimental parameters and the analysis of the macrographs of the welds. On the other hand, we used a so-called "double ellipsoïd" (DE) which takes the MIG only contribution including the bead into account. The comparison between experimental result and numerical result shows a good agreement.
Animal model for ultraviolet radiation-induced melanoma: Platyfish-swordtail hybrid
Setlow, R.B.; Woodhead, A.D.; Grist, E. )
1989-11-01
Sunlight exposure is strongly indicated as one of the important etiologic agents in human cutaneous malignant melanoma. However, because of the absence of good animal models, it has not been possible to estimate the wavelengths or wavelength regions involved. We have developed a useful animal model from crosses and backcrosses of platyfish (Xiphophorus maculatus) and swordtails (Xiphophorus helleri). Two strains of these fish are susceptible to invasive melanoma induction by exposure to filtered radiation from sunlamps in the wavelength ranges lambda greater than 290 nm and lambda greater than 304 nm. Multiple exposures on 5-20 consecutive days beginning on day 5 after birth or a single exposure of approximately 200 J/(m2.day) of lambda greater than 304 nm result in a tumor prevalence of 20% to 40% at 4 months of age compared with a background rate of 12% in one strain and 2% in another. Exposure of the fish to visible light after UV exposure reduces the prevalence to background. The melanomas are similar in many respects to mammalian melanomas, as judged by light and electron microscopy. The genetics of the crosses determined by others and the high sensitivity of the hybrids to melanoma induction indicate that the UV radiation probably inactivates the one tumor repressor gene (or a small number of tumor repressor genes) in the hybrid fish. The small size of the animals and their high susceptibility to melanoma induction make them ideal for action spectroscopy.
Modeling plasma-assisted growth of graphene-carbon nanotube hybrid
NASA Astrophysics Data System (ADS)
Tewari, Aarti
2016-08-01
A theoretical model describing the growth of graphene-CNT hybrid in a plasma medium is presented. Using the model, the growth of carbon nanotube (CNT) on a catalyst particle and thereafter the growth of the graphene on the CNT is studied under the purview of plasma sheath and number density kinetics of different plasma species. It is found that the plasma parameter such as ion density; gas ratios and process parameter such as source power affect the CNT and graphene dimensions. The variation in growth rates of graphene and CNT under different plasma power, gas ratios, and ion densities is analyzed. Based on the results obtained, it can be concluded that higher hydrocarbon ion densities and gas ratios of hydrocarbon to hydrogen favor the growth of taller CNTs and graphene, respectively. In addition, the CNT tip radius reduces with hydrogen ion density and higher plasma power favors graphene with lesser thickness. The present study can help in better understanding of the graphene-CNT hybrid growth in a plasma medium.
Two hybrid Artificial Intelligence approaches for modeling rainfall-runoff process
NASA Astrophysics Data System (ADS)
Nourani, Vahid; Kisi, Özgür; Komasi, Mehdi
2011-05-01
SummaryThe need for accurate modeling of the rainfall-runoff process has grown rapidly in the past decades. However, considering the high stochastic property of the process, many models are still being developed in order to define such a complex phenomenon. Recently, Artificial Intelligence (AI) techniques such as the Artificial Neural Network (ANN) and the Adaptive Neural-Fuzzy Inference System (ANFIS) have been extensively used by hydrologists for rainfall-runoff modeling as well as for other fields of hydrology. In this paper, two hybrid AI-based models which are reliable in capturing the periodicity features of the process are introduced for watershed rainfall-runoff modeling. In the first model, the SARIMAX (Seasonal Auto Regressive Integrated Moving Average with exogenous input)-ANN model, an ANN is used to find the non-linear relationship among the residuals of the fitted linear SARIMAX model. In the second model, the wavelet-ANFIS model, wavelet transform is linked to the ANFIS concept and the main time series of two variables (rainfall and runoff) are decomposed into some multi-frequency time series by wavelet transform. Afterwards, these time series are imposed as input data to the ANFIS to predict the runoff discharge one time step ahead. The obtained results of the models applications for the rainfall-runoff modeling of two watersheds (located in Azerbaijan, Iran) show that, although the proposed models can predict both short and long terms runoff discharges by considering seasonality effects, the second model is relatively more appropriate because it uses the multi-scale time series of rainfall and runoff data in the ANFIS input layer.
NASA Astrophysics Data System (ADS)
Ezzedine, S. M.; Lomov, I.; Ryerson, F. J.; Glascoe, L. G.
2011-12-01
Numerical simulations become increasingly widespread to support decision-making and policy-making processes in energy-related emerging technologies such as enhanced geothermal systems, extraction of tight-gas to name a few. However, numerical models typically have uncertainty associated with their inputs (parametric, conceptual and structural), leading to uncertainty in model outputs. Effective abstraction of model results to decision-making requires proper characterization, propagation, and analysis of that uncertainty. Propagation of uncertainty often relies on complex multiphysics models. For instance, fluid-induced fracturing calls for hydro-mechanical, or hydro-thermal-mechanical or hydro-thermal-mechanical-chemical coupling. For the past decade several complex coupled deterministic models have been proposed to address the hydro-fracking problem with moderate successes. Despite that these models can be used as drivers for the uncertainty quantification, they are numerically and computationally cumbersome. In this paper, we present a surrogate model that can handle, for instance, 1) the hydromechanical coupling with minimum computational costs, 2) the tracking of simultaneous propagation of hundreds of fracture tips, with propagation velocities proportional to the stress intensity factor at each crack tip, 3) and the propagation of uncertainty from inputs to outputs, for example via Monte Carlo simulation. We also present a novel hybrid modeling scheme designed for propagating uncertainty and performing a global sensitivity analysis, while maintaining the quantitative rigor of the analysis by providing confidence intervals on predictions. (Prepared by LLNL under Contract DE-AC52-07NA27344).
A simple and transferable all-atom/coarse-grained hybrid model to study membrane processes.
Genheden, Samuel; Essex, Jonathan W
2015-10-13
We present an efficient all-atom/coarse-grained hybrid model and apply it to membrane processes. This model is an extension of the all-atom/ELBA model applied previously to processes in water. Here, we improve the efficiency of the model by implementing a multiple-time step integrator that allows the atoms and the coarse-grained beads to be propagated at different timesteps. Furthermore, we fine-tune the interaction between the atoms and the coarse-grained beads by computing the potential of mean force of amino acid side chain analogs along the membrane normal and comparing to atomistic simulations. The model was independently validated on the calculation of small-molecule partition coefficients. Finally, we apply the model to membrane peptides. We studied the tilt angle of the Walp23 and Kalp23 helices in two different model membranes and the stability of the glycophorin A dimer. The model is efficient, accurate, and straightforward to use, as it does not require any extra interaction particles, layers of atomistic solvent molecules or tabulated potentials, thus offering a novel, simple approach to study membrane processes. PMID:26574264
Establishment of a hybrid rainfall-runoff model for use in the Noah LSM
NASA Astrophysics Data System (ADS)
Xu, Jingwen; Zhang, Wanchang; Zheng, Ziyan; Chen, Jing; Jiao, Meiyan
2012-02-01
There is an increasing trend to incorporate the basin hydrological model into the traditional land surface model (LSM) to improve the description of hydrological processes in them. For incorporating with the Noah LSM, a new rainfall-runoff model named XXT (the first X stands for Xinanjiang, the second X stands for hybrid, and T stands for TOPMODEL) was developed and presented in this study, based on the soil moisture storage capacity distribution curve (SMSCC), some essential modules of the Xinanjiang model, together with the simple model framework of the TOPMODEL (a topography based hydrological model). The innovation of XXT is that the water table is incorporated into SMSCC and it connects the surface runoff production with base flow production. This improves the description of the dynamically varying saturated areas that produce runoff and also captures the physical underground water level. XXT was tested in a small-scale watershed Youshuijie (946 km2) and a large-scale watershed Yinglouxia (10009 km2) in China. The results show that XXT has better performance against the TOPMODEL and the Xinanjiang model for the two watersheds in both the calibration period and the validation period in terms of the Nash-Sutcliffe efficiency. Moreover, XXT captures the largest peak flow well for both the small- and large-scale watersheds during the validation period, while the TOPMODEL produces significant overestimates or underestimates, so does the Xinanjiang model.
NASA Astrophysics Data System (ADS)
Zarafshan, P.; Moosavian, S. Ali A.
2013-10-01
Dynamics modelling and control of multi-body space robotic systems composed of rigid and flexible elements is elaborated here. Control of such systems is highly complicated due to severe under-actuated condition caused by flexible elements, and an inherent uneven nonlinear dynamics. Therefore, developing a compact dynamics model with the requirement of limited computations is extremely useful for controller design, also to develop simulation studies in support of design improvement, and finally for practical implementations. In this paper, the Rigid-Flexible Interactive dynamics Modelling (RFIM) approach is introduced as a combination of Lagrange and Newton-Euler methods, in which the motion equations of rigid and flexible members are separately developed in an explicit closed form. These equations are then assembled and solved simultaneously at each time step by considering the mutual interaction and constraint forces. The proposed approach yields a compact model rather than common accumulation approach that leads to a massive set of equations in which the dynamics of flexible elements is united with the dynamics equations of rigid members. To reveal such merits of this new approach, a Hybrid Suppression Control (HSC) for a cooperative object manipulation task will be proposed, and applied to usual space systems. A Wheeled Mobile Robotic (WMR) system with flexible appendages as a typical space rover is considered which contains a rigid main body equipped with two manipulating arms and two flexible solar panels, and next a Space Free Flying Robotic system (SFFR) with flexible members is studied. Modelling verification of these complicated systems is vigorously performed using ANSYS and ADAMS programs, while the limited computations of RFIM approach provides an efficient tool for the proposed controller design. Furthermore, it will be shown that the vibrations of the flexible solar panels results in disturbing forces on the base which may produce undesirable errors
A hybrid modeling approach to resolve pollutant concentrations in an urban area
NASA Astrophysics Data System (ADS)
Stein, Ariel F.; Isakov, Vlad; Godowitch, James; Draxler, Roland R.
A modeling tool that can resolve contributions from individual sources to the urban environment is critical for air-toxics exposure assessments. Air toxics are often chemically reactive and may have background concentrations originated from distant sources. Grid models are the best-suited tools to handle the regional features of these chemicals. However, these models are not designed to resolve pollutant concentrations on local scales. Moreover, for many species of interest, having reaction time scales that are longer than the travel time across an urban area, chemical reactions can be ignored in describing local dispersion from strong individual sources making Lagrangian and plume-dispersion models practical. In this study, we test the feasibility of developing an urban hybrid simulation system. In this combination, the Community Multi-scale Air Quality model (CMAQ) provides the regional background concentrations and urban-scale photochemistry, and local models such as Hybrid Single Particle Lagrangian Integrated Trajectory model (HYSPLIT) and AMS/EPA Regulatory Model (AERMOD) provide the more spatially resolved concentrations due to local emission sources. In the initial application, the HYSPLIT, AERMOD, and CMAQ models are used in combination to calculate high-resolution benzene concentrations in the Houston area. The study period is from 18 August to 4 September of 2000. The Mesoscale Model 5 (MM5) is used to create meteorological fields with a horizontal resolution of 1×1 km 2. In another variation to this approach, multiple HYSPLIT simulations are used to create a concentration ensemble to estimate the contribution to the concentration variability from point sources. HYSPLIT simulations are used to model two sources of concentration variability; one due to variability created by different particle trajectory pathways in the turbulent atmosphere and the other due to different flow regimes that might be introduced when using gridded data to represent
NASA Astrophysics Data System (ADS)
Suzuki, Kensuke
A new analysis tool, an unsteady Hybrid Navier-Stokes/Vortex Model, for a horizontal axis wind turbine (HAWT) in yawed flow is presented, and its convergence and low cost computational performance are demonstrated. In earlier work, a steady Hybrid Navier-Stokes/Vortex Model was developed with a view to improving simulation results obtained by participants of the NASA Ames blind comparison workshop, following the NREL Unsteady Aerodynamics Experiment. The hybrid method was shown to better predict rotor torque and power over the range of wind speeds, from fully attached to separated flows. A decade has passed since the workshop was held and three dimensional unsteady Navier-Stokes analyses have become available using super computers. In the first chapter, recent results of unsteady Euler and Navier-Stokes computations are reviewed as standard references of what is currently possible and are contrasted with results of the Hybrid Navier-Stokes/Vortex Model in steady flow. In Chapter 2, the computational method for the unsteady Hybrid model is detailed. The grid generation procedure, using ICEM CFD, is presented in Chapter 3. Steady and unsteady analysis results for the NREL Phase IV rotor and for a modified "swept NREL rotor" are presented in Chapter 4-Chapter 7.
The paper presents a hybrid air quality modeling approach and its application in NEXUS in order to provide spatial and temporally varying exposure estimates and identification of the mobile source contribution to the total pollutant exposure. Model-based exposure metrics, associa...
Park, Hahnbeom; Lee, Gyu Rie; Heo, Lim; Seok, Chaok
2014-01-01
Protein loop modeling is a tool for predicting protein local structures of particular interest, providing opportunities for applications involving protein structure prediction and de novo protein design. Until recently, the majority of loop modeling methods have been developed and tested by reconstructing loops in frameworks of experimentally resolved structures. In many practical applications, however, the protein loops to be modeled are located in inaccurate structural environments. These include loops in model structures, low-resolution experimental structures, or experimental structures of different functional forms. Accordingly, discrepancies in the accuracy of the structural environment assumed in development of the method and that in practical applications present additional challenges to modern loop modeling methods. This study demonstrates a new strategy for employing a hybrid energy function combining physics-based and knowledge-based components to help tackle this challenge. The hybrid energy function is designed to combine the strengths of each energy component, simultaneously maintaining accurate loop structure prediction in a high-resolution framework structure and tolerating minor environmental errors in low-resolution structures. A loop modeling method based on global optimization of this new energy function is tested on loop targets situated in different levels of environmental errors, ranging from experimental structures to structures perturbed in backbone as well as side chains and template-based model structures. The new method performs comparably to force field-based approaches in loop reconstruction in crystal structures and better in loop prediction in inaccurate framework structures. This result suggests that higher-accuracy predictions would be possible for a broader range of applications. The web server for this method is available at http://galaxy.seoklab.org/loop with the PS2 option for the scoring function. PMID:25419655
Modeling the two-hybrid detector: experimental bias on protein interaction networks.
Stibius, Karin B; Sneppen, Kim
2007-10-01
This work was done to investigate the two-hybrid experiment for finding protein-protein interactions to explain the asymmetry found in the experimental data, and to help screen the data for high confidence interactions. By looking at the bait-prey experimental setup the resulting protein interaction network can be examined as a directed network (bait --> prey). We have investigated two possible scenarios for the asymmetry in the directed network by developing a biochemical model for the protein-DNA and protein-protein bindings inside the living yeast. One scenario assumes a background activity of bait proteins acting even without the prey, the other scenario explores the asymmetry in the chemistry associated with the bait being automatically located in the right position on the DNA. We conclude that the latter model gives the best description of the observed asymmetry. PMID:17557786
NASA Astrophysics Data System (ADS)
Samejima, Masaki; Akiyoshi, Masanori; Mitsukuni, Koshichiro; Komoda, Norihisa
We propose a business scenario evaluation method using qualitative and quantitative hybrid model. In order to evaluate business factors with qualitative causal relations, we introduce statistical values based on propagation and combination of effects of business factors by Monte Carlo simulation. In propagating an effect, we divide a range of each factor by landmarks and decide an effect to a destination node based on the divided ranges. In combining effects, we decide an effect of each arc using contribution degree and sum all effects. Through applied results to practical models, it is confirmed that there are no differences between results obtained by quantitative relations and results obtained by the proposed method at the risk rate of 5%.
NASA Astrophysics Data System (ADS)
Naseri Kouzehgarani, Asal
2009-12-01
Most models of aircraft trajectories are non-linear and stochastic in nature; and their internal parameters are often poorly defined. The ability to model, simulate and analyze realistic air traffic management conflict detection scenarios in a scalable, composable, multi-aircraft fashion is an extremely difficult endeavor. Accurate techniques for aircraft mode detection are critical in order to enable the precise projection of aircraft conflicts, and for the enactment of altitude separation resolution strategies. Conflict detection is an inherently probabilistic endeavor; our ability to detect conflicts in a timely and accurate manner over a fixed time horizon is traded off against the increased human workload created by false alarms---that is, situations that would not develop into an actual conflict, or would resolve naturally in the appropriate time horizon-thereby introducing a measure of probabilistic uncertainty in any decision aid fashioned to assist air traffic controllers. The interaction of the continuous dynamics of the aircraft, used for prediction purposes, with the discrete conflict detection logic gives rise to the hybrid nature of the overall system. The introduction of the probabilistic element, common to decision alerting and aiding devices, places the conflict detection and resolution problem in the domain of probabilistic hybrid phenomena. A hidden Markov model (HMM) has two stochastic components: a finite-state Markov chain and a finite set of output probability distributions. In other words an unobservable stochastic process (hidden) that can only be observed through another set of stochastic processes that generate the sequence of observations. The problem of self separation in distributed air traffic management reduces to the ability of aircraft to communicate state information to neighboring aircraft, as well as model the evolution of aircraft trajectories between communications, in the presence of probabilistic uncertain dynamics as well
Building a hybrid patient's model for augmented reality in surgery: a registration problem.
Lavallée, S; Cinquin, P; Szeliski, R; Peria, O; Hamadeh, A; Champleboux, G; Troccaz, J
1995-03-01
In the field of Augmented Reality in Surgery, building a hybrid patient's model, i.e. merging all the data and systems available for a given application, is a difficult but crucial technical problem. The purpose is to merge all the data that constitute the patient model with the reality of the surgery, i.e. the surgical tools and feedback devices. In this paper, we first develop this concept, we show that this construction comes to a problem of registration between various sensor data, and we detail a general framework of registration. The state of the art in this domain is presented. Finally, we show results that we have obtained using a method which is based on the use of anatomical reference surfaces. We show that in many clinical cases, registration is only possible through the use of internal patient structures. PMID:7554833
Ultraviolet A does not induce melanomas in a Xiphophorus hybrid fish model
Mitchell, David L.; Fernandez, André A.; Nairn, Rodney S.; Garcia, Rachel; Paniker, Lakshmi; Trono, David; Thames, Howard D.; Gimenez-Conti, Irma
2010-01-01
We examined the wavelength dependence of ultraviolet (UV) ra-diation (UVR)-induced melanoma in a Xiphophorus backcross hybrid model previously reported to be susceptible to melanoma induction by ultraviolet A (UVA) and visible light. Whereas ultraviolet B (UVB) irradiation of neonates yielded high frequencies of melanomas in pigmented fish, UVA irradiation resulted in melanoma frequencies that were not significantly different from unirradiated fish. Spontaneous and UV-induced melanoma frequencies correlated with the degree of pigmentation as expected from previous studies, and the histopathology phenotypes of the melanomas were not found in significantly different proportions in UV-treated and -untreated tumor-bearing fish. Our results support the conclusion that a brief early-life exposure to UVB radiation causes melanoma formation in this animal model. These data are consistent with an essential role for direct DNA damage, including cyclobutane dimers and (6-4) photoproducts, in the etiology of melanoma. PMID:20439744
Hybrid Wing Body Model Identification Using Forced-Oscillation Water Tunnel Data
NASA Technical Reports Server (NTRS)
Murphy, Patrick C.; Vicroy, Dan D.; Kramer, Brian; Kerho, Michael
2014-01-01
Static and dynamic testing of the NASA 0.7 percent scale Hybrid Wing Body (HWB) configuration was conducted in the Rolling Hills Research Corporation water tunnel to investigate aerodynamic behavior over a large range of angle-of-attack and to develop models that can predict aircraft response in nonlinear unsteady flight regimes. This paper reports primarily on the longitudinal axis results. Flow visualization tests were also performed. These tests provide additional static data and new dynamic data that complement tests conducted at NASA Langley 14- by 22-Foot Subsonic Tunnel. HWB was developed to support the NASA Environmentally Responsible Aviation Project goals of lower noise, emissions, and fuel burn. This study also supports the NASA Aviation Safety Program efforts to model and control advanced transport configurations in loss-of-control conditions.
PWR hybrid computer model for assessing the safety implications of control systems
Smith, O L; Renier, J P; Difilippo, F C; Clapp, N E; Sozer, A; Booth, R S; Craddick, W G; Morris, D G
1986-03-01
The ORNL study of safety-related aspects of nuclear power plant control systems consists of two interrelated tasks: (1) failure mode and effects analysis (FMEA) that identified single and multiple component failures that might lead to significant plant upsets and (2) computer models that used these failures as initial conditions and traced the dynamic impact on the control system and remainder of the plant. This report describes the simulation of Oconee Unit 1, the first plant analyzed. A first-principles, best-estimate model was developed and implemented on a hybrid computer consisting of AD-4 analog and PDP-10 digital machines. Controls were placed primarily on the analog to use its interactive capability to simulate operator action. 48 refs., 138 figs., 15 tabs.
Local tetrahedron modeling of microelectronics using the finite-volume hybrid-grid technique
Riley, D.J.; Turner, C.D.
1995-12-01
The finite-volume hybrid-grid (FVHG) technique uses both structured and unstructured grid regions in obtaining a solution to the time-domain Maxwell`s equations. The method is based on explicit time differencing and utilizes rectilinear finite-difference time-domain (FDTD) and nonorthogonal finite-volume time-domain (FVTD). The technique directly couples structured FDTD grids with unstructured FVTD grids without the need for spatial interpolation across grid interfaces. In this paper, the FVHG method is applied to simple planar microelectronic devices. Local tetrahedron grids are used to model portions of the device under study, with the remainder of the problem space being modeled with cubical hexahedral cells. The accuracy of propagating microstrip-guided waves from a low-density hexahedron region through a high-density tetrahedron grid is investigated.
NASA Technical Reports Server (NTRS)
Venkatesan, C.; Friedmann, P. P.
1984-01-01
Hybrid Heavy Lift Airship (HHLA) is a proposed candidate vehicle aimed at providing heavy lift capability at low cost. This vehicle consists of a buoyant envelope attached to a supporting structure to which four rotor systems, taken from existing helicopters are attached. Nonlinear equations of motion capable of modelling the dynamics of this coupled multi-rotor/support frame/vehicle system have been developed. Using these equations of motion the aeroelastic and aeromechanical stability analysis is performed aimed at identifying potential instabilities which could occur for this type of vehicle. The coupling between various blade, supporting structure and rigid body modes is identified. Furthermore, the effects of changes in buoyancy ratio (Buoyant lift/total weight) on the dynamic characteristics of the vehicle are studied. The dynamic effects found are of considerable importance for the design of such vehicles. The analytical model developed is also useful for studying the aeromechanical stability of single rotor and tandem rotor coupled rotor/fuselage systems.
Botros, Youssry Y.; VanBaren, Philip; Ebbini, Emad S.
2010-01-01
A computationally efficient hybrid ray–physical optics (HRPO) model is presented for the analysis and synthesis of multiple-focus ultrasound heating patterns through the human rib cage. In particular, a ray method is used to propagate the ultrasound fields from the source to the frontal plane of the rib cage. The physical-optics integration method is then employed to obtain the intensity pattern inside the rib cage. The solution of the matrix system is carried out by using the pseudo inverse technique to synthesize the desired heating pattern. The proposed technique guides the fields through the intercostal spacings between the solid ribs and, thus, minimal intensity levels are observed over the solid ribs. This simulation model allows for the design and optimization of large-aperture phased-array applicator systems for noninvasive ablative thermal surgery in the heart and liver through the rib cage. PMID:9353983
NASA Astrophysics Data System (ADS)
Tang, Xian-Zhu; McDevitt, C. J.; Guo, Zehua; Berk, H. L.
2014-03-01
Inertial confinement fusion requires an imploded target in which a central hot spot is surrounded by a cold and dense pusher. The hot spot/pusher interface can take complicated shape in three dimensions due to hydrodynamic mix. It is also a transition region where the Knudsen and inverse Knudsen layer effect can significantly modify the fusion reactivity in comparison with the commonly used value evaluated with background Maxwellians. Here, we describe a hybrid model that couples the kinetic correction of fusion reactivity to global hydrodynamic implosion simulations. The key ingredient is a non-perturbative treatment of the tail ions in the interface region where the Gamow ion Knudsen number approaches or surpasses order unity. The accuracy of the coupling scheme is controlled by the precise criteria for matching the non-perturbative kinetic model to perturbative solutions in both configuration space and velocity space.
A Hybrid Model for Erythrocyte Membrane: A Single Unit of Protein Network Coupled with Lipid Bilayer
Zhu, Qiang; Vera, Carlos; Asaro, Robert J.; Sche, Paul; Sung, L. Amy
2007-01-01
To investigate the nanomechanics of the erythrocyte membrane we developed a hybrid model that couples the actin-spectrin network to the lipid bilayer. This model features a Fourier space Brownian dynamics model of the bilayer, a Brownian dynamics model of the actin protofilament, and a modified wormlike-chain model of the spectrin (including a cable-dynamics model to predict the oscillation in tension). This model enables us to predict the nanomechanics of single or multiple units of the protein network, the lipid bilayer, and the effect of their interactions. The present work is focused on the attitude of the actin protofilament at the equilibrium states coupled with the elevations of the lipid bilayer through their primary linkage at the suspension complex in deformations. Two different actin-spectrin junctions are considered at the junctional complex. With a point-attachment junction, large pitch angles and bifurcation of yaw angles are predicted. Thermal fluctuations at bifurcation may lead to mode-switching, which may affect the network and the physiological performance of the membrane. In contrast, with a wrap-around junction, pitch angles remain small, and the occurrence of bifurcation is greatly reduced. These simulations suggest the importance of three-dimensional molecular junctions and the lipid bilayer/protein network coupling on cell membrane mechanics. PMID:17449663
A Hybrid Approach for Highly Coarse-grained Lipid Bilayer Models
Srivastava, Anand; Voth, Gregory A.
2012-01-01
We present a systematic methodology to develop highly coarse-grained (CG) lipid models for large scale bio-membrane simulations, in which we derive CG interactions using a powerful combination of the multiscale coarse-graining (MS-CG) method, and an analytical form of the CG potential to model interactions at short range. The resulting hybrid coarse-graining (HCG) methodology is used to develop a three-site solvent-free model for 1,2-dilauroyl-sn-glycero-3-phosphocholine (DLPC), 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC), and a 1:1 mixture of 1,2-dioleoyl-sn-glycero-3-phospho-L-serine (DOPS) and DOPC. In addition, we developed a four-site model of DOPC, demonstrating the capability of the HCG methodology in designing model lipid systems of a desired resolution. We carried out microsecond-scale molecular dynamics (MD) simulations of large vesicles, highlighting the ability of the model to study systems at mesoscopic length and time scales. The models of DLPC, DOPC and DOPC-DOPS have elastic properties consistent with experiment and structural properties such as the radial distribution functions (RDF), bond and angle distributions, and the z-density distributions that compare well with reference all-atom systems. PMID:25100925
Assessing the impact of policy changes in the Icelandic cod fishery using a hybrid simulation model.
Sigurðardóttir, Sigríður; Johansson, Björn; Margeirsson, Sveinn; Viðarsson, Jónas R
2014-01-01
Most of the Icelandic cod is caught in bottom trawlers or longliners. These two fishing methods are fundamentally different and have different economic, environmental, and even social effects. In this paper we present a hybrid-simulation framework to assess the impact of changing the ratio between cod quota allocated to vessels with longlines and vessels with bottom trawls. It makes use of conventional bioeconomic models and discrete event modelling and provides a framework for simulating life cycle assessment (LCA) for a cod fishery. The model consists of two submodels, a system dynamics model describing the biological aspect of the fishery and a discrete event model for fishing activities. The model was run multiple times for different quota allocation scenarios and results are presented where different scenarios are presented in the three dimensions of sustainability: environmental, social, and economic. The optimal allocation strategy depends on weighing the three different factors. The results were encouraging first-steps towards a useful modelling method but the study would benefit greatly from better data on fishing activities. PMID:24778597
Assessing the Impact of Policy Changes in the Icelandic Cod Fishery Using a Hybrid Simulation Model
Sigurðardóttir, Sigríður; Johansson, Björn; Margeirsson, Sveinn; Viðarsson, Jónas R.
2014-01-01
Most of the Icelandic cod is caught in bottom trawlers or longliners. These two fishing methods are fundamentally different and have different economic, environmental, and even social effects. In this paper we present a hybrid-simulation framework to assess the impact of changing the ratio between cod quota allocated to vessels with longlines and vessels with bottom trawls. It makes use of conventional bioeconomic models and discrete event modelling and provides a framework for simulating life cycle assessment (LCA) for a cod fishery. The model consists of two submodels, a system dynamics model describing the biological aspect of the fishery and a discrete event model for fishing activities. The model was run multiple times for different quota allocation scenarios and results are presented where different scenarios are presented in the three dimensions of sustainability: environmental, social, and economic. The optimal allocation strategy depends on weighing the three different factors. The results were encouraging first-steps towards a useful modelling method but the study would benefit greatly from better data on fishing activities. PMID:24778597
Computational lymphatic node models in pediatric and adult hybrid phantoms for radiation dosimetry
NASA Astrophysics Data System (ADS)
Lee, Choonsik; Lamart, Stephanie; Moroz, Brian E.
2013-03-01
We developed models of lymphatic nodes for six pediatric and two adult hybrid computational phantoms to calculate the lymphatic node dose estimates from external and internal radiation exposures. We derived the number of lymphatic nodes from the recommendations in International Commission on Radiological Protection (ICRP) Publications 23 and 89 at 16 cluster locations for the lymphatic nodes: extrathoracic, cervical, thoracic (upper and lower), breast (left and right), mesentery (left and right), axillary (left and right), cubital (left and right), inguinal (left and right) and popliteal (left and right), for different ages (newborn, 1-, 5-, 10-, 15-year-old and adult). We modeled each lymphatic node within the voxel format of the hybrid phantoms by assuming that all nodes have identical size derived from published data except narrow cluster sites. The lymph nodes were generated by the following algorithm: (1) selection of the lymph node site among the 16 cluster sites; (2) random sampling of the location of the lymph node within a spherical space centered at the chosen cluster site; (3) creation of the sphere or ovoid of tissue representing the node based on lymphatic node characteristics defined in ICRP Publications 23 and 89. We created lymph nodes until the pre-defined number of lymphatic nodes at the selected cluster site was reached. This algorithm was applied to pediatric (newborn, 1-, 5-and 10-year-old male, and 15-year-old males) and adult male and female ICRP-compliant hybrid phantoms after voxelization. To assess the performance of our models for internal dosimetry, we calculated dose conversion coefficients, called S values, for selected organs and tissues with Iodine-131 distributed in six lymphatic node cluster sites using MCNPX2.6, a well validated Monte Carlo radiation transport code. Our analysis of the calculations indicates that the S values were significantly affected by the location of the lymph node clusters and that the values increased for
NASA Astrophysics Data System (ADS)
Schuster, Jonathan
Infrared (IR) detectors are well established as a vital sensor technology for military, defense and commercial applications. Due to the expense and effort required to fabricate pixel arrays, it is imperative to develop numerical simulation models to perform predictive device simulations which assess device characteristics and design considerations. Towards this end, we have developed a robust three-dimensional (3D) numerical simulation model for IR detector pixel arrays. We used the finite-difference time-domain technique to compute the optical characteristics including the reflectance and the carrier generation rate in the device. Subsequently, we employ the finite element method to solve the drift-diffusion equations to compute the electrical characteristics including the I(V) characteristics, quantum efficiency, crosstalk and modulation transfer function. We use our 3D numerical model to study a new class of detector based on the nBn-architecture. This detector is a unipolar unity-gain barrier device consisting of a narrow-gap absorber layer, a wide-gap barrier layer, and a narrow-gap collector layer. We use our model to study the underlying physics of these devices and to explain the anomalously long lateral collection lengths for photocarriers measured experimentally. Next, we investigate the crosstalk in HgCdTe photovoltaic pixel arrays employing a photon-trapping (PT) structure realized with a periodic array of pillars intended to provide broadband operation. The PT region drastically reduces the crosstalk; making the use of the PT structures not only useful to obtain broadband operation, but also desirable for reducing crosstalk, especially in small pitch detector arrays. Then, the power and flexibility of the nBn architecture is coupled with a PT structure to engineer spectrally filtering detectors. Last, we developed a technique to reduce the cost of large-format, high performance HgCdTe detectors by nondestructively screen-testing detector arrays prior
Exact hybrid particle/population simulation of rule-based models of biochemical systems.
Hogg, Justin S; Harris, Leonard A; Stover, Lori J; Nair, Niketh S; Faeder, James R
2014-04-01
Detailed modeling and simulation of biochemical systems is complicated by the problem of combinatorial complexity, an explosion in the number of species and reactions due to myriad protein-protein interactions and post-translational modifications. Rule-based modeling overcomes this problem by representing molecules as structured objects and encoding their interactions as pattern-based rules. This greatly simplifies the process of model specification, avoiding the tedious and error prone task of manually enumerating all species and reactions that can potentially exist in a system. From a simulation perspective, rule-based models can be expanded algorithmically into fully-enumerated reaction networks and simulated using a variety of network-based simulation methods, such as ordinary differential equations or Gillespie's algorithm, provided that the network is not exceedingly large. Alternatively, rule-based models can be simulated directly using particle-based kinetic Monte Carlo methods. This "network-free" approach produces exact stochastic trajectories with a computational cost that is independent of network size. However, memory and run time costs increase with the number of particles, limiting the size of system that can be feasibly simulated. Here, we present a hybrid particle/population simulation method that combines the best attributes of both the network-based and network-free approaches. The method takes as input a rule-based model and a user-specified subset of species to treat as population variables rather than as particles. The model is then transformed by a process of "partial network expansion" into a dynamically equivalent form that can be simulated using a population-adapted network-free simulator. The transformation method has been implemented within the open-source rule-based modeling platform BioNetGen, and resulting hybrid models can be simulated using the particle-based simulator NFsim. Performance tests show that significant memory savings
Exact Hybrid Particle/Population Simulation of Rule-Based Models of Biochemical Systems
Stover, Lori J.; Nair, Niketh S.; Faeder, James R.
2014-01-01
Detailed modeling and simulation of biochemical systems is complicated by the problem of combinatorial complexity, an explosion in the number of species and reactions due to myriad protein-protein interactions and post-translational modifications. Rule-based modeling overcomes this problem by representing molecules as structured objects and encoding their interactions as pattern-based rules. This greatly simplifies the process of model specification, avoiding the tedious and error prone task of manually enumerating all species and reactions that can potentially exist in a system. From a simulation perspective, rule-based models can be expanded algorithmically into fully-enumerated reaction networks and simulated using a variety of network-based simulation methods, such as ordinary differential equations or Gillespie's algorithm, provided that the network is not exceedingly large. Alternatively, rule-based models can be simulated directly using particle-based kinetic Monte Carlo methods. This “network-free” approach produces exact stochastic trajectories with a computational cost that is independent of network size. However, memory and run time costs increase with the number of particles, limiting the size of system that can be feasibly simulated. Here, we present a hybrid particle/population simulation method that combines the best attributes of both the network-based and network-free approaches. The method takes as input a rule-based model and a user-specified subset of species to treat as population variables rather than as particles. The model is then transformed by a process of “partial network expansion” into a dynamically equivalent form that can be simulated using a population-adapted network-free simulator. The transformation method has been implemented within the open-source rule-based modeling platform BioNetGen, and resulting hybrid models can be simulated using the particle-based simulator NFsim. Performance tests show that significant memory
One-Dimensional Hybrid Satellite Track Model for the Dynamics Explorer 2 (DE 2) Satellite
NASA Technical Reports Server (NTRS)
Deng, Wei; Killeen, T. L.; Burns, A. G.; Johnson, R. M.; Emery, B. A.; Roble, R. G.; Winningham, J. D.; Gary, J. B.
1995-01-01
A one-dimensional hybrid satellite track model has been developed to calculate the high-latitude thermospheric/ionospheric structure below the satellite altitude using Dynamics Explorer 2 (DE 2) satellite measurements and theory. This model is based on Emery et al. satellite track code but also includes elements of Roble et al. global mean thermosphere/ionosphere model. A number of parameterizations and data handling techniques are used to input satellite data from several DE 2 instruments into this model. Profiles of neutral atmospheric densities are determined from the MSIS-90 model and measured neutral temperatures. Measured electron precipitation spectra are used in an auroral model to calculate particle impact ionization rates below the satellite. These rates are combined with a solar ionization rate profile and used to solve the O(+) diffusion equation, with the measured electron density as an upper boundary condition. The calculated O(+) density distribution, as well as the ionization profiles, are then used in a photochemical equilibrium model to calculate the electron and molecular ion densities. The electron temperature is also calculated by solving the electron energy equation with an upper boundary condition determined by the DE 2 measurement. The model enables calculations of altitude profiles of conductivity and Joule beating rate along and below the satellite track. In a first application of the new model, a study is made of thermospheric and ionospheric structure below the DE 2 satellite for a single orbit which occurred on October 25, 1981. The field-aligned Poynting flux, which is independently obtained for this orbit, is compared with the model predictions of the height-integrated energy conversion rate. Good quantitative agreement between these two estimates has been reached. In addition, measurements taken at the incoherent scatter radar site at Chatanika (65.1 deg N, 147.4 deg W) during a DE 2 overflight are compared with the model
Hybrid Ontology for Semantic Information Retrieval Model Using Keyword Matching Indexing System
Uthayan, K. R.; Anandha Mala, G. S.
2015-01-01
Ontology is the process of growth and elucidation of concepts of an information domain being common for a group of users. Establishing ontology into information retrieval is a normal method to develop searching effects of relevant information users require. Keywords matching process with historical or information domain is significant in recent calculations for assisting the best match for specific input queries. This research presents a better querying mechanism for information retrieval which integrates the ontology queries with keyword search. The ontology-based query is changed into a primary order to predicate logic uncertainty which is used for routing the query to the appropriate servers. Matching algorithms characterize warm area of researches in computer science and artificial intelligence. In text matching, it is more dependable to study semantics model and query for conditions of semantic matching. This research develops the semantic matching results between input queries and information in ontology field. The contributed algorithm is a hybrid method that is based on matching extracted instances from the queries and information field. The queries and information domain is focused on semantic matching, to discover the best match and to progress the executive process. In conclusion, the hybrid ontology in semantic web is sufficient to retrieve the documents when compared to standard ontology. PMID:25922851
Hybrid neutron stars with the Dyson-Schwinger quark model and various quark-gluon vertices
NASA Astrophysics Data System (ADS)
Chen, H.; Wei, J.-B.; Baldo, M.; Burgio, G. F.; Schulze, H.-J.
2015-05-01
We study cold dense quark matter and hybrid neutron stars with a Dyson-Schwinger quark model and various choices of the quark-gluon vertex. We obtain the equation of state of quark matter in beta equilibrium and investigate the hadron-quark phase transition in combination with a hadronic equation of state derived within the Brueckner-Hartree-Fock many-body theory. Comparing with the results for quark matter within the rainbow approximation, the Ball-Chiu (BC) Ansatz and the 1BC Ansatz for the quark-gluon vertex lead to a reduction of the effective interaction at finite chemical potential, qualitatively similar to the effect of our gluon propagator. We find that the phase transition and the equation of state of the quark or mixed phase and consequently the resulting hybrid star mass and radius depend mainly on a global reduction of the effective interaction due to effects of both the quark-gluon vertex and gluon propagator, but are not sensitive to details of the vertex Ansatz.
Effects of correlated hybridization in the single-impurity Anderson model
NASA Astrophysics Data System (ADS)
Líbero, Valter; Veiga, Rodrigo
2013-03-01
The development of new materials often dependents on the theoretical foundations which study the microscopic matter, i.e., the way atoms interact and create distinct configurations. Among the interesting materials, those with partially filled d or f orbitals immersed in nonmagnetic metals have been described by the Anderson model, which takes into account Coulomb correlation (U) when a local level (energy Ed) is doubled occupied, and an electronic hybridization between local levels and conduction band states. In addition, here we include a correlated hybridization term, which depends on the local-level occupation number involved. This term breaks particle-hole symmetry (even when U + 2Ed = 0), enhances charge fluctuations on local levels and as a consequence strongly modifies the crossover between the Hamiltonian fixed-points, even suppressing one or other. We exemplify these behaviors showing data obtained from the Numerical Renormalization Group (NRG) computation for the impurity temperature-dependent specific heat, entropy and magnetic susceptibility. The interleaving procedure is used to recover the continuum spectrum after the NRG-logarithmic discretization of the conduction band. Fundação de Amparo à Pesquisa do Estado de São Paulo - FAPESP.
Jin, Zhongyuan; Liu, Baoan; Feng, Deyun; Chen, Chen; Li, Xiang; Hu, Yongbin; Peng, Jinwu; Liu, Yu; Du, Jing; Fu, Chunyan; Wen, Jifang
2008-08-01
The critical molecular mechanism in the development of the pulmonary fibrosis remains unknown, leaving diagnosed patients with a poor prognosis. To isolate the genes specifically up-regulated in pulmonary fibrosis, we established a rat silicosis model 360 d after treatment with crystalline silica suspension. Radiographs of chests showed that some scattered high-density shadows appeared in the lung field. Typical microscopic fibrosing silicotic nodules formed in the lung, alveolar epithelial cells and bronchial epithelial cells, particularly around the partial fibrosing silicotic nodules; some of them showed atypical hyperplasia that suggested a correlation between silicosis and lung cancer. Suppression subtractive hybridization analysis was performed to compare gene expression in lung tissue with silicosis and normal lung tissue. Reverse transcription-polymerase chain reaction showed that the expressions of seven novel cDNA sequences identified by suppression subtractive hybridization in lung tissue with silicosis differed from normal lung tissue. Bioinformatics analysis showed that 47 positive clones represented 35 genes containing two putative proteins and four predicted similar proteins. The analysis also showed that some screened genes in silicosis, such as prolyl 4-hydroxylases, actin-related protein-2/3 complex and acidic mammalian chitinase, have not been previously reported. These genes may provide new clues for investigating the molecular mechanisms in the development of pulmonary fibrosis. PMID:18685790
Quasi-linear modeling of lower hybrid current drive in ITER and DEMO
NASA Astrophysics Data System (ADS)
Cardinali, A.; Cesario, R.; Panaccione, L.; Santini, F.; Amicucci, L.; Castaldo, C.; Ceccuzzi, S.; Mirizzi, F.; Tuccillo, A. A.
2015-12-01
First pass absorption of the Lower Hybrid waves in thermonuclear devices like ITER and DEMO is modeled by coupling the ray tracing equations with the quasi-linear evolution of the electron distribution function in 2D velocity space. As usually assumed, the Lower Hybrid Current Drive is not effective in a plasma of a tokamak fusion reactor, owing to the accessibility condition which, depending on the density, restricts the parallel wavenumber to values greater than n∥crit and, at the same time, to the high electron temperature that would enhance the wave absorption and then restricts the RF power deposition to the very periphery of the plasma column (near the separatrix). In this work, by extensively using the "raystar" code, a parametric study of the propagation and absorption of the LH wave as function of the coupled wave spectrum (as its width, and peak value), has been performed very accurately. Such a careful investigation aims at controlling the power deposition layer possibly in the external half radius of the plasma, thus providing a valuable aid to the solution of how to control the plasma current profile in a toroidal magnetic configuration, and how to help the suppression of MHD mode that can develop in the outer part of the plasma. This analysis is useful not only for exploring the possibility of profile control of a pulsed operation reactor as well as the tearing mode stabilization, but also in order to reconsider the feasibility of steady state regime for DEMO.
Biogas desulfurization and biogas upgrading using a hybrid membrane system--modeling study.
Makaruk, A; Miltner, M; Harasek, M
2013-01-01
Membrane gas permeation using glassy membranes proved to be a suitable method for biogas upgrading and natural gas substitute production on account of low energy consumption and high compactness. Glassy membranes are very effective in the separation of bulk carbon dioxide and water from a methane-containing stream. However, the content of hydrogen sulfide can be lowered only partially. This work employs process modeling based upon the finite difference method to evaluate a hybrid membrane system built of a combination of rubbery and glassy membranes. The former are responsible for the separation of hydrogen sulfide and the latter separate carbon dioxide to produce standard-conform natural gas substitute. The evaluation focuses on the most critical upgrading parameters like achievable gas purity, methane recovery and specific energy consumption. The obtained results indicate that the evaluated hybrid membrane configuration is a potentially efficient system for the biogas processing tasks that do not require high methane recoveries, and allows effective desulfurization for medium and high hydrogen sulfide concentrations without additional process steps. PMID:23168631
Modeling and energy management control design for a fuel cell hybrid passenger bus
NASA Astrophysics Data System (ADS)
Simmons, Kyle; Guezennec, Yann; Onori, Simona
2014-01-01
This paper presents the modeling and supervisory energy management design of a hybrid fuel cell/battery-powered passenger bus. With growing concerns about petroleum usage and greenhouse gas emissions in the transportation sector, finding alternative methods for vehicle propulsion is necessary. Proton Exchange Membrane (PEM) fuel cell systems are viable possibilities for energy converters due to their high efficiencies and zero emissions. It has been shown that the benefits of PEM fuel cell systems can be greatly improved through hybridization. In this work, the challenge of developing an on-board energy management strategy with near-optimal performance is addressed by a two-step process. First, an optimal control based on Pontryagin's Minimum Principle (PMP) is implemented to find the global optimal solution which minimizes fuel consumption, for different drive cycles, with and without grade. The optimal solutions are analyzed in order to aid in development of a practical controller suitable for on-board implementation, in the form of an Auto-Regressive Moving Average (ARMA) regulator. Simulation results show that the ARMA controller is capable of achieving fuel economy within 3% of the PMP controller while being able to limit the transient demand on the fuel cell system.
Communication: double-hybrid functionals from adiabatic-connection: the QIDH model.
Brémond, Éric; Sancho-García, Juan Carlos; Pérez-Jiménez, Ángel José; Adamo, Carlo
2014-07-21
A new approach stemming from the adiabatic-connection (AC) formalism is proposed to derive parameter-free double-hybrid (DH) exchange-correlation functionals. It is based on a quadratic form that models the integrand of the coupling parameter, whose components are chosen to satisfy several well-known limiting conditions. Its integration leads to DHs containing a single parameter controlling the amount of exact exchange, which is determined by requiring it to depend on the weight of the MP2 correlation contribution. Two new parameter-free DHs functionals are derived in this way, by incorporating the non-empirical PBE and TPSS functionals in the underlying expression. Their extensive testing using the GMTKN30 benchmark indicates that they are in competition with state-of-the-art DHs, yet providing much better self-interaction errors and opening a new avenue towards the design of accurate double-hybrid exchange-correlation functionals departing from the AC integrand. PMID:25053294
Hybrid ontology for semantic information retrieval model using keyword matching indexing system.
Uthayan, K R; Mala, G S Anandha
2015-01-01
Ontology is the process of growth and elucidation of concepts of an information domain being common for a group of users. Establishing ontology into information retrieval is a normal method to develop searching effects of relevant information users require. Keywords matching process with historical or information domain is significant in recent calculations for assisting the best match for specific input queries. This research presents a better querying mechanism for information retrieval which integrates the ontology queries with keyword search. The ontology-based query is changed into a primary order to predicate logic uncertainty which is used for routing the query to the appropriate servers. Matching algorithms characterize warm area of researches in computer science and artificial intelligence. In text matching, it is more dependable to study semantics model and query for conditions of semantic matching. This research develops the semantic matching results between input queries and information in ontology field. The contributed algorithm is a hybrid method that is based on matching extracted instances from the queries and information field. The queries and information domain is focused on semantic matching, to discover the best match and to progress the executive process. In conclusion, the hybrid ontology in semantic web is sufficient to retrieve the documents when compared to standard ontology. PMID:25922851
A Hybrid Double-Layer Master-Slave Model For Multicore-Node Clusters
NASA Astrophysics Data System (ADS)
Liu, Gang; Schmider, Hartmut; Edgecombe, Kenneth E.
2012-10-01
The Double-Layer Master-Slave Model (DMSM) is a suitable hybrid model for executing a workload that consists of multiple independent tasks of varying length on a cluster consisting of multicore nodes. In this model, groups of individual tasks are first deployed to the cluster nodes through an MPI based Master-Slave model. Then, each group is processed by multiple threads on the node through an OpenMP based All-Slave approach. The lack of thread safety of most MPI libraries has to be addressed by a judicious use of OpenMP critical regions and locks. The HPCVL DMSM Library implements this model in Fortran and C. It requires a minimum of user input to set up the framework for the model and to define the individual tasks. Optionally, it supports the dynamic distribution of task-related data and the collection of results at runtime. This library is freely available as source code. Here, we outline the working principles of the library and on a few examples demonstrate its capability to efficiently distribute a workload on a distributed-memory cluster with shared-memory nodes.
Predictive-model-based dynamic coordination control strategy for power-split hybrid electric bus
NASA Astrophysics Data System (ADS)
Zeng, Xiaohua; Yang, Nannan; Wang, Junnian; Song, Dafeng; Zhang, Nong; Shang, Mingli; Liu, Jianxin
2015-08-01
Parameter-matching methods and optimal control strategies of the top-selling hybrid electric vehicle (HEV), namely, power-split HEV, are widely studied. In particular, extant research on control strategy focuses on the steady-state energy management strategy to obtain better fuel economy. However, given that multi-power sources are highly coupled in power-split HEVs and influence one another during mode shifting, conducting research on dynamic coordination control strategy (DCCS) to achieve riding comfort is also important. This paper proposes a predictive-model-based DCCS. First, the dynamic model of the objective power-split HEV is built and the mode shifting process is analyzed based on the developed model to determine the reason for the system shock generated. Engine torque estimation algorithm is then designed according to the principle of the nonlinear observer, and the prediction model of the degree of shock is established based on the theory of model predictive control. Finally, the DCCS with adaptation for a complex driving cycle is realized by combining the feedback control and the predictive model. The presented DCCS is validated on the co-simulation platform of AMESim and Simulink. Results show that the shock during mode shifting is well controlled, thereby improving riding comfort.
A hybrid SEA/modal technique for modeling structural-acoustic interior noise in rotorcraft
NASA Astrophysics Data System (ADS)
Jayachandran, V.; Bonilha, M. W.
2003-03-01
This paper describes a hybrid technique that combines Statistical Energy Analysis (SEA) predictions for structural vibration with acoustic modal summation techniques to predict interior noise levels in rotorcraft. The method was applied for predicting the sound field inside a mock-up of the interior panel system of the Sikorsky S-92 helicopter. The vibration amplitudes of the frame and panel systems were predicted using a detailed SEA model and these were used as inputs to the model of the interior acoustic space. The spatial distribution of the vibration field on individual panels, and their coupling to the acoustic space were modeled using stochastic techniques. Leakage and nonresonant transmission components were accounted for using space-averaged values obtained from a SEA model of the complete structural-acoustic system. Since the cabin geometry was quite simple, the modeling of the interior acoustic space was performed using a standard modal summation technique. Sound pressure levels predicted by this approach at specific microphone locations were compared with measured data. Agreement within 3 dB in one-third octave bands above 40 Hz was observed. A large discrepancy in the one-third octave band in which the first acoustic mode is resonant (31.5 Hz) was observed. Reasons for such a discrepancy are discussed in the paper. The developed technique provides a method for modeling helicopter cabin interior noise in the frequency mid-range where neither FEA nor SEA is individually effective or accurate.
Hybrid modeling of spatial continuity for application to numerical inverse problems
Friedel, Michael J.; Iwashita, Fabio
2013-01-01
A novel two-step modeling approach is presented to obtain optimal starting values and geostatistical constraints for numerical inverse problems otherwise characterized by spatially-limited field data. First, a type of unsupervised neural network, called the self-organizing map (SOM), is trained to recognize nonlinear relations among environmental variables (covariates) occurring at various scales. The values of these variables are then estimated at random locations across the model domain by iterative minimization of SOM topographic error vectors. Cross-validation is used to ensure unbiasedness and compute prediction uncertainty for select subsets of the data. Second, analytical functions are fit to experimental variograms derived from original plus resampled SOM estimates producing model variograms. Sequential Gaussian simulation is used to evaluate spatial uncertainty associated with the analytical functions and probable range for constraining variables. The hybrid modeling of spatial continuity is demonstrated using spatially-limited hydrologic measurements at different scales in Brazil: (1) physical soil properties (sand, silt, clay, hydraulic conductivity) in the 42 km2 Vargem de Caldas basin; (2) well yield and electrical conductivity of groundwater in the 132 km2 fractured crystalline aquifer; and (3) specific capacity, hydraulic head, and major ions in a 100,000 km2 transboundary fractured-basalt aquifer. These results illustrate the benefits of exploiting nonlinear relations among sparse and disparate data sets for modeling spatial continuity, but the actual application of these spatial data to improve numerical inverse modeling requires testing.
Hybrid-PIC Modeling of a High-Voltage, High-Specific-Impulse Hall Thruster
NASA Technical Reports Server (NTRS)
Smith, Brandon D.; Boyd, Iain D.; Kamhawi, Hani; Huang, Wensheng
2013-01-01
The primary life-limiting mechanism of Hall thrusters is the sputter erosion of the discharge channel walls by high-energy propellant ions. Because of the difficulty involved in characterizing this erosion experimentally, many past efforts have focused on numerical modeling to predict erosion rates and thruster lifespan, but those analyses were limited to Hall thrusters operating in the 200-400V discharge voltage range. Thrusters operating at higher discharge voltages (V(sub d) >= 500 V) present an erosion environment that may differ greatly from that of the lower-voltage thrusters modeled in the past. In this work, HPHall, a well-established hybrid-PIC code, is used to simulate NASA's High-Voltage Hall Accelerator (HiVHAc) at discharge voltages of 300, 400, and 500V as a first step towards modeling the discharge channel erosion. It is found that the model accurately predicts the thruster performance at all operating conditions to within 6%. The model predicts a normalized plasma potential profile that is consistent between all three operating points, with the acceleration zone appearing in the same approximate location. The expected trend of increasing electron temperature with increasing discharge voltage is observed. An analysis of the discharge current oscillations shows that the model predicts oscillations that are much greater in amplitude than those measured experimentally at all operating points, suggesting that the differences in oscillation amplitude are not strongly associated with discharge voltage.
NASA Astrophysics Data System (ADS)
Yung, K. L.; He, Lan; Xu, Yan; Shen, Y. W.
2005-12-01
This Note proposes a new hybrid model that combines the Gay-Berne/Lennard-Jones (GB/LJ) and bead-spring models to simulate semiflexible main-chain liquid-crystalline polymers (LCPs) for improving simulation efficiency without compromising accuracy. In the new model, one bead and two nonlinear springs are used to describe the flexible spacers between two adjacent rigid units described by ellipsoidal particles. The model is found to be able to describe, with accuracy, detailed structural properties of semiflexible main-chain LCPs, such as the odd-even effects of their thermodynamic properties, where the bead-spring model cannot depict. In our experiments, the speed of simulation for the hybrid model was shown to be up to ten times faster than that for the GB/LJ model when the number of molecular chains exceeded 150.
Wave dispersion in the hybrid-Vlasov model: Verification of Vlasiator
Kempf, Yann; Pokhotelov, Dimitry; Koskinen, Hannu E. J.; Alfthan, Sebastian von; Palmroth, Minna; Vaivads, Andris
2013-11-15
Vlasiator is a new hybrid-Vlasov plasma simulation code aimed at simulating the entire magnetosphere of the Earth. The code treats ions (protons) kinetically through Vlasov's equation in the six-dimensional phase space while electrons are a massless charge-neutralizing fluid [M. Palmroth et al., J. Atmos. Sol.-Terr. Phys. 99, 41 (2013); A. Sandroos et al., Parallel Comput. 39, 306 (2013)]. For first global simulations of the magnetosphere, it is critical to verify and validate the model by established methods. Here, as part of the verification of Vlasiator, we characterize the low-β plasma wave modes described by this model and compare with the solution computed by the Waves in Homogeneous, Anisotropic Multicomponent Plasmas (WHAMP) code [K. Rönnmark, Kiruna Geophysical Institute Reports No. 179, 1982], using dispersion curves and surfaces produced with both programs. The match between the two fundamentally different approaches is excellent in the low-frequency, long wavelength range which is of interest in global magnetospheric simulations. The left-hand and right-hand polarized wave modes as well as the Bernstein modes in the Vlasiator simulations agree well with the WHAMP solutions. Vlasiator allows a direct investigation of the importance of the Hall term by including it in or excluding it from Ohm's law in simulations. This is illustrated showing examples of waves obtained using the ideal Ohm's law and Ohm's law including the Hall term. Our analysis emphasizes the role of the Hall term in Ohm's law in obtaining wave modes departing from ideal magnetohydrodynamics in the hybrid-Vlasov model.
NASA Technical Reports Server (NTRS)
Smith, Andrew M.; LaVerde, Bruce; Teague, David W.
2010-01-01
In the lower frequency range, where particular boundary conditions can make a significant difference to panel response characteristics Statistical Energy Analysis (SEA) has never been the analytical tool of choice. In addition to boundary condition effects, SEA is not well suited in frequency bands where no modes or less than a few modes exist. The advent of the Hybrid Module has enabled integration of Finite Element Analysis to expand and enhance the capability for response calculations within VA One into the lower frequency range. Exploration of several additional modeling approaches was completed for the cylindrical orthogrid panel test article that was examined in Reference 1. Comparison of the new analytical response predictions with the measured response data from ground test and the pure SEA results from the reference will be presented. One approach that is considered promising is the periodic subsystem capability. Initially, a detailed FEM of just one region of the test article is defined. After evaluating this small region using symmetric boundary conditions, the FEM may be expanded to determine the properties of the entire system using similar connected regions that map over the entire test article. Another approach is the direct use of a very detailed finite element model of the entire panel, explicitly modeling pocket and rib details of the structure. A third approach is to approximate localized structure geometry details with a smeared property generalization using a PCOMP (NASTRAN card used to define layered composite structures) to define skin layer and ribbed layer for the orthogrid panel. The authors expect to demonstrate that the integrated Hybrid/FEM approach increases confidence in response prediction in the lower frequency range (for example from 20-300 Hz for the test article under consideration). In addition the strength and weakness of each additional approach will be highlighted and compared to those reported with those reported in an
Bellazzi, R; Guglielmann, R; Ironi, L; Patrini, C
2001-08-01
Models of the dynamics of complex metabolic systems offer potential benefits to the deep comprehension of the system under study as well as for the performance of certain tasks. Unfortunately, dynamic modeling of a great deal of metabolic systems may be problematic due to the incompleteness of the available knowledge about the underlying mechanisms and to the lack of an adequate observational data set. In theory, a valid alternative to classical structural modeling through ordinary differential equations could be represented by input-output approaches. But, in practice, such methods, which learn the nonlinear dynamics of the system from input-output data, fail when the experimental data set is poor either in size or in quality. Such a situation is not rare in the case of metabolic systems. This paper deals with a hybrid approach which aims at overcoming the problems addressed above. More specifically, it allows us to solve the identification problems of the intracellular thiamine kinetics in the intestine tissue. The method, which is half way between the structural and input-output approach, uses the outcomes of the simulation of a qualitative structural model to build a good initialization of a fuzzy system identifier. Such an initialization allows us to efficiently cope with both the incompleteness of knowledge and the inadequacy of the available data set, and to derive an input-output model of the intracellular thiamine kinetics in the intestine tissue. The comparison of the predictions of the intracellular thiamine kinetics obtained by the application of such a model with those obtained by traditional approaches, namely compartmental models, neural networks, and fuzzy systems, highlighted a better performance of our model. As the structural assumptions are relaxed, we obtained a model slightly less informative than a purely structural one but robust enough to be used as a simulator. The paper also discusses the interpretative potential offered by such a model
Incorporating a Turbulence Transport Model into 2-D Hybrid Hall Thruster Simulations
NASA Astrophysics Data System (ADS)
Cha, Eunsun; Cappelli, Mark A.; Fernandez, Eduardo
2014-10-01
2-D hybrid simulations of Hall plasma thrusters that do not resolve cross-field transport-generating fluctuations require a model to capture how electrons migrate across the magnetic field. We describe the results of integrating a turbulent electron transport model into simulations of plasma behavior in a plane spanned by the E and B field vectors. The simulations treat the electrons as a fluid and the heavy species (ions/neutrals) as discrete particles. The transport model assumes that the turbulent eddy cascade in the electron fluid to smaller scales is the primary means of electron energy dissipation. Using this model, we compare simulations to experimental measurements made on a laboratory Hall discharge over a range of discharge voltage. Both the current-voltage trends as well as the plasma properties such as plasma temperature, electron density, and ion velocities seem agree favorably with experiments, where a simple Bohm transport model tends to perform poorly in capturing much of the discharge behavior.
Design and implementation of a hybrid MPI-CUDA model for the Smith-Waterman algorithm.
Khaled, Heba; Faheem, Hossam El Deen Mostafa; El Gohary, Rania
2015-01-01
This paper provides a novel hybrid model for solving the multiple pair-wise sequence alignment problem combining message passing interface and CUDA, the parallel computing platform and programming model invented by NVIDIA. The proposed model targets homogeneous cluster nodes equipped with similar Graphical Processing Unit (GPU) cards. The model consists of the Master Node Dispatcher (MND) and the Worker GPU Nodes (WGN). The MND distributes the workload among the cluster working nodes and then aggregates the results. The WGN performs the multiple pair-wise sequence alignments using the Smith-Waterman algorithm. We also propose a modified implementation to the Smith-Waterman algorithm based on computing the alignment matrices row-wise. The experimental results demonstrate a considerable reduction in the running time by increasing the number of the working GPU nodes. The proposed model achieved a performance of about 12 Giga cell updates per second when we tested against the SWISS-PROT protein knowledge base running on four nodes. PMID:26510289
Hybrid Modeling of Plasmas and Applications to Fusion and Space Physics.
NASA Astrophysics Data System (ADS)
Kazeminejad, Farzad
Since the early days of controlled fusion research, plasma physicists have encountered great challenges in obtaining solutions to the highly nonlinear equations which govern the behavior of fusion plasmas; with the growth of other applications of plasma physics (space plasmas, plasma accelerators, ... etc.) these problems have grown in importance. Obtaining reasonable solutions to the nonlinear equations is crucial to our understanding of the behavior of plasmas. With the advent of high speed computers, computer modeling of plasmas has moved into the front row of the tools used in research of their nonlinear plasma dynamics. There are roughly speaking two types of plasma models, particle models and fluid models. Particle models try to emulate nature by following the motion of a large number of charged particles in their self consistent electromagnetic fields. Fluid models on the other hand use macroscopic fluid equations to model the plasma. MHD models are typical of this type. Particle models in general require larger memory for the computer due to the massive amounts of data associated with the particles' kinematical variables. Particle models are generally limited to studying small regions of plasma for relatively short time intervals. Fluid models are better fit to handle large scales and long times; i.e., quite often the complete plasma involved in an experiment. The drawback of the fluid models however is that, they miss the physical phenomenon taking place at the microscale and these phenomenon can influence the properties of fluid; i.e., its resistivity, viscosity, heat transport, etc. One can attempt to put these effects in as phenomenological coefficients, but such approaches are always somewhat ad hoc. Another approach is to start with fluid models and incorporate more physics. Such models are referred to as hybrid models. In this thesis, two such models are discussed. They are then applied to two problems; the first is a simulation of the artificial
NASA Astrophysics Data System (ADS)
Wen, De-Qi; Liu, Wei; Liu, Yong-Xin; Gao, Fei; Wang, You-Nian
2015-09-01
Traditional fluid simulation and Particle-in-Cell/Monte-Carlo collision (PIC/MCC) are very time consuming in inductively coupled plasma. In this work, a hybrid model, i.e. global model coupled bidirectional with parallel Monte-Carlo collision (MCC) sheath model, is developed to investigate inductively coupled plasma discharge with bias source. The global model is applied to calculate plasma density in bulk plasma. The sheath model is performed to consistently calculate the electric field, ion kinetic and the sheath thickness above the bias electrode. Moreover, specific numbers of ions are tracked and ultimately ion energy distribution functions (IEDFs) incident into bias electrode are obtained from MCC module. It is found that as the bias amplitude increases, the energy width of both IEDFs becomes wider, and the total outlines of IEDFs move towards higher energy. The results from the model are validated by experimental measurement and a qualitative agreement is obtained. The advantage of this model is that plasma density, ion flux and IEDF, which are widely concerned in the actual process, could be obtained within an hour. This work was supported by the National Natural Science Foundation of China (NSFC) (Grant No. 11205025 and 11335004) and (Grant No.11405018), the Important National Science and Technology Specific Project (Grant No. 2011ZX02403-001).
Effect of data quality on a hybrid Coulomb/STEP model for earthquake forecasting
NASA Astrophysics Data System (ADS)
Steacy, Sandy; Jimenez, Abigail; Gerstenberger, Matt; Christophersen, Annemarie
2014-05-01
Operational earthquake forecasting is rapidly becoming a 'hot topic' as civil protection authorities seek quantitative information on likely near future earthquake distributions during seismic crises. At present, most of the models in public domain are statistical and use information about past and present seismicity as well as b-value and Omori's law to forecast future rates. A limited number of researchers, however, are developing hybrid models which add spatial constraints from Coulomb stress modeling to existing statistical approaches. Steacy et al. (2013), for instance, recently tested a model that combines Coulomb stress patterns with the STEP (short-term earthquake probability) approach against seismicity observed during the 2010-2012 Canterbury earthquake sequence. They found that the new model performed at least as well as, and often better than, STEP when tested against retrospective data but that STEP was generally better in pseudo-prospective tests that involved data actually available within the first 10 days of each event of interest. They suggested that the major reason for this discrepancy was uncertainty in the slip models and, in particular, in the geometries of the faults involved in each complex major event. Here we test this hypothesis by developing a number of retrospective forecasts for the Landers earthquake using hypothetical slip distributions developed by Steacy et al. (2004) to investigate the sensitivity of Coulomb stress models to fault geometry and earthquake slip. Specifically, we consider slip models based on the NEIC location, the CMT solution, surface rupture, and published inversions and find significant variation in the relative performance of the models depending upon the input data.
Spatiotemporal groundwater level modeling using hybrid artificial intelligence-meshless method
NASA Astrophysics Data System (ADS)
Nourani, Vahid; Mousavi, Shahram
2016-05-01
Uncertainties of the field parameters, noise of the observed data and unknown boundary conditions are the main factors involved in the groundwater level (GL) time series which limit the modeling and simulation of GL. This paper presents a hybrid artificial intelligence-meshless model for spatiotemporal GL modeling. In this way firstly time series of GL observed in different piezometers were de-noised using threshold-based wavelet method and the impact of de-noised and noisy data was compared in temporal GL modeling by artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS). In the second step, both ANN and ANFIS models were calibrated and verified using GL data of each piezometer, rainfall and runoff considering various input scenarios to predict the GL at one month ahead. In the final step, the simulated GLs in the second step of modeling were considered as interior conditions for the multiquadric radial basis function (RBF) based solve of governing partial differential equation of groundwater flow to estimate GL at any desired point within the plain where there is not any observation. In order to evaluate and compare the GL pattern at different time scales, the cross-wavelet coherence was also applied to GL time series of piezometers. The results showed that the threshold-based wavelet de-noising approach can enhance the performance of the modeling up to 13.4%. Also it was found that the accuracy of ANFIS-RBF model is more reliable than ANN-RBF model in both calibration and validation steps.
Higher Order, Hybrid BEM/FEM Methods Applied to Antenna Modeling
NASA Technical Reports Server (NTRS)
Fink, P. W.; Wilton, D. R.; Dobbins, J. A.
2002-01-01
In this presentation, the authors address topics relevant to higher order modeling using hybrid BEM/FEM formulations. The first of these is the limitation on convergence rates imposed by geometric modeling errors in the analysis of scattering by a dielectric sphere. The second topic is the application of an Incomplete LU Threshold (ILUT) preconditioner to solve the linear system resulting from the BEM/FEM formulation. The final tOpic is the application of the higher order BEM/FEM formulation to antenna modeling problems. The authors have previously presented work on the benefits of higher order modeling. To achieve these benefits, special attention is required in the integration of singular and near-singular terms arising in the surface integral equation. Several methods for handling these terms have been presented. It is also well known that achieving he high rates of convergence afforded by higher order bases may als'o require the employment of higher order geometry models. A number of publications have described the use of quadratic elements to model curved surfaces. The authors have shown in an EFIE formulation, applied to scattering by a PEC .sphere, that quadratic order elements may be insufficient to prevent the domination of modeling errors. In fact, on a PEC sphere with radius r = 0.58 Lambda(sub 0), a quartic order geometry representation was required to obtain a convergence benefi.t from quadratic bases when compared to the convergence rate achieved with linear bases. Initial trials indicate that, for a dielectric sphere of the same radius, - requirements on the geometry model are not as severe as for the PEC sphere. The authors will present convergence results for higher order bases as a function of the geometry model order in the hybrid BEM/FEM formulation applied to dielectric spheres. It is well known that the system matrix resulting from the hybrid BEM/FEM formulation is ill -conditioned. For many real applications, a good preconditioner is required
Preynas, M.; Ekedahl, A.; Fedorczak, N.; Goniche, M.; Guilhem, D.; Gunn, J. P.; Hillairet, J.; Litaudon, X.
2011-12-23
A new concept of lower hybrid antenna for current drive has been proposed for ITER [Bibet et al, Nuclear Fusion 1995]: the Passive Active Multijunction (PAM) antenna that relies on a periodic combination of active and passive waveguides. An actively cooled PAM antenna at 3.7 GHz has been recently installed on the tokamak Tore Supra. The paper summarizes the comprehensive experimental characterization of the linear coupling properties of the PAM antenna to the Tore Supra plasmas. These experimental results are systematically compared with the linear wave coupling theory via the linear ALOHA code. Good agreement between experimental results and ALOHA have been obtained. The detailed validation of the coupling modelling is an important step toward the validation of the PAM concept in view of further optimizing the electromagnetic properties of the future ITER antenna.
Zhao, Weizhao; Li, Xiping; Chen, Hairong; Manns, Fabrice
2012-01-01
Medical Imaging is a key training component in Biomedical Engineering programs. Medical imaging education is interdisciplinary training, involving physics, mathematics, chemistry, electrical engineering, computer engineering, and applications in biology and medicine. Seeking an efficient teaching method for instructors and an effective learning environment for students has long been a goal for medical imaging education. By the support of NSF grants, we developed the medical imaging teaching software (MITS) and associated dynamic assessment tracking system (DATS). The MITS/DATS system has been applied to junior and senior medical imaging classes through a hybrid teaching model. The results show that student's learning gain improved, particularly in concept understanding and simulation project completion. The results also indicate disparities in subjective perception between junior and senior classes. Three institutions are collaborating to expand the courseware system and plan to apply it to different class settings. PMID:23367069
Applications integration in a hybrid cloud computing environment: modelling and platform
NASA Astrophysics Data System (ADS)
Li, Qing; Wang, Ze-yuan; Li, Wei-hua; Li, Jun; Wang, Cheng; Du, Rui-yang
2013-08-01
With the development of application services providers and cloud computing, more and more small- and medium-sized business enterprises use software services and even infrastructure services provided by professional information service companies to replace all or part of their information systems (ISs). These information service companies provide applications, such as data storage, computing processes, document sharing and even management information system services as public resources to support the business process management of their customers. However, no cloud computing service vendor can satisfy the full functional IS requirements of an enterprise. As a result, enterprises often have to simultaneously use systems distributed in different clouds and their intra enterprise ISs. Thus, this article presents a framework to integrate applications deployed in public clouds and intra ISs. A run-time platform is developed and a cross-computing environment process modelling technique is also developed to improve the feasibility of ISs under hybrid cloud computing environments.
NASA Astrophysics Data System (ADS)
Preynas, M.; Ekedahl, A.; Fedorczak, N.; Goniche, M.; Guilhem, D.; Gunn, J. P.; Hillairet, J.; Litaudon, X.
2011-12-01
A new concept of lower hybrid antenna for current drive has been proposed for ITER [Bibet et al, Nuclear Fusion 1995]: the Passive Active Multijunction (PAM) antenna that relies on a periodic combination of active and passive waveguides. An actively cooled PAM antenna at 3.7 GHz has been recently installed on the tokamak Tore Supra. The paper summarizes the comprehensive experimental characterization of the linear coupling properties of the PAM antenna to the Tore Supra plasmas. These experimental results are systematically compared with the linear wave coupling theory via the linear ALOHA code. Good agreement between experimental results and ALOHA have been obtained. The detailed validation of the coupling modelling is an important step toward the validation of the PAM concept in view of further optimizing the electromagnetic properties of the future ITER antenna.
A Hybrid Model for Individual Identification Based on Keystroke Data in Japanese Free Text Typing
NASA Astrophysics Data System (ADS)
Samura, Toshiharu; Nishimura, Haruhiko
We have investigated several characteristics of keystroke dynamics in Japanese free text typing. We performed experiments on 189 subjects, representing three groups according to the number of letters they could type in five minutes. In this experiment, we extracted the feature indices from the keystroke timing for each alphabet single letter and for two-letter combinations composed of consonant and vowel pairs in Japanese text. Taking into account two identification methods using weighted Euclidean distance (WED) and Vector Disorder (VD), we proposed their hybrid model for individual identification based on keystroke data in Japanese free text typing. By evaluating the personal identification for the three groups, its high performance was confirmed in proportion to the typing level of the group.
Hybrid-Space Density Matrix Renormalization Group Study of the Two-Dimensional Hubbard Model
NASA Astrophysics Data System (ADS)
Ehlers, Georg; Noack, Reinhard M.
We investigate the ground state of the two-dimensional Hubbard model on a cylinder geometry at intermediate coupling and weak doping. We study properties such as the behavior of the ground-state energy, pair-field correlations, and the appearance of stripes. We find striped ground states generically, with the width of the stripes depending on the filling, the boundary conditions, and the circumference of the cylinder. Furthermore, we analyse the interplay between the different stripe configurations and the decay of the pairing correlations. Our analysis is based on a hybrid-space density matrix renormalization group (DMRG) approach, which uses a momentum-space representation in the transverse and a real-space representation in the longitudinal direction. Exploiting the transverse momentum quantum number makes significant speedup and memory savings compared to the real-space DMRG possible. In particular, we obtain computational costs that are independent of the cylinder width for fixed size of the truncated Hilbert space.
Wang, Yi; Cheng, Jie-Zhi; Ni, Dong; Lin, Muqing; Qin, Jing; Luo, Xiongbiao; Xu, Ming; Xie, Xiaoyan; Heng, Pheng Ann
2016-02-01
Registration and fusion of magnetic resonance (MR) and 3D transrectal ultrasound (TRUS) images of the prostate gland can provide high-quality guidance for prostate interventions. However, accurate MR-TRUS registration remains a challenging task, due to the great intensity variation between two modalities, the lack of intrinsic fiducials within the prostate, the large gland deformation caused by the TRUS probe insertion, and distinctive biomechanical properties in patients and prostate zones. To address these challenges, a personalized model-to-surface registration approach is proposed in this study. The main contributions of this paper can be threefold. First, a new personalized statistical deformable model (PSDM) is proposed with the finite element analysis and the patient-specific tissue parameters measured from the ultrasound elastography. Second, a hybrid point matching method is developed by introducing the modality independent neighborhood descriptor (MIND) to weight the Euclidean distance between points to establish reliable surface point correspondence. Third, the hybrid point matching is further guided by the PSDM for more physically plausible deformation estimation. Eighteen sets of patient data are included to test the efficacy of the proposed method. The experimental results demonstrate that our approach provides more accurate and robust MR-TRUS registration than state-of-the-art methods do. The averaged target registration error is 1.44 mm, which meets the clinical requirement of 1.9 mm for the accurate tumor volume detection. It can be concluded that the presented method can effectively fuse the heterogeneous image information in the elastography, MR, and TRUS to attain satisfactory image alignment performance. PMID:26441446
Monitoring global land surface drought based on a hybrid evapotranspiration model
NASA Astrophysics Data System (ADS)
Yao, Yunjun; Liang, Shunlin; Qin, Qiming; Wang, Kaicun; Zhao, Shaohua
2011-06-01
The latent heat of evapotranspiration (ET) plays an important role in the assessment of drought severity as one sensitive indicator of land drought status. A simple and accurate method of estimating global ET for the monitoring of global land surface droughts from remote sensing data is essential. The objective of this research is to develop a hybrid ET model by introducing empirical coefficients based on a simple linear two-source land ET model, and to then use this model to calculate the Evaporative Drought Index (EDI) based on the actual estimated ET and the potential ET in order to characterize global surface drought conditions. This is done using the Global Energy and Water Cycle Experiment (GEWEX) Surface Radiation Budget (SRB) products, AVHRR-NDVI products from the Global Inventory Modeling and Mapping Studies (GIMMS) group, and National Centers for Environmental Prediction Reanalysis-2 (NCEP-2) datasets. We randomly divided 22 flux towers into two groups and performed a series of cross-validations using ground measurements collected from the corresponding flux towers. The validation results from the second group of flux towers using the data from the first group for calibration show that the daily bias varies from -6.72 W/m 2 to 12.95 W/m 2 and the average monthly bias is -1.73 W/m 2. Similarly, the validation results of the first group of flux towers using data from second group for calibration show that the daily bias varies from -12.91 W/m 2 to 10.26 W/m 2 and the average monthly bias is -3.59 W/m 2. To evaluate the reliability of the hybrid ET model on a global scale, we compared the estimated ET from the GEWEX, AVHRR-GIMMS-NDVI, and NECP-2 datasets with the latent heat flux from the Global Soil Wetness Project-2 (GSWP-2) datasets. We found both of them to be in good agreement, which further supports the validity of our model's global ET estimation. Significantly, the patterns of monthly EDI anomalies have a good spatial and temporal correlation with
Saturn's magnetosphere interaction with Titan for T5 encounter: 3D hybrid modeling. First results
NASA Astrophysics Data System (ADS)
Simpson, D. G.; Lipatov, A. S.; Sittler, E. C.; Hartle, R. E.; Cooper, J. F.
2011-12-01
Wave-particle interactions play a very important role in the plasma dynamics near Titan: mass loading, excitation of low-frequency waves and formation of the particle velocity distribution function (e.g. ring/shell-like distributions, etc.) The kinetic approach is important for estimating collision processes; e.g., charge exchange. In this report we discuss results of 3D hybrid modeling of the interaction between Saturn's magnetosphere and Titan's atmosphere/ionosphere. The modeling is based on recent analysis of the Cassini Plasma Spectrometer (CAPS) and the Cassini Ion, and Neutral Mass Spectrometer (INMS) measurements during the T5 flyby through Titan's ram-side and polar ionosphere [1,2]. Magnetic field data was used from the MAG instrument [3]. In our model the background ions (O+, H+), all pickup ions, and ionospheric ions are considered as a particles, whereas the electrons are described as a fluid. Inhomogeneous photoionization (in the dayside ionosphere), electron-impact ionization, and charge exchange are included in our model. The temperature of the background electrons and pickup electrons was also incorporated into the generalized Ohm's law. We also take into account collisions between ions and neutrals. In our hybrid simulations we use Chamberlain profiles for the exosphere's components. The moon is considered as a weakly conducting body. Special attention will be paid to comparing the modeling results with a single-fluid multi-species 3D MHD model [4], which included complex chemistry but does not produce finite gyroradius and kinetic effects. References [1] Sittler, E.C., et al., Energy Deposition Processes in Titan's Atmosphere and Its Induced Magnetosphere. In: Titan from Cassini-Huygens, Brown, R.H., Lebreton, J.P., Waite, J.H., Eds., Springer, (Dordrecht, Heidelberg, London, New York), pp. 393-455. [2] Agren, K., et al., On magnetosphere electron impact ionization and dynamics in Titan's ram-side and polar ionosphere -- a Cassini case study, Ann
Zou, Weizhong; Larson, Ronald G
2016-08-10
We present a hybrid model for polymeric glasses under deformation that combines a minimal model of segmental dynamics with a beads-and-springs model of a polymer, solved by Brownian dynamics (BD) simulations, whose relaxation is coupled to the segmental dynamics through the drag coefficient of the beads. This coarse-grained model allows simulations that are much faster than molecular dynamics and successfully capture the entire range of mechanical response including yielding, plastic flow, strain-hardening, and incomplete strain recovery. The beads-and-springs model improves upon the dumbbell model for glassy polymers proposed by Fielding et al. (Phys. Rev. Lett., 2012, 108, 048301) by capturing the small elastic recoil seen experimentally without the use of ad hoc adjustments of parameters required in the model of Fielding et al. With appropriate choice of parameters, predictions of creep, recovery, and segmental relaxation are found to be in good agreement with poly(methylmethacrylate) (PMMA) data of Lee et al. (Science, 2009, 323, 231-234). Our model shows dramatic differences in behavior of the segmental relaxation time between extensional creep and steady extension, and between extension and shear. The non-monotonic response of the segmental relaxation time to extensional creep and the small elastic recovery after removal of stress are shown to arise from sub-chains that are trapped between folds, and that become highly oriented and stretched at strains of order unity, connecting the behavior of glassy polymers under creep to that of dilute polymer solutions under fast extensional flows. We are also able to predict the effects of polymer pre-orientation in the parallel or orthogonal direction on the subsequent response to extensional deformation. PMID:27453365
Dynamic modeling of hybrid renewable energy systems for off-grid applications
NASA Astrophysics Data System (ADS)
Hasemeyer, Mark David
The volatile prices of fossil fuels and their contribution to global warming have caused many people to turn to renewable energy systems. Many developing communities are forced to use these systems as they are too far from electrical distribution. As a result, numerous software models have been developed to simulate hybrid renewable energy systems. However almost, if not all, implementations are static in design. A static design limits the ability of the model to account for changes over time. Dynamic modeling can be used to fill the gaps where other modeling techniques fall short. This modeling practice allows the user to account for the effects of technological and economic factors over time. These factors can include changes in energy demand, energy production, and income level. Dynamic modeling can be particularly useful for developing communities who are off-grid and developing at rapid rates. In this study, a dynamic model was used to evaluate a real world system. A non-governmental organization interested in improving their current infrastructure was selected. Five different scenarios were analyzed and compared