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Sample records for hybrid modelling approach

  1. Hybrid approaches to physiologic modeling and prediction

    Science.gov (United States)

    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.

  2. Infectious disease modeling a hybrid system approach

    CERN Document Server

    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.

  3. A hybrid approach to empirical magnetosphere modeling

    Science.gov (United States)

    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.

  4. 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.

  5. A novel Monte Carlo approach to hybrid local volatility models

    NARCIS (Netherlands)

    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,

  6. Hybrid continuum-atomistic approach to model electrokinetics in nanofluidics.

    Science.gov (United States)

    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.

  7. 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.)

  8. Mobile phone use while driving: a hybrid modeling approach.

    Science.gov (United States)

    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.

  9. 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...

  10. Development of a hybrid modeling approach for predicting intensively managed Douglas-fir growth at multiple scales.

    Science.gov (United States)

    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...

  11. A new approach to flow simulation using hybrid models

    Science.gov (United States)

    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.

  12. Child human model development: a hybrid validation approach

    NARCIS (Netherlands)

    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

  13. 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.

  14. A Hybrid Approach for Efficient Modeling of Medium-Frequency Propagation in Coal Mines.

    Science.gov (United States)

    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.

  15. A Hybrid Approach for Efficient Modeling of Medium-Frequency Propagation in Coal Mines

    Science.gov (United States)

    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

  16. Optimal design of supply chain network under uncertainty environment using hybrid analytical and simulation modeling approach

    Science.gov (United States)

    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.

  17. 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.

  18. 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.

  19. A hybrid model for mapping simplified seismic response via a GIS-metamodel approach

    Science.gov (United States)

    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.

  20. New hybrid turbulence modelling approach, with application to dynamic stall control

    Science.gov (United States)

    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.

  1. A hybrid, coupled approach for modeling charged fluids from the nano to the mesoscale

    Science.gov (United States)

    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.

  2. 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

  3. A Hybrid Latent Class Analysis Modeling Approach to Analyze Urban Expressway Crash Risk.

    Science.gov (United States)

    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.

  4. 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.

  5. A Hybrid Analytical/Simulation Modeling Approach for Planning and Optimizing Mass Tactical Airborne Operations

    Science.gov (United States)

    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

  6. Valuation and Modeling of EQ-5D-5L Health States Using a Hybrid Approach.

    Science.gov (United States)

    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.

  7. A hybrid approach to modeling and control of vehicle height for electronically controlled air suspension

    Science.gov (United States)

    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.

  8. Formal verification of dynamic hybrid systems: a NuSMV-based model checking approach

    Directory of Open Access Journals (Sweden)

    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.

  9. Totally stapled gastrojejunal anastomosis using hybrid NOTES: single 12-mm trocar approach in a porcine model.

    Science.gov (United States)

    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.

  10. A Novel Modelling Approach for Condensing Boilers Based on Hybrid Dynamical Systems

    Directory of Open Access Journals (Sweden)

    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.

  11. Cluster dynamics modelling of materials: A new hybrid deterministic/stochastic coupling approach

    Science.gov (United States)

    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.

  12. Hybrid metaheuristic approaches to the expectation maximization for estimation of the hidden Markov model for signal modeling.

    Science.gov (United States)

    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.

  13. Personalized blood glucose prediction: A hybrid approach using grammatical evolution and physiological models.

    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.

  14. Hybrid Neural Network Approach Based Tool for the Modelling of Photovoltaic Panels

    Directory of Open Access Journals (Sweden)

    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.

  15. Modelling of Hydrothermal Unit Commitment Coordination Using Efficient Metaheuristic Algorithm: A Hybridized Approach

    Directory of Open Access Journals (Sweden)

    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.

  16. Novel approach for streamflow forecasting using a hybrid ANFIS-FFA model

    Science.gov (United States)

    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

  17. The Importance of Being Hybrid for Spatial Epidemic Models:A Multi-Scale Approach

    Directory of Open Access Journals (Sweden)

    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.

  18. A hybrid approach to monthly streamflow forecasting: Integrating hydrological model outputs into a Bayesian artificial neural network

    Science.gov (United States)

    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.

  19. Clustering hybrid regression: a novel computational approach to study and model biohydrogen production through dark fermentation.

    Science.gov (United States)

    Nikhil; Koskinen, Perttu E P; Visa, Ari; Kaksonen, Anna H; Puhakka, Jaakko A; Yli-Harja, Olli

    2008-10-01

    Clustering hybrid regression (CHR) approach was developed and evaluated using data from H(2)-producing glucose-based, suspended-cell bioreactor operated for 5 months. The aim was to describe the relationship between metabolic end products and H(2)-production rate. Self-organizing maps (SOM) were used to better visualize the dataset and to detect main metabolic patterns in bioprocess data. SOM detected three distinct metabolic patterns with butyrate, acetate and ethanol as dominant metabolites, respectively. Butyrate dominated metabolism was related to high H(2) production, while acetate and ethanol dominated metabolisms resulted in low H(2) production. CHR models performed well [mean square error (MSE) 0.55 and 0.56] in modeling the H(2)-production rate. The results validate the suitability of the CHR approach in describing the bioprocess behavior and in the modeling of H(2) production rate. The developed model can help in discovering key metabolic interactions and suitable process parameters from complex datasets, and increase the understanding of the bioprocesses occurring in engineered and natural environments.

  20. A Hybrid Generalized Hidden Markov Model-Based Condition Monitoring Approach for Rolling Bearings.

    Science.gov (United States)

    Liu, Jie; Hu, Youmin; Wu, Bo; Wang, Yan; Xie, Fengyun

    2017-05-18

    The operating condition of rolling bearings affects productivity and quality in the rotating machine process. Developing an effective rolling bearing condition monitoring approach is critical to accurately identify the operating condition. In this paper, a hybrid generalized hidden Markov model-based condition monitoring approach for rolling bearings is proposed, where interval valued features are used to efficiently recognize and classify machine states in the machine process. In the proposed method, vibration signals are decomposed into multiple modes with variational mode decomposition (VMD). Parameters of the VMD, in the form of generalized intervals, provide a concise representation for aleatory and epistemic uncertainty and improve the robustness of identification. The multi-scale permutation entropy method is applied to extract state features from the decomposed signals in different operating conditions. Traditional principal component analysis is adopted to reduce feature size and computational cost. With the extracted features' information, the generalized hidden Markov model, based on generalized interval probability, is used to recognize and classify the fault types and fault severity levels. Finally, the experiment results show that the proposed method is effective at recognizing and classifying the fault types and fault severity levels of rolling bearings. This monitoring method is also efficient enough to quantify the two uncertainty components.

  1. A hybrid deterministic-probabilistic approach to model the mechanical response of helically arranged hierarchical strands

    Science.gov (United States)

    Fraldi, M.; Perrella, G.; Ciervo, M.; Bosia, F.; Pugno, N. M.

    2017-09-01

    Very recently, a Weibull-based probabilistic strategy has been successfully applied to bundles of wires to determine their overall stress-strain behaviour, also capturing previously unpredicted nonlinear and post-elastic features of hierarchical strands. This approach is based on the so-called ;Equal Load Sharing (ELS); hypothesis by virtue of which, when a wire breaks, the load acting on the strand is homogeneously redistributed among the surviving wires. Despite the overall effectiveness of the method, some discrepancies between theoretical predictions and in silico Finite Element-based simulations or experimental findings might arise when more complex structures are analysed, e.g. helically arranged bundles. To overcome these limitations, an enhanced hybrid approach is proposed in which the probability of rupture is combined with a deterministic mechanical model of a strand constituted by helically-arranged and hierarchically-organized wires. The analytical model is validated comparing its predictions with both Finite Element simulations and experimental tests. The results show that generalized stress-strain responses - incorporating tension/torsion coupling - are naturally found and, once one or more elements break, the competition between geometry and mechanics of the strand microstructure, i.e. the different cross sections and helical angles of the wires in the different hierarchical levels of the strand, determines the no longer homogeneous stress redistribution among the surviving wires whose fate is hence governed by a ;Hierarchical Load Sharing; criterion.

  2. Analyzing Economic Effects with Energy Mix Changes: A Hybrid CGE Model Approach

    Directory of Open Access Journals (Sweden)

    Taesik Yun

    2016-10-01

    Full Text Available We evaluate the micro and macro-economic effects with the hybrid mixed complementary approach we design to take account of these unique features of the Korean electricity industry. The features we consider are not only the electricity itself but also the Korean electricity market mechanism. Unlike typical commodities, the electricity has unique features. As well known, the electricity supply is not easy to meet an instant hike of rump sum demand of electricity in a smooth and timely manner, since the quantity of power generating is fixed at specific time with the limited capacities. On top of that, we add the Korean electricity market mechanism that the selling price through the Korea Power Exchange (KPX is unitary, although the marginal production cost of each generating technology. From the modeling point of view, we segment the Korean electricity industry into nine generating technologies such as six conventional and three renewable technologies. In addition, we construct the specifically defined 40-by-40 SAM table to include electricity generating sectors by different resources. With these assumptions, four scenarios for policy simulation are designed according to the supply share reduction of the nuclear power generation. The research result shows micro and macro-economic indices are negatively impacted especially in cases that the share of nuclear power is lower than that of basis case.

  3. A hybrid classical-quantum approach for ultra-scaled confined nanostructures : modeling and simulation*

    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.

  4. Very-short-term wind power prediction by a hybrid model with single- and multi-step approaches

    Science.gov (United States)

    Mohammed, E.; Wang, S.; Yu, J.

    2017-05-01

    Very-short-term wind power prediction (VSTWPP) has played an essential role for the operation of electric power systems. This paper aims at improving and applying a hybrid method of VSTWPP based on historical data. The hybrid method is combined by multiple linear regressions and least square (MLR&LS), which is intended for reducing prediction errors. The predicted values are obtained through two sub-processes:1) transform the time-series data of actual wind power into the power ratio, and then predict the power ratio;2) use the predicted power ratio to predict the wind power. Besides, the proposed method can include two prediction approaches: single-step prediction (SSP) and multi-step prediction (MSP). WPP is tested comparatively by auto-regressive moving average (ARMA) model from the predicted values and errors. The validity of the proposed hybrid method is confirmed in terms of error analysis by using probability density function (PDF), mean absolute percent error (MAPE) and means square error (MSE). Meanwhile, comparison of the correlation coefficients between the actual values and the predicted values for different prediction times and window has confirmed that MSP approach by using the hybrid model is the most accurate while comparing to SSP approach and ARMA. The MLR&LS is accurate and promising for solving problems in WPP.

  5. 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...

  6. Modeling level change in Lake Urmia using hybrid artificial intelligence approaches

    Science.gov (United States)

    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.

  7. Modeling and Optimizing Energy Utilization of Steel Production Process: A Hybrid Petri Net Approach

    Directory of Open Access Journals (Sweden)

    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.

  8. Hybrid spiking models.

    Science.gov (United States)

    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.

  9. A hybrid-dimensional approach for an efficient numerical modeling of the hydro-mechanics of fractures

    Science.gov (United States)

    Vinci, C.; Renner, J.; Steeb, H.

    2014-02-01

    Characterization of subsurface fluid flow requires accounting for hydro-mechanical coupling between fluid-pressure variations and rock deformation. Particularly, flow of a compressible fluid along compliant hydraulic conduits, such as joints, fractures, or faults, is strongly affected by the associated deformation of the surrounding rock. We investigated and compared two alternative numerical modeling approaches that describe the transient fluid-pressure distribution along a single deformable fracture embedded in a rock matrix. First, we analyzed the coupled hydro-mechanical problem within the framework of Biot's poroelastic equations. Second, in a hybrid-dimensional approach, deformation characteristics of the surrounding rock were combined with a one-dimensional approximation of the fluid-flow problem to account for the high aspect ratios of fractures and the associated numerical problems. A dimensional analysis of the governing equations reveals that the occurring physical phenomena strongly depend on the geometry of the hydraulic conduit and on the boundary conditions. For the analyzed geometries, hydro-mechanical coupling effects dominate and convection effects can be neglected. Numerical solutions for coupled hydro-mechanical phenomena were obtained and compared to field data to characterize the fractured rock in the vicinity of an injection borehole. Either approach captures convection, diffusion, and hydro-mechanical effects, yet the hybrid-dimensional approach is advantageous due to its applicability to problems involving high-aspect-ratio features. For such cases, the modeling of pumping tests by means of the hybrid-dimensional approach showed that the observed inverse-pressure responses are the result of the coupling between the fluid flow in the fracture and the rock deformation caused by fluid-pressure variations along the fracture. Storage capacity as a single parameter of a fracture is insufficient to address all aspects of the coupling.

  10. 2D hybrid analysis: Approach for building three-dimensional atomic model by electron microscopy image matching.

    Science.gov (United States)

    Matsumoto, Atsushi; Miyazaki, Naoyuki; Takagi, Junichi; Iwasaki, Kenji

    2017-03-23

    In this study, we develop an approach termed "2D hybrid analysis" for building atomic models by image matching from electron microscopy (EM) images of biological molecules. The key advantage is that it is applicable to flexible molecules, which are difficult to analyze by 3DEM approach. In the proposed approach, first, a lot of atomic models with different conformations are built by computer simulation. Then, simulated EM images are built from each atomic model. Finally, they are compared with the experimental EM image. Two kinds of models are used as simulated EM images: the negative stain model and the simple projection model. Although the former is more realistic, the latter is adopted to perform faster computations. The use of the negative stain model enables decomposition of the averaged EM images into multiple projection images, each of which originated from a different conformation or orientation. We apply this approach to the EM images of integrin to obtain the distribution of the conformations, from which the pathway of the conformational change of the protein is deduced.

  11. A multinomial logit model-Bayesian network hybrid approach for driver injury severity analyses in rear-end crashes.

    Science.gov (United States)

    Chen, Cong; Zhang, Guohui; Tarefder, Rafiqul; Ma, Jianming; Wei, Heng; Guan, Hongzhi

    2015-07-01

    Rear-end crash is one of the most common types of traffic crashes in the U.S. A good understanding of its characteristics and contributing factors is of practical importance. Previously, both multinomial Logit models and Bayesian network methods have been used in crash modeling and analysis, respectively, although each of them has its own application restrictions and limitations. In this study, a hybrid approach is developed to combine multinomial logit models and Bayesian network methods for comprehensively analyzing driver injury severities in rear-end crashes based on state-wide crash data collected in New Mexico from 2010 to 2011. A multinomial logit model is developed to investigate and identify significant contributing factors for rear-end crash driver injury severities classified into three categories: no injury, injury, and fatality. Then, the identified significant factors are utilized to establish a Bayesian network to explicitly formulate statistical associations between injury severity outcomes and explanatory attributes, including driver behavior, demographic features, vehicle factors, geometric and environmental characteristics, etc. The test results demonstrate that the proposed hybrid approach performs reasonably well. The Bayesian network reference analyses indicate that the factors including truck-involvement, inferior lighting conditions, windy weather conditions, the number of vehicles involved, etc. could significantly increase driver injury severities in rear-end crashes. The developed methodology and estimation results provide insights for developing effective countermeasures to reduce rear-end crash injury severities and improve traffic system safety performance. Copyright © 2015 Elsevier Ltd. All rights reserved.

  12. Hybrid approaches for multiple-species stochastic reaction–diffusion models

    Energy Technology Data Exchange (ETDEWEB)

    Spill, Fabian, E-mail: fspill@bu.edu [Department of Biomedical Engineering, Boston University, 44 Cummington Street, Boston, MA 02215 (United States); Department of Mechanical Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139 (United States); Guerrero, Pilar [Department of Mathematics, University College London, Gower Street, London WC1E 6BT (United Kingdom); Alarcon, Tomas [Centre de Recerca Matematica, Campus de Bellaterra, Edifici C, 08193 Bellaterra (Barcelona) (Spain); Departament de Matemàtiques, Universitat Atonòma de Barcelona, 08193 Bellaterra (Barcelona) (Spain); Maini, Philip K. [Wolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Oxford OX2 6GG (United Kingdom); Byrne, Helen [Wolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Oxford OX2 6GG (United Kingdom); Computational Biology Group, Department of Computer Science, University of Oxford, Oxford OX1 3QD (United Kingdom)

    2015-10-15

    Reaction–diffusion models are used to describe systems in fields as diverse as physics, chemistry, ecology and biology. The fundamental quantities in such models are individual entities such as atoms and molecules, bacteria, cells or animals, which move and/or react in a stochastic manner. If the number of entities is large, accounting for each individual is inefficient, and often partial differential equation (PDE) models are used in which the stochastic behaviour of individuals is replaced by a description of the averaged, or mean behaviour of the system. In some situations the number of individuals is large in certain regions and small in others. In such cases, a stochastic model may be inefficient in one region, and a PDE model inaccurate in another. To overcome this problem, we develop a scheme which couples a stochastic reaction–diffusion system in one part of the domain with its mean field analogue, i.e. a discretised PDE model, in the other part of the domain. The interface in between the two domains occupies exactly one lattice site and is chosen such that the mean field description is still accurate there. In this way errors due to the flux between the domains are small. Our scheme can account for multiple dynamic interfaces separating multiple stochastic and deterministic domains, and the coupling between the domains conserves the total number of particles. The method preserves stochastic features such as extinction not observable in the mean field description, and is significantly faster to simulate on a computer than the pure stochastic model. - Highlights: • A novel hybrid stochastic/deterministic reaction–diffusion simulation method is given. • Can massively speed up stochastic simulations while preserving stochastic effects. • Can handle multiple reacting species. • Can handle moving boundaries.

  13. World Automata: a compositional approach to model implicit communication in hierarchical Hybrid Systems

    Directory of Open Access Journals (Sweden)

    Marta Capiluppi

    2013-08-01

    Full Text Available We propose an extension of Hybrid I/O Automata (HIOAs to model agent systems and their implicit communication through perturbation of the environment, like localization of objects or radio signals diffusion and detection. The new object, called World Automaton (WA, is built in such a way to preserve as much as possible of the compositional properties of HIOAs and its underlying theory. From the formal point of view we enrich classical HIOAs with a set of world variables whose values are functions both of time and space. World variables are treated similarly to local variables of HIOAs, except in parallel composition, where the perturbations produced by world variables are summed. In such way, we obtain a structure able to model both agents and environments, thus inducing a hierarchy in the model and leading to the introduction of a new operator. Indeed this operator, called inplacement, is needed to represent the possibility of an object (WA of living inside another object/environment (WA.

  14. Hybrid approach for the assessment of PSA models by means of binary decision diagrams

    Energy Technology Data Exchange (ETDEWEB)

    Ibanez-Llano, Cristina, E-mail: cristina.ibanez@iit.upcomillas.e [Instituto de Investigacion Tecnologica (IIT), Escuela Tecnica Superior de Ingenieria ICAI, Universidad Pontificia Comillas, C/Santa Cruz de Marcenado 26, 28015 Madrid (Spain); Rauzy, Antoine, E-mail: Antoine.RAUZY@3ds.co [Dassault Systemes, 10 rue Marcel Dassault CS 40501, 78946 Velizy Villacoublay Cedex (France); Melendez, Enrique, E-mail: ema@csn.e [Consejo de Seguridad Nuclear (CSN), C/Justo Dorado 11, 28040 Madrid (Spain); Nieto, Francisco, E-mail: nieto@iit.upcomillas.e [Instituto de Investigacion Tecnologica (IIT), Escuela Tecnica Superior de Ingenieria ICAI, Universidad Pontificia Comillas, C/Santa Cruz de Marcenado 26, 28015 Madrid (Spain)

    2010-10-15

    Binary decision diagrams are a well-known alternative to the minimal cutsets approach to assess the reliability Boolean models. They have been applied successfully to improve the fault trees models assessment. However, its application to solve large models, and in particular the event trees coming from the PSA studies of the nuclear industry, remains to date out of reach of an exact evaluation. For many real PSA models it may be not possible to compute the BDD within reasonable amount of time and memory without considering the truncation or simplification of the model. This paper presents a new approach to estimate the exact probabilistic quantification results (probability/frequency) based on combining the calculation of the MCS and the truncation limits, with the BDD approach, in order to have a better control on the reduction of the model and to properly account for the success branches. The added value of this methodology is that it is possible to ensure a real confidence interval of the exact value and therefore an explicit knowledge of the error bound. Moreover, it can be used to measure the acceptability of the results obtained with traditional techniques. The new method was applied to a real life PSA study and the results obtained confirm the applicability of the methodology and open a new viewpoint for further developments.

  15. Resolving the cycle skip introduced by the multi-layer static model using a hybrid approach

    Science.gov (United States)

    Tawadros, Emad Ekladios Toma

    Cycle skips (breaks) in seismic data are occasionally irresolvable using conventional static correction programs. Such artificial cycle skips can be misleading for interpreters and introduce false subsurface images. After applying datum static corrections using either the single-layer or multi-layer models, artificial cycle skips might develop in the data. Although conventional residual static correction techniques are occasionally able to solve this problem, they fail in solving many other cases. A new approach is introduced in this study to resolve this problem by forming a static model that is free of these artificial cycle skips, which can be used as a pilot volume for residual statics calculation. The pilot volume is formed by combining the high-frequency static component of the single-layer model which show better static solution at the static problem locations and the low-frequency static component of the two-layer model. This new approach is applied on a 3-D seismic data set from Haba Field of Eastern Saudi Arabia where a major cycle skip was introduced by the multilayer model. Results show a better image of the subsurface structure after application of the new approach.

  16. Detection of cardiovascular anomalies: Hybrid systems approach

    KAUST Repository

    Ledezma, Fernando

    2012-06-06

    In this paper, we propose a hybrid interpretation of the cardiovascular system. Based on a model proposed by Simaan et al. (2009), we study the problem of detecting cardiovascular anomalies that can be caused by variations in some physiological parameters, using an observerbased approach. We present the first numerical results obtained. © 2012 IFAC.

  17. A Model-Driven Approach for Hybrid Power Estimation in Embedded Systems Design

    Directory of Open Access Journals (Sweden)

    Ben Atitallah Rabie

    2011-01-01

    Full Text Available Abstract As technology scales for increased circuit density and performance, the management of power consumption in system-on-chip (SoC is becoming critical. Today, having the appropriate electronic system level (ESL tools for power estimation in the design flow is mandatory. The main challenge for the design of such dedicated tools is to achieve a better tradeoff between accuracy and speed. This paper presents a consumption estimation approach allowing taking the consumption criterion into account early in the design flow during the system cosimulation. The originality of this approach is that it allows the power estimation for both white-box intellectual properties (IPs using annotated power models and black-box IPs using standalone power estimators. In order to obtain accurate power estimates, our simulations were performed at the cycle-accurate bit-accurate (CABA level, using SystemC. To make our approach fast and not tedious for users, the simulated architectures, including standalone power estimators, were generated automatically using a model driven engineering (MDE approach. Both annotated power models and standalone power estimators can be used together to estimate the consumption of the same architecture, which makes them complementary. The simulation results showed that the power estimates given by both estimation techniques for a hardware component are very close, with a difference that does not exceed 0.3%. This proves that, even when the IP code is not accessible or not modifiable, our approach allows obtaining quite accurate power estimates that early in the design flow thanks to the automation offered by the MDE approach.

  18. A Hybrid Fuzzy GJR-GARCH Modeling Approach for Stock Market Volatility Forecasting

    Directory of Open Access Journals (Sweden)

    Leandro Maciel

    2012-09-01

    Full Text Available Forecasting stock market returns volatility is a challenging task that has attracted the attention of market practitioners, regulators and academics in recent years. This paper proposes a Fuzzy GJR-GARCH model to forecast the volatility of S&P 500 and Ibovespa indexes. The model comprises both the concept of fuzzy inference systems and GJR-GARCH modeling approach in order to consider the principles of time-varying volatility, leverage effects and volatility clustering, in which changes are cataloged by similarity. Moreover, a differential evolution (DE algorithm is suggested to solve the problem of Fuzzy GJR-GARCH parameters estimation. The results indicate that the proposed method offers significant improvements in volatility forecasting performance in comparison with GARCH-type models and with a current Fuzzy-GARCH model reported in the literature. Furthermore, the DE-based algorithm aims to achieve an optimal solution with a rapid convergence rate.

  19. Model-Based Prognostics of Hybrid Systems

    Science.gov (United States)

    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.

  20. Complete Structural Model of Escherichia coli RNA Polymerase from a Hybrid Approach

    Energy Technology Data Exchange (ETDEWEB)

    Opalka, N.; Brown, J; Lane, W; Twist, K; Landick, R; Asturias, F; Darst, S

    2010-01-01

    The Escherichia coli transcription system is the best characterized from a biochemical and genetic point of view and has served as a model system. Nevertheless, a molecular understanding of the details of E. coli transcription and its regulation, and therefore its full exploitation as a model system, has been hampered by the absence of high-resolution structural information on E. coli RNA polymerase (RNAP). We use a combination of approaches, including high-resolution X-ray crystallography, ab initio structural prediction, homology modeling, and single-particle cryo-electron microscopy, to generate complete atomic models of E. coli core RNAP and an E. coli RNAP ternary elongation complex. The detailed and comprehensive structural descriptions can be used to help interpret previous biochemical and genetic data in a new light and provide a structural framework for designing experiments to understand the function of the E. coli lineage-specific insertions and their role in the E. coli transcription program. Transcription, or the synthesis of RNA from DNA, is one of the most important processes in the cell. The central enzyme of transcription is the DNA-dependent RNA polymerase (RNAP), a large, macromolecular assembly consisting of at least five subunits. Historically, much of our fundamental information on the process of transcription has come from genetic and biochemical studies of RNAP from the model bacterium Escherichia coli. More recently, major breakthroughs in our understanding of the mechanism of action of RNAP have come from high resolution crystal structures of various bacterial, archaebacterial, and eukaryotic enzymes. However, all of our high-resolution bacterial RNAP structures are of enzymes from the thermophiles Thermus aquaticus or T. thermophilus, organisms with poorly characterized transcription systems. It has thus far proven impossible to obtain a high-resolution structure of E. coli RNAP, which has made it difficult to relate the large collection

  1. Modeling and Control of Cogeneration Power Plants: A Hybrid System Approach

    NARCIS (Netherlands)

    G. Ferrari-Trecate (Giancarlo); E. Gallestey (Eduardo); P. Letizia (Paolo); M. Spedicato (Matteo); M. Morari (Manfred); M. Antoine (Marc)

    2004-01-01

    textabstractIn this paper the short term scheduling optimization of a combined cycle power plant is accomplished by exploiting hybrid systems, i.e. systems evolving according to continuous dynamics, discrete dynamics, and logic rules. Discrete features of a power plant are, for instance, the

  2. Photodegradation study of decabromodiphenyl ether by UV spectrophotometry and a hybrid hard- and soft-modelling approach.

    Science.gov (United States)

    Mas, Sílvia; de Juan, Anna; Lacorte, Sílvia; Tauler, Romà

    2008-06-16

    This work presents an exploratory study of the photochemical degradation process of decabromodiphenyl ether (decaBDE) and gives an interpretation of the kinetic pathway, species and effects of the key factors involved in the degradation process. Use of lowly brominated diphenyl ethers (PBDE) has been banned by the EU and there seems to be evidence of the photolytic degradation of highly brominated PBDEs into lowly brominated congeners. Hence, the importance of knowing the photodegradation process of decaBDE. The photodegradation was investigated under UV light by UV-spectrophotometric monitoring. A novel hybrid data analysis approach, based on the combination of hard- and soft-spectrophotometric multivariate curve resolution, was applied to elucidate the mechanism of the degradation process, to resolve kinetic profiles and pure spectra of the photodegradation products and to evaluate the rate constants. The photodegradation process could be described with a kinetic model based on three consecutive first-order reactions and a decrease of the degradation process was observed as solvent polarity increased. Complementary identification of photodegradation products by gas chromatography coupled to mass spectrometry using negative chemical ionization (GC-NCI-MS) is attempted. This work presents a novel attempt of describing in a comprehensive way the photochemical degradation process of decaBDE, with all successive steps and related rate constants. This study proves also the potential of the proposed hybrid data analysis methodology as a general strategy to interpret the evolution of these photochemical reactions.

  3. Chaotic system synchronization with an unknown master model using a hybrid HOD active control approach

    Energy Technology Data Exchange (ETDEWEB)

    Du Shengzhi [Department of EAD, ICT Faculty, Tshwane University of Technology, Pretoria 0001 (South Africa); French South Africa Technical Institute of Electronics (F' SATIE), Tshwane University of Technology, Pretoria 0001 (South Africa)], E-mail: dushengzhi@gmail.com; Wyk, Barend J. van; Qi Guoyuan; Tu Chunling [French South Africa Technical Institute of Electronics (F' SATIE), Tshwane University of Technology, Pretoria 0001 (South Africa)

    2009-11-15

    In this paper, a hybrid method using active control and a High Order Differentiator (HOD) methodology is proposed to synchronize chaotic systems. Compared to some traditional active control methods, this new method can synchronize chaotic systems where only output states of the master system are available, i.e. the system is considered a black box. The HOD is used to estimate the derivative information of the master system followed by an active control methodology relying on HOD information. The Qi hyperchaotic system is used to verify the performance of this hybrid method. The proposed method is also compared to some traditional methods. Experimental results show that the proposed method has high synchronization precision and speed and is robust against uncertainties in the master system. The circus implements of the proposed synchronizing scheme are included in this paper. The simulation results show the feasibility of the proposed scheme.

  4. Forecasting optimal solar energy supply in Jiangsu Province (China): a systematic approach using hybrid of weather and energy forecast models.

    Science.gov (United States)

    Zhao, Xiuli; Asante Antwi, Henry; Yiranbon, Ethel

    2014-01-01

    The idea of aggregating information is clearly recognizable in the daily lives of all entities whether as individuals or as a group, since time immemorial corporate organizations, governments, and individuals as economic agents aggregate information to formulate decisions. Energy planning represents an investment-decision problem where information needs to be aggregated from credible sources to predict both demand and supply of energy. To do this there are varying methods ranging from the use of portfolio theory to managing risk and maximizing portfolio performance under a variety of unpredictable economic outcomes. The future demand for energy and need to use solar energy in order to avoid future energy crisis in Jiangsu province in China require energy planners in the province to abandon their reliance on traditional, "least-cost," and stand-alone technology cost estimates and instead evaluate conventional and renewable energy supply on the basis of a hybrid of optimization models in order to ensure effective and reliable supply. Our task in this research is to propose measures towards addressing optimal solar energy forecasting by employing a systematic optimization approach based on a hybrid of weather and energy forecast models. After giving an overview of the sustainable energy issues in China, we have reviewed and classified the various models that existing studies have used to predict the influences of the weather influences and the output of solar energy production units. Further, we evaluate the performance of an exemplary ensemble model which combines the forecast output of two popular statistical prediction methods using a dynamic weighting factor.

  5. Forecasting Optimal Solar Energy Supply in Jiangsu Province (China): A Systematic Approach Using Hybrid of Weather and Energy Forecast Models

    Science.gov (United States)

    Zhao, Xiuli; Yiranbon, Ethel

    2014-01-01

    The idea of aggregating information is clearly recognizable in the daily lives of all entities whether as individuals or as a group, since time immemorial corporate organizations, governments, and individuals as economic agents aggregate information to formulate decisions. Energy planning represents an investment-decision problem where information needs to be aggregated from credible sources to predict both demand and supply of energy. To do this there are varying methods ranging from the use of portfolio theory to managing risk and maximizing portfolio performance under a variety of unpredictable economic outcomes. The future demand for energy and need to use solar energy in order to avoid future energy crisis in Jiangsu province in China require energy planners in the province to abandon their reliance on traditional, “least-cost,” and stand-alone technology cost estimates and instead evaluate conventional and renewable energy supply on the basis of a hybrid of optimization models in order to ensure effective and reliable supply. Our task in this research is to propose measures towards addressing optimal solar energy forecasting by employing a systematic optimization approach based on a hybrid of weather and energy forecast models. After giving an overview of the sustainable energy issues in China, we have reviewed and classified the various models that existing studies have used to predict the influences of the weather influences and the output of solar energy production units. Further, we evaluate the performance of an exemplary ensemble model which combines the forecast output of two popular statistical prediction methods using a dynamic weighting factor. PMID:24511292

  6. Energy based hybrid turbulence modeling

    Science.gov (United States)

    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.

  7. Hybrid plasma modeling.

    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.

  8. Modelling of blast-induced damage in tunnels using a hybrid finite-discrete numerical approach

    Directory of Open Access Journals (Sweden)

    Amichai Mitelman

    2014-12-01

    Full Text Available This paper presents the application of a hybrid finite-discrete element method to study blast-induced damage in circular tunnels. An extensive database of field tests of underground explosions above tunnels is used for calibrating and validating the proposed numerical method; the numerical results are shown to be in good agreement with published data for large-scale physical experiments. The method is then used to investigate the influence of rock strength properties on tunnel durability to withstand blast loads. The presented analysis considers blast damage in tunnels excavated through relatively weak (sandstone and strong (granite rock materials. It was found that higher rock strength will increase the tunnel resistance to the load on one hand, but decrease attenuation on the other hand. Thus, under certain conditions, results for weak and strong rock masses are similar.

  9. Travelling waves in hybrid chemotaxis models

    CERN Document Server

    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...

  10. Hybrid Quantum Mechanics/Molecular Mechanics/Coarse Grained Modeling: A Triple-Resolution Approach for Biomolecular Systems.

    Science.gov (United States)

    Sokkar, Pandian; Boulanger, Eliot; Thiel, Walter; Sanchez-Garcia, Elsa

    2015-04-14

    We present a hybrid quantum mechanics/molecular mechanics/coarse-grained (QM/MM/CG) multiresolution approach for solvated biomolecular systems. The chemically important active-site region is treated at the QM level. The biomolecular environment is described by an atomistic MM force field, and the solvent is modeled with the CG Martini force field using standard or polarizable (pol-CG) water. Interactions within the QM, MM, and CG regions, and between the QM and MM regions, are treated in the usual manner, whereas the CG-MM and CG-QM interactions are evaluated using the virtual sites approach. The accuracy and efficiency of our implementation is tested for two enzymes, chorismate mutase (CM) and p-hydroxybenzoate hydroxylase (PHBH). In CM, the QM/MM/CG potential energy scans along the reaction coordinate yield reaction energies that are too large, both for the standard and polarizable Martini CG water models, which can be attributed to adverse effects of using large CG water beads. The inclusion of an atomistic MM water layer (10 Å for uncharged CG water and 5 Å for polarizable CG water) around the QM region improves the energy profiles compared to the reference QM/MM calculations. In analogous QM/MM/CG calculations on PHBH, the use of the pol-CG description for the outer water does not affect the stabilization of the highly charged FADHOOH-pOHB transition state compared to the fully atomistic QM/MM calculations. Detailed performance analysis in a glycine-water model system indicates that computation times for QM energy and gradient evaluations at the density functional level are typically reduced by 40-70% for QM/MM/CG relative to fully atomistic QM/MM calculations.

  11. A hybrid nudging-ensemble Kalman filter approach to data assimilation. Part II: application in a shallow-water model

    Directory of Open Access Journals (Sweden)

    Lili Lei

    2012-05-01

    Full Text Available A hybrid nudging-ensemble Kalman filter (HNEnKF data assimilation approach, explored in the Lorenz three-variable system in Part I, is tested in a two-dimensional shallow-water model for dynamic analysis and numerical weather prediction. The HNEnKF effectively combines the advantages of the ensemble Kalman filter (EnKF and the observation nudging to achieve more gradual and continuous data assimilation by computing the nudging coefficients from the flow-dependent, time-varying error covariances of the EnKF. It can also transform the gain matrix of the EnKF into additional terms in the model's predictive equations to assist the data assimilation process. The HNEnKF is tested for both a wave case and a vortex case with different observation frequencies and observation networks. The HNEnKF generally produces smaller root mean square (RMS errors than either nudging or EnKF alone. It also has better temporal smoothness than the EnKF and lagged ensemble Kalman smoother (EnKS. The HNEnKF allows the gain matrix of the EnKF to be applied gradually in time, reducing the error spikes commonly found around the analysis times when using intermittent data assimilation methods. Therefore, the HNEnKF produces a seamless analysis with better inter-variable consistency and dynamic balance than the intermittent EnKF.

  12. Performance of Irikura Recipe Rupture Model Generator in Earthquake Ground Motion Simulations with Graves and Pitarka Hybrid Approach

    Science.gov (United States)

    Pitarka, Arben; Graves, Robert; Irikura, Kojiro; Miyake, Hiroe; Rodgers, Arthur

    2017-09-01

    We analyzed the performance of the Irikura and Miyake (Pure and Applied Geophysics 168(2011):85-104, 2011) (IM2011) asperity-based kinematic rupture model generator, as implemented in the hybrid broadband ground motion simulation methodology of Graves and Pitarka (Bulletin of the Seismological Society of America 100(5A):2095-2123, 2010), for simulating ground motion from crustal earthquakes of intermediate size. The primary objective of our study is to investigate the transportability of IM2011 into the framework used by the Southern California Earthquake Center broadband simulation platform. In our analysis, we performed broadband (0-20 Hz) ground motion simulations for a suite of M6.7 crustal scenario earthquakes in a hard rock seismic velocity structure using rupture models produced with both IM2011 and the rupture generation method of Graves and Pitarka (Bulletin of the Seismological Society of America, 2016) (GP2016). The level of simulated ground motions for the two approaches compare favorably with median estimates obtained from the 2014 Next Generation Attenuation-West2 Project (NGA-West2) ground motion prediction equations (GMPEs) over the frequency band 0.1-10 Hz and for distances out to 22 km from the fault. We also found that, compared to GP2016, IM2011 generates ground motion with larger variability, particularly at near-fault distances (1 s). For this specific scenario, the largest systematic difference in ground motion level for the two approaches occurs in the period band 1-3 s where the IM2011 motions are about 20-30% lower than those for GP2016. We found that increasing the rupture speed by 20% on the asperities in IM2011 produced ground motions in the 1-3 s bandwidth that are in much closer agreement with the GMPE medians and similar to those obtained with GP2016. The potential implications of this modification for other rupture mechanisms and magnitudes are not yet fully understood, and this topic is the subject of ongoing study. We concluded

  13. Performance of Irikura recipe rupture model generator in earthquake ground motion simulations with Graves and Pitarka hybrid approach

    Science.gov (United States)

    Pitarka, Arben; Graves, Robert; Irikura, Kojiro; Miyake, Hiroe; Rodgers, Arthur

    2017-01-01

    We analyzed the performance of the Irikura and Miyake (Pure and Applied Geophysics 168(2011):85–104, 2011) (IM2011) asperity-based kinematic rupture model generator, as implemented in the hybrid broadband ground motion simulation methodology of Graves and Pitarka (Bulletin of the Seismological Society of America 100(5A):2095–2123, 2010), for simulating ground motion from crustal earthquakes of intermediate size. The primary objective of our study is to investigate the transportability of IM2011 into the framework used by the Southern California Earthquake Center broadband simulation platform. In our analysis, we performed broadband (0–20 Hz) ground motion simulations for a suite of M6.7 crustal scenario earthquakes in a hard rock seismic velocity structure using rupture models produced with both IM2011 and the rupture generation method of Graves and Pitarka (Bulletin of the Seismological Society of America, 2016) (GP2016). The level of simulated ground motions for the two approaches compare favorably with median estimates obtained from the 2014 Next Generation Attenuation-West2 Project (NGA-West2) ground motion prediction equations (GMPEs) over the frequency band 0.1–10 Hz and for distances out to 22 km from the fault. We also found that, compared to GP2016, IM2011 generates ground motion with larger variability, particularly at near-fault distances (1 s). For this specific scenario, the largest systematic difference in ground motion level for the two approaches occurs in the period band 1–3 s where the IM2011 motions are about 20–30% lower than those for GP2016. We found that increasing the rupture speed by 20% on the asperities in IM2011 produced ground motions in the 1–3 s bandwidth that are in much closer agreement with the GMPE medians and similar to those obtained with GP2016. The potential implications of this modification for other rupture mechanisms and magnitudes are not yet fully understood, and this topic is the subject of ongoing study

  14. Hybrid Approach for Modeling Chemical Kinetics and Turbulence Effects on Combustion-Instability Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Combustion instabilities pose a significant technical risk in the development of liquid and solid rocket motors. Much of the effort in modeling combustion...

  15. Hybrid approaches for multiple-species stochastic reaction-diffusion models

    CERN Document Server

    Spill, Fabian; Alarcon, Tomas; Maini, Philip K; Byrne, Helen

    2015-01-01

    Reaction-diffusion models are used to describe systems in fields as diverse as physics, chemistry, ecology and biology. The fundamental quantities in such models are individual entities such as atoms and molecules, bacteria, cells or animals, which move and/or react in a stochastic manner. If the number of entities is large, accounting for each individual is inefficient, and often partial differential equation (PDE) models are used in which the stochastic behaviour of individuals is replaced by a description of the averaged, or mean behaviour of the system. In some situations the number of individuals is large in certain regions and small in others. In such cases, a stochastic model may be inefficient in one region, and a PDE model inaccurate in another. To overcome this problem, we develop a scheme which couples a stochastic reaction-diffusion system in one part of the domain with its mean field analogue, i.e. a discretised PDE model, in the other part of the domain. The interface in between the two domains ...

  16. Hybrid approaches for multiple-species stochastic reaction-diffusion models

    Science.gov (United States)

    Spill, Fabian; Guerrero, Pilar; Alarcon, Tomas; Maini, Philip K.; Byrne, Helen

    2015-10-01

    Reaction-diffusion models are used to describe systems in fields as diverse as physics, chemistry, ecology and biology. The fundamental quantities in such models are individual entities such as atoms and molecules, bacteria, cells or animals, which move and/or react in a stochastic manner. If the number of entities is large, accounting for each individual is inefficient, and often partial differential equation (PDE) models are used in which the stochastic behaviour of individuals is replaced by a description of the averaged, or mean behaviour of the system. In some situations the number of individuals is large in certain regions and small in others. In such cases, a stochastic model may be inefficient in one region, and a PDE model inaccurate in another. To overcome this problem, we develop a scheme which couples a stochastic reaction-diffusion system in one part of the domain with its mean field analogue, i.e. a discretised PDE model, in the other part of the domain. The interface in between the two domains occupies exactly one lattice site and is chosen such that the mean field description is still accurate there. In this way errors due to the flux between the domains are small. Our scheme can account for multiple dynamic interfaces separating multiple stochastic and deterministic domains, and the coupling between the domains conserves the total number of particles. The method preserves stochastic features such as extinction not observable in the mean field description, and is significantly faster to simulate on a computer than the pure stochastic model.

  17. Hybrid approaches for multiple-species stochastic reaction-diffusion models.

    KAUST Repository

    Spill, Fabian

    2015-10-01

    Reaction-diffusion models are used to describe systems in fields as diverse as physics, chemistry, ecology and biology. The fundamental quantities in such models are individual entities such as atoms and molecules, bacteria, cells or animals, which move and/or react in a stochastic manner. If the number of entities is large, accounting for each individual is inefficient, and often partial differential equation (PDE) models are used in which the stochastic behaviour of individuals is replaced by a description of the averaged, or mean behaviour of the system. In some situations the number of individuals is large in certain regions and small in others. In such cases, a stochastic model may be inefficient in one region, and a PDE model inaccurate in another. To overcome this problem, we develop a scheme which couples a stochastic reaction-diffusion system in one part of the domain with its mean field analogue, i.e. a discretised PDE model, in the other part of the domain. The interface in between the two domains occupies exactly one lattice site and is chosen such that the mean field description is still accurate there. In this way errors due to the flux between the domains are small. Our scheme can account for multiple dynamic interfaces separating multiple stochastic and deterministic domains, and the coupling between the domains conserves the total number of particles. The method preserves stochastic features such as extinction not observable in the mean field description, and is significantly faster to simulate on a computer than the pure stochastic model.

  18. A Novel Modelling Approach for Condensing Boilers Based on Hybrid Dynamical Systems

    NARCIS (Netherlands)

    Satyavada, H.; Baldi, S.

    2016-01-01

    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

  19. Damage and failure modelling of hybrid three-dimensional textile composites: a mesh objective multi-scale approach

    Science.gov (United States)

    Patel, Deepak K.

    2016-01-01

    This paper is concerned with predicting the progressive damage and failure of multi-layered hybrid textile composites subjected to uniaxial tensile loading, using a novel two-scale computational mechanics framework. These composites include three-dimensional woven textile composites (3DWTCs) with glass, carbon and Kevlar fibre tows. Progressive damage and failure of 3DWTCs at different length scales are captured in the present model by using a macroscale finite-element (FE) analysis at the representative unit cell (RUC) level, while a closed-form micromechanics analysis is implemented simultaneously at the subscale level using material properties of the constituents (fibre and matrix) as input. The N-layers concentric cylinder (NCYL) model (Zhang and Waas 2014 Acta Mech. 225, 1391–1417; Patel et al. submitted Acta Mech.) to compute local stress, srain and displacement fields in the fibre and matrix is used at the subscale. The 2-CYL fibre–matrix concentric cylinder model is extended to fibre and (N−1) matrix layers, keeping the volume fraction constant, and hence is called the NCYL model where the matrix damage can be captured locally within each discrete layer of the matrix volume. The influence of matrix microdamage at the subscale causes progressive degradation of fibre tow stiffness and matrix stiffness at the macroscale. The global RUC stiffness matrix remains positive definite, until the strain softening response resulting from different failure modes (such as fibre tow breakage, tow splitting in the transverse direction due to matrix cracking inside tow and surrounding matrix tensile failure outside of fibre tows) are initiated. At this stage, the macroscopic post-peak softening response is modelled using the mesh objective smeared crack approach (Rots et al. 1985 HERON 30, 1–48; Heinrich and Waas 2012 53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference, Honolulu, HI, 23–26 April 2012. AIAA 2012-1537). Manufacturing

  20. Simulation-based model checking approach to cell fate specification during Caenorhabditis elegans vulval development by hybrid functional Petri net with extension.

    Science.gov (United States)

    Li, Chen; Nagasaki, Masao; Ueno, Kazuko; Miyano, Satoru

    2009-04-27

    Model checking approaches were applied to biological pathway validations around 2003. Recently, Fisher et al. have proved the importance of model checking approach by inferring new regulation of signaling crosstalk in C. elegans and confirming the regulation with biological experiments. They took a discrete and state-based approach to explore all possible states of the system underlying vulval precursor cell (VPC) fate specification for desired properties. However, since both discrete and continuous features appear to be an indispensable part of biological processes, it is more appropriate to use quantitative models to capture the dynamics of biological systems. Our key motivation of this paper is to establish a quantitative methodology to model and analyze in silico models incorporating the use of model checking approach. A novel method of modeling and simulating biological systems with the use of model checking approach is proposed based on hybrid functional Petri net with extension (HFPNe) as the framework dealing with both discrete and continuous events. Firstly, we construct a quantitative VPC fate model with 1761 components by using HFPNe. Secondly, we employ two major biological fate determination rules - Rule I and Rule II - to VPC fate model. We then conduct 10,000 simulations for each of 48 sets of different genotypes, investigate variations of cell fate patterns under each genotype, and validate the two rules by comparing three simulation targets consisting of fate patterns obtained from in silico and in vivo experiments. In particular, an evaluation was successfully done by using our VPC fate model to investigate one target derived from biological experiments involving hybrid lineage observations. However, the understandings of hybrid lineages are hard to make on a discrete model because the hybrid lineage occurs when the system comes close to certain thresholds as discussed by Sternberg and Horvitz in 1986. Our simulation results suggest that: Rule I

  1. A Hybrid Approach to Clinical Question Answering

    Science.gov (United States)

    2014-11-01

    participation in TREC, we submitted a single run using a hybrid Natural Language Processing ( NLP )-driven approach to accomplish the given task. Evaluation re...for the CDS track uses a variety of NLP - based techniques to address the clinical questions provided. We present a description of our approach, and...discuss our experimental setup, results and eval- uation in the subsequent sections. 2 Description of Our Approach Our hybrid NLP -driven method presents a

  2. Hybrid Models in Loop Quantum Cosmology

    CERN Document Server

    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...

  3. Hybrid modelling of anaerobic wastewater treatment processes.

    Science.gov (United States)

    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.

  4. Hybrid soft computing approaches research and applications

    CERN Document Server

    Dutta, Paramartha; Chakraborty, Susanta

    2016-01-01

    The book provides a platform for dealing with the flaws and failings of the soft computing paradigm through different manifestations. The different chapters highlight the necessity of the hybrid soft computing methodology in general with emphasis on several application perspectives in particular. Typical examples include (a) Study of Economic Load Dispatch by Various Hybrid Optimization Techniques, (b) An Application of Color Magnetic Resonance Brain Image Segmentation by ParaOptiMUSIG activation Function, (c) Hybrid Rough-PSO Approach in Remote Sensing Imagery Analysis,  (d) A Study and Analysis of Hybrid Intelligent Techniques for Breast Cancer Detection using Breast Thermograms, and (e) Hybridization of 2D-3D Images for Human Face Recognition. The elaborate findings of the chapters enhance the exhibition of the hybrid soft computing paradigm in the field of intelligent computing.

  5. A Novel Hybrid Approach for Numerical Modeling of the Nucleating Flow in Laval Nozzle and Transonic Steam Turbine Blades

    Directory of Open Access Journals (Sweden)

    Edris Yousefi Rad

    2017-08-01

    Full Text Available In the present research, considering the importance of desirable steam turbine design, improvement of numerical modeling of steam two-phase flows in convergent and divergent channels and the blades of transonic steam turbines has been targeted. The first novelty of this research is the innovative use of combined Convective Upstream Pressure Splitting (CUSP and scalar methods to update the flow properties at each calculation point. In other words, each property (density, temperature, pressure and velocity at each calculation point can be computed from either the CUSP or scalar method, depending on the least deviation criterion. For this reason this innovative method is named “hybrid method”. The next novelty of this research is the use of an inverse method alongside the proposed hybrid method to find the amount of the important parameter z in the CUSP method, which is herein referred to as “CUSP’s convergence parameter”. Using a relatively simple computational grid, firstly, five cases with similar conditions to those of the main cases under study in this research with available experimental data were used to obtain the value of z by the Levenberg-Marquardt inverse method. With this innovation, first, an optimum value of z = 2.667 was obtained using the inverse method and then directly used for the main cases considered in the research. Given that the aim is to investigate the two-dimensional, steady state, inviscid and adiabatic modeling of steam nucleating flows in three different nozzle and turbine blade geometries, flow simulation was performed using a relatively simple mesh and the innovative proposed hybrid method (scalar + CUSP, with the desired value of z = 2.667 . A comparison between the results of the hybrid modeling of the three main cases with experimental data showed a very good agreement, even within shock zones, including the condensation shock region, revealing the efficiency of this numerical modeling method innovation

  6. Online model checking approach based parameter estimation to a neuronal fate decision simulation model in Caenorhabditis elegans with hybrid functional Petri net with extension.

    Science.gov (United States)

    Li, Chen; Nagasaki, Masao; Koh, Chuan Hock; Miyano, Satoru

    2011-05-01

    Mathematical modeling and simulation studies are playing an increasingly important role in helping researchers elucidate how living organisms function in cells. In systems biology, researchers typically tune many parameters manually to achieve simulation results that are consistent with biological knowledge. This severely limits the size and complexity of simulation models built. In order to break this limitation, we propose a computational framework to automatically estimate kinetic parameters for a given network structure. We utilized an online (on-the-fly) model checking technique (which saves resources compared to the offline approach), with a quantitative modeling and simulation architecture named hybrid functional Petri net with extension (HFPNe). We demonstrate the applicability of this framework by the analysis of the underlying model for the neuronal cell fate decision model (ASE fate model) in Caenorhabditis elegans. First, we built a quantitative ASE fate model containing 3327 components emulating nine genetic conditions. Then, using our developed efficient online model checker, MIRACH 1.0, together with parameter estimation, we ran 20-million simulation runs, and were able to locate 57 parameter sets for 23 parameters in the model that are consistent with 45 biological rules extracted from published biological articles without much manual intervention. To evaluate the robustness of these 57 parameter sets, we run another 20 million simulation runs using different magnitudes of noise. Our simulation results concluded that among these models, one model is the most reasonable and robust simulation model owing to the high stability against these stochastic noises. Our simulation results provide interesting biological findings which could be used for future wet-lab experiments.

  7. Travelling Waves in Hybrid Chemotaxis Models

    KAUST Repository

    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.

  8. Hybrid resolution approaches for dynamic assignment problem of reusable containers

    Directory of Open Access Journals (Sweden)

    Ech-Charrat Mohammed Rida

    2017-01-01

    Full Text Available In this study, we are interested in the reusing activities of reverse logistics. We focus on the dynamic assignment of reusable containers problem (e.g. gas bottles, beverages, pallets, maritime containers, etc.. The objective is to minimize the collect, reloading, storage and redistribution operations costs over a fixed planning horizon taking into account the greenhouse gas emissions. We present a new generic Mixed Integer Programming (MIP model for the problem. The proposed model was solved using the IBM ILOG CPLEX optimization software; this method yield exact solutions, but it is very time consuming. So we adapted two hybrid approaches using a genetic algorithm to solve the problem at a reduced time (The second hybrid approach is enhanced with a local search procedure based on the Variable Neighborhood Search VNS. The numerical results show that both developed hybrid approaches generate high-quality solutions in a moderate computational time, especially the second hybrid method.

  9. A "Hybrid" Approach for Synthesizing Optimal Controllers of Hybrid Systems

    DEFF Research Database (Denmark)

    Zhao, Hengjun; Zhan, Naijun; Kapur, Deepak

    2012-01-01

    We propose an approach to reduce the optimal controller synthesis problem of hybrid systems to quantifier elimination; furthermore, we also show how to combine quantifier elimination with numerical computation in order to make it more scalable but at the same time, keep arising errors due...

  10. A Hybrid Approach to Protect Palmprint Templates

    Directory of Open Access Journals (Sweden)

    Hailun Liu

    2014-01-01

    Full Text Available Biometric template protection is indispensable to protect personal privacy in large-scale deployment of biometric systems. Accuracy, changeability, and security are three critical requirements for template protection algorithms. However, existing template protection algorithms cannot satisfy all these requirements well. In this paper, we propose a hybrid approach that combines random projection and fuzzy vault to improve the performances at these three points. Heterogeneous space is designed for combining random projection and fuzzy vault properly in the hybrid scheme. New chaff point generation method is also proposed to enhance the security of the heterogeneous vault. Theoretical analyses of proposed hybrid approach in terms of accuracy, changeability, and security are given in this paper. Palmprint database based experimental results well support the theoretical analyses and demonstrate the effectiveness of proposed hybrid approach.

  11. 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...

  12. An Innovative Hybrid 3D Analytic-Numerical Approach for System Level Modelling of PEM Fuel Cells

    Directory of Open Access Journals (Sweden)

    Gregor Tavčar

    2013-10-01

    Full Text Available The PEM fuel cell model presented in this paper is based on modelling species transport and coupling electrochemical reactions to species transport in an innovative way. Species transport is modelled by obtaining a 2D analytic solution for species concentration distribution in the plane perpendicular to the gas-flow and coupling consecutive 2D solutions by means of a 1D numerical gas-flow model. The 2D solution is devised on a jigsaw puzzle of multiple coupled domains which enables the modelling of parallel straight channel fuel cells with realistic geometries. Electrochemical and other nonlinear phenomena are coupled to the species transport by a routine that uses derivative approximation with prediction-iteration. A hybrid 3D analytic-numerical fuel cell model of a laboratory test fuel cell is presented and evaluated against a professional 3D computational fluid dynamic (CFD simulation tool. This comparative evaluation shows very good agreement between results of the presented model and those of the CFD simulation. Furthermore, high accuracy results are achieved at computational times short enough to be suitable for system level simulations. This computational efficiency is owed to the semi-analytic nature of its species transport modelling and to the efficient computational coupling of electrochemical kinetics and species transport.

  13. 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...

  14. Hybrid Localization Approach for Underwater Sensor Networks

    Directory of Open Access Journals (Sweden)

    Pei-Hsuan Tsai

    2017-01-01

    Full Text Available Underwater Wireless Sensor Networks (UWSNs are widely used to collect data in the marine environment. Location and time are essential aspects when sensors collect data, particularly in the case of location-aware data. Many studies on terrestrial sensor networks consider sensor locations as the locations where data is collected and focus on sensor positioning when sensors are fixed. However, underwater sensors are mobile networks and the sensor locations change continuously. Localization schemes designed for static sensor networks need to run periodically to update locations and consume considerable sensor power and increase the communication overhead; hence, they cannot be applied to UWSNs. This paper presents a hybrid localization approach with data-location correction, called Data Localization Correction Approach (DLCA, which positions data without additional communication overhead and power consumption on sensors. Without loss of generality, we simulate the ocean environment based on a kinematic model and meandering current mobility model and conduct extensive simulations. Our results show that DLCA can significantly reduce communication costs, while maintaining relatively high localization accuracy.

  15. Accelerated Model Predictive Control for Electric Vehicle Integrated Microgrid Energy Management: A Hybrid Robust and Stochastic Approach

    Directory of Open Access Journals (Sweden)

    Zhenya Ji

    2016-11-01

    Full Text Available A microgrid with an advanced energy management approach is a feasible solution for accommodating the development of distributed generators (DGs and electric vehicles (EVs. At the primary stage of development, the total number of EVs in a microgrid is fairly small but increases promptly. Thus, it makes most prediction models for EV charging demand difficult to apply at present. To overcome the inadaptability, a novel robust approach is proposed to handle EV charging demand predictions along with demand-side management (DSM on the condition of satisfying each EV user’s demand. Variables with stochastic forecast models join the objective function in the form of probability-constrained scenarios. This paper proposes a scenario-based model predictive control (MPC approach combining both robust and stochastic models to minimize the total operational cost for energy management. To overcome the concern about the convergence time increasing from the combination of scenarios, the Benders decomposition (BD technique is further adopted to improve computational efficiency. Simulation results on a combined heat and power microgrid indicate that the proposed scenario-based MPC approach achieves a better economic performance than a traditional deterministic MPC (DMPC approach, while ensuring EV charging demands, as well as minimizing the trade-off between optimal solutions and computing times.

  16. A Hybrid Approach for Correcting Grammatical Errors

    Science.gov (United States)

    Lee, Kiyoung; Kwon, Oh-Woog; Kim, Young-Kil; Lee, Yunkeun

    2015-01-01

    This paper presents a hybrid approach for correcting grammatical errors in the sentences uttered by Korean learners of English. The error correction system plays an important role in GenieTutor, which is a dialogue-based English learning system designed to teach English to Korean students. During the talk with GenieTutor, grammatical error…

  17. A HYBRID APPROACH FOR POLARITY SHIFT DETECTION

    Directory of Open Access Journals (Sweden)

    Michele Mistry

    2017-07-01

    Full Text Available Now-a-days sentiment analysis has become a hot research area. With the increasing use of internet, people express their views by using social media, blogs, etc. So there is a dire need to analyze people’s opinions. Sentiment classification is the main task of sentiment analysis. But while classifying sentiments, the problem of polarity shift occurs. Polarity shift is considered as a very crucial problem. Polarity shift changes a text from positive to negative and vice versa. In this paper, a hybrid approach is proposed for polarity shift detection of negation (explicit and implicit and contrast. The hybrid approach consists of a rule-based approach for detecting explicit negation and contrast and a lexicon called SentiWordNet for detecting implicit negation. The proposed approach outperforms its baselines.

  18. Modeling protective anti-tumor immunity via preventative cancer vaccines using a hybrid agent-based and delay differential equation approach.

    Directory of Open Access Journals (Sweden)

    Peter S Kim

    Full Text Available A next generation approach to cancer envisions developing preventative vaccinations to stimulate a person's immune cells, particularly cytotoxic T lymphocytes (CTLs, to eliminate incipient tumors before clinical detection. The purpose of our study is to quantitatively assess whether such an approach would be feasible, and if so, how many anti-cancer CTLs would have to be primed against tumor antigen to provide significant protection. To understand the relevant dynamics, we develop a two-compartment model of tumor-immune interactions at the tumor site and the draining lymph node. We model interactions at the tumor site using an agent-based model (ABM and dynamics in the lymph node using a system of delay differential equations (DDEs. We combine the models into a hybrid ABM-DDE system and investigate dynamics over a wide range of parameters, including cell proliferation rates, tumor antigenicity, CTL recruitment times, and initial memory CTL populations. Our results indicate that an anti-cancer memory CTL pool of 3% or less can successfully eradicate a tumor population over a wide range of model parameters, implying that a vaccination approach is feasible. In addition, sensitivity analysis of our model reveals conditions that will result in rapid tumor destruction, oscillation, and polynomial rather than exponential decline in the tumor population due to tumor geometry.

  19. Elastic Model Transitions: a Hybrid Approach Utilizing Quadratic Inequality Constrained Least Squares (LSQI) and Direct Shape Mapping (DSM)

    Science.gov (United States)

    Jurenko, Robert J.; Bush, T. Jason; Ottander, John A.

    2014-01-01

    A method for transitioning linear time invariant (LTI) models in time varying simulation is proposed that utilizes both quadratically constrained least squares (LSQI) and Direct Shape Mapping (DSM) algorithms to determine physical displacements. This approach is applicable to the simulation of the elastic behavior of launch vehicles and other structures that utilize multiple LTI finite element model (FEM) derived mode sets that are propagated throughout time. The time invariant nature of the elastic data for discrete segments of the launch vehicle trajectory presents a problem of how to properly transition between models while preserving motion across the transition. In addition, energy may vary between flex models when using a truncated mode set. The LSQI-DSM algorithm can accommodate significant changes in energy between FEM models and carries elastic motion across FEM model transitions. Compared with previous approaches, the LSQI-DSM algorithm shows improvements ranging from a significant reduction to a complete removal of transients across FEM model transitions as well as maintaining elastic motion from the prior state.

  20. Compositional Modelling of Stochastic Hybrid Systems

    NARCIS (Netherlands)

    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

  1. 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.

  2. Weather forecasting based on hybrid neural model

    Science.gov (United States)

    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.

  3. Weather forecasting based on hybrid neural model

    Science.gov (United States)

    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.

  4. 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...

  5. A hybrid approach to masquerade detection | Sodiya | Journal of ...

    African Journals Online (AJOL)

    In this work, a hybrid approach that combined Naïve Bayes and Semi-Global alignment (Nab-Sem) for efficient masquerade detection is proposed. The purpose of this work is to separate the user modeling and session comparing tasks for better performance. Naïve Bayes was used to recognize patterns in the users' blocks ...

  6. Approaches to hybrid synthetic devices

    Science.gov (United States)

    Verma, Vivek

    All living creatures are made up of cells that have the ability to replicate themselves in a repetitive process called cell division. As these cells mature and divide into two there is an extensive movement of cellular components. In order to perform this essential task that sustains life, cells have evolved machines composed of proteins. Biological motors, such as kinesin, transport intracellular cargo and position organelles in eukaryotic cells via unidirectional movement on cytoskeletal tracts called microtubules. Biomolecular motor proteins have the potential to be used as 'nano-engines' for switchable devices, directed self assembly, controlled bioseparations and powering nano- and microelectromechanical systems. However, engineering such systems requires fabrication processes that are compatible with biological materials such as kinesin motor proteins and microtubules. The first objective of the research was to establish biocompatibility between protein systems and nanofabrication. The second objective was to use current micro- and nanofabrication techniques for patterning proteins at specific locations and to study role of casein in supporting the operation of surface bound kinesin. The third objective was to link kinesin and microtubule system to cellulose nanowhiskers. The effects of micro- and nanofabrication processing chemicals and resists on the functionality of casein, kinesin, and microtubule proteins are systematically examined to address the important missing link of the biocompatibility of micro- and nanofabrication processes needed to realize hybrid system fabrication. It was found that both casein, which is used to prevent motor denaturation on surfaces, and kinesin motors are surprisingly tolerant of most of the processing chemicals examined. Microtubules, however, are much more sensitive. Exposure to the processing chemicals leads to depolymerization, which is partially attributed to the pH of the solutions examined. When the chemicals were

  7. Body Fat Percentage Prediction Using Intelligent Hybrid Approaches

    Directory of Open Access Journals (Sweden)

    Yuehjen E. Shao

    2014-01-01

    Full Text Available Excess of body fat often leads to obesity. Obesity is typically associated with serious medical diseases, such as cancer, heart disease, and diabetes. Accordingly, knowing the body fat is an extremely important issue since it affects everyone’s health. Although there are several ways to measure the body fat percentage (BFP, the accurate methods are often associated with hassle and/or high costs. Traditional single-stage approaches may use certain body measurements or explanatory variables to predict the BFP. Diverging from existing approaches, this study proposes new intelligent hybrid approaches to obtain fewer explanatory variables, and the proposed forecasting models are able to effectively predict the BFP. The proposed hybrid models consist of multiple regression (MR, artificial neural network (ANN, multivariate adaptive regression splines (MARS, and support vector regression (SVR techniques. The first stage of the modeling includes the use of MR and MARS to obtain fewer but more important sets of explanatory variables. In the second stage, the remaining important variables are served as inputs for the other forecasting methods. A real dataset was used to demonstrate the development of the proposed hybrid models. The prediction results revealed that the proposed hybrid schemes outperformed the typical, single-stage forecasting models.

  8. 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.

  9. A hybrid multi-criteria decision modeling approach for the best biodiesel blend selection based on ANP-TOPSIS analysis

    Directory of Open Access Journals (Sweden)

    G. Sakthivel

    2015-03-01

    Full Text Available The ever increasing demand and depletion of fossil fuels had an adverse impact on environmental pollution. The selection of appropriate source of biodiesel and proper blending of biodiesel plays a major role in alternate energy production. This paper describes an application of hybrid Multi Criteria Decision Making (MCDM technique for the selection of optimum fuel blend in fish oil biodiesel for the IC engine. The proposed model, Analytical Network Process (ANP is integrated with Technique for Order Performance by Similarity to Ideal Solution (TOPSIS and VlseKriterijumska Optimizacija I Kompromisno Resenje (in Serbian (VIKOR to evaluate the optimum blend. Evaluation of suitable blend is based on the exploratory analysis of the performance, emission and combustion parameters of the single cylinder, constant speed direct injection diesel engine at different load conditions. Here the ANP is used to determine the relative weights of the criteria, whereas TOPSIS and VIKOR are used for obtaining the final ranking of alternative blends. An efficient pair-wise comparison process and ranking of alternatives can be achieved for optimum blend selection through the integration of ANP with TOPSIS and VIKOR. The obtained preference order of the blends for ANP-VIKOR and ANP-TOPSIS are B20 > Diesel > B40 > B60 > B80 > B100 and B20 > B40 > Diesel > B60 > B80 > B100 respectively. Hence by comparing both these methods, B20 is selected as the best blend to operate the internal combustion engines. This paper highlights a new insight into MCDM techniques to evaluate the best fuel blend for the decision makers such as engine manufactures and R& D engineers to meet the fuel economy and emission norms to empower the green revolution.

  10. A HYBRID APPROACH FOR RURAL FEEDER DESIGN

    Directory of Open Access Journals (Sweden)

    DAMANJEET KAUR

    2012-08-01

    Full Text Available In this paper, a population based approach for conductor size selection in rural radial distribution system is presented. The proposed hybrid approach implies a particle swarm optimization (PSO approach in combination with mutant property of differential evolution (DE for conductor size selection in radial distribution system. The conductor size for each feeder segment is selected such that the total cost of capital investment and capitalized cost of energy losses is minimized while constraints of voltage at each node and current carrying capacity of conductor is within the limits. The applicability and effectiveness of the proposed method is demonstrated with the help of 32-node test system.

  11. Modeling of Quasi-Four-Phase Flow in Continuous Casting Mold Using Hybrid Eulerian and Lagrangian Approach

    Science.gov (United States)

    Liu, Zhongqiu; Sun, Zhenbang; Li, Baokuan

    2017-04-01

    Lagrangian tracking model combined with Eulerian multi-phase model is employed to predict the time-dependent argon-steel-slag-air quasi-four-phase flow inside a slab continuous casting mold. The Eulerian approach is used for the description of three phases (molten steel, liquid slag, and air at the top of liquid slag layer). The dispersed argon bubble injected from the SEN is treated in the Lagrangian way. The complex interfacial momentum transfers between various phases are considered. Validation is supported by the measurement data of cold model experiments and industrial practice. Close agreements were achieved for the gas volume fraction, liquid flow pattern, level fluctuation, and exposed slag eye phenomena. Many known phenomena and new predictions were successfully reproduced using this model. The vortex slag entrapment phenomenon at the slag-steel interface was obtained using this model, some small slag drops are sucked deep into the liquid pool of molten steel. Varying gas flow rates have a large effect on the steel flow pattern in the upper recirculation zone. Three typical flow patterns inside the mold with different argon gas flow rates have been obtained: double roll, three roll, and single roll. Effects of argon gas flow rate, casting speed, and slag layer thickness on the exposed slag eye and level fluctuation at the slag-steel interface were studied. A dimensionless value of H ave/ h was proposed to describe the time-averaged level fluctuation of slag-steel interface. The exposed slag eye near the SEN would be formed when the value of H ave/ h is larger than 0.4.

  12. 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

  13. Numerical modelling in building thermo-aeraulics: from CFD modelling to an hybrid finite volume / zonal approach; Modelisation numerique de la thermoaeraulique du batiment: des modeles CFD a une approche hybride volumes finis / zonale

    Energy Technology Data Exchange (ETDEWEB)

    Bellivier, A.

    2004-05-15

    For 3D modelling of thermo-aeraulics in building using field codes, it is necessary to reduce the computing time in order to model increasingly larger volumes. The solution suggested in this study is to couple two modelling: a zonal approach and a CFD approach. The first part of the work that was carried out is the setting of a simplified CFD modelling. We propose rules for use of coarse grids, a constant effective viscosity law and adapted coefficients for heat exchange in the framework of building thermo-aeraulics. The second part of this work concerns the creation of fluid Macro-Elements and their coupling with a calculation of CFD finite volume type. Depending on the boundary conditions of the problem, a local description of the driving flow is proposed via the installation and use of semi-empirical evolution laws. The Macro-Elements is then inserted in CFD computation: the values of velocity calculated by the evolution laws are imposed on the CFD cells corresponding to the Macro-Element. We use these two approaches on five cases representative of thermo-aeraulics in buildings. The results are compared with experimental data and with traditional RANS simulations. We highlight the significant gain of time that our approach allows while preserving a good quality of numerical results. (author)

  14. Hybrid methodological approach to context-dependent speech recognition

    Directory of Open Access Journals (Sweden)

    Dragiša Mišković

    2017-01-01

    Full Text Available Although the importance of contextual information in speech recognition has been acknowledged for a long time now, it has remained clearly underutilized even in state-of-the-art speech recognition systems. This article introduces a novel, methodologically hybrid approach to the research question of context-dependent speech recognition in human–machine interaction. To the extent that it is hybrid, the approach integrates aspects of both statistical and representational paradigms. We extend the standard statistical pattern-matching approach with a cognitively inspired and analytically tractable model with explanatory power. This methodological extension allows for accounting for contextual information which is otherwise unavailable in speech recognition systems, and using it to improve post-processing of recognition hypotheses. The article introduces an algorithm for evaluation of recognition hypotheses, illustrates it for concrete interaction domains, and discusses its implementation within two prototype conversational agents.

  15. A Hybrid Strong/Weak Coupling Approach to Jet Quenching

    CERN Document Server

    Casalderrey-Solana, Jorge; Milhano, José Guilherme; Pablos, Daniel; Rajagopal, Krishna

    2014-01-01

    We propose and explore a new hybrid approach to jet quenching in a strongly coupled medium. The basis of this phenomenological approach is to treat physics processes at different energy scales differently. The high-$Q^2$ processes associated with the QCD evolution of the jet from production as a single hard parton through its fragmentation, up to but not including hadronization, are treated perturbatively. The interactions between the partons in the shower and the deconfined matter within which they find themselves lead to energy loss. The momentum scales associated with the medium (of the order of the temperature) and with typical interactions between partons in the shower and the medium are sufficiently soft that strongly coupled physics plays an important role in energy loss. We model these interactions using qualitative insights from holographic calculations of the energy loss of energetic light quarks and gluons in a strongly coupled plasma, obtained via gauge/gravity duality. We embed this hybrid model ...

  16. 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.

  17. A hybrid neurogenetic approach for stock forecasting.

    Science.gov (United States)

    Kwon, Yung-Keun; Moon, Byung-Ro

    2007-05-01

    In this paper, we propose a hybrid neurogenetic system for stock trading. A recurrent neural network (NN) having one hidden layer is used for the prediction model. The input features are generated from a number of technical indicators being used by financial experts. The genetic algorithm (GA) optimizes the NN's weights under a 2-D encoding and crossover. We devised a context-based ensemble method of NNs which dynamically changes on the basis of the test day's context. To reduce the time in processing mass data, we parallelized the GA on a Linux cluster system using message passing interface. We tested the proposed method with 36 companies in NYSE and NASDAQ for 13 years from 1992 to 2004. The neurogenetic hybrid showed notable improvement on the average over the buy-and-hold strategy and the context-based ensemble further improved the results. We also observed that some companies were more predictable than others, which implies that the proposed neurogenetic hybrid can be used for financial portfolio construction.

  18. Modelling freeway networks by hybrid stochastic models

    OpenAIRE

    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...

  19. Ethanol mediated As(III) adsorption onto Zn-loaded pinecone biochar: Experimental investigation, modeling, and optimization using hybrid artificial neural network-genetic algorithm approach.

    Science.gov (United States)

    Zafar, Mohd; Van Vinh, N; Behera, Shishir Kumar; Park, Hung-Suck

    2017-04-01

    Organic matters (OMs) and their oxidization products often influence the fate and transport of heavy metals in the subsurface aqueous systems through interaction with the mineral surfaces. This study investigates the ethanol (EtOH)-mediated As(III) adsorption onto Zn-loaded pinecone (PC) biochar through batch experiments conducted under Box-Behnken design. The effect of EtOH on As(III) adsorption mechanism was quantitatively elucidated by fitting the experimental data using artificial neural network and quadratic modeling approaches. The quadratic model could describe the limiting nature of EtOH and pH on As(III) adsorption, whereas neural network revealed the stronger influence of EtOH (64.5%) followed by pH (20.75%) and As(III) concentration (14.75%) on the adsorption phenomena. Besides, the interaction among process variables indicated that EtOH enhances As(III) adsorption over a pH range of 2 to 7, possibly due to facilitation of ligand-metal(Zn) binding complexation mechanism. Eventually, hybrid response surface model-genetic algorithm (RSM-GA) approach predicted a better optimal solution than RSM, i.e., the adsorptive removal of As(III) (10.47μg/g) is facilitated at 30.22mg C/L of EtOH with initial As(III) concentration of 196.77μg/L at pH5.8. The implication of this investigation might help in understanding the application of biochar for removal of various As(III) species in the presence of OM. Copyright © 2016. Published by Elsevier B.V.

  20. A Hybrid Neural Network Approach for Kinematic Modeling of a Novel 6-UPS Parallel Human-Like Mastication Robot

    Directory of Open Access Journals (Sweden)

    Hadi Kalani

    2016-04-01

    Full Text Available Introduction we aimed to introduce a 6-universal-prismatic-spherical (UPS parallel mechanism for the human jaw motion and theoretically evaluate its kinematic problem. We proposed a strategy to provide a fast and accurate solution to the kinematic problem. The proposed strategy could accelerate the process of solution-finding for the direct kinematic problem by reducing the number of required iterations in order to reach the desired accuracy level. Materials and Methods To overcome the direct kinematic problem, an artificial neural network and third-order Newton-Raphson algorithm were combined to provide an improved hybrid method. In this method, approximate solution was presented for the direct kinematic problem by the neural network. This solution could be considered as the initial guess for the third-order Newton-Raphson algorithm to provide an answer with the desired level of accuracy. Results The results showed that the proposed combination could help find a approximate solution and reduce the execution time for the direct kinematic problem, The results showed that muscular actuations showed periodic behaviors, and the maximum length variation of temporalis muscle was larger than that of masseter and pterygoid muscles. By reducing the processing time for solving the direct kinematic problem, more time could be devoted to control calculations.. In this method, for relatively high levels of accuracy, the number of iterations and computational time decreased by 90% and 34%, respectively, compared to the conventional Newton method. Conclusion The present analysis could allow researchers to characterize and study the mastication process by specifying different chewing patterns (e.g., muscle displacements.

  1. Physics-based preoperative approach planning using hybrid virtual bodies.

    Science.gov (United States)

    Nakao, Megumi; Kuroda, Tomohiro; Komori, Masaru; Oyama, Hiroshi; Komeda, Masashi

    2004-01-01

    This paper proposes a hybrid model mixing geometry and volume data to improve representation of virtual bodies. This model applies object-oriented data models and rendering techniques to virtual organs, and enables both interactive VR simulation and detailed volume visualization of tissue of interest (e.g. coronary). Also, a physics-based framework interactively simulates estimated surgical fields which are used in preoperative discussion. Based on the proposed methods, a VR-based strategic planning system is developed. The system does not need high cost manual segmentation of patient dataset and efficiently supports planning of surgical approaches in cardiovascular surgery.

  2. Location Selection for Wind Farms Using GIS Multi-Criteria Hybrid Model: An Approach Based on Fuzzy and Rough Numbers

    National Research Council Canada - National Science Library

    Dragan Pamučar; Ljubomir Gigović; Zoran Bajić; Miljojko Janošević

    2017-01-01

    This paper presents spatial mathematical model in order to identify sites for the wind farms installment which can have significant support for the planners in the area of strategy and management of wind power use...

  3. Performance of Irikura's Recipe Rupture Model Generator in Earthquake Ground Motion Simulations as Implemented in the Graves and Pitarka Hybrid Approach.

    Energy Technology Data Exchange (ETDEWEB)

    Pitarka, A. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2016-11-22

    We analyzed the performance of the Irikura and Miyake (2011) (IM2011) asperity-­ based kinematic rupture model generator, as implemented in the hybrid broadband ground-­motion simulation methodology of Graves and Pitarka (2010), for simulating ground motion from crustal earthquakes of intermediate size. The primary objective of our study is to investigate the transportability of IM2011 into the framework used by the Southern California Earthquake Center broadband simulation platform. In our analysis, we performed broadband (0 -­ 20Hz) ground motion simulations for a suite of M6.7 crustal scenario earthquakes in a hard rock seismic velocity structure using rupture models produced with both IM2011 and the rupture generation method of Graves and Pitarka (2016) (GP2016). The level of simulated ground motions for the two approaches compare favorably with median estimates obtained from the 2014 Next Generation Attenuation-­West2 Project (NGA-­West2) ground-­motion prediction equations (GMPEs) over the frequency band 0.1–10 Hz and for distances out to 22 km from the fault. We also found that, compared to GP2016, IM2011 generates ground motion with larger variability, particularly at near-­fault distances (<12km) and at long periods (>1s). For this specific scenario, the largest systematic difference in ground motion level for the two approaches occurs in the period band 1 – 3 sec where the IM2011 motions are about 20 – 30% lower than those for GP2016. We found that increasing the rupture speed by 20% on the asperities in IM2011 produced ground motions in the 1 – 3 second bandwidth that are in much closer agreement with the GMPE medians and similar to those obtained with GP2016. The potential implications of this modification for other rupture mechanisms and magnitudes are not yet fully understood, and this topic is the subject of ongoing study.

  4. A novel hybrid MCDM model for performance evaluation of research and technology organizations based on BSC approach.

    Science.gov (United States)

    Varmazyar, Mohsen; Dehghanbaghi, Maryam; Afkhami, Mehdi

    2016-10-01

    Balanced Scorecard (BSC) is a strategic evaluation tool using both financial and non-financial indicators to determine the business performance of organizations or companies. In this paper, a new integrated approach based on the Balanced Scorecard (BSC) and multi-criteria decision making (MCDM) methods are proposed to evaluate the performance of research centers of research and technology organization (RTO) in Iran. Decision-Making Trial and Evaluation Laboratory (DEMATEL) are employed to reflect the interdependencies among BSC perspectives. Then, Analytic Network Process (ANP) is utilized to weight the indices influencing the considered problem. In the next step, we apply four MCDM methods including Additive Ratio Assessment (ARAS), Complex Proportional Assessment (COPRAS), Multi-Objective Optimization by Ratio Analysis (MOORA), and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for ranking of alternatives. Finally, the utility interval technique is applied to combine the ranking results of MCDM methods. Weighted utility intervals are computed by constructing a correlation matrix between the ranking methods. A real case is presented to show the efficacy of the proposed approach. Copyright © 2016 Elsevier Ltd. All rights reserved.

  5. Stock selection using a hybrid MCDM approach

    Directory of Open Access Journals (Sweden)

    Tea Poklepović

    2014-12-01

    Full Text Available The problem of selecting the right stocks to invest in is of immense interest for investors on both emerging and developed capital markets. Moreover, an investor should take into account all available data regarding stocks on the particular market. This includes fundamental and stock market indicators. The decision making process includes several stocks to invest in and more than one criterion. Therefore, the task of selecting the stocks to invest in can be viewed as a multiple criteria decision making (MCDM problem. Using several MCDM methods often leads to divergent rankings. The goal of this paper is to resolve these possible divergent results obtained from different MCDM methods using a hybrid MCDM approach based on Spearman’s rank correlation coefficient. Five MCDM methods are selected: COPRAS, linear assignment, PROMETHEE, SAW and TOPSIS. The weights for all criteria are obtained by using the AHP method. Data for this study includes information on stock returns and traded volumes from March 2012 to March 2014 for 19 stocks on the Croatian capital market. It also includes the most important fundamental and stock market indicators for selected stocks. Rankings using five selected MCDM methods in the stock selection problem yield divergent results. However, after applying the proposed approach the final hybrid rankings are obtained. The results show that the worse stocks to invest in happen to be the same when the industry is taken into consideration or when not. However, when the industry is taken into account, the best stocks to invest in are slightly different, because some industries are more profitable than the others.

  6. Boltzmann Transport in Hybrid PIC HET Modeling

    Science.gov (United States)

    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

  7. Modelling of Hybrid Materials and Interface Defects through Homogenization Approach for the Prediction of Effective Thermal Conductivity of FRP Composites Using Finite Element Method

    Directory of Open Access Journals (Sweden)

    C. Mahesh

    2013-01-01

    Full Text Available Finite element method is effectively used to homogenize the thermal conductivity of FRP composites consisting of hybrid materials and fibre-matrix debonds at some of the fibres. The homogenized result at microlevel is used to determine the property of the layer using macromechanics principles; thereby, it is possible to minimize the computational efforts required to solve the problem as in state through only micromechanics approach. The working of the proposed procedure is verified for three different problems: (i hybrid composite having two different fibres in alternate layers, (ii fibre-matrix interface debond in alternate layers, and (iii fibre-matrix interface debond at one fibre in a group of four fibres in one unit cell. It is observed that the results are in good agreement with those obtained through pure micro-mechanics approach.

  8. Hybrid artificial intelligence approach based on neural fuzzy inference model and metaheuristic optimization for flood susceptibilitgy modeling in a high-frequency tropical cyclone area using GIS

    Science.gov (United States)

    Tien Bui, Dieu; Pradhan, Biswajeet; Nampak, Haleh; Bui, Quang-Thanh; Tran, Quynh-An; Nguyen, Quoc-Phi

    2016-09-01

    This paper proposes a new artificial intelligence approach based on neural fuzzy inference system and metaheuristic optimization for flood susceptibility modeling, namely MONF. In the new approach, the neural fuzzy inference system was used to create an initial flood susceptibility model and then the model was optimized using two metaheuristic algorithms, Evolutionary Genetic and Particle Swarm Optimization. A high-frequency tropical cyclone area of the Tuong Duong district in Central Vietnam was used as a case study. First, a GIS database for the study area was constructed. The database that includes 76 historical flood inundated areas and ten flood influencing factors was used to develop and validate the proposed model. Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Receiver Operating Characteristic (ROC) curve, and area under the ROC curve (AUC) were used to assess the model performance and its prediction capability. Experimental results showed that the proposed model has high performance on both the training (RMSE = 0.306, MAE = 0.094, AUC = 0.962) and validation dataset (RMSE = 0.362, MAE = 0.130, AUC = 0.911). The usability of the proposed model was evaluated by comparing with those obtained from state-of-the art benchmark soft computing techniques such as J48 Decision Tree, Random Forest, Multi-layer Perceptron Neural Network, Support Vector Machine, and Adaptive Neuro Fuzzy Inference System. The results show that the proposed MONF model outperforms the above benchmark models; we conclude that the MONF model is a new alternative tool that should be used in flood susceptibility mapping. The result in this study is useful for planners and decision makers for sustainable management of flood-prone areas.

  9. Bond graph model-based fault diagnosis of hybrid systems

    CERN Document Server

    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...

  10. 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...

  11. Hybrid Modelling of Individual Movement and Collective Behaviour

    KAUST Repository

    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.

  12. Multilayer Approach for Advanced Hybrid Lithium Battery

    KAUST Repository

    Ming, Jun

    2016-06-06

    Conventional intercalated rechargeable batteries have shown their capacity limit, and the development of an alternative battery system with higher capacity is strongly needed for sustainable electrical vehicles and hand-held devices. Herein, we introduce a feasible and scalable multilayer approach to fabricate a promising hybrid lithium battery with superior capacity and multivoltage plateaus. A sulfur-rich electrode (90 wt % S) is covered by a dual layer of graphite/Li4Ti5O12, where the active materials S and Li4Ti5O12 can both take part in redox reactions and thus deliver a high capacity of 572 mAh gcathode -1 (vs the total mass of electrode) or 1866 mAh gs -1 (vs the mass of sulfur) at 0.1C (with the definition of 1C = 1675 mA gs -1). The battery shows unique voltage platforms at 2.35 and 2.1 V, contributed from S, and 1.55 V from Li4Ti5O12. A high rate capability of 566 mAh gcathode -1 at 0.25C and 376 mAh gcathode -1 at 1C with durable cycle ability over 100 cycles can be achieved. Operando Raman and electron microscope analysis confirm that the graphite/Li4Ti5O12 layer slows the dissolution/migration of polysulfides, thereby giving rise to a higher sulfur utilization and a slower capacity decay. This advanced hybrid battery with a multilayer concept for marrying different voltage plateaus from various electrode materials opens a way of providing tunable capacity and multiple voltage platforms for energy device applications. © 2016 American Chemical Society.

  13. Fluid and hybrid models for streamers

    Science.gov (United States)

    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.

  14. Forecasting conditional climate-change using a hybrid approach

    Science.gov (United States)

    Esfahani, Akbar Akbari; Friedel, Michael J.

    2014-01-01

    A novel approach is proposed to forecast the likelihood of climate-change across spatial landscape gradients. This hybrid approach involves reconstructing past precipitation and temperature using the self-organizing map technique; determining quantile trends in the climate-change variables by quantile regression modeling; and computing conditional forecasts of climate-change variables based on self-similarity in quantile trends using the fractionally differenced auto-regressive integrated moving average technique. The proposed modeling approach is applied to states (Arizona, California, Colorado, Nevada, New Mexico, and Utah) in the southwestern U.S., where conditional forecasts of climate-change variables are evaluated against recent (2012) observations, evaluated at a future time period (2030), and evaluated as future trends (2009–2059). These results have broad economic, political, and social implications because they quantify uncertainty in climate-change forecasts affecting various sectors of society. Another benefit of the proposed hybrid approach is that it can be extended to any spatiotemporal scale providing self-similarity exists.

  15. Hybrid ODE/SSA methods and the cell cycle model

    Science.gov (United States)

    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.

  16. Evaluating Tidal Marsh Sustainability in the Face of Sea-Level Rise: A Hybrid Modeling Approach Applied to San Francisco Bay

    Science.gov (United States)

    Stralberg, Diana; Brennan, Matthew; Callaway, John C.; Wood, Julian K.; Schile, Lisa M.; Jongsomjit, Dennis; Kelly, Maggi; Parker, V. Thomas; Crooks, Stephen

    2011-01-01

    Background Tidal marshes will be threatened by increasing rates of sea-level rise (SLR) over the next century. Managers seek guidance on whether existing and restored marshes will be resilient under a range of potential future conditions, and on prioritizing marsh restoration and conservation activities. Methodology Building upon established models, we developed a hybrid approach that involves a mechanistic treatment of marsh accretion dynamics and incorporates spatial variation at a scale relevant for conservation and restoration decision-making. We applied this model to San Francisco Bay, using best-available elevation data and estimates of sediment supply and organic matter accumulation developed for 15 Bay subregions. Accretion models were run over 100 years for 70 combinations of starting elevation, mineral sediment, organic matter, and SLR assumptions. Results were applied spatially to evaluate eight Bay-wide climate change scenarios. Principal Findings Model results indicated that under a high rate of SLR (1.65 m/century), short-term restoration of diked subtidal baylands to mid marsh elevations (−0.2 m MHHW) could be achieved over the next century with sediment concentrations greater than 200 mg/L. However, suspended sediment concentrations greater than 300 mg/L would be required for 100-year mid marsh sustainability (i.e., no elevation loss). Organic matter accumulation had minimal impacts on this threshold. Bay-wide projections of marsh habitat area varied substantially, depending primarily on SLR and sediment assumptions. Across all scenarios, however, the model projected a shift in the mix of intertidal habitats, with a loss of high marsh and gains in low marsh and mudflats. Conclusions/Significance Results suggest a bleak prognosis for long-term natural tidal marsh sustainability under a high-SLR scenario. To minimize marsh loss, we recommend conserving adjacent uplands for marsh migration, redistributing dredged sediment to raise elevations, and

  17. Scalar field dark matter in hybrid approach

    Science.gov (United States)

    Friedrich, Pavel; Prokopec, Tomislav

    2017-10-01

    We develop a hybrid formalism suitable for modeling scalar field dark matter, in which the phase-space distribution associated with the real scalar field is modeled by statistical equal-time two-point functions and gravity is treated by two stochastic gravitational fields in the longitudinal gauge (in this work we neglect vector and tensor gravitational perturbations). Inspired by the commonly used Newtonian Vlasov-Poisson system, we firstly identify a suitable combination of equal-time two-point functions that defines the phase-space distribution associated with the scalar field and then derive both a kinetic equation that contains relativistic scalar matter corrections as well as linear gravitational scalar field equations whose sources can be expressed in terms of a momentum integral over the phase-space distribution function. Our treatment generalizes the commonly used classical scalar field formalism, in that it allows for modeling of (dynamically generated) vorticity and perturbations in anisotropic stresses of the scalar field. It also allows for a systematic inclusion of relativistic and higher-order corrections that may be used to distinguish different dark matter scenarios. We also provide initial conditions for the statistical equal-time two-point functions of the matter scalar field in terms of gravitational potentials and the scale factor.

  18. A Hybrid Approach for Fault Detection in Autonomous Physical Agents

    Science.gov (United States)

    2014-05-01

    positives (false alarms). In this paper we aim to extend the state of the art by describing a hybrid approach which is based on the SFDD approach and...ttributes with c rue : onstruction is owever, this o nd not the decis When no oth ecides on a cla n this particular hange the maj ree makes the s...hybrid approach tends to 0. We chose to demonstrate how a hybrid approach extends the state of the art with the use of, and a comparison to the SFDD

  19. WEB CONTENT EXTRACTION USING HYBRID APPROACH

    Directory of Open Access Journals (Sweden)

    K. Nethra

    2014-01-01

    Full Text Available The World Wide Web has rich source of voluminous and heterogeneous information which continues to expand in size and complexity. Many Web pages are unstructured and semi-structured, so it consists of noisy information like advertisement, links, headers, footers etc. This noisy information makes extraction of Web content tedious. Many techniques that were proposed for Web content extraction are based on automatic extraction and hand crafted rule generation. Automatic extraction technique is done through Web page segmentation, but it increases the time complexity. Hand crafted rule generation uses string manipulation function for rule generation, but generating those rules is very difficult. A hybrid approach is proposed to extract main content from Web pages. A HTML Web page is converted to DOM tree and features are extracted and with the extracted features, rules are generated. Decision tree classification and Naïve Bayes classification are machine learning methods used for rules generation. By using the rules, noisy part in the Web page is discarded and informative content in the Web page is extracted. The performance of both decision tree classification and Naïve Bayes classification are measured with metrics like precision, recall, F-measure and accuracy.

  20. Hybrid oil film approach to measuring skin friction distribution

    Science.gov (United States)

    Kurita, Mitsuru; Iijima, Hidetoshi

    2017-05-01

    This paper describes a technique for quantitatively measuring the time-averaged skin friction distribution on a wind tunnel test model. The technique is a hybrid oil film approach that is based on the combination of the qualitative skin friction distribution obtained from luminescent oil film and the quantitative local skin friction measurements obtained from oil film interferometry in another blowing of the same flow condition. To demonstrate its validity, the proposed method was applied to the flow field around a vortex generator on a flat plate, and successfully measured the quantitative skin friction distribution.

  1. 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....

  2. 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

  3. Modeling hybrid perovskites by molecular dynamics.

    Science.gov (United States)

    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.

  4. On a Variational Approach to Optimization of Hybrid Mechanical Systems

    Directory of Open Access Journals (Sweden)

    Vadim Azhmyakov

    2010-01-01

    Full Text Available This paper deals with multiobjective optimization techniques for a class of hybrid optimal control problems in mechanical systems. We deal with general nonlinear hybrid control systems described by boundary-value problems associated with hybrid-type Euler-Lagrange or Hamilton equations. The variational structure of the corresponding solutions makes it possible to reduce the original “mechanical” problem to an auxiliary multiobjective programming reformulation. This approach motivates possible applications of theoretical and computational results from multiobjective optimization related to the original dynamical optimization problem. We consider first order optimality conditions for optimal control problems governed by hybrid mechanical systems and also discuss some conceptual algorithms.

  5. HYbrid Coordinate Ocean Model (HYCOM): Global

    Data.gov (United States)

    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)...

  6. An Adaptive and Hybrid Approach for Revisiting the Visibility Pipeline

    Directory of Open Access Journals (Sweden)

    Ícaro Lins Leitão da Cunha

    2016-04-01

    Full Text Available We revisit the visibility problem, which is traditionally known in Computer Graphics and Vision fields as the process of computing a (potentially visible set of primitives in the computational model of a scene. We propose a hybrid solution that uses a dry structure (in the sense of data reduction, a triangulation of the type J1a, to accelerate the task of searching for visible primitives. We came up with a solution that is useful for real-time, on-line, interactive applications as 3D visualization. In such applications the main goal is to load the minimum amount of primitives from the scene during the rendering stage, as possible. For this purpose, our algorithm executes the culling by using a hybrid paradigm based on viewing-frustum, back-face culling and occlusion models. Results have shown substantial improvement over these traditional approaches if applied separately. This novel approach can be used in devices with no dedicated processors or with low processing power, as cell phones or embedded displays, or to visualize data through the Internet, as in virtual museums applications.

  7. A Hybrid Model Approach for Achieving the Highest Level of Matching Between the “Print and Original” in the Sheet-Fed Offset Process

    Directory of Open Access Journals (Sweden)

    Rajendrakumar Anayath

    2015-09-01

    Full Text Available This study was designed to explore an optimized hybrid system through dual measurement approach of contrast measurement method and CIE L*a*b* measurement method to arrive a logical interface for achieving the highest matching between the print and original in sheet fed offset printing process. The work was started with the detailed study of contrast measurement, CIE L*a*b* measurement method, visual and computational intelligence based assessment and control. The master was designed in such a way that value of density and other values can be measured easily in effective way. X-Rite eXact instrument is used for capturing the readings, the 10 standard observers were selected initially by manual method and finally by using on line Fransworth-Munsell 100 Hue Colour Vision Test and visual assessments and judgement were done on X-Rite’s Macbeth Lighting Booth and their visual assessments are recorded, analyzed and represented. All the parameters like Paper, Ink, Measuring Conditions and Measuring Instruments etc. were maintained in compliance with ISO specifications. After the analysis of data, the study reached to the following main conclusion i.e. It is observed that almost in all the cases, preference of the Standard Observers are for Delta E Value leading to the higher contrast value instead of Minimum Delta E with less contrast value. Therefore the dual approach of “Hybrid System” will help us to arrive at the most convincing, measurable and perceptually acceptable print result which will be the highest (closest match to the original by clubbing the best of “CIE Lab, Contrast Method and Standard Observers Visual Perception” as there are positives and negatives in all these three when one approaches individually. The objective of this paper was to develop a dual measurement approach of CIE Lab & Contrast to arrive at a logical inference for the highest level of matching between the original and print in the sheet fed offset printing.

  8. 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...

  9. Hybrid perovskites: Approaches towards light-emitting devices

    KAUST Repository

    Alias, Mohd Sharizal

    2016-10-06

    The high optical gain and absorption of organic-inorganic hybrid perovskites have attracted extensive research for photonic device applications. Using the bromide halide as an example, we present key approaches of our work towards realizing efficient perovskites based light-emitters. The approaches involved determination of optical constants for the hybrid perovskites thin films, fabrication of photonic nanostructures in the form of subwavelength grating reflector patterned directly on the hybrid perovskites as light manipulation layer, and enhancing the emission property of the hybrid perovskites by using microcavity structure. Our results provide a platform for realization of hybrid perovskites based light-emitting devices for solid-state lighting and display applications. © 2016 IEEE.

  10. Understanding the formation and influence of attitudes in patients' treatment choices for lower back pain: Testing the benefits of a hybrid choice model approach

    DEFF Research Database (Denmark)

    Kløjgaard, Mirja Elisabeth; Hess, S.

    2014-01-01

    in health economics. The present paper looks at the formation of such attitudes and their role in patients treatment choices in the context of low back pain. We use stated choice data collected from a sample of 561 patients with 348 respondents referred to a regional spine centre in Middelfart, Denmark...... in spring/summer 2012. We show how the hybrid model structure is able to make a link between attitudinal questions and treatment choices, and also explains variation of these attitudes across key socio-demographic groups. However, we also show how, in this case, only a small share of the overall...

  11. GPCR-I-TASSER: A hybrid approach to G protein-coupled receptor structure modeling and the application to the human genome

    Science.gov (United States)

    Zhang, Jian; Yang, Jianyi; Jang, Richard; Zhang, Yang

    2015-01-01

    SUMMARY Experimental structure determination remains very difficult for G protein-coupled receptors (GPCRs). We propose a new hybrid protocol to construct GPCR structure models that integrates experimental mutagenesis data with ab initio transmembrane (TM) helix assembly simulations. The method was tested on 24 known GPCRs where the ab initio TM-helix assembly procedure constructed the correct fold for 20 cases. When combined with weak-homology and sparse mutagenesis restraints, the method generated correct folds for all the tested cases with an average C-alpha RMSD 2.4 Å in the TM-regions. The new hybrid protocol was applied to model all 1026 GPCRs in the human genome, where 923 have a high confidence score that are expected to have correct folds; these contain many pharmaceutically important families with no previously solved structures, including Trace amine, Prostanoids, Releasing hormones, Melanocortins, Vasopressin and Neuropeptide Y receptors. The results demonstrate new progress on genome-wide structure modeling of transmembrane proteins. PMID:26190572

  12. A hybrid approach for estimating spatial evapotranspiration from satellite imagery

    Science.gov (United States)

    Neale, C. M. U.; Gonzalez-Dugo, M. P.; Mateos, L.; Kustas, W. P.; Kaheil, Y.

    2007-10-01

    Two common approaches for estimating crop evapotranspiration (ET) using satellite imagery are the reflectance-based crop coefficient method and the energy balance method. The reflectance-based crop coefficient method relates a reflectance-based vegetation index such as the soil adjusted vegetation index (SAVI) to ET basal crop coefficients such as those described by Wright (1982) [1] and the FAO 56 manual [2]. A time-series of remotely sensed inputs is then used to build the crop coefficient curve in each field being monitored. In order to obtain actual ET, a water balance must be maintained in the root zone of the crop in order to make the appropriate adjustments due to soil moisture deficits and wet soil surface from irrigation and/or rain. Ground meteorological data must be provided by a weather station located in the modeled area for the estimation of reference ET. In the energy balance approach, surface temperatures are used in the estimation of sensible heat fluxes and depending on the complexity of the model, different methods are used to either handle the aerodynamic temperature term or deal with sparse canopies (empirical approaches, two-source model, SEBAL model). Remotely sensed inputs are also used for the estimation of net radiation and soil heat flux, with latent heat flux (ET) obtained as a residual from the energy balance equation. The energy balance approach results in the actual ET being estimated directly. Instantaneous values of ET must be extrapolated to the entire day and over time in between satellite overpass inputs. This paper describes a hybrid approach that uses both methods in combination to monitor actual ET over a growing season for irrigated and non-irrigated crops. The model has been coded in an ArcGIS environment, using visual basic for the calculations. This paper describes the modeling environment and coded ET models within and presents some application results.

  13. 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.

  14. Assessing Wheat Frost Risk with the Support of GIS: An Approach Coupling a Growing Season Meteorological Index and a Hybrid Fuzzy Neural Network Model

    Directory of Open Access Journals (Sweden)

    Yaojie Yue

    2016-12-01

    Full Text Available Crop frost, one kind of agro-meteorological disaster, often causes significant loss to agriculture. Thus, evaluating the risk of wheat frost aids scientific response to such disasters, which will ultimately promote food security. Therefore, this paper aims to propose an integrated risk assessment model of wheat frost, based on meteorological data and a hybrid fuzzy neural network model, taking China as an example. With the support of a geographic information system (GIS, a comprehensive method was put forward. Firstly, threshold temperatures of wheat frost at three growth stages were proposed, referring to phenology in different wheat growing areas and the meteorological standard of Degree of Crop Frost Damage (QX/T 88-2008. Secondly, a vulnerability curve illustrating the relationship between frost hazard intensity and wheat yield loss was worked out using hybrid fuzzy neural network model. Finally, the wheat frost risk was assessed in China. Results show that our proposed threshold temperatures are more suitable than using 0 °C in revealing the spatial pattern of frost occurrence, and hybrid fuzzy neural network model can further improve the accuracy of the vulnerability curve of wheat subject to frost with limited historical hazard records. Both these advantages ensure the precision of wheat frost risk assessment. In China, frost widely distributes in 85.00% of the total winter wheat planting area, but mainly to the north of 35°N; the southern boundary of wheat frost has moved northward, potentially because of the warming climate. There is a significant trend that suggests high risk areas will enlarge and gradually expand to the south, with the risk levels increasing from a return period of 2 years to 20 years. Among all wheat frost risk levels, the regions with loss rate ranges from 35.00% to 45.00% account for the largest area proportion, ranging from 58.60% to 63.27%. We argue that for wheat and other frost-affected crops, it is

  15. Analysis and Simulation of Hybrid Models for Reaction Networks

    OpenAIRE

    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.

  16. Multi-temporal land use classification using hybrid approach

    Directory of Open Access Journals (Sweden)

    Lakshmi N. Kantakumar

    2015-12-01

    Full Text Available Land use and land cover (LULC classification of a satellite image is one of the prerequisites and plays an indispensable role in many land use inventories and environmental modeling. Many studies viz., forest inventories, hydrology and biodiversity studies, etc., are in demand to account the dynamics of land use and phenology of vegetation. Multi-temporal land use classification accounts the phenology of vegetation and land use dynamics of the study area. In this study, a hybrid classification scheme was developed to prepare a multi-temporal land use classification data set of Sawantwadi taluka of Maharashtra state in India. Parametric classification methods like maximum likelihood and ISODATA clustering methods are combined with the non-parametric decision tree approach to generate the multi-temporal LULC dataset. The accuracy assessment results have shown very promising results with a 93% overall accuracy with a kappa of 0.92.

  17. Dry Port Location Problem: A Hybrid Multi-Criteria Approach

    Directory of Open Access Journals (Sweden)

    BENTALEB Fatimazahra

    2016-03-01

    Full Text Available Choosing a location for a dry port is a problem which becomes more essential and crucial. This study deals with the problem of locating dry ports. On this matter, a model combining multi-criteria (MACBETH and mono-criteria (BARYCENTER methods to find a solution to dry port location problem has been proposed. In the first phase, a systematic literature review was carried out on dry port location problem and then a methodological classification was presented for this research. In the second phase, a hybrid multi-criteria approach was developed in order to determine the best dry port location taking different criteria into account. A Computational practice and a qualitative analysis from a case study in the Moroccan context have been provided. The results show that the optimal location is very convenient with the geographical region and the government policies.

  18. Reduced density matrix hybrid approach: Application to electronic energy transfer

    Energy Technology Data Exchange (ETDEWEB)

    Berkelbach, Timothy C.; Reichman, David R. [Department of Chemistry, Columbia University, 3000 Broadway, New York, New York 10027 (United States); Markland, Thomas E. [Department of Chemistry, Stanford University, 333 Campus Drive, Stanford, California 94305 (United States)

    2012-02-28

    Electronic energy transfer in the condensed phase, such as that occurring in photosynthetic complexes, frequently occurs in regimes where the energy scales of the system and environment are similar. This situation provides a challenge to theoretical investigation since most approaches are accurate only when a certain energetic parameter is small compared to others in the problem. Here we show that in these difficult regimes, the Ehrenfest approach provides a good starting point for a dynamical description of the energy transfer process due to its ability to accurately treat coupling to slow environmental modes. To further improve on the accuracy of the Ehrenfest approach, we use our reduced density matrix hybrid framework to treat the faster environmental modes quantum mechanically, at the level of a perturbative master equation. This combined approach is shown to provide an efficient and quantitative description of electronic energy transfer in a model dimer and the Fenna-Matthews-Olson complex and is used to investigate the effect of environmental preparation on the resulting dynamics.

  19. QCD string model for hybrid adiabatic potentials

    OpenAIRE

    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.

  20. Vehicle height and posture control of the electronic air suspension system using the hybrid system approach

    Science.gov (United States)

    Sun, Xiaoqiang; Cai, Yingfeng; Chen, Long; Liu, Yanling; Wang, Shaohua

    2016-03-01

    The electronic air suspension (EAS) system can improve ride comfort, fuel economy and handling safety of vehicles by adjusting vehicle height. This paper describes the development of a novel controller using the hybrid system approach to adjust the vehicle height (height control) and to regulate the roll and pitch angles of the vehicle body during the height adjustment process (posture control). The vehicle height adjustment system of EAS poses challenging hybrid control problems, since it features different discrete modes of operation, where each mode has an associated linear continuous-time dynamic. In this paper, we propose a novel approach to the modelling and controller design problem for the vehicle height adjustment system of EAS. The system model is described firstly in the hybrid system description language (HYSDEL) to obtain a mixed logical dynamical (MLD) hybrid model. For the resulting model, a hybrid model predictive controller is tuned to improve the vehicle height and posture tracking accuracy and to achieve the on-off statuses direct control of solenoid valves. The effectiveness and performance of the proposed approach are demonstrated by simulations and actual vehicle tests.

  1. 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...

  2. Hybrid attacks on model-based social recommender systems

    Science.gov (United States)

    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.

  3. The innovative concept of three-dimensional hybrid receptor modeling

    Science.gov (United States)

    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.

  4. Agricultural Tractor Selection: A Hybrid and Multi-Attribute Approach

    Directory of Open Access Journals (Sweden)

    Jorge L. García-Alcaraz

    2016-02-01

    Full Text Available Usually, agricultural tractor investments are assessed using traditional economic techniques that only involve financial attributes, resulting in reductionist evaluations. However, tractors have qualitative and quantitative attributes that must be simultaneously integrated into the evaluation process. This article reports a hybrid and multi-attribute approach to assessing a set of agricultural tractors based on AHP-TOPSIS. To identify the attributes in the model, a survey including eighteen attributes was given to agricultural machinery salesmen and farmers for determining their importance. The list of attributes was presented to a decision group for a case of study, and their importance was estimated using AHP and integrated into the TOPSIS technique. In this case, one tractor was selected from a set of six alternatives, integrating six attributes in the model: initial cost, annual maintenance cost, liters of diesel per hour, safety of the operator, maintainability and after-sale customer service offered by the supplier. Based on the results obtained, the model can be considered easy to apply and to have good acceptance among farmers and salesmen, as there are no special software requirements for the application.

  5. A hybrid approach to designing inbound-resupply strategies

    NARCIS (Netherlands)

    Dullaert, Wout; Vernimmen, Bert; Raa, Birger; Witlox, Frank

    A new hybrid approach was developed to determine the optimal inbound-resupply strategy when suppliers ship goods to receivers. The optimal reorder level was calculated on the basis of a simulation of the distribution of demand and the lead time of the various sourcing alternatives. An evolutionary

  6. Modelling the solar wind interaction with Mercury by a quasi-neutral hybrid model

    Directory of Open Access Journals (Sweden)

    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

  7. 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.

  8. Parameter estimation of ion current formulations requires hybrid optimization approach to be both accurate and reliable

    Directory of Open Access Journals (Sweden)

    Axel eLoewe

    2016-01-01

    Full Text Available Computational models of cardiac electrophysiology provided insights into arrhythmogenesis and paved the way towards tailored therapies in the last years. To fully leverage in-silico models in future research, these models need to be adapted to reflect pathologies, genetic alterations, or pharmacological effects, however. A common approach is to leave the structure of established models unaltered and estimate the values of a set of parameters. Today's high-throughput patch clamp data acquisition methods require robust, unsupervised algorithms that estimate parameters both accurate and reliably.In this work, two classes of optimization approaches are evaluated: gradient-based trust-region reflective and derivative-free particle swarm algorithms. Using synthetic input data and different ion current formulations from the Courtemanche et al. electrophysiological model of human atrial myocytes, we show that none of the two schemes alone succeeds to meet all requirements. Sequential combination of the two algorithms did improve the performance to some extent but not satisfactorily. Thus, we propose a novel hybrid approach coupling the two algorithms in each iteration. This hybrid approach yielded very accurate estimates with minimal dependency on the initial guess using synthetic input data for which a ground truth parameter set exists. When applied to measured data, the hybrid approach yielded the best fit, again with minimal variation. Using the proposed algorithm, a single run is sufficient to estimate the parameters. The degree of superiority over the other investigated algorithms in terms of accuracy and robustness depended on the type of current. In contrast to the non-hybrid approaches, the proposed method proved to be optimal for data of arbitrary signal to noise ratio. The hybrid algorithm proposed in this work provides an important tool to integrate experimental data into computational models both accurately and robustly allowing to assess

  9. Understanding the Effect of Statins and Patient Adherence in Atherosclerosis via a Quantitative Systems Pharmacology Model Using a Novel, Hybrid, and Multi-Scale Approach

    Directory of Open Access Journals (Sweden)

    Cesar Pichardo-Almarza

    2017-09-01

    Full Text Available Background and Objective: Statins are one of the most prescribed drugs to treat atherosclerosis. They inhibit the hepatic HMG-CoA reductase, causing a reduction of circulating cholesterol and LDL levels. Statins have had undeniable success; however, the benefits of statin therapy crystallize only if patients adhere to the prescribed treatment, which is far away from reality since adherence decreases with time with around half of patients discontinue statin therapy within the first year. The objective of this work is to; firstly, demonstrate a formal in-silico methodology based on a hybrid, multiscale mathematical model used to study the effect of statin treatment on atherosclerosis under different patient scenarios, including cases where the influence of medication adherence is examined and secondly, to propose a flexible simulation framework that allows extensions or simplifications, allowing the possibility to design other complex simulation strategies, both interesting features for software development.Methods: Different mathematical modeling paradigms are used to present the relevant dynamic behavior observed in biological/physiological data and clinical trials. A combination of continuous and discrete event models are coupled to simulate the pharmacokinetics (PK of statins, their pharmacodynamic (PD effect on lipoproteins levels (e.g., LDL and relevant inflammatory pathways whilst simultaneously studying the dynamic effect of flow-related variables on atherosclerosis progression.Results: Different scenarios were tested showing the impact of: (1 patient variability: a virtual population shows differences in plaque growth for different individuals could be as high as 100%; (2 statin effect on atherosclerosis: it is shown how a patient with a 1-year statin treatment will reduce his plaque growth by 2–3% in a 2-year period; (3 medical adherence: we show that a patient missing 10% of the total number of doses could increase the plaque growth

  10. Solving University Scheduling Problem Using Hybrid Approach

    Directory of Open Access Journals (Sweden)

    Aftab Ahmed Shaikh

    2011-10-01

    Full Text Available In universities scheduling curriculum activity is an essential job. Primarily, scheduling is a distribution of limited resources under interrelated constraints. The set of hard constraints demand the highest priority and should not to be violated at any cost, while the maximum soft constraints satisfaction mounts the quality scale of solution. In this research paper, a novel bisected approach is introduced that is comprisesd of GA (Genetic Algorithm as well as Backtracking Recursive Search. The employed technique deals with both hard and soft constraints successively. The first phase decisively is focused over elimination of all the hard constraints bounded violations and eventually produces partial solution for subsequent step. The second phase is supposed to draw the best possible solution on the search space. Promising results are obtained by implementation on the real dataset. The key points of the research approach are to get assurance of hard constraints removal from the dataset and minimizing computational time for GA by initializing pre-processed set of chromosomes.

  11. 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.

  12. A hybrid least squares support vector machines and GMDH approach for river flow forecasting

    Science.gov (United States)

    Samsudin, R.; Saad, P.; Shabri, A.

    2010-06-01

    This paper proposes a novel hybrid forecasting model, which combines the group method of data handling (GMDH) and the least squares support vector machine (LSSVM), known as GLSSVM. The GMDH is used to determine the useful input variables for LSSVM model and the LSSVM model which works as time series forecasting. In this study the application of GLSSVM for monthly river flow forecasting of Selangor and Bernam River are investigated. The results of the proposed GLSSVM approach are compared with the conventional artificial neural network (ANN) models, Autoregressive Integrated Moving Average (ARIMA) model, GMDH and LSSVM models using the long term observations of monthly river flow discharge. The standard statistical, the root mean square error (RMSE) and coefficient of correlation (R) are employed to evaluate the performance of various models developed. Experiment result indicates that the hybrid model was powerful tools to model discharge time series and can be applied successfully in complex hydrological modeling.

  13. A hybrid approach to decision making and information fusion: Combining humans and artificial agents

    NARCIS (Netherlands)

    Groen, F.C.A.; Pavlin, G.; Winterboer, A.; Evers, V.

    This paper argues that hybrid human–agent systems can support powerful solutions to relevant problems such as Environmental Crisis management. However, it shows that such solutions require comprehensive approaches covering different aspects of data processing, model construction and the usage. In

  14. Day-Ahead Wind Power Forecasting Using a Two-Stage Hybrid Modeling Approach Based on SCADA and Meteorological Information, and Evaluating the Impact of Input-Data Dependency on Forecasting Accuracy

    Directory of Open Access Journals (Sweden)

    Dehua Zheng

    2017-12-01

    Full Text Available The power generated by wind generators is usually associated with uncertainties, due to the intermittency of wind speed and other weather variables. This creates a big challenge for transmission system operators (TSOs and distribution system operators (DSOs in terms of connecting, controlling and managing power networks with high-penetration wind energy. Hence, in these power networks, accurate wind power forecasts are essential for their reliable and efficient operation. They support TSOs and DSOs in enhancing the control and management of the power network. In this paper, a novel two-stage hybrid approach based on the combination of the Hilbert-Huang transform (HHT, genetic algorithm (GA and artificial neural network (ANN is proposed for day-ahead wind power forecasting. The approach is composed of two stages. The first stage utilizes numerical weather prediction (NWP meteorological information to predict wind speed at the exact site of the wind farm. The second stage maps actual wind speed vs. power characteristics recorded by SCADA. Then, the wind speed forecast in the first stage for the future day is fed to the second stage to predict the future day’s wind power. Comparative selection of input-data parameter sets for the forecasting model and impact analysis of input-data dependency on forecasting accuracy have also been studied. The proposed approach achieves significant forecasting accuracy improvement compared with three other artificial intelligence-based forecasting approaches and a benchmark model using the smart persistence method.

  15. A hybrid computational model for phagocyte transmigration

    OpenAIRE

    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...

  16. 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.

  17. ANN Approach for State Estimation of Hybrid Systems and Its Experimental Validation

    Directory of Open Access Journals (Sweden)

    Shijoh Vellayikot

    2015-01-01

    Full Text Available A novel artificial neural network based state estimator has been proposed to ensure the robustness in the state estimation of autonomous switching hybrid systems under various uncertainties. Taking the autonomous switching three-tank system as benchmark hybrid model working under various additive and multiplicative uncertainties such as process noise, measurement error, process–model parameter variation, initial state mismatch, and hand valve faults, real-time performance evaluation by the comparison of it with other state estimators such as extended Kalman filter and unscented Kalman Filter was carried out. The experimental results reported with the proposed approach show considerable improvement in the robustness in performance under the considered uncertainties.

  18. Parametric Linear Hybrid Automata for Complex Environmental Systems Modeling

    Directory of Open Access Journals (Sweden)

    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

  19. Application of soft computing based hybrid models in hydrological variables modeling: a comprehensive review

    Science.gov (United States)

    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.

  20. Hybrid ablation for atrial fibrillation: current approaches and future directions.

    Science.gov (United States)

    Bisleri, Gianluigi; Glover, Benedict

    2017-01-01

    Catheter ablation of atrial fibrillation has rapidly evolved during the past decade: although the treatment of paroxysmal atrial fibrillation via a transcatheter approach has been consistently successful, persistent and long-standing atrial fibrillation still represents a major clinical challenge with less favorable outcomes to date. Because novel, minimally invasive surgical approaches have been developed for atrial fibrillation ablation, the aim of the present review is to analyze the current evidence surrounding the integration of surgical and transcatheter strategies in a hybrid fashion for the treatment of atrial fibrillation. Long-standing persistent, atrial fibrillation requires further understanding. Wide antral circumferential ablation of the pulmonary veins represents the cornerstone of any ablation therapy. Additional linear lesions and/or targeting complex fractionated atrial electrograms may also be considered. One of the limitations is achieving a transmural lesion. The combined endocardial and epicardial approach may represent a superior approach. Hybrid ablation of atrial fibrillation represents a novel therapeutic strategy for the treatment of complex scenarios, such as long-standing persistent atrial fibrillation. A specialized team including dedicated surgeons and cardiologists appears to be crucial in order to achieve durable and satisfactory outcomes following hybrid ablation of atrial fibrillation.

  1. 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...

  2. Comments On Clock Models In Hybrid Automata And Hybrid Control Systems

    OpenAIRE

    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.

  3. Green material selection for sustainability: A hybrid MCDM approach

    Science.gov (United States)

    Zhang, Honghao; Peng, Yong; Tian, Guangdong; Wang, Danqi; Xie, Pengpeng

    2017-01-01

    Green material selection is a crucial step for the material industry to comprehensively improve material properties and promote sustainable development. However, because of the subjectivity and conflicting evaluation criteria in its process, green material selection, as a multi-criteria decision making (MCDM) problem, has been a widespread concern to the relevant experts. Thus, this study proposes a hybrid MCDM approach that combines decision making and evaluation laboratory (DEMATEL), analytical network process (ANP), grey relational analysis (GRA) and technique for order performance by similarity to ideal solution (TOPSIS) to select the optimal green material for sustainability based on the product's needs. A nonlinear programming model with constraints was proposed to obtain the integrated closeness index. Subsequently, an empirical application of rubbish bins was used to illustrate the proposed method. In addition, a sensitivity analysis and a comparison with existing methods were employed to validate the accuracy and stability of the obtained final results. We found that this method provides a more accurate and effective decision support tool for alternative evaluation or strategy selection. PMID:28498864

  4. Green material selection for sustainability: A hybrid MCDM approach.

    Science.gov (United States)

    Zhang, Honghao; Peng, Yong; Tian, Guangdong; Wang, Danqi; Xie, Pengpeng

    2017-01-01

    Green material selection is a crucial step for the material industry to comprehensively improve material properties and promote sustainable development. However, because of the subjectivity and conflicting evaluation criteria in its process, green material selection, as a multi-criteria decision making (MCDM) problem, has been a widespread concern to the relevant experts. Thus, this study proposes a hybrid MCDM approach that combines decision making and evaluation laboratory (DEMATEL), analytical network process (ANP), grey relational analysis (GRA) and technique for order performance by similarity to ideal solution (TOPSIS) to select the optimal green material for sustainability based on the product's needs. A nonlinear programming model with constraints was proposed to obtain the integrated closeness index. Subsequently, an empirical application of rubbish bins was used to illustrate the proposed method. In addition, a sensitivity analysis and a comparison with existing methods were employed to validate the accuracy and stability of the obtained final results. We found that this method provides a more accurate and effective decision support tool for alternative evaluation or strategy selection.

  5. Towards a Hybrid Approach to Context Reasoning for Underwater Robots

    Directory of Open Access Journals (Sweden)

    Xin Li

    2017-02-01

    Full Text Available Ontologies have been widely used to facilitate semantic interoperability and serve as a common information model in many applications or domains. The Smart and Networking Underwater Robots in Cooperation Meshes (SWARMs project, aiming to facilitate coordination and cooperation between heterogeneous underwater vehicles, also adopts ontologies to formalize information that is necessarily exchanged between vehicles. However, how to derive more useful contexts based on ontologies still remains a challenge. In particular, the extreme nature of the underwater environment introduces uncertainties in context data, thus imposing more difficulties in context reasoning. None of the existing context reasoning methods could individually deal with all intricacies in the underwater robot field. To this end, this paper presents the first proposal applying a hybrid context reasoning mechanism that includes ontological, rule-based, and Multi-Entity Bayesian Network (MEBN reasoning methods to reason about contexts and their uncertainties in the underwater robot field. The theoretical foundation of applying this reasoning mechanism in underwater robots is given by a case study on the oil spill monitoring. The simulated reasoning results are useful for further decision-making by operators or robots and they show that the consolidation of different reasoning methods is a promising approach for context reasoning in underwater robots.

  6. Clustering based hybrid approach for facility location problem

    Directory of Open Access Journals (Sweden)

    Ashish Sharma

    2017-12-01

    Full Text Available The main objective of facility location problem is the utilization of the facility by maximum number of possible customers so that the profit is maximized. For instance, in some services like wireless sensor networks, Wi-Fi, repeaters, etc., where the service area is limited, some specific equipment is installed in such a way that it could be used by maximum number of users. Here, the number of users for a particular facility is optimized with the help of clustering technique. The study develops a model for facility allocation problem. For the solution algorithm, a hybrid approach which is based on clustering and mixed integer linear programming (MILP is proposed. The proposed method consists of two parts where in the first part, the K-means clustering technique is used and in the second part, for each cluster an MILP technique is implemented so that the facility which yields the maximum profit is obtained. Numerical examples for clustering and without clustering are presented. Analysis shows that due to clustering the average distance between facility and customer is significantly reduced.

  7. Design of Xen Hybrid Multiple Police Model

    Science.gov (United States)

    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.

  8. A hybrid approach to simulate multiple photon scattering in X-ray imaging

    Energy Technology Data Exchange (ETDEWEB)

    Freud, N. [CNDRI, Laboratory of Nondestructive Testing using Ionizing Radiations, INSA-Lyon Scientific and Technical University, Bat. Antoine de Saint-Exupery, 20, avenue Albert Einstein, 69621 Villeurbanne Cedex (France)]. E-mail: nicolas.freud@insa-lyon.fr; Letang, J.-M. [CNDRI, Laboratory of Nondestructive Testing using Ionizing Radiations, INSA-Lyon Scientific and Technical University, Bat. Antoine de Saint-Exupery, 20, avenue Albert Einstein, 69621 Villeurbanne Cedex (France); Babot, D. [CNDRI, Laboratory of Nondestructive Testing using Ionizing Radiations, INSA-Lyon Scientific and Technical University, Bat. Antoine de Saint-Exupery, 20, avenue Albert Einstein, 69621 Villeurbanne Cedex (France)

    2005-01-01

    A hybrid simulation approach is proposed to compute the contribution of scattered radiation in X- or {gamma}-ray imaging. This approach takes advantage of the complementarity between the deterministic and probabilistic simulation methods. The proposed hybrid method consists of two stages. Firstly, a set of scattering events occurring in the inspected object is determined by means of classical Monte Carlo simulation. Secondly, this set of scattering events is used as a starting point to compute the energy imparted to the detector, with a deterministic algorithm based on a 'forced detection' scheme. For each scattering event, the probability for the scattered photon to reach each pixel of the detector is calculated using well-known physical models (form factor and incoherent scattering function approximations, in the case of Rayleigh and Compton scattering respectively). The results of the proposed hybrid approach are compared to those obtained with the Monte Carlo method alone (Geant4 code) and found to be in excellent agreement. The convergence of the results when the number of scattering events increases is studied. The proposed hybrid approach makes it possible to simulate the contribution of each type (Compton or Rayleigh) and order of scattering, separately or together, with a single PC, within reasonable computation times (from minutes to hours, depending on the number of pixels of the detector). This constitutes a substantial benefit, compared to classical simulation methods (Monte Carlo or deterministic approaches), which usually requires a parallel computing architecture to obtain comparable results.

  9. A novel hybridization approach for detection of citrus viroids.

    Science.gov (United States)

    Murcia, N; Serra, P; Olmos, A; Duran-Vila, N

    2009-04-01

    Citrus plants are natural hosts of several viroid species all belonging to the family Pospiviroidae. Previous attempts to detect viroids from field-grown species and cultivars yielded erratic results unless analyses were performed using Etrog citron a secondary bio-amplification host. To overcome the use of Etrog citron a number of RT-PCR approaches have been proposed with different degrees of success. Here we report the suitability of an easy to handle northern hybridization protocol for viroid detection of samples collected from field-grown citrus species and cultivars. The protocol involves: (i) Nucleic acid preparations from bark tissue samples collected from field-grown trees regardless of the growing season and storage conditions; (ii) Separation in 5% PAGE or 1% agarose, blotting to membrane and fixing; (iii) Hybridization with viroid-specific DIG-labelled probes and detection with anti-DIG-alkaline phosphatase conjugate and autoradiography with the CSPD substrate. The method has been tested with viroid-infected trees of sweet orange, lemon, mandarin, grapefruit, sour orange, Swingle citrumello, Tahiti lime and Mexican lime. This novel hybridization approach is extremely sensitive, easy to handle and shortens the time needed for reliable viroid indexing tests. The suitability of PCR generated DIG-labelled probes and the sensitivity achieved when the samples are separated and blotted from non-denaturing gels are discussed.

  10. Hybrid quantum-classical modeling of quantum dot devices

    Science.gov (United States)

    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.

  11. A hybrid approach to near-optimal launch vehicle guidance

    Science.gov (United States)

    Leung, Martin S. K.; Calise, Anthony J.

    1992-01-01

    This paper evaluates a proposed hybrid analytical/numerical approach to launch-vehicle guidance for ascent to orbit injection. The feedback-guidance approach is based on a piecewise nearly analytic zero-order solution evaluated using a collocation method. The zero-order solution is then improved through a regular perturbation analysis, wherein the neglected dynamics are corrected in the first-order term. For real-time implementation, the guidance approach requires solving a set of small dimension nonlinear algebraic equations and performing quadrature. Assessment of performance and reliability are carried out through closed-loop simulation for a vertically launched 2-stage heavy-lift capacity vehicle to a low earth orbit. The solutions are compared with optimal solutions generated from a multiple shooting code. In the example the guidance approach delivers over 99.9 percent of optimal performance and terminal constraint accuracy.

  12. A hybrid model for opinion formation

    Science.gov (United States)

    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.

  13. 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.

  14. 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.

  15. Hybrid Modeling Method for a DEP Based Particle Manipulation

    Directory of Open Access Journals (Sweden)

    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.

  16. Hybrid modeling method for a DEP based particle manipulation.

    Science.gov (United States)

    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.

  17. A hybrid model of mammalian cell cycle regulation.

    Directory of Open Access Journals (Sweden)

    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.

  18. 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)

  19. A hybrid approach for efficient anomaly detection using metaheuristic methods

    Science.gov (United States)

    Ghanem, Tamer F.; Elkilani, Wail S.; Abdul-kader, Hatem M.

    2014-01-01

    Network intrusion detection based on anomaly detection techniques has a significant role in protecting networks and systems against harmful activities. Different metaheuristic techniques have been used for anomaly detector generation. Yet, reported literature has not studied the use of the multi-start metaheuristic method for detector generation. This paper proposes a hybrid approach for anomaly detection in large scale datasets using detectors generated based on multi-start metaheuristic method and genetic algorithms. The proposed approach has taken some inspiration of negative selection-based detector generation. The evaluation of this approach is performed using NSL-KDD dataset which is a modified version of the widely used KDD CUP 99 dataset. The results show its effectiveness in generating a suitable number of detectors with an accuracy of 96.1% compared to other competitors of machine learning algorithms. PMID:26199752

  20. A hybrid approach for efficient anomaly detection using metaheuristic methods

    Directory of Open Access Journals (Sweden)

    Tamer F. Ghanem

    2015-07-01

    Full Text Available Network intrusion detection based on anomaly detection techniques has a significant role in protecting networks and systems against harmful activities. Different metaheuristic techniques have been used for anomaly detector generation. Yet, reported literature has not studied the use of the multi-start metaheuristic method for detector generation. This paper proposes a hybrid approach for anomaly detection in large scale datasets using detectors generated based on multi-start metaheuristic method and genetic algorithms. The proposed approach has taken some inspiration of negative selection-based detector generation. The evaluation of this approach is performed using NSL-KDD dataset which is a modified version of the widely used KDD CUP 99 dataset. The results show its effectiveness in generating a suitable number of detectors with an accuracy of 96.1% compared to other competitors of machine learning algorithms.

  1. A hybrid approach for efficient anomaly detection using metaheuristic methods.

    Science.gov (United States)

    Ghanem, Tamer F; Elkilani, Wail S; Abdul-Kader, Hatem M

    2015-07-01

    Network intrusion detection based on anomaly detection techniques has a significant role in protecting networks and systems against harmful activities. Different metaheuristic techniques have been used for anomaly detector generation. Yet, reported literature has not studied the use of the multi-start metaheuristic method for detector generation. This paper proposes a hybrid approach for anomaly detection in large scale datasets using detectors generated based on multi-start metaheuristic method and genetic algorithms. The proposed approach has taken some inspiration of negative selection-based detector generation. The evaluation of this approach is performed using NSL-KDD dataset which is a modified version of the widely used KDD CUP 99 dataset. The results show its effectiveness in generating a suitable number of detectors with an accuracy of 96.1% compared to other competitors of machine learning algorithms.

  2. Approaches to Low Fuel Regression Rate in Hybrid Rocket Engines

    Directory of Open Access Journals (Sweden)

    Dario Pastrone

    2012-01-01

    Full Text Available Hybrid rocket engines are promising propulsion systems which present appealing features such as safety, low cost, and environmental friendliness. On the other hand, certain issues hamper the development hoped for. The present paper discusses approaches addressing improvements to one of the most important among these issues: low fuel regression rate. To highlight the consequence of such an issue and to better understand the concepts proposed, fundamentals are summarized. Two approaches are presented (multiport grain and high mixture ratio which aim at reducing negative effects without enhancing regression rate. Furthermore, fuel material changes and nonconventional geometries of grain and/or injector are presented as methods to increase fuel regression rate. Although most of these approaches are still at the laboratory or concept scale, many of them are promising.

  3. Recent advances on hybrid approaches for designing intelligent systems

    CERN Document Server

    Melin, Patricia; Pedrycz, Witold; Kacprzyk, Janusz

    2014-01-01

    This book describes recent advances on hybrid intelligent systems using soft computing techniques for diverse areas of application, such as intelligent control and robotics, pattern recognition, time series prediction and optimization complex problems. Soft Computing (SC) consists of several intelligent computing paradigms, including fuzzy logic, neural networks, and bio-inspired optimization algorithms, which can be used to produce powerful hybrid intelligent systems. The book is organized in five main parts, which contain a group of papers around a similar subject. The first part consists of papers with the main theme of type-2 fuzzy logic, which basically consists of papers that propose new models and applications for type-2 fuzzy systems. The second part contains papers with the main theme of bio-inspired optimization algorithms, which are basically papers using nature-inspired techniques to achieve optimization of complex optimization problems in diverse areas of application. The third part contains pape...

  4. A hybrid approach for minimizing makespan in permutation flowshop scheduling

    DEFF Research Database (Denmark)

    Govindan, Kannan; Balasundaram, R.; Baskar, N.

    2017-01-01

    This work proposes a hybrid approach for solving traditional flowshop scheduling problems to reduce the makespan (total completion time). To solve scheduling problems, a combination of Decision Tree (DT) and Scatter Search (SS) algorithms are used. Initially, the DT is used to generate a seed...... solution which is then given input to the SS to obtain optimal / near optimal solutions of makespan. The DT used the entropy function to convert the given problem into a tree structured format / set of rules. The SS provides an extensive investigation of the search space through diversification...

  5. Integrated approach for fusion multi-physics coupled analyses based on hybrid CAD and mesh geometries

    Energy Technology Data Exchange (ETDEWEB)

    Qiu, Yuefeng, E-mail: yuefeng.qiu@kit.edu; Lu, Lei; Fischer, Ulrich

    2015-10-15

    Highlights: • Integrated approach for neutronics, thermal and structural analyses was developed. • MCNP5/6, TRIPOLI-4 were coupled with CFX, Fluent and ANSYS Workbench. • A novel meshing approach has been proposed for describing MC geometry. - Abstract: Coupled multi-physics analyses on fusion reactor devices require high-fidelity neutronic models, and flexible, accurate data exchanging between various calculation codes. An integrated coupling approach has been developed to enable the conversion of CAD, mesh, or hybrid geometries for Monte Carlo (MC) codes MCNP5/6, TRIPOLI-4, and translation of nuclear heating data for CFD codes Fluent, CFX and structural mechanical software ANSYS Workbench. The coupling approach has been implemented based on SALOME platform with CAD modeling, mesh generation and data visualization capabilities. A novel meshing approach has been developed for generating suitable meshes for MC geometry descriptions. The coupling approach has been concluded to be reliable and efficient after verification calculations of several application cases.

  6. Does the acceptance of hybrid learning affect learning approaches in France?

    Directory of Open Access Journals (Sweden)

    Lionel Di Marco

    2017-10-01

    Full Text Available Purpose Acceptance of a learning technology affects students’ intention to use that technology, but the influence of the acceptance of a learning technology on learning approaches has not been investigated in the literature. A deep learning approach is important in the field of health, where links must be created between skills, knowledge, and habits. Our hypothesis was that acceptance of a hybrid learning model would affect students’ way of learning. Methods We analysed these concepts, and their correlations, in the context of a flipped classroom method using a local learning management system. In a sample of all students within a single year of study in the midwifery program (n= 38, we used 3 validated scales to evaluate these concepts (the Study Process Questionnaire, My Intellectual Work Tools, and the Hybrid E-Learning Acceptance Model: Learner Perceptions. Results Our sample had a positive acceptance of the learning model, but a neutral intention to use it. Students reported that they were distractible during distance learning. They presented a better mean score for the deep approach than for the superficial approach (P< 0.001, which is consistent with their declared learning strategies (personal reorganization of information; search and use of examples. There was no correlation between poor acceptance of the learning model and inadequate learning approaches. The strategy of using deep learning techniques was moderately correlated with acceptance of the learning model (rs= 0.42, P= 0.03. Conclusion Learning approaches were not affected by acceptance of a hybrid learning model, due to the flexibility of the tool. However, we identified problems in the students’ time utilization, which explains their neutral intention to use the system.

  7. Multiscale Modeling of Graphite/CNT/Epoxy Hybrid Composites

    Science.gov (United States)

    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

  8. Pseudospectral Model for Hybrid PIC Hall-effect Thruster Simulation

    Science.gov (United States)

    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

  9. 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

  10. A Low Cost, Hybrid Approach to Data Mining Project

    Data.gov (United States)

    National Aeronautics and Space Administration — The proposed effort will combine a low cost physical modeling approach with inductive, data-centered modeling in an aerosopace relevant context to demonstrate...

  11. Rapid Deployment of Optimal Control for Building HVAC Systems using Innovative Software Tools and a Hybrid Heuristic/Model Based Control Approach

    Science.gov (United States)

    2017-03-21

    35 4.2.2 System Economics ...Environmental, Energy, and Economic Performance,” which built on EO 13423 by adding specific target language. In the area of building performance, the goal was...of existing HVAC equipment. Energy saving performance could be improved by expanding the BrightBox approach (for customers where it makes economic

  12. Hybrid modelling of a sugar boiling process

    CERN Document Server

    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...

  13. New MPPT algorithm for PV applications based on hybrid dynamical approach

    KAUST Repository

    Elmetennani, Shahrazed

    2016-10-24

    This paper proposes a new Maximum Power Point Tracking (MPPT) algorithm for photovoltaic applications using the multicellular converter as a stage of power adaptation. The proposed MPPT technique has been designed using a hybrid dynamical approach to model the photovoltaic generator. The hybrid dynamical theory has been applied taking advantage of the particular topology of the multicellular converter. Then, a hybrid automata has been established to optimize the power production. The maximization of the produced solar energy is achieved by switching between the different operative modes of the hybrid automata, which is conditioned by some invariance and transition conditions. These conditions have been validated by simulation tests under different conditions of temperature and irradiance. Moreover, the performance of the proposed algorithm has been then evaluated by comparison with standard MPPT techniques numerically and by experimental tests under varying external working conditions. The results have shown the interesting features that the hybrid MPPT technique presents in terms of performance and simplicity for real time implementation.

  14. 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.

  15. 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...

  16. HYBRID2: A versatile model of the performance of hybrid power systems

    Science.gov (United States)

    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.

  17. Hybrid Dynamical Systems Modeling, Stability, and Robustness

    CERN Document Server

    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

  18. Hybrid App Approach: Could It Mark the End of Native App Domination?

    OpenAIRE

    Minh Q. Huynh; Prashant Ghimire; Donny Truong

    2017-01-01

    Aim/Purpose: Despite millions of apps on the market, it is still challenging to develop a mobile app that can run across platforms using the same code. Background: This paper explores a potential solution for developing cross platform apps by presenting the hybrid app approach. Methodology: The paper first describes a brief evolution of the different mobile app development approaches and then compares them with the hybrid app approach. Next, it focuses on one specific hybrid app de...

  19. An FEM-Based State Estimation Approach to Nonlinear Hybrid Positioning Systems

    Directory of Open Access Journals (Sweden)

    Yu-Xin Zhao

    2013-01-01

    Full Text Available For hybrid positioning systems (HPSs, the estimator design is a crucial and important problem. In this paper, a finite-element-method- (FEM- based state estimation approach is proposed to HPS. As the weak solution of hybrid stochastic differential model is denoted by the Kolmogorov's forward equation, this paper constructs its interpolating point through the classical fourth-order Runge-Kutta method. Then, it approaches the solution with biquadratic interpolation function to obtain a prior probability density function of the state. A posterior probability density function is gained through Bayesian formula finally. In theory, the proposed scheme has more advantages in the performance of complexity and convergence for low-dimensional systems. By taking an illustrative example, numerical experiment results show that the new state estimator is feasible and has good performance than PF and UKF.

  20. Hybrid Approach to State Estimation for Bioprocess Control.

    Science.gov (United States)

    Simutis, Rimvydas; Lübbert, Andreas

    2017-03-08

    An improved state estimation technique for bioprocess control applications is proposed where a hybrid version of the Unscented Kalman Filter (UKF) is employed. The underlying dynamic system model is formulated as a conventional system of ordinary differential equations based on the mass balances of the state variables biomass, substrate, and product, while the observation model, describing the less established relationship between the state variables and the measurement quantities, is formulated in a data driven way. The latter is formulated by means of a support vector regression (SVR) model. The UKF is applied to a recombinant therapeutic protein production process using Escherichia coli bacteria. Additionally, the state vector was extended by the specific biomass growth rate µ in order to allow for the estimation of this key variable which is crucial for the implementation of innovative control algorithms in recombinant therapeutic protein production processes. The state estimates depict a sufficiently low noise level which goes perfectly with different advanced bioprocess control applications.

  1. A hybrid neural network model for noisy data regression.

    Science.gov (United States)

    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.

  2. 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

  3. 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 ...

  4. 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...

  5. Hybrid x-space: a new approach for MPI reconstruction.

    Science.gov (United States)

    Tateo, A; Iurino, A; Settanni, G; Andrisani, A; Stifanelli, P F; Larizza, P; Mazzia, F; Mininni, R M; Tangaro, S; Bellotti, R

    2016-06-07

    Magnetic particle imaging (MPI) is a new medical imaging technique capable of recovering the distribution of superparamagnetic particles from their measured induced signals. In literature there are two main MPI reconstruction techniques: measurement-based (MB) and x-space (XS). The MB method is expensive because it requires a long calibration procedure as well as a reconstruction phase that can be numerically costly. On the other side, the XS method is simpler than MB but the exact knowledge of the field free point (FFP) motion is essential for its implementation. Our simulation work focuses on the implementation of a new approach for MPI reconstruction: it is called hybrid x-space (HXS), representing a combination of the previous methods. Specifically, our approach is based on XS reconstruction because it requires the knowledge of the FFP position and velocity at each time instant. The difference with respect to the original XS formulation is how the FFP velocity is computed: we estimate it from the experimental measurements of the calibration scans, typical of the MB approach. Moreover, a compressive sensing technique is applied in order to reduce the calibration time, setting a fewer number of sampling positions. Simulations highlight that HXS and XS methods give similar results. Furthermore, an appropriate use of compressive sensing is crucial for obtaining a good balance between time reduction and reconstructed image quality. Our proposal is suitable for open geometry configurations of human size devices, where incidental factors could make the currents, the fields and the FFP trajectory irregular.

  6. A hybrid beach morphology model applied to a high energy sandy beach

    NARCIS (Netherlands)

    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

  7. Mechanical Properties of Graphene Nanoplatelet/Carbon Fiber/Epoxy Hybrid Composites: Multiscale Modeling and Experiments

    Science.gov (United States)

    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.

  8. Mechanical Properties of Graphene Nanoplatelet Carbon Fiber Epoxy Hybrid Composites: Multiscale Modeling and Experiments

    Science.gov (United States)

    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.

  9. Design, analysis and modeling of a novel hybrid powertrain system based on hybridized automated manual transmission

    Science.gov (United States)

    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.

  10. Modélisation du procédé de soudage hybride Arc / Laser par une approche level set application aux toles d'aciers de fortes épaisseurs A level-set approach for the modelling of hybrid arc/laser welding process application for high thickness steel sheets joining

    Directory of Open Access Journals (Sweden)

    Desmaison Olivier

    2013-11-01

    Full Text Available Le procédé de soudage hybride Arc/Laser est une solution aux assemblages difficiles de tôles de fortes épaisseurs. Ce procédé innovant associe deux sources de chaleur : un arc électrique produit par une torche MIG et une source laser placée en amont. Ce couplage améliore le rendement du procédé, la qualité du cordon et les déformations finales. La modélisation de ce procédé par une approche Level Set permet une prédiction du développement du cordon et du champ de température associé. La simulation du soudage multi-passes d'une nuance d'acier 18MnNiMo5 est présentée ici et les résultats sont comparés aux observations expérimentales. The hybrid arc/laser welding process has been developed in order to overcome the difficulties encountered for joining high thickness steel sheets. This innovative process gathers two heat sources: an arc source developed by a MIG torch and a pre-located laser source. This coupling improves the efficiency of the process, the weld bead quality and the final deformations. The Level-Set approach for the modelling of this process enables the prediction of the weld bead development and the temperature field evolution. The simulation of the multi-passes welding of a 18MnNiMo5 steel grade is detailed and the results are compared to the experimental observations.

  11. 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...

  12. Deducing hybrid performance from parental metabolic profiles of young primary roots of maize by using a multivariate diallel approach.

    Science.gov (United States)

    Feher, Kristen; Lisec, Jan; Römisch-Margl, Lilla; Selbig, Joachim; Gierl, Alfons; Piepho, Hans-Peter; Nikoloski, Zoran; Willmitzer, Lothar

    2014-01-01

    Heterosis, the greater vigor of hybrids compared to their parents, has been exploited in maize breeding for more than 100 years to produce ever better performing elite hybrids of increased yield. Despite extensive research, the underlying mechanisms shaping the extent of heterosis are not well understood, rendering the process of selecting an optimal set of parental lines tedious. This study is based on a dataset consisting of 112 metabolite levels in young roots of four parental maize inbred lines and their corresponding twelve hybrids, along with the roots' biomass as a heterotic trait. Because the parental biomass is a poor predictor for hybrid biomass, we established a model framework to deduce the biomass of the hybrid from metabolite profiles of its parental lines. In the proposed framework, the hybrid metabolite levels are expressed relative to the parental levels by incorporating the standard concept of additivity/dominance, which we name the Combined Relative Level (CRL). Our modeling strategy includes a feature selection step on the parental levels which are demonstrated to be predictive of CRL across many hybrid metabolites. We demonstrate that these selected parental metabolites are further predictive of hybrid biomass. Our approach directly employs the diallel structure in a multivariate fashion, whereby we attempt to not only predict macroscopic phenotype (biomass), but also molecular phenotype (metabolite profiles). Therefore, our study provides the first steps for further investigations of the genetic determinants to metabolism and, ultimately, growth. Finally, our success on the small-scale experiments implies a valid strategy for large-scale experiments, where parental metabolite profiles may be used together with profiles of selected hybrids as a training set to predict biomass of all possible hybrids.

  13. Deducing hybrid performance from parental metabolic profiles of young primary roots of maize by using a multivariate diallel approach.

    Directory of Open Access Journals (Sweden)

    Kristen Feher

    Full Text Available Heterosis, the greater vigor of hybrids compared to their parents, has been exploited in maize breeding for more than 100 years to produce ever better performing elite hybrids of increased yield. Despite extensive research, the underlying mechanisms shaping the extent of heterosis are not well understood, rendering the process of selecting an optimal set of parental lines tedious. This study is based on a dataset consisting of 112 metabolite levels in young roots of four parental maize inbred lines and their corresponding twelve hybrids, along with the roots' biomass as a heterotic trait. Because the parental biomass is a poor predictor for hybrid biomass, we established a model framework to deduce the biomass of the hybrid from metabolite profiles of its parental lines. In the proposed framework, the hybrid metabolite levels are expressed relative to the parental levels by incorporating the standard concept of additivity/dominance, which we name the Combined Relative Level (CRL. Our modeling strategy includes a feature selection step on the parental levels which are demonstrated to be predictive of CRL across many hybrid metabolites. We demonstrate that these selected parental metabolites are further predictive of hybrid biomass. Our approach directly employs the diallel structure in a multivariate fashion, whereby we attempt to not only predict macroscopic phenotype (biomass, but also molecular phenotype (metabolite profiles. Therefore, our study provides the first steps for further investigations of the genetic determinants to metabolism and, ultimately, growth. Finally, our success on the small-scale experiments implies a valid strategy for large-scale experiments, where parental metabolite profiles may be used together with profiles of selected hybrids as a training set to predict biomass of all possible hybrids.

  14. The hybrid thermography approach applied to architectural structures

    Science.gov (United States)

    Sfarra, S.; Ambrosini, D.; Paoletti, D.; Nardi, I.; Pasqualoni, G.

    2017-07-01

    This work contains an overview of infrared thermography (IRT) method and its applications relating to the investigation of architectural structures. In this method, the passive approach is usually used in civil engineering, since it provides a panoramic view of the thermal anomalies to be interpreted also thanks to the use of photographs focused on the region of interest (ROI). The active approach, is more suitable for laboratory or indoor inspections, as well as for objects having a small size. The external stress to be applied is thermal, coming from non-natural apparatus such as lamps or hot / cold air jets. In addition, the latter permits to obtain quantitative information related to defects not detectable to the naked eyes. Very recently, the hybrid thermography (HIRT) approach has been introduced to the attention of the scientific panorama. It can be applied when the radiation coming from the sun, directly arrives (i.e., possibly without the shadow cast effect) on a surface exposed to the air. A large number of thermograms must be collected and a post-processing analysis is subsequently applied via advanced algorithms. Therefore, an appraisal of the defect depth can be obtained passing through the calculation of the combined thermal diffusivity of the materials above the defect. The approach is validated herein by working, in a first stage, on a mosaic sample having known defects while, in a second stage, on a Church built in L'Aquila (Italy) and covered with a particular masonry structure called apparecchio aquilano. The results obtained appear promising.

  15. A novel approach identifying hybrid sterility QTL on the autosomes of Drosophila simulans and D. mauritiana.

    Science.gov (United States)

    Dickman, Christopher T D; Moehring, Amanda J

    2013-01-01

    When species interbreed, the hybrid offspring that are produced are often sterile. If only one hybrid sex is sterile, it is almost always the heterogametic (XY or ZW) sex. Taking this trend into account, the predominant model used to explain the genetic basis of F1 sterility involves a deleterious interaction between recessive sex-linked loci from one species and dominant autosomal loci from the other species. This model is difficult to evaluate, however, as only a handful of loci influencing interspecies hybrid sterility have been identified, and their autosomal genetic interactors have remained elusive. One hindrance to their identification has been the overwhelming effect of the sex chromosome in mapping studies, which could 'mask' the ability to accurately map autosomal factors. Here, we use a novel approach employing attached-X chromosomes to create reciprocal backcross interspecies hybrid males that have a non-recombinant sex chromosome and recombinant autosomes. The heritable variation in phenotype is thus solely caused by differences in the autosomes, thereby allowing us to accurately identify the number and location of autosomal sterility loci. In one direction of backcross, all males were sterile, indicating that sterility could be entirely induced by the sex chromosome complement in these males. In the other direction, we identified nine quantitative trait loci that account for a surprisingly large amount (56%) of the autosome-induced phenotypic variance in sterility, with a large contribution of autosome-autosome epistatic interactions. These loci are capable of acting dominantly, and thus could contribute to F1 hybrid sterility.

  16. Hybrid models for chemical reaction networks: Multiscale theory and application to gene regulatory systems.

    Science.gov (United States)

    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.

  17. Hybrid models for chemical reaction networks: Multiscale theory and application to gene regulatory systems

    Science.gov (United States)

    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.

  18. Hybrid Computational Model for High-Altitude Aeroassist Vehicles Project

    Data.gov (United States)

    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...

  19. 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.

  20. Identification and Prediction of Large Pedestrian Flow in Urban Areas Based on a Hybrid Detection Approach

    Directory of Open Access Journals (Sweden)

    Kaisheng Zhang

    2016-12-01

    Full Text Available Recently, population density has grown quickly with the increasing acceleration of urbanization. At the same time, overcrowded situations are more likely to occur in populous urban areas, increasing the risk of accidents. This paper proposes a synthetic approach to recognize and identify the large pedestrian flow. In particular, a hybrid pedestrian flow detection model was constructed by analyzing real data from major mobile phone operators in China, including information from smartphones and base stations (BS. With the hybrid model, the Log Distance Path Loss (LDPL model was used to estimate the pedestrian density from raw network data, and retrieve information with the Gaussian Progress (GP through supervised learning. Temporal-spatial prediction of the pedestrian data was carried out with Machine Learning (ML approaches. Finally, a case study of a real Central Business District (CBD scenario in Shanghai, China using records of millions of cell phone users was conducted. The results showed that the new approach significantly increases the utility and capacity of the mobile network. A more reasonable overcrowding detection and alert system can be developed to improve safety in subway lines and other hotspot landmark areas, such as the Bundle, People’s Square or Disneyland, where a large passenger flow generally exists.

  1. Minimally Invasive Treatment of the Thoracic Spine Disease: Completely Percutaneous and Hybrid Approaches

    OpenAIRE

    Tamburrelli Francesco Ciro; Scaramuzzo Laura; Genitiempo Maurizio; Proietti Luca

    2013-01-01

    The aim of the study was to evaluate the feasibility of a limited invasive approach for the treatment of upper thoracic spine disease. Seven patients with type-A thoracic fractures and three with tumors underwent long thoracic stabilization through a minimally invasive approach. Four patients underwent a completely percutaneous approach while the other three underwent a modified hybrid technique, a combination of percutaneous and open approach. The hybrid constructs were realized using a perc...

  2. 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.

  3. A state-space free-vortex hybrid wake model for helicopter rotors

    Science.gov (United States)

    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.

  4. Chromosomal regions involved in hybrid performance and heterosis: their AFLP(R)-based identification and practical use in prediction models.

    Science.gov (United States)

    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.

  5. Modeling and Simulation of Hybrid Solar Photovoltaic, Wind turbine and Hydraulic Power System

    OpenAIRE

    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...

  6. Hybrid bioinorganic approach to solar-to-chemical conversion.

    Science.gov (United States)

    Nichols, Eva M; Gallagher, Joseph J; Liu, Chong; Su, Yude; Resasco, Joaquin; Yu, Yi; Sun, Yujie; Yang, Peidong; Chang, Michelle C Y; Chang, Christopher J

    2015-09-15

    Natural photosynthesis harnesses solar energy to convert CO2 and water to value-added chemical products for sustaining life. We present a hybrid bioinorganic approach to solar-to-chemical conversion in which sustainable electrical and/or solar input drives production of hydrogen from water splitting using biocompatible inorganic catalysts. The hydrogen is then used by living cells as a source of reducing equivalents for conversion of CO2 to the value-added chemical product methane. Using platinum or an earth-abundant substitute, α-NiS, as biocompatible hydrogen evolution reaction (HER) electrocatalysts and Methanosarcina barkeri as a biocatalyst for CO2 fixation, we demonstrate robust and efficient electrochemical CO2 to CH4 conversion at up to 86% overall Faradaic efficiency for ≥ 7 d. Introduction of indium phosphide photocathodes and titanium dioxide photoanodes affords a fully solar-driven system for methane generation from water and CO2, establishing that compatible inorganic and biological components can synergistically couple light-harvesting and catalytic functions for solar-to-chemical conversion.

  7. Fuzzy hybrid MCDM approach for selection of wind turbine service technicians

    Directory of Open Access Journals (Sweden)

    Goutam Kumar Bose

    2016-01-01

    Full Text Available This research paper is aimed to present a fuzzy Hybrid Multi-criteria decision making (MCDM methodology for selecting employees. The present study aspires to present the hybrid approach of Fuzzy multiple MCDM techniques with tactical viewpoint to support the recruitment process of wind turbine service technicians. The methodology is based on the application of Fuzzy ARAS (Additive Ratio Assessment and Fuzzy MOORA (Multi-Objective Optimization on basis of Ratio Analysis which are integrated through group decision making (GDM method in the model for selection of wind turbine service technicians’ ranking. Here a group of experts from different fields of expertise are engaged to finalize the decision. Series of tests are conducted regarding physical fitness, technical written test, practical test along with general interview and medical examination to facilitate the final selection using the above techniques. In contrast to single decision making approaches, the proposed group decision making model efficiently supports the wind turbine service technicians ranking process. The effectiveness of the proposed approach manifest from the case study of service technicians required for the maintenance department of wind power plant using Fuzzy ARAS and Fuzzy MOORA. This set of potential technicians is evaluated based on five main criteria.

  8. A gas storage example as a benchmark for hybrid modelling: a comparative study; Une etude comparative de modelisation hybride sur un exemple de stockage de gaz

    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.

  9. Hybrid App Approach: Could It Mark the End of Native App Domination?

    Directory of Open Access Journals (Sweden)

    Minh Q. Huynh

    2017-04-01

    Full Text Available Aim/Purpose: Despite millions of apps on the market, it is still challenging to develop a mobile app that can run across platforms using the same code. Background: This paper explores a potential solution for developing cross platform apps by presenting the hybrid app approach. Methodology: The paper first describes a brief evolution of the different mobile app development approaches and then compares them with the hybrid app approach. Next, it focuses on one specific hybrid app development framework called Ionic. Contribution: The paper presents the hybrid app approach as an emerging trend in mobile app development and concludes with the highlight of its advantages and teaching implications. Findings: The hybrid app approach reduces the learning curve and offers tools to allow the reuse of code to create apps for different mobile devices. Recommendations for Practitioners: The experience that the paper describes in using Ionic framework to create a hybrid app can be adopted in a web design or mobile app development course. Impact on Society\t: The advance in hybrid framework in general and the growing acceptance of open source framework, such as Ionic in particular, may provide an alternative to the native app domination and may trigger the rapid rise of hybrid apps in the years to come.

  10. MADYMO facet Hybrid III 5th percentile model

    NARCIS (Netherlands)

    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

  11. 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 ...

  12. Dynamic Hybrid Model for Short-Term Electricity Price Forecasting

    Directory of Open Access Journals (Sweden)

    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.

  13. 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.

  14. Hybrid Metaheuristic Approach for Nonlocal Optimization of Molecular Systems.

    Science.gov (United States)

    Dresselhaus, Thomas; Yang, Jack; Kumbhar, Sadhana; Waller, Mark P

    2013-04-09

    Accurate modeling of molecular systems requires a good knowledge of the structure; therefore, conformation searching/optimization is a routine necessity in computational chemistry. Here we present a hybrid metaheuristic optimization (HMO) algorithm, which combines ant colony optimization (ACO) and particle swarm optimization (PSO) for the optimization of molecular systems. The HMO implementation meta-optimizes the parameters of the ACO algorithm on-the-fly by the coupled PSO algorithm. The ACO parameters were optimized on a set of small difluorinated polyenes where the parameters exhibited small variance as the size of the molecule increased. The HMO algorithm was validated by searching for the closed form of around 100 molecular balances. Compared to the gradient-based optimized molecular balance structures, the HMO algorithm was able to find low-energy conformations with a 87% success rate. Finally, the computational effort for generating low-energy conformation(s) for the phenylalanyl-glycyl-glycine tripeptide was approximately 60 CPU hours with the ACO algorithm, in comparison to 4 CPU years required for an exhaustive brute-force calculation.

  15. A Hybrid Metaheuristic-Based Approach for the Aerodynamic Optimization of Small Hybrid Wind Turbine Rotors

    Directory of Open Access Journals (Sweden)

    José F. Herbert-Acero

    2014-01-01

    Full Text Available This work presents a novel framework for the aerodynamic design and optimization of blades for small horizontal axis wind turbines (WT. The framework is based on a state-of-the-art blade element momentum model, which is complemented with the XFOIL 6.96 software in order to provide an estimate of the sectional blade aerodynamics. The framework considers an innovative nested-hybrid solution procedure based on two metaheuristics, the virtual gene genetic algorithm and the simulated annealing algorithm, to provide a near-optimal solution to the problem. The objective of the study is to maximize the aerodynamic efficiency of small WT (SWT rotors for a wide range of operational conditions. The design variables are (1 the airfoil shape at the different blade span positions and the radial variation of the geometrical variables of (2 chord length, (3 twist angle, and (4 thickness along the blade span. A wind tunnel validation study of optimized rotors based on the NACA 4-digit airfoil series is presented. Based on the experimental data, improvements in terms of the aerodynamic efficiency, the cut-in wind speed, and the amount of material used during the manufacturing process were achieved. Recommendations for the aerodynamic design of SWT rotors are provided based on field experience.

  16. Mechanisms Underlying Mammalian Hybrid Sterility in Two Feline Interspecies Models.

    Science.gov (United States)

    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.

  17. Solving Problem of Graph Isomorphism by Membrane-Quantum Hybrid Model

    Directory of Open Access Journals (Sweden)

    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.

  18. An Improved Approach for Hybrid Rocket Injection System Design

    OpenAIRE

    M. Invigorito; G. Elia; M. Panelli

    2016-01-01

    Hybrid propulsion combines beneficial properties of both solid and liquid rockets, such as multiple restarts, throttability as well as simplicity and reduced costs. A nitrous oxide (N2O)/paraffin-based hybrid rocket engine demonstrator is currently under development at the Italian Aerospace Research Center (CIRA) within the national research program HYPROB, funded by the Italian Ministry of Research. Nitrous oxide belongs to the class of self-pressurizing propellants that exhibit a high vapor...

  19. 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.

  20. Unilateral robotic hybrid mini-maze: a novel experimental approach.

    Science.gov (United States)

    Moslemi, Mohammad; Rawashdeh, Badi; Meyer, Mark; Nguyen, Duy; Poston, Robert; Gharagozloo, Farid

    2016-03-01

    A complete Cox maze IV procedure is difficult to accomplish using current endoscopic and minimally invasive techniques. These techniques are hampered by inability to adequately dissect the posterior structures of the heart and place all necessary lesions. We present a novel approach, using robotic technology, that achieves placement of all the lesions of the complete maze procedure. In three cadaveric human models, the technical feasibility of using robotic instruments through the right chest to dissect the posterior structures of the heart and place all Cox maze lesions was performed. The entire posterior aspect of the heart was dissected in the cadaveric model facilitating successful placement of all Cox maze IV lesions with robotic assistance through minimally invasive incisions. The robotic Cox maze IV procedure through the novel right thoracic approach is feasible. This obviates the need for sternotomy and avoids the associated morbidity of the conventional Cox-maze procedure. Copyright © 2015 John Wiley & Sons, Ltd.

  1. Application of hybrid life cycle approaches to emerging energy technologies--the case of wind power in the UK.

    Science.gov (United States)

    Wiedmann, Thomas O; Suh, Sangwon; Feng, Kuishuang; Lenzen, Manfred; Acquaye, Adolf; Scott, Kate; Barrett, John R

    2011-07-01

    Future energy technologies will be key for a successful reduction of man-made greenhouse gas emissions. With demand for electricity projected to increase significantly in the future, climate policy goals of limiting the effects of global atmospheric warming can only be achieved if power generation processes are profoundly decarbonized. Energy models, however, have ignored the fact that upstream emissions are associated with any energy technology. In this work we explore methodological options for hybrid life cycle assessment (hybrid LCA) to account for the indirect greenhouse gas (GHG) emissions of energy technologies using wind power generation in the UK as a case study. We develop and compare two different approaches using a multiregion input-output modeling framework - Input-Output-based Hybrid LCA and Integrated Hybrid LCA. The latter utilizes the full-sized Ecoinvent process database. We discuss significance and reliability of the results and suggest ways to improve the accuracy of the calculations. The comparison of hybrid LCA methodologies provides valuable insight into the availability and robustness of approaches for informing energy and environmental policy.

  2. Hybrid ensemble learning approach for generation of classification rules

    OpenAIRE

    Liu, Han; Gegov, Alexander Emilov; Cocea, Mihaela

    2015-01-01

    Due to the daily increase in the size of data, machine learning has become a popular approach for intelligent processing of data. In particular, machine learning algorithms are used to discover meaningful knowledge or build predictive models from data. For example, inductive learning algorithms involve generation of rules which can be in the form of either a decision tree or if-then rules. However, most of learning algorithms suffer from overfitting of training data. In other words, these lea...

  3. Hybrid Model GSTAR-SUR-NN For Precipitation Data

    OpenAIRE

    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...

  4. A Hybrid Model for Predicting the Prevalence of Schistosomiasis in Humans of Qianjiang City, China

    Science.gov (United States)

    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

  5. 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.

  6. Generator maintenance scheduling in power systems using metaheuristic-based hybrid approaches

    Energy Technology Data Exchange (ETDEWEB)

    Dahal, Keshav P. [School of Informatics, University of Bradford, Bradford (United Kingdom); Chakpitak, Nopasit [College of Arts, Media and Technology, Chiang Mai University, Chiang Mai (Thailand)

    2007-05-15

    The effective maintenance scheduling of power system generators is very important for the economical and reliable operation of a power system. This represents a tough scheduling problem which continues to present a challenge for efficient optimization solution techniques. This paper presents the application of metaheuristic approaches, such as a genetic algorithm (GA), simulated annealing (SA) and their hybrid for generator maintenance scheduling (GMS) in power systems using an integer representation. This paper mainly focuses on the application of GA/SA and GA/SA/heuristic hybrid approaches. GA/SA hybrid uses the probabilistic acceptance criterion of SA within the GA framework. GA/SA/heuristic hybrid combines heuristic approaches within the GA/SA hybrid to seed the initial population. A case study is formulated in this paper as an integer programming problem using a reliability-based objective function and typical problem constraints. The implementation and performance of the metaheuristic approaches and their hybrid for the test case study are discussed. The results obtained are promising and show that the hybrid approaches are less sensitive to the variations of technique parameters and offer an effective alternative for solving the generator maintenance scheduling problem. (author)

  7. A model updating method for hybrid composite/aluminum bolted joints using modal test data

    Science.gov (United States)

    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.

  8. 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 ...

  9. 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.

  10. A Hybrid PCA-CART-MARS-Based Prognostic Approach of the Remaining Useful Life for Aircraft Engines

    Directory of Open Access Journals (Sweden)

    Fernando Sánchez Lasheras

    2015-03-01

    Full Text Available Prognostics is an engineering discipline that predicts the future health of a system. In this research work, a data-driven approach for prognostics is proposed. Indeed, the present paper describes a data-driven hybrid model for the successful prediction of the remaining useful life of aircraft engines. The approach combines the multivariate adaptive regression splines (MARS technique with the principal component analysis (PCA, dendrograms and classification and regression trees (CARTs. Elements extracted from sensor signals are used to train this hybrid model, representing different levels of health for aircraft engines. In this way, this hybrid algorithm is used to predict the trends of these elements. Based on this fitting, one can determine the future health state of a system and estimate its remaining useful life (RUL with accuracy. To evaluate the proposed approach, a test was carried out using aircraft engine signals collected from physical sensors (temperature, pressure, speed, fuel flow, etc.. Simulation results show that the PCA-CART-MARS-based approach can forecast faults long before they occur and can predict the RUL. The proposed hybrid model presents as its main advantage the fact that it does not require information about the previous operation states of the input variables of the engine. The performance of this model was compared with those obtained by other benchmark models (multivariate linear regression and artificial neural networks also applied in recent years for the modeling of remaining useful life. Therefore, the PCA-CART-MARS-based approach is very promising in the field of prognostics of the RUL for aircraft engines.

  11. A hybrid fuzzy stochastic analytical hierarchy process (FSAHP) approach for evaluating ballast water treatment technologies

    National Research Council Canada - National Science Library

    Jing, Liang; Chen, Bing; Zhang, Baiyu; Peng, Hongxuan

    2013-01-01

    .... This paper presents a novel hybrid fuzzy stochastic analytical hierarchy process (FSAHP) approach to aid decision making by incorporating fuzzy and stochastic uncertainty into the traditional analytic hierarchy process (AHP...

  12. SPELL CHECKING AND ERROR CORRECTING SYSTEM FOR TEXT PARAGRAPHS WRITTEN IN PUNJABI LANGUAGE USING HYBRID APPROACH

    OpenAIRE

    Harpreet Kaur; Navroop Kaur

    2016-01-01

    Spell checking and correcting them is very important phase of any word processing system. There are various word processing software are available for various languages like English, Hindi. We have developed a spell checker and error correcting system for Punjabi language. The proposed system use hybrid approach which s a combination of various approaches like rule based approach, dictionary lookup approach , edit distance approach and N-Gram approach. Proposed system is tested with various i...

  13. Hybrid programming model for implicit PDE simulations on multicore architectures

    KAUST Repository

    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.

  14. A Hybrid Process Monitoring and Fault Diagnosis Approach for Chemical Plants

    Directory of Open Access Journals (Sweden)

    Lijie Guo

    2015-01-01

    Full Text Available Given their potentially enormous risk, process monitoring and fault diagnosis for chemical plants have recently been the focus of many studies. Based on hazard and operability (HAZOP analysis, kernel principal component analysis (KPCA, wavelet neural network (WNN, and fault tree analysis (FTA, a hybrid process monitoring and fault diagnosis approach is proposed in this study. HAZOP analysis helps identify the fault modes and determine process variables monitored. The KPCA model is then constructed to reduce monitoring variable dimensionality. Meanwhile, the fault features of the monitoring variables are extracted, so then process monitoring can be performed with the squared prediction error (SPE statistics of KPCA. Then, multiple WNN models are designed through the use of low-dimensional sample data preprocessed by KPCA as the training and test samples to detect the fault mode online. Finally, FTA approach is introduced to further locate the fault root causes of the fault mode. The proposed approach is applied to process monitoring and fault diagnosis in a depropanizer unit. Case study results indicate that this approach can be applicable to process monitoring and diagnosis in large-scale chemical plants. Accordingly, the approach can serve as an early and reliable basis for technicians’ and operators’ safety management decision-making.

  15. 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.

  16. A Hybrid Approach to Online and Traditional Learning during a Boundary Layer Meteorology Course

    Science.gov (United States)

    Kelsey, E. P.; Yarker, M. B.; Mesquita, M. D. S.

    2014-12-01

    This project discusses a case study, where eight graduate students in a Boundary Layer Meteorology course at Plymouth State University collected observation data and ran the WRF model in order to explore the relationships between model output, observation data, and boundary layer theory. At the end of the course, the students drafted a paper highlighting their findings, which has been submitted for publication. As a part of the course, the students were provided with a unique learning opportunity to collect meteorological data for a boundary layer phenomenon of their choice, analyze the data and compare it to theory learned in class, and run a numerical model to test the model forecast skill of the observations. Students had access to the Plymouth State University (PSU) radiosonde system and the Mount Washington Observatory Mesonet stations that measure wind, temperature, and relative humidity. Additionally, they had access to the NCAR Yellowstone supercomputer to run their WRF model simulations. This course used a hybrid approach to learning about running the WRF model, which included the in-class material and an online WRF modelling course. For the purposes of this class, the hybrid approach included having the students take the online tutorial and have weekly videoconference meetings with the online course tutor, who lives in Norway. This, in conjunction with the traditional in-class portion, provided multiple modes of learning WRF, access to more expertise in running numerical models, and an opportunity to meet a foreign researcher. Survey results indicate that the students found it helpful to run the model as a part of understanding the atmosphere. A few students recognized that having experience running a model could help them in their future research if they ever need to run WRF or any other atmospheric research model. Most students report that it was useful to compare model data to observed data in order to evaluate the model and compare their findings to

  17. Simulation of Mercury's magnetosheath with a combined hybrid-paraboloid model

    Science.gov (United States)

    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.

  18. 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.

  19. 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.

  20. Hybrid Analytical and Data-Driven Modeling for Feed-Forward Robot Control.

    Science.gov (United States)

    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.

  1. Hybrid Analytical and Data-Driven Modeling for Feed-Forward Robot Control †

    Science.gov (United States)

    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

  2. Hybrid network defense model based on fuzzy evaluation.

    Science.gov (United States)

    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.

  3. Modeling of hybrid vehicle fuel economy and fuel engine efficiency

    Science.gov (United States)

    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.

  4. Process planning optimization on turning machine tool using a hybrid genetic algorithm with local search approach

    Directory of Open Access Journals (Sweden)

    Yuliang Su

    2015-04-01

    Full Text Available A turning machine tool is a kind of new type of machine tool that is equipped with more than one spindle and turret. The distinctive simultaneous and parallel processing abilities of turning machine tool increase the complexity of process planning. The operations would not only be sequenced and satisfy precedence constraints, but also should be scheduled with multiple objectives such as minimizing machining cost, maximizing utilization of turning machine tool, and so on. To solve this problem, a hybrid genetic algorithm was proposed to generate optimal process plans based on a mixed 0-1 integer programming model. An operation precedence graph is used to represent precedence constraints and help generate a feasible initial population of hybrid genetic algorithm. Encoding strategy based on data structure was developed to represent process plans digitally in order to form the solution space. In addition, a local search approach for optimizing the assignments of available turrets would be added to incorporate scheduling with process planning. A real-world case is used to prove that the proposed approach could avoid infeasible solutions and effectively generate a global optimal process plan.

  5. Hybrid-impulsive second order sliding mode control: Lyapunov approach

    NARCIS (Netherlands)

    Shtessel, Y.; Glumineau, A.; Plestan, F.; Weiss, M.

    2013-01-01

    A perturbed nonlinear system of relative degree two controlled by discontinuous-impulsive feedbacks is studied. The hybrid-impulsive terms serve to drive instantaneously the system trajectories to the origin or to its small vicinity. In particular, impulsive-twisting control exhibits an uniform

  6. Hybrid Engine Powered City Car: Fuzzy Controlled Approach

    Science.gov (United States)

    Rahman, Ataur; Mohiuddin, AKM; Hawlader, MNA; Ihsan, Sany

    2017-03-01

    This study describes a fuzzy controlled hybrid engine powered car. The car is powered by the lithium ion battery capacity of 1000 Wh is charged by the 50 cc hybrid engine and power regenerative mode. The engine is operated with lean mixture at 3000 rpm to charge the battery. The regenerative mode that connects with the engine generates electrical power of 500-600 W for the deceleration of car from 90 km/h to 20 km/h. The regenerated electrical power has been used to power the air-conditioning system and to meet the other electrical power. The battery power only used to propel the car. The regenerative power also found charging the battery for longer operation about 40 minutes and more. The design flexibility of this vehicle starts with whole-vehicle integration based on radical light weighting, drag reduction, and accessory efficiency. The energy efficient hybrid engine cut carbon dioxide (CO2) and nitrogen oxides (N2O) emission about 70-80% as the loads on the crankshaft such as cam-follower and its associated rotating components are replaced by electromagnetic systems, and the flywheel, alternator and starter motor are replaced by a motor generator. The vehicle was tested and found that it was able to travel 70 km/litre with the power of hybrid engine.

  7. A hybrid finite difference and integral equation method for modeling and inversion of marine CSEM data

    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....

  8. A Hybrid Metaheuristic-Based Approach for the Aerodynamic Optimization of Small Hybrid Wind Turbine Rotors

    DEFF Research Database (Denmark)

    Herbert-Acero, José F.; Martínez-Lauranchet, Jaime; Probst, Oliver

    2014-01-01

    of the sectional blade aerodynamics. The framework considers an innovative nested-hybrid solution procedure based on two metaheuristics, the virtual gene genetic algorithm and the simulated annealing algorithm, to provide a near-optimal solution to the problem. The objective of the study is to maximize...

  9. Evaluation of Hybrid Learning in a Construction Engineering Context: A Mixed-Method Approach

    Science.gov (United States)

    Karabulut-Ilgu, Aliye; Jahren, Charles

    2016-01-01

    Engineering educators call for a widespread implementation of hybrid learning to respond to rapidly changing demands of the 21st century. In response to this call, a junior-level course in the Construction Engineering program entitled Construction Equipment and Heavy Construction Methods was converted into a hybrid learning model. The overarching…

  10. 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.

  11. Application of stochastic frontier approach model to assess technical ...

    African Journals Online (AJOL)

    Application of stochastic frontier approach model to assess technical efficiency in Kenya's maize production. ... primary school education would enhance maize productivity. Thus, if hybrid seeds, tractor services and agricultural credit ... efficiency would increase. Key words: Socio-economic factors, farm characteristics, maize ...

  12. A Hybrid Heuristic Optimization Approach for Leak Detection in Pipe Networks Using Ordinal Optimization Approach and the Symbiotic Organism Search

    Directory of Open Access Journals (Sweden)

    Chao-Chih Lin

    2017-10-01

    Full Text Available A new transient-based hybrid heuristic approach is developed to optimize a transient generation process and to detect leaks in pipe networks. The approach couples the ordinal optimization approach (OOA and the symbiotic organism search (SOS to solve the optimization problem by means of iterations. A pipe network analysis model (PNSOS is first used to determine steady-state head distribution and pipe flow rates. The best transient generation point and its relevant valve operation parameters are optimized by maximizing the objective function of transient energy. The transient event is created at the chosen point, and the method of characteristics (MOC is used to analyze the transient flow. The OOA is applied to sift through the candidate pipes and the initial organisms with leak information. The SOS is employed to determine the leaks by minimizing the sum of differences between simulated and computed head at the observation points. Two synthetic leaking scenarios, a simple pipe network and a water distribution network (WDN, are chosen to test the performance of leak detection ordinal symbiotic organism search (LDOSOS. Leak information can be accurately identified by the proposed approach for both of the scenarios. The presented technique makes a remarkable contribution to the success of leak detection in the pipe networks.

  13. Aeroacoustic analysis of the human phonation process based on a hybrid acoustic PIV approach

    Science.gov (United States)

    Lodermeyer, Alexander; Tautz, Matthias; Becker, Stefan; Döllinger, Michael; Birk, Veronika; Kniesburges, Stefan

    2018-01-01

    The detailed analysis of sound generation in human phonation is severely limited as the accessibility to the laryngeal flow region is highly restricted. Consequently, the physical basis of the underlying fluid-structure-acoustic interaction that describes the primary mechanism of sound production is not yet fully understood. Therefore, we propose the implementation of a hybrid acoustic PIV procedure to evaluate aeroacoustic sound generation during voice production within a synthetic larynx model. Focusing on the flow field downstream of synthetic, aerodynamically driven vocal folds, we calculated acoustic source terms based on the velocity fields obtained by time-resolved high-speed PIV applied to the mid-coronal plane. The radiation of these sources into the acoustic far field was numerically simulated and the resulting acoustic pressure was finally compared with experimental microphone measurements. We identified the tonal sound to be generated downstream in a small region close to the vocal folds. The simulation of the sound propagation underestimated the tonal components, whereas the broadband sound was well reproduced. Our results demonstrate the feasibility to locate aeroacoustic sound sources inside a synthetic larynx using a hybrid acoustic PIV approach. Although the technique employs a 2D-limited flow field, it accurately reproduces the basic characteristics of the aeroacoustic field in our larynx model. In future studies, not only the aeroacoustic mechanisms of normal phonation will be assessable, but also the sound generation of voice disorders can be investigated more profoundly.

  14. Facile approach to prepare Pt decorated SWNT/graphene hybrid catalytic ink

    Energy Technology Data Exchange (ETDEWEB)

    Mayavan, Sundar, E-mail: sundarmayavan@cecri.res.in [Centre for Innovation in Energy Research, CSIR–Central Electrochemical Research Institute, Karaikudi 630006, Tamil Nadu (India); Department of Nuclear and Quantum Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 305-701 (Korea, Republic of); Mandalam, Aditya; Balasubramanian, M. [Centre for Innovation in Energy Research, CSIR–Central Electrochemical Research Institute, Karaikudi 630006, Tamil Nadu (India); Sim, Jun-Bo [Department of Nuclear and Quantum Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 305-701 (Korea, Republic of); Choi, Sung-Min, E-mail: sungmin@kaist.ac.kr [Department of Nuclear and Quantum Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 305-701 (Korea, Republic of)

    2015-07-15

    Highlights: • Pt NPs were in situ synthesized onto CNT–graphene support in aqueous solution. • The as-prepared material was used directly as a catalyst ink without further treatment. • Catalyst ink is active toward methanol oxidation. • This approach realizes both scalable and greener production of hybrid catalysts. - Abstract: Platinum nanoparticles were in situ synthesized onto hybrid support involving graphene and single walled carbon nanotube in aqueous solution. We investigate the reduction of graphene oxide, and platinum nanoparticle functionalization on hybrid support by X-ray photoelectron spectroscopy, Raman spectroscopy, X-ray diffraction, scanning electron microscopy and transmission electron microscopy. The as-prepared platinum on hybrid support was used directly as a catalyst ink without further treatment and is active toward methanol oxidation. This work realizes both scalable and greener production of highly efficient hybrid catalysts, and would be valuable for practical applications of graphene based fuel cell catalysts.

  15. Model-based Dynamic Control Allocation in a Hybrid Neuroprosthesis.

    Science.gov (United States)

    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.

  16. 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....

  17. New Models of Hybrid Leadership in Global Higher Education

    Science.gov (United States)

    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.…

  18. 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...

  19. 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...

  20. A HYBRID GENETIC ALGORITHM-NEURAL NETWORK APPROACH FOR PRICING CORES AND REMANUFACTURED CORES

    Directory of Open Access Journals (Sweden)

    M. Seidi

    2012-01-01

    Full Text Available

    ENGLISH ABSTRACT:Sustainability has become a major issue in most economies, causing many leading companies to focus on product recovery and reverse logistics. Remanufacturing is an industrial process that makes used products reusable. One of the important aspects in both reverse logistics and remanufacturing is the pricing of returned and remanufactured products (called cores. In this paper, we focus on pricing the cores and remanufactured cores. First we present a mathematical model for this purpose. Since this model does not satisfy our requirements, we propose a simulation optimisation approach. This approach consists of a hybrid genetic algorithm based on a neural network employed as the fitness function. We use automata learning theory to obtain the learning rate required for training the neural network. Numerical results demonstrate that the optimal value of the acquisition price of cores and price of remanufactured cores is obtained by this approach.

    AFRIKAANSE OPSOMMING: Volhoubaarheid het ‘n belangrike saak geword in die meeste ekonomieë, wat verskeie maatskappye genoop het om produkherwinning en omgekeerde logistiek te onder oë te neem. Hervervaardiging is ‘n industriële proses wat gebruikte produkte weer bruikbaar maak. Een van die belangrike aspekte in beide omgekeerde logistiek en hervervaardiging is die prysbepaling van herwinne en hervervaardigde produkte. Hierdie artikel fokus op die prysbepalingsaspekte by wyse van ‘n wiskundige model.

  1. Polymer Combustion as a Basis for Hybrid Propulsion: A Comprehensive Review and New Numerical Approaches

    Directory of Open Access Journals (Sweden)

    Vasily Novozhilov

    2011-10-01

    Full Text Available Hybrid Propulsion is an attractive alternative to conventional liquid and solid rocket motors. This is an active area of research and technological developments. Potential wide application of Hybrid Engines opens the possibility for safer and more flexible space vehicle launching and manoeuvring. The present paper discusses fundamental combustion issues related to further development of Hybrid Rockets. The emphasis is made on the two aspects: (1 properties of potential polymeric fuels, and their modification, and (2 implementation of comprehensive CFD models for combustion in Hybrid Engines. Fundamentals of polymeric fuel combustion are discussed. Further, steps necessary to accurately describe their burning behaviour by means of CFD models are investigated. Final part of the paper presents results of preliminary CFD simulations of fuel burning process in Hybrid Engine using a simplified set-up.

  2. A hybrid approach for probabilistic forecasting of electricity price

    DEFF Research Database (Denmark)

    Wan, Can; Xu, Zhao; Wang, Yelei

    2014-01-01

    The electricity market plays a key role in realizing the economic prophecy of smart grids. Accurate and reliable electricity market price forecasting is essential to facilitate various decision making activities of market participants in the future smart grid environment. However, due...... electricity price forecasting is proposed in this paper. The effectiveness of the proposed hybrid method has been validated through comprehensive tests using real price data from Australian electricity market....

  3. Lead-acid battery model for hybrid energy storage

    OpenAIRE

    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 ...

  4. Modeling, hybridization, and optimal charging of electrical energy storage systems

    Science.gov (United States)

    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

  5. Material Modelling - Composite Approach

    DEFF Research Database (Denmark)

    Nielsen, Lauge Fuglsang

    1997-01-01

    , and internal stresses caused by drying shrinkage with experimental results reported in the literature on the mechanical behavior of mature concretes. It is then concluded that the model presented applied in general with respect to age at loading.From a stress analysis point of view the most important finding...... is successfully justified comparing predicted results with experimental data obtained in the HETEK-project on creep, relaxation, and shrinkage of very young concretes cured at a temperature of T = 20^o C and a relative humidity of RH = 100%. The model is also justified comparing predicted creep, shrinkage......, linear-viscoelastic analysis methods are justified from the age of approximately 10 hours.The rheological properties of plain cement paste are determined. These properties are the principal material properties needed in any stress analysis of concrete. Shrinkage (autogeneous or drying) of mortar...

  6. Prediction of Currency Volume Issued in Taiwan Using a Hybrid Artificial Neural Network and Multiple Regression Approach

    Directory of Open Access Journals (Sweden)

    Yuehjen E. Shao

    2013-01-01

    Full Text Available Because the volume of currency issued by a country always affects its interest rate, price index, income levels, and many other important macroeconomic variables, the prediction of currency volume issued has attracted considerable attention in recent years. In contrast to the typical single-stage forecast model, this study proposes a hybrid forecasting approach to predict the volume of currency issued in Taiwan. The proposed hybrid models consist of artificial neural network (ANN and multiple regression (MR components. The MR component of the hybrid models is established for a selection of fewer explanatory variables, wherein the selected variables are of higher importance. The ANN component is then designed to generate forecasts based on those important explanatory variables. Subsequently, the model is used to analyze a real dataset of Taiwan's currency from 1996 to 2011 and twenty associated explanatory variables. The prediction results reveal that the proposed hybrid scheme exhibits superior forecasting performance for predicting the volume of currency issued in Taiwan.

  7. A hybrid analytical-numerical approach for the analysis of salient-pole synchronous generators with a symmetrical damper cage

    OpenAIRE

    Nuzzo, Stefano; Bolognesi, Paolo; Galea, Michael; Gerada, C.

    2017-01-01

    The equivalent circuit approach has been widely exploited for the theoretical analysis of electromagnetic devices. However, in the field of classical wound-field synchronous generators, the presence of the damper cage complicates the analysis of such devices and the accurate prediction of the inherent induced currents is still matter of ongoing research. 12Focus is given to the accurate prediction of the no-load voltage waveform, by implementing a hybrid analytical-numerical model for a speci...

  8. Modelling Shallow Water Wakes Using a Hybrid Turbulence Model

    Directory of Open Access Journals (Sweden)

    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.

  9. Hybrid BEM/empirical approach for scattering of correlated sources in rocket noise prediction

    Science.gov (United States)

    Barbarino, Mattia; Adamo, Francesco P.; Bianco, Davide; Bartoccini, Daniele

    2017-09-01

    Empirical models such as the Eldred standard model are commonly used for rocket noise prediction. Such models directly provide a definition of the Sound Pressure Level through the quadratic pressure term by uncorrelated sources. In this paper, an improvement of the Eldred Standard model has been formulated. This new formulation contains an explicit expression for the acoustic pressure of each noise source, in terms of amplitude and phase, in order to investigate the sources correlation effects and to propagate them through a wave equation. In particular, the correlation effects between adjacent and not-adjacent sources have been modeled and analyzed. The noise prediction obtained with the revised Eldred-based model has then been used for formulating an empirical/BEM (Boundary Element Method) hybrid approach that allows an evaluation of the scattering effects. In the framework of the European Space Agency funded program VECEP (VEga Consolidation and Evolution Programme), these models have been applied for the prediction of the aeroacoustics loads of the VEGA (Vettore Europeo di Generazione Avanzata - Advanced Generation European Carrier Rocket) launch vehicle at lift-off and the results have been compared with experimental data.

  10. A Novel Design Approach to X-Band Minkowski Reflectarray Antennas using the Full-Wave EM Simulation-based Complete Neural Model with a Hybrid GA-NM Algorithm

    Directory of Open Access Journals (Sweden)

    F. GUNEŞ

    2014-04-01

    Full Text Available In this work, a novel multi-objective design optimization procedure is presented for the Minkowski Reflectarray RAs using a complete 3-D CST Microwave Studio MWS-based Multilayer Perceptron Neural Network MLP NN model including the substrate constant εr with a hybrid Genetic GA and Nelder-Mead NM algorithm. The MLP NN model provides an accurate and fast model and establishes the reflection phase of a unit Minkowski RA element as a continuous function within the input domain including the substrate 1 ≤ εr ≤ 6; 0.5mm ≤ h ≤ 3mm in the frequency between 8GHz ≤ f ≤ 12GHz. This design procedure enables a designer to obtain not only the most optimum Minkowski RA design all throughout the X- band, at the same time the optimum Minkowski RAs on the selected substrates. Moreover a design of a fully optimized X-band 15×15 Minkowski RA antenna is given as a worked example with together the tolerance analysis and its performance is also compared with those of the optimized RAs on the selected traditional substrates. Finally it may be concluded that the presented robust and systematic multi-objective design procedure is conveniently applied to the Microstrip Reflectarray RAs constructed from the advanced patches.

  11. A hybrid agent-based computational economics and optimization approach for supplier selection problem

    Directory of Open Access Journals (Sweden)

    Zahra Pourabdollahi

    2017-12-01

    Full Text Available Supplier evaluation and selection problem is among the most important of logistics decisions that have been addressed extensively in supply chain management. The same logistics decision is also important in freight transportation since it identifies trade relationships between business establishments and determines commodity flows between production and consumption points. The commodity flows are then used as input to freight transportation models to determine cargo movements and their characteristics including mode choice and shipment size. Various approaches have been proposed to explore this latter problem in previous studies. Traditionally, potential suppliers are evaluated and selected using only price/cost as the influential criteria and the state-of-practice methods. This paper introduces a hybrid agent-based computational economics and optimization approach for supplier selection. The proposed model combines an agent-based multi-criteria supplier evaluation approach with a multi-objective optimization model to capture both behavioral and economical aspects of the supplier selection process. The model uses a system of ordered response models to determine importance weights of the different criteria in supplier evaluation from a buyers’ point of view. The estimated weights are then used to calculate a utility for each potential supplier in the market and rank them. The calculated utilities are then entered into a mathematical programming model in which best suppliers are selected by maximizing the total accrued utility for all buyers and minimizing total shipping costs while balancing the capacity of potential suppliers to ensure market clearing mechanisms. The proposed model, herein, was implemented under an operational agent-based supply chain and freight transportation framework for the Chicago Metropolitan Area.

  12. Likelihood of financial distress in Canadian oil and gas market: An optimized hybrid forecasting approach

    Directory of Open Access Journals (Sweden)

    Mohammad Mahbobi

    2017-05-01

    Full Text Available Forecasting models are built on either multivariate parametric or nonparametric methodologies. We attempt to optimize the accuracy of the forecasts combining these approaches to make a robust hybrid forecasting model in predicting the likelihood of financial distress for companies in the Canadian oil and gas market. The proposed approach combined the forecasts out of a multivariate logit model based on the conventional Altman’s Z-score with a nonparametric Artificial Neural Network (ANN technique. The sample firms are publicly traded and listed on the Toronto Stock Exchange (TSX and span over a period from first quarter of 1999 to the last quarter of 2014. The results of a proposed three-stage estimation process for the period of 2015-2020 indicated that besides the fact that Canadian energy sector will go through ups and downs regarding the likelihood of financial distress, this industry would face a hard time by late 2020. Results show that the forecasting accuracy out of the proposed three-stage forecasting technique is significantly superior to the outcomes of any individual forecasting techniques, i.e. ANN and logit models.

  13. Dynamic Hybrid Model for Short-Term Electricity Price Forecasting

    OpenAIRE

    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...

  14. 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)

  15. Control and fault diagnosis based sliding mode observer of a multicellular converter: Hybrid approach

    KAUST Repository

    Benzineb, Omar

    2013-01-01

    In this article, the diagnosis of a three cell converter is developed. The hybrid nature of the system represented by the presence of continuous and discrete dynamics is taken into account in the control design. The idea is based on using a hybrid control and an observer-type sliding mode to generate residuals from the observation errors of the system. The simulation results are presented at the end to illustrate the performance of the proposed approach. © 2013 FEI STU.

  16. 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.

  17. Anisotropic ghost dark energy cosmological model with hybrid expansion law

    Science.gov (United States)

    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.

  18. Speech Segmentation to Phonemes Based on Hybrid Hidden Markov Models

    OpenAIRE

    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...

  19. Particle production and chemical freezeout from the hybrid UrQMD approach at NICA energies

    Energy Technology Data Exchange (ETDEWEB)

    Nasser Tawfik, Abdel [Modern University for Technology and Information (MTI), Egyptian Center for Theoretical Physics (ECTP), Cairo (Egypt); World Laboratory for Cosmology and Particle Physics (WLCAPP), Cairo (Egypt); Abou-Salem, Loutfy I. [Benha University, Physics Department, Faculty of Science, Benha (Egypt); Shalaby, Asmaa G.; Hanafy, Mahmoud [World Laboratory for Cosmology and Particle Physics (WLCAPP), Cairo (Egypt); Benha University, Physics Department, Faculty of Science, Benha (Egypt); Sorin, Alexander [Joint Institute for Nuclear Research, Bogoliubov Laboratory of Theoretical Physics, Dubna, Moscow region (Russian Federation); Joint Institute for Nuclear Research, Veksler and Baldin Laboratory of High Energy Physics, Dubna, Moscow region (Russian Federation); National Research Nuclear University (MEPhI), Moscow (Russian Federation); Dubna International University, Dubna (Russian Federation); Rogachevsky, Oleg; Scheinast, Werner [Joint Institute for Nuclear Research, Veksler and Baldin Laboratory of High Energy Physics, Dubna, Moscow region (Russian Federation)

    2016-10-15

    The energy dependence of various particle ratios is calculated within the Ultra-relativistic Quantum Molecular Dynamics approach and compared with the hadron resonance gas (HRG) model and measurements from various experiments, including RHIC-BES, SPS and AGS. It is found that the UrQMD particle ratios agree well with the experimental results at the RHIC-BES energies. Thus, we have utilized UrQMD in simulating particle ratios at other beam energies down to 3GeV, which will be accessed at NICA and FAIR future facilities. We observe that the particle ratios for crossover and first-order phase transition, implemented in the hybrid UrQMD v3.4, are nearly indistinguishable, especially at low energies (at large baryon chemical potentials or high density). (orig.)

  20. Dynamic Analysis and Design Optimization of Series Hydraulic Hybrid System through Power Bond Graph Approach

    Directory of Open Access Journals (Sweden)

    R. Ramakrishnan

    2014-01-01

    Full Text Available The availability of natural gas and crude oil resources has been declining over the years. In automobile sector, the consumption of crude oil is 63% of total crude oil production in the world. Hence, automobile industries are placing more emphasis on energy efficient hydraulic hybrid systems, which can replace their conventional transmission systems. Series hydraulic hybrid system (SHHS is a multidomain mechatronics system with two distinct power sources that includes prime mover and hydropneumatic accumulator. It replaces the conventional transmission system to drive the vehicle. The sizing of the subsystems in SHHS plays a major role in improving the energy efficiency of the vehicle. In this paper, a power bond graph approach is used to model the dynamics of the SHHS. The obtained simulation results indicate the energy flow during various modes of operations. It also includes the dynamic response of hydropneumatic accumulator, prime mover, and system output speed. Further, design optimization of the system is carried out to optimize the process parameters for maximizing the system energy efficiency. This leads to increase in fuel economy and environmentally friendly vehicle.

  1. A hybrid CPU-GPGPU approach for real-time elastography.

    Science.gov (United States)

    Yang, Xu; Deka, Sthiti; Righetti, Raffaella

    2011-12-01

    Ultrasound elastography is becoming a widely available clinical imaging tool. In recent years, several real- time elastography algorithms have been proposed; however, most of these algorithms achieve real-time frame rates through compromises in elastographic image quality. Cross-correlation- based elastographic techniques are known to provide high- quality elastographic estimates, but they are computationally intense and usually not suitable for real-time clinical applications. Recently, the use of massively parallel general purpose graphics processing units (GPGPUs) for accelerating computationally intense operations in biomedical applications has received great interest. In this study, we investigate the use of the GPGPU to speed up generation of cross-correlation-based elastograms and achieve real-time frame rates while preserving elastographic image quality. We propose and statistically analyze performance of a new hybrid model of computation suitable for elastography applications in which sequential code is executed on the CPU and parallel code is executed on the GPGPU. Our results indicate that the proposed hybrid approach yields optimal results and adequately addresses the trade-off between speed and quality.

  2. An hybrid and non-modern approach to urban studies

    Directory of Open Access Journals (Sweden)

    Marc Grau i Solés

    2012-03-01

    Full Text Available This article draws upon the so-called Forat de la Vergonya urban controversy and the urban transformation process of a neighborhood in Barcelona: el Casc Antic. Drawing on inputs from Actor-Network Theory (ANT, the city is explored as a multiple urban assemblage. Besides, we analyze the dichotomous nature of the modern notion of politics. Especially, the role of object-subject dichotomy is explored. Through the analysis of citizen participation opportunities we propose a new hybrid notion of citizen participation and urban policy.

  3. A new hybrid numerical scheme for modelling elastodynamics in unbounded media with near-source heterogeneities

    Science.gov (United States)

    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.

  4. A multidisciplinary approach to study the functional properties of neuron-like cell models constituting a living bio-hybrid system: SH-SY5Y cells adhering to PANI substrate

    Science.gov (United States)

    Caponi, S.; Mattana, S.; Ricci, M.; Sagini, K.; Juarez-Hernandez, L. J.; Jimenez-Garduño, A. M.; Cornella, N.; Pasquardini, L.; Urbanelli, L.; Sassi, P.; Morresi, A.; Emiliani, C.; Fioretto, D.; Dalla Serra, M.; Pederzolli, C.; Iannotta, S.; Macchi, P.; Musio, C.

    2016-11-01

    A living bio-hybrid system has been successfully implemented. It is constituted by neuroblastic cells, the SH-SY5Y human neuroblastoma cells, adhering to a poly-anyline (PANI) a semiconductor polymer with memristive properties. By a multidisciplinary approach, the biocompatibility of the substrate has been analyzed and the functionality of the adhering cells has been investigated. We found that the PANI films can support the cell adhesion. Moreover, the SH-SY5Y cells were successfully differentiated into neuron-like cells for in vitro applications demonstrating that PANI can also promote cell differentiation. In order to deeply characterize the modifications of the bio-functionality induced by the cell-substrate interaction, the functional properties of the cells have been characterized by electrophysiology and Raman spectroscopy. Our results confirm that the PANI films do not strongly affect the general properties of the cells, ensuring their viability without toxic effects on their physiology. Ascribed to the adhesion process, however, a slight increase of the markers of the cell suffering has been evidenced by Raman spectroscopy and accordingly the electrophysiology shows a reduction at positive stimulations in the cells excitability.

  5. A multidisciplinary approach to study the functional properties of neuron-like cell models constituting a living bio-hybrid system: SH-SY5Y cells adhering to PANI substrate

    Directory of Open Access Journals (Sweden)

    S. Caponi

    2016-11-01

    Full Text Available A living bio-hybrid system has been successfully implemented. It is constituted by neuroblastic cells, the SH-SY5Y human neuroblastoma cells, adhering to a poly-anyline (PANI a semiconductor polymer with memristive properties. By a multidisciplinary approach, the biocompatibility of the substrate has been analyzed and the functionality of the adhering cells has been investigated. We found that the PANI films can support the cell adhesion. Moreover, the SH-SY5Y cells were successfully differentiated into neuron-like cells for in vitro applications demonstrating that PANI can also promote cell differentiation. In order to deeply characterize the modifications of the bio-functionality induced by the cell-substrate interaction, the functional properties of the cells have been characterized by electrophysiology and Raman spectroscopy. Our results confirm that the PANI films do not strongly affect the general properties of the cells, ensuring their viability without toxic effects on their physiology. Ascribed to the adhesion process, however, a slight increase of the markers of the cell suffering has been evidenced by Raman spectroscopy and accordingly the electrophysiology shows a reduction at positive stimulations in the cells excitability.

  6. Hybrid Model Predictive Control for Optimizing Gestational Weight Gain Behavioral Interventions.

    Science.gov (United States)

    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.

  7. Transmission network expansion planning based on hybridization model of neural networks and harmony search algorithm

    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.

  8. Modelling and Optimising the Value of a Hybrid Solar-Wind System

    Science.gov (United States)

    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.

  9. 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

  10. A NOVEL APPROACH FOR DENOISING ELECTROCARDIOGRAM SIGNAL USING HYBRID TECHNIQUE

    Directory of Open Access Journals (Sweden)

    HARJEET KAUR

    2017-07-01

    Full Text Available One of the core concerns in the area of Biomedical Signal Processing has been the extraction of pure cardiologic indices from noisy measurements. Frequently, it is found that treatment of the patient suffers due to improper information of Electrocardiogram (ECG signal since it is highly prone to the disturbances such as noise contamination, artifacts and other signals interference. Therefore, an ECG signal must be denoised so that the misrepresentations can be eliminated from the original signal for the perfect diagnosing of the condition and performance of the heart. In this paper, hybrid techniques including combination of Median filter, Savitzky-Golay filter and Extended Kalman filter along with Discrete Wavelet Transform have been focussed for separation of noise from ECG signal. The hybrid methods for obtaining a clean ECG signal are designed and implemented in MATLAB environment by utilizing MIT-BIH Arrhythmia database. Performance of different algorithms is compared on the basis of signal to noise ratio (SNR and mean square error (MSE and it has been noticed that Extended Kalman filter followed by Discrete Wavelet Transform provides better results for both the parameters.

  11. Multiview coding mode decision with hybrid optimal stopping model.

    Science.gov (United States)

    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.

  12. Design, Operation and Control Modelling of SOFC/GT Hybrid Systems

    OpenAIRE

    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...

  13. A hybrid solution approach for a multi-objective closed-loop logistics network under uncertainty

    Science.gov (United States)

    Mehrbod, Mehrdad; Tu, Nan; Miao, Lixin

    2014-09-01

    The design of closed-loop logistics (forward and reverse logistics) has attracted growing attention with the stringent pressures of customer expectations, environmental concerns and economic factors. This paper considers a multi-product, multi-period and multi-objective closed-loop logistics network model with regard to facility expansion as a facility location-allocation problem, which more closely approximates real-world conditions. A multi-objective mixed integer nonlinear programming formulation is linearized by defining new variables and adding new constraints to the model. By considering the aforementioned model under uncertainty, this paper develops a hybrid solution approach by combining an interactive fuzzy goal programming approach and robust counterpart optimization based on three well-known robust counterpart optimization formulations. Finally, this paper compares the results of the three formulations using different test scenarios and parameter-sensitive analysis in terms of the quality of the final solution, CPU time, the level of conservatism, the degree of closeness to the ideal solution, the degree of balance involved in developing a compromise solution, and satisfaction degree.

  14. A stage structured hybrid model for within-host emerging infectious disease modelling

    Directory of Open Access Journals (Sweden)

    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.

  15. 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.

  16. HYBRID MODELS FOR TRAJECTORY ERROR MODELLING IN URBAN ENVIRONMENTS

    Directory of Open Access Journals (Sweden)

    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.

  17. A hybrid level set/volume-of-fluid approach for simulation of nearshore hydrodynamics

    Science.gov (United States)

    Bakhtyar, R.; Kees, C. E.; Miller, C. T.; Farthing, M. W.

    2013-12-01

    Wave breaking can play an important role in hydrodynamics near the coast and subsequently can be a factor in beach morphodynamics. However, an accurate understanding of the wave breaking and mixing of water and air at the free surface has yet to be achieved. Numerical models, based on single phase flow, have been used to study the nearshore hydrodynamics, but air-water two-phase flow is not well understood, and so there is a need for additional investigation into the details of this type of flow. The main objective of this study was to de¬velop further understanding of surf-swash zone hydrodynamics under a variety of wave forcing conditions. The main tool used was a com-prehensive two-phase numerical model - combining two-dimensional wave solver with the state-of-the-art 'Eulerian' technique for free surface modeling- of nearshore hydrodynamics. Surf-swash zone hydrodynamics were modeled using the Navier-Stokes equations, combined with turbulence closure model and a hybrid level set/volume-of-fluid approach. The hybrid level set/volume-of-fluid approach combines the accuracy and conceptual simplicity of front-tracking using level set methods with the conservation properties of volume-of fluid methods. The solver was discretized using a finite element method. The model's grid convergence and refinement were investigated in order to obtain high accuracy at an acceptable computational cost while retain robustness. The numerical set-up was tested against the well-known experimental data, with good agreement found. The numerical results showed that the maximum turbulent kinetic energy, turbulence dissipation rate, and velocity components are located near the free surface in the wave breaking area. The model is appropriate for the simulation of air-water mixing flow, undertow distribution, and turbulence characteristics in the nearshore zone. Generally, the analysis shows that, with reasonable hypotheses, it is possible to simulate the surf-swash zone hydrodynamics

  18. A hybrid QFD-based approach in addressing supplier selection problem in product improvement process

    Directory of Open Access Journals (Sweden)

    Mehdi Rajabi Asadabadi

    2014-08-01

    Full Text Available This paper is about creating a hybrid QFD-based approach in which the best supplier is selected considering changing customer needs. In most previous studies employing a QFD approach, the possibility of changing customer needs is ignored. On the other hand, supplier selection is a challenging problem that could have been addressed by such a QFD. This paper attempts to create a hybrid QFD-based approach in which the internal relations between the elements are considered. It connects the new QFD to suppliers’ qualifications to create a hybrid supplier selection process. The best suppliers are selected based on the priorities of customer needs for each level of the product improvement plan. When a product is to be developed, the proposed methodology seems to create an efficient solution for supplier selection problem with respect to quality factors.

  19. Hybrid BARC approaches for FEOL and BEOL intergration

    Science.gov (United States)

    Perez, Willie; Turner, Stephen; Brakensiek, Nick; Mills, Lynne; Wilson, Larry; Popa, Paul

    2005-05-01

    Spin on bottom anti-reflective coatings were introduced to the semiconductor industry about 20 years ago to help control substrate reflectivity, improve critical dimension (CD) control, and, most importantly, improve depth of focus window, thus improving throughput and yields. Bottom anti-reflective coating (BARC) materials are either inorganic or organic in nature. Inorganic BARCs are chemical vapor deposition (CVD) films that work on the principal of destructive interference to eliminate reflectivity and demand tight thickness control in the BARC layer. In contrast, organic BARCs are generally spin-on polymeric materials that reduce substrate reflectivity by absorbing exposure radiation to provide greater latitude in thickness control. As an added benefit, organic spin-on BARCs also provide a level of planarization efficiency prior to photoresist deposition to improve depth of focus and process window in the photolithography step. As the feature sizes continue to shrink, etching becomes very challenging due to thin ArF photoresist (PR) layers which are much less etch resistant compared to KrF photoresists. The reduced thickness, as well as the reduced etch resistance, of the PR makes it nearly impossible to use the PR as both an imaging and a pattern transfer layer. This has lead to the development of a new class of spin-on "hybrid" BARC materials which not only have improved etch selectivity to the PR due to inorganic functionality but also have the absorbing properties, and hence offer greater process latitude. Hybrid BARC (H-BARC) materials enable the BARC layer to act as both an anti-reflective coating and as a pattern transfer layer in standard etch-back integration schemes. Due to the polymeric functionality associated with H-BARCs, these materials have exceptional gap-fill and planarization properties and can also be used in via-first dual damascene applications where similar etch characteristics between interlayer dielectric materials and the via

  20. Strategies for efficient numerical implementation of hybrid multi-scale agent-based models to describe biological systems.

    Science.gov (United States)

    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.

  1. Neural system modeling and simulation using Hybrid Functional Petri Net.

    Science.gov (United States)

    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.

  2. Hybrid Quantum-Classical Approach to Quantum Optimal Control.

    Science.gov (United States)

    Li, Jun; Yang, Xiaodong; Peng, Xinhua; Sun, Chang-Pu

    2017-04-14

    A central challenge in quantum computing is to identify more computational problems for which utilization of quantum resources can offer significant speedup. Here, we propose a hybrid quantum-classical scheme to tackle the quantum optimal control problem. We show that the most computationally demanding part of gradient-based algorithms, namely, computing the fitness function and its gradient for a control input, can be accomplished by the process of evolution and measurement on a quantum simulator. By posing queries to and receiving answers from the quantum simulator, classical computing devices update the control parameters until an optimal control solution is found. To demonstrate the quantum-classical scheme in experiment, we use a seven-qubit nuclear magnetic resonance system, on which we have succeeded in optimizing state preparation without involving classical computation of the large Hilbert space evolution.

  3. Reverse engineering cellular decisions for hybrid reconfigurable network modeling

    Science.gov (United States)

    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.

  4. Integrative approaches to hybrid multifunctional materials: from multidisciplinary research to applied technologies.

    Science.gov (United States)

    Nicole, Lionel; Rozes, Laurence; Sanchez, Clément

    2010-08-03

    Achieving nanostructured or hierarchical hybrid architectures involves cross-cutting synthetic strategies where all facettes of chemistry (organic, polymers, solid-state, physical, materials chemistries, biochemistry, etc..), soft matter and ingenious processing are synergistically coupled. These cross-cutting approaches are in the vein of bio-inspired synthesis strategies where the integration of different areas of expertise allows the development of complex systems of various shapes with perfect mastery at different size scales, composition, porosity, functionality, and morphology. These strategies coined "Integrative Chemistry" open a land of opportunities to create advanced hybrid materials with organic-inorganic or bio-inorganic character. These hybrid materials represent not only a new field of basic research where creative chemists can express themselves, but also, via their remarkable new properties and multifunctional nature, hybrids are allowing the emergence of innovative industrial applications in extremely diverse fields.

  5. Preliminary analysis on hybrid Box-Jenkins - GARCH modeling in forecasting gold price

    Science.gov (United States)

    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.

  6. 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

  7. A New Efficient Hybrid Intelligent Model for Biodegradation Process of DMP with Fuzzy Wavelet Neural Networks

    Science.gov (United States)

    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.

  8. Hybrid-model for computed tomography simulations and post-patient collimator design

    Science.gov (United States)

    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.

  9. A hybrid wavelet transform based short-term wind speed forecasting approach.

    Science.gov (United States)

    Wang, Jujie

    2014-01-01

    It is important to improve the accuracy of wind speed forecasting for wind parks management and wind power utilization. In this paper, a novel hybrid approach known as WTT-TNN is proposed for wind speed forecasting. In the first step of the approach, a wavelet transform technique (WTT) is used to decompose wind speed into an approximate scale and several detailed scales. In the second step, a two-hidden-layer neural network (TNN) is used to predict both approximated scale and detailed scales, respectively. In order to find the optimal network architecture, the partial autocorrelation function is adopted to determine the number of neurons in the input layer, and an experimental simulation is made to determine the number of neurons within each hidden layer in the modeling process of TNN. Afterwards, the final prediction value can be obtained by the sum of these prediction results. In this study, a WTT is employed to extract these different patterns of the wind speed and make it easier for forecasting. To evaluate the performance of the proposed approach, it is applied to forecast Hexi Corridor of China's wind speed. Simulation results in four different cases show that the proposed method increases wind speed forecasting accuracy.

  10. A Hybrid Wavelet Transform Based Short-Term Wind Speed Forecasting Approach

    Directory of Open Access Journals (Sweden)

    Jujie Wang

    2014-01-01

    Full Text Available It is important to improve the accuracy of wind speed forecasting for wind parks management and wind power utilization. In this paper, a novel hybrid approach known as WTT-TNN is proposed for wind speed forecasting. In the first step of the approach, a wavelet transform technique (WTT is used to decompose wind speed into an approximate scale and several detailed scales. In the second step, a two-hidden-layer neural network (TNN is used to predict both approximated scale and detailed scales, respectively. In order to find the optimal network architecture, the partial autocorrelation function is adopted to determine the number of neurons in the input layer, and an experimental simulation is made to determine the number of neurons within each hidden layer in the modeling process of TNN. Afterwards, the final prediction value can be obtained by the sum of these prediction results. In this study, a WTT is employed to extract these different patterns of the wind speed and make it easier for forecasting. To evaluate the performance of the proposed approach, it is applied to forecast Hexi Corridor of China’s wind speed. Simulation results in four different cases show that the proposed method increases wind speed forecasting accuracy.

  11. Multi-scenario analysis: a new hybrid approach to inform earthquake disaster risk planning

    Science.gov (United States)

    Robinson, Tom; Rosser, Nick

    2017-04-01

    Current earthquake risk assessments take one of two approaches: deterministic (scenario) or probabilistic, but both have notable limitations. Deterministic approaches are limited by a focus on a single scenario, as the results of the analysis are only relevant to the scenario selected, which is unlikely to represent the earthquake that occurs next, nor its impacts. Alternatively, probabilistic approaches are sensitive to the completeness of evidence of past earthquakes, which is inadequate in most seismically-active parts of the world. Consequently, earthquake risk assessments have failed to inform planning prior to major earthquakes such as the 2005 Kashmir and 2008 Wenchuan disasters. This study presents a new hybrid approach for earthquake risk assessments that maintains the high detail of deterministic approaches but considers numerous scenarios simultaneously, similar to probabilistic approaches. The aim of such an approach is to identify impacts that recur in multiple scenarios, or impacts that occur irrespective of the given scenario. Such recurring impacts can be considered the most likely consequences to occur in the next earthquake, despite the precise details of the next earthquake remaining unknown. To demonstrate this, we apply the method to Nepal, one of the most seismically at-risk nations in the world. We model 30 different potential earthquake scenarios throughout the country with magnitude ranges 8.6 to 7.0 for three different times of day (night-time, mid-week day-time, weekend day-time) for a total of 90 different scenarios. By combining the results from each scenario for individual districts, we are able to assess which districts are most at risk of losses in the next earthquake. By focussing on fatalities as a percentage of total population, we rank each district by its: (a) median modelled fatalities; (b) percentage of scenarios with >0 fatalities; (c) inter-quartile range of modelled fatalities; and (d) maximum modelled fatalities. Combining

  12. A Hybrid Multiple Criteria Decision Making Model for Supplier Selection

    OpenAIRE

    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...

  13. A Novel of Hybrid Maintenance Management Models for Industrial Applications

    OpenAIRE

    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...

  14. Hybrid adiabatic potentials in the QCD string model

    OpenAIRE

    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.

  15. A light neutralino in hybrid models of supersymmetry breaking

    CERN Document Server

    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.

  16. Hybrid Mesons Masses in a Quark-Gluon Constituent Model

    CERN Document Server

    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.

  17. 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

  18. 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.

  19. Modeling Hybrid Systems in the Concurrent Constraint Paradigm

    Directory of Open Access Journals (Sweden)

    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.

  20. Hybrid modeling for quality by design and PAT-benefits and challenges of applications in biopharmaceutical industry.

    Science.gov (United States)

    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.

  1. 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.

  2. Template-Assisted Metabolic Reconstruction and Assembly of Hybrid Bacterial Models.

    Science.gov (United States)

    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.

  3. 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...

  4. DyHAP: Dynamic Hybrid ANFIS-PSO Approach for Predicting Mobile Malware.

    Directory of Open Access Journals (Sweden)

    Firdaus Afifi

    Full Text Available To deal with the large number of malicious mobile applications (e.g. mobile malware, a number of malware detection systems have been proposed in the literature. In this paper, we propose a hybrid method to find the optimum parameters that can be used to facilitate mobile malware identification. We also present a multi agent system architecture comprising three system agents (i.e. sniffer, extraction and selection agent to capture and manage the pcap file for data preparation phase. In our hybrid approach, we combine an adaptive neuro fuzzy inference system (ANFIS and particle swarm optimization (PSO. Evaluations using data captured on a real-world Android device and the MalGenome dataset demonstrate the effectiveness of our approach, in comparison to two hybrid optimization methods which are differential evolution (ANFIS-DE and ant colony optimization (ANFIS-ACO.

  5. DyHAP: Dynamic Hybrid ANFIS-PSO Approach for Predicting Mobile Malware.

    Science.gov (United States)

    Afifi, Firdaus; Anuar, Nor Badrul; Shamshirband, Shahaboddin; Choo, Kim-Kwang Raymond

    2016-01-01

    To deal with the large number of malicious mobile applications (e.g. mobile malware), a number of malware detection systems have been proposed in the literature. In this paper, we propose a hybrid method to find the optimum parameters that can be used to facilitate mobile malware identification. We also present a multi agent system architecture comprising three system agents (i.e. sniffer, extraction and selection agent) to capture and manage the pcap file for data preparation phase. In our hybrid approach, we combine an adaptive neuro fuzzy inference system (ANFIS) and particle swarm optimization (PSO). Evaluations using data captured on a real-world Android device and the MalGenome dataset demonstrate the effectiveness of our approach, in comparison to two hybrid optimization methods which are differential evolution (ANFIS-DE) and ant colony optimization (ANFIS-ACO).

  6. A hybrid-stress finite element approach for stress and vibration analysis in linear anisotropic elasticity

    Science.gov (United States)

    Oden, J. Tinsley; Fly, Gerald W.; Mahadevan, L.

    1987-01-01

    A hybrid stress finite element method is developed for accurate stress and vibration analysis of problems in linear anisotropic elasticity. A modified form of the Hellinger-Reissner principle is formulated for dynamic analysis and an algorithm for the determination of the anisotropic elastic and compliance constants from experimental data is developed. These schemes were implemented in a finite element program for static and dynamic analysis of linear anisotropic two dimensional elasticity problems. Specific numerical examples are considered to verify the accuracy of the hybrid stress approach and compare it with that of the standard displacement method, especially for highly anisotropic materials. It is that the hybrid stress approach gives much better results than the displacement method. Preliminary work on extensions of this method to three dimensional elasticity is discussed, and the stress shape functions necessary for this extension are included.

  7. Hybrid Geoid Model: Theory and Application in Brazil.

    Science.gov (United States)

    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.

  8. 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.

  9. Modelling and forecasting monthly and daily river discharge data using hybrid models and considering autoregressive heteroscedasticity

    Science.gov (United States)

    Szolgayova, Elena

    2010-05-01

    hydrological models. However, the GARCH family of models proved to be suited in removing it only in daily time step. The basic GARCH model was not applicable on any of the time series. In all other investigated cases, the EGARCH(1,1) model had to be used. Unlike in econometric time series, where the so called leverage effect (i.e. the series reacts more strongly to negative changes) is present and pointed out by this model, here the data tends to react more strongly on positive changes. In this particular case it was found, that the general property of hydrological processes, that the rise of discharge is rainfall driven (a highly nonlinear chaotic intermittent process) and the decrease of discharge is ruled by the damping effects of the water storage in the driven system (catchment or river reach), is present also in the hydrological model error series. This shows, that the modelling and forecasting of floods (pulse like rising discharge) is a more demanding task than that of droughts (slowly decreasing flows). Even though the GARCH models did show partial improvements in the modelling and forecasting of flows, they still have several serious disadvantages (such as high sensitivity to the chosen fitting period) and possible further use should be further investigated. These results are of importance with respect to future attempts of modelling of error time series of hydrological models in such hybrid frameworks. They underpin the need of a non-mechanistic approach in the case based analysis of such data and the physical interpretation of statistical modelling results.

  10. Modeling and Density Estimation of an Urban Freeway Network Based on Dynamic Graph Hybrid Automata.

    Science.gov (United States)

    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.

  11. A hybrid clustering approach to recognition of protein families in 114 microbial genomes

    Directory of Open Access Journals (Sweden)

    Gogarten J Peter

    2004-04-01

    Full Text Available Abstract Background Grouping proteins into sequence-based clusters is a fundamental step in many bioinformatic analyses (e.g., homology-based prediction of structure or function. Standard clustering methods such as single-linkage clustering capture a history of cluster topologies as a function of threshold, but in practice their usefulness is limited because unrelated sequences join clusters before biologically meaningful families are fully constituted, e.g. as the result of matches to so-called promiscuous domains. Use of the Markov Cluster algorithm avoids this non-specificity, but does not preserve topological or threshold information about protein families. Results We describe a hybrid approach to sequence-based clustering of proteins that combines the advantages of standard and Markov clustering. We have implemented this hybrid approach over a relational database environment, and describe its application to clustering a large subset of PDB, and to 328577 proteins from 114 fully sequenced microbial genomes. To demonstrate utility with difficult problems, we show that hybrid clustering allows us to constitute the paralogous family of ATP synthase F1 rotary motor subunits into a single, biologically interpretable hierarchical grouping that was not accessible using either single-linkage or Markov clustering alone. We describe validation of this method by hybrid clustering of PDB and mapping SCOP families and domains onto the resulting clusters. Conclusion Hybrid (Markov followed by single-linkage clustering combines the advantages of the Markov Cluster algorithm (avoidance of non-specific clusters resulting from matches to promiscuous domains and single-linkage clustering (preservation of topological information as a function of threshold. Within the individual Markov clusters, single-linkage clustering is a more-precise instrument, discerning sub-clusters of biological relevance. Our hybrid approach thus provides a computationally efficient

  12. Hybrid energy system evaluation in water supply system energy production: neural network approach

    Energy Technology Data Exchange (ETDEWEB)

    Goncalves, Fabio V.; Ramos, Helena M. [Civil Engineering Department, Instituto Superior Tecnico, Technical University of Lisbon, Av. Rovisco Pais, 1049-001, Lisbon (Portugal); Reis, Luisa Fernanda R. [Universidade de Sao Paulo, EESC/USP, Departamento de Hidraulica e Saneamento., Avenida do Trabalhador Saocarlense, 400, Sao Carlos-SP (Brazil)

    2010-07-01

    Water supply systems are large consumers of energy and the use of hybrid systems for green energy production is this new proposal. This work presents a computational model based on neural networks to determine the best configuration of a hybrid system to generate energy in water supply systems. In this study the energy sources to make this hybrid system can be the national power grid, micro-hydro and wind turbines. The artificial neural network is composed of six layers, trained to use data generated by a model of hybrid configuration and an economic simulator - CES. The reason for the development of an advanced model of forecasting based on neural networks is to allow rapid simulation and proper interaction with hydraulic and power model simulator - HPS. The results show that this computational model is useful as advanced decision support system in the design of configurations of hybrid power systems applied to water supply systems, improving the solutions in the development of its global energy efficiency.

  13. 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.

  14. A hybrid deep neural network and physically based distributed model for river stage prediction

    Science.gov (United States)

    hitokoto, Masayuki; sakuraba, Masaaki

    2016-04-01

    architecture of the ANN model, sensitivity analysis was done by the case study approach. The prediction result was evaluated by the superior 4 flood events by the leave-one-out cross validation. The prediction result of the basic 4 layer ANN was better than the conventional 3 layer ANN model. However, the result did not reproduce well the biggest flood event, supposedly because the lack of the sufficient high-water level flood event in the training data. The result of the hybrid model outperforms the basic ANN model and distributed model, especially improved the performance of the basic ANN model in the biggest flood event.

  15. A Game-Theoretic approach to Fault Diagnosis of Hybrid Systems

    Directory of Open Access Journals (Sweden)

    Davide Bresolin

    2011-06-01

    Full Text Available Physical systems can fail. For this reason the problem of identifying and reacting to faults has received a large attention in the control and computer science communities. In this paper we study the fault diagnosis problem for hybrid systems from a game-theoretical point of view. A hybrid system is a system mixing continuous and discrete behaviours that cannot be faithfully modeled neither by using a formalism with continuous dynamics only nor by a formalism including only discrete dynamics. We use the well known framework of hybrid automata for modeling hybrid systems, and we define a Fault Diagnosis Game on them, using two players: the environment and the diagnoser. The environment controls the evolution of the system and chooses whether and when a fault occurs. The diagnoser observes the external behaviour of the system and announces whether a fault has occurred or not. Existence of a winning strategy for the diagnoser implies that faults can be detected correctly, while computing such a winning strategy corresponds to implement a diagnoser for the system. We will show how to determine the existence of a winning strategy, and how to compute it, for some decidable classes of hybrid automata like o-minimal hybrid automata.

  16. Hybrid approach for attenuation correction in PET/MR scanners

    Energy Technology Data Exchange (ETDEWEB)

    Santos Ribeiro, A., E-mail: afribeiro@fc.ul.pt [Institute of Biophysics and Biomedical Engineering, Faculty of Sciences, University of Lisbon, Lisbon (Portugal); Rota Kops, E.; Herzog, H. [Institute of Neuroscience and Medicine, Forschungszentrum Juelich, Juelich (Germany); Almeida, P. [Institute of Biophysics and Biomedical Engineering, Faculty of Sciences, University of Lisbon, Lisbon (Portugal)

    2014-01-11

    Aim: Attenuation correction (AC) of PET images is still one of the major limitations of hybrid PET/MR scanners. Different methods have been proposed to obtain the AC map from morphological MR images. Although, segmentation methods normally fail to differentiate air and bone regions, while template or atlas methods usually cannot accurately represent regions anatomically different from the template image. In this study a feed forward neural network (FFNN) algorithm is presented which directly outputs the attenuation coefficients by non-linear regression of the images acquired with an ultrashort echo time (UTE) sequence guided by the template-based AC map (TAC-map). Materials and methods: MR as well as CT data were acquired in four subjects. The UTE images and the TAC-map were the inputs of the presented FFNN algorithm for training as well as classification. The resulting attenuation maps were compared with CT-based, PNN-based and TAC maps. All the AC maps were used to reconstruct the PET emission data which were then compared for the different methods. Results: For each subject dice coefficients D were calculated between each method and the respective CT-based AC maps. The resulting Ds show higher values for all FFNN-based tissues comparatively to both TAC-based and PNN-based methods, particularly for bone tissue (D=0.77, D=0.51 and D=0.71, respectively). The AC-corrected PET images with the FFNN-based map show an overall lower relative difference (RD=3.90%) than those AC-corrected with the PNN-based (RD=4.44%) or template-based (RD=4.43%) methods. Conclusion: Our results show that an enhancement of current methods can be performed by combining both information of new MR image sequence techniques and general information provided from template techniques. Nevertheless, the number of tested subjects is statistically low and current analysis for a larger dataset is being carried out.

  17. 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.

  18. Lower hybrid current drive: an overview of simulation models, benchmarking with experiment, and predictions for future devices

    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)

  19. Students' Game Performance Improvements during a Hybrid Sport Education-Step-Game-Approach Volleyball Unit

    Science.gov (United States)

    Araújo, Rui; Mesquita, Isabel; Hastie, Peter; Pereira, Cristiana

    2016-01-01

    The purpose of this study was to examine a hybrid combination of sport education and the step-game-approach (SGA) on students' gameplay performance in volleyball, taking into account their sex and skill-level. Seventeen seventh-grade students (seven girls, 10 boys, average age 11.8) participated in a 25-lesson volleyball season, in which the…

  20. On the Use of Hybrid Development Approaches in Software and Systems Development

    DEFF Research Database (Denmark)

    Kuhrmann, Marco; Münch, Jürgen; Diebold, Philipp

    2016-01-01

    embody this framework with more agile (and/or lean) practices to keep their flexibility. The paper at hand provides insights into the HELENA study with which we aim to investigate the use of “Hybrid dEveLopmENt Approaches in software systems development”. We present the survey design and initial findings...

  1. The business case for condition-based maintenance: a hybrid (non-) financial approach

    NARCIS (Netherlands)

    Tiddens, W.W.; Tinga, T.; Braaksma, A.J.J.; Brouwer, O.; Cepin, Marko; Bris, Radim

    2017-01-01

    Although developing business cases is key for evaluating project success, the costs and benefits of condition-based maintenance (CBM) implementations are often not explicitly defined and evaluated. Using the design science methodology, we developed a hybrid business case approach to help managers

  2. Hybrid approach for complex coronary artery and valve disease: a clinical follow-up study.

    Science.gov (United States)

    Peels, J O J; Jessurun, G A J; Boonstra, P W; Ebels, T; van Veldhuisen, D J; van der Horst, I C C; Zijlstra, F

    2007-01-01

    For patients suffering from complex coronary artery disease (CAD) with or without concomitant valve disease, no evidence is available in the current guidelines to propose a predefined treatment regimen. We sought to assess the clinical impact of an unconventional or extended definition of the hybrid approach that combines percutaneous coronary intervention (PCI) and cardiac surgery in subjects suffering from severe solitary CAD or combined with valve disease. Between July 2002 and August 2004, 18 consecutive patients with complex CAD with or without significant valve disease who qualified for a hybrid approach were enrolled in a clinical follow-up study. Four patients eventually did not complete the proposed interventions. One patient refused treatment after inclusion, one patient died before treatment could be undertaken and two patients died after surgery but before PCI. In the other 14 cases combined treatment was technically successful. After a mean follow-up period of 15alpha5 months two patients had died, one due to sudden cardiac death and one of a noncardiac cause. No other major adverse clinical events were reported. A marked increase in quality of life was reported in those alive. Hybrid approach had a favourable long-term outcome in patients with complex cardiovascular disease undergoing successful treatment; however, this was observed at the expense of significant periprocedural mortality in these high-risk subjects. Therefore we believe that hybrid approaches may provide an alternative for selected cases. (Neth Heart J 2007;15:329-4.).

  3. A hybrid approach for quantifying aortic valve stenosis using impedance cardiography and echocardiography.

    Science.gov (United States)

    Daralammouri, Yunis; Ayoub, Khubaib; Badrieh, Najwan; Lauer, Bernward

    2016-01-22

    Impedance cardiography (IC) is a noninvasive modality that utilizes changes in impedance across the thorax to assess hemodynamic parameters, including stroke volume (SV). This study compared aortic valve area (AVA) as assessed by a hybrid approach of transthoracic echocardiography (TTE) and impedance cardiography (IC) to AVA determined at cardiac catheterization using the Gorlin equation. A total of 30 patients with moderate to severe aortic stenosis underwent AVA measurement using two different approaches: using the continuity equation (CE) in a hybrid method combining IC and TTE (AVA = stroke by volume impedance cardiography/trans-aortic-VTI) and using the Gorlin equation. Patient age ranged from 37 to 82 years (mean 48); there were 21 men and 9 women. Twenty-five patients were in sinus rhythm, and five had atrial fibrillation. There was no statistically significant difference for the mean AVA between the two methods (0.7 ± 0.24 cm(2) using the Gorlin equation versus 0.7 ± 0.23 cm(2) using the hybrid approach, p = 0.17; r = 0.76, p hybrid method using impedance cardiography and TTE is a reasonable, clinically applicable approach to evaluate AVA and has significant correlation to invasive measurement using the Gorlin equation.

  4. TwitterNEED: a hybrid approach for named entity extraction and disambiguation for tweets

    NARCIS (Netherlands)

    Habib, Mena Badieh; van Keulen, Maurice

    Twitter is a rich source of continuously and instantly updated information. Shortness and informality of tweets are challenges for Natural Language Processing tasks. In this paper, we present TwitterNEED, a hybrid approach for Named Entity Extraction and Named Entity Disambiguation for tweets. We

  5. A hybrid partial least squares and random forest approach to ...

    African Journals Online (AJOL)

    Up to date forest inventory data has become increasingly essential for sustainable planning and management of a commercial forest plantation. Forest inventory data may be collected in the form of traditional field based approaches or using remote sensing techniques. The aim of this study was to examine the utility of the ...

  6. Hybrid automata models of cardiac ventricular electrophysiology for real-time computational applications.

    Science.gov (United States)

    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.

  7. A Hybrid Stochastic Approach for Self-Location of Wireless Sensors in Indoor Environments

    Directory of Open Access Journals (Sweden)

    Alejandro Canovas

    2009-05-01

    Full Text Available Indoor location systems, especially those using wireless sensor networks, are used in many application areas. While the need for these systems is widely proven, there is a clear lack of accuracy. Many of the implemented applications have high errors in their location estimation because of the issues arising in the indoor environment. Two different approaches had been proposed using WLAN location systems: on the one hand, the so-called deductive methods take into account the physical properties of signal propagation. These systems require a propagation model, an environment map, and the position of the radio-stations. On the other hand, the so-called inductive methods require a previous training phase where the system learns the received signal strength (RSS in each location. This phase can be very time consuming. This paper proposes a new stochastic approach which is based on a combination of deductive and inductive methods whereby wireless sensors could determine their positions using WLAN technology inside a floor of a building. Our goal is to reduce the training phase in an indoor environment, but, without an loss of precision. Finally, we compare the measurements taken using our proposed method in a real environment with the measurements taken by other developed systems. Comparisons between the proposed system and other hybrid methods are also provided.

  8. Multiobjective muffler shape optimization with hybrid acoustics modeling.

    Science.gov (United States)

    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

  9. Hybrid Adaptive Flight Control with Model Inversion Adaptation

    Science.gov (United States)

    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.

  10. 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.

  11. A hybrid approach to incorporating climate change and variability into climate scenario for impact assessments

    OpenAIRE

    Gebretsadik, Yohannes; Strzepek, Kenneth; Schlosser, C. Adam

    2014-01-01

    Traditional 'delta-change' approach of scenario generation for climate change impact assessment to water resources strongly depends on the selected base-case observed historical climate conditions that the climate shocks are to be super-imposed. This method disregards the combined effect of climate change and the inherent hydro-climatological variability in the system. Here we demonstrated a hybrid uncertainty approach in which uncertainties in historical climate variability are combined with...

  12. Use of a novel hybrid approach to salvage an attempted transcatheter pulmonary valve implant.

    Science.gov (United States)

    Berman, Darren P; Burke, Redmond; Zahn, Evan M

    2012-06-01

    Transcatheter pulmonary valve implantation in the setting of right ventricle-to-pulmonary artery conduit dysfunction is a relatively new procedure with encouraging early and midterm results. Malpositioning of the valve during implantation is a potentially serious complication. This report describes a case in which valve malpositioning was avoided by the use of a unique hybrid approach. This approach may prove to be useful for a select group of patients requiring pulmonary valve replacement.

  13. A Bio-Inspired Hybrid Thermal Management Approach for 3-D Network-on-Chip Systems.

    Science.gov (United States)

    Dash, Ranjita; Risco-Martin, Jose L; Turuk, Ashok Kumar; Ayala, Jose L; Pangracious, Vinod; Majumdar, Amartya

    2017-12-01

    3-D network-on-chip (NoC) systems are getting popular among the integrated circuit (IC) manufacturer because of reduced latency, heterogeneous integration of technologies on a single chip, high yield, and consumption of less interconnecting power. However, the addition of functional units in the -direction has resulted in higher on-chip temperature and appearance of local hotspots on the die. The increase in temperature degrades the performance, lifetime, and reliability, and increases the maintenance cost of 3-D ICs. To keep the heat within an acceptable limit, floorplanning is the widely accepted solution. Proper arrangement of functional units across different layers can lead to uniform thermal distribution in the chip. For systems with high density of elements, few hotspots cannot be eliminated in the floorplanning approach. To overcome, liquid microchannel cooling technology has emerged as an efficient and scalable solution for 3-D NoC. In this paper, we propose a novel hybrid algorithm combining both floorplanning, and liquid microchannel placement to alleviate the hotspots in high-density systems. A mathematical model is proposed to deal with heat transfer due to diffusion and convention. The proposed approach is independent of topology. Three different topologies: 3-D stacked homogeneous mesh architecture, 3-D stacked heterogeneous mesh architecture, and 3-D stacked ciliated mesh architecture are considered to check the effectiveness of the proposed algorithm in hotspot reduction. A thermal comparison is made with and without the proposed thermal management approach for the above architectures considered. It is observed that there is a significant reduction in on-chip temperature when the proposed thermal management approach is applied.

  14. 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.

  15. Optimizing Thermal-Elastic Properties of C/C–SiC Composites Using a Hybrid Approach and PSO Algorithm

    Directory of Open Access Journals (Sweden)

    Yingjie Xu

    2016-03-01

    Full Text Available Carbon fiber-reinforced multi-layered pyrocarbon–silicon carbide matrix (C/C–SiC composites are widely used in aerospace structures. The complicated spatial architecture and material heterogeneity of C/C–SiC composites constitute the challenge for tailoring their properties. Thus, discovering the intrinsic relations between the properties and the microstructures and sequentially optimizing the microstructures to obtain composites with the best performances becomes the key for practical applications. The objective of this work is to optimize the thermal-elastic properties of unidirectional C/C–SiC composites by controlling the multi-layered matrix thicknesses. A hybrid approach based on micromechanical modeling and back propagation (BP neural network is proposed to predict the thermal-elastic properties of composites. Then, a particle swarm optimization (PSO algorithm is interfaced with this hybrid model to achieve the optimal design for minimizing the coefficient of thermal expansion (CTE of composites with the constraint of elastic modulus. Numerical examples demonstrate the effectiveness of the proposed hybrid model and optimization method.

  16. A hybrid nudging-ensemble Kalman filter approach to data assimilation. Part I: application in the Lorenz system

    Directory of Open Access Journals (Sweden)

    Lili Lei

    2012-05-01

    Full Text Available A hybrid data assimilation approach combining nudging and the ensemble Kalman filter (EnKF for dynamic analysis and numerical weather prediction is explored here using the non-linear Lorenz three-variable model system with the goal of a smooth, continuous and accurate data assimilation. The hybrid nudging-EnKF (HNEnKF computes the hybrid nudging coefficients from the flow-dependent, time-varying error covariance matrix from the EnKF's ensemble forecasts. It extends the standard diagonal nudging terms to additional off-diagonal statistical correlation terms for greater inter-variable influence of the innovations in the model's predictive equations to assist in the data assimilation process. The HNEnKF promotes a better fit of an analysis to data compared to that achieved by either nudging or incremental analysis update (IAU. When model error is introduced, it produces similar or better root mean square errors compared to the EnKF while minimising the error spikes/discontinuities created by the intermittent EnKF. It provides a continuous data assimilation with better inter-variable consistency and improved temporal smoothness than that of the EnKF. Data assimilation experiments are also compared to the ensemble Kalman smoother (EnKS. The HNEnKF has similar or better temporal smoothness than that of the EnKS, and with much smaller central processing unit (CPU time and data storage requirements.

  17. Aerodynamic Shape Optimization Design of Wing-Body Configuration Using a Hybrid FFD-RBF Parameterization Approach

    Science.gov (United States)

    Liu, Yuefeng; Duan, Zhuoyi; Chen, Song

    2017-10-01

    Aerodynamic shape optimization design aiming at improving the efficiency of an aircraft has always been a challenging task, especially when the configuration is complex. In this paper, a hybrid FFD-RBF surface parameterization approach has been proposed for designing a civil transport wing-body configuration. This approach is simple and efficient, with the FFD technique used for parameterizing the wing shape and the RBF interpolation approach used for handling the wing body junction part updating. Furthermore, combined with Cuckoo Search algorithm and Kriging surrogate model with expected improvement adaptive sampling criterion, an aerodynamic shape optimization design system has been established. Finally, the aerodynamic shape optimization design on DLR F4 wing-body configuration has been carried out as a study case, and the result has shown that the approach proposed in this paper is of good effectiveness.

  18. A hybrid DEM-SPH model for deformable landslide and its generated surge waves

    Science.gov (United States)

    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.

  19. Interval forecasts of a novelty hybrid model for wind speeds

    Directory of Open Access Journals (Sweden)

    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.

  20. Hybrid perturbation methods based on statistical time series models

    Science.gov (United States)

    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.

  1. KNGEOID14: A national hybrid geoid model in Korea

    Science.gov (United States)

    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.

  2. A Hybrid Sensing Approach for Pure and Adulterated Honey Classification

    Directory of Open Access Journals (Sweden)

    Ammar Zakaria

    2012-10-01

    Full Text Available This paper presents a comparison between data from single modality and fusion methods to classify Tualang honey as pure or adulterated using Linear Discriminant Analysis (LDA and Principal Component Analysis (PCA statistical classification approaches. Ten different brands of certified pure Tualang honey were obtained throughout peninsular Malaysia and Sumatera, Indonesia. Various concentrations of two types of sugar solution (beet and cane sugar were used in this investigation to create honey samples of 20%, 40%, 60% and 80% adulteration concentrations. Honey data extracted from an electronic nose (e-nose and Fourier Transform Infrared Spectroscopy (FTIR were gathered, analyzed and compared based on fusion methods. Visual observation of classification plots revealed that the PCA approach able to distinct pure and adulterated honey samples better than the LDA technique. Overall, the validated classification results based on FTIR data (88.0% gave higher classification accuracy than e-nose data (76.5% using the LDA technique. Honey classification based on normalized low-level and intermediate-level FTIR and e-nose fusion data scored classification accuracies of 92.2% and 88.7%, respectively using the Stepwise LDA method. The results suggested that pure and adulterated honey samples were better classified using FTIR and e-nose fusion data than single modality data.

  3. 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...

  4. Ionocovalency and Applications 1. Ionocovalency Model and Orbital Hybrid Scales

    Directory of Open Access Journals (Sweden)

    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.

  5. A hybrid partial least squares and random forest approach to ...

    African Journals Online (AJOL)

    Nicole Reddy

    Satellite based remote sensing data have been used to predict .... Equation (1). The linear regression model is then fit to the latent variables known as the PLS factors in an orthogonal space (M) (Equation 2). = 0 + ∑ ... mean square error (RMSE) for the validation sample data were computed (Equation 3). Dataset.

  6. A hybrid approach on the management of crop pests | Onuodu ...

    African Journals Online (AJOL)

    This algorithm has been implemented using JAVA and MATLAB. The new method has been applied on agro-based datasets of soybean and yeast for forming clusters that could help farmers in the management of crop pests. The model developed could be beneficial to Nigerian farmers and the Agro-based industries, ...

  7. A Hybrid Approach to Sign Language Recognition (extended abstract)

    NARCIS (Netherlands)

    Hendriks, E.A.; Reinders, M.J.T.

    2008-01-01

    Methods commonly used for speech and sign language recognition often rely on outputs of Hidden Markov Models (HMM) or Dynamic TimeWarping (DTW) for classification, which aremerely factorized observation likelihoods. Instead, we propose to use Statistical DTW (SDTW) only for warping, while

  8. Modeling and Simulation Based on the Hybrid System of Leasing Equipment Optimal Allocation

    Directory of Open Access Journals (Sweden)

    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.

  9. Assessment of the hybrid propagation model, Volume 2: Comparison with the Integrated Noise Model

    Science.gov (United States)

    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...

  10. A Hybrid Harmony Search Algorithm Approach for Optimal Power Flow

    Directory of Open Access Journals (Sweden)

    Mimoun YOUNES

    2012-08-01

    Full Text Available Optimal Power Flow (OPF is one of the main functions of Power system operation. It determines the optimal settings of generating units, bus voltage, transformer tap and shunt elements in Power System with the objective of minimizing total production costs or losses while the system is operating within its security limits. The aim of this paper is to propose a novel methodology (BCGAs-HSA that solves OPF including both active and reactive power dispatch It is based on combining the binary-coded genetic algorithm (BCGAs and the harmony search algorithm (HSA to determine the optimal global solution. This method was tested on the modified IEEE 30 bus test system. The results obtained by this method are compared with those obtained with BCGAs or HSA separately. The results show that the BCGAs-HSA approach can converge to the optimum solution with accuracy compared to those reported recently in the literature.

  11. Two stage hybrid approach for complex aortic coarctation repair

    Directory of Open Access Journals (Sweden)

    Crockett James

    2009-02-01

    Full Text Available Abstract Background Management of an adult patient with aortic coarctation and an associated cardiac pathology poses a great surgical challenge since there are no standard guidelines for the therapy of such complex pathology. Debate exists not only on which lesion should be corrected first, but also upon the type and timing of the procedure. Surgery can be one- or two-staged. Both of these strategies are accomplice with elevate morbidity and mortality. Case report In the face of such an extended surgical approach, balloon dilatation seems preferable for treatment of severe aortic coarctation. We present an adult male patient with aortic coarctation combined with ascending aorta aneurysm and concomitant aortic valve regurgitation. The aortic coarctation was corrected first, using percutaneous balloon dilatation; and in a second stage the aortic regurgitation and ascending aorta aneurysm was treated by Bentall procedure. The patients' postoperative period was uneventful. Three years after the operation he continues to do well.

  12. 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

  13. Rotating hybrid stars with the Dyson-Schwinger quark model

    Science.gov (United States)

    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.

  14. 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...

  15. The Hybrid Airline Model. Generating Quality for Passengers

    Directory of Open Access Journals (Sweden)

    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.

  16. 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....

  17. Minimally Invasive Treatment of the Thoracic Spine Disease: Completely Percutaneous and Hybrid Approaches

    Directory of Open Access Journals (Sweden)

    Tamburrelli Francesco Ciro

    2013-01-01

    Full Text Available The aim of the study was to evaluate the feasibility of a limited invasive approach for the treatment of upper thoracic spine disease. Seven patients with type-A thoracic fractures and three with tumors underwent long thoracic stabilization through a minimally invasive approach. Four patients underwent a completely percutaneous approach while the other three underwent a modified hybrid technique, a combination of percutaneous and open approach. The hybrid constructs were realized using a percutaneous approach to the spine distally to the spinal lesion and by open approach proximally. In two patients, the stabilization was extended proximally up to the cervical spine. Clinical and radiographic assessment was performed during the first year after the operation at 3, 6, and 12 months. No technically related complications were seen. The postoperative recovery was rapid even in the tumor patients with neurologic impairment. Blood loss was irrelevant. At one-year follow-up there was no loosening or breakage of the screws or failure of the implants. When technically feasible a completely percutaneous approach has to be taken in consideration; otherwise, a combined open-percutaneous approach could be planned to minimize the invasivity of a completely open approach to the thoracic spine.

  18. A bottom-up approach for the synthesis of highly ordered fullerene-intercalated graphene hybrids

    Directory of Open Access Journals (Sweden)

    Dimitrios eGournis

    2015-02-01

    Full Text Available Much of the research effort on graphene focuses on its use as a building block for the development of new hybrid nanostructures with well-defined dimensions and properties suitable for applications such as gas storage, heterogeneous catalysis, gas/liquid separations, nanosensing and biomedicine. Towards this aim, here we describe a new bottom-up approach, which combines self-assembly with the Langmuir Schaefer deposition technique to synthesize graphene-based layered hybrid materials hosting fullerene molecules within the interlayer space. Our film preparation consists in a bottom-up layer-by-layer process that proceeds via the formation of a hybrid organo-graphene oxide Langmuir film. The structure and composition of these hybrid fullerene-containing thin multilayers deposited on hydrophobic substrates were characterized by a combination of X-ray diffraction, Raman and X-ray photoelectron spectroscopies, atomic force microscopy and conductivity measurements. The latter revealed that the presence of C60 within the interlayer spacing leads to an increase in electrical conductivity of the hybrid material as compared to the organo-graphene matrix alone.

  19. A Lookahead Behavior Model for Multi-Agent Hybrid Simulation

    Directory of Open Access Journals (Sweden)

    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.

  20. Monthly reservoir inflow forecasting using a new hybrid SARIMA genetic programming approach

    Science.gov (United States)

    Moeeni, Hamid; Bonakdari, Hossein; Ebtehaj, Isa

    2017-03-01

    Forecasting reservoir inflow is one of the most important components of water resources and hydroelectric systems operation management. Seasonal autoregressive integrated moving average (SARIMA) models have been frequently used for predicting river flow. SARIMA models are linear and do not consider the random component of statistical data. To overcome this shortcoming, monthly inflow is predicted in this study based on a combination of seasonal autoregressive integrated moving average (SARIMA) and gene expression programming (GEP) models, which is a new hybrid method (SARIMA-GEP). To this end, a four-step process is employed. First, the monthly inflow datasets are pre-processed. Second, the datasets are modelled linearly with SARIMA and in the third stage, the non-linearity of residual series caused by linear modelling is evaluated. After confirming the non-linearity, the residuals are modelled in the fourth step using a gene expression programming (GEP) method. The proposed hybrid model is employed to predict the monthly inflow to the Jamishan Dam in west Iran. Thirty years' worth of site measurements of monthly reservoir dam inflow with extreme seasonal variations are used. The results of this hybrid model (SARIMA-GEP) are compared with SARIMA, GEP, artificial neural network (ANN) and SARIMA-ANN models. The results indicate that the SARIMA-GEP model ( R 2=78.8, VAF =78.8, RMSE =0.89, MAPE =43.4, CRM =0.053) outperforms SARIMA and GEP and SARIMA-ANN ( R 2=68.3, VAF =66.4, RMSE =1.12, MAPE =56.6, CRM =0.032) displays better performance than the SARIMA and ANN models. A comparison of the two hybrid models indicates the superiority of SARIMA-GEP over the SARIMA-ANN model.

  1. NBI - plasma vaporization hybrid approach in bladder cancer endoscopic management.

    Science.gov (United States)

    Stănescu, F; Geavlete, B; Georgescu, D; Jecu, M; Moldoveanu, C; Adou, L; Bulai, C; Ene, C; Geavlete, P

    2014-06-15

    A prospective study was performed aiming to evaluate the surgical efficacy, perioperative safety profile, diagnostic accuracy and medium term results of a multi-modal approach consisting in narrow band imaging (NBI) cystoscopy and bipolar plasma vaporization (BPV) when compared to the standard protocol represented by white light cystoscopy (WLC) and transurethral resection of bladder tumors (TURBT). A total of 260 patients with apparently at least one bladder tumor over 3 cm were included in the trial. In the first group, 130 patients underwent conventional and NBI cystoscopy followed by BPV, while in a similar number of cases of the second arm, classical WLC and TURBT were applied. In all non-muscle invasive bladder tumors' (NMIBT) pathologically confirmed cases, standard monopolar Re-TUR was performed at 4-6 weeks after the initial intervention, followed by one year' BCG immunotherapy. The follow-up protocol included abdominal ultrasound, urinary cytology and WLC, performed every 3 months for a period of 2 years. The obturator nerve stimulation, bladder wall perforation, mean hemoglobin level drop, postoperative bleeding, catheterization period and hospital stay were significantly reduced for the plasma vaporization technique by comparison to conventional resection. Concerning tumoral detection, the present data confirmed the NBI superiority when compared to standard WLC regardless of tumor stage (95.3% vs. 65.1% for CIS, 93.3% vs. 82.2% for pTa, 97.4% vs. 94% for pT1, 95% vs. 84.2% overall). During standard Re-TUR the overall (6.3% versus 17.4%) and primary site (3.6% versus 12.8%) residual tumors' rates were significantly lower for the NBI-BPV group. The 1 (7.2% versus 18.3%) and 2 (11.5% versus 25.8%) years' recurrence rates were substantially lower for the combined approach. NBI cystoscopy significantly improved diagnostic accuracy, while bipolar technology showed a higher surgical efficiency, lower morbidity and faster postoperative recovery. The combined

  2. Efficient Vaccine Distribution Based on a Hybrid Compartmental Model.

    Directory of Open Access Journals (Sweden)

    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.

  3. A hybrid model for spatially and temporally resolved ozone exposures in the continental United States.

    Science.gov (United States)

    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.

  4. 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.

  5. A Short-Term and High-Resolution System Load Forecasting Approach Using Support Vector Regression with Hybrid Parameters Optimization

    Energy Technology Data Exchange (ETDEWEB)

    Jiang, Huaiguang [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

    2017-08-25

    This work proposes an approach for distribution system load forecasting, which aims to provide highly accurate short-term load forecasting with high resolution utilizing a support vector regression (SVR) based forecaster and a two-step hybrid parameters optimization method. Specifically, because the load profiles in distribution systems contain abrupt deviations, a data normalization is designed as the pretreatment for the collected historical load data. Then an SVR model is trained by the load data to forecast the future load. For better performance of SVR, a two-step hybrid optimization algorithm is proposed to determine the best parameters. In the first step of the hybrid optimization algorithm, a designed grid traverse algorithm (GTA) is used to narrow the parameters searching area from a global to local space. In the second step, based on the result of the GTA, particle swarm optimization (PSO) is used to determine the best parameters in the local parameter space. After the best parameters are determined, the SVR model is used to forecast the short-term load deviation in the distribution system.

  6. A terahertz performance of hybrid single walled CNT based amplifier with analytical approach

    Science.gov (United States)

    Kumar, Sandeep; Song, Hanjung

    2018-01-01

    This work is focuses on terahertz performance of hybrid single walled carbon nanotube (CNT) based amplifier and proposed for measurement of soil parameters application. The proposed circuit topology provides hybrid structure which achieves wide impedance bandwidth of 0.33 THz within range of 1.07-THz to 1.42-THz with fractional amount of 28%. The single walled RF CNT network executes proposed ambition and proves its ability to resonant at 1.25-THz with analytical approach. Moreover, a RF based microstrip transmission line radiator used as compensator in the circuit topology which achieves more than 30 dB of gain. A proper methodology is chosen for achieves stability at circuit level in order to obtain desired optimal conditions. The fundamental approach optimizes matched impedance condition at (50+j0) Ω and noise variation with impact of series resistances for the proposed hybrid circuit topology and demonstrates the accuracy of performance parameters at the circuit level. The chip fabrication of the proposed circuit by using RF based commercial CMOS process of 45 nm which reveals promising results with simulation one. Additionally, power measurement analysis achieves highest output power of 26 dBm with power added efficiency of 78%. The succeed minimum noise figure from 0.6 dB to 0.4 dB is outstanding achievement for circuit topology at terahertz range. The chip area of hybrid circuit is 0.65 mm2 and power consumption of 9.6 mW.

  7. Novelties in hybrid zones: crossroads between population genomic and ecological approaches.

    Directory of Open Access Journals (Sweden)

    Caroline Costedoat

    Full Text Available BACKGROUND: Interspecific hybridization is widespread, occurring in a taxonomically diverse array of species. The Cyprinidae family, which displays more than 30% hybridization, is a good candidate for studies of processes underlying isolation and speciation, such as genetic exchange between previously isolated lineages. This is particularly relevant in the case of recent hybridization between an invasive species, Chondrostoma nasus nasus (from Eastern Europe, and C. toxostoma toxostoma (a threatened species endemic to southern France, in which bidirectional introgressive hybridization has been demonstrated. METHODOLOGY/PRINCIPAL FINDINGS: We studied 128 specimens from reference populations and 1495 hybrid zone specimens (two years of sampling and four stations, using five molecular markers (one mitochondrial gene, four nuclear introns, morphology (meristic and plastic characters and life history traits (weight, size, coefficient of condition, sex, age, shoaling. We identified 65 hybrid combinations and visualized spatial and temporal changes in composition. The direction of mitochondrial introgression was density-dependent in favor of the rarer species and we demonstrate that the sexual selection hypothesis is a preponderant explanation in the asymmetry of introgression. Despite genomic evolution in the hybrid zone, convergence was observed for body shape and coefficient of condition, indicating changes in foraging behavior with respect to reference populations, reflecting strong environmental pressure. CONCLUSIONS/SIGNIFICANCE: The complex rules of hybrid zone dynamics are established very early in the contact zone. We propose "inheritance from the rare species" as a new evolutionary hypothesis for animal models. The endemic species was not assimilated by the invasive species. Survival rates for this species were highest in the middle of the river (the warmest part due to a trade-off between food availability and fecundity. The environment

  8. A hybrid PSO-ANFIS approach for short-term wind power prediction in Portugal

    Energy Technology Data Exchange (ETDEWEB)

    Pousinho, H.M.I. [Department of Electromechanical Engineering, University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilha (Portugal); Mendes, V.M.F. [Department of Electrical Engineering and Automation, Instituto Superior de Engenharia de Lisboa, R. Conselheiro Emidio Navarro, 1950-062 Lisbon (Portugal); Catalao, J.P.S. [Department of Electromechanical Engineering, University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilha (Portugal); Center for Innovation in Electrical and Energy Engineering, Instituto Superior Tecnico, Technical University of Lisbon, Av. Rovisco Pais, 1049-001 Lisbon (Portugal)

    2011-01-15

    The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Wind power prediction plays a key role in tackling these challenges. The contribution of this paper is to propose a new hybrid approach, combining particle swarm optimization and adaptive-network-based fuzzy inference system, for short-term wind power prediction in Portugal. Significant improvements regarding forecasting accuracy are attainable using the proposed approach, in comparison with the results obtained with five other approaches. (author)

  9. A Piecewise Affine Hybrid Systems Approach to Fault Tolerant Satellite Formation Control

    DEFF Research Database (Denmark)

    Grunnet, Jacob Deleuran; Larsen, Jesper Abildgaard; Bak, Thomas

    2008-01-01

    In this paper a procedure for modelling satellite formations   including failure dynamics as a piecewise-affine hybrid system is   shown. The formulation enables recently developed methods and tools   for control and analysis of piecewise-affine systems to be applied   leading to synthesis of fau...

  10. Spin injection across a hybrid heterojunction: Theoretical understanding and experimental approach (invited)

    DEFF Research Database (Denmark)

    Hu, C.M.; Nitta, J.; Jensen, Ane

    2002-01-01

    Spin injection across a hybrid ferromagnet/semiconductor junction has proven to be difficult, unlike in an all-metal junction used in giant magnetoresistance devices. The difference responsible is highlighted in a simple model. We perform spin-injection-detection experiments on devices with two f...

  11. Exact hybrid particle/population simulation of rule-based models of biochemical systems.

    Science.gov (United States)

    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

  12. Axelrod Model of Social Influence with Cultural Hybridization

    Science.gov (United States)

    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.

  13. A Probability-Based Hybrid User Model for Recommendation System

    Directory of Open Access Journals (Sweden)

    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.

  14. An Interactive Personalized Recommendation System Using the Hybrid Algorithm Model

    Directory of Open Access Journals (Sweden)

    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.

  15. A fuzzy hybrid approach for project manager selection

    Directory of Open Access Journals (Sweden)

    Ahmad Jafarnejad Chaghooshi

    2016-09-01

    Full Text Available Suitable project manager has a significant impact on successful accomplishment of the project. Managers should possess such skills in order to effectively cope with the competition. In this respect, selecting managers based on their skills can lead to a competitive advantage towards the achievement of organizational goals. selection of the suitable project manager can be viewed as a multi-criteria decision making (MCDM problem and an extensive evaluation of criteria, such as Technical skills, experience skills, Personal qualities and the related criteria must be considered in the selection process of project manager. The fuzzy set theory and MCDM methods appears as an essential tools to provide a decision framework that incorporates imprecise judgments and multi criteria nature of project manager selection process inherent in this process. This paper proposes the joint use of the Fuzzy DEMATEL (FDEMATEL and Fuzzy VIKOR methods for the decision-making process of selecting the most suitable managers for projects. First, with the opinions of the senior managers based on project management competency model (ICB-IPMA, all the criteria required for the selection are gathered. Then the FDEMATEL method is used to prioritize the importance of various criteria and FVIKOR used to rank the alternatives in a preferred order to select the best project managers from a number of alternatives. Next, a real case study used to illustrate the process of the proposed method. Finally, some conclusions are discussed at the end of this study.

  16. Noise Propagation and Uncertainty Quantification in Hybrid Multiphysics Models: Initiation and Reaction Propagation in Energetic Materials

    Science.gov (United States)

    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

  17. Dynamic Modeling and Simulation of a Switched Reluctance Motor in a Series Hybrid Electric Vehicle

    OpenAIRE

    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...

  18. A hybrid approach for short-term forecasting of wind speed.

    Science.gov (United States)

    Tatinati, Sivanagaraja; Veluvolu, Kalyana C

    2013-01-01

    We propose a hybrid method for forecasting the wind speed. The wind speed data is first decomposed into intrinsic mode functions (IMFs) with empirical mode decomposition. Based on the partial autocorrelation factor of the individual IMFs, adaptive methods are then employed for the prediction of IMFs. Least squares-support vector machines are employed for IMFs with weak correlation factor, and autoregressive model with Kalman filter is employed for IMFs with high correlation factor. Multistep prediction with the proposed hybrid method resulted in improved forecasting. Results with wind speed data show that the proposed method provides better forecasting compared to the existing methods.

  19. A hybrid approach to crowd density estimation using statistical leaning and texture classification

    Science.gov (United States)

    Li, Yin; Zhou, Bowen

    2013-12-01

    Crowd density estimation is a hot topic in computer vision community. Established algorithms for crowd density estimation mainly focus on moving crowds, employing background modeling to obtain crowd blobs. However, people's motion is not obvious in most occasions such as the waiting hall in the airport or the lobby in the railway station. Moreover, conventional algorithms for crowd density estimation cannot yield desirable results for all levels of crowding due to occlusion and clutter. We propose a hybrid method to address the aforementioned problems. First, statistical learning is introduced for background subtraction, which comprises a training phase and a test phase. The crowd images are grided into small blocks which denote foreground or background. Then HOG features are extracted and are fed into a binary SVM for each block. Hence, crowd blobs can be obtained by the classification results of the trained classifier. Second, the crowd images are treated as texture images. Therefore, the estimation problem can be formulated as texture classification. The density level can be derived according to the classification results. We validate the proposed algorithm on some real scenarios where the crowd motion is not so obvious. Experimental results demonstrate that our approach can obtain the foreground crowd blobs accurately and work well for different levels of crowding.

  20. Three-dimensional ductile fracture analysis with a hybrid multiresolution approach and microtomography

    Science.gov (United States)

    Tang, Shan; Kopacz, Adrian M.; Chan O'Keeffe, Stephanie; Olson, Gregory B.; Liu, Wing Kam

    2013-11-01

    A modified-JIC test on CT (compact tension) specimens of an alloy (Ti-Modified 4330 steel) was carried out. The microstructure (primary and secondary inclusions) in the fracture process zone and fracture surface are reconstructed with a microtomography technique. The zig-zag fracture profile resulting from nucleation of microvoid sheets at the secondary population of inclusions is observed. Embedding the experimentally reconstructed microstructure into the fracture process zone, the ductile fracture process occurring at different length scales within the microstructure is modeled by a hybrid multiresolution approach. In combination with the large scale simulation, detailed studies and statistical analysis show that shearing of microvoids (the secondary population of voids) determines the mixed mode zig-zag fracture profile. The deformation in the macro and micro zones along with the interaction between them affects the fracture process. The observed zig-zag fracture profile in the experiment is also reasonably captured. Simulations can provide a more detailed understanding of the mechanics of the fracture process than experiments which is beneficial in microstructure design to improve performance of alloys.

  1. Hybrid 3D printing and electrodeposition approach for controllable 3D alginate hydrogel formation.

    Science.gov (United States)

    Shang, Wanfeng; Liu, Yanting; Wan, Wenfeng; Hu, Chengzhi; Liu, Zeyang; Wong, Chin To; Fukuda, Toshio; Shen, Yajing

    2017-06-07

    Calcium alginate hydrogels are widely used as biocompatible materials in a substantial number of biomedical applications. This paper reports on a hybrid 3D printing and electrodeposition approach for forming 3D calcium alginate hydrogels in a controllable manner. Firstly, a specific 3D hydrogel printing system is developed by integrating a customized ejection syringe with a conventional 3D printer. Then, a mixed solution of sodium alginate and CaCO3 nanoparticles is filled into the syringe and can be continuously ejected out of the syringe nozzle onto a conductive substrate. When applying a DC voltage (∼5 V) between the substrate (anode) and the nozzle (cathode), the Ca(2+) released from the CaCO3 particles can crosslink the alginate to form calcium alginate hydrogel on the substrate. To elucidate the gel formation mechanism and better control the gel growth, we can further establish and verify a gel growth model by considering several key parameters, i.e., applied voltage and deposition time. The experimental results indicate that the alginate hydrogel of various 3D structures can be formed by controlling the movement of the 3D printer. A cell viability test is conducted and shows that the encapsulated cells in the gel can maintain a high survival rate (∼99% right after gel formation). This research establishes a reliable method for the controllable formation of 3D calcium alginate hydrogel, exhibiting great potential for use in basic biology and applied biomedical engineering.

  2. Systems biology by the rules: hybrid intelligent systems for pathway modeling and discovery.

    Science.gov (United States)

    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

  3. Systems biology by the rules: hybrid intelligent systems for pathway modeling and discovery

    Directory of Open Access Journals (Sweden)

    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

  4. Progress in Hybrid RANS-LES Modelling : Papers Contributed to the 4th Symposium on Hybrid RANS-LES Methods

    CERN Document Server

    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.

  5. Hybrid 3D model for the interaction of plasma thruster plumes with nearby objects

    Science.gov (United States)

    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.

  6. Modeling wall effects in a micro-scale shock tube using hybrid MD-DSMC algorithm

    Science.gov (United States)

    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.

  7. Current approaches to model extracellular electrical neural microstimulation

    Directory of Open Access Journals (Sweden)

    Sébastien eJoucla

    2014-02-01

    Full Text Available Nowadays, high-density microelectrode arrays provide unprecedented possibilities to precisely activate spatially well-controlled central nervous system (CNS areas. However, this requires optimizing stimulating devices, which in turn requires a good understanding of the effects of microstimulation on cells and tissues. In this context, modeling approaches provide flexible ways to predict the outcome of electrical stimulation in terms of CNS activation. In this paper, we present state-of-the-art modeling methods with sufficient details to allow the reader to rapidly build numerical models of neuronal extracellular microstimulation. These include 1 the computation of the electrical potential field created by the stimulation in the tissue, and 2 the response of a target neuron to this field. Two main approaches are described: First we describe the classical hybrid approach that combines the finite element modeling of the potential field with the calculation of the neuron’s response in a cable equation framework (compartmentalized neuron models. Then, we present a whole finite element approach allows the simultaneous calculation of the extracellular and intracellular potentials, by representing the neuronal membrane with a thin-film approximation. This approach was previously introduced in the frame of neural recording, but has never been implemented to determine the effect of extracellular stimulation on the neural response at a sub-compartment level. Here, we show on an example that the latter modeling scheme can reveal important sub-compartment behavior of the neural membrane that cannot be resolved using the hybrid approach. The goal of this paper is also to describe in detail the practical implementation of these methods to allow the reader to easily build new models using standard software packages. These modeling paradigms, depending on the situation, should help build more efficient high-density neural prostheses for CNS rehabilitation.

  8. Benchmarking novel approaches for modelling species range dynamics.

    Science.gov (United States)

    Zurell, Damaris; Thuiller, Wilfried; Pagel, Jörn; Cabral, Juliano S; Münkemüller, Tamara; Gravel, Dominique; Dullinger, Stefan; Normand, Signe; Schiffers, Katja H; Moore, Kara A; Zimmermann, Niklaus E

    2016-08-01

    Increasing biodiversity loss due to climate change is one of the most vital challenges of the 21st century. To anticipate and mitigate biodiversity loss, models are needed that reliably project species' range dynamics and extinction risks. Recently, several new approaches to model range dynamics have been developed to supplement correlative species distribution models (SDMs), but applications clearly lag behind model development. Indeed, no comparative analysis has been performed to evaluate their performance. Here, we build on process-based, simulated data for benchmarking five range (dynamic) models of varying complexity including classical SDMs, SDMs coupled with simple dispersal or more complex population dynamic models (SDM hybrids), and a hierarchical Bayesian process-based dynamic range model (DRM). We specifically test the effects of demographic and community processes on model predictive performance. Under current climate, DRMs performed best, although only marginally. Under climate change, predictive performance varied considerably, with no clear winners. Yet, all range dynamic models improved predictions under climate change substantially compared to purely correlative SDMs, and the population dynamic models also predicted reasonable extinction risks for most scenarios. When benchmarking data were simulated with more complex demographic and community processes, simple SDM hybrids including only dispersal often proved most reliable. Finally, we found that structural decisions during model building can have great impact on model accuracy, but prior system knowledge on important processes can reduce these uncertainties considerably. Our results reassure the clear merit in using dynamic approaches for modelling species' response to climate change but also emphasize several needs for further model and data improvement. We propose and discuss perspectives for improving range projections through combination of multiple models and for making these approaches

  9. A Hybrid Multiple Criteria Decision Making Model for Supplier Selection

    Directory of Open Access Journals (Sweden)

    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.

  10. Hybrid FEA/SEA Assessment for an Orthogrid Cylindrical Panel Section and Periodic Subsystem Modeling Evaluation

    Science.gov (United States)

    Smith, Andrew M.; LaVerde, Bruce; Teague, David W.

    2010-01-01

    In the lower frequency range, where particular boundary conditions can make a significant difference to panel response characteristics Statistical Energy Analysis (SEA) has never been the analytical tool of choice. In addition to boundary condition effects, SEA is not well suited in frequency bands where no modes or less than a few modes exist. The advent of the Hybrid Module has enabled integration of Finite Element Analysis to expand and enhance the capability for response calculations within VA One into the lower frequency range. Exploration of several additional modeling approaches was completed for the cylindrical orthogrid panel test article that was examined in Reference 1. Comparison of the new analytical response predictions with the measured response data from ground test and the pure SEA results from the reference will be presented. One approach that is considered promising is the periodic subsystem capability. Initially, a detailed FEM of just one region of the test article is defined. After evaluating this small region using symmetric boundary conditions, the FEM may be expanded to determine the properties of the entire system using similar connected regions that map over the entire test article. Another approach is the direct use of a very detailed finite element model of the entire panel, explicitly modeling pocket and rib details of the structure. A third approach is to approximate localized structure geometry details with a smeared property generalization using a PCOMP (NASTRAN card used to define layered composite structures) to define skin layer and ribbed layer for the orthogrid panel. The authors expect to demonstrate that the integrated Hybrid/FEM approach increases confidence in response prediction in the lower frequency range (for example from 20-300 Hz for the test article under consideration). In addition the strength and weakness of each additional approach will be highlighted and compared to those reported with those reported in an

  11. Hybrid Model GSTAR-SUR-NN For Precipitation Data

    Directory of Open Access Journals (Sweden)

    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.

  12. HEDR modeling approach: Revision 1

    Energy Technology Data Exchange (ETDEWEB)

    Shipler, D.B.; Napier, B.A.

    1994-05-01

    This report is a revision of the previous Hanford Environmental Dose Reconstruction (HEDR) Project modeling approach report. This revised report describes the methods used in performing scoping studies and estimating final radiation doses to real and representative individuals who lived in the vicinity of the Hanford Site. The scoping studies and dose estimates pertain to various environmental pathways during various periods of time. The original report discussed the concepts under consideration in 1991. The methods for estimating dose have been refined as understanding of existing data, the scope of pathways, and the magnitudes of dose estimates were evaluated through scoping studies.

  13. A novel hybrid forecasting model for PM₁₀ and SO₂ daily concentrations.

    Science.gov (United States)

    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.

  14. Model-Invariant Hybrid LES-RANS Computation of Separated Flow Past Periodic Hills

    Science.gov (United States)

    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.

  15. A Hybrid Supervised/Unsupervised Machine Learning Approach to Solar Flare Prediction

    Science.gov (United States)

    Benvenuto, Federico; Piana, Michele; Campi, Cristina; Massone, Anna Maria

    2018-01-01

    This paper introduces a novel method for flare forecasting, combining prediction accuracy with the ability to identify the most relevant predictive variables. This result is obtained by means of a two-step approach: first, a supervised regularization method for regression, namely, LASSO is applied, where a sparsity-enhancing penalty term allows the identification of the significance with which each data feature contributes to the prediction; then, an unsupervised fuzzy clustering technique for classification, namely, Fuzzy C-Means, is applied, where the regression outcome is partitioned through the minimization of a cost function and without focusing on the optimization of a specific skill score. This approach is therefore hybrid, since it combines supervised and unsupervised learning; realizes classification in an automatic, skill-score-independent way; and provides effective prediction performances even in the case of imbalanced data sets. Its prediction power is verified against NOAA Space Weather Prediction Center data, using as a test set, data in the range between 1996 August and 2010 December and as training set, data in the range between 1988 December and 1996 June. To validate the method, we computed several skill scores typically utilized in flare prediction and compared the values provided by the hybrid approach with the ones provided by several standard (non-hybrid) machine learning methods. The results showed that the hybrid approach performs classification better than all other supervised methods and with an effectiveness comparable to the one of clustering methods; but, in addition, it provides a reliable ranking of the weights with which the data properties contribute to the forecast.

  16. A hybrid deformable model for simulating prostate brachytherapy

    Science.gov (United States)

    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.

  17. Towards a hybrid strong/weak coupling approach to jet quenching

    CERN Document Server

    Casalderrey-Solana, Jorge; Milhano, José Guilherme; Pablos, Daniel; Rajagopal, Krishna

    2014-01-01

    We explore a novel hybrid model containing both strong and weak coupling physics for high energy jets traversing a deconfined medium. This model is based on supplementing a perturbative DGLAP shower with strongly coupled energy loss rate. We embed this system into a realistic hydrodynamic evolution of hot QCD plasma. We confront our results with LHC data, obtaining good agreement for jet RAARAA, dijet imbalance AJAJ and fragmentation functions.

  18. heartBEATS: A hybrid energy approach for real-time B-spline explicit active tracking of surfaces.

    Science.gov (United States)

    Barbosa, Daniel; Pedrosa, João; Heyde, Brecht; Dietenbeck, Thomas; Friboulet, Denis; Bernard, Olivier; D'hooge, Jan

    2017-07-29

    In this manuscript a novel method is presented for left ventricle (LV) tracking in three-dimensional ultrasound data using a hybrid approach combining segmentation and tracking-based clues. This is accomplished by coupling an affine motion model to an existing LV segmentation framework and introducing an energy term that penalizes the deviation to the affine motion estimated using a global Lucas-Kanade algorithm. The hybrid nature of the proposed solution can be seen as using the estimated affine motion to enhance the temporal coherence of the segmented surfaces, by enforcing the tracking of consistent patterns, while the underlying segmentation algorithm allows to locally refine the estimated global motion. The proposed method was tested on a dataset composed of 24 4D ultrasound sequences from both healthy volunteers and diseased patients. The proposed hybrid tracking platform offers a competitive solution for fast assessment of relevant LV volumetric indices, by combining the robustness of affine motion tracking with the low computational burden of the underlying segmentation algorithm. Copyright © 2017 Elsevier Ltd. All rights reserved.

  19. 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

  20. Modeling Approaches in Planetary Seismology

    Science.gov (United States)

    Weber, Renee; Knapmeyer, Martin; Panning, Mark; Schmerr, Nick

    2014-01-01

    Of the many geophysical means that can be used to probe a planet's interior, seismology remains the most direct. Given that the seismic data gathered on the Moon over 40 years ago revolutionized our understanding of the Moon and are still being used today to produce new insight into the state of the lunar interior, it is no wonder that many future missions, both real and conceptual, plan to take seismometers to other planets. To best facilitate the return of high-quality data from these instruments, as well as to further our understanding of the dynamic processes that modify a planet's interior, various modeling approaches are used to quantify parameters such as the amount and distribution of seismicity, tidal deformation, and seismic structure on and of the terrestrial planets. In addition, recent advances in wavefield modeling have permitted a renewed look at seismic energy transmission and the effects of attenuation and scattering, as well as the presence and effect of a core, on recorded seismograms. In this chapter, we will review these approaches.

  1. Hybrid Block Copolymers Constituted by Peptides and Synthetic Polymers: An Overview of Synthetic Approaches, Supramolecular Behavior and Potential Applications

    Directory of Open Access Journals (Sweden)

    Jordi Puiggalí

    2013-02-01

    Full Text Available Hybrid block copolymers based on peptides and synthetic polymers, displaying different types of topologies, offer new possibilities to integrate the properties and functions of biomacromolecules and synthetic polymers in a single hybrid material. This review provides a current status report of the field concerning peptide-synthetic polymer hybrids. The first section is focused on the different synthetic approaches that have been used within the last three years for the preparation of peptide-polymer hybrids having different topologies. In the last two sections, the attractive properties, displayed in solution or in the solid state, together with the potential applications of this type of macromolecules or supramolecular systems are highlighted.

  2. A hybrid approach using chaotic dynamics and global search algorithms for combinatorial optimization problems

    Science.gov (United States)

    Igeta, Hideki; Hasegawa, Mikio

    Chaotic dynamics have been effectively applied to improve various heuristic algorithms for combinatorial optimization problems in many studies. Currently, the most used chaotic optimization scheme is to drive heuristic solution search algorithms applicable to large-scale problems by chaotic neurodynamics including the tabu effect of the tabu search. Alternatively, meta-heuristic algorithms are used for combinatorial optimization by combining a neighboring solution search algorithm, such as tabu, gradient, or other search method, with a global search algorithm, such as genetic algorithms (GA), ant colony optimization (ACO), or others. In these hybrid approaches, the ACO has effectively optimized the solution of many benchmark problems in the quadratic assignment problem library. In this paper, we propose a novel hybrid method that combines the effective chaotic search algorithm that has better performance than the tabu search and global search algorithms such as ACO and GA. Our results show that the proposed chaotic hybrid algorithm has better performance than the conventional chaotic search and conventional hybrid algorithms. In addition, we show that chaotic search algorithm combined with ACO has better performance than when combined with GA.

  3. A novel simplified model for torsional vibration analysis of a series-parallel hybrid electric vehicle

    Science.gov (United States)

    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.

  4. A Hybrid Approach Using an Artificial Bee Algorithm with Mixed Integer Programming Applied to a Large-Scale Capacitated Facility Location Problem

    Directory of Open Access Journals (Sweden)

    Guillermo Cabrera G.

    2012-01-01

    Full Text Available We present a hybridization of two different approaches applied to the well-known Capacitated Facility Location Problem (CFLP. The Artificial Bee algorithm (BA is used to select a promising subset of locations (warehouses which are solely included in the Mixed Integer Programming (MIP model. Next, the algorithm solves the subproblem by considering the entire set of customers. The hybrid implementation allows us to bypass certain inherited weaknesses of each algorithm, which means that we are able to find an optimal solution in an acceptable computational time. In this paper we demonstrate that BA can be significantly improved by use of the MIP algorithm. At the same time, our hybrid implementation allows the MIP algorithm to reach the optimal solution in a considerably shorter time than is needed to solve the model using the entire dataset directly within the model. Our hybrid approach outperforms the results obtained by each technique separately. It is able to find the optimal solution in a shorter time than each technique on its own, and the results are highly competitive with the state-of-the-art in large-scale optimization. Furthermore, according to our results, combining the BA with a mathematical programming approach appears to be an interesting research area in combinatorial optimization.

  5. Dynamic Modeling and Simulation on a Hybrid Power System for Electric Vehicle Applications

    OpenAIRE

    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...

  6. Modeling and simulation of a hybrid ship power system

    Science.gov (United States)

    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.

  7. Dynamic Performance Evaluation of Photovoltaic Power Plant by Stochastic Hybrid Fault Tree Automaton Model

    Directory of Open Access Journals (Sweden)

    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.

  8. Safe Neighborhood Computation for Hybrid System Verification

    Directory of Open Access Journals (Sweden)

    Yi Deng

    2015-01-01

    Full Text Available For the design and implementation of engineering systems, performing model-based analysis can disclose potential safety issues at an early stage. The analysis of hybrid system models is in general difficult due to the intrinsic complexity of hybrid dynamics. In this paper, a simulation-based approach to formal verification of hybrid systems is presented.

  9. Applying a Hybrid MCDM Model for Six Sigma Project Selection

    Directory of Open Access Journals (Sweden)

    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.

  10. 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.

  11. Thermodynamic Modeling and Dispatch of Distributed Energy Technologies including Fuel Cell -- Gas Turbine Hybrids

    Science.gov (United States)

    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

  12. A Hybrid Approach to Cognitive Engineering: Supporting Development of a Revolutionary Warfighter-Centered Command and Control System

    National Research Council Canada - National Science Library

    Ockerman, Jennifer; McKneely, Jennifer A; Koterba, Nathan

    2005-01-01

    ...) for the requirements analysis and design of revolutionary command and control systems and domains. This hybrid approach uses knowledge elicitation and representation techniques from several current cognitive engineering methodologies...

  13. Exploring key factors in online shopping with a hybrid model.

    Science.gov (United States)

    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.

  14. A hybrid approach to transport processes in the Gulf of Naples: an application to phytoplankton and zooplankton population dynamics

    Science.gov (United States)

    Grieco, L.; Tremblay, L.-B.; Zambianchi, E.

    2005-03-01

    A hybrid numerical approach was developed to study the dispersion of passive/reactive tracers in the Gulf of Naples (GON). To this end, an Eulerian and a Lagrangian scheme were implemented in the barotropic form of the Princeton Ocean Model (POM) and applied to the dispersion of zoo- and phytoplankton in the GON. The hybrid technique was first validated by comparing the tracer concentration patterns from the Eulerian model and maps of particle positions from the Lagrangian model. Excellent agreement in both spatial distribution and temporal evolution of these quantities was found between the two models. Second, the circulation in the GON was simulated using the POM model. While using simplified forcing fields, the simulated circulation patterns in the GON reproduce many observed features. These include the flushing of the GON waters typically occurring in spring and the formation of a close cyclonic gyre (trapping and homogenizing tracers in the GON) in autumn. The circulation patterns are strongly influenced by both the surface wind stresses and bathymetry and only "remotely" by the Tyrrhenian circulation. For the biological application, the spatial and temporal evolution of passive tracers (e.g., nutrients) was simulated using the Eulerian approach and that of the zoo- and phytoplankton using the Lagrangian approach. These populations were assumed to follow a prey-predator relationship and were studied using a grid resolution of 1.5 km. At these scales, the biological and physical processes (e.g., grazing, phyto- and zooplankton growth rate, mesoscale eddies, horizontal turbulent diffusion), influence plankton heterogeneity and patchiness. In particular, the model results show that phytoplankton variability have spatial and temporal scales similar than those of the carrying capacity (considered here as the effect of a limiting nutrient), yet bigger than the flow turbulence due to diffusion processes. The zooplankton population on the other hand develops on

  15. A hybrid simulation approach for integrating safety behavior into construction planning: An earthmoving case study.

    Science.gov (United States)

    Goh, Yang Miang; Askar Ali, Mohamed Jawad

    2016-08-01

    One of the key challenges in improving construction safety and health is the management of safety behavior. From a system point of view, workers work unsafely due to system level issues such as poor safety culture, excessive production pressure, inadequate allocation of resources and time and lack of training. These systemic issues should be eradicated or minimized during planning. However, there is a lack of detailed planning tools to help managers assess the impact of their upstream decisions on worker safety behavior. Even though simulation had been used in construction planning, the review conducted in this study showed that construction safety management research had not been exploiting the potential of simulation techniques. Thus, a hybrid simulation framework is proposed to facilitate integration of safety management considerations into construction activity simulation. The hybrid framework consists of discrete event simulation (DES) as the core, but heterogeneous, interactive and intelligent (able to make decisions) agents replace traditional entities and resources. In addition, some of the cognitive processes and physiological aspects of agents are captured using system dynamics (SD) approach. The combination of DES, agent-based simulation (ABS) and SD allows a more "natural" representation of the complex dynamics in construction activities. The proposed hybrid framework was demonstrated using a hypothetical case study. In addition, due to the lack of application of factorial experiment approach in safety management simulation, the case study demonstrated sensitivity analysis and factorial experiment to guide future research. Copyright © 2015 Elsevier Ltd. All rights reserved.

  16. Branding approach and valuation models

    Directory of Open Access Journals (Sweden)

    Mamula Tatjana

    2006-01-01

    Full Text Available Much of the skill of marketing and branding nowadays is concerned with building equity for products whose characteristics, pricing, distribution and availability are really quite close to each other. Brands allow the consumer to shop with confidence. The real power of successful brands is that they meet the expectations of those that buy them or, to put it another way, they represent a promise kept. As such they are a contract between a seller and a buyer: if the seller keeps to its side of the bargain, the buyer will be satisfied; if not, the buyer will in future look elsewhere. Understanding consumer perceptions and associations is an important first step to understanding brand preferences and choices. In this paper, we discuss different models to measure value of brand according to couple of well known approaches according to request by companies. We rely upon several empirical examples.

  17. Prediction of hybrid means from a partial circulant diallel table using the ordinary least square and the mixed model methods

    Directory of Open Access Journals (Sweden)

    Américo José dos Santos Reis

    2005-01-01

    Full Text Available By definition, the genetic effects obtained from a circulant diallel table are random. However, because of the methods of analysis, those effects have been considered as fixed. Two different statistical approaches were applied. One assumed the model to be fixed and obtained solutions through the ordinary least square (OLS method. The other assumed a mixed model and estimated the fixed effects (BLUE by generalized least squares (GLS and the best linear unbiased predictor (BLUP of the random effects. The goal of this study was to evaluate the consequences when considering these effects as fixed or random, using the coefficient of correlation between the responses of observed and non-observed hybrids. Crossings were made between S1 inbred lines from two maize populations developed at Universidade Federal de Goiás, the UFG-Samambaia "Dent" and UFG-Samambaia "Flint". A circulant inter-group design was applied, and there were five (s = 5 crossings for each parent. The predictions were made using a reduced model. Diallels with different sizes of s (from 2 to 5 were simulated, and the coefficients of correlation were obtained using two different approaches for each size of s. In the first approach, the observed hybrids were included in both the estimation of the genetic parameters and the coefficient of correlation, while in the second a cross-validation process was employed. In this process, the set of hybrids was divided in two groups: one group, comprising 75% of the original group, to estimate the genetic parameters, and a second one, consisting of the remaining 25%, to validate the predictions. In all cases, a bootstrap process with 200 resamplings was used to generate the empirical distribution of the correlation coefficient. This coefficient showed a decrease as the value of s decreased. The cross-validation method allowed to estimate the bias magnitude in evaluating the correlation coefficient using the same hybrids, to predict the genetic

  18. Contribution to the optimal design of an hybrid parallel power-train: choice of a battery model; Contribution a la conception optimale d'une motorisation hybride parallele. Choix d'un modele d'accumulateur

    Energy Technology Data Exchange (ETDEWEB)

    Kuhn, E.

    2004-09-15

    This work deals with the dynamical and energetic modeling of a 42 V NiMH battery, the model of which is taking into account into a control law for an hybrid electrical vehicle. Using an inventory of the electrochemical phenomena, an equivalent electrical scheme has been established. In this model, diffusion phenomena were represented using non integer derivatives. This tool leads to a very good approximation of diffusion phenomena, nevertheless such a pure mathematical approach did not allow to represent energetic losses inside the battery. Consequently, a second model, made of a series of electric circuits has been proposed to represent energetic transfers. This second model has been used in the determination of a control law which warrants an autonomous management of electrical energy embedded in a parallel hybrid electrical vehicle, and to prevent deep discharge of the battery. (author)

  19. Control-relevant modeling and simulation of a SOFC-GT hybrid system

    Directory of Open Access Journals (Sweden)

    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.

  20. Pedagogy and Process: A Case Study of Writing in a Hybrid Learning Model

    Science.gov (United States)

    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…

  1. A practical approach to FRET-based PNA fluorescence in situ hybridization.

    Science.gov (United States)

    Blanco, Ana M; Artero, Rubén

    2010-12-01

    Given the demand for improved methods for detecting and characterizing RNA variants in situ, we developed a quantitative method for detecting RNA alternative splicing variants that combines in situ hybridization of fluorescently labeled peptide nucleic acid (PNA) probes with confocal microscopy Förster resonance energy transfer (FRET). The use of PNA probes complementary to sequences flanking a given splice junction allows to specifically quantify, within the cell, the RNA isoform generating such splice junction as FRET efficiency measure. The FRET-based PNA fluorescence in situ hybridization (FP-FISH) method offers a conceptually new approach for characterizing at the subcellular level not only splice variant isoform structure, location, and dynamics but also potentially a wide variety of close range RNA-RNA interactions. In this paper, we explain the FP-FISH technique workflow for reliable and reproducible results. Copyright © 2010 Elsevier Inc. All rights reserved.

  2. A general approach to synthesize asymmetric hybrid nanoparticles by interfacial reactions.

    Science.gov (United States)

    He, Jie; Perez, Maria Teresa; Zhang, Peng; Liu, Yijing; Babu, Taarika; Gong, Jinlong; Nie, Zhihong

    2012-02-29

    Asymmetric multicomponent nanoparticles (AMNPs) offer new opportunities for new-generation materials with improved or new synergetic properties not found in their individual components. There is, however, an urgent need for a synthetic strategy capable of preparing hybrid AMNPs with fine-tuned structural and compositional complexities. Herein, we report a new paradigm for the controllable synthesis of polymer/metal AMNPs with well-controlled size, shape, composition, and morphology by utilizing interfacial polymerization. The hybrid AMNPs display a new level of structural-architectural sophistication, such as controlled domain size and the number of each component of AMNPs. The approach is simple, versatile, cost-effective, and scalable for synthesizing large quantities of AMNPs. Our method may pave a new route to the design and synthesis of advanced breeds of building blocks for functional materials and devices. © 2012 American Chemical Society

  3. Recent Development in Pulmonary Valve Replacement after Tetralogy of Fallot Repair: The Emergence of Hybrid Approaches.

    Science.gov (United States)

    Suleiman, Tariq; Kavinsky, Clifford J; Skerritt, Clare; Kenny, Damien; Ilbawi, Michael N; Caputo, Massimo

    2015-01-01

    An increasing number of patients with tetralogy of Fallot require repeat surgical intervention for pulmonary valve replacement secondary to pulmonary regurgitation. Catheter-based interventions have emerged as an attractive alternative to surgery in this patient population but it is limited by patient size or the anatomy of the right ventricular outflow tract. Hybrid approaches involving both cardiac interventionists and surgeons are being developed to overcome these limitations. The purpose of this review is to highlight the recent advances in the hybrid field of pulmonary valve replacement, summarizing the advantages and disadvantages of the "traditional" surgical and the new catheter-based techniques and discuss the direction future research should take to determine the optimal management for individual patients.

  4. Approach to Hybrid Energy Storage Systems Dimensioning for Urban Electric Buses Regarding Efficiency and Battery Aging

    Directory of Open Access Journals (Sweden)

    Jorge Nájera

    2017-10-01

    Full Text Available This paper focuses on Hybrid Energy Storage Systems (HESS, consisting of a combination of batteries and Electric Double Layer Capacitors (EDLC, for electric urban busses. The aim of the paper is to develop a methodology to determine the hybridization percentage that allows the electric bus to work with the highest efficiency while reducing battery aging, depending on the chosen topology, control strategy, and driving cycle. Three power electronic topologies are qualitatively analyzed based on different criteria, with the topology selected as the favorite being analyzed in detail. The whole system under study is comprised of the following elements: a battery pack (LiFePO4 batteries, an EDLC pack, up to two DC-DC converters (depending on the topology, and an equivalent load, which behaves as an electric bus drive (including motion resistances and inertia. Mathematical models for the battery, EDLCs, DC-DC converter, and the vehicle itself are developed for this analysis. The methodology presented in this work, as the main scientific contribution, considers performance variation (energy efficiency and battery aging and hybridization percentage (ratio between batteries and EDLCs, defined in terms of mass, using a power load profile based on standard driving cycles. The results state that there is a hybridization percentage that increases energy efficiency and reduces battery aging, maximizing the economic benefits of the vehicle, for every combination of topology, type of storage device, control strategy, and driving cycle.

  5. A hybrid approach for integrated healthcare cooperative purchasing and supply chain configuration.

    Science.gov (United States)

    Rego, Nazaré; Claro, João; Pinho de Sousa, Jorge

    2014-12-01

    This paper presents an innovative and flexible approach for recommending the number, size and composition of purchasing groups, for a set of hospitals willing to cooperate, while minimising their shared supply chain costs. This approach makes the financial impact of the various cooperation alternatives transparent to the group and the individual participants, opening way to a negotiation process concerning the allocation of the cooperation costs and gains. The approach was developed around a hybrid Variable Neighbourhood Search (VNS)/Tabu Search metaheuristic, resulting in a flexible tool that can be applied to purchasing groups with different characteristics, namely different operative and market circumstances, and to supply chains with different topologies and atypical cost characteristics. Preliminary computational results show the potential of the approach in solving a broad range of problems.

  6. 3D hybrid modelling of vascular network formation.

    Science.gov (United States)

    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

  7. 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.

  8. Corresponding-states behavior of SPC/E-based modified (bent and hybrid) water models

    Science.gov (United States)

    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.

  9. Coupling discrete and continuum concentration particle models for multiscale and hybrid molecular-continuum simulations

    Science.gov (United States)

    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.

  10. Experts and Machines against Bullies: A Hybrid Approach to Detect Cyberbullies

    OpenAIRE

    Dadvar, M.; Trieschnigg, Rudolf Berend; de Jong, Franciska M. G.

    2014-01-01

    Cyberbullying is becoming a major concern in online environments with troubling consequences. However, most of the technical studies have focused on the detection of cyberbullying through identifying harassing comments rather than preventing the incidents by detecting the bullies. In this work we study the automatic detection of bully users on YouTube. We compare three types of automatic detection: an expert system, supervised machine learning models, and a hybrid type combining the two. All ...

  11. Solving Constrained Global Optimization Problems by Using Hybrid Evolutionary Computing and Artificial Life Approaches

    Directory of Open Access Journals (Sweden)

    Jui-Yu Wu

    2012-01-01

    Full Text Available This work presents a hybrid real-coded genetic algorithm with a particle swarm optimization (RGA-PSO algorithm and a hybrid artificial immune algorithm with a PSO (AIA-PSO algorithm for solving 13 constrained global optimization (CGO problems, including six nonlinear programming and seven generalized polynomial programming optimization problems. External RGA and AIA approaches are used to optimize the constriction coefficient, cognitive parameter, social parameter, penalty parameter, and mutation probability of an internal PSO algorithm. CGO problems are then solved using the internal PSO algorithm. The performances of the proposed RGA-PSO and AIA-PSO algorithms are evaluated using 13 CGO problems. Moreover, numerical results obtained using the proposed RGA-PSO and AIA-PSO algorithms are compared with those obtained using published individual GA and AIA approaches. Experimental results indicate that the proposed RGA-PSO and AIA-PSO algorithms converge to a global optimum solution to a CGO problem. Furthermore, the optimum parameter settings of the internal PSO algorithm can be obtained using the external RGA and AIA approaches. Also, the proposed RGA-PSO and AIA-PSO algorithms outperform some published individual GA and AIA approaches. Therefore, the proposed RGA-PSO and AIA-PSO algorithms are highly promising stochastic global optimization methods for solving CGO problems.

  12. Integrating Modelling Approaches for Understanding Telecoupling: Global Food Trade and Local Land Use

    Directory of Open Access Journals (Sweden)

    James D. A. Millington

    2017-08-01

    Full Text Available The telecoupling framework is an integrated concept that emphasises socioeconomic and environmental interactions between distant places. Viewed through the lens of the telecoupling framework, land use and food consumption are linked across local to global scales by decision-making agents and trade flows. Quantitatively modelling the dynamics of telecoupled systems like this could be achieved using numerous different modelling approaches. For example, previous approaches to modelling global food trade have often used partial equilibrium economic models, whereas recent approaches to representing local land use decision-making have widely used agent-based modelling. System dynamics models are well established for representing aggregated flows and stores of products and values between distant locations. We argue that hybrid computational models will be useful for capitalising on the strengths these different modelling approaches each have for representing the various concepts in the telecoupling framework. However, integrating multiple modelling approaches into hybrid models faces challenges, including data requirements and uncertainty assessment. To help guide the development of hybrid models for investigating sustainability through the telecoupling framework here we examine important representational and modelling considerations in the context of global food trade and local land use. We report on the development of our own model that incorporates multiple modelling approaches in a modular approach to negotiate the trade-offs between ideal representation and modelling resource constraints. In this initial modelling our focus is on land use and food trade in and between USA, China and Brazil, but also accounting for the rest of the world. We discuss the challenges of integrating multiple modelling approaches to enable analysis of agents, flows, and feedbacks in the telecoupled system. Our analysis indicates differences in representation of agency

  13. Neural and hybrid modeling: an alternative route to efficiently predict the behavior of biotechnological processes aimed at biofuels obtainment.

    Science.gov (United States)

    Curcio, Stefano; Saraceno, Alessandra; Calabrò, Vincenza; Iorio, Gabriele

    2014-01-01

    The present paper was aimed at showing that advanced modeling techniques, based either on artificial neural networks or on hybrid systems, might efficiently predict the behavior of two biotechnological processes designed for the obtainment of second-generation biofuels from waste biomasses. In particular, the enzymatic transesterification of waste-oil glycerides, the key step for the obtainment of biodiesel, and the anaerobic digestion of agroindustry wastes to produce biogas were modeled. It was proved that the proposed modeling approaches provided very accurate predictions of systems behavior. Both neural network and hybrid modeling definitely represented a valid alternative to traditional theoretical models, especially when comprehensive knowledge of the metabolic pathways, of the true kinetic mechanisms, and of the transport phenomena involved in biotechnological processes was difficult to be achieved.

  14. Neural and Hybrid Modeling: An Alternative Route to Efficiently Predict the Behavior of Biotechnological Processes Aimed at Biofuels Obtainment

    Directory of Open Access Journals (Sweden)

    Stefano Curcio

    2014-01-01

    Full Text Available The present paper was aimed at showing that advanced modeling techniques, based either on artificial neural networks or on hybrid systems, might efficiently predict the behavior of two biotechnological processes designed for the obtainment of second-generation biofuels from waste biomasses. In particular, the enzymatic transesterification of waste-oil glycerides, the key step for the obtainment of biodiesel, and the anaerobic digestion of agroindustry wastes to produce biogas were modeled. It was proved that the proposed modeling approaches provided very accurate predictions of systems behavior. Both neural network and hybrid modeling definitely represented a valid alternative to traditional theoretical models, especially when comprehensive knowledge of the metabolic pathways, of the true kinetic mechanisms, and of the transport phenomena involved in biotechnological processes was difficult to be achieved.

  15. Neural and Hybrid Modeling: An Alternative Route to Efficiently Predict the Behavior of Biotechnological Processes Aimed at Biofuels Obtainment

    Science.gov (United States)

    Saraceno, Alessandra; Calabrò, Vincenza; Iorio, Gabriele

    2014-01-01

    The present paper was aimed at showing that advanced modeling techniques, based either on artificial neural networks or on hybrid systems, might efficiently predict the behavior of two biotechnological processes designed for the obtainment of second-generation biofuels from waste biomasses. In particular, the enzymatic transesterification of waste-oil glycerides, the key step for the obtainment of biodiesel, and the anaerobic digestion of agroindustry wastes to produce biogas were modeled. It was proved that the proposed modeling approaches provided very accurate predictions of systems behavior. Both neural network and hybrid modeling definitely represented a valid alternative to traditional theoretical models, especially when comprehensive knowledge of the metabolic pathways, of the true kinetic mechanisms, and of the transport phenomena involved in biotechnological processes was difficult to be achieved. PMID:24516363

  16. A hybrid cellular automaton model of solid tumor growth and bioreductive drug transport.

    Science.gov (United States)

    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.

  17. Hybrid Quantization: From Bianchi I to the Gowdy Model

    CERN Document Server

    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...

  18. Assessment of the hybrid propagation model, Volume 1: Analysis of noise propagation effects

    Science.gov (United States)

    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...

  19. Modelling of a Hybrid UAV Using Test Flight Data

    NARCIS (Netherlands)

    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

  20. Broadband ground motion simulation using a paralleled hybrid approach of Frequency Wavenumber and Finite Difference method

    Science.gov (United States)

    Chen, M.; Wei, S.</