Izhikevich, Eugene M
2010-11-13
I review a class of hybrid models of neurons that combine continuous spike-generation mechanisms and a discontinuous 'after-spike' reset of state variables. Unlike Hodgkin-Huxley-type conductance-based models, the hybrid spiking models have a few parameters derived from the bifurcation theory; instead of matching neuronal electrophysiology, they match neuronal dynamics. I present a method of after-spike resetting suitable for hardware implementation of such models, and a hybrid numerical method for simulations of large-scale biological spiking networks.
Energy Technology Data Exchange (ETDEWEB)
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.
Model Reduction of Hybrid Systems
DEFF Research Database (Denmark)
Shaker, Hamid Reza
matrices are constructed based on the convex combinations of the generalized gramians. However this framework is less conservative than the first one, it does not guarantee the stability for all switching signals. The stability preservation is studied for this reduction technique. The third framework......High-Technological solutions of today are characterized by complex dynamical models. A lot of these models have inherent hybrid/switching structure. Hybrid/switched systems are powerful models for distributed embedded systems design where discrete controls are applied to continuous processes...... of hybrid systems, designing controllers and implementations is very high so that the use of these models is limited in applications where the size of the state space is large. To cope with complexity, model reduction is a powerful technique. This thesis presents methods for model reduction and stability...
Compositional Modelling of Stochastic Hybrid Systems
Strubbe, S.N.
2005-01-01
In this thesis we present a modelling framework for compositional modelling of stochastic hybrid systems. Hybrid systems consist of a combination of continuous and discrete dynamics. The state space of a hybrid system is hybrid in the sense that it consists of a continuous component and a discrete
Hybrid Model of Content Extraction
DEFF Research Database (Denmark)
Qureshi, Pir Abdul Rasool; Memon, Nasrullah
2012-01-01
We present a hybrid model for content extraction from HTML documents. The model operates on Document Object Model (DOM) tree of the corresponding HTML document. It evaluates each tree node and associated statistical features like link density and text distribution across the node to predict...... model outperformed other existing content extraction models. We present a browser based implementation of the proposed model as proof of concept and compare the implementation strategy with various state of art implementations. We also discuss various applications of the proposed model with special...
Hybrid2 - The hybrid power system simulation model
Energy Technology Data Exchange (ETDEWEB)
Baring-Gould, E.I.; Green, H.J.; Dijk, V.A.P. van [National Renewable Energy Lab., Golden, CO (United States); Manwell, J.F. [Univ. of Massachusetts, Amherst, MA (United States)
1996-12-31
There is a large-scale need and desire for energy in remote communities, especially in the developing world; however the lack of a user friendly, flexible performance prediction model for hybrid power systems incorporating renewables hindered the analysis of hybrids as options to conventional solutions. A user friendly model was needed with the versatility to simulate the many system locations, widely varying hardware configurations, and differing control options for potential hybrid power systems. To meet these ends, researchers from the National Renewable Energy Laboratory (NREL) and the University of Massachusetts (UMass) developed the Hybrid2 software. This paper provides an overview of the capabilities, features, and functionality of the Hybrid2 code, discusses its validation and future plans. Model availability and technical support provided to Hybrid2 users are also discussed. 12 refs., 3 figs., 4 tabs.
Energy based hybrid turbulence modeling
Haering, Sigfried; Moser, Robert
2015-11-01
Traditional hybrid approaches exhibit deficiencies when used for fluctuating smooth-wall separation and reattachment necessitating ad-hoc delaying functions and model tuning making them no longer useful as a predictive tool. Additionally, complex geometries and flows often require high cell aspect-ratios and large grid gradients as a compromise between resolution and cost. Such transitions and inconsistencies in resolution detrimentally effect the fidelity of the simulation. We present the continued development of a new hybrid RANS/LES modeling approach specifically developed to address these challenges. In general, modeled turbulence is returned to resolved scales by reduced or negative model viscosity until a balance between theoretical and actual modeled turbulent kinetic energy is attained provided the available resolution. Anisotropy in the grid and resolved field are directly integrated into this balance. A viscosity-based correction is proposed to account for resolution inhomogeneities. Both the hybrid framework and resolution gradient corrections are energy conserving through an exchange of resolved and modeled turbulence.
Interdisciplinarity as Hybrid Modeling
DEFF Research Database (Denmark)
Hvidtfeldt, Rolf
2017-01-01
interdisciplinarity is viewed in part as a process of integrating distinct scientific representational approaches. The analysis suggests that present methods for the evaluation of interdisciplinary projects places too much emphasis non-epistemic aspects of disciplinary integrations while more or less ignoring whether...... specific interdis- ciplinary collaborations puts us in a better, or worse, epistemic position. This leads to the conclusion that there are very good reasons for recommending a more cautious, systematic, and stringent approach to the development, evaluation, and execution of interdisciplinary science.......In this paper, I present a philosophical analysis of interdisciplinary scientific activities. I suggest that it is a fruitful approach to view interdisciplinarity in light of the recent literature on scientific representations. For this purpose I develop a meta-representational model in which...
Hybrid Models for Sequential Decision Making
National Research Council Canada - National Science Library
Sun, Ron
2000-01-01
To study hybrid architectures of complex learning, especially as applied to a simulated minefield navigation task, we developed a hybrid connectionist model CLARION as a demonstration of the approach...
Modelling freeway networks by hybrid stochastic models
Boel, R.; Mihaylova, L.
2004-01-01
Traffic flow on freeways is a nonlinear, many-particle phenomenon, with complex interactions between the vehicles. This paper presents a stochastic hybrid model of freeway traffic at a time scale and at a level of detail suitable for on-line flow estimation, for routing and ramp metering control. The model describes the evolution of continuous and discrete state variables. The freeway is considered as a network of components, each component representing a different section of the network. The...
Model-Based Prognostics of Hybrid Systems
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.
Boltzmann Transport in Hybrid PIC HET Modeling
2015-07-01
Paper 3. DATES COVERED (From - To) July 2015-July 2015 4. TITLE AND SUBTITLE Boltzmann transport in hybrid PIC HET modeling 5a. CONTRACT NUMBER In...reproduce experimentally observed mobility trends derived from HPHall, a workhorse hybrid- PIC HET simulation code. 15. SUBJECT TERMS 16. SECURITY...Std. 239.18 Boltzmann transport in hybrid PIC HET modeling IEPC-2015- /ISTS-2015-b- Presented at Joint Conference of 30th International
Travelling waves in hybrid chemotaxis models
Franz, Benjamin; Painter, Kevin J; Erban, Radek
2013-01-01
Hybrid models of chemotaxis combine agent-based models of cells with partial differential equation models of extracellular chemical signals. In this paper, travelling wave properties of hybrid models of bacterial chemotaxis are investigated. Bacteria are modelled using an agent-based (individual-based) approach with internal dynamics describing signal transduction. In addition to the chemotactic behaviour of the bacteria, the individual-based model also includes cell proliferation and death. Cells consume the extracellular nutrient field (chemoattractant) which is modelled using a partial differential equation. Mesoscopic and macroscopic equations representing the behaviour of the hybrid model are derived and the existence of travelling wave solutions for these models is established. It is shown that cell proliferation is necessary for the existence of non-transient (stationary) travelling waves in hybrid models. Additionally, a numerical comparison between the wave speeds of the continuum models and the hybr...
Statistical Model Checking for Stochastic Hybrid Systems
DEFF Research Database (Denmark)
David, Alexandre; Du, Dehui; Larsen, Kim Guldstrand
2012-01-01
This paper presents novel extensions and applications of the UPPAAL-SMC model checker. The extensions allow for statistical model checking of stochastic hybrid systems. We show how our race-based stochastic semantics extends to networks of hybrid systems, and indicate the integration technique...
Towards Modelling of Hybrid Systems
DEFF Research Database (Denmark)
Wisniewski, Rafal
2006-01-01
The article is an attempt to use methods of category theory and topology for analysis of hybrid systems. We use the notion of a directed topological space; it is a topological space together with a set of privileged paths. Dynamical systems are examples of directed topological spaces. A hybrid...... system consists of a number of dynamical systems that are glued together according to information encoded in the discrete part of the system. We develop a definition of a hybrid system as a functor from the category generated by a transition system to the category of directed topological spaces. Its...... directed homotopy colimit (geometric realization) is a single directed topological space. The behavior of hybrid systems can be then understood in terms of the behavior of dynamical systems through the directed homotopy colimit....
Modeling hybrid perovskites by molecular dynamics.
Mattoni, Alessandro; Filippetti, Alessio; Caddeo, Claudia
2017-02-01
The topical review describes the recent progress in the modeling of hybrid perovskites by molecular dynamics simulations. Hybrid perovskites and in particular methylammonium lead halide (MAPI) have a tremendous technological relevance representing the fastest-advancing solar material to date. They also represent the paradigm of an organic-inorganic crystalline material with some conceptual peculiarities: an inorganic semiconductor for what concerns the electronic and absorption properties with a hybrid and solution processable organic-inorganic body. After briefly explaining the basic concepts of ab initio and classical molecular dynamics, the model potential recently developed for hybrid perovskites is described together with its physical motivation as a simple ionic model able to reproduce the main dynamical properties of the material. Advantages and limits of the two strategies (either ab initio or classical) are discussed in comparison with the time and length scales (from pico to microsecond scale) necessary to comprehensively study the relevant properties of hybrid perovskites from molecular reorientations to electrocaloric effects. The state-of-the-art of the molecular dynamics modeling of hybrid perovskites is reviewed by focusing on a selection of showcase applications of methylammonium lead halide: molecular cations disorder; temperature evolution of vibrations; thermally activated defects diffusion; thermal transport. We finally discuss the perspectives in the modeling of hybrid perovskites by molecular dynamics.
Travelling Waves in Hybrid Chemotaxis Models
Franz, Benjamin
2013-12-18
Hybrid models of chemotaxis combine agent-based models of cells with partial differential equation models of extracellular chemical signals. In this paper, travelling wave properties of hybrid models of bacterial chemotaxis are investigated. Bacteria are modelled using an agent-based (individual-based) approach with internal dynamics describing signal transduction. In addition to the chemotactic behaviour of the bacteria, the individual-based model also includes cell proliferation and death. Cells consume the extracellular nutrient field (chemoattractant), which is modelled using a partial differential equation. Mesoscopic and macroscopic equations representing the behaviour of the hybrid model are derived and the existence of travelling wave solutions for these models is established. It is shown that cell proliferation is necessary for the existence of non-transient (stationary) travelling waves in hybrid models. Additionally, a numerical comparison between the wave speeds of the continuum models and the hybrid models shows good agreement in the case of weak chemotaxis and qualitative agreement for the strong chemotaxis case. In the case of slow cell adaptation, we detect oscillating behaviour of the wave, which cannot be explained by mean-field approximations. © 2013 Society for Mathematical Biology.
HYbrid Coordinate Ocean Model (HYCOM): Global
National Oceanic and Atmospheric Administration, Department of Commerce — Global HYbrid Coordinate Ocean Model (HYCOM) and U.S. Navy Coupled Ocean Data Assimilation (NCODA) 3-day, daily forecast at approximately 9-km (1/12-degree)...
A Hybrid 3D Indoor Space Model
Directory of Open Access Journals (Sweden)
A. Jamali
2016-10-01
Full Text Available GIS integrates spatial information and spatial analysis. An important example of such integration is for emergency response which requires route planning inside and outside of a building. Route planning requires detailed information related to indoor and outdoor environment. Indoor navigation network models including Geometric Network Model (GNM, Navigable Space Model, sub-division model and regular-grid model lack indoor data sources and abstraction methods. In this paper, a hybrid indoor space model is proposed. In the proposed method, 3D modeling of indoor navigation network is based on surveying control points and it is less dependent on the 3D geometrical building model. This research proposes a method of indoor space modeling for the buildings which do not have proper 2D/3D geometrical models or they lack semantic or topological information. The proposed hybrid model consists of topological, geometrical and semantical space.
Hybrid Models in Loop Quantum Cosmology
Navascués, B Elizaga; Marugán, G A Mena
2016-01-01
In the framework of Loop Quantum Cosmology, inhomogeneous models are usually quantized by means of a hybrid approach that combines loop quantization techniques with standard quantum field theory methods. This approach is based on a splitting of the phase space in a homogeneous sector, formed by global, zero-modes, and an inhomogeneous sector, formed by the remaining, infinite number of modes, that describe the local degrees of freedom. Then, the hybrid quantization is attained by adopting a loop representation for the homogeneous gravitational sector, while a Fock representation is used for the inhomogeneities. The zero-mode of the Hamiltonian constraint operator couples the homogeneous and inhomogeneous sectors. The hybrid approach, therefore, is expected to provide a suitable quantum theory in regimes where the main quantum effects of the geometry are those affecting the zero-modes, while the inhomogeneities, still being quantum, can be treated in a more conventional way. This hybrid strategy was first prop...
Hybrid modelling of anaerobic wastewater treatment processes.
Karama, A; Bernard, O; Genovesi, A; Dochain, D; Benhammou, A; Steyer, J P
2001-01-01
This paper presents a hybrid approach for the modelling of an anaerobic digestion process. The hybrid model combines a feed-forward network, describing the bacterial kinetics, and the a priori knowledge based on the mass balances of the process components. We have considered an architecture which incorporates the neural network as a static model of unmeasured process parameters (kinetic growth rate) and an integrator for the dynamic representation of the process using a set of dynamic differential equations. The paper contains a description of the neural network component training procedure. The performance of this approach is illustrated with experimental data.
Weather forecasting based on hybrid neural model
Saba, Tanzila; Rehman, Amjad; AlGhamdi, Jarallah S.
2017-02-01
Making deductions and expectations about climate has been a challenge all through mankind's history. Challenges with exact meteorological directions assist to foresee and handle problems well in time. Different strategies have been investigated using various machine learning techniques in reported forecasting systems. Current research investigates climate as a major challenge for machine information mining and deduction. Accordingly, this paper presents a hybrid neural model (MLP and RBF) to enhance the accuracy of weather forecasting. Proposed hybrid model ensure precise forecasting due to the specialty of climate anticipating frameworks. The study concentrates on the data representing Saudi Arabia weather forecasting. The main input features employed to train individual and hybrid neural networks that include average dew point, minimum temperature, maximum temperature, mean temperature, average relative moistness, precipitation, normal wind speed, high wind speed and average cloudiness. The output layer composed of two neurons to represent rainy and dry weathers. Moreover, trial and error approach is adopted to select an appropriate number of inputs to the hybrid neural network. Correlation coefficient, RMSE and scatter index are the standard yard sticks adopted for forecast accuracy measurement. On individual standing MLP forecasting results are better than RBF, however, the proposed simplified hybrid neural model comes out with better forecasting accuracy as compared to both individual networks. Additionally, results are better than reported in the state of art, using a simple neural structure that reduces training time and complexity.
Weather forecasting based on hybrid neural model
Saba, Tanzila; Rehman, Amjad; AlGhamdi, Jarallah S.
2017-11-01
Making deductions and expectations about climate has been a challenge all through mankind's history. Challenges with exact meteorological directions assist to foresee and handle problems well in time. Different strategies have been investigated using various machine learning techniques in reported forecasting systems. Current research investigates climate as a major challenge for machine information mining and deduction. Accordingly, this paper presents a hybrid neural model (MLP and RBF) to enhance the accuracy of weather forecasting. Proposed hybrid model ensure precise forecasting due to the specialty of climate anticipating frameworks. The study concentrates on the data representing Saudi Arabia weather forecasting. The main input features employed to train individual and hybrid neural networks that include average dew point, minimum temperature, maximum temperature, mean temperature, average relative moistness, precipitation, normal wind speed, high wind speed and average cloudiness. The output layer composed of two neurons to represent rainy and dry weathers. Moreover, trial and error approach is adopted to select an appropriate number of inputs to the hybrid neural network. Correlation coefficient, RMSE and scatter index are the standard yard sticks adopted for forecast accuracy measurement. On individual standing MLP forecasting results are better than RBF, however, the proposed simplified hybrid neural model comes out with better forecasting accuracy as compared to both individual networks. Additionally, results are better than reported in the state of art, using a simple neural structure that reduces training time and complexity.
QCD string model for hybrid adiabatic potentials
Kalashnikova, Yu. S.; Kuzmenko, D. S.
2001-01-01
Hybrid adiabatic potentials are considered in the framework of the QCD string model. The einbein field formalism is applied to obtain the large-distance behaviour of adiabatic potentials. The calculated excitation curves are shown to be the result of interplay between potential-type longitudinal and string-type transverse vibrations. The results are compared with recent lattice data.
Model FORC diagrams for hybrid magnetic elastomers
Energy Technology Data Exchange (ETDEWEB)
Vaganov, M.V., E-mail: mikhail.vaganov.sci@gmail.com.ru [Institute of Continuous Media Mechanics, Russian Academy of Sciences, Ural Branch, Perm, 614013 (Russian Federation); Linke, J.; Odenbach, S. [Technische Universität Dresden, Dresden, 01062 Germany (Germany); Raikher, Yu.L. [Institute of Continuous Media Mechanics, Russian Academy of Sciences, Ural Branch, Perm, 614013 (Russian Federation); Ural Federal University, Ekaterinburg, 620083 (Russian Federation)
2017-06-01
We propose a model of hybrid magnetic elastomers filled with a mixture of magnetically soft and magnetically hard microparticles. The magnetically hard particles are described by the Stoner–Wohlfarth model, the magnetically soft phase obeys the Fröhlich–Kennelly equation. The interaction between the two types of particles is described by the mean-field approach. First-order reversal curve (FORC) diagrams were calculated for different values of the elastomer matrix elasticity. We demonstrate that the diagrams display specific new features, which identify the presence of both a deformable matrix and the two types of magnetic particles. - Highlights: • A model of hybrid magnetic elastomers is proposed. • The magnetically hard particles are described by the Stoner–Wohlfarth model. • The magnetically soft phase obeys the Fröhlich–Kennelly equation. The interaction between the phases is described by the mean-field approach. • FORC diagrams are calculated for different values of the elastomer matrix elasticity.
Hybrid Energy System Modeling in Modelica
Energy Technology Data Exchange (ETDEWEB)
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.
Mathematical Modeling of Hybrid Electrical Engineering Systems
Directory of Open Access Journals (Sweden)
A. A. Lobaty
2016-01-01
Full Text Available A large class of systems that have found application in various industries and households, electrified transportation facilities and energy sector has been classified as electrical engineering systems. Their characteristic feature is a combination of continuous and discontinuous modes of operation, which is reflected in the appearance of a relatively new term “hybrid systems”. A wide class of hybrid systems is pulsed DC converters operating in a pulse width modulation, which are non-linear systems with variable structure. Using various methods for linearization it is possible to obtain linear mathematical models that rather accurately simulate behavior of such systems. However, the presence in the mathematical models of exponential nonlinearities creates considerable difficulties in the implementation of digital hardware. The solution can be found while using an approximation of exponential functions by polynomials of the first order, that, however, violates the rigor accordance of the analytical model with characteristics of a real object. There are two practical approaches to synthesize algorithms for control of hybrid systems. The first approach is based on the representation of the whole system by a discrete model which is described by difference equations that makes it possible to synthesize discrete algorithms. The second approach is based on description of the system by differential equations. The equations describe synthesis of continuous algorithms and their further implementation in a digital computer included in the control loop system. The paper considers modeling of a hybrid electrical engineering system using differential equations. Neglecting the pulse duration, it has been proposed to describe behavior of vector components in phase coordinates of the hybrid system by stochastic differential equations containing generally non-linear differentiable random functions. A stochastic vector-matrix equation describing dynamics of the
A hybrid computational model for phagocyte transmigration
Xue, Jiaxing; Gao, Jean; Tang, Liping
2008-01-01
Phagocyte transmigration is the initiation of a series of phagocyte responses that are believed important in the formation of fibrotic capsules surrounding implanted medical devices. Understanding the molecular mechanisms governing phagocyte transmigration is highly desired in order to improve the stability and functionality of the implanted devices. A hybrid computational model that combines control theory and kinetics Monte Carlo (KMC) algorithm is proposed to simulate and predict phagocyte...
Modelling Chemical Preservation of Plantain Hybrid Fruits
Directory of Open Access Journals (Sweden)
Ogueri Nwaiwu
2017-08-01
Full Text Available New plantain hybrids plants have been developed but not much has been done on the post-harvest keeping quality of the fruits and how they are affected by microbial colonization. Hence fruits from a tetraploid hybrid PITA 2 (TMPx 548-9 obtained by crossing plantain varieties Obino l’Ewai and Calcutta 4 (AA and two local triploid (AAB plantain landraces Agbagba and Obino l’Ewai were subjected to various concentrations of acetic, sorbic and propionic acid to determine the impact of chemical concentration, chemical type and plantain variety on ripening and weight loss of plantain fruits. Analysis of titratable acidity, moisture content and total soluble solids showed that there were no significant differences between fruits of hybrid and local varieties. The longest time to ripening from harvest (24 days was achieved with fruits of Agbagba treated with 3% propionic acid. However, fruits of PITA 2 hybrid treated with propionic and sorbic acid at 3% showed the longest green life which indicated that the chemicals may work better at higher concentrations. The Obino l’Ewai cultivar had the highest weight loss for all chemical types used. Modelling data obtained showed that plantain variety had the most significant effect on ripening and indicates that ripening of the fruits may depend on the plantain variety. It appears that weight loss of fruits from the plantain hybrid and local cultivars was not affected by the plantain variety, chemical type. The chemicals at higher concentrations may have an effect on ripening of the fruits and will need further investigation.
Hybrid approaches to physiologic modeling and prediction
Olengü, Nicholas O.; Reifman, Jaques
2005-05-01
This paper explores how the accuracy of a first-principles physiological model can be enhanced by integrating data-driven, "black-box" models with the original model to form a "hybrid" model system. Both linear (autoregressive) and nonlinear (neural network) data-driven techniques are separately combined with a first-principles model to predict human body core temperature. Rectal core temperature data from nine volunteers, subject to four 30/10-minute cycles of moderate exercise/rest regimen in both CONTROL and HUMID environmental conditions, are used to develop and test the approach. The results show significant improvements in prediction accuracy, with average improvements of up to 30% for prediction horizons of 20 minutes. The models developed from one subject's data are also used in the prediction of another subject's core temperature. Initial results for this approach for a 20-minute horizon show no significant improvement over the first-principles model by itself.
Comments On Clock Models In Hybrid Automata And Hybrid Control Systems
Oltean, Virginia Ecaterina; Carstoiu, Dorin
2001-01-01
Hybrid systems have received a lot of attention in the past decade and a number of different models have been proposed in order to establish mathematical framework that is able to handle both continuous and discrete aspects. This contribution is focused on two models: hybrid automata and hybrid control systems with continuous-discrete interface and the importance of clock models is emphasized. Simple and relevant examples, some taken from the literature, accompany the presentation.
Design of Xen Hybrid Multiple Police Model
Sun, Lei; Lin, Renhao; Zhu, Xianwei
2017-10-01
Virtualization Technology has attracted more and more attention. As a popular open-source virtualization tools, XEN is used more and more frequently. Xsm, XEN security model, has also been widespread concern. The safety status classification has not been established in the XSM, and it uses the virtual machine as a managed object to make Dom0 a unique administrative domain that does not meet the minimum privilege. According to these questions, we design a Hybrid multiple police model named SV_HMPMD that organically integrates multiple single security policy models include DTE,RBAC,BLP. It can fullfill the requirement of confidentiality and integrity for security model and use different particle size to different domain. In order to improve BLP’s practicability, the model introduce multi-level security labels. In order to divide the privilege in detail, we combine DTE with RBAC. In order to oversize privilege, we limit the privilege of domain0.
Infectious disease modeling a hybrid system approach
Liu, Xinzhi
2017-01-01
This volume presents infectious diseases modeled mathematically, taking seasonality and changes in population behavior into account, using a switched and hybrid systems framework. The scope of coverage includes background on mathematical epidemiology, including classical formulations and results; a motivation for seasonal effects and changes in population behavior, an investigation into term-time forced epidemic models with switching parameters, and a detailed account of several different control strategies. The main goal is to study these models theoretically and to establish conditions under which eradication or persistence of the disease is guaranteed. In doing so, the long-term behavior of the models is determined through mathematical techniques from switched systems theory. Numerical simulations are also given to augment and illustrate the theoretical results and to help study the efficacy of the control schemes.
Fluid and hybrid models for streamers
Bonaventura, Zdeněk
2016-09-01
Streamers are contracted ionizing waves with self-generated field enhancement that propagate into a low-ionized medium exposed to high electric field leaving filamentary trails of plasma behind. The widely used model to study streamer dynamics is based on drift-diffusion equations for electrons and ions, assuming local field approximation, coupled with Poisson's equation. For problems where presence of energetic electrons become important a fluid approach needs to be extended by a particle model, accompanied also with Monte Carlo Collision technique, that takes care of motion of these electrons. A combined fluid-particle approach is used to study an influence of surface emission processes on a fast-pulsed dielectric barrier discharge in air at atmospheric pressure. It is found that fluid-only model predicts substantially faster reignition dynamics compared to coupled fluid-particle model. Furthermore, a hybrid model can be created in which the population of electrons is divided in the energy space into two distinct groups: (1) low energy `bulk' electrons that are treated with fluid model, and (2) high energy `beam' electrons, followed as particles. The hybrid model is then capable not only to deal with streamer discharges in laboratory conditions, but also allows us to study electron acceleration in streamer zone of lighting leaders. There, the production of fast electrons from streamers is investigated, since these (runaway) electrons act as seeds for the relativistic runaway electron avalanche (RREA) mechanism, important for high-energy atmospheric physics phenomena. Results suggest that high energy electrons effect the streamer propagation, namely the velocity, the peak electric field, and thus also the production rate of runaway electrons. This work has been supported by the Czech Science Foundation research project 15-04023S.
A hybrid model for opinion formation
Borra, Domenica; Lorenzi, Tommaso
2013-06-01
This paper presents a hybrid model for opinion formation in a large group of agents exposed to the persuasive action of a small number of strong opinion leaders. The model is defined by coupling a finite difference equation for the dynamics of leaders opinion with a continuous integro-differential equation for the dynamics of the others. Such a definition stems from the idea that the leaders are few and tend to retain original opinions, so that their dynamics occur on a longer time scale with respect to the one of the other agents. A general well-posedness result is established for the initial value problem linked to the model. The asymptotic behavior in time of the related solution is characterized for some general parameter settings, which mimic distinct social scenarios, where different emerging behaviors can be observed. Analytical results are illustrated and extended through numerical simulations.
Modeling of renewable hybrid energy sources
Directory of Open Access Journals (Sweden)
Dumitru Cristian Dragos
2009-12-01
Full Text Available Recent developments and trends in the electric power consumption indicate an increasing use of renewable energy. Renewable energy technologies offer the promise of clean, abundant energy gathered from self-renewing resources such as the sun, wind, earth and plants. Virtually all regions of the world have renewable resources of one type or another. By this point of view studies on renewable energies focuses more and more attention. The present paper intends to present different mathematical models related to different types of renewable energy sources such as: solar energy and wind energy. It is also presented the validation and adaptation of such models to hybrid systems working in geographical and meteorological conditions specific to central part of Transylvania region. The conclusions based on validation of such models are also shown.
Hybrid2: The hybrid system simulation model, Version 1.0, user manual
Energy Technology Data Exchange (ETDEWEB)
Baring-Gould, E.I.
1996-06-01
In light of the large scale desire for energy in remote communities, especially in the developing world, the need for a detailed long term performance prediction model for hybrid power systems was seen. To meet these ends, engineers from the National Renewable Energy Laboratory (NREL) and the University of Massachusetts (UMass) have spent the last three years developing the Hybrid2 software. The Hybrid2 code provides a means to conduct long term, detailed simulations of the performance of a large array of hybrid power systems. This work acts as an introduction and users manual to the Hybrid2 software. The manual describes the Hybrid2 code, what is included with the software and instructs the user on the structure of the code. The manual also describes some of the major features of the Hybrid2 code as well as how to create projects and run hybrid system simulations. The Hybrid2 code test program is also discussed. Although every attempt has been made to make the Hybrid2 code easy to understand and use, this manual will allow many organizations to consider the long term advantages of using hybrid power systems instead of conventional petroleum based systems for remote power generation.
Modelling supervisory controller for hybrid power systems
Energy Technology Data Exchange (ETDEWEB)
Pereira, A.; Bindner, H.; Lundsager, P. [Risoe National Lab., Roskilde (Denmark); Jannerup, O. [Technical Univ. of Denmark, Dept. of Automation, Lyngby (Denmark)
1999-03-01
Supervisory controllers are important to achieve optimal operation of hybrid power systems. The performance and economics of such systems depend mainly on the control strategy for switching on/off components. The modular concept described in this paper is an attempt to design standard supervisory controllers that could be used in different applications, such as village power and telecommunication applications. This paper presents some basic aspects of modelling and design of modular supervisory controllers using the object-oriented modelling technique. The functional abstraction hierarchy technique is used to formulate the control requirements and identify the functions of the control system. The modular algorithm is generic and flexible enough to be used with any system configuration and several goals (different applications). The modularity includes accepting modification of system configuration and goals during operation with minor or no changes in the supervisory controller. (au)
Multiscale Modeling of Graphite/CNT/Epoxy Hybrid Composites
2016-03-09
proposal, was Efficiently and accurately predict the influence of epoxy resin type on the performance of graphite /carbon nanotube/epoxy hybrid...AFRL-AFOSR-VA-TR-2016-0154 Multiscale Modeling of Graphite /CNT/Epoxy Hybrid Composites Gregory Odegard MICHIGAN TECHNOLOGICAL UNIVERSITY Final Report...SUBTITLE Multiscale Modeling of Graphite /CNT/Epoxy Hybrid Composites 5a. CONTRACT NUMBER 5b. GRANT NUMBER FA9550-13-1-0030 5c. PROGRAM ELEMENT NUMBER
Pseudospectral Model for Hybrid PIC Hall-effect Thruster Simulation
2015-07-01
Paper 3. DATES COVERED (From - To) July 2015-July 2015 4. TITLE AND SUBTITLE Pseudospectral model for hybrid PIC Hall-effect thruster simulationect...of a pseudospectral azimuthal-axial hybrid- PIC HET code which is designed to explicitly resolve and filter azimuthal fluctuations in the...661-275-5908 Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std. 239.18 Pseudospectral model for hybrid PIC Hall-effect thruster simulation IEPC
Hybrid discrete choice models: Gained insights versus increasing effort
Energy Technology Data Exchange (ETDEWEB)
Mariel, Petr, E-mail: petr.mariel@ehu.es [UPV/EHU, Economía Aplicada III, Avda. Lehendakari Aguire, 83, 48015 Bilbao (Spain); Meyerhoff, Jürgen [Institute for Landscape Architecture and Environmental Planning, Technical University of Berlin, D-10623 Berlin, Germany and The Kiel Institute for the World Economy, Duesternbrooker Weg 120, 24105 Kiel (Germany)
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. - Highlights: • The paper compares performance of a Hybrid Choice Model (HCM) and a classical Random Parameter Logit (RPL) model. • The HCM indeed provides insights regarding preference heterogeneity not gained from the RPL. • The RPL has similar predictive power as the HCM in our data. • The costs of estimating HCM seem to be justified when learning more on taste heterogeneity is a major study objective.
Exploratory Topology Modelling of Form-Active Hybrid Structures
DEFF Research Database (Denmark)
Holden Deleuran, Anders; Pauly, Mark; Tamke, Martin
2016-01-01
that enables designers and engineers to iteratively construct and manipulate form-active hybrid assembly topology on the fly. The pipeline implements Kangaroo2's projection-based methods for modelling hybrid structures consisting of slender beams and cable networks. A selection of design modelling sketches...
HYBRID2: A versatile model of the performance of hybrid power systems
Green, H. James; Manwell, James
1995-04-01
In 1993, the National Renewable Laboratory (NREL) made an assessment of the available tools from the United States and Europe for predicting the long-term performance of hybrid power systems. By hybrid power the authors mean combinations of two or more power sources wind turbines, photovoltaics (PV), diesel gensets, or other generators into integrated systems for electric power generation in remote locations. Their conclusion was that there was no single, user-friendly tool capable of modeling the full range of hybrid power technologies being considered for the 1990s and beyond. The existing tools were, in particular, lacking flexibility in system configuration and in dispatch of components. As a result, NREL developed a specification for a model, called HYBRID2, for making comparisons of competing technology options on a level playing field. This specification was prepared with a range of potential users in mind including not only the US Department of Energy (DOE) renewable energy programs, but also the US wind industry, technical consultants, international development institutions/banks, and rural electrification programs in developing countries. During 1994, NREL and subcontractor, the University of Massachusetts (UMass), began development of HYBRID2 with funding from the DOE Wind Energy Program. It builds on the wind/diesel model, HYBRID1, developed previously by UMass, and expands that model to accommodate the wider array of technologies used in hybrid power systems. This paper will provide an overview of the model's features, functions, and status.
Hybrid Dynamical Systems Modeling, Stability, and Robustness
Goebel, Rafal; Teel, Andrew R
2012-01-01
Hybrid dynamical systems exhibit continuous and instantaneous changes, having features of continuous-time and discrete-time dynamical systems. Filled with a wealth of examples to illustrate concepts, this book presents a complete theory of robust asymptotic stability for hybrid dynamical systems that is applicable to the design of hybrid control algorithms--algorithms that feature logic, timers, or combinations of digital and analog components. With the tools of modern mathematical analysis, Hybrid Dynamical Systems unifies and generalizes earlier developments in continuous-time and discret
Modelling of data uncertainties on hybrid computers
Energy Technology Data Exchange (ETDEWEB)
Schneider, Anke (ed.)
2016-06-15
The codes d{sup 3}f and r{sup 3}t are well established for modelling density-driven flow and nuclide transport in the far field of repositories for hazardous material in deep geological formations. They are applicable in porous media as well as in fractured rock or mudstone, for modelling salt- and heat transport as well as a free groundwater surface. Development of the basic framework of d{sup 3}f and r{sup 3}t had begun more than 20 years ago. Since that time significant advancements took place in the requirements for safety assessment as well as for computer hardware development. The period of safety assessment for a repository of high-level radioactive waste was extended to 1 million years, and the complexity of the models is steadily growing. Concurrently, the demands on accuracy increase. Additionally, model and parameter uncertainties become more and more important for an increased understanding of prediction reliability. All this leads to a growing demand for computational power that requires a considerable software speed-up. An effective way to achieve this is the use of modern, hybrid computer architectures which requires basically the set-up of new data structures and a corresponding code revision but offers a potential speed-up by several orders of magnitude. The original codes d{sup 3}f and r{sup 3}t were applications of the software platform UG /BAS 94/ whose development had begun in the early nineteennineties. However, UG had recently been advanced to the C++ based, substantially revised version UG4 /VOG 13/. To benefit also in the future from state-of-the-art numerical algorithms and to use hybrid computer architectures, the codes d{sup 3}f and r{sup 3}t were transferred to this new code platform. Making use of the fact that coupling between different sets of equations is natively supported in UG4, d{sup 3}f and r{sup 3}t were combined to one conjoint code d{sup 3}f++. A direct estimation of uncertainties for complex groundwater flow models with the
Throughput capacity computation model for hybrid wireless networks
African Journals Online (AJOL)
wireless networks. We present in this paper, a computational model for obtaining throughput capacity for hybrid wireless networks. For a hybrid network with n nodes and m base stations, we observe through simulation that the throughput capacity increases linearly with the base station infrastructure connected by the wired ...
Transient Model of Hybrid Concentrated Photovoltaic with Thermoelectric Generator
DEFF Research Database (Denmark)
Mahmoudi Nezhad, Sajjad; Qing, Shaowei; Rezaniakolaei, Alireza
2017-01-01
Transient performance of a concentrated photovoltaic thermoelectric (CPV-TEG) hybrid system is modeled and investigated. A heat sink with water, as the working fluid has been implemented as the cold reservoir of the hybrid system to harvest the heat loss from CPV cell and to increase the efficiency...
Wu, Guang; Dong, Zuomin
2017-09-01
Hybrid electric vehicles are widely accepted as a promising short to mid-term technical solution due to noticeably improved efficiency and lower emissions at competitive costs. In recent years, various hybrid powertrain systems were proposed and implemented based on different types of conventional transmission. Power-split system, including Toyota Hybrid System and Ford Hybrid System, are well-known examples. However, their relatively low torque capacity, and the drive of alternative and more advanced designs encouraged other innovative hybrid system designs. In this work, a new type of hybrid powertrain system based hybridized automated manual transmission (HAMT) is proposed. By using the concept of torque gap filler (TGF), this new hybrid powertrain type has the potential to overcome issue of torque gap during gearshift. The HAMT design (patent pending) is described in details, from gear layout and design of gear ratios (EV mode and HEV mode) to torque paths at different gears. As an analytical tool, mutli-body model of vehicle equipped with this HAMT was built to analyze powertrain dynamics at various steady and transient modes. A gearshift was decomposed and analyzed based basic modes. Furthermore, a Simulink-SimDriveline hybrid vehicle model was built for the new transmission, driveline and vehicle modular. Control strategy has also been built to harmonically coordinate different powertrain components to realize TGF function. A vehicle launch simulation test has been completed under 30% of accelerator pedal position to reveal details during gearshift. Simulation results showed that this HAMT can eliminate most torque gap that has been persistent issue of traditional AMT, improving both drivability and performance. This work demonstrated a new type of transmission that features high torque capacity, high efficiency and improved drivability.
Modelling and Verifying Communication Failure of Hybrid Systems in HCSP
DEFF Research Database (Denmark)
Wang, Shuling; Nielson, Flemming; Nielson, Hanne Riis
2016-01-01
.e. the communication itself fails to occur. To address this issue, this paper proposes a formal framework by extending HCSP, a formal modeling language for hybrid systems, for modeling and verifying hybrid systems in the absence of receiving messages due to communication failure. We present two inference systems......Hybrid systems are dynamic systems with interacting discrete computation and continuous physical processes. They have become ubiquitous in our daily life, e.g. automotive, aerospace and medical systems, and in particular, many of them are safety-critical. For a safety-critical hybrid system......, the physical process evolves continuously with respect to time, and the discrete controller monitors and controls the physical process in a correct way such that the whole system satisfies the given safety requirements. The safety of hybrid systems depends heavily on the control from the controllers. However...
Bond graph model-based fault diagnosis of hybrid systems
Borutzky, Wolfgang
2015-01-01
This book presents a bond graph model-based approach to fault diagnosis in mechatronic systems appropriately represented by a hybrid model. The book begins by giving a survey of the fundamentals of fault diagnosis and failure prognosis, then recalls state-of-art developments referring to latest publications, and goes on to discuss various bond graph representations of hybrid system models, equations formulation for switched systems, and simulation of their dynamic behavior. The structured text: • focuses on bond graph model-based fault detection and isolation in hybrid systems; • addresses isolation of multiple parametric faults in hybrid systems; • considers system mode identification; • provides a number of elaborated case studies that consider fault scenarios for switched power electronic systems commonly used in a variety of applications; and • indicates that bond graph modelling can also be used for failure prognosis. In order to facilitate the understanding of fault diagnosis and the presented...
Hybrid Modelling of Individual Movement and Collective Behaviour
Franz, Benjamin
2013-01-01
Mathematical models of dispersal in biological systems are often written in terms of partial differential equations (PDEs) which describe the time evolution of population-level variables (concentrations, densities). A more detailed modelling approach is given by individual-based (agent-based) models which describe the behaviour of each organism. In recent years, an intermediate modelling methodology - hybrid modelling - has been applied to a number of biological systems. These hybrid models couple an individual-based description of cells/animals with a PDE-model of their environment. In this chapter, we overview hybrid models in the literature with the focus on the mathematical challenges of this modelling approach. The detailed analysis is presented using the example of chemotaxis, where cells move according to extracellular chemicals that can be altered by the cells themselves. In this case, individual-based models of cells are coupled with PDEs for extracellular chemical signals. Travelling waves in these hybrid models are investigated. In particular, we show that in contrary to the PDEs, hybrid chemotaxis models only develop a transient travelling wave. © 2013 Springer-Verlag Berlin Heidelberg.
Hybrid ODE/SSA methods and the cell cycle model
Wang, S.; Chen, M.; Cao, Y.
2017-07-01
Stochastic effect in cellular systems has been an important topic in systems biology. Stochastic modeling and simulation methods are important tools to study stochastic effect. Given the low efficiency of stochastic simulation algorithms, the hybrid method, which combines an ordinary differential equation (ODE) system with a stochastic chemically reacting system, shows its unique advantages in the modeling and simulation of biochemical systems. The efficiency of hybrid method is usually limited by reactions in the stochastic subsystem, which are modeled and simulated using Gillespie's framework and frequently interrupt the integration of the ODE subsystem. In this paper we develop an efficient implementation approach for the hybrid method coupled with traditional ODE solvers. We also compare the efficiency of hybrid methods with three widely used ODE solvers RADAU5, DASSL, and DLSODAR. Numerical experiments with three biochemical models are presented. A detailed discussion is presented for the performances of three ODE solvers.
Hybrid Computational Model for High-Altitude Aeroassist Vehicles Project
National Aeronautics and Space Administration — A hybrid continuum/noncontinuum computational model will be developed for analyzing the aerodynamics and heating on aeroassist vehicles. Unique features of this...
Nuclear Hybrid Energy System Modeling: RELAP5 Dynamic Coupling Capabilities
Energy Technology Data Exchange (ETDEWEB)
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.
MADYMO facet Hybrid III 5th percentile model
Margerie, L.; Hovenga, E.; Boucher, H.; Kant, R.; Subbian, T.; Co, J.; Xu, B.; Ojemudia, D.; Ng, J.
2000-01-01
A new MADYMO model of the Hybrid III 5th percentile female dummy has been developed. Most attention is placed on modeling the thorax, pelvis- abdomen, head and neck. Those parts are modelled with facet surfaces and deformable bodies are used for the thorax. The remaining dummy parts are identical to
Partitioning and interpolation based hybrid ARIMA–ANN model for ...
Indian Academy of Sciences (India)
Time series forecasting; ARIMA; ANN; partitioning and interpolation; Box–Jenkins methodology ... Further, on different experimental TSD like sunspots TSD and electricity price TSD, the proposed hybrid model is applied along with four existing state-of-the-art models and it is found that the proposed model outperforms all ...
Nuclear Hybrid Energy System Model Stability Testing
Energy Technology Data Exchange (ETDEWEB)
Greenwood, Michael Scott [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Cetiner, Sacit M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Fugate, David W. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
2017-04-01
A Nuclear Hybrid Energy System (NHES) uses a nuclear reactor as the basic power generation unit, and the power generated is used by multiple customers as combinations of thermal power or electrical power. The definition and architecture of a particular NHES can be adapted based on the needs and opportunities of different localities and markets. For example, locations in need of potable water may be best served by coupling a desalination plant to the NHES. Similarly, a location near oil refineries may have a need for emission-free hydrogen production. Using the flexible, multi-domain capabilities of Modelica, Argonne National Laboratory, Idaho National Laboratory, and Oak Ridge National Laboratory are investigating the dynamics (e.g., thermal hydraulics and electrical generation/consumption) and cost of a hybrid system. This paper examines the NHES work underway, emphasizing the control system developed for individual subsystems and the overall supervisory control system.
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. © The Author 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
A Hybrid Model of a Brushless DC Motor
DEFF Research Database (Denmark)
Bendtsen, Jan Dimon; Hansen, Hans Brink; Kallesøe, Carsten Skovmose
2007-01-01
This paper presents a novel approach to modeling of a Brush-Less Direct Current Motor (BLDCM) driven by an inverter using hybrid systems theory. Hybrid systems combine continuous and discrete (event-based) dynamics, which is exactly the case in an inverter-driven BLDCM. The model presented...... in this work consists of a general automaton with discrete states, combined with a set of continuous dynamic equations describing the electro-mechanical behavior of the motor. One of the significant benefits of this strategy is that the model describes the motor under all possible operating conditions...
Hybrid Model GSTAR-SUR-NN For Precipitation Data
Agus Dwi Sulistyono; Waego Hadi Nugroho; Rahma Fitriani; Atiek Iriani
2016-01-01
Spatio-temporal model that have been developed such as Space-Time Autoregressive (STAR) model, Generalized Space-Time Autoregressive (GSTAR), GSTAR-OLS and GSTAR-SUR. Besides spatio-temporal phenomena, in daily life, we often find nonlinear phenomena, uncommon patterns and unidentified characteristics of the data. One of current developed nonlinear model is a neural network. This study is conducted to form a hybrid model GSTAR-SUR-NN to develop spatio-temporal model that has better prediction...
Hybrid continuum-atomistic approach to model electrokinetics in nanofluidics
Energy Technology Data Exchange (ETDEWEB)
Amani, Ehsan, E-mail: eamani@aut.ac.ir; Movahed, Saeid, E-mail: smovahed@aut.ac.ir
2016-06-07
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. - Highlights: • A hybrid continuum-atomistic model is proposed for electrokinetics in nanochannels. • The model is validated by molecular dynamics. • This is a promising approach to model more complicated geometries and physics.
Evaluation of models generated via hybrid evolutionary algorithms ...
African Journals Online (AJOL)
2016-04-02
Apr 2, 2016 ... Evaluation of models generated via hybrid evolutionary algorithms for the prediction of Microcystis concentrations ... evolutionary algorithms (HEA) proved to be highly applica- ble to the hypertrophic reservoirs of .... Principal component analysis (PCA) was carried out on the input dataset used for the model ...
Model for optimum design of standalone hybrid renewable energy ...
African Journals Online (AJOL)
An optimization model for the design of a hybrid renewable energy microgrid supplying an isolated load has been developed. This is achieved in two steps. The first step developed a linear programming model that uses the average pattern of demand, wind, and solar energy to determine the optimal configuration.
Hybrid programming model for implicit PDE simulations on multicore architectures
Kaushik, Dinesh
2011-01-01
The complexity of programming modern multicore processor based clusters is rapidly rising, with GPUs adding further demand for fine-grained parallelism. This paper analyzes the performance of the hybrid (MPI+OpenMP) programming model in the context of an implicit unstructured mesh CFD code. At the implementation level, the effects of cache locality, update management, work division, and synchronization frequency are studied. The hybrid model presents interesting algorithmic opportunities as well: the convergence of linear system solver is quicker than the pure MPI case since the parallel preconditioner stays stronger when hybrid model is used. This implies significant savings in the cost of communication and synchronization (explicit and implicit). Even though OpenMP based parallelism is easier to implement (with in a subdomain assigned to one MPI process for simplicity), getting good performance needs attention to data partitioning issues similar to those in the message-passing case. © 2011 Springer-Verlag.
Nuclear Hybrid Energy Systems FY16 Modeling Efforts at ORNL
Energy Technology Data Exchange (ETDEWEB)
Cetiner, Sacit M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Greenwood, Michael Scott [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Harrison, Thomas J. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Qualls, A. L. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Guler Yigitoglu, Askin [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Fugate, David W. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
2016-09-01
A nuclear hybrid system uses a nuclear reactor as the basic power generation unit. The power generated by the nuclear reactor is utilized by one or more power customers as either thermal power, electrical power, or both. In general, a nuclear hybrid system will couple the nuclear reactor to at least one thermal power user in addition to the power conversion system. The definition and architecture of a particular nuclear hybrid system is flexible depending on local markets needs and opportunities. For example, locations in need of potable water may be best served by coupling a desalination plant to the nuclear system. Similarly, an area near oil refineries may have a need for emission-free hydrogen production. A nuclear hybrid system expands the nuclear power plant from its more familiar central power station role by diversifying its immediately and directly connected customer base. The definition, design, analysis, and optimization work currently performed with respect to the nuclear hybrid systems represents the work of three national laboratories. Idaho National Laboratory (INL) is the lead lab working with Argonne National Laboratory (ANL) and Oak Ridge National Laboratory. Each laboratory is providing modeling and simulation expertise for the integration of the hybrid system.
Static stiffness modeling of a novel hybrid redundant robot machine
Energy Technology Data Exchange (ETDEWEB)
Li Ming, E-mail: hackingming@gmail.com [Laboratory of Intelligent Machines, Lappeenranta University of Technology (Finland); Wu Huapeng; Handroos, Heikki [Laboratory of Intelligent Machines, Lappeenranta University of Technology (Finland)
2011-10-15
This paper presents a modeling method to study the stiffness of a hybrid serial-parallel robot IWR (Intersector Welding Robot) for the assembly of ITER vacuum vessel. The stiffness matrix of the basic element in the robot is evaluated using matrix structural analysis (MSA); the stiffness of the parallel mechanism is investigated by taking account of the deformations of both hydraulic limbs and joints; the stiffness of the whole integrated robot is evaluated by employing the virtual joint method and the principle of virtual work. The obtained stiffness model of the hybrid robot is analytical and the deformation results of the robot workspace under certain external load are presented.
Modeling of hybrid vehicle fuel economy and fuel engine efficiency
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.
Hybrid attacks on model-based social recommender systems
Yu, Junliang; Gao, Min; Rong, Wenge; Li, Wentao; Xiong, Qingyu; Wen, Junhao
2017-10-01
With the growing popularity of the online social platform, the social network based approaches to recommendation emerged. However, because of the open nature of rating systems and social networks, the social recommender systems are susceptible to malicious attacks. In this paper, we present a certain novel attack, which inherits characteristics of the rating attack and the relation attack, and term it hybrid attack. Furtherly, we explore the impact of the hybrid attack on model-based social recommender systems in multiple aspects. The experimental results show that, the hybrid attack is more destructive than the rating attack in most cases. In addition, users and items with fewer ratings will be influenced more when attacked. Last but not the least, the findings suggest that spammers do not depend on the feedback links from normal users to become more powerful, the unilateral links can make the hybrid attack effective enough. Since unilateral links are much cheaper, the hybrid attack will be a great threat to model-based social recommender systems.
The innovative concept of three-dimensional hybrid receptor modeling
Stojić, A.; Stanišić Stojić, S.
2017-09-01
The aim of this study was to improve the current understanding of air pollution transport processes at regional and long-range scale. For this purpose, three-dimensional (3D) potential source contribution function and concentration weighted trajectory models, as well as new hybrid receptor model, concentration weighted boundary layer (CWBL), which uses a two-dimensional grid and a planetary boundary layer height as a frame of reference, are presented. The refined approach to hybrid receptor modeling has two advantages. At first, it considers whether each trajectory endpoint meets the inclusion criteria based on planetary boundary layer height, which is expected to provide a more realistic representation of the spatial distribution of emission sources and pollutant transport pathways. Secondly, it includes pollutant time series preprocessing to make hybrid receptor models more applicable for suburban and urban locations. The 3D hybrid receptor models presented herein are designed to identify altitude distribution of potential sources, whereas CWBL can be used for analyzing the vertical distribution of pollutant concentrations along the transport pathway.
Analysis and Simulation of Hybrid Models for Reaction Networks
Kreim, Michael
2014-01-01
The dynamics of biochemical reaction networks can be described by a variety of models, like the Reaction Rate equation (RRE), the Chemical Master equation (CME) or the Fokker-Planck equation (FPE). In this thesis, the behaviour of these different models is analysed. It is shown that the FPE can be motivated as an approximation of the CME and convergence is proven. Furthermore, two hybrid models are constructed by combining different approaches and convergence properties are proven and discussed.
Model-based Dynamic Control Allocation in a Hybrid Neuroprosthesis.
Kirsch, Nicholas A; Bao, Xuefeng; Alibeji, Naji A; Dicianno, Brad E; Sharma, Nitin
2017-09-22
A hybrid neuroprosthesis that combines human muscle power, elicited through functional electrical stimulation (FES), with a powered orthosis may be advantageous over a sole FES or a powered exoskeleton-based rehabilitation system. The hybrid system can conceivably overcome torque reduction due to FESinduced muscle fatigue by complementarily using torque from the powered exoskeleton. The second advantage of the hybrid system is that the use of human muscle power can supplement the powered exoskeleton's power (motor torque) requirements; thus, potentially reducing the size and weight of a walking restoration system. To realize these advantages, however, it is unknown how to concurrently optimize desired control performance and allocation of control inputs between FES and electric motor. In this paper, a model predictive control-based dynamic control allocation (DCA) is used to allocate control between FES and the electric motor that simultaneously maintain a desired knee angle. The experimental results, depicting the performance of the DCA method while the muscle fatigues, are presented for an able-bodied participant and a participant with spinal cord injury. The experimental results showed that the motor torque recruited by the hybrid system was less than that recruited by the motor-only system, the algorithm can be easily used to allocate more control input to the electric motor as the muscle fatigues, and the muscle fatigue induced by the hybrid system was found to be less than the fatigue induced by sole FES. These results validate the aforementioned advantages of the hybrid system; thus implying the hybrid technology's potential use in walking rehabilitation.
Efficient Proof Engines for Bounded Model Checking of Hybrid Systems
DEFF Research Database (Denmark)
Fränzle, Martin; Herde, Christian
2005-01-01
of the various optimizations that arise naturally in the bounded model checking context, e.g. isomorphic replication of learned conflict clauses or tailored decision strategies, and extends them to the hybrid domain. We demonstrate that those optimizations are crucial to the performance of the tool....
A novel Monte Carlo approach to hybrid local volatility models
van der Stoep, A.W.; Grzelak, L.A.; Oosterlee, C.W.
2017-01-01
We present in a Monte Carlo simulation framework, a novel approach for the evaluation of hybrid local volatility [Risk, 1994, 7, 18–20], [Int. J. Theor. Appl. Finance, 1998, 1, 61–110] models. In particular, we consider the stochastic local volatility model—see e.g. Lipton et al. [Quant. Finance,
New Models of Hybrid Leadership in Global Higher Education
Tonini, Donna C.; Burbules, Nicholas C.; Gunsalus, C. K.
2016-01-01
This manuscript highlights the development of a leadership preparation program known as the Nanyang Technological University Leadership Academy (NTULA), exploring the leadership challenges unique to a university undergoing rapid growth in a highly multicultural context, and the hybrid model of leadership it developed in response to globalization.…
Model Predictive Control of the Hybrid Ventilation for Livestock
DEFF Research Database (Denmark)
Wu, Zhuang; Stoustrup, Jakob; Trangbæk, Klaus
2006-01-01
In this paper, design and simulation results of Model Predictive Control (MPC) strategy for livestock hybrid ventilation systems and associated indoor climate through variable valve openings and exhaust fans are presented. The design is based on thermal comfort parameters for poultry in barns...
Hybrid time/frequency domain modeling of nonlinear components
DEFF Research Database (Denmark)
Wiechowski, Wojciech Tomasz; Lykkegaard, Jan; Bak, Claus Leth
2007-01-01
This paper presents a novel, three-phase hybrid time/frequency methodology for modelling of nonlinear components. The algorithm has been implemented in the DIgSILENT PowerFactory software using the DIgSILENT Programming Language (DPL), as a part of the work described in [1]. Modified HVDC benchmark...
Lead-acid battery model for hybrid energy storage
BUTTERBACH, S; Vulturescu, Bogdan; FORGEZ, C; Coquery, Gérard; Friedrich, G
2011-01-01
This paper deals with the design of hybrid energy storage for an electric waste collection vehicle. The hybrid storage is made of lead-acid batteries and supercapacitors. A detailed lead-acid model is proposed in order to take into account the charge of the battery during regenerative braking. The vehicle was simulated on an urban driving cycle for a full working day. The reduction of the consumed energy due to an increased recovery capacity is outlined in this paper as a main benefit of the ...
Hybrid modelling of a sugar boiling process
Lauret, Alfred Jean Philippe; Gatina, Jean Claude
2012-01-01
The first and maybe the most important step in designing a model-based predictive controller is to develop a model that is as accurate as possible and that is valid under a wide range of operating conditions. The sugar boiling process is a strongly nonlinear and nonstationary process. The main process nonlinearities are represented by the crystal growth rate. This paper addresses the development of the crystal growth rate model according to two approaches. The first approach is classical and consists of determining the parameters of the empirical expressions of the growth rate through the use of a nonlinear programming optimization technique. The second is a novel modeling strategy that combines an artificial neural network (ANN) as an approximator of the growth rate with prior knowledge represented by the mass balance of sucrose crystals. The first results show that the first type of model performs local fitting while the second offers a greater flexibility. The two models were developed with industrial data...
Modelling and analysis of real-time and hybrid systems
Energy Technology Data Exchange (ETDEWEB)
Olivero, A.
1994-09-29
This work deals with the modelling and analysis of real-time and hybrid systems. We first present the timed-graphs as model for the real-time systems and we recall the basic notions of the analysis of real-time systems. We describe the temporal properties on the timed-graphs using TCTL formulas. We consider two methods for property verification: in one hand we study the symbolic model-checking (based on backward analysis) and in the other hand we propose a verification method derived of the construction of the simulation graph (based on forward analysis). Both methods have been implemented within the KRONOS verification tool. Their application for the automatic verification on several real-time systems confirms the practical interest of our approach. In a second part we study the hybrid systems, systems combining discrete components with continuous ones. As in the general case the analysis of this king of systems is not decidable, we identify two sub-classes of hybrid systems and we give a construction based method for the generation of a timed-graph from an element into the sub-classes. We prove that in one case the timed-graph obtained is bi-similar with the considered system and that there exists a simulation in the other case. These relationships allow the application of the described technics on the hybrid systems into the defined sub-classes. (authors). 60 refs., 43 figs., 8 tabs., 2 annexes.
A hybrid society model for simulating residential electricity consumption
Energy Technology Data Exchange (ETDEWEB)
Xu, Minjie [School of Electrical Engineering, Beijing Jiaotong University, Beijing (China); State Power Economic Research Institute, Beijing (China); Hu, Zhaoguang [State Power Economic Research Institute, Beijing (China); Wu, Junyong; Zhou, Yuhui [School of Electrical Engineering, Beijing Jiaotong University, Beijing (China)
2008-12-15
In this paper, a hybrid social model of econometric model and social influence model is proposed for evaluating the influence of pricing policy and public education policy on residential habit of electricity using in power resources management. And, a hybrid society simulation platform based on the proposed model, called residential electricity consumption multi-agent systems (RECMAS), is designed for simulating residential electricity consumption by multi-agent system. RECMAS is composed of consumer agent, power supplier agent, and policy maker agent. It provides the policy makers with a useful tool to evaluate power price policies and public education campaigns in different scenarios. According to an influenced diffusion mechanism, RECMAS can simulate the residential electricity demand-supply chain and analyze impacts of the factors on residential electricity consumption. Finally, the proposed method is used to simulate urban residential electricity consumption in China. (author)
Hybrid Neuro-Fuzzy Classifier Based On Nefclass Model
Directory of Open Access Journals (Sweden)
Bogdan Gliwa
2011-01-01
Full Text Available The paper presents hybrid neuro-fuzzy classifier, based on NEFCLASS model, which wasmodified. The presented classifier was compared to popular classifiers – neural networks andk-nearest neighbours. Efficiency of modifications in classifier was compared with methodsused in original model NEFCLASS (learning methods. Accuracy of classifier was testedusing 3 datasets from UCI Machine Learning Repository: iris, wine and breast cancer wisconsin.Moreover, influence of ensemble classification methods on classification accuracy waspresented.
Anisotropic ghost dark energy cosmological model with hybrid expansion law
Mahanta, Chandra Rekha; Sarma, Nitin
2017-11-01
In this paper, we study the anisotropic Bianchi type-VI0 metric filled with dark matter and anisotropic ghost dark energy. We have solved the Einstein's field equations by considering hybrid expansion law (HEL) for the average scale factor. It is found that at later times the universe becomes spatially homogeneous, isotropic and flat. From a state finder diagnosis, it is found that our model is having similar behavior like ɅCDM model at late phase of cosmic time.
Speech Segmentation to Phonemes Based on Hybrid Hidden Markov Models
Jingbin, Yan; Shi, Wu; Tkachenia, A. V.; Kheidorov, I. E.
2009-01-01
In this paper we develop automatic speech segmentation to phonemes using hybrid system based on Hidden Markov Model (HMM) and Artificial Neutral Network (ANN). It was shown that usage of ANN in order to estimate local probability in HMM leads to optimal global probability estimation in the general case, without imposition of additional model conditions. The result of automatic segmentation is close to the manual one, and can be successfully used in real applications for speech data s...
A hybrid approach to empirical magnetosphere modeling
Tsyganenko, N. A.; Andreeva, V. A.
2017-08-01
A new approach has been devised and explored to reconstruct magnetospheric configurations, based on spacecraft data and a synthesis of two methods of modeling the magnetic field of extraterrestrial currents. The main idea is to combine within a single framework (1) a modular structure explicitly representing separate contributions to the total field from the magnetopause, ring, tail, and field-aligned currents, and (2) a system of densely distributed field sources, modeled by the radial basis functions (RBF). In such an arrangement, the modular part takes on a role of the principal component representing the gross large-scale structure of the magnetosphere, whereas the RBF part serves as a higher-order correction that compensates for the lack of flexibility of the modular component. The approach has been tested on four subsets of spacecraft data, corresponding to four phases of a geomagnetic storm, and was shown to tangibly improve the model's performance. In particular, it allows proper representation of magnetic effects of the field-aligned currents both at low altitudes and in the distant magnetosphere, as well as inclusion of extensive high-latitude field depressions associated with diamagnetism of the polar cusp plasma, missing in earlier empirical models. It also helps to more accurately model the nightside magnetosphere, so that most of the large-scale magnetotail field is compactly described by a dedicated module inherited from an earlier empirical model, while the RBF component's task is to resolve finer details in the inner magnetosphere.
Hybrid neural network bushing model for vehicle dynamics simulation
Energy Technology Data Exchange (ETDEWEB)
Sohn, Jeong Hyun [Pukyong National University, Busan (Korea, Republic of); Lee, Seung Kyu [Hyosung Corporation, Changwon (Korea, Republic of); Yoo, Wan Suk [Pusan National University, Busan (Korea, Republic of)
2008-12-15
Although the linear model was widely used for the bushing model in vehicle suspension systems, it could not express the nonlinear characteristics of bushing in terms of the amplitude and the frequency. An artificial neural network model was suggested to consider the hysteretic responses of bushings. This model, however, often diverges due to the uncertainties of the neural network under the unexpected excitation inputs. In this paper, a hybrid neural network bushing model combining linear and neural network is suggested. A linear model was employed to represent linear stiffness and damping effects, and the artificial neural network algorithm was adopted to take into account the hysteretic responses. A rubber test was performed to capture bushing characteristics, where sine excitation with different frequencies and amplitudes is applied. Random test results were used to update the weighting factors of the neural network model. It is proven that the proposed model has more robust characteristics than a simple neural network model under step excitation input. A full car simulation was carried out to verify the proposed bushing models. It was shown that the hybrid model results are almost identical to the linear model under several maneuvers
Multiview coding mode decision with hybrid optimal stopping model.
Zhao, Tiesong; Kwong, Sam; Wang, Hanli; Wang, Zhou; Pan, Zhaoqing; Kuo, C-C Jay
2013-04-01
In a generic decision process, optimal stopping theory aims to achieve a good tradeoff between decision performance and time consumed, with the advantages of theoretical decision-making and predictable decision performance. In this paper, optimal stopping theory is employed to develop an effective hybrid model for the mode decision problem, which aims to theoretically achieve a good tradeoff between the two interrelated measurements in mode decision, as computational complexity reduction and rate-distortion degradation. The proposed hybrid model is implemented and examined with a multiview encoder. To support the model and further promote coding performance, the multiview coding mode characteristics, including predicted mode probability and estimated coding time, are jointly investigated with inter-view correlations. Exhaustive experimental results with a wide range of video resolutions reveal the efficiency and robustness of our method, with high decision accuracy, negligible computational overhead, and almost intact rate-distortion performance compared to the original encoder.
Hydraulic Hybrid Excavator—Mathematical Model Validation and Energy Analysis
Directory of Open Access Journals (Sweden)
Paolo Casoli
2016-11-01
Full Text Available Recent demands to reduce pollutant emissions and improve energy efficiency have driven the implementation of hybrid solutions in mobile machinery. This paper presents the results of a numerical and experimental analysis conducted on a hydraulic hybrid excavator (HHE. The machinery under study is a middle size excavator, whose standard version was modified with the introduction of an energy recovery system (ERS. The proposed ERS layout was designed to recover the potential energy of the boom, using a hydraulic accumulator as a storage device. The recovered energy is utilized through the pilot pump of the machinery which operates as a motor, thus reducing the torque required from the internal combustion engine (ICE. The analysis reported in this paper validates the HHE model by comparing numerical and experimental data in terms of hydraulic and mechanical variables and fuel consumption. The mathematical model shows its capability to reproduce the realistic operating conditions of the realized prototype, tested on the field. A detailed energy analysis comparison between the standard and the hybrid excavator models was carried out to evaluate the energy flows along the system, showing advantages, weaknesses and possibilities to further improve the machinery efficiency. Finally, the fuel consumption estimated by the model and that measured during the experiments are presented to highlight the fuel saving percentages. The HHE model is an important starting point for the development of other energy saving solutions.
Hybrid continuum-atomistic approach to model electrokinetics in nanofluidics.
Amani, Ehsan; Movahed, Saeid
2016-06-07
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. Copyright © 2016 Elsevier B.V. All rights reserved.
Neural system modeling and simulation using Hybrid Functional Petri Net.
Tang, Yin; Wang, Fei
2012-02-01
The Petri net formalism has been proved to be powerful in biological modeling. It not only boasts of a most intuitive graphical presentation but also combines the methods of classical systems biology with the discrete modeling technique. Hybrid Functional Petri Net (HFPN) was proposed specially for biological system modeling. An array of well-constructed biological models using HFPN yielded very interesting results. In this paper, we propose a method to represent neural system behavior, where biochemistry and electrical chemistry are both included using the Petri net formalism. We built a model for the adrenergic system using HFPN and employed quantitative analysis. Our simulation results match the biological data well, showing that the model is very effective. Predictions made on our model further manifest the modeling power of HFPN and improve the understanding of the adrenergic system. The file of our model and more results with their analysis are available in our supplementary material.
Modelling the solar wind interaction with Mercury by a quasi-neutral hybrid model
Directory of Open Access Journals (Sweden)
E. Kallio
2003-11-01
Full Text Available Quasi-neutral hybrid model is a self-consistent modelling approach that includes positively charged particles and an electron fluid. The approach has received an increasing interest in space plasma physics research because it makes it possible to study several plasma physical processes that are difficult or impossible to model by self-consistent fluid models, such as the effects associated with the ions’ finite gyroradius, the velocity difference between different ion species, or the non-Maxwellian velocity distribution function. By now quasi-neutral hybrid models have been used to study the solar wind interaction with the non-magnetised Solar System bodies of Mars, Venus, Titan and comets. Localized, two-dimensional hybrid model runs have also been made to study terrestrial dayside magnetosheath. However, the Hermean plasma environment has not yet been analysed by a global quasi-neutral hybrid model. In this paper we present a new quasi-neutral hybrid model developed to study various processes associated with the Mercury-solar wind interaction. Emphasis is placed on addressing advantages and disadvantages of the approach to study different plasma physical processes near the planet. The basic assumptions of the approach and the algorithms used in the new model are thoroughly presented. Finally, some of the first three-dimensional hybrid model runs made for Mercury are presented. The resulting macroscopic plasma parameters and the morphology of the magnetic field demonstrate the applicability of the new approach to study the Mercury-solar wind interaction globally. In addition, the real advantage of the kinetic hybrid model approach is to study the property of individual ions, and the study clearly demonstrates the large potential of the approach to address these more detailed issues by a quasi-neutral hybrid model in the future.Key words. Magnetospheric physics (planetary magnetospheres; solar wind-magnetosphere interactions – Space plasma
Reverse engineering cellular decisions for hybrid reconfigurable network modeling
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.
Modelling hybrid stars in quark-hadron approaches
Energy Technology Data Exchange (ETDEWEB)
Schramm, S. [FIAS, Frankfurt am Main (Germany); Dexheimer, V. [Kent State University, Department of Physics, Kent, OH (United States); Negreiros, R. [Federal Fluminense University, Gragoata, Niteroi (Brazil)
2016-01-15
The density in the core of neutron stars can reach values of about 5 to 10 times nuclear matter saturation density. It is, therefore, a natural assumption that hadrons may have dissolved into quarks under such conditions, forming a hybrid star. This star will have an outer region of hadronic matter and a core of quark matter or even a mixed state of hadrons and quarks. In order to investigate such phases, we discuss different model approaches that can be used in the study of compact stars as well as being applicable to a wider range of temperatures and densities. One major model ingredient, the role of quark interactions in the stability of massive hybrid stars is discussed. In this context, possible conflicts with lattice QCD simulations are investigated. (orig.)
A Hybrid Multiple Criteria Decision Making Model for Supplier Selection
Wu, Chung-Min; Hsieh, Ching-Lin; Chang, Kuei-Lun
2013-01-01
The sustainable supplier selection would be the vital part in the management of a sustainable supply chain. In this study, a hybrid multiple criteria decision making (MCDM) model is applied to select optimal supplier. The fuzzy Delphi method, which can lead to better criteria selection, is used to modify criteria. Considering the interdependence among the selection criteria, analytic network process (ANP) is then used to obtain their weights. To avoid calculation and additional pairwise compa...
A Novel of Hybrid Maintenance Management Models for Industrial Applications
Tahir, Zulkifli
2010-01-01
It is observed through empirical studies that the effectiveness of industrial process have been increased by a well organized of machines maintenance structure. In current research, a novel of maintenance concept has been designed by hybrid several maintenance management models with Decision Making Grid (DMG), Analytic Hierarchy Process (AHP) and Fuzzy Logic. The concept is designed for maintenance personnel to evaluate and benchmark the maintenance operations and to reveal important maintena...
Hybrid adiabatic potentials in the QCD string model
Kalashnikova, Yu. S.; Kuzmenko, D. S.
2002-01-01
The short- and intermediate-distance behaviour of the hybrid adiabatic potentials is calculated in the framework of the QCD string model. The calculations are performed with the inclusion of Coulomb force. Spin-dependent force and the so-called string correction term are treated as perturbation at the leading potential-type regime. Reasonably good agreement with lattice measurements takes place for adiabatic curves excited with magnetic components of field strength correlators.
A light neutralino in hybrid models of supersymmetry breaking
Dudas, Emilian; Parmentier, Jeanne; 10.1016
2008-01-01
We show that in gauge mediation models where heavy messenger masses are provided by the adjoint Higgs field of an underlying SU(5) theory, a generalized gauge mediation spectrum arises with the characteristic feature of having a neutralino much lighter than in the standard gauge or gravity mediation schemes. This naturally fits in a hybrid scenario where gravity mediation, while subdominant with respect to gauge mediation, provides mu and B mu parameters in the TeV range.
Hybrid Mesons Masses in a Quark-Gluon Constituent Model
Iddir, F; CERN. Geneva; Iddir, Farida; Semlala, Lahouari
2002-01-01
QCD theory allows the existence of states which cannot be built by the naive quark model; both theoretical arguments and experimental data confirm the hypothesis that gluons may have freedom degrees at the constituent level, and should be confined. In this work, we use a phenomenological potential motivated by QCD (with some relativistic corrections) to determine the masses and the wavefunctions of several hybrid mesons, within the context of a constituent q-qbar-g model. We compare our estimates of the masses with the predictions of other theoretical models and with the observed masses of candidates.
Magnetic equivalent circuit model for unipolar hybrid excitation synchronous machine
Directory of Open Access Journals (Sweden)
Kupiec Emil
2015-03-01
Full Text Available Lately, there has been increased interest in hybrid excitation electrical machines. Hybrid excitation is a construction that combines permanent magnet excitation with wound field excitation. Within the general classification, these machines can be classified as modified synchronous machines or inductor machines. These machines may be applied as motors and generators. The complexity of electromagnetic phenomena which occur as a result of coupling of magnetic fluxes of separate excitation systems with perpendicular magnetic axis is a motivation to formulate various mathematical models of these machines. The presented paper discusses the construction of a unipolar hybrid excitation synchronous machine. The magnetic equivalent circuit model including nonlinear magnetization curves is presented. Based on this model, it is possible to determine the multi-parameter relationships between the induced voltage and magnetomotive force in the excitation winding. Particular attention has been paid to the analysis of the impact of additional stator and rotor yokes on above relationship. Induced voltage determines the remaining operating parameters of the machine, both in the motor and generator mode of operation. The analysis of chosen correlations results in an identification of the effective control range of electromotive force of the machine.
Modeling Hybrid Systems in the Concurrent Constraint Paradigm
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Damián Adalid
2015-01-01
Full Text Available Hybrid systems, which combine discrete and continuous dynamics, require quality modeling languages to be either described or analyzed. The Concurrent Constraint paradigm (ccp is an expressive declarative paradigm, characterized by the use of a common constraint store to communicate and synchronize concurrent agents. In this paradigm, the information is stated in the form of constraints, in contrast to the variable/value style typical of imperative languages. Several extensions of ccp have been proposed in order to model reactive systems. One of these extensions is the Timed Concurrent Constraint Language (tccp that adds to ccp a notion of discrete time and new features to model time-out and preemption actions. The goal of this paper is to explore the expressive power of tccp to describe hybrid systems. We introduce the language Hy-tccp as a conservative extension of tccp, by adding a notion of continuous time and new constructs to describe the continuous dynamics of hybrid systems. In this paper, we present the syntax and the operational semantics of Hy-tccp together with some examples that show the expressive power of our new language.
Parametric Linear Hybrid Automata for Complex Environmental Systems Modeling
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Samar Hayat Khan Tareen
2015-07-01
Full Text Available Environmental systems, whether they be weather patterns or predator-prey relationships, are dependent on a number of different variables, each directly or indirectly affecting the system at large. Since not all of these factors are known, these systems take on non-linear dynamics, making it difficult to accurately predict meaningful behavioral trends far into the future. However, such dynamics do not warrant complete ignorance of different efforts to understand and model close approximations of these systems. Towards this end, we have applied a logical modeling approach to model and analyze the behavioral trends and systematic trajectories that these systems exhibit without delving into their quantification. This approach, formalized by René Thomas for discrete logical modeling of Biological Regulatory Networks (BRNs and further extended in our previous studies as parametric biological linear hybrid automata (Bio-LHA, has been previously employed for the analyses of different molecular regulatory interactions occurring across various cells and microbial species. As relationships between different interacting components of a system can be simplified as positive or negative influences, we can employ the Bio-LHA framework to represent different components of the environmental system as positive or negative feedbacks. In the present study, we highlight the benefits of hybrid (discrete/continuous modeling which lead to refinements among the fore-casted behaviors in order to find out which ones are actually possible. We have taken two case studies: an interaction of three microbial species in a freshwater pond, and a more complex atmospheric system, to show the applications of the Bio-LHA methodology for the timed hybrid modeling of environmental systems. Results show that the approach using the Bio-LHA is a viable method for behavioral modeling of complex environmental systems by finding timing constraints while keeping the complexity of the model
Scalability of Sustainable Business Models in Hybrid Organizations
Directory of Open Access Journals (Sweden)
Adam Jabłoński
2016-02-01
Full Text Available The dynamics of change in modern business create new mechanisms for company management to determine their pursuit and the achievement of their high performance. This performance maintained over a long period of time becomes a source of ensuring business continuity by companies. An ontological being enabling the adoption of such assumptions is such a business model that has the ability to generate results in every possible market situation and, moreover, it has the features of permanent adaptability. A feature that describes the adaptability of the business model is its scalability. Being a factor ensuring more work and more efficient work with an increasing number of components, scalability can be applied to the concept of business models as the company’s ability to maintain similar or higher performance through it. Ensuring the company’s performance in the long term helps to build the so-called sustainable business model that often balances the objectives of stakeholders and shareholders, and that is created by the implemented principles of value-based management and corporate social responsibility. This perception of business paves the way for building hybrid organizations that integrate business activities with pro-social ones. The combination of an approach typical of hybrid organizations in designing and implementing sustainable business models pursuant to the scalability criterion seems interesting from the cognitive point of view. Today, hybrid organizations are great spaces for building effective and efficient mechanisms for dialogue between business and society. This requires the appropriate business model. The purpose of the paper is to present the conceptualization and operationalization of scalability of sustainable business models that determine the performance of a hybrid organization in the network environment. The paper presents the original concept of applying scalability in sustainable business models with detailed
Abstraction and Counterexample-Guided Refinement in Model Checking of Hybrid Systems
National Research Council Canada - National Science Library
Clarke, Edmund; Fehnker, Ansgar; Han, Zhi; Krogh, Bruce; Ouaknine, Joel; Stursberg, Olaf; Theobald, Michael
2003-01-01
Hybrid dynamic systems include both continuous and discrete state variables. Properties of hybrid systems, which have an infinite state space, can often be verified using ordinary model checking together with a finite-state abstraction...
Hybrid Geoid Model: Theory and Application in Brazil.
Arana, Daniel; Camargo, Paulo O; Guimarães, Gabriel N
2017-01-01
Determination of the ellipsoidal height by Global Navigation Satellite Systems (GNSS) is becoming better known and used for purposes of leveling with the aid of geoid models. However, the disadvantage of this method is the quality of the geoid models, which degrade heights and limit the application of the method. In order to provide better quality in transforming height using GNSS leveling, this research aims to develop a hybridization methodology of gravimetric geoid models EGM08, MAPGEO2015 and GEOIDSP2014 for the State of São Paulo, providing more consistent models with GNSS technology. Radial Basis Function (RBF) neural networks were used to obtain the corrector surface, based on differences between geoid model undulations and the undulations obtained by GNSS tracking in benchmarks. The experiments showed that the most suitable interpolation for correction modeling is the linear RBF. Checkpoints indicate that the geoid hybrid models feature root mean square deviation ± 0.107, ± 0.104 and ± 0.098 m, respectively. The results shows an improvement of 30 to 40% in consistencies compared with the gravimetric geoids, providing users with better quality in transformation of geometric to orthometric heights.
Hybrid Geoid Model: Theory and Application in Brazil
Directory of Open Access Journals (Sweden)
DANIEL ARANA
Full Text Available Determination of the ellipsoidal height by Global Navigation Satellite Systems (GNSS is becoming better known and used for purposes of leveling with the aid of geoid models. However, the disadvantage of this method is the quality of the geoid models, which degrade heights and limit the application of the method. In order to provide better quality in transforming height using GNSS leveling, this research aims to develop a hybridization methodology of gravimetric geoid models EGM08, MAPGEO2015 and GEOIDSP2014 for the State of São Paulo, providing more consistent models with GNSS technology. Radial Basis Function (RBF neural networks were used to obtain the corrector surface, based on differences between geoid model undulations and the undulations obtained by GNSS tracking in benchmarks. The experiments showed that the most suitable interpolation for correction modeling is the linear RBF. Checkpoints indicate that the geoid hybrid models feature root mean square deviation ± 0.107, ± 0.104 and ± 0.098 m, respectively. The results shows an improvement of 30 to 40% in consistencies compared with the gravimetric geoids, providing users with better quality in transformation of geometric to orthometric heights.
MODEL APLIKASI FIKIH MUAMALAH PADA FORMULASI HYBRID CONTRACT
Directory of Open Access Journals (Sweden)
Ali Murtadho
2013-10-01
Full Text Available Modern literatures of fiqh mu’āmalah talk alot about various contract formulation with capability of maximizing profit in shariah finance industry. This new contract modification is the synthesis among existing contracts which is formulated in such a way to be an integrated contract. This formulation is known as a hybrid contract or multicontract (al-'uqūd al-murakkabah. Some of them are, bay' bi thaman 'ājil, Ijārah muntahiyah bi ’l-tamlīk dan mushārakah mutanāqiṣah. This study intends to further describe models of hybrid contract, and explore the shari'ah principles in modern financial institutions. This study found a potential shift from the ideal values of the spirit of shari'ah into the spirit of competition based shari'ah formally.
Active diagnosis of hybrid systems - A model predictive approach
DEFF Research Database (Denmark)
Tabatabaeipour, Seyed Mojtaba; Ravn, Anders P.; Izadi-Zamanabadi, Roozbeh
2009-01-01
A method for active diagnosis of hybrid systems is proposed. The main idea is to predict the future output of both normal and faulty model of the system; then at each time step an optimization problem is solved with the objective of maximizing the difference between the predicted normal and faulty...... outputs constrained by tolerable performance requirements. As in standard model predictive control, the first element of the optimal input is applied to the system and the whole procedure is repeated until the fault is detected by a passive diagnoser. It is demonstrated how the generated excitation signal...
A Simple Hybrid Model for Short-Term Load Forecasting
Directory of Open Access Journals (Sweden)
Suseelatha Annamareddi
2013-01-01
Full Text Available The paper proposes a simple hybrid model to forecast the electrical load data based on the wavelet transform technique and double exponential smoothing. The historical noisy load series data is decomposed into deterministic and fluctuation components using suitable wavelet coefficient thresholds and wavelet reconstruction method. The variation characteristics of the resulting series are analyzed to arrive at reasonable thresholds that yield good denoising results. The constitutive series are then forecasted using appropriate exponential adaptive smoothing models. A case study performed on California energy market data demonstrates that the proposed method can offer high forecasting precision for very short-term forecasts, considering a time horizon of two weeks.
Multiobjective muffler shape optimization with hybrid acoustics modeling.
Airaksinen, Tuomas; Heikkola, Erkki
2011-09-01
This paper considers the combined use of a hybrid numerical method for the modeling of acoustic mufflers and a genetic algorithm for multiobjective optimization. The hybrid numerical method provides accurate modeling of sound propagation in uniform waveguides with non-uniform obstructions. It is based on coupling a wave based modal solution in the uniform sections of the waveguide to a finite element solution in the non-uniform component. Finite element method provides flexible modeling of complicated geometries, varying material parameters, and boundary conditions, while the wave based solution leads to accurate treatment of non-reflecting boundaries and straightforward computation of the transmission loss (TL) of the muffler. The goal of optimization is to maximize TL at multiple frequency ranges simultaneously by adjusting chosen shape parameters of the muffler. This task is formulated as a multiobjective optimization problem with the objectives depending on the solution of the simulation model. NSGA-II genetic algorithm is used for solving the multiobjective optimization problem. Genetic algorithms can be easily combined with different simulation methods, and they are not sensitive to the smoothness properties of the objective functions. Numerical experiments demonstrate the accuracy and feasibility of the model-based optimization method in muffler design. © 2011 Acoustical Society of America
Hybrid Adaptive Flight Control with Model Inversion Adaptation
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.
Probabilistic logic modeling of network reliability for hybrid network architectures
Energy Technology Data Exchange (ETDEWEB)
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.
Modeling a PV-FC-Hydrogen Hybrid Power Generation System
Directory of Open Access Journals (Sweden)
S. Javadpoor
2017-04-01
Full Text Available Electrical grid expansion onto remote areas is often not cost-effective and/or technologically feasible. Thus, isolated electrical systems are preferred in such cases. This paper focuses on a hybrid photovoltaic (PV-hydrogen/fuel cell (FC system which basic components include a PV, a FC, alkaline water electrolysis and a hydrogen gas tank. To increase the response rate, supercapacitors or small batteries are usually employed in such systems. This study focuses on the dynamics of the system. In the suggested structure, the PV is used as the main source of power. The FC is connected to the load in parallel with the PV by a transducer in order to inject the differential power while reducing power generation in relation to power consumption. An electrolyzer is used to convert the surplus power to hydrogen. This study studies a conventional hybrid photovoltaic-hydrogen/fuel cell system to evaluate different loading behaviors. Software modeling is done for the suggested hybrid system using MATLAB/SIMULINK.
Interval forecasts of a novelty hybrid model for wind speeds
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Shanshan Qin
2015-11-01
Full Text Available The utilization of wind energy, as a booming technology in the field of renewable energies, has been highly regarded around the world. Quantification of uncertainties associated with accurate wind speed forecasts is essential for regulating wind power generation and integration. However, it remains difficult work primarily due to the stochastic and nonlinear characteristics of wind speed series. Traditional models for wind speed forecasting mostly focus on generating certain predictive values, which cannot properly handle uncertainties. For quantifying potential uncertainties, a hybrid model constructed by the Cuckoo Search Optimization (CSO-based Back Propagation Neural Network (BPNN is proposed to establish wind speed interval forecasts (IFs by estimating the lower and upper bounds. The quality of IFs is assessed quantitatively using IFs coverage probability (IFCP and IFs normalized average width (IFNAW. Moreover, to assess the overall quality of IFs comprehensively, a tradeoff between informativeness (IFNAW and validity (IFCP of IFs is examined by coverage width-based criteria (CWC. As an applicative study, wind speeds from the Xinjiang Region in China are used to validate the proposed hybrid model. The results demonstrate that the proposed model can construct higher quality IFs for short-term wind speed forecasts.
Hybrid perturbation methods based on statistical time series models
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.
KNGEOID14: A national hybrid geoid model in Korea
Kang, S.; Sung, Y. M.; KIM, H.; Kim, Y. S.
2016-12-01
This study describes in brief the construction of a national hybrid geoid model in Korea, KNGEOID14, which can be used as an accurate vertical datum in/around Korea. The hybrid geoid model should be determined by fitting the gravimetric geoid to the geometric geoid undulations from GNSS/Leveling data which were presented the local vertical level. For developing the gravimetric geoid model, we determined all frequency parts (long, middle and short-frequency) of gravimetric geoid using all available data with optimal remove-restore technique based on EGM2008 reference surface. In remove-restore technique, the EGM2008 model to degree 360, RTM reduction method were used for calculating the long, middle and short-frequency part of gravimetric geoid, respectively. A number of gravity data compiled for modeling the middle-frequency part, residual geoid, containing 8,866 points gravity data on land and ocean areas. And, the DEM data gridded by 100m×100m were used for short-frequency part, is the topographic effect on the geoid generated by RTM method. The accuracy of gravimetric geoid model were evaluated by comparison with GNSS/Leveling data was about -0.362m ± 0.055m. Finally, we developed the national hybrid geoid model in Korea, KNGEOID14, corrected to gravimetric geoid with the correction term by fitting the about 1,200 GNSS/Leveling data on Korean bench marks. The correction term is modeled using the difference between GNSS/Leveling derived geoidal heights and gravimetric geoidal heights. The stochastic model used in the calculation of correction term is the LSC technique based on second-order Markov covariance function. The post-fit error (mean and std. dev.) of the KNGEOID14 model was evaluated as 0.001m ± 0.033m. Concerning the result of this study, the accurate orthometric height at any points in Korea will be easily and precisely calculated by combining the geoidal height from KNGEOID14 and ellipsoidal height from GPS observation technique.
Hybrid Compensatory-Noncompensatory Choice Sets in Semicompensatory Models
DEFF Research Database (Denmark)
Kaplan, Sigal; Bekhor, Shlomo; Shiftan, Yoram
2013-01-01
Semicompensatory models represent a choice process consisting of an elimination-based choice set formation on satisfaction of criterion thresholds and a utility-based choice. Current semicompensatory models assume a purely noncompensatory choice set formation and therefore do not support...... by a mathematical model that combines multinomial-response and ordered-response thresholds with a utility-based choice. The proposed model is applied to a stated preference experiment of off-campus rental apartment choices by students. Results demonstrate the applicability and feasibility of incorporating...... multinomial criteria that involve trade-offs between attributes at the choice set formation stage. This study proposes a novel behavioral paradigm consisting of a hybrid compensatory-noncompensatory choice set formation process, followed by compensatory choice. The behavioral paradigm is represented...
Ionocovalency and Applications 1. Ionocovalency Model and Orbital Hybrid Scales
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Yonghe Zhang
2010-11-01
Full Text Available 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.
Modeling and Simulation Based on the Hybrid System of Leasing Equipment Optimal Allocation
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Ying Tian
2015-01-01
Full Text Available Modeling of the hybrid system of leasing equipment optimal allocation and its optimal control methods are put forward based on the hybrid characteristics of succession and dispersion. After studying equipment unit’s hybrid automata model (the hybrid and basic structure, the hybrid system facing manufacture demand can be considered as the synthesis of some hybrid and basic structures, which efficiently avoid combination explosion of models due to the increase of systematic scale. On this basis, we study the hybrid and optimal control methods that meet the demand for some equipment and achieve the usage rate maximization. Following that, calculating methods of performance optimization and simulation are put forward based on the first- and second-order subsection linear model. At last, we also have made the numerical simulating calculation on the equipment’s optimal matching of some leasing company.
Assessment of the hybrid propagation model, Volume 2: Comparison with the Integrated Noise Model
2012-08-31
This is the second of two volumes of the report on the Hybrid Propagation Model (HPM), an advanced prediction model for aviation noise propagation. This volume presents comparisons of the HPM and the Integrated Noise Model (INM) for conditions of une...
A hybrid model of mammalian cell cycle regulation.
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Rajat Singhania
2011-02-01
Full Text Available The timing of DNA synthesis, mitosis and cell division is regulated by a complex network of biochemical reactions that control the activities of a family of cyclin-dependent kinases. The temporal dynamics of this reaction network is typically modeled by nonlinear differential equations describing the rates of the component reactions. This approach provides exquisite details about molecular regulatory processes but is hampered by the need to estimate realistic values for the many kinetic constants that determine the reaction rates. It is difficult to estimate these kinetic constants from available experimental data. To avoid this problem, modelers often resort to 'qualitative' modeling strategies, such as Boolean switching networks, but these models describe only the coarsest features of cell cycle regulation. In this paper we describe a hybrid approach that combines the best features of continuous differential equations and discrete Boolean networks. Cyclin abundances are tracked by piecewise linear differential equations for cyclin synthesis and degradation. Cyclin synthesis is regulated by transcription factors whose activities are represented by discrete variables (0 or 1 and likewise for the activities of the ubiquitin-ligating enzyme complexes that govern cyclin degradation. The discrete variables change according to a predetermined sequence, with the times between transitions determined in part by cyclin accumulation and degradation and as well by exponentially distributed random variables. The model is evaluated in terms of flow cytometry measurements of cyclin proteins in asynchronous populations of human cell lines. The few kinetic constants in the model are easily estimated from the experimental data. Using this hybrid approach, modelers can quickly create quantitatively accurate, computational models of protein regulatory networks in cells.
Software development infrastructure for the HYBRID modeling and simulation project
Energy Technology Data Exchange (ETDEWEB)
Epiney, Aaron S. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Kinoshita, Robert A. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Kim, Jong Suk [Idaho National Lab. (INL), Idaho Falls, ID (United States); Rabiti, Cristian [Idaho National Lab. (INL), Idaho Falls, ID (United States); Greenwood, M. Scott [Idaho National Lab. (INL), Idaho Falls, ID (United States)
2016-09-01
One of the goals of the HYBRID modeling and simulation project is to assess the economic viability of hybrid systems in a market that contains renewable energy sources like wind. The idea is that it is possible for the nuclear plant to sell non-electric energy cushions, which absorb (at least partially) the volatility introduced by the renewable energy sources. This system is currently modeled in the Modelica programming language. To assess the economics of the system, an optimization procedure is trying to find the minimal cost of electricity production. The RAVEN code is used as a driver for the whole problem. It is assumed that at this stage, the HYBRID modeling and simulation framework can be classified as non-safety “research and development” software. The associated quality level is Quality Level 3 software. This imposes low requirements on quality control, testing and documentation. The quality level could change as the application development continues.Despite the low quality requirement level, a workflow for the HYBRID developers has been defined that include a coding standard and some documentation and testing requirements. The repository performs automated unit testing of contributed models. The automated testing is achieved via an open-source python script called BuildingsP from Lawrence Berkeley National Lab. BuildingsPy runs Modelica simulation tests using Dymola in an automated manner and generates and runs unit tests from Modelica scripts written by developers. In order to assure effective communication between the different national laboratories a biweekly videoconference has been set-up, where developers can report their progress and issues. In addition, periodic face-face meetings are organized intended to discuss high-level strategy decisions with management. A second means of communication is the developer email list. This is a list to which everybody can send emails that will be received by the collective of the developers and managers
Rotating hybrid stars with the Dyson-Schwinger quark model
Wei, J.-B.; Chen, H.; Burgio, G. F.; Schulze, H.-J.
2017-08-01
We study rapidly rotating hybrid stars with the Dyson-Schwinger model for quark matter and the Brueckner-Hartree-Fock many-body theory with realistic two-body and three-body forces for nuclear matter. We determine the maximum gravitational mass, equatorial radius, and rotation frequency of stable stellar configurations by considering the constraints of the Keplerian limit and the secular axisymmetric instability, and compare with observational data. We also discuss the rotational evolution for constant baryonic mass and find a spin-up phenomenon for supramassive stars before they collapse to black holes.
On The Modelling Of Hybrid Aerostatic - Gas Journal Bearings
DEFF Research Database (Denmark)
Morosi, Stefano; Santos, Ilmar
2011-01-01
modeling for hybrid lubrication of a compressible fluid film journal bearing. Additional forces are generated by injecting pressurized air into the bearing gap through orifices located on the bearing walls. A modified form of the compressible Reynolds equation for active lubrication is derived. By solving......Gas journal bearing have been increasingly adopted in modern turbo-machinery applications, as they meet the demands of operation at higher rotational speeds, in clean environment and great efficiency. Due to the fact that gaseous lubricants, typically air, have much lower viscosity than more...
The Hybrid Airline Model. Generating Quality for Passengers
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Bogdan AVRAM
2017-12-01
Full Text Available This research aims to investigate the different strategies adopted by the airline companies in adapting to the ongoing changes while developing products and services for passengers in order to increase their yield, load factor and passenger satisfaction. Finding a balance between costs and services quality in the airline industry is a crucial task for every airline wanting to gain a competitive advantage on the market. Also, the rise of the hybrid business operating model has brought up many challenges for airlines as the line between legacy carriers and low-cost carriers is getting thinner in terms of costs and innovative ideas to create a superior product for the passengers.
What Hybrid Business Models can Teach Sustainable Supply Chain Management
DEFF Research Database (Denmark)
Bals, Lydia; Tate, Wendy L.
2017-01-01
. This chapter reflects on research that looked at the literature on hybrid business models and social entrepreneurship in order to bridge these streams of literature to literature on sustainable supply chain management. Following the literature analysis, case-based research that related specifically to social......Integrating triple bottom line (TBL; economic, social and environmental) sustainability into supply chains is a major challenge. Progress has been made to address the economic and environmental dimensions in supply chain management research however, the social dimension is still underrepresented...... management....
A Lookahead Behavior Model for Multi-Agent Hybrid Simulation
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Mei Yang
2017-10-01
Full Text Available In the military field, multi-agent simulation (MAS plays an important role in studying wars statistically. For a military simulation system, which involves large-scale entities and generates a very large number of interactions during the runtime, the issue of how to improve the running efficiency is of great concern for researchers. Current solutions mainly use hybrid simulation to gain fewer updates and synchronizations, where some important continuous models are maintained implicitly to keep the system dynamics, and partial resynchronization (PR is chosen as the preferable state update mechanism. However, problems, such as resynchronization interval selection and cyclic dependency, remain unsolved in PR, which easily lead to low update efficiency and infinite looping of the state update process. To address these problems, this paper proposes a lookahead behavior model (LBM to implement a PR-based hybrid simulation. In LBM, a minimal safe time window is used to predict the interactions between implicit models, upon which the resynchronization interval can be efficiently determined. Moreover, the LBM gives an estimated state value in the lookahead process so as to break the state-dependent cycle. The simulation results show that, compared with traditional mechanisms, LBM requires fewer updates and synchronizations.
A hybrid neural network model for noisy data regression.
Lee, Eric W M; Lim, Chee Peng; Yuen, Richard K K; Lo, S M
2004-04-01
A hybrid neural network model, based on the fusion of fuzzy adaptive resonance theory (FA ART) and the general regression neural network (GRNN), is proposed in this paper. Both FA and the GRNN are incremental learning systems and are very fast in network training. The proposed hybrid model, denoted as GRNNFA, is able to retain these advantages and, at the same time, to reduce the computational requirements in calculating and storing information of the kernels. A clustering version of the GRNN is designed with data compression by FA for noise removal. An adaptive gradient-based kernel width optimization algorithm has also been devised. Convergence of the gradient descent algorithm can be accelerated by the geometric incremental growth of the updating factor. A series of experiments with four benchmark datasets have been conducted to assess and compare effectiveness of GRNNFA with other approaches. The GRNNFA model is also employed in a novel application task for predicting the evacuation time of patrons at typical karaoke centers in Hong Kong in the event of fire. The results positively demonstrate the applicability of GRNNFA in noisy data regression problems.
Fahimi, Farzad; Yaseen, Zaher Mundher; El-shafie, Ahmed
2017-05-01
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.
Efficient Vaccine Distribution Based on a Hybrid Compartmental Model.
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Zhiwen Yu
Full Text Available 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.
Hybrid Modeling Method for a DEP Based Particle Manipulation
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Mohamad Sawan
2013-01-01
Full Text Available 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.
Hybrid modeling method for a DEP based particle manipulation.
Miled, Mohamed Amine; Gagne, Antoine; Sawan, Mohamad
2013-01-30
In this paper, a new modeling approach for Dielectrophoresis (DEP) based particle manipulation is presented. The proposed method fulfills missing links in finite element modeling between the multiphysic simulation and the biological behavior. This technique is amongst the first steps to develop a more complex platform covering several types of manipulations such as magnetophoresis and optics. The modeling approach is based on a hybrid interface using both ANSYS and MATLAB to link the propagation of the electrical field in the micro-channel to the particle motion. ANSYS is used to simulate the electrical propagation while MATLAB interprets the results to calculate cell displacement and send the new information to ANSYS for another turn. The beta version of the proposed technique takes into account particle shape, weight and its electrical properties. First obtained results are coherent with experimental results.
Hybrid quantum-classical modeling of quantum dot devices
Kantner, Markus; Mittnenzweig, Markus; Koprucki, Thomas
2017-11-01
The design of electrically driven quantum dot devices for quantum optical applications asks for modeling approaches combining classical device physics with quantum mechanics. We connect the well-established fields of semiclassical semiconductor transport theory and the theory of open quantum systems to meet this requirement. By coupling the van Roosbroeck system with a quantum master equation in Lindblad form, we introduce a new hybrid quantum-classical modeling approach, which provides a comprehensive description of quantum dot devices on multiple scales: it enables the calculation of quantum optical figures of merit and the spatially resolved simulation of the current flow in realistic semiconductor device geometries in a unified way. We construct the interface between both theories in such a way, that the resulting hybrid system obeys the fundamental axioms of (non)equilibrium thermodynamics. We show that our approach guarantees the conservation of charge, consistency with the thermodynamic equilibrium and the second law of thermodynamics. The feasibility of the approach is demonstrated by numerical simulations of an electrically driven single-photon source based on a single quantum dot in the stationary and transient operation regime.
Axelrod Model of Social Influence with Cultural Hybridization
Radillo-Díaz, Alejandro; Pérez, Luis A.; Del Castillo-Mussot, Marcelo
2012-10-01
Since cultural interactions between a pair of social agents involve changes in both individuals, we present simulations of a new model based on Axelrod's homogenization mechanism that includes hybridization or mixture of the agents' features. In this new hybridization model, once a cultural feature of a pair of agents has been chosen for the interaction, the average of the values for this feature is reassigned as the new value for both agents after interaction. Moreover, a parameter representing social tolerance is implemented in order to quantify whether agents are similar enough to engage in interaction, as well as to determine whether they belong to the same cluster of similar agents after the system has reached the frozen state. The transitions from a homogeneous state to a fragmented one decrease in abruptness as tolerance is increased. Additionally, the entropy associated to the system presents a maximum within the transition, the width of which increases as tolerance does. Moreover, a plateau was found inside the transition for a low-tolerance system of agents with only two cultural features.
A Probability-Based Hybrid User Model for Recommendation System
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Jia Hao
2016-01-01
Full Text Available With the rapid development of information communication technology, the available information or knowledge is exponentially increased, and this causes the well-known information overload phenomenon. This problem is more serious in product design corporations because over half of the valuable design time is consumed in knowledge acquisition, which highly extends the design cycle and weakens the competitiveness. Therefore, the recommender systems become very important in the domain of product domain. This research presents a probability-based hybrid user model, which is a combination of collaborative filtering and content-based filtering. This hybrid model utilizes user ratings and item topics or classes, which are available in the domain of product design, to predict the knowledge requirement. The comprehensive analysis of the experimental results shows that the proposed method gains better performance in most of the parameter settings. This work contributes a probability-based method to the community for implement recommender system when only user ratings and item topics are available.
An Interactive Personalized Recommendation System Using the Hybrid Algorithm Model
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Yan Guo
2017-10-01
Full Text Available With the rapid development of e-commerce, the contradiction between the disorder of business information and customer demand is increasingly prominent. This study aims to make e-commerce shopping more convenient, and avoid information overload, by an interactive personalized recommendation system using the hybrid algorithm model. The proposed model first uses various recommendation algorithms to get a list of original recommendation results. Combined with the customer’s feedback in an interactive manner, it then establishes the weights of corresponding recommendation algorithms. Finally, the synthetic formula of evidence theory is used to fuse the original results to obtain the final recommendation products. The recommendation performance of the proposed method is compared with that of traditional methods. The results of the experimental study through a Taobao online dress shop clearly show that the proposed method increases the efficiency of data mining in the consumer coverage, the consumer discovery accuracy and the recommendation recall. The hybrid recommendation algorithm complements the advantages of the existing recommendation algorithms in data mining. The interactive assigned-weight method meets consumer demand better and solves the problem of information overload. Meanwhile, our study offers important implications for e-commerce platform providers regarding the design of product recommendation systems.
Modelling the solar wind interaction with Mercury by a quasi-neutral hybrid model
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E. Kallio
Full Text Available Quasi-neutral hybrid model is a self-consistent modelling approach that includes positively charged particles and an electron fluid. The approach has received an increasing interest in space plasma physics research because it makes it possible to study several plasma physical processes that are difficult or impossible to model by self-consistent fluid models, such as the effects associated with the ions’ finite gyroradius, the velocity difference between different ion species, or the non-Maxwellian velocity distribution function. By now quasi-neutral hybrid models have been used to study the solar wind interaction with the non-magnetised Solar System bodies of Mars, Venus, Titan and comets. Localized, two-dimensional hybrid model runs have also been made to study terrestrial dayside magnetosheath. However, the Hermean plasma environment has not yet been analysed by a global quasi-neutral hybrid model.
In this paper we present a new quasi-neutral hybrid model developed to study various processes associated with the Mercury-solar wind interaction. Emphasis is placed on addressing advantages and disadvantages of the approach to study different plasma physical processes near the planet. The basic assumptions of the approach and the algorithms used in the new model are thoroughly presented. Finally, some of the first three-dimensional hybrid model runs made for Mercury are presented.
The resulting macroscopic plasma parameters and the morphology of the magnetic field demonstrate the applicability of the new approach to study the Mercury-solar wind interaction globally. In addition, the real advantage of the kinetic hybrid model approach is to study the property of individual ions, and the study clearly demonstrates the large potential of the approach to address these more detailed issues by a quasi-neutral hybrid model in the future.
Key words. Magnetospheric physics
2016-05-23
AFRL-AFOSR-VA-TR-2016-0200 Noise Propagation and Uncertainty Quantification in Hybrid Multiphysics Models Daniel Tartakovsky UNIVERSITY OF CALIFORNIA...2016 Title: Noise Propagation and Uncertainty Quantification in Hybrid Multi-Physics Models Subtitle: Initiation and Reaction Propagation in...and Uncertainty Quantification in Hybrid Multi-Physics Models Task: Initiation and Reaction Propagation in Energetic Materials AFOSR award: FA9550-12-1
Dynamic Modeling and Simulation of a Switched Reluctance Motor in a Series Hybrid Electric Vehicle
Siavash Sadeghi; Mojtaba Mirsalim; Arash Hassanpour Isfahani
2010-01-01
Dynamic behavior analysis of electric motors is required in order to accuratelyevaluate the performance, energy consumption and pollution level of hybrid electricvehicles. Simulation tools for hybrid electric vehicles are divided into steady state anddynamic models. Tools with steady-state models are useful for system-level analysiswhereas tools that utilize dynamic models give in-depth information about the behavior ofsublevel components. For the accurate prediction of hybrid electric vehicl...
Haase, Werner; Peng, Shia-Hui; Schwamborn, Dieter
2013-01-01
The present book contains contributions presented at the Fourth Symposium on Hybrid RANS-LES Methods, held in Beijing, China, 28-30 September 2011, being a continuation of symposia taking place in Stockholm (Sweden, 2005), in Corfu (Greece, 2007), and Gdansk (Poland, 2009). The contributions to the last two symposia were published as NNFM, Vol. 97 and Vol. 111. At the Beijing symposium, along with seven invited keynotes, another 46 papers (plus 5 posters) were presented addressing topics on Novel turbulence-resolving simulation and modelling, Improved hybrid RANS-LES methods, Comparative studies of difference modelling methods, Modelling-related numerical issues and Industrial applications.. The present book reflects recent activities and new progress made in the development and applications of hybrid RANS-LES methods in general.
A Hybrid Multiple Criteria Decision Making Model for Supplier Selection
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Chung-Min Wu
2013-01-01
Full Text Available The sustainable supplier selection would be the vital part in the management of a sustainable supply chain. In this study, a hybrid multiple criteria decision making (MCDM model is applied to select optimal supplier. The fuzzy Delphi method, which can lead to better criteria selection, is used to modify criteria. Considering the interdependence among the selection criteria, analytic network process (ANP is then used to obtain their weights. To avoid calculation and additional pairwise comparisons of ANP, a technique for order preference by similarity to ideal solution (TOPSIS is used to rank the alternatives. The use of a combination of the fuzzy Delphi method, ANP, and TOPSIS, proposing an MCDM model for supplier selection, and applying these to a real case are the unique features of this study.
Hybrid Model GSTAR-SUR-NN For Precipitation Data
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Agus Dwi Sulistyono
2016-05-01
Full Text Available Spatio-temporal model that have been developed such as Space-Time Autoregressive (STAR model, Generalized Space-Time Autoregressive (GSTAR, GSTAR-OLS and GSTAR-SUR. Besides spatio-temporal phenomena, in daily life, we often find nonlinear phenomena, uncommon patterns and unidentified characteristics of the data. One of current developed nonlinear model is a neural network. This study is conducted to form a hybrid model GSTAR-SUR-NN to develop spatio-temporal model that has better prediction. This research is conducted on ten-daily rainfall data at 2005 - 2015 for Blimbing, Singosari, Karangploso, Dau, and Wagir region. Based on the results of this research, indicated that the accuracy of GSTAR ((1, 1,2,3,12,36-SUR model used cross-covariance weight has relatively similar to GSTAR ((1, 1,2,3 , 12.36-SUR-NN (25-14-5 for Blimbing and Singosari region with 5% error level. While Karangploso, Dau, and Wagir, GSTAR ((1, 1,2,3,12,36-SUR-NN (25-14-5 model has better accuracy in predicting the precipitation at three locations with the value of R2prediction for each location is 0.992, 0.580, and 0.474.
Hybrid model decomposition of speech and noise in a radial basis function neural model framework
DEFF Research Database (Denmark)
Sørensen, Helge Bjarup Dissing; Hartmann, Uwe
1994-01-01
The aim of the paper is to focus on a new approach to automatic speech recognition in noisy environments where the noise has either stationary or non-stationary statistical characteristics. The aim is to perform automatic recognition of speech in the presence of additive car noise. The technique...... applied is based on a combination of the hidden Markov model (HMM) decomposition method, for speech recognition in noise, developed by Varga and Moore (1990) from DRA and the hybrid (HMM/RBF) recognizer containing hidden Markov models and radial basis function (RBF) neural networks, developed by Singer...... and Lippmann (1992) from MIT Lincoln Lab. The present authors modified the hybrid recognizer to fit into the decomposition method to achieve high performance speech recognition in noisy environments. The approach has been denoted the hybrid model decomposition method and it provides an optimal method...
A hybrid deformable model for simulating prostate brachytherapy
Levin, David; Fenster, Aaron; Ladak, Hanif M.
2006-03-01
Ultrasound (US) guided prostate brachytherapy is a minimally invasive form of cancer treatment during which a needle is used to insert radioactive seeds into the prostate at pre-planned positions. Interaction with the needle can cause the prostate to deform and this can lead to inaccuracy in seed placement. Virtual reality (VR) simulation could provide a way for surgical residents to practice compensating for these deformations. To facilitate such a tool, we have developed a hybrid deformable model that combines ChainMail distance constraints with mass-spring physics to provide realistic, yet customizable deformations. Displacements generated by the model were used to warp a baseline US image to simulate an acquired US sequence. The algorithm was evaluated using a gelatin phantom with a Young's modulus approximately equal to that of the prostate (60 kPa). A 2D US movie was acquired while the phantom underwent needle insertion and inter-frame displacements were calculated using normalized cross correlation. The hybrid model was used to simulate the same needle insertion and the two sets of displacements were compared on a frame-by-frame basis. The average perpixel displacement error was 0.210 mm. A simulation rate of 100 frames per second was achieved using a 1000 element triangular mesh while warping a 300x400 pixel US image on an AMD Athlon 1.1 Ghz computer with 1 GB of RAM and an ATI Radeon 9800 Pro graphics card. These results show that this new deformable model can provide an accurate solution to the problem of simulating real-time prostate brachytherapy.
Modeling integrated cellular machinery using hybrid Petri-Boolean networks.
Directory of Open Access Journals (Sweden)
Natalie Berestovsky
Full Text Available The behavior and phenotypic changes of cells are governed by a cellular circuitry that represents a set of biochemical reactions. Based on biological functions, this circuitry is divided into three types of networks, each encoding for a major biological process: signal transduction, transcription regulation, and metabolism. This division has generally enabled taming computational complexity dealing with the entire system, allowed for using modeling techniques that are specific to each of the components, and achieved separation of the different time scales at which reactions in each of the three networks occur. Nonetheless, with this division comes loss of information and power needed to elucidate certain cellular phenomena. Within the cell, these three types of networks work in tandem, and each produces signals and/or substances that are used by the others to process information and operate normally. Therefore, computational techniques for modeling integrated cellular machinery are needed. In this work, we propose an integrated hybrid model (IHM that combines Petri nets and Boolean networks to model integrated cellular networks. Coupled with a stochastic simulation mechanism, the model simulates the dynamics of the integrated network, and can be perturbed to generate testable hypotheses. Our model is qualitative and is mostly built upon knowledge from the literature and requires fine-tuning of very few parameters. We validated our model on two systems: the transcriptional regulation of glucose metabolism in human cells, and cellular osmoregulation in S. cerevisiae. The model produced results that are in very good agreement with experimental data, and produces valid hypotheses. The abstract nature of our model and the ease of its construction makes it a very good candidate for modeling integrated networks from qualitative data. The results it produces can guide the practitioner to zoom into components and interconnections and investigate them
Modelling Shallow Water Wakes Using a Hybrid Turbulence Model
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Clemente Rodriguez-Cuevas
2014-01-01
Full Text Available A numerical research with different turbulence models for shallow water equations was carried out. This was done in order to investigate which model has the ability to reproduce more accurately the wakes produced by the shock of the water hitting a submerged island inside a canal. The study of this phenomenon is important for the numerical methods application advancement in the simulation of free surface flows since these models involve a number of simplifications and assumptions that can have a significant impact on the numerical solutions quality and thus can not reproduce correctly the physical phenomenon. The numerical experiments were carried out on an experimental case under controlled conditions, consisting of a channel with a submerged conical island. The numerical scheme is based on the Eulerian-Lagrangian finite volume method with four turbulence models, three mixing lengths (ml, and one joining k-ϵ on the horizontal axis with a mixing-length model (ml on the vertical axis. The experimental results show that a k-ϵ with ml turbulence model makes it possible to approach the experimental results in a more qualitative manner. We found that when using only a k-ϵ model in the vertical and horizontal direction, the numerical results overestimate the experimental data. Additionally the computing time is reduced by simplifying the turbulence model.
A new approach to flow simulation using hybrid models
Solgi, Abazar; Zarei, Heidar; Nourani, Vahid; Bahmani, Ramin
2017-11-01
The necessity of flow prediction in rivers, for proper management of water resource, and the need for determining the inflow to the dam reservoir, designing efficient flood warning systems and so forth, have always led water researchers to think about models with high-speed response and low error. In the recent years, the development of Artificial Neural Networks and Wavelet theory and using the combination of models help researchers to estimate the river flow better and better. In this study, daily and monthly scales were used for simulating the flow of Gamasiyab River, Nahavand, Iran. The first simulation was done using two types of ANN and ANFIS models. Then, using wavelet theory and decomposing input signals of the used parameters, sub-signals were obtained and were fed into the ANN and ANFIS to obtain hybrid models of WANN and WANFIS. In this study, in addition to the parameters of precipitation and flow, parameters of temperature and evaporation were used to analyze their effects on the simulation. The results showed that using wavelet transform improved the performance of the models in both monthly and daily scale. However, it had a better effect on the monthly scale and the WANFIS was the best model.
Tang, Xiaolin; Yang, Wei; Hu, Xiaosong; Zhang, Dejiu
2017-02-01
In this study, based on our previous work, a novel simplified torsional vibration dynamic model is established to study the torsional vibration characteristics of a compound planetary hybrid propulsion system. The main frequencies of the hybrid driveline are determined. In contrast to vibration characteristics of the previous 16-degree of freedom model, the simplified model can be used to accurately describe the low-frequency vibration property of this hybrid powertrain. This study provides a basis for further vibration control of the hybrid powertrain during the process of engine start/stop.
Dynamic Modeling and Simulation on a Hybrid Power System for Electric Vehicle Applications
Hong-Wen He; Rui Xiong; Yu-Hua Chang
2010-01-01
Hybrid power systems, formed by combining high-energy-density batteries and high-power-density ultracapacitors in appropriate ways, provide high-performance and high-efficiency power systems for electric vehicle applications. This paper first establishes dynamic models for the ultracapacitor, the battery and a passive hybrid power system, and then based on the dynamic models a comparative simulation between a battery only power system and the proposed hybrid power system was done under the UD...
Modeling and simulation of a hybrid ship power system
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.
Applying a Hybrid MCDM Model for Six Sigma Project Selection
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Fu-Kwun Wang
2014-01-01
Full Text Available Six Sigma is a project-driven methodology; the projects that provide the maximum financial benefits and other impacts to the organization must be prioritized. Project selection (PS is a type of multiple criteria decision making (MCDM problem. In this study, we present a hybrid MCDM model combining the decision-making trial and evaluation laboratory (DEMATEL technique, analytic network process (ANP, and the VIKOR method to evaluate and improve Six Sigma projects for reducing performance gaps in each criterion and dimension. We consider the film printing industry of Taiwan as an empirical case. The results show that our study not only can use the best project selection, but can also be used to analyze the gaps between existing performance values and aspiration levels for improving the gaps in each dimension and criterion based on the influential network relation map.
Exploring the lambda model of the hybrid superstring
Energy Technology Data Exchange (ETDEWEB)
Schmidtt, David M. [Instituto de Física Teórica IFT/UNESP,Rua Dr. Bento Teobaldo Ferraz 271, Bloco II, CEP 01140-070, São Paulo-SP (Brazil)
2016-10-26
The purpose of this contribution is to initiate the study of integrable deformations for different superstring theory formalisms that manifest the property of (classical) integrability. In this paper we choose the hybrid formalism of the superstring in the background AdS{sub 2}×S{sup 2} and explore in detail the most immediate consequences of its λ-deformation. The resulting action functional corresponds to the λ-model of the matter part of the fairly more sophisticated pure spinor formalism, which is also known to be classical integrable. In particular, the deformation preserves the integrability and the one-loop conformal invariance of its parent theory, hence being a marginal deformation.
HYBRID MODELS FOR TRAJECTORY ERROR MODELLING IN URBAN ENVIRONMENTS
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E. Angelatsa
2016-06-01
Full Text Available 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.
Bounded Model Checking and Inductive Verification of Hybrid Discrete-Continuous Systems
DEFF Research Database (Denmark)
Becker, Bernd; Behle, Markus; Eisenbrand, Fritz
2004-01-01
We present a concept to signicantly advance the state of the art for bounded model checking (BMC) and inductive verication (IV) of hybrid discrete-continuous systems. Our approach combines the expertise of partners coming from dierent domains, like hybrid systems modeling and digital circuit...
Control-relevant modeling and simulation of a SOFC-GT hybrid system
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Rambabu Kandepu
2006-07-01
Full Text Available In this paper, control-relevant models of the most important components in a SOFC-GT hybrid system are described. Dynamic simulations are performed on the overall hybrid system. The model is used to develop a simple control structure, but the simulations show that more elaborate control is needed.
Pedagogy and Process: A Case Study of Writing in a Hybrid Learning Model
Keiner, Jason F.
2017-01-01
This qualitative case study explored the perceived experiences and outcomes of writing in a hybrid model of instruction in a large suburban high school. In particular, the impact of a hybrid model on the writing process and on future writing performance were examined. In addition, teacher expectation and teacher attitude and their impact upon…
3D hybrid modelling of vascular network formation.
Perfahl, Holger; Hughes, Barry D; Alarcón, Tomás; Maini, Philip K; Lloyd, Mark C; Reuss, Matthias; Byrne, Helen M
2017-02-07
We develop an off-lattice, agent-based model to describe vasculogenesis, the de novo formation of blood vessels from endothelial progenitor cells during development. The endothelial cells that comprise our vessel network are viewed as linearly elastic spheres that move in response to the forces they experience. We distinguish two types of endothelial cells: vessel elements are contained within the network and tip cells are located at the ends of vessels. Tip cells move in response to mechanical forces caused by interactions with neighbouring vessel elements and the local tissue environment, chemotactic forces and a persistence force which accounts for their tendency to continue moving in the same direction. Vessel elements are subject to similar mechanical forces but are insensitive to chemotaxis. An angular persistence force representing interactions with the local tissue is introduced to stabilise buckling instabilities caused by cell proliferation. Only vessel elements proliferate, at rates which depend on their degree of stretch: elongated elements have increased rates of proliferation, and compressed elements have reduced rates. Following division, the fate of the new cell depends on the local mechanical environment: the probability of forming a new sprout is increased if the parent vessel is highly compressed and the probability of being incorporated into the parent vessel increased if the parent is stretched. Simulation results reveal that our hybrid model can reproduce the key qualitative features of vasculogenesis. Extensive parameter sensitivity analyses show that significant changes in network size and morphology are induced by varying the chemotactic sensitivity of tip cells, and the sensitivities of the proliferation rate and the sprouting probability to mechanical stretch. Varying the chemotactic sensitivity directly influences the directionality of the networks. The degree of branching, and thereby the density of the networks, is influenced by the
Status and modeling improvements of hybrid wind/PV/diesel power systems for Brazilian applications
Energy Technology Data Exchange (ETDEWEB)
McGowan, J.G.; Manwell, J.F.; Avelar, C. [Univ. of Massachusetts, Amherst, MA (United States); Taylor, R. [National Renewable Energy Lab., Golden, CO (United States)
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. Copyright © 2015 Elsevier Ltd. All rights reserved.
Hybrid Quantization: From Bianchi I to the Gowdy Model
Martín-Benito, Mercedes; Wilson-Ewing, Edward
2010-01-01
The Gowdy cosmologies are vacuum solutions to the Einstein equations which possess two space-like Killing vectors and whose spatial sections are compact. We consider the simplest of these cosmological models: the case where the spatial topology is that of a three-torus and the gravitational waves are linearly polarized. The subset of homogeneous solutions to this Gowdy model are vacuum Bianchi I spacetimes with a three-torus topology. We deepen the analysis of the loop quantization of these Bianchi I universes adopting the improved dynamics scheme put forward recently by Ashtekar and Wilson-Ewing. Then, we revisit the hybrid quantization of the Gowdy $T^3$ cosmologies by combining this loop quantum cosmology description with a Fock quantization of the inhomogeneities over the homogeneous Bianchi I background. We show that, in vacuo, the Hamiltonian constraint of both the Bianchi I and the Gowdy models can be regarded as an evolution equation with respect to the volume of the Bianchi I universe. This evolution...
A. Weiskittel; D. Maguire; R. Monserud
2007-01-01
Hybrid models offer the opportunity to improve future growth projections by combining advantages of both empirical and process-based modeling approaches. Hybrid models have been constructed in several regions and their performance relative to a purely empirical approach has varied. A hybrid model was constructed for intensively managed Douglas-fir plantations in the...
Modeling, hybridization, and optimal charging of electrical energy storage systems
Parvini, Yasha
The rising rate of global energy demand alongside the dwindling fossil fuel resources has motivated research for alternative and sustainable solutions. Within this area of research, electrical energy storage systems are pivotal in applications including electrified vehicles, renewable power generation, and electronic devices. The approach of this dissertation is to elucidate the bottlenecks of integrating supercapacitors and batteries in energy systems and propose solutions by the means of modeling, control, and experimental techniques. In the first step, the supercapacitor cell is modeled in order to gain fundamental understanding of its electrical and thermal dynamics. The dependence of electrical parameters on state of charge (SOC), current direction and magnitude (20-200 A), and temperatures ranging from -40°C to 60°C was embedded in this computationally efficient model. The coupled electro-thermal model was parameterized using specifically designed temporal experiments and then validated by the application of real world duty cycles. Driving range is one of the major challenges of electric vehicles compared to combustion vehicles. In order to shed light on the benefits of hybridizing a lead-acid driven electric vehicle via supercapacitors, a model was parameterized for the lead-acid battery and combined with the model already developed for the supercapacitor, to build the hybrid battery-supercapacitor model. A hardware in the loop (HIL) setup consisting of a custom built DC/DC converter, micro-controller (muC) to implement the power management strategy, 12V lead-acid battery, and a 16.2V supercapacitor module was built to perform the validation experiments. Charging electrical energy storage systems in an efficient and quick manner, motivated to solve an optimal control problem with the objective of maximizing the charging efficiency for supercapacitors, lead-acid, and lithium ion batteries. Pontryagins minimum principle was used to solve the problems
Assessment of the hybrid propagation model, Volume 1: Analysis of noise propagation effects
2012-08-31
This is the first of two volumes of a report on the Hybrid Propagation Model (HPM), an advanced prediction model for aviation noise propagation. This volume presents the noise level predictions for eleven different sets of propagation conditions, run...
Modelling of a Hybrid UAV Using Test Flight Data
Smeur, E.J.J.; Chu, Q.P.; De Croon, G.C.H.E.; Remes, B.; De Wagter, C.; Van der Horst, E
2014-01-01
The concept of an aircraft capable of both hover as well as fast forward flight (hybrid) has recently been implemented on unmanned aerial vehicles (UAV). Hybrid UAVs combine hover capability with long range and endurance. As UAVs are often required to operate without human intervention, there is a
Development of hybrid 3-D hydrological modeling for the NCAR Community Earth System Model (CESM)
Energy Technology Data Exchange (ETDEWEB)
Zeng, Xubin [Univ. of Arizona, Tucson, AZ (United States); Troch, Peter [Univ. of Arizona, Tucson, AZ (United States); Pelletier, Jon [Univ. of Arizona, Tucson, AZ (United States); Niu, Guo-Yue [Univ. of Arizona, Tucson, AZ (United States); Gochis, David [NCAR Research Applications Lab., Boulder, CO (United States)
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).
Dynamic Hybrid Model for Short-Term Electricity Price Forecasting
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Marin Cerjan
2014-05-01
Full Text Available Accurate forecasting tools are essential in the operation of electric power systems, especially in deregulated electricity markets. Electricity price forecasting is necessary for all market participants to optimize their portfolios. In this paper we propose a hybrid method approach for short-term hourly electricity price forecasting. The paper combines statistical techniques for pre-processing of data and a multi-layer (MLP neural network for forecasting electricity price and price spike detection. Based on statistical analysis, days are arranged into several categories. Similar days are examined by correlation significance of the historical data. Factors impacting the electricity price forecasting, including historical price factors, load factors and wind production factors are discussed. A price spike index (CWI is defined for spike detection and forecasting. Using proposed approach we created several forecasting models of diverse model complexity. The method is validated using the European Energy Exchange (EEX electricity price data records. Finally, results are discussed with respect to price volatility, with emphasis on the price forecasting accuracy.
A hybrid simulation model for a stable auroral arc
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P. Janhunen
Full Text Available We present a new type of hybrid simulation model, intended to simulate a single stable auroral arc in the latitude/altitude plane. The ionospheric ions are treated as particles, the electrons are assumed to follow a Boltzmann response and the magnetospheric ions are assumed to be so hot that they form a background population unaffected by the electric fields that arise. The system is driven by assumed parallel electron energisation causing a primary negative charge cloud and an associated potential structure to build up. The results show how a closed potential structure and density depletion of an auroral arc build up and how they decay after the driver is turned off. The model also produces upgoing energetic ion beams and predicts strong static perpendicular electric fields to be found in a relatively narrow altitude range (~ 5000–11 000 km.
Key words. Magnetospheric physics (magnetosphere-ionosphere interactions; auroral phenomena – Space plasma physics (numerical simulation studies
Hybrid CMS methods with model reduction for assembly of structures
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.
Thermal equilibrium solution to new model of bipolar hybrid quantum hydrodynamics
Di Michele, Federica; Mei, Ming; Rubino, Bruno; Sampalmieri, Rosella
2017-08-01
In this paper we study the hybrid quantum hydrodynamic model for nano-sized bipolar semiconductor devices in thermal equilibrium. By introducing a hybrid version of the Bhom potential, we derive a bipolar hybrid quantum hydrodynamic model, which is able to account for quantum effects in a localized region of the device for both electrons and holes. Coupled with Poisson equation for the electric potential, the steady-state system is regionally degenerate in its ellipticity, due to the quantum effect only in part of the device. This regional degeneracy of ellipticity makes the study more challenging. The main purpose of the paper is to investigate the existence and uniqueness of the weak solutions to this new type of equations. We first establish the uniform boundedness of the smooth solutions to the modified bipolar quantum hydrodynamic model by the variational method, then we use the compactness technique to prove the existence of weak solutions to the original hybrid system by taking hybrid limit. In particular, we account for two different kinds of hybrid behaviour. We perform the first hybrid limit when both electrons and holes behave quantum in a given region of the device, and the second one when only one carrier exhibits hybrid behaviour, whereas the other one is presented classically in the whole domain. The semi-classical limit results are also obtained. Finally, the theoretical results are tested numerically on a simple toy model.
J.J.H. Fey
1996-01-01
textabstractControl and verification of hybrid systems is studied using two industrial examples. The hybrid models of a conveyor-belt and of a biochemical plant for the production of ethanol are specified in the formalism $chi .$ A verification of the closed-loop systems for those examples,
Hybrid model for forecasting time series with trend, seasonal and salendar variation patterns
Suhartono; Rahayu, S. P.; Prastyo, D. D.; Wijayanti, D. G. P.; Juliyanto
2017-09-01
Most of the monthly time series data in economics and business in Indonesia and other Moslem countries not only contain trend and seasonal, but also affected by two types of calendar variation effects, i.e. the effect of the number of working days or trading and holiday effects. The purpose of this research is to develop a hybrid model or a combination of several forecasting models to predict time series that contain trend, seasonal and calendar variation patterns. This hybrid model is a combination of classical models (namely time series regression and ARIMA model) and/or modern methods (artificial intelligence method, i.e. Artificial Neural Networks). A simulation study was used to show that the proposed procedure for building the hybrid model could work well for forecasting time series with trend, seasonal and calendar variation patterns. Furthermore, the proposed hybrid model is applied for forecasting real data, i.e. monthly data about inflow and outflow of currency at Bank Indonesia. The results show that the hybrid model tend to provide more accurate forecasts than individual forecasting models. Moreover, this result is also in line with the third results of the M3 competition, i.e. the hybrid model on average provides a more accurate forecast than the individual model.
A global hybrid coupled model based on Atmosphere-SST feedbacks
Cimatoribus, Andrea A; Dijkstra, Henk A
2011-01-01
A global hybrid coupled model is developed, with the aim of studying the effects of ocean-atmosphere feedbacks on the stability of the Atlantic meridional overturning circulation. The model includes a global ocean general circulation model and a statistical atmosphere model. The statistical atmosphere model is based on linear regressions of data from a fully coupled climate model on sea surface temperature both locally and hemispherically averaged, being the footprint of Atlantic meridional overturning variability. It provides dynamic boundary conditions to the ocean model for heat, freshwater and wind-stress. A basic but consistent representation of ocean-atmosphere feedbacks is captured in the hybrid coupled model and it is more than ten times faster than the fully coupled climate model. The hybrid coupled model reaches a steady state with a climate close to the one of the fully coupled climate model, and the two models also have a similar response (collapse) of the Atlantic meridional overturning circulati...
Concept analysis of moral courage in nursing: A hybrid model.
Sadooghiasl, Afsaneh; Parvizy, Soroor; Ebadi, Abbas
2018-02-01
Moral courage is one of the most fundamental virtues in the nursing profession, however, little attention has been paid to it. As a result, no exact and clear definition of moral courage has ever been accessible. This study is carried out for the purposes of defining and clarifying its concept in the nursing profession. This study used a hybrid model of concept analysis comprising three phases, namely, a theoretical phase, field work phase, and a final analysis phase. To find relevant literature, electronic search of valid databases was utilized using keywords related to the concept of courage. Field work data were collected over an 11 months' time period from 2013 to 2014. In the field work phase, in-depth interviews were performed with 10 nurses. The conventional content analysis was used in two theoretical and field work phases using Graneheim and Lundman stages, and the results were combined in the final analysis phase. Ethical consideration: Permission for this study was obtained from the ethics committee of Tehran University of Medical Sciences. Oral and written informed consent was received from the participants. From the sum of 750 gained titles in theoretical phase, 26 texts were analyzed. The analysis resulted in 494 codes in text analysis and 226 codes in interview analysis. The literature review in the theoretical phase revealed two features of inherent-transcendental characteristics, two of which possessed a difficult nature. Working in the field phase added moral self-actualization characteristic, rationalism, spiritual beliefs, and scientific-professional qualifications to the feature of the concept. Moral courage is a pure and prominent characteristic of human beings. The antecedents of moral courage include model orientation, model acceptance, rationalism, individual excellence, acquiring academic and professional qualification, spiritual beliefs, organizational support, organizational repression, and internal and external personal barriers
Predicting System Accidents with Model Analysis During Hybrid Simulation
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.
Magnetic equivalent circuit model for unipolar hybrid excitation synchronous machine
Kupiec Emil; Przyborowski Włodzimierz
2015-01-01
Lately, there has been increased interest in hybrid excitation electrical machines. Hybrid excitation is a construction that combines permanent magnet excitation with wound field excitation. Within the general classification, these machines can be classified as modified synchronous machines or inductor machines. These machines may be applied as motors and generators. The complexity of electromagnetic phenomena which occur as a result of coupling of magnetic fluxes of separate excitation syste...
Dynamic Modeling and Simulation on a Hybrid Power System for Electric Vehicle Applications
Directory of Open Access Journals (Sweden)
Hong-Wen He
2010-11-01
Full Text Available Hybrid power systems, formed by combining high-energy-density batteries and high-power-density ultracapacitors in appropriate ways, provide high-performance and high-efficiency power systems for electric vehicle applications. This paper first establishes dynamic models for the ultracapacitor, the battery and a passive hybrid power system, and then based on the dynamic models a comparative simulation between a battery only power system and the proposed hybrid power system was done under the UDDS (Urban Dynamometer Driving Schedule. The simulation results showed that the hybrid power system could greatly optimize and improve the efficiency of the batteries and their dynamic current was also decreased due to the participation of the ultracapacitors, which would have a good influence on batteries’ cycle life. Finally, the parameter matching for the passive hybrid power system was studied by simulation and comparisons.
HyLTL: a temporal logic for model checking hybrid systems
Directory of Open Access Journals (Sweden)
Davide Bresolin
2013-08-01
Full Text Available The model-checking problem for hybrid systems is a well known challenge in the scientific community. Most of the existing approaches and tools are limited to safety properties only, or operates by transforming the hybrid system to be verified into a discrete one, thus loosing information on the continuous dynamics of the system. In this paper we present a logic for specifying complex properties of hybrid systems called HyLTL, and we show how it is possible to solve the model checking problem by translating the formula into an equivalent hybrid automaton. In this way the problem is reduced to a reachability problem on hybrid automata that can be solved by using existing tools.
Application of a New Hybrid Fuzzy AHP Model to the Location Choice
Directory of Open Access Journals (Sweden)
Chien-Chang Chou
2013-01-01
Full Text Available The purpose of this paper is to propose a new hybrid fuzzy Analytic Hierarchy Process (AHP algorithm to deal with the decision-making problems in an uncertain and multiple-criteria environment. In this study, the proposed hybrid fuzzy AHP model is applied to the location choices of international distribution centers in international ports from the view of multiple-nation corporations. The results show that the proposed new hybrid fuzzy AHP model is an appropriate tool to solve the decision-making problems in an uncertain and multiple-criteria environment.
Doubly hybrid density functional xDH-PBE0 from a parameter-free global hybrid model PBE0
Zhang, Igor Ying; Su, Neil Qiang; Brémond, Éric A. G.; Adamo, Carlo; Xu, Xin
2012-05-01
Following the XYG3 model which uses orbitals and density from B3LYP, an empirical doubly hybrid (DH) functional is developed by using inputs from PBE0. This new functional, named xDH-PBE0, has been tested on a number of different molecular properties, including atomization energies, bond dissociation enthalpies, reaction barrier heights, and nonbonded interactions. From the results obtained, xDH-PBE0 not only displays a significant improvement with respect to the parent PBE0, but also shows a performance that is comparable to XYG3. Arguably, while PBE0 is a parameter-free global hybrid (GH) functional, the B3LYP GH functional contains eight fit parameters. From a more general point of view, the present work points out that reliable and general-purpose DHs can be obtained with a limited number of fit parameters.
Hybrid Electric Vehicle Experimental Model with CAN Network Real Time Control
Directory of Open Access Journals (Sweden)
RATOI, M.
2010-05-01
Full Text Available In this paper an experimental model with a distributed control system of a hybrid electrical vehicle is presented. A communication CAN network of high speed (1 Mbps assures a distributed control of the all components. The modeling and the control of different operating regimes are realized on an experimental test-bench of a hybrid electrical vehicle. The experimental results concerning the variations of the mains variables (currents, torques, speeds are presented.
Mathematical modeling of drying behavior of cashew in a solar biomass hybrid dryer
Directory of Open Access Journals (Sweden)
S. Dhanushkodi
2017-12-01
Full Text Available The main objective of this study is to analyze the drying behavior of cashew nut experimentally in a solar biomass hybrid dryer using mathematical models. Suitability of fifteen different mathematical drying models available in the literature is used to describe the drying characteristics of cashew. Experimental data of moisture ratio, temperature and relative humidity obtained from different dryer conditions were fitted to the various empirical drying models. The performance of the drying model was compared based on their correlation co-efficient (R2, Root Mean Square Error (RMSE and Reduced Chi-Square (Ï2 between the observed moisture ratios. The two terms and Midilli models showed the best fit under solar drying. Page model was found to be the best model for describing the thin layer drying behavior of cashew for biomass drying and hybrid drying. Keywords: Drying models, Solar drying, Biomass drying, Hybrid drying, Cashew kernel moisture ratio
Bariotakis, Michael; Koutroumpa, Konstantina; Karousou, Regina; Pirintsos, Stergios A
2016-12-01
The role of environment and the relative significance of endogenous versus exogenous selection in shaping hybrid zones have been crucial issues in the studies of hybridization. Recent advances in ecological niche modeling (ENM) offer new methodological tools, especially in combination with the genotyping of individuals in the hybrid zone. Here, we study the hybrid zone between the widely known spices Origanum onites and Origanum vulgare ssp. hirtum in Crete. We analyze the genetic structure of both parental taxa and their hybrid Origanum × intercendens using AFLP markers on 15 sympatric and 12 allopatric populations and employ ecological niche modeling and niche similarity tests to study their niche patterns. We complement these analyses with seed viability measurements. Our study revealed that the hybridizing taxa O. onites and O. vulgare ssp. hirtum and the resulting genotypic classes showed geographical and environmental niche similarities based on the predictions of ENMs and the subsequent similarity tests. The occurrence of the hybrid zone is not directly dependent on environmental factors which favor the fitness of the hybrid compared to the parental taxa, but rather on aspects such as historical factors and management practices, which may contribute to the localization and maintenance of the contact zone between parental species. Our results suggest that if a minimum required niche differentiation between genotypic classes is not achieved, environmental dependence might not have a prominent role on the outcome of the hybridization.
Frog: Asynchronous Graph Processing on GPU with Hybrid Coloring Model
Energy Technology Data Exchange (ETDEWEB)
Shi, Xuanhua; Luo, Xuan; Liang, Junling; Zhao, Peng; Di, Sheng; He, Bingsheng; Jin, Hai
2018-01-01
GPUs have been increasingly used to accelerate graph processing for complicated computational problems regarding graph theory. Many parallel graph algorithms adopt the asynchronous computing model to accelerate the iterative convergence. Unfortunately, the consistent asynchronous computing requires locking or atomic operations, leading to significant penalties/overheads when implemented on GPUs. As such, coloring algorithm is adopted to separate the vertices with potential updating conflicts, guaranteeing the consistency/correctness of the parallel processing. Common coloring algorithms, however, may suffer from low parallelism because of a large number of colors generally required for processing a large-scale graph with billions of vertices. We propose a light-weight asynchronous processing framework called Frog with a preprocessing/hybrid coloring model. The fundamental idea is based on Pareto principle (or 80-20 rule) about coloring algorithms as we observed through masses of realworld graph coloring cases. We find that a majority of vertices (about 80%) are colored with only a few colors, such that they can be read and updated in a very high degree of parallelism without violating the sequential consistency. Accordingly, our solution separates the processing of the vertices based on the distribution of colors. In this work, we mainly answer three questions: (1) how to partition the vertices in a sparse graph with maximized parallelism, (2) how to process large-scale graphs that cannot fit into GPU memory, and (3) how to reduce the overhead of data transfers on PCIe while processing each partition. We conduct experiments on real-world data (Amazon, DBLP, YouTube, RoadNet-CA, WikiTalk and Twitter) to evaluate our approach and make comparisons with well-known non-preprocessed (such as Totem, Medusa, MapGraph and Gunrock) and preprocessed (Cusha) approaches, by testing four classical algorithms (BFS, PageRank, SSSP and CC). On all the tested applications and
Stochastic hybrid model of spontaneous dendritic NMDA spikes.
Bressloff, Paul C; Newby, Jay M
2014-02-01
Following recent advances in imaging techniques and methods of dendritic stimulation, active voltage spikes have been observed in thin dendritic branches of excitatory pyramidal neurons, where the majority of synapses occur. The generation of these dendritic spikes involves both Na(+) ion channels and M-methyl-D-aspartate receptor (NMDAR) channels. During strong stimulation of a thin dendrite, the resulting high levels of glutamate, the main excitatory neurotransmitter in the central nervous system and an NMDA agonist, modify the current-voltage (I-V) characteristics of an NMDAR so that it behaves like a voltage-gated Na(+) channel. Hence, the NMDARs can fire a regenerative dendritic spike, just as Na(+) channels support the initiation of an action potential following membrane depolarization. However, the duration of the dendritic spike is of the order 100 ms rather than 1 ms, since it involves slow unbinding of glutamate from NMDARs rather than activation of hyperpolarizing K(+) channels. It has been suggested that dendritic NMDA spikes may play an important role in dendritic computations and provide a cellular substrate for short-term memory. In this paper, we consider a stochastic, conductance-based model of dendritic NMDA spikes, in which the noise originates from the stochastic opening and closing of a finite number of Na(+) and NMDA receptor ion channels. The resulting model takes the form of a stochastic hybrid system, in which membrane voltage evolves according to a piecewise deterministic dynamics that is coupled to a jump Markov process describing the opening and closing of the ion channels. We formulate the noise-induced initiation and termination of a dendritic spike in terms of a first-passage time problem, under the assumption that glutamate unbinding is negligible, which we then solve using a combination of WKB methods and singular perturbation theory. Using a stochastic phase-plane analysis we then extend our analysis to take proper account of the
Addressing Cognitive Processes in e-learning: TSOI Hybrid Learning Model
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…
Model-based health monitoring of hybrid systems
Wang, Danwei; Low, Chang Boon; Arogeti, Shai
2013-01-01
Offers in-depth comprehensive study on health monitoring for hybrid systems Includes new concepts, such as GARR, mode tracking and multiple failure prognosis Contains many examples, making the developed techniques easily understandable and accessible Introduces state-of-the-art algorithms and methodologies from experienced researchers
FISH-ing for Genes: Modeling Fluorescence "in situ" Hybridization
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…
AMITIS: A 3D GPU-Based Hybrid-PIC Model for Space and Plasma Physics
Fatemi, Shahab; Poppe, Andrew R.; Delory, Gregory T.; Farrell, William M.
2017-05-01
We have developed, for the first time, an advanced modeling infrastructure in space simulations (AMITIS) with an embedded three-dimensional self-consistent grid-based hybrid model of plasma (kinetic ions and fluid electrons) that runs entirely on graphics processing units (GPUs). The model uses NVIDIA GPUs and their associated parallel computing platform, CUDA, developed for general purpose processing on GPUs. The model uses a single CPU-GPU pair, where the CPU transfers data between the system and GPU memory, executes CUDA kernels, and writes simulation outputs on the disk. All computations, including moving particles, calculating macroscopic properties of particles on a grid, and solving hybrid model equations are processed on a single GPU. We explain various computing kernels within AMITIS and compare their performance with an already existing well-tested hybrid model of plasma that runs in parallel using multi-CPU platforms. We show that AMITIS runs ∼10 times faster than the parallel CPU-based hybrid model. We also introduce an implicit solver for computation of Faraday’s Equation, resulting in an explicit-implicit scheme for the hybrid model equation. We show that the proposed scheme is stable and accurate. We examine the AMITIS energy conservation and show that the energy is conserved with an error < 0.2% after 500,000 timesteps, even when a very low number of particles per cell is used.
Non-linear hybrid control oriented modelling of a digital displacement machine
DEFF Research Database (Denmark)
Pedersen, Niels Henrik; Johansen, Per; Andersen, Torben O.
2017-01-01
Proper feedback control of digital fluid power machines (Pressure, flow, torque or speed control) requires a control oriented model, from where the system dynamics can be analyzed, stability can be proven and design criteria can be specified. The development of control oriented models for hydraul...... Transmission (DFPT) comprising two variable speed DDM’s with asynchronous control sampling schemes. A validation with respect to a non-linear dynamical model representing the physical system, shows the usefulness of the hybrid model with respect to feedback control development........ In this paper, a control oriented hybrid model is established, which combines the continuous non-linear pressure chamber dynamics and the discrete shaft position dependent activation of the pressure chambers. The hybrid machine model is further extended to describe the dynamics of a Digital Fluid Power...
Rath, S.; Sengupta, P. P.; Singh, A. P.; Marik, A. K.; Talukdar, P.
2013-07-01
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.
Modelling biochemical networks with intrinsic time delays: a hybrid semi-parametric approach
Directory of Open Access Journals (Sweden)
Oliveira Rui
2010-09-01
Full Text Available Abstract Background This paper presents a method for modelling dynamical biochemical networks with intrinsic time delays. Since the fundamental mechanisms leading to such delays are many times unknown, non conventional modelling approaches become necessary. Herein, a hybrid semi-parametric identification methodology is proposed in which discrete time series are incorporated into fundamental material balance models. This integration results in hybrid delay differential equations which can be applied to identify unknown cellular dynamics. Results The proposed hybrid modelling methodology was evaluated using two case studies. The first of these deals with dynamic modelling of transcriptional factor A in mammalian cells. The protein transport from the cytosol to the nucleus introduced a delay that was accounted for by discrete time series formulation. The second case study focused on a simple network with distributed time delays that demonstrated that the discrete time delay formalism has broad applicability to both discrete and distributed delay problems. Conclusions Significantly better prediction qualities of the novel hybrid model were obtained when compared to dynamical structures without time delays, being the more distinctive the more significant the underlying system delay is. The identification of the system delays by studies of different discrete modelling delays was enabled by the proposed structure. Further, it was shown that the hybrid discrete delay methodology is not limited to discrete delay systems. The proposed method is a powerful tool to identify time delays in ill-defined biochemical networks.
Development of a Hybrid III 5th percentile facet dummy model
Made, R. van der; Margerie, L.; Hovenga, E.; Kant, R.; Co, J.; Xu, B.; Sriram, N.S.; Laituri, T.
2001-01-01
A MADYMO multibody model of the Hybrid III 5th percentile female dummy has been developed. Most attention is placed on modeling the thorax, pelvis- abdomen, head and neck. Those parts are modeled with facet surfaces and deformable bodies are used for the thorax. The remaining dummy parts are
Energy Technology Data Exchange (ETDEWEB)
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.
Dynamic Hybrid Model for Short-Term Electricity Price Forecasting
Marin Cerjan; Marin Matijaš; Marko Delimar
2014-01-01
Accurate forecasting tools are essential in the operation of electric power systems, especially in deregulated electricity markets. Electricity price forecasting is necessary for all market participants to optimize their portfolios. In this paper we propose a hybrid method approach for short-term hourly electricity price forecasting. The paper combines statistical techniques for pre-processing of data and a multi-layer (MLP) neural network for forecasting electricity price and price spike det...
Variable Bus Voltage Modeling for Series Hybrid Electric Vehicle Simulation
Merkle, Matthew Alan
1997-01-01
A growing dependence on foreign oil, along with a heightened concern over the environmental impact of personal transportation, had led the U. S. government to investigate and sponsor research into advanced transportation concepts. One of these future technologies is the hybrid electric vehicle (HEV), typically featuring both an internal combustion engine and an electric motor, with the goal of producing fewer emissions while obtaining superior fuel economy. While vehicles such as the Virg...
Hybrid Predictive Models for Accurate Forecasting in PV Systems
Directory of Open Access Journals (Sweden)
Marco Mussetta
2013-04-01
Full Text Available The accurate forecasting of energy production from renewable sources represents an important topic also looking at different national authorities that are starting to stimulate a greater responsibility towards plants using non-programmable renewables. In this paper the authors use advanced hybrid evolutionary techniques of computational intelligence applied to photovoltaic systems forecasting, analyzing the predictions obtained by comparing different definitions of the forecasting error.
Adaptive control using a hybrid-neural model: application to a polymerisation reactor
Directory of Open Access Journals (Sweden)
Cubillos F.
2001-01-01
Full Text Available This work presents the use of a hybrid-neural model for predictive control of a plug flow polymerisation reactor. The hybrid-neural model (HNM is based on fundamental conservation laws associated with a neural network (NN used to model the uncertain parameters. By simulations, the performance of this approach was studied for a peroxide-initiated styrene tubular reactor. The HNM was synthesised for a CSTR reactor with a radial basis function neural net (RBFN used to estimate the reaction rates recursively. The adaptive HNM was incorporated in two model predictive control strategies, a direct synthesis scheme and an optimum steady state scheme. Tests for servo and regulator control showed excellent behaviour following different setpoint variations, and rejecting perturbations. The good generalisation and training capacities of hybrid models, associated with the simplicity and robustness characteristics of the MPC formulations, make an attractive combination for the control of a polymerisation reactor.
A state-space free-vortex hybrid wake model for helicopter rotors
Wasileski, Bryan J.
This paper presents the development of a new hybrid wake model merging two distinctly different modeling approaches into a single, more comprehensive solution. The objective of the work was to leverage the strengths of each individual wake model creating a more flexible and extensible solution that could be used across the entire flight envelope of a helicopter. The results of the work indicate that the two wakes models can be successfully merged. The results also show that hybrid wake provides a mechanism by which finite-state wake imparts a level of stability on the free wake solution allowing the free wake to provide consistent, repeatable results from hover through high speed forward flight. While the new hybrid wake includes the geometric distortion needed for predicting the off-axis control response, the new model, as configured in this work, shows no sign of improvement in this area.
Bias-dependent hybrid PKI empirical-neural model of microwave FETs
Marinković, Zlatica; Pronić-Rančić, Olivera; Marković, Vera
2011-10-01
Empirical models of microwave transistors based on an equivalent circuit are valid for only one bias point. Bias-dependent analysis requires repeated extractions of the model parameters for each bias point. In order to make model bias-dependent, a new hybrid empirical-neural model of microwave field-effect transistors is proposed in this article. The model is a combination of an equivalent circuit model including noise developed for one bias point and two prior knowledge input artificial neural networks (PKI ANNs) aimed at introducing bias dependency of scattering (S) and noise parameters, respectively. The prior knowledge of the proposed ANNs involves the values of the S- and noise parameters obtained by the empirical model. The proposed hybrid model is valid in the whole range of bias conditions. Moreover, the proposed model provides better accuracy than the empirical model, which is illustrated by an appropriate modelling example of a pseudomorphic high-electron mobility transistor device.
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
Szolgayova, Elena
2010-05-01
Hybrid modelling, used for simulation and forecasting of hydrological time series, involving both process-based and data-driven types of models combines the available domain knowledge and process physics with the recent advances in data driven tools. In this way, complex hydrological processes can be modelled and forecasted by decomposing the problem into several smaller sub - problems and using process physics based models where these are most appropriate, and data dictated tools (such as ANN, time series models or traditional statistics) for the residual data, when necessary. The fitting and forecasting performance of such models have to be explored case based. So far, only a few attempts to apply various nonlinear time series models within such a framework were reported in the hydrological modelling literature. This contribution presents results concerning the possibility to use GARCH type of models for such purposes. More specifically, error time series from two hydrological conceptual models were analyzed (applied on time series measured from the Hron and Morava Rivers in Slovakia), concentrating on the improvement of the modelling and forecasting performance of these models. The goal of investigation was to try to expand the knowledge in the time series modelling of hydrological model error time series with the aim to test and develop appropriate methods for various time steps from the GARCH family of models. In order to achieve this, following steps were taken: 1. The presence of heteroscedasticity was verified in time series. 2. A model from the GARCH family was fitted on the data, comparing the fit with a fit of an ARMA model. 3. One - step - ahead forecasts from the fitted models were produced, performing comparisons. The investigation of model properties and performances was thoroughly tested under various conditions of their future practical applications. In general, heteroscedasticity was present in the majority of the error time series of the
A hybrid model for mapping simplified seismic response via a GIS-metamodel approach
Grelle, G.; Bonito, L.; Revellino, P.; Guerriero, L.; Guadagno, F. M.
2014-07-01
In earthquake-prone areas, site seismic response due to lithostratigraphic sequence plays a key role in seismic hazard assessment. A hybrid model, consisting of GIS and metamodel (model of model) procedures, was introduced aimed at estimating the 1-D spatial seismic site response in accordance with spatial variability of sediment parameters. Inputs and outputs are provided and processed by means of an appropriate GIS model, named GIS Cubic Model (GCM). This consists of a block-layered parametric structure aimed at resolving a predicted metamodel by means of pixel to pixel vertical computing. The metamodel, opportunely calibrated, is able to emulate the classic shape of the spectral acceleration response in relation to the main physical parameters that characterize the spectrum itself. Therefore, via the GCM structure and the metamodel, the hybrid model provides maps of normalized acceleration response spectra. The hybrid model was applied and tested on the built-up area of the San Giorgio del Sannio village, located in a high-risk seismic zone of southern Italy. Efficiency tests showed a good correspondence between the spectral values resulting from the proposed approach and the 1-D physical computational models. Supported by lithology and geophysical data and corresponding accurate interpretation regarding modelling, the hybrid model can be an efficient tool in assessing urban planning seismic hazard/risk.
A hybrid algorithm and its applications to fuzzy logic modeling of nonlinear systems
Wang, Zhongjun
System models allow us to simulate and analyze system dynamics efficiently. Most importantly, system models allow us to make prediction about system behaviors and to perform system parametric variation analysis without having to build the actual systems. The fuzzy logic modeling technique has been successfully applied in complex nonlinear system modeling such as unsteady aerodynamics modeling etc. recently. However, the current forward search algorithm to identify fuzzy logic model structures is very time-consuming. It is not unusual to spend several days or even a few weeks in computer CPU time to obtain better nonlinear system model structures by this forward search. Moreover, how to speed up the fuzzy logic model parameter identification process is also challenging when the number of influencing variables of nonlinear systems is large. To solve these problems, a hybrid algorithm for the nonlinear system modeling is proposed, formalized, implemented, and evaluated in this dissertation. By combining the fuzzy logic modeling technique with genetic algorithms, the developed hybrid algorithm is applied to both fuzzy logic model structure identification and model parameter identification. In the model structure identification process, the hybrid algorithm has the ability to find feasible structures more efficiently and effectively than the forward search. In the model parameter identification process (by using Newton gradient descent algorithm), the proposed hybrid algorithm incorporates genetic search algorithm to dynamically select convergence factors. It has the advantages of quick search yet maintains the monotonically convergent properties of the Newton gradient descent algorithm. To evaluate the properties of the developed hybrid algorithm, a nonlinear, unsteady aerodynamic normal force model with a complex system involving fourteen influencing variables is established from flight data. The results show that this hybrid algorithm can identify the aerodynamic
Ismail, S.; Samsudin, R.; Shabri, A.
2010-10-01
Successful river flow time series forecasting is a major goal and an essential procedure that is necessary in water resources planning and management. This study introduced a new hybrid model based on a combination of two familiar non-linear method of mathematical modeling: Self Organizing Map (SOM) and Least Square Support Vector Machine (LSSVM) model referred as SOM-LSSVM model. The hybrid model uses the SOM algorithm to cluster the training data into several disjointed clusters and the individual LSSVM is used to forecast the river flow. The feasibility of this proposed model is evaluated to actual river flow data from Bernam River located in Selangor, Malaysia. Their results have been compared to those obtained using LSSVM and artificial neural networks (ANN) models. The experiment results show that the SOM-LSSVM model outperforms other models for forecasting river flow. It also indicates that the proposed model can forecast more precisely and provides a promising alternative technique in river flow forecasting.
Modeling and Simulation of Renewable Hybrid Power System using Matlab Simulink Environment
Directory of Open Access Journals (Sweden)
Cristian Dragoş Dumitru
2010-12-01
Full Text Available The paper presents the modeling of a solar-wind-hydroelectric hybrid system in Matlab/Simulink environment. The application is useful for analysis and simulation of a real hybrid solar-wind-hydroelectric system connected to a public grid. Application is built on modular architecture to facilitate easy study of each component module influence. Blocks like wind model, solar model, hydroelectric model, energy conversion and load are implemented and the results of simulation are also presented. As an example, one of the most important studies is the behavior of hybrid system which allows employing renewable and variable in time energy sources while providing a continuous supply. Application represents a useful tool in research activity and also in teaching
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.
Hadden, Cameron M.; Klimek-McDonald, Danielle R.; Pineda, Evan J.; King, Julie A.; Reichanadter, Alex M.; Miskioglu, Ibrahim; Gowtham, S.; Odegard, Gregory M.
2015-01-01
Because of the relatively high specific mechanical properties of carbon fiber/epoxy composite materials, they are often used as structural components in aerospace applications. Graphene nanoplatelets (GNPs) can be added to the epoxy matrix to improve the overall mechanical properties of the composite. The resulting GNP/carbon fiber/epoxy hybrid composites have been studied using multiscale modeling to determine the influence of GNP volume fraction, epoxy crosslink density, and GNP dispersion on the mechanical performance. The hierarchical multiscale modeling approach developed herein includes Molecular Dynamics (MD) and micromechanical modeling, and it is validated with experimental testing of the same hybrid composite material system. The results indicate that the multiscale modeling approach is accurate and provides physical insight into the composite mechanical behavior. Also, the results quantify the substantial impact of GNP volume fraction and dispersion on the transverse mechanical properties of the hybrid composite, while the effect on the axial properties is shown to be insignificant.
A Hybrid Approach for Efficient Modeling of Medium-Frequency Propagation in Coal Mines.
Brocker, Donovan E; Sieber, Peter E; Waynert, Joseph A; Li, Jingcheng; Werner, Pingjuan L; Werner, Douglas H
2015-02-01
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.
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
Coupled thermal model of photovoltaic-thermoelectric hybrid panel for sample cities in Europe
DEFF Research Database (Denmark)
Rezaniakolaei, Alireza; Sera, Dezso; Rosendahl, Lasse Aistrup
2016-01-01
of the hybrid system under different weather conditions. The model takes into account solar irradiation, wind speed and ambient temperature as well as convective and radiated heat losses from the front and rear surfaces of the panel. The model is developed for three sample cities in Europe with different......In general, modeling of photovoltaic-thermoelectric (PV/TEG) hybrid panels have been mostly simplified and disconnected from the actual ambient conditions and thermal losses from the panel. In this study, a thermally coupled model of PV/TEG panel is established to precisely predict performance...... weather conditions. The results show that radiated heat loss from the front surface and the convective heat loss due to the wind speed are the most critical parameters on performance of the hybrid panel performance. The results also indicate that, with existing thermoelectric materials, the power...
Fluid Petri Nets and hybrid model-checking: a comparative case study
Energy Technology Data Exchange (ETDEWEB)
Gribaudo, M.; Horvath, A.; Bobbio, A.; Tronci, E.; Ciancamerla, E.; Minichino, M
2003-09-01
The modeling and analysis of hybrid systems is a recent and challenging research area which is actually dominated by two main lines: a functional analysis based on the description of the system in terms of discrete state (hybrid) automata (whose goal is to ascertain conformity and reachability properties), and a stochastic analysis (whose aim is to provide performance and dependability measures). This paper investigates a unifying view between formal methods and stochastic methods by proposing an analysis methodology of hybrid systems based on Fluid Petri Nets (FPNs). FPNs can be analyzed directly using appropriate tools. Our paper shows that the same FPN model can be fed to different functional analyzers for model checking. In order to extensively explore the capability of the technique, we have converted the original FPN into languages for discrete as well as hybrid as well as stochastic model checkers. In this way, a first comparison among the modeling power of well known tools can be carried out. Our approach is illustrated by means of a 'real world' hybrid system: the temperature control system of a co-generative plant.
Wu, Xingfu
2013-12-01
In this paper, we present a performance modeling framework based on memory bandwidth contention time and a parameterized communication model to predict the performance of OpenMP, MPI and hybrid applications with weak scaling on three large-scale multicore supercomputers: IBM POWER4, POWER5+ and BlueGene/P, and analyze the performance of these MPI, OpenMP and hybrid applications. We use STREAM memory benchmarks and Intel\\'s MPI benchmarks to provide initial performance analysis and model validation of MPI and OpenMP applications on these multicore supercomputers because the measured sustained memory bandwidth can provide insight into the memory bandwidth that a system should sustain on scientific applications with the same amount of workload per core. In addition to using these benchmarks, we also use a weak-scaling hybrid MPI/OpenMP large-scale scientific application: Gyrokinetic Toroidal Code (GTC) in magnetic fusion to validate our performance model of the hybrid application on these multicore supercomputers. The validation results for our performance modeling method show less than 7.77% error rate in predicting the performance of hybrid MPI/OpenMP GTC on up to 512 cores on these multicore supercomputers. © 2013 Elsevier Inc.
Modeling hydraulic regenerative hybrid vehicles using AMESim and Matlab/Simulink
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.
Hybrid neural modelling of an anaerobic digester with respect to biological constraints.
Karama, A; Bernard, O; Gouzé, J L; Benhammou, A; Dochain, D
2001-01-01
A hybrid model for an anaerobic digestion process is proposed. The fermentation is assumed to be performed in two steps, acidogenesis and methanogenesis, by two bacterial populations. The model is based on mass balance equations, and the bacterial growth rates are represented by neural networks. In order to guarantee the biological meaning of the hybrid model (positivity of the concentrations, boundedness, saturation or inhibition of the growth rates) outside the training data set, a method that imposes constraints in the neural network is proposed. The method is applied to experimental data from a fixed bed reactor.
A model updating method for hybrid composite/aluminum bolted joints using modal test data
Adel, Farhad; Shokrollahi, Saeed; Jamal-Omidi, Majid; Ahmadian, Hamid
2017-05-01
The aim of this paper is to present a simple and applicable model for predicting the dynamic behavior of bolted joints in hybrid aluminum/composite structures and its model updating using modal test data. In this regards, after investigations on bolted joints in metallic structures which led to a new concept called joint affected region (JAR) published in Shokrollahi and Adel (2016), now, a doubly connective layer is established in order to simulate the bolted joint interfaces in hybrid structures. Using the proposed model, the natural frequencies of the hybrid bolted joint structure are computed and compared to the modal test results in order to evaluate and verify the new model predictions. Because of differences in the results of two approaches, the finite element (FE) model is updated based on the genetic algorithm (GA) by minimizing the differences between analytical model and test results. This is done by identifying the parameters at the JAR including isotropic Young's modulus in metallic substructure and that of anisotropic composite substructure. The updated model compared to the initial model simulates experimental results more properly. Therefore, the proposed model can be used for modal analysis of the hybrid joint interfaces in complex and large structures.
Modeling of Hybrid Permanent Magnetic-Gas Bearings
DEFF Research Database (Denmark)
Morosi, Stefano; Santos, Ilmar
2009-01-01
. In the present paper both the technologies are combined with the aim of developing a new kind of hybrid permanent magnetic - gas bearing. This new kind of machine is intended to exploit the benefits of the two technologies while minimizing their drawbacks. The poor start-up and low speed operation performance...... of the gas bearing is balanced by the properties of the passive magnetic one. At high speeds the dynamic characteristics of the gas bearing are improved by offsetting the stator ring of the permanent magnetic bearing. Furthermore this design shows a kind of redundancy, which offers soft failure properties...
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
Holmqvist, Kristian; Davidsson, Johan; Mendoza-Vazquez, Manuel; Rundberget, Peter; Svensson, Mats Y; Thorn, Stefan; Törnvall, Fredrik
2014-01-01
The main aim of this study was to improve the quality of injury risk assessments in steering wheel rim to chest impacts when using the Hybrid III crash test dummy in frontal heavy goods vehicle (HGV) collision tests. Correction factors for chest injury criteria were calculated as the model chest injury parameter ratios between finite element (FE) Hybrid III, evaluated in relevant load cases, and the Total Human Model for Safety (THUMS). This is proposed to be used to compensate Hybrid III measurements in crash tests where steering wheel rim to chest impacts occur. The study was conducted in an FE environment using an FE-Hybrid III model and the THUMS. Two impactor shapes were used, a circular hub and a long, thin horizontal bar. Chest impacts at velocities ranging from 3.0 to 6.0 m/s were simulated at 3 impact height levels. A ratio between FE-Hybrid III and THUMS chest injury parameters, maximum chest compression C max, and maximum viscous criterion VC max, were calculated for the different chest impact conditions to form a set of correction factors. The definition of the correction factor is based on the assumption that the response from a circular hub impact to the middle of the chest is well characterized and that injury risk measures are independent of impact height. The current limits for these chest injury criteria were used as a basis to develop correction factors that compensate for the limitations in biofidelity of the Hybrid III in steering wheel rim to chest impacts. The hub and bar impactors produced considerably higher C max and VC max responses in the THUMS compared to the FE-Hybrid III. The correction factor for the responses of the FE-Hybrid III showed that the criteria responses for the bar impactor were consistently overestimated. Ratios based on Hybrid III and THUMS responses provided correction factors for the Hybrid III responses ranging from 0.84 to 0.93. These factors can be used to estimate C max and VC max values when the Hybrid III is
Timetable optimization for single bus line based on hybrid vehicle size model
Directory of Open Access Journals (Sweden)
Daniel(Jian Sun
2015-06-01
Full Text Available This study proposes a flexible timetable optimization method based on hybrid vehicle size model to tackle the bus demand fluctuations in transit operation. Three different models for hybrid vehicle, large vehicle and small vehicle are built in this study, respectively. With the operation data of Shanghai Transit Route 55 at peak and off-peak hours, a heuristic algorithm was proposed to solve the problem. The results indicate that the hybrid vehicle size model excels the other two modes both in the total time and total cost. The study verifies the rationality of the strategy of hybrid vehicle size model and highlights the importance of the adaptive vehicle size in dealing with the bus demand fluctuation. The main innovation of the study is that unlike traditional timetables, the arrangement of the scheduling interval and the corresponding bus type or size are both involved in the timetable of hybrid vehicle size bus mode, which will be more effective to solve the problem of passenger demand fluctuation. Findings from this research would provide a new perspective to improve the level of regular bus service.
A hybrid beach morphology model applied to a high energy sandy beach
Karunarathna, H.; Ranasinghe, Ranasinghe W M R J B; Reeve, D.E.
2015-01-01
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
Examining the Etiology of Reading Disability as Conceptualized by the Hybrid Model
Erbeli, Florina; Hart, Sara A.; Wagner, Richard K.; Taylor, Jeanette
2018-01-01
A fairly recent definition of reading disability (RD) is that in the form of a hybrid model. The model views RD as a latent construct that is manifested through various observable unexpected impairments in reading-related skills and through inadequate response to intervention. The current report evaluated this new conceptualization of RD from an…
Multi-Zone hybrid model for failure detection of the stable ventilation systems
DEFF Research Database (Denmark)
Gholami, Mehdi; Schiøler, Henrik; Soltani, Mohsen
2010-01-01
In this paper, a conceptual multi-zone model for climate control of a live stock building is elaborated. The main challenge of this research is to estimate the parameters of a nonlinear hybrid model. A recursive estimation algorithm, the Extended Kalman Filter (EKF) is implemented for estimation...
Rapidity distributions of hadrons in the HydHSD hybrid model
Energy Technology Data Exchange (ETDEWEB)
Khvorostukhin, A. S., E-mail: hvorost@theor.jinr.ru; Toneev, V. D. [Joint Institute for Nuclear Research (Russian Federation)
2017-03-15
A multistage hybrid model intended for describing heavy-ion interactions in the energy region of the NICA collider under construction in Dubna is proposed. The model combines the initial, fast, interaction stage described by the model of hadron string dynamics (HSD) and the subsequent evolution that the expanding system formed at the first stage experiences at the second stage and which one treats on the basis of ideal hydrodynamics; after the completion of the second stage, the particles involved may still undergo rescattering (third interaction stage). The model admits three freeze-out scenarios: isochronous, isothermal, and isoenergetic. Generally, the HydHSD hybrid model developed in the present study provides fairly good agreement with available experimental data on proton rapidity spectra. It is shown that, within this hybrid model, the two-humped structure of proton rapidity distributions can be obtained either by increasing the freeze-out temperature and energy density or by more lately going over to the hydrodynamic stage. Although the proposed hybrid model reproduces rapidity spectra of protons, it is unable to describe rapidity distributions of pions, systematically underestimating their yield. It is necessary to refine the model by including viscosity effects at the hydrodynamic stage of evolution of the system and by considering in more detail the third interaction stage.
Hybrid Analytical and Data-Driven Modeling for Feed-Forward Robot Control †
Directory of Open Access Journals (Sweden)
René Felix Reinhart
2017-02-01
Full Text Available Feed-forward model-based control relies on models of the controlled plant, e.g., in robotics on accurate knowledge of manipulator kinematics or dynamics. However, mechanical and analytical models do not capture all aspects of a plant’s intrinsic properties and there remain unmodeled dynamics due to varying parameters, unmodeled friction or soft materials. In this context, machine learning is an alternative suitable technique to extract non-linear plant models from data. However, fully data-based models suffer from inaccuracies as well and are inefficient if they include learning of well known analytical models. This paper thus argues that feed-forward control based on hybrid models comprising an analytical model and a learned error model can significantly improve modeling accuracy. Hybrid modeling here serves the purpose to combine the best of the two modeling worlds. The hybrid modeling methodology is described and the approach is demonstrated for two typical problems in robotics, i.e., inverse kinematics control and computed torque control. The former is performed for a redundant soft robot and the latter for a rigid industrial robot with redundant degrees of freedom, where a complete analytical model is not available for any of the platforms.
Hybrid Analytical and Data-Driven Modeling for Feed-Forward Robot Control.
Reinhart, René Felix; Shareef, Zeeshan; Steil, Jochen Jakob
2017-02-08
Feed-forward model-based control relies on models of the controlled plant, e.g., in robotics on accurate knowledge of manipulator kinematics or dynamics. However, mechanical and analytical models do not capture all aspects of a plant's intrinsic properties and there remain unmodeled dynamics due to varying parameters, unmodeled friction or soft materials. In this context, machine learning is an alternative suitable technique to extract non-linear plant models from data. However, fully data-based models suffer from inaccuracies as well and are inefficient if they include learning of well known analytical models. This paper thus argues that feed-forward control based on hybrid models comprising an analytical model and a learned error model can significantly improve modeling accuracy. Hybrid modeling here serves the purpose to combine the best of the two modeling worlds. The hybrid modeling methodology is described and the approach is demonstrated for two typical problems in robotics, i.e., inverse kinematics control and computed torque control. The former is performed for a redundant soft robot and the latter for a rigid industrial robot with redundant degrees of freedom, where a complete analytical model is not available for any of the platforms.
Hybrid Analytical and Data-Driven Modeling for Feed-Forward Robot Control †
Reinhart, René Felix; Shareef, Zeeshan; Steil, Jochen Jakob
2017-01-01
Feed-forward model-based control relies on models of the controlled plant, e.g., in robotics on accurate knowledge of manipulator kinematics or dynamics. However, mechanical and analytical models do not capture all aspects of a plant’s intrinsic properties and there remain unmodeled dynamics due to varying parameters, unmodeled friction or soft materials. In this context, machine learning is an alternative suitable technique to extract non-linear plant models from data. However, fully data-based models suffer from inaccuracies as well and are inefficient if they include learning of well known analytical models. This paper thus argues that feed-forward control based on hybrid models comprising an analytical model and a learned error model can significantly improve modeling accuracy. Hybrid modeling here serves the purpose to combine the best of the two modeling worlds. The hybrid modeling methodology is described and the approach is demonstrated for two typical problems in robotics, i.e., inverse kinematics control and computed torque control. The former is performed for a redundant soft robot and the latter for a rigid industrial robot with redundant degrees of freedom, where a complete analytical model is not available for any of the platforms. PMID:28208697
DEFF Research Database (Denmark)
Fontenete, Sílvia; Guimarães, Nuno; Wengel, Jesper
2016-01-01
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......Abstract 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...... (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...
Directory of Open Access Journals (Sweden)
Zhibin Miao
2015-08-01
Full Text Available More and more hybrid electric vehicles are driven since they offer such advantages as energy savings and better active safety performance. Hybrid vehicles have two or more power driving systems and frequently switch working condition, so controlling stability is very important. In this work, a two-stage Kalman algorithm method is used to fuse data in hybrid vehicle stability testing. First, the RT3102 navigation system and Dewetron system are introduced. Second, a modeling of data fusion is proposed based on the Kalman filter. Then, this modeling is simulated and tested on a sample vehicle, using Carsim and Simulink software to test the results. The results showed the merits of this modeling.
Design and fabrication of a hybrid maglev model employing PML and SML
Sun, R. X.; Zheng, J.; Zhan, L. J.; Huang, S. Y.; Li, H. T.; Deng, Z. G.
2017-10-01
A hybrid maglev model combining permanent magnet levitation (PML) and superconducting magnetic levitation (SML) was designed and fabricated to explore a heavy-load levitation system advancing in passive stability and simple structure. In this system, the PML was designed to levitate the load, and the SML was introduced to guarantee the stability. In order to realize different working gaps of the two maglev components, linear bearings were applied to connect the PML layer (for load) and the SML layer (for stability) of the hybrid maglev model. Experimental results indicate that the hybrid maglev model possesses excellent advantages of heavy-load ability and passive stability at the same time. This work presents a possible way to realize a heavy-load passive maglev concept.
van Lith, Pascal; van Lith, P.F.; Betlem, Bernardus H.L.; Roffel, B.
2002-01-01
Hybrid fuzzy-first principles models can be a good alternative if a complete physical model is difficult to derive. These hybrid models consist of a framework of dynamic mass and energy balances, supplemented by fuzzy submodels describing additional equations, such as mass transformation and
Lith, Pascal F. van; Betlem, Ben H.L.; Roffel, Brian
2002-01-01
Hybrid fuzzy-first principles models can be a good alternative if a complete physical model is difficult to derive. These hybrid models consist of a framework of dynamic mass and energy balances, supplemented by fuzzy submodels describing additional equations, such as mass transformation and
A hybrid learning scheme combining EM and MASMOD algorithms for fuzzy local linearization modeling.
Gan, Q; Harris, C J
2001-01-01
Fuzzy local linearization (FLL) is a useful divide-and-conquer method for coping with complex problems such as modeling unknown nonlinear systems from data for state estimation and control. Based on a probabilistic interpretation of FLL, the paper proposes a hybrid learning scheme for FLL modeling, which uses a modified adaptive spline modeling (MASMOD) algorithm to construct the antecedent parts (membership functions) in the FLL model, and an expectation-maximization (EM) algorithm to parameterize the consequent parts (local linear models). The hybrid method not only has an approximation ability as good as most neuro-fuzzy network models, but also produces a parsimonious network structure (gain from MASMOD) and provides covariance information about the model error (gain from EM) which is valuable in applications such as state estimation and control. Numerical examples on nonlinear time-series analysis and nonlinear trajectory estimation using FLL models are presented to validate the derived algorithm.
Hybrid Spatial Data Model for Indoor Space: Combined Topology and Grid
Directory of Open Access Journals (Sweden)
Zhiyong Lin
2017-11-01
Full Text Available The construction and application of an indoor spatial data model is an important prerequisite to meet the requirements of diversified indoor spatial location services. The traditional indoor spatial topology model focuses on the construction of topology information. It has high path analysis and query efficiency, but ignores the spatial location information. The grid model retains the plane position information by grid, but increases the data volume and complexity of the model and reduces the efficiency of the model analysis. This paper presents a hybrid model for interior space based on topology and grid. Based on the spatial meshing and spatial division of the interior space, the model retains the position information and topological connectivity information of the interior space by establishing the connection or affiliation between the grid subspace and the topological subspace. The model improves the speed of interior spatial analysis and solves the problem of the topology information and location information updates not being synchronized. In this study, the A* shortest path query efficiency of typical daily indoor activities under the grid model and the hybrid model were compared for the indoor plane of an apartment and a shopping mall. The results obtained show that the hybrid model is 43% higher than the A* algorithm of the grid model as a result of the existence of topology communication information. This paper provides a useful idea for the establishment of a highly efficient and highly available interior spatial data model.
A Hybrid LDA+gCCA Model for fMRI Data Classification and Visualization.
Afshin-Pour, Babak; Shams, Seyed-Mohammad; Strother, Stephen
2015-05-01
Linear predictive models are applied to functional MRI (fMRI) data to estimate boundaries that predict experimental task states for scans. These boundaries are visualized as statistical parametric maps (SPMs) and range from low to high spatial reproducibility across subjects (e.g., Strother , 2004; LaConte , 2003). Such inter-subject pattern reproducibility is an essential characteristic of interpretable SPMs that generalize across subjects. Therefore, we introduce a flexible hybrid model that optimizes reproducibility by simultaneously enhancing the prediction power and reproducibility. This hybrid model is formed by a weighted summation of the optimization functions of a linear discriminate analysis (LDA) model and a generalized canonical correlation (gCCA) model (Afshin-Pour , 2012). LDA preserves the model's ability to discriminate the fMRI scans of multiple brain states while gCCA finds a linear combination for each subject's scans such that the estimated boundary map is reproducible. The hybrid model is implemented in a split-half resampling framework (Strother , 2010) which provides reproducibility (r) and prediction (p) quality metrics. Then the model was compared with LDA, and Gaussian Naive Bayes (GNB). For simulated fMRI data, the hybrid model outperforms the other two techniques in terms of receiver operating characteristic (ROC) curves, particularly for detecting less predictable but spatially reproducible networks. These techniques were applied to real fMRI data to estimate the maps for two task contrasts. Our results indicate that compared to LDA and GNB, the hybrid model can provide maps with large increases in reproducibility for small reductions in prediction, which are jointly closer to the ideal performance point of (p=1, r=1).
Wen Zhu; Junsheng Liu; Meng Li
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 foun...
Modeling and Simulation of Hybrid Solar Photovoltaic, Wind turbine and Hydraulic Power System
Sami, S; D. Icaza
2015-01-01
This paper presents the modeling and simulation of the energy conversion equations describing the total power generated by a hybrid system of solar photovoltaic, wind turbine and hydraulic turbine. To validate this simulation model, the aforementioned equations were coded with MATLAB V13.2, compared to experimental data. The model is intended to be used as an optimization and design tool. A block diagram approach was used during the simulation with MATLAB. The model predicted results compared...
A stage structured hybrid model for within-host emerging infectious disease modelling
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Soumya Banerjee
2017-12-01
Full Text Available Stochasticity and spatial distribution of the pathogen play a critical role in determining the outcome of an infection. 1 in a million immune system cells are specific to a particular pathogen. The serendipitous encounter of such a rare immune system cell with its fated antigen can determine the mortality of the infected animal. Moreover, pathogens may remain initially localized in a small volume of tissue. Hence stochastic and spatial aspects play an important role in pathogenesis, especially early on in the infection. Current efforts at investigating the effect of stochasticity and space in modeling of host immune response and pathogens use agent based models (ABMs. However these are computationally expensive. Population level approaches like ordinary differential equations (ODEs are computationally tractable. However they make simplifying assumptions that are unlikely to be true early on in the infection. We proposed a stage-structured hybrid model that aims to strike a balance between the detail of representation of an ABM and the computational tractability of an ODE model. It uses a spatially explicit ABM in the initial stage of infection, and a coarse-grained but computationally tractable ODE model in the latter stages of infection. Such an approach might hold promise in: 1 modeling of other emerging pathogens where the initial stochasticity of the pathogen dictates the trajectory of pathogenesis, and 2 lead to insights into immune system inspired strategies and architectures for distributed systems of computers.
Solving Problem of Graph Isomorphism by Membrane-Quantum Hybrid Model
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Artiom Alhazov
2015-10-01
Full Text Available This work presents the application of new parallelization methods based on membrane-quantum hybrid computing to graph isomorphism problem solving. Applied membrane-quantum hybrid computational model was developed by authors. Massive parallelism of unconventional computing is used to implement classic brute force algorithm efficiently. This approach does not suppose any restrictions of considered graphs types. The estimated performance of the model is less then quadratic that makes a very good result for the problem of \\textbf{NP} complexity.
Daily air quality index forecasting with hybrid models: A case in China.
Zhu, Suling; Lian, Xiuyuan; Liu, Haixia; Hu, Jianming; Wang, Yuanyuan; Che, Jinxing
2017-12-01
Air quality is closely related to quality of life. Air pollution forecasting plays a vital role in air pollution warnings and controlling. However, it is difficult to attain accurate forecasts for air pollution indexes because the original data are non-stationary and chaotic. The existing forecasting methods, such as multiple linear models, autoregressive integrated moving average (ARIMA) and support vector regression (SVR), cannot fully capture the information from series of pollution indexes. Therefore, new effective techniques need to be proposed to forecast air pollution indexes. The main purpose of this research is to develop effective forecasting models for regional air quality indexes (AQI) to address the problems above and enhance forecasting accuracy. Therefore, two hybrid models (EMD-SVR-Hybrid and EMD-IMFs-Hybrid) are proposed to forecast AQI data. The main steps of the EMD-SVR-Hybrid model are as follows: the data preprocessing technique EMD (empirical mode decomposition) is utilized to sift the original AQI data to obtain one group of smoother IMFs (intrinsic mode functions) and a noise series, where the IMFs contain the important information (level, fluctuations and others) from the original AQI series. LS-SVR is applied to forecast the sum of the IMFs, and then, S-ARIMA (seasonal ARIMA) is employed to forecast the residual sequence of LS-SVR. In addition, EMD-IMFs-Hybrid first separately forecasts the IMFs via statistical models and sums the forecasting results of the IMFs as EMD-IMFs. Then, S-ARIMA is employed to forecast the residuals of EMD-IMFs. To certify the proposed hybrid model, AQI data from June 2014 to August 2015 collected from Xingtai in China are utilized as a test case to investigate the empirical research. In terms of some of the forecasting assessment measures, the AQI forecasting results of Xingtai show that the two proposed hybrid models are superior to ARIMA, SVR, GRNN, EMD-GRNN, Wavelet-GRNN and Wavelet-SVR. Therefore, the
A New Method for Modeling and Control of Hybrid Stepper Motors
Directory of Open Access Journals (Sweden)
George Mihalache
2014-09-01
Full Text Available Over time the mathematical models of the hybrid stepper motors (HSM have been developed in various forms. In this paper we propose to use for HSM a model of a two-phase synchronous machine with permanent magnet in which the number of pole pairs is equal to the number of rotor teeth of the HSM. It analyzes the behavior of hybrid stepper motor controlled in open loop. Control signals are obtained by implementing the control sequences:one-phase-on, two-phases-on, half step.
Bigaj, Janusz; Osikowski, Artur; Hofman, Sebastian; Falniowski, Andrzej; Panz, Tomasz; Grzmil, Pawel; Vandenbulcke, Franck
2018-01-01
Lumbricid earthworms Eisenia andrei (Ea) and E. fetida (Ef) are simultaneous hermaphrodites with reciprocal insemination capable of self-fertilization while the existence of hybridization of these two species was still debatable. During the present investigation fertile hybrids of Ea and Ef were detected. Virgin specimens of Ea and Ef were laboratory crossed (Ea+Ef) and their progeny was doubly identified. 1 –identified by species-specific maternally derived haploid mitochondrial DNA sequences of the COI gene being either ‘a’ for worms hatched from Ea ova or ‘f’ for worms hatched from Ef ova. 2 –identified by the diploid maternal/paternal nuclear DNA sequences of 28s rRNA gene being either ‘AA’ for Ea, ‘FF’ for Ef, or AF/FA for their hybrids derived either from the ‘aA’ or ‘fF’ ova, respectively. Among offspring of Ea+Ef pairs in F1 generation there were mainly aAA and fFF earthworms resulted from the facilitated self-fertilization and some aAF hybrids from aA ova but none fFA hybrids from fF ova. In F2 generation resulting from aAF hybrids mated with aAA a new generations of aAA and aAF hybrids were noticed, while aAF hybrids mated with fFF gave fFF and both aAF and fFA hybrids. Hybrids intercrossed together produced plenty of cocoons but no hatchlings independently whether aAF+aAF or aAF+fFA were mated. These results indicated that Ea and Ef species, easy to maintain in laboratory and commonly used as convenient models in biomedicine and ecotoxicology, may also serve in studies on molecular basis of interspecific barriers and mechanisms of introgression and speciation. Hypothetically, their asymmetrical hybridization can be modified by some external factors. PMID:29370238
Robust dynamics in minimal hybrid models of genetic networks.
Perkins, Theodore J; Wilds, Roy; Glass, Leon
2010-11-13
Many gene-regulatory networks necessarily display robust dynamics that are insensitive to noise and stable under evolution. We propose that a class of hybrid systems can be used to relate the structure of these networks to their dynamics and provide insight into the origin of robustness. In these systems, the genes are represented by logical functions, and the controlling transcription factor protein molecules are real variables, which are produced and destroyed. As the transcription factor concentrations cross thresholds, they control the production of other transcription factors. We discuss mathematical analysis of these systems and show how the concepts of robustness and minimality can be used to generate putative logical organizations based on observed symbolic sequences. We apply the methods to control of the cell cycle in yeast.
Accuracy improvement of a hybrid robot for ITER application using POE modeling method
Energy Technology Data Exchange (ETDEWEB)
Wang, Yongbo, E-mail: yongbo.wang@hotmail.com [Laboratory of Intelligent Machines, Lappeenranta University of Technology, FIN-53851 Lappeenranta (Finland); Wu, Huapeng; Handroos, Heikki [Laboratory of Intelligent Machines, Lappeenranta University of Technology, FIN-53851 Lappeenranta (Finland)
2013-10-15
Highlights: ► The product of exponential (POE) formula for error modeling of hybrid robot. ► Differential Evolution (DE) algorithm for parameter identification. ► Simulation results are given to verify the effectiveness of the method. -- Abstract: This paper focuses on the kinematic calibration of a 10 degree-of-freedom (DOF) redundant serial–parallel hybrid robot to improve its accuracy. The robot was designed to perform the assembling and repairing tasks of the vacuum vessel (VV) of the international thermonuclear experimental reactor (ITER). By employing the product of exponentials (POEs) formula, we extended the POE-based calibration method from serial robot to redundant serial–parallel hybrid robot. The proposed method combines the forward and inverse kinematics together to formulate a hybrid calibration method for serial–parallel hybrid robot. Because of the high nonlinear characteristics of the error model and too many error parameters need to be identified, the traditional iterative linear least-square algorithms cannot be used to identify the parameter errors. This paper employs a global optimization algorithm, Differential Evolution (DE), to identify parameter errors by solving the inverse kinematics of the hybrid robot. Furthermore, after the parameter errors were identified, the DE algorithm was adopted to numerically solve the forward kinematics of the hybrid robot to demonstrate the accuracy improvement of the end-effector. Numerical simulations were carried out by generating random parameter errors at the allowed tolerance limit and generating a number of configuration poses in the robot workspace. Simulation of the real experimental conditions shows that the accuracy of the end-effector can be improved to the same precision level of the given external measurement device.
Evolutionary Implications of Mechanistic Models of TE-Mediated Hybrid Incompatibility
Castillo, Dean M.; Moyle, Leonie C.
2012-01-01
New models of TE repression in plants (specifically Arabidopsis) have suggested specific mechanisms by which TE misregulation in hybrids might result in the expression of hybrid inviability. If true, these models suggest as yet undescribed consequences for (1) mechanistic connections between hybrid problems expressed at different postzygotic stages (e.g., inviability versus sterility), (2) the predicted strength, stage, and direction of isolation between diverging lineages that differ in TE activity, and (3) the association between species attributes that influence TE dynamics (e.g., mode of reproduction, geographical structure) and the rate at which they could accumulate incompatibilities. In this paper, we explore these implications and outline future empirical directions for generating data necessary to evaluate them. PMID:22518335
Directory of Open Access Journals (Sweden)
Xiangyong Chen
2014-01-01
hybrid dynamic systems is established based on Lanchester equation in a (n,1 battle, where a heterogeneous force of n different troop types faces a homogeneous force. This model can be characterized by the interaction of continuous-time models (governed by Lanchester equation, and discrete event systems (described by variable tactics. Furthermore, an expository discussion is presented on an optimal variable tactics control problem for warfare hybrid dynamic system. The optimal control strategies are designed based on dynamic programming and differential game theory. As an example of the consequences of this optimal control problem, we take the (2, 1 case and solve the optimal strategies in a (2, 1 case. Simulation results show the feasibility of warfare hybrid system model and the effectiveness of the optimal control strategies designed.
A hybrid modelling approach to simulating foot-and-mouth disease outbreaks in Australian livestock
Directory of Open Access Journals (Sweden)
Richard A Bradhurst
2015-03-01
Full Text Available Foot-and-mouth disease (FMD is a highly contagious and economically important viral disease of cloven-hoofed animals. Australia's freedom from FMD underpins a valuable trade in live animals and animal products. An outbreak of FMD would result in the loss of export markets and cause severe disruption to domestic markets. The prevention of, and contingency planning for, FMD are of key importance to government, industry, producers and the community. The spread and control of FMD is complex and dynamic due to a highly contagious multi-host pathogen operating in a heterogeneous environment across multiple jurisdictions. Epidemiological modelling is increasingly being recognized as a valuable tool for investigating the spread of disease under different conditions and the effectiveness of control strategies. Models of infectious disease can be broadly classified as: population-based models that are formulated from the top-down and employ population-level relationships to describe individual-level behaviour, individual-based models that are formulated from the bottom-up and aggregate individual-level behaviour to reveal population-level relationships, or hybrid models which combine the two approaches into a single model.The Australian Animal Disease Spread (AADIS hybrid model employs a deterministic equation-based model (EBM to model within-herd spread of FMD, and a stochastic, spatially-explicit agent-based model (ABM to model between-herd spread and control. The EBM provides concise and computationally efficient predictions of herd prevalence and clinical signs over time. The ABM captures the complex, stochastic and heterogeneous environment in which an FMD epidemic operates. The AADIS event-driven hybrid EBM/ABM architecture is a flexible, efficient and extensible framework for modelling the spread and control of disease in livestock on a national scale. We present an overview of the AADIS hybrid approach and a description of the model
Winkelmann, Stefanie; Schütte, Christof
2017-09-21
Well-mixed stochastic chemical kinetics are properly modeled by the chemical master equation (CME) and associated Markov jump processes in molecule number space. If the reactants are present in large amounts, however, corresponding simulations of the stochastic dynamics become computationally expensive and model reductions are demanded. The classical model reduction approach uniformly rescales the overall dynamics to obtain deterministic systems characterized by ordinary differential equations, the well-known mass action reaction rate equations. For systems with multiple scales, there exist hybrid approaches that keep parts of the system discrete while another part is approximated either using Langevin dynamics or deterministically. This paper aims at giving a coherent overview of the different hybrid approaches, focusing on their basic concepts and the relation between them. We derive a novel general description of such hybrid models that allows expressing various forms by one type of equation. We also check in how far the approaches apply to model extensions of the CME for dynamics which do not comply with the central well-mixed condition and require some spatial resolution. A simple but meaningful gene expression system with negative self-regulation is analysed to illustrate the different approximation qualities of some of the hybrid approaches discussed. Especially, we reveal the cause of error in the case of small volume approximations.
Ultra-Short-Term Wind Power Prediction Using a Hybrid Model
Mohammed, E.; Wang, S.; Yu, J.
2017-05-01
This paper aims to develop and apply a hybrid model of two data analytical methods, multiple linear regressions and least square (MLR&LS), for ultra-short-term wind power prediction (WPP), for example taking, Northeast China electricity demand. The data was obtained from the historical records of wind power from an offshore region, and from a wind farm of the wind power plant in the areas. The WPP achieved in two stages: first, the ratios of wind power were forecasted using the proposed hybrid method, and then the transformation of these ratios of wind power to obtain forecasted values. The hybrid model combines the persistence methods, MLR and LS. The proposed method included two prediction types, multi-point prediction and single-point prediction. WPP is tested by applying different models such as autoregressive moving average (ARMA), autoregressive integrated moving average (ARIMA) and artificial neural network (ANN). By comparing results of the above models, the validity of the proposed hybrid model is confirmed in terms of error and correlation coefficient. Comparison of results confirmed that the proposed method works effectively. Additional, forecasting errors were also computed and compared, to improve understanding of how to depict highly variable WPP and the correlations between actual and predicted wind power.
Winkelmann, Stefanie; Schütte, Christof
2017-09-01
Well-mixed stochastic chemical kinetics are properly modeled by the chemical master equation (CME) and associated Markov jump processes in molecule number space. If the reactants are present in large amounts, however, corresponding simulations of the stochastic dynamics become computationally expensive and model reductions are demanded. The classical model reduction approach uniformly rescales the overall dynamics to obtain deterministic systems characterized by ordinary differential equations, the well-known mass action reaction rate equations. For systems with multiple scales, there exist hybrid approaches that keep parts of the system discrete while another part is approximated either using Langevin dynamics or deterministically. This paper aims at giving a coherent overview of the different hybrid approaches, focusing on their basic concepts and the relation between them. We derive a novel general description of such hybrid models that allows expressing various forms by one type of equation. We also check in how far the approaches apply to model extensions of the CME for dynamics which do not comply with the central well-mixed condition and require some spatial resolution. A simple but meaningful gene expression system with negative self-regulation is analysed to illustrate the different approximation qualities of some of the hybrid approaches discussed. Especially, we reveal the cause of error in the case of small volume approximations.
Modelling the creep behaviour of tempered martensitic steel based on a hybrid approach
Energy Technology Data Exchange (ETDEWEB)
Yadav, Surya Deo, E-mail: surya.yadav@tugraz.at [Institute of Materials Science and Welding, Graz University of Technology, Kopernikusgasse 24, A-8010 Graz (Austria); Sonderegger, Bernhard, E-mail: bernhard.sonderegger@tugraz.at [Institute of Materials Science and Welding, Graz University of Technology, Kopernikusgasse 24, A-8010 Graz (Austria); Stracey, Muhammad, E-mail: strmuh001@myuct.ac.za [Centre for Materials Engineering, Department of Mechanical Engineering, University of Cape Town, Cape Town (South Africa); Poletti, Cecilia, E-mail: cecilia.poletti@tugraz.at [Institute of Materials Science and Welding, Graz University of Technology, Kopernikusgasse 24, A-8010 Graz (Austria)
2016-04-26
In this work, we present a novel hybrid approach to describe and model the creep behaviour of tempered martensitic steels. The hybrid approach couples a physically based model with a continuum damage mechanics (CDM) model. The creep strain is modelled describing the motions of three categories of dislocations: mobile, dipole and boundary. The initial precipitate state is simulated using the thermodynamic software tool MatCalc. The particle radii and number densities are incorporated into the creep model in terms of Zener drag pressure. The Orowan's equation for creep strain rate is modified to account for tertiary creep using softening parameters related to precipitate coarsening and cavitation. For the first time the evolution of internal variables such as dislocation densities, glide velocities, effective stresses on dislocations, internal stress from the microstructure, subgrain size, pressure on subgrain boundaries and softening parameters is discussed in detail. The model is validated with experimental data of P92 steel reported in the literature.
Simulation of Mercury's magnetosheath with a combined hybrid-paraboloid model
Parunakian, David; Dyadechkin, Sergey; Alexeev, Igor; Belenkaya, Elena; Khodachenko, Maxim; Kallio, Esa; Alho, Markku
2017-08-01
In this paper we introduce a novel approach for modeling planetary magnetospheres that involves a combination of the hybrid model and the paraboloid magnetosphere model (PMM); we further refer to it as the combined hybrid model. While both of these individual models have been successfully applied in the past, their combination enables us both to overcome the traditional difficulties of hybrid models to develop a self-consistent magnetic field and to compensate the lack of plasma simulation in the PMM. We then use this combined model to simulate Mercury's magnetosphere and investigate the geometry and configuration of Mercury's magnetosheath controlled by various conditions in the interplanetary medium. The developed approach provides a unique comprehensive view of Mercury's magnetospheric environment for the first time. Using this setup, we compare the locations of the bow shock and the magnetopause as determined by simulations with the locations predicted by stand-alone PMM runs and also verify the magnetic and dynamic pressure balance at the magnetopause. We also compare the results produced by these simulations with observational data obtained by the magnetometer on board the MErcury Surface, Space ENvironment, GEochemistry, and Ranging (MESSENGER) spacecraft along a dusk-dawn orbit and discuss the signatures of the magnetospheric features that appear in these simulations. Overall, our analysis suggests that combining the semiempirical PMM with a self-consistent global kinetic model creates new modeling possibilities which individual models cannot provide on their own.
Modeling of plasma and thermo-fluid transport in hybrid welding
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
A 5G Hybrid Channel Model Considering Rays and Geometric Stochastic Propagation Graph
DEFF Research Database (Denmark)
Steinböck, Gerhard; Karstensen, Anders; Kyösti, Pekka
2016-01-01
We consider a ray-tracing tool, in particular the METIS map based model for deterministic simulation of the channel impulse response. The ray-tracing tool is extended by adding a geometric stochastic propagation graph to model additional stochastic paths and the dense multipath components observed...... concept of a hybrid model that allows to simulate computationally efficient deterministic paths and the dense multipath components in a spatially consistent way....
Energy Technology Data Exchange (ETDEWEB)
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.
Solving Problems in Various Domains by Hybrid Models of High Performance Computations
Directory of Open Access Journals (Sweden)
Yurii Rogozhin
2014-03-01
Full Text Available This work presents a hybrid model of high performance computations. The model is based on membrane system (P~system where some membranes may contain quantum device that is triggered by the data entering the membrane. This model is supposed to take advantages of both biomolecular and quantum paradigms and to overcome some of their inherent limitations. The proposed approach is demonstrated through two selected problems: SAT, and image retrieving.
Development of hybrid 3-D hydrological modeling for the NCAR Community Earth System Model (CESM)
Energy Technology Data Exchange (ETDEWEB)
Zeng, Xubin [Univ. of Arizona, Tucson, AZ (United States); Troch, Peter [Univ. of Arizona, Tucson, AZ (United States); Pelletier, Jon [Univ. of Arizona, Tucson, AZ (United States); Niu, Guo-Yue [Univ. of Arizona, Tucson, AZ (United States); Gochis, David [NCAR Research Applications (RAL), Boulder, CO (United States)
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
Strategy and gaps for modeling, simulation, and control of hybrid systems
Energy Technology Data Exchange (ETDEWEB)
Rabiti, Cristian [Idaho National Lab. (INL), Idaho Falls, ID (United States); Garcia, Humberto E. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Hovsapian, Rob [Idaho National Lab. (INL), Idaho Falls, ID (United States); Kinoshita, Robert [Idaho National Lab. (INL), Idaho Falls, ID (United States); Mesina, George L. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Bragg-Sitton, Shannon M. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Boardman, Richard D. [Idaho National Lab. (INL), Idaho Falls, ID (United States)
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
Exploring key factors in online shopping with a hybrid model.
Chen, Hsiao-Ming; Wu, Chia-Huei; Tsai, Sang-Bing; Yu, Jian; Wang, Jiangtao; Zheng, Yuxiang
2016-01-01
Nowadays, the web increasingly influences retail sales. An in-depth analysis of consumer decision-making in the context of e-business has become an important issue for internet vendors. However, factors affecting e-business are complicated and intertwined. To stimulate online sales, understanding key influential factors and causal relationships among the factors is important. To gain more insights into this issue, this paper introduces a hybrid method, which combines the Decision Making Trial and Evaluation Laboratory (DEMATEL) with the analytic network process, called DANP method, to find out the driving factors that influence the online business mostly. By DEMATEL approach the causal graph showed that "online service" dimension has the highest degree of direct impact on other dimensions; thus, the internet vendor is suggested to made strong efforts on service quality throughout the online shopping process. In addition, the study adopted DANP to measure the importance of key factors, among which "transaction security" proves to be the most important criterion. Hence, transaction security should be treated with top priority to boost the online businesses. From our study with DANP approach, the comprehensive information can be visually detected so that the decision makers can spotlight on the root causes to develop effectual actions.
Photonic states mixing beyond the plasmon hybridization model
Energy Technology Data Exchange (ETDEWEB)
Suryadharma, Radius N. S.; Iskandar, Alexander A., E-mail: iskandar@fi.itb.ac.id; Tjia, May-On [Physics of Magnetism and Photonics Research Division, Faculty of Mathematics and Natural Sciences, Institut Teknologi Bandung, Jl. Ganesha 10, Bandung 40132 (Indonesia)
2016-07-28
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.
Fuzzy logic-based analogue forecasting and hybrid modelling of horizontal visibility
Tuba, Zoltán; Bottyán, Zsolt
2017-02-01
Forecasting visibility is one of the greatest challenges in aviation meteorology. At the same time, high accuracy visibility forecasts can significantly reduce or make avoidable weather-related risk in aviation as well. To improve forecasting visibility, this research links fuzzy logic-based analogue forecasting and post-processed numerical weather prediction model outputs in hybrid forecast. Performance of analogue forecasting model was improved by the application of Analytic Hierarchy Process. Then, linear combination of the mentioned outputs was applied to create ultra-short term hybrid visibility prediction which gradually shifts the focus from statistical to numerical products taking their advantages during the forecast period. It gives the opportunity to bring closer the numerical visibility forecast to the observations even it is wrong initially. Complete verification of categorical forecasts was carried out; results are available for persistence and terminal aerodrome forecasts (TAF) as well in order to compare. The average value of Heidke Skill Score (HSS) of examined airports of analogue and hybrid forecasts shows very similar results even at the end of forecast period where the rate of analogue prediction in the final hybrid output is 0.1-0.2 only. However, in case of poor visibility (1000-2500 m), hybrid (0.65) and analogue forecasts (0.64) have similar average of HSS in the first 6 h of forecast period, and have better performance than persistence (0.60) or TAF (0.56). Important achievement that hybrid model takes into consideration physics and dynamics of the atmosphere due to the increasing part of the numerical weather prediction. In spite of this, its performance is similar to the most effective visibility forecasting methods and does not follow the poor verification results of clearly numerical outputs.
Hybrid ensemble 4DVar assimilation of stratospheric ozone using a global shallow water model
Directory of Open Access Journals (Sweden)
D. R. Allen
2016-07-01
Full Text Available 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.
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…
Modeling and Nonlinear Control of Electric Power Stage in Hybrid Electric Vehicle
DEFF Research Database (Denmark)
Tahri, A.; El Fadil, H.; Guerrero, Josep M.
2014-01-01
This paper deals with the problem of modeling and controlling the electric power stage of hybrid electric vehicle. The controlled system consists of a fuel cell (FC) as a main source, a supercapacitor as an auxiliary source, two DC-DC power converters, an inverter and a traction induction motor...
Hybrid neural network model for the design of beam subjected to ...
Indian Academy of Sciences (India)
This paper demonstrates the applicability of Artiﬁcial Neural Networks (ANN) and Genetic Algorithms (GA) for the design of beams subjected to moment and shear. A hybrid neural network model which combines the features of feed forward neural networks and genetic algorithms has been developed for the design of beam ...
Hybrid Model of Inhomogeneous Solar Wind Plasma Heating by Alfven Wave Spectrum: Parametric Studies
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.
Improving head and neck CTA with hybrid and model-based iterative reconstruction techniques
Niesten, J. M.; van der Schaaf, I. C.; Vos, P. C.; Willemink, MJ; Velthuis, B. K.
2015-01-01
AIM: To compare image quality of head and neck computed tomography angiography (CTA) reconstructed with filtered back projection (FBP), hybrid iterative reconstruction (HIR) and model-based iterative reconstruction (MIR) algorithms. MATERIALS AND METHODS: The raw data of 34 studies were
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…
Sun, Xiaoqiang; Yuan, Chaochun; Cai, Yingfeng; Wang, Shaohua; Chen, Long
2017-09-01
This paper presents the hybrid modeling and the model predictive control of an air suspension system with damping multi-mode switching damper. Unlike traditional damper with continuously adjustable damping, in this study, a new damper with four discrete damping modes is applied to vehicle semi-active air suspension. The new damper can achieve different damping modes by just controlling the on-off statuses of two solenoid valves, which makes its damping adjustment more efficient and more reliable. However, since the damping mode switching induces different modes of operation, the air suspension system with the new damper poses challenging hybrid control problem. To model both the continuous/discrete dynamics and the switching between different damping modes, the framework of mixed logical dynamical (MLD) systems is used to establish the system hybrid model. Based on the resulting hybrid dynamical model, the system control problem is recast as a model predictive control (MPC) problem, which allows us to optimize the switching sequences of the damping modes by taking into account the suspension performance requirements. Numerical simulations results demonstrate the efficacy of the proposed control method finally.
Zhu, Wen; Liu, Junsheng; 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.
Directory of Open Access Journals (Sweden)
Wen Zhu
2014-01-01
Full Text Available 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.
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
Jackson, Chris J; Izadikah, Zahra; Oei, Tian P S
2012-06-01
Jackson's (2005, 2008a) hybrid model of learning identifies a number of learning mechanisms that lead to the emergence and maintenance of the balance between rationality and irrationality. We test a general hypothesis that Jackson's model will predict depressive symptoms, such that poor learning is related to depression. We draw comparisons between Jackson's model and Ellis' (2004) Rational Emotive Behavior Therapy and Theory (REBT) and thereby provide a set of testable learning mechanisms potentially underlying REBT. Results from 80 patients diagnosed with depression completed the learning styles profiler (LSP; Jackson, 2005) and two measures of depression. Results provide support for the proposed model of learning and further evidence that low rationality is a key predictor of depression. We conclude that the hybrid model of learning has the potential to explain some of the learning and cognitive processes related to the development and maintenance of irrational beliefs and depression. Copyright © 2011. Published by Elsevier B.V.
Simulation-optimization framework for multi-site multi-season hybrid stochastic streamflow modeling
Srivastav, Roshan; Srinivasan, K.; Sudheer, K. P.
2016-11-01
A simulation-optimization (S-O) framework is developed for the hybrid stochastic modeling of multi-site multi-season streamflows. The multi-objective optimization model formulated is the driver and the multi-site, multi-season hybrid matched block bootstrap model (MHMABB) is the simulation engine within this framework. The multi-site multi-season simulation model is the extension of the existing single-site multi-season simulation model. A robust and efficient evolutionary search based technique, namely, non-dominated sorting based genetic algorithm (NSGA - II) is employed as the solution technique for the multi-objective optimization within the S-O framework. The objective functions employed are related to the preservation of the multi-site critical deficit run sum and the constraints introduced are concerned with the hybrid model parameter space, and the preservation of certain statistics (such as inter-annual dependence and/or skewness of aggregated annual flows). The efficacy of the proposed S-O framework is brought out through a case example from the Colorado River basin. The proposed multi-site multi-season model AMHMABB (whose parameters are obtained from the proposed S-O framework) preserves the temporal as well as the spatial statistics of the historical flows. Also, the other multi-site deficit run characteristics namely, the number of runs, the maximum run length, the mean run sum and the mean run length are well preserved by the AMHMABB model. Overall, the proposed AMHMABB model is able to show better streamflow modeling performance when compared with the simulation based SMHMABB model, plausibly due to the significant role played by: (i) the objective functions related to the preservation of multi-site critical deficit run sum; (ii) the huge hybrid model parameter space available for the evolutionary search and (iii) the constraint on the preservation of the inter-annual dependence. Split-sample validation results indicate that the AMHMABB model is
Angular Structure of Jet Quenching Within a Hybrid Strong/Weak Coupling Model
Casalderrey-Solana, Jorge; Milhano, Guilherme; Pablos, Daniel; Rajagopal, Krishna
2017-01-01
Within the context of a hybrid strong/weak coupling model of jet quenching, we study the modification of the angular distribution of the energy within jets in heavy ion collisions, as partons within jet showers lose energy and get kicked as they traverse the strongly coupled plasma produced in the collision. To describe the dynamics transverse to the jet axis, we add the effects of transverse momentum broadening into our hybrid construction, introducing a parameter $K\\equiv \\hat q/T^3$ that governs its magnitude. We show that, because of the quenching of the energy of partons within a jet, even when $K\
DEFF Research Database (Denmark)
Yoon, Daeung; Zhdanov, Michael; Cai, Hongzhu
2015-01-01
) and integral equation (IE) methods. In the framework of this approach, we solve the Maxwell's equations for anomalous electric fields using the FD approximation on a staggered grid. Once the unknown electric fields in the computation domain of the FD method are computed, the electric and magnetic fields...... for numerical differentiation and interpolation. We have also developed an algorithm for 3D inversion of MCSEM data based on the hybrid FD-IE method. A model study for the 3D inversion of MCSEM data is presented to demonstrate the effectiveness of the developed hybrid method....
Kuba, N.; Murakami, M.
2010-01-01
The effect of hygroscopic seeding on warm rain clouds was examined using a hybrid cloud microphysical model combining a Lagrangian cloud condensation nuclei (CCN) activation model, a semi-Lagrangian droplet growth model, and an Eulerian spatial model for advection and sedimentation of droplets. This hybrid cloud microphysical model accurately estimated the effects of CCN on cloud microstructure and suggested the following conclusions for a moderate continental air mass (an air mass wit...
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.
Directory of Open Access Journals (Sweden)
Claudio S Quilodrán
Full Text Available 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.
Wind speed forecasting in three different regions of Mexico, using a hybrid ARIMA-ANN model
Energy Technology Data Exchange (ETDEWEB)
Cadenas, Erasmo [Facultad de Ingenieria Mecanica, Universidad Michoacana de San Nicolas de Hidalgo, Santiago Tapia No. 403, Centro (Mexico); Rivera, Wilfrido [Centro de Ivestigacion en Energia, Universidad Nacional Autonoma de Mexico, Apartado Postal 34, Temixco 62580, Morelos (Mexico)
2010-12-15
In this paper the wind speed forecasting in the Isla de Cedros in Baja California, in the Cerro de la Virgen in Zacatecas and in Holbox in Quintana Roo is presented. The time series utilized are average hourly wind speed data obtained directly from the measurements realized in the different sites during about one month. In order to do wind speed forecasting Hybrid models consisting of Autoregressive Integrated Moving Average (ARIMA) models and Artificial Neural Network (ANN) models were developed. The ARIMA models were first used to do the wind speed forecasting of the time series and then with the obtained errors ANN were built taking into account the nonlinear tendencies that the ARIMA technique could not identify, reducing with this the final errors. Once the Hybrid models were developed 48 data out of sample for each one of the sites were used to do the wind speed forecasting and the results were compared with the ARIMA and the ANN models working separately. Statistical error measures such as the mean error (ME), the mean square error (MSE) and the mean absolute error (MAE) were calculated to compare the three methods. The results showed that the Hybrid models predict the wind velocities with a higher accuracy than the ARIMA and ANN models in the three examined sites. (author)
Vuylsteke, M; Kuiper, M; Stam, P
2000-09-01
In this paper, a novel approach towards the prediction of hybrid performance and heterosis is presented. Here, we describe an approach based on: (i) the assessment of associations between AFLP(R) markers and hybrid performance and specific combining ability (SCA) across a set of hybrids; and (ii) the assumption that the joint effect of genetic factors (loci) determined this way can be obtained by addition. Estimated gene effects for grain yield varied from additive, partial dominance to overdominance. This procedure was applied to 53 interheterotic hybrids out of a 13 by 13 half-diallel among maize inbreds, evaluated for grain yield. The hybrid value, representing the joint effect of the genetic factors, accounted for up to 62.4% of the variation in the hybrid performance observed, whereas the corresponding efficiency of the SCA model was 36.8%. Efficiency of the prediction for hybrid performance was evaluated by means of a cross-validation procedure for grain yield of (i) the 53 interheterotic hybrids and (ii) 16 hybrids partly related to the 13 by 13 half-diallel. Comparisons in prediction efficiency with the 'distance' model were made. Because the map position of the selected markers is known, putative quantitative trait loci (QTL) affecting grain yield, in terms of hybrid performance or heterosis, are identified. Some QTL of grain yield detected in the present study were located in the vicinity of loci reported earlier as having quantitative effects on grain yield.
Comparing hybrid data assimilation methods on the Lorenz 1963 model with increasing non-linearity
Directory of Open Access Journals (Sweden)
Michael Goodliff
2015-05-01
Full Text Available We systematically compare the performance of ETKF-4DVAR, 4DVAR-BEN and 4DENVAR with respect to two traditional methods (4DVAR and ETKF and an ensemble transform Kalman smoother (ETKS on the Lorenz 1963 model. We specifically investigated this performance with increasing non-linearity and using a quasi-static variational assimilation algorithm as a comparison. Using the analysis root mean square error (RMSE as a metric, these methods have been compared considering (1 assimilation window length and observation interval size and (2 ensemble size to investigate the influence of hybrid background error covariance matrices and non-linearity on the performance of the methods. For short assimilation windows with close to linear dynamics, it has been shown that all hybrid methods show an improvement in RMSE compared to the traditional methods. For long assimilation window lengths in which non-linear dynamics are substantial, the variational framework can have difficulties finding the global minimum of the cost function, so we explore a quasi-static variational assimilation (QSVA framework. Of the hybrid methods, it is seen that under certain parameters, hybrid methods which do not use a climatological background error covariance do not need QSVA to perform accurately. Generally, results show that the ETKS and hybrid methods that do not use a climatological background error covariance matrix with QSVA outperform all other methods due to the full flow dependency of the background error covariance matrix which also allows for the most non-linearity.
Promoting Student Autonomy and Competence Using a Hybrid Model for Teaching Physical Activity
Directory of Open Access Journals (Sweden)
Christine Bachman
2015-01-01
Full Text Available For approximately twenty-years, Web-enhanced learning environments have been popular in higher education. Much research has examined how best practices can integrate technology, pedagogical theories, and resources to enhance learning. Numerous studies of hybrid teaching have revealed mostly positive effects. Yet, very little research has examined how to teach a successful physical activity course using a hybrid format. Review of the literature: We reviewed the research regarding the design and implementation of a Web-enhanced physical activity course in a college population using pedagogical principles of learning and the10 self-determination theory. Method: Data were collected from students at the beginning and end of the course. The hybrid course consisted of completing weekly online activities, and selecting and participating in a face-to-face physical activity based on student’s choice. Conclusion: The authors propose this template as a model to assist faculty in designing and implementing a blended physical activity course.
Model predictive control for power fluctuation supression in hybrid wind/PV/battery systems
DEFF Research Database (Denmark)
You, Shi; Liu, Zongyu; Zong, Yi
2015-01-01
A hybrid energy system, the combination of wind turbines, PV panels and battery storage with effective control mechanism, represents a promising solution to the power fluctuation problem when integrating renewable energy resources (RES) into conventional power systems. This paper proposes a model...... predictive control (MPC)-based algorithm for battery management in a hybrid wind/PV/battery system to suppress the short-term power fluctuation on the ‘minute’ scale. A case study with data collected from a practical hybrid system setup is used to demonstrate the effectiveness of the proposed algorithm...... together with a Monte Carlo simulation-based sensitivity analysis. In addition to illustrating the complementarity between the fluctuations of wind power and PV power, the results prove the proposed MPC algorithm is effective in fluctuation suppression but sensitive to factors such as forecast accuracy...
Analytical modeling of the gas generator frequency response in hybrid rocket boosters
Osherov, A.; Natan, B.; Gany, A.
1996-10-01
Différent types of hybrid engines are considered candidates for space launchers. The gas generator hybrid engine consists of a fuel-rich solid propellant gas generator whose partially burned products are mixed and further burned with a liquid oxidizer in a separate combustion chamber. The objective of this paper is to model and analyze the frequency response characteristics of such a gas generator, as a part of the problem of hybrid rockets longitudinal dynamic instability (POGO). The analysis takes into account the coupling between the gas flow within the grain ports and the elastic body vibrations. In principle, the gas generator admittance coincides with the response of a 'quarter-wave' resonator with dissipative force. It is found that the gas generator structure elasticity affects significantly the GG admittance in both the resonance frequency and the amplification factor.
A hybrid finite-difference and analytic element groundwater model
Haitjema, Henk M.; Feinstein, Daniel T.; Hunt, Randall J.; Gusyev, Maksym
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.
A hybrid, coupled approach for modeling charged fluids from the nano to the mesoscale
Cheung, James; Frischknecht, Amalie L.; Perego, Mauro; Bochev, Pavel
2017-11-01
We develop and demonstrate a new, hybrid simulation approach for charged fluids, which combines the accuracy of the nonlocal, classical density functional theory (cDFT) with the efficiency of the Poisson-Nernst-Planck (PNP) equations. The approach is motivated by the fact that the more accurate description of the physics in the cDFT model is required only near the charged surfaces, while away from these regions the PNP equations provide an acceptable representation of the ionic system. We formulate the hybrid approach in two stages. The first stage defines a coupled hybrid model in which the PNP and cDFT equations act independently on two overlapping domains, subject to suitable interface coupling conditions. At the second stage we apply the principles of the alternating Schwarz method to the hybrid model by using the interface conditions to define the appropriate boundary conditions and volume constraints exchanged between the PNP and the cDFT subdomains. Numerical examples with two representative examples of ionic systems demonstrate the numerical properties of the method and its potential to reduce the computational cost of a full cDFT calculation, while retaining the accuracy of the latter near the charged surfaces.
Directory of Open Access Journals (Sweden)
Pietra Paola
2012-04-01
Full Text Available We propose a hybrid classical-quantum model to study the motion of electrons in ultra-scaled confined nanostructures. The transport of charged particles, considered as one dimensional, is described by a quantum effective mass model in the active zone coupled directly to a drift-diffusion problem in the rest of the device. We explain how this hybrid model takes into account the peculiarities due to the strong confinement and we present numerical simulations for a simplified carbon nanotube. Nous proposons un modèle hybride classique-quantique pour décrire le mouvement des électrons dans des nanostructures très fortement confinées. Le transport des particules, consideré unidimensionel, est décrit par un modèle quantique avec masse effective dans la zone active couplé à un problème de dérive-diffusion dans le reste du domaine. Nous expliquons comment ce modèle hybride prend en compte les spécificités de ce très fort confinement et nous présentons des résultats numériques pour un nanotube de carbone simplifié.
Modeling Hybridization Kinetics of Gene Probes in a DNA Biochip Using FEMLAB.
Munir, Ahsan; Waseem, Hassan; Williams, Maggie R; Stedtfeld, Robert D; Gulari, Erdogan; Tiedje, James M; Hashsham, Syed A
2017-05-29
Microfluidic DNA biochips capable of detecting specific DNA sequences are useful in medical diagnostics, drug discovery, food safety monitoring and agriculture. They are used as miniaturized platforms for analysis of nucleic acids-based biomarkers. Binding kinetics between immobilized single stranded DNA on the surface and its complementary strand present in the sample are of interest. To achieve optimal sensitivity with minimum sample size and rapid hybridization, ability to predict the kinetics of hybridization based on the thermodynamic characteristics of the probe is crucial. In this study, a computer aided numerical model for the design and optimization of a flow-through biochip was developed using a finite element technique packaged software tool (FEMLAB; package included in COMSOL Multiphysics) to simulate the transport of DNA through a microfluidic chamber to the reaction surface. The model accounts for fluid flow, convection and diffusion in the channel and on the reaction surface. Concentration, association rate constant, dissociation rate constant, recirculation flow rate, and temperature were key parameters affecting the rate of hybridization. The model predicted the kinetic profile and signal intensities of eighteen 20-mer probes targeting vancomycin resistance genes (VRGs). Predicted signal intensities and hybridization kinetics strongly correlated with experimental data in the biochip (R² = 0.8131).
Modeling Hybridization Kinetics of Gene Probes in a DNA Biochip Using FEMLAB
Directory of Open Access Journals (Sweden)
Ahsan Munir
2017-05-01
Full Text Available Microfluidic DNA biochips capable of detecting specific DNA sequences are useful in medical diagnostics, drug discovery, food safety monitoring and agriculture. They are used as miniaturized platforms for analysis of nucleic acids-based biomarkers. Binding kinetics between immobilized single stranded DNA on the surface and its complementary strand present in the sample are of interest. To achieve optimal sensitivity with minimum sample size and rapid hybridization, ability to predict the kinetics of hybridization based on the thermodynamic characteristics of the probe is crucial. In this study, a computer aided numerical model for the design and optimization of a flow-through biochip was developed using a finite element technique packaged software tool (FEMLAB; package included in COMSOL Multiphysics to simulate the transport of DNA through a microfluidic chamber to the reaction surface. The model accounts for fluid flow, convection and diffusion in the channel and on the reaction surface. Concentration, association rate constant, dissociation rate constant, recirculation flow rate, and temperature were key parameters affecting the rate of hybridization. The model predicted the kinetic profile and signal intensities of eighteen 20-mer probes targeting vancomycin resistance genes (VRGs. Predicted signal intensities and hybridization kinetics strongly correlated with experimental data in the biochip (R2 = 0.8131.
A hybrid model for the computationally-efficient simulation of the cerebellar granular layer
Directory of Open Access Journals (Sweden)
Anna eCattani
2016-04-01
Full Text Available 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.
A hybrid deep neural network and physically based distributed model for river stage prediction
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
Huang, Mingzhi; Zhang, Tao; Ruan, Jujun; Chen, Xiaohong
2017-01-01
A new efficient hybrid intelligent approach based on fuzzy wavelet neural network (FWNN) was proposed for effectively modeling and simulating biodegradation process of Dimethyl phthalate (DMP) in an anaerobic/anoxic/oxic (AAO) wastewater treatment process. With the self learning and memory abilities of neural networks (NN), handling uncertainty capacity of fuzzy logic (FL), analyzing local details superiority of wavelet transform (WT) and global search of genetic algorithm (GA), the proposed hybrid intelligent model can extract the dynamic behavior and complex interrelationships from various water quality variables. For finding the optimal values for parameters of the proposed FWNN, a hybrid learning algorithm integrating an improved genetic optimization and gradient descent algorithm is employed. The results show, compared with NN model (optimized by GA) and kinetic model, the proposed FWNN model have the quicker convergence speed, the higher prediction performance, and smaller RMSE (0.080), MSE (0.0064), MAPE (1.8158) and higher R2 (0.9851) values. which illustrates FWNN model simulates effluent DMP more accurately than the mechanism model.
Evaluation of models generated via hybrid evolutionary algorithms ...
African Journals Online (AJOL)
This model showed a square correlation coefficient (R2) of 0.90 when tested with the testing dataset (chosen by bootstrapping from the 2000–2009 input dataset) and a R2 of 0.53 when tested with the 3-year 'unseen' dataset from 2010–2012. Keywords: cyanobacteria, drinking water treatment works, prediction models, ...
Hybrid modeling and empirical analysis of automobile supply chain network
Sun, Jun-yan; Tang, Jian-ming; Fu, Wei-ping; Wu, Bing-ying
2017-05-01
Based on the connection mechanism of nodes which automatically select upstream and downstream agents, a simulation model for dynamic evolutionary process of consumer-driven automobile supply chain is established by integrating ABM and discrete modeling in the GIS-based map. Firstly, the rationality is proved by analyzing the consistency of sales and changes in various agent parameters between the simulation model and a real automobile supply chain. Second, through complex network theory, hierarchical structures of the model and relationships of networks at different levels are analyzed to calculate various characteristic parameters such as mean distance, mean clustering coefficients, and degree distributions. By doing so, it verifies that the model is a typical scale-free network and small-world network. Finally, the motion law of this model is analyzed from the perspective of complex self-adaptive systems. The chaotic state of the simulation system is verified, which suggests that this system has typical nonlinear characteristics. This model not only macroscopically illustrates the dynamic evolution of complex networks of automobile supply chain but also microcosmically reflects the business process of each agent. Moreover, the model construction and simulation of the system by means of combining CAS theory and complex networks supplies a novel method for supply chain analysis, as well as theory bases and experience for supply chain analysis of auto companies.
Child human model development: a hybrid validation approach
Forbes, P.A.; Rooij, L. van; Rodarius, C.; Crandall, J.
2008-01-01
The current study presents a development and validation approach of a child human body model that will help understand child impact injuries and improve the biofidelity of child anthropometric test devices. Due to the lack of fundamental child biomechanical data needed to fully develop such models a
Hybrid Model Predictive Control for Optimizing Gestational Weight Gain Behavioral Interventions.
Dong, Yuwen; Rivera, Daniel E; Downs, Danielle S; Savage, Jennifer S; Thomas, Diana M; Collins, Linda M
2013-01-01
Excessive gestational weight gain (GWG) represents a major public health issue. In this paper, we pursue a control engineering approach to the problem by applying model predictive control (MPC) algorithms to act as decision policies in the intervention for assigning optimal intervention dosages. The intervention components consist of education, behavioral modification and active learning. The categorical nature of the intervention dosage assignment problem dictates the need for hybrid model predictive control (HMPC) schemes, ultimately leading to improved outcomes. The goal is to design a controller that generates an intervention dosage sequence which improves a participant's healthy eating behavior and physical activity to better control GWG. An improved formulation of self-regulation is also presented through the use of Internal Model Control (IMC), allowing greater flexibility in describing self-regulatory behavior. Simulation results illustrate the basic workings of the model and demonstrate the benefits of hybrid predictive control for optimized GWG adaptive interventions.
Accurate modeling of switched reluctance machine based on hybrid trained WNN
Directory of Open Access Journals (Sweden)
Shoujun Song
2014-04-01
Full Text Available 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.
Accurate modeling of switched reluctance machine based on hybrid trained WNN
Song, Shoujun; Ge, Lefei; Ma, Shaojie; Zhang, Man
2014-04-01
According to the strong nonlinear electromagnetic characteristics of switched reluctance machine (SRM), a novel accurate modeling method is proposed based on hybrid trained wavelet neural network (WNN) which combines improved genetic algorithm (GA) with gradient descent (GD) method to train the network. In the novel method, WNN is trained by GD method based on the initial weights obtained per improved GA optimization, and the global parallel searching capability of stochastic algorithm and local convergence speed of deterministic algorithm are combined to enhance the training accuracy, stability and speed. Based on the measured electromagnetic characteristics of a 3-phase 12/8-pole SRM, the nonlinear simulation model is built by hybrid trained WNN in Matlab. The phase current and mechanical characteristics from simulation under different working conditions meet well with those from experiments, which indicates the accuracy of the model for dynamic and static performance evaluation of SRM and verifies the effectiveness of the proposed modeling method.
Chiadamrong, N.; Piyathanavong, V.
2017-04-01
Models that aim to optimize the design of supply chain networks have gained more interest in the supply chain literature. Mixed-integer linear programming and discrete-event simulation are widely used for such an optimization problem. We present a hybrid approach to support decisions for supply chain network design using a combination of analytical and discrete-event simulation models. The proposed approach is based on iterative procedures until the difference between subsequent solutions satisfies the pre-determined termination criteria. The effectiveness of proposed approach is illustrated by an example, which shows closer to optimal results with much faster solving time than the results obtained from the conventional simulation-based optimization model. The efficacy of this proposed hybrid approach is promising and can be applied as a powerful tool in designing a real supply chain network. It also provides the possibility to model and solve more realistic problems, which incorporate dynamism and uncertainty.
Hybrid Scheme for Modeling Local Field Potentials from Point-Neuron Networks
DEFF Research Database (Denmark)
Hagen, Espen; Dahmen, David; Stavrinou, Maria L
2016-01-01
on populations of network-equivalent multicompartment neuron models with layer-specific synaptic connectivity, can be used with an arbitrary number of point-neuron network populations, and allows for a full separation of simulated network dynamics and LFPs. We apply the scheme to a full-scale cortical network...... and electrophysiological features of neurons near the recording electrode, as well as synaptic inputs from the entire network. Here we propose a hybrid modeling scheme combining efficient point-neuron network models with biophysical principles underlying LFP generation by real neurons. The LFP predictions rely...... model for a ∼1 mm(2) patch of primary visual cortex, predict laminar LFPs for different network states, assess the relative LFP contribution from different laminar populations, and investigate effects of input correlations and neuron density on the LFP. The generic nature of the hybrid scheme and its...
Directory of Open Access Journals (Sweden)
Mohammad Taghi Ameli
2012-01-01
Full Text Available Transmission Network Expansion Planning (TNEP is a basic part of power network planning that determines where, when and how many new transmission lines should be added to the network. So, the TNEP is an optimization problem in which the expansion purposes are optimized. Artificial Intelligence (AI tools such as Genetic Algorithm (GA, Simulated Annealing (SA, Tabu Search (TS and Artificial Neural Networks (ANNs are methods used for solving the TNEP problem. Today, by using the hybridization models of AI tools, we can solve the TNEP problem for large-scale systems, which shows the effectiveness of utilizing such models. In this paper, a new approach to the hybridization model of Probabilistic Neural Networks (PNNs and Harmony Search Algorithm (HSA was used to solve the TNEP problem. Finally, by considering the uncertain role of the load based on a scenario technique, this proposed model was tested on the Garver’s 6-bus network.
A Hybrid Setarx Model for Spikes in Tight Electricity Markets
Directory of Open Access Journals (Sweden)
Carlo Lucheroni
2012-01-01
Full Text Available The paper discusses a simple looking but highly nonlinear regime-switching, self-excited threshold model for hourly electricity prices in continuous and discrete time. The regime structure of the model is linked to organizational features of the market. In continuous time, the model can include spikes without using jumps, by defining stochastic orbits. In passing from continuous time to discrete time, the stochastic orbits survive discretization and can be identified again as spikes. A calibration technique suitable for the discrete version of this model, which does not need deseasonalization or spike filtering, is developed, tested and applied to market data. The discussion of the properties of the model uses phase-space analysis, an approach uncommon in econometrics. (original abstract
A hybrid source apportionment model integrating measured data and air quality model results
Schichtel, Bret A.; Malm, William C.; Gebhart, Kristi A.; Barna, Michael G.; Knipping, Eladio M.
2006-04-01
The Big Bend Regional Aerosol and Visibility (BRAVO) study was an intensive air quality study designed to understand the causes of haze in Big Bend National Park. Daily speciated fine aerosols were measured from July through October 1999 at 37 sites located mostly in Texas. In support of BRAVO, two chemical transport models (CTMs) were used to apportion particulate sulfate at Big Bend and other sites in Texas to sources in the eastern and western United States, Texas, Mexico, and the Carbón I and II coal-fired power plants, located 225 km southeast of Big Bend in Mexico. Analysis of the CTM source attribution results and comparison to results from receptor models revealed systematic biases. To reduce the multiplicative biases, a hybrid source apportionment model, based on inverse modeling, was developed that adjusted the initial CTM source contributions so the modeled sulfate concentrations optimally fit the measured data, resulting in refined daily source contributions. The method was tested using synthetic data and successfully reduced source attribution biases. The refined sulfate source attribution results reduced the initial eastern U.S. contribution to Big Bend, averaged over the BRAVO study period, from ˜40% to ˜30%, while Mexico's contribution increased from 24-32% to ˜40%. The contribution from the Carbón facility increased from ˜14% to over 20%. Contributions from Texas and the western United States changed little, with final contributions of ˜16% and 5-9%, respectively. The increase in Mexico's contribution is consistent with more recent SO2 emissions estimates that indicate that the BRAVO Mexican SO2 emissions were underestimated. Source attribution results for other monitoring sites in west Texas were similar to results at Big Bend. In eastern Texas, the eastern United States accounted for up to 70% of the measured sulfate, with Texas contributing ˜20-30%.
Energy Technology Data Exchange (ETDEWEB)
Champagnat, R.; Valette, R. [Centre National de la Recherche Scientifique (CNRS), 31 - Toulouse (France). Laboratoire d`Analyse et d`Architecture des Systemes; Pingaud, H.; Flaus, J.M. [ENSIGC, Ecole Nationale Superieure d`Ingenieurs de Genie Chimique, 31 - Toulouse (France); Alla, H. [ENSIEG, Ecole Nationale Superieure d`Ingenieurs Electriciens de Grenoble, 38 (France); Valentin-Roubinet, C. [Universite Claude Bernard, 69 - Villeurbanne (France). LAGEP, Laboratoire d`Automatique et de Genie des Pocedes
1998-06-01
This paper presents a comparative study of various approaches for modeling hybrid systems by means of Petri nets. The comparison is based on a simplified view of an industrial device: a gas storage unit. This example illustrates the limits of the discrete-time based approach offered by Coloured Petri nets, those of Hybrid Petri nets when some continuous variables are connected by algebraic constraints and those of Petri nets with differential algebraic equations when some continuous variables are shared by various sub-models. (authors) 27 refs.
Development and evaluation of a watershed-scale hybrid hydrologic model
Cho, Younghyun
2016-01-01
A watershed-scale hybrid hydrologic model (Distributed-Clark), which is a lumped conceptual and distributed feature model, was developed to predict spatially distributed short- and long-term rainfall runoff generation and routing using relatively simple methodologies and state-of-the-art spatial data in a GIS environment. In Distributed-Clark, spatially distributed excess rainfall estimated with the SCS curve number method and a GIS-based set of separated unit hydrographs (spatially distribut...
Valuation and Modeling of EQ-5D-5L Health States Using a Hybrid Approach.
Ramos-Goñi, Juan M; Pinto-Prades, Jose L; Oppe, Mark; Cabasés, Juan M; Serrano-Aguilar, Pedro; Rivero-Arias, Oliver
2017-07-01
The EQ-5D instrument is the most widely used preference-based health-related quality of life questionnaire in cost-effectiveness analysis of health care technologies. Recently, a version called EQ-5D-5L with 5 levels on each dimension was developed. This manuscript explores the performance of a hybrid approach for the modeling of EQ-5D-5L valuation data. Two elicitation techniques, the composite time trade-off, and discrete choice experiments, were applied to a sample of the Spanish population (n=1000) using a computer-based questionnaire. The sampling process consisted of 2 stages: stratified sampling of geographic area, followed by systematic sampling in each area. A hybrid regression model combining composite time trade-off and discrete choice data was used to estimate the potential value sets using main effects as starting point. The comparison between the models was performed using the criteria of logical consistency, goodness of fit, and parsimony. Twenty-seven participants from the 1000 were removed following the exclusion criteria. The best-fitted model included 2 significant interaction terms but resulted in marginal improvements in model fit compared to the main effects model. We therefore selected the model results with main effects as a potential value set for this methodological study, based on the parsimony criteria. The results showed that the main effects hybrid model was consistent, with a range of utility values between 1 and -0.224. This paper shows the feasibility of using a hybrid approach to estimate a value set for EQ-5D-5L valuation data.
Preliminary Hybrid Modeling of the Panama Canal: Operations and Salinity Diffusion
Directory of Open Access Journals (Sweden)
Luis Rabelo
2012-01-01
Full Text Available This paper deals with the initial modeling of water salinity and its diffusion into the lakes during lock operation on the Panama Canal. A hybrid operational model was implemented using the AnyLogic software simulation environment. This was accomplished by generating an operational discrete-event simulation model and a continuous simulation model based on differential equations, which modeled the salinity diffusion in the lakes. This paper presents that unique application and includes the effective integration of lock operations and its impact on the environment.
THYME: Toolkit for Hybrid Modeling of Electric Power Systems
Energy Technology Data Exchange (ETDEWEB)
2011-01-01
THYME is an object oriented library for building models of wide area control and communications in electric power systems. This software is designed as a module to be used with existing open source simulators for discrete event systems in general and communication systems in particular. THYME consists of a typical model for simulating electro-mechanical transients (e.g., as are used in dynamic stability studies), data handling objects to work with CDF and PTI formatted power flow data, and sample models of discrete sensors and controllers.
Hybrid Computational Model for High-Altitude Aeroassist Vehicles Project
National Aeronautics and Space Administration — The proposed effort addresses a need for accurate computational models to support aeroassist and entry vehicle system design over a broad range of flight conditions...
Directory of Open Access Journals (Sweden)
Kang-Wook Lee
2017-05-01
Full Text Available An important issue for international businesses and academia is selecting countries in which to expand in order to achieve entrepreneurial sustainability. This study develops a country selection model for sustainable construction businesses using both objective and subjective information. The objective information consists of 14 variables related to country risk and project performance in 32 countries over 25 years. This hybrid model applies subjective weighting from industrial experts to objective information using a fuzzy LinPreRa-based Analytic Hierarchy Process. The hybrid model yields a more accurate country selection compared to a purely objective information-based model in experienced countries. Interestingly, the hybrid model provides some different predictions with only subjective opinions in unexperienced countries, which implies that expert opinion is not always reliable. In addition, feedback from five experts in top international companies is used to validate the model’s completeness, effectiveness, generality, and applicability. The model is expected to aid decision makers in selecting better candidate countries that lead to sustainable business success.
Hybrid modeling of microbial exopolysaccharide (EPS) production: The case of Enterobacter A47.
Marques, Rodolfo; von Stosch, Moritz; Portela, Rui M C; Torres, Cristiana A V; Antunes, Sílvia; Freitas, Filomena; Reis, Maria A M; Oliveira, Rui
2017-03-20
Enterobacter A47 is a bacterium that produces high amounts of a fucose-rich exopolysaccharide (EPS) from glycerol residue of the biodiesel industry. The fed-batch process is characterized by complex non-linear dynamics with highly viscous pseudo-plastic rheology due to the accumulation of EPS in the culture medium. In this paper, we study hybrid modeling as a methodology to increase the predictive power of models for EPS production optimization. We compare six hybrid structures that explore different levels of knowledge-based and machine-learning model components. Knowledge-based components consist of macroscopic material balances, Monod type kinetics, cardinal temperature and pH (CTP) dependency and power-law viscosity models. Unknown dependencies are set to be identified by a feedforward artificial neural network (ANN). A semiparametric identification schema is applied resorting to a data set of 13 independent fed-batch experiments. A parsimonious hybrid model was identified that describes the dynamics of the 13 experiments with the same parameterization. The final model is specific to Enterobacter A47 but can be easily extended to other microbial EPS processes. Copyright © 2017 Elsevier B.V. All rights reserved.
Template-Assisted Metabolic Reconstruction and Assembly of Hybrid Bacterial Models.
Vignolini, Tiziano; Mengoni, Alessio; Fondi, Marco
2018-01-01
Intraspecific genomic exchanges happen frequently between bacteria living in the same natural environment and can also be performed artificially in the laboratory for basic research or genetic/metabolic engineering purposes. In silico metabolic reconstruction and simulation of the metabolism of the hybrid strains that result from these processes can be used to predict the phenotypic outcome of such genomic rearrangements; this can be especially helpful as a designing tool in the purview of synthetic biology. However, reconstructing the metabolism of a bacterium with a hybrid genome through in silico approaches is not a trivial task, as it requires taking into account the complex relationships existing between metabolic genes and how they change (or remain unchanged) when new genes are placed in a different genomic context. Furthermore, in order to "mix" the metabolic models of different bacterial strains one needs at least two different metabolic models to begin with, and reconstructing a genome-scale model from the ground up is a challenging task itself, requiring an intensive manual effort and a great deal of information. In this chapter, we propose two general protocols to address the aforementioned issues of: (1) quickly generating strain-specific metabolic models, given the relevant genomic sequence and an already existing, high-quality metabolic model of a different strain belonging to the same species, and (2) reconstructing the metabolic model of a hybrid strain containing genomic elements from two different parental strains.
Hybrid Scheme for Modeling Local Field Potentials from Point-Neuron Networks.
Hagen, Espen; Dahmen, David; Stavrinou, Maria L; Lindén, Henrik; Tetzlaff, Tom; van Albada, Sacha J; Grün, Sonja; Diesmann, Markus; Einevoll, Gaute T
2016-12-01
With rapidly advancing multi-electrode recording technology, the local field potential (LFP) has again become a popular measure of neuronal activity in both research and clinical applications. Proper understanding of the LFP requires detailed mathematical modeling incorporating the anatomical and electrophysiological features of neurons near the recording electrode, as well as synaptic inputs from the entire network. Here we propose a hybrid modeling scheme combining efficient point-neuron network models with biophysical principles underlying LFP generation by real neurons. The LFP predictions rely on populations of network-equivalent multicompartment neuron models with layer-specific synaptic connectivity, can be used with an arbitrary number of point-neuron network populations, and allows for a full separation of simulated network dynamics and LFPs. We apply the scheme to a full-scale cortical network model for a ∼1 mm(2) patch of primary visual cortex, predict laminar LFPs for different network states, assess the relative LFP contribution from different laminar populations, and investigate effects of input correlations and neuron density on the LFP. The generic nature of the hybrid scheme and its public implementation in hybridLFPy form the basis for LFP predictions from other and larger point-neuron network models, as well as extensions of the current application with additional biological detail. © The Author 2016. Published by Oxford University Press.
Quilodrán, Claudio S; Montoya-Burgos, Juan I; Currat, Mathias
2015-02-01
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.
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.
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.
Modelling and Optimising the Value of a Hybrid Solar-Wind System
Nair, Arjun; Murali, Kartik; Anbuudayasankar, S. P.; Arjunan, C. V.
2017-05-01
In this paper, a net present value (NPV) approach for a solar hybrid system has been presented. The system, in question aims at supporting an investor by assessing an investment in solar-wind hybrid system in a given area. The approach follow a combined process of modelling the system, with optimization of major investment-related variables to maximize the financial yield of the investment. The consideration of solar wind hybrid supply presents significant potential for cost reduction. The investment variables concern the location of solar wind plant, and its sizing. The system demand driven, meaning that its primary aim is to fully satisfy the energy demand of the customers. Therefore, the model is a practical tool in the hands of investor to assess and optimize in financial terms an investment aiming at covering real energy demand. Optimization is performed by taking various technical, logical constraints. The relation between the maximum power obtained between individual system and the hybrid system as a whole in par with the net present value of the system has been highlighted.
Introducing A Hybrid Data Mining Model to Evaluate Customer Loyalty
Directory of Open Access Journals (Sweden)
H. Alizadeh
2016-12-01
Full Text Available The main aim of this study was introducing a comprehensive model of bank customers᾽ loyalty evaluation based on the assessment and comparison of different clustering methods᾽ performance. This study also pursues the following specific objectives: a using different clustering methods and comparing them for customer classification, b finding the effective variables in determining the customer loyalty, and c using different collective classification methods to increase the modeling accuracy and comparing the results with the basic methods. Since loyal customers generate more profit, this study aims at introducing a two-step model for classification of customers and their loyalty. For this purpose, various methods of clustering such as K-medoids, X-means and K-means were used, the last of which outperformed the other two through comparing with Davis-Bouldin index. Customers were clustered by using K-means and members of these four clusters were analyzed and labeled. Then, a predictive model was run based on demographic variables of customers using various classification methods such as DT (Decision Tree, ANN (Artificial Neural Networks, NB (Naive Bayes, KNN (K-Nearest Neighbors and SVM (Support Vector Machine, as well as their bagging and boosting to predict the class of loyal customers. The results showed that the bagging-ANN was the most accurate method in predicting loyal customers. This two-stage model can be used in banks and financial institutions with similar data to identify the type of future customers.
Hybrid Corporate Performance Prediction Model Considering Technical Capability
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Joonhyuck Lee
2016-07-01
Full Text Available Many studies have tried to predict corporate performance and stock prices to enhance investment profitability using qualitative approaches such as the Delphi method. However, developments in data processing technology and machine-learning algorithms have resulted in efforts to develop quantitative prediction models in various managerial subject areas. We propose a quantitative corporate performance prediction model that applies the support vector regression (SVR algorithm to solve the problem of the overfitting of training data and can be applied to regression problems. The proposed model optimizes the SVR training parameters based on the training data, using the genetic algorithm to achieve sustainable predictability in changeable markets and managerial environments. Technology-intensive companies represent an increasing share of the total economy. The performance and stock prices of these companies are affected by their financial standing and their technological capabilities. Therefore, we apply both financial indicators and technical indicators to establish the proposed prediction model. Here, we use time series data, including financial, patent, and corporate performance information of 44 electronic and IT companies. Then, we predict the performance of these companies as an empirical verification of the prediction performance of the proposed model.
Hybrid Modelling of a Traveling Wave Piezoelectric Motor
DEFF Research Database (Denmark)
El, Ghouti N.
This thesis considers the modeling of the traveling wave piezoelectric motor (PEM). The rotary traveling wave ultrasonic motor "Shinsei type USR60" is the case study considered in this work. The traveling wave PEM has excellent performance and many useful features such as high holding torque, high...... of an ultrasonic traveling wave rotary piezoelectric motor. This approach is carried out on the basis of the experimental investigation combined with the electrical network method. Consequently, an insight in the analysis of the electromechanical coupling force factor, which is responsible for the electrical...... for control purposes. Consequently, a general state space model is derived on the basis of the special design of the motor of interest, which is a two phase symmetrical system. Furthermore, a simplified model is derived within the framework of various assumptions on the behavior of the stator, which makes...
Formal verification of dynamic hybrid systems: a NuSMV-based model checking approach
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Xu Zhi
2018-01-01
Full Text Available Software security is an important and challenging research topic in developing dynamic hybrid embedded software systems. Ensuring the correct behavior of these systems is particularly difficult due to the interactions between the continuous subsystem and the discrete subsystem. Currently available security analysis methods for system risks have been limited, as they rely on manual inspections of the individual subsystems under simplifying assumptions. To improve this situation, a new approach is proposed that is based on the symbolic model checking tool NuSMV. A dual PID system is used as an example system, for which the logical part and the computational part of the system are modeled in a unified manner. Constraints are constructed on the controlled object, and a counter-example path is ultimately generated, indicating that the hybrid system can be analyzed by the model checking tool.
New hybrid turbulence modelling approach, with application to dynamic stall control
Haering, Sigfried; Moser, Robert
2014-11-01
We present numerical studies of a stalled airfoil experiencing transitory flow control using a new hybrid RANS/LES modeling approach developed specifically for such challenging flow scenarios. Traditional hybrid approaches exhibit deficiencies when used for fluctuating smooth-wall separation and reattachment necessitating ad-hoc delaying functions and model tuning making them no longer useful as a predictive tool. Additionally, complex geometries and flows often require high cell aspect-ratios and large grid gradients as a compromise between resolution and cost. Such transitions and inconsistencies in resolution detrimentally effect the fidelity of the simulation. Our approach more naturally transitions between RANS to LES obviating the need for tuning and directly accounts for anisotropy and inhomogeneity in the flow and grid. The results of these simulations not only provide fundamental insight into experimentally observed stall control mechanisms but also display the versatility and accuracy of the new modeling method in simulating complex flow phenomena.
Model-Invariant Hybrid Computations of Separated Flows for RCA Standard Test Cases
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
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.
Parameters Design for a Parallel Hybrid Electric Bus Using Regenerative Brake Model
Directory of Open Access Journals (Sweden)
Zilin Ma
2014-01-01
Full Text Available A design methodology which uses the regenerative brake model is introduced to determine the major system parameters of a parallel electric hybrid bus drive train. Hybrid system parameters mainly include the power rating of internal combustion engine (ICE, gear ratios of transmission, power rating, and maximal torque of motor, power, and capacity of battery. The regenerative model is built in the vehicle model to estimate the regenerative energy in the real road conditions. The design target is to ensure that the vehicle meets the specified vehicle performance, such as speed and acceleration, and at the same time, operates the ICE within an expected speed range. Several pairs of parameters are selected from the result analysis, and the fuel saving result in the road test shows that a 25% reduction is achieved in fuel consumption.
Developed Hybrid Model for Propylene Polymerisation at Optimum Reaction Conditions
Directory of Open Access Journals (Sweden)
Mohammad Jakir Hossain Khan
2016-02-01
Full Text Available A statistical model combined with CFD (computational fluid dynamic method was used to explain the detailed phenomena of the process parameters, and a series of experiments were carried out for propylene polymerisation by varying the feed gas composition, reaction initiation temperature, and system pressure, in a fluidised bed catalytic reactor. The propylene polymerisation rate per pass was considered the response to the analysis. Response surface methodology (RSM, with a full factorial central composite experimental design, was applied to develop the model. In this study, analysis of variance (ANOVA indicated an acceptable value for the coefficient of determination and a suitable estimation of a second-order regression model. For better justification, results were also described through a three-dimensional (3D response surface and a related two-dimensional (2D contour plot. These 3D and 2D response analyses provided significant and easy to understand findings on the effect of all the considered process variables on expected findings. To diagnose the model adequacy, the mathematical relationship between the process variables and the extent of polymer conversion was established through the combination of CFD with statistical tools. All the tests showed that the model is an excellent fit with the experimental validation. The maximum extent of polymer conversion per pass was 5.98% at the set time period and with consistent catalyst and co-catalyst feed rates. The optimum conditions for maximum polymerisation was found at reaction temperature (RT 75 °C, system pressure (SP 25 bar, and 75% monomer concentration (MC. The hydrogen percentage was kept fixed at all times. The coefficient of correlation for reaction temperature, system pressure, and monomer concentration ratio, was found to be 0.932. Thus, the experimental results and model predicted values were a reliable fit at optimum process conditions. Detailed and adaptable CFD results were capable
Spatial self-organization in hybrid models of multicellular adhesion
Bonforti, Adriano; Duran-Nebreda, Salva; Montañez, Raúl; Solé, Ricard
2016-10-01
Spatial self-organization emerges in distributed systems exhibiting local interactions when nonlinearities and the appropriate propagation of signals are at work. These kinds of phenomena can be modeled with different frameworks, typically cellular automata or reaction-diffusion systems. A different class of dynamical processes involves the correlated movement of agents over space, which can be mediated through chemotactic movement or minimization of cell-cell interaction energy. A classic example of the latter is given by the formation of spatially segregated assemblies when cells display differential adhesion. Here, we consider a new class of dynamical models, involving cell adhesion among two stochastically exchangeable cell states as a minimal model capable of exhibiting well-defined, ordered spatial patterns. Our results suggest that a whole space of pattern-forming rules is hosted by the combination of physical differential adhesion and the value of probabilities modulating cell phenotypic switching, showing that Turing-like patterns can be obtained without resorting to reaction-diffusion processes. If the model is expanded allowing cells to proliferate and die in an environment where diffusible nutrient and toxic waste are at play, different phases are observed, characterized by regularly spaced patterns. The analysis of the parameter space reveals that certain phases reach higher population levels than other modes of organization. A detailed exploration of the mean-field theory is also presented. Finally, we let populations of cells with different adhesion matrices compete for reproduction, showing that, in our model, structural organization can improve the fitness of a given cell population. The implications of these results for ecological and evolutionary models of pattern formation and the emergence of multicellularity are outlined.
Ranjbaran, Mina; Galiana, Henrietta L.
2015-01-01
The vestibulo-ocular reflex (VOR) is an involuntary eye movement evoked by head movements. It is also influenced by viewing distance. This paper presents a hybrid nonlinear bilateral model for the horizontal angular vestibulo-ocular reflex (AVOR) in the dark. The model is based on known interconnections between saccadic burst circuits in the brainstem and ocular premotor areas in the vestibular nuclei during fast and slow phase intervals of nystagmus. We implemented a viable switching strategy for the timing of nystagmus events to allow emulation of real nystagmus data. The performance of the hybrid model is evaluated with simulations, and results are consistent with experimental observations. The hybrid model replicates realistic AVOR nystagmus patterns during sinusoidal or step head rotations in the dark and during interactions with vergence, e.g., fixation distance. By simply assigning proper nonlinear neural computations at the premotor level, the model replicates all reported experimental observations. This work sheds light on potential underlying neural mechanisms driving the context dependent AVOR and explains contradictory results in the literature. Moreover, context-dependent behaviors in more complex motor systems could also rely on local nonlinear neural computations. PMID:25709578
Directory of Open Access Journals (Sweden)
Mina eRanjbaran
2015-02-01
Full Text Available The vestibulo-ocular reflex (VOR is an involuntary eye movement evoked by head movements. It is also influenced by viewing distance. This paper presents a hybrid nonlinear bilateral model for the horizontal angular vestibulo-ocular reflex (AVOR in the dark. The model is based on known interconnections between saccadic burst circuits in the brainstem and ocular premotor areas in the vestibular nuclei during fast and slow phase intervals of nystagmus. We implemented a viable switching strategy for the timing of nystagmus events to allow emulation of real nystagmus data. The performance of the hybrid model is evaluated with simulations, and results are consistent with experimental observations. The hybrid model replicates realistic AVOR nystagmus patterns during sinusoidal or step head rotations in the dark and during interactions with vergence, e.g. fixation distance. By simply assigning proper nonlinear neural computations at the premotor level, the model replicates all reported experimental observations. This work sheds light on potential underlying neural mechanisms driving the context dependent AVOR and explains contradictory results in the literature. Moreover, context-dependent behaviors in more complex motor systems could also rely on local nonlinear neural computations.
Directory of Open Access Journals (Sweden)
Zhukov Ilya S.
2016-01-01
Full Text Available On the basis of obtained analytical estimate of characteristics of hybrid solid-propellant rocket engine verification of earlier developed physical and mathematical model of processes in a hybrid solid-propellant rocket engine for quasi-steady-state flow regime was performed. Comparative analysis of calculated and analytical data indicated satisfactory comparability of simulation results.
DEFF Research Database (Denmark)
Han, Renke; Meng, Lexuan; Guerrero, Josep M.
2017-01-01
The paper proposes a hybrid droop control strategy to enhance the stability and increase maximum constant power loads (CPLs) capability of DC microgrids in a realistic scenario. By capturing the detailed model of inner control loops and hybrid droop control and general dc MG topology, a thorough...
DEFF Research Database (Denmark)
Han, Renke; Meng, Lexuan; Guerrero, Josep M.
2017-01-01
The paper proposes a hybrid droop control strategy to enhance the stability and increase maximum constant power loads (CPLs) capability of DC microgrids in a realistic scenario. By capturing the detailed model of inner control loops and hybrid droop control and general dc MG topology, a thorough ...
Scaling Properties of a Hybrid Fermi-Ulam-Bouncer Model
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Diego F. M. Oliveira
2009-01-01
under the framework of scaling description. The model is described by using a two-dimensional nonlinear area preserving mapping. Our results show that the chaotic regime below the lowest energy invariant spanning curve is scaling invariant and the obtained critical exponents are used to find a universal plot for the second momenta of the average velocity.
Pore-to-Darcy Scale Hybrid Multiscale Finite Volume Model for Reactive Flow and Transport
Barajas-Solano, D. A.; Tartakovsky, A. M.
2016-12-01
In the present work we develop a hybrid scheme for the coupling and temporal integration of grid-based, continuum models for pore-scale and Darcy-scale flow and reactive transport. The hybrid coupling strategy consists on applying Darcy-scale and pore-scale flow and reactive transport models over overlapping subdomains Ω C and Ω F, and enforcing continuity of state and fluxes by means of restriction and prolongation operations defined over the overlap subdomain Ω hs ≡ Ω C \\cap Ω F. For the pore-scale model, we use a Multiscale Finite Volume (MsFV) characterization of the pore-scale state in terms of Darcy-scale degrees of freedom and local functions defined as the solution of pore-scale problems. The hybrid MsFV coupling results in a local-global combination of effective mass balance relations for the Darcy-scale degrees of freedom and local problems for the pore-scale degrees of freedom that capture pore-scale behavior. Our scheme allows for the rapid coarsening of pore-scale models and the adaptive enrichment of Darcy-scale models with pore-scale information. Additionally, we propose a strategy for modeling the dynamics of the pore-scale solid-liquid boundary due to precipitation and dissolution phenomena, based on the Diffuse Domain method (DDM), which is incorporated into the MsFV approximation of pore-scale states. We apply the proposed hybrid scheme to a reactive flow and transport problem in porous media subject to heterogeneous reactions and the corresponding precipitation and dissolution phenomena.
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.
Influence of Li-ion Battery Models in the Sizing of Hybrid Storage Systems with Supercapacitors
DEFF Research Database (Denmark)
Pinto, Claudio; Barreras, Jorge Varela; de Castro, Ricardo
2014-01-01
This paper presents a comparative study of the influence of different aggregated electrical circuit battery models in the sizing process of a hybrid energy storage system (ESS), composed by Li-ion batteries and supercapacitors (SCs). The aim is to find the number of cells required to propel...... a certain vehicle over a predefined driving cycle. During this process, three battery models will be considered. The first consists in a linear static zeroeth order battery model over a restricted operating window. The second is a non-linear static model, while the third takes into account first...
The characteristic analysis of a hybrid multifluid turbulent-mix model
Energy Technology Data Exchange (ETDEWEB)
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.
Dynamical analysis of Parkinsonian state emulated by hybrid Izhikevich neuron models
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
Reduction and identification for hybrid dynamical models of terrestrial locomotion
Burden, Samuel A.; Sastry, S. Shankar
2013-06-01
The study of terrestrial locomotion has compelling applications ranging from design of legged robots to development of novel prosthetic devices. From a first-principles perspective, the dynamics of legged locomotion seem overwhelmingly complex as nonlinear rigid body dynamics couple to a granular substrate through viscoelastic limbs. However, a surfeit of empirical data demonstrates that animals use a small fraction of their available degrees-of-freedom during locomotion on regular terrain, suggesting that a reduced-order model can accurately describe the dynamical variation observed during steady-state locomotion. Exploiting this emergent phenomena has the potential to dramatically simplify design and control of micro-scale legged robots. We propose a paradigm for studying dynamic terrestrial locomotion using empirically-validated reduced{order models.
Calibrated and Interactive Modelling of Form-Active Hybrid Structures
DEFF Research Database (Denmark)
Quinn, Gregory; Holden Deleuran, Anders; Piker, Daniel
2016-01-01
at a fraction of the weight of traditional building elements and do so with a clear aesthetic expression of force flow and equilibrium. The design of FAHS is limited by one significant restriction: the geometry definition, form-finding and structural analysis are typically performed in separate and bespoke...... software packages which introduce interruptions and data exchange issues in the modelling pipeline. The mechanical precision, stability and open software architecture of Kangaroo has facilitated the development of proof-of-concept modelling pipelines which tackle this challenge and enable powerful...... materially-informed sketching. Making use of a projection-based dynamic relaxation solver for structural analysis, explorative design has proven to be highly effective....
Hybrid [sigma]-p Coordinate Choices for a Global Model
2009-01-01
Variational Data Assimilation System (NAVDAS), the National Aeronautics and Space Ad- ministration’s (NASA’s) Global Modeling and Assim- ilation Office ( GMAO ...NOGAPS/ GMAO reanalysis fields at 0000 UTC 11 Jan 2003 using NOGHYB, NEWHYB1, NEWHYB2, and vertical coordinates (columns 2–5, respectively). Contour...from 2-, 4-, and 8-day fore- casts initialized on 11 January using different vertical coordinates, with the NOGAPS/ GMAO reanalysis fields shown in
Modeling and Simulation for Hybrid of PV-Wind system
Maged N. F. Nashed; Salah G. Ramadan; Abeer A. M. El-Hady; Shawky H. Arafa
2015-01-01
The rising consumption rate of fossil fuels causes a significant pollution impact on the atmosphere, unwanted greenhouse gases has drawn worldwide attention towards renewable energy sources. Moreover, in recent year’s generation of electricity using the different types of renewable sources are specifically evaluated in the economical performance of the overall equipment. This paper focuses on the modeling and analysis of a Standalone Photovoltaic (PV)- wind energy hybr...
Hybrid empirical--theoretical approach to modeling uranium adsorption
Energy Technology Data Exchange (ETDEWEB)
Hull, Larry C.; Grossman, Christopher; Fjeld, Robert A.; Coates, John T.; Elzerman, Alan W
2004-05-01
An estimated 330 metric tons of U are buried in the radioactive waste Subsurface Disposal Area (SDA) at the Idaho National Engineering and Environmental Laboratory (INEEL). An assessment of U transport parameters is being performed to decrease the uncertainty in risk and dose predictions derived from computer simulations of U fate and transport to the underlying Snake River Plain Aquifer. Uranium adsorption isotherms were measured for 14 sediment samples collected from sedimentary interbeds underlying the SDA. The adsorption data were fit with a Freundlich isotherm. The Freundlich n parameter is statistically identical for all 14 sediment samples and the Freundlich K{sub f} parameter is correlated to sediment surface area (r{sup 2}=0.80). These findings suggest an efficient approach to material characterization and implementation of a spatially variable reactive transport model that requires only the measurement of sediment surface area. To expand the potential applicability of the measured isotherms, a model is derived from the empirical observations by incorporating concepts from surface complexation theory to account for the effects of solution chemistry. The resulting model is then used to predict the range of adsorption conditions to be expected in the vadose zone at the SDA based on the range in measured pore water chemistry. Adsorption in the deep vadose zone is predicted to be stronger than in near-surface sediments because the total dissolved carbonate decreases with depth.
Hybrid simulation models for data-intensive systems
AUTHOR|(INSPIRE)INSPIRE-00473067
Data-intensive systems are used to access and store massive amounts of data by combining the storage resources of multiple data-centers, usually deployed all over the world, in one system. This enables users to utilize these massive storage capabilities in a simple and efficient way. However, with the growth of these systems it becomes a hard problem to estimate the effects of modifications to the system, such as data placement algorithms or hardware upgrades, and to validate these changes for potential side effects. This thesis addresses the modeling of operational data-intensive systems and presents a novel simulation model which estimates the performance of system operations. The running example used throughout this thesis is the data-intensive system Rucio, which is used as the data man- agement system of the ATLAS experiment at CERN’s Large Hadron Collider. Existing system models in literature are not applicable to data-intensive workflows, as they only consider computational workflows or make assumpti...
Amir, Sahar Z.
2017-06-09
A Hybrid Embedded Fracture (HEF) model was developed to reduce various computational costs while maintaining physical accuracy (Amir and Sun, 2016). HEF splits the computations into fine scale and coarse scale. Fine scale solves analytically for the matrix-fracture flux exchange parameter. Coarse scale solves for the properties of the entire system. In literature, fractures were assumed to be either vertical or horizontal for simplification (Warren and Root, 1963). Matrix-fracture flux exchange parameter was given few equations built on that assumption (Kazemi, 1968; Lemonnier and Bourbiaux, 2010). However, such simplified cases do not apply directly for actual random fracture shapes, directions, orientations …etc. This paper shows that the HEF fine scale analytic solution (Amir and Sun, 2016) generates the flux exchange parameter found in literature for vertical and horizontal fracture cases. For other fracture cases, the flux exchange parameter changes according to the angle, slop, direction, … etc. This conclusion rises from the analysis of both: the Discrete Fracture Network (DFN) and the HEF schemes. The behavior of both schemes is analyzed with exactly similar fracture conditions and the results are shown and discussed. Then, a generalization is illustrated for any slightly compressible single-phase fluid within fractured porous media and its results are discussed.
Hybrid Model for Homogenization of the Elastoplastic Properties of Isotropic Matrix Composites
Fedotov, A. F.
2017-07-01
A hybrid homogenization model for calculating the effective elastoplastic properties of isotropic matrix composites is suggested. The hybrid model combines the continuous deformation models of heterogeneous solid and porous materials. A distinctive feature of the model is the calculation of concentration coefficients of the average Hill strains in terms of the effective volumes of strain averaging. The effective volumes of averaging are determined by solving the boundary-value problem on plastic deformation of a simplified structural model of a two-phase composite considering the porous state of matrix. A comparison of calculation results with experimental data upon constructing deformation diagrams for polymer-matrix and metal-matrix composites is carried out. The possibility of changing the properties of the metal matrix in producing composites is mentioned. Therefore, the adequacy of analytical models greatly depends on the accuracy of identification of material constants of the matrix. On the whole, the new model described the plastic deformation of matrix composites more accurately than the Mori-Tanaka model. The analytical model proposed has a simpler sampling scheme, a simple computation algorithm, and ensured the same calculation accuracy for the deformation diagram of an aluminum-matrix composite as the numerical finite-element model created by the ABAQUS software.
A hybrid DEM-SPH model for deformable landslide and its generated surge waves
Tan, Hai; Chen, Shenghong
2017-10-01
Reservoir bank landslide and its generated surge waves are catastrophic hazards which may give rise to additional sedimentation, destroy hydraulic structures, and even cause fatalities. Since this process is very complex involving landslide impact, wave generation and propagation, it cannot be well captured with traditional numerical approaches. In this paper, a hybrid DEM-SPH model is presented to simulate landslide and to reproduce its generated surge waves. This model consists of discrete element method (DEM) for solid phase and smoothed particle hydrodynamics (SPH) for fluid phase as well as drag force and buoyancy for solid-fluid interaction. Meanwhile, the δ-SPH algorithm is employed to eliminate spurious numerical noise on the pressure field. Submarine rigid block slide is numerically tested to validate the proposed hybrid model, and the computed wave profiles exhibit a satisfactory agreement with the experiment. The hybrid model is further extended towards the submarine granular deformable slide which generates smaller and less violent surge waves. Kinetic and potential energy of both solid and fluid particle system are extracted to throw a light upon the process of landslide water interaction from an energy perspective. Finally, a sensitivity analysis on particle friction coefficient indicates that the lubrication of the solid particles is another important effect influencing the underwater landslide movement in addition to the drag effect.
A Hybrid Latent Class Analysis Modeling Approach to Analyze Urban Expressway Crash Risk.
Yu, Rongjie; Wang, Xuesong; Abdel-Aty, Mohamed
2017-04-01
Crash risk analysis is rising as a hot research topic as it could reveal the relationships between traffic flow characteristics and crash occurrence risk, which is beneficial to understand crash mechanisms which would further refine the design of Active Traffic Management System (ATMS). However, the majority of the current crash risk analysis studies have ignored the impact of geometric characteristics on crash risk estimation while recent studies proved that crash occurrence risk was affected by the various alignment features. In this study, a hybrid Latent Class Analysis (LCA) modeling approach was proposed to account for the heterogeneous effects of geometric characteristics. Crashes were first segmented into homogenous subgroups, where the optimal number of latent classes was identified based on bootstrap likelihood ratio tests. Then, separate crash risk analysis models were developed using Bayesian random parameter logistic regression technique; data from Shanghai urban expressway system were employed to conduct the empirical study. Different crash risk contributing factors were unveiled by the hybrid LCA approach and better model goodness-of-fit was obtained while comparing to an overall total crash model. Finally, benefits of the proposed hybrid LCA approach were discussed. Copyright © 2017 Elsevier Ltd. All rights reserved.
Modeling and Density Estimation of an Urban Freeway Network Based on Dynamic Graph Hybrid Automata.
Chen, Yangzhou; Guo, Yuqi; Wang, Ying
2017-03-29
In this paper, in order to describe complex network systems, we firstly propose a general modeling framework by combining a dynamic graph with hybrid automata and thus name it Dynamic Graph Hybrid Automata (DGHA). Then we apply this framework to model traffic flow over an urban freeway network by embedding the Cell Transmission Model (CTM) into the DGHA. With a modeling procedure, we adopt a dual digraph of road network structure to describe the road topology, use linear hybrid automata to describe multi-modes of dynamic densities in road segments and transform the nonlinear expressions of the transmitted traffic flow between two road segments into piecewise linear functions in terms of multi-mode switchings. This modeling procedure is modularized and rule-based, and thus is easily-extensible with the help of a combination algorithm for the dynamics of traffic flow. It can describe the dynamics of traffic flow over an urban freeway network with arbitrary topology structures and sizes. Next we analyze mode types and number in the model of the whole freeway network, and deduce a Piecewise Affine Linear System (PWALS) model. Furthermore, based on the PWALS model, a multi-mode switched state observer is designed to estimate the traffic densities of the freeway network, where a set of observer gain matrices are computed by using the Lyapunov function approach. As an example, we utilize the PWALS model and the corresponding switched state observer to traffic flow over Beijing third ring road. In order to clearly interpret the principle of the proposed method and avoid computational complexity, we adopt a simplified version of Beijing third ring road. Practical application for a large-scale road network will be implemented by decentralized modeling approach and distributed observer designing in the future research.
Hybrid fluid/kinetic model for parallel heat conduction
Energy Technology Data Exchange (ETDEWEB)
Callen, J.D.; Hegna, C.C.; Held, E.D. [Univ. of Wisconsin, Madison, WI (United States)
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.
Jian, Weilin; He, Daohang; Song, Shaoyun
2016-08-01
Natural stilbenes (especially resveratrol) play important roles in plant protection by acting as both constitutive and inducible defenses. However, their exogenous applications on crops as fungicidal agents are challenged by their oxidative degradation and limited availability. In this study, a new class of resveratrol-inspired oxadiazole-stilbene hybrids was synthesized via Wittig-Horner reaction. Bioassay results indicated that some of the compounds exhibited potent fungicidal activity against Botrytis cinerea in vitro. Among these stilbene hybrids, compounds 11 showed promising inhibitory activity with the EC50 value of 144.6 μg/mL, which was superior to that of resveratrol (315.6 μg/mL). Remarkably, the considerably abnormal mycelial morphology was observed in the presence of compound 11. The inhibitory profile was further proposed by homology modeling and molecular docking studies, which showed the possible interaction of resveratrol and oxadiazole-stilbene hybrids with the cytochrome P450-dependent sterol 14α-demethylase from B. cinerea (BcCYP51) for the first time. Taken together, these results would provide new insights into the fungicidal mechanism of stilbenes, as well as an important clue for biology-oriented synthesis of stilbene hybrids with improved bioactivity against plant pathogenic fungi in crop protection.
Hybrid model of the radiation-induced bystander effect
Energy Technology Data Exchange (ETDEWEB)
Braga, Viviane V.B.; Faria, Fernando Pereira de; Grynberg, Suely Epsztein, E-mail: vitoriabraga06@gmail.com, E-mail: fernandopereirabh@gmail.com, E-mail: seg@cdtn.br [Centro de Desenvolvimento da Tecnologia Nuclear (CDTN/CNEN-MG), Belo Horizonte, MG (Brazil)
2013-07-01
The radiation-induced bystander effect (RIBE) refer to biological alterations in non-irradiated cells that occupy the same medium (culture or tissue) of irradiated cells. The biochemical mechanisms of the RIBE are not completely elucidated. However, several experiments indicate its existence. The objective of this work is to quantify the effect via stochastic and deterministic approaches. The hypotheses of the model are: a) one non-irradiated healthy cell interacts with signals that propagate through the medium. These signals are released by irradiated cells. At the time of interaction cell-signal, the cell can become damaged and signaling or damage and not signaling; b) Both types of damage cells repair with certain rate becoming health cells; c) The diffusion of signals obey the discrete diffusion equation with decay in two dimensions. d) The signal concentration released by irradiated cells depends on the dose in the low dose range (< 0.3 Gy) and saturates for higher dose values. As expected, the temporal analysis of the model as a function of the repair rate shows that the survival fraction decreases as the repair rate is reduced. The analysis of the extent of damage triggered by a signal concentration released by a single irradiated cell at time zero show that the damage grows with the maximum simulation time. The results show good agreement with the experimental data. The stochastic and deterministic methods used are in qualitative agreement, as expected. (author)
Hajarolasvadi, Setare; Elbanna, Ahmed E.
2017-11-01
The finite difference (FD) and the spectral boundary integral (SBI) methods have been used extensively to model spontaneously-propagating shear cracks in a variety of engineering and geophysical applications. In this paper, we propose a new modelling approach in which these two methods are combined through consistent exchange of boundary tractions and displacements. Benefiting from the flexibility of FD and the efficiency of SBI methods, the proposed hybrid scheme will solve a wide range of problems in a computationally efficient way. We demonstrate the validity of the approach using two examples for dynamic rupture propagation: one in the presence of a low-velocity layer and the other in which off-fault plasticity is permitted. We discuss possible potential uses of the hybrid scheme in earthquake cycle simulations as well as an exact absorbing boundary condition.
Hybrid Model For Reverberant Indoor Radio Channels Using Rays and Graphs
DEFF Research Database (Denmark)
Steinböck, Gerhard; Gan, Mingming; Meissner, Paul
2016-01-01
efficient calculation of the channel transfer function considering infinitely many components. We use ray-tracing and the theory of room electromagnetics to obtain the parameter settings for the propagation graph. Thus the proposed hybrid model does not require new or additional parameters in comparison....... This diffuse tail is difficult to include in ray-tracing due to the computational complexity. We propose a hybrid model to include deterministic components and the diffuse tail by combining ray-tracing with a propagation graph. The recursive structure of the propagation graph allows for a computationally......Ray-tracing tools allow for deterministic simulation of the channel impulse response. Studies show that these tools work well when the impulse response consists only of a few distinct components. However, measurements of the channel impulse response in indoor environments show a diffuse tail...
Energy Management Strategy Based on the Driving Cycle Model for Plugin Hybrid Electric Vehicles
Directory of Open Access Journals (Sweden)
Xiaoling Fu
2014-01-01
Full Text Available The energy management strategy (EMS for a plugin hybrid electric vehicle (PHEV is proposed based on the driving cycle model and dynamic programming (DP algorithm. A driving cycle model is constructed by collecting and processing the driving data of a certain school bus. The state of charge (SOC profile can be obtained by the DP algorithm for the whole driving cycle. In order to optimize the energy management strategy in the hybrid power system, the optimal motor torque control sequence can be calculated using the DP algorithm for the segments between the traffic intersections. Compared with the traditional charge depleting-charge sustaining (CDCS strategy, the test results on the ADVISOR platform show a significant improvement in fuel consumption using the EMS proposed in this paper.
Polese, Lino; Merigliano, Stefano; Mungo, Benedetto; Rizzato, Roberto; Luisetto, Roberto; Ancona, Ermanno; Norberto, Lorenzo
2012-09-01
The aim of this study was to evaluate the feasibility of a totally stapled gastrojejunal anastomosis performed using one transabdominal 12-mm trocar and a gastroscope in a porcine model. The procedure was carried out on six domestic pigs weighing 45 kg using a hybrid technique with a gastroscope and a 12-mm Hasson trocar, positioned in the left hypochondrium. At the end of the procedure a mechanical circular 21-mm gastrojejunal anastomosis was performed by inserting the stapler through a small gastrotomy after enlarging the trocar incision. In all six cases the procedure was completed through a single 3 cm abdominal incision and without complications. The mean operating time was 2 h, and endoscopic investigation showed that the anastomoses were intact, patent, and airtight. Totally stapled gastrojejunal anastomosis using a hybrid NOTES-single 12-mm trocar approach is a feasible procedure in the porcine model. Further survival studies are warranted, particularly to evaluate the functional results of this procedure.
ANALYSIS OF ASSEMBLY SUITABILITY OF THE HYBRID NODE BASED ON WELD DISTORTION PREDICTION MODELS
Directory of Open Access Journals (Sweden)
Tomasz Urbański
2015-08-01
Full Text Available The article presents an analysis of assembly suitability of the innovative hybrid node. Weld distortions are a factor that affects significantly the quality of a structure during its pre-fabrication stage, thus increasing manufacturing costs . For the purposes of this analysis, such distortion forms were chosen that are the highest-ranking ones in the technological hierarchy. The analysis was performed taking advantage of significant parameters in order to demonstrate the possibilities of using mathematical models determined on the basis of a designed experiment to modify the construction technology as early as during the stage of the hybrid node’s manufacture. It was shown that using the above-mentioned theoretical models a technological assessment of the structural component can be performed by selecting such system of parameters that will produce distortions at a level acceptable from the point of view of further assembly suitability.
An advanced environment for hybrid modeling of biological systems based on modelica.
Pross, Sabrina; Bachmann, Bernhard
2011-01-20
Biological systems are often very complex so that an appropriate formalism is needed for modeling their behavior. Hybrid Petri Nets, consisting of time-discrete Petri Net elements as well as continuous ones, have proven to be ideal for this task. Therefore, a new Petri Net library was implemented based on the object-oriented modeling language Modelica which allows the modeling of discrete, stochastic and continuous Petri Net elements by differential, algebraic and discrete equations. An appropriate Modelica-tool performs the hybrid simulation with discrete events and the solution of continuous differential equations. A special sub-library contains so-called wrappers for specific reactions to simplify the modeling process. The Modelica-models can be connected to Simulink-models for parameter optimization, sensitivity analysis and stochastic simulation in Matlab. The present paper illustrates the implementation of the Petri Net component models, their usage within the modeling process and the coupling between the Modelica-tool Dymola and Matlab/Simulink. The application is demonstrated by modeling the metabolism of Chinese Hamster Ovary Cells.
Directory of Open Access Journals (Sweden)
C. Fernandez-Lozano
2013-01-01
Full Text Available Given the background of the use of Neural Networks in problems of apple juice classification, this paper aim at implementing a newly developed method in the field of machine learning: the Support Vector Machines (SVM. Therefore, a hybrid model that combines genetic algorithms and support vector machines is suggested in such a way that, when using SVM as a fitness function of the Genetic Algorithm (GA, the most representative variables for a specific classification problem can be selected.
Fernandez-Lozano, C.; Canto, C.; Gestal, M.; Andrade-Garda, J. M.; Rabuñal, J. R.; Dorado, J.; Pazos, A.
2013-01-01
Given the background of the use of Neural Networks in problems of apple juice classification, this paper aim at implementing a newly developed method in the field of machine learning: the Support Vector Machines (SVM). Therefore, a hybrid model that combines genetic algorithms and support vector machines is suggested in such a way that, when using SVM as a fitness function of the Genetic Algorithm (GA), the most representative variables for a specific classification problem can be selected. PMID:24453933
A Novel Hybrid BND-FOA-LSSVM Model for Electricity Price Forecasting
Weishang Guo; Zhenyu Zhao
2017-01-01
Accurate electricity price forecasting plays an important role in the profits of electricity market participants and the healthy development of electricity market. However, the electricity price time series hold the characteristics of volatility and randomness, which make it quite hard to forecast electricity price accurately. In this paper, a novel hybrid model for electricity price forecasting was proposed combining Beveridge-Nelson decomposition (BND) method, fruit fly optimization algorit...
A Hybrid Model for Multiscale Laser Plasma Simulations with Detailed Collisional Physics
2017-06-15
important physical process as possible with as little computational cost as possible. • To that end, we are in the early processes of characterizing...Detailed Collisional Physics David Bilyeu, Carl Lederman, Richard Abrantes Air Force Research Laboratory (AFMC) AFRL/RQRS 1 Ara Drive Edwards AFB, CA...for Public Release; Distribution is Unlimited. PA# 17383 A Hybrid Model for Multiscale Laser Plasma Simulations with Detailed Collisional Physics
Investigation of a Hybrid Winding Concept for Toroidal Inductors using 3D Finite Element Modeling
DEFF Research Database (Denmark)
Schneider, Henrik; Andersen, Thomas; Mønster, Jakob Døllner
2013-01-01
This paper investigates a hybrid winding concept for a toroidal inductor by simulating the winding resistance as a function of frequency. The problem of predicting the resistance of a non-uniform and complex winding shape is solved using 3D Finite Element Modeling. A prototype is built and tested...... experimentally to verify the simulation results. Finally COMSOL LiveLink to CAD is utilized to highlight a bottleneck for this kind of winding scheme....
A Hybrid Model for Multiscale Laser Plasma Simulations with Detailed Collisional Physics
2016-11-29
other provision of law, no person shall be subject to any penalty for failing to comply with a collection of information if it does not display a ...Briefing Charts 3. DATES COVERED (From - To) 02 November 2016 – 30 November 2016 4. TITLE AND SUBTITLE A Hybrid Model for Multiscale Laser Plasma...Briefing Charts 15. SUBJECT TERMS N/ A 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER OF PAGES 19a. NAME OF RESPONSIBLE
Design, Operation and Control Modelling of SOFC/GT Hybrid Systems
Stiller, Christoph
2006-01-01
This thesis focuses on modelling-based design, operation and control of solid oxide fuel cell (SOFC) and gas turbine (GT) hybrid systems. Fuel cells are a promising approach to high-efficiency power generation, as they directly convert chemical energy to electric work. High-temperature fuel cells such as the SOFC can be integrated in gas turbine processes, which further increases the electrical efficiency to values up to 70%. However, there are a number of obstacles for safe operation of such...
1995-05-01
Vol. 31, No. 6, November- December 1983, pp. 1030-1052. Taha , Hamdy A ., Operations Research: An Introduction, MacMillan Press, New York, 1992. Tzong... A HYBRID ANALYTICAL/SIMULATION MODELING APPROACH FOR PLANNING AND OPTIMIZING MASS TACTICAL AIRBORNE OPERATIONS by DAVID DOUGLAS BRIGGS M.S.B.A...Science College of Engineering University of Central Florida Orlando, Florida A COO MDiatr;,~i’ Spring Term 1995 This Document Contains Missing Page/s That
Frequency Dependent Spencer Modeling of Magnetorheological Damper Using Hybrid Optimization Approach
Directory of Open Access Journals (Sweden)
Ali Fellah Jahromi
2015-01-01
Full Text Available Magnetorheological dampers have been widely used in civil and automotive industries. The nonlinear behavior of MR fluid makes MR damper modeling a challenging problem. In this paper, a frequency dependent MR damper model is proposed based on Spencer MR damper model. The parameters of the model are identified using an experimental data based hybrid optimization approach which is a combination of Genetic Algorithm and Sequential Quadratic Programming approach. The frequency in the proposed model is calculated using measured relative velocity and relative displacement between MR damper ends. Therefore, the MR damper model will be function of frequency. The mathematical model is validated using the experimental results which confirm the improvement in the accuracy of the model and consistency in the variation damping with the frequency.
Andalam, Sidharta; Ramanna, Harshavardhan; Malik, Avinash; Roop, Parthasarathi; Patel, Nitish; Trew, Mark L
2016-08-01
Virtual heart models have been proposed for closed loop validation of safety-critical embedded medical devices, such as pacemakers. These models must react in real-time to off-the-shelf medical devices. Real-time performance can be obtained by implementing models in computer hardware, and methods of compiling classes of Hybrid Automata (HA) onto FPGA have been developed. Models of ventricular cardiac cell electrophysiology have been described using HA which capture the complex nonlinear behavior of biological systems. However, many models that have been used for closed-loop validation of pacemakers are highly abstract and do not capture important characteristics of the dynamic rate response. We developed a new HA model of cardiac cells which captures dynamic behavior and we implemented the model in hardware. This potentially enables modeling the heart with over 1 million dynamic cells, making the approach ideal for closed loop testing of medical devices.
Modeling and Analysis of Asynchronous Systems Using SAL and Hybrid SAL
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.
Fontenete, Sílvia; Guimarães, Nuno; Wengel, Jesper; Azevedo, Nuno Filipe
2016-01-01
The thermodynamics and kinetics of DNA hybridization, i.e. the process of self-assembly of one, two or more complementary nucleic acid strands, has been studied for many years. The appearance of the nearest-neighbor model led to several theoretical and experimental papers on DNA thermodynamics that provide reasonably accurate thermodynamic information on nucleic acid duplexes and allow estimation of the melting temperature. Because there are no thermodynamic models specifically developed to predict the hybridization temperature of a probe used in a fluorescence in situ hybridization (FISH) procedure, the melting temperature is used as a reference, together with corrections for certain compounds that are used during FISH. However, the quantitative relation between melting and experimental FISH temperatures is poorly described. In this review, various models used to predict the melting temperature for rRNA targets, for DNA oligonucleotides and for nucleic acid mimics (chemically modified oligonucleotides), will be addressed in detail, together with a critical assessment of how this information should be used in FISH.
Modelling of combined ICRF and NBI heating in JET hybrid plasmas
Directory of Open Access Journals (Sweden)
Gallart Dani
2017-01-01
Full Text Available During the 2015-2016 JET campaigns many efforts have been devoted to the exploration of high performance plasma scenarios envisaged for ITER operation. In this paper we model the combined ICRF+NBI heating in selected key hybrid discharges using PION. The antenna frequency was tuned to match the cyclotron frequency of minority hydrogen (H at the center of the tokamak coinciding with the second harmonic cyclotron resonance of deuterium. The modelling takes into account the synergy between ICRF and NBI heating through the second harmonic cyclotron resonance of deuterium beam ions which allows us to assess its impact on the neutron rate RNT. We evaluate the influence of H concentration which was varied in different discharges in order to test their role in the heating performance. According to our modelling, the ICRF enhancement of RNT increases by decreasing the H concentration which increases the ICRF power absorbed by deuterons. We find that in the recent hybrid discharges this ICRF enhancement was in the range of 10-25%. Finally, we extrapolate the results to D-T and find that the best performing hybrid discharges correspond to an equivalent fusion power of ∼7.0 MW in D-T.
Analysis of the PEDOT:PSS/Si nanowire hybrid solar cell with a tail state model
Ho, Kuan-Ying; Li, Chi-Kang; Syu, Hong-Jhang; Lai, Yi; Lin, Ching-Fuh; Wu, Yuh-Renn
2016-12-01
In this paper, the electrical properties of the poly(3,4-ethylenedioxythiophene): poly(styrenesulfonate) (PEDOT:PSS)/silicon nanowire hybrid solar cell have been analyzed and an optimized structure is proposed. In addition, the planar PEDOT:PSS/c-Si hybrid solar cell is also modeled for comparison. We first developed a simulation software which is capable of modeling organic/inorganic hybrid solar cells by including Gaussian shape density of states into Poisson and drift-diffusion solver to present the tail states and trap states in the organic material. Therefore, the model can handle carrier transport, generation, and recombination in both organic and inorganic materials. Our results show that at the applied voltage near open-circuit voltage (Voc), the recombination rate becomes much higher at the PEDOT:PSS/Si interface region, which limits the fill factor and Voc. Hence, a modified structure with a p-type amorphous silicon (a-Si) layer attached on the interface of Si layer and an n+-type Si layer inserted near the bottom contact are proposed. The highest conversion efficiency of 16.10% can be achieved if both structures are applied.
Hierarchical Fault Diagnosis for a Hybrid System Based on a Multidomain Model
Directory of Open Access Journals (Sweden)
Jiming Ma
2015-01-01
Full Text Available The diagnosis procedure is performed by integrating three steps: multidomain modeling, event identification, and failure event classification. Multidomain model can describe the normal and fault behaviors of hybrid systems efficiently and can meet the diagnosis requirements of hybrid systems. Then the multidomain model is used to simulate and obtain responses under different failure events; the responses are further utilized as a priori information when training the event identification library. Finally, a brushless DC motor is selected as the study case. The experimental result indicates that the proposed method could identify the known and unknown failure events of the studied system. In particular, for a system with less response information under a failure event, the accuracy of diagnosis seems to be higher. The presented method integrates the advantages of current quantitative and qualitative diagnostic procedures and can distinguish between failures caused by parametric and abrupt structure faults. Another advantage of our method is that it can remember unknown failure types and automatically extend the adaptive resonance theory neural network library, which is extremely useful for complex hybrid systems.
Modeling and design of a high efficiency hybrid heat pump clothes dryer
Energy Technology Data Exchange (ETDEWEB)
TeGrotenhuis, Ward; Butterfield, Andrew; Caldwell, Dustin; Crook, Alexander; Winkelman, Austin
2017-09-01
Computational modeling is used to design a hybrid heat pump clothes dryer capable of saving 50% of the energy used by residential clothes dryers with comparable drying times. The model represents the various stages of a drying cycle from warm-up through constant drying rate and falling drying rate phases and finishing with a cooldown phase. The model is fit to data acquired from a U.S. commercial standard vented electric dryer, and when a hybrid heat pump system is added, the energy factor increases from 3.0 lbs/kWh to 5.7-6.0 lbs/kWh, depending on the increase in blower motor power. The hybrid heat pump system is designed from off-the-shelf components and includes a recuperative heat exchanger, an electric element, and an R-134a vapor compression heat pump. Parametric studies of element power and heating element use show a trade-off between energy savings and cycle time. Results show a step-change in energy savings from heat pump dryers currently marketed in the U.S. based on performance represented by Enery Star from standardized DOE testing.
Simplified Model for the Hybrid Method to Design Stabilising Piles Placed at the Toe of Slopes
Directory of Open Access Journals (Sweden)
Dib M.
2018-01-01
Full Text Available Stabilizing precarious slopes by installing piles has become a widespread technique for landslides prevention. The design of slope-stabilizing piles by the finite element method is more accurate comparing to the conventional methods. This accuracy is because of the ability of this method to simulate complex configurations, and to analyze the soil-pile interaction effect. However, engineers prefer to use the simplified analytical techniques to design slope stabilizing piles, this is due to the high computational resources required by the finite element method. Aiming to combine the accuracy of the finite element method with simplicity of the analytical approaches, a hybrid methodology to design slope stabilizing piles was proposed in 2012. It consists of two steps; (1: an analytical estimation of the resisting force needed to stabilize the precarious slope, and (2: a numerical analysis to define the adequate pile configuration that offers the required resisting force. The hybrid method is applicable only for the analysis and the design of stabilizing piles placed in the middle of the slope, however, in certain cases like road constructions, piles are needed to be placed at the toe of the slope. Therefore, in this paper a simplified model for the hybrid method is dimensioned to analyze and design stabilizing piles placed at the toe of a precarious slope. The validation of the simplified model is presented by a comparative analysis with the full coupled finite element model.
From CAD to Digital Modeling: the Necessary Hybridization of Processes
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.
Energy Technology Data Exchange (ETDEWEB)
Zhang, Zhen [School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072 (China); Xia, Changliang [School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072 (China); Tianjin Engineering Center of Electric Machine System Design and Control, Tianjin 300387 (China); Yan, Yan, E-mail: yanyan@tju.edu.cn [School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072 (China); Geng, Qiang [Tianjin Engineering Center of Electric Machine System Design and Control, Tianjin 300387 (China); Shi, Tingna [School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072 (China)
2017-08-01
Highlights: • A hybrid analytical model is developed for field calculation of multilayer IPM machines. • The rotor magnetic field is calculated by the magnetic equivalent circuit method. • The field in the stator and air-gap is calculated by subdomain technique. • The magnetic scalar potential on rotor surface is modeled as trapezoidal distribution. - Abstract: Due to the complicated rotor structure and nonlinear saturation of rotor bridges, it is difficult to build a fast and accurate analytical field calculation model for multilayer interior permanent magnet (IPM) machines. In this paper, a hybrid analytical model suitable for the open-circuit field calculation of multilayer IPM machines is proposed by coupling the magnetic equivalent circuit (MEC) method and the subdomain technique. In the proposed analytical model, the rotor magnetic field is calculated by the MEC method based on the Kirchhoff’s law, while the field in the stator slot, slot opening and air-gap is calculated by subdomain technique based on the Maxwell’s equation. To solve the whole field distribution of the multilayer IPM machines, the coupled boundary conditions on the rotor surface are deduced for the coupling of the rotor MEC and the analytical field distribution of the stator slot, slot opening and air-gap. The hybrid analytical model can be used to calculate the open-circuit air-gap field distribution, back electromotive force (EMF) and cogging torque of multilayer IPM machines. Compared with finite element analysis (FEA), it has the advantages of faster modeling, less computation source occupying and shorter time consuming, and meanwhile achieves the approximate accuracy. The analytical model is helpful and applicable for the open-circuit field calculation of multilayer IPM machines with any size and pole/slot number combination.
Determination of inhibition in the enzymatic hydrolysis of cellobiose using hybrid neural modeling
Directory of Open Access Journals (Sweden)
F. C. Corazza
2005-03-01
Full Text Available Neural networks and hybrid models were used to study substrate and product inhibition observed in the enzymatic hydrolysis of cellobiose at 40ºC, 50ºC and 55ºC, pH 4.8, using cellobiose solutions with or without the addition of exogenous glucose. Firstly, the initial velocity method and nonlinear fitting with StatisticaÒ were used to determine the kinetic parameters for either the uncompetitive or the competitive substrate inhibition model at a negligible product concentration and cellobiose from 0.4 to 2.0 g/L. Secondly, for six different models of substrate and product inhibitions and data for low to high cellobiose conversions in a batch reactor, neural networks were used for fitting the product inhibition parameter to the mass balance equations derived for each model. The two models found to be best were: 1 noncompetitive inhibition by substrate and competitive by product and 2 uncompetitive inhibition by substrate and competitive by product; however, these models’ correlation coefficients were quite close. To distinguish between them, hybrid models consisting of neural networks and first principle equations were used to select the best inhibition model based on the smallest norm observed, and the model with noncompetitive inhibition by substrate and competitive inhibition by product was shown to be the best predictor of cellobiose hydrolysis reactor behavior.
Hybrid Markov chain models of S-I-R disease dynamics.
Rebuli, Nicolas P; Bean, N G; Ross, J V
2017-09-01
Deterministic epidemic models are attractive due to their compact nature, allowing substantial complexity with computational efficiency. This partly explains their dominance in epidemic modelling. However, the small numbers of infectious individuals at early and late stages of an epidemic, in combination with the stochastic nature of transmission and recovery events, are critically important to understanding disease dynamics. This motivates the use of a stochastic model, with continuous-time Markov chains being a popular choice. Unfortunately, even the simplest Markovian S-I-R model-the so-called general stochastic epidemic-has a state space of order [Formula: see text], where N is the number of individuals in the population, and hence computational limits are quickly reached. Here we introduce a hybrid Markov chain epidemic model, which maintains the stochastic and discrete dynamics of the Markov chain in regions of the state space where they are of most importance, and uses an approximate model-namely a deterministic or a diffusion model-in the remainder of the state space. We discuss the evaluation, efficiency and accuracy of this hybrid model when approximating the distribution of the duration of the epidemic and the distribution of the final size of the epidemic. We demonstrate that the computational complexity is [Formula: see text] and that under suitable conditions our approximations are highly accurate.
A Hybrid Resynthesis Model for Hammer-String Interaction of Piano Tones
Directory of Open Access Journals (Sweden)
Jensen Kristoffer
2004-01-01
Full Text Available 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.
Modeling And Simulation As The Basis For Hybridity In The Graphic Discipline Learning/Teaching Area
Directory of Open Access Journals (Sweden)
Jana Žiljak Vujić
2009-01-01
Full Text Available Only some fifteen years have passed since the scientific graphics discipline was established. In the transition period from the College of Graphics to «Integrated Graphic Technology Studies» to the contemporary Faculty of Graphics Arts with the University in Zagreb, three main periods of development can be noted: digital printing, computer prepress and automatic procedures in postpress packaging production. Computer technology has enabled a change in the methodology of teaching graphics technology and studying it on the level of secondary and higher education. The task has been set to create tools for simulating printing processes in order to master the program through a hybrid system consisting of methods that are separate in relation to one another: learning with the help of digital models and checking in the actual real system. We are setting a hybrid project for teaching because the overall acquired knowledge is the result of completely different methods. The first method is on the free programs level functioning without consequences. Everything remains as a record in the knowledge database that can be analyzed, statistically processed and repeated with new parameter values of the system being researched. The second method uses the actual real system where the results are in proving the value of new knowledge and this is something that encourages and stimulates new cycles of hybrid behavior in mastering programs. This is the area where individual learning incurs. The hybrid method allows the possibility of studying actual situations on a computer model, proving it on an actual real model and entering the area of learning envisaging future development.
A hybrid energy model for region based curve evolution - Application to CTA coronary segmentation.
Jawaid, Muhammad Moazzam; Rajani, Ronak; Liatsis, Panos; Reyes-Aldasoro, Constantino Carlos; Slabaugh, Greg
2017-06-01
State-of-the-art medical imaging techniques have enabled non-invasive imaging of the internal organs. However, high volumes of imaging data make manual interpretation and delineation of abnormalities cumbersome for clinicians. These challenges have driven intensive research into efficient medical image segmentation. In this work, we propose a hybrid region-based energy formulation for effective segmentation in computed tomography angiography (CTA) imagery. The proposed hybrid energy couples an intensity-based local term with an efficient discontinuity-based global model of the image for optimal segmentation. The segmentation is achieved using a level set formulation due to the computational robustness. After validating the statistical significance of the hybrid energy, we applied the proposed model to solve an important clinical problem of 3D coronary segmentation. An improved seed detection method is used to initialize the level set evolution. Moreover, we employed an auto-correction feature that captures the emerging peripheries during the curve evolution for completeness of the coronary tree. We evaluated the segmentation accuracy of the proposed energy model against the existing techniques in two stages. Qualitative and quantitative results demonstrate the effectiveness of the proposed framework with a consistent mean sensitivity and specificity measures of 80% across the CTA data. Moreover, a high degree of agreement with respect to the inter-observer differences justifies the generalization of the proposed method. The proposed method is effective to segment the coronary tree from the CTA volume based on hybrid image based energy, which can improve the clinicians ability to detect arterial abnormalities. Copyright © 2017 Elsevier B.V. All rights reserved.
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.
Cilfone, Nicholas A; Kirschner, Denise E; Linderman, Jennifer J
2015-03-01
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.
Franchimon, Ellen F.; Hiremath, K.R.; Stoffer, Remco; Hammer, Manfred
2013-01-01
Whispering gallery modes supported by open circular dielectric cavities are embedded into a nonparametric two-dimensional frequency domain hybrid coupled mode theory framework. Regular aggregates of these cavities, including straight access channels, are investigated. The model enables convenient
National Research Council Canada - National Science Library
Boutkhoum, Omar; Hanine, Mohamed; Agouti, Tarik; Tikniouine, Abdessadek
2015-01-01
..., customers, and most other things. Based on the integration of environmental, economic and social decisive elements of sustainable development, this paper presents a hybrid decision making model combining fuzzy multi-criteria analysis...
Hybrid-model for computed tomography simulations and post-patient collimator design
Xu, Horace; Tao, Kun; GK, Padmashree; Wu, Mingye; Cao, Ximiao; Long, Yong; Yan, Ming; Yao, Yangyang; De Man, Bruno
2014-03-01
Ray-tracing based simulation methods are widely used in modeling X-ray propagation, detection and imaging. While most of the existing simulation methods rely on analytical modeling, a novel hybrid approach comprising of statistical modeling and analytical approaches, is proposed here. Our hybrid simulator is a unique combination of analytical modeling for evoking the fundamentals of X-ray transport through ray-tracing, and a look-up-table (LUT) based approach for integrating it with the Monte Carlo simulations that model optical photon-transport within scintillator. The LUT approach for scintillation-based X-ray detection invokes depth-dependent gain factors to account for intra-pixel absorption and light-transport, together with incident-angle dependent effects for inter-pixel X-ray absorption (parallax effect). The model simulates the post-patient collimator for scatter-rejection, as an X-ray shadow on scintillator, while handling its position with respect to the pixel boundary, by a smart over-sampling strategy for high efficiency. We have validated this simulator for computed tomography system-simulations, by using real data from GE Brivo CT385. The level of accuracy of image noise and spatial resolution is better than 98%. We have used the simulator for designing the post-patient collimator, and measured modulation transfer function (MTF) for different widths of the collimator plate. Validation and simulation study clearly demonstrates that the hybrid simulator is an accurate, reliable, efficient tool for realistic system-level simulations. It could be deployed for research, design and development purposes to model any scintillator-based X-ray imaging-system (2-dimensional and 3-dimensional), while being equally applicable for medical and industrial imaging.
A hybrid ARIMA and neural network model applied to forecast catch volumes of Selar crumenophthalmus
Aquino, Ronald L.; Alcantara, Nialle Loui Mar T.; Addawe, Rizavel C.
2017-11-01
The Selar crumenophthalmus with the English name big-eyed scad fish, locally known as matang-baka, is one of the fishes commonly caught along the waters of La Union, Philippines. The study deals with the forecasting of catch volumes of big-eyed scad fish for commercial consumption. The data used are quarterly caught volumes of big-eyed scad fish from 2002 to first quarter of 2017. This actual data is available from the open stat database published by the Philippine Statistics Authority (PSA)whose task is to collect, compiles, analyzes and publish information concerning different aspects of the Philippine setting. Autoregressive Integrated Moving Average (ARIMA) models, Artificial Neural Network (ANN) model and the Hybrid model consisting of ARIMA and ANN were developed to forecast catch volumes of big-eyed scad fish. Statistical errors such as Mean Absolute Errors (MAE) and Root Mean Square Errors (RMSE) were computed and compared to choose the most suitable model for forecasting the catch volume for the next few quarters. A comparison of the results of each model and corresponding statistical errors reveals that the hybrid model, ARIMA-ANN (2,1,2)(6:3:1), is the most suitable model to forecast the catch volumes of the big-eyed scad fish for the next few quarters.
Forecasting currency circulation data of Bank Indonesia by using hybrid ARIMAX-ANN model
Prayoga, I. Gede Surya Adi; Suhartono, Rahayu, Santi Puteri
2017-05-01
The purpose of this study is to forecast currency inflow and outflow data of Bank Indonesia. Currency circulation in Indonesia is highly influenced by the presence of Eid al-Fitr. One way to forecast the data with Eid al-Fitr effect is using autoregressive integrated moving average with exogenous input (ARIMAX) model. However, ARIMAX is a linear model, which cannot handle nonlinear correlation structures of the data. In the field of forecasting, inaccurate predictions can be considered caused by the existence of nonlinear components that are uncaptured by the model. In this paper, we propose a hybrid model of ARIMAX and artificial neural networks (ANN) that can handle both linear and nonlinear correlation. This method was applied for 46 series of currency inflow and 46 series of currency outflow. The results showed that based on out-of-sample root mean squared error (RMSE), the hybrid models are up to10.26 and 10.65 percent better than ARIMAX for inflow and outflow series, respectively. It means that ANN performs well in modeling nonlinear correlation of the data and can increase the accuracy of linear model.
Barzegar, Rahim; Fijani, Elham; Asghari Moghaddam, Asghar; Tziritis, Evangelos
2017-12-01
Accurate prediction of groundwater level (GWL) fluctuations can play an important role in water resources management. The aims of the research are to evaluate the performance of different hybrid wavelet-group method of data handling (WA-GMDH) and wavelet-extreme learning machine (WA-ELM) models and to combine different wavelet based models for forecasting the GWL for one, two and three months step-ahead in the Maragheh-Bonab plain, NW Iran, as a case study. The research used totally 367 monthly GWLs (m) datasets (Sep 1985-Mar 2016) which were split into two subsets; the first 312 datasets (85% of total) were used for model development (training) and the remaining 55 ones (15% of total) for model evaluation (testing). The stepwise selection was used to select appropriate lag times as the inputs of the proposed models. The performance criteria such as coefficient of determination (R2), root mean square error (RMSE) and Nash-Sutcliffe efficiency coefficient (NSC) were used for assessing the efficiency of the models. The results indicated that the ELM models outperformed GMDH models. To construct the hybrid wavelet based models, the inputs and outputs were decomposed into sub-time series employing different maximal overlap discrete wavelet transform (MODWT) functions, namely Daubechies, Symlet, Haar and Dmeyer of different orders at level two. Subsequently, these sub-time series were served in the GMDH and ELM models as an input dataset to forecast the multi-step-ahead GWL. The wavelet based models improved the performances of GMDH and ELM models for multi-step-ahead GWL forecasting. To combine the advantages of different wavelets, a least squares boosting (LSBoost) algorithm was applied. The use of the boosting multi-WA-neural network models provided the best performances for GWL forecasts in comparison with single WA-neural network-based models. Copyright © 2017 Elsevier B.V. All rights reserved.
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
DEFF Research Database (Denmark)
Coman, Paul Tiberiu; Veje, Christian
2014-01-01
This paper presents a dynamic model for simulating the heat dissipation and the impact of Phase Change Materials (PCMs) on the peak temperature in Lithium-ion batteries during discharging operation of a hybrid truck under different ambient temperatures.......This paper presents a dynamic model for simulating the heat dissipation and the impact of Phase Change Materials (PCMs) on the peak temperature in Lithium-ion batteries during discharging operation of a hybrid truck under different ambient temperatures....
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
DEVELOPMENT OF A HYBRID FUZZY GENETIC ALGORITHM MODEL FOR SOLVING TRANSPORTATION SCHEDULING PROBLEM
Directory of Open Access Journals (Sweden)
H.C.W. Lau
2015-12-01
Full Text Available There has been an increasing public demand for passenger rail service in the recent times leading to a strong focus on the need for effective and efficient use of resources and managing the increasing passenger requirements, service reliability and variability by the railway management. Whilst shortening the passengers’ waiting and travelling time is important for commuter satisfaction, lowering operational costs is equally important for railway management. Hence, effective and cost optimised train scheduling based on the dynamic passenger demand is one of the main issues for passenger railway management. Although the passenger railway scheduling problem has received attention in operations research in recent years, there is limited literature investigating the adoption of practical approaches that capitalize on the merits of mathematical modeling and search algorithms for effective cost optimization. This paper develops a hybrid fuzzy logic based genetic algorithm model to solve the multi-objective passenger railway scheduling problem aiming to optimize total operational costs at a satisfactory level of customer service. This hybrid approach integrates genetic algorithm with the fuzzy logic approach which uses the fuzzy controller to determine the crossover rate and mutation rate in genetic algorithm approach in the optimization process. The numerical study demonstrates the improvement of the proposed hybrid approach, and the fuzzy genetic algorithm has demonstrated its effectiveness to generate better results than standard genetic algorithm and other traditional heuristic approaches, such as simulated annealing.
Elenchezhiyan, M; Prakash, J
2015-09-01
In this work, state estimation schemes for non-linear hybrid dynamic systems subjected to stochastic state disturbances and random errors in measurements using interacting multiple-model (IMM) algorithms are formulated. In order to compute both discrete modes and continuous state estimates of a hybrid dynamic system either an IMM extended Kalman filter (IMM-EKF) or an IMM based derivative-free Kalman filters is proposed in this study. The efficacy of the proposed IMM based state estimation schemes is demonstrated by conducting Monte-Carlo simulation studies on the two-tank hybrid system and switched non-isothermal continuous stirred tank reactor system. Extensive simulation studies reveal that the proposed IMM based state estimation schemes are able to generate fairly accurate continuous state estimates and discrete modes. In the presence and absence of sensor bias, the simulation studies reveal that the proposed IMM unscented Kalman filter (IMM-UKF) based simultaneous state and parameter estimation scheme outperforms multiple-model UKF (MM-UKF) based simultaneous state and parameter estimation scheme. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.
A novel hybrid forecasting model for PM₁₀ and SO₂ daily concentrations.
Wang, Ping; Liu, Yong; Qin, Zuodong; Zhang, Guisheng
2015-02-01
Air-quality forecasting in urban areas is difficult because of the uncertainties in describing both the emission and meteorological fields. The use of incomplete information in the training phase restricts practical air-quality forecasting. In this paper, we propose a hybrid artificial neural network and a hybrid support vector machine, which effectively enhance the forecasting accuracy of an artificial neural network (ANN) and support vector machine (SVM) by revising the error term of the traditional methods. The hybrid methodology can be described in two stages. First, we applied the ANN or SVM forecasting system with historical data and exogenous parameters, such as meteorological variables. Then, the forecasting target was revised by the Taylor expansion forecasting model using the residual information of the error term in the previous stage. The innovation involved in this approach is that it sufficiently and validly utilizes the useful residual information on an incomplete input variable condition. The proposed method was evaluated by experiments using a 2-year dataset of daily PM₁₀ (particles with a diameter of 10 μm or less) concentrations and SO₂ (sulfur dioxide) concentrations from four air pollution monitoring stations located in Taiyuan, China. The theoretical analysis and experimental results demonstrated that the forecasting accuracy of the proposed model is very promising. Copyright © 2014 Elsevier B.V. All rights reserved.
Electric and hybrid vehicles: power sources, models, sustainability, infrastructure and the market
National Research Council Canada - National Science Library
Pistoia, G
2010-01-01
... for simulation studies Velocity scheduling using traffic preview Hybrid vehicles with telematics Optimal management of hybrid vehicles with telematics Conclusions and future opportunities 1. 2. 3...
Energy Technology Data Exchange (ETDEWEB)
Calvo, Robson A.; Martinkoski, Ricardo [Centro Federal de Educacao Tecnologica do Parana (CEFET), Curitiba, PR (Brazil); Neves Junior, Flavio [Centro Federal de Educacao Tecnologica do Parana (CEFET), Curitiba, PR (Brazil). Programa de Pos-Graduacao em Engenharia Eletrica e Informatica Industrial
2003-07-01
The objective of this article is to apply techniques of formal specification in modelling of natural gas transmission and distribution systems. In this case the formal models are characterized by using hybrid automata. Initially the existent components in the net are modeled and represented by independent hybrid automata. The global dynamics is obtained through the product hybrid automata. Languages representing the desirable states of the system are obtained from the hybrid automata, allowing a hybrid control procedure. An automatic tool as SHIFT must be used to modelling and simulation. (author)
Hybrid control of bifurcation and chaos in stroboscopic model of Internet congestion control system
Ding, Da-Wei; Zhu, Jie; Luo, Xiao-Shu
2008-01-01
Interaction between transmission control protocol (TCP) and random early detection (RED) gateway in the Internet congestion control system has been modelled as a discrete-time dynamic system which exhibits complex bifurcating and chaotic behaviours. In this paper, a hybrid control strategy using both state feedback and parameter perturbation is employed to control the bifurcation and stabilize the chaotic orbits embedded in this discrete-time dynamic system of TCP/RED. Theoretical analysis and numerical simulations show that the bifurcation is delayed and the chaotic orbits are stabilized to a fixed point, which reliably achieves a stable average queue size in an extended range of parameters and even completely eliminates the chaotic behaviour in a particular range of parameters. Therefore it is possible to decrease the sensitivity of RED to parameters. By using the hybrid strategy, we may improve the stability and performance of TCP/RED congestion control system significantly.
Dynamic Modeling and Control Strategy Optimization for a Hybrid Electric Tracked Vehicle
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Hong Wang
2015-01-01
Full Text Available A new hybrid electric tracked bulldozer composed of an engine generator, two driving motors, and an ultracapacitor is put forward, which can provide high efficiencies and less fuel consumption comparing with traditional ones. This paper first presents the terramechanics of this hybrid electric tracked bulldozer. The driving dynamics for this tracked bulldozer is then analyzed. After that, based on analyzing the working characteristics of the engine, generator, and driving motors, the power train system model and control strategy optimization is established by using MATLAB/Simulink and OPTIMUS software. Simulation is performed under a representative working condition, and the results demonstrate that fuel economy of the HETV can be significantly improved.
Sexual Satisfaction Concept Analysis in Iranian Married Women: A Hybrid Model Study.
Parsa Yekta, Zohre; Raisi, Firoozeh; Ebadi, Abbas; Shahvari, Zahra
2015-05-20
Sexual satisfaction is considered to be a sexual right and an important component of sexual health. The purpose of this qualitative study was to clarify the meaning and the nature of sexual satisfaction in Iranian married women, and to provide a cultural-based definition of it. Sexual satisfaction was examined in three phases by the Hybrid Model of concept analysis: (1) the theoretical phase; (2) the fieldwork phase and (3) the analytical phase. Hybrid concept analysis method was chosen because its inclusion of married women's perspectives enriches the limits of sexual health search literature. The critical attributes of sexual satisfaction were investigated. They included 'two-dimensional structure', 'an affective response', 'a means to achieve marital satisfaction', 'unique', 'a concept based on expectations' and 'a concept on shadow of values'. The concept analysis of sexual satisfaction showed some of the attributes and antecedents for this concept that, have not been mentioned in the literature.
Shape memory alloy micro-actuator performance prediction using a hybrid constitutive model
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.
Hybrid Modeling of Flotation Height in Air Flotation Oven Based on Selective Bagging Ensemble Method
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Shuai Hou
2013-01-01
Full Text Available The accurate prediction of the flotation height is very necessary for the precise control of the air flotation oven process, therefore, avoiding the scratch and improving production quality. In this paper, a hybrid flotation height prediction model is developed. Firstly, a simplified mechanism model is introduced for capturing the main dynamic behavior of the process. Thereafter, for compensation of the modeling errors existing between actual system and mechanism model, an error compensation model which is established based on the proposed selective bagging ensemble method is proposed for boosting prediction accuracy. In the framework of the selective bagging ensemble method, negative correlation learning and genetic algorithm are imposed on bagging ensemble method for promoting cooperation property between based learners. As a result, a subset of base learners can be selected from the original bagging ensemble for composing a selective bagging ensemble which can outperform the original one in prediction accuracy with a compact ensemble size. Simulation results indicate that the proposed hybrid model has a better prediction performance in flotation height than other algorithms’ performance.
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Hai An
2016-08-01
Full Text Available Aiming to resolve the problems of a variety of uncertainty variables that coexist in the engineering structure reliability analysis, a new hybrid reliability index to evaluate structural hybrid reliability, based on the random–fuzzy–interval model, is proposed in this article. The convergent solving method is also presented. First, the truncated probability reliability model, the fuzzy random reliability model, and the non-probabilistic interval reliability model are introduced. Then, the new hybrid reliability index definition is presented based on the random–fuzzy–interval model. Furthermore, the calculation flowchart of the hybrid reliability index is presented and it is solved using the modified limit-step length iterative algorithm, which ensures convergence. And the validity of convergent algorithm for the hybrid reliability model is verified through the calculation examples in literature. In the end, a numerical example is demonstrated to show that the hybrid reliability index is applicable for the wear reliability assessment of mechanisms, where truncated random variables, fuzzy random variables, and interval variables coexist. The demonstration also shows the good convergence of the iterative algorithm proposed in this article.
An Efficient Hybrid DSMC/MD Algorithm for Accurate Modeling of Micro Gas Flows
Liang, Tengfei
2013-01-01
Aiming at simulating micro gas flows with accurate boundary conditions, an efficient hybrid algorithmis developed by combining themolecular dynamics (MD) method with the direct simulationMonte Carlo (DSMC)method. The efficiency comes from the fact that theMD method is applied only within the gas-wall interaction layer, characterized by the cut-off distance of the gas-solid interaction potential, to resolve accurately the gas-wall interaction process, while the DSMC method is employed in the remaining portion of the flow field to efficiently simulate rarefied gas transport outside the gas-wall interaction layer. A unique feature about the present scheme is that the coupling between the two methods is realized by matching the molecular velocity distribution function at the DSMC/MD interface, hence there is no need for one-toone mapping between a MD gas molecule and a DSMC simulation particle. Further improvement in efficiency is achieved by taking advantage of gas rarefaction inside the gas-wall interaction layer and by employing the "smart-wall model" proposed by Barisik et al. The developed hybrid algorithm is validated on two classical benchmarks namely 1-D Fourier thermal problem and Couette shear flow problem. Both the accuracy and efficiency of the hybrid algorithm are discussed. As an application, the hybrid algorithm is employed to simulate thermal transpiration coefficient in the free-molecule regime for a system with atomically smooth surface. Result is utilized to validate the coefficients calculated from the pure DSMC simulation with Maxwell and Cercignani-Lampis gas-wall interaction models. ©c 2014 Global-Science Press.
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Basavin Dmitry
2017-01-01
Full Text Available This paper is dedicated to the issue of modeling information flows in networks with complex topologies and it describes a comparison of the sequential (written in the MATLAB language and parallel (based on GPGPU technology software implementations of the hybrid fluid model (HFM of Internet traffic. Obtained performance estimates of both software implementations indicate a higher performance of parallel software implementation HFM. The directions of further research, the results of which will be the basis for the later development of parallel software implementation HFM are proposed.
Novel approach for streamflow forecasting using a hybrid ANFIS-FFA model
Yaseen, Zaher Mundher; Ebtehaj, Isa; Bonakdari, Hossein; Deo, Ravinesh C.; Danandeh Mehr, Ali; Mohtar, Wan Hanna Melini Wan; Diop, Lamine; El-shafie, Ahmed; Singh, Vijay P.
2017-11-01
The present study proposes a new hybrid evolutionary Adaptive Neuro-Fuzzy Inference Systems (ANFIS) approach for monthly streamflow forecasting. The proposed method is a novel combination of the ANFIS model with the firefly algorithm as an optimizer tool to construct a hybrid ANFIS-FFA model. The results of the ANFIS-FFA model is compared with the classical ANFIS model, which utilizes the fuzzy c-means (FCM) clustering method in the Fuzzy Inference Systems (FIS) generation. The historical monthly streamflow data for Pahang River, which is a major river system in Malaysia that characterized by highly stochastic hydrological patterns, is used in the study. Sixteen different input combinations with one to five time-lagged input variables are incorporated into the ANFIS-FFA and ANFIS models to consider the antecedent seasonal variations in historical streamflow data. The mean absolute error (MAE), root mean square error (RMSE) and correlation coefficient (r) are used to evaluate the forecasting performance of ANFIS-FFA model. In conjunction with these metrics, the refined Willmott's Index (Drefined), Nash-Sutcliffe coefficient (ENS) and Legates and McCabes Index (ELM) are also utilized as the normalized goodness-of-fit metrics. Comparison of the results reveals that the FFA is able to improve the forecasting accuracy of the hybrid ANFIS-FFA model (r = 1; RMSE = 0.984; MAE = 0.364; ENS = 1; ELM = 0.988; Drefined = 0.994) applied for the monthly streamflow forecasting in comparison with the traditional ANFIS model (r = 0.998; RMSE = 3.276; MAE = 1.553; ENS = 0.995; ELM = 0.950; Drefined = 0.975). The results also show that the ANFIS-FFA is not only superior to the ANFIS model but also exhibits a parsimonious modelling framework for streamflow forecasting by incorporating a smaller number of input variables required to yield the comparatively better performance. It is construed that the FFA optimizer can thus surpass the accuracy of the traditional ANFIS model in general
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.
Elsheikh, Ahmed H.
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. © 2013 Elsevier Inc.
Swarm Intelligence-Based Hybrid Models for Short-Term Power Load Prediction
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Jianzhou Wang
2014-01-01
Full Text Available Swarm intelligence (SI is widely and successfully applied in the engineering field to solve practical optimization problems because various hybrid models, which are based on the SI algorithm and statistical models, are developed to further improve the predictive abilities. In this paper, hybrid intelligent forecasting models based on the cuckoo search (CS as well as the singular spectrum analysis (SSA, time series, and machine learning methods are proposed to conduct short-term power load prediction. The forecasting performance of the proposed models is augmented by a rolling multistep strategy over the prediction horizon. The test results are representative of the out-performance of the SSA and CS in tuning the seasonal autoregressive integrated moving average (SARIMA and support vector regression (SVR in improving load forecasting, which indicates that both the SSA-based data denoising and SI-based intelligent optimization strategy can effectively improve the model’s predictive performance. Additionally, the proposed CS-SSA-SARIMA and CS-SSA-SVR models provide very impressive forecasting results, demonstrating their strong robustness and universal forecasting capacities in terms of short-term power load prediction 24 hours in advance.
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Yuqi Dong
2016-12-01
Full Text Available Accurate short-term electrical load forecasting plays a pivotal role in the national economy and people’s livelihood through providing effective future plans and ensuring a reliable supply of sustainable electricity. Although considerable work has been done to select suitable models and optimize the model parameters to forecast the short-term electrical load, few models are built based on the characteristics of time series, which will have a great impact on the forecasting accuracy. For that reason, this paper proposes a hybrid model based on data decomposition considering periodicity, trend and randomness of the original electrical load time series data. Through preprocessing and analyzing the original time series, the generalized regression neural network optimized by genetic algorithm is used to forecast the short-term electrical load. The experimental results demonstrate that the proposed hybrid model can not only achieve a good fitting ability, but it can also approximate the actual values when dealing with non-linear time series data with periodicity, trend and randomness.
Hybrid pathwise sensitivity methods for discrete stochastic models of chemical reaction systems.
Wolf, Elizabeth Skubak; Anderson, David F
2015-01-21
Stochastic models are often used to help understand the behavior of intracellular biochemical processes. The most common such models are continuous time Markov chains (CTMCs). Parametric sensitivities, which are derivatives of expectations of model output quantities with respect to model parameters, are useful in this setting for a variety of applications. In this paper, we introduce a class of hybrid pathwise differentiation methods for the numerical estimation of parametric sensitivities. The new hybrid methods combine elements from the three main classes of procedures for sensitivity estimation and have a number of desirable qualities. First, the new methods are unbiased for a broad class of problems. Second, the methods are applicable to nearly any physically relevant biochemical CTMC model. Third, and as we demonstrate on several numerical examples, the new methods are quite efficient, particularly if one wishes to estimate the full gradient of parametric sensitivities. The methods are rather intuitive and utilize the multilevel Monte Carlo philosophy of splitting an expectation into separate parts and handling each in an efficient manner.
A Modified Hybrid III 6-Year-Old Dummy Head Model for Lateral Impact Assessment
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I. A. Rafukka
2016-01-01
Full Text Available Hybrid III six-year-old (6YO child dummy head model was developed and validated for frontal impact assessment according to the specifications contained in Code of Federal Regulations, Title 49, Part 572.122, Subpart N by Livermore Software Technology Corporation (LSTC. This work is aimed at improving biofidelity of the head for frontal impact and also extending its application to lateral impact assessment by modifying the head skin viscoelastic properties and validating the head response using the scaled nine-year-old (9YO child cadaver head response recently published in the literature. The modified head model was validated for two drop heights for frontal, right, and left parietal impact locations. Peak resultant acceleration of the modified head model appeared to have good correlation with scaled 9YO child cadaver head response for frontal impact on dropping from 302 mm height and fair correlation with 12.3% difference for 151 mm drop height. Right parietal peak resultant acceleration values correlate well with scaled 9YO head experimental data for 153 mm drop height, while fair correlation with 16.4% difference was noticed for 302 mm drop height. Left parietal, however, shows low biofidelity for the two drop heights as the difference in head acceleration response was within 30%. The modified head model could therefore be used to estimate injuries in vehicle crash for head parietal impact locations which cannot be measured by the current hybrid III dummy head model.
A Novel Modelling Approach for Condensing Boilers Based on Hybrid Dynamical Systems
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Harish Satyavada
2016-04-01
Full Text Available Condensing boilers use waste heat from flue gases to pre-heat cold water entering the boiler. Flue gases are condensed into liquid form, thus recovering their latent heat of vaporization, which results in as much as 10%–12% increase in efficiency. Modeling these heat transfer phenomena is crucial to control this equipment. Despite the many approaches to the condensing boiler modeling, the following shortcomings are still not addressed: thermal dynamics are oversimplified with a nonlinear efficiency curve (which is calculated at steady-state; the dry/wet heat exchange is modeled in a fixed proportion. In this work we cover these shortcomings by developing a novel hybrid dynamic model which avoids the static nonlinear efficiency curve and accounts for a time-varying proportion of dry/wet heat exchange. The procedure for deriving the model is described and the efficiency of the resulting condensing boiler is shown.
A simplified model for nonlinear cross-phase modulation in hybrid optical coherent system.
Tao, Zhenning; Yan, Weizhen; Oda, Shoichiro; Hoshida, Takeshi; Rasmussen, Jens C
2009-08-03
Cross-phase modulation (XPM) has been considered as one of the ultimate obstacles for optical coherent dense wavelength division multiplexing (DWDM) systems. In order to facilitate the XPM analysis, a simplified model was proposed. The model reduced the distributed XPM phenomena to a lumped phase modulation. The XPM phase noise was generated by a linear system which was determined by the DWDM system parameters and whose inputs were undistorted pump channel intensity waveforms. The model limitations induced by the lumped phase modulation and undistorted pumps approximations were intensively discussed and verified. The simplified model showed a good agreement with simulations and experiments for a typical hybrid optical coherent system. Various XPM phenomena were explained by the proposed model.
An Investigation of a Hybrid Mixing Timescale Model for PDF Simulations of Turbulent Premixed Flames
Zhou, Hua; Kuron, Mike; Ren, Zhuyin; Lu, Tianfeng; Chen, Jacqueline H.
2016-11-01
Transported probability density function (TPDF) method features the generality for all combustion regimes, which is attractive for turbulent combustion simulations. However, the modeling of micromixing due to molecular diffusion is still considered to be a primary challenge for TPDF method, especially in turbulent premixed flames. Recently, a hybrid mixing rate model for TPDF simulations of turbulent premixed flames has been proposed, which recovers the correct mixing rates in the limits of flamelet regime and broken reaction zone regime while at the same time aims to properly account for the transition in between. In this work, this model is employed in TPDF simulations of turbulent premixed methane-air slot burner flames. The model performance is assessed by comparing the results from both direct numerical simulation (DNS) and conventional constant mechanical-to-scalar mixing rate model. This work is Granted by NSFC 51476087 and 91441202.
Systems biology by the rules: hybrid intelligent systems for pathway modeling and discovery.
Bosl, William J
2007-02-15
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. 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. 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 their knowledge base without
Systems biology by the rules: hybrid intelligent systems for pathway modeling and discovery
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Bosl William J
2007-02-01
Full Text Available Abstract 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
Modeling level change in Lake Urmia using hybrid artificial intelligence approaches
Esbati, M.; Ahmadieh Khanesar, M.; Shahzadi, Ali
2017-06-01
The investigation of water level fluctuations in lakes for protecting them regarding the importance of these water complexes in national and regional scales has found a special place among countries in recent years. The importance of the prediction of water level balance in Lake Urmia is necessary due to several-meter fluctuations in the last decade which help the prevention from possible future losses. For this purpose, in this paper, the performance of adaptive neuro-fuzzy inference system (ANFIS) for predicting the lake water level balance has been studied. In addition, for the training of the adaptive neuro-fuzzy inference system, particle swarm optimization (PSO) and hybrid backpropagation-recursive least square method algorithm have been used. Moreover, a hybrid method based on particle swarm optimization and recursive least square (PSO-RLS) training algorithm for the training of ANFIS structure is introduced. In order to have a more fare comparison, hybrid particle swarm optimization and gradient descent are also applied. The models have been trained, tested, and validated based on lake level data between 1991 and 2014. For performance evaluation, a comparison is made between these methods. Numerical results obtained show that the proposed methods with a reasonable error have a good performance in water level balance prediction. It is also clear that with continuing the current trend, Lake Urmia will experience more drop in the water level balance in the upcoming years.
Finite element modelling of concrete beams reinforced with hybrid fiber reinforced bars
Smring, Santa binti; Salleh, Norhafizah; Hamid, NoorAzlina Abdul; Majid, Masni A.
2017-11-01
Concrete is a heterogeneous composite material made up of cement, sand, coarse aggregate and water mixed in a desired proportion to obtain the required strength. Plain concrete does not with stand tension as compared to compression. In order to compensate this drawback steel reinforcement are provided in concrete. Now a day, for improving the properties of concrete and also to take up tension combination of steel and glass fibre-reinforced polymer (GFRP) bars promises favourable strength, serviceability, and durability. To verify its promise and support design concrete structures with hybrid type of reinforcement, this study have investigated the load-deflection behaviour of concrete beams reinforced with hybrid GFRP and steel bars by using ATENA software. Fourteen beams, including six control beams reinforced with only steel or only GFRP bars, were analysed. The ratio and the ordinate of GFRP to steel were the main parameters investigated. The behaviour of these beams was investigated via the load-deflection characteristics, cracking behaviour and mode of failure. Hybrid GFRP-Steel reinforced concrete beam showed the improvement in both ultimate capacity and deflection concomitant to the steel reinforced concrete beam. On the other hand, finite element (FE) modelling which is ATENA were validated with previous experiment and promising the good result to be used for further analyses and development in the field of present study.
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.
Di, Qian; Rowland, Sebastian; Koutrakis, Petros; Schwartz, Joel
2017-01-01
Ground-level ozone is an important atmospheric oxidant, which exhibits considerable spatial and temporal variability in its concentration level. Existing modeling approaches for ground-level ozone include chemical transport models, land-use regression, Kriging, and data fusion of chemical transport models with monitoring data. Each of these methods has both strengths and weaknesses. Combining those complementary approaches could improve model performance. Meanwhile, satellite-based total column ozone, combined with ozone vertical profile, is another potential input. The authors propose a hybrid model that integrates the above variables to achieve spatially and temporally resolved exposure assessments for ground-level ozone. The authors used a neural network for its capacity to model interactions and nonlinearity. Convolutional layers, which use convolution kernels to aggregate nearby information, were added to the neural network to account for spatial and temporal autocorrelation. The authors trained the model with the Air Quality System (AQS) 8-hr daily maximum ozone in the continental United States from 2000 to 2012 and tested it with left out monitoring sites. Cross-validated R2 on the left out monitoring sites ranged from 0.74 to 0.80 (mean 0.76) for predictions on 1 km × 1 km grid cells, which indicates good model performance. Model performance remains good even at low ozone concentrations. The prediction results facilitate epidemiological studies to assess the health effect of ozone in the long term and the short term. Ozone monitors do not provide full data coverage over the United States, which is an obstacle to assess the health effect of ozone when monitoring data are not available. This paper used a hybrid approach to combine satellite-based ozone measurements, chemical transport model simulations, land-use terms, and other auxiliary variables to obtain spatially and temporally resolved ground-level ozone estimation.
von Stosch, Moritz; Davy, Steven; Francois, Kjell; Galvanauskas, Vytautas; Hamelink, Jan-Martijn; Luebbert, Andreas; Mayer, Martin; Oliveira, Rui; O'Kennedy, Ronan; Rice, Paul; Glassey, Jarka
2014-06-01
This report highlights the drivers, challenges, and enablers of the hybrid modeling applications in biopharmaceutical industry. It is a summary of an expert panel discussion of European academics and industrialists with relevant scientific and engineering backgrounds. Hybrid modeling is viewed in its broader sense, namely as the integration of different knowledge sources in form of parametric and nonparametric models into a hybrid semi-parametric model, for instance the integration of fundamental and data-driven models. A brief description of the current state-of-the-art and industrial uptake of the methodology is provided. The report concludes with a number of recommendations to facilitate further developments and a wider industrial application of this modeling approach. These recommendations are limited to further exploiting the benefits of this methodology within process analytical technology (PAT) applications in biopharmaceutical industry. Copyright © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Modeling and Optimizing Energy Utilization of Steel Production Process: A Hybrid Petri Net Approach
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Peng Wang
2013-01-01
Full Text Available The steel industry is responsible for nearly 9% of anthropogenic energy utilization in the world. It is urgent to reduce the total energy utilization of steel industry under the huge pressures on reducing energy consumption and CO2 emission. Meanwhile, the steel manufacturing is a typical continuous-discrete process with multiprocedures, multiobjects, multiconstraints, and multimachines coupled, which makes energy management rather difficult. In order to study the energy flow within the real steel production process, this paper presents a new modeling and optimization method for the process based on Hybrid Petri Nets (HPN in consideration of the situation above. Firstly, we introduce the detailed description of HPN. Then the real steel production process from one typical integrated steel plant is transformed into Hybrid Petri Net model as a case. Furthermore, we obtain a series of constraints of our optimization model from this model. In consideration of the real process situation, we pick the steel production, energy efficiency and self-made gas surplus as the main optimized goals in this paper. Afterwards, a fuzzy linear programming method is conducted to obtain the multiobjective optimization results. Finally, some measures are suggested to improve this low efficiency and high whole cost process structure.
A Mathematical and Numerical Model for the Analysis of Hybrid Rocket Motors
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Florin MINGIREANU
2011-12-01
Full Text Available The hybrid rocket motors (HRM use a two-phase propellant system. This offers some remarkable advantages but also arises some difficulties like the neutralization of their instabilities. The non-acoustic combustion instabilities are high-amplitude pressure oscillations that have too low frequencies to be associated with acoustics. Acoustic type combustion instabilities are self-excited oscillations generated by the interaction between acoustic waves and combustion. The goal of the present work is to 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. This model must be useful for transient and stability analysis and also for scaling of HRMs. The numerical results obtained with our model show a good agreement with published experimental and numerical results. The computational and stability analysis models developed in this work are simple, computationally efficient and offer the advantage of taking into account a large number of functional and constructive parameters that are used by the engineers.
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Suman Sutradhar
2016-01-01
Full Text Available In this paper, a novel approach of hybridization of two efficient metaheuristic algorithms is proposed for energy system analysis and modelling based on a hydro and thermal based power system in both single and multiobjective environment. The scheduling of hydro and thermal power is modelled descriptively including the handling method of various practical nonlinear constraints. The main goal for the proposed modelling is to minimize the total production cost (which is highly nonlinear and nonconvex problem and emission while satisfying involved hydro and thermal unit commitment limitations. The cascaded hydro reservoirs of hydro subsystem and intertemporal constraints regarding thermal units along with nonlinear nonconvex, mixed-integer mixed-binary objective function make the search space highly complex. To solve such a complicated system, a hybridization of Gray Wolf Optimization and Artificial Bee Colony algorithm, that is, h-ABC/GWO, is used for better exploration and exploitation in the multidimensional search space. Two different test systems are used for modelling and analysis. Experimental results demonstrate the superior performance of the proposed algorithm as compared to other recently reported ones in terms of convergence and better quality of solutions.
Solving Optimal Control Problem of Monodomain Model Using Hybrid Conjugate Gradient Methods
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Kin Wei Ng
2012-01-01
Full Text Available We present the numerical solutions for the PDE-constrained optimization problem arising in cardiac electrophysiology, that is, the optimal control problem of monodomain model. The optimal control problem of monodomain model is a nonlinear optimization problem that is constrained by the monodomain model. The monodomain model consists of a parabolic partial differential equation coupled to a system of nonlinear ordinary differential equations, which has been widely used for simulating cardiac electrical activity. Our control objective is to dampen the excitation wavefront using optimal applied extracellular current. Two hybrid conjugate gradient methods are employed for computing the optimal applied extracellular current, namely, the Hestenes-Stiefel-Dai-Yuan (HS-DY method and the Liu-Storey-Conjugate-Descent (LS-CD method. Our experiment results show that the excitation wavefronts are successfully dampened out when these methods are used. Our experiment results also show that the hybrid conjugate gradient methods are superior to the classical conjugate gradient methods when Armijo line search is used.
Hybrid 3D model for the interaction of plasma thruster plumes with nearby objects
Cichocki, Filippo; Domínguez-Vázquez, Adrián; Merino, Mario; Ahedo, Eduardo
2017-12-01
This paper presents a hybrid particle-in-cell (PIC) fluid approach to model the interaction of a plasma plume with a spacecraft and/or any nearby object. Ions and neutrals are modeled with a PIC approach, while electrons are treated as a fluid. After a first iteration of the code, the domain is split into quasineutral and non-neutral regions, based on non-neutrality criteria, such as the relative charge density and the Debye length-to-cell size ratio. At the material boundaries of the former quasineutral region, a dedicated algorithm ensures that the Bohm condition is met. In the latter non-neutral regions, the electron density and electric potential are obtained by solving the coupled electron momentum balance and Poisson equations. Boundary conditions for both the electric current and potential are finally obtained with a plasma sheath sub-code and an equivalent circuit model. The hybrid code is validated by applying it to a typical plasma plume–spacecraft interaction scenario, and the physics and capabilities of the model are finally discussed.
Modeling wall effects in a micro-scale shock tube using hybrid MD-DSMC algorithm
Watvisave, D. S.; Puranik, B. P.; Bhandarkar, U. V.
2016-07-01
Wall effects in a micro-scale shock tube are investigated using the Direct Simulation Monte Carlo method as well as a hybrid Molecular Dynamics-Direct Simulation Monte Carlo algorithm. In the Direct Simulation Monte Carlo simulations, the Cercignani-Lampis-Lord model of gas-surface interactions is employed to incorporate the wall effects, and it is shown that the shock attenuation is significantly affected by the choice of the values of tangential momentum accommodation coefficient. A loosely coupled Molecular Dynamics-Direct Simulation Monte Carlo approach is then employed to demonstrate incomplete accommodation in micro-scale shock tube flows. This approach uses fixed values of the accommodation coefficients in the gas-surface interaction model, with their values determined from a separate dynamically similar Molecular Dynamics simulation. Finally, a completely coupled Molecular Dynamics-Direct Simulation Monte Carlo algorithm is used, wherein the bulk of the flow is modeled using Direct Simulation Monte Carlo, while the interaction of gas molecules with the shock tube walls is modeled using Molecular Dynamics. The two regions are separate and coupled both ways using buffer zones and a bootstrap coupling algorithm that accounts for the mismatch of the number of molecules in both regions. It is shown that the hybrid method captures the effect of local properties that cannot be captured using a single value of accommodation coefficient for the entire domain.
Directory of Open Access Journals (Sweden)
Iván Contreras
Full Text Available The large patient variability in human physiology and the effects of variables such as exercise or meals challenge current prediction modeling techniques. Physiological models are very precise but they are typically complex and specific physiological knowledge is required. In contrast, data-based models allow the incorporation of additional inputs and accurately capture the relationship between these inputs and the outcome, but at the cost of losing the physiological meaning of the model. In this work, we designed a hybrid approach comprising physiological models for insulin and grammatical evolution, taking into account the clinical harm caused by deviations from the target blood glucose by using a penalizing fitness function based on the Clarke error grid. The prediction models were built using data obtained over 14 days for 100 virtual patients generated by the UVA/Padova T1D simulator. Midterm blood glucose was predicted for the 100 virtual patients using personalized models and different scenarios. The results obtained were promising; an average of 98.31% of the predictions fell in zones A and B of the Clarke error grid. Midterm predictions using personalized models are feasible when the configuration of grammatical evolution explored in this study is used. The study of new alternative models is important to move forward in the development of alarm-and-control applications for the management of type 1 diabetes and the customization of the patient's treatments. The hybrid approach can be adapted to predict short-term blood glucose values to detect continuous glucose-monitoring sensor errors and to estimate blood glucose values when the continuous glucose-monitoring system fails to provide them.
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
A dynamic hybrid RANS/LES modeling methodology for turbulent/transitional flow field prediction
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
Energy Technology Data Exchange (ETDEWEB)
Tikare, Veena [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Hernandez-Rivera, Efrain [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Madison, Jonathan D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Holm, Elizabeth Ann [Carnegie Mellon Univ., Pittsburgh, PA (United States); Patterson, Burton R. [Univ. of Florida, Gainesville, FL (United States). Dept. of Materials Science and Engineering; Homer, Eric R. [Brigham Young Univ., Provo, UT (United States). Dept. of Mechanical Engineering
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.
An isothermal model of a hybrid Stirling/reverse-Brayton cryocooler
Nellis, G. F.; Maddocks, J. R.
2003-01-01
This paper presents a model of a cryogenic refrigerator that integrates a reverse-Brayton lower temperature stage with a 2-piston Stirling upper temperature stage using a rectification system of check valves and buffer volumes. The numerical model extends the isothermal Schmidt analysis of the Stirling cycle by deriving the additional dimensionless governing equations that characterize the recuperative system. Numerical errors are quantified and the results are verified against analytical solutions in the appropriate limits. The model is used to explore the effect of the rectification system's characteristics on the overall cycle's behavior. Finally, the model is used to optimize the hybrid system's design by varying the swept volume ratio and phase angle in order to maximize the refrigeration per unit of heat transfer in the recuperator and regenerator.
Representing hybrid compensatory non-compensatory choice set formation in semi-compensatory models
DEFF Research Database (Denmark)
Kaplan, Sigal; Bekhor, Shlomo; Shigtan, Yoram
2012-01-01
Semi-compensatory models represent a choice process consisting of an elimination-based choice set formation upon satisfying criteria thresholds and a utility-based choice. Current semi-compensatory models assume a purely non-compensatory choice set formation and hence do not support multinomial...... model that combines multinomial-response and ordered-response thresholds with a utility-based choice. The proposed model is applied to a stated preference experiment of off-campus rental apartment choices by students. Results demonstrate the applicability and feasibility of incorporating multinomial...... criteria that involve trade-offs among attributes at the choice set formation stage. This study proposes a novel behavioral paradigm comprising a hybrid compensatory non-compensatory choice set formation process, followed by compensatory choice. The behavioral paradigm is represented by a mathematical...
A hybrid model of laser energy deposition for multi-dimensional simulations of plasmas and metals
Basko, Mikhail M.; Tsygvintsev, Ilia P.
2017-05-01
The hybrid model of laser energy deposition is a combination of the geometrical-optics ray-tracing method with the one-dimensional (1D) solution of the Helmholtz wave equation in regions where the geometrical optics becomes inapplicable. We propose an improved version of this model, where a new physically consistent criterion for transition to the 1D wave optics is derived, and a special rescaling procedure of the wave-optics deposition profile is introduced. The model is intended for applications in large-scale two- and three-dimensional hydrodynamic codes. Comparison with exact 1D solutions demonstrates that it can fairly accurately reproduce the absorption fraction in both the s- and p-polarizations on arbitrarily steep density gradients, provided that a sufficiently accurate algorithm for gradient evaluation is used. The accuracy of the model becomes questionable for long laser pulses simulated on too fine grids, where the hydrodynamic self-focusing instability strongly manifests itself.
Hybrid Wavelet-Postfix-GP Model for Rainfall Prediction of Anand Region of India
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Vipul K. Dabhi
2014-01-01
Full Text Available An accurate prediction of rainfall is crucial for national economy and management of water resources. The variability of rainfall in both time and space makes the rainfall prediction a challenging task. The present work investigates the applicability of a hybrid wavelet-postfix-GP model for daily rainfall prediction of Anand region using meteorological variables. The wavelet analysis is used as a data preprocessing technique to remove the stochastic (noise component from the original time series of each meteorological variable. The Postfix-GP, a GP variant, and ANN are then employed to develop models for rainfall using newly generated subseries of meteorological variables. The developed models are then used for rainfall prediction. The out-of-sample prediction performance of Postfix-GP and ANN models is compared using statistical measures. The results are comparable and suggest that Postfix-GP could be explored as an alternative tool for rainfall prediction.
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Ferdinando Chiacchio
2018-01-01
Full Text Available The contribution of renewable energies to the reduction of the impact of fossil fuels sources and especially energy supply in remote areas has occupied a role more and more important during last decades. The estimation of renewable power plants performances by means of deterministic models is usually limited by the innate variability of the energy resources. The accuracy of energy production forecasting results may be inadequate. An accurate feasibility analysis requires taking into account the randomness of the primary resource operations and the effect of component failures in the energy production process. This paper treats a novel approach to the estimation of energy production in a real photovoltaic power plant by means of dynamic reliability analysis based on Stochastic Hybrid Fault Tree Automaton (SHyFTA. The comparison between real data, deterministic model and SHyFTA model confirm how the latter better estimate energy production than deterministic model.
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A. M. Gashimov
2013-01-01
Full Text Available The paper considers problems pertaining to modeling and simulation of operational hybrid system modes of the distributed generation comprising conventional sources – modular diesel generators, gas-turbine power units; and renewable sources – wind and solar power plants. Operational modes of the hybrid system have been investigated under conditions of electrical connection with electric power system and in case of its isolated operation. As a consequence
MURUGESAN, KARTHIK; SENNIAPPAN, VIJAYACHITRA
2016-01-01
A dynamic modeling of Fuel cell/Battery assisted hybrid electric vehicle system is presented in this article and two suitable power sharing control strategies are integrated into the system with the objective of minimizing the fuel consumption and maximizing the battery life through its safe operating limit. This prominent goal is accomplished into the developed hybrid vehicle system by incorporating suitable control strategies without compromising the drivability of the vehicle. The proposed...
Cluster dynamics modelling of materials: A new hybrid deterministic/stochastic coupling approach
Terrier, Pierre; Athènes, Manuel; Jourdan, Thomas; Adjanor, Gilles; Stoltz, Gabriel
2017-12-01
Deterministic simulations of the rate equations governing cluster dynamics in materials are limited by the number of equations to integrate. Stochastic simulations are limited by the high frequency of certain events. We propose a coupling method combining deterministic and stochastic approaches. It allows handling different time scale phenomena for cluster dynamics. This method, based on a splitting of the dynamics, is generic and we highlight two different hybrid deterministic/stochastic methods. These coupling schemes are highly parallelizable and specifically designed to treat large size cluster problems. The proof of concept is made on a simple model of vacancy clustering under thermal ageing.
Model-Invariant Hybrid LES-RANS Computation of Separated Flow Past Periodic Hills
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.
Energy Technology Data Exchange (ETDEWEB)
Jaschke, P.
2000-02-01
Mathematical models of the dynamic performance of hydrodynamic couplings are developed using hybrid modelling, i.e. a combination of analytical physical modelling and black box identification. The models developed were verified by measurements on a model powertrain. [German] In dieser Arbeit werden mit Hilfe der hybriden Modellierung mathematische Modelle zur Beschreibung des dynamischen Betriebsverhaltens hydrodynamischer Kupplungen ermittelt. Die Hybride Modellierung stellt eine Kombination der analytisch physikalischen Modellierung und der Black-Box-Identifikation dar. Diese Modellierungsart ist ausgewaehlt worden, um die Vorteile der analytisch physikalischen Modellierung und der Black-Box-Identifikation hydrodynamischer Kupplungen zu verbinden und deren Nachteile gering zu halten. Auf dieser Basis ist eine Vorgehensweise vorgestellt worden, die die Ermittlung der Modelle mit wenig Aufwand ermoeglicht. Mit Hilfe der Modelltheorie wird gezeigt, wie die ermittelten mathematischen Modelle zur Simulation des dynamischen Betriebsverhaltens geometrisch aehnlicher Kupplungen unterschiedlicher Baugroessen verwendet werden koennen. Darueber hinaus wird dargelegt, wie die ermittelten Modelle mit Modellen anderer Antriebsstrangelemente gekoppelt werden koennen, um Antriebsstrangsimulationen zu ermoeglichen. Verifikationsmessungen an einem Modellantriebsstrang verdeutlichen die Guete und Verwendbarkeit der mathematischen Modelle. (orig.)
High performance hybrid functional Petri net simulations of biological pathway models on CUDA.
Chalkidis, Georgios; Nagasaki, Masao; Miyano, Satoru
2011-01-01
Hybrid functional Petri nets are a wide-spread tool for representing and simulating biological models. Due to their potential of providing virtual drug testing environments, biological simulations have a growing impact on pharmaceutical research. Continuous research advancements in biology and medicine lead to exponentially increasing simulation times, thus raising the demand for performance accelerations by efficient and inexpensive parallel computation solutions. Recent developments in the field of general-purpose computation on graphics processing units (GPGPU) enabled the scientific community to port a variety of compute intensive algorithms onto the graphics processing unit (GPU). This work presents the first scheme for mapping biological hybrid functional Petri net models, which can handle both discrete and continuous entities, onto compute unified device architecture (CUDA) enabled GPUs. GPU accelerated simulations are observed to run up to 18 times faster than sequential implementations. Simulating the cell boundary formation by Delta-Notch signaling on a CUDA enabled GPU results in a speedup of approximately 7x for a model containing 1,600 cells.
Modeling of hybridized infrared arrays for characterization of interpixel capacitive coupling
Donlon, Kevan; Ninkov, Zoran; Baum, Stefi; Cheng, Linpeng
2017-02-01
Interpixel capacitance (IPC) is a deterministic electronic coupling resulting in a portion of signal incident on one pixel of a hybridized detector array being measured in adjacent pixels. Data collected by light sensitive HgCdTe arrays that exhibit this coupling typically goes uncorrected or is corrected by treating the coupling as a fixed point spread function. Evidence suggests that this coupling is not uniform across signal and background levels. Subarrays of pixels using design parameters based upon HgCdTe indium hybridized arrays akin to those contained in the James Webb Space Telescope's NIRcam have been modeled from first principles using Lumerical DEVICE Software. This software simultaneously solves Poisson's equation and the drift diffusion equations yielding charge distributions and electric fields. Modeling of this sort generates the local point spread function across a range of detector parameters. This results in predictive characterization of IPC across scene and device parameters that would permit proper photometric correction and signal restoration to the data. Additionally, the ability to visualize potential distributions and couplings as generated by the models yields insight that can be used to minimize IPC coupling in the design of future detectors.
Hybrid Neural Network Approach Based Tool for the Modelling of Photovoltaic Panels
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Antonino Laudani
2015-01-01
Full Text Available A hybrid neural network approach based tool for identifying the photovoltaic one-diode model is presented. The generalization capabilities of neural networks are used together with the robustness of the reduced form of one-diode model. Indeed, from the studies performed by the authors and the works present in the literature, it was found that a direct computation of the five parameters via multiple inputs and multiple outputs neural network is a very difficult task. The reduced form consists in a series of explicit formulae for the support to the neural network that, in our case, is aimed at predicting just two parameters among the five ones identifying the model: the other three parameters are computed by reduced form. The present hybrid approach is efficient from the computational cost point of view and accurate in the estimation of the five parameters. It constitutes a complete and extremely easy tool suitable to be implemented in a microcontroller based architecture. Validations are made on about 10000 PV panels belonging to the California Energy Commission database.
The Importance of Being Hybrid for Spatial Epidemic Models:A Multi-Scale Approach
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Arnaud Banos
2015-11-01
Full Text Available This work addresses the spread of a disease within an urban system, deﬁnedas a network of interconnected cities. The ﬁrst step consists of comparing two differentapproaches: a macroscopic one, based on a system of coupled Ordinary DifferentialEquations (ODE Susceptible-Infected-Recovered (SIR systems exploiting populations onnodes and ﬂows on edges (so-called metapopulational model, and a hybrid one, couplingODE SIR systems on nodes and agents traveling on edges. Under homogeneous conditions(mean ﬁeld approximation, this comparison leads to similar results on the outputs on whichwe focus (the maximum intensity of the epidemic, its duration and the time of the epidemicpeak. However, when it comes to setting up epidemic control strategies, results rapidlydiverge between the two approaches, and it appears that the full macroscopic model is notcompletely adapted to these questions. In this paper, we focus on some control strategies,which are quarantine, avoidance and risk culture, to explore the differences, advantages anddisadvantages of the two models and discuss the importance of being hybrid when modelingand simulating epidemic spread at the level of a whole urban system.
Cutting Modeling of Hybrid CFRP/Ti Composite with Induced Damage Analysis
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Jinyang Xu
2016-01-01
Full Text Available In hybrid carbon fiber reinforced polymer (CFRP/Ti machining, the bi-material interface is the weakest region vulnerable to severe damage formation when the tool cutting from one phase to another phase and vice versa. The interface delamination as well as the composite-phase damage is the most serious failure dominating the bi-material machining. In this paper, an original finite element (FE model was developed to inspect the key mechanisms governing the induced damage formation when cutting this multi-phase material. The hybrid composite model was constructed by establishing three disparate physical constituents, i.e., the Ti phase, the interface, and the CFRP phase. Different constitutive laws and damage criteria were implemented to build up the entire cutting behavior of the bi-material system. The developed orthogonal cutting (OC model aims to characterize the dynamic mechanisms of interface delamination formation and the affected interface zone (AIZ. Special focus was made on the quantitative analyses of the parametric effects on the interface delamination and composite-phase damage. The numerical results highlighted the pivotal role of AIZ in affecting the formation of interface delamination, and the significant impacts of feed rate and cutting speed on delamination extent and fiber/matrix failure.
Cutting Modeling of Hybrid CFRP/Ti Composite with Induced Damage Analysis
Xu, Jinyang; El Mansori, Mohamed
2016-01-01
In hybrid carbon fiber reinforced polymer (CFRP)/Ti machining, the bi-material interface is the weakest region vulnerable to severe damage formation when the tool cutting from one phase to another phase and vice versa. The interface delamination as well as the composite-phase damage is the most serious failure dominating the bi-material machining. In this paper, an original finite element (FE) model was developed to inspect the key mechanisms governing the induced damage formation when cutting this multi-phase material. The hybrid composite model was constructed by establishing three disparate physical constituents, i.e., the Ti phase, the interface, and the CFRP phase. Different constitutive laws and damage criteria were implemented to build up the entire cutting behavior of the bi-material system. The developed orthogonal cutting (OC) model aims to characterize the dynamic mechanisms of interface delamination formation and the affected interface zone (AIZ). Special focus was made on the quantitative analyses of the parametric effects on the interface delamination and composite-phase damage. The numerical results highlighted the pivotal role of AIZ in affecting the formation of interface delamination, and the significant impacts of feed rate and cutting speed on delamination extent and fiber/matrix failure. PMID:28787824
A Hybrid Distance-Based Ideal-Seeking Consensus Ranking Model
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Madjid Tavana
2007-01-01
Full Text Available Ordinal consensus ranking problems have received much attention in the management science literature. A problem arises in situations where a group of k decision makers (DMs is asked to rank order n alternatives. The question is how to combine the DM rankings into one consensus ranking. Several different approaches have been suggested to aggregate DM responses into a compromise or consensus ranking; however, the similarity of consensus rankings generated by the different algorithms is largely unknown. In this paper, we propose a new hybrid distance-based ideal-seeking consensus ranking model (DCM. The proposed hybrid model combines parts of the two commonly used consensus ranking techniques of Beck and Lin (1983 and Cook and Kress (1985 into an intuitive and computationally simple model. We illustrate our method and then run a Monte Carlo simulation across a range of k and n to compare the similarity of the consensus rankings generated by our method with the best-known method of Borda and Kendall (Kendall 1962 and the two methods proposed by Beck and Lin (1983 and Cook and Kress (1985. DCM and Beck and Lin's method yielded the most similar consensus rankings, whereas the Cook-Kress method and the Borda-Kendall method yielded the least similar consensus rankings.
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.
Corresponding-states behavior of SPC/E-based modified (bent and hybrid) water models
Weiss, Volker C.
2017-02-01
The remarkable and sometimes anomalous properties of water can be traced back at the molecular level to the tetrahedral coordination of molecules due to the ability of a water molecule to form four hydrogen bonds to its neighbors; this feature allows for the formation of a network that greatly influences the thermodynamic behavior. Computer simulations are becoming increasingly important for our understanding of water. Molecular models of water, such as SPC/E, are needed for this purpose, and they have proved to capture many important features of real water. Modifications of the SPC/E model have been proposed, some changing the H-O-H angle (bent models) and others increasing the importance of dispersion interactions (hybrid models), to study the structural features that set water apart from other polar fluids and from simple fluids such as argon. Here, we focus on the properties at liquid-vapor equilibrium and study the coexistence curve, the interfacial tension, and the vapor pressure in a corresponding-states approach. In particular, we calculate Guggenheim's ratio for the reduced apparent enthalpy of vaporization and Guldberg's ratio for the reduced normal boiling point. This analysis offers additional insight from a more macroscopic, thermodynamic perspective and augments that which has already been learned at the molecular level from simulations. In the hybrid models, the relative importance of dispersion interactions is increased, which turns the modified water into a Lennard-Jones-like fluid. Consequently, in a corresponding-states framework, the typical behavior of simple fluids, such as argon, is seen to be approached asymptotically. For the bent models, decreasing the bond angle turns the model essentially into a polar diatomic fluid in which the particles form linear molecular arrangements; as a consequence, characteristic features of the corresponding-states behavior of hydrogen halides emerge.
Hybrid mathematical model of cardiomyocyte turnover in the adult human heart.
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Jeremy A Elser
Full Text Available The capacity for cardiomyocyte regeneration in the healthy adult human heart is fundamentally relevant for both myocardial homeostasis and cardiomyopathy therapeutics. However, estimates of cardiomyocyte turnover rates conflict greatly, with a study employing C14 pulse-chase methodology concluding 1% annual turnover in youth declining to 0.5% with aging and another using cell population dynamics indicating substantial, age-increasing turnover (4% increasing to 20%.Create a hybrid mathematical model to critically examine rates of cardiomyocyte turnover derived from alternative methodologies.Examined in isolation, the cell population analysis exhibited severe sensitivity to a stem cell expansion exponent (20% variation causing 2-fold turnover change and apoptosis rate. Similarly, the pulse-chase model was acutely sensitive to assumptions of instantaneous incorporation of atmospheric C14 into the body (4-fold impact on turnover in young subjects while numerical restrictions precluded otherwise viable solutions. Incorporating considerations of primary variable sensitivity and controversial model assumptions, an unbiased numerical solver identified a scenario of significant, age-increasing turnover (4-6% increasing to 15-22% with age that was compatible with data from both studies, provided that successive generations of cardiomyocytes experienced higher attrition rates than predecessors.Assignment of histologically-observed stem/progenitor cells into discrete regenerative phenotypes in the cell population model strongly influenced turnover dynamics without being directly testable. Alternatively, C14 trafficking assumptions and restrictive models in the pulse-chase model artificially eliminated high-turnover solutions. Nevertheless, discrepancies among recent cell turnover estimates can be explained and reconciled. The hybrid mathematical model provided herein permits further examination of these and forthcoming datasets.
Hybrid fluid/kinetic modeling of Pluto’s escaping atmosphere
Erwin, Justin; Tucker, O. J.; Johnson, Robert E.
2013-09-01
Predicting the rate of escape and thermal structure of Pluto’s upper atmosphere in preparation for the New Horizons Spacecraft encounter in 2015 is important for planning and interpreting the expected measurements. Having a moderate Jeans parameter Pluto’s atmosphere does not fit the classic definition of Jeans escape for light species escaping from the terrestrial planets, nor does it fit the hydrodynamic outflow from comets and certain exoplanets. It has been proposed for some time that Pluto lies in the region of slow hydrodynamic escape. Using a hybrid fluid/molecular-kinetic model, we previously demonstrated the typical implementation of this model fails to correctly describe the appropriate temperature structure for the upper atmosphere for solar minimum conditions. Here we use a time-dependent solver to allow us to extend those simulations to higher heating rates and we examine fluid models in which Jeans-like escape expressions are used for the upper boundary conditions. We compare these to hybrid simulations of the atmosphere under heating conditions roughly representative of solar minimum and mean conditions as these bracket conditions expected during the New Horizon encounter. Although we find escape rates comparable to those previously estimated by the slow hydrodynamic escape model, and roughly consistent with energy limited escape, our model produces a much more extended atmosphere with higher temperatures roughly consistent with recent observations of CO. Such an extended atmosphere will be affected by Charon and will affect Pluto’s interaction with the solar wind at the New Horizon encounter. For the parameter space covered, we also find an inverse relationship between exobase temperature and altitude and the Jeans escape rate that is consistent with the energy limited escape rate. Since we have previously shown that such models can be scaled, these results have implications for modeling exoplanet atmospheres for which the energy limited
A Hybrid Windkessel Model of Blood Flow in Arterial Tree Using Velocity Profile Method
Aboelkassem, Yasser; Virag, Zdravko
2016-11-01
For the study of pulsatile blood flow in the arterial system, we derived a coupled Windkessel-Womersley mathematical model. Initially, a 6-elements Windkessel model is proposed to describe the hemodynamics transport in terms of constant resistance, inductance and capacitance. This model can be seen as a two compartment model, in which the compartments are connected by a rigid pipe, modeled by one inductor and resistor. The first viscoelastic compartment models proximal part of the aorta, the second elastic compartment represents the rest of the arterial tree and aorta can be seen as the connection pipe. Although the proposed 6-elements lumped model was able to accurately reconstruct the aortic pressure, it can't be used to predict the axial velocity distribution in the aorta and the wall shear stress and consequently, proper time varying pressure drop. We then modified this lumped model by replacing the connection pipe circuit elements with a vessel having a radius R and a length L. The pulsatile flow motions in the vessel are resolved instantaneously along with the Windkessel like model enable not only accurate prediction of the aortic pressure but also wall shear stress and frictional pressure drop. The proposed hybrid model has been validated using several in-vivo aortic pressure and flow rate data acquired from different species such as, humans, dogs and pigs. The method accurately predicts the time variation of wall shear stress and frictional pressure drop. Institute for Computational Medicine, Dept. Biomedical Engineering.
Hybrid LCA model for assessing the embodied environmental impacts of buildings in South Korea
Energy Technology Data Exchange (ETDEWEB)
Jang, Minho, E-mail: minmin40@hanmail.net [Asset Management Division, Mate Plus Co., Ltd., 9th Fl., Financial News Bldg. 24-5 Yeouido-dong, Yeongdeungpo-gu, Seoul, 150-877 (Korea, Republic of); Hong, Taehoon, E-mail: hong7@yonsei.ac.kr [Department of Architectural Engineering, Yonsei University, Seoul, 120-749 (Korea, Republic of); Ji, Changyoon, E-mail: chnagyoon@yonsei.ac.kr [Department of Architectural Engineering, Yonsei University, Seoul, 120-749 (Korea, Republic of)
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.
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.
Treatment of early and late reflections in a hybrid computer model for room acoustics
DEFF Research Database (Denmark)
Naylor, Graham
1992-01-01
The ODEON computer model for acoustics in large rooms is intended for use both in design (by predicting room acoustical indices quickly and easily) and in research (by forming the basis of an auralization system and allowing study of various room acoustical phenomena). These conflicting demands...... preclude the use of both ``pure'' image source and ``pure'' particle tracing methods. A hybrid model has been developed, in which rays discover potential image sources up to a specified order. Thereafter, the same ray tracing process is used in a different way to rapidly generate a dense reverberant decay....... In this paper the computational model is described. Particular attention is paid to alternative methods of implementing the reverberant tail, and to the problems that arise when joining early and late parts of a reflectogram generated with different algorithms. A companion paper presents the features...
Modeling of temperature field and fluid flow in hybrid welding process
Directory of Open Access Journals (Sweden)
W. Piekarska
2009-07-01
Full Text Available Mathematical and numerical model of the temperature field and the velocity field in melted zone concerning the hybrid laser – arc process was presented in this paper. The temperature field was determined by solution the transient heat transfer equation with activity of inner heat sources. Fluid flow in welding pool was determined by solution of the Navier – Stokes equation in Chorin’s projection. The fuzzy solidification front was assumed in a numerical algorithm with linear approximation of the solid phase in mushy zone. Fluid flow through porous medium was considered in mushy zone according to Darcy’s model. In the base of elaborated models and realized algorithms, results of computer simulations were presented in this study. Temperature distribution in the weld and velocity distribution in melted zone as well as welding pool shape and heat affected zone were illustrated.
ISG hybrid powertrain: a rule-based driver model incorporating look-ahead information
Shen, Shuiwen; Zhang, Junzhi; Chen, Xiaojiang; Zhong, Qing-Chang; Thornton, Roger
2010-03-01
According to European regulations, if the amount of regenerative braking is determined by the travel of the brake pedal, more stringent standards must be applied, otherwise it may adversely affect the existing vehicle safety system. The use of engine or vehicle speed to derive regenerative braking is one way to avoid strict design standards, but this introduces discontinuity in powertrain torque when the driver releases the acceleration pedal or applies the brake pedal. This is shown to cause oscillations in the pedal input and powertrain torque when a conventional driver model is adopted. Look-ahead information, together with other predicted vehicle states, are adopted to control the vehicle speed, in particular, during deceleration, and to improve the driver model so that oscillations can be avoided. The improved driver model makes analysis and validation of the control strategy for an integrated starter generator (ISG) hybrid powertrain possible.
Molecular modeling of biomolecules by paramagnetic NMR and computational hybrid methods.
Pilla, Kala Bharath; Gaalswyk, Kari; MacCallum, Justin L
2017-11-01
The 3D atomic structures of biomolecules and their complexes are key to our understanding of biomolecular function, recognition, and mechanism. However, it is often difficult to obtain structures, particularly for systems that are complex, dynamic, disordered, or exist in environments like cell membranes. In such cases sparse data from a variety of paramagnetic NMR experiments offers one possible source of structural information. These restraints can be incorporated in computer modeling algorithms that can accurately translate the sparse experimental data into full 3D atomic structures. In this review, we discuss various types of paramagnetic NMR/computational hybrid modeling techniques that can be applied to successful modeling of not only the atomic structure of proteins but also their interacting partners. This article is part of a Special Issue entitled: Biophysics in Canada, edited by Lewis Kay, John Baenziger, Albert Berghuis and Peter Tieleman. Copyright © 2017 Elsevier B.V. All rights reserved.
Directory of Open Access Journals (Sweden)
Aijia Ouyang
2015-01-01
Full Text Available Nonlinear Muskingum models are important tools in hydrological forecasting. In this paper, we have come up with a class of new discretization schemes including a parameter θ to approximate the nonlinear Muskingum model based on general trapezoid formulas. The accuracy of these schemes is second order, if θ≠1/3, but interestingly when θ=1/3, the accuracy of the presented scheme gets improved to third order. Then, the present schemes are transformed into an unconstrained optimization problem which can be solved by a hybrid invasive weed optimization (HIWO algorithm. Finally, a numerical example is provided to illustrate the effectiveness of the present methods. The numerical results substantiate the fact that the presented methods have better precision in estimating the parameters of nonlinear Muskingum models.
Hybrid Multi-Physics Modeling of an Ultra-Fast Electro-Mechanical Actuator
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Ara Bissal
2015-12-01
Full Text Available The challenges of an HVDC breaker are to generate impulsive forces in the order of hundreds of kilonewtons within fractions of a millisecond, to withstand the arising internal mechanical stresses and to transmit these forces via an electrically-insulating device to the contact system with minimum time delay. In this work, several models were developed with different levels of complexity, computation time and accuracy. Experiments were done with two mushroom-shaped armatures to validate the developed simulation models. It was concluded that although the electromagnetic force generation mechanism is highly sensitive to the mechanical response of the system, the developed first order hybrid model is able to predict the performance of the breaker with good accuracy.
Coupled Hybrid Continuum-Discrete Model of Tumor Angiogenesis and Growth.
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Jie Lyu
Full Text Available The processes governing tumor growth and angiogenesis are codependent. To study the relationship between them, we proposed a coupled hybrid continuum-discrete model. In this model, tumor cells, their microenvironment (extracellular matrixes, matrix-degrading enzymes, and tumor angiogenic factors, and their network of blood vessels, described by a series of discrete points, were considered. The results of numerical simulation reveal the process of tumor growth and the change in microenvironment from avascular to vascular stage, indicating that the network of blood vessels develops gradually as the tumor grows. Our findings also reveal that a tumor is divided into three regions: necrotic, semi-necrotic, and well-vascularized. The results agree well with the previous relevant studies and physiological facts, and this model represents a platform for further investigations of tumor therapy.
Number of Clusters and the Quality of Hybrid Predictive Models in Analytical CRM
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Łapczyński Mariusz
2014-08-01
Full Text Available Making more accurate marketing decisions by managers requires building effective predictive models. Typically, these models specify the probability of customer belonging to a particular category, group or segment. The analytical CRM categories refer to customers interested in starting cooperation with the company (acquisition models, customers who purchase additional products (cross- and up-sell models or customers intending to resign from the cooperation (churn models. During building predictive models researchers use analytical tools from various disciplines with an emphasis on their best performance. This article attempts to build a hybrid predictive model combining decision trees (C&RT algorithm and cluster analysis (k-means. During experiments five different cluster validity indices and eight datasets were used. The performance of models was evaluated by using popular measures such as: accuracy, precision, recall, G-mean, F-measure and lift in the first and in the second decile. The authors tried to find a connection between the number of clusters and models' quality.
Wu, Xingfu
2011-08-01
In this paper, we present a performance modeling framework based on memory bandwidth contention time and a parameterized communication model to predict the performance of OpenMP, MPI and hybrid applications with weak scaling on three large-scale multicore clusters: IBM POWER4, POWER5+ and Blue Gene/P, and analyze the performance of these MPI, OpenMP and hybrid applications. We use STREAM memory benchmarks to provide initial performance analysis and model validation of MPI and OpenMP applications on these multicore clusters because the measured sustained memory bandwidth can provide insight into the memory bandwidth that a system should sustain on scientific applications with the same amount of workload per core. In addition to using these benchmarks, we also use a weak-scaling hybrid MPI/OpenMP large-scale scientific application: Gyro kinetic Toroidal Code in magnetic fusion to validate our performance model of the hybrid application on these multicore clusters. The validation results for our performance modeling method show less than 7.77% error rate in predicting the performance of hybrid MPI/OpenMP GTC on up to 512 cores on these multicore clusters. © 2011 IEEE.
"Antelope": a hybrid-logic model checker for branching-time Boolean GRN analysis
Directory of Open Access Journals (Sweden)
Arellano Gustavo
2011-12-01
model checkers (e.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.
A hybrid multi-compartment model of granuloma formation and T cell priming in Tuberculosis
Marino, Simeone; El-Kebir, Mohammed; Kirschner, Denise
2013-01-01
Tuberculosis is a worldwide health problem with 2 billion people infected with Mycobacterium tuberculosis (Mtb, the bacteria causing TB). The hallmark of infection is the emergence of organized structures of immune cells forming primarily in the lung in response to infection. Granulomas physically contain and immunologically restrain bacteria that cannot be cleared. We have developed several models that spatially characterize the dynamics of the host–mycobacterial interaction, and identified mechanisms that control granuloma formation and development. In particular, we published several agent-based models (ABMs) of granuloma formation in TB that include many subtypes of T cell populations, macrophages as well as key cytokine and chemokine effector molecules. These ABM studies emphasize the important role of T-cell related mechanisms in infection progression, such as magnitude and timing of T cell recruitment, and macrophage activation. In these models, the priming and recruitment of T cells from the lung draining lymph node (LN) was captured phenomenologically. In addition to these ABM studies, we have also developed several multi-organ models using ODEs to examine trafficking of cells between, for example, the lung and LN. While we can predict temporal dynamic behaviors, those models are not coupled to the spatial aspects of granuloma. To this end, we have developed a multi-organ model that is hybrid: an ABM for the lung compartment and a non-linear system of ODE representing the lymph node compartment. This hybrid multi-organ approach to study TB granuloma formation in the lung and immune priming in the LN allows us to dissect protective mechanisms that cannot be achieved using the single compartment or multi-compartment ODE system. The main finding of this work is that trafficking of important cells known as antigen presenting cells from the lung to the lymph node is a key control mechanism for protective immunity: the entire spectrum of infection outcomes can
Energy Technology Data Exchange (ETDEWEB)
Bonoli, P.T. [Plasma Science and Fusion Center (PSFC), MIT, Cambridge, MA (United States); Barbato, E. [ENEA, Frascati (Italy). Centro Ricerche Energia; Harvey, R.W. [CompX, Del Mar, California (United States); Imbeaux, F. [Association Euratom-CEA Cadarache, 13 - Saint-Paul-lez-Durance (France). Dept. de Recherches sur la Fusion Controlee
2003-07-01
This paper reviews the status of lower hybrid current drive (LHCD) simulation and modeling. We first discuss modules used for wave propagation, absorption, and current drive with particular emphasis placed on comparing exact numerical solutions of the Fokker Planck equation in 2-dimension with solution methods that employ 1-dimensional and adjoint approaches. We also survey model predictions for LHCD in past and present experiments showing detailed comparisons between simulated and observed current drive efficiencies and hard X-ray profiles. Finally we discuss several model predictions for lower hybrid current profile control in proposed next step reactor options. (authors)
DEFF Research Database (Denmark)
Pinto, Cláudio; Barreras, Jorge V.; de Castro, Ricardo
2017-01-01
This paper presents a study of the combined influence of battery models and sizing strategy for hybrid and battery-based electric vehicles. In particular, the aim is to find the number of battery (and supercapacitor) cells to propel a light vehicle to run two different standard driving cycles....... Despite the same tendency, when a hybrid vehicle is taken into account, the influence of the battery models is dependent on the sizing strategy. In this work, two sizing strategies are evaluated: dynamic programming and filter-based. For the latter, the complexity of the battery model has a clear...
Optimal Power Flow Modelling and Analysis of Hybrid AC-DC Grids with Offshore Wind Power Plant
DEFF Research Database (Denmark)
Dhua, Debasish; Huang, Shaojun; Wu, Qiuwei
2017-01-01
, it is essential to develop a suitable model and apply optimization algorithms for different application scenarios. The objective of this work is to develop a generalized model and evaluate the Optimal Power Flow (OPF) solutions in a hybrid AC/DC system including HVDC (LCC based) and offshore WPP (VSC based......, the wind power production level also plays a major role in a hybrid system on transmission loss evaluation. The developed model is tested in Low, Medium and High wind power production levels to determine the objective function of the OPF solution. MATLAB Optimization Toolbox and MATLAB script are used...
Role of the lower hybrid spectrum in the current drive modeling for DEMO scenarios
Cardinali, A.; Castaldo, C.; Cesario, R.; Santini, F.; Amicucci, L.; Ceccuzzi, S.; Galli, A.; Mirizzi, F.; Napoli, F.; Panaccione, L.; Schettini, G.; Tuccillo, A. A.
2017-07-01
The active control of the radial current density profile is one of the major issues of thermonuclear fusion energy research based on magnetic confinement. The lower hybrid current drive could in principle be used as an efficient tool. However, previous understanding considered the electron temperature envisaged in a reactor at the plasma periphery too large to allow penetration of the coupled radio frequency (RF) power due to strong Landau damping. In this work, we present new numerical results based on quasilinear theory, showing that the injection of power spectra with different {n}// widths of the main lobe produce an RF-driven current density profile spanning most of the outer radial half of the plasma ({n}// is the refractive index in a parallel direction to the confinement magnetic field). Plasma kinetic profiles envisaged for the DEMO reactor are used as references. We demonstrate the robustness of the modeling results concerning the key role of the spectral width in determining the lower hybrid-driven current density profile. Scans of plasma parameters are extensively carried out with the aim of excluding the possibility that any artefact of the utilised numerical modeling would produce any novelty. We neglect here the parasitic effect of spectral broadening produced by linear scattering due to plasma density fluctuations, which mainly occurs for low magnetic field devices. This effect will be analyzed in other work that completes the report on the present breakthrough.
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.
Modeling, simulation, and concept studies of a fuel cell hybrid electric vehicle powertrain
Energy Technology Data Exchange (ETDEWEB)
Oezbek, Markus
2010-03-29
This thesis focuses on the development of a fuel cell-based hybrid electric powertrain for smaller (2 kW) hybrid electric vehicles (HEVs). A Hardware-in-the-Loop test rig is designed and built with the possibility to simulate any load profile for HEVs in a realistic environment, whereby the environment is modeled. Detailed simulation models of the test rig are developed and validated to real physical components and control algorithms are designed for the DC/DC-converters and the fuel cell system. A state-feedback controller is developed for the DC/DC-converters where the state-space averaging method is used for the development. For the fuel cells, a gain-scheduling controller based on state feedback is developed and compared to two conventional methods. The design process of an HEV with regard to a given load profile is introduced with comparison between SuperCaps and batteries. The HEV is also evaluated with an introduction to different power management concepts with regard to fuel consumption, dynamics, and fuel cell deterioration rate. The power management methods are implemented in the test rig and compared. (orig.)
2-D Hybrid Model to Study Flow Curvature Effect on Low Frequency Plasma Turbulence
Sen, S.; Lin, D.; Scales, W.; Goldstein, M.
2017-10-01
In this study of flow curvature effects, a two-dimensional hybrid model is used to simulate the Kelvin-Helmholtz instability (KHI). The hybrid model treats the ions as particles, and electrons as massless fluid. Pressure and resistivity are assumed as isotropic. A classical configuration for the study of KHI is investigated, i.e. transverse shear flow to uniform background magnetic field. This is thought as the most unstable situation in magnetohydrodynamic (MHD) theory. There are 50 super particles per cell in the current simulations, which number could be increased to as much as 200 in the future. The boundary is periodic along the flow direction and reflective in the perpendicular direction. The code was originally developed by the Los Alamos National Laboratory and has been successfully applied to the study of Kelvin-Helmholtz instability on the Earth's magnetopause. In this study, the code has been running on the Advanced Research Computing (ARC) platforms of Virginia Tech. Four distinct shear profiles are simulated to investigate the effects of flow curvature on the growth of the KH instability: uniform flow, linear shear without curvature, quadratic profile with positive curvature, and quadratic profile with negative curvature. This work is supported by the DOE Grant DE-SC0016397.
Modeling plasma-assisted growth of graphene-carbon nanotube hybrid
Energy Technology Data Exchange (ETDEWEB)
Tewari, Aarti [Department of Applied Physics, Delhi Technological University, Shahbad Daulatpur, Bawana Road, Delhi 110 042 (India)
2016-08-15
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.
Application of a hybrid association rules/decision tree model for drought monitoring
Nourani, Vahid; Molajou, Amir
2017-12-01
The previous researches have shown that the incorporation of the oceanic-atmospheric climate phenomena such as Sea Surface Temperature (SST) into hydro-climatic models could provide important predictive information about hydro-climatic variability. In this paper, the hybrid application of two data mining techniques (decision tree and association rules) was offered to discover affiliation between drought of Tabriz and Kermanshah synoptic stations (located in Iran) and de-trend SSTs of the Black, Mediterranean and Red Seas. Two major steps of the proposed model were the classification of de-trend SST data and selecting the most effective groups and extracting hidden information involved in the data. The techniques of decision tree which can identify the good traits from a data set for the classification purpose were used for classification and selecting the most effective groups and association rules were employed to extract the hidden predictive information from the large observed data. To examine the accuracy of the rules, confidence and Heidke Skill Score (HSS) measures were calculated and compared for different considering lag times. The computed measures confirm reliable performance of the proposed hybrid data mining method to forecast drought and the results show a relative correlation between the Mediterranean, Black and Red Sea de-trend SSTs and drought of Tabriz and Kermanshah synoptic stations so that the confidence between the monthly Standardized Precipitation Index (SPI) values and the de-trend SST of seas is higher than 70 and 80% respectively for Tabriz and Kermanshah synoptic stations.
Slow electron energy balance for hybrid models of direct-current glow discharges
Eliseev, S. I.; Bogdanov, E. A.; Kudryavtsev, A. A.
2017-09-01
In this paper, we present the formulation of slow electron energy balance for hybrid models of direct current (DC) glow discharge. Electrons originating from non-local ionization (secondary) contribute significantly to the energy balance of slow electrons. An approach towards calculating effective energy brought by a secondary electron to the group of slow electrons by means of Coulomb collisions is suggested. The value of effective energy shows a considerable dependence on external parameters of a discharge, such as gas pressure, type, and geometric parameters. The slow electron energy balance was implemented into a simple hybrid model that uses analytical formulation for the description of non-local ionization by fast electrons. Simulations of short (without positive column) DC glow discharge in argon are carried out for a range of gas pressures. Comparison with experimental data showed generally good agreement in terms of current-voltage characteristics, electron density, and electron temperature. Simulations also capture the trend of increasing electron density with decreasing pressure observed in the experiment. Analysis shows that for considered conditions, the product of maximum electron density ne and electron temperature Te in negative glow is independent of gas pressure and depends on the gas type, cathode material, and discharge current. Decreasing gas pressure reduces the heating rate of slow electrons during Coulomb collisions with secondary electrons, which leads to lower values of Te and, in turn, higher maximum ne.
A Hybrid Semi-Supervised Anomaly Detection Model for High-Dimensional Data
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Hongchao Song
2017-01-01
Full Text Available Anomaly detection, which aims to identify observations that deviate from a nominal sample, is a challenging task for high-dimensional data. Traditional distance-based anomaly detection methods compute the neighborhood distance between each observation and suffer from the curse of dimensionality in high-dimensional space; for example, the distances between any pair of samples are similar and each sample may perform like an outlier. In this paper, we propose a hybrid semi-supervised anomaly detection model for high-dimensional data that consists of two parts: a deep autoencoder (DAE and an ensemble k-nearest neighbor graphs- (K-NNG- based anomaly detector. Benefiting from the ability of nonlinear mapping, the DAE is first trained to learn the intrinsic features of a high-dimensional dataset to represent the high-dimensional data in a more compact subspace. Several nonparametric KNN-based anomaly detectors are then built from different subsets that are randomly sampled from the whole dataset. The final prediction is made by all the anomaly detectors. The performance of the proposed method is evaluated on several real-life datasets, and the results confirm that the proposed hybrid model improves the detection accuracy and reduces the computational complexity.
A Hybrid Semi-Supervised Anomaly Detection Model for High-Dimensional Data.
Song, Hongchao; Jiang, Zhuqing; Men, Aidong; Yang, Bo
2017-01-01
Anomaly detection, which aims to identify observations that deviate from a nominal sample, is a challenging task for high-dimensional data. Traditional distance-based anomaly detection methods compute the neighborhood distance between each observation and suffer from the curse of dimensionality in high-dimensional space; for example, the distances between any pair of samples are similar and each sample may perform like an outlier. In this paper, we propose a hybrid semi-supervised anomaly detection model for high-dimensional data that consists of two parts: a deep autoencoder (DAE) and an ensemble k-nearest neighbor graphs- (K-NNG-) based anomaly detector. Benefiting from the ability of nonlinear mapping, the DAE is first trained to learn the intrinsic features of a high-dimensional dataset to represent the high-dimensional data in a more compact subspace. Several nonparametric KNN-based anomaly detectors are then built from different subsets that are randomly sampled from the whole dataset. The final prediction is made by all the anomaly detectors. The performance of the proposed method is evaluated on several real-life datasets, and the results confirm that the proposed hybrid model improves the detection accuracy and reduces the computational complexity.
Modeling and Control of Fluid Flow Networks with Application to a Nuclear-Solar Hybrid Plant
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Zhe Dong
2017-11-01
Full Text Available Fluid flow networks (FFNs can be utilized to integrate multiple once-through heat supply system (OTHSS modules based on either the same or different energy resources such as the renewable, nuclear and fossil for multi-modular and hybrid energy systems. Modeling and control is very important for the safe, stable and efficient operation of the FFNs, whose objective is to maintain both the flowrates and pressure-drops of the network branches within specific bounds. In this paper, a differential-algebraic nonlinear dynamic model for general FFNs with multiple pump branches is proposed based on both the branch hydraulics and network graph properties. Then, an adaptive decentralized FFN flowrate-pressure control law, which takes a proportional-integral (PI form with saturation on the integral terms, is established. This newly-built control not only guarantees satisfactory closed-loop global stability but also has no need for the values of network hydraulic parameters. This adaptive control is then applied to the flowrate-pressure regulation of the secondary FFN of a two-modular nuclear-solar hybrid energy system and numerical simulation results show the feasibility and high performance of this network control strategy. Due to its concise form, this new flowrate-pressure FFN controller can be easily implemented practically.
Petsev, Nikolai D.; Leal, L. Gary; Shell, M. Scott
2017-12-01
Hybrid molecular-continuum simulation techniques afford a number of advantages for problems in the rapidly burgeoning area of nanoscale engineering and technology, though they are typically quite complex to implement and limited to single-component fluid systems. We describe an approach for modeling multicomponent hydrodynamic problems spanning multiple length scales when using particle-based descriptions for both the finely resolved (e.g., molecular dynamics) and coarse-grained (e.g., continuum) subregions within an overall simulation domain. This technique is based on the multiscale methodology previously developed for mesoscale binary fluids [N. D. Petsev, L. G. Leal, and M. S. Shell, J. Chem. Phys. 144, 084115 (2016)], simulated using a particle-based continuum method known as smoothed dissipative particle dynamics. An important application of this approach is the ability to perform coupled molecular dynamics (MD) and continuum modeling of molecularly miscible binary mixtures. In order to validate this technique, we investigate multicomponent hybrid MD-continuum simulations at equilibrium, as well as non-equilibrium cases featuring concentration gradients.
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 hybrid cellular automaton model of solid tumor growth and bioreductive drug transport.
Kazmi, Nabila; Hossain, M A; Phillips, Roger M
2012-01-01
Bioreductive drugs are a class of hypoxia selective drugs that are designed to eradicate the hypoxic fraction of solid tumors. Their activity depends upon a number of biological and pharmacological factors and we used a mathematical modeling approach to explore the dynamics of tumor growth, infusion, and penetration of the bioreductive drug Tirapazamine (TPZ). An in-silico model is implemented to calculate the tumor mass considering oxygen and glucose as key microenvironmental parameters. The next stage of the model integrated extra cellular matrix (ECM), cell-cell adhesion, and cell movement parameters as growth constraints. The tumor microenvironments strongly influenced tumor morphology and growth rates. Once the growth model was established, a hybrid model was developed to study drug dynamics inside the hypoxic regions of tumors. The model used 10, 50 and 100 \\mu {\\rm M} as TPZ initial concentrations and determined TPZ pharmacokinetic (PK) (transport) and pharmacodynamics (cytotoxicity) properties inside hypoxic regions of solid tumor. The model results showed that diminished drug transport is a reason for TPZ failure and recommend the optimization of the drug transport properties in the emerging TPZ generations. The modeling approach used in this study is novel and can be a step to explore the behavioral dynamics of TPZ.
Directory of Open Access Journals (Sweden)
Dezhi Zhang
2015-01-01
Full Text Available This paper presents an optimization decision model for a production system that comprises the hybrid make-to-stock/assemble-to-order (MTS/ATO organization mode with demand uncertainty, which can be described as a two-stage decision model. In the first decision stage (i.e., before acquiring the actual demand information of the customer, we have studied the optimal quantities of the finished products and components, while in the second stage (i.e., after acquiring the actual demand information of the customer, we have made the optimal decision on the assignment of components to satisfy the remaining demand. The optimal conditions on production and inventory decision are deduced, as well as the bounds of the total procurement quantity of the components in the ATO phase and final products generated in the MTS phase. Finally, an example is given to illustrate the above optimal model. The findings are shown as follows: the hybrid MTS and ATO production system reduces uncertain demand risk by arranging MTS phase and ATO phase reasonably and improves the expected profit of manufacturer; applying the strategy of component commonality can reduce the total inventory level, as well as the risk induced by the lower accurate demand forecasting.
Dunn, Barbara; Paulish, Terry; Stanbery, Alison; Piotrowski, Jeff; Koniges, Gregory; Kroll, Evgueny; Louis, Edward J.; Liti, Gianni; Sherlock, Gavin; Rosenzweig, Frank
2013-01-01
Genome rearrangements are associated with eukaryotic evolutionary processes ranging from tumorigenesis to speciation. Rearrangements are especially common following interspecific hybridization, and some of these could be expected to have strong selective value. To test this expectation we created de novo interspecific yeast hybrids between two diverged but largely syntenic Saccharomyces species, S. cerevisiae and S. uvarum, then experimentally evolved them under continuous ammonium limitation. We discovered that a characteristic interspecific genome rearrangement arose multiple times in independently evolved populations. We uncovered nine different breakpoints, all occurring in a narrow ∼1-kb region of chromosome 14, and all producing an “interspecific fusion junction” within the MEP2 gene coding sequence, such that the 5′ portion derives from S. cerevisiae and the 3′ portion derives from S. uvarum. In most cases the rearrangements altered both chromosomes, resulting in what can be considered to be an introgression of a several-kb region of S. uvarum into an otherwise intact S. cerevisiae chromosome 14, while the homeologous S. uvarum chromosome 14 experienced an interspecific reciprocal translocation at the same breakpoint within MEP2, yielding a chimaeric chromosome; these events result in the presence in the cell of two MEP2 fusion genes having identical breakpoints. Given that MEP2 encodes for a high-affinity ammonium permease, that MEP2 fusion genes arise repeatedly under ammonium-limitation, and that three independent evolved isolates carrying MEP2 fusion genes are each more fit than their common ancestor, the novel MEP2 fusion genes are very likely adaptive under ammonium limitation. Our results suggest that, when homoploid hybrids form, the admixture of two genomes enables swift and otherwise unavailable evolutionary innovations. Furthermore, the architecture of the MEP2 rearrangement suggests a model for rapid introgression, a phenomenon seen in
Directory of Open Access Journals (Sweden)
Barbara Dunn
2013-03-01
Full Text Available Genome rearrangements are associated with eukaryotic evolutionary processes ranging from tumorigenesis to speciation. Rearrangements are especially common following interspecific hybridization, and some of these could be expected to have strong selective value. To test this expectation we created de novo interspecific yeast hybrids between two diverged but largely syntenic Saccharomyces species, S. cerevisiae and S. uvarum, then experimentally evolved them under continuous ammonium limitation. We discovered that a characteristic interspecific genome rearrangement arose multiple times in independently evolved populations. We uncovered nine different breakpoints, all occurring in a narrow ~1-kb region of chromosome 14, and all producing an "interspecific fusion junction" within the MEP2 gene coding sequence, such that the 5' portion derives from S. cerevisiae and the 3' portion derives from S. uvarum. In most cases the rearrangements altered both chromosomes, resulting in what can be considered to be an introgression of a several-kb region of S. uvarum into an otherwise intact S. cerevisiae chromosome 14, while the homeologous S. uvarum chromosome 14 experienced an interspecific reciprocal translocation at the same breakpoint within MEP2, yielding a chimaeric chromosome; these events result in the presence in the cell of two MEP2 fusion genes having identical breakpoints. Given that MEP2 encodes for a high-affinity ammonium permease, that MEP2 fusion genes arise repeatedly under ammonium-limitation, and that three independent evolved isolates carrying MEP2 fusion genes are each more fit than their common ancestor, the novel MEP2 fusion genes are very likely adaptive under ammonium limitation. Our results suggest that, when homoploid hybrids form, the admixture of two genomes enables swift and otherwise unavailable evolutionary innovations. Furthermore, the architecture of the MEP2 rearrangement suggests a model for rapid introgression, a
DEFF Research Database (Denmark)
Solberg, Brian; Andersen, Palle; Maciejowski, Jan
2008-01-01
This paper discusses the application of hybrid model predictive control to control switching between different burner modes in a novel compact marine boiler design. A further purpose of the present work is to point out problems with finite horizon model predictive control applied to systems for w...
Scriven, P. N.; Bossuyt, P. M. M.
2010-01-01
The aim of this study was to develop and use theoretical models to investigate the accuracy of the fluorescence in situ hybridization (FISH) technique in testing a single nucleus from a preimplantation embryo without the complicating effect of mosaicism. Mathematical models were constructed for
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.
Directory of Open Access Journals (Sweden)
Hahnbeom Park
Full Text Available 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.
Hybrid 2D-3D modelling of GTA welding with filler wire addition
Traidia, Abderrazak
2012-07-01
A hybrid 2D-3D model for the numerical simulation of Gas Tungsten Arc welding is proposed in this paper. It offers the possibility to predict the temperature field as well as the shape of the solidified weld joint for different operating parameters, with relatively good accuracy and reasonable computational cost. Also, an original approach to simulate the effect of immersing a cold filler wire in the weld pool is presented. The simulation results reveal two important observations. First, the weld pool depth is locally decreased in the presence of filler metal, which is due to the energy absorption by the cold feeding wire from the hot molten pool. In addition, the weld shape, maximum temperature and thermal cycles in the workpiece are relatively well predicted even when a 2D model for the arc plasma region is used. © 2012 Elsevier Ltd. All rights reserved.
ANALISIS DESAIN PICKUP PIEZOELEKTRIK DARI MODEL HYBRID SOLAR CELL-PIEZOELECTRIC UNTUK DAYA RENDAH
Directory of Open Access Journals (Sweden)
Ery Diniardi
2017-06-01
Full Text Available Indonesia merupakan negera yang memiliki sumber energi baru dan terbarukan yang belum dikembangkan secara optimal dan besar-besaran digali dan digunakan, terutama energy sel surya dan energi air hujan. Kelebihan dari iklim tropis, yaitu hujan dan panas, sudah seharusnya dikembangkan secara masif dan secara diversifikasi energy. Bukan hanya energy fosil yang digunakan, tetapi energy yang ada disekitar kita. Salah satunya energy air hujan dengan menggunakan Piezolektrik. Bahan piezoelektrik yang mampu mengubah energi mekanik menjadi energi listrik menjadi sumber utama pembahasan dalam penelitian ini. Banyaknya energi yang dihasilkan dari benturan air hujan dapat dihitung menggunakan model mekanik-elektrik. Besarnya energi yang bisa dihasilkan bergantung secara langsung kepada ukuran membran piezoelektrik, ukuran titik air hujan dan frekuensinya. Dan juga sel surya yang digunakan sebagai penghasil listrik. Apabila kedua energy ini digabungkan seperti apakah hasilnya. Dalam penelitian ini akan dikaji mengenai analisis desain pickup Piezoelektrik dari model hybrid pembangkit listrik ini.
Hybrid Fluid/Kinetic Modeling Of Magnetized High Energy Density Plasmas
Hansen, David; Held, Eric; King, Jacob; Stoltz, Peter; Masti, Robert; Srinivasan, Bhuvana
2017-10-01
MHD modeling with an equation of state (EOS) of the Rayleigh-Taylor (RT) instabily in Z indicates that it is seeded by the electro-thermal instability. Large thermodynamic drives associated with gradients at the interface between the liner and the coronal regions distort distribution functions and likely lead to non-local transport effects in a plasma which varies from weakly to strongly coupled. In this work, we discuss using effective potential theory along with a Chapman-Ensksog-like (CEL) formalism to develop hybrid fluid/kinetic modeling capabilities for these plasmas. Effective potential theory addresses the role of Coulomb collisions on transport across coupling regimes and the CEL approach bridges the gap between full-blow kinetic simulations and the EOS tables, which only depend locally on density and temperature. Quantitative results on the Spitzer problem across coupling coupling regimes will be presented as a first step. DOE Grant No. DE-SC0016525.
Adaptive hybrid likelihood model for visual tracking based on Gaussian particle filter
Wang, Yong; Tan, Yihua; Tian, Jinwen
2010-07-01
We present a new scheme based on multiple-cue integration for visual tracking within a Gaussian particle filter framework. The proposed method integrates the color, shape, and texture cues of an object to construct a hybrid likelihood model. During the measurement step, the likelihood model can be switched adaptively according to environmental changes, which improves the object representation to deal with the complex disturbances, such as appearance changes, partial occlusions, and significant clutter. Moreover, the confidence weights of the cues are adjusted online through the estimation using a particle filter, which ensures the tracking accuracy and reliability. Experiments are conducted on several real video sequences, and the results demonstrate that the proposed method can effectively track objects in complex scenarios. Compared with previous similar approaches through some quantitative and qualitative evaluations, the proposed method performs better in terms of tracking robustness and precision.
Local tetrahedron modeling of microelectronics using the finite-volume hybrid-grid technique
Energy Technology Data Exchange (ETDEWEB)
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.
PWR hybrid computer model for assessing the safety implications of control systems
Energy Technology Data Exchange (ETDEWEB)
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.
A hybrid of monopoly and perfect competition model for hi-tech products
Yang, P. C.; Wee, H. M.; Pai, S.; Yang, H. J.; Wee, P. K. P.
2010-11-01
For Hi-tech products, the demand rate, the component cost as well as the selling price usually decline significantly with time. In the case of perfect competition, shortages usually result in lost sales; while in a monopoly, shortages will be completely backordered. However, neither perfect competition nor monopoly exists. Therefore, there is a need to develop a replenishment model considering a hybrid of perfect competition and monopoly when the cost, price and demand are decreasing simultaneously. A numerical example and sensitivity analysis are carried out to illustrate this model. The results show that a higher decline-rate in the component cost leads to a smaller service level and a larger replenishment interval. When the component cost decline rate increases and the selling price decline rate decreases simultaneously, the replenishment interval decreases. In perfect competition it is better to have a high service level, while for the case with monopoly, keeping a low service level is better due to complete backordering.
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.
Assessing the Impact of Policy Changes in the Icelandic Cod Fishery Using a Hybrid Simulation Model
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Sigríður Sigurðardóttir
2014-01-01
Full Text Available 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.
Hoseinian, Fatemeh Sadat; Rezai, Bahram; Kowsari, Elaheh
2017-12-15
Prediction of Ni(II) removal during ion flotation is necessary for increasing the process efficiency by suitable modeling and simulation. In this regard, a new predictive model based on the hybrid neural genetic algorithm (GANN) was developed to predict the Ni(II) ion removal and water removal during the process from aqueous solutions using ion flotation. A multi-layer GANN model was trained to develop a predictive model based on the important effective variables on the Ni(II) ion flotation. The input variables of the model were pH, collector concentration, frother concentration, impeller speed and flotation time, while the removal percentage of Ni(II) ions and water during ion flotation were the outputs. The most effective input variables on Ni(II) removal and water removal were evaluated using the sensitivity analysis. The sensitivity analysis of the model shows that all input variables have a significant impact on the outputs. The results show that the proposed GANN models can be used to predict the Ni(II) removal and water removal during ion flotation. Copyright © 2017 Elsevier Ltd. All rights reserved.