A hybrid mammalian cell cycle model

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Vincent Noël

2013-08-01

Full Text Available Hybrid modeling provides an effective solution to cope with multiple time scales dynamics in systems biology. Among the applications of this method, one of the most important is the cell cycle regulation. The machinery of the cell cycle, leading to cell division and proliferation, combines slow growth, spatio-temporal re-organisation of the cell, and rapid changes of regulatory proteins concentrations induced by post-translational modifications. The advancement through the cell cycle comprises a well defined sequence of stages, separated by checkpoint transitions. The combination of continuous and discrete changes justifies hybrid modelling approaches to cell cycle dynamics. We present a piecewise-smooth version of a mammalian cell cycle model, obtained by hybridization from a smooth biochemical model. The approximate hybridization scheme, leading to simplified reaction rates and binary event location functions, is based on learning from a training set of trajectories of the smooth model. We discuss several learning strategies for the parameters of the hybrid model.

Comments On Clock Models In Hybrid Automata And Hybrid Control Systems

Directory of Open Access Journals (Sweden)

Virginia Ecaterina OLTEAN

2001-12-01

Full Text Available 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.

Hybrid Reynolds-Averaged/Large Eddy Simulation of a Cavity Flameholder; Assessment of Modeling Sensitivities

Science.gov (United States)

Baurle, R. A.

2015-01-01

Steady-state and scale-resolving simulations have been performed for flow in and around a model scramjet combustor flameholder. The cases simulated corresponded to those used to examine this flowfield experimentally using particle image velocimetry. A variety of turbulence models were used for the steady-state Reynolds-averaged simulations which included both linear and non-linear eddy viscosity models. The scale-resolving simulations used a hybrid Reynolds-averaged / large eddy simulation strategy that is designed to be a large eddy simulation everywhere except in the inner portion (log layer and below) of the boundary layer. Hence, this formulation can be regarded as a wall-modeled large eddy simulation. This effort was undertaken to formally assess the performance of the hybrid Reynolds-averaged / large eddy simulation modeling approach in a flowfield of interest to the scramjet research community. The numerical errors were quantified for both the steady-state and scale-resolving simulations prior to making any claims of predictive accuracy relative to the measurements. The steady-state Reynolds-averaged results showed a high degree of variability when comparing the predictions obtained from each turbulence model, with the non-linear eddy viscosity model (an explicit algebraic stress model) providing the most accurate prediction of the measured values. The hybrid Reynolds-averaged/large eddy simulation results were carefully scrutinized to ensure that even the coarsest grid had an acceptable level of resolution for large eddy simulation, and that the time-averaged statistics were acceptably accurate. The autocorrelation and its Fourier transform were the primary tools used for this assessment. The statistics extracted from the hybrid simulation strategy proved to be more accurate than the Reynolds-averaged results obtained using the linear eddy viscosity models. However, there was no predictive improvement noted over the results obtained from the explicit

A New Hybrid Viscoelastic Soft Tissue Model based on Meshless Method for Haptic Surgical Simulation

Science.gov (United States)

Bao, Yidong; Wu, Dongmei; Yan, Zhiyuan; Du, Zhijiang

2013-01-01

This paper proposes a hybrid soft tissue model that consists of a multilayer structure and many spheres for surgical simulation system based on meshless. To improve accuracy of the model, tension is added to the three-parameter viscoelastic structure that connects the two spheres. By using haptic device, the three-parameter viscoelastic model (TPM) produces accurate deformationand also has better stress-strain, stress relaxation and creep properties. Stress relaxation and creep formulas have been obtained by mathematical formula derivation. Comparing with the experimental results of the real pig liver which were reported by Evren et al. and Amy et al., the curve lines of stress-strain, stress relaxation and creep of TPM are close to the experimental data of the real liver. Simulated results show that TPM has better real-time, stability and accuracy. PMID:24339837

Deriving simulators for hybrid Chi models

NARCIS (Netherlands)

Beek, van D.A.; Man, K.L.; Reniers, M.A.; Rooda, J.E.; Schiffelers, R.R.H.

2006-01-01

The hybrid Chi language is formalism for modeling, simulation and verification of hybrid systems. The formal semantics of hybrid Chi allows the definition of provably correct implementations for simulation, verification and realtime control. This paper discusses the principles of deriving an

Modeling and experimental validation of a Hybridized Energy Storage System for automotive applications

Science.gov (United States)

Fiorenti, Simone; Guanetti, Jacopo; Guezennec, Yann; Onori, Simona

2013-11-01

This paper presents the development and experimental validation of a dynamic model of a Hybridized Energy Storage System (HESS) consisting of a parallel connection of a lead acid (PbA) battery and double layer capacitors (DLCs), for automotive applications. The dynamic modeling of both the PbA battery and the DLC has been tackled via the equivalent electric circuit based approach. Experimental tests are designed for identification purposes. Parameters of the PbA battery model are identified as a function of state of charge and current direction, whereas parameters of the DLC model are identified for different temperatures. A physical HESS has been assembled at the Center for Automotive Research The Ohio State University and used as a test-bench to validate the model against a typical current profile generated for Start&Stop applications. The HESS model is then integrated into a vehicle simulator to assess the effects of the battery hybridization on the vehicle fuel economy and mitigation of the battery stress.

A closed-loop hybrid physiological model relating to subjects under physical stress.

Science.gov (United States)

El-Samahy, Emad; Mahfouf, Mahdi; Linkens, Derek A

2006-11-01

The objective of this research study is to derive a comprehensive physiological model relating to subjects under physical stress conditions. The model should describe the behaviour of the cardiovascular system, respiratory system, thermoregulation and brain activity in response to physical workload. An experimental testing rig was built which consists of recumbent high performance bicycle for inducing the physical load and a data acquisition system comprising monitors and PCs. The signals acquired and used within this study are the blood pressure, heart rate, respiration, body temperature, and EEG signals. The proposed model is based on a grey-box based modelling approach which was used because of the sufficient level of details it provides. Cardiovascular and EEG Data relating to 16 healthy subject volunteers (data from 12 subjects were used for training/validation and the data from 4 subjects were used for model testing) were collected using the Finapres and the ProComp+ monitors. For model validation, residual analysis via the computing of the confidence intervals as well as related histograms was performed. Closed-loop simulations for different subjects showed that the model can provide reliable predictions for heart rate, blood pressure, body temperature, respiration, and the EEG signals. These findings were also reinforced by the residual analyses data obtained, which suggested that the residuals were within the 90% confidence bands and that the corresponding histograms were of a normal distribution. A higher intelligent level was added to the model, based on neural networks, to extend the capabilities of the model to predict over a wide range of subjects dynamics. The elicited physiological model describing the effect of physiological stress on several physiological variables can be used to predict performance breakdown of operators in critical environments. Such a model architecture lends itself naturally to exploitation via feedback control in a 'reverse

Hybrid rocket engine, theoretical model and experiment

Science.gov (United States)

Chelaru, Teodor-Viorel; Mingireanu, Florin

2011-06-01

The purpose of this paper is to build a theoretical model for the hybrid rocket engine/motor and to validate it using experimental results. The work approaches the main problems of the hybrid motor: the scalability, the stability/controllability of the operating parameters and the increasing of the solid fuel regression rate. At first, we focus on theoretical models for hybrid rocket motor and compare the results with already available experimental data from various research groups. A primary computation model is presented together with results from a numerical algorithm based on a computational model. We present theoretical predictions for several commercial hybrid rocket motors, having different scales and compare them with experimental measurements of those hybrid rocket motors. Next the paper focuses on tribrid rocket motor concept, which by supplementary liquid fuel injection can improve the thrust controllability. A complementary computation model is also presented to estimate regression rate increase of solid fuel doped with oxidizer. Finally, the stability of the hybrid rocket motor is investigated using Liapunov theory. Stability coefficients obtained are dependent on burning parameters while the stability and command matrixes are identified. The paper presents thoroughly the input data of the model, which ensures the reproducibility of the numerical results by independent researchers.

Hybrid simulation models of production networks

CERN Document Server

Kouikoglou, Vassilis S

2001-01-01

This book is concerned with a most important area of industrial production, that of analysis and optimization of production lines and networks using discrete-event models and simulation. The book introduces a novel approach that combines analytic models and discrete-event simulation. Unlike conventional piece-by-piece simulation, this method observes a reduced number of events between which the evolution of the system is tracked analytically. Using this hybrid approach, several models are developed for the analysis of production lines and networks. The hybrid approach combines speed and accuracy for exceptional analysis of most practical situations. A number of optimization problems, involving buffer design, workforce planning, and production control, are solved through the use of hybrid models.

Analysis of chromosome aberration data by hybrid-scale models

International Nuclear Information System (INIS)

Indrawati, Iwiq; Kumazawa, Shigeru

2000-02-01

This paper presents a new methodology for analyzing data of chromosome aberrations, which is useful to understand the characteristics of dose-response relationships and to construct the calibration curves for the biological dosimetry. The hybrid scale of linear and logarithmic scales brings a particular plotting paper, where the normal section paper, two types of semi-log papers and the log-log paper are continuously connected. The hybrid-hybrid plotting paper may contain nine kinds of linear relationships, and these are conveniently called hybrid scale models. One can systematically select the best-fit model among the nine models by among the conditions for a straight line of data points. A biological interpretation is possible with some hybrid-scale models. In this report, the hybrid scale models were applied to separately reported data on chromosome aberrations in human lymphocytes as well as on chromosome breaks in Tradescantia. The results proved that the proposed models fit the data better than the linear-quadratic model, despite the demerit of the increased number of model parameters. We showed that the hybrid-hybrid model (both variables of dose and response using the hybrid scale) provides the best-fit straight lines to be used as the reliable and readable calibration curves of chromosome aberrations. (author)

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.

Biochemical response of hybrid black poplar tissue culture (Populus × canadensis) on water stress.

Science.gov (United States)

Popović, B M; Štajner, D; Ždero-Pavlović, R; Tari, I; Csiszár, J; Gallé, Á; Poór, P; Galović, V; Trudić, B; Orlović, S

2017-05-01

In this study, poplar tissue culture (hybrid black poplar, M1 genotype) was subjected to water stress influenced by polyethyleneglycol 6000 (100 and 200 mOsm PEG 6000). The aim of the research was to investigate the biochemical response of poplar tissue culture on water deficit regime. Antioxidant status was analyzed including antioxidant enzymes, superoxide-dismutase (SOD), catalase (CAT), guiacol-peroxidase (GPx), glutathione-peroxidase (GSH-Px), glutathione-reductase, reduced glutathione, total phenol content, Ferric reducing antioxidant power and DPPH radical antioxidant power. Polyphenol oxidase and phenylalanine-ammonium-lyase were determined as enzymatic markers of polyphenol metabolism. Among oxidative stress parameters lipid peroxidation, carbonyl-proteins, hydrogen-peroxide, reactive oxygen species, nitric-oxide and peroxynitrite were determined. Proline, proline-dehydrogenase and glycinebetaine were measured also as parameters of water stress. Cell viability is finally determined as a biological indicator of osmotic stress. It was found that water stress induced reactive oxygen and nitrogen species and lipid peroxidation in leaves of hybrid black poplar and reduced cell viability. Antioxidant enzymes including SOD, GPx, CAT and GSH-Px were induced but total phenol content and antioxidant capacity were reduced by PEG 6000 mediated osmotic stress. The highest biochemical response and adaptive reaction was the increase of proline and GB especially by 200 mOsm PEG. While long term molecular analysis will be necessary to fully address the poplar potentials for water stress adaptation, our results on hybrid black poplar suggest that glycine-betaine, proline and PDH enzyme might be the most important markers of poplar on water stress and that future efforts should be focused on these markers and strategies to enhance their concentration in poplar.

Studies on Screening of Maize (Zea mays L.) Hybrids under Drought Stress Conditions

OpenAIRE

Zahoor Ahmad

2015-01-01

Drought is one of the most serious problems posing a grave threat to cereals production including maize. Two experiments (lab and wire house) were conducted to screen out the most tolerant and most sensitive maize hybrids (7386, 6525, Hycorn, 9696, 32B33, 3672, MMRI and 31P41) under artificial imposing drought stress by PEG-6000 and under water stress applied after seedling emergence. In first experiment five water stress levels such as zero (control), -0.2 MPa, -0.4 MPa, -0.6 MPa, and -0.8 M...

Influence of Stress Shape Function on Analysis of Contact Problem Using Hybrid Photoelasticity

International Nuclear Information System (INIS)

Shin, Dongchul; Hawong, Jaisug

2013-01-01

In this research, a study on stress shape functions was conducted to analyze the contact stress problem by using a hybrid photoelasticity. Because the contact stress problem is generally solved as a half-plane problem, the relationship between two analytical stress functions, which are compositions of the Airy stress function, was similar to one of the crack problem. However, this relationship in itself could not be used to solve the contact stress problem (especially one with singular points). Therefore, to analyze the contact stress problem more correctly, stress shape functions based on the condition of two contact end points had to be considered in the form of these two analytical stress functions. The four types of stress shape functions were related to the stress singularities at the two contact end points. Among them, the primary two types used for the analysis of an O-ring were selected, and their validities were verified in this work

Optimal Design for Hybrid Ratio of Carbon/Basalt Hybrid Fiber Reinforced Resin Matrix Composites

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XU Hong

2017-08-01

Full Text Available The optimum hybrid ratio range of carbon/basalt hybrid fiber reinforced resin composites was studied. Hybrid fiber composites with nine different hybrid ratios were prepared before tensile test.According to the structural features of plain weave, the unit cell's performance parameters were calculated. Finite element model was established by using SHELL181 in ANSYS. The simulated values of the sample stiffness in the model were approximately similar to the experimental ones. The stress nephogram shows that there is a critical hybrid ratio which divides the failure mechanism of HFRP into single failure state and multiple failure state. The tensile modulus, strength and limit tensile strain of HFRP with 45% resin are simulated by finite element method. The result shows that the tensile modulus of HFRP with 60% hybrid ratio increases by 93.4% compared with basalt fiber composites (BFRP, and the limit tensile strain increases by 11.3% compared with carbon fiber composites(CFRP.

Exploratory Topology Modelling of Form-Active Hybrid Structures

DEFF Research Database (Denmark)

Holden Deleuran, Anders; Pauly, Mark; Tamke, Martin

2016-01-01

The development of novel form-active hybrid structures (FAHS) is impeded by a lack of modelling tools that allow for exploratory topology modelling of shaped assemblies. We present a flexible and real-time computational design modelling pipeline developed for the exploratory modelling of FAHS...... 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...

Hybrid Multi-Physics Modeling of an Ultra-Fast Electro-Mechanical Actuator

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Ara Bissal

2015-12-01

Full Text Available The challenges of an HVDC breaker are to generate impulsive forces in the order of hundreds of kilonewtons within fractions of a millisecond, to withstand the arising internal mechanical stresses and to transmit these forces via an electrically-insulating device to the contact system with minimum time delay. In this work, several models were developed with different levels of complexity, computation time and accuracy. Experiments were done with two mushroom-shaped armatures to validate the developed simulation models. It was concluded that although the electromagnetic force generation mechanism is highly sensitive to the mechanical response of the system, the developed first order hybrid model is able to predict the performance of the breaker with good accuracy.

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.

Hybrid discrete choice models: Gained insights versus increasing effort

International Nuclear Information System (INIS)

Mariel, Petr; Meyerhoff, Jürgen

2016-01-01

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.

Strain Rate Dependent Behavior and Modeling for Compression Response of Hybrid Fiber Reinforced Concrete

Directory of Open Access Journals (Sweden)

S.M. Ibrahim

Full Text Available Abstract This paper investigates the stress-strain characteristics of Hybrid fiber reinforced concrete (HFRC composites under dynamic compression using Split Hopkinson Pressure Bar (SHPB for strain rates in the range of 25 to 125 s-1. Three types of fibers - hooked ended steel fibers, monofilament crimped polypropylene fibers and staple Kevlar fibers were used in the production of HFRC composites. The influence of different fibers in HFRC composites on the failure mode, dynamic increase factor (DIF of strength, toughness and strain are also studied. Degree of fragmentation of HFRC composite specimens increases with increase in the strain rate. Although the use of high percentage of steel fibers leads to the best performance but among the hybrid fiber combinations studied, HFRC composites with relatively higher percentage of steel fibers and smaller percentage of polypropylene and Kevlar fibers seem to reflect the equally good synergistic effects of fibers under dynamic compression. A rate dependent analytical model is proposed for predicting complete stress-strain curves of HFRC composites. The model is based on a comprehensive fiber reinforcing index and complements well with the experimental results.

Hybrid Models of Alternative Current Filter for Hvdc

Directory of Open Access Journals (Sweden)

Ufa Ruslan A.

2017-01-01

Full Text Available Based on a hybrid simulation concept of HVDC, the developed hybrid AC filter models, providing the sufficiently full and adequate modeling of all single continuous spectrum of quasi-steady-state and transient processes in the filter, are presented. The obtained results suggest that usage of the hybrid simulation approach is carried out a methodically accurate with guaranteed instrumental error solution of differential equation systems of mathematical models of HVDC.

Three-dimensional linear fracture mechanics analysis by a displacement-hybrid finite-element model

International Nuclear Information System (INIS)

Atluri, S.N.; Kathiresan, K.; Kobayashi, A.S.

1975-01-01

This paper deals with a finite-element procedures for the calculation of modes I, II and III stress intensity factors, which vary, along an arbitrarily curved three-dimensional crack front in a structural component. The finite-element model is based on a modified variational principle of potential energy with relaxed continuity requirements for displacements at the inter-element boundary. The variational principle is a three-field principle, with the arbitrary interior displacements for the element, interelement boundary displacements, and element boundary tractions as variables. The unknowns in the final algebraic system of equations, in the present displacement hybrid finite element model, are the nodal displacements and the three elastic stress intensity factors. Special elements, which contain proper square root and inverse square root crack front variations in displacements and stresses, respectively, are used in a fixed region near the crack front. Interelement displacement compatibility is satisfied by assuming an independent interelement boundary displacement field, and using a Lagrange multiplier technique to enforce such interelement compatibility. These Lagrangean multipliers, which are physically the boundary tractions, are assumed from an equilibrated stress field derived from three-dimensional Beltrami (or Maxwell-Morera) stress functions that are complete. However, considerable care should be exercised in the use of these stress functions such that the stresses produced by any of these stress function components are not linearly dependent

Some hybrid models applicable to dose-response relationships

International Nuclear Information System (INIS)

Kumazawa, Shigeru

1992-01-01

A new type of models of dose-response relationships has been studied as an initial stage to explore a reliable extrapolation of the relationships decided by high dose data to the range of low dose covered by radiation protection. The approach is to use a 'hybrid scale' of linear and logarithmic scales; the first model is that the normalized surviving fraction (ρ S > 0) in a hybrid scale decreases linearly with dose in a linear scale, and the second is that the induction in a log scale increases linearly with the normalized dose (τ D > 0) in a hybrid scale. The hybrid scale may reflect an overall effectiveness of a complex system against adverse events caused by various agents. Some data of leukemia in the atomic bomb survivors and of rodent experiments were used to show the applicability of hybrid scale models. The results proved that proposed models fit these data not less than the popular linear-quadratic models, providing the possible interpretation of shapes of dose-response curves, e.g. shouldered survival curves varied by recovery time. (author)

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

Hybrid computer modelling in plasma physics

International Nuclear Information System (INIS)

Hromadka, J; Ibehej, T; Hrach, R

2016-01-01

Our contribution is devoted to development of hybrid modelling techniques. We investigate sheath structures in the vicinity of solids immersed in low temperature argon plasma of different pressures by means of particle and fluid computer models. We discuss the differences in results obtained by these methods and try to propose a way to improve the results of fluid models in the low pressure area. There is a possibility to employ Chapman-Enskog method to find appropriate closure relations of fluid equations in a case when particle distribution function is not Maxwellian. We try to follow this way to enhance fluid model and to use it in hybrid plasma model further. (paper)

Examining the dimensional structure models of secondary traumatic stress based on DSM-5 symptoms.

Science.gov (United States)

Mordeno, Imelu G; Go, Geraldine P; Yangson-Serondo, April

2017-02-01

Latent factor structure of Secondary Traumatic Stress (STS) has been examined using Diagnostic Statistic Manual-IV (DSM-IV)'s Posttraumatic Stress Disorder (PTSD) nomenclature. With the advent of Diagnostic Statistic Manual-5 (DSM-5), there is an impending need to reexamine STS using DSM-5 symptoms in light of the most updated PTSD models in the literature. The study investigated and determined the best fitted PTSD models using DSM-5 PTSD criteria symptoms. Confirmatory factor analysis (CFA) was conducted to examine model fit using the Secondary Traumatic Stress Scale in 241 registered and practicing Filipino nurses (166 females and 75 males) who worked in the Philippines and gave direct nursing services to patients. Based on multiple fit indices, the results showed the 7-factor hybrid model, comprising of intrusion, avoidance, negative affect, anhedonia, externalizing behavior, anxious arousal, and dysphoric arousal factors has excellent fit to STS. This model asserts that: (1) hyperarousal criterion needs to be divided into anxious and dysphoric arousal factors; (2) symptoms characterizing negative and positive affect need to be separated to two separate factors, and; (3) a new factor would categorize externalized, self-initiated impulse and control-deficit behaviors. Comparison of nested and non-nested models showed Hybrid model to have superior fit over other models. The specificity of the symptom structure of STS based on DSM-5 PTSD criteria suggests having more specific interventions addressing the more elaborate symptom-groupings that would alleviate the condition of nurses exposed to STS on a daily basis. Copyright © 2016 Elsevier B.V. All rights reserved.

Ectopic expression of a horseradish peroxidase enhances growth rate and increases oxidative stress resistance in hybrid aspen.

Science.gov (United States)

Kawaoka, Akiyoshi; Matsunaga, Etsuko; Endo, Saori; Kondo, Shinkichi; Yoshida, Kazuya; Shinmyo, Atsuhiko; Ebinuma, Hiroyasu

2003-07-01

We previously demonstrated that overexpression of the horseradish (Armoracia rusticana) peroxidase prxC1a gene stimulated the growth rate of tobacco (Nicotiana tabacum) plants. Here, the cauliflower mosaic virus 35S::prxC1a construct was introduced into hybrid aspen (Populus sieboldii x Populus grandidentata). The growth rate of these transformed hybrid aspen plants was substantially increased under greenhouse conditions. The average stem length of transformed plants was 25% greater than that of control plants. There was no other obvious phenotypic difference between the transformed and control plants. Fast-growing transformed hybrid aspen showed high levels of expression of prxC1a and had elevated peroxidase activities toward guaiacol and ascorbate. However, there was no increase of the endogenous class I ascorbate peroxidase activities in the transformed plants by separate assay and activity staining of native polyacrylamide gel electrophoresis. Furthermore, calli derived from the transformed hybrid aspen grew faster than those from control plants and were resistant to the oxidative stress imposed by hydrogen peroxide. Therefore, enhanced peroxidase activity affects plant growth rate and oxidative stress resistance.

Extension to linear dynamics for hybrid stress finite element formulation based on additional displacements

Science.gov (United States)

Sumihara, K.

Based upon legitimate variational principles, one microscopic-macroscopic finite element formulation for linear dynamics is presented by Hybrid Stress Finite Element Method. The microscopic application of Geometric Perturbation introduced by Pian and the introduction of infinitesimal limit core element (Baby Element) have been consistently combined according to the flexible and inherent interpretation of the legitimate variational principles initially originated by Pian and Tong. The conceptual development based upon Hybrid Finite Element Method is extended to linear dynamics with the introduction of physically meaningful higher modes.

Cloning the Gravity and Shear Stress Related Genes from MG-63 Cells by Subtracting Hybridization

Science.gov (United States)

Zhang, Shu; Dai, Zhong-quan; Wang, Bing; Cao, Xin-sheng; Li, Ying-hui; Sun, Xi-qing

2008-06-01

Background The purpose of the present study was to clone the gravity and shear stress related genes from osteoblast-like human osteosarcoma MG-63 cells by subtractive hybridization. Method MG-63 cells were divided into two groups (1G group and simulated microgravity group). After cultured for 60 h in two different gravitational environments, two groups of MG-63 cells were treated with 1.5Pa fluid shear stress (FSS) for 60 min, respectively. The total RNA in cells was isolated. The gravity and shear stress related genes were cloned by subtractive hybridization. Result 200 clones were gained. 30 positive clones were selected using PCR method based on the primers of vector and sequenced. The obtained sequences were analyzed by blast. changes of 17 sequences were confirmed by RT-PCR and these genes are related to cell proliferation, cell differentiation, protein synthesis, signal transduction and apoptosis. 5 unknown genes related to gravity and shear stress were found. Conclusion In this part of our study, our result indicates that simulated microgravity may change the activities of MG-63 cells by inducing the functional alterations of specific genes.

Comparative proteome analysis of drought-sensitive and drought-tolerant rapeseed roots and their hybrid F1 line under drought stress.

Science.gov (United States)

Mohammadi, Payam Pour; Moieni, Ahmad; Komatsu, Setsuko

2012-11-01

Rapeseed (Brassica napus L.), which is the third leading source of vegetable oil, is sensitive to drought stress during the early vegetative growth stage. To investigate the initial response of rapeseed to drought stress, changes in the protein expression profiles of drought-sensitive (RGS-003) and drought-tolerant lines (SLM-003), and their F1 hybrid, were analyzed using a proteomics approach. Seven-day-old rapeseed seedlings were treated with drought stress by restricting water for 7 days, and proteins were extracted from roots and separated by two-dimensional polyacrylamide gel electrophoresis. In the sensitive rapeseed line, 35 protein spots were differentially expressed under drought stress, and proteins related to metabolism, energy, disease/defense, and transport were decreased. In the tolerant line, 32 protein spots were differentially expressed under drought stress, and proteins involved in metabolism, disease/defense, and transport were increased, while energy-related proteins were decreased. Six protein spots in F1 hybrid were common among expressed proteins in the drought-sensitive and -tolerant lines. Notably, tubulin beta-2 and heat shock protein 70 were decreased in the drought-sensitive line and hybrid F1 plants, while jasmonate-inducible protein and 20S proteasome subunit PAF1 were increased in the F1 hybrids and drought-tolerant line. These results indicate that (1) V-type H(+) ATPase, plasma-membrane associated cation-binding protein, HSP 90, and elongation factor EF-2 have a role in the drought tolerance of rapeseed; (2) The decreased levels of heat shock protein 70 and tubulin beta-2 in the drought-sensitive and hybrid F1 lines might explain the reduced growth of these lines in drought conditions.

Modeling of Hybrid Growth Wastewater Bio-reactor

International Nuclear Information System (INIS)

EI Nashaei, S.; Garhyan, P.; Prasad, P.; Abdel Halim, H.S.; Ibrahim, G.

2004-01-01

The attached/suspended growth mixed reactors are considered one of the recently tried approaches to improve the performance of the biological treatment by increasing the volume of the accumulated biomass in terms of attached growth as well as suspended growth. Moreover, the domestic WW can be easily mixed with a high strength non-hazardous industrial wastewater and treated together in these bio-reactors if the need arises. Modeling of Hybrid hybrid growth wastewater reactor addresses the need of understanding the rational of such system in order to achieve better design and operation parameters. This paper aims at developing a heterogeneous mathematical model for hybrid growth system considering the effect of diffusion, external mass transfer, and power input to the system in a rational manner. The model will be based on distinguishing between liquid/solid phase (bio-film and bio-floc). This model would be a step ahead to the fine tuning the design of hybrid systems based on the experimental data of a pilot plant to be implemented in near future

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

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E. Kallio

Full Text Available Quasi-neutral hybrid model is a self-consistent modelling approach that includes positively charged particles and an electron fluid. The approach has received an increasing interest in space plasma physics research because it makes it possible to study several plasma physical processes that are difficult or impossible to model by self-consistent fluid models, such as the effects associated with the ions’ finite gyroradius, the velocity difference between different ion species, or the non-Maxwellian velocity distribution function. By now quasi-neutral hybrid models have been used to study the solar wind interaction with the non-magnetised Solar System bodies of Mars, Venus, Titan and comets. Localized, two-dimensional hybrid model runs have also been made to study terrestrial dayside magnetosheath. However, the Hermean plasma environment has not yet been analysed by a global quasi-neutral hybrid model.

In this paper we present a new quasi-neutral hybrid model developed to study various processes associated with the Mercury-solar wind interaction. Emphasis is placed on addressing advantages and disadvantages of the approach to study different plasma physical processes near the planet. The basic assumptions of the approach and the algorithms used in the new model are thoroughly presented. Finally, some of the first three-dimensional hybrid model runs made for Mercury are presented.

The resulting macroscopic plasma parameters and the morphology of the magnetic field demonstrate the applicability of the new approach to study the Mercury-solar wind interaction globally. In addition, the real advantage of the kinetic hybrid model approach is to study the property of individual ions, and the study clearly demonstrates the large potential of the approach to address these more detailed issues by a quasi-neutral hybrid model in the future.

Key words. Magnetospheric physics

Study of Stress Migration Failure in SiLKTM/SiO2 Hybrid Cu Interconnects

International Nuclear Information System (INIS)

Tsuchikawa, Haruo; Nakamura, Tomoji; Suzuki, Takashi; Mori, Hiroko; Shono, Ken

2004-01-01

Stress migration (SM) behavior is studied for a 130nm-node SiLK TM /SiO2 hybrid structure in which the interlevel dielectrics (ILD) consist of SiLK TM for trench levels and SiO2 for via levels. The failure rate dependence on the temperature, line width and circuit is examined in detail. Furthermore, an effect of dielectric deposition process on the reliability of the hybrid interconnects is investigated. It has been found that SM behavior is essentially similar to that reported in Cu/SiO2 systems. It has also been clarified that SiO2 PVD conditions at via level had a large impact on the failure rate. Therefore, the control of ILD deposition conditions is found to be one of the key factors in suppressing the SM failure. In order to examine the effect of the PVD conditions, the residual stress in vias were measured by using X-ray diffraction method. The results show that σx (the stress component parallel to the surface) in vias greatly depends on the PVD conditions. Then, the relationship between the PVD conditions and the SM failure rate is clarified

Causality in Psychiatry: A Hybrid Symptom Network Construct Model

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Gerald eYoung

2015-11-01

Full Text Available Causality or etiology in psychiatry is marked by standard biomedical, reductionistic models (symptoms reflect the construct involved that inform approaches to nosology, or classification, such as in the DSM-5 (Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition; American Psychiatric Association, 2013. However, network approaches to symptom interaction (i.e., symptoms are formative of the construct; e.g., McNally, Robinaugh, Wu, Wang, Deserno, & Borsboom, 2014, for PTSD (posttraumatic stress disorder are being developed that speak to bottom-up processes in mental disorder, in contrast to the typical top-down psychological construct approach. The present article presents a hybrid top-down, bottom-up model of the relationship between symptoms and mental disorder, viewing symptom expression and their causal complex as a reciprocally dynamic system with multiple levels, from lower-order symptoms in interaction to higher-order constructs affecting them. The hybrid model hinges on good understanding of systems theory in which it is embedded, so that the article reviews in depth nonlinear dynamical systems theory (NLDST. The article applies the concept of emergent circular causality (Young, 2011 to symptom development, as well. Conclusions consider that symptoms vary over several dimensions, including: subjectivity; objectivity; conscious motivation effort; and unconscious influences, and the degree to which individual (e.g., meaning and universal (e.g., causal processes are involved. The opposition between science and skepticism is a complex one that the article addresses in final comments.

A hybrid absorbing boundary condition for frequency-domain finite-difference modelling

International Nuclear Information System (INIS)

Ren, Zhiming; Liu, Yang

2013-01-01

Liu and Sen (2010 Geophysics 75 A1–6; 2012 Geophys. Prospect. 60 1114–32) proposed an efficient hybrid scheme to significantly absorb boundary reflections for acoustic and elastic wave modelling in the time domain. In this paper, we extend the hybrid absorbing boundary condition (ABC) into the frequency domain and develop specific strategies for regular-grid and staggered-grid modelling, respectively. Numerical modelling tests of acoustic, visco-acoustic, elastic and vertically transversely isotropic (VTI) equations show significant absorptions for frequency-domain modelling. The modelling results of the Marmousi model and the salt model also demonstrate the effectiveness of the hybrid ABC. For elastic modelling, the hybrid Higdon ABC and the hybrid Clayton and Engquist (CE) ABC are implemented, respectively. Numerical simulations show that the hybrid Higdon ABC gets better absorption than the hybrid CE ABC, especially for S-waves. We further compare the hybrid ABC with the classical perfectly matched layer (PML). Results show that the two ABCs cost the same computation time and memory space for the same absorption width. However, the hybrid ABC is more effective than the PML for the same small absorption width and the absorption effects of the two ABCs gradually become similar when the absorption width is increased. (paper)

Model Reduction of Hybrid Systems

DEFF Research Database (Denmark)

Shaker, Hamid Reza

gramians. Generalized gramians are the solutions to the observability and controllability Lyapunov inequalities. In the first framework the projection matrices are found based on the common generalized gramians. This framework preserves the stability of the original switched system for all switching...... is guaranteed to be preserved for arbitrary switching signal. To compute the common generalized gramians linear matrix inequalities (LMI’s) need to be solved. These LMI’s are not always feasible. In order to solve the problem of conservatism, the second framework is presented. In this method the projection......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...

Mathematical Modeling of Hybrid Electrical Engineering Systems

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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

Modeling of residual stress state in turning of 304L

International Nuclear Information System (INIS)

Valiorgue, F.; Rech, J.; Bergheau, J.M.

2010-01-01

Research presented in this paper aims to link machining parameters to residual stress state and helps understanding mechanisms responsible of machined surface properties modifications. The first presented works are based on an experimental campaign. They reproduce the finishing turning operation of 304L and allow observing the residual stress state evolution at the work piece surface and for an affected depth of 0.2 mm for such processes. Then, the finishing turning operation is simulated numerically in order to realize the same sensitivity study to cutting parameters. This simulation is based on an hybrid approach mixing experimental data and numerical simulation. This method allows getting round the classical difficulties of turning simulation by applying equivalent thermo mechanical loadings onto the work piece surface without modeling the material separation phenomena. Moreover the numerical model uses an hardening law taking into account dynamic recrystallization phenomena. (authors)

Probabilistic modelling and analysis of stand-alone hybrid power systems

International Nuclear Information System (INIS)

Lujano-Rojas, Juan M.; Dufo-López, Rodolfo; Bernal-Agustín, José L.

2013-01-01

As a part of the Hybrid Intelligent Algorithm, a model based on an ANN (artificial neural network) has been proposed in this paper to represent hybrid system behaviour considering the uncertainty related to wind speed and solar radiation, battery bank lifetime, and fuel prices. The Hybrid Intelligent Algorithm suggests a combination of probabilistic analysis based on a Monte Carlo simulation approach and artificial neural network training embedded in a genetic algorithm optimisation model. The installation of a typical hybrid system was analysed. Probabilistic analysis was used to generate an input–output dataset of 519 samples that was later used to train the ANNs to reduce the computational effort required. The generalisation ability of the ANNs was measured in terms of RMSE (Root Mean Square Error), MBE (Mean Bias Error), MAE (Mean Absolute Error), and R-squared estimators using another data group of 200 samples. The results obtained from the estimation of the expected energy not supplied, the probability of a determined reliability level, and the estimation of expected value of net present cost show that the presented model is able to represent the main characteristics of a typical hybrid power system under uncertain operating conditions. - Highlights: • This paper presents a probabilistic model for stand-alone hybrid power system. • The model considers the main sources of uncertainty related to renewable resources. • The Hybrid Intelligent Algorithm has been applied to represent hybrid system behaviour. • The installation of a typical hybrid system was analysed. • The results obtained from the study case validate the presented model

Selection on crop-derived traits and QTL in sunflower (Helianthus annuus) crop-wild hybrids under water stress.

Science.gov (United States)

Owart, Birkin R; Corbi, Jonathan; Burke, John M; Dechaine, Jennifer M

2014-01-01

Locally relevant conditions, such as water stress in irrigated agricultural regions, should be considered when assessing the risk of crop allele introgression into wild populations following hybridization. Although research in cultivars has suggested that domestication traits may reduce fecundity under water stress as compared to wild-like phenotypes, this has not been investigated in crop-wild hybrids. In this study, we examine phenotypic selection acting on, as well as the genetic architecture of vegetative, reproductive, and physiological characteristics in an experimental population of sunflower crop-wild hybrids grown under wild-like low water conditions. Crop-derived petiole length and head diameter were favored in low and control water environments. The direction of selection differed between environments for leaf size and leaf pressure potential. Interestingly, the additive effect of the crop-derived allele was in the direction favored by selection for approximately half the QTL detected in the low water environment. Selection favoring crop-derived traits and alleles in the low water environment suggests that a subset of these alleles would be likely to spread into wild populations under water stress. Furthermore, differences in selection between environments support the view that risk assessments should be conducted under multiple locally relevant conditions.

Performance of two-lobe hole-entry hybrid journal bearing system under the combined influence of textured surface and couple stress lubricant

Science.gov (United States)

Khatri, Chandra B.; Sharma, Satish C.

2018-02-01

Textured surface in journal bearings is becoming an important area of investigation during the last few years. Surface textures have the shapes of micro-dimple with a small diameter and depth having order of magnitude of bearing clearance. This paper presents the influence of couple stress lubricant on the circular and non-circular hole-entry hybrid journal bearing system and reports the comparative study between the textured and non-textured circular/non-circular hybrid journal bearing system. The governing Reynolds equation has been modified for the couple stress lubricant flow in the clearance of bearing and journal. The FEM technique has been applied to solve the modified Reynolds equation together with restrictor flow equation. The numerically simulated results indicate that the influence of couple stress lubricant is significantly more in textured journal bearing than that of non-textured journal bearing. Further, it has been observed that the textured two-lobe (δ = 1.1) hybrid journal bearing lubricated with couple stress lubricant provides larger values of fluid film stiffness coefficients and stability threshold speed against other bearings studied in the present paper.

Modelling dependable systems using hybrid Bayesian networks

International Nuclear Information System (INIS)

Neil, Martin; Tailor, Manesh; Marquez, David; Fenton, Norman; Hearty, Peter

2008-01-01

A hybrid Bayesian network (BN) is one that incorporates both discrete and continuous nodes. In our extensive applications of BNs for system dependability assessment, the models are invariably hybrid and the need for efficient and accurate computation is paramount. We apply a new iterative algorithm that efficiently combines dynamic discretisation with robust propagation algorithms on junction tree structures to perform inference in hybrid BNs. We illustrate its use in the field of dependability with two example of reliability estimation. Firstly we estimate the reliability of a simple single system and next we implement a hierarchical Bayesian model. In the hierarchical model we compute the reliability of two unknown subsystems from data collected on historically similar subsystems and then input the result into a reliability block model to compute system level reliability. We conclude that dynamic discretisation can be used as an alternative to analytical or Monte Carlo methods with high precision and can be applied to a wide range of dependability problems

Drought Stress Responses of Sunflower Germplasm Developed after Wide Hybridization

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Roumiana Dimova Vassilevska-Ivanova

2016-10-01

Full Text Available Response of sunflower germplasms viz. cultivated sunflower H. annuus and two breeding lines H. annuus x T. rotundifolia and H. annuus x V. encelioides developed after wide hybridization were used for identification of drought tolerant sunflower genotypes at the seedling growth stage. Three water stress levels of zero (control, -0.4, and -0.8 MPa were developed using polyethyleneglycol-6000 (PEG-6000. Physiological and biochemical stress determining parameters such as root and shoots length, fresh weight, antioxidant enzyme activities (superoxide dismutase (SOD, catalase (CAT, guaiacol peroxidase (GPO, ascorbate peroxidase (APX and antioxidant metabolite content (total antioxidant capacity, total phenols and total flavonoids content were compared between seedlings of all three genotypes. Results revealed that sunflower genotypes have similar responses at two osmotic potentials for shoot and root length and fresh weight. The data also showed that drought stresss could induce oxidative stress, as indicated by the increase level of ascorbate peroxidase and guaiacol peroxidase at -04 MPa in H. annuus cv 1114. Although the activity of ascorbate peroxidase and guaiacol peroxidase was differentially influenced by drought, the changes of antioxidant enzyme activities such as catalase, superoxide dismutase, guaiacol peroxidase, and ascorbate peroxidase subjected to drought stress follow a similar pattern in both breeding lines, indicating that similar defense systems might be involved in the oxidative stress injury in sunflowers. Increase in content of phenols and flavonoids were detected for all three genotypes under stress, which showed that these were major antioxidant metabolites in scavenging cellular H2O2.

Modelling of fluid flow phenomenon in laser+GMAW hybrid welding of aluminum alloy considering three phase coupling and arc plasma shear stress

Science.gov (United States)

Xu, Guoxiang; Li, Pengfei; Cao, Qingnan; Hu, Qingxian; Gu, Xiaoyan; Du, Baoshuai

2018-03-01

The present study aims to develop a unified three dimensional numerical model for fiber laser+GMAW hybrid welding, which is used to study the fluid flow phenomena in hybrid welding of aluminum alloy and the influence of laser power on weld pool dynamic behavior. This model takes into account the coupling of gas, liquid and metal phases. Laser heat input is described using a cone heat source model with changing peak power density, its height being determined based on the keyhole size. Arc heat input is modeled as a double ellipsoid heat source. The arc plasma flow and droplet transfer are simulated through the two simplified models. The temperature and velocity fields for different laser powers are calculated. The computed results are in general agreement with the experimental data. Both the peak and average values of fluid flow velocity during hybrid welding are much higher than those of GMAW. At a low level of laser power, both the arc force and droplet impingement force play a relatively large role on fluid flow in the hybrid welding. Keyhole depth always oscillates within a range. With an increase in laser power, the weld pool behavior becomes more complex. An anti-clockwise vortex is generated and the stability of keyhole depth is improved. Besides, the effects of laser power on different driving forces of fluid flow in weld pool are also discussed.

Hybrid photovoltaic–thermal solar collectors dynamic modeling

International Nuclear Information System (INIS)

Amrizal, N.; Chemisana, D.; Rosell, J.I.

2013-01-01

Highlights: ► A hybrid photovoltaic/thermal dynamic model is presented. ► The model, once calibrated, can predict the power output for any set of climate data. ► The physical electrical model includes explicitly thermal and irradiance dependences. ► The results agree with those obtained through steady-state characterization. ► The model approaches the junction cell temperature through the system energy balance. -- Abstract: A hybrid photovoltaic/thermal transient model has been developed and validated experimentally. The methodology extends the quasi-dynamic thermal model stated in the EN 12975 in order to involve the electrical performance and consider the dynamic behavior minimizing constraints when characterizing the collector. A backward moving average filtering procedure has been applied to improve the model response for variable working conditions. Concerning the electrical part, the model includes the thermal and radiation dependences in its variables. The results revealed that the characteristic parameters included in the model agree reasonably well with the experimental values obtained from the standard steady-state and IV characteristic curve measurements. After a calibration process, the model is a suitable tool to predict the thermal and electrical performance of a hybrid solar collector, for a specific weather data set.

Evaporator modeling - A hybrid approach

International Nuclear Information System (INIS)

Ding Xudong; Cai Wenjian; Jia Lei; Wen Changyun

2009-01-01

In this paper, a hybrid modeling approach is proposed to model two-phase flow evaporators. The main procedures for hybrid modeling includes: (1) Based on the energy and material balance, and thermodynamic principles to formulate the process fundamental governing equations; (2) Select input/output (I/O) variables responsible to the system performance which can be measured and controlled; (3) Represent those variables existing in the original equations but are not measurable as simple functions of selected I/Os or constants; (4) Obtaining a single equation which can correlate system inputs and outputs; and (5) Identify unknown parameters by linear or nonlinear least-squares methods. The method takes advantages of both physical and empirical modeling approaches and can accurately predict performance in wide operating range and in real-time, which can significantly reduce the computational burden and increase the prediction accuracy. The model is verified with the experimental data taken from a testing system. The testing results show that the proposed model can predict accurately the performance of the real-time operating evaporator with the maximum error of ±8%. The developed models will have wide applications in operational optimization, performance assessment, fault detection and diagnosis

Finite element modelling to assess the effect of surface mounted piezoelectric patch size on vibration response of a hybrid beam

Science.gov (United States)

Rahman, N.; Alam, M. N.

2018-02-01

Vibration response analysis of a hybrid beam with surface mounted patch piezoelectric layer is presented in this work. A one dimensional finite element (1D-FE) model based on efficient layerwise (zigzag) theory is used for the analysis. The beam element has eight mechanical and a variable number of electrical degrees of freedom. The beams are also modelled in 2D-FE (ABAQUS) using a plane stress piezoelectric quadrilateral element for piezo layers and a plane stress quadrilateral element for the elastic layers of hybrid beams. Results are presented to assess the effect of size of piezoelectric patch layer on the free and forced vibration responses of thin and moderately thick beams under clamped-free and clamped-clamped configurations. The beams are subjected to unit step loading and harmonic loading to obtain the forced vibration responses. The vibration control using in phase actuation potential on piezoelectric patches is also studied. The 1D-FE results are compared with the 2D-FE results.

A Structural Model Decomposition Framework for Hybrid Systems Diagnosis

Science.gov (United States)

Daigle, Matthew; Bregon, Anibal; Roychoudhury, Indranil

2015-01-01

Nowadays, a large number of practical systems in aerospace and industrial environments are best represented as hybrid systems that consist of discrete modes of behavior, each defined by a set of continuous dynamics. These hybrid dynamics make the on-line fault diagnosis task very challenging. In this work, we present a new modeling and diagnosis framework for hybrid systems. Models are composed from sets of user-defined components using a compositional modeling approach. Submodels for residual generation are then generated for a given mode, and reconfigured efficiently when the mode changes. Efficient reconfiguration is established by exploiting causality information within the hybrid system models. The submodels can then be used for fault diagnosis based on residual generation and analysis. We demonstrate the efficient causality reassignment, submodel reconfiguration, and residual generation for fault diagnosis using an electrical circuit case study.

A Novel Hybrid Similarity Calculation Model

Directory of Open Access Journals (Sweden)

Xiaoping Fan

2017-01-01

Full Text Available This paper addresses the problems of similarity calculation in the traditional recommendation algorithms of nearest neighbor collaborative filtering, especially the failure in describing dynamic user preference. Proceeding from the perspective of solving the problem of user interest drift, a new hybrid similarity calculation model is proposed in this paper. This model consists of two parts, on the one hand the model uses the function fitting to describe users’ rating behaviors and their rating preferences, and on the other hand it employs the Random Forest algorithm to take user attribute features into account. Furthermore, the paper combines the two parts to build a new hybrid similarity calculation model for user recommendation. Experimental results show that, for data sets of different size, the model’s prediction precision is higher than the traditional recommendation algorithms.

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.

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...

Modelling and control of a light-duty hybrid electric truck

OpenAIRE

Park, Jong-Kyu

2006-01-01

This study is concentrated on modelling and developing the controller for the light-duty hybrid electric truck. The hybrid electric vehicle has advantages in fuel economy. However, there have been relatively few studies on commercial HEVs, whilst a considerable number of studies on the hybrid electric system have been conducted in the field of passenger cars. So the current status and the methodologies to develop the LD hybrid electric truck model have been studied through the ...

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.

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.

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.

Development of nondestructive hybrid measuring method for three-dimensional residual stress distribution of thick welded joint. Hybrid measuring method of inherent strain method and neutron diffraction method

International Nuclear Information System (INIS)

Nakacho, Keiji; Kasahara, Norifumi; Tamura, Ryota

2012-01-01

The measuring methods of the residual stress are classified into destructive one and nondestructive one. The inherent strain method (ISM) is destructive one. The neutron diffraction method (NDM) is nondestructive one. But the measurable depth is limited within about 20 mm and the method cannot measure the weld zone, without destruction of the object. So, in this study, the hybrid measuring method has been developed, by combining the ISM and the NDM. The theory of the hybrid method is the same as the ISM. In the analysis, the strains measured by the NDM without destruction are used. This hybrid measuring method is a true nondestructive measuring method for a thick welded joint. The applicability of the hybrid method has been verified by simulation, using a butt welded joint of thick pipes. In the simulation, the reliable order of the strains measured by the present NDM is very important, and was considered as 10 micro. The measurable regions by the present NDM were assumed. Under the above conditions, the data (the residual elastic strains assumed to be measured by the NDM) were made, and used in the ISM. As a result of such simulation, it has been cleared that the estimated residual stress has very high accuracy, if enough data are used. The required number of data is less than the ISM. (author)

Stress field models from Maxwell stress functions: southern California

Science.gov (United States)

Bird, Peter

2017-08-01

The lithospheric stress field is formally divided into three components: a standard pressure which is a function of elevation (only), a topographic stress anomaly (3-D tensor field) and a tectonic stress anomaly (3-D tensor field). The boundary between topographic and tectonic stress anomalies is somewhat arbitrary, and here is based on the modeling tools available. The topographic stress anomaly is computed by numerical convolution of density anomalies with three tensor Green's functions provided by Boussinesq, Cerruti and Mindlin. By assuming either a seismically estimated or isostatic Moho depth, and by using Poisson ratio of either 0.25 or 0.5, I obtain four alternative topographic stress models. The tectonic stress field, which satisfies the homogeneous quasi-static momentum equation, is obtained from particular second derivatives of Maxwell vector potential fields which are weighted sums of basis functions representing constant tectonic stress components, linearly varying tectonic stress components and tectonic stress components that vary harmonically in one, two and three dimensions. Boundary conditions include zero traction due to tectonic stress anomaly at sea level, and zero traction due to the total stress anomaly on model boundaries at depths within the asthenosphere. The total stress anomaly is fit by least squares to both World Stress Map data and to a previous faulted-lithosphere, realistic-rheology dynamic model of the region computed with finite-element program Shells. No conflict is seen between the two target data sets, and the best-fitting model (using an isostatic Moho and Poisson ratio 0.5) gives minimum directional misfits relative to both targets. Constraints of computer memory, execution time and ill-conditioning of the linear system (which requires damping) limit harmonically varying tectonic stress to no more than six cycles along each axis of the model. The primary limitation on close fitting is that the Shells model predicts very sharp

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.

Hybrid dynamics for currency modeling

OpenAIRE

Theodosopoulos, Ted; Trifunovic, Alex

2006-01-01

We present a simple hybrid dynamical model as a tool to investigate behavioral strategies based on trend following. The multiplicative symbolic dynamics are generated using a lognormal diffusion model for the at-the-money implied volatility term structure. Thus, are model exploits information from derivative markets to obtain qualititative properties of the return distribution for the underlier. We apply our model to the JPY-USD exchange rate and the corresponding 1mo., 3mo., 6mo. and 1yr. im...

Meta-analysis of studies using suppression subtractive hybridization and microarrays to investigate the effects of environmental stress on gene transcription in oysters.

Science.gov (United States)

Anderson, Kelli; Taylor, Daisy A; Thompson, Emma L; Melwani, Aroon R; Nair, Sham V; Raftos, David A

2015-01-01

Many microarray and suppression subtractive hybridization (SSH) studies have analyzed the effects of environmental stress on gene transcription in marine species. However, there have been no unifying analyses of these data to identify common stress response pathways. To address this shortfall, we conducted a meta-analysis of 14 studies that investigated the effects of different environmental stressors on gene expression in oysters. The stressors tested included chemical contamination, hypoxia and infection, as well as extremes of temperature, pH and turbidity. We found that the expression of over 400 genes in a range of oyster species changed significantly after exposure to environmental stress. A repeating pattern was evident in these transcriptional responses, regardless of the type of stress applied. Many of the genes that responded to environmental stress encoded proteins involved in translation and protein processing (including molecular chaperones), the mitochondrial electron transport chain, anti-oxidant activity and the cytoskeleton. In light of these findings, we put forward a consensus model of sub-cellular stress responses in oysters.

Optimization of hybrid model on hajj travel

Science.gov (United States)

Cahyandari, R.; Ariany, R. L.; Sukono

2018-03-01

Hajj travel insurance is an insurance product offered by the insurance company in preparing funds to perform the pilgrimage. This insurance product helps would-be pilgrims to set aside a fund of saving hajj with regularly, but also provides funds of profit sharing (mudharabah) and insurance protection. Scheme of insurance product fund management is largely using the hybrid model, which is the fund from would-be pilgrims will be divided into three account management, that is personal account, tabarru’, and ujrah. Scheme of hybrid model on hajj travel insurance was already discussed at the earlier paper with titled “The Hybrid Model Algorithm on Sharia Insurance”, taking the example case of Mitra Mabrur Plus product from Bumiputera company. On these advanced paper, will be made the previous optimization model design, with partition of benefit the tabarru’ account. Benefits such as compensation for 40 critical illness which initially only for participants of insurance only, on optimization is intended for participants of the insurance and his heir, also to benefit the hospital bills. Meanwhile, the benefits of death benefit is given if the participant is fixed die.

Bearing Stress at Failure of Double-Lap Hybrid Joints in Woven Fabric Kenaf Fiber Composite Plates under Quasi-static Loading

Directory of Open Access Journals (Sweden)

Lee Sim Yee

2017-01-01

Full Text Available The present paper is focused on the bearing stress at failure of double-lap woven fabric kenaf fiber reinforced polymer (KFRP hybrid bonded-bolted joints in experimental frameworks. The effects of different normalized plate width (plate width/hole diameter, W/d, lay-up types and bolt loads were incorporated in current study as specified in testing series. Generally, hybrid joint coupons separated within adhesive layer prior to net-tension failure or bearing/net-tension failure. The bearing stress at failure increased as W/d ratio increment, critical W/d is given as four and three in clamped and finger tight condition respectively. Lay-up types present insignificant effect to bearing stress at failure due to low volume fiber fraction in kenaf fiber composites. Combination of thicker and clamped conditions plate demonstrated greater bearing stress than equivalent finger-tight (FT conditions due to higher load transferred from friction, as expected.

Effects of Salinity Stress on Morphological and Physiological Characteristics of some Local Landrace and Inter specific Hybrids of Cucurbits Seedlings as Rootstocks

Directory of Open Access Journals (Sweden)

Ali Farhadi

2017-12-01

Full Text Available Introduction: Salinity stress is regarded as one of the most important abiotic factors in plant limiting growth, particularly in arid and semi-arid regions. The reduction of plant growth by salinity stress has been well documented. When water supply is limited, plant structure is modified by increasing the root: shoot ratio. To reduce of losses in vegetative growth and production of plant and to improve water use efficiency under saline conditions in high-yielding genotypes grafting them onto rootstocks could bereduced the effect of saline stress on plant shoot. Grafting is a routine technique in continuous cropping systems. Most of the species of cucurbits are distributed in the dry regions. The objective of this studywas investigated the effectiveness of salinity stress on accessions of cucurbita and hybrid inter specific which enter from another country to Iran. Materials and Methods: This research was conducted in laboratory and greenhouse at the Research Center of Agricultural and Natural Resources of Isfahan during 2013-2014 growing season. A factorial experiment based on completely randomized design with three replications was conducted for rootstock and irrigation water salinity.. In the first experiment 25 seeds of rootstocks were sown in petri dishes with 10 cm diameter and irrigated by 10 ml of saline water. Rootstocks included 20 different local landraces and interspecific hybrids (C.moschata cv. Isfahan and Koshk, C.pepo cv. Alvar, Tiran, Koshk and Asgharabad, C. maxima cv. Kermanshah, Shahreza, Mohamadiyeh and Alvar, Lagenaria Siceraria, Luffa cylindrica, Trichosanthes cucumerina, RZ-Ferro, Es113, Ews910, Ews909, Ews913, 426 and Es152. Salinity stress was 6 levels (0, 2, 4, 6, 8 and 10 ds/m of NaCl. Germination, diameter of stem, height of root and stem, shoot and root fresh mass, vigor index and root: shoot ratio were evaluated. In the second experiment seeds were sown in plastic pot by soil media. Seedlings were irrigated daily

Identification of single nucleotide polymorphisms (SNPs at candidate genes involved in abiotic stress in two Prosopis species of hybrids

Directory of Open Access Journals (Sweden)

Maria F. Pomponio

2014-12-01

Full Text Available Aim of the study: Identify and compare SNPs on candidate genes related to abiotic stress in Prosopis chilensis, Prosopis flexuosa and interspecific hybridsArea of the study: Chaco árido, Argentina. Material and Methods: Fragments from 6 candidate genes were sequenced in 60 genotypes. DNA polymorphisms were analyzed.Main Results: The analysis revealed that the hybrids had the highest rate of polymorphism, followed by P. flexuosa and P. chilensis, the values found are comparable to other forest tree species.Research highlights: This approach will help to study genetic diversity variation on natural populations for assessing the effects of environmental changes.Keywords: SNPs; abiotic stress; interspecific variation; molecular markers. 

Superconductivity in the periodic Anderson model with anisotropic hybridization

International Nuclear Information System (INIS)

Sarasua, L.G.; Continentino, Mucio A.

2003-01-01

In this work we study superconductivity in the periodic Anderson model with both on-site and intersite hybridization, including the interband Coulomb repulsion. We show that the presence of the intersite hybridization together with the on-site hybridization significantly affects the superconducting properties of the system. The symmetry of the hybridization has a strong influence in the symmetry of the superconducting order parameter of the ground state. The interband Coulomb repulsion may increase or decrease the superconducting critical temperature at small values of this interaction, while is detrimental to superconductivity for strong values. We show that the present model can give rise to positive or negative values of dT c /dP, depending on the values of the system parameters

Daily air quality index forecasting with hybrid models: A case in China

International Nuclear Information System (INIS)

Zhu, Suling; Lian, Xiuyuan; Liu, Haixia; Hu, Jianming; Wang, Yuanyuan; Che, Jinxing

2017-01-01

Air quality is closely related to quality of life. Air pollution forecasting plays a vital role in air pollution warnings and controlling. However, it is difficult to attain accurate forecasts for air pollution indexes because the original data are non-stationary and chaotic. The existing forecasting methods, such as multiple linear models, autoregressive integrated moving average (ARIMA) and support vector regression (SVR), cannot fully capture the information from series of pollution indexes. Therefore, new effective techniques need to be proposed to forecast air pollution indexes. The main purpose of this research is to develop effective forecasting models for regional air quality indexes (AQI) to address the problems above and enhance forecasting accuracy. Therefore, two hybrid models (EMD-SVR-Hybrid and EMD-IMFs-Hybrid) are proposed to forecast AQI data. The main steps of the EMD-SVR-Hybrid model are as follows: the data preprocessing technique EMD (empirical mode decomposition) is utilized to sift the original AQI data to obtain one group of smoother IMFs (intrinsic mode functions) and a noise series, where the IMFs contain the important information (level, fluctuations and others) from the original AQI series. LS-SVR is applied to forecast the sum of the IMFs, and then, S-ARIMA (seasonal ARIMA) is employed to forecast the residual sequence of LS-SVR. In addition, EMD-IMFs-Hybrid first separately forecasts the IMFs via statistical models and sums the forecasting results of the IMFs as EMD-IMFs. Then, S-ARIMA is employed to forecast the residuals of EMD-IMFs. To certify the proposed hybrid model, AQI data from June 2014 to August 2015 collected from Xingtai in China are utilized as a test case to investigate the empirical research. In terms of some of the forecasting assessment measures, the AQI forecasting results of Xingtai show that the two proposed hybrid models are superior to ARIMA, SVR, GRNN, EMD-GRNN, Wavelet-GRNN and Wavelet-SVR. Therefore, the

Hybrid model for simulation of plasma jet injection in tokamak

Science.gov (United States)

Galkin, Sergei A.; Bogatu, I. N.

2016-10-01

Hybrid kinetic model of plasma treats the ions as kinetic particles and the electrons as charge neutralizing massless fluid. The model is essentially applicable when most of the energy is concentrated in the ions rather than in the electrons, i.e. it is well suited for the high-density hyper-velocity C60 plasma jet. The hybrid model separates the slower ion time scale from the faster electron time scale, which becomes disregardable. That is why hybrid codes consistently outperform the traditional PIC codes in computational efficiency, still resolving kinetic ions effects. We discuss 2D hybrid model and code with exact energy conservation numerical algorithm and present some results of its application to simulation of C60 plasma jet penetration through tokamak-like magnetic barrier. We also examine the 3D model/code extension and its possible applications to tokamak and ionospheric plasmas. The work is supported in part by US DOE DE-SC0015776 Grant.

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.

Reactor systems modeling for ICF hybrids

International Nuclear Information System (INIS)

Berwald, D.H.; Meier, W.R.

1980-10-01

The computational models of ICF reactor subsystems developed by LLNL and TRW are described and a computer program was incorporated for use in the EPRI-sponsored Feasibility Assessment of Fusion-Fission Hybrids. Representative parametric variations have been examined. Many of the ICF subsystem models are very preliminary and more quantitative models need to be developed and included in the code

Internal stress distribution of X-ring using photoelastic experimental hybrid method

Energy Technology Data Exchange (ETDEWEB)

Bernard, Alunda Ouma [Dedan Kimathi University of Technology, Nyeri (Kenya); Hawong, Jai Sug; Lim, Hyun Seok [Yeungnam University, Gyeongsan (Korea, Republic of); Shin, Dong Chul [Koje College, Geoje (Korea, Republic of)

2014-05-15

Sealing elements are essential parts of many machines, and are used to prevent the loss of a fluid or gas. When such fluids are not properly sealed, catastrophic failures may result. Many different types of rings have been developed to suit various industrial needs. Considerable research has been done on the O-ring. We analyze the internal stresses developed in an X-ring under a uniform squeeze rate of 20%, which is suitable for static applications, using a photoelastic experimental hybrid method. The internal pressures applied were 0.98, 1.96, 2.94, 3.92, 4.90, and 5.88 MPa. We show that sealing rings with X geometry have considerably higher internal stresses than O-ring seals. In addition, we demonstrate that after extrusion, for an internal pressure of 5.88 MPa, the two lobes on the upper contact surface merge, thereby increasing the contact length of the upper side significantly. Extrusion in the X-ring occurred when the internal pressure was 4.90 MPa.

Stochastic linear hybrid systems: Modeling, estimation, and application

Science.gov (United States)

Seah, Chze Eng

Hybrid systems are dynamical systems which have interacting continuous state and discrete state (or mode). Accurate modeling and state estimation of hybrid systems are important in many applications. We propose a hybrid system model, known as the Stochastic Linear Hybrid System (SLHS), to describe hybrid systems with stochastic linear system dynamics in each mode and stochastic continuous-state-dependent mode transitions. We then develop a hybrid estimation algorithm, called the State-Dependent-Transition Hybrid Estimation (SDTHE) algorithm, to estimate the continuous state and discrete state of the SLHS from noisy measurements. It is shown that the SDTHE algorithm is more accurate or more computationally efficient than existing hybrid estimation algorithms. Next, we develop a performance analysis algorithm to evaluate the performance of the SDTHE algorithm in a given operating scenario. We also investigate sufficient conditions for the stability of the SDTHE algorithm. The proposed SLHS model and SDTHE algorithm are illustrated to be useful in several applications. In Air Traffic Control (ATC), to facilitate implementations of new efficient operational concepts, accurate modeling and estimation of aircraft trajectories are needed. In ATC, an aircraft's trajectory can be divided into a number of flight modes. Furthermore, as the aircraft is required to follow a given flight plan or clearance, its flight mode transitions are dependent of its continuous state. However, the flight mode transitions are also stochastic due to navigation uncertainties or unknown pilot intents. Thus, we develop an aircraft dynamics model in ATC based on the SLHS. The SDTHE algorithm is then used in aircraft tracking applications to estimate the positions/velocities of aircraft and their flight modes accurately. Next, we develop an aircraft conformance monitoring algorithm to detect any deviations of aircraft trajectories in ATC that might compromise safety. In this application, the SLHS

Fluid Petri Nets and hybrid model-checking: a comparative case study

International Nuclear Information System (INIS)

Gribaudo, M.; Horvath, A.; Bobbio, A.; Tronci, E.; Ciancamerla, E.; Minichino, M.

2003-01-01

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

Model Predictive Control for Connected Hybrid Electric Vehicles

Directory of Open Access Journals (Sweden)

Kaijiang Yu

2015-01-01

Full Text Available This paper presents a new model predictive control system for connected hybrid electric vehicles to improve fuel economy. The new features of this study are as follows. First, the battery charge and discharge profile and the driving velocity profile are simultaneously optimized. One is energy management for HEV for Pbatt; the other is for the energy consumption minimizing problem of acc control of two vehicles. Second, a system for connected hybrid electric vehicles has been developed considering varying drag coefficients and the road gradients. Third, the fuel model of a typical hybrid electric vehicle is developed using the maps of the engine efficiency characteristics. Fourth, simulations and analysis (under different parameters, i.e., road conditions, vehicle state of charge, etc. are conducted to verify the effectiveness of the method to achieve higher fuel efficiency. The model predictive control problem is solved using numerical computation method: continuation and generalized minimum residual method. Computer simulation results reveal improvements in fuel economy using the proposed control method.

Kalman Filtered Bio Heat Transfer Model Based Self-adaptive Hybrid Magnetic Resonance Thermometry.

Science.gov (United States)

Zhang, Yuxin; Chen, Shuo; Deng, Kexin; Chen, Bingyao; Wei, Xing; Yang, Jiafei; Wang, Shi; Ying, Kui

2017-01-01

To develop a self-adaptive and fast thermometry method by combining the original hybrid magnetic resonance thermometry method and the bio heat transfer equation (BHTE) model. The proposed Kalman filtered Bio Heat Transfer Model Based Self-adaptive Hybrid Magnetic Resonance Thermometry, abbreviated as KalBHT hybrid method, introduced the BHTE model to synthesize a window on the regularization term of the hybrid algorithm, which leads to a self-adaptive regularization both spatially and temporally with change of temperature. Further, to decrease the sensitivity to accuracy of the BHTE model, Kalman filter is utilized to update the window at each iteration time. To investigate the effect of the proposed model, computer heating simulation, phantom microwave heating experiment and dynamic in-vivo model validation of liver and thoracic tumor were conducted in this study. The heating simulation indicates that the KalBHT hybrid algorithm achieves more accurate results without adjusting λ to a proper value in comparison to the hybrid algorithm. The results of the phantom heating experiment illustrate that the proposed model is able to follow temperature changes in the presence of motion and the temperature estimated also shows less noise in the background and surrounding the hot spot. The dynamic in-vivo model validation with heating simulation demonstrates that the proposed model has a higher convergence rate, more robustness to susceptibility problem surrounding the hot spot and more accuracy of temperature estimation. In the healthy liver experiment with heating simulation, the RMSE of the hot spot of the proposed model is reduced to about 50% compared to the RMSE of the original hybrid model and the convergence time becomes only about one fifth of the hybrid model. The proposed model is able to improve the accuracy of the original hybrid algorithm and accelerate the convergence rate of MR temperature estimation.

Underground water stress release models

Science.gov (United States)

Li, Yong; Dang, Shenjun; Lü, Shaochuan

2011-08-01

The accumulation of tectonic stress may cause earthquakes at some epochs. However, in most cases, it leads to crustal deformations. Underground water level is a sensitive indication of the crustal deformations. We incorporate the information of the underground water level into the stress release models (SRM), and obtain the underground water stress release model (USRM). We apply USRM to the earthquakes occurred at Tangshan region. The analysis shows that the underground water stress release model outperforms both Poisson model and stress release model. Monte Carlo simulation shows that the simulated seismicity by USRM is very close to the real seismicity.

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)...

A Hybrid Wind-Farm Parametrization for Mesoscale and Climate Models

Science.gov (United States)

Pan, Yang; Archer, Cristina L.

2018-04-01

To better understand the potential impact of wind farms on weather and climate at the regional to global scales, a new hybrid wind-farm parametrization is proposed for mesoscale and climate models. The proposed parametrization is a hybrid model because it is not based on physical processes or conservation laws, but on the multiple linear regression of the results of large-eddy simulations (LES) with the geometric properties of the wind-farm layout (e.g., the blockage ratio and blockage distance). The innovative aspect is that each wind turbine is treated individually based on its position in the farm and on the wind direction by predicting the velocity upstream of each turbine. The turbine-induced forces and added turbulence kinetic energy (TKE) are first derived analytically and then implemented in the Weather Research and Forecasting model. Idealized simulations of the offshore Lillgrund wind farm are conducted. The wind-speed deficit and TKE predicted with the hybrid model are in excellent agreement with those from the LES results, while the wind-power production estimated with the hybrid model is within 10% of that observed. Three additional wind farms with larger inter-turbine spacing than at Lillgrund are also considered, and a similar agreement with LES results is found, proving that the hybrid parametrization works well with any wind farm regardless of the spacing between turbines. These results indicate the wind-turbine position, wind direction, and added TKE are essential in accounting for the wind-farm effects on the surroundings, for which the hybrid wind-farm parametrization is a promising tool.

Rapidity distributions of hadrons in the HydHSD hybrid model

Energy Technology Data Exchange (ETDEWEB)

Khvorostukhin, A. S., E-mail: hvorost@theor.jinr.ru; Toneev, V. D. [Joint Institute for Nuclear Research (Russian Federation)

2017-03-15

A multistage hybrid model intended for describing heavy-ion interactions in the energy region of the NICA collider under construction in Dubna is proposed. The model combines the initial, fast, interaction stage described by the model of hadron string dynamics (HSD) and the subsequent evolution that the expanding system formed at the first stage experiences at the second stage and which one treats on the basis of ideal hydrodynamics; after the completion of the second stage, the particles involved may still undergo rescattering (third interaction stage). The model admits three freeze-out scenarios: isochronous, isothermal, and isoenergetic. Generally, the HydHSD hybrid model developed in the present study provides fairly good agreement with available experimental data on proton rapidity spectra. It is shown that, within this hybrid model, the two-humped structure of proton rapidity distributions can be obtained either by increasing the freeze-out temperature and energy density or by more lately going over to the hydrodynamic stage. Although the proposed hybrid model reproduces rapidity spectra of protons, it is unable to describe rapidity distributions of pions, systematically underestimating their yield. It is necessary to refine the model by including viscosity effects at the hydrodynamic stage of evolution of the system and by considering in more detail the third interaction stage.

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.

A four-stage hybrid model for hydrological time series forecasting.

Science.gov (United States)

Di, Chongli; Yang, Xiaohua; Wang, Xiaochao

2014-01-01

Hydrological time series forecasting remains a difficult task due to its complicated nonlinear, non-stationary and multi-scale characteristics. To solve this difficulty and improve the prediction accuracy, a novel four-stage hybrid model is proposed for hydrological time series forecasting based on the principle of 'denoising, decomposition and ensemble'. The proposed model has four stages, i.e., denoising, decomposition, components prediction and ensemble. In the denoising stage, the empirical mode decomposition (EMD) method is utilized to reduce the noises in the hydrological time series. Then, an improved method of EMD, the ensemble empirical mode decomposition (EEMD), is applied to decompose the denoised series into a number of intrinsic mode function (IMF) components and one residual component. Next, the radial basis function neural network (RBFNN) is adopted to predict the trend of all of the components obtained in the decomposition stage. In the final ensemble prediction stage, the forecasting results of all of the IMF and residual components obtained in the third stage are combined to generate the final prediction results, using a linear neural network (LNN) model. For illustration and verification, six hydrological cases with different characteristics are used to test the effectiveness of the proposed model. The proposed hybrid model performs better than conventional single models, the hybrid models without denoising or decomposition and the hybrid models based on other methods, such as the wavelet analysis (WA)-based hybrid models. In addition, the denoising and decomposition strategies decrease the complexity of the series and reduce the difficulties of the forecasting. With its effective denoising and accurate decomposition ability, high prediction precision and wide applicability, the new model is very promising for complex time series forecasting. This new forecast model is an extension of nonlinear prediction models.

A Four-Stage Hybrid Model for Hydrological Time Series Forecasting

Science.gov (United States)

Di, Chongli; Yang, Xiaohua; Wang, Xiaochao

2014-01-01

Hydrological time series forecasting remains a difficult task due to its complicated nonlinear, non-stationary and multi-scale characteristics. To solve this difficulty and improve the prediction accuracy, a novel four-stage hybrid model is proposed for hydrological time series forecasting based on the principle of ‘denoising, decomposition and ensemble’. The proposed model has four stages, i.e., denoising, decomposition, components prediction and ensemble. In the denoising stage, the empirical mode decomposition (EMD) method is utilized to reduce the noises in the hydrological time series. Then, an improved method of EMD, the ensemble empirical mode decomposition (EEMD), is applied to decompose the denoised series into a number of intrinsic mode function (IMF) components and one residual component. Next, the radial basis function neural network (RBFNN) is adopted to predict the trend of all of the components obtained in the decomposition stage. In the final ensemble prediction stage, the forecasting results of all of the IMF and residual components obtained in the third stage are combined to generate the final prediction results, using a linear neural network (LNN) model. For illustration and verification, six hydrological cases with different characteristics are used to test the effectiveness of the proposed model. The proposed hybrid model performs better than conventional single models, the hybrid models without denoising or decomposition and the hybrid models based on other methods, such as the wavelet analysis (WA)-based hybrid models. In addition, the denoising and decomposition strategies decrease the complexity of the series and reduce the difficulties of the forecasting. With its effective denoising and accurate decomposition ability, high prediction precision and wide applicability, the new model is very promising for complex time series forecasting. This new forecast model is an extension of nonlinear prediction models. PMID:25111782

Hybrid modelling framework by using mathematics-based and information-based methods

International Nuclear Information System (INIS)

Ghaboussi, J; Kim, J; Elnashai, A

2010-01-01

Mathematics-based computational mechanics involves idealization in going from the observed behaviour of a system into mathematical equations representing the underlying mechanics of that behaviour. Idealization may lead mathematical models that exclude certain aspects of the complex behaviour that may be significant. An alternative approach is data-centric modelling that constitutes a fundamental shift from mathematical equations to data that contain the required information about the underlying mechanics. However, purely data-centric methods often fail for infrequent events and large state changes. In this article, a new hybrid modelling framework is proposed to improve accuracy in simulation of real-world systems. In the hybrid framework, a mathematical model is complemented by information-based components. The role of informational components is to model aspects which the mathematical model leaves out. The missing aspects are extracted and identified through Autoprogressive Algorithms. The proposed hybrid modelling framework has a wide range of potential applications for natural and engineered systems. The potential of the hybrid methodology is illustrated through modelling highly pinched hysteretic behaviour of beam-to-column connections in steel frames.

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...... significance of the node towards overall content provided by the document. Once significance of the nodes is determined, the formatting characteristics like fonts, styles and the position of the nodes are evaluated to identify the nodes with similar formatting as compared to the significant nodes. The proposed...

Model predictive control of hybrid systems : stability and robustness

NARCIS (Netherlands)

Lazar, M.

2006-01-01

This thesis considers the stabilization and the robust stabilization of certain classes of hybrid systems using model predictive control. Hybrid systems represent a broad class of dynamical systems in which discrete behavior (usually described by a finite state machine) and continuous behavior

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.

Identification of single nucleotide polymorphisms (SNPs) at candidate genes involved in abiotic stress in two Prosopis species of hybrids

OpenAIRE

Maria F. Pomponio; Susana Marcucci Poltri; Diego Lopez Lauenstein; Susana Torales

2014-01-01

Aim of the study: Identify and compare SNPs on candidate genes related to abiotic stress in Prosopis chilensis, Prosopis flexuosa and interspecific hybridsArea of the study: Chaco árido, Argentina. Material and Methods: Fragments from 6 candidate genes were sequenced in 60 genotypes. DNA polymorphisms were analyzed.Main Results: The analysis revealed that the hybrids had the highest rate of polymorphism, followed by P. flexuosa and P. chilensis, the values found are comparable to other forest...

Hybrid model for forecasting time series with trend, seasonal and salendar variation patterns

Science.gov (United States)

Suhartono; Rahayu, S. P.; Prastyo, D. D.; Wijayanti, D. G. P.; Juliyanto

2017-09-01

Most of the monthly time series data in economics and business in Indonesia and other Moslem countries not only contain trend and seasonal, but also affected by two types of calendar variation effects, i.e. the effect of the number of working days or trading and holiday effects. The purpose of this research is to develop a hybrid model or a combination of several forecasting models to predict time series that contain trend, seasonal and calendar variation patterns. This hybrid model is a combination of classical models (namely time series regression and ARIMA model) and/or modern methods (artificial intelligence method, i.e. Artificial Neural Networks). A simulation study was used to show that the proposed procedure for building the hybrid model could work well for forecasting time series with trend, seasonal and calendar variation patterns. Furthermore, the proposed hybrid model is applied for forecasting real data, i.e. monthly data about inflow and outflow of currency at Bank Indonesia. The results show that the hybrid model tend to provide more accurate forecasts than individual forecasting models. Moreover, this result is also in line with the third results of the M3 competition, i.e. the hybrid model on average provides a more accurate forecast than the individual model.

Craniomandibular form and body size variation of first generation mouse hybrids: A model for hominin hybridization.

Science.gov (United States)

Warren, Kerryn A; Ritzman, Terrence B; Humphreys, Robyn A; Percival, Christopher J; Hallgrímsson, Benedikt; Ackermann, Rebecca Rogers

2018-03-01

Hybridization occurs in a number of mammalian lineages, including among primate taxa. Analyses of ancient genomes have shown that hybridization between our lineage and other archaic hominins in Eurasia occurred numerous times in the past. However, we still have limited empirical data on what a hybrid skeleton looks like, or how to spot patterns of hybridization among fossils for which there are no genetic data. Here we use experimental mouse models to supplement previous studies of primates. We characterize size and shape variation in the cranium and mandible of three wild-derived inbred mouse strains and their first generation (F 1 ) hybrids. The three parent taxa in our analysis represent lineages that diverged over approximately the same period as the human/Neanderthal/Denisovan lineages and their hybrids are variably successful in the wild. Comparisons of body size, as quantified by long bone measurements, are also presented to determine whether the identified phenotypic effects of hybridization are localized to the cranium or represent overall body size changes. The results indicate that hybrid cranial and mandibular sizes, as well as limb length, exceed that of the parent taxa in all cases. All three F 1 hybrid crosses display similar patterns of size and form variation. These results are generally consistent with earlier studies on primates and other mammals, suggesting that the effects of hybridization may be similar across very different scenarios of hybridization, including different levels of hybrid fitness. This paper serves to supplement previous studies aimed at identifying F 1 hybrids in the fossil record and to introduce further research that will explore hybrid morphologies using mice as a proxy for better understanding hybridization in the hominin fossil record. Copyright © 2017 Elsevier Ltd. All rights reserved.

A model for particle acceleration in lower hybrid collapse

International Nuclear Information System (INIS)

Retterer, J.M.

1997-01-01

A model for particle acceleration during the nonlinear collapse of lower hybrid waves is described. Using the Musher-Sturman wave equation to describe the effects of nonlinear processes and a velocity diffusion equation for the particle velocity distribution, the model self-consistently describes the exchange of energy between the fields and the particles in the local plasma. Two-dimensional solutions are presented for the modulational instability of a plane wave and the collapse of a cylindrical wave packet. These calculations were motivated by sounding rocket observations in the vicinity of auroral arcs in the Earth close-quote s ionosphere, which have revealed the existence of large-amplitude lower-hybrid wave packets associated with ions accelerated to energies of 100 eV. The scaling of the sizes of these wave packets is consistent with the theory of lower-hybrid collapse and the observed lower-hybrid field amplitudes are adequate to accelerate the ionospheric ions to the observed energies

Two Back Stress Hardening Models in Rate Independent Rigid Plastic Deformation

Science.gov (United States)

Yun, Su-Jin

In the present work, the constitutive relations based on the combination of two back stresses are developed using the Armstrong-Frederick, Phillips and Ziegler’s type hardening rules. Various evolutions of the kinematic hardening parameter can be obtained by means of a simple combination of back stress rate using the rule of mixtures. Thus, a wide range of plastic deformation behavior can be depicted depending on the dominant back stress evolution. The ultimate back stress is also determined for the present combined kinematic hardening models. Since a kinematic hardening rule is assumed in the finite deformation regime, the stress rate is co-rotated with respect to the spin of substructure obtained by incorporating the plastic spin concept. A comparison of the various co-rotational rates is also included. Assuming rigid plasticity, the continuum body consists of the elastic deformation zone and the plastic deformation zone to form a hybrid finite element formulation. Then, the plastic deformation behavior is investigated under various loading conditions with an assumption of the J2 deformation theory. The plastic deformation localization turns out to be strongly dependent on the description of back stress evolution and its associated hardening parameters. The analysis for the shear deformation with fixed boundaries is carried out to examine the deformation localization behavior and the evolution of state variables.

Residual Stress Measurement of SiC tile/Al7075 Hybrid Composites by Neutron Diffraction

Energy Technology Data Exchange (ETDEWEB)

Park, Jong Bok; Lee, Jun Ho; Hong, Soon Hyung; Ryu, Ho Jin [KAIST, Daejeon (Korea, Republic of); Lee, Sang Bok; Lee, Sang Kwan [Korea Institute of Materials Science, Changwon (Korea, Republic of); Muslihd, M. Rifai [Center for Advanced Materials Science and Technology, Tangerang (India)

2016-05-15

In this research, SiC which has low density, high compressive strength, and high elastic modulus was used to fabricate the armor plate. In addition, Al which has low density and high toughness was used for a metal matrix of the composites. If two materials are combined, the composite can be effective materials for light weight armor applications. However, the existence of a large difference in coefficients of thermal expansion (CTE) between SiC and Al matrix, SiC/Al composites can have residual stresses while cooled in the fabrication process. Previous research reported that residual stresses in the composites or microstructures have an effect on the fatigue life and their mechanical properties. Some researchers reported about the residual stresses in the SiCp/Al metal matrix composites by numerical simulation systems, X-ray diffraction, and destructive methods. In order to analyze the residual stress of SiC/Al composites, the neutron diffraction as the non-destructive method was performed in this research. The 50 vol.% SiC{sub p}/Al7075 composites and SiC tile inserted 50 vol.% SiC{sub p}/Al7075 hybrid composites were measured to analyze the residual stress of Al (111) and SiC (111). Both samples had the tensile residual stresses in the Al (111) and the compressive residual stresses in the SiC (111) due to the difference in CTE.

Hybrid Modeling and Optimization of Yogurt Starter Culture Continuous Fermentation

Directory of Open Access Journals (Sweden)

Silviya Popova

2009-10-01

Full Text Available The present paper presents a hybrid model of yogurt starter mixed culture fermentation. The main nonlinearities within a classical structure of continuous process model are replaced by neural networks. The new hybrid model accounts for the dependence of the two microorganisms' kinetics from the on-line measured characteristics of the culture medium - pH. Then the model was used further for calculation of the optimal time profile of pH. The obtained results are with agreement with the experimental once.

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...

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 veri...

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.

Modeling and optimization of batteryless hybrid PV (photovoltaic)/Diesel systems for off-grid applications

International Nuclear Information System (INIS)

Tsuanyo, David; Azoumah, Yao; Aussel, Didier; Neveu, Pierre

2015-01-01

This paper presents a new model and optimization procedure for off-grid hybrid PV (photovoltaic)/Diesel systems operating without battery storage. The proposed technico-economic model takes into account the variability of both the solar irradiation and the electrical loads. It allows optimizing the design and the operation of the hybrid systems by searching their lowest LCOE (Levelized Cost of Electricity). Two cases have been investigated: identical Diesel generators and Diesel generators with different sizes, and both are compared to conventional standalone Diesel generator systems. For the same load profile, the optimization results show that the LCOE of the optimized batteryless hybrid solar PV/Diesel (0.289 €/kWh for the hybrid system with identical Diesel generators and 0.284 €/kWh for the hybrid system with different sizes of Diesel generators) is lower than the LCOE obtained with standalone Diesel generators (0.32 €/kWh for the both cases). The obtained results are then confirmed by HOMER (Hybrid Optimization Model for Electric Renewables) software. - Highlights: • A technico-economic model for optimal design and operation management of batteryless hybrid systems is developed. • The model allows optimizing design and operation of hybrid systems by ensuring their lowest LCOE. • The model was validated by HOMER. • Batteryless hybrid system are suitable for off-grid applications

Comparison of a hybrid model to a global model of atmospheric pressure radio-frequency capacitive discharges

International Nuclear Information System (INIS)

Lazzaroni, C; Lieberman, M A; Lichtenberg, A J; Chabert, P

2012-01-01

A one-dimensional hybrid analytical-numerical global model of atmospheric pressure radio-frequency (rf) driven capacitive discharges, previously developed, is compared with a basic global model. A helium feed gas with small admixtures of oxygen is studied. For the hybrid model, the electrical characteristics are calculated analytically as a current-driven homogeneous discharge. The electron power balance is solved analytically to determine a time-varying Maxwellian electron temperature, which oscillates on the rf timescale. Averaging over the rf period yields effective rate coefficients for gas phase activated processes. For the basic global model, the electron temperature is constant in time and the sheath physics is neglected. For both models, the particle balance relations for all species are integrated numerically to determine the equilibrium discharge parameters. Variations of discharge parameters with composition and rf power are determined and compared. The rate coefficients for electron-activated processes are strongly temperature dependent, leading to significantly larger neutral and charged particle densities for the hybrid model. For small devices, finite sheath widths limit the operating regimes to low O 2 fractions. This is captured by the hybrid model but cannot be predicted from the basic global model.

Ultra-Short-Term Wind Power Prediction Using a Hybrid Model

Science.gov (United States)

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

2017-05-01

This paper aims to develop and apply a hybrid model of two data analytical methods, multiple linear regressions and least square (MLR&LS), for ultra-short-term wind power prediction (WPP), for example taking, Northeast China electricity demand. The data was obtained from the historical records of wind power from an offshore region, and from a wind farm of the wind power plant in the areas. The WPP achieved in two stages: first, the ratios of wind power were forecasted using the proposed hybrid method, and then the transformation of these ratios of wind power to obtain forecasted values. The hybrid model combines the persistence methods, MLR and LS. The proposed method included two prediction types, multi-point prediction and single-point prediction. WPP is tested by applying different models such as autoregressive moving average (ARMA), autoregressive integrated moving average (ARIMA) and artificial neural network (ANN). By comparing results of the above models, the validity of the proposed hybrid model is confirmed in terms of error and correlation coefficient. Comparison of results confirmed that the proposed method works effectively. Additional, forecasting errors were also computed and compared, to improve understanding of how to depict highly variable WPP and the correlations between actual and predicted wind power.

A hybrid agent-based approach for modeling microbiological systems.

Science.gov (United States)

Guo, Zaiyi; Sloot, Peter M A; Tay, Joc Cing

2008-11-21

Models for systems biology commonly adopt Differential Equations or Agent-Based modeling approaches for simulating the processes as a whole. Models based on differential equations presuppose phenomenological intracellular behavioral mechanisms, while models based on Multi-Agent approach often use directly translated, and quantitatively less precise if-then logical rule constructs. We propose an extendible systems model based on a hybrid agent-based approach where biological cells are modeled as individuals (agents) while molecules are represented by quantities. This hybridization in entity representation entails a combined modeling strategy with agent-based behavioral rules and differential equations, thereby balancing the requirements of extendible model granularity with computational tractability. We demonstrate the efficacy of this approach with models of chemotaxis involving an assay of 10(3) cells and 1.2x10(6) molecules. The model produces cell migration patterns that are comparable to laboratory observations.

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.

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

OpenAIRE

Rambabu Kandepu; Lars Imsland; Christoph Stiller; Bjarne A. Foss; Vinay Kariwala

2006-01-01

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.

Modelling and Verifying Communication Failure of Hybrid Systems in HCSP

DEFF Research Database (Denmark)

Wang, Shuling; Nielson, Flemming; Nielson, Hanne Riis

2016-01-01

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......, in the presence of communication failure, the expected control from the controller will get lost and as a consequence the physical process cannot behave as expected. In this paper, we mainly consider the communication failure caused by the non-engagement of one party in communication action, i.......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...

A hybrid modeling with data assimilation to evaluate human exposure level

Science.gov (United States)

Koo, Y. S.; Cheong, H. K.; Choi, D.; Kim, A. L.; Yun, H. Y.

2015-12-01

Exposure models are designed to better represent human contact with PM (Particulate Matter) and other air pollutants such as CO, SO2, O3, and NO2. The exposure concentrations of the air pollutants to human are determined by global and regional long range transport of global and regional scales from Europe and China as well as local emissions from urban and road vehicle sources. To assess the exposure level in detail, the multiple scale influence from background to local sources should be considered. A hybrid air quality modeling methodology combing a grid-based chemical transport model with a local plume dispersion model was used to provide spatially and temporally resolved air quality concentration for human exposure levels in Korea. In the hybrid modeling approach, concentrations from a grid-based chemical transport model and a local plume dispersion model are added to provide contributions from photochemical interactions, long-range (regional) transport and local-scale dispersion. The CAMx (Comprehensive Air quality Model with Extensions was used for the background concentrations from anthropogenic and natural emissions in East Asia including Korea while the road dispersion by vehicle emission was calculated by CALPUFF model. The total exposure level of the pollutants was finally assessed by summing the background and road contributions. In the hybrid modeling, the data assimilation method based on the optimal interpolation was applied to overcome the discrepancies between the model predicted concentrations and observations. The air quality data from the air quality monitoring stations in Korea. The spatial resolution of the hybrid model was 50m for the Seoul Metropolitan Ares. This example clearly demonstrates that the exposure level could be estimated to the fine scale for the exposure assessment by using the hybrid modeling approach with data assimilation.

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

A hybrid parallel framework for the cellular Potts model simulations

Energy Technology Data Exchange (ETDEWEB)

Jiang, Yi [Los Alamos National Laboratory; He, Kejing [SOUTH CHINA UNIV; Dong, Shoubin [SOUTH CHINA UNIV

2009-01-01

The Cellular Potts Model (CPM) has been widely used for biological simulations. However, most current implementations are either sequential or approximated, which can't be used for large scale complex 3D simulation. In this paper we present a hybrid parallel framework for CPM simulations. The time-consuming POE solving, cell division, and cell reaction operation are distributed to clusters using the Message Passing Interface (MPI). The Monte Carlo lattice update is parallelized on shared-memory SMP system using OpenMP. Because the Monte Carlo lattice update is much faster than the POE solving and SMP systems are more and more common, this hybrid approach achieves good performance and high accuracy at the same time. Based on the parallel Cellular Potts Model, we studied the avascular tumor growth using a multiscale model. The application and performance analysis show that the hybrid parallel framework is quite efficient. The hybrid parallel CPM can be used for the large scale simulation ({approx}10{sup 8} sites) of complex collective behavior of numerous cells ({approx}10{sup 6}).

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.

A new adaptive hybrid electromagnetic damper: modelling, optimization, and experiment

International Nuclear Information System (INIS)

Asadi, Ehsan; Ribeiro, Roberto; Behrad Khamesee, Mir; Khajepour, Amir

2015-01-01

This paper presents the development of a new electromagnetic hybrid damper which provides regenerative adaptive damping force for various applications. Recently, the introduction of electromagnetic technologies to the damping systems has provided researchers with new opportunities for the realization of adaptive semi-active damping systems with the added benefit of energy recovery. In this research, a hybrid electromagnetic damper is proposed. The hybrid damper is configured to operate with viscous and electromagnetic subsystems. The viscous medium provides a bias and fail-safe damping force while the electromagnetic component adds adaptability and the capacity for regeneration to the hybrid design. The electromagnetic component is modeled and analyzed using analytical (lumped equivalent magnetic circuit) and electromagnetic finite element method (FEM) (COMSOL ® software package) approaches. By implementing both modeling approaches, an optimization for the geometric aspects of the electromagnetic subsystem is obtained. Based on the proposed electromagnetic hybrid damping concept and the preliminary optimization solution, a prototype is designed and fabricated. A good agreement is observed between the experimental and FEM results for the magnetic field distribution and electromagnetic damping forces. These results validate the accuracy of the modeling approach and the preliminary optimization solution. An analytical model is also presented for viscous damping force, and is compared with experimental results The results show that the damper is able to produce damping coefficients of 1300 and 0–238 N s m −1 through the viscous and electromagnetic components, respectively. (paper)

Three hybridization models based on local search scheme for job shop scheduling problem

Science.gov (United States)

Balbi Fraga, Tatiana

2015-05-01

This work presents three different hybridization models based on the general schema of Local Search Heuristics, named Hybrid Successive Application, Hybrid Neighborhood, and Hybrid Improved Neighborhood. Despite similar approaches might have already been presented in the literature in other contexts, in this work these models are applied to analyzes the solution of the job shop scheduling problem, with the heuristics Taboo Search and Particle Swarm Optimization. Besides, we investigate some aspects that must be considered in order to achieve better solutions than those obtained by the original heuristics. The results demonstrate that the algorithms derived from these three hybrid models are more robust than the original algorithms and able to get better results than those found by the single Taboo Search.

Dynamic Model of Islamic Hybrid Securities: Empirical Evidence From Malaysia Islamic Capital Market

Directory of Open Access Journals (Sweden)

Jaafar Pyeman

2016-12-01

Full Text Available Capital structure selection is fundamentally important in corporate financial management as it influence on mutually return and risk to stakeholders. Despite of Malaysia’s position as one of the major players of Islamic Financial Market, there are still lack of studies has been conducted on the capital structure of shariah compliant firms especially related to hybrid securities. The objective of this study is to determine the hybrid securities issuance model among the shariah compliant firms in Malaysia. As such, this study is to expand the literature review by providing comprehensive analysis on the hybrid capital structure and to develop dynamic Islamic hybrid securities model for shariah compliant firms. We use panel data of 50 companies that have been issuing the hybrid securities from the year of 2004- 2012. The outcomes of the studies are based on the dynamic model GMM estimation for the determinants of hybrid securities. Based on our model, risk and growth are considered as the most determinant factors for issuing convertible bond and loan stock. These results suggest that, the firms that have high risk but having good growth prospect will choose hybrid securities of convertible bond. The model also support the backdoor equity listing hypothesis by Stein (1992 where the hybrid securities enable the profitable firms to venture into positive NPV project by issuing convertible bond as it offer lower coupon rate as compare to the normal debt rate

Modelling of hybrid energy system - Part I: Problem formulation and model development

Energy Technology Data Exchange (ETDEWEB)

Gupta, Ajai; Saini, R.P.; Sharma, M.P. [Alternate Hydro Energy Centre, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand 247667 (India)

2011-02-15

A well designed hybrid energy system can be cost effective, has a high reliability and can improve the quality of life in remote rural areas. The economic constraints can be met, if these systems are fundamentally well designed, use appropriate technology and make use effective dispatch control techniques. The first paper of this tri-series paper, presents the analysis and design of a mixed integer linear mathematical programming model (time series) to determine the optimal operation and cost optimization for a hybrid energy generation system consisting of a photovoltaic array, biomass (fuelwood), biogas, small/micro-hydro, a battery bank and a fossil fuel generator. The optimization is aimed at minimizing the cost function based on demand and potential constraints. Further, mathematical models of all other components of hybrid energy system are also developed. This is the generation mix of the remote rural of India; it may be applied to other rural areas also. (author)

STRESS INDUCED OBESITY: LESSONS FROM RODENT MODELS OF STRESS

Directory of Open Access Journals (Sweden)

Zachary Robert Patterson

2013-07-01

Full Text Available Stress is defined as the behavioral and physiological responses generated in the face of, or in anticipation of, a perceived threat. The stress response involves activation of the sympathetic nervous system and recruitment of the hypothalamic-pituitary-adrenal (HPA axis. When an organism encounters a stressor (social, physical, etc., these endogenous stress systems are stimulated in order to generate a fight-or-flight response, and manage the stressful situation. As such, an organism is forced to liberate energy resources in attempt to meet the energetic demands posed by the stressor. A change in the energy homeostatic balance is thus required to exploit an appropriate resource and deliver useable energy to the target muscles and tissues involved in the stress response. Acutely, this change in energy homeostasis and the liberation of energy is considered advantageous, as it is required for the survival of the organism. However, when an organism is subjected to a prolonged stressor, as is the case during chronic stress, a continuous irregularity in energy homeostasis is considered detrimental and may lead to the development of metabolic disturbances such as cardiovascular disease, type II diabetes mellitus and obesity. This concept has been studied extensively using animal models, and the neurobiological underpinnings of stress induced metabolic disorders are beginning to surface. However, different animal models of stress continue to produce divergent metabolic phenotypes wherein some animals become anorexic and loose body mass while others increase food intake and body mass and become vulnerable to the development of metabolic disturbances. It remains unclear exactly what factors associated with stress models can be used to predict the metabolic outcome of the organism. This review will explore a variety of rodent stress models and discuss the elements that influence the metabolic outcome in order to further our understanding of stress

Analyses of large quasistatic deformations of inelastic bodies by a new hybrid-stress finite element algorithm

Science.gov (United States)

Reed, K. W.; Atluri, S. N.

1983-01-01

A new hybrid-stress finite element algorithm, suitable for analyses of large, quasistatic, inelastic deformations, is presented. The algorithm is base upon a generalization of de Veubeke's complementary energy principle. The principal variables in the formulation are the nominal stress rate and spin, and thg resulting finite element equations are discrete versions of the equations of compatibility and angular momentum balance. The algorithm produces true rates, time derivatives, as opposed to 'increments'. There results a complete separation of the boundary value problem (for stress rate and velocity) and the initial value problem (for total stress and deformation); hence, their numerical treatments are essentially independent. After a fairly comprehensive discussion of the numerical treatment of the boundary value problem, we launch into a detailed examination of the numerical treatment of the initial value problem, covering the topics of efficiency, stability and objectivity. The paper is closed with a set of examples, finite homogeneous deformation problems, which serve to bring out important aspects of the algorithm.

A new hybrid model optimized by an intelligent optimization algorithm for wind speed forecasting

International Nuclear Information System (INIS)

Su, Zhongyue; Wang, Jianzhou; Lu, Haiyan; Zhao, Ge

2014-01-01

Highlights: • A new hybrid model is developed for wind speed forecasting. • The model is based on the Kalman filter and the ARIMA. • An intelligent optimization method is employed in the hybrid model. • The new hybrid model has good performance in western China. - Abstract: Forecasting the wind speed is indispensable in wind-related engineering studies and is important in the management of wind farms. As a technique essential for the future of clean energy systems, reducing the forecasting errors related to wind speed has always been an important research subject. In this paper, an optimized hybrid method based on the Autoregressive Integrated Moving Average (ARIMA) and Kalman filter is proposed to forecast the daily mean wind speed in western China. This approach employs Particle Swarm Optimization (PSO) as an intelligent optimization algorithm to optimize the parameters of the ARIMA model, which develops a hybrid model that is best adapted to the data set, increasing the fitting accuracy and avoiding over-fitting. The proposed method is subsequently examined on the wind farms of western China, where the proposed hybrid model is shown to perform effectively and steadily

[Effects of exogenous silicon on the pollination and fertility characteristics of hybrid rice under heat stress during anthesis].

Science.gov (United States)

Wu, Chen-Yang; Chen, Dan; Luo, Hai-Wei; Yao, Yi-min; Wang, Zhi-Wei; Tsutomu, Matsui; Tian, Xiao-Hai

2013-11-01

Taking two medium-maturing indica rice hybrids Jinyou 63 and Shanyou 63 as test materials, this paper studied the effects of applying silicon fertilizer on the flag leaf chlorophyll content, photosynthetic properties, antioxidant enzyme activities, malondialdehyde (MDA) content, pollen vigor, anther acid invertase activity, pollination, and seed-setting of hybrid rice under the heat stress during anthesis. This study was conducted in pots and under growth chamber. Soluble solution of silicon fertilizer applied as Na2SiO3 x 9H2O was sprayed on the growing plants after early jointing stage, with three times successively and at an interval of one week. The pots were then moved into growth chamber to subject to normal temperature vs. high temperature (termed as heat stress) for five days. In treatment normal temperature, the average daily temperature was set at 26.6 degrees C, and the maximum daily temperature was set at 29.4 degres C; in treatment high temperature, the average and the maximum daily temperature were set at 33.2 degrees C and 40.1 degrees C, respectively. As compared with the control, applying silicon increased the flag leaf chlorophyll content significantly, improved the net photosynthetic rate and stomatal conductance, decreased the accumulative inter- cellular CO2 concentration, improved the leaf photosynthesis, reduced the MDA content, and improved the activities of SOD, POD and CAT under heat stress. In addition, applying silicon improved the anther acid invertase activity and the pollen vigor, increased the anther basal dehiscence width, total number of pollination per stigma, germinated number, germination rate of pollen, and percentage of florets with more than 10 germinated pollen grains, decreased the percentage of florets with fewer than 20 germinated pollen grains, and thus, alleviated the fertility loss of Jinyou 63 and Shanyou 63 under heat stress by 13.4% and 14.1%, respectively. It was suggested that spraying exogenous silicon in the

Stomatal characteristics of Eucalyptus grandis clonal hybrids in ...

African Journals Online (AJOL)

This study describes the stomatal response occurring during water stress and subsequent recovery of three Eucalyptus grandis clonal hybrids. The aim was to investigate the degree to which stomatal conductance (gs) and stomatal density differ between the clonal hybrids across seasons and in response to water stress.

A modeling method for hybrid energy behaviors in flexible machining systems

International Nuclear Information System (INIS)

Li, Yufeng; He, Yan; Wang, Yan; Wang, Yulin; Yan, Ping; Lin, Shenlong

2015-01-01

Increasingly environmental and economic pressures have led to great concerns regarding the energy consumption of machining systems. Understanding energy behaviors of flexible machining systems is a prerequisite for improving energy efficiency of these systems. This paper proposes a modeling method to predict energy behaviors in flexible machining systems. The hybrid energy behaviors not only depend on the technical specification related of machine tools and workpieces, but are significantly affected by individual production scenarios. In the method, hybrid energy behaviors are decomposed into Structure-related energy behaviors, State-related energy behaviors, Process-related energy behaviors and Assignment-related energy behaviors. The modeling method for the hybrid energy behaviors is proposed based on Colored Timed Object-oriented Petri Net (CTOPN). The former two types of energy behaviors are modeled by constructing the structure of CTOPN, whist the latter two types of behaviors are simulated by applying colored tokens and associated attributes. Machining on two workpieces in the experimental workshop were undertaken to verify the proposed modeling method. The results showed that the method can provide multi-perspective transparency on energy consumption related to machine tools, workpieces as well as production management, and is particularly suitable for flexible manufacturing system when frequent changes in machining systems are often encountered. - Highlights: • Energy behaviors in flexible machining systems are modeled in this paper. • Hybrid characteristics of energy behaviors are examined from multiple viewpoints. • Flexible modeling method CTOPN is used to predict the hybrid energy behaviors. • This work offers a multi-perspective transparency on energy consumption

Hybrid quantum teleportation: A theoretical model

Energy Technology Data Exchange (ETDEWEB)

Takeda, Shuntaro; Mizuta, Takahiro; Fuwa, Maria; Yoshikawa, Jun-ichi; Yonezawa, Hidehiro; Furusawa, Akira [Department of Applied Physics, School of Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656 (Japan)

2014-12-04

Hybrid quantum teleportation – continuous-variable teleportation of qubits – is a promising approach for deterministically teleporting photonic qubits. We propose how to implement it with current technology. Our theoretical model shows that faithful qubit transfer can be achieved for this teleportation by choosing an optimal gain for the teleporter’s classical channel.

Hybrid model of steam boiler

International Nuclear Information System (INIS)

Rusinowski, Henryk; Stanek, Wojciech

2010-01-01

In the case of big energy boilers energy efficiency is usually determined with the application of the indirect method. Flue gas losses and unburnt combustible losses have a significant influence on the boiler's efficiency. To estimate these losses the knowledge of the operating parameters influence on the flue gases temperature and the content of combustible particles in the solid combustion products is necessary. A hybrid model of a boiler developed with the application of both analytical modelling and artificial intelligence is described. The analytical part of the model includes the balance equations. The empirical models express the dependence of the flue gas temperature and the mass fraction of the unburnt combustibles in solid combustion products on the operating parameters of a boiler. The empirical models have been worked out by means of neural and regression modelling.

A Hybrid Acoustic and Pronunciation Model Adaptation Approach for Non-native Speech Recognition

Science.gov (United States)

Oh, Yoo Rhee; Kim, Hong Kook

In this paper, we propose a hybrid model adaptation approach in which pronunciation and acoustic models are adapted by incorporating the pronunciation and acoustic variabilities of non-native speech in order to improve the performance of non-native automatic speech recognition (ASR). Specifically, the proposed hybrid model adaptation can be performed at either the state-tying or triphone-modeling level, depending at which acoustic model adaptation is performed. In both methods, we first analyze the pronunciation variant rules of non-native speakers and then classify each rule as either a pronunciation variant or an acoustic variant. The state-tying level hybrid method then adapts pronunciation models and acoustic models by accommodating the pronunciation variants in the pronunciation dictionary and by clustering the states of triphone acoustic models using the acoustic variants, respectively. On the other hand, the triphone-modeling level hybrid method initially adapts pronunciation models in the same way as in the state-tying level hybrid method; however, for the acoustic model adaptation, the triphone acoustic models are then re-estimated based on the adapted pronunciation models and the states of the re-estimated triphone acoustic models are clustered using the acoustic variants. From the Korean-spoken English speech recognition experiments, it is shown that ASR systems employing the state-tying and triphone-modeling level adaptation methods can relatively reduce the average word error rates (WERs) by 17.1% and 22.1% for non-native speech, respectively, when compared to a baseline ASR system.

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.

To stress or not to stress: a question of models.

Science.gov (United States)

Gray, J Megan; Chaouloff, Francis; Hill, Matthew N

2015-01-05

Stress research is a rapidly evolving field that encompasses numerous disciplines ranging from neuroscience to metabolism. With many new researchers migrating into the field, navigating the hows and whys of specific research questions can sometimes be enigmatic given the availability of so many models in the stress field. Additionally, as with every field, there are many seemingly minor experimental details that can have dramatic influences on data interpretation, although many of these are unknown to those not familiar with the field. The aim of this overview is to provide some suggestions and points to guide researchers moving into the stress field and highlight relevant methodological points that they should consider when choosing a model for stress and deciding how to structure a study. We briefly provide a primer on the basics of endpoint measurements in the stress field, factors to consider when choosing a model for acute stress, the difference between repeated and chronic stress, and importantly, influencing variables that modulate endpoints of analysis in stress work. Copyright © 2015 John Wiley & Sons, Inc.

Modeling and Simulation of Renewable Hybrid Power System using Matlab Simulink Environment

Directory of Open Access Journals (Sweden)

Cristian Dragoş Dumitru

2010-12-01

Full Text Available The paper presents the modeling of a solar-wind-hydroelectric hybrid system in Matlab/Simulink environment. The application is useful for analysis and simulation of a real hybrid solar-wind-hydroelectric system connected to a public grid. Application is built on modular architecture to facilitate easy study of each component module influence. Blocks like wind model, solar model, hydroelectric model, energy conversion and load are implemented and the results of simulation are also presented. As an example, one of the most important studies is the behavior of hybrid system which allows employing renewable and variable in time energy sources while providing a continuous supply. Application represents a useful tool in research activity and also in teaching

Hybrid programming model for implicit PDE simulations on multicore architectures

KAUST Repository

Kaushik, Dinesh; Keyes, David E.; Balay, Satish; Smith, Barry F.

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.

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

Stress-reducing preventive maintenance model for a unit under stressful environment

International Nuclear Information System (INIS)

Park, J.H.; Chang, Woojin; Lie, C.H.

2012-01-01

We develop a preventive maintenance (PM) model for a unit operated under stressful environment. The PM model in this paper consists of a failure rate model and two cost models to determine the optimal PM scheduling which minimizes a cost rate. The assumption for the proposed model is that stressful environment accelerates the failure of the unit and periodic maintenances reduce stress from outside. The failure rate model handles the maintenance effect of PM using improvement and stress factors. The cost models are categorized into two failure recognition cases: immediate failure recognition and periodic failure detection. The optimal PM scheduling is obtained by considering the trade-off between the related cost and the lifetime of a unit in our model setting. The practical usage of our proposed model is tested through a numerical example.

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.

Hybrid modelling of soil-structure interaction for embedded structures

International Nuclear Information System (INIS)

Gupta, S.; Penzien, J.

1981-01-01

The basic methods currently being used for the analysis of soil-structure interaction fail to properly model three-dimensional embedded structures with flexible foundations. A hybrid model for the analysis of soil-structure interaction is developed in this investigation which takes advantage of the desirable features of both the finite element and substructure methods and which minimizes their undesirable features. The hybrid model is obtained by partitioning the total soil-structure system into a nearfield and a far-field with a smooth hemispherical interface. The near-field consists of the structure and a finite region of soil immediately surrounding its base. The entire near-field may be modelled in three-dimensional form using the finite element method; thus, taking advantage of its ability to model irregular geometries, and the non-linear soil behavior in the immediate vicinity of the structure. (orig./WL)

Modeling hydraulic regenerative hybrid vehicles using AMESim and Matlab/Simulink

Science.gov (United States)

Lynn, Alfred; Smid, Edzko; Eshraghi, Moji; Caldwell, Niall; Woody, Dan

2005-05-01

This paper presents the overview of the simulation modeling of a hydraulic system with regenerative braking used to improve vehicle emissions and fuel economy. Two simulation software packages were used together to enhance the simulation capability for fuel economy results and development of vehicle and hybrid control strategy. AMESim, a hydraulic simulation software package modeled the complex hydraulic circuit and component hardware and was interlinked with a Matlab/Simulink model of the vehicle, engine and the control strategy required to operate the vehicle and the hydraulic hybrid system through various North American and European drive cycles.

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.

Mitochondrial Dysfunction Causes Oxidative Stress and Tapetal Apoptosis in Chemical Hybridization Reagent-Induced Male Sterility in Wheat

Directory of Open Access Journals (Sweden)

Shuping Wang

2018-01-01

Full Text Available Male sterility in plants has been strongly linked to mitochondrial dysfunction. Chemical hybridization agent (CHA-induced male sterility is an important tool in crop heterosis. Therefore, it is important to better understand the relationship between mitochondria and CHA-induced male sterility in wheat. This study reports on the impairment of mitochondrial function duo to CHA-SQ-1, which occurs by decreasing cytochrome oxidase and adenosine triphosphate synthase protein levels and theirs activities, respiratory rate, and in turn results in the inhibition of the mitochondrial electron transport chain (ETC, excessive production of reactive oxygen species (ROS and disruption of the alternative oxidase pathway. Subsequently, excessive ROS combined with MnSOD defects results in damage to the mitochondrial membrane, followed by ROS release into the cytoplasm. The microspores underwent severe oxidative stress during pollen development. Furthermore, chronic oxidative stress, together with the overexpression of type II metacaspase, triggered premature tapetal apoptosis, which resulted in pollen abortion. Accordingly, we propose a metabolic pathway for mitochondrial-mediated male sterility in wheat, which provides information on the molecular events underlying CHA-SQ-1-induced abortion of anthers and may serve as an additional guide to the practical application of hybrid breeding.

Lemon Odor Reduces Stress-induced Neuronal Activation in the Emotion Expression System: An Animal Model Study

Science.gov (United States)

Sanada, Kazue; Sugimoto, Koji; Shutoh, Fumihiro; Hisano, Setsuji

Perception of particular sensory stimuli from the surroundings can influence emotion in individuals. In an uncomfortable situation, humans protect themselves from some aversive stimulus by acutely evoking a stress response. Animal model studies have contributed to an understanding of neuronal mechanisms underlying the stress response in humans. To study a possible anti-stressful effect of lemon odor, an excitation of neurons secreting corticotropin-releasing hormone (CRH) as a primary factor of the hypothalamic-pituitary-adrenal axis (HPA) was analyzed in animal model experiments, in which rats are restrained in the presence or absence of the odor. The effect was evaluated by measuring expression of c-Fos (an excited neuron marker) in the hypothalamic paraventricular nucleus (PVN), a key structure of the HPA in the brain. We prepared 3 animal groups: Groups S, L and I. Groups S and L were restrained for 30 minutes while being blown by air and being exposed to the lemon odor, respectively. Group I was intact without any treatment. Two hours later of the onset of experiments, brains of all groups were sampled and processed for microscopic examination. Brain sections were processed for c-Fos immunostaining and/or in situ hybridization for CRH. In Group S but not in Group I, c-Fos expression was found in the PVN. A combined in situ hybridization-immunohistochemical dual labeling revealed that CRH mRNA-expressing neurons express c-Fos. In computer-assisted automatic counting, the incidence of c-Fos-expressing neurons in the entire PVN was statistically lower in Group L than in Group S. Detailed analysis of PVN subregions demonstrated that c-Fos-expressing neurons are fewer in Group L than in Group S in the dorsal part of the medial parvocellular subregion. These results may suggest that lemon odor attenuates the restraint stress-induced neuronal activation including CRH neurons, presumably mimicking an aspect of stress responses in humans.

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.

Activity Recognition Using Hybrid Generative/Discriminative Models on Home Environments Using Binary Sensors

Directory of Open Access Journals (Sweden)

Araceli Sanchis

2013-04-01

Full Text Available Activities of daily living are good indicators of elderly health status, and activity recognition in smart environments is a well-known problem that has been previously addressed by several studies. In this paper, we describe the use of two powerful machine learning schemes, ANN (Artificial Neural Network and SVM (Support Vector Machines, within the framework of HMM (Hidden Markov Model in order to tackle the task of activity recognition in a home setting. The output scores of the discriminative models, after processing, are used as observation probabilities of the hybrid approach. We evaluate our approach by comparing these hybrid models with other classical activity recognition methods using five real datasets. We show how the hybrid models achieve significantly better recognition performance, with significance level p < 0:05, proving that the hybrid approach is better suited for the addressed domain.

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.

Synthesis of a hybrid model of the VSC FACTS devices and HVDC technologies

Science.gov (United States)

Borovikov, Yu S.; Gusev, A. S.; Sulaymanov, A. O.; Ufa, R. A.

2014-10-01

The motivation of the presented research is based on the need for development of new methods and tools for adequate simulation of FACTS devices and HVDC systems as part of real electric power systems (EPS). The Research object: An alternative hybrid approach for synthesizing VSC-FACTS and -HVDC hybrid model is proposed. The results: the VSC- FACTS and -HVDC hybrid model is designed in accordance with the presented concepts of hybrid simulation. The developed model allows us to carry out adequate simulation in real time of all the processes in HVDC, FACTS devices and EPS as a whole without any decomposition and limitation on their duration, and also use the developed tool for effective solution of a design, operational and research tasks of EPS containing such devices.

Synthesis of a hybrid model of the VSC FACTS devices and HVDC technologies

International Nuclear Information System (INIS)

Borovikov, Yu S; Gusev, A S; Sulaymanov, A O; Ufa, R A

2014-01-01

The motivation of the presented research is based on the need for development of new methods and tools for adequate simulation of FACTS devices and HVDC systems as part of real electric power systems (EPS). The Research object: An alternative hybrid approach for synthesizing VSC-FACTS and -HVDC hybrid model is proposed. The results: the VSC- FACTS and -HVDC hybrid model is designed in accordance with the presented concepts of hybrid simulation. The developed model allows us to carry out adequate simulation in real time of all the processes in HVDC, FACTS devices and EPS as a whole without any decomposition and limitation on their duration, and also use the developed tool for effective solution of a design, operational and research tasks of EPS containing such devices

Model predictive control of an air suspension system with damping multi-mode switching damper based on hybrid model

Science.gov (United States)

Sun, Xiaoqiang; Yuan, Chaochun; Cai, Yingfeng; Wang, Shaohua; Chen, Long

2017-09-01

This paper presents the hybrid modeling and the model predictive control of an air suspension system with damping multi-mode switching damper. Unlike traditional damper with continuously adjustable damping, in this study, a new damper with four discrete damping modes is applied to vehicle semi-active air suspension. The new damper can achieve different damping modes by just controlling the on-off statuses of two solenoid valves, which makes its damping adjustment more efficient and more reliable. However, since the damping mode switching induces different modes of operation, the air suspension system with the new damper poses challenging hybrid control problem. To model both the continuous/discrete dynamics and the switching between different damping modes, the framework of mixed logical dynamical (MLD) systems is used to establish the system hybrid model. Based on the resulting hybrid dynamical model, the system control problem is recast as a model predictive control (MPC) problem, which allows us to optimize the switching sequences of the damping modes by taking into account the suspension performance requirements. Numerical simulations results demonstrate the efficacy of the proposed control method finally.

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.

A hybrid hydrostatic and non-hydrostatic numerical model for shallow flow simulations

Science.gov (United States)

Zhang, Jingxin; Liang, Dongfang; Liu, Hua

2018-05-01

Hydrodynamics of geophysical flows in oceanic shelves, estuaries, and rivers, are often studied by solving shallow water model equations. Although hydrostatic models are accurate and cost efficient for many natural flows, there are situations where the hydrostatic assumption is invalid, whereby a fully hydrodynamic model is necessary to increase simulation accuracy. There is a growing concern about the decrease of the computational cost of non-hydrostatic pressure models to improve the range of their applications in large-scale flows with complex geometries. This study describes a hybrid hydrostatic and non-hydrostatic model to increase the efficiency of simulating shallow water flows. The basic numerical model is a three-dimensional hydrostatic model solved by the finite volume method (FVM) applied to unstructured grids. Herein, a second-order total variation diminishing (TVD) scheme is adopted. Using a predictor-corrector method to calculate the non-hydrostatic pressure, we extended the hydrostatic model to a fully hydrodynamic model. By localising the computational domain in the corrector step for non-hydrostatic pressure calculations, a hybrid model was developed. There was no prior special treatment on mode switching, and the developed numerical codes were highly efficient and robust. The hybrid model is applicable to the simulation of shallow flows when non-hydrostatic pressure is predominant only in the local domain. Beyond the non-hydrostatic domain, the hydrostatic model is still accurate. The applicability of the hybrid method was validated using several study cases.

A hybrid society model for simulating residential electricity consumption

International Nuclear Information System (INIS)

Xu, Minjie; Hu, Zhaoguang; Wu, Junyong; Zhou, Yuhui

2008-01-01

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)

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)

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.

Hybrid Electric Vehicle Experimental Model with CAN Network Real Time Control

Directory of Open Access Journals (Sweden)

RATOI, M.

2010-05-01

Full Text Available In this paper an experimental model with a distributed control system of a hybrid electrical vehicle is presented. A communication CAN network of high speed (1 Mbps assures a distributed control of the all components. The modeling and the control of different operating regimes are realized on an experimental test-bench of a hybrid electrical vehicle. The experimental results concerning the variations of the mains variables (currents, torques, speeds are presented.

Hybrid neural network bushing model for vehicle dynamics simulation

International Nuclear Information System (INIS)

Sohn, Jeong Hyun; Lee, Seung Kyu; Yoo, Wan Suk

2008-01-01

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

Bias-dependent hybrid PKI empirical-neural model of microwave FETs

Science.gov (United States)

Marinković, Zlatica; Pronić-Rančić, Olivera; Marković, Vera

2011-10-01

Empirical models of microwave transistors based on an equivalent circuit are valid for only one bias point. Bias-dependent analysis requires repeated extractions of the model parameters for each bias point. In order to make model bias-dependent, a new hybrid empirical-neural model of microwave field-effect transistors is proposed in this article. The model is a combination of an equivalent circuit model including noise developed for one bias point and two prior knowledge input artificial neural networks (PKI ANNs) aimed at introducing bias dependency of scattering (S) and noise parameters, respectively. The prior knowledge of the proposed ANNs involves the values of the S- and noise parameters obtained by the empirical model. The proposed hybrid model is valid in the whole range of bias conditions. Moreover, the proposed model provides better accuracy than the empirical model, which is illustrated by an appropriate modelling example of a pseudomorphic high-electron mobility transistor device.

A study on the development of photoelastic experimental hybrid method for colour isochromatics (I)

International Nuclear Information System (INIS)

Hawong, Jai Sug; Nam, Jeong Hwan; Kim, Kyo Hyoung; Kwon, O Sung; Kwon, Gun; Park, Sung Han

2010-01-01

Isochromatics obtained from photoelastic experiment shows the stress distributions of the full field of a structure under load. Therefore, stress distributions of the structure can be read at a glance through isochromatics. Many experimental data can be obtained from isochromatics which are then used in various photoelastic experimental hybrid methods for stress analysis. Monochromatic light has however, until now been used in the photoelastic experimental hybrid method to produce black and white isochromatics. The use of black and white isochromatics in photoelastic experimental hybrid method for black and white isochromatics requires high fringe orders in order to obtain sufficient experimental data for photoelastic hybrid techniques. Accordingly, this paper develops the photoelastic experimental hybrid method for color isochromatics in which a fringe order of 1 is enough to gather the experimental data of the photoelastic experimental hybrid method. The method was applied to validate stress concentration problems. Experimental results from this study indicated that the photoelastic experimental hybrid method for color isochromatics is more precise than the photoelastic experimental hybrid method for black and white isochromatics. The use of few fringe orders in photoelastic experimental hybrid method for color isochromatics can offer significant advantages in stress analysis of real components using reflective-type photoelastic experimental method

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

Directory of Open Access Journals (Sweden)

René Felix Reinhart

2017-02-01

Full Text Available Feed-forward model-based control relies on models of the controlled plant, e.g., in robotics on accurate knowledge of manipulator kinematics or dynamics. However, mechanical and analytical models do not capture all aspects of a plant’s intrinsic properties and there remain unmodeled dynamics due to varying parameters, unmodeled friction or soft materials. In this context, machine learning is an alternative suitable technique to extract non-linear plant models from data. However, fully data-based models suffer from inaccuracies as well and are inefficient if they include learning of well known analytical models. This paper thus argues that feed-forward control based on hybrid models comprising an analytical model and a learned error model can significantly improve modeling accuracy. Hybrid modeling here serves the purpose to combine the best of the two modeling worlds. The hybrid modeling methodology is described and the approach is demonstrated for two typical problems in robotics, i.e., inverse kinematics control and computed torque control. The former is performed for a redundant soft robot and the latter for a rigid industrial robot with redundant degrees of freedom, where a complete analytical model is not available for any of the platforms.

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

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

Hybrid nested sampling algorithm for Bayesian model selection applied to inverse subsurface flow problems

KAUST Repository

Elsheikh, Ahmed H.; Wheeler, Mary Fanett; Hoteit, Ibrahim

2014-01-01

A Hybrid Nested Sampling (HNS) algorithm is proposed for efficient Bayesian model calibration and prior model selection. The proposed algorithm combines, Nested Sampling (NS) algorithm, Hybrid Monte Carlo (HMC) sampling and gradient estimation using

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.

Gravitational waves in hybrid quintessential inflationary models

International Nuclear Information System (INIS)

Sa, Paulo M; Henriques, Alfredo B

2011-01-01

The generation of primordial gravitational waves is investigated within the hybrid quintessential inflationary model. Using the method of continuous Bogoliubov coefficients, we calculate the full gravitational-wave energy spectrum. The post-inflationary kination period, characteristic of quintessential inflationary models, leaves a clear signature on the spectrum, namely, a sharp rise of the gravitational-wave spectral energy density Ω GW at high frequencies. For appropriate values of the parameters of the model, Ω GW can be as high as 10 -12 in the MHz-GHz range of frequencies.

Two-field axion-monodromy hybrid inflation model: Dante's Waterfall

Science.gov (United States)

Carone, Christopher D.; Erlich, Joshua; Sensharma, Anuraag; Wang, Zhen

2015-02-01

We describe a hybrid axion-monodromy inflation model motivated by the Dante's Inferno scenario. In Dante's Inferno, a two-field potential features a stable trench along which a linear combination of the two fields slowly rolls, rendering the dynamics essentially identical to that of single-field chaotic inflation. A shift symmetry allows for the Lyth bound to be effectively evaded as in other axion-monodromy models. In our proposal, the potential is concave downward near the origin and the inflaton trajectory is a gradual downward spiral, ending at a point where the trench becomes unstable. There, the fields begin falling rapidly towards the minimum of the potential and inflation terminates as in a hybrid model. We find parameter choices that reproduce observed features of the cosmic microwave background, and discuss our model in light of recent results from the BICEP2 and Planck experiments.

Design and fabrication of a hybrid maglev model employing PML and SML

Science.gov (United States)

Sun, R. X.; Zheng, J.; Zhan, L. J.; Huang, S. Y.; Li, H. T.; Deng, Z. G.

2017-10-01

A hybrid maglev model combining permanent magnet levitation (PML) and superconducting magnetic levitation (SML) was designed and fabricated to explore a heavy-load levitation system advancing in passive stability and simple structure. In this system, the PML was designed to levitate the load, and the SML was introduced to guarantee the stability. In order to realize different working gaps of the two maglev components, linear bearings were applied to connect the PML layer (for load) and the SML layer (for stability) of the hybrid maglev model. Experimental results indicate that the hybrid maglev model possesses excellent advantages of heavy-load ability and passive stability at the same time. This work presents a possible way to realize a heavy-load passive maglev concept.

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

Directory of Open Access Journals (Sweden)

Hong-Wen He

2010-11-01

Full Text Available Hybrid power systems, formed by combining high-energy-density batteries and high-power-density ultracapacitors in appropriate ways, provide high-performance and high-efficiency power systems for electric vehicle applications. This paper first establishes dynamic models for the ultracapacitor, the battery and a passive hybrid power system, and then based on the dynamic models a comparative simulation between a battery only power system and the proposed hybrid power system was done under the UDDS (Urban Dynamometer Driving Schedule. The simulation results showed that the hybrid power system could greatly optimize and improve the efficiency of the batteries and their dynamic current was also decreased due to the participation of the ultracapacitors, which would have a good influence on batteries’ cycle life. Finally, the parameter matching for the passive hybrid power system was studied by simulation and comparisons.

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...

Biochemical components and dry matter of lemon and mandarin hybrids under salt stress

Directory of Open Access Journals (Sweden)

Francisco V. da S. Sá

Full Text Available ABSTRACT The objective was to study the biochemical changes and dry matter content in lemon and mandarin hybrids under salt stress during rootstock formation. For this, a study was conducted in randomized complete block, using a 2 x 5 factorial scheme, with two salinity levels (0.3 and 4.0 dS m-1 applied in five citrus rootstock genotypes (1. TSKC x CTARG - 019; 2. LRF; 3. TSKC x (LCR x TR - 040; 4. LCRSTC and 5. LVK, with three replicates and four plants per plot. At 90 days after sowing, saline treatments started to be applied and continued until 120 days after sowing, the moment in which the plants were collected for evaluation of biochemical characteristics and phytomass accumulation. The increase in water salinity negatively affected the biochemical components and dry matter accumulation of citrus genotypes. The genotypes TSKC x (LCR x TR - 040, LCRSTC and LVK were the least affected by salt stress, standing out as the materials most tolerant to salinity.

Euro hybrid materials and structures. Proceedings

Energy Technology Data Exchange (ETDEWEB)

Hausmann, Joachim M.; Siebert, Marc (eds.)

2016-08-01

In order to use the materials as best as possible, several different materials are usually mixed in one component, especially in the field of lightweight design. If these combinations of materials are joined inherently, they are called multi material design products or hybrid structures. These place special requirements on joining technology, design methods and manufacturing and are challenging in other aspects, too. The eight chapters with manuscripts of the presentations are: Chapter 1- Interface: What happens in the interface between the two materials? Chapter 2 - Corrosion and Residual Stresses: How about galvanic corrosion and thermal residual stresses in the contact zone of different materials? Chapter 3 - Characterization: How to characterize and test hybrid materials? Chapter 4 - Design: What is a suitable design and dimensioning method for hybrid structures? Chapter 5 - Machining and Processing: How to machine and process hybrid structures and materials? Chapter 6 - Component Manufacturing: What is a suitable manufacturing route for hybrid structures? Chapter 7 - Non-Destructive Testing and Quality Assurance: How to assure the quality of material and structures? Chapter 8 - Joining: How to join components of different materials?.

Euro hybrid materials and structures. Proceedings

International Nuclear Information System (INIS)

Hausmann, Joachim M.; Siebert, Marc

2016-01-01

In order to use the materials as best as possible, several different materials are usually mixed in one component, especially in the field of lightweight design. If these combinations of materials are joined inherently, they are called multi material design products or hybrid structures. These place special requirements on joining technology, design methods and manufacturing and are challenging in other aspects, too. The eight chapters with manuscripts of the presentations are: Chapter 1- Interface: What happens in the interface between the two materials? Chapter 2 - Corrosion and Residual Stresses: How about galvanic corrosion and thermal residual stresses in the contact zone of different materials? Chapter 3 - Characterization: How to characterize and test hybrid materials? Chapter 4 - Design: What is a suitable design and dimensioning method for hybrid structures? Chapter 5 - Machining and Processing: How to machine and process hybrid structures and materials? Chapter 6 - Component Manufacturing: What is a suitable manufacturing route for hybrid structures? Chapter 7 - Non-Destructive Testing and Quality Assurance: How to assure the quality of material and structures? Chapter 8 - Joining: How to join components of different materials?

Structural hybrid reliability index and its convergent solving method based on random–fuzzy–interval reliability model

Directory of Open Access Journals (Sweden)

Hai An

2016-08-01

Full Text Available Aiming to resolve the problems of a variety of uncertainty variables that coexist in the engineering structure reliability analysis, a new hybrid reliability index to evaluate structural hybrid reliability, based on the random–fuzzy–interval model, is proposed in this article. The convergent solving method is also presented. First, the truncated probability reliability model, the fuzzy random reliability model, and the non-probabilistic interval reliability model are introduced. Then, the new hybrid reliability index definition is presented based on the random–fuzzy–interval model. Furthermore, the calculation flowchart of the hybrid reliability index is presented and it is solved using the modified limit-step length iterative algorithm, which ensures convergence. And the validity of convergent algorithm for the hybrid reliability model is verified through the calculation examples in literature. In the end, a numerical example is demonstrated to show that the hybrid reliability index is applicable for the wear reliability assessment of mechanisms, where truncated random variables, fuzzy random variables, and interval variables coexist. The demonstration also shows the good convergence of the iterative algorithm proposed in this article.

Model-on-Demand Predictive Control for Nonlinear Hybrid Systems With Application to Adaptive Behavioral Interventions

Science.gov (United States)

Nandola, Naresh N.; Rivera, Daniel E.

2011-01-01

This paper presents a data-centric modeling and predictive control approach for nonlinear hybrid systems. System identification of hybrid systems represents a challenging problem because model parameters depend on the mode or operating point of the system. The proposed algorithm applies Model-on-Demand (MoD) estimation to generate a local linear approximation of the nonlinear hybrid system at each time step, using a small subset of data selected by an adaptive bandwidth selector. The appeal of the MoD approach lies in the fact that model parameters are estimated based on a current operating point; hence estimation of locations or modes governed by autonomous discrete events is achieved automatically. The local MoD model is then converted into a mixed logical dynamical (MLD) system representation which can be used directly in a model predictive control (MPC) law for hybrid systems using multiple-degree-of-freedom tuning. The effectiveness of the proposed MoD predictive control algorithm for nonlinear hybrid systems is demonstrated on a hypothetical adaptive behavioral intervention problem inspired by Fast Track, a real-life preventive intervention for improving parental function and reducing conduct disorder in at-risk children. Simulation results demonstrate that the proposed algorithm can be useful for adaptive intervention problems exhibiting both nonlinear and hybrid character. PMID:21874087

Performance modeling of hybrid MPI/OpenMP scientific applications on large-scale multicore supercomputers

KAUST Repository

Wu, Xingfu; Taylor, Valerie

2013-01-01

In this paper, we present a performance modeling framework based on memory bandwidth contention time and a parameterized communication model to predict the performance of OpenMP, MPI and hybrid applications with weak scaling on three large-scale multicore supercomputers: IBM POWER4, POWER5+ and BlueGene/P, and analyze the performance of these MPI, OpenMP and hybrid applications. We use STREAM memory benchmarks and Intel's MPI benchmarks to provide initial performance analysis and model validation of MPI and OpenMP applications on these multicore supercomputers because the measured sustained memory bandwidth can provide insight into the memory bandwidth that a system should sustain on scientific applications with the same amount of workload per core. In addition to using these benchmarks, we also use a weak-scaling hybrid MPI/OpenMP large-scale scientific application: Gyrokinetic Toroidal Code (GTC) in magnetic fusion to validate our performance model of the hybrid application on these multicore supercomputers. The validation results for our performance modeling method show less than 7.77% error rate in predicting the performance of hybrid MPI/OpenMP GTC on up to 512 cores on these multicore supercomputers. © 2013 Elsevier Inc.

Performance modeling of hybrid MPI/OpenMP scientific applications on large-scale multicore supercomputers

KAUST Repository

Wu, Xingfu

2013-12-01

In this paper, we present a performance modeling framework based on memory bandwidth contention time and a parameterized communication model to predict the performance of OpenMP, MPI and hybrid applications with weak scaling on three large-scale multicore supercomputers: IBM POWER4, POWER5+ and BlueGene/P, and analyze the performance of these MPI, OpenMP and hybrid applications. We use STREAM memory benchmarks and Intel\\'s MPI benchmarks to provide initial performance analysis and model validation of MPI and OpenMP applications on these multicore supercomputers because the measured sustained memory bandwidth can provide insight into the memory bandwidth that a system should sustain on scientific applications with the same amount of workload per core. In addition to using these benchmarks, we also use a weak-scaling hybrid MPI/OpenMP large-scale scientific application: Gyrokinetic Toroidal Code (GTC) in magnetic fusion to validate our performance model of the hybrid application on these multicore supercomputers. The validation results for our performance modeling method show less than 7.77% error rate in predicting the performance of hybrid MPI/OpenMP GTC on up to 512 cores on these multicore supercomputers. © 2013 Elsevier Inc.

AMITIS: A 3D GPU-Based Hybrid-PIC Model for Space and Plasma Physics

Science.gov (United States)

Fatemi, Shahab; Poppe, Andrew R.; Delory, Gregory T.; Farrell, William M.

2017-05-01

We have developed, for the first time, an advanced modeling infrastructure in space simulations (AMITIS) with an embedded three-dimensional self-consistent grid-based hybrid model of plasma (kinetic ions and fluid electrons) that runs entirely on graphics processing units (GPUs). The model uses NVIDIA GPUs and their associated parallel computing platform, CUDA, developed for general purpose processing on GPUs. The model uses a single CPU-GPU pair, where the CPU transfers data between the system and GPU memory, executes CUDA kernels, and writes simulation outputs on the disk. All computations, including moving particles, calculating macroscopic properties of particles on a grid, and solving hybrid model equations are processed on a single GPU. We explain various computing kernels within AMITIS and compare their performance with an already existing well-tested hybrid model of plasma that runs in parallel using multi-CPU platforms. We show that AMITIS runs ∼10 times faster than the parallel CPU-based hybrid model. We also introduce an implicit solver for computation of Faraday’s Equation, resulting in an explicit-implicit scheme for the hybrid model equation. We show that the proposed scheme is stable and accurate. We examine the AMITIS energy conservation and show that the energy is conserved with an error < 0.2% after 500,000 timesteps, even when a very low number of particles per cell is used.

Gravitational waves in hybrid quintessential inflationary models

Energy Technology Data Exchange (ETDEWEB)

Sa, Paulo M [Departamento de Fisica, Faculdade de Ciencias e Tecnologia, Universidade do Algarve, Campus de Gambelas, 8005-139 Faro (Portugal); Henriques, Alfredo B, E-mail: pmsa@ualg.pt, E-mail: alfredo.henriques@ist.utl.pt [Centro Multidisciplinar de Astrofisica - CENTRA and Departamento de Fisica, Instituto Superior Tecnico, UTL, Av. Rovisco Pais, 1049-001 Lisboa (Portugal)

2011-09-22

The generation of primordial gravitational waves is investigated within the hybrid quintessential inflationary model. Using the method of continuous Bogoliubov coefficients, we calculate the full gravitational-wave energy spectrum. The post-inflationary kination period, characteristic of quintessential inflationary models, leaves a clear signature on the spectrum, namely, a sharp rise of the gravitational-wave spectral energy density {Omega}{sub GW} at high frequencies. For appropriate values of the parameters of the model, {Omega}{sub GW} can be as high as 10{sup -12} in the MHz-GHz range of frequencies.

Application of a New Hybrid RANS/LES Modeling Paradigm to Compressible Flow

Science.gov (United States)

Oliver, Todd; Pederson, Clark; Haering, Sigfried; Moser, Robert

2017-11-01

It is well-known that traditional hybrid RANS/LES modeling approaches suffer from a number of deficiencies. These deficiencies often stem from overly simplistic blending strategies based on scalar measures of turbulence length scale and grid resolution and from use of isotropic subgrid models in LES regions. A recently developed hybrid modeling approach has shown promise in overcoming these deficiencies in incompressible flows [Haering, 2015]. In the approach, RANS/LES blending is accomplished using a hybridization parameter that is governed by an additional model transport equation and is driven to achieve equilibrium between the resolved and unresolved turbulence for the given grid. Further, the model uses an tensor eddy viscosity that is formulated to represent the effects of anisotropic grid resolution on subgrid quantities. In this work, this modeling approach is extended to compressible flows and implemented in the compressible flow solver SU2 (http://su2.stanford.edu/). We discuss both modeling and implementation challenges and show preliminary results for compressible flow test cases with smooth wall separation.

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.

Modelling of loading, stress relaxation and stress recovery in a shape memory polymer.

Science.gov (United States)

Sweeney, J; Bonner, M; Ward, I M

2014-09-01

A multi-element constitutive model for a lactide-based shape memory polymer has been developed that represents loading to large tensile deformations, stress relaxation and stress recovery at 60, 65 and 70°C. The model consists of parallel Maxwell arms each comprising neo-Hookean and Eyring elements. Guiu-Pratt analysis of the stress relaxation curves yields Eyring parameters. When these parameters are used to define the Eyring process in a single Maxwell arm, the resulting model yields at too low a stress, but gives good predictions for longer times. Stress dip tests show a very stiff response on unloading by a small strain decrement. This would create an unrealistically high stress on loading to large strain if it were modelled by an elastic element. Instead it is modelled by an Eyring process operating via a flow rule that introduces strain hardening after yield. When this process is incorporated into a second parallel Maxwell arm, there results a model that fully represents both stress relaxation and stress dip tests at 60°C. At higher temperatures a third arm is required for valid predictions. Crown Copyright © 2014. Published by Elsevier Ltd. All rights reserved.

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.

On the Likely Utility of Hybrid Weights Optimized for Variances in Hybrid Error Covariance Models

Science.gov (United States)

Satterfield, E.; Hodyss, D.; Kuhl, D.; Bishop, C. H.

2017-12-01

Because of imperfections in ensemble data assimilation schemes, one cannot assume that the ensemble covariance is equal to the true error covariance of a forecast. Previous work demonstrated how information about the distribution of true error variances given an ensemble sample variance can be revealed from an archive of (observation-minus-forecast, ensemble-variance) data pairs. Here, we derive a simple and intuitively compelling formula to obtain the mean of this distribution of true error variances given an ensemble sample variance from (observation-minus-forecast, ensemble-variance) data pairs produced by a single run of a data assimilation system. This formula takes the form of a Hybrid weighted average of the climatological forecast error variance and the ensemble sample variance. Here, we test the extent to which these readily obtainable weights can be used to rapidly optimize the covariance weights used in Hybrid data assimilation systems that employ weighted averages of static covariance models and flow-dependent ensemble based covariance models. Univariate data assimilation and multi-variate cycling ensemble data assimilation are considered. In both cases, it is found that our computationally efficient formula gives Hybrid weights that closely approximate the optimal weights found through the simple but computationally expensive process of testing every plausible combination of weights.

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

Integrated Inflammatory Stress (ITIS) Model

DEFF Research Database (Denmark)

Bangsgaard, Elisabeth O.; Hjorth, Poul G.; Olufsen, Mette S.

2017-01-01

maintains a long-term level of the stress hormone cortisol which is also anti-inflammatory. A new integrated model of the interaction between these two subsystems of the inflammatory system is proposed and coined the integrated inflammatory stress (ITIS) model. The coupling mechanisms describing....... A constant activation results in elevated levels of the variables in the model while a prolonged change of the oscillations in ACTH and cortisol concentrations is the most pronounced result of different LPS doses predicted by the model....

Using the hybrid fuzzy goal programming model and hybrid genetic algorithm to solve a multi-objective location routing problem for infectious waste disposaL

Energy Technology Data Exchange (ETDEWEB)

Wichapa, Narong; Khokhajaikiat, Porntep

2017-07-01

Disposal of infectious waste remains one of the most serious problems in the social and environmental domains of almost every nation. Selection of new suitable locations and finding the optimal set of transport routes to transport infectious waste, namely location routing problem for infectious waste disposal, is one of the major problems in hazardous waste management. Design/methodology/approach: Due to the complexity of this problem, location routing problem for a case study, forty hospitals and three candidate municipalities in sub-Northeastern Thailand, was divided into two phases. The first phase is to choose suitable municipalities using hybrid fuzzy goal programming model which hybridizes the fuzzy analytic hierarchy process and fuzzy goal programming. The second phase is to find the optimal routes for each selected municipality using hybrid genetic algorithm which hybridizes the genetic algorithm and local searches including 2-Opt-move, Insertion-move and ?-interchange-move. Findings: The results indicate that the hybrid fuzzy goal programming model can guide the selection of new suitable municipalities, and the hybrid genetic algorithm can provide the optimal routes for a fleet of vehicles effectively. Originality/value: The novelty of the proposed methodologies, hybrid fuzzy goal programming model, is the simultaneous combination of both intangible and tangible factors in order to choose new suitable locations, and the hybrid genetic algorithm can be used to determine the optimal routes which provide a minimum number of vehicles and minimum transportation cost under the actual situation, efficiently.

Using the hybrid fuzzy goal programming model and hybrid genetic algorithm to solve a multi-objective location routing problem for infectious waste disposaL

International Nuclear Information System (INIS)

Wichapa, Narong; Khokhajaikiat, Porntep

2017-01-01

Disposal of infectious waste remains one of the most serious problems in the social and environmental domains of almost every nation. Selection of new suitable locations and finding the optimal set of transport routes to transport infectious waste, namely location routing problem for infectious waste disposal, is one of the major problems in hazardous waste management. Design/methodology/approach: Due to the complexity of this problem, location routing problem for a case study, forty hospitals and three candidate municipalities in sub-Northeastern Thailand, was divided into two phases. The first phase is to choose suitable municipalities using hybrid fuzzy goal programming model which hybridizes the fuzzy analytic hierarchy process and fuzzy goal programming. The second phase is to find the optimal routes for each selected municipality using hybrid genetic algorithm which hybridizes the genetic algorithm and local searches including 2-Opt-move, Insertion-move and ?-interchange-move. Findings: The results indicate that the hybrid fuzzy goal programming model can guide the selection of new suitable municipalities, and the hybrid genetic algorithm can provide the optimal routes for a fleet of vehicles effectively. Originality/value: The novelty of the proposed methodologies, hybrid fuzzy goal programming model, is the simultaneous combination of both intangible and tangible factors in order to choose new suitable locations, and the hybrid genetic algorithm can be used to determine the optimal routes which provide a minimum number of vehicles and minimum transportation cost under the actual situation, efficiently.

Hybrid Spatial Data Model for Indoor Space: Combined Topology and Grid

Directory of Open Access Journals (Sweden)

Zhiyong Lin

2017-11-01

Full Text Available The construction and application of an indoor spatial data model is an important prerequisite to meet the requirements of diversified indoor spatial location services. The traditional indoor spatial topology model focuses on the construction of topology information. It has high path analysis and query efficiency, but ignores the spatial location information. The grid model retains the plane position information by grid, but increases the data volume and complexity of the model and reduces the efficiency of the model analysis. This paper presents a hybrid model for interior space based on topology and grid. Based on the spatial meshing and spatial division of the interior space, the model retains the position information and topological connectivity information of the interior space by establishing the connection or affiliation between the grid subspace and the topological subspace. The model improves the speed of interior spatial analysis and solves the problem of the topology information and location information updates not being synchronized. In this study, the A* shortest path query efficiency of typical daily indoor activities under the grid model and the hybrid model were compared for the indoor plane of an apartment and a shopping mall. The results obtained show that the hybrid model is 43% higher than the A* algorithm of the grid model as a result of the existence of topology communication information. This paper provides a useful idea for the establishment of a highly efficient and highly available interior spatial data model.

Computational analysis on plug-in hybrid electric motorcycle chassis

Science.gov (United States)

Teoh, S. J.; Bakar, R. A.; Gan, L. M.

2013-12-01

Plug-in hybrid electric motorcycle (PHEM) is an alternative to promote sustainability lower emissions. However, the PHEM overall system packaging is constrained by limited space in a motorcycle chassis. In this paper, a chassis applying the concept of a Chopper is analysed to apply in PHEM. The chassis 3dimensional (3D) modelling is built with CAD software. The PHEM power-train components and drive-train mechanisms are intergraded into the 3D modelling to ensure the chassis provides sufficient space. Besides that, a human dummy model is built into the 3D modelling to ensure the rider?s ergonomics and comfort. The chassis 3D model then undergoes stress-strain simulation. The simulation predicts the stress distribution, displacement and factor of safety (FOS). The data are used to identify the critical point, thus suggesting the chassis design is applicable or need to redesign/ modify to meet the require strength. Critical points mean highest stress which might cause the chassis to fail. This point occurs at the joints at triple tree and bracket rear absorber for a motorcycle chassis. As a conclusion, computational analysis predicts the stress distribution and guideline to develop a safe prototype chassis.

Fuzzy logic-based analogue forecasting and hybrid modelling of horizontal visibility

Science.gov (United States)

Tuba, Zoltán; Bottyán, Zsolt

2018-04-01

Forecasting visibility is one of the greatest challenges in aviation meteorology. At the same time, high accuracy visibility forecasts can significantly reduce or make avoidable weather-related risk in aviation as well. To improve forecasting visibility, this research links fuzzy logic-based analogue forecasting and post-processed numerical weather prediction model outputs in hybrid forecast. Performance of analogue forecasting model was improved by the application of Analytic Hierarchy Process. Then, linear combination of the mentioned outputs was applied to create ultra-short term hybrid visibility prediction which gradually shifts the focus from statistical to numerical products taking their advantages during the forecast period. It gives the opportunity to bring closer the numerical visibility forecast to the observations even it is wrong initially. Complete verification of categorical forecasts was carried out; results are available for persistence and terminal aerodrome forecasts (TAF) as well in order to compare. The average value of Heidke Skill Score (HSS) of examined airports of analogue and hybrid forecasts shows very similar results even at the end of forecast period where the rate of analogue prediction in the final hybrid output is 0.1-0.2 only. However, in case of poor visibility (1000-2500 m), hybrid (0.65) and analogue forecasts (0.64) have similar average of HSS in the first 6 h of forecast period, and have better performance than persistence (0.60) or TAF (0.56). Important achievement that hybrid model takes into consideration physics and dynamics of the atmosphere due to the increasing part of the numerical weather prediction. In spite of this, its performance is similar to the most effective visibility forecasting methods and does not follow the poor verification results of clearly numerical outputs.

Evaluation of vertical coordinate and vertical mixing algorithms in the HYbrid-Coordinate Ocean Model (HYCOM)

Science.gov (United States)

Halliwell, George R.

Vertical coordinate and vertical mixing algorithms included in the HYbrid Coordinate Ocean Model (HYCOM) are evaluated in low-resolution climatological simulations of the Atlantic Ocean. The hybrid vertical coordinates are isopycnic in the deep ocean interior, but smoothly transition to level (pressure) coordinates near the ocean surface, to sigma coordinates in shallow water regions, and back again to level coordinates in very shallow water. By comparing simulations to climatology, the best model performance is realized using hybrid coordinates in conjunction with one of the three available differential vertical mixing models: the nonlocal K-Profile Parameterization, the NASA GISS level 2 turbulence closure, and the Mellor-Yamada level 2.5 turbulence closure. Good performance is also achieved using the quasi-slab Price-Weller-Pinkel dynamical instability model. Differences among these simulations are too small relative to other errors and biases to identify the "best" vertical mixing model for low-resolution climate simulations. Model performance deteriorates slightly when the Kraus-Turner slab mixed layer model is used with hybrid coordinates. This deterioration is smallest when solar radiation penetrates beneath the mixed layer and when shear instability mixing is included. A simulation performed using isopycnic coordinates to emulate the Miami Isopycnic Coordinate Ocean Model (MICOM), which uses Kraus-Turner mixing without penetrating shortwave radiation and shear instability mixing, demonstrates that the advantages of switching from isopycnic to hybrid coordinates and including more sophisticated turbulence closures outweigh the negative numerical effects of maintaining hybrid vertical coordinates.

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…

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.

Design Optimization of Hybrid FRP/RC Bridge

Science.gov (United States)

Papapetrou, Vasileios S.; Tamijani, Ali Y.; Brown, Jeff; Kim, Daewon

2018-04-01

The hybrid bridge consists of a Reinforced Concrete (RC) slab supported by U-shaped Fiber Reinforced Polymer (FRP) girders. Previous studies on similar hybrid bridges constructed in the United States and Europe seem to substantiate these hybrid designs for lightweight, high strength, and durable highway bridge construction. In the current study, computational and optimization analyses were carried out to investigate six composite material systems consisting of E-glass and carbon fibers. Optimization constraints are determined by stress, deflection and manufacturing requirements. Finite Element Analysis (FEA) and optimization software were utilized, and a framework was developed to run the complete analyses in an automated fashion. Prior to that, FEA validation of previous studies on similar U-shaped FRP girders that were constructed in Poland and Texas is presented. A finer optimization analysis is performed for the case of the Texas hybrid bridge. The optimization outcome of the hybrid FRP/RC bridge shows the appropriate composite material selection and cross-section geometry that satisfies all the applicable Limit States (LS) and, at the same time, results in the lightest design. Critical limit states show that shear stress criteria determine the optimum design for bridge spans less than 15.24 m and deflection criteria controls for longer spans. Increased side wall thickness can reduce maximum observed shear stresses, but leads to a high weight penalty. A taller cross-section and a thicker girder base can efficiently lower the observed deflections and normal stresses. Finally, substantial weight savings can be achieved by the optimization framework if base and side-wall thickness are treated as independent variables.

An investigation into the reduction of log-layer mismatch in wall-modeled LES with a hybrid RANS/LES approach

Science.gov (United States)

Balin, Riccardo; Spalart, Philippe R.; Jansen, Kenneth E.

2017-11-01

Hybrid RANS/LES modeling approaches used in the context of wall-modeled LES (WMLES) of channel flows and boundary layers often suffer from a mismatch in the RANS and LES log-layer intercepts of the mean velocity profile. In the vicinity of the interface between the RANS and LES regions, the mean velocity gradient is too steep causing a departure from the log-law, an over-prediction of the velocity in the outer layer and an under-prediction of the skin-friction. This steep gradient is attributed to inadequate modeled Reynolds stresses in the upper portion of the RANS layer and at the interface. Channel flow computations were carried out with the IDDES approach of Shur et al. in WMLES mode based on the Spalart-Allmaras RANS model. This talk investigates the robustness of this approach for unstructured grids and explores changes required for grids where insufficient elevation of the Reynolds stresses is observed. Awards of computer time were provided by Innovative and Novel Computational Impact on Theory and Experiment (INCITE) and Early Science programs. Resources of the Argonne Leadership Computing Facility, a DOE Office of Science User Facility, were used.

Parametric optimization and design validation based on finite element analysis of hybrid socket adapter for transfemoral prosthetic knee.

Science.gov (United States)

Kumar, Neelesh

2014-10-01

Finite element analysis has been universally employed for the stress and strain analysis in lower extremity prosthetics. The socket adapter was the principal subject of interest due to its importance in deciding the knee motion range. This article focused on the static and dynamic stress analysis of the designed hybrid adapter developed by the authors. A standard mechanical design validation approach using von Mises was followed. Four materials were considered for the analysis, namely, carbon fiber, oil-filled nylon, Al-6061, and mild steel. The paper analyses the static and dynamic stress on designed hybrid adapter which incorporates features of conventional male and female socket adapters. The finite element analysis was carried out for possible different angles of knee flexion simulating static and dynamic gait situation. Research was carried out on available design of socket adapter. Mechanical design of hybrid adapter was conceptualized and a CAD model was generated using Inventor modelling software. Static and dynamic stress analysis was carried out on different materials for optimization. The finite element analysis was carried out on the software Autodesk Inventor Professional Ver. 2011. The peak value of von Mises stress occurred in the neck region of the adapter and in the lower face region at rod eye-adapter junction in static and dynamic analyses, respectively. Oil-filled nylon was found to be the best material among the four with respect to strength, weight, and cost. Research investigations on newer materials for development of improved prosthesis will immensely benefit the amputees. The study analyze the static and dynamic stress on the knee joint adapter to provide better material used for hybrid design of adapter. © The International Society for Prosthetics and Orthotics 2013.

Fluid Survival Tool: A Model Checker for Hybrid Petri Nets

NARCIS (Netherlands)

Postema, Björn Frits; Remke, Anne Katharina Ingrid; Haverkort, Boudewijn R.H.M.; Ghasemieh, Hamed

2014-01-01

Recently, algorithms for model checking Stochastic Time Logic (STL) on Hybrid Petri nets with a single general one-shot transition (HPNG) have been introduced. This paper presents a tool for model checking HPNG models against STL formulas. A graphical user interface (GUI) not only helps to

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.

Hybrid ATDL-gamma distribution model for predicting area source acid gas concentrations

Energy Technology Data Exchange (ETDEWEB)

Jakeman, A J; Taylor, J A

1985-01-01

An air quality model is developed to predict the distribution of concentrations of acid gas in an urban airshed. The model is hybrid in character, combining reliable features of a deterministic ATDL-based model with statistical distributional approaches. The gamma distribution was identified from a range of distributional models as the best model. The paper shows that the assumptions of a previous hybrid model may be relaxed and presents a methodology for characterizing the uncertainty associated with model predictions. Results are demonstrated for the 98-percentile predictions of 24-h average data over annual periods at six monitoring sites. This percentile relates to the World Health Organization goal for acid gas concentrations.

A computational model for lower hybrid current drive

International Nuclear Information System (INIS)

Englade, R.C.; Bonoli, P.T.; Porkolab, M.

1983-01-01

A detailed simulation model for lower hybrid (LH) current drive in toroidal devices is discussed. This model accounts reasonably well for the magnitude of radio frequency (RF) current observed in the PLT and Alcator C devices. It also reproduces the experimental dependencies of RF current generation on toroidal magnetic field and has provided insights about mechanisms which may underlie the observed density limit of current drive. (author)

Hierarchical models and iterative optimization of hybrid systems

Energy Technology Data Exchange (ETDEWEB)

Rasina, Irina V. [Ailamazyan Program Systems Institute, Russian Academy of Sciences, Peter One str. 4a, Pereslavl-Zalessky, 152021 (Russian Federation); Baturina, Olga V. [Trapeznikov Control Sciences Institute, Russian Academy of Sciences, Profsoyuznaya str. 65, 117997, Moscow (Russian Federation); Nasatueva, Soelma N. [Buryat State University, Smolina str.24a, Ulan-Ude, 670000 (Russian Federation)

2016-06-08

A class of hybrid control systems on the base of two-level discrete-continuous model is considered. The concept of this model was proposed and developed in preceding works as a concretization of the general multi-step system with related optimality conditions. A new iterative optimization procedure for such systems is developed on the base of localization of the global optimality conditions via contraction the control set.

Effects of natural hybrid and non-hybrid Epichloë endophytes on the response of Hordelymus europaeus to drought stress.

Science.gov (United States)

Oberhofer, Martina; Güsewell, Sabine; Leuchtmann, Adrian

2014-01-01

Interspecific hybrid endophytes of the genus Epichloë (Ascomycota, Clavicipitaceae) are prevalent in wild grass populations, possibly because of their larger gene variation, resulting in increased fitness benefits for host plants; however, the reasons are not yet known. We tested hypotheses regarding niche expansion mediated by hybrid endophytes, population-dependent interactions and local co-adaptation in the woodland grass Hordelymus europaeus, which naturally hosts both hybrid and non-hybrid endophyte taxa. Seedlings derived from seeds of four grass populations made endophyte free were re-inoculated with hybrid or non-hybrid endophyte strains, or left endophyte free. Plants were grown in the glasshouse with or without drought treatment. Endophyte infection increased plant biomass and tiller production by 10-15% in both treatments. Endophyte types had similar effects on growth, but opposite effects on reproduction: non-hybrid endophytes increased seed production, whereas hybrid endophytes reduced or prevented it completely. The results are consistent with the observation that non-hybrid endophytes in H. europaeus prevail at dry sites, but cannot explain the prevalence of hybrid endophytes. Thus, our results do not support the hypothesis of niche expansion of hybrid-infected plants. Moreover, plants inoculated with native relative to foreign endophytes yielded higher infections, but both showed similar growth and survival, suggesting weak co-adaptation. © 2013 The Authors. New Phytologist © 2013 New Phytologist Trust.

Kinetics model of bainitic transformation with stress

Science.gov (United States)

Zhou, Mingxing; Xu, Guang; Hu, Haijiang; Yuan, Qing; Tian, Junyu

2018-01-01

Thermal simulations were conducted on a Gleeble 3800 simulator. The main purpose is to investigate the effects of stress on the kinetics of bainitic transformation in a Fe-C-Mn-Si advanced high strength bainitic steel. Previous studies on modeling the kinetics of stress affected bainitic transformation only considered the stress below the yield strength of prior austenite. In the present study, the stress above the yield strength of prior austenite is taken into account. A new kinetics model of bainitic transformation dependent on the stress (including the stresses below and above the yield strength of prior austenite) and the transformation temperature is proposed. The new model presents a good agreement with experimental results. In addition, it is found that the acceleration degree of stress on bainitic transformation increases with the stress whether its magnitude is below or above the yield strength of austenite, but the increasing rate gradually slows down when the stress is above the yield strength of austenite.

The Cheshire Cat principle for hybrid bag models

International Nuclear Information System (INIS)

Nielsen, H.B.

1987-05-01

The Cheshire Cat point of view where the bag in the chiral bag model has no physical significance, but only a notational one is argued for. It is explained how a fermion - in, say, a 1+1 dimensional exact Cheshire Cat model - escapes the bag by means of an anomaly. The possibility to construct sophisticated hybrid bag models is suggested which use the lack of physical significance of the bag to fix the many parameters so as to anyway give hope of a phenomenologically sensible model. (orig.)

A control-oriented cycle-life model for hybrid electric vehicle lithium-ion batteries

International Nuclear Information System (INIS)

Suri, Girish; Onori, Simona

2016-01-01

In this paper, a semi-empirical Lithium-iron phosphate-graphite battery aging model is identified over data mimicking actual cycling conditions that a hybrid electric vehicle battery encounters under real driving scenarios. The aging model is then used to construct the severity factor map, used to characterize relative aging of the battery under different operating conditions. This is used as a battery degradation criterion within a multi-objective optimization problem where battery aging minimization is to be achieved along with fuel consumption minimization. The method proposed is general and can be applied to other battery chemistry as well as different vehicular applications. Finally, simulations conducted using a hybrid electric vehicle simulator show how the two modeling tools developed in this paper, i.e., the severity factor map and the aging model, can be effectively used in a multi-objective optimization problem to predict and control battery degradation. - Highlights: • Battery aging model for hybrid electric vehicles using real driving conditions data. • Development of a modeling tool to assess battery degradation for real time optimization. • "3"1P NMR analysis of an enzyme-treated extract showed expected hydrolysis of P forms. • Development of an energy management strategy to minimize battery degradation. • Simulation results from hybrid electric vehicle simulator.

Modeling and Simulation of Multi-scale Environmental Systems with Generalized Hybrid Petri Nets

Directory of Open Access Journals (Sweden)

Mostafa eHerajy

2015-07-01

Full Text Available Predicting and studying the dynamics and properties of environmental systems necessitates the construction and simulation of mathematical models entailing different levels of complexities. Such type of computational experiments often require the combination of discrete and continuous variables as well as processes operating at different time scales. Furthermore, the iterative steps of constructing and analyzing environmental models might involve researchers with different background. Hybrid Petri nets may contribute in overcoming such challenges as they facilitate the implementation of systems integrating discrete and continuous dynamics. Additionally, the visual depiction of model components will inevitably help to bridge the gap between scientists with distinct expertise working on the same problem. Thus, modeling environmental systems with hybrid Petri nets enables the construction of complex processes while keeping the models comprehensible for researchers working on the same project with significantly divergent education path. In this paper we propose the utilization of a special class of hybrid Petri nets, Generalized Hybrid Petri Nets (GHPN, to model and simulate environmental systems exposing processes interacting at different time-scales. GHPN integrate stochastic and deterministic semantics as well as other types of special basic events. Moreover, a case study is presented to illustrate the use of GHPN in constructing and simulating multi-timescale environmental scenarios.

Static stiffness modeling of a novel hybrid redundant robot machine

International Nuclear Information System (INIS)

Li Ming; Wu Huapeng; Handroos, Heikki

2011-01-01

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.

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 ... evolutionary algorithms (HEA) proved to be highly applica- ble to the hypertrophic reservoirs of South Africa. .... discovered and optimised using a large-scale parallel computational device and relevant soft-.

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.

Complete modeling and software implementation of a virtual solar hydrogen hybrid system

International Nuclear Information System (INIS)

Pedrazzi, S.; Zini, G.; Tartarini, P.

2010-01-01

A complete mathematical model and software implementation of a solar hydrogen hybrid system has been developed and applied to real data. The mathematical model has been derived from sub-models taken from literature with appropriate modifications and improvements. The model has been implemented as a stand-alone virtual energy system in a model-based, multi-domain software environment. A test run has then been performed on typical residential user data-sets over a year-long period. Results show that the virtual hybrid system can bring about complete grid independence; in particular, hydrogen production balance is positive (+1.25 kg) after a year's operation with a system efficiency of 7%.

Deep Belief Network Based Hybrid Model for Building Energy Consumption Prediction

Directory of Open Access Journals (Sweden)

Chengdong Li

2018-01-01

Full Text Available To enhance the prediction performance for building energy consumption, this paper presents a modified deep belief network (DBN based hybrid model. The proposed hybrid model combines the outputs from the DBN model with the energy-consuming pattern to yield the final prediction results. The energy-consuming pattern in this study represents the periodicity property of building energy consumption and can be extracted from the observed historical energy consumption data. The residual data generated by removing the energy-consuming pattern from the original data are utilized to train the modified DBN model. The training of the modified DBN includes two steps, the first one of which adopts the contrastive divergence (CD algorithm to optimize the hidden parameters in a pre-train way, while the second one determines the output weighting vector by the least squares method. The proposed hybrid model is applied to two kinds of building energy consumption data sets that have different energy-consuming patterns (daily-periodicity and weekly-periodicity. In order to examine the advantages of the proposed model, four popular artificial intelligence methods—the backward propagation neural network (BPNN, the generalized radial basis function neural network (GRBFNN, the extreme learning machine (ELM, and the support vector regressor (SVR are chosen as the comparative approaches. Experimental results demonstrate that the proposed DBN based hybrid model has the best performance compared with the comparative techniques. Another thing to be mentioned is that all the predictors constructed by utilizing the energy-consuming patterns perform better than those designed only by the original data. This verifies the usefulness of the incorporation of the energy-consuming patterns. The proposed approach can also be extended and applied to some other similar prediction problems that have periodicity patterns, e.g., the traffic flow forecasting and the electricity consumption

Post-traumatic stress disorder and beyond: an overview of rodent stress models.

Science.gov (United States)

Schöner, Johanna; Heinz, Andreas; Endres, Matthias; Gertz, Karen; Kronenberg, Golo

2017-10-01

Post-traumatic stress disorder (PTSD) is a psychiatric disorder of high prevalence and major socioeconomic impact. Patients suffering from PTSD typically present intrusion and avoidance symptoms and alterations in arousal, mood and cognition that last for more than 1 month. Animal models are an indispensable tool to investigate underlying pathophysiological pathways and, in particular, the complex interplay of neuroendocrine, genetic and environmental factors that may be responsible for PTSD induction. Since the 1960s, numerous stress paradigms in rodents have been developed, based largely on Seligman's seminal formulation of 'learned helplessness' in canines. Rodent stress models make use of physiological or psychological stressors such as foot shock, underwater trauma, social defeat, early life stress or predator-based stress. Apart from the brief exposure to an acute stressor, chronic stress models combining a succession of different stressors for a period of several weeks have also been developed. Chronic stress models in rats and mice may elicit characteristic PTSD-like symptoms alongside, more broadly, depressive-like behaviours. In this review, the major existing rodent models of PTSD are reviewed in terms of validity, advantages and limitations; moreover, significant results and implications for future research-such as the role of FKBP5, a mediator of the glucocorticoid stress response and promising target for therapeutic interventions-are discussed. © 2017 The Authors. Journal of Cellular and Molecular Medicine published by John Wiley & Sons Ltd and Foundation for Cellular and Molecular Medicine.

Simulation-optimization framework for multi-site multi-season hybrid stochastic streamflow modeling

Science.gov (United States)

Srivastav, Roshan; Srinivasan, K.; Sudheer, K. P.

2016-11-01

A simulation-optimization (S-O) framework is developed for the hybrid stochastic modeling of multi-site multi-season streamflows. The multi-objective optimization model formulated is the driver and the multi-site, multi-season hybrid matched block bootstrap model (MHMABB) is the simulation engine within this framework. The multi-site multi-season simulation model is the extension of the existing single-site multi-season simulation model. A robust and efficient evolutionary search based technique, namely, non-dominated sorting based genetic algorithm (NSGA - II) is employed as the solution technique for the multi-objective optimization within the S-O framework. The objective functions employed are related to the preservation of the multi-site critical deficit run sum and the constraints introduced are concerned with the hybrid model parameter space, and the preservation of certain statistics (such as inter-annual dependence and/or skewness of aggregated annual flows). The efficacy of the proposed S-O framework is brought out through a case example from the Colorado River basin. The proposed multi-site multi-season model AMHMABB (whose parameters are obtained from the proposed S-O framework) preserves the temporal as well as the spatial statistics of the historical flows. Also, the other multi-site deficit run characteristics namely, the number of runs, the maximum run length, the mean run sum and the mean run length are well preserved by the AMHMABB model. Overall, the proposed AMHMABB model is able to show better streamflow modeling performance when compared with the simulation based SMHMABB model, plausibly due to the significant role played by: (i) the objective functions related to the preservation of multi-site critical deficit run sum; (ii) the huge hybrid model parameter space available for the evolutionary search and (iii) the constraint on the preservation of the inter-annual dependence. Split-sample validation results indicate that the AMHMABB model is

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...

Non-Poisson counting statistics of a hybrid G-M counter dead time model

International Nuclear Information System (INIS)

Lee, Sang Hoon; Jae, Moosung; Gardner, Robin P.

2007-01-01

The counting statistics of a G-M counter with a considerable dead time event rate deviates from Poisson statistics. Important characteristics such as observed counting rates as a function true counting rates, variances and interval distributions were analyzed for three dead time models, non-paralyzable, paralyzable and hybrid, with the help of GMSIM, a Monte Carlo dead time effect simulator. The simulation results showed good agreements with the models in observed counting rates and variances. It was found through GMSIM simulations that the interval distribution for the hybrid model showed three distinctive regions, a complete cutoff region for the duration of the total dead time, a degraded exponential and an enhanced exponential regions. By measuring the cutoff and the duration of degraded exponential from the pulse interval distribution, it is possible to evaluate the two dead times in the hybrid model

Coupled thermal model of photovoltaic-thermoelectric hybrid panel for sample cities in Europe

DEFF Research Database (Denmark)

Rezaniakolaei, Alireza; Sera, Dezso; Rosendahl, Lasse Aistrup

2016-01-01

of the hybrid system under different weather conditions. The model takes into account solar irradiation, wind speed and ambient temperature as well as convective and radiated heat losses from the front and rear surfaces of the panel. The model is developed for three sample cities in Europe with different......In general, modeling of photovoltaic-thermoelectric (PV/TEG) hybrid panels have been mostly simplified and disconnected from the actual ambient conditions and thermal losses from the panel. In this study, a thermally coupled model of PV/TEG panel is established to precisely predict performance...... weather conditions. The results show that radiated heat loss from the front surface and the convective heat loss due to the wind speed are the most critical parameters on performance of the hybrid panel performance. The results also indicate that, with existing thermoelectric materials, the power...

Solar central receiver hybrid power system, Phase I. Volume 3. Appendices. Final technical report, October 1978-August 1979

Energy Technology Data Exchange (ETDEWEB)

None

1979-09-01

A design study for a central receiver/fossil fuel hybrid power system using molten salts for heat transfer and heat storage is presented. This volume contains the appendices: (A) parametric salt piping data; (B) sample heat exchanger calculations; (C) salt chemistry and salt/materials compatibility evaluation; (D) heliostat field coordinates; (E) data lists; (F) STEAEC program input data; (G) hybrid receiver design drawings; (H) hybrid receiver absorber tube thermal math model; (I) piping stress analysis; (J) 100-MWe 18-hour storage solar central receiver hybrid power system capital cost worksheets; and (K) 500-MWe 18-hour solar central receiver hybrid power system cost breakdown. (WHK)

Bayesian inference for hybrid discrete-continuous stochastic kinetic models

International Nuclear Information System (INIS)

Sherlock, Chris; Golightly, Andrew; Gillespie, Colin S

2014-01-01

We consider the problem of efficiently performing simulation and inference for stochastic kinetic models. Whilst it is possible to work directly with the resulting Markov jump process (MJP), computational cost can be prohibitive for networks of realistic size and complexity. In this paper, we consider an inference scheme based on a novel hybrid simulator that classifies reactions as either ‘fast’ or ‘slow’ with fast reactions evolving as a continuous Markov process whilst the remaining slow reaction occurrences are modelled through a MJP with time-dependent hazards. A linear noise approximation (LNA) of fast reaction dynamics is employed and slow reaction events are captured by exploiting the ability to solve the stochastic differential equation driving the LNA. This simulation procedure is used as a proposal mechanism inside a particle MCMC scheme, thus allowing Bayesian inference for the model parameters. We apply the scheme to a simple application and compare the output with an existing hybrid approach and also a scheme for performing inference for the underlying discrete stochastic model. (paper)

Performance Modeling of Hybrid MPI/OpenMP Scientific Applications on Large-scale Multicore Cluster Systems

KAUST Repository

Wu, Xingfu; Taylor, Valerie

2011-01-01

In this paper, we present a performance modeling framework based on memory bandwidth contention time and a parameterized communication model to predict the performance of OpenMP, MPI and hybrid applications with weak scaling on three large-scale multicore clusters: IBM POWER4, POWER5+ and Blue Gene/P, and analyze the performance of these MPI, OpenMP and hybrid applications. We use STREAM memory benchmarks to provide initial performance analysis and model validation of MPI and OpenMP applications on these multicore clusters because the measured sustained memory bandwidth can provide insight into the memory bandwidth that a system should sustain on scientific applications with the same amount of workload per core. In addition to using these benchmarks, we also use a weak-scaling hybrid MPI/OpenMP large-scale scientific application: Gyro kinetic Toroidal Code in magnetic fusion to validate our performance model of the hybrid application on these multicore clusters. The validation results for our performance modeling method show less than 7.77% error rate in predicting the performance of hybrid MPI/OpenMP GTC on up to 512 cores on these multicore clusters. © 2011 IEEE.

Performance Modeling of Hybrid MPI/OpenMP Scientific Applications on Large-scale Multicore Cluster Systems

KAUST Repository

Wu, Xingfu

2011-08-01

In this paper, we present a performance modeling framework based on memory bandwidth contention time and a parameterized communication model to predict the performance of OpenMP, MPI and hybrid applications with weak scaling on three large-scale multicore clusters: IBM POWER4, POWER5+ and Blue Gene/P, and analyze the performance of these MPI, OpenMP and hybrid applications. We use STREAM memory benchmarks to provide initial performance analysis and model validation of MPI and OpenMP applications on these multicore clusters because the measured sustained memory bandwidth can provide insight into the memory bandwidth that a system should sustain on scientific applications with the same amount of workload per core. In addition to using these benchmarks, we also use a weak-scaling hybrid MPI/OpenMP large-scale scientific application: Gyro kinetic Toroidal Code in magnetic fusion to validate our performance model of the hybrid application on these multicore clusters. The validation results for our performance modeling method show less than 7.77% error rate in predicting the performance of hybrid MPI/OpenMP GTC on up to 512 cores on these multicore clusters. © 2011 IEEE.

Prediction of residual stress for dissimilar metals welding at nuclear power plants using fuzzy neural network models

International Nuclear Information System (INIS)

Na, Man Gyun; Kim, Jin Weon; Lim, Dong Hyuk

2007-01-01

A fuzzy neural network model is presented to predict residual stress for dissimilar metal welding under various welding conditions. The fuzzy neural network model, which consists of a fuzzy inference system and a neuronal training system, is optimized by a hybrid learning method that combines a genetic algorithm to optimize the membership function parameters and a least squares method to solve the consequent parameters. The data of finite element analysis are divided into four data groups, which are split according to two end-section constraints and two prediction paths. Four fuzzy neural network models were therefore applied to the numerical data obtained from the finite element analysis for the two end-section constraints and the two prediction paths. The fuzzy neural network models were trained with the aid of a data set prepared for training (training data), optimized by means of an optimization data set and verified by means of a test data set that was different (independent) from the training data and the optimization data. The accuracy of fuzzy neural network models is known to be sufficiently accurate for use in an integrity evaluation by predicting the residual stress of dissimilar metal welding zones

Strain-rate dependence for Ni/Al hybrid foams

Directory of Open Access Journals (Sweden)

Jung Anne

2015-01-01

Full Text Available Shock absorption often needs stiff but lightweight materials that exhibit a large kinetic energy absorption capability. Open-cell metal foams are artificial structures, which due to their plateau stress, including a strong hysteresis, can in principle absorb large amounts of energy. However, their plateau stress is too low for many applications. In this study, we use highly novel and promising Ni/Al hybrid foams which consist of standard, open-cell aluminium foams, where nanocrystalline nickel is deposited by electrodeposition as coating on the strut surface. The mechanical behaviour of cellular materials, including their behaviour under higher strain-rates, is governed by their microstructure due to the properties of the strut material, pore/strut geometry and mass distribution over the struts. Micro-inertia effects are strongly related to the microstructure. For a conclusive model, the exact real microstructure is needed. In this study a micro-focus computer tomography (μCT system has been used for the analysis of the microstructure of the foam samples and for the development of a microstructural Finite Element (micro-FE mesh. The microstructural FE models have been used to model the mechanical behaviour of the Ni/Al hybrid foams under dynamic loading conditions. The simulations are validated by quasi-static compression tests and dynamic split Hopkinson pressure bar tests.

HYBRID WAYS OF DOING: A MODEL FOR TEACHING PUBLIC SPACE

Directory of Open Access Journals (Sweden)

Gabrielle Bendiner-Viani

2010-07-01

Full Text Available This paper addresses an exploratory practice undertaken by the authors in a co-taught class to hybridize theory, research and practice. This experiment in critical transdisciplinary design education took the form of a “critical studio + practice-based seminar on public space”, two interlinked classes co-taught by landscape architect Elliott Maltby and environmental psychologist Gabrielle Bendiner-Viani at the Parsons, The New School for Design. This design process was grounded in the political and social context of the contested East River waterfront of New York City and valued both intensive study (using a range of social science and design methods and a partnership with a local community organization, engaging with the politics, issues and human needs of a complex site. The paper considers how we encouraged interdisciplinary collaboration and dialogue between teachers as well as between liberal arts and design students and developed strategies to overcome preconceived notions of traditional “studio” and “seminar” work. By exploring the challenges and adjustments made during the semester and the process of teaching this class, this paper addresses how we moved from a model of intertwining theory, research and practice, to a hybrid model of multiple ways of doing, a model particularly apt for teaching public space. Through examples developed for and during our course, the paper suggests practical ways of supporting this transdisciplinary hybrid model.

Hybrid Modeling Improves Health and Performance Monitoring

Science.gov (United States)

2007-01-01

Scientific Monitoring Inc. was awarded a Phase I Small Business Innovation Research (SBIR) project by NASA's Dryden Flight Research Center to create a new, simplified health-monitoring approach for flight vehicles and flight equipment. The project developed a hybrid physical model concept that provided a structured approach to simplifying complex design models for use in health monitoring, allowing the output or performance of the equipment to be compared to what the design models predicted, so that deterioration or impending failure could be detected before there would be an impact on the equipment's operational capability. Based on the original modeling technology, Scientific Monitoring released I-Trend, a commercial health- and performance-monitoring software product named for its intelligent trending, diagnostics, and prognostics capabilities, as part of the company's complete ICEMS (Intelligent Condition-based Equipment Management System) suite of monitoring and advanced alerting software. I-Trend uses the hybrid physical model to better characterize the nature of health or performance alarms that result in "no fault found" false alarms. Additionally, the use of physical principles helps I-Trend identify problems sooner. I-Trend technology is currently in use in several commercial aviation programs, and the U.S. Air Force recently tapped Scientific Monitoring to develop next-generation engine health-management software for monitoring its fleet of jet engines. Scientific Monitoring has continued the original NASA work, this time under a Phase III SBIR contract with a joint NASA-Pratt & Whitney aviation security program on propulsion-controlled aircraft under missile-damaged aircraft conditions.

The influence of nonlocal hybridization on ground-state properties of the Falicov-Kimball model

International Nuclear Information System (INIS)

Farkasovsky, Pavol

2005-01-01

The density matrix renormalization group is used to examine effects of nonlocal hybridization on ground-state properties of the Falicov-Kimball model (FKM) in one dimension. Special attention is devoted to the problem of hybridization-induced insulator-metal transition. It is shown that the picture of insulator-metal transitions found for the FKM with nonlocal hybridization strongly differs from one found for the FKM without hybridization (as well as with local hybridization). The effect of nonlocal hybridization is so strong that it can induce the insulator-metal transition, even in the half-filled band case where the ground states of the FKM without hybridization are insulating for all finite Coulomb interactions. Outside the half-filled band case the metal-insulator transition driven by pressure is found for finite values of nonlocal hybridization

Effect of platform connection and abutment material on stress distribution in single anterior implant-supported restorations: a nonlinear 3-dimensional finite element analysis.

Science.gov (United States)

Carvalho, Marco Aurélio; Sotto-Maior, Bruno Salles; Del Bel Cury, Altair Antoninha; Pessanha Henriques, Guilherme Elias

2014-11-01

Although various abutment connections and materials have recently been introduced, insufficient data exist regarding the effect of stress distribution on their mechanical performance. The purpose of this study was to investigate the effect of different abutment materials and platform connections on stress distribution in single anterior implant-supported restorations with the finite element method. Nine experimental groups were modeled from the combination of 3 platform connections (external hexagon, internal hexagon, and Morse tapered) and 3 abutment materials (titanium, zirconia, and hybrid) as follows: external hexagon-titanium, external hexagon-zirconia, external hexagon-hybrid, internal hexagon-titanium, internal hexagon-zirconia, internal hexagon-hybrid, Morse tapered-titanium, Morse tapered-zirconia, and Morse tapered-hybrid. Finite element models consisted of a 4×13-mm implant, anatomic abutment, and lithium disilicate central incisor crown cemented over the abutment. The 49 N occlusal loading was applied in 6 steps to simulate the incisal guidance. Equivalent von Mises stress (σvM) was used for both the qualitative and quantitative evaluation of the implant and abutment in all the groups and the maximum (σmax) and minimum (σmin) principal stresses for the numerical comparison of the zirconia parts. The highest abutment σvM occurred in the Morse-tapered groups and the lowest in the external hexagon-hybrid, internal hexagon-titanium, and internal hexagon-hybrid groups. The σmax and σmin values were lower in the hybrid groups than in the zirconia groups. The stress distribution concentrated in the abutment-implant interface in all the groups, regardless of the platform connection or abutment material. The platform connection influenced the stress on abutments more than the abutment material. The stress values for implants were similar among different platform connections, but greater stress concentrations were observed in internal connections

An Advanced Environment for Hybrid Modeling of Biological Systems Based on Modelica

Directory of Open Access Journals (Sweden)

Proß Sabrina

2011-03-01

Full Text Available Biological systems are often very complex so that an appropriate formalism is needed for modeling their behavior. Hybrid Petri Nets, consisting of time-discrete Petri Net elements as well as continuous ones, have proven to be ideal for this task. Therefore, a new Petri Net library was implemented based on the object-oriented modeling language Modelica which allows the modeling of discrete, stochastic and continuous Petri Net elements by differential, algebraic and discrete equations. An appropriate Modelica-tool performs the hybrid simulation with discrete events and the solution of continuous differential equations. A special sub-library contains so-called wrappers for specific reactions to simplify the modeling process.

Thermal modeling of a hydraulic hybrid vehicle transmission based on thermodynamic analysis

International Nuclear Information System (INIS)

Kwon, Hyukjoon; Sprengel, Michael; Ivantysynova, Monika

2016-01-01

Hybrid vehicles have become a popular alternative to conventional powertrain architectures by offering improved fuel efficiency along with a range of environmental benefits. Hydraulic Hybrid Vehicles (HHV) offer one approach to hybridization with many benefits over competing technologies. Among these benefits are lower component costs, more environmentally friendly construction materials, and the ability to recover a greater quantity of energy during regenerative braking which make HHVs partially well suited to urban environments. In order to further the knowledge base regarding HHVs, this paper explores the thermodynamic characteristics of such a system. A system model is detailed for both the hydraulic and thermal components of a closed circuit hydraulic hybrid transmission following the FTP-72 driving cycle. Among the new techniques proposed in this paper is a novel method for capturing rapid thermal transients. This paper concludes by comparing the results of this model with experimental data gathered on a Hardware-in-the-Loop (HIL) transmission dynamometer possessing the same architecture, components, and driving cycle used within the simulation model. This approach can be used for several applications such as thermal stability analysis of HHVs, optimal thermal management, and analysis of the system's thermodynamic efficiency. - Highlights: • Thermal modeling for HHVs is introduced. • A model for the hydraulic and thermal system is developed for HHVs. • A novel method for capturing rapid thermal transients is proposed. • The thermodynamic system diagram of a series HHV is predicted.

Hybrid Scheme for Modeling Local Field Potentials from Point-Neuron Networks.

Science.gov (United States)

Hagen, Espen; Dahmen, David; Stavrinou, Maria L; Lindén, Henrik; Tetzlaff, Tom; van Albada, Sacha J; Grün, Sonja; Diesmann, Markus; Einevoll, Gaute T

2016-12-01

With rapidly advancing multi-electrode recording technology, the local field potential (LFP) has again become a popular measure of neuronal activity in both research and clinical applications. Proper understanding of the LFP requires detailed mathematical modeling incorporating the anatomical and electrophysiological features of neurons near the recording electrode, as well as synaptic inputs from the entire network. Here we propose a hybrid modeling scheme combining efficient point-neuron network models with biophysical principles underlying LFP generation by real neurons. The LFP predictions rely on populations of network-equivalent multicompartment neuron models with layer-specific synaptic connectivity, can be used with an arbitrary number of point-neuron network populations, and allows for a full separation of simulated network dynamics and LFPs. We apply the scheme to a full-scale cortical network model for a ∼1 mm 2 patch of primary visual cortex, predict laminar LFPs for different network states, assess the relative LFP contribution from different laminar populations, and investigate effects of input correlations and neuron density on the LFP. The generic nature of the hybrid scheme and its public implementation in hybridLFPy form the basis for LFP predictions from other and larger point-neuron network models, as well as extensions of the current application with additional biological detail. © The Author 2016. Published by Oxford University Press.

Model-based design approaches for plug-in hybrid vehicle design

Energy Technology Data Exchange (ETDEWEB)

Mendes, C.J. [CrossChasm Technologies, Cambridge, ON (Canada); Stevens, M.B.; Fowler, M.W. [Waterloo Univ., ON (Canada). Dept. of Chemical Engineering; Fraser, R.A. [Waterloo Univ., ON (Canada). Dept. of Mechanical Engineering; Wilhelm, E.J. [Paul Scherrer Inst., Villigen (Switzerland). Energy Systems Analysis

2007-07-01

A model-based design process for plug-in hybrid vehicles (PHEVs) was presented. The paper discussed steps between the initial design concept and a working vehicle prototype, and focused on an investigation of the software-in-the-loop (SIL), hardware-in-the-loop (HIL), and component-in-the-loop (CIL) design phases. The role and benefits of using simulation were also reviewed. A method for mapping and identifying components was provided along with a hybrid control strategy and component-level control optimization process. The role of simulation in component evaluation, architecture design, and de-bugging procedures was discussed, as well as the role simulation networks can play in speeding deployment times. The simulations focused on work performed on a 2005 Chevrolet Equinox converted to a fuel cell hybrid electric vehicle (FCHEV). Components were aggregated to create a complete virtual vehicle. A simplified vehicle model was implemented onto the on-board vehicle control hardware. Optimization metrics were estimated at 10 alpha values during each control loop iteration. The simulation was then used to tune the control system under a variety of drive cycles and conditions. A CIL technique was used to place a physical hybrid electric vehicle (HEV) component under the control of a real time HEV/PHEV simulation. It was concluded that controllers should have a standardized component description that supports integration into advanced testing procedures. 4 refs., 9 figs.

Improving Hybrid III injury assessment in steering wheel rim to chest impacts using responses from finite element Hybrid III and human body model.

Science.gov (United States)

Holmqvist, Kristian; Davidsson, Johan; Mendoza-Vazquez, Manuel; Rundberget, Peter; Svensson, Mats Y; Thorn, Stefan; Törnvall, Fredrik

2014-01-01

The main aim of this study was to improve the quality of injury risk assessments in steering wheel rim to chest impacts when using the Hybrid III crash test dummy in frontal heavy goods vehicle (HGV) collision tests. Correction factors for chest injury criteria were calculated as the model chest injury parameter ratios between finite element (FE) Hybrid III, evaluated in relevant load cases, and the Total Human Model for Safety (THUMS). This is proposed to be used to compensate Hybrid III measurements in crash tests where steering wheel rim to chest impacts occur. The study was conducted in an FE environment using an FE-Hybrid III model and the THUMS. Two impactor shapes were used, a circular hub and a long, thin horizontal bar. Chest impacts at velocities ranging from 3.0 to 6.0 m/s were simulated at 3 impact height levels. A ratio between FE-Hybrid III and THUMS chest injury parameters, maximum chest compression C max, and maximum viscous criterion VC max, were calculated for the different chest impact conditions to form a set of correction factors. The definition of the correction factor is based on the assumption that the response from a circular hub impact to the middle of the chest is well characterized and that injury risk measures are independent of impact height. The current limits for these chest injury criteria were used as a basis to develop correction factors that compensate for the limitations in biofidelity of the Hybrid III in steering wheel rim to chest impacts. The hub and bar impactors produced considerably higher C max and VC max responses in the THUMS compared to the FE-Hybrid III. The correction factor for the responses of the FE-Hybrid III showed that the criteria responses for the bar impactor were consistently overestimated. Ratios based on Hybrid III and THUMS responses provided correction factors for the Hybrid III responses ranging from 0.84 to 0.93. These factors can be used to estimate C max and VC max values when the Hybrid III is

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.

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.

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.

Hybrid Computational Model for High-Altitude Aeroassist Vehicles, Phase I

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...

A Hybrid Model for Forecasting Sales in Turkish Paint Industry

Directory of Open Access Journals (Sweden)

Alp Ustundag

2009-12-01

Full Text Available Sales forecasting is important for facilitating effective and efficient allocation of scarce resources. However, how to best model and forecast sales has been a long-standing issue. There is no best forecasting method that is applicable in all circumstances. Therefore, confidence in the accuracy of sales forecasts is achieved by corroborating the results using two or more methods. This paper proposes a hybrid forecasting model that uses an artificial intelligence method (AI with multiple linear regression (MLR to predict product sales for the largest Turkish paint producer. In the hybrid model, three different AI methods, fuzzy rule-based system (FRBS, artificial neural network (ANN and adaptive neuro fuzzy network (ANFIS, are used and compared to each other. The results indicate that FRBS yields better forecasting accuracy in terms of root mean squared error (RMSE and mean absolute percentage error (MAPE.

Optimization of ultrasonic array inspections using an efficient hybrid model and real crack shapes

Energy Technology Data Exchange (ETDEWEB)

Felice, Maria V., E-mail: maria.felice@bristol.ac.uk [Department of Mechanical Engineering, University of Bristol, Bristol, U.K. and NDE Laboratory, Rolls-Royce plc., Bristol (United Kingdom); Velichko, Alexander, E-mail: p.wilcox@bristol.ac.uk; Wilcox, Paul D., E-mail: p.wilcox@bristol.ac.uk [Department of Mechanical Engineering, University of Bristol, Bristol (United Kingdom); Barden, Tim; Dunhill, Tony [NDE Laboratory, Rolls-Royce plc., Bristol (United Kingdom)

2015-03-31

Models which simulate the interaction of ultrasound with cracks can be used to optimize ultrasonic array inspections, but this approach can be time-consuming. To overcome this issue an efficient hybrid model is implemented which includes a finite element method that requires only a single layer of elements around the crack shape. Scattering Matrices are used to capture the scattering behavior of the individual cracks and a discussion on the angular degrees of freedom of elastodynamic scatterers is included. Real crack shapes are obtained from X-ray Computed Tomography images of cracked parts and these shapes are inputted into the hybrid model. The effect of using real crack shapes instead of straight notch shapes is demonstrated. An array optimization methodology which incorporates the hybrid model, an approximate single-scattering relative noise model and the real crack shapes is then described.

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 ... and increasing the rated power of the wind energy conversion system (WECS) or solar ... a 70% reduction in gas emissions and an 80% reduction in energy costs.

Modeling and performance analysis of a concentrated photovoltaic–thermoelectric hybrid power generation system

International Nuclear Information System (INIS)

Lamba, Ravita; Kaushik, S.C.

2016-01-01

Highlights: • Thermodynamic model of concentrated photovoltaic–thermoelectric system is analysed. • Thomson effect reduces the power output of PV, TE and hybrid PV–TEG system. • Effect of thermocouple number, irradiance, PV and TE current have been studied. • The optimum concentration ratio for maximum power output has been found out. • The overall efficiency and power output of hybrid PV–TEG system has been improved. - Abstract: In this study, a thermodynamic model for analysing the performance of a concentrated photovoltaic–thermoelectric generator (CPV–TEG) hybrid system including Thomson effect in conjunction with Seebeck, Joule and Fourier heat conduction effects has been developed and simulated in MATALB environment. The expressions for calculating the temperature of photovoltaic (PV) module, hot and cold sides of thermoelectric (TE) module are derived analytically as well. The effect of concentration ratio, number of thermocouples in TE module, solar irradiance, PV module current and TE module current on power output and efficiency of the PV, TEG and hybrid PV–TEG system have been studied. The optimum concentration ratio corresponding to maximum power output of the hybrid system has been found out. It has been observed that by considering Thomson effect in TEG module, the power output of the PV, TE and hybrid PV–TEG systems decreases and at C = 1 and 5, it reduces the power output of hybrid system by 0.7% and 4.78% respectively. The results of this study may provide basis for performance optimization of a practical irreversible CPV–TEG hybrid system.

Modeling Hybridization Kinetics of Gene Probes in a DNA Biochip Using FEMLAB

Science.gov (United States)

Munir, Ahsan; Waseem, Hassan; Williams, Maggie R.; Stedtfeld, Robert D.; Gulari, Erdogan; Tiedje, James M.; Hashsham, Syed A.

2017-01-01

Microfluidic DNA biochips capable of detecting specific DNA sequences are useful in medical diagnostics, drug discovery, food safety monitoring and agriculture. They are used as miniaturized platforms for analysis of nucleic acids-based biomarkers. Binding kinetics between immobilized single stranded DNA on the surface and its complementary strand present in the sample are of interest. To achieve optimal sensitivity with minimum sample size and rapid hybridization, ability to predict the kinetics of hybridization based on the thermodynamic characteristics of the probe is crucial. In this study, a computer aided numerical model for the design and optimization of a flow-through biochip was developed using a finite element technique packaged software tool (FEMLAB; package included in COMSOL Multiphysics) to simulate the transport of DNA through a microfluidic chamber to the reaction surface. The model accounts for fluid flow, convection and diffusion in the channel and on the reaction surface. Concentration, association rate constant, dissociation rate constant, recirculation flow rate, and temperature were key parameters affecting the rate of hybridization. The model predicted the kinetic profile and signal intensities of eighteen 20-mer probes targeting vancomycin resistance genes (VRGs). Predicted signal intensities and hybridization kinetics strongly correlated with experimental data in the biochip (R2 = 0.8131). PMID:28555058

Modeling Hybridization Kinetics of Gene Probes in a DNA Biochip Using FEMLAB

Directory of Open Access Journals (Sweden)

Ahsan Munir

2017-05-01

Full Text Available Microfluidic DNA biochips capable of detecting specific DNA sequences are useful in medical diagnostics, drug discovery, food safety monitoring and agriculture. They are used as miniaturized platforms for analysis of nucleic acids-based biomarkers. Binding kinetics between immobilized single stranded DNA on the surface and its complementary strand present in the sample are of interest. To achieve optimal sensitivity with minimum sample size and rapid hybridization, ability to predict the kinetics of hybridization based on the thermodynamic characteristics of the probe is crucial. In this study, a computer aided numerical model for the design and optimization of a flow-through biochip was developed using a finite element technique packaged software tool (FEMLAB; package included in COMSOL Multiphysics to simulate the transport of DNA through a microfluidic chamber to the reaction surface. The model accounts for fluid flow, convection and diffusion in the channel and on the reaction surface. Concentration, association rate constant, dissociation rate constant, recirculation flow rate, and temperature were key parameters affecting the rate of hybridization. The model predicted the kinetic profile and signal intensities of eighteen 20-mer probes targeting vancomycin resistance genes (VRGs. Predicted signal intensities and hybridization kinetics strongly correlated with experimental data in the biochip (R2 = 0.8131.

Numerical model for the analysis of unbounded prestressed structures using the hybrid type finite element method

International Nuclear Information System (INIS)

Barbieri, R.A.; Gastal, F.P.S.L.; Filho, A.C.

2005-01-01

Unbounded prestressed concrete has a growing importance all over the world and may be an useful technique for the structures involved in the construction of nuclear facilities. The absence of bonding means no strain compatibility so that equations developed for reinforced concrete are no longer valid. Practical estimates about the ultimate stress in the unbounded tendons may be obtained with empirical or numerical methods only. In order to contribute to the understanding on the behaviour of unbounded prestressed concrete members, a numerical model has been developed using a hybrid type finite element formulation for planar frame structures. Instead of short elements, as in the conventional finite element formulation, long elements may be used, improving computational efficiency. A further advantage is that the curvature variation within the element is obtained with higher accuracy if compared to the traditional formulation. This feature is important for unbounded tendons since its stresses depend on the whole member deformation. Second order effects in the planar frame are considered with either Updated or Partially Updated Lagrangian approaches. Instantaneous and time dependent behaviour as well as cyclic loads are considered too. Comparison with experimental results for prestressed concrete beams shows the adequacy of the proposed model. (authors)

Driving-behavior-aware stochastic model predictive control for plug-in hybrid electric buses

International Nuclear Information System (INIS)

Li, Liang; You, Sixiong; Yang, Chao; Yan, Bingjie; Song, Jian; Chen, Zheng

2016-01-01

Highlights: • The novel approximated global optimal energy management strategy has been proposed for hybrid powertrains. • Eight typical driving behaviors have been classified with K-means to deal with the multiplicative traffic conditions. • The stochastic driver models of different driving behaviors were established based on the Markov chains. • ECMS was used to modify the SMPC-based energy management strategy to improve its fuel economy. • The approximated global optimal energy management strategy for plug-in hybrid electric buses has been verified and analyzed. - Abstract: Driving cycles of a city bus is statistically characterized by some repetitive features, which makes the predictive energy management strategy very desirable to obtain approximate optimal fuel economy of a plug-in hybrid electric bus. But dealing with the complicated traffic conditions and finding an approximated global optimal strategy which is applicable to the plug-in hybrid electric bus still remains a challenging technique. To solve this problem, a novel driving-behavior-aware modified stochastic model predictive control method is proposed for the plug-in hybrid electric bus. Firstly, the K-means is employed to classify driving behaviors, and the driver models based on Markov chains is obtained under different kinds of driving behaviors. While the obtained driver behaviors are regarded as stochastic disturbance inputs, the local minimum fuel consumption might be obtained with a traditional stochastic model predictive control at each step, taking tracking the reference battery state of charge trajectory into consideration in the finite predictive horizons. However, this technique is still accompanied by some working points with reduced/worsened fuel economy. Thus, the stochastic model predictive control is modified with the equivalent consumption minimization strategy to eliminate these undesirable working points. The results in real-world city bus routines show that the

Hybrid artificial bee colony algorithm for parameter optimization of five-parameter bidirectional reflectance distribution function model.

Science.gov (United States)

Wang, Qianqian; Zhao, Jing; Gong, Yong; Hao, Qun; Peng, Zhong

2017-11-20

A hybrid artificial bee colony (ABC) algorithm inspired by the best-so-far solution and bacterial chemotaxis was introduced to optimize the parameters of the five-parameter bidirectional reflectance distribution function (BRDF) model. To verify the performance of the hybrid ABC algorithm, we measured BRDF of three kinds of samples and simulated the undetermined parameters of the five-parameter BRDF model using the hybrid ABC algorithm and the genetic algorithm, respectively. The experimental results demonstrate that the hybrid ABC algorithm outperforms the genetic algorithm in convergence speed, accuracy, and time efficiency under the same conditions.

From hybrid swarms to swarms of hybrids

Science.gov (United States)

Stohlgren, Thomas J.; Szalanski, Allen L; Gaskin, John F.; Young, Nicholas E.; West, Amanda; Jarnevich, Catherine S.; Tripodi, Amber

2014-01-01

Science has shown that the introgression or hybridization of modern humans (Homo sapiens) with Neanderthals up to 40,000 YBP may have led to the swarm of modern humans on earth. However, there is little doubt that modern trade and transportation in support of the humans has continued to introduce additional species, genotypes, and hybrids to every country on the globe. We assessed the utility of species distributions modeling of genotypes to assess the risk of current and future invaders. We evaluated 93 locations of the genus Tamarix for which genetic data were available. Maxent models of habitat suitability showed that the hybrid, T. ramosissima x T. chinensis, was slightly greater than the parent taxa (AUCs > 0.83). General linear models of Africanized honey bees, a hybrid cross of Tanzanian Apis mellifera scutellata and a variety of European honey bee including A. m. ligustica, showed that the Africanized bees (AUC = 0.81) may be displacing European honey bees (AUC > 0.76) over large areas of the southwestern U.S. More important, Maxent modeling of sub-populations (A1 and A26 mitotypes based on mDNA) could be accurately modeled (AUC > 0.9), and they responded differently to environmental drivers. This suggests that rapid evolutionary change may be underway in the Africanized bees, allowing the bees to spread into new areas and extending their total range. Protecting native species and ecosystems may benefit from risk maps of harmful invasive species, hybrids, and genotypes.

Hybrid modeling approach to improve the forecasting capability for the gaseous radionuclide in a nuclear site

International Nuclear Information System (INIS)

Jeong, Hyojoon; Hwang, Wontae; Kim, Eunhan; Han, Moonhee

2012-01-01

Highlights: ► This study is to improve the reliability of air dispersion modeling. ► Tracer experiments assumed gaseous radionuclides were conducted at a nuclear site. ► The performance of a hybrid modeling combined ISC with ANFIS was investigated.. ► Hybrid modeling approach shows better performance rather than a single ISC model. - Abstract: Predicted air concentrations of radioactive materials are important for an environmental impact assessment for the public health. In this study, the performance of a hybrid modeling combined with the industrial source complex (ISC) model and an adaptive neuro-fuzzy inference system (ANFIS) for predicting tracer concentrations was investigated. Tracer dispersion experiments were performed to produce the field data assuming the accidental release of radioactive material. ANFIS was trained in order that the outputs of the ISC model are similar to the measured data. Judging from the higher correlation coefficients between the measured and the calculated ones, the hybrid modeling approach could be an appropriate technique for an improvement of the modeling capability to predict the air concentrations for radioactive materials.

Hybrid micro/nanostructural surface offering improved stress distribution and enhanced osseointegration properties of the biomedical titanium implant.

Science.gov (United States)

Hou, Ping-Jen; Ou, Keng-Liang; Wang, Chin-Chieh; Huang, Chiung-Fang; Ruslin, Muhammad; Sugiatno, Erwan; Yang, Tzu-Sen; Chou, Hsin-Hua

2018-03-01

The aim of the present study was to investigate the surface characteristic, biomechanical behavior, hemocompatibility, bone tissue response and osseointegration of the optimal micro-arc oxidation surface-treated titanium (MST-Ti) dental implant. The surface characteristic, biomechanical behavior and hemocompatibility of the MST-Ti dental implant were performed using scanning electron microscope, finite element method, blood dripping and immersion tests. The mini-pig model was utilized to evaluate the bone tissue response and osseointegration of the MST-Ti dental implant in vivo. Data were analyzed by analysis of variance using the Student's t-test (P ≤ 0.05). The hybrid volcano-like micro/nanoporous structure was formed on the surface of the MST-Ti dental implant. The hybrid volcano-like micro/nanoporous surface played an important role to improve the stress transfer between fixture, cortical bone and cancellous bone for the MST-Ti dental implant. Moreover, the MST-Ti implant was considered to have the outstanding hemocompatibility. In vivo testing results showed that the bone-to-implant contact (BIC) ratio significantly altered as the implant with micro/nanoporous surface. After 12 weeks of implantation, the MST-Ti dental implant group exhibited significantly higher BIC ratio than the untreated dental implant group. In addition, the MST-Ti dental implant group also presented an enhancing osseointegration, particularly in the early stages of bone healing. It can be concluded that the micro-arc oxidation approach induced the formation of micro/nanoporous surface is a promising and reliable alternative surface modification for Ti dental implant applications. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Novel Hybrid Model for Drawing Trace Reconstruction from Multichannel Surface Electromyographic Activity.

Science.gov (United States)

Chen, Yumiao; Yang, Zhongliang

2017-01-01

Recently, several researchers have considered the problem of reconstruction of handwriting and other meaningful arm and hand movements from surface electromyography (sEMG). Although much progress has been made, several practical limitations may still affect the clinical applicability of sEMG-based techniques. In this paper, a novel three-step hybrid model of coordinate state transition, sEMG feature extraction and gene expression programming (GEP) prediction is proposed for reconstructing drawing traces of 12 basic one-stroke shapes from multichannel surface electromyography. Using a specially designed coordinate data acquisition system, we recorded the coordinate data of drawing traces collected in accordance with the time series while 7-channel EMG signals were recorded. As a widely-used time domain feature, Root Mean Square (RMS) was extracted with the analysis window. The preliminary reconstruction models can be established by GEP. Then, the original drawing traces can be approximated by a constructed prediction model. Applying the three-step hybrid model, we were able to convert seven channels of EMG activity recorded from the arm muscles into smooth reconstructions of drawing traces. The hybrid model can yield a mean accuracy of 74% in within-group design (one set of prediction models for all shapes) and 86% in between-group design (one separate set of prediction models for each shape), averaged for the reconstructed x and y coordinates. It can be concluded that it is feasible for the proposed three-step hybrid model to improve the reconstruction ability of drawing traces from sEMG.

Interfacial characteristics of hybrid nanocomposite under thermomechanical loading

Science.gov (United States)

Choyal, Vijay; Kundalwal, Shailesh I.

2017-12-01

In this work, an improved shear lag model was developed to investigate the interfacial characteristics of three-phase hybrid nanocomposite which is reinforced with microscale fibers augmented with carbon nanotubes on their circumferential surfaces. The shear lag model accounts for (i) radial and axial deformations of different transversely isotropic constituents, (ii) thermomechanical loads on the representative volume element (RVE), and (iii) staggering effect of adjacent RVEs. The results from the current newly developed shear lag model are validated with the finite element simulations and found to be in good agreement. This study reveals that the reduction in the maximum value of the axial stress in the fiber and the interfacial shear stress along its length become more pronounced in the presence of applied thermomechanical loads on the staggered RVEs. The existence of shear tractions along the RVE length plays a significant role in the interfacial characteristics and cannot be ignored.

A Generalized Hybrid Multiscale Modeling Approach for Flow and Reactive Transport in Porous Media

Science.gov (United States)

Yang, X.; Meng, X.; Tang, Y. H.; Guo, Z.; Karniadakis, G. E.

2017-12-01

Using emerging understanding of biological and environmental processes at fundamental scales to advance predictions of the larger system behavior requires the development of multiscale approaches, and there is strong interest in coupling models at different scales together in a hybrid multiscale simulation framework. A limited number of hybrid multiscale simulation methods have been developed for subsurface applications, mostly using application-specific approaches for model coupling. The proposed generalized hybrid multiscale approach is designed with minimal intrusiveness to the at-scale simulators (pre-selected) and provides a set of lightweight C++ scripts to manage a complex multiscale workflow utilizing a concurrent coupling approach. The workflow includes at-scale simulators (using the lattice-Boltzmann method, LBM, at the pore and Darcy scale, respectively), scripts for boundary treatment (coupling and kriging), and a multiscale universal interface (MUI) for data exchange. The current study aims to apply the generalized hybrid multiscale modeling approach to couple pore- and Darcy-scale models for flow and mixing-controlled reaction with precipitation/dissolution in heterogeneous porous media. The model domain is packed heterogeneously that the mixing front geometry is more complex and not known a priori. To address those challenges, the generalized hybrid multiscale modeling approach is further developed to 1) adaptively define the locations of pore-scale subdomains, 2) provide a suite of physical boundary coupling schemes and 3) consider the dynamic change of the pore structures due to mineral precipitation/dissolution. The results are validated and evaluated by comparing with single-scale simulations in terms of velocities, reactive concentrations and computing cost.

Vortical structures and pressure pulsations in draft tube of a Francis-99 turbine at part load: RANS and hybrid RANS/LES analysis

International Nuclear Information System (INIS)

Gavrilov, A.A.; Sentyabov, A.V.; Dekterev, A.A.; Hanjalić, K.

2017-01-01

Highlights: • Simulations showed the formation of spiralling coherent vortices in the draft tube. • Both hybrid RANS-LES and Re-stress models reproduced well the measured fluctuations. • Re-stress model resolved the precessing vortex core and coherent spiralling vortices. - Abstract: Recognizing the limitations of the conventional linear-eddy-viscosity (LEVM) Reynolds-averaged Navier–Stokes (RANS) models to reproduce complex three-dimensional unsteady flows in hydraulic machinery, we performed a comparative assessment of a second-moment (Re-stress model, RSM) RANS closure and a hybrid RANS/LES method in capturing the flow and vortical structures in the draft tube of a Francis hydroturbine at off-design conditions. Considered is a case of part load (PL) at a flow rate of only 35% of the best efficiency point (BEP) characterised by multiple unsteady vortex systems. Despite some remaining uncertainties in generating the inflow conditions, both approaches reproduced reasonably well the measured mean velocity and the rms of its fluctuations, as well as the pressure spectrum with peaks detecting the precessing vortex core. In contrast to the common LEVMs, the Re-stress closure showed sufficient receptivity to intrinsic unsteadiness and reproduced well the overall flow and vortical patterns as well as the associated pressure pulsations in accord with the experiments. The hybrid RANS/LES method gave similar predictions as the RSM, but resolving a wider range of scales, which however, showed no significant effect on the dynamics of the dominant processing vortex core and the pressure pulsations.

Energy Efficiency Comparison between Hydraulic Hybrid and Hybrid Electric Vehicles

Directory of Open Access Journals (Sweden)

Jia-Shiun Chen

2015-05-01

Full Text Available Conventional vehicles tend to consume considerable amounts of fuel, which generates exhaust gases and environmental pollution during intermittent driving cycles. Therefore, prospective vehicle designs favor improved exhaust emissions and energy consumption without compromising vehicle performance. Although pure electric vehicles feature high performance and low pollution characteristics, their limitations are their short driving range and high battery costs. Hybrid electric vehicles (HEVs are comparatively environmentally friendly and energy efficient, but cost substantially more compared with conventional vehicles. Hydraulic hybrid vehicles (HHVs are mainly operated using engines, or using alternate combinations of engine and hydraulic power sources while vehicles accelerate. When the hydraulic system accumulator is depleted, the conventional engine reengages; concurrently, brake-regenerated power is recycled and reused by employing hydraulic motor–pump modules in circulation patterns to conserve fuel and recycle brake energy. This study adopted MATLAB Simulink to construct complete HHV and HEV models for backward simulations. New European Driving Cycles were used to determine the changes in fuel economy. The output of power components and the state-of-charge of energy could be retrieved. Varying power component models, energy storage component models, and series or parallel configurations were combined into seven different vehicle configurations: the conventional manual transmission vehicle, series hybrid electric vehicle, series hydraulic hybrid vehicle, parallel hybrid electric vehicle, parallel hydraulic hybrid vehicle, purely electric vehicle, and hydraulic-electric hybrid vehicle. The simulation results show that fuel consumption was 21.80% lower in the series hydraulic hybrid vehicle compared to the series hybrid electric vehicle; additionally, fuel consumption was 3.80% lower in the parallel hybrid electric vehicle compared to the

Soil Compressibility Models for a Wide Stress Range

KAUST Repository

Chong, Song-Hun

2016-03-03

Soil compressibility models with physically correct asymptotic void ratios are required to analyze situations that involve a wide stress range. Previously suggested models and other functions are adapted to satisfy asymptotic void ratios at low and high stress levels; all updated models involve four parameters. Compiled consolidation data for remolded and natural clays are used to test the models and to develop correlations between model parameters and index properties. Models can adequately fit soil compression data for a wide range of stresses and soil types; in particular, models that involve the power of the stress σ\\'β display higher flexibility to capture the brittle response of some natural soils. The use of a single continuous function avoids numerical discontinuities or the need for ad hoc procedures to determine the yield stress. The tangent stiffness-readily computed for all models-should not be mistaken for the small-strain constant-fabric stiffness. © 2016 American Society of Civil Engineers.

A general model of distant hybridization reveals the conditions for extinction in Atlantic salmon and brown trout.

Science.gov (United States)

Quilodrán, Claudio S; Currat, Mathias; Montoya-Burgos, Juan I

2014-01-01

Interspecific hybridization is common in nature but can be increased in frequency or even originated by human actions, such as species introduction or habitat modification, which may threaten species persistence. When hybridization occurs between distantly related species, referred to as "distant hybridization," the resulting hybrids are generally infertile or fertile but do not undergo chromosomal recombination during gametogenesis. Here, we present a model describing this frequent but poorly studied interspecific hybridization to assess its consequences on parental species and to anticipate the conditions under which they can reach extinction. Our general model fully incorporates three important processes: density-dependent competition, dominance/recessivity inheritance of traits and assortative mating. We demonstrate its use and flexibility by assessing population extinction risk between Atlantic salmon and brown trout in Norway, whose interbreeding has recently increased due to farmed fish releases into the wild. We identified the set of conditions under which hybridization may threaten salmonid species. Thanks to the flexibility of our model, we evaluated the effect of an additional risk factor, a parasitic disease, and showed that the cumulative effects dramatically increase the extinction risk. The consequences of distant hybridization are not genetically, but demographically mediated. Our general model is useful to better comprehend the evolution of such hybrid systems and we demonstrated its importance in the field of conservation biology to set up management recommendations when this increasingly frequent type of hybridization is in action.

A General Model of Distant Hybridization Reveals the Conditions for Extinction in Atlantic Salmon and Brown Trout

Science.gov (United States)

Quilodrán, Claudio S.; Currat, Mathias; Montoya-Burgos, Juan I.

2014-01-01

Interspecific hybridization is common in nature but can be increased in frequency or even originated by human actions, such as species introduction or habitat modification, which may threaten species persistence. When hybridization occurs between distantly related species, referred to as “distant hybridization,” the resulting hybrids are generally infertile or fertile but do not undergo chromosomal recombination during gametogenesis. Here, we present a model describing this frequent but poorly studied interspecific hybridization to assess its consequences on parental species and to anticipate the conditions under which they can reach extinction. Our general model fully incorporates three important processes: density-dependent competition, dominance/recessivity inheritance of traits and assortative mating. We demonstrate its use and flexibility by assessing population extinction risk between Atlantic salmon and brown trout in Norway, whose interbreeding has recently increased due to farmed fish releases into the wild. We identified the set of conditions under which hybridization may threaten salmonid species. Thanks to the flexibility of our model, we evaluated the effect of an additional risk factor, a parasitic disease, and showed that the cumulative effects dramatically increase the extinction risk. The consequences of distant hybridization are not genetically, but demographically mediated. Our general model is useful to better comprehend the evolution of such hybrid systems and we demonstrated its importance in the field of conservation biology to set up management recommendations when this increasingly frequent type of hybridization is in action. PMID:25003336

A general model of distant hybridization reveals the conditions for extinction in Atlantic salmon and brown trout.

Directory of Open Access Journals (Sweden)

Claudio S Quilodrán

Full Text Available Interspecific hybridization is common in nature but can be increased in frequency or even originated by human actions, such as species introduction or habitat modification, which may threaten species persistence. When hybridization occurs between distantly related species, referred to as "distant hybridization," the resulting hybrids are generally infertile or fertile but do not undergo chromosomal recombination during gametogenesis. Here, we present a model describing this frequent but poorly studied interspecific hybridization to assess its consequences on parental species and to anticipate the conditions under which they can reach extinction. Our general model fully incorporates three important processes: density-dependent competition, dominance/recessivity inheritance of traits and assortative mating. We demonstrate its use and flexibility by assessing population extinction risk between Atlantic salmon and brown trout in Norway, whose interbreeding has recently increased due to farmed fish releases into the wild. We identified the set of conditions under which hybridization may threaten salmonid species. Thanks to the flexibility of our model, we evaluated the effect of an additional risk factor, a parasitic disease, and showed that the cumulative effects dramatically increase the extinction risk. The consequences of distant hybridization are not genetically, but demographically mediated. Our general model is useful to better comprehend the evolution of such hybrid systems and we demonstrated its importance in the field of conservation biology to set up management recommendations when this increasingly frequent type of hybridization is in action.

Exploring the tensile strain energy absorption of hybrid modified epoxies containing soft particles

International Nuclear Information System (INIS)

Abadyan, M.; Bagheri, R.; Kouchakzadeh, M.A.; Hosseini Kordkheili, S.A.

2011-01-01

Research highlights: → Two epoxy systems have been modified by combination of fine and coarse modifiers. → While both hybrid systems reveal synergistic K IC , no synergism is observed in tensile test. → It is found that coarse particles induce stress concentration in hybrid samples. → Stress concentration leads to fracture of samples at lower energy absorption levels. -- Abstract: In this paper, tensile strain energy absorption of two different hybrid modified epoxies has been systematically investigated. In one system, epoxy has been modified by amine-terminated butadiene acrylonitrile (ATBN) and hollow glass spheres as fine and coarse modifiers, respectively. The other hybrid epoxy has been modified by the combination of ATBN and recycled Tire particles. The results of fracture toughness measurement of blends revealed synergistic toughening for both hybrid systems in some formulations. However, no evidence of synergism is observed in tensile test of hybrid samples. Scanning electron microscope (SEM), transmission optical microscope (TOM) and finite element (FEM) simulation were utilized to study deformation mechanisms of hybrid systems in tensile test. It is found that coarse particles induce stress concentration in hybrid samples. This produces non-uniform strain localized regions which lead to fracture of hybrid samples at lower tensile loading and energy absorption levels.

Hybrid incompatibility arises in a sequence-based bioenergetic model of transcription factor binding.

Science.gov (United States)

Tulchinsky, Alexander Y; Johnson, Norman A; Watt, Ward B; Porter, Adam H

2014-11-01

Postzygotic isolation between incipient species results from the accumulation of incompatibilities that arise as a consequence of genetic divergence. When phenotypes are determined by regulatory interactions, hybrid incompatibility can evolve even as a consequence of parallel adaptation in parental populations because interacting genes can produce the same phenotype through incompatible allelic combinations. We explore the evolutionary conditions that promote and constrain hybrid incompatibility in regulatory networks using a bioenergetic model (combining thermodynamics and kinetics) of transcriptional regulation, considering the bioenergetic basis of molecular interactions between transcription factors (TFs) and their binding sites. The bioenergetic parameters consider the free energy of formation of the bond between the TF and its binding site and the availability of TFs in the intracellular environment. Together these determine fractional occupancy of the TF on the promoter site, the degree of subsequent gene expression and in diploids, and the degree of dominance among allelic interactions. This results in a sigmoid genotype-phenotype map and fitness landscape, with the details of the shape determining the degree of bioenergetic evolutionary constraint on hybrid incompatibility. Using individual-based simulations, we subjected two allopatric populations to parallel directional or stabilizing selection. Misregulation of hybrid gene expression occurred under either type of selection, although it evolved faster under directional selection. Under directional selection, the extent of hybrid incompatibility increased with the slope of the genotype-phenotype map near the derived parental expression level. Under stabilizing selection, hybrid incompatibility arose from compensatory mutations and was greater when the bioenergetic properties of the interaction caused the space of nearly neutral genotypes around the stable expression level to be wide. F2's showed higher

Hybrid sediment transport model for the “linguado” channel, state of Santa Catarina, Brazil

Directory of Open Access Journals (Sweden)

Edison Conde Perez dos Santos

2017-12-01

Full Text Available This study involves an assessment of various artificial intelligence-related techniques which aim to produce a more robust system for sediment transport modeling. The intelligent systems developed in this research are directly applicable to academic knowledge and use data from a report on "water circulation assessment in the “Linguado” Channel and Babitonga Bay ,”Santa Catarina”, Brazil, developed by  Military Engineering Institute (IME. The solution employed for sediment transport was built using an intelligent system from the conception of two hybrid models. The first was a Neuro-Fuzzy (ANFIS hybrid model for the study of hydrodynamic behavior, aiming to determine flow rate in the channel. The second was a fuzzy genetic model, able to assess sediment transport in the “Linguado” Channel. The study's conclusion compares the different effects involved in the dredging equilibrium in the “Linguado” Channel according to this hybrid model with the results obtained using a finite element model in the MIKE21® software.

Model Predictive Control of the Hybrid Ventilation for Livestock

DEFF Research Database (Denmark)

Wu, Zhuang; Stoustrup, Jakob; Trangbæk, Klaus

2006-01-01

In this paper, design and simulation results of Model Predictive Control (MPC) strategy for livestock hybrid ventilation systems and associated indoor climate through variable valve openings and exhaust fans are presented. The design is based on thermal comfort parameters for poultry in barns...

Hybrid 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.

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.

Non-linear hybrid control oriented modelling of a digital displacement machine

DEFF Research Database (Denmark)

Pedersen, Niels Henrik; Johansen, Per; Andersen, Torben O.

2017-01-01

Proper feedback control of digital fluid power machines (Pressure, flow, torque or speed control) requires a control oriented model, from where the system dynamics can be analyzed, stability can be proven and design criteria can be specified. The development of control oriented models for hydraulic...... Digital Displacement Machines (DDM) is complicated due to non-smooth machine behavior, where the dynamics comprises both analog, digital and non-linear elements. For a full stroke operated DDM the power throughput is altered in discrete levels based on the ratio of activated pressure chambers....... In this paper, a control oriented hybrid model is established, which combines the continuous non-linear pressure chamber dynamics and the discrete shaft position dependent activation of the pressure chambers. The hybrid machine model is further extended to describe the dynamics of a Digital Fluid Power...

A Model of Teacher Stress

Science.gov (United States)

Kyriacou, Chris; Sutcliffe, John

1978-01-01

A definition and model of teacher stress is presented which conceptualizes teacher stress as a response syndrome (anger or depression) mediated by (1) an appraisal of threat to the teacher's self-esteem or well-being and (2) coping mechanisms activated to reduce the perceived threat. (Author)

Modeling and Optimal Control of a Class of Warfare Hybrid Dynamic Systems Based on Lanchester (n,1 Attrition Model

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Xiangyong Chen

2014-01-01

hybrid dynamic systems is established based on Lanchester equation in a (n,1 battle, where a heterogeneous force of n different troop types faces a homogeneous force. This model can be characterized by the interaction of continuous-time models (governed by Lanchester equation, and discrete event systems (described by variable tactics. Furthermore, an expository discussion is presented on an optimal variable tactics control problem for warfare hybrid dynamic system. The optimal control strategies are designed based on dynamic programming and differential game theory. As an example of the consequences of this optimal control problem, we take the (2, 1 case and solve the optimal strategies in a (2, 1 case. Simulation results show the feasibility of warfare hybrid system model and the effectiveness of the optimal control strategies designed.

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

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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.

Hybrid Wound Filaments for Greater Resistance to Impacts

Science.gov (United States)

DeLay, Thomas K.; Patterson, James E.; Olson, Michael A.

2008-01-01

A hybrid material containing wound filaments made of a hybrid of high-strength carbon fibers and poly(phenylene benzobisoxazole) [PBO] fibers is discussed. This hybrid material is chosen in an effort to increase the ability of the pressure vessel to resist damage by low-speed impacts (e.g., dropping of tools on the vessel or bumping of the vessel against hard objects during installation and use) without significantly increasing the weight of the vessel. While the basic concept of hybridizing fibers in filament-wound structures is not new, the use of hybridization to increase resistance to impacts is an innovation, and can be expected to be of interest in the composite-pressure-vessel industry. The precise types and the proportions of the high-strength carbon fibers and the PBO fibers in the hybrid are chosen, along with the filament-winding pattern, to maximize the advantageous effects and minimize the disadvantageous effects of each material. In particular, one seeks to (1) take advantage of the ability of the carbon fibers to resist stress rupture while minimizing their contribution to vulnerability of the vessel to impact damage and (2) take advantage of the toughness of the PBO fibers while minimizing their contribution to vulnerability of the vessel to stress rupture. Experiments on prototype vessels fabricated according to this concept have shown promising results. At the time of reporting the information for this article, research toward understanding and optimizing the performances of PBO fibers so as to minimize their contribution to vulnerability of the pressure vessel to stress rupture had yet to be performed.

Hybrid quantum computation

International Nuclear Information System (INIS)

Sehrawat, Arun; Englert, Berthold-Georg; Zemann, Daniel

2011-01-01

We present a hybrid model of the unitary-evolution-based quantum computation model and the measurement-based quantum computation model. In the hybrid model, part of a quantum circuit is simulated by unitary evolution and the rest by measurements on star graph states, thereby combining the advantages of the two standard quantum computation models. In the hybrid model, a complicated unitary gate under simulation is decomposed in terms of a sequence of single-qubit operations, the controlled-z gates, and multiqubit rotations around the z axis. Every single-qubit and the controlled-z gate are realized by a respective unitary evolution, and every multiqubit rotation is executed by a single measurement on a required star graph state. The classical information processing in our model requires only an information flow vector and propagation matrices. We provide the implementation of multicontrol gates in the hybrid model. They are very useful for implementing Grover's search algorithm, which is studied as an illustrative example.

A New Model for Baryogenesis through Hybrid Inflation

International Nuclear Information System (INIS)

Delepine, D.; Prieto, C. Martinez; Lopez, L. A. Urena

2009-01-01

We propose a hybrid inflation model with a complex waterfall field which contains an interaction term that breaks the U(1) global symmetry associated to the waterfall field charge. The asymmetric evolution of the real and imaginary parts of the complex field during the phase transition at the end of inflation translates into a charge asymmetry.

Internal stress model for pre-primary stage of low-stress creep

International Nuclear Information System (INIS)

Kloc, L

2010-01-01

Initial transient stage in low-stress creep experiments was observed in all such experiments. Recently, evidences were presented that this stage cannot be considered as a normal creep primary stage, though the shape of the creep curve is similar. The strain reached during this so called pre-primary stage is fully recoverable upon unloading; the internal stresses must play important role in the effect. Model of standard linear anelastic solid was modified by introduction of creeping body instead of viscous dashpot. Both power law and hyperbolic sine creep law were used to fit observed creep curves of model and structural materials. Mainly the model using hyeprbolic sine creep law provides good fit to individual creep curves and sets of creep curves at different stresses.

A hybrid fuzzy multi-criteria decision making model for green ...

African Journals Online (AJOL)

A hybrid fuzzy multi-criteria decision making model for green supplier selection. ... Hence,supplier selection is significant factor in supply chain success. ... reduce purchasing cost, lead time and improve quality and environmental issue.

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.

Numerical analysis of stiffener for hybrid drive unite

Directory of Open Access Journals (Sweden)

Jakubovičová Lenka

2018-01-01

Full Text Available The matter of this article is a stress-strain analysis of hybrid drive prototype unit connected directly to convention Concrete Transit Mixer Gearbox. The unite was developed with intention to do field test on existing convection machines with possibility to use existing interfaces. The hybrid drive unit consists from electric and hydrostatic motor connected through addition mechanical transmission gearbox. The question is if today standard interface is good enough or need additional support a “stiffener”. Two engineering design were analysed. The first one includes using the stiffener to fixate the construction of hybrid drive unite connected to the planetary gear. The second one is without the stiffener. For strain-stress analysis, a finite element software ANSYS Workbench was used.

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.

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.

Elastic-plastic and creep analyses by assumed stress finite elements

International Nuclear Information System (INIS)

Pian, T.H.H.; Spilker, R.L.; Lee, S.W.

1975-01-01

A formulation is presented of incremental finite element solutions for both initial stress and initial strain problems based on modified complementary energy principle with relaxed inter-element continuity requirement. The corresponding finite element model is the assumed stress hybrid model which has stress parameters in the interior of each element and displacements at the individual nodes as unknowns. The formulation includes an important consideration that the states of stress and strain and the beginning of each increment may not satisfy the equilibrium and compatibility equations. These imbalance and mismatch conditions all lead to correction terms for the equivalent nodal forces of the matrix equations. The initial stress method is applied to elastic-plastic analysis of structures. In this case the stress parameters for the individual elements can be eliminated resulting to a system of equations with only nodal displacements as unknowns. Two different complementary energy principles can be formulated, in one of which the equilibrium of the final state of stress is maintained while in the other the equilibrium of the stress increments is maintained. Each of these two different formulations can be combined with different iterative schemes to be used at each incremental steps of the elastic-plastic analysis. It is also indicated clearly that for the initial stress method the state of stress at the beginning of each increments is in general, not in equilibrium and an imbalance correction is needed. Results of a comprehensive evaluation of various solution procedures by the initial stress method using the assumed stress hybrid elements are presented. The example used is the static response of a thick wall cylinder of elastic-perfectly plastic material under internal pressure. Solid of revolution elements with rectangular cross sections are used

Software development infrastructure for the HYBRID modeling and simulation project

International Nuclear Information System (INIS)

Epiney, Aaron S.; Kinoshita, Robert A.; Kim, Jong Suk; Rabiti, Cristian; Greenwood, M. Scott

2016-01-01

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

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

Group X hybrid histidine kinase Chk1 is dispensable for stress adaptation, host-pathogen interactions and virulence in the opportunistic yeast Candida guilliermondii.

Science.gov (United States)

Navarro-Arias, María J; Dementhon, Karine; Defosse, Tatiana A; Foureau, Emilien; Courdavault, Vincent; Clastre, Marc; Le Gal, Solène; Nevez, Gilles; Le Govic, Yohann; Bouchara, Jean-Philippe; Giglioli-Guivarc'h, Nathalie; Noël, Thierry; Mora-Montes, Hector M; Papon, Nicolas

2017-09-01

Hybrid histidine kinases (HHKs) progressively emerge as prominent sensing proteins in the fungal kingdom and as ideal targets for future therapeutics. The group X HHK is of major interest, since it was demonstrated to play an important role in stress adaptation, host-pathogen interactions and virulence in some yeast and mold models, and particularly Chk1, that corresponds to the sole group X HHK in Candida albicans. In the present work, we investigated the role of Chk1 in the low-virulence species Candida guilliermondii, in order to gain insight into putative conservation of the role of group X HHK in opportunistic yeasts. We demonstrated that disruption of the corresponding gene CHK1 does not influence growth, stress tolerance, drug susceptibility, protein glycosylation or cell wall composition in C. guilliermondii. In addition, we showed that loss of CHK1 does not affect C. guilliermondii ability to interact with macrophages and to stimulate cytokine production by human peripheral blood mononuclear cells. Finally, the C. guilliermondii chk1 null mutant was found to be as virulent as the wild-type strain in the experimental model Galleria mellonella. Taken together, our results demonstrate that group X HHK function is not conserved in Candida species. Copyright © 2017 Institut Pasteur. Published by Elsevier Masson SAS. All rights reserved.

Dynamical analysis of Parkinsonian state emulated by hybrid Izhikevich neuron models

Science.gov (United States)

Liu, Chen; Wang, Jiang; Yu, Haitao; Deng, Bin; Wei, Xile; Li, Huiyan; Loparo, Kenneth A.; Fietkiewicz, Chris

2015-11-01

Computational models play a significant role in exploring novel theories to complement the findings of physiological experiments. Various computational models have been developed to reveal the mechanisms underlying brain functions. Particularly, in the development of therapies to modulate behavioral and pathological abnormalities, computational models provide the basic foundations to exhibit transitions between physiological and pathological conditions. Considering the significant roles of the intrinsic properties of the globus pallidus and the coupling connections between neurons in determining the firing patterns and the dynamical activities of the basal ganglia neuronal network, we propose a hypothesis that pathological behaviors under the Parkinsonian state may originate from combined effects of intrinsic properties of globus pallidus neurons and synaptic conductances in the whole neuronal network. In order to establish a computational efficient network model, hybrid Izhikevich neuron model is used due to its capacity of capturing the dynamical characteristics of the biological neuronal activities. Detailed analysis of the individual Izhikevich neuron model can assist in understanding the roles of model parameters, which then facilitates the establishment of the basal ganglia-thalamic network model, and contributes to a further exploration of the underlying mechanisms of the Parkinsonian state. Simulation results show that the hybrid Izhikevich neuron model is capable of capturing many of the dynamical properties of the basal ganglia-thalamic neuronal network, such as variations of the firing rates and emergence of synchronous oscillations under the Parkinsonian condition, despite the simplicity of the two-dimensional neuronal model. It may suggest that the computational efficient hybrid Izhikevich neuron model can be used to explore basal ganglia normal and abnormal functions. Especially it provides an efficient way of emulating the large-scale neuron network

Modeling the geometric formation and powder deposition mass in laser induction hybrid cladding

International Nuclear Information System (INIS)

Huang, Yong Jun; Yuan, Sheng Fa

2012-01-01

A new laser induction hybrid cladding technique on cylinder work piece is presented. Based on a series of laser induction hybrid experiments by off axial powder feeding, the predicting models of individual clad geometric formation and powder catchment were developed in terms of powder feeding rate, laser special energy and induction energy density using multiple regression analysis. In addition, confirmation tests were performed to make a comparison between the predicting results and measured ones. Via the experiments and analysis, the conclusions can be lead to that the process parameters have crucial influence on the clad geometric formation and powder catchment, and that the predicting model reflects well the relationship between the clad geometric formation and process parameters in laser induction hybrid cladding

STRESS RESPONSE STUDIES USING ANIMAL MODELS

Science.gov (United States)

This presentation will provide the evidence that ozone exposure in animal models induce neuroendocrine stress response and this stress response modulates lung injury and inflammation through adrenergic and glucocorticoid receptors.

Hybrid modeling of microbial exopolysaccharide (EPS) production: The case of Enterobacter A47.

Science.gov (United States)

Marques, Rodolfo; von Stosch, Moritz; Portela, Rui M C; Torres, Cristiana A V; Antunes, Sílvia; Freitas, Filomena; Reis, Maria A M; Oliveira, Rui

2017-03-20

Enterobacter A47 is a bacterium that produces high amounts of a fucose-rich exopolysaccharide (EPS) from glycerol residue of the biodiesel industry. The fed-batch process is characterized by complex non-linear dynamics with highly viscous pseudo-plastic rheology due to the accumulation of EPS in the culture medium. In this paper, we study hybrid modeling as a methodology to increase the predictive power of models for EPS production optimization. We compare six hybrid structures that explore different levels of knowledge-based and machine-learning model components. Knowledge-based components consist of macroscopic material balances, Monod type kinetics, cardinal temperature and pH (CTP) dependency and power-law viscosity models. Unknown dependencies are set to be identified by a feedforward artificial neural network (ANN). A semiparametric identification schema is applied resorting to a data set of 13 independent fed-batch experiments. A parsimonious hybrid model was identified that describes the dynamics of the 13 experiments with the same parameterization. The final model is specific to Enterobacter A47 but can be easily extended to other microbial EPS processes. Copyright © 2017 Elsevier B.V. All rights reserved.

3D printed barium titanate/poly-(vinylidene fluoride) nano-hybrid with anisotropic dielectric properties

DEFF Research Database (Denmark)

Phatharapeetranun, N.; Ksapabutr, B.; Marani, D.

2017-01-01

properties of the starting materials are optimized to shape the hybrid by the precision-extrusion-based fuse deposition modeling technique. The 3D-printed BTNFs allow complex shapes with different degrees of fiber alignment as the result of printing shear stress and the chemical composition of the starting...

A Hybrid Method for Modeling and Solving Supply Chain Optimization Problems with Soft and Logical Constraints

Directory of Open Access Journals (Sweden)

Paweł Sitek

2016-01-01

Full Text Available This paper presents a hybrid method for modeling and solving supply chain optimization problems with soft, hard, and logical constraints. Ability to implement soft and logical constraints is a very important functionality for supply chain optimization models. Such constraints are particularly useful for modeling problems resulting from commercial agreements, contracts, competition, technology, safety, and environmental conditions. Two programming and solving environments, mathematical programming (MP and constraint logic programming (CLP, were combined in the hybrid method. This integration, hybridization, and the adequate multidimensional transformation of the problem (as a presolving method helped to substantially reduce the search space of combinatorial models for supply chain optimization problems. The operation research MP and declarative CLP, where constraints are modeled in different ways and different solving procedures are implemented, were linked together to use the strengths of both. This approach is particularly important for the decision and combinatorial optimization models with the objective function and constraints, there are many decision variables, and these are summed (common in manufacturing, supply chain management, project management, and logistic problems. The ECLiPSe system with Eplex library was proposed to implement a hybrid method. Additionally, the proposed hybrid transformed model is compared with the MILP-Mixed Integer Linear Programming model on the same data instances. For illustrative models, its use allowed finding optimal solutions eight to one hundred times faster and reducing the size of the combinatorial problem to a significant extent.

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.

A hybrid reliability algorithm using PSO-optimized Kriging model and adaptive importance sampling

Science.gov (United States)

Tong, Cao; Gong, Haili

2018-03-01

This paper aims to reduce the computational cost of reliability analysis. A new hybrid algorithm is proposed based on PSO-optimized Kriging model and adaptive importance sampling method. Firstly, the particle swarm optimization algorithm (PSO) is used to optimize the parameters of Kriging model. A typical function is fitted to validate improvement by comparing results of PSO-optimized Kriging model with those of the original Kriging model. Secondly, a hybrid algorithm for reliability analysis combined optimized Kriging model and adaptive importance sampling is proposed. Two cases from literatures are given to validate the efficiency and correctness. The proposed method is proved to be more efficient due to its application of small number of sample points according to comparison results.

A control-oriented simulation model of a power-split hybrid electric vehicle

International Nuclear Information System (INIS)

Cipek, Mihael; Pavković, Danijel; Petrić, Joško

2013-01-01

Highlights: ► A simulation model of a two mode power-split hybrid electric vehicle (HEV) is proposed. ► Modeling the energy losses in the HEV transmission components are presented. ► The control optimization model implementation aspects are discussed. -- Abstract: A simulation model of a two mode power-split hybrid electric vehicle (HEV) is proposed in this paper for the purpose of HEV dynamics analysis and control system design. The bond graph methodology is used to model dominant dynamic effects of the mechanical part of the HEV transmission. Simple quasi-static battery model, the environment model, the tire and the power losses model of a vehicle are included, as well. A low-level electric generator speed control loop is designed, which includes a PI controller tuned according to the symmetrical optimum tuning procedure. Finally, off-line optimization by conjugate gradient-based BPTT-like optimal control algorithm, which is based on the presented mathematical model, is also given in the paper.

Improvement and Validation of Weld Residual Stress Modelling Procedure

International Nuclear Information System (INIS)

Zang, Weilin; Gunnars, Jens; Dong, Pingsha; Hong, Jeong K.

2009-06-01

The objective of this work is to identify and evaluate improvements for the residual stress modelling procedure currently used in Sweden. There is a growing demand to eliminate any unnecessary conservatism involved in residual stress assumptions. The study was focused on the development and validation of an improved weld residual stress modelling procedure, by taking advantage of the recent advances in residual stress modelling and stress measurement techniques. The major changes applied in the new weld residual stress modelling procedure are: - Improved procedure for heat source calibration based on use of analytical solutions. - Use of an isotropic hardening model where mixed hardening data is not available. - Use of an annealing model for improved simulation of strain relaxation in re-heated material. The new modelling procedure is demonstrated to capture the main characteristics of the through thickness stress distributions by validation to experimental measurements. Three austenitic stainless steel butt-welds cases are analysed, covering a large range of pipe geometries. From the cases it is evident that there can be large differences between the residual stresses predicted using the new procedure, and the earlier procedure or handbook recommendations. Previously recommended profiles could give misleading fracture assessment results. The stress profiles according to the new procedure agree well with the measured data. If data is available then a mixed hardening model should be used

Improvement and Validation of Weld Residual Stress Modelling Procedure

Energy Technology Data Exchange (ETDEWEB)

Zang, Weilin; Gunnars, Jens (Inspecta Technology AB, Stockholm (Sweden)); Dong, Pingsha; Hong, Jeong K. (Center for Welded Structures Research, Battelle, Columbus, OH (United States))

2009-06-15

The objective of this work is to identify and evaluate improvements for the residual stress modelling procedure currently used in Sweden. There is a growing demand to eliminate any unnecessary conservatism involved in residual stress assumptions. The study was focused on the development and validation of an improved weld residual stress modelling procedure, by taking advantage of the recent advances in residual stress modelling and stress measurement techniques. The major changes applied in the new weld residual stress modelling procedure are: - Improved procedure for heat source calibration based on use of analytical solutions. - Use of an isotropic hardening model where mixed hardening data is not available. - Use of an annealing model for improved simulation of strain relaxation in re-heated material. The new modelling procedure is demonstrated to capture the main characteristics of the through thickness stress distributions by validation to experimental measurements. Three austenitic stainless steel butt-welds cases are analysed, covering a large range of pipe geometries. From the cases it is evident that there can be large differences between the residual stresses predicted using the new procedure, and the earlier procedure or handbook recommendations. Previously recommended profiles could give misleading fracture assessment results. The stress profiles according to the new procedure agree well with the measured data. If data is available then a mixed hardening model should be used

Study on driver model for hybrid truck based on driving simulator experimental results

Directory of Open Access Journals (Sweden)

Dam Hoang Phuc

2018-04-01

Full Text Available In this paper, a proposed car-following driver model taking into account some features of both the compensatory and anticipatory model representing the human pedal operation has been verified by driving simulator experiments with several real drivers. The comparison between computer simulations performed by determined model parameters with the experimental results confirm the correctness of this mathematical driver model and identified model parameters. Then the driver model is joined to a hybrid vehicle dynamics model and the moderate car following maneuver simulations with various driver parameters are conducted to investigate influences of driver parameters on vehicle dynamics response and fuel economy. Finally, major driver parameters involved in the longitudinal control of drivers are clarified. Keywords: Driver model, Driver-vehicle closed-loop system, Car Following, Driving simulator/hybrid electric vehicle (B1

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.

A modeling method of semiconductor fabrication flows with extended knowledge hybrid Petri nets

Institute of Scientific and Technical Information of China (English)

Zhou Binghai; Jiang Shuyu; Wang Shijin; Wu bin

2008-01-01

A modeling method of extended knowledge hybrid Petri nets (EKHPNs), incorporating object-oriented methods into hybrid Petri nets (HPNs), was presented and used for the representation and modeling of semiconductor wafer fabrication flows. To model the discrete and continuous parts of a complex semiconductor wafer fabrication flow, the HPNs were introduced into the EKHPNs. Object-oriented methods were combined into the EKHPNs for coping with the complexity of the fabrication flow. Knowledge annotations were introduced to solve input and output conflicts of the EKHPNs.Finally, to demonstrate the validity of the EKHPN method, a real semiconductor wafer fabrication case was used to illustrate the modeling procedure. The modeling results indicate that the proposed method can be used to model a complex semiconductor wafer fabrication flow expediently.

Modeling and Optimal Control of a Class of Warfare Hybrid Dynamic Systems Based on Lanchester (n,1) Attrition Model

OpenAIRE

Chen, Xiangyong; Zhang, Ancai

2014-01-01

For the particularity of warfare hybrid dynamic process, a class of warfare hybrid dynamic systems is established based on Lanchester equation in a (n,1) battle, where a heterogeneous force of n different troop types faces a homogeneous force. This model can be characterized by the interaction of continuous-time models (governed by Lanchester equation), and discrete event systems (described by variable tactics). Furthermore, an expository discussion is presented on an optimal variable tact...

Evaluation and Control of Thiol-ene/Thiol-epoxy Hybrid Networks.

Science.gov (United States)

Carioscia, Jacquelyn A; Stansbury, Jeffrey W; Bowman, Christopher N

2007-03-08

The development of thiol-ene/thiol-epoxy hybrid networks offers the advantage of tailorable polymerization kinetics while producing a highly crosslinked, high T(g) polymer that has significantly reduced shrinkage stress. Stoichiometric mixtures of pentaerythritol tetra(3-mercaptopropionate) (PETMP)/triallyl-1,3,5-triazine-2,4,6-trione (TATATO) (thiol-ene, mixture 1) and PETMP/bisphenol a diglycidyl ether (BADGE) (thiol-epoxy, mixture 2) were prepared and hybrid mixtures of 75/25, 50/50, 25/75, and 10/90 w/w of mixtures 1 and 2 were polymerized using a combination of both radical and anionic initiation. The light exposure timing and the relative initiation conditions of the two types were used to control the order and relative rates of the radical and anionic polymerizations. The 50/50 w/w thiol-ene/thiol-epoxy hybrid material exhibited a final stress of only 0.2 MPa, which is 90 % lower than the stress developed in a control dimethacrylate resin. Kinetic analysis indicates composition affects network development in thiol-ene/thiol-epoxy hybrid networks and produces materials with robust mechanical properties.

New Hybrid Variational Recovery Model for Blurred Images with Multiplicative Noise

DEFF Research Database (Denmark)

Dong, Yiqiu; Zeng, Tieyong

2013-01-01

A new hybrid variational model for recovering blurred images in the presence of multiplicative noise is proposed. Inspired by previous work on multiplicative noise removal, an I-divergence technique is used to build a strictly convex model under a condition that ensures the uniqueness...

Dimensional structure of DSM-5 posttraumatic stress symptoms in Spanish trauma victims.

Science.gov (United States)

Soberón, Carmen; Crespo, María; Del Mar Gómez-Gutiérrez, María; Fernández-Lansac, Violeta; Armour, Cherie

2016-01-01

Confirmatory factor analytic studies have shown that posttraumatic stress disorder (PTSD) symptoms included in the fifth edition of the Diagnostic and Statistical Manual Disorders (DSM-5) may be better explained by two 6-factor models (the Externalizing Behaviours model and the Anhedonia model) and a 7-factor Hybrid model. The latter model comprises the symptom clusters of intrusion, avoidance, negative affect, anhedonia, externalizing behaviours, and anxious and dysphoric arousal. This model has received empirical support mainly in American samples. Of note, there have been a limited number of studies conducted on samples from other countries. This study aimed to examine the underlying dimensionality of DSM-5 PTSD symptoms in a Spanish clinical sample exposed to a range of traumatic events. Participants included 165 adults (78.8% females) seeking treatment in trauma services in the Madrid area (Spain). PTSD was assessed using the Global Assessment of Posttraumatic Stress Scale 5, a Spanish self-report instrument assessing posttraumatic symptoms according to the DSM-5 criteria. Confirmatory factor analyses were conducted in Mplus. Both the 7-factor Hybrid model and the 6-factor Anhedonia model demonstrated good and equivalent fit to the data. The findings of this study replicate and extend previous research by providing support for both the 7-factor Hybrid model and the 6-factor Anhedonia model in a clinical sample of Spanish trauma survivors. Given equivalent fit for these two models and the fewer number of latent factors in the Anhedonia model, it was selected as optimal in a traumatized Spanish sample. Implications and future research directions are discussed.

Country Selection Model for Sustainable Construction Businesses Using Hybrid of Objective and Subjective Information

Directory of Open Access Journals (Sweden)

Kang-Wook Lee

2017-05-01

Full Text Available An important issue for international businesses and academia is selecting countries in which to expand in order to achieve entrepreneurial sustainability. This study develops a country selection model for sustainable construction businesses using both objective and subjective information. The objective information consists of 14 variables related to country risk and project performance in 32 countries over 25 years. This hybrid model applies subjective weighting from industrial experts to objective information using a fuzzy LinPreRa-based Analytic Hierarchy Process. The hybrid model yields a more accurate country selection compared to a purely objective information-based model in experienced countries. Interestingly, the hybrid model provides some different predictions with only subjective opinions in unexperienced countries, which implies that expert opinion is not always reliable. In addition, feedback from five experts in top international companies is used to validate the model’s completeness, effectiveness, generality, and applicability. The model is expected to aid decision makers in selecting better candidate countries that lead to sustainable business success.

Modelling of combined ICRF and NBI heating in JET hybrid plasmas

Directory of Open Access Journals (Sweden)

Gallart Dani

2017-01-01

Full Text Available During the 2015-2016 JET campaigns many efforts have been devoted to the exploration of high performance plasma scenarios envisaged for ITER operation. In this paper we model the combined ICRF+NBI heating in selected key hybrid discharges using PION. The antenna frequency was tuned to match the cyclotron frequency of minority hydrogen (H at the center of the tokamak coinciding with the second harmonic cyclotron resonance of deuterium. The modelling takes into account the synergy between ICRF and NBI heating through the second harmonic cyclotron resonance of deuterium beam ions which allows us to assess its impact on the neutron rate RNT. We evaluate the influence of H concentration which was varied in different discharges in order to test their role in the heating performance. According to our modelling, the ICRF enhancement of RNT increases by decreasing the H concentration which increases the ICRF power absorbed by deuterons. We find that in the recent hybrid discharges this ICRF enhancement was in the range of 10-25%. Finally, we extrapolate the results to D-T and find that the best performing hybrid discharges correspond to an equivalent fusion power of ∼7.0 MW in D-T.

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.…

A hybrid modeling approach for option pricing

Science.gov (United States)

Hajizadeh, Ehsan; Seifi, Abbas

2011-11-01

The complexity of option pricing has led many researchers to develop sophisticated models for such purposes. The commonly used Black-Scholes model suffers from a number of limitations. One of these limitations is the assumption that the underlying probability distribution is lognormal and this is so controversial. We propose a couple of hybrid models to reduce these limitations and enhance the ability of option pricing. The key input to option pricing model is volatility. In this paper, we use three popular GARCH type model for estimating volatility. Then, we develop two non-parametric models based on neural networks and neuro-fuzzy networks to price call options for S&P 500 index. We compare the results with those of Black-Scholes model and show that both neural network and neuro-fuzzy network models outperform Black-Scholes model. Furthermore, comparing the neural network and neuro-fuzzy approaches, we observe that for at-the-money options, neural network model performs better and for both in-the-money and an out-of-the money option, neuro-fuzzy model provides better results.

Hybrid Model for e-Learning Quality Evaluation

Directory of Open Access Journals (Sweden)

Suzana M. Savic

2012-02-01

Full Text Available E-learning is becoming increasingly important for the competitive advantage of economic organizations and higher education institutions. Therefore, it is becoming a significant aspect of quality which has to be integrated into the management system of every organization or institution. The paper examines e-learning quality characteristics, standards, criteria and indicators and presents a multi-criteria hybrid model for e-learning quality evaluation based on the method of Analytic Hierarchy Process, trend analysis, and data comparison.

A comprehensive model of stress - The roles of experienced stress and neuroticism in explaining the stress-distress relationship

NARCIS (Netherlands)

De Jong, GM; van Sonderen, E; Emmelkamp, PMG

1999-01-01

Background: In this study, a complex theoretical model regarding the stress-distress relationship was evaluated. The various components in the model included experienced stress (daily hassles), psychological distress, neuroticism, problem-focused coping, avoidant coping, satisfaction with received

Image Restoration Based on the Hybrid Total-Variation-Type Model

OpenAIRE

Shi, Baoli; Pang, Zhi-Feng; Yang, Yu-Fei

2012-01-01

We propose a hybrid total-variation-type model for the image restoration problem based on combining advantages of the ROF model with the LLT model. Since two ${L}^{1}$ -norm terms in the proposed model make it difficultly solved by using some classically numerical methods directly, we first employ the alternating direction method of multipliers (ADMM) to solve a general form of the proposed model. Then, based on the ADMM and the Moreau-Yosida decomposition theory, a more efficient method call...

Evaluation of the Aqua‎Crop Model to Simulate Maize Yiled Response under Salinity Stress

Directory of Open Access Journals (Sweden)

Aida Mehrazar

2017-01-01

Full Text Available Introduction: Limited water resources and its salinity uptrend has caused reducing water and soil quality and consequently reducing the crop production. Thus, use of saline water is the management strategies to decrease drought and water crisis. Furthermore, simulation models are valuable tools for improving on-farm water management and study about the effects of water quality and quantity on crop yield.. The AquaCrop model has recently been developed by the FAO which has the ability to check the production process under different propositions. The initial version of the model was introduced for simulation of crop yield and soil water movement in 2007, that the effect of salinity on crop yield was not considered. Version 4 of the model was released in 2012 in which also considered the effects of salinity on crop yield and simulation of solute Transmission in soil profile. Material and methods: In this project, evaluation of the AquaCrop model and its accuracy was studied in the simulating yield of maize under salt stress. This experiment was conducted in Karaj, on maize hybrid (Zea ma ys L in a sandy soil for investigation of salinity stress on maize yield in 2011-2012. This experiment was conducted in form of randomized complete block design in four replications and five levels of salinity treatments including 0, 4.53, 9.06, 13.59 and 18.13 dS/m at the two times sampling. To evaluate the effect of different levels of salinity on the yield of maize was used Version 4 AquaCrop model and SAS ver 9.1 software .The model calibration was performed by comparing the results of the field studies and the results of simulations in the model. In calculating the yield under different scenarios of salt stress by using AquaCrop, the model needs climate data, soil data, vegetation data and information related to farm management. The effects of salinity on yield and some agronomic and physiological traits of hybrid maize (Shoot length, root length, dry weight

Modeling stress wave propagation in rocks by distinct lattice spring model

Directory of Open Access Journals (Sweden)

Gaofeng Zhao

2014-08-01

Full Text Available In this paper, the ability of the distinct lattice spring model (DLSM for modeling stress wave propagation in rocks was fully investigated. The influence of particle size on simulation of different types of stress waves (e.g. one-dimensional (1D P-wave, 1D S-wave and two-dimensional (2D cylindrical wave was studied through comparing results predicted by the DLSM with different mesh ratios (lr and those obtained from the corresponding analytical solutions. Suggested values of lr were obtained for modeling these stress waves accurately. Moreover, the weak material layer method and virtual joint plane method were used to model P-wave and S-wave propagating through a single discontinuity. The results were compared with the classical analytical solutions, indicating that the virtual joint plane method can give better results and is recommended. Finally, some remarks of the DLSM on modeling of stress wave propagation in rocks were provided.

Abscisic acid, a stress hormone helps in improving water relations and yield of sunflower (helianthus annuus l.) hybrids under drought

International Nuclear Information System (INIS)

Hussain, S.; Saleem, M.F.; Cheema, M.A.; Ashraf, M.Y.; Haq, M.A.

2010-01-01

Genotypic variation in water relations under drought is an important index of studying drought tolerance of crops. Abscisic acid (ABA) application helped in mitigating drought stress by improving water relations and yield. Three sunflower hybrids viz., DK-4040 (tall stature), S-278 (medium stature) and SF-187 (short stature) were subjected to different irrigation and ABA application regimes i.e., four irrigations (25 days after sowing (DAS), at bud initiation, at flower initiation and at achene formation) and with no ABA spray, three irrigations (25 days after sowing, at flower initiation and at achene formation) and with no ABA spray, three irrigations (25 days after sowing, at flower initiation and at achene formation) and with ABA spray at bud initiation, three irrigations (25 days after sowing), at bud initiation and at achene formation) and with no ABA spray, three irrigations (25 days after sowing), at bud initiation and at achene formation) and with ABA spray at flower initiation. The experiment was laid out in randomized complete block design with split plot arrangement and had three replications. Exogenous application of ABA under drought at either stage (bud or flower initiation) was helpful in ameliorating drought stress by improving water relations and yield of sunflower hybrids; however response was better when ABA was applied under drought at bud initiation than at flower initiation stage. Sunflower hybrid DK- 4040 showed better enhancement of drought tolerance by exogenous application of ABA under drought than SF-187 and S-278 because it showed more improvement in water potential, osmotic potential, turgor pressure, relative leaf water contents and achene yield. (author)

Accuracy improvement of a hybrid robot for ITER application using POE modeling method

International Nuclear Information System (INIS)

Wang, Yongbo; Wu, Huapeng; Handroos, Heikki

2013-01-01

Highlights: ► The product of exponential (POE) formula for error modeling of hybrid robot. ► Differential Evolution (DE) algorithm for parameter identification. ► Simulation results are given to verify the effectiveness of the method. -- Abstract: This paper focuses on the kinematic calibration of a 10 degree-of-freedom (DOF) redundant serial–parallel hybrid robot to improve its accuracy. The robot was designed to perform the assembling and repairing tasks of the vacuum vessel (VV) of the international thermonuclear experimental reactor (ITER). By employing the product of exponentials (POEs) formula, we extended the POE-based calibration method from serial robot to redundant serial–parallel hybrid robot. The proposed method combines the forward and inverse kinematics together to formulate a hybrid calibration method for serial–parallel hybrid robot. Because of the high nonlinear characteristics of the error model and too many error parameters need to be identified, the traditional iterative linear least-square algorithms cannot be used to identify the parameter errors. This paper employs a global optimization algorithm, Differential Evolution (DE), to identify parameter errors by solving the inverse kinematics of the hybrid robot. Furthermore, after the parameter errors were identified, the DE algorithm was adopted to numerically solve the forward kinematics of the hybrid robot to demonstrate the accuracy improvement of the end-effector. Numerical simulations were carried out by generating random parameter errors at the allowed tolerance limit and generating a number of configuration poses in the robot workspace. Simulation of the real experimental conditions shows that the accuracy of the end-effector can be improved to the same precision level of the given external measurement device

Accuracy improvement of a hybrid robot for ITER application using POE modeling method

Energy Technology Data Exchange (ETDEWEB)

Wang, Yongbo, E-mail: yongbo.wang@hotmail.com [Laboratory of Intelligent Machines, Lappeenranta University of Technology, FIN-53851 Lappeenranta (Finland); Wu, Huapeng; Handroos, Heikki [Laboratory of Intelligent Machines, Lappeenranta University of Technology, FIN-53851 Lappeenranta (Finland)

2013-10-15

Highlights: ► The product of exponential (POE) formula for error modeling of hybrid robot. ► Differential Evolution (DE) algorithm for parameter identification. ► Simulation results are given to verify the effectiveness of the method. -- Abstract: This paper focuses on the kinematic calibration of a 10 degree-of-freedom (DOF) redundant serial–parallel hybrid robot to improve its accuracy. The robot was designed to perform the assembling and repairing tasks of the vacuum vessel (VV) of the international thermonuclear experimental reactor (ITER). By employing the product of exponentials (POEs) formula, we extended the POE-based calibration method from serial robot to redundant serial–parallel hybrid robot. The proposed method combines the forward and inverse kinematics together to formulate a hybrid calibration method for serial–parallel hybrid robot. Because of the high nonlinear characteristics of the error model and too many error parameters need to be identified, the traditional iterative linear least-square algorithms cannot be used to identify the parameter errors. This paper employs a global optimization algorithm, Differential Evolution (DE), to identify parameter errors by solving the inverse kinematics of the hybrid robot. Furthermore, after the parameter errors were identified, the DE algorithm was adopted to numerically solve the forward kinematics of the hybrid robot to demonstrate the accuracy improvement of the end-effector. Numerical simulations were carried out by generating random parameter errors at the allowed tolerance limit and generating a number of configuration poses in the robot workspace. Simulation of the real experimental conditions shows that the accuracy of the end-effector can be improved to the same precision level of the given external measurement device.

A hierarchical stress release model for synthetic seismicity

Science.gov (United States)

Bebbington, Mark

1997-06-01

We construct a stochastic dynamic model for synthetic seismicity involving stochastic stress input, release, and transfer in an environment of heterogeneous strength and interacting segments. The model is not fault-specific, having a number of adjustable parameters with physical interpretation, namely, stress relaxation, stress transfer, stress dissipation, segment structure, strength, and strength heterogeneity, which affect the seismicity in various ways. Local parameters are chosen to be consistent with large historical events, other parameters to reproduce bulk seismicity statistics for the fault as a whole. The one-dimensional fault is divided into a number of segments, each comprising a varying number of nodes. Stress input occurs at each node in a simple random process, representing the slow buildup due to tectonic plate movements. Events are initiated, subject to a stochastic hazard function, when the stress on a node exceeds the local strength. An event begins with the transfer of excess stress to neighboring nodes, which may in turn transfer their excess stress to the next neighbor. If the event grows to include the entire segment, then most of the stress on the segment is transferred to neighboring segments (or dissipated) in a characteristic event. These large events may themselves spread to other segments. We use the Middle America Trench to demonstrate that this model, using simple stochastic stress input and triggering mechanisms, can produce behavior consistent with the historical record over five units of magnitude. We also investigate the effects of perturbing various parameters in order to show how the model might be tailored to a specific fault structure. The strength of the model lies in this ability to reproduce the behavior of a general linear fault system through the choice of a relatively small number of parameters. It remains to develop a procedure for estimating the internal state of the model from the historical observations in order to

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

A viable D-term hybrid inflation model

Science.gov (United States)

Kadota, Kenji; Kobayashi, Tatsuo; Sumita, Keigo

2017-11-01

We propose a new model of the D-term hybrid inflation in the framework of supergravity. Although our model introduces, analogously to the conventional D-term inflation, the inflaton and a pair of scalar fields charged under a U(1) gauge symmetry, we study the logarithmic and exponential dependence on the inflaton field, respectively, for the Kähler and superpotential. This results in a characteristic one-loop scalar potential consisting of linear and exponential terms, which realizes the small-field inflation dominated by the Fayet-Iliopoulos term. With the reasonable values for the coupling coefficients and, in particular, with the U(1) gauge coupling constant comparable to that of the Standard Model, our D-term inflation model can solve the notorious problems in the conventional D-term inflation, namely, the CMB constraints on the spectral index and the generation of cosmic strings.

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.

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.

Modeling and design of a high-performance hybrid actuator

Science.gov (United States)

Aloufi, Badr; Behdinan, Kamran; Zu, Jean

2016-12-01

This paper presents the model and design of a novel hybrid piezoelectric actuator which provides high active and passive performances for smart structural systems. The actuator is composed of a pair of curved pre-stressed piezoelectric actuators, so-called commercially THUNDER actuators, installed opposite each other using two clamping mechanisms constructed of in-plane fixable hinges, grippers and solid links. A fully mathematical model is developed to describe the active and passive dynamics of the actuator and investigate the effects of its geometrical parameters on the dynamic stiffness, free displacement and blocked force properties. Among the literature that deals with piezoelectric actuators in which THUNDER elements are used as a source of electromechanical power, the proposed study is unique in that it presents a mathematical model that has the ability to predict the actuator characteristics and achieve other phenomena, such as resonances, mode shapes, phase shifts, dips, etc. For model validation, the measurements of the free dynamic response per unit voltage and passive acceleration transmissibility of a particular actuator design are used to check the accuracy of the results predicted by the model. The results reveal that there is a good agreement between the model and experiment. Another experiment is performed to teste the linearity of the actuator system by examining the variation of the output dynamic responses with varying forces and voltages at different frequencies. From the results, it can be concluded that the actuator acts approximately as a linear system at frequencies up to 1000 Hz. A parametric study is achieved here by applying the developed model to analyze the influence of the geometrical parameters of the fixable hinges on the active and passive actuator properties. The model predictions in the frequency range of 0-1000 Hz show that the hinge thickness, radius, and opening angle parameters have great effects on the frequency dynamic

Structural hybrid reliability index and its convergent solving method based on random–fuzzy–interval reliability model

OpenAIRE

Hai An; Ling Zhou; Hui Sun

2016-01-01

Aiming to resolve the problems of a variety of uncertainty variables that coexist in the engineering structure reliability analysis, a new hybrid reliability index to evaluate structural hybrid reliability, based on the random–fuzzy–interval model, is proposed in this article. The convergent solving method is also presented. First, the truncated probability reliability model, the fuzzy random reliability model, and the non-probabilistic interval reliability model are introduced. Then, the new...

Adaptability of grades and hybrids of tangerine in a subtropical zone of Russia

Directory of Open Access Journals (Sweden)

Julia Abilphazova

2015-08-01

Full Text Available Results of researches of various cultivars and hybrids of tangerine growing in the conditions of the humid subtropics of Russia and possessing valuable physiological and biochemical markers are presented in article. The stress factors limiting cultivation of tangerine culture in Krasnodar region are defined. The assessment of the water saving and enzymes activity in tangerine leaves is given. Changes of physiological parameters at influence of a stressful factor are shown. The analysis of water deficiency is revealed existence of essential distinctions between cultivars and hybrids. Change of thickness of a leaf blade of tangerine is the important diagnostic characteristic testifying the ability of leaf tissues to accumulate and keep water. Researches are showing that difference between catalase action of cultivars and hybrids are insignificant. Strengthening of enzyme activity can testify to bigger violation of a functional state of plant cultivars in comparison with the hybrides. Water deficiency and drought resistance coefficient can be used for diagnostics of stability of tangerine to hydrothermal factors. Correlation coefficients between the studied markers were calculated and regression models of their interrelation were given. So, there was a high correlation between thickness of a leaf blade and water deficiency index; close correlation between water deficiency and thickness of a leaf blade, as well as dependence of average degree on water deficiency and catalase activity were noted. There were revealed tangerine cultivars and hybrids which are stable in in the changing environmental conditions and have high biochemical value of fruits.

Numerical weather prediction (NWP) and hybrid ARMA/ANN model to predict global radiation

International Nuclear Information System (INIS)

Voyant, Cyril; Muselli, Marc; Paoli, Christophe; Nivet, Marie-Laure

2012-01-01

We propose in this paper an original technique to predict global radiation using a hybrid ARMA/ANN model and data issued from a numerical weather prediction model (NWP). We particularly look at the multi-layer perceptron (MLP). After optimizing our architecture with NWP and endogenous data previously made stationary and using an innovative pre-input layer selection method, we combined it to an ARMA model from a rule based on the analysis of hourly data series. This model has been used to forecast the hourly global radiation for five places in Mediterranean area. Our technique outperforms classical models for all the places. The nRMSE for our hybrid model MLP/ARMA is 14.9% compared to 26.2% for the naïve persistence predictor. Note that in the standalone ANN case the nRMSE is 18.4%. Finally, in order to discuss the reliability of the forecaster outputs, a complementary study concerning the confidence interval of each prediction is proposed. -- Highlights: ► Time series forecasting with hybrid method based on the use of ALADIN numerical weather model, ANN and ARMA. ► Innovative pre-input layer selection method. ► Combination of optimized MLP and ARMA model obtained from a rule based on the analysis of hourly data series. ► Stationarity process (method and control) for the global radiation time series.

Hybrid CFD/CAA Modeling for Liftoff Acoustic Predictions

Science.gov (United States)

Strutzenberg, Louise L.; Liever, Peter A.

2011-01-01

This paper presents development efforts at the NASA Marshall Space flight Center to establish a hybrid Computational Fluid Dynamics and Computational Aero-Acoustics (CFD/CAA) simulation system for launch vehicle liftoff acoustics environment analysis. Acoustic prediction engineering tools based on empirical jet acoustic strength and directivity models or scaled historical measurements are of limited value in efforts to proactively design and optimize launch vehicles and launch facility configurations for liftoff acoustics. CFD based modeling approaches are now able to capture the important details of vehicle specific plume flow environment, identifY the noise generation sources, and allow assessment of the influence of launch pad geometric details and sound mitigation measures such as water injection. However, CFD methodologies are numerically too dissipative to accurately capture the propagation of the acoustic waves in the large CFD models. The hybrid CFD/CAA approach combines the high-fidelity CFD analysis capable of identifYing the acoustic sources with a fast and efficient Boundary Element Method (BEM) that accurately propagates the acoustic field from the source locations. The BEM approach was chosen for its ability to properly account for reflections and scattering of acoustic waves from launch pad structures. The paper will present an overview of the technology components of the CFD/CAA framework and discuss plans for demonstration and validation against test data.

ANSYS Modeling of Hydrostatic Stress Effects

Science.gov (United States)

Allen, Phillip A.

1999-01-01

Classical metal plasticity theory assumes that hydrostatic pressure has no effect on the yield and postyield behavior of metals. Plasticity textbooks, from the earliest to the most modem, infer that there is no hydrostatic effect on the yielding of metals, and even modem finite element programs direct the user to assume the same. The object of this study is to use the von Mises and Drucker-Prager failure theory constitutive models in the finite element program ANSYS to see how well they model conditions of varying hydrostatic pressure. Data is presented for notched round bar (NRB) and "L" shaped tensile specimens. Similar results from finite element models in ABAQUS are shown for comparison. It is shown that when dealing with geometries having a high hydrostatic stress influence, constitutive models that have a functional dependence on hydrostatic stress are more accurate in predicting material behavior than those that are independent of hydrostatic stress.

Using the hybrid fuzzy goal programming model and hybrid genetic algorithm to solve a multi-objective location routing problem for infectious waste disposal

Directory of Open Access Journals (Sweden)

Narong Wichapa

2017-11-01

Originality/value: The novelty of the proposed methodologies, hybrid fuzzy goal programming model, is the simultaneous combination of both intangible and tangible factors in order to choose new suitable locations, and the hybrid genetic algorithm can be used to determine the optimal routes which provide a minimum number of vehicles and minimum transportation cost under the actual situation, efficiently.

Modelling of a Hybrid Energy System for Autonomous Application

Directory of Open Access Journals (Sweden)

Yang He

2013-10-01

Full Text Available A hybrid energy system (HES is a trending power supply solution for autonomous devices. With the help of an accurate system model, the HES development will be efficient and oriented. In spite of various precise unit models, a HES system is hardly developed. This paper proposes a system modelling approach, which applies the power flux conservation as the governing equation and adapts and modifies unit models of solar cells, piezoelectric generators, a Li-ion battery and a super-capacitor. A generalized power harvest, storage and management strategy is also suggested to adapt to various application scenarios.

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.

Hybrid model for the decay of nuclear giant resonances

International Nuclear Information System (INIS)

Hussein, M.S.

1986-12-01

The decay properties of nuclear giant multipole resonances are discussed within a hybrid model that incorporates, in a unitary consistent way, both the coherent and statistical features. It is suggested that the 'direct' decay of the GR is described with continuum first RPA and the statistical decay calculated with a modified Hauser-Feshbach model. Application is made to the decay of the giant monopole resonance in 208 Pb. Suggestions are made concerning the calculation of the mixing parameter using the statistical properties of the shell model eigenstates at high excitation energies. (Author) [pt

Hybrid approach to structure modeling of the histamine H3 receptor: Multi-level assessment as a tool for model verification.

Directory of Open Access Journals (Sweden)

Jakub Jończyk

Full Text Available The crucial role of G-protein coupled receptors and the significant achievements associated with a better understanding of the spatial structure of known receptors in this family encouraged us to undertake a study on the histamine H3 receptor, whose crystal structure is still unresolved. The latest literature data and availability of different software enabled us to build homology models of higher accuracy than previously published ones. The new models are expected to be closer to crystal structures; and therefore, they are much more helpful in the design of potential ligands. In this article, we describe the generation of homology models with the use of diverse tools and a hybrid assessment. Our study incorporates a hybrid assessment connecting knowledge-based scoring algorithms with a two-step ligand-based docking procedure. Knowledge-based scoring employs probability theory for global energy minimum determination based on information about native amino acid conformation from a dataset of experimentally determined protein structures. For a two-step docking procedure two programs were applied: GOLD was used in the first step and Glide in the second. Hybrid approaches offer advantages by combining various theoretical methods in one modeling algorithm. The biggest advantage of hybrid methods is their intrinsic ability to self-update and self-refine when additional structural data are acquired. Moreover, the diversity of computational methods and structural data used in hybrid approaches for structure prediction limit inaccuracies resulting from theoretical approximations or fuzziness of experimental data. The results of docking to the new H3 receptor model allowed us to analyze ligand-receptor interactions for reference compounds.

Predictive simulation of bidirectional Glenn shunt using a hybrid blood vessel model.

Science.gov (United States)

Li, Hao; Leow, Wee Kheng; Chiu, Ing-Sh

2009-01-01

This paper proposes a method for performing predictive simulation of cardiac surgery. It applies a hybrid approach to model the deformation of blood vessels. The hybrid blood vessel model consists of a reference Cosserat rod and a surface mesh. The reference Cosserat rod models the blood vessel's global bending, stretching, twisting and shearing in a physically correct manner, and the surface mesh models the surface details of the blood vessel. In this way, the deformation of blood vessels can be computed efficiently and accurately. Our predictive simulation system can produce complex surgical results given a small amount of user inputs. It allows the surgeon to easily explore various surgical options and evaluate them. Tests of the system using bidirectional Glenn shunt (BDG) as an application example show that the results produc by the system are similar to real surgical results.

Dimensional structure of DSM-5 posttraumatic stress symptoms in Spanish trauma victims

OpenAIRE

Sober?n, Carmen; Crespo, Mar?a; del Mar G?mez-Guti?rrez, Mar?a; Fern?ndez-Lansac, Violeta; Armour, Cherie

2016-01-01

Background Confirmatory factor analytic studies have shown that posttraumatic stress disorder (PTSD) symptoms included in the fifth edition of the Diagnostic and Statistical Manual Disorders (DSM-5) may be better explained by two 6-factor models (the Externalizing Behaviours model and the Anhedonia model) and a 7-factor Hybrid model. The latter model comprises the symptom clusters of intrusion, avoidance, negative affect, anhedonia, externalizing behaviours, and anxious and dysphoric arousal....

Modeling Exposure to Heat Stress with a Simple Urban Model

Directory of Open Access Journals (Sweden)

Peter Hoffmann

2018-01-01

Full Text Available As a first step in modeling health-related urban well-being (UrbWellth, a mathematical model is constructed that dynamically simulates heat stress exposure of commuters in an idealized city. This is done by coupling the Simple Urban Radiation Model (SURM, which computes the mean radiant temperature ( T m r t , with a newly developed multi-class multi-mode traffic model. Simulation results with parameters chosen for the city of Hamburg for a hot summer day show that commuters are potentially most exposed to heat stress in the early afternoon when T m r t has its maximum. Varying the morphology with respect to street width and building height shows that a more compact city configuration reduces T m r t and therefore the exposure to heat stress. The impact resulting from changes in the city structure on traffic is simulated to determine the time spent outside during the commute. While the time in traffic jams increases for compact cities, the total commuting time decreases due to shorter distances between home and work place. Concerning adaptation measures, it is shown that increases in the albedo of the urban surfaces lead to an increase in daytime heat stress. Dramatic increases in heat stress exposure are found when both, wall and street albedo, are increased.

Finite-Control-Set Model Predictive Control (FCS-MPC) for Islanded Hybrid Microgrids

OpenAIRE

Yi, Zhehan; Babqi, Abdulrahman J.; Wang, Yishen; Shi, Di; Etemadi, Amir H.; Wang, Zhiwei; Huang, Bibin

2018-01-01

Microgrids consisting of multiple distributed energy resources (DERs) provide a promising solution to integrate renewable energies, e.g., solar photovoltaic (PV) systems. Hybrid AC/DC microgrids leverage the merits of both AC and DC power systems. In this paper, a control strategy for islanded multi-bus hybrid microgrids is proposed based on the Finite-Control-Set Model Predictive Control (FCS-MPC) technologies. The control loops are expedited by predicting the future states and determining t...

Apricot - An Object-Oriented Modeling Language for Hybrid Systems

OpenAIRE

Fang, Huixing; Zhu, Huibiao; Shi, Jianqi

2013-01-01

We propose Apricot as an object-oriented language for modeling hybrid systems. The language combines the features in domain specific language and object-oriented language, that fills the gap between design and implementation, as a result, we put forward the modeling language with simple and distinct syntax, structure and semantics. In addition, we introduce the concept of design by convention into Apricot.As the characteristic of object-oriented and the component architecture in Apricot, we c...

Prediction of CO concentrations based on a hybrid Partial Least Square and Support Vector Machine model

Science.gov (United States)

Yeganeh, B.; Motlagh, M. Shafie Pour; Rashidi, Y.; Kamalan, H.

2012-08-01

Due to the health impacts caused by exposures to air pollutants in urban areas, monitoring and forecasting of air quality parameters have become popular as an important topic in atmospheric and environmental research today. The knowledge on the dynamics and complexity of air pollutants behavior has made artificial intelligence models as a useful tool for a more accurate pollutant concentration prediction. This paper focuses on an innovative method of daily air pollution prediction using combination of Support Vector Machine (SVM) as predictor and Partial Least Square (PLS) as a data selection tool based on the measured values of CO concentrations. The CO concentrations of Rey monitoring station in the south of Tehran, from Jan. 2007 to Feb. 2011, have been used to test the effectiveness of this method. The hourly CO concentrations have been predicted using the SVM and the hybrid PLS-SVM models. Similarly, daily CO concentrations have been predicted based on the aforementioned four years measured data. Results demonstrated that both models have good prediction ability; however the hybrid PLS-SVM has better accuracy. In the analysis presented in this paper, statistic estimators including relative mean errors, root mean squared errors and the mean absolute relative error have been employed to compare performances of the models. It has been concluded that the errors decrease after size reduction and coefficients of determination increase from 56 to 81% for SVM model to 65-85% for hybrid PLS-SVM model respectively. Also it was found that the hybrid PLS-SVM model required lower computational time than SVM model as expected, hence supporting the more accurate and faster prediction ability of hybrid PLS-SVM model.

Computation of the Lyapunov exponents in the compass-gait model under OGY control via a hybrid Poincaré map

International Nuclear Information System (INIS)

Gritli, Hassène; Belghith, Safya

2015-01-01

Highlights: • A numerical calculation method of the Lyapunov exponents in the compass-gait model under OGY control is proposed. • A new linearization method of the impulsive hybrid dynamics around a one-periodic hybrid limit cycle is achieved. • We develop a simple analytical expression of a controlled hybrid Poincaré map. • A dimension reduction of the hybrid Poincaré map is realized. • We describe the numerical computation procedure of the Lyapunov exponents via the designed hybrid Poincaré map. - Abstract: This paper aims at providing a numerical calculation method of the spectrum of Lyapunov exponents in a four-dimensional impulsive hybrid nonlinear dynamics of a passive compass-gait model under the OGY control approach by means of a controlled hybrid Poincaré map. We present a four-dimensional simplified analytical expression of such hybrid map obtained by linearizing the uncontrolled impulsive hybrid nonlinear dynamics around a desired one-periodic passive hybrid limit cycle. In order to compute the spectrum of Lyapunov exponents, a dimension reduction of the controlled hybrid Poincaré map is realized. The numerical calculation of the spectrum of Lyapunov exponents using the reduced-dimension controlled hybrid Poincaré map is given in detail. In order to show the effectiveness of the developed method, the spectrum of Lyapunov exponents is calculated as the slope (bifurcation) parameter varies and hence used to predict the walking dynamics behavior of the compass-gait model under the OGY control.

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.

Recent progress in lower hybrid current drive theory and experiments

International Nuclear Information System (INIS)

Barbato, E.

1998-01-01

In this paper lower hybrid current drive (LHCD) experimental milestones paving the way for future experiments are briefly summarized. The current drive efficiency scaling with the electron temperature is discussed. The role of wave propagation in determining the power deposition profile is stressed and methods are discussed to control the current density profile. Modelling of negative central shear configurations, experimentally obtained by LHCD, are reported. A good agreement is found between the modelling results and the experimental findings, thus showing that a good degree of understanding has been achieved in LHCD theory. (author)

Hybrid systems, optimal control and hybrid vehicles theory, methods and applications

CERN Document Server

Böhme, Thomas J

2017-01-01

This book assembles new methods showing the automotive engineer for the first time how hybrid vehicle configurations can be modeled as systems with discrete and continuous controls. These hybrid systems describe naturally and compactly the networks of embedded systems which use elements such as integrators, hysteresis, state-machines and logical rules to describe the evolution of continuous and discrete dynamics and arise inevitably when modeling hybrid electric vehicles. They can throw light on systems which may otherwise be too complex or recondite. Hybrid Systems, Optimal Control and Hybrid Vehicles shows the reader how to formulate and solve control problems which satisfy multiple objectives which may be arbitrary and complex with contradictory influences on fuel consumption, emissions and drivability. The text introduces industrial engineers, postgraduates and researchers to the theory of hybrid optimal control problems. A series of novel algorithmic developments provides tools for solving engineering pr...

Stress field modelling from digital geological map data

Science.gov (United States)

Albert, Gáspár; Barancsuk, Ádám; Szentpéteri, Krisztián

2016-04-01

To create a model for the lithospheric stress a functional geodatabase is required which contains spatial and geodynamic parameters. A digital structural-geological map is a geodatabase, which usually contains enough attributes to create a stress field model. Such a model is not accurate enough for engineering-geological purposes because simplifications are always present in a map, but in many cases maps are the only sources for a tectonic analysis. The here presented method is designed for field geologist, who are interested to see the possible realization of the stress field over the area, on which they are working. This study presents an application which can produce a map of 3D stress vectors from a kml-file. The core application logic is implemented on top of a spatially aware relational database management system. This allows rapid and geographically accurate analysis of the imported geological features, taking advantage of standardized spatial algorithms and indexing. After pre-processing the map features in a GIS, according to the Type-Property-Orientation naming system, which was described in a previous study (Albert et al. 2014), the first stage of the algorithm generates an irregularly spaced point cloud by emitting a pattern of points within a user-defined buffer zone around each feature. For each point generated, a component-wise approximation of the tensor field at the point's position is computed, derived from the original feature's geodynamic properties. In a second stage a weighted moving average method calculates the stress vectors in a regular grid. Results can be exported as geospatial data for further analysis or cartographic visualization. Computation of the tensor field's components is based on the implementation of the Mohr diagram of a compressional model, which uses a Coulomb fracture criterion. Using a general assumption that the main principal stress must be greater than the stress from the overburden, the differential stress is

A Hybrid Teaching and Learning Model

Science.gov (United States)

Juhary, Jowati Binti

This paper aims at analysing the needs for a specific teaching and learning model for the National Defence University of Malaysia (NDUM). The main argument is that whether there are differences between teaching and learning for academic component versus military component at the university. It is further argued that in order to achieve excellence, there should be one teaching and learning culture. Data were collected through interviews with military cadets. It is found that there are variations of teaching and learning strategies for academic courses, in comparison to a dominant teaching and learning style for military courses. Thus, in the interest of delivering quality education and training for students at the university, the paper argues that possibly a hybrid model for teaching and learning is fundamental in order to generate a one culture of academic and military excellence for the NDUM.

Kinematic modeling of a 7-degree of freedom spatial hybrid manipulator for medical surgery.

Science.gov (United States)

Singh, Amanpreet; Singla, Ekta; Soni, Sanjeev; Singla, Ashish

2018-01-01

The prime objective of this work is to deal with the kinematics of spatial hybrid manipulators. In this direction, in 1955, Denavit and Hartenberg proposed a consistent and concise method, known as D-H parameters method, to deal with kinematics of open serial chains. From literature review, it is found that D-H parameter method is widely used to model manipulators consisting of lower pairs. However, the method leads to ambiguities when applied to closed-loop, tree-like and hybrid manipulators. Furthermore, in the dearth of any direct method to model closed-loop, tree-like and hybrid manipulators, revisions of this method have been proposed from time-to-time by different researchers. One such kind of revision using the concept of dummy frames has successfully been proposed and implemented by the authors on spatial hybrid manipulators. In that work, authors have addressed the orientational inconsistency of the D-H parameter method, restricted to body-attached frames only. In the current work, the condition of body-attached frames is relaxed and spatial frame attachment is considered to derive the kinematic model of a 7-degree of freedom spatial hybrid robotic arm, along with the development of closed-loop constraints. The validation of the new kinematic model has been performed with the help of a prototype of this 7-degree of freedom arm, which is being developed at Council of Scientific & Industrial Research-Central Scientific Instruments Organisation Chandigarh to aid the surgeon during a medical surgical task. Furthermore, the developed kinematic model is used to develop the first column of the Jacobian matrix, which helps in providing the estimate of the tip velocity of the 7-degree of freedom manipulator when the first joint velocity is known.

Effective-mass model and magneto-optical properties in hybrid perovskites

Science.gov (United States)

Yu, Z. G.

2016-06-01

Hybrid inorganic-organic perovskites have proven to be a revolutionary material for low-cost photovoltaic applications. They also exhibit many other interesting properties, including giant Rashba splitting, large-radius Wannier excitons, and novel magneto-optical effects. Understanding these properties as well as the detailed mechanism of photovoltaics requires a reliable and accessible electronic structure, on which models of transport, excitonic, and magneto-optical properties can be efficiently developed. Here we construct an effective-mass model for the hybrid perovskites based on the group theory, experiment, and first-principles calculations. Using this model, we relate the Rashba splitting with the inversion-asymmetry parameter in the tetragonal perovskites, evaluate anisotropic g-factors for both conduction and valence bands, and elucidate the magnetic-field effect on photoluminescence and its dependence on the intensity of photoexcitation. The diamagnetic effect of exciton is calculated for an arbitrarily strong magnetic field. The pronounced excitonic peak emerged at intermediate magnetic fields in cyclotron resonance is assigned to the 3D±2 states, whose splitting can be used to estimate the difference in the effective masses of electron and hole.

A hybrid spatiotemporal drought forecasting model for operational use

Science.gov (United States)

Vasiliades, L.; Loukas, A.

2010-09-01

Drought forecasting plays an important role in the planning and management of natural resources and water resource systems in a river basin. Early and timelines forecasting of a drought event can help to take proactive measures and set out drought mitigation strategies to alleviate the impacts of drought. Spatiotemporal data mining is the extraction of unknown and implicit knowledge, structures, spatiotemporal relationships, or patterns not explicitly stored in spatiotemporal databases. As one of data mining techniques, forecasting is widely used to predict the unknown future based upon the patterns hidden in the current and past data. This study develops a hybrid spatiotemporal scheme for integrated spatial and temporal forecasting. Temporal forecasting is achieved using feed-forward neural networks and the temporal forecasts are extended to the spatial dimension using a spatial recurrent neural network model. The methodology is demonstrated for an operational meteorological drought index the Standardized Precipitation Index (SPI) calculated at multiple timescales. 48 precipitation stations and 18 independent precipitation stations, located at Pinios river basin in Thessaly region, Greece, were used for the development and spatiotemporal validation of the hybrid spatiotemporal scheme. Several quantitative temporal and spatial statistical indices were considered for the performance evaluation of the models. Furthermore, qualitative statistical criteria based on contingency tables between observed and forecasted drought episodes were calculated. The results show that the lead time of forecasting for operational use depends on the SPI timescale. The hybrid spatiotemporal drought forecasting model could be operationally used for forecasting up to three months ahead for SPI short timescales (e.g. 3-6 months) up to six months ahead for large SPI timescales (e.g. 24 months). The above findings could be useful in developing a drought preparedness plan in the region.

Properties of hybrid stars in an extended MIT bag model

International Nuclear Information System (INIS)

Bao Tmurbagan; Liu Guangzhou; Zhu Mingfeng

2009-01-01

The properties of hybrid stars are investigated in the framework of the relativistic mean field theory (RMFT) and an MIT bag model with density-dependent bag constant to describe the hadron phase (HP) and quark phase (QP), respectively. We find that the density-dependent B(ρ) decreases with baryon density ρ; this decrement makes the strange quark matter become more energetically favorable than ever; which makes the threshold densities of the hadron-quark phase transition lower than those of the original bag constant case. In this case, the hyperon degrees of freedom can not be considered. As a result, the equations of state of a star in the mixed phase (MP) become softer whereas those in the QP become stiffer, and the radii of the star obviously decrease. This indicates that the extended MIT bag model is more suitable to describe hybrid stars with small radii. (authors)

A proposed residual stress model for oblique turning

International Nuclear Information System (INIS)

Elkhabeery, M. M.

2001-01-01

A proposed mathematical model is presented for predicting the residual stresses caused by turning. Effects of change in tool free length, cutting speed, feed rate, and the tensile strength of work piece material on the maximum residual stress are investigated. The residual stress distribution in the surface region due to turning under unlubricated condition is determined using a deflection etching technique. To reduce the number of experiments required and build the mathematical model for these variables, Response Surface Methodology (RSM) is used. In addition, variance analysis and an experimental check are conducted to determine the prominent parameters and the adequacy of the model. The results show that the tensile stress of the work piece material, cutting speed, and feed rate have significant effects on the maximum residual stresses. The proposed model, that offering good correlation between the experimental and predicted results, is useful in selecting suitable cutting parameters for the machining of different materials. (author)

Modeling plasma-assisted growth of graphene-carbon nanotube hybrid

International Nuclear Information System (INIS)

Tewari, Aarti

2016-01-01

A theoretical model describing the growth of graphene-CNT hybrid in a plasma medium is presented. Using the model, the growth of carbon nanotube (CNT) on a catalyst particle and thereafter the growth of the graphene on the CNT is studied under the purview of plasma sheath and number density kinetics of different plasma species. It is found that the plasma parameter such as ion density; gas ratios and process parameter such as source power affect the CNT and graphene dimensions. The variation in growth rates of graphene and CNT under different plasma power, gas ratios, and ion densities is analyzed. Based on the results obtained, it can be concluded that higher hydrocarbon ion densities and gas ratios of hydrocarbon to hydrogen favor the growth of taller CNTs and graphene, respectively. In addition, the CNT tip radius reduces with hydrogen ion density and higher plasma power favors graphene with lesser thickness. The present study can help in better understanding of the graphene-CNT hybrid growth in a plasma medium.

Modeling plasma-assisted growth of graphene-carbon nanotube hybrid

Energy Technology Data Exchange (ETDEWEB)

Tewari, Aarti [Department of Applied Physics, Delhi Technological University, Shahbad Daulatpur, Bawana Road, Delhi 110 042 (India)

2016-08-15

A theoretical model describing the growth of graphene-CNT hybrid in a plasma medium is presented. Using the model, the growth of carbon nanotube (CNT) on a catalyst particle and thereafter the growth of the graphene on the CNT is studied under the purview of plasma sheath and number density kinetics of different plasma species. It is found that the plasma parameter such as ion density; gas ratios and process parameter such as source power affect the CNT and graphene dimensions. The variation in growth rates of graphene and CNT under different plasma power, gas ratios, and ion densities is analyzed. Based on the results obtained, it can be concluded that higher hydrocarbon ion densities and gas ratios of hydrocarbon to hydrogen favor the growth of taller CNTs and graphene, respectively. In addition, the CNT tip radius reduces with hydrogen ion density and higher plasma power favors graphene with lesser thickness. The present study can help in better understanding of the graphene-CNT hybrid growth in a plasma medium.

An Introduction to the Hybrid Approach of Neural Networks and the Linear Regression Model : An Illustration in the Hedonic Pricing Model of Building Costs

OpenAIRE

浅野, 美代子; マーコ, ユー K.W.

2007-01-01

This paper introduces the hybrid approach of neural networks and linear regression model proposed by Asano and Tsubaki (2003). Neural networks are often credited with its superiority in data consistency whereas the linear regression model provides simple interpretation of the data enabling researchers to verify their hypotheses. The hybrid approach aims at combing the strengths of these two well-established statistical methods. A step-by-step procedure for performing the hybrid approach is pr...

Dimensional structure of DSM-5 posttraumatic stress symptoms in Spanish trauma victims

Directory of Open Access Journals (Sweden)

Carmen Soberón

2016-12-01

Full Text Available Background: Confirmatory factor analytic studies have shown that posttraumatic stress disorder (PTSD symptoms included in the fifth edition of the Diagnostic and Statistical Manual Disorders (DSM-5 may be better explained by two 6-factor models (the Externalizing Behaviours model and the Anhedonia model and a 7-factor Hybrid model. The latter model comprises the symptom clusters of intrusion, avoidance, negative affect, anhedonia, externalizing behaviours, and anxious and dysphoric arousal. This model has received empirical support mainly in American samples. Of note, there have been a limited number of studies conducted on samples from other countries. Objective: This study aimed to examine the underlying dimensionality of DSM-5 PTSD symptoms in a Spanish clinical sample exposed to a range of traumatic events. Method: Participants included 165 adults (78.8% females seeking treatment in trauma services in the Madrid area (Spain. PTSD was assessed using the Global Assessment of Posttraumatic Stress Scale 5, a Spanish self-report instrument assessing posttraumatic symptoms according to the DSM-5 criteria. Confirmatory factor analyses were conducted in Mplus. Results: Both the 7-factor Hybrid model and the 6-factor Anhedonia model demonstrated good and equivalent fit to the data. Conclusions: The findings of this study replicate and extend previous research by providing support for both the 7-factor Hybrid model and the 6-factor Anhedonia model in a clinical sample of Spanish trauma survivors. Given equivalent fit for these two models and the fewer number of latent factors in the Anhedonia model, it was selected as optimal in a traumatized Spanish sample. Implications and future research directions are discussed. Highlights of the article:

Data Fusion Modeling for an RT3102 and Dewetron System Application in Hybrid Vehicle Stability Testing

Directory of Open Access Journals (Sweden)

Zhibin Miao

2015-08-01

Full Text Available More and more hybrid electric vehicles are driven since they offer such advantages as energy savings and better active safety performance. Hybrid vehicles have two or more power driving systems and frequently switch working condition, so controlling stability is very important. In this work, a two-stage Kalman algorithm method is used to fuse data in hybrid vehicle stability testing. First, the RT3102 navigation system and Dewetron system are introduced. Second, a modeling of data fusion is proposed based on the Kalman filter. Then, this modeling is simulated and tested on a sample vehicle, using Carsim and Simulink software to test the results. The results showed the merits of this modeling.

Maximum Mass of Hybrid Stars in the Quark Bag Model

Science.gov (United States)

Alaverdyan, G. B.; Vartanyan, Yu. L.

2017-12-01

The effect of model parameters in the equation of state for quark matter on the magnitude of the maximum mass of hybrid stars is examined. Quark matter is described in terms of the extended MIT bag model including corrections for one-gluon exchange. For nucleon matter in the range of densities corresponding to the phase transition, a relativistic equation of state is used that is calculated with two-particle correlations taken into account based on using the Bonn meson-exchange potential. The Maxwell construction is used to calculate the characteristics of the first order phase transition and it is shown that for a fixed value of the strong interaction constant αs, the baryon concentrations of the coexisting phases grow monotonically as the bag constant B increases. It is shown that for a fixed value of the strong interaction constant αs, the maximum mass of a hybrid star increases as the bag constant B decreases. For a given value of the bag parameter B, the maximum mass rises as the strong interaction constant αs increases. It is shown that the configurations of hybrid stars with maximum masses equal to or exceeding the mass of the currently known most massive pulsar are possible for values of the strong interaction constant αs > 0.6 and sufficiently low values of the bag constant.

Mathematical Modeling and Digital Control of A Hybrid Switching Buck Converter

Directory of Open Access Journals (Sweden)

Muhammad Umar Abbasi

2017-06-01

Full Text Available The aim of this paper is to describe mathematical modeling and digital control of a hybrid switching buck converter. This converter belongs to a class of so called hybrid switching converters and contains a resonant capacitor, resonant inductor and a diode in addition to original buck converter components. The dc gain of this converter is shown to be independent of resonant branch parameters. Moreover the dc conversion ratio is derived for both ideal case and including main inductor dc resistance. Small signal model of the converter is derived and is shown to be similar to conventional buck converter. Simulation results in SIMPLIS Software as well as experimental results of digital control using an 8 bit STM microcontroller are presented. The potential advantages and applications of this converter are discussed.

A Hybrid Distance-Based Ideal-Seeking Consensus Ranking Model

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Madjid Tavana

2007-01-01

Full Text Available Ordinal consensus ranking problems have received much attention in the management science literature. A problem arises in situations where a group of k decision makers (DMs is asked to rank order n alternatives. The question is how to combine the DM rankings into one consensus ranking. Several different approaches have been suggested to aggregate DM responses into a compromise or consensus ranking; however, the similarity of consensus rankings generated by the different algorithms is largely unknown. In this paper, we propose a new hybrid distance-based ideal-seeking consensus ranking model (DCM. The proposed hybrid model combines parts of the two commonly used consensus ranking techniques of Beck and Lin (1983 and Cook and Kress (1985 into an intuitive and computationally simple model. We illustrate our method and then run a Monte Carlo simulation across a range of k and n to compare the similarity of the consensus rankings generated by our method with the best-known method of Borda and Kendall (Kendall 1962 and the two methods proposed by Beck and Lin (1983 and Cook and Kress (1985. DCM and Beck and Lin's method yielded the most similar consensus rankings, whereas the Cook-Kress method and the Borda-Kendall method yielded the least similar consensus rankings.

A 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.

Design, test and model of a hybrid magnetostrictive hydraulic actuator

International Nuclear Information System (INIS)

Chaudhuri, Anirban; Yoo, Jin-Hyeong; Wereley, Norman M

2009-01-01

The basic operation of hybrid hydraulic actuators involves high frequency bi-directional operation of an active material that is converted to uni-directional motion of hydraulic fluid using valves. A hybrid actuator was developed using magnetostrictive material Terfenol-D as the driving element and hydraulic oil as the working fluid. Two different lengths of Terfenol-D rod, 51 and 102 mm, with the same diameter, 12.7 mm, were used. Tests with no load and with load were carried out to measure the performance for uni-directional motion of the output piston at different pumping frequencies. The maximum no-load flow rates were 24.8 cm 3 s −1 and 22.7 cm 3 s −1 with the 51 mm and 102 mm long rods respectively, and the peaks were noted around 325 Hz pumping frequency. The blocked force of the actuator was close to 89 N in both cases. A key observation was that, at these high pumping frequencies, the inertial effects of the fluid mass dominate over the viscous effects and the problem becomes unsteady in nature. In this study, we also develop a mathematical model of the hydraulic hybrid actuator in the time domain to show the basic operational principle under varying conditions and to capture phenomena affecting system performance. Governing equations for the pumping piston and output shaft were obtained from force equilibrium considerations, while compressibility of the working fluid was taken into account by incorporating the bulk modulus. Fluid inertia was represented by a lumped parameter approach to the transmission line model, giving rise to strongly coupled ordinary differential equations. The model was then used to calculate the no-load velocities of the actuator at different pumping frequencies and simulation results were compared with experimental data for model validation

Modelling and simulation of a hybrid solar heating system for greenhouse applications using Matlab/Simulink

International Nuclear Information System (INIS)

Kıyan, Metin; Bingöl, Ekin; Melikoğlu, Mehmet; Albostan, Ayhan

2013-01-01

Highlights: • Matlab/Simulink modelling of a solar hybrid greenhouse. • Estimation of greenhouse gas emission reductions. • Feasibility and cost analysis of the system. - Abstract: Solar energy is a major renewable energy source and hybrid solar systems are gaining increased academic and industrial attention due to the unique advantages they offer. In this paper, a mathematical model has been developed to investigate the thermal behavior of a greenhouse heated by a hybrid solar collector system. This hybrid system contains an evacuated tube solar heat collector unit, an auxiliary fossil fuel heating unit, a hot water storage unit, control and piping units. A Matlab/Simulink based model and software has been developed to predict the storage water temperature, greenhouse indoor temperature and the amount of auxiliary fuel, as a function of various design parameters of the greenhouse such as location, dimensions, and meteorological data of the region. As a case study, a greenhouse located in Şanlıurfa/Turkey has been simulated based on recent meteorological data and aforementioned hybrid system. The results of simulations performed on an annual basis indicate that revising the existing fossil fuel system with the proposed hybrid system, is economically feasible for most cases, however it requires a slightly longer payback period than expected. On the other hand, by reducing the greenhouse gas emissions significantly, it has a considerable positive environmental impact. The developed dynamic simulation method can be further used for designing heating systems for various solar greenhouses and optimizing the solar collector and thermal storage sizes

Qualitative Fault Isolation of Hybrid Systems: A Structural Model Decomposition-Based Approach

Science.gov (United States)

Bregon, Anibal; Daigle, Matthew; Roychoudhury, Indranil

2016-01-01

Quick and robust fault diagnosis is critical to ensuring safe operation of complex engineering systems. A large number of techniques are available to provide fault diagnosis in systems with continuous dynamics. However, many systems in aerospace and industrial environments are best represented as hybrid systems that consist of discrete behavioral modes, each with its own continuous dynamics. These hybrid dynamics make the on-line fault diagnosis task computationally more complex due to the large number of possible system modes and the existence of autonomous mode transitions. This paper presents a qualitative fault isolation framework for hybrid systems based on structural model decomposition. The fault isolation is performed by analyzing the qualitative information of the residual deviations. However, in hybrid systems this process becomes complex due to possible existence of observation delays, which can cause observed deviations to be inconsistent with the expected deviations for the current mode in the system. The great advantage of structural model decomposition is that (i) it allows to design residuals that respond to only a subset of the faults, and (ii) every time a mode change occurs, only a subset of the residuals will need to be reconfigured, thus reducing the complexity of the reasoning process for isolation purposes. To demonstrate and test the validity of our approach, we use an electric circuit simulation as the case study.

Prediction of Chl-a concentrations in an eutrophic lake using ANN models with hybrid inputs

Science.gov (United States)

Aksoy, A.; Yuzugullu, O.

2017-12-01

Chlorophyll-a (Chl-a) concentrations in water bodies exhibit both spatial and temporal variations. As a result, frequent sampling is required with higher number of samples. This motivates the use of remote sensing as a monitoring tool. Yet, prediction performances of models that convert radiance values into Chl-a concentrations can be poor in shallow lakes. In this study, Chl-a concentrations in Lake Eymir, a shallow eutrophic lake in Ankara (Turkey), are determined using artificial neural network (ANN) models that use hybrid inputs composed of water quality and meteorological data as well as remotely sensed radiance values to improve prediction performance. Following a screening based on multi-collinearity and principal component analysis (PCA), dissolved-oxygen concentration (DO), pH, turbidity, and humidity were selected among several parameters as the constituents of the hybrid input dataset. Radiance values were obtained from QuickBird-2 satellite. Conversion of the hybrid input into Chl-a concentrations were studied for two different periods in the lake. ANN models were successful in predicting Chl-a concentrations. Yet, prediction performance declined for low Chl-a concentrations in the lake. In general, models with hybrid inputs were superior over the ones that solely used remotely sensed data.

STRESS MODELING IN COMPOSITE PRODUCTS USING STANDARD OPTICALLY SENSITIVE MATERIAL

Directory of Open Access Journals (Sweden)

Elifkhan K. Agakhanov

2017-01-01

Full Text Available Abstract. Objectives The problem of physically modelling stresses in a compound solid body of revolution having a complex shape and with a complex load distribution is considered. According to the similarity criteria of stress, deformations and displacements from the volume forces decrease proportionally to the scale of similarity of geometric dimensions, which complicates their direct modelling by the photoelasticity method typically using models made from epoxy materials. Methods Based on the principle of the independent action of the forces, the initial problem is represented as the sum of two problems. In the first uniform problem, the stresses in the body of revolution from the centrifugal forces are simulated by the conventional “freezing” method. In order to solve the second nonuniform problem, the stresses in the region of the model, corresponding to the acting centrifugal forces, are “frozen”. The models are glued in a natural state at room temperature, and the compound model is annealed. Results The band patterns in sections as well as components of radial, tangential and axial stresses on contours and in sections of models are obtained by the methods of normal transmission and numerical integration of the equilibrium equation. According to the modelling criteria, the formula for the transition from stresses in models to stresses in the natural structure is established. The results of the analysis of the effect of a body's material density ratio on the stress state of the entire structure are obtained. Conclusion  Axial stresses have insignificant value as compared to radial and tangential stresses; in addition, the ratio of the densities of the compound body has both a quantitative and qualitative influence on the stress state of the structure.

A plastic damage model with stress triaxiality-dependent hardening

International Nuclear Information System (INIS)

Shen Xinpu; Shen Guoxiao; Zhou Lin

2005-01-01

Emphases of this study were placed on the modelling of plastic damage behaviour of prestressed structural concrete, with special attention being paid to the stress-triaxiality dependent plastic hardening law and the corresponding damage evolution law. A definition of stress triaxiality was proposed and introduced in the model presented here. Drucker-Prager -type plasticity was adopted in the formulation of the plastic damage constitutive equations. Numerical validations were performed for the proposed plasticity-based damage model with a driver subroutine developed in this study. The predicted stress-strain behaviour seems reasonably accurate for the uniaxial tension and uniaxial compression compared with the experimental data reported in references. Numerical calculations of compressions under various hydrostatic stress confinements were carried out in order to validate the stress triaxiality dependent properties of the model. (authors)

Coarse-graining and hybrid methods for efficient simulation of stochastic multi-scale models of tumour growth

International Nuclear Information System (INIS)

Cruz, Roberto de la; Guerrero, Pilar; Calvo, Juan; Alarcón, Tomás

2017-01-01

The development of hybrid methodologies is of current interest in both multi-scale modelling and stochastic reaction–diffusion systems regarding their applications to biology. We formulate a hybrid method for stochastic multi-scale models of cells populations that extends the remit of existing hybrid methods for reaction–diffusion systems. Such method is developed for a stochastic multi-scale model of tumour growth, i.e. population-dynamical models which account for the effects of intrinsic noise affecting both the number of cells and the intracellular dynamics. In order to formulate this method, we develop a coarse-grained approximation for both the full stochastic model and its mean-field limit. Such approximation involves averaging out the age-structure (which accounts for the multi-scale nature of the model) by assuming that the age distribution of the population settles onto equilibrium very fast. We then couple the coarse-grained mean-field model to the full stochastic multi-scale model. By doing so, within the mean-field region, we are neglecting noise in both cell numbers (population) and their birth rates (structure). This implies that, in addition to the issues that arise in stochastic-reaction diffusion systems, we need to account for the age-structure of the population when attempting to couple both descriptions. We exploit our coarse-graining model so that, within the mean-field region, the age-distribution is in equilibrium and we know its explicit form. This allows us to couple both domains consistently, as upon transference of cells from the mean-field to the stochastic region, we sample the equilibrium age distribution. Furthermore, our method allows us to investigate the effects of intracellular noise, i.e. fluctuations of the birth rate, on collective properties such as travelling wave velocity. We show that the combination of population and birth-rate noise gives rise to large fluctuations of the birth rate in the region at the leading edge

Inhibition, Updating Working Memory, and Shifting Predict Reading Disability Symptoms in a Hybrid Model: Project KIDS.

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Daucourt, Mia C; Schatschneider, Christopher; Connor, Carol M; Al Otaiba, Stephanie; Hart, Sara A

2018-01-01

Recent achievement research suggests that executive function (EF), a set of regulatory processes that control both thought and action necessary for goal-directed behavior, is related to typical and atypical reading performance. This project examines the relation of EF, as measured by its components, Inhibition, Updating Working Memory, and Shifting, with a hybrid model of reading disability (RD). Our sample included 420 children who participated in a broader intervention project when they were in KG-third grade (age M = 6.63 years, SD = 1.04 years, range = 4.79-10.40 years). At the time their EF was assessed, using a parent-report Behavior Rating Inventory of Executive Function (BRIEF), they had a mean age of 13.21 years ( SD = 1.54 years; range = 10.47-16.63 years). The hybrid model of RD was operationalized as a composite consisting of four symptoms, and set so that any child could have any one, any two, any three, any four, or none of the symptoms included in the hybrid model. The four symptoms include low word reading achievement, unexpected low word reading achievement, poorer reading comprehension compared to listening comprehension, and dual-discrepancy response-to-intervention, requiring both low achievement and low growth in word reading. The results of our multilevel ordinal logistic regression analyses showed a significant relation between all three components of EF (Inhibition, Updating Working Memory, and Shifting) and the hybrid model of RD, and that the strength of EF's predictive power for RD classification was the highest when RD was modeled as having at least one or more symptoms. Importantly, the chances of being classified as having RD increased as EF performance worsened and decreased as EF performance improved. The question of whether any one EF component would emerge as a superior predictor was also examined and results showed that Inhibition, Updating Working Memory, and Shifting were equally valuable as predictors of the hybrid model of RD

Forecasting Inflow and Outflow of Money Currency in East Java Using a Hybrid Exponential Smoothing and Calendar Variation Model

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Susanti, Ana; Suhartono; Jati Setyadi, Hario; Taruk, Medi; Haviluddin; Pamilih Widagdo, Putut

2018-03-01

Money currency availability in Bank Indonesia can be examined by inflow and outflow of money currency. The objective of this research is to forecast the inflow and outflow of money currency in each Representative Office (RO) of BI in East Java by using a hybrid exponential smoothing based on state space approach and calendar variation model. Hybrid model is expected to generate more accurate forecast. There are two studies that will be discussed in this research. The first studies about hybrid model using simulation data that contain pattern of trends, seasonal and calendar variation. The second studies about the application of a hybrid model for forecasting the inflow and outflow of money currency in each RO of BI in East Java. The first of results indicate that exponential smoothing model can not capture the pattern calendar variation. It results RMSE values 10 times standard deviation of error. The second of results indicate that hybrid model can capture the pattern of trends, seasonal and calendar variation. It results RMSE values approaching the standard deviation of error. In the applied study, the hybrid model give more accurate forecast for five variables : the inflow of money currency in Surabaya, Malang, Jember and outflow of money currency in Surabaya and Kediri. Otherwise, the time series regression model yields better for three variables : outflow of money currency in Malang, Jember and inflow of money currency in Kediri.

Swarm Intelligence-Based Hybrid Models for Short-Term Power Load Prediction

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Jianzhou Wang

2014-01-01

Full Text Available Swarm intelligence (SI is widely and successfully applied in the engineering field to solve practical optimization problems because various hybrid models, which are based on the SI algorithm and statistical models, are developed to further improve the predictive abilities. In this paper, hybrid intelligent forecasting models based on the cuckoo search (CS as well as the singular spectrum analysis (SSA, time series, and machine learning methods are proposed to conduct short-term power load prediction. The forecasting performance of the proposed models is augmented by a rolling multistep strategy over the prediction horizon. The test results are representative of the out-performance of the SSA and CS in tuning the seasonal autoregressive integrated moving average (SARIMA and support vector regression (SVR in improving load forecasting, which indicates that both the SSA-based data denoising and SI-based intelligent optimization strategy can effectively improve the model’s predictive performance. Additionally, the proposed CS-SSA-SARIMA and CS-SSA-SVR models provide very impressive forecasting results, demonstrating their strong robustness and universal forecasting capacities in terms of short-term power load prediction 24 hours in advance.

Forecasting solar radiation using an optimized hybrid model by Cuckoo Search algorithm

International Nuclear Information System (INIS)

Wang, Jianzhou; Jiang, He; Wu, Yujie; Dong, Yao

2015-01-01

Due to energy crisis and environmental problems, it is very urgent to find alternative energy sources nowadays. Solar energy, as one of the great potential clean energies, has widely attracted the attention of researchers. In this paper, an optimized hybrid method by CS (Cuckoo Search) on the basis of the OP-ELM (Optimally Pruned Extreme Learning Machine), called CS-OP-ELM, is developed to forecast clear sky and real sky global horizontal radiation. First, MRSR (Multiresponse Sparse Regression) and LOO-CV (leave-one-out cross-validation) can be applied to rank neurons and prune the possibly meaningless neurons of the FFNN (Feed Forward Neural Network), respectively. Then, Direct strategy and Direct-Recursive strategy based on OP-ELM are introduced to build a hybrid model. Furthermore, CS (Cuckoo Search) optimized algorithm is employed to determine the proper weight coefficients. In order to verify the effectiveness of the developed method, hourly solar radiation data from six sites of the United States has been collected, and methods like ARMA (Autoregression moving average), BP (Back Propagation) neural network and OP-ELM can be compared with CS-OP-ELM. Experimental results show the optimized hybrid method CS-OP-ELM has the best forecasting performance. - Highlights: • An optimized hybrid method called CS-OP-ELM is proposed to forecast solar radiation. • CS-OP-ELM adopts multiple variables dataset as input variables. • Direct and Direct-Recursive strategy are introduced to build a hybrid model. • CS (Cuckoo Search) algorithm is used to determine the optimal weight coefficients. • The proposed method has the best performance compared with other methods

Parameters Design for a Parallel Hybrid Electric Bus Using Regenerative Brake Model

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Zilin Ma

2014-01-01

Full Text Available A design methodology which uses the regenerative brake model is introduced to determine the major system parameters of a parallel electric hybrid bus drive train. Hybrid system parameters mainly include the power rating of internal combustion engine (ICE, gear ratios of transmission, power rating, and maximal torque of motor, power, and capacity of battery. The regenerative model is built in the vehicle model to estimate the regenerative energy in the real road conditions. The design target is to ensure that the vehicle meets the specified vehicle performance, such as speed and acceleration, and at the same time, operates the ICE within an expected speed range. Several pairs of parameters are selected from the result analysis, and the fuel saving result in the road test shows that a 25% reduction is achieved in fuel consumption.

Microstructure Characterization and Stress Corrosion Evaluation of Autogenous and Hybrid Friction Stir Welded Al-Cu-Li 2195 Alloy

Science.gov (United States)

Li, Zhixian; Arbegast, William J.; Meletis, Efstathios I.

1997-01-01

Friction stir welding process is being evaluated for application on the Al-Cu-Li 2195 Super-Light Weight External Tank of the Space Transportation System. In the present investigation Al-Cu-Li 2195 plates were joined by autogenous friction stir welding (FSW) and hybrid FSW (friction stir welding over existing variable polarity plasma arc weld). Optical microscopy and transmission electron microscopy (TEM) were utilized to characterize microstructures of the weldments processed by both welding methods. TEM observations of autogenous FSW coupons in the center section of the dynamically-recrystallized zone showed an equiaxed recrystallized microstructure with an average grain size of approx. 3.8 microns. No T(sub 1), precipitates were present in the above-mentioned zone. Instead, T(sub B) and alpha precipitates were found in this zone with a lower population. Alternate immersion, anodic polarization, constant load, and slow strain tests were carried out to evaluate the general corrosion and stress-corrosion properties of autogenous and hybrid FSW prepared coupons. The experimental results will be discussed.

A hybrid model for dissolved oxygen prediction in aquaculture based on multi-scale features

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Chen Li

2018-03-01

Full Text Available To increase prediction accuracy of dissolved oxygen (DO in aquaculture, a hybrid model based on multi-scale features using ensemble empirical mode decomposition (EEMD is proposed. Firstly, original DO datasets are decomposed by EEMD and we get several components. Secondly, these components are used to reconstruct four terms including high frequency term, intermediate frequency term, low frequency term and trend term. Thirdly, according to the characteristics of high and intermediate frequency terms, which fluctuate violently, the least squares support vector machine (LSSVR is used to predict the two terms. The fluctuation of low frequency term is gentle and periodic, so it can be modeled by BP neural network with an optimal mind evolutionary computation (MEC-BP. Then, the trend term is predicted using grey model (GM because it is nearly linear. Finally, the prediction values of DO datasets are calculated by the sum of the forecasting values of all terms. The experimental results demonstrate that our hybrid model outperforms EEMD-ELM (extreme learning machine based on EEMD, EEMD-BP and MEC-BP models based on the mean absolute error (MAE, mean absolute percentage error (MAPE, mean square error (MSE and root mean square error (RMSE. Our hybrid model is proven to be an effective approach to predict aquaculture DO.